Members of the 

U.S. Advisory Commission on Intergovernmental Relations 

(February 1992) 

Private Citizens 

Daniel J. Elazar, Philadelphia, Pennsylvania 

Robert B. Hawkins, Jr., Chairman, San Francisco, California 

Mary Ellen Joyce, Arlington, Virginia 

Members of the U.S. Senate 

Daniel K. Akaka, Hawaii 

Dave Durenberger, Minnesota 

Charles S. Robb, Virginia 

Members of the U.S. House of Representatives 

Donald M. Payne, New Jersey 

Craig Thomas, Wyoming 

Ted Weiss, New York 

Officers of the Executive Branch, U.S. Government 

Debra Rae Anderson, Deputy Assistant to the President, 

Director of Intergovernmental Affairs 

Samuel K. Skinner, White House Chief of Staff 

Kvxncy 

Governors 

John Ashcroft, Missouri 

George A. Sinner, North Dakota 

Stan Stephens, Montana 

Vucancy 

Mayors 

Victor H. Ashe, Knoxville, Tennessee 

Robert M. Isaac, Colorado Springs, Colorado 

Joseph A. Leafe, Norfolk, Virginia 

Vucuncy 

Members of State Legislatures 

David E. Nething, North Dakota Senate 

Samuel B. Nunez, Jr., President, Louisiana Senate 

Ted L. Strickland, Colorado Senate 

Elected County Officials 

Ann Klinger, Merced County, California, Board of Supervisors 

D. Michael Stewart, Salt Lake County, Utah, County Commission 

Vucancy 
A Commission Report 

Metropolitan 

Organization: 

The Allegheny 

County 

Case 

ADVISORY 

COMMISSION ON 

INTERGOVERNMENTAL 

RELATIONS 

Washington, DC 20575 

February 1992 M-181 
U.S. Advisory Commission on 

Intergovernmental Relations 

800 K Street, NW 

Suite 450, South Building 

Washington, DC 20575 

(202) 653-5640 

FAX (202) 653-5429 

ii US. Advisory Commission on Intergovernmental Relations 
Acknowledgments 

This report is the product of collaborative research, 

under contract with the Commission, by Roger B. Parks, 

Director of the Center for Policy and Public Management, 

School of Environmental and Public Affairs, Indiana University, who was the principal investigator, and Ronald J. 

Oakerson, Senior Scientist at the Workshop in Political 

Theory and Policy Analysis, Indiana University. Parks had 

primary responsibility for Chapters 2,4, and 6, and Oakerson for Chapters 3 and 5. Chapters 1 and 7 were written 

collaboratively. The report was edited by Joan Casey. Secretarial assistance was supplied by Lori Coffel. 

Preliminary plans for the study were reviewed by an 

Academic Advisory Board. The members were: Louis de 

Alessi, Robert Bish, James Ferris, Bryan Jones, Ted Kolderie, Daniel Mandelker, Stephen Mehay, Elinor Ostrom, Paul Peterson, Derek Shearer, and Richard Wagner. 

Initial findings were reviewed at two critics’ sessions convened by ACIR on August 14,1989, in Pittsburgh, and August 15 in Washington, DC. The sessions were attended by 

Richard Conaway, Claire Daehnick, Richard G. DePietress, 

William Dodge, Donald Elliott, Sharon Gladowski, Mary 

Jane Hirt, Norm Howenstein, Leonard G. Jackson, Edward 

Kiely, Ted Koldene, Joseph F. Laguna, James Manley, Boyd 

Mesinger, Paul R. Ostrowslu, George Scarborough, Mark 

Schneider, Marilyn Skolnick, David A. Vazrelnov, and Richard K. Winters. Written comments were received from 

John Bosley, Donald Chisholm, and Irving Hand. 

Many other public officials, private citizens, and 

scholars in Allegheny County and elsewhere were kind 

enough to share their insights and, frequently, data and 

analyses bearing on the county, in the course of the research. Their contributions came in the form of interviews, reports, and critiques of working drafts of this 

report. These contributors are listed on the following 

page. To each, we offer our thanks. 

At ACIR, the report was critically reviewed by Robert 

D. Ebel, former finance research director; Robert W. Rafuse, Jr., former senior fellow; Carol E. Cohen, former se- nior analyst; Elliott J. Dubin, senior analyst; and Vincent 

J. Munley, former visiting scholar. 

Acknowledgments for a study this size always entail 

the risk of overlooking a significant contributor. To anyone 

we have neglected to mention, please accept our apology 

and our thanks. Acknowledgment as a contributor does 

not imply agreement with the data, analysis, or interpretations presented. 

The Commission and its staff retain final responsibility for the content of the report. 

John Kincaid 

Executive Director 

Bruce D. McDowell 

Director, Government Policy Research 

U.S. Advisory Commission on Intergovernmental Relations iii 
iv US. Advisory Commission on Intergovernmental Relations 
Contributors to the Research 

Roger Ahlbrandt, Professor, Graduate School of Business, UniChristine Altenburger, Associate Professor, Graduate School of 

William Bagshaw, President, Mon-Yough Fire Defense Council 

David Bcrquist, Senior Research Associatc. Pennsylvania EconoRay Bodnar, Mayor, Munhall 

Eugene A. Bolt, Superintendent, Brentwood Borough School 

Marshall Bond, Manager, Intergovernmental Cooperation ProRosemary Bradley, Executive Director, Twin Rivers Council of 

Celeste Calfe, Executive Director, Allegheny Valley North CounRobert Callen, Executive Director, Steel Valley Council of GovLinda Croushore, Director, Mon Vallcy Education Consortium 

Richard Crowley, Council President, Braddock 

James Cunningham, Professor, School of Social Work, University 

Claire Daehnick, Director, Research Services, Coalition to ImRichard DePietress, Manager, Municipal Programs, SouthwestJohn S. Di Santi, Superintendent, Deer Lakes School District 

Fred Fesselmeyer, Mayor, Pennsbury Village 

Tom Foerster, Chairman, Allegheny County Commissioners 

Michael Foreman, Pennsylvania Department of Community AfWilliam Fox, Department of Development, Allegheny County 

Wayne Fusaro, Municipal Senices & Programs Division, DepartSharon Gladowski, Allegheny League of Municipalities 

Louis Gorski, Borough Manager, Dormont 

Donna Grande, Member of Council, Heidelberg 

Edward Haney, Council President, Brentwood 

Charles Henry, Fire Commissioner, State of Pennsylvania 

Mary Jane Hirt, Manager, Township of Ohara 

Charles Hoffman, Local Government Advisor, Pennsylvania DeJoseph L. Hoffman, Executive Director, A. W. Beattie VocationJoseph Hohman, Director, Department of Development, AllegEdgar J. Holz, Executive Director, Allegheny Intermediate Unit 

versity of Pittsburgh 

Public and International Affairs, Univcrsity of Pittsburgh 

my League, Western Division 

District 

gram, Greater Pittsburgh Chamber of Commerce 

Governments 

cil of Governments 

ernments 

of Pittsburgh 

prove Management in State and Local Government 

ern Pennsylvania Regional Planning Commission 

fairs 

ment of Development, Allegheny County 

partment of Community Affairs 

al-Technical School 

heny County 

Brenda Honick, Secretary, Dravosburg 

Norman Howenstein, Executive Director, Southwestern PennLeonard Jackson, Inspector, Allegheny County Police 

Kevin Kearns, Assistant Dean for External Programs, Graduate 

School of Public and International Affairs, University of 

Pittsburgh 

sylvania Regional Planning Commission 

Chet C. Kent, Superintendent, Keystone Oaks School District 

Edward S. Kieley, Executive Director, Pennsylvania Economy 

Ellen Kight, Regional Director, Pennsylvania Department of 

Rodger K. Knapp, Superintendent, Riverview School District 

Judith L Kording, Executive Director, Quaker Valley Council of 

Robert Kroner, Superintendent, Allegheny County Police 

John Lattanzi, Fire Chief, Clairton 

Charles Liebcrth, Assistant Director, Coalition to Improve Management in State and Local Government 

James C. Manley, Superintendent, Northgate School District 

K. D. Marinelli, Assistant Manager, Churchill 

Pamela Martz, Research Director, River Cities Project, School of 

Social Work, University of Pittsburgh 

Stephen Mastrofski, Associate Professor, Pennsylvania State 

University 

Matt Mathew, Executive Director, Allegheny League of Municipalities 

Lany McDonald, Chief of Roads, Allegheny County 

Boyd Messinger, Manager, Public Safety Programs, Pennsylvania 

David Miller, Assistant Director, Pennsylvania Economy 

Jack Miller, Allegheny County Fire Academy 

Joseph P. Moses, Director, Department of Maintenance, AllegElvina Nicola, Secretary, Brentwood 

Earl O’Connel, Council President, Wilmerding 

Domer Omdorf, Municipal Police Consultant Manager, PennsylPaul Ostrowski, Chief Engineer, Allegheny County Department 

Memll Parker, Director, Allegheny County Fire Academy 

Steven Perry, Manager, Sewickley 

Nancy Petrusic, Director, North Hills Council of Governments 

Raymond L. Reaves, Director, Department of Planning, AllegEdmond J. Reddy, Secretary-Manager, Whitehall 

League, Western Division 

Community Affairs 

Governments 

Economy League, Western Division 

League, Western Division 

heny County 

vania Department of Community Affairs 

of Maintenance 

heny County 

U.S. Advisory Commission on Intergovernmental Relations v 
Keith Robb, Local Government Specialist, Pennsylvania DepartGeorge Scarborough, Director, Char-West Council of GovemA. Vaughn Seigworth, Instructor, Allegheny County Fire AcadePhyllis Senato, Clerk, Duquesne 

Thomas Smith, Mayor, Borough of Blawnox 

Ellis Stonecipher, Director, Turtle Creek Valley Council of GovRobert F! Strauss, Professor, School of Urban and Public Affairs, 

ment of Community Affairs 

mcnts 

my 

ernments 

Carnegie-Mellon University 

Thelma W. Stucke, Secretary/Manager, Crescent Township 

Milton Supak, Former Council President, Rankin 

Jack Thomas, Manager, Marketing Division, Department of DeWilliam L. Torlidas, Superintendent, South Park School District 

David Varrelman, Chief of Police, Mt. Lebanon 

Jeff Washinger, Fire/Emergency Services Specialist, Pennsylvania Department of Community Affairs 

Becky Wehrer, Secretary, Munhall 

Michael B. Weir, Assistant Director, Pennsylvania Economy 

League, Western Division 

Richard Winters, Sergeant, Allegheny County Police 

velopment, Allegheny County 

vi U.S. Advisory Commission on Intergovernmental Relations 
Contents 

Chapter I Metropolitan Organization: Toward a Further Understanding ................................. 

Metropolitan Organization and Governance ................................................. Accumulating Evidence: Fragmentation, Complexity, and Performance ......................... The ACIR Research Program: Exploring Functional Arrangements ............................. A Theory of Local Public Economies ....................................................... Functional Dimensions of Metropolitan Organization ....................................... 

Local Government Constitution ........................................................ Multijurisdictional Forums for Discussion and Negotiation ................................. Large Investment in Representation .................................................... Citizen Officials Overlapping Jurisdictions and Special Districts ........................................... Separation of Provision and Production .................................................. Coordinated and Joint Service Production 

The Allegheny County Case Study .......................................................... Prospectus ........................................................................... 

Chapter 2 Allegheny County: Patterns of Complex Organization ......................................... County History and Growth ................................................................ Municipal Incorporation ................................................................... Metropolitan Reform in Allegheny County .................................................. County Demographics .................................................................. 

Introduction .......................................................................... 

...................................................................... 

............................................... Criteria ..................................................................... for the Study 

Race ................................................................................ Income .............................................................................. BasicPoliticalGeography ............................................................... 

Local Attachment ..................................................................... 

Municipalities ........................................................................ 

Overlapping Jurisdictions, Special Districts, and Quasi-Governments .......................... 

County Government .................................................................. Special Districts and Quasi-Governmental Jurisdictions ................................... School Districts and Intermediate Units ................................................. Municipal Authorities ................................................................. Volunteer Fire Companies ............................................................. Public Entrepreneurship and the Development of Multiorganizational Arrangements ............. County Government as an Intergovernmental Partner ..................................... Allegheny League of Municipalities ..................................................... Councils of Governments .............................................................. Public-Private Partnerships ............................................................. Nonprofit Organizations ............................................................... Intergovernmental Cooperation Program ................................................ Local Officials and Managers .......................................................... Fiscal Patterns ........................................................................... Municipal Revenues ................................................................... County Government Revenues ......................................................... School District Revenues .............................................................. Summary ................................................................................ 

1 

1 

1 

2 

2 

3 

3 

3 

4 

4 

4 

4 

4 

4 

4 

5 

6 

9 

9 

9 

10 

11 

11 

11 

12 

12 

13 

15 

15 

15 

15 

16 

16 

16 

17 

17 

18 

19 

20 

20 

20 

21 

21 

23 

23 

23 

U.S. Advisory Commission on Intergovernmental Relations vii 
Chapter 3 Metropolitan Governance: State Rules and Local Choices ..................................... 

A Local Government Constitution .......................................................... Rules of Association ...................................................................... Townships ............................................................................ 

Cities ................................................................................ Home Rule Municipalities ............................................................. Volunteer Fire Companies ............................................................. School Districts ....................................................................... County Government .................................................................. Municipal Authorities ................................................................. Environmental Improvement Compacts ................................................. Boundary Adjustment Rules ............................................................... Annexat ion .......................................................................... Consolidation ........................................................................ Fiscal Rules .............................................................................. Real Estate Taxes ..................................................................... Act 51 1 Taxes ......................................................................... Special Tax Districts ................................................................... Debt Rules ........................................................................... Contractual Rules ........................................................................ Local Government Formation in Allegheny County ........................................... Summary ................................................................................ 

Municipal Services: Police, Streets, Fire Protection ........................................... 

Police Services ........................................................................... Jurisdiction Size and Costs Per Capita ................................................... Police Service Expenditures and Population Served ....................................... Service Components .................................................................. Cooperative Production Arrangements .................................................. Police Services-A Summary ........................................................... Street Services ........................................................................... 

County and Municipal Street Production ................................................ Street Service Costs and Population Served .............................................. Cooperation in Street Services and Public Works ......................................... Fire Services ............................................................................. Cooperation in Fire Protection ......................................................... Summay ................................................................................ 

Chapter 5 Public Education ......................................................................... 

Introduction ............................................................................. School District Organization ............................................................... Organizational Linkages ................................................................... 

Jointures ............................................................................. Intermediate Units .................................................................... Independent Consortia ................................................................ Specialized Production Arrangements ....................................................... Special Education ..................................................................... Vocational-Technical and Alternative Education .......................................... Auxiliary Services ..................................................................... Summary ............................................................................ Performance Patterns ..................................................................... The Effect of District Size ............................................................. The Effect of Service Conditions ....................................................... The Effect of Per-Pupil Expenditures ................................................... The Effect of School District Size ....................................................... Northgate School District: A Closer Look ................................................... Patterns of Provision ...................................................................... 

Boroughs ............................................................................ 

Chapter 4 

27 

27 

27 

27 

28 

28 

29 

29 

29 

29 

29 

30 

30 

30 

30 

31 

31 

31 

32 

32 

33 

33 

34 

39 

39 

40 

41 

43 

44 

44 

45 

45 

45 

46 

47 

48 

48 

53 

53 

53 

53 

54 

54 

55 

55 

55 

56 

56 

56 

57 

57 

57 

58 

58 

59 

60 

viii US . Advisory Commission on Intergovernmental Relations 
How Much Disparity? ................................................................. State Assistance ...................................................................... Variation in Local Provision ............................................................ Disparities ........................................................................... Summary ................................................................................ 

Chapter 6 The Political Economy of Allegheny County .................................................. 

Introduction ............................................................................. Population Served and Municipal Expenditures .............................................. Municipal Fiscal Variations ................................................................ Variation in Own-source Revenues ...................................................... Variation in Household ?ax Costs ....................................................... 

Pittsburgh: A Special Case ............................................................. Variation in Per-Pupil School Revenues ..................................................... Metropolitan Problem Solving: Economic Dcveloprnent Issues ................................. Summary ................................................................................ 

Governing a Metropolitan County .......................................................... Functional Patterns of Metropolitan Organization ............................................ 

Patterned Inequalities? ................................................................ 

Chapter 7 

A Metropolitan Legal Framework ...................................................... Community-Based Organization ........................................................ An Overlying County Government ...................................................... Multiple Ties and Overlays ............................................................. FunctionalEvaluation ..................................................................... Self-Determination and Citizen Choice ........ , ......................................... Representation and Accountability ...................................................... Competition .......................................................................... 

Production Efficiency .................................................................. 

Coordination, Metropolitan Problem Solving, and Public Entrepreneurship .................. Fiscal Evaluation ......................................................................... 

Equity ............................................................................... Summary ................................................................................ 

60 

61 

61 

62 

64 

69 

69 

69 

71 

72 

74 

75 

76 

76 

78 

78 

81 

81 

82 

82 

83 

83 

84 

84 

84 

85 

85 

86 

86 

87 

87 

Appendix Data and Data Sources .................................................................... 89 

figure 2.1 Chanpin Real Per Capita Income. 1979.1985 ................................................ 12 

Figure 2.2 Allegheny County Municipalities ........................................................... 14 

figure 2.3 Revenue Sources for County Municipalities. 1985 ............................................ 22 

figure 4.1 Per Capita Police Service Expenditures in Suburban Municipalities. 1985 ........................ 

figure 4.5 Per Capita Fire Expenditures in Suburban Municipalities. 1985 ................................. 

figure 5.1 Variations in Per Student Spending ......................................................... 63 

Table 2.1 Allegheny County Demographics. by Region ................................................. 11 

Table 2.2 Municipal Governments in Allegheny County ................................................ 12 

Table 2.3 Types of Municipalities in Allegheny County ................................................. 15 

Table 2.4 Allegheny County Councils of Governments (COGS) ......................................... 18 

Figures and Tables 

42 

43 

45 

46 

47 

figure 4.2 

figure 4.3 

Figure 4.4 

Municipal Police Expenditures Per Capita and Per $1. 000 Personal Income. 1985 ................. Per Capita Street Service Expenditures in Suburban Municipalities. 1985 ........................ Municipal Street Service Expenditures Per Capita and Per $1. 000 Personal Income. 1985 .......... 

Table 2.5 

Table 4.1 

Table 4.2 

Table 4.4 

Table 4.5 

Table 4.6 

Revenues in 1985. by Source (Excluding Public Service Enterprises) ............................ 

Police Service Provision in Allegheny County Municipalitiesa .................................. Police Service Production by Allegheny County Municipalities ................................. 

in Suburban Municipalities. 1985 ........................................................... Police Dispatch Arrangements for Allegheny Count Police Departments ....................... 

in Suburban Municipalities. 1985 ........................................................... 

20 

39 

41 

Table 4.3 Police Department Characteristics .......................................................... 41 

Per Capita Expenditure Elasticities and Partial Coefficients for Police Services 

42 

43 

46 

Per Capita Expenditure Elasticities and Partial Coe P ficients for Street Services 

U.S. Advisory Commission on Intergovernmental Relations ix 
Table 5.1 

Table 5.2 

Table 5.3 

Tnble 5.4 

Table 5.5 

Service Conditions Model Explaining School District County Performance Levels 

School District Effectiveness. Measured by Difference between Observed 

and Predicted Performance Levels on “TELLS” Tests. by Size Groups .......................... Local Tmx Effort. Allegheny County School Districts Ranked by Actual Local Revenue ........... Disparities among School Districts in Allegheny County-Potentially Disadvantaged Districts ..... Disparities among School Districts in Allegheny County-Potentially Advantaged Districts ........ 

on “TELLS” Tests. Allegheny County ....................................................... 

Table 6.1 

Table 6.2 

Table 6.3 

Table 6.4 

Table 6.5 

Table 6.6 

Table 6.7 

Per Capita Expenditure Elasticities and Partial Coefficients for Common Local Services 

Average Per Capita Revenues by Source for Suburban Municipalities in Each Revenue Base Group. 1985 .................................................................................... Relationships of Community Characteristics with Per Capita Own Source Revenues 

in Suburban Municipalities. 1985 ........................................................... Relationships of Community Characteristics with Household Cost Burdens in Suburban Municipalities, 1985 ................................................................................... 

Relationships of Suburban School District Characteristics with Local School Revenues 

in Suburban Municipalities. 1985 ........................................................... Factors Explaining Variation in Per Capita Own Source Revenues of Suburban Municipalities. 1985 .... 

School Revenue Variations in Allegheny County ............................................. 

per Average Daily Membership. 1985 ....................................................... 

Table A-I Population. Households. Land Area. Income. and Poverty Data ................................ Table A-2 

Table A-3 Per Capita Revenues and Expenditures. 1985 ................................................ Table A-4 Employment. Household Burdens. 1985 ..................................................... 

Population and Housing Characteristics. Density. Population Change. Property Value and .... 

57 

59 

62 

65 

66 

71 

72 

73 

73 

75 

77 

77 

90 

93 

96 

99 

x U.S. Advisory Commission on Intergovernmental Relations 
Chapter 7 

Metropolitan Organization: 

Toward a Further Und%rstanding 

INTRODUCTION 2) The question of governance-what patterns are 

more likely to enable individuals to establish and 

maintain desirable patterns of organization in 

view of changing preferences, technologies, and 

other circumstances of metropolitan life?3 

In its 1988 report entitled Metropolitan Organization: 

The St. Louis Case,’ the Advisory Commission on Intergovernmental Relations (ACIR) focused on organization and 

governance in comulex metrouolitan areas. The report 

The problem of metropolitan organization in 

20th-century America has been viewed, by many 

observers, as presenting first and foremost a chalZenge of reform. Today, propositions linking the 

fragmentation of jurisdictions with disorganization and ineffectiveness can no longer be accepted as self-evident. The basic problems of 

metropolitan organization have come to pose, 

first and foremost, a challenge of understanding. 

For this puqose, the ACIR has undertaken a research program consisting of a series of case studies, beginning in the St. Louis area. From a 

better understanding of metropolitan organization and governance, more discriminating and, in 

the end, more effective efforts to adjust the structure of metropolitan areas can be developed. In 

the absence of understanding, reform efforts, to 

the extent they are successful, may yield a harvest 

of unintended consequences.z 

This report continues the effort to learn how complex 

metropolitan areas function, with a case study of Allegheny 

County, Pennsylvania, the central county of the Pittsburgh 

metropolitan area. 

M ET ROPO LlTAN 0 RCAN IZATl ON 

AND GOVERNANCE 

A concern with both organization and governance sug1) The question of organization-what patterns are 

more likely to be responsive to citizen preferences, 

efficient in producing services, and equitable in financing and delivering services? 

gests two basic questions: 

ten labeled fragmentation-result in less responsivkness, 

less efficiency, and less equity, or do metropolitan areas 

behave as “local public economie~”~ that develop a variety 

of organizational arrangements closely matched to diverse 

public problems? The question of governance leads to a 

focus on the institutional arrangements that may allow individuals to control and direct the development of local 

public economies. 

Metropolitan organization presents a complicated 

puzzle. Citizen preferences for public services are diverse, 

varying from place to place within a metropolitan area 

over time. Moreover, preferences can be aggregated at 

different levels with different results-from neighborhoods to cities and towns, counties, sub-metropolitan regions, and the metropolitan area as a whole. Public 

services also differ in their scale of effects-air pollution 

control affects an entire airshed; police patrol may affect a 

single neighborhood. Technologies to produce public services exhibit gross differences in scale economies. Resources to provide services are not distributed uniformly 

across a metropolitan area, and achieving fiscal equity 

does not guarantee equity in service delivery. 

Such a diverse array of problems is unlikely to be addressed satisfactorily by a boiler-plate solution applied 

uniformly across metropolitan areas, or even across different communities within a single area. Solutions depend on 

the specifics of time and place rather than on abstract 

knowledge of a single correct pattern. 

In the early reform literature, metropolitan areas 

were viewed as failing to conform to a rational pattern of 

organization. The recommended pattern usually was a 

single, areawide government. Later, a two-tier variant was 

introduced. Common to both was a presumption in favor 

of uniform arrangements to provide and produce specific 

services throughout a metropolitan area. Metropolitan arU.S. Advisory Commission on Intergovernmental Relations 1 
eas with large numbers of local governments were viewed 

as organizationally “fragmented” and affected by an as- sortment of ills, including inefficiencies and inequities. 

If solutions depend on the specifics of time and place, 

however, there is no single correct structure to organize 

the provision and production of services. Diverse organi- zational arrangements are appropriate. If this diversity is 

recognized, the basic approach to governance of metro- politan areas must be different. Local citizens and their 

elected officials would need structures that empower 

them to make choices among alternatives. The gover- nance structures of metropolitan areas should, in this 

view, be sufficiently open to allow for a variety of arrangements that respond to variable conditions? 

ACCUMULATI NG EVIDENCE: 

FRAGMENTATION, COMPLEXITY, 

AND PERFORMANCE 

Increasingly, research indicates that fragmented met- ropolitan areas can be more efficient in providing public 

services. In one of the most careful studies to date, Mark 

Schneider reports that growth in local expenditures, con- trolling for relevant service conditions that serve as 

proxies for service demand, was slower in more frag- mented metropolitan areas than in less fragmented area6 

This finding is consistent with a growing body of local public 

finance research.’ Christopher Bell reports similar results 

with respect to school district organization in the states8 

Problems with the measurement of structure, however, limit what can be learned from this research. The fragmentation of a metropolitan area is usually measured as a 

ratio of the number of jurisdictions to population. Sometimes, only particular types of jurisdictions are counted, 

such as municipalities, yielding a measure of horizontal 

fragmentation. Other measures include all jurisdictions 

considered to be governmental in nature by the US. Census of Governments, thus summing over jurisdictions that 

do and do not overlap territorially. In neither case does 

fragmentation measure the vertical structure of a metropolitan area (i.e., the amount of territorial overlap among 

jurisdictions). Nor does it measure the presence of nongovernmental public bodies created by local governments. 

Metropolitan areas that are more fragmented in juris- dictional terms tend to have more complex patterns of organization, developing a variety of multilevel or 

multiscale arrangements. To describe such systems accurately requires a careful mapping of the relationships 

among jurisdictions. The structure cannot be summed up 

adequately in a single indicator that measures the number 

of governments per capita. 

Evidence has begun to emerge that complex metropolitan areas may be more efficient than those that are organized more simply, whether the latter are highly 

consolidated or highly fragmented. David Chicoine and 

Norman Walzer report higher citizen perceptions of quality for some services (libraries and streets) for which provi- sion was concentrated, as well as for some others 

(education and parks) with fragmented provisi~n.~ The 

implication is that a mixture of service arrangements may 

be appropriate. Roger Parks reports higher technical effi-- 

2 U.S. Advisory Commission on Intergovernmental Relations 

ciency in police service in metropolitan areas that combine 

fragmentation of patrol and immediate response to citizen 

requests with more concentrated radio communications 

and investigation of the most serious crimes. A combination of small and large police service producers organized 

in nested arrangements was found superior both to pure hor- izontal fragmentation and to full vertical consolidation.1° 

Research reporting positive effects in cases of juris- dictional fragmentation and organizational complexity 

challenges the presumptions that underlie traditional 

metropolitan reform. It also challenges all students of 

metropolitan organization to understand and explain how 

fragmentation can yield positive effects. Metropolitan areas with similar populations and comparable numbers of 

governmental units may still have significantly different 

organizations and operations.’L Complex metropolitan areas can be understood only on their own terms; researchers must get “inside” fragmented systems to see how they 

are organized and governed.12 

THE ACIR RESEARCH PROGRAM: 

EXPLORING FUNCTIONAL ARRANGEMENTS 

The ACIR research program on the organization of 

local public economies seeks to investigate the character- istics of organization and governance in jurisdictionally 

fragmented metropolitan areas. The focus of inquiry is on 

functional arrangements for taxation, service delivery, 

and g0vernan~e.I~ These functional arrangements (action 

patterns) can be distinguished from jurisdictional arrangements (authority patterns). 

The problem of metropolitan organization is con- cerned with how authority patterns affect action patterns. 

Jurisdictional arrangements establish the legal capacity to 

create a range of different functional arrangements. Jurisdictional arrangements do not determine functional arrangements, but create possibilities within limits. While 

some possibilities are foreclosed by fragmentation, left 

open is a wide variety of arrangements for interjurisdictional coordination. 

Functional arrangements can be viewed as intermediate or intervening variables, linking (1) jurisdictional arrangements (some configuration of fragmentation and 

overlap) and (2) outcomes (efficiency, responsiveness, and 

equity). The range of possible functional arrangements includes independent action by each jurisdiction (with potential duplication) and various forms of coordinated 

action by two or more jurisdictions. The decisionmaking 

processes may include cooperation, contracting, collusion, competition, conflict, negotiation and conflict resolution, rulemaking and enforcement, problem solving, 

and “buck passing.” 

This approach to metropolitan research takes a vital 

step beyond a simple focus on jurisdictional arrangements 

to look at the relevant functional processes and arrangements. In this way, it may be possible to discover the basic 

organizational dynamics of a jurisdictionally fragmented 

metropolitan area. 

The ACIR research program includes case studies of 

individual metropolitan areas that examine the linkages 

between jurisdictional and functional patterns. Individual 
case studies cannot assess the comparative performance 

of more or less fragmented areas. Other researchers are 

pursuing comparative analysis of service provision based 

on performance mea~urernents.’~ The functional arrangements studied for this report lead directly to outcomes of 

service provision, and studying those arrangements may 

lead to suggestions for improving the functioning of metropolitan areas. If, as research indicates, metropolitan areas that exhibit a high degree of jurisdictional 

fragmentation can perform comparatively well, it is important to learn how and why. 

A THEORY OF LOCAL PUBLIC ECONOMIES 

The theoretical orientation used in this report distinguishes the “provision” of public services from their “production.”15 Provision refers to collective-choice processes 

that determine (1) what goods and services to provide, (2) 

what private activities to regulate, (3) the amount of reve- nue to raise and how to raise it, and (4) the quantities and 

quality standards of goods and services to be provided. 

Production refers to the technical processes of combining 

resources to make a product or render a service. 

Different considerations apply to the organization of 

a collectivity to provide a service than to the organization 

of an agency or firm to produce a service. Local govern- ments are primarily provision units that decide what services will be provided and how, but do not necessarily 

organize production in-house. The collective decision to 

organize a provision unit reflects the existence of a community demand for service-a community is willing and 

able to pay for something that its citizens want. Provision 

can be differentiated in two complementary ways. One 

method (corresponding to some measures of fragmenta- tion) divides responsibility among a set of nonoverlapping 

jurisdictions, such as municipalities or school districts. 

Another approach divides responsibility between jurisdictions that overlap territorially. Provision units may or may 

not be in a position to organize their own production 

units-police departments or fire departments, for example. 

Local governments can arrange for production in a variety 

of ways, including in-house production, intergovernmental 

and private contracts, coordinated or joint production, franchises, vouchers, and the encouragement of voluntary pro- duction.16 Such arrangements allow providers to capture the 

benefits of economies of scale without being limited to producing everything at a single scale of organization identical 

to that of provision. 

In most metropolitan areas, therefore, the structure 

of the production side of a local public economy tends to 

be different from the provision side. For example, there 

are usually fewer producers than providers of a service, 

due at least in part to economies of scale in production. 

Some small providers of direct services, like police patrol, 

may choose to contract with other production units. Moreover, various indirect service components can be differentiated and produced under arrangements that reflect 

diverse economies of scale. For example, the number of 

units that produce police communications and dispatch 

will tend to be less than the number that produce routine 

patrol; still fewer units may be involved in the production 

of police training and the investigation of serious crimes. 

Services such as these are often produced by joint units 

created by intergovernmental agreements, by larger scale 

patrol producers under contract, or by units organized by 

overlapping county or state jurisdictions.” 

Among the issues that can be addressed by nesting 

smaller units inside larger ones is distributional equity. 

One popular view is that fiscal equity is best obtained by 

enlarging the size of jurisdictions to encompass economically diverse communities, creating a broader tax base and, 

in theory, allowing more resources to be distriiuted to 

poorer areas. 

Public economies can be organized, however, so that 

overlying jurisdictions can raise revenues for purposes of 

redistribution without depriving distressed communities 

of their autonomy as provision units. If citizen preferences 

within large general units support resource redistniution 

to distressed communities, they may also support redistribution to smaller autonomous units by overlying jurisdic- tions. Counties, for example, are often useful arenas for 

redistribution, and they have increased this role significantly in the last decade.” Preserving the jurisdictional 

autonomy of communities in need has the advantages of 

encouraging local self-reliance, allowing recipient corn- munities to control many aspects of provision (including 

the choice of services to be provided), and enabling them 

to monitor and control important aspects of production 

whether or not production is organized in-house. 

FU N CTI ONAL DIM ENS1 ONS 

OF METROPOLITAN ORGANIZATION 

The ACIR study of St. Louis City and County identi- fied a number of characteristics of metropolitan organiza- tion and go~ernance,’~ many of which can be considered 

attributes of “civil community,” as described by Daniel J. 

Elazar, that enable jurisdictionally fragmented areas to 

function in coherent ways.2o The characteristics of St. 

Louis County, which are summarized here, became working hypotheses in the study of Allegheny County. 

local Government Constitution 

One basic attribute of metropolitan governance in areas with substantial jurisdictional fragmentation appears 

to be a body of rules that applies to the formation, modifi- cation, and conduct of local governments. This body of 

rules can be understood as a “local government constitu- tion” or legal framework that enables communities to constitute governmental units. Two levels of governance are 

implied: (1) one level is concerned with the choice of rules 

that enable the creation and adjustment of local govern- ments within legal constraints; (2) another level is concerned with making choices that establish and maintain 

discrete local governments. In part, fragmentation derives 

from the rules of local government formation and bound- ary adjustment that allow a large number of jurisdictions 

to be created and maintained with qualified independence 

from one another. At the same time, the local government 

constitution includes to some extent a capability for adjusting authority relationships. In this sense, the legal 

framework may include mechanisms of metropolitan gov- ernance (capabilities to make and adjust rules across 

U.S. Advisory Commission on Intergovernmental Relations 3 
boundaries) in the absence of a single metropolitan government. Because most of the rules that apply to local 

governments are embodied in either state statutes or state 

constitutions, the character of metropolitan governance 

depends to a large degree on institutional arrangements 

that vary state by state. 

Multijurisdictional Forums 

for Discussion and Negotiation 

Closely related to the rules that make up a local government constitution are metropolitan arrangements that 

facilitate discussion and negotiation. Statewide and countywide leagues of municipalities, county associations, and 

other local government associations (including, for example, school superintendents, police and fire chiefs), bring 

local officials together to share information and discuss 

common issues. In addition, many metropolitan areas 

have active councils of governments that bring together 

elected and appointed officials. These mechanisms facili- tate the use of local initiative and consensus building in securing adjustments in the legal framework under which 

local public agencies work and interact with one another. 

Large Investment in Representation 

A large number of locally elected officials with correspondingly small constituencies reflects a major investment in political representation. Low ratios of citizens to 

elected officials allow citizens to have easy access to local 

governments and an effective voice in decisionmaking. Jurisdictional fragmentation and proliferation apparently 

are associated with a determination on the oart of citizens 

Special districts that provide specific services are use- ful complements to primary jurisdictions, such as small local municipalities and school districts. Often, they address 

somewhat larger scale concerns, some areawide and some 

not, that are difficult either for smaller jurisdictions to address separately or for larger jurisdictions to address uniformly. In terms of production, special districts can 

capture scale economies that differ from the boundaries 

of general local governments. 

In addition to special districts, general governments 

overlap in metropolitan areas. This overlay can provide a 

basis for metropolitan governance based on rules that apply to local governments within the larger jurisdiction, as 

well as for organizing an overlying government to provide 

a limited range of services. 

Separation of Provision and Production 

Frequently in jurisdictionally fragmented areas, local 

units that make provision for a service do not choose to 

produce the service, but enter into contractual arrangements with other governmental units or private firms. 

There is no economic reason to restrict the organization of 

local governments to those that are able to produce all, or 

any, of the direct services they provide. Very small municipalities frequently choose to make decisions related to 

provision, while obtaining services from public and private 

vendors. Even larger municipalities often choose to arrange for the production of indirect or auxiliary servicesand some direct services-by others. This makes good 

economic sense in view of the economies of scale that apply to the components of public service delivery. 

to maintain high levels of representatioi. Territorially 

overlapping jurisdictions provide channels of representation at different geographic scales. Representation in a 

county council adds to representation by municipal and, 

sometimes, special district officers. 

Citizen Officials 

Coordinated and Joint Service Production 

Closely related to the separation of provision and 

Production is joint production by multiple providers as 

well as coordination among separate producers. Rang- ing from informal cooperation and mutual aid among 

service delivery personnel to jointly administered projects, programs, and facilities, these ties and overlays 

add a critical dimension to the organization of the production side of 

a local public economy. 

Small local jurisdictions also tend to rely on part-time, 

“amateur” elected officials, not only as representatives 

but also as executives and administrators. such as .-~ mayor or 

village president. Citizens serve in lieu of and often in addition to full-time professional employees. Although frequently paid for their time, the rate of pay generally does 

not compensate them at market value; thus, most citizen 

officials are more nearly volunteers than employees. 

When serving in lieu of professionals, citizens perform essential functions in small jurisdictions. When serving in 

addition to professionals, however, citizens can be viewed 

as contributing both a local perspective and a level of information that professionals are somewhat less likely to 

bring to bear on their work. 

Overlapping Jurisdictions 

and Special Districts 

Jurisdictional overlap can be used as a tool of coordination among fragmented jurisdictions. Two types of overlapping jurisdictions are found: special districts and 

overlying general governments. 

CRITERIA FOR THE STUDY 

In the St. Louis study, seven criteria were used to 

evaluate the provision and production of public services.*’ 

The same criteria are used in this study, plus one having to 

do with “public entrepreneurship,” derived from the St. 

Louis study. 

Six of the criteria deal with functional arrangements 

and associated decisionmaking processes: 

Self-Determination and Citizen Choice. To what extent are citizens able to establish and control a variety 

of local governments, adjust their boundaries, and 

transfer authority among jurisdictions? To what extent can citizens choose among jurisdictions to locate 

a residence or business? The question is one of process, not just rules: to what extent do the rules of 

self-determination enable self-determination and citizen choice to occur? 

4 US. Advisory Commission on Intergovernmental Relations 
Representation and Accountability. Can communities 

of interest of differing sizes gain effective representa- tion of their views? Are the costs to citizens of making 

their views known to public officials kept reasonably 

low? Are elected public officials and administrators ef- fectively accountable to the communities of interest 

(neighborhood, municipal, county, metropolitan)? 

Coordination. Is production coordinated for closely 

related services and service components? Do serious 

deficiencies develop- the price, perhaps, of too much 

self-determination-or does significant functional 

coordination emerge from arrangements that cross 

jurisdictional boundaries? 

Competition among Service Producers. Do local ju- risdictions “shop around” for the most economical 

method of service production? Does this competition 

effectively yield cost savings and/or service benefits 

taking into account the costs of occasional shifting 

among producers? 

Metropolitan Problem Solving. Are genuinely 

metropolitanwide problems effectively addressed on 

a metropolitan basis? 

Public Entrepreneurship. This criterion is added in 

view of findings from the St. Louis study. Public entrepreneurship-the work of officials and citizens who 

initiate ideas and who carry the burden of ensuring 

discussion, compromise, and creative settlement of 

differences-spurs innovation, often consisting of 

new interjurisdictional efforts. One of the measures 

of a productive public economy is the level of 

entrepreneurial activity aimed at addressing problems, improving services, or securing more efficient 

and effective service production.22 

These criteria do not answer performance questions 

directly, such as how good garbage pick-up or police protection or street maintenance may be in any jurisdiction of 

a metropolitan area. The criteria do identify processes or 

arrangements that are necessary to effective and efficient 

performance, even if they do not guarantee it. 

Additional criteria are needed to evaluate fiscal relationships among local governments. These are: 

Productive Efficiency. Are services and service components produced for populations large enough to 

capture any returns to population size? Are there significant uncaptured economies of scale or size? 

Equity. Do fiscal differences among local jurisdictions 

reflect patterns of racial or income differences? To 

what extent are some types of communities relatively 

advantaged or disadvantaged in fiscal capacity? 

Although fiscal data alone, without performance measures, do not permit a definitive assessment of efficiency 

or equity, the relationships among fiscal variables provide 

an indication in each case. 

THE ALLEGHENY COUNTY CASE STUDY 

Allegheny County was selected for study because it is, 

by conventional measure, the premier fragmented metropolitan county with more than one million residents. By 

Census of Governments count, Allegheny County had 323 

governments in 1982. With a 1980 population of 1,450,186, 

Allegheny County’s fragmentation “score” is 2.23 governments per 10,000 residents. St. Louis County has a fragmentation score of 1.55, while Cook County, Illinois, with 

516 governments, has a score of 0.98. 

Allegheny County, like St. Louis County, is a “hard 

case” in the sense that by traditional accounts of metropolitan organization it should exhibit all of the pathologies of 

fragmentation. If confusion, discord, and a lack of cooper- ation among independent governments are characteristics 

of fragmented metropolitan areas, Allegheny County 

should exhibit them all. 

Allegheny is the central county of the four-county 

Pittsburgh metropolitan area, which contains a total popu- lation of 2.2 million. Pittsburgh, Allegheny’s central city, is 

home to nearly 30 percent of the county’s population and 

the principal place of work for many more. The county 

outside of Pittsburgh is fully incorporated by an additional 

129 m~nicipalities~~ thatrange in population from 127 to 

nearly 58,000 (almost evenly split above and below 5,000 

population). Twelve municipalities have fewer than 1,000 

residents. Most of the municipalities are members of one 

of eight councils of governments, 

Elementary and secondary education is provided by 

43 independent school districts, with two overlapping intermediate units for specialized services. Fire protection is 

supplied principally by approximately 250 volunteer fire 

companies. Only three of the municipalities have fully 

paid fire departments, although several more employ 

some paid fire personnel. The paid and volunteer fire 

companies are linked by fire defense councils, associations 

that facilitate cooperation in fire fighting, training, and 

equipment sharing. 

By conventional measure, Allegheny County has 

more and substantially different fragmentation than St. 

Louis City and County. Pittsburgh is approximately the 

same size as St. Louis, and includes approximately the 

same proportion of city-county residents. Pittsburgh, however, is an integral part of Allegheny County, where St. 

Louis City is constitutionally separate from St. Louis 

County. There are, therefore, two nonoverlapping county 

governments in St. Louis as opposed to the single county 

government in Allegheny. Outside of their central cities, 

the areas differ in the form of fragmentation. While Al- legheny County is fully incorporated, St. Louis County is 

only 60 percent so, when measured in population terms. 

Allegheny County government is not responsible for providing urbadsuburban type services to a substantial population. St. Louis County government provides urban/ 

suburban services to nearly 400,000 residents of unincorporated territory. 

The areas differ, too, in how they provide and produce 

public services. Allegheny County has many more police 

departments and school districts than St. Louis County. 

Allegheny County has many fewer public fire departUS. Advisory Commission on Intergovernmental Relations 5 
ments, but more fire companies, most of which are volunteer. St. Louis’ departments are paid or mixed paid and 

volunteer. Allegheny County has more public departments that produce street services, but has virtually none 

of the private street associations found throughout much 

of St. Louis City and County. 

Allegheny County also has a different “reform” history. Where St. Louis and St. Louis County frequently have 

attempted total or partial consolidation of independent 

jurisdictions, Allegheny County has consistently taken a 

two-tier, federated approach, leaving existing jurisdictions 

intact. Traditional metropolitan reform has been on the 

public agenda much less frequently in Allegheny County, 

with the last major effort in 1929 (see Chapter 2). Subsequent efforts have focused on altering the structure of 

county government through adoption of home rule charters. These efforts have not been successful. 

As in St. Louis and St. Louis County, Allegheny 

County residents have not opposed efforts to address regional issues when the approach preserved local jurisdictional autonomy. Authorities for the provision and 

production of some services, such as water supply and sewage collection and treatment, overlap large numbers of 

municipalities. Eight councils of governments link municipalities in regions (see Chapter 2). Municipalities commonly cooperate for the production of police and street 

services (see Chapter 4). There is formal cooperation 

among independent school districts through overlapping 

intermediate units governed by the districts (see Chapter 

5). The volunteer and public fire companies are linked by 

membership in one of eight fire associations, and they report extensive cooperation in fire suppression and other 

activities (see Chapter 4). Thus, Allegheny County, like 

St. Louis County, is not “balkanized” in the pejorative 

sense meant by critics of fragmentation. Rather, it has a 

complex organization. Allegheny’s complexity, like its 

fragmentation, is different from that in St. Louis City and 

County, thus affording the opportunity to learn more 

about the operation of complex organizational patterns in 

mu1 tijurisdictional metropolitan settings. 

PROSPECTUS 

Chapter 2 describes patterns of growth and the present political geography of Allegheny County, including its 

municipalities, school districts, volunteer fire companies, 

and the county government. The chapter includes a broad 

description of intergovernmental cooperation, with special attention to councils of governments. Basic fiscal arrangements are described, and a history of past reform 

efforts is included. Chapter 3 analyzes the basic governance structure of the county, describing the rules that 

comprise its local government constitution. 

Chapter 4 analyzes patterns of provision and production for police, street, and fire services. Chapter 5 focuses 

on elementary and secondary education. 

Chapter 6 analyzes the political economy of Allegheny 

County. Analyses of returns to population size in service 

production and of the extent of fiscal disparities among 

the county’s municipalities and school districts are included. Chapter 7 concludes the report with a discussionof the functional dimensions of metropolitan organization 

in Allegheny County, and the application of the evaluative 

criteria discussed above. 

This study concentrated on police, street, fire, and 

education because they are large, traditional functions of 

government with predominantly local responsibilities. 

There are, however, many other local functions, such as 

mass transportation, environmental protection, solid 

waste management, welfare, and housing, in which local 

governments have significant, often growing, roles. Studies of these additional functions, along the lines of inquiry used in this report, would extend existing knowledge of 

how metropolitan governance works, and should be pursued. Until that is done, care should be exercised to avoid 

overgeneralizing the findings in this report. 

Notes 

US. Advisory Commission on Intergovernmental Relations 

(ACIR), Metropolitan Organization: The St. Louis Case (Wash- ington, DC, 1988). 

Ibid, p. 12. 

These questions are posed by Roger B. Parks and Ronald J. 

Oakerson in “Metropolitan Organization and Governance: A 

Local Public Economy Approach,” Urban Afiairs Quartedy 25 

(September 1989): 18-29. 

ACIR, The Olgaiiization of Local Public Economies (Washington, DC, 1987). 

For a comprehensive review of research on organizational and 

interorganizational structure in metropolitan areas and the relationships of structure and performance, see Vincent Ostrom, Robert Bish, and Elinor Ostrom, Local Govenunertt in 

the United States (San Francisco: ICS Press, 1988). 

Mark Schneider, “Fragmentation and the Growth of Government,’’ Public Choice 4.8 (1986): 255-263. ’ Recent reports include Randall Eberts and Timothy Gronberg, “Can Competition among Local Governments Constrain Government Spending?” Federal Reserve Bank of 

Cleveland Economic Review 24 (Quarter 1,1988): 2-9; Thomas 

J. DiLorenzo, “Economic Competition and Political Competition: An Empirical Note,”PubZic Choice 40 (1983); and Jeffrey 

S. Zax, “The Effects of Jurisdiction Types and Numbers on Lo- cal Public Finance.” in Harvev S. Rosen. ed.. Fiscal Federalism: 

Quantitative Studies (Chicagb: University of Chicago Press, 

1988), pp. 79-103. 

Christopher Bell, “The Assignment of Fiscal Responsibility in 

a Federal State: An Empirical Assessment,”Nationd TuxJoiirnal41 (June 1988): 191-207. 

David L. Chicoine and Norman Walzer, Goveniriiental Stnrctureand Local Piiblic Finance (Boston: Oelgeschlager, Gunn & 

Hain, 1985). 

lo Technical efficiency measures the transformation of available 

resource inputs to valued outputs, and thus goes beyond efficiency characterizations that focus solely on public expenditures. See Roger B. Parks, “Metropolitan Structure and 

Systemic Performance: The Case of Police Service Delivery,” 

in K. Hanf and T A. J. Toonen, eds., Policy Iiiip1ementation in 

Federal and Unita~y States (Dordrecht, Netherlands: Martinus 

Nijhoff Publishers, 1985), pp. 161-191. The complex mixture of 

service arrangements discussed here should not be confused 

with reform proposals for a simplified two-tier approach. 

l1 See the work of David R. Reynolds comparing the organiza- tion of St. Louis, Detroit, and Los Angeles in his “Progress toward Achieving Efficient and Responsive Spatial-Political 

Systems in Urban America,” in John S. Adams, ed., Urban 

6 US. Advisory Commission on Intergovernmental Relations 
Policymaking and Metropolitan Dynamics: A Coriiparative Geogmphical Analysis (Cambridge, Massachusetts: Ballingcr Pub- lishing Company, 1976), pp. 63-53. 

l2 ACIR, Metropolitan Oiganization: Die St. Loiris Case, p. 3. 

l3 The remainder of this section repeats the arguments posed in 

ACIR, Metropolitan Oqpnization: The St. Loiiis Case, pp. 3-4. 

l4 No system of government is perfect. It is always possible to 

point to problems and shortcomings. Metropolitan reform ad- vocates use the manifestation of problems and shortcomings 

to argue for reform, but the evaluation of institutional per- formance requires a compamtive assessment of institutions. 

Only on this basis can we know whether proposed reforms are 

more likely to solve problems or make them worse. The simple 

existence of problems and shortcomings does not establish 

that a metropolitan area is not comparatively well governed. 

Moreover, there are difficulties with performance measure- ment in the public sector. In the absence of a cardinal scale of 

measurement for goods and services such as police and education, the best one can do is to compare the performance of one 

institution with another. See notes 5 through 11. 

Is This distinction was introduced by Vincent Ostrom, Charles 

M. Tiebout, and Robert Warren, “The Organization of Government in Metropolitan Areas: A Theoretical Inquiry,” 

American Political Science Review 55 @ecember 1961): 

l6 Vincent Ostrom and Elinor Ostrom, “Public Goods and Public Choices,” in E. s. Savas, ed., Alternatives for Delivering Pub83 1-842. 

lic Seivices: Toward Improved Pe~obnvance (Boulder: Westview 

Press, 1977), pp. 7-49. 

l7 Elinor Ostrom, Roger B. Parks, and Gordon F? Whitaker, Pat- terns of Metropolitan Policing (Cambridge, Massachusetts: Ballinger Publishing Company, 1978). 

l8 Mark Schneider and Kce Ok Park, “Metropolitan Counties as 

Service Delivery Agents: The Still Forgotten Governments,” 

PiiDlic Administration Review 49 (July/August 1989): 345-352. 

See also Edwin Benton and Platon Rigos, “Patterns of Metro- politan Service Dominance: Central City and Central County 

Service Roles Compared,” Urban Affairs Quarterly 20 (March 

l9 These conclusions are detailed in ACIR, Metropolitan Otganization: The St. Louis Case, Chapter 8. 

2o Daniel J. Elazar, Cities of the Prairie: The Metropolitan Frontier 

and American Politics (New York: Basic Books, 1970) and 

American Federa1ism:A Viewfrom the States, 2nd Edition (New 

York: Thomas Y. Crowell, 1972), pp. 183-192. 

21 ACIR, Metropolitan Organization: The St. Loiiis Case, pp. 7-8. 

22For a further discussion of the importance of public 

entrepreneurship, see Ronald J. Oakerson and Roger B. 

Parks, “Citizen Voice and Public Entrepreneurship: The Organizational Dynamic of a Complex Metropolitan County,” 

Publiiis: The Journal of Federalism 18 (Fall 1988): 91-112. 

23 Two of these, McDonald and Trafford Boroughs, lie partially 

in Al!egheny County. The majority of the population of each 

borough resides in adjacent counties of the PMSA. 

1985): 285-302. 

U.S. Advisory Commission on Intergovernmental Relations 7 
8 U.S. Advisory Commission on Intergovernmental Relations 
Allegheny County: 

Patterns of Complex Organization 

COUNTY HISTORY AND GROWTH 

The first permanent European settlement of Allegheny 

County dates to 1742, with the construction of a log cabin 

on the shore of the Monongahela River at present-day 

Braddock.’ In 1754, French troops and their Indian allies 

drove off a small group of Virginians who were constructing a fort at the Forks of the Ohio, the confluence of the 

Allegheny and Monongahela Rivers, and completed its 

construction as Fort Duquesne. The French tenure was 

short lived, however. After an initial debacle in which a 

British expedition under General Edward Braddock (with 

aide-de-camp George Washington) was roundly defeated, 

a second British expedition led by General John Forbes 

dislodged the French in 1756, dismantling their stockade 

and constructing Fort Pitt. Fort Pitt withstood its last major Indian attack in 1762-1763, thus assuring British and, 

later, United States control of the region. The struggle for 

control over the temtory of AIlegheny County continued, 

however, with Virginia and Pennsylvania claiming jurisdiction. Virginia established early control, but the ratification 

of the Mason-Dixon line in 1780 resolved the dispute in 

Pennsylvania’s favor. 

Allegheny County came into existence in 1788, 

created from portions of Washington and Westmoreland 

counties, with the town of Allegheny designated as county 

seat. At its creation, the county extended to the shores of 

Lake Erie. As additional counties were created in Pennsylvania, Allegheny County’s borders shrank, reaching 

their current configuration by 1800. 

Pittsburgh was designated as the county seat in 1791, 

replacing its cross-river rival, Allegheny. Pittsburgh was 

incorporated as a borough under the laws of the Commonwealth in 1794 and became a city in 1816. With a population of 6,000, Pittsburgh was regarded as the “Gateway to 

the West,”* offering ready river transportation down the 

Ohio to the Mississippi and on to New Orleans. The 

county population in 1816 was roughly 10,000. 

Pittsburgh and Allegheny County grew at a rapid pace 

throughout the 19th century. Their growth was fueled by 

one of the most remarkable outpourings of commercial 

and industrial development in the United States, indeed 

in the world. The region’s development resulted in part 

from its geographic location west of the Allegheny mountains, protecting its infant glass and iron industries from 

eastern competitors, and at the origin of the Ohio river, 

yielding easy access to markets. A second factor was the richness of the region’s resources, with ampIe reserves of coal 

and other raw Still a third factor was rich human 

capital in the persons of entrepreneurs and inventors-such 

as Andrew Carnegie in iron and steel; George Westinghouse 

with air brakes and alternating current; Henry Heinz with 

horseradish, which developed into the “57 Varieties”; and 

the Mellons with their banking enterprise^.^ A fourth factor 

in the region’s development was the flood of immjgmntsinitially English, Scotch-Irish, and German, and later, Scandinavian, eastern European, and southern black-who 

worked the enormous mills in “hell with the lid off,” as Lincoln Steffens described Pittsburgh in 1903.5 

MUNICIPAL INCORPORATION 

By 1910, Allegheny County’s population exceeded 

one million, and Pittsburgh’s, 550,000. In 1907, Pittsburgh 

had become the nation’s sixth largest city by virtue of its 

merger with the neighboring city of Allegheny, a source of 

substantial controversy.6 By this time, the county’s political geography had emerged in a configuration quite similar to that found today. 

Allegheny County has been incorporated since its creation in 1788. At that time, seven townships recognized as 

municipal governments in Pennsylvania comprised the 

county. In 1800, there were ten townships. The creation of 

new municipalities, leading to the present 130 townships, 

boroughs, and cities, occurred mainly through incorporating 

new boroughs within townships, splitting townships into two 

or more separate municipalities, and, to a much lesser extent, combining smaller municipalities to form cities. 

At the end of the Civil War, 38 of the present Allegheny County municipalities were in existence.’ The major 

growth in number of municipalities occurred in the 

post-Civil War period, especiallyat the end of the 19th and 

start of the 20th centuries (43 between 1891 and 1910,12 in 

1892 alone). By 1910, the county had 108 municipalities. 

During thepost-World War I1 period, 1945-1960, when the 

number of suburban municipalities was growing rapidly 

around many American cities, growth around Pittsburgh 

slowed, with only eight new municipal governments coming into existence. Since 1960, only one new municipality 

has been created in Allegheny County. 

“Suburbanization” appears to have taken place in 

Allegheny County well before it occurred in many other 

metropolitan counties, in part because many of the new 

U.S. Advisory Commission on Intergovernmental Relations 9 
municipalities were not suburbs of the type created in later years. They were not tracts of residential housing providing escape from the central city. They were “mill 

towns,”created at the instigation of private entrepreneurs 

to encapsulate their major mills and factories, protect 

them from taxation and regulation, and provide them with 

local police powers that could be and were used to ward off 

union organization in the mills.’ 

Twenty-nine municipalities were created in the valleys of the Monongahela and Youghiogheny rivers and 

along nrtle Creek after the Civil War, all but four by 1910. 

These municipalities (Braddock, Rankin, East Pittsburgh, 

Munhall, Duquesne, Clairton, and their neighbors) were 

places of immense industrial creativity. The mills and factories built there, most of which are idle today, employed 

upwards of 100,000 men in theirprime, and stand as monuments to their creators and to those who worked in them. 

In the early days of air transportation, the glow at night 

from the “Mon Valley” blast furnaces provided pilots with 

their major navigational checkpoint when flying west from 

New York toward Chicago. 

During this period, 25 new municipalities were 

created in the valleys of the Allegheny and Ohio rivers. If 

not mill towns, many of these were at least company 

towns, incorporated to buffer a new commercial or industrial enterprise from undue taxation and to provide it with 

a friendly local administration. Incorporations of new resi- dential communities occurred, some of them on the hills 

above the company towns, to provide amenities for mill owners and managers. The period was one of massive immigra- tion from Europe, especially eastern Europe. Social and 

ethnic segregation in separately incorporated municipalities 

allowed accommodation to distinct differences in life styles. 

Around the lowland mills crowded the immigrants, 

the Slavs, the Germans, the Italians, and the Irish 

with their tolerance for saloons and their devotion 

to the Roman Catholic Church. On the has lived 

the Presbyterians with their abhorrence for alcohol 

and their dedication to Protestantism? 

Areas outside of the river valleys developed and incorporated as transportation routes linking them to Pittsburgh 

were established. Communities in what is now called Parkway West developed after the opening of the Point Bridge in 

1876. Communities in the South Hills and Parkway West developed further as inclines were constructed on Mts. Washington and Oliver, and after the boring of the Liberty and 

Fort Pitt tubes through Mt. Washington. 

METROPOLITAN REFORM 

IN ALLEGHENY COUNTY 

Throughout the first three decades of the 20th century, Pittsburgh expanded its boundaries through annexations-the forced annexation of the city of Allegheny in 

1907 being the largest.’” These annexations were authorized by special legislation enacted by the Pennsylvania 

General Assembly, allowing the mergers to be decided by 

a simple majority of voters in Pittsburgh and the area to be 

annexed, rather than by concurrent majorities in both. In 

response, the League of Boroughs and Townships of Ale-- 

gheny County was formed in 1910-11 to combat Pittsburgh’s initiatives in the General Assembly.” The league 

was successful in defeating several annexation bills and 

other legislation to create a metropolitan district government during the years up to 1923. Pittsburgh continued to 

grow by annexation, principally where residents of the 

area to be annexed signed petitions suppoiling annexation.I2 Pittsburgh legislators continued to submit bills to al- low unilateral expansion by the city. They were concerned 

that Pittsburgh was falling behind its industrial rivals in population size and, therefore, attractiveness to new industy. 

In 1923, the Commission to Study Municipal Consolidation was appointed by the governor, with representatives of Pittsburgh, the third class cities of Clairton, 

Duquesne, and McKeesport, and the boroughs and townships in Allegheny County. The commission, with re- search support from prominent political scientists 

associated with the National Municipal League, developed an enabling amendment to the Pennsylvania Consti- tution authorizing residents of Allegheny County to 

create, if they so chose, a federated city of Pittsburgh. The 

federated city would become, its proponents argued, the 

nation’s fourth largest city in the 1930 census. The amendment was approved by the General Assembly and by voters statewide in 1928. The commission submitted a charter 

for a federated city to the General Assembly the following 

year. After substantial amendment to limit the functions 

to be consolidated, the proposed charter was approved 

and sent to Allegheny County voters for their consideration.13 All existing municipalities were to be retained intact. 

In June 1929, the charter was voted on, receiving a 68 

percent majority of positive votes countywide and majori- ties in 82 of 123 municipalities-exactly two-thirds. The 

vote was not sufficient for adoption of the plan, however. 

The commission had proposed a majority vote in a major- ity of communities; the state Senate changed the requirement to a majority vote in two-thirds of the communities; the 

House of Representatives modified the rule again, to a 

two-thirds majority in a majority of communities. It was this 

last requirement that defeated the plan-the two-thirds majority was obtained in only 50 of the 123 rnunicipalitie~.’~ 

There was some controversy over whether the House 

amendment was a fluke or a deliberate action by opponents of the plan. The president of the League of Boroughs and Townships, Joseph T. Miller, also chairman of 

the commission and a strong supporter of the plan, described the action as no more than a “printer’s option in 

setting his type,” but others were more skeptical. “One 

Pittsburgh reformer” was quoted saying that “it would be 

difficult to elect the twelve Apostles if one had to get a 

two-thirds vote from all the boroughs and townships in 

Allegheny County.”15 Whether a fluke or not, it allowed a 

minority of county residents from predominantly working 

class and rural cities, boroughs, and townships to thwart the 

wishes of a substantial majority of their fellow citizensi6 

Joseph Miller and others continued to argue for reform in Allegheny County following the 1929 charter defeat, but with little success. In 1951, a Metropolitan Study 

Commission recommended the transfer of a number of 

functions from municipalities to the county. County as10 U.S. Advisory Commission on Intergovernmental Relations 
Region 

Pittsburgh-Mt. Oliver 

Allegheny-Valley North 

Eastern Suburbs 

Mon Valley 

South Hills 

Parkway West 

Ohio Valley 

North Hills 

Table 2.7 

Allegheny County Demographics, by Region 

Percent Percent 

Number below Per Per Change 

of Percent Poverty Capita Capita in Real 

Munici- Population Nonwhite Line Income Income Income 

palities’ (1984 est.) (1980) (1979) (1979) (1985) (1979-85) 

2 406,943 

17 73,390 

7 151,289 

33 199,194 

14 237,524 

22 13 1,432 

18 39,298 

15 170,093 

24.7% 

1.7% 

12.4% 

10.1% 

2.1% 

3.6% 

4.1% 

1.2% 

16.5% 

6.5% 

5.1% 

10.3% 

3.7% 

6.8% 

5.6% 

4.2% 

$6,838 

9,200 

8,163 

7,067 

9,529 

7,878 

9,836 

8,774 

$9,985 

13,540 

11,621 

9,500 

13,649 

11,086 

14,292 

12,649 

-2.2% 

-1.4 

-4.6 

-10.0 

-4.1 

-5.7 

-2.7 

-3.4 

Total County’ 128 1,409,163 10.9% 9.1% 8,003 11,439 -4.3% 

Excluding McDonald and Trafford. 

Source: Pennsylvania State Data Center, Diskette User’s Data Express (LlUDEl); and 1980 Census of Population and Housing. Data 

Tape STF-3. 

sumption of responsibilities for public health, a regional 

transit authority, and libraries was implemented to greater 

or lesser extent. Assumption of broader responsibilities 

was rejected, as was an urban home rule charter for the 

county. Later attempts to adopt a home rule county charter were defeated at the polls in 1974 and 1978. Residents 

of Pittsburgh and 16 other municipalities approved home 

rule charters during this period. County home rule, however, is thought to imply a greater county role in metropolitan governance. The strong attachment to local authority 

found among county residents and local officials (see below) 

prompted their defeat of the county home rule proposals. 

COUNTY DEMOGRAPHICS 

Allegheny County can be thought of as an amalgamation of many diverse “neighborhoods.” Pittsburgh is composed of distinct, identifiable neighborhoods, many with 

strong community-based organizations.” Many of the 

neighborhoods outside Pittsburgh are incorporated as independent municipalities, while other municipalities contain many neighborhoods within their boundaries. 

Describing the county at the neighborhood level is a 

taskbeyond the scope of this study. Even describing it municipality by municipality would be tedious. Fortunately, 

the neighborhoods and municipalities lie naturally in a 

smaller number of identifiable regions. These regions, with 

names like the Mon Valley, North Hills, and Parkway West, 

contain relatively identifiable population groupings that tend 

to differ from one another. The following discussion of 

county demographics is organized around these regions. “ 

Race 

In 1980, approximately 11 percent of Allegheny 

County’s population was nonwhite, virtually all of them 

blacks. The black population is concentrated predominantly in Pittsburgh (two-thirds) and in a small number of 

communities located east and southeast of Pittsburgh, including the Mon Valley communities of Braddock, Clairton, Duquesne, Homestead, McKeesport, and Rankin, 

and adjoining communities in the Eastern Suburbs, such 

as Monroeville, Penn Hills, and Wilkinsburg. This concentration is illustrated in able 2.1, with Pittsburgh’s nonwhite percentage approximately twice the county average, 

the Eastern Suburbs and Mon Valley at or near that average, and low percentages in the remaining regions. 

Income 

In 1979, approximately 9 percent of the county’spopulation had incomes below the poverty level (see %ble 2.1). 

The lowest per capita incomes and the highest percentage 

of residents with incomes below the poverty level were in 

Pittsburgh-Mt. Oliver, followed by the communities in the 

Mon Valley. Between 1979 and 1985, per capita income 

(measured in constant 1982 dollars) declined by 10 percent 

in the Mon Valley, as a result the closing of major steel 

mills and related businesses during and following the recession of 1982. Most of the mills remain closed, and many 

former mill workers are ~nemployed.’~ The highest per 

capita incomes in 1985 were in the Allegheny Valley 

North, South Hills, and Ohio Valley communities. Especially low-ranking communities were Braddock, Duquesne, Haysville, Homestead, North Braddock, and 

Rankin, all with per capita incomes below $8,000. The top 

end of the income scale included Edgeworth, Fox Chapel, 

and Sewickley Heights, all with per capita incomes approximating $40,000. 

Figure 2.1 is a scatter plot of the percentage change in 

real per capita income changes measured in constant dollars from 1979 to 1985 against 1979 per capita income. The 

economic plight of many Mon Valley communities is high- lighted in the Figure. Mon Valley communities are identified by an open box and communities in the rest of the 

county by an “x.” Most Mon Valley communities were 

among the lowest in per capita income in 1979, and they 

suffered among the greatest percentage declines in income from 1979 to 1985. 

Duquesne, Munhall, and Liberty, for example, had declines of 14 percent or greater in real income. Communities 

U.S. Advisory Commission on Intergovernmental Relations 11 
Figure 2.1 

Change in Real Per Capita Income, 1979-1 985 

(constant 1982 dollars) 

15.0!%, I 

0 5 10 15 20 2s 30 3s 

Per Capita Income in 1979 (thousands) 0 = Mon Valley community. 

with the greatest percentage increase in real per capita income over this period included Marshal (+ 11.2 percent), 

Bradford Woods (+ 9.9, Blawnox (+ 8.4), and Ohio (+ 7.6). 

BASIC POLITICAL GEOGRAPHY 

Allegheny County has 128 municipalities of six legal 

classes.20 (The constitutional and statutory rules for each 

class and their governmental structures are discussed in 

Chapter 3). Municipalities include one second class city, 

Pittsburgh, with a home rule charter; two third class cities, 

Clairton and Duquesne; 76 boroughs; 33 townships-21 of 

the first class and 16 of the second class; and 16 home rule 

municipalities in the suburban county. Of the home rule 

municipalities outside Pittsburgh, one was originally a 

third class city; six were boroughs, five were first class 

townships, and four were originally second class townships. In addition to the municipalities, there are 43 independent school districts. Overlaid on these municipalities 

and school districts are 8 councils of governments 

(COGs), 2 educational intermediate units, 136 single purpose municipal authorities, 13 multipurpose authorities, 

and the Allegheny County government. The county also 

contains some 250 volunteer fire companies, which operate more or less independently of the municipalities in 

which they are located. Counting only publicly organized 

provision units, excluding fire companies but including 

COGs, intermediate units, and municipal authorities, the 

number of local governments in Allegheny County is 330. 

Allegheny County’s population in 1984 was 1,409,163, 

yielding a ratio of approximately one governmental unit 

for every 4,300 county residents. By this ratio, Allegheny 

County is shown to have more governments for its population than any other county with one million residents or 

more in the United States. 

Municipalities 

Most of Allegheny County’s municipalities are 

small-68 of them, more than half, had fewer than 5,000 

residents in 1984, and 12 have fewer than 1,000. Figure 2.2 

depicts the municipal geography of Allegheny County, 

Table 2.2 

Municipal Governments in Allegheny County 

Population Percent of Land Area 

Population Number’ (1984 est.) Total Population (square miles) 

0-1,000 12 6,358 0.5% 16.0 

l,oo 1-2,000 18 27,490 20 36.9 

2,001-5,000 38 133,453 9.5 152.4 

5,001-10,000 32 248,732 17.6 176.7 

10,001-20,000 14 195,308 13.8 111.0 

20,001-58,000 13 395,239 28.0 181.5 

Pittsburgh 1 402,583 28.6 55.1 

Totals 128 1,409,163 100.0 729.6 

Excluding McDonald and Trafford. 

Source: Pennsylvania State Data Center, Diskette User’s Data Express (DUDE1). 

Percent of 

Total Land Area 

2.2% 

5.0 

20.9 

24.2 

15.2 

24.9 

7.6 

100.0 

12 U.S. Advisory Commission on Intergovernmental Relations 
and Bble 2.2 describes the distribution of local governments in population and land area. Despite the presence 

of many small municipalities in the county, most Allegheny 

County residents live in the larger municipalities. Eighty 

percent of the municipalities contain only about 30 percent of the county population. Pittsburgh includes 29 percent of the county population, and municipalities with 

populations of more than 20,000 residents accounted for 

another 28 percent.21 

A remarkable feature of municipal government in Allegheny County (and throughout Pennsylvania) is the large 

number of locally elected officials. Although a complete 

count is not available, the minimum number that could be 

elected under the governing codes is nearly 1,300, or approximately one elected official for every 1,100 citizens. 

Thisis one of the highest elected official to citizen ratios in 

the nation.22 

Especially in the smaller municipalities, elected officials 

serve as part-time administrators of municipal affairs. In the 

smaller boroughs and townships, elected council members, 

commissioners, and supervisors exercise collective responsibility for municipal service delivery, with administrative support from a part-time municipal secretary. Of the 68 

communities with populations of less than 5,000, only 12 reported full-time managers, and 5 had full-time secretaries in 

198’7F3 Larger municipalities were more likely to have 

full-time administrators. Thirteen of the 32 municipalities 

with populations between 5,OOO and 10,OOO employed 

full-time managers; 8 employed full-time secretaries. Of the 

27 municipalities with populations greater than lO,OOO, all 

but three reported a full-time manager or secretary. 

Pittsburgh, with a 1984 population exceeding 400,000, 

is the largest municipality in the county. The next largest, 

Penn Hills, has fewer than 60,000 residents, and only 13 

suburban municipalities exceed 20,000 population. The 

two third class cities include slightly more than 20,000 residents and less than 5 percent of the county land area 

Wble 2.3). The most numerous municipalities by type are 

76 boroughs, which together contain approximately the 

same percentage of the county population as Pittsburgh. 

However, because of their larger land area, they are less 

densely populated on average than the central city. First 

class townships include about 14 percent of the county 

population and nearly 19 percent of its land area, while 

townships of the second class include 5 percent of the population and 25 percent of the land area. The second class 

townships comprise most of the semi-rural, relatively undeveloped parts of the The 16 suburban home 

rule municipalities include 22 percent of the county population and 25 percent of its land area. 

Since Pittsburgh is a home rule city, slightly more than 

half of Allegheny County’s citizens reside in communities 

with home rule powers. Twelve of the 16 home rule munic- 

@ties employ full-time managers, while one reported employing a secretary full time. Full-time managers or 

secretaries were also reported by more than half of the fmt 

class townships and two-thirds of townships of the second 

class. Boroughs are much less likely to have full-time administrators in manager (19) or secretary (10) positions. 

LOCAL ATTACHMENT 

A strong attachment to local authority characterizes 

Allegheny County officials and citizens.25 Allegheny 

County residents are often second, third, and even fourth 

generation residents with firm social ties to their communities. This attachment carries over into a stout resistance to 

proposals that would consolidate local municipalities. 

“Metropolitanism” is a term that is widely known and used 

with a distinctly negative connotation throughout the suburban portion of the county. Although willing to engage in a 

variety of interjurisdictional cooperative ventures and to 

create overlying arrangements for particular purposes, residents and local officials have not been willing to entertain 

proposals that would erase the separate identity of their 

communities. Metropolitan reform, at least in the traditional 

sense, is not part of the policy agenda of Allegheny County. 

Various factors explain this enduring attachment to 

local communities, although no single one is overriding. 

These factors include historical patterns of municipal development and reform in the county and the state, together with economic, social, ethnic, and topographical 

features of the county. 

To begin with, the topography is more conducive to 

the formation of local than countywide attachments. The 

county is cut into three sections by its major rivers, the Allegheny and the Monongahela, which combine in Pittsburgh to form the Ohio. The Youghioheny River and 

Turtle Creek further bisect the southeastern part of the 

county. Bridges across these rivers afford some linkages 

among separate communities-Pittsburgh is tied together 

by such bridges-but for long stretches of each river no 

cross-river traffic is possible. Steep ridges rise rapidly from 

the river banks in much of the county, making traffic between river valleys and surrounding areas difficult. Ravines cut partially into these ridges, making traffic along the 

river valleys difficult in a number of areas. Outside of the river valleys, much of the county’s terrain is quite rugged, repeating the pattern of steep ridges cut by ravines.26 

Original settlements in Allegheny County formed 

along the river banks and in the ravines running down to 

the rivers, on the hilltops cut by these ravines, and in similar topographic formations along and above the many 

streams. These settlements could not easily expand into 

one another as they grew, and so amalgamation into larger 

communities was slowed if not prevented. Following 

adoption of a permissive incorporation law in 1834, settlements as small as 300 persons could secede from existing 

townships, forming new townships and borough^.^' 

Economic forces, too, worked to create and maintain 

many distinct communities. The river valleys, as discussed 

above, are home to many relatively small towns, most of 

which have existed for close to a century, if not longer. 

These towns, created at the instigation of or captured by 

the owners of their large industrial plants, served to protect those investments from taxationby largerunits of government, and provided the mill owners with local police 

powers that could be used against union organizers. Absentee industrial property owners exerted major influence 

U.S. Advisory Commission on Intergovernmental Relations 13 
Figure 2.2 

Allegheny County Municipalities 

14 U.S. Advisory Commission on Intergovernmental Relations 
~~ ~~~ ~ 

Table 2.3 

Types of Municipalities in Allegheny County 

Class of Population Percent Land Area Percent 

Municipality Number’ (1984 est.) of Population (square miles) of Land Area 

Second Class City (Pittsburgh) 1 402,583 28.6% 55.1 7.6% 

Third Class City 2 22,040 1.6 4.5 0.6 

Borough 76 409,149 29.0 171.9 23.6 

Second Class Township 12 70,617 5.0 181.4 24.9 

Home Rule 16 309,360 22.0 181.9 24.9 

First Class Township 21 195,414 13.9 134.8 18.5 

Total County 128 1,409,163 100.0 729.6 100.0 

Excluding McDonald and Trafford. 

Source: Pennsylvania State Data Center, Diskette User’s Data Express (DUDEl). 

over government and politics in these towns for many 

years.28 Although their influence waned with the closing 

of the mills, a process mostly completed by the recession 

of the early 1980s, the spirit of local autonomy they helped 

to foster continues today. 

A further contribution to strong local attachments is the 

ethnic diversity of Allegheny County. Immigrants from many 

nations and ethnic backgrounds flocked to the county seeking the jobs made available by the rapid industrialization of 

the post-Civil War period through World War I. In 1910, 

more than 600,OOO of the county’s one million residents were 

either foreign born or the children of foreign-born parents.% 

Black Americans, too, migrated to the countyduring thispenod, also seeking jobs in the expanding industries.30 A 1922 

description, albeit of Pittsburgh and not the entire county, 

remains applicable in many areas today: 

. . . Pittsburgh is a city in which are many isolated 

settlements and communities, difficult or indirect of access. [The foreign born exhibited the] 

natural tendency to live in groups according to 

nationality. This tendency, combined with classifications of an economic character. . . is often further intensified by the physical segregation 

induced by the rough t~pography,~~ 

Prior instances of forced consolidation, including the annexations by Pittsburgh discussed earlier, contniute to 

strong local attachments. In the early 196os, many school districts were forced to consolidate with one or more of their 

neighbors in order to receive state funds for education. 

Those mergers, according to several persons interviewed for 

this study, continue as an unpleasant memory for many 

county residents, contributing to their wariness toward initiatives that can be tarred with the label of metropolitanism. 

OVERLAPPING JURISDICTIONS, 

SPECIAL DISTRICTS, 

AND QUASI-GOVERNMENTS 

In spite of and perhaps related to their preferences 

for independent local jurisdictions, Allegheny County residents have developed a number of overlapping jurisdic- tions and cooperative ventures that link politically 

autonomous units in functional combinations. These combinations contribute significantly to the viability of the 

county’s system of local government. In Allegheny 

County, as elsewhere, jurisdictional fragmentation does 

not necessarily produce functional fragmentation. 

County Government 

The principal local jurisdiction is the Allegheny 

County government. It is the only second class county in 

Pennsylvania. Its form of government is the same as that 

of most counties in the commonwealth, with the exception 

of Philadelphia (the only first class city-county) and a few 

counties that have adopted home rule charters. Residents 

elect three county commissioners, who serve as the governing board, and a number of “row offices,” including 

sheriff, district attorney, prothon~tary,~~ clerk of courts, 

register of wills, recorder of deeds, two jury commissioners, controller, and treasurer. 

Special Districts 

and Quasi-Governmental Jurisdictions 

Overlaid on the municipal and county governments of 

Allegheny County are many special district governments 

and quasi-governmental units. School districts are the 

only form of extra-municipal special district allowed direct 

access to the taxbase in Pennsyl~ania.~~ Somewhat akin to 

special districts elsewhere, but limited to the issuance of 

revenue bonds to finance their operations, are singlepurpose and multipurpose “municipal authorities,” many 

of which extend across municipal or school district boundaries. Nestled within the borders of most municipal governments are the service areas of one or more of the 

volunteer fire companies. These companies, while organized independently of municipal governments, are supported in part by municipal revenues and, often, have 

contractual linkages to the municipalities in which they 

are found. 

School Districts and Intermediate Units 

The 43 independent school districts range in size from 

the Piltsburgh-Mt. Oliver district, with an average daily student membership of approximately 4O,OOO, down to approximately 900 students. District populations range from fewer 

than 9,000 persons to more than 400,OOO. School districts are 

organized both within and across municipal boundaries. 

U.S. Advisory Commission on Intergovernmental Relations 15 
School districts are governed by nine-member school 

boards elected at large. The school boards “hire all school 

personnel, provide for school buildings, buy textbooks and 

other supplies, levy taxes, and issue bonds for school purpose~.”~~ A district superintendent is chosen by the board 

to provide administrative leadership. 

Overlaid on the school districts are intermediate units, 

“established to provide specialized services on a regional bask*,)35 Intermediate units were established originally by the 

Pennsylvania Department of Education, but are governed by 

boards composed of local school board members. There are 

two intermediate units in Allegheny County, one organized 

by the Pittsburgh school district, which also includes the municipality of Mt. Oliver, and the second by the remaining 42 

districts. The intermediate units provide “consultative, advisory, and educational program services to component school 

districts,” and “furnish ancillary services necessary to provide 

opportunity for adequate basic services to all One 

important service provided by intermediate units is special 

education for handicapped students. 

Municipal Authorities 

Municipal authorities are corporate political bodies 

established by other local government units for purposes 

of borrowing money and supplying one or more specialized services. Many authorities were created to overcome 

restrictions on municipal and school district debt that 

applied prior to state constitutional amendments adopted 

in 1968. Even though these debt restrictions are no longer 

as stringent, authorities have continued to be created at a 

significant rate. About one-third of the existing active authorities were created after this constitutional change, 

with significant additions in water, sewer, and health authorities. There were 136 single-purpose and 13 multipurpose authorities in the county in 1985.37 

The largest number of authorities provide school 

buildings,38 sewer or water facilities, and parking facilities. 

The largest authorities are the Allegheny County Sanitary 

Authority (ALCOSAN), providing sewage collection and 

treatment for Pittsburgh and many county municipalities; 

Port Authority Transit (PAT), operatinga countywide transit system created from the consolidation of a number of 

failing private transit companies; and the Municipal Authority of the Borough of West View, which provides water 

service to many municipalities in Allegheny and adjacent 

counties. Municipal authorities, unlike other local government units (except two intermediate units), have nodirectly elected governing officials. They are governed by 

boards, with members appointed by the governing bodies 

of the units that create them. 

Volunteer Fire Companies 

An estimated 250 volunteer fire companies are the 

principal providers of fire protection in suburban Allegheny 

County.39 The companies serve all municipalities, except 

Pittsburgh, McKeesport, and Wilkinsburg, which have 

full-time paid departments. Some municipalities employ a 

few paid fire fighters, often as drivers for municipally 

owned equipment, while relying predominantly on the 

volunteer companies for fire suppression. The volunteer 

companies have no legal standing as units of government, 

but most of them receive partial funding from the municipalities. The companies select their own members, elect 

their own officers, and raise the bulk of their revenues 

through public appeals, carnivals, bake sales, bingo games, 

and the like. By local reports, frre companies are important 

actors in local politics, endorsing candidates for local office 

and supporting the campaigns of those endorsed. 

PU BLlC ENTREPRENEURSHIP 

AND THE DEVELOPMENT 

OF MULTIORCANIZATIONAL 

ARRANGEMENTS 

Allegheny County is overlaid with a variety of functional and intergovernmental arrangements that serve to 

knit separate governmental units together to pursue common purposes. The county government and a number of 

public and private associations, organizations, and individuals support existing arrangements and foster the development of new ones. Among the functional overlays are 

the intermediate units for public education and fire defense councils and associations linking the volunteer fire 

companies. Multijurisdictional functional arrangements 

are found in police and street services as well. The councils of governments (COGS) are multifunctional overlays 

in addition to the county government. 

During this century, there have been several efforts to 

reform the municipal political geography. These efforts, 

envisioning a two-tier, federated structure with an enhanced role for county government, have been resisted by 

citizens and officials. In the words of a 1982 report sponsored by the Allegheny Conference on Community Development (ACCD) on prospects for intergovernmental 

cooperation in the county, “(1)t appears likely that such efforts, however well intentioned, will continue to be 

doomed as long as they smack of ‘metropolitanism’ or in 

any way resemble efforts to restructure local government.”40 While major local government restructuring in 

Allegheny County, as elsewhere in metropolitan America, is not viewed with favor, interlocal cooperation has 

created a network of functional ties and overlays that con- tinues to grow. The Allegheny Conference surveyed citizens and elected and appointed officials, and found that: 

Citizens indicate strong support for intergovernElected officials indicate substantial support for 

mental cooperation. 

cooperation. 

Appointed officials indicate high levels of involvement in cooperative arrangements and perceive even 

greater potential for future cooperati~n.~~ 

The consortium recommended a number of actions to encourage such cooperation. To a greater or lesser extent, 

most of the recommended actions have been undertaken. 

This is not to say that cooperation and coordination 

have been achieved in all parts of the county or in all ser- vices. Instances of failure to cooperate or coordinate similar services among municipalities can be found in most of 

the county. Local attachments and “turf” considerations 

16 U.S. Advisory Commission on Intergovernmental Relations 
have impeded joint ventures. Such ventures require careful negotiation and attention to local prerogatives. Assessing the extent of desirable cooperation and coordination 

among municipalities and other governmental units in Allegheny County is akin to the fabled “half-full or halfempty” conundrum. A wide variety of joint ventures can 

be identified, and public entrepreneurship continues to 

seek ways to increase the range of cooperative and coordinated arrangements. 

Jurisdictional fragmentation is often fertile ground 

for public entrepreneurship. Entrepreneurial efforts proceed within the informal bounds laid out by long-standing 

public opinion. Within these constraints, elected and appointed officials in the county government, municipalities 

and school districts, local foundations, universities, community organizations, and intergovernmental organizations exercise the initiative associated with public 

entrepreneurship. 

Among the organizations active in fostering intergovernmental cooperation in Allegheny County are the 

county commissioners and various departments and bureaus of county government; the state, principally through 

the regional office of the Department of Community 

Affairs; the Allegheny League of Municipalities and its 

constituent organizations; the subcounty councils of governments; the Southwestern Pennsylvania Regional Planning Commission; academics from the major universities; 

and private and nonprofit organizations, such as the Allegheny Conference on Community Development, the Intergovernmental Cooperation Program now housed with 

the Greater Pittsburgh Chamber of Commerce, the Pennsylvania Economy League, and the Coalition to Improve 

Management in State and Local Government (at Carnegie Mellon University). 

County Government 

as an Intergovernmental Partner 

The county government is an active participant in numerous interlocal cooperative ventures, and often an initiator or sponsor. In 1968, the county established the 

Authority for Improvements in Municipalities with a $30 

million bond issue. Managed by the county’s Department 

of Development, the authority makes loans and grants to 

municipalities for infrastructure improvements. Through 

1986, the authority’s loans totaled $12 million and its 

grants, $5.6 million>* The grants are used to encourage 

functional cooperation, as in the sewer maintenance and 

cleaning program (SMAC), in which equipment was purchased for each COG for use in its member municipalities. 

The SMAC program was developed as part of the Intergovernmental Cooperation Program (see below), as was 

the Local Government Academy, which provides training 

for officials and their staffs. The academy is now funded 

principally by the county government. 

The Department of Development administers the 

county’s community development block grant (CDBG) 

funds, principally through COGS, which consider requests 

for funding and approve bids on projects. 

The county departments of Planning and Development have been working with groups of municipalities to 

develop cooperative storm water management systems. 

One such system, an intermunicipal stormwater district, 

would cover 24 municipalities in the North Hills, and would 

be funded by user charges. Authorization for such a system 

requires state legislation, which the county is ~eeking.4~ 

The county also assists municipalities in augmenting 

local service capacities. The County Police and Fire Training Academy offers entry and in-service training for police 

and fire fighters, with reimbursement from the state. The 

county operates a crime lab that is used by municipal de- partments, and county police supply back-up investigative 

services on request. 

The county government has been active in attempts to 

reduce the economic distress of communities that suffered major losses from the decline of steel and related industries, especially in the Mon Valley. In 1986, the county 

commissioners appointed a 16-member Mon Valley Com- mission to study problems and make recommendations for 

revitalization. Based on detailed reviews of data, studies, 

and public forums convened by seven task forces, the commission recommended priority actions to assist citizens 

and local governments. Recommendations related to local 

government included: 

Prepare legislation and regulations for a larger 

state role in monitoring municipalities, preventing distress, and intervening where necessary. 

Evaluate alternative structures, including the 

creation of a service district, COG based where 

possible, to undertake major functions, such as: 

water, sewer, stormwater, waste disposal, and, 

potentially, parks and recreation, planning, code 

enforcement, and development. 

Assist municipalities in evaluating their fiscal and 

management capacities and in taking remedial 

action. 

Provide targeted incentives for local government 

modernization, such as conditional loans and 

grants.44 

The commission drew particular attention to a need for 

“increased cooperation among communities” in the 

Valley, citing existing COGS as a structure for such cooperati~n.~’ Partial implementation of the commission’s rec- ommendations is under way, including an assessment of 

local governments’ service capacities undertaken by the 

Southwestern Pennsylvania Regional Planning Commission. 

Allegheny league of Municipalities 

The Allegheny League of Municipalities (ALOM) 

links associations of boroughs and townships of the first 

and second class, and serves as secretariat for each. Membership in ALOM is maintained by Pittsburgh, the third 

class cities of Clairton and Duquesne, three large home 

rule municipalities (McKeesport, Mt. Lebanon, and Penn 

Hills), and two large municipal authorities (ALCOSAN 

and Westview Water Authority). The league is active in 

lobbying the General Assembly for legislation beneficial 

to its membership and sponsors a conference each spring 

to bring together local elected officials and members of the 

U.S. Advisory Commission on Intergovernmental Relations 1 7 
Table 2.4 

Allegheny County Councils of Governments (COGs) 

I Name Members Location Major Services* 

Turtle Creek Valley 

Steel Valley 

Twin Rivers 

Quaker Valley 

Char-West 

North Hills 

Allegheny Valley North 

South Hills Area 

17 

9 

11 

15 

20 

12 

15 

15 

Southeast, Near Pittsburgh 

South, in Mon Valley 

Extreme Southeast 

Northwest 

West, Near Airport 

North 

Northeast 

Southwest 

Payroll and billing 

Street maintenance pool 

P 1 an n i n g 

Shared finance manager 

Joint dispatch Firing range 

Joint purchasing 

Planning (airport expansion and solid waste) 

Credit Union 

Planning (emergency management) 

Planning (priority street maintenance) 

Credit union 

Joint purchasing council 

1 *In addition to CDBG and SMAC activities. 

General Assembly. The league is fiianced by its members, 

by a contribution from the county commissioners, and by 

funds raised from workshops and the annual conference. 

ALOM sponsors two nonprofit corporations-Municipal Risk Management (MRM), which performs a broker/ 

agent function in securing workmen’s compensation insurance, and Municipal Risk Property & Casualty 

(MRPC), which performs a similar role in securing property/casualty insurance. MRM and MRPC negotiate 

group policies for members, resulting in substantial dollar 

savings on their insurance coverage. ALOM formed these 

corporations in 1980 after exploring the possibility of a 

risk-sharing, self-insurance pool among its members, finding that Pennsylvania law did not permit a self-insurance 

pool, and lobbying successfully for legislation that allowed 

pooling of insurance coverage among municipalities. 

Councils of Governments 

Municipalities in Allegheny County have formed 

eight councils of governments (COGs) that provide a continuing association among member boroughs, townships, 

and third class cities. The legal form of association is a 

voluntary intergovernmental agreement adopted by ordinance or resolution of each governing body. The Pennsylvania Department of Community Affairs (DCA) argues 

that this form of association becomes valuable when there 

are cooperative agreements among several municipalities 

or for several functions.& COGs were formed in various 

parts of the county during the 1970s, beginning withTurtle 

Creek Valley COG, just southeast of Pittsburgh, in 1971. 

A small COG formed in the Churchill area east of Pittsburgh became inactive in 1982.47Two COGs in the western 

part of the county merged to form Char-West COG in 

1981. Of the 130 municipalities in the county, 114 are now 

COG members, including 86 percent of the county population outside Pittsburgh [Table 2.41. 

The county government, although not formally a 

member of any COG, maintains an active liaison with each 

of them through its Department of Development and Authority for Improvements in Municipalities. One of the 

principal COG activities has been the distribution of 

CDBG funds allocated to them by the county government, which receives federal CDBG funding for all municipalities except Pittsburgh and “hold harmless” Model 

Cities. The success of the COGs can be traced in part to 

their usefulness in implementing the CDBG program. 

The COGs also participate in the SMAC program, initially funded by the county government in 1984, producing 

services for member municipalities on a fee basis. 

Although state law does not prescribe a structure for 

governing, financing, and administering COGs, a fairly 

common pattern has evolved, with variations in detail. 

Most COGS have two governing bodies: a general assembly composed of all elected officials of the member municipalities, which meets annually to review COG activities, 

adopt the budget, and amend by-laws; and a board of directors, usually composed of one elected official designated by each municipality, which meets monthly. One of 

the COGs experienced a controversy over the participation of borough mayors in its governance; the latest attempted resolution allows mayors to serve as alternates, but 

not as regular board members. All of the COGs raise part of 

their revenue from member dues. Some use a three-tier 

dues structure based on population. Others use a formula 

based on population and assessed valuation. The Turtle 

Creek Valley COG relies on a flat rate per municipality. 

Each COG employs an executive director, appointed 

by the board of directors. Some COG executive directors 

are professional public administrators; others are not.48 

The COGs range in size from 9 to 20 members and in populations served from 54,000 to 130,000 residents. None of 

the COGs is a “big budget” operation; none has an elaborate office complex. The number of full-time staff is minimal. As one executive director remarked, the COGs are 

best understood as ‘‘extensions’’ of their member municipalities, not as independent or freestanding organizations. 

Grantsmanship is an important part of all COG activities, though it is more important in some than in others. 

COGs have obtained one-time grants, mostly from the 

state, to conduct feasibility studies, purchase capital 

equipment, and introduce programs. The potential of 

18 U.S. Advisory Commission on Intergovernmental Relations 
such COGS as Xrtle Creek Valley and Steel Valley to 

serve a number of distressed municipalities is, arguably, 

tied to future grant support. 

The entrepreneurial activities of the COGs have not 

been limited to seeking grants. Increasingly, led perhaps 

by ’Ibrtle Creek Valley’s entry into supplying computer 

payroll and accounting services, the COGS have turned to 

fee-based service delivery as a source of support. This is a 

productive form of public entrepreneurship that increases 

the capacity for self-reliance among small municipalities. 

By searching out functions for which cost savings can be 

realized from increasing the scale of production, COGs 

improve the productivity of their members. 

Each COG has developed its own service orientation. 

7brtle Creekvalley, the oldest COG, performs a computerized payroll and accounts payable service for 12 municipalities, and has begun doing utility billings-a service 

dominated by private contractors among small municipalities in the county-and tax collections. The South Hills 

Area COG (SHACOG) houses a joint purchasing council 

for municipal commodities that serves some 60 municipalities (this program preceded the establishment of SHACOG). Twin Rivers COG, located in the southeastern 

part of the county, recently began managing a joint dispatch service for several area police, fire, and emergency 

medical departments, and, for a number of years, has operated a police firing range. Twin Rivers and Steel Valley 

COGs double as regional planning commissions. With 

grant support from the Intergovernmental Cooperation 

Program, Steel Valley COG supplies a shared finance 

manager for three municipalities. Quaker Valley COG, 

just northeast of Pittsburgh, has started manufacturing 

traffic control signs, and Steel Valley COG furnishes 

street sweeping services to five COG members and three 

nonmembers. Char-West runs a surplus property auction 

for municipalities, with help from other COGs. 

The COGs serve as centers of innovation in intergovernmental cooperation and as vehicles for the diffusion of innovations. Success in one COG stimulates 

efforts in others. Quaker Valley COG, after the fashion 

of %in Rivers, has received a grant from the state Department of Community Affairs to study the feasibility 

of joint dispatch for member municipalities. Quaker 

Valley, Steel Valley, Twin Rivers, and North Hills 

COGs, emulating nrtle Creek Valley, are developing 

the capabilities to operate a payroll and billing service. 

no COGs (SHACOG and North Hills) now operate a 

credit union for municipal employees. 

Innovation is continuing in many COGs. Turtle Creek 

Valley is developing joint street maintenance programs 

among small municipalities, with a strong emphasis on 

preventive maintenance. Allegheny Valley North is planning to install a hydropower generator on an Allegheny 

River lock and dam. Profits from the sale of electric power 

will be divided among 13 participating communities. 

Char-West is developing plans to acquire and operate a 

solid waste disposal site-a move that could relieve rapidly escalating cost pressures on municipal solid waste collection in the county. 

Many services supplied by one COG also benefit municipalities in others, as well as nonmunicipal agencies. 

SHACOG’s credit union also serves municipal employees 

in Char-West and Quaker Valley. The joint dispatch service operated by Twin Rivers serves volunteer fire companies as well as municipal police departments. As a 

group, the eight COGs contribute to countywide coordination and problem solving (outside Pittsburgh). The joint 

purchasing council operated by SHACOG, the surplus 

property auction organized by Char-West, and the possible solid waste disposal site being developed by Char-West 

potentially have a countywide clientele. 

COGs have become significant arenas for public 

entrepreneurship in many parts of Allegheny County. In 

the words of the Mon Valley Commission, COGs “future 

viability depends on three factors: (1) their ability to raise 

money, especially in an era when grants are declining; (2) 

their capacity to identify programs which are acceptable to 

the membership but which may address controversial 

areawide issues; (3) their acceptance as a legitimate 

areawide voice on problems confronting the area.”49 COG 

directors and officers can be viewed as public entrepreneurs who remain “in business” as long as their work is 

beneficial to their member communities. 

Another benefit of the COGs is their function as forums for discussion among officials.50 COGs have likewise 

contributed to regular meetings of service administrators-as in the meetings of police chiefs sponsored by the 

Steel Valley and Twin Rivers COGs and similar meetings 

of public works foremen in these COGS and Turtle Creek 

Valley.s1 These, too, have led to joint service activitiesshared dispatch and combined public works teams, for example-that might not have occurred otherwise. 

Public-Private Partnerships 

Pittsburgh and Allegheny County have for years had 

strong public-piivate partnerships. The chief executives of 

the major corporations and banks headquartered there 

have taken a continuing interest in public affairs that has 

affected the area significantly. The most visible and important of the many organizations fostering private involvement in public affairs have been the Greater 

Pittsburgh Chamber of Commerce and the Allegheny 

Conference on Community Development (ACCD).52 

ACCD was instrumental in achieving smoke control during the late 1940s, and worked closely with the Chamber in 

achieving flood control for the area. In partnership with 

Pittsburgh’s Mayor David L. Lawrence, ACCD was a major contributor to Renaissance I, the renewal of downtown 

as the “Golden Triangle.” During the 1960s and early 

1970s, ACCD sponsored or participated in efforts to defuse racial tensions in Pittsburgh. In the mid to late 1970s, 

the Chamber of Commerce, with significant efforts by executives from the Mellon Bank, worked with the county 

commissioners and the mayor to form ComPAC and ComPEP, both involving teams of loaned corporate executives 

who worked with the countyand city to improve managerial efficiency. ACCD and the Chamber have continued to 

be active in community affairs, with ACCD providing initial co-sponsorship of the Intergovernmental Cooperation 

US. Advisory Commission on Intergovernmental Relations 19 
Revenue Source 

Revenue Source 

Population 1984 

Total Revenues 

Table 2.5 

Revenues in 1985, by Source 

(Excluding Public Service Enterprises) 

Pittsburgh Third Class Cities Boroughs 

Percent Percent Percent 

Per ofTotal Per of Total Per of Total 

Total Capita Revenues Total Capita Revenues Total Capita Revenues 

402,583 22,040 409,149 

$289,049,039 $717.99 100.0% $4,817,044 $218.56 100.0% $88,195,002 $215.56 100.0% 

Tix Revenues 

Total 197,583,275 490.79 68.4 2,783,090 126.27 57.8 57,734,380 141.11 65.5 

Real Estate 93,147,493 231.37 32.2 2,288,480 103.83 47.5 38,311,756 93.64 43.4 

Earned Income 55,570,577 138.04 19.2 294,628 13.37 6.1 14,096,543 34.45 16.0 

Real Transfers 4,372,326 10.86 1.5 17,613 0.80 0.4 1,761,028 4.30 2.0 

Mercantile 5,374,733 13.35 1.9 87,001 3.95 1.8 909,926 2.22 1.0 

All Other 39,118,146 97.17 13.5 95,368 4.33 2.0 2,655,127 6.49 3.0 

Total 91,465,764 227.20 31.6 2,033,954 92.28 42.2 30,460,622 74.45 34.5 

Licenses, Permits, Fines, Forfeits, 

Use of Money, and Properly 21,924,134 54.46 7.6 169,878 7.71 3.5 5,281,212 12.91 6.0 

Intergovernmental Grants 

and Aid 56,408,281 140.12 19.5 695,304 31.55 14.4 10,664,506 26.07 12.1 

Departmental Services 5,033,577 12.50 1.7 35,160 1.60 0.7 2,804,193 6.85 3.2 

Sewer Rents and Charges 605,646 1.50 0.2 886,648 40.23 18.4 6,317,868 15.44 7.2 

All Other 7,494,126 18.62 2.6 246,964 11.21 5.1 5,392,842 13.18 6.1 

Miscellaneous 

Program and the Chamber now supporting it financially 

(see below). ACCD, the Chamber, and many corporations 

contributed executive and managerial personnel to the 

work of the Mon Valley Commission cited above. 

Nonprofit Organizations 

Other significant organizations contributing to public 

entrepreileurship in Allegheny County include nonprofit 

organizations such as the Pennsylvania Economy League 

(Western Division), and the Coalition to Improve Management in State and Local Government. The Economy 

League, closely associated over the years with ACCD, 

provides research and consultation services to county and 

municipal governments and school districts. The league is 

supported in major part by membership fees paid by corporations, allowing it to provide its services at relatively low 

cost. The league served as plan coordinator for financial recovery plans developed under Pennsylvania’s Distressed 

Community Act in the Allegheny County communities of 

Clairton, Braddock, and Wilkinshurg, with continuing efforts 

to implement the plans in the latter two communities. 

The coalition has both a national program and a local 

one focused on improvements in Allegheny County. The 

coalition was instrumental in the establishment of an Office of Management and Productivity in the county government, provides consulting support to the local COGs, 

and is developing a handbook on strengthening local government capabilities for intergovernmental cooperation. 

Intergovernmental Cooperation Program 

The Intergovernmental Cooperation Program (ICP) 

was formed as a committee of the Allegheny League of 

Municipalities in 1982, with funding from Allegheny 

County and the Allegheny Conference on Community 

Development. It incorporated as a nonprofit organization 

in 1985, but was unsuccessful at obtaining continued funding. It is now sponsored by the Greater Pittsburgh Chamber of Commerce, which provides administrative support 

and financing for the program’s staff. 

The ICP has initiated a number of cooperative ventures. It hasbeen a catalyst, along with the county government, in the formation of the councils of governmentsand 

has helped the COGs to implement cooperative ventures. 

Among these are sharing major public works equipment 

(equipment purchased with funds from AIM), pilot projects for a shared finance director in the Steel Valley COG 

and a shared public works professional in the nrtle Creek 

Valley COG, the development of a microcomputer information network linking the eight county COGs (COGNET), 

and a demonstration Disaster Management Project with the 

North Hills COG.53 The ICP, through its public safety com- mittee, is working with a consulting finn on the development 

of a plan for an enhanced 911 system. The ICP presents Intergovernmental Cooperation Awards each year to individuals, municipalities, and other organizations that have 

contributed to cooperative arrangements in the county at the 

Allegheny League of Municipalities Conference, recognizing their contributions and drawing attention to further op- portunities for interlocal cooperation. 

Local Officials and Managers 

Municipalities in Pennsylvania are empowered to 

“jointly cooperate. . . in the exercise or in the performance 

of their respective governmental functions, powers, or respon~bilities.”~~ Local officials and managers in Allegheny 

County have used this power extensively. Informal sharing 

of equipment or personnel expertise is reported to be 

widespread. Some communities agree to provide services 

(snow removal, for example) in a remote part of an adjoining municipality to which they have easier road access. 

Written agreements are common, often for reciprocal as20 U.S. Advisory Commission on Intergovernmental Relations 
Table 2.5 (cont.) 

Revenues in 1985, by Source 

(Excluding Public Service Enterprises) 

First Class Townships Second Class Townships Home Rule Municipalities Municipal Total 

Percent Percent Percent Percent 

Per of Total Per of Total Per of Total Per of Total 

Total Capita Revenues Total Capita Revenues Total Capita Revenues Total Capita Revenues 

195,414 70,617 309,360 1,409,163 

$34,215,418 $175.09 100.0% $13,618,811 $192.85 100.0% $85,647,369 $276.85 100.0% $515,542,683 $365.85 100.0% 

23,623,238 120.89 69.0 7,760,668 109.90 57.0 55,058,250 177.97 64.3 344,542,901 244.50 66.8 

13,397,781 68.56 39.2 3,888,272 55.06 28.6 25,958,185 83.91 30.3 176,991,967 125.60 34.3 

7,634,744 39.07 22.3 2,857,776 40.47 21.0 20,404,489 65.96 23.8 100,858,757 71.57 19.6 

884,797 4.53 2.6 436,500 6.18 3.2 3,832,870 12.39 4.5 11,305,134 8.02 2.2 

784,706 4.02 2.3 55,499 0.79 0.4 2,068,556 6.69 2.4 9,280,421 6.59 1.8 

921,210 4.71 2.7 522,621 7.40 3.8 2,794,150 9.03 3.3 46,106,622 32.72 8.9 

10,592,180 54.20 31.0 5,858,145 82.96 43.0 30,589,119 98.88 35.7 170,999,784 121.35 33.2 

1,733,874 8.87 5.1 793,152 11.23 5.8 5,115,495 16.54 6.0 35,017,745 24.85 6.8 

4,425,436 22.65 12.9 1,747,256 24.74 12.8 10,511,331 33.98 12.3 84,452,114 59.93 16.4 

928,388 4.75 2.7 466,098 6.60 3.4 4,104,508 13.27 4.8 13,371,924 9.49 2.6 

2,138,028 10.94 6.2 1,740,738 24.65 12.8 7,806,061 25.23 9.1 19,494,989 13.83 3.8 

1,366,454 6.99 4.0 1,110,901 15.73 8.2 3,051,724 9.86 3.6 18,663,011 13.24 3.6 

sistance in emergency situati~ns.~~ These informal and 

%formal cooperative agreements also evidence widespread 

public entrepreneurship in the county. 

FISCAL PATTERNS 

In 1985, Allegheny County general governments and 

school districts raised slightly more than $1.8 billion in to- tal revenues. Municipalities accounted for roughly 30 percent of the total, some $553 million.56 Revenues of 

bAllegheny County government were $461 million, about 

25 percent of the School district revenues accounted for the remaining $800 million, or 45 percent of 

all revenues.58 These data understate total governmental 

and quasi-governmental revenues in the county by an unknown but not insignificant amount. They do not include 

revenues of municipal authorities (principally user charges 

and lease payments) or volunteer fire companies (in addition 

to revenues they receive from the municipalities). 

Municipal Revenues 

Municipal governments in Pennsylvania have access 

to a wide range of tax and other revenue sources. Excluding Philadelphia, which has a unique revenue structure, 

total municipal revenues in the state split roughly in half 

. between those raised from taxes and from nontax sources 

. (such as fees, grants, and aid from other governments), 

and revenues of public service enterprises (such as municipal water and electrical utilitie~).~~The most important tax 

source for Pennsylvania municipalities is the real estate 

tax, which accounted for 52.5percent of municipal tax revenues statewide (and 25.3 percent of total revenues, excluding Philadelphia) in 1982. Other taxes available to 

municipalities include taxes on earned income (generally the 

second most important tax source), occupation, occupational 

privilege, intangible personal property, real estate transfer, 

amusements, and mercantilehusiness privileges. 

Municipalities in the county obtained about twothirds of their total revenues from tax sources in 1985, substantially above the state average. The revenue sources 

used most heavily were the real estate tax (34 percent of 

total revenues and 51 percent of tax revenues); the tax on 

earned income (nearly 20 percent of total and 29 percent 

of taxrevenues); and grants and other aid from the county, 

state, and federal governments (approximately 16 percent 

of revenue~].~The remaining 30 percent of municipal revenues consisted of real property transfer, mercantile and 

other “nuisance taxes” authorized under Act 511, and miscellaneous revenue sources, such as licenses and permits, 

fines and forfeitures, use of money and property, departmental services, sanitary sewer rents, and other miscellaneous revenues @ble 2.5).61 

In percentage terms, third class cities and boroughs 

were most dependent on the property tax, raising more 

than 40 percent of their revenues on average from this tax 

(Ihble 2.5 and Figure 2.3, Panel A). First class townships 

also relied heavily on the real estate tax, while second class 

townships and home rule municipalities made the least 

use of the property tax on Townships and home 

rule municipalities made the heaviest use of the earned income while third class cities used this source much 

less than average. Pittsburgh benefited most from county, 

state, and federal grants and aid. For Pittsburgh, the bulk 

of the grant and aid revenues were from federal grant programs, while for the other municipalities the revenues 

were split roughly evenly between such grants and state 

highway aid from the motor fuels tax. 

In absolute terms, Pittsburgh raised more revenues in 

1985 than the rest of the municipalities combined (56 percent). The city’s per capita revenues were higher than all 

but Sewickley Heights. Pittsburgh raised more revenues 

U.S. Advisory Commission on Intergovernmental Relations 21 
I 

E 

PANEL A. PERCENT OF REVENUES BY SOURCE 

Figure 2.3 

Revenue Sources for County Municipalities, 1985 

(Excluding Revenues of Public Service Enterprises) 

PANEL €3. PER CAPITA REVENUES BY SOURCE 

---- I - I 

(700 

6600 

$500 

S400 

1300 

$200 

1100 

60 

22 US. Advisory Commission on Intergovernmental Relations 
per capita from each of the major revenue sources Wble 

2.5 and Figure 2.3, Panel B), including about twice as much 

from the property tax, three times as much from earned 

income taxes, five times as much from grants and aid, and 

four times as much from other sources. Pittsburgh’s real 

estate and earned income tax rates are substantially higher than most municipalities.” Its status as the area’s major 

employment center accounts for much of these differences-Pittsburgh’s employment in 1985 was about one-half 

of the county total.65 The city’s size makes it eligible for 

grants that are not available to other municipalities. Pittsburgh obtained about two-thirds of all grant and aid funds 

allocated to municipalities in Allegheny County during 1985. 

Pittsburgh also pays for services from its own revenues 

that in surrounding municipalities are often the responsibility of the county government or overlying municipal authorities, or are franchised to private suppliers. For example, 

Pittsburgh spent more than $8 million for health services in 

1985, more than 80 percent of the county total. The city 

spent nearly $17 million on parks and recreation services, approximately two-thirds of the amount spent by municipalities 

countpde, and its refuse collection and disposal costs of $9 

million were 42 percent of the total. Differences in service 

responsibilities are important to an understanding of revenue differences between Pittsburgh and its neighbors. 

Outside Pittsburgh, average per capita revenues in 1985 

were highest in home rule municipalities and lowest in first 

and second class townships Pble 2.5 and Figure 2.3, Panel 

B). The higher revenues of home rule municipalities are at 

least in part a function of additional service responsibilities. 

About 31 percent of the suburban population resides in 

home rule municipalities, but they spend 55 percent of the 

suburban total for libraries and for parks and recreation and 

two-thirds of the total for health services. Their spending for 

common services such as general administration, police, and 

streets and highways is roughly proportional to the suburban 

average. Townships of the first and second class have expenditures for these common services that are roughly proportional to their share of county population. However, their 

expenditures for liiraries, parks and recreation, and health 

services are substantially lower in total and as a percentage 

of suburban spending. They rely more extensively on county 

provision of these services. 

County Cover n m en t Revenues 

Allegheny County government had revenues of $461 

million in 19KM Forty-two percent of these revenues 

were intergovernmental transfers, 80 percent of which 

came from the state. Fifty-eight percent were own-source 

revenues, two-thirds of which were derived from the real 

estate tax, the only major tax source available. The county 

derived 22 percent of its own-source revenues from user 

charges, principally charges for services at the county airports and county hospitals, and 10 percent in miscellaneous revenues, principally interest on investments. 

School District Revenues 

Of the $800 million revenues of Allegheny County 

school districts in the 1984-85 school year, $539 million or 

about two-thirds was raised locally, $235 million (29 percent) came from the state, $23 million came from the federal government, and about $3 million came from other 

unspecified sources.67 The local percentage of total school 

revenues ranged from just over 50 percent in one district 

(South Allegheny) to over 80 percent in five wealthy districtsm Of the revenues raised locally, $371 million (69 

percent of local revenue and 46 percent of total revenue), 

came from the real estate tax, while $92 million (17 percent) came from Act 511 taxes, principally the earned income tax, which school districts share with municipalities. 

SUMMARY 

Allegheny County is a collection of diverse communities. These communities, whether organized as independent municipalities or neighborhoods within the larger 

municipalities, or as independent school districts, maintain a strong attachment to their community identities. 

Overlying these local communities are a city government 

(in Pittsburgh), councils of governments for most municipalities outside Pittsburgh, a county government, two intermediate units for educational purposes, and fire 

defense councils and associations for fire services. These 

overlays provide opportunities for collaboration and coordination among the local communities, while preserving 

their jurisdictional independence. 

Notes 

This section draws on Henry Steele Commager, “Forts in the 

Wilderness,” in Stefan Lorant, ed., Pittsburgh: The Story of an 

American City (Garden City, New York: Doubleday & Compa- ny, 1964), pp. 9-46; and on material contained in Allegheny 

County Board of Commissioners and Allegheny County Bicentennial Commission, Welcome to Alleglleny County, 1987 

Geneml Information Map (Pittsburgh, 1987); and League of 

Women Voters, Allegheny County Government: Organization, 

Facilities and Services (Pittsburgh, 1971). 

Lorant, “Gateway to the West,” in Lorant, pp. 47-79. 

Oscar Handlin, “The City Grows,” in Lorant, pp. 81-128. 

John Morton Blum, “The Entrepreneurs,” in Lorant, pp. 

Lincoln Steffens, “Pittsburg: A City Ashamed,” McClure’s 

Magazine, May 1903 (also in Die Shame of the Cities). 

The merger took place against the expressed wishes of much of 

Allegheny’s population, and was made possible by an act of the 

Pennsylvania General Assembly (Guthrie-Watson Greater 

Pittsburgh bill) permitting merger by a simple majority vote in 

a referendum held in Pittsburgh and Allegheny. Legal protest 

against the law and merger led to the U.S. Supreme Court’s 

Hunter v. Pittsburgh decision in 1907, incorporating “Dillon’s 

Rule” into federal jurisprudence. 

“In existence” means existence as a municipality with the present 

name or a close substitute. Because municipal creation in Pennsylvania consists of secession from or splitting existing munidpalities, the boundaries of many of these 38 communities are quite 

different today. The dates of municipal incorporation used for 

this section are taken from Allegheny Board of Commissioners 

and Bicentennial Commission, I.Velconie to Allegheny County. 

Roy Lubove, Twentieth Centwy Pittsburgh (New York John 

Wiley & Sons, 1969). For example, in the bitter Homestead 

strike of 1892, in which strikers fought private police and, later, 

the state militia that attempted to reopen the mills. See Henry 

David, “Problems of Labor,’’ in Lorant, pp. 207-218. During the 

steel industry strike of 1919, the mayor of Duquesne denied a 

meeting permit to union organizers, and is reputed to have said, 

219-260. 

U.S. Advisory Commission on Intergovernmental Relations 23 
“Jesus Christ himself couldn’t hold a [union] meeting in Duquesne.” hbve, p. 12, quoting from S. Adele Shaw, “Closed 

Towns: Intimidation as It is Practiced in the Pittsburgh Steel District,” Survey 43 (November 8, 1919) : 62 

Jon C. Teaford, City and Suburb: The Political Fragmentation of 

Metmpolitan America, 1850-1970 (Baltimore: Johns Hopkins 

University Press, 1979), p. 12. 

lo hbove, p. 27. To this day, some of the street names and street 

numbering in Pittsburgh’s North Side, previously the City of 

Allegheny, are retained by local residents as they were prior to 

this shotgun mamage. 

l1 This discussion draws on Lubove, pp. 97-101, and on Teaford. 

A catalog of Pittsburgh’s growth through annexation can be 

found in City of Pittsburgh 1975 Annual Report (Pittsburgh: 

City Controller, 1975), pp. 108-110. 

l3 See Teaford, pp. 154-57, for a discussion of the commission’s 

proposed charter and the legislature’s amendments. 

l4 See Lubove, p. 101. Teaford reports that the two-thirds major- ity requirement was met in 48 of 122 municipalities, p. 167. 

See Lubove, p. 100; and Teaford, pp. 126-127. The quote (by 

Teaford, p. 169) is from the Homestead Messenger, June 26, 

1929, p. 4. 

l6 Teaford provides data showing the vote distribution across 

municipalities characterized by the median value of monthly 

rentals, a measure of local wealth, and by distance from the 

center of Pittsburgh, a measure of rural character. See Tables 

12 and 13, pp. 169-170. Support for the charter was clearly related to the wealth and urban character of the communities. 

Blue collar and rural communities opposed it. 

l7 A 1980 survey identified 74 separate neighborhoods in Pittsburgh, with populations ranging from 900 to 25,000. See Roger 

S. Ahlbrandt, Jr., Neighbodioodr, People, and Community 

(New York Plenum Press, 1984). 

l8 The reZion names and definitions used in this discussion fol- low quite closely those used in Franklin Toker, Pittsburgh: An 

Urban Portrait (University Park: Pennsylvania State University 

Press, 1986), pp. 263-315. 

l9 For an insightful discussion of the difficulties and opportunities 

for improvement in the Mon Valley, see Mon Valley Commission, Report to the Allegheny County Board of Commissioners: 

For the Economic Revitalization of the Monongahela, Youghiohey, and Turtle Creek Valleys Pttsburgh, February 1987). 

2o Two additional municipalities, McDonald and Trafford, are lo- cated partially in Allegheny County and partially in adjacent 

counties, and are not included in this count. 

21 The distribution of population in Allegheny County is sub- stantially more skewed toward the smaller municipalities than 

that found in the recent ACIR study of St. Louis City and 

County. In St. Louis, about 90,000 persons resided in munici- palities with fewer than 5,000 residents, and 826,000 resided in 

either the city or the large unincorporated county jurisdiction. 

In Allegheny County, 168,000 persons live in small communi- ties-those with fewer than 5,000 inhabitants-and 402,000 in 

Pittsburgh, the only large jurisdiction. St. Louis has more of 

the very smallest local governments than does Allegheny 

County, however, with 22 communities of fewer than 1,000 

residents compared to Allegheny’s 12. See US. Advisory 

Csmmission on Intergovernmental Relations, Metropolitan 

Organization: The St. Louis Cae, (Washington, DC, 1988). 

22 The small municipalities elect as many officials as do their 

larger neighbors. Elected official to citizen ratios in these small 

communities are, therefore, especially high. 

23 Allegheny League of Municipalities, Report of Wage and Salary 

Programs in tlie Municipalities of Allegheny County-1987 

(Plttsburgh, 1987). The survey includes data for 101 of the 

county’s 130 municipalities (the 29 not responding were pre- dominantly small municipalities). The counts in this section 

include managers and municipal secretaries who are listed as 

full time and whose salary compensation appeared consistent 

with full-time employment. The latter qualification yields 

somewhat lower counts than the league’s summary tables. Persons listed as managerhecretary were counted as managers. 

24 Six of the 12 second class townships have population densities 

of less than 300 persons per square mile, the minimum density 

required for changing their status to first class (see Chapter 3). 

25 Early evidence of this strong local attachment is that Allegheny 

Countywas the site of the Whiskey Rebellion of 1794, the first 

armed post-constitutional challenge to the federal government of the United States. 

26 In response to this pattern of ridges and ravines, the City of 

Pittsburgh has 720 bridges and the remainder of Allegheny 

County has 1,000-more bridges, we were told, than any city in 

the world except Venice. 

’’ Teaford, p. 7. 

28 Their influence had positive as well as negative aspects in the 

eyes of at least one observer. Referring to Munhall, she found 

“the influence of the Carnegie Steel Company practically 

dominatesborough action and has made the local government 

efficient and without suspicion of graft.” Margaret Byington, 

Homestead: The Households of a Mill Town (New York, 1910), 

pp. 20-21, quoted in Teaford, p. 15. 

29 Lubove, p. 3. 

30 See Thomas Bell, Out of this Furnace (Pittsburg:University of 

Pittsburgh Press, 1976). 

31 Frederick Bigger, “Pittsburgh and the Pittsburgh Plan,” Ad 

and Architecture 14 (November-December 1922): 271-272, 

quoted in Lubove, p. 88. 

32 “The Prothonotary is the chief clerk of the Civil Division and 

the Family Division of Common Pleas Court. He is responsible 

for keeping records in civil actions and in . . . family related 

matters. . . which come under the jurisdiction of the Court. He 

issues writs, initiates the execution of judgments and keeps 

records of judgments paid, takes bail on bonds in civil cases, 

processes appeals to the Superior and Supreme Courts and 

from decisions of the Board of Viewers. Among his other duties are the recording of charters of nonprofit corporations, the 

recording of fictitious names in business, the recording of all 

municipal claims and tax liens, and the filing of annual reports 

from municipal auditors, treasurers and tax collectors.” 

League of Women Voters, pp. 16-17. 

33 Special taxing districts for local projects (e.g., water, sewer, or 

street lighting projects) are permitted within the boundaries of 

Pennsylvania townships. 

34 Department of Community Affairs, Citizen’s Guide to Petirtrylvania Local Government (Harrisburg, 1984), pp. 3-4. 

35 League of Women Voters, 1971, p. 70. 

36 Citizen’s Guide, pp. 3-4. 

37 Department of Community Affairs, Directory of Municipal Au- thoritiesin PennJylvarria 1985 (Harrisburg, 1985). Active authorities are those that this directory does not list as “terminated.” 

A number of active authorities had no outstanding debt in 

1985. 

38 These are referred to as “lease back” arrangements, whereby 

an authority issues revenue debt for the construction of a 

school facility, then retires the debt by leasing the facility back 

to the authority’s sponsoring school district. 

39 Estimate provided by Merrill Parker, Director, Allegheny 

County Fire Academy. 

24 U.S. Advisory Commission on Intergovernmental Relations 
Allegheny Conference on Community Development and 

Consortium for Public Administration Field Services, To 

Cooperate or Not to Cooperate: A Report on Intergovemmen?al 

Coopemtion in Allegheny County (Pittsburgh, April 1982), p. 15. 

41 Ibid, pp. 21-23. 

42 Allegheny County Department of Development, Allegheny 

County Economic Resource Profire mttsburgh, August 1987), p. 

2 

43 Interview with Ray Reaves, Director, Allegheny County De- partment of Planning, March 29, 1988. 

Mon Valley Commission, Report, pp. 15-16. 

45 Ibid., p. 10. 

46 Department of Community Affairs, “COGs and Intergovernmental Cooperation,” 4th Edition (Hanisburg, 1986) p. 9. 

47 The members were Wilkins Township and the boroughs of 

Forest Hills, Churchill, and Chalfont. Chalfont is now a mem- ber of Turtle Creek Valley COG. A fire chiefs association con- tinues to serve the same four municipalities. 

One manager of a home rule municipality interviewed for this 

research indicated that there has been a tendency for the 

COGs to replace professionally trained directors with aperson 

selected from the COG staff, usually with less formal training, 

as turnover in directors occurred. This appears to have oc- curred in at least two of the COGs in recent years, but the extent of the trend countywide could not be ascertained, nor 

could its implications, if any, for COG viability. 

49 Mon Valley Commission, Report, p. 126. While speaking particularly of the three COGs in the Mon Valley region, these 

conditions for continued viability are appropriate to COGs 

throughout the county. 

Donald Chisholm identifies these informal linkages as essential to coordination in systems of multiple, independent orga- nizations. See Chisholm, “I11 structured problems, informal 

mechanisms, and the design of public organizations,” in Jan 

Erik Lane, ed., Bureaucracy and Public Choice (Beverly Hills: 

SAGE Publications, 1987) pp. 76-93; and Coordination without 

Hiemhy: Informal Structures in Multiorganirational Systems 

(Berkeley: University of California Press, 1989). 

51 See Mon Valley Commission Local Government Task Force 

Draft Report (Pittsburgh, 1987). 

52 For an extensive discussion of the Conference and its activities, 

see Shelby Stewman and Joel A. Tarr, “Four Decades of Public 

Private Partnerships in Pittsburgh,” in R. Scott Fosler and Renee A. Berger, eds., Public-Private Partnerships in American Cities (Lexington, Massachusetts: D.C. Heath Company, 

Lexington Books, 1982), pp. 59-127. 

53 COGNET encountered significant difficulties in linking the 

different hardware and software systems used by the eight 

COGs, and is no longer operating. 

53 ES. 481; Intergovernmental Cooperation Law (Act 180) 1972 

55 Department of Community Affairs, “COGS and Intergovemmental Cooperation,” p. 4. 

Preliminary report of Local Government Financial Statistics 

1985 made available by the Division of Municipal Statistics, 

Pennsylvania Department of Community Affairs. These data are 

compiled from the ‘Annual Audit and Financial Report’’ (fom 

DCA BLGS 30) submitted to the Division by each municipality. 

57 U.S. Advisory Commission on Intergovernmental Relations, 

CityCounty Finance Diskettes, FY 1985 (Washington, DC, 

’* Pennsylvania Department of Education, Bureau of BasicEducation Financial Administration, Division of Child Accounting 

and Subsidy Research, Selected Revenue Data and Equalized 

Mills for Pennsylvania Public Schools, 1984-85 (Harrisburg, 

1985). 

’’ Data for 1982 from Department of Community Affairs, Bureau of Local Government Services, Tawation Manual, Fourth 

Edition (Harrisburg, 1986), p. 3. 

Municipal revenues discussed in this section exclude those of 

publicservice enterprises such as local water and electrical sys- tems. In a few municipalities, these enterprises account for 

substantial revenues and expenditures, but in most municipalities such enterprises are operated by legally separate munici- pal authorities. 

Department of Community Affairs, Local Government Fi17uncia1 Statistics, 1985, Tables I-IV. 

62 This difference is in part a function of millage rate limitations. 

Second class townships are limited to 14 mills, third class cities 

to 25 mills, and boroughs and first class townships to 30 mills. 

These limits may be exceeded by 5 mills with court approval, 

and the limits no longer apply if a municipality adopts a home 

rule charter. 

63 For home rule municipalities, this increased reliance on the 

earned income tax results partially from the higher rates they 

impose. In 1987,s of the 16 suburban home rule municipalities 

imposed earned income tax rates higher than the 0.5 percent 

rate used in other municipalities. See Pennsylvania Economy 

League, “Compilation of Assessments and Tax Rates of Allegheny County Cities, Boroughs, Townships, and School Districts 1987” (Pittsburgh, 1987). 

Pittsburgh’s real estate tax millage rate is not limited by state 

law, although the city is constrained to tax buildings at one half 

the rate levied on land. In 1985, the city’s millage rate was 

52.067. Its adjusted millage rate, computed by the Pennsylvania Department of Community Affairs as the rate applied to 

actual market value of property, was 15.982, higher than every 

municipality except Clairton, and approximately 2.5 times the 

county average. Pittsburgh’s earned income tax rate is similarly 

unconstrained by state law. In 1985, it was 2.125 percent of residents’ income, more than double the rate of most other municipalities (Pittsburgh’s school district adds an additional 1.875 

percent to this rate, for a total of 4 percent. Non residents are 

not subject to this tax if their home municipality levies the tax. 

Most do so at a rate of 1 percent for the combined municipal 

and school levy. This 3 percent spread in earned income tax 

rates is said by many in the area to account for a large portion 

of Pittsburgh’s population loss in recent years. 

65 Southwestern Pennsylvania Regional Planning Commission, 

Cycle IV Forecasts. 

66 ACIR, City County Finance Diskettes. 

67 Department of Education, Selected Revenire Data and Equalized Mills for Pennsylvania Public Schools, 1984-85. 

State aid in Pennsylvania, as elsewhere in the United States, is 

targeted toward local school districts with lesser amounts of resources. 

1988). 

U.S. Advisory Commission on Intergovernmental Relations 25 
26 US. Advisory Commission on Intergovernmental Relations 
Metropolitan Governance: 

State Rules and Local Choices 

A LOCAL GOVERNMENT CONSTITUTION 

Local government in Allegheny County is organized 

by citizens and officials under state constitutional and statutory authority. The entire body of state law that pertains 

to local governments can be considered a “local government constitution,” which entails two levels of choice: 

Level One: State legislators and constitution makers 

choose enabling rules that allow citizens and officials to create and subsequently modify local governments, each endowed with a limited range of 

legal powers. 

Level Two: Local citizens and officials choose to 

create specific local governments, or to modify 

those already created, by adopting or amending 

municipal charters or other organic acts. 

Both choices are constitutional in a functional sense-the 

rules chosen create governance structures but do not directlygovern. The second level is nested within the firstthe choices that constitute local governments and 

interlocal relationships are made within a framework of 

state law and the state constitution. The complex state-local 

relationship is often summed up by the proposition that local governments are “creatures of the state.” This legal 

doctrine, known as Dillon’s Rule, is part of Pennsylvania 

legal tradition.’ In a literal sense, however, the characterization is usually incorrect. More accurately, local governments might be characterized as the “creatures” of local 

communities.2 State law is frequently the parent of a process of local government formation and thus only indirectly the parent of local governments. This is ordinarily the 

case in Pennsylvania. Four different types of rules make 

up a local government constitution: 

1) Rules of association-specifying how local gov- ernment units may be created; 

2) Fiscal rules-specifying the ways in which local 

governments may raise revenue; 

3) Boundary adjustment rules-specifying how local government boundaries may be changed; 

4) Contractual rules-specifying how local govern- ment units may enter into agreements with one 

another. 

= 

The discussion in this chapter examines these four sets 

of rules, then turns to the pattern of choice in Allegheny 

County. 

RULES OF ASSOCIATION 

Pennsylvania local government law underwent considerable change as a result of the adoption of a new state 

constitution in 1968. Pre-1968 statutes governing municipal annexation and consolidation were eventually invalidated by the courts on the basis of the constitutional 

provisions. Although the state legislature retains constitutional authority to prescribe new rules on these matters, it 

has not done so. Pre-1968 legislation pertaining to municipal incorporation and school district consolidation remains valid. 

The new constitution extended optional home rule 

authority to all counties and municipalities. This authority 

was implemented by the Home Rule Charter and Optional Plans Law of 1972.3 

All Pennsylvania citizens reside in the jurisdiction of a 

municipality. There is no unincorporated territory in the 

state. Municipalities include township^,^ boroughs, and 

cities, in addition to home rule municipalities, which are 

treated here as a separate class of locaI government. All 

four types exist side by side in Allegheny County. Townships are the basic municipal unit. Boroughs and cities 

displace township organization through a process of incorporation. Since 1972, any municipality has been free to 

adopt a home rule charter. In the absence of unincorporated territory, county governments are overlying jurisdictions (except in the consolidated city-county of 

Philadelphia) whose role in municipal service provision is 

supplementary, never exclusive. 

Towns hips 

Townships originally were formed either by special 

state legislation or by county courts. After Pennsylvania 

was fully organized, new townships were formed by dividing existing ones. In 1937, the legislature repealed the procedures for division of townships. State law classifies 

townships as first class or second class. There are 21 first 

class and 12 second class townships in Allegheny County. 

A second class township is the historic township form. 

It remains what might be called the “default option,” 

which will exist unless citizens take action to create a different type of municipality. Second class townships orgaU.S. Advisory Commission on Intergovernmental Relations 27 
nize territory (largely rural) that in many other states 

would be unincorporated. Second class townships are governed by a board of three supervisors, elected at large for 

staggered, six-year terms. The number of supervisors may 

be increased to five with voter approval.’ To become a first 

class township, a population density of at least 300 persons 

per square mile is required, and voters must approve the 

change in a referendum. The governing body is composed 

either of five commissioners elected at large or up to 15 

commissioners elected by ward. 

Township supervisors or commissioners may, by ordinance, create an office of township manager. More than half 

of the first class townships and two-thirds of the second class 

townships report either full-time managers or full-time secretaries, though the duties of secretaries vary and may not 

include supervisory authority over department heads. 

Boroughs 

Townships and boroughs are nonoverlapping units. 

Borough incorporation is equivalent to secession from a 

township, except when an entire township becomes a borough. There are 76 boroughs, making them the most numerous class of local government in the county. 

Borough incorporation is treated as a judicial action, 

A majority of citizens (required to be resident freeholders, 

but not necessarily local voters) petitions the court of common pleas for incorporation as a borough. Prior to 1981, 

the incorporation was decreed by the court pursuant to 

such a petition. Since 1981, state law has required approval 

of a proposed incorporation by a majority in a referendum. 

There is no statutory requirement of minimum population, 

and the legal view is that the incorporation of totally undeveloped territory, with no resident voters, is still permissible. 

Also since 1981, state law has required that the court 

appoint a borough advisory board when there is an incorporation petition. Approval of the petition is discretionary, based on court findings in accordance with common 

law and statutory criteria of appropriateness. The advisory 

board members may represent interests that oppose incorporation, such as the existing township government. Borough incorporation petitions have been denied on the 

basis of advisory board findings, even when a substantial 

majority of affected residents signed the petition. Borough incorporation is not automatic even when it is favored by an extraordinary majority, but is contingent on 

majority agreement by freeholders and voters in addition 

to third-party review and approval on the basis of legal and 

technical criteria. Incorporation requires local consent, 

but communities seeking incorporation do not enjoy full 

powers of self-determination. 

Borough disincorporation procedures, since passage 

of the 1968 state constitution, are somewhat unclear. Ten 

percent of the registered voters may petition to annul the 

bormgh charter. Approval by the voters creates a new second class township (the default option) from the borough 

territory. Prior to 1968, the Borough Code authorized the 

reversion of borough territory to the township from which 

it was created, but this provision has been held invalid in 

the courts? 

Boroughs, by statute, have what is popularly known as 

a “weak mayor” form of government. The mayor is separately elected for a four-year term and has a veto power 

over the council (that can be overridden by a two-thirds 

majority). The mayor has no appointment powers, and ad- ministrative responsibilities are limited to supervision of 

the police department (e.g., making out work schedules 

for police officers). The office lacks a critical element of 

executive authority-powers of appointment and removal 

-and is widely regarded as largely ceremonial. A “good 

mayor” is highly visible in the community and regularlyattends the social functions of churches and other community organizations. 

Power is concentrated in the elected council, which 

determines its own numbers and method of election: 

three, five, or seven councilmen if elected at large, and 

one, two, or three from each ward if elected by ward. The 

council elects a president from among its own members, 

who usually exercises political leadership. In most boroughs, the council functions as a legislative body and an 

administrative team. Each member of council chairs a 

committee responsible for supervising a specific function. 

Any council member is free to give directions to municipal 

employees, subject to the scrutiny of the council and the 

president. A borough secretary is usually employed (mostly part time) to administer routine matters. Department 

heads report directly to council. 

The council also may create, by ordinance, an office of 

borough manager, who becomes the chief administrative 

officer. Afewboroughs have upgraded the position of secretary to secretary-manager. Nineteen boroughs in Allegheny County report a full-time manager, and ten have a 

full-time secretary. The manager or secretary-manager 

system substantially alters the structure of borough government by unifying administrative supervision in a single 

appointed officer. 

Cities 

Pennsylvania has four classes of cities, based on population. Philadelphia, the only city with more than a million 

residents, is the only city of the first class. Pittsburgh is the 

only second class city, and Scranton is the only city designated class two-A. All other cities are considered third 

class, although those that meet the population requirement of 100,000 for class two-A have the option of joining 

that class. (Clairton and Duquesne arc the only remaining 

third class cities in Allegheny County.) 

The incorporation of third class cities is different from 

boroughs in two ways. First, there is a minimum population requirement of 10,000. Second, unlike new boroughs, 

new cities are not carved out of the jurisdiction of another 

government but result only from a change of status by an 

entire township or borough or from consolidation. City incorporation, therefore, does not engender the degree of 

intergovernmental conflict often associated with borough 

incorporation. Since 1945, only three new cities have been 

created in the state. 

Third class cities have a commission form of government, unless a mayor-council or council-manager form is 

adopted by referendum. Under the commission form, a mayor and four council members constitute the governingbody, 

28 U.S. Advisory Commission on Intergovernmental Relations 
each member taking administrative responsibility for one of 

five major departments. The mayor is presiding officer. 

Home Rule Municipalities 

The 1968 state constitution permits all municipalities 

to frame their own home rule charters. The 1972 implementing legislation’ provides a two-step charter procedure. First, voters must approve the creation of a 

government study commission. The issue may be placed 

on the ballot either by initiative petition or by ordinance. 

Members of the commission are elected at the same time. 

Second, if the commission recommends a new charter, it 

must be approved by a simple majority of the voters. Home 

rule municipalities do not rely on state law for authorization to act and are not subject to those portions of the state 

code that apply to municipal governments (i.e., township, 

borough, and third class cities codes). Home rule municipalities are subject to general legislation that applies to all 

municipalities, and may exercise only those powers not 

prohibited by the state constitution, general law, or the local charter. Boroughs and townships that adopt a home 

rule charter also frequently adopt the new title of “municipality.” Seventeen Allegheny County municipalities have 

reorganized under home rule charters. This number includes five former townships of the first class and four of 

the second class, six former boroughs, one former third 

class city (McKeesport), and the City of Pittsburgh. With 

the exception of Pittsubrgh, the trend has been for home 

rule municipalities to create some variation of council-manager government. 

The state constitution may also allow a community 

within an incorporated jurisdiction (including cities) to 

form a new, independent municipality, subject to voter approval in the entire jurisdiction. In 1985, the Allegheny 

County Board of Elections accepted petitions for a referendum to determine whether the first ward of the City of 

Clairton would be reestablished as the Borough of Wilson. 

The board ruled that the question had to be put before 

voters in the entire city, and the proposal was defeated.* 

Volunteer Fire Com pan ies 

Somewhat different rules of association apply to fire 

protection than to other services. Provision by privately 

organized, volunteer fire companies is common throughout suburban Allegheny County. Municipal governing 

bodies may not change from volunteers to paidprofessionals (or vice versa) without referendum approval by a majority of voters? The requirement also applies to changes 

from a mixed system. Different rules also apply to raking 

municipal revenue to support fire protection (see discussion under “fiscal rules”). 

School Districts 

The formation of school districts in Pennsylvania historically was tied to the formation of municipalities. Since 

1911, state law has prescribed that each new municipality 

constitute a separate school district, with the exception of 

very small municipalities,1° If the new district would be 

fourth class, which has a resident population of less than 

5,000, district formation required approval by state school 

officials. In 1965, the requirement of state approval was 

broadened to include new third class districts, with resident populations up to 30,000.” With these exceptions, 

school district boundaries tend to follow municipal boundaries. School districts that subsequently were consolidated 

(see discussion of boundary adjustment rules) usually 

overlie two or more entire municipalities rather than containing parts of different municipalities,’* a “patchwork” 

pattern frequently found elsewhere. 

Third and fourth class school districts are governed by 

nine-member boards of school directors elected for 

four-year overlapping terms. The legislature has also 

created 29 “intermediate units” throughout the state to 

provide consulting, advisory, and program services to 

school districts (see Chapter 5). The school districts generally are responsible for program operation. 

Community colleges maybe established by school districts, municipalities, intermediate units, or the joint action of any of these units. Each institution is governed bya 

board of trustees appointed by local government, or in 

Pittsburgh (as a second class city) by the mayor with approval of the council. 

County Government 

Although counties are also allowed to frame home rule 

charters, Allegheny County has not done so. It retains the 

traditional form of government provided by the state constitution and laws. The principal governing body is a threemember county commission, required to be bipartisan. 

There are 11 separately elected constitutional officers. The 

powers and duties of the county government and its offices 

are prescribed by statute. Allegheny is the only county of the 

second class (there are nine classes), and state law pertaining 

to the county government is, in effect, special legislation. 

This special legislation does not include rules affecting municipalities or school districts within the county. 

Municipal Authorities 

The Municipality Authorities Act, originally enacted 

in 1935,13 authorizes any county, municipality, or school 

district to form a “municipal authority” to perform specific 

functions. The local governing body, not the voters, 

creates the authority and appoints a five-member board of 

directors. Charged with responsibilities related to a particular purpose or project, municipal authorities may borrow 

money and issue revenue bonds, exercise the power of eminent domain, and impose service charges, but they do not 

have the power to tax.14 Municipalities often create authorities to finance and operate water and sewer systems. 

School districts create municipal authorities to finance 

and construct school buildings. Counties and municipalities may also create housing authorities and industrial development authorities, organized and governed along similar 

lines, but authorized under separate state legislation. 

The Municipality Authorities Act also authorizes two 

or more local governments, again including counties, municipalities, and school districts, to create “joint authorities.”15 A joint authority board must have a number of 

members at least equal to the number of participating local governments, but no less than five. The composition of 

U.S. Advisory Commission on Intergovernmental Relations 29 
each board is established by the authority’s articles of incorporation, giving the governments the flexibility to 

negotiate representation arrangements. New local governments may join an existing authority with approval of 

the authority board and the governing bodies of the other 

members. Current members may withdraw with approval 

of the authority board, provided that the authority has not 

issued bonds or other obligations. 

Joint authorities enable a group of small local governments to finance and construct large capital projects, such 

as water and sewer systems, transit systems, and airports, 

that would not be economically feasible for each government acting alone. The same arrangement allows county 

governments to join with municipalities in common projects. According to the Pennsylvania Department of Community Affairs (DCA), the creation of joint authorities 

was greatly stimulated in the 1960s when new state and 

federal legislation began to require higher levels of sewage treatment and to extend those requirements to many 

more communities. The U.S. Environmental Protection 

Agency (EPA) required construction of regional treatment facilities as a condition for receipt of grants. According to DCA, joint authorities created for this purpose 

often “represented the first time neighboring municipalities had ever cooperated in a joint program involving a 

heavy capital eXpenditure.”16 

Allegheny County, as a county of the second class, is 

authorized to create a port authority, governed by a board 

appointed by the county commissioners, which may impose user charges and issue revenue bonds. The Port Authority of Allegheny County provides bus and rail transit. 

A second class county (Allegheny County) or a second 

class city (Pittsburgh) may establish individual or joint 

public auditorium authorities. In the case of a city-county 

authority, two members of the governing board are appointed by the county commissioners, two by the mayor, and 

one jointly. Two auditorium authorities have been formedthe Pittsburgh-Allegheny County Public Auditorium Au- thority and the Pittsburgh City Stadium Authority. 

Environmental Improvement Compacts 

The 1968 Pennsylvania Constitution required the 

state legislature to provide for “area governments” that 

wou1.d include two or more m~nicipalities.’~ Accordingly, 

the Environmental Improvement Compact Law of 1972 

authorized the creation of area compacts by referendum, 

with concurrent majorities required among all affected 

municipalities. A compact, governed by an elected board 

of five, seven, or nine members, is authorized to conduct 

any governmental function, and may levy a real estate tax 

of up to 2 mills, impose service charges, issue bonds, and 

exercise the power of eminent domain.i6 

Compacts potentially represent a step beyond joint 

authorities in several respects. A compact constitutes a 

new, independent local government, created by citizens, 

not by local governing bodies. The compact board is 

elected, not appointed by local governing bodies, and has 

the power to tax, albeit a very limited power compared to 

municipalities. Thus far, the authority to create compact 

governments has not been used. 

BOUNDARY ADJUSTMENT RULES 

The boundaries of local governments are generally 

modified in one of two ways: annexation of new territory 

by an existing local government or consolidation of two or 

more units into a single government. The rules for making 

such adjustments vary widely from state to state. In Pennsylvania, annexation was made extraordinarily difficult by 

the 1968 state constitution, and consolidation, as in most 

states, is allowed only with the concurrent approval of voters in the affected jurisdiction^.'^ 

Annexation 

Like incorporation, municipal annexation becomes a 

much different issue in a state with no unincorporated 

territory. Before 1968, second class townships, although 

considered municipal corporations, were subject to annexation by boroughs and cities but were not allowed toannex 

territory from boroughs or cities. This was addressed by 

the 1968 constitution in two ways. 

First, the constitution authorizes boundary changes by a 

citizen initiative and referendum procedure, without action 

by municipal The procedure requires approval by 

concurrent majorities of voters in each municipality. Townships may acquire additional temtory, but only if the voters 

in another jurisdiction petition for and agree to the change. 

The same holds for boroughs and cities. There is no requitement that the territory added be contiguous.21 

Second, the state legislature wasdirected to enact a 

uniform annexation procedure for all types of municipal 

government. The legislature has not established such a 

procedure, resulting in the invalidation of all previously 

existing statutes without any replacement except the 

initiative and referendum. 

As a result, municipal annexation has been virtually 

eliminated. In its place is a relatively minor provision for 

boundary adjustment with the mutual consent of voters in 

the affected municipalities. The principal implication of 

this situation is that township residents may not obtain annexation by an adjacent borough or city without the consent of a majority of township voters. Under the 1968 

constitution, township residents cannot be given this capability without also allowing borough or city residents to 

seek annexation by an adjacent township. Boroughs and 

cities are apparently unwilling to risk the possibility of losing territory to townships in order to get the power to annex territory from townships. 

Consolidation 

Consolidation of local governments in Pennsylvania 

can take one of two forms: (1) absorption of one municipal unit by another and (2) the combination of two or more 

units to create a new unit. The 1968 constitution provides 

for consolidation by citizen initiative and referendum, 

with concurrent majorities in the affected jurisdictions. As 

with annexation, there is no requirement that local governments choosing to consolidate be contiguous. 

Neither annexation nor consolidation has been of 

great importance in Allegheny County since 1945. The absorption of Eden Park Borough by Mckeesport City in 

1952 has been the only consolidation. 

30 U.S. Advisory Commission on Intergovernmental Relations 
School district consolidation, or “combination” in the 

term used by state law, may be accomplished by a simple 

majority vote of the boards of school directors, with approval of the state board of education. Approval by local 

voters is not required. “Combined” districts need not be 

contiguous. During the 1960s, the state legislature provided for a special process of school reorganization in an 

effort to reduce the large number of small school districts. 

Reorganization plans were submitted to the state Department of Public Instruction by county boards of education 

(since abolished, replaced by intermediate units) and approved by the state Council of Basic Education. (School 

district consolidation is discussed further in Chapter 5.) 

FISCAL RULES 

The state code for each class of local government 

(e.g., the Borough Code or Public School Code) contains 

taxing authority. Additional taxing authority for local governments (in some cases redundant authority) is established by the Local ’EIX Enabling Act (1965), widely known 

as Act 511. This legislation allows local governments to exercise a broad range of taxing powers except a sales tax. In 

addition to real estate taxes, the most common sources of 

revenue are taxes on income, some of which apply to nonresidents; intangible personal property; occupation; occupation privilege; amusement; mercantile or business 

privilege; and a head tax. The local government codes and 

Act 511 establish revenue limits. Real estate tax limits do 

not apply to home rule municipalities, and are of only secondary importance in school districts. 

In nearly every instance, the taxing power is vested by 

state law in the local governing body (elected council or 

board), with no requirements for voter approval, except 

for initial approval of a few special purpose levies in boroughs and second class townships. Home rule municipalities and counties may establish their own rules with 

respect to electoral consent. 

Real Estate Taxes 

Real estate taxes have millage limits that differ among 

the classes of local governments. Boroughs and first class 

townships may levy up to 30 mills, but second class townships are limited to 16 mills. Third class cities are limited 

to 25 mills. Third class cities, boroughs, and townships may 

obtain court approval to exceed the limits by as much as 5 

All municipalities may also levy real estate taxes 

earmarked for specific purposes allowed by state law, including a levy of 3 mills to support volunteer fire companies in boroughs and townshipsz3 and an unlimited levy for 

debt service. For Allegheny County, the only second class 

county, the real estate tax is limited to 20 mills, 5 mills less 

than most other counties. However, the county has authority to use a variety of special levies. 

School districts have considerably greater authority to 

raise revenue. Although nominally limited to 25 mills on 

real estate, the districts also may levy a rate sufficient to 

meet minimum state requirements for teachers’ and supervisors’ salaries and to pay for building rentals and sinkingfund charges on indebtedness. They may also employ a 

number of special levies. In practice, therefore, school 

boards typically levy real estate taxes well in excess of the 

millage limit. In this way, the fiscal rules create an asymmetry between overlapping municipalities and school districts that frequently contributes to ill-will between their 

governing bodies. 

The 1968 constitution allows counties and municipalities to reconstitute themselves under home rule authority, 

which allows them, in part, to write their own fiscal rulesin 

the process of framing a charter. Home rule communities 

may establish real estate tax limits or have no limit. All local governments, however, remain limited to the taxes 

(e.g., real estate or income) authorized by the state legislature. Home rule thus overrides statutory real estate tax 

limits, but does not leave local governments free to enact 

any type of tax they please. 

Act 51 1 Taxes 

authorizes 

supplementary revenue sources for municipalities and 

school districts but not for Instead of enumerating each tax allowed, the statute provides general authority for political subdivisions to levy taxes on “persons, 

transactions, occupations, privileges, subjects and personal property.. . and upon the transfer of real property, or 

of any interest in real property within the limits of such political subdivisions. . . .”26 The total amount of Act 511 

taxes that may be imposed by any jurisdiction is limited to 

the amount that would be raised by a tax of 12 mills on the 

total market valuation of real estate in the jurisdiction. 

The statute establishes a large, somewhat indefinite set of 

local taxes in order to create a limited supplementary 

source of revenue. 

In addition to the general limit on all revenue from 

Act 511 taxes, the statute limits the rates on specific levies 

(none of the limits apply to home rule municipalities). The 

specific limits, rather than the general limit, have been the 

principal constraint on local taxing capabiliti~s.2~ Earned 

income taxes are limited to 1 percent, per capita taxes 

(head taxes) and occupational privilege taxes (distinguished from occupation taxes, discussed below) to $10 

per person,2s real estate transfer taxes to 1 percent of the 

amount of the transaction, and an amusement tax to 10 

percent (only Pittsburgh may impose this taxon movie theaters). Mercantile or business-privilege taxes are limited 

to 1 mill on the gross receipts from wholesale transactions 

and 1.5 mills on retail transactions (2 mills in Pittsburgh). 

Most of these tax sources raise revenue directly from 

residents of the taxing jurisdiction. There are two, relatively minor, exceptions. The occupational privilege tax is 

levied by and paid to the employing jurisdiction.29 The other exception is the earned income tax, with an important 

qualification. Municipalities (but not school districts) may 

impose the income tax on nonresident~,~~ who receive a 

tax credit if their jurisdiction of residence also has imposed 

an earned income tax. All communities in Allegheny 

County have adopted an earned income tax, thus virtually 

erasing the revenues that might be obtained from a nonresident levy.3i 

The indirect source of revenues collected from businesses may lie outside the jurisdiction. Those who ultiAct 511, the 1965 LocalTax Enabling 

U.S. Advisory Commission on Intergovernmental Relations 31 
mately pay a tax may be different from those who initially 

pay it.32 Two Act 511 tax sources have a clear potential for 

reaching nonresidents. The amusement tax may easily 

function as a 10 percent sales tax paid by consumers re- gardless of where they reside. Mercantile and business 

privilege measured by gross receipts, may be 

passed on to consumers, much like a sales tax. Pittsburgh 

may levy a tax of 2 mills on retail vendors (including restaurants), and the Pittsburgh School District is authorized 

by the Public School Code to levy a mercantile tax of 

one-half mill, including places of amusement, over and 

above the mercantile and amusement taxes authorized by 

Act 511.34The burden of commercial real estate taxes also 

may be borne, in part, by nonresidents, reflected in the 

prices that consumers pay for goods and services. (An 

analysis of the capacity of Allegheny County municipali- ties to raise revenues from nonresidents can be found in 

Chapter 6.) 

Act 511 overrides previous state restrictions on the 

power of local units to levy occupation taxes, which are 

based, like property taxes, on an assessed valuation of the 

occupati~n.~~ Only two small municipalities in Allegheny 

County made use of this tax in 1985. 

Many Act 511 taxes are subject to sharing between 

municipalities and overlapping school districts. In addition 

to the flat-rate occupation tax mentioned above, shared 

taxes are the per capita tax, earned income tax, real estate 

transfer tax, and occupational privilege tax. Sharing is either on a 50150 basis or as agreed to by the two jurisdictions. The requirement does not mean that both 

governingbodies must consent to the levy; however, if one 

unit decides to use the tax, it must share the revenues.% 

The result is to tie the process of raising revenue for one 

jurisdiction to that of another. A community decision to 

raise more revenue for schools, from most Act 511 

sources, cannot be made without also increasing revenue 

raised for municipal purposes, and vice versa.37 

The general language of Act 511 taxes creates some 

scope for local creativity in devising new taxes, with the 

added advantage that locally devised taxes are not subject 

to rate limitation. Efforts by school districts to levy taxes 

on residential construction ran into legal and political opposition and were eventually prohibited by the state legislat~re.~~ Taxes on the gross receipts of commercial parking 

lots have been allowed by the courts under the general au- thority of Act 511. In Allegheny County, the Moon Area 

School District, which encompasses the Greater Pittsburgh International Airport, levied such a tax at a rate of 

15 percent.39 The absence of rate limitation potentially allows the imposition of confiscatory rates. The City of Pittsburgh adopted a similar tax on commercial parking lots, 

eventually increasing the rate to 20 percent of gross receipts. The U.S. Supreme Court refused todeclare the tax 

unconstitutional under the Fifth and Fourteenth Amendments even though the city’s parking authority was a competitor with the taxpayers and the tax could render 

commercial parking unprofitable?O 

County governments, while not included in the general authorization of Act 511, may supplement their revenues from real estate taxes with a tax on intangible 

personal property.41 Originally mandated by state law in 

1913 and set at 4 mills, the county tax was made optional in 

1978.42 This tax source is reserved to county governments 

by Act 511, which prohibits municipalities and school districts from taxing personal property subject to taxation by 

counties.43 The City of Pittsburgh and the Pittsburgh 

School District are exempt from the prohibition, and are 

separately authorized to levy a personal property tax of 4 

mills each. As a result, Pittsburgh residents are subject to 

an effective rate of 12 mills on personal property. 

Special lax Districts 

Special tax districts are often created in relatively 

large heterogeneous jurisdictions, such as counties, as a 

means of increasing the level of service provision. In the 

absence of unincorporated territory, there is likely to be 

less need for this institutional device, and its use is quite 

limited in Pennsylvania. The principal demand for such 

districts would arise in second class townships, the “default form” of Pennsylvania local government. Second 

class townships are, in fact, authorized to create special tax 

districts to provide fire hydrants, street lighting, and police 

protection, on petition by a majority of the property own- ers in an area. Libraries are one municipal-type service 

that Pennsylvania county governments sometimes provide. Municipalities that maintain a library may, with voter 

approval, withdraw from a county library district and cease 

to pay county library taxes, in effect creating a special tax 

district in the remainder of the 

Debt Rules 

The 1968 Pennsylvania Constitution rewrote the basic 

rules governing municipal debt. The previous constitution 

had set a municipal debt ceiling at 15 percent of the assessed valuation of taxable property. Debt in excess of 5 

percent required voter approval. The new constitution 

does not establish debt ceilings, but does authorize the 

legislature to fix limits based on the total revenues of a 

municipality rather than on the assessed valuation of 

property. Accordingly, in 1972, the legislature provided 

for the computation of a local “borrowing base” byaveraging the total of money received by a local government unit 

from all sources for the preceding three fiscal years.4’The 

Local Government Unit Debt Act (1972) also prescribes 

limits of 300 percent of the borrowing base for counties 

and 250 percent for all other local government~.~~ The

statute defines local governments as cities, boroughs, 

townships, and school districts. Authorities are not included; they may issue revenue bonds but may not incur 

general obligation debt. 

The legislature also defined a category of debt not 

mentioned in the constitution. “Lease rental debt” consists of payments by a municipality or school district to an 

authority for the use of a facility, which the authority uses 

for debt service. Court decisions under the old constitution had defined such payments as n~ndebt,~~ thus allowing municipalities to create a municipal authority to avoid 

constitutionally imposed debt ceilings. The Local Government Unit Debt Act, however, explicitly treats such payments as debt and prescnies a second set of debt limits that 

32 US. Advisory Commission on Intergovernmental Relations 
include lease rental debt, 400 percent of borrowing capacity 

for counties and 350 percent for all other local governments. 

Both the old and new state constitutions exempted 

“self-liquidating” debt from limitation .48 The exception 

applies to debt incurred for projects that are supported 

from project-generated revenues. Thus, municipalities, 

like authorities, are free to issue revenue bonds without 

legal constraint. 

The 1968 constitution permits local governments to 

supplement their borrowing capacity by obtaining voter 

approval for a debt issue. The legislature distinguishes 

“electoral debt” from “nonelectoral debt.” Debt approved 

by the voters in a referendum is not included in the computation of a jurisdiction’s nonelectoral debt.49 The ballot 

issue must specify the purpose or project for which funds 

will be used. Referenda also are required to convert nonelectoral to electoral debt and to change the purpose for 

which electoral debt was incurred. 

The new constitution and implementing legislation 

created greater borrowing freedom for municipal officials 

and, at the same time, gave local citizens the power to 

ovemde statutoq limitations by majority vote in a referendum. The loophole that allowed local governments to 

use authorities to evade debt limits was plugged. Since 

1972, there has been no reason to create municipal authorities to expand debt capacity. Municipalities enjoy greater 

freedom to incur debt, but local officials are somewhat 

more constrained, given the inability to use authorities to 

increase debt without limit. 

CONTRACTUAL RULES 

The Intergovernmental Cooperation Act of 197250 

implementing Article IX, Section 5, of the state constitution, authorizes counties, municipalities, and school districts to enter into joint service agreement~.~~ Theonly 

requirement is that each jurisdiction be authorized to undertake any function to be performed jointly. Local governments also are authorized to transfer functions. 

Interlocal agreements were first authorized by state law in 

1943, but the old law excluded school districts and did not 

permit transfer of functions.52 Citizens may use the initiative and referendum to compel their governing bodies to 

enter into an intergovernmental agreement or to transfer 

 function^?^ Among the joint activities that can be set up 

under the Intergovernmental Cooperation Act are mutual aid agreements, parallel-action agreements (e.g., agreements for joint financial support of community libraries or 

volunteer fire cornpanie~),~~ contract purchase of services, 

and joint service production (e.g., an emergency dispatch 

center). Councils of governments (COGS) are created under the same intergovernmental authority. 

LOCAL GOVERNMENT FORMATION 

IN ALLEGHENY COUNTY 

A local government constitution consists of possibilities-options-until communities choose to create government units and arrangements. The rules of association, 

together with the fiscal, boundary change, and contractual 

rules, establish the legal constraints and opportunities within 

which communities create the institutions of local government. The citizens and elected officials of Allegheny County 

have used their authority to form governmental units sclcctively, over the years, to establish and maintain a large number of municipalities and municipal authorities, but to resist 

consolidation of local governments, including (often without 

success) state efforts to consolidate school districts. 

Historically, municipal incorporation- especially boroughs-was an important way by which Allegheny County 

communities constituted local governments. Most of the 

76 boroughs were formed prior to World War I.55 Development generally featured dense residential use of land and 

“Main Street” shopping, often, in the Mon Valley, clustered around a large steel plant. To govern these communities, boroughswere carved out of the territory of existing 

townships, displacing township organization. In more recent years, suburban development became less intensive, 

and began to feature large residential lots in subdivisions 

separated by expanses of open space. Shopping centers replaced Main Street, and industrial development slowed. 

Borough incorporation also came to a virtual standstill.’6 

Instead, second class townships were upgraded, and many 

of those undergoing population growth became first class 

townships or adopted home rule charters.” Today, 21 of 

the 33 townships (64 percent) are first class, making them 

the second most numerous class.5s Eight of the remaining 

second class townships have population densities that 

would permit first class status, but they have not chosen to 

exercise the option. 

Despite its infrequent use in recent years, borough incorporation continues to offer local communities a potential option. The most recent incorporation, in 1976, was 

Pennsbury Village, a 500-unit condominium community 

occupying 46.7 acres east of Pittsburgh, formerly in Robinson Township. Originally a rental community, the units 

were sold as condominiums in 1973. A perceived lack of 

adequate street maintenance and police protection from 

the township government led to consideration of forming 

aborough, but the major impetus came when the township 

sought to require residents of Pennsbury Village, which 

had its own wastewater treatment plant, to connect to a 

new township facility at a one-time cost of $200,000 plus a 

tap-in fee of $37,000 and a monthly charge of $30 per unit 

thereafter. By comparison, incorporation required, in addition to time and effort, collecting contributions to cover 

legal costs of slightly over $20,000. Today, the borough 

government and the condominium association function 

side by side, each electing a council. The condominium 

council, with a budget still three to four times the size of 

the borough budget, retains responsibility for the maintenance of common grounds- 38 buildings, lawns, and recreational facilities. The borough government is responsible for 

police, fire, emergency medical service, streets, trash collection, and wastewater treatment. The borough council contracts with the nearby Borough of Camegie for police, fire, 

and ambulance services, and employs an engineer to offer 

technical advice on street maintenance and operation of the 

wastewater treatment plant. 

In sharp contrast to the consolidation of school districts (see Chapter S), Allegheny County has seen little activity related to the consolidation of municipalities in 

U.S. Advisory Commission on Intergovernmental Relations 33 
recent decades. The 1968 state constitution modified the 

consolidation rules to allow for citizen initiative and referendum without participation by municipal officials. Since 

that time, 21 citizen initiatives have been on the ballot 

throughout the state (none in Allegheny County), only 

two of which were approved.59 

The most numerous type of local government in Allegheny County is the municipal authority. As discussed 

above, before 1968, authorities were created in part to 

evade debt limits. They also are used as intergovernmental arrangements. About one-third of the 149 municipal 

authorities in Allegheny County in 1985 were created after the adoption of the 1968 constitution. Most of the recently established authorities are for water, sewer, and 

health services, functions for which there are likely to be significant economies from intergovernmental cooperation. 

Absent in Allegheny County-and throughout Pennsylvania-are special purpose governments, other than 

school districts, with separately elected officials and independent taxing powers. Municipal authorities lack both of 

these features. In other states with large numbers of local 

governments, independent special districts are often used 

to provide fire protection, parks, and libraries, in addition 

to water and sewer facilities. Compact governments, a 

type of unit created pursuant to the 1968 constitution to 

provide opportunities for “area government,’’ could possibly be used as special governments. The statute, however, 

is very general-even vague-in its language; one interpretation is that compact governments are not special 

units, but a new “level of government,’’M, Greater specificity may be required to enable communities to create limitedpurpose governments rather than “area governments” 

with general powers, albeit very limited fiscal powers. In 

any event, there is no particular demand for this type of 

jurisdiction. 

Each of the municipal classes-cities, boroughs, and 

first and second class townships-have drawn on the home 

rule powers made available by the 1968 constitution. 

McKeesport adopted a home rule charter in 1973, and 

Pittsburgh did so in 1974. Six former boroughs and 9 former townships have done the same. In addition, two townships have adopted optional plans of government, creating 

township managers. Home rule charters, in addition to enhancing the revenue powers of municipalities, enable boroughs and townships to redesign their forms of 

government. Most have chosen to create some variation 

of the council-manager form. Communities that want to 

retain the historic borough or township government have 

not adopted home rule charters and operate under the local government code for their municipal class. 

SUMMARY 

The character of governance in a metropolitan county 

such as Allegheny depends on (1) the nature of the rules 

that apply to diverse local governments and (2) the nature 

of the process for making and adjusting those rules. On 

the one hand, the legal framework gives citizens and 

elected officials considerable authority to create and 

maintain a variety of local government units. On the other 

hand, the process for adjusting the legal framework includes 

a state constitutional requirement for uniform statewide 

legislation within municipal classes. 

Most of the flexibility available to local communities 

derives from borough incorporation, optional plans of 

government, home rule charters, and the creation of municipal authorities. Citizen consent is required in all cases 

except the creation of municipal authorities. Boundaryadjustments between municipalities require concurrent majorities in both jurisdictions. As a result, it is more difficult 

for a portion of a township to annex itself to an adjoining 

borough or city than to incorporate as a borough. 

The use of the initiative and referendum has been 

slow to develop in Pennsylvania. One result has been a 

widespread reliance on nonbinding advisory referenda on 

controversial issues.61 Although the 1968 constitution instituted initiative and referendum procedures to decide 

boundary adjustments, the voting rule is such that few 

boundary adjustments can succeed. 

Perhaps the principal authority in the hands of citizens is the power to frame and adopt home rule charters 

that contain broad initiative and referendum powers on 

other issues as 

State law makes very little use of citizen referenda in 

the local fiscal rules, with the exception of debt approval. 

Municipal officials who seek to raise the real estate tax 

rate above the statutory limit must take their case to court 

rather than to the voters. School district directors have 

even less restriction on their ability to raise rates. As a result, local citizens are required to take their case against a 

tax increase to local officials, rather than having local officials bring their case for a tax increase to them. 

There is some difference in the way different local 

governments are treated by the state constitution. Allegheny County, the City of Pittsburgh, and the Pittsburgh 

School District are governed by what is, in effect, special 

legislation. Pittsburgh is a home rule city, reducing its dependence on state legislation while allowing a degree of 

special treatment by the state legislature. At the same 

time, the townships, boroughs, and other school districts 

in the county are governed by general law applicable to 

broad municipal classes. The result is an ability to tailor the 

local government constitution to the needs of Pittsburgh and 

Allegheny County, while other governments in the county 

are treated exactly like similar units throughout the state. 

The Allegheny County government, although an 

overlying unit with countywide jurisdiction, has little authority over other governments in the county. County government is broader than municipalities and school 

districts, but it is not a “higher” government in a hierarchical sense. Instead, the basic governance of Allegheny 

County m a multijurisdictional metropolitan area is mainly 

through the state constitution and statewide legislation. 

The rules that govern the formation of local governments, 

modifications of boundaries, revenue-raising capabilities 

and limitations, and interjurisdictional relationships are 

state rules. The Pennsylvania Constitution requires that 

state legislation with respect to local government “be uniform as to all classes of local government regarding procedural Local or special laws that would regulate 

the affairs of local governments, or that would create new 

34 U.S. Advisory Commission on Intergovernmental Relations 
townships or boroughs, or modify the boundaries of townships, boroughs, or school districts, are explicitly forbidden.64 Legislation that applies exclusively to the City of 

Pittsburgh or to Allegheny County (but not to other local 

governments in the county) is allowed on the basis of classification by population. Whether this practice is a matter 

of constitutional necessity or legislative custom is unclear. 

Uniform state legislation may attenuate the process 

of metropolitan governance in Allegheny County. Local 

governments are unable to negotiate a settlement of common issues and have that settlement translated into state 

legislation. The major issues affecting Allegheny County 

as a metropolitan area become entangled with statewide 

issues. Conflicts among townships, boroughs, cities, and 

school districts must be settled on a statewide basis if 

settlements are to be incorporated as a part of uniform 

legislation. Important intergovernmental issues, such as 

the tension between townships and boroughs over annexation, remain unresolved. Other issues, such as the fiscal 

formula relating the revenue-raising powers of a central 

city like Pittsburgh to those of the surrounding governments, have to be settled in the same way throughout the 

state instead of being adapted to the specific time-and-place 

conditions of a complex metropolitan area. 

In its study of St. Louis County, ACIR concluded that 

metropolitan governance need not require a metropolitan 

government. Governance does depend, nevertheless, on a 

rulemaking capability that is metropolitan in scope. State 

rulesapply to Allegheny County in its entirety, and, therefore, the minimal condition for metropolitan governance 

is met. There are rules, and they apply countywide. The 

difficulty is that the same rules apply simultaneously to the 

rest of the state. This has the effect of reducing the incentives of local officials to engage in forms of entrepreneurship 

that would depend on adjustments in general state law. 

One feature of the local government constitution in 

Pennsylvania, however, appears to mitigate intergovernmental conflict: the absence of unincorporated territory. 

The existence of second class townships as a “default” 

form of local government means that county governments 

are, outside Philadelphia, always an overlying unit, never 

the only local jurisdiction in a community. Counties and 

municipalities are not rivals contesting for unincorporated 

territory. This situation may leave county officials free to 

adopt strategies that are generally supportive of local municipalities, including a central city, such as Pittsburgh. 

A major area of unresolved conflict in Allegheny 

County concerns fiscal rules. The City of Pittsburgh is concerned that it is precluded from levying an income tax on 

nonresidents. The provision that keeps Pittsburgh from 

doing so, however, is part of Act 511 authority given to 

classes of municipalities on a statewide basis. All that the 

suburban jurisdictions must do, under state law, to deny 

Pittsburgh a nonresident tax is to enact an income tax on 

their residents. Changing the rules depends on statewide 

negotiations, not just on an accommodation between 

Pittsburgh and its surrounding municipalities. Maintaining an appropriate fiscal balance between the central city 

and the suburbs may require occasional tinkering with the 

fiscal rules-a process that would seem to face prohibitive 

obstacles, including costs of time and effort, if the whole 

state is affected by a change. 

Notes 

Robert E. Woodside, Penmylvania Constitutional Law (Sayre, 

Pennsylvania: Murrelle Printing Co., 1985), pp. 507-509. DilIon’s Rule became a part of federal precedent on appeal of a 

Pennsylvania case, Hunter v. Pittsburgh, upholding Pitts- burgh’s unilateral annexation of the City of Allegheny. 

See US. Advisory Commission on Intergovernmental Rela- tions (ACIR), The Organiration of Local Public Economies 

(Washington, DC, 1987); and Ronald J. Oakerson and Roger 

B. Parks, “Local Government Constitutions: A Different View 

of Metropolitan Governance,” Amen‘can Review of Public Ad- ministration 19 (December 1989): 279-294. 

53 Pennsylvania Statutes, Chapter lf2. 

In many other states, mostly in the Midwest, townships are not 

considered to be municipal corporations as they are in Penn- sylvania and throughout New England. 

Pennsylvania Department of Community Development, Ref- erendum Handbook, 4th Ed. (Harrisburg, 1987), p. 26. 

The provision was held to violate the constitutional require- ment of a uniform boundary change law, discussed below. See 

Referendum Handbook, pp. 28-29. 

53 Pennsylvania Statutes, Chapter l/2; Home Rule Charter 

and Optional Plans Law. Philadelphia has had home rule au- thority since 1952. 

Pennsylvania Department of Community Affairs, Boundary 

Change Rules (Harrisburg, 1985), p. 24. 

See the discussion in Referendum Handbook, pp. 17-19. 

lo 24 Pennsylvania Statutes 2-201. 

l1 School districts are classified by five population classes for leg- islative purposes. See Chapter 5. 

l2 Formerly, state law allowed a majority of taxable inhabitants of 

any contiguous territory to form an “independent” district by 

petition to the court of common pleas. Concurrent majorities 

were required if the proposed district included temtory within 

more than a single established district. The formation of inde- pendent districts was disallowed in 1965, except to join another 

school district. 

l3 53 Pennsylvania Statutes 306. 

l4 Townships may also create special taxing districts for portions 

of a township, but these districts have no independent author- ity or separate governing body. See discussion of fiscal rules. 

l5 Pennsylvania Department of Community Affah, COGsundlntergovemmental Cooperation, 4th Ed. (Harrisburg, 19861 pp. 7-8. 

Ibid., p. 7. 

l7 Ibid., p. 2. 

l8 The only other provision for special purpose governments 

with independent powers of taxation is for the creation of wa- ter supply districts, which may be formed in any county on the 

petition of resident landowners to an appropriate court. 

l9 Some students of local government see any reliance on con- current majorities as reactionary, evoking the spirit of John C. 

Calhoun, and used as a selfish device by some groups to evade 

their responsibility for the greater public good. Others argue 

that the idea of concurrent majorities is based on a venerable 

federalist or covenantal principle-a principle of union as the 

foundation for achieving a greater public good. The principle 

comes into play every time a state is admitted to the union 

called the United States of America. Admission to the Union 

requires the consent of the Union and the consent of the peo- ple who live in the prospective state. Furthermore, the boundU.S. Advisory Commission on Intergovernmental Relations 35 
aries of a state cannot be changed without its consent. Clearly, 

the principle underlying the use of concurrent majorities did 

not die with Calhoun. The Advisory Commission on Intergovernmental Relations has endorsed the use of concurrent majorities to effect municipal consolidation. See ACIR, Stare and 

Local Roles in the Federal Systeni (Washington, DC, 1982) p. 448. 

*O The procedure requires a petition signed by registered voters 

comprising 5 percent of the total number of votes cast for the 

office of governor in the last election vjithin each municipality. 

Referendum approval requires a simple majority of the votes 

cast in each municipality. 

21 Referendum Handbook, pp. 14-15. 

22 The municipality may be required to show that its request is 

based on due and reasonable cause, that it has exhausted all 

reasonable means of additional taxation, and that it has diligently explored all the facts necessary to form an intelligent 

judgment. The court does not determine the necessity or wis- dom of the tax increase, but merely inquires as to whether the 

municipality’s request is an abuse of discretion. 

23 Additional levies for the support of fire protection must be approved by voters in a referendum. Also with voter approval, 

second class townships may levy aspecial real estate taxup to 2 

mills for fire hydrants. Boroughs may impose an additional levy of 

8 mills to provide fire hydrants, fire hose, and street lighting, again 

with voter approval. (Referendum Handbook, p. 14.) 

24 53 Pennsylvania Statutes 6901. 

25 Philadelphia, as a first class city, is also excluded from Act511. 

26 53 Pennsylvania Statutes 6901 (Local Tax Enabling Act, Sec- tion 2). 

27 Pennsylvania Department of Community Affairs, Tmration 

Manual, 4th Ed. (Harrisburg, 1986), p. 14. 

28 In the case of third class cities, the Act 511 per capita tax may 

be levied on top of a $5 head tax authorized by the Third Class 

City Code. It may also be levied by Pittsburgh in addition to a 

$1 poll tax (a head tax that has no relation to voting). 

29 See Tmtion Manual, p. 23. 

30 Home rule municipalities are limited to the statutory rate of 1 

percent for nonresidents. 

31 In fact, the crediting rule creates a powerful incentive for all 

jurisdictions within a common area of employment to adopt 

the income tax once any significant number of jurisdictions has 

done so. Thus, the enabling provision alone virtually guarantees that the earned income tax will be universally used in a 

metropolitan area. The earned income tax is the second larg- est local revenue producer in the state, but this may be a result 

of the incentive created by state law rather than local preference. A much different pattern is found in the Philadelphia 

metropolitan area. Philadelphia is authorized separately to 

levy a wage and net profits tax, including a levy on nonresidents. No provision is made for crediting an Act 511 income 

tax against the Philadelphia tax. The Pennsylvania Department of Community Affairs reports that 119 municipalities in 

the four suburban counties that border Philadelphia (Bucks, 

Chester, Delaware, and Montgomery) have no earned income 

tax (Taration Marzual, p. 15). In this case, the reverse strategy 

may be at work-suburban communities choose not to enact 

an earned income tax in order to attract businesses to relocate 

from Philadelphia. The only other communities in the state 

without an earned income tax are located in predominantly ru- ral areas. 

32 This phenomenon, known as “tax incidence,” is a complicated 

subject in the study of public finance, and cannot be explored 

here. 

33 Although Pennsylvania law distinguishes mercantile from 

business privilege taxes, the difference is “more semantic than 

real” (Tmation Manual, p. 27). 

34 Ibid. 

35 In Pennsylvania, occupations are subject to taxation on the basis of assessed valuation, much like property. The system dates 

from its use in England during the colonial period, when many 

occupations were owned as property and could be sold or 

transferred to others (Taration Manual, p. 23). County assessment boards in Pennsylvania determine the assessed valua- tion of occupations, usually by creating a hierarchy of 

occupation classes. Municipalities are authorized by the state 

codes to levy an occupation tax on a millage basis up to the 

same limit as the real estate tax. The occupation tax is levied 

only on residents. Act 511 overrides the taxceilingbyauthorizing municipalities to levy an occupation tax without a millage 

limit. The law extends this authority to school districts, some of 

which obtain high occupation tax yields by setting extremely 

high rates (Ibid.). In addition, Act 511 authorizes a flat-rate 

occupation tax limited to $10. 

36 The sharing requirement for earned income taxes does not ap 

ply to revenue raised by a home rule municipality in excess of 

the statutory rate limit. 

37 The sharing requirement would appear to contradict one major purpose of creating a separate and independent school dis- trict -to avoid mixing school-related decisions with other 

political decisions. 

38 Tawation Manual, pp. 36-37. 

39 The tax was upheld by the state supreme court, which con- cluded that interstate commerce was unaffected and that tax- payers benefited from a civilized society made possible in part 

by education. See Ibid., p. 36. 

City of Pittsburgh v. Alco Parking Corp., 417 U.S. 369 (1974). 

See discussion in Taration Manual, p. 36. 

41 The City of Philadelphia, in effect a city-county, also may levy 

this tax, as may the Philadelphia School District (which does 

not do so). See Tmafiori Manual, p. 19. Allegheny County is also 

authorized to levy a 1 percent tax on hotel Mom rentals, with rev- enues earmarked to support convention centers. Ibid., p. 35. 

42 Ibid., p. 19. 

43 53 Pennsylvania Statutes 6902 (6), Local Tax Enabling Act, 

44 Referendum Handbook, p. 24. 

45 53 Pennsylvania Statutes 6780-2 (16), Local Government Unit 

46 These limits do not apply to Philadelphia or to the Philadel47 See Walter W. Shearer, “Local Government Debt,” Section 10, 

Section 2 (6). 

Debt Act of 1972. 

phia school district. 

in Woodside, pp. 531-532. 

See Shearer, p. 531. 

53 Pennsylvania Statutes 481. 

Philadelphia, as a first class city, is excluded from this act. 

49 Referenduni Handbook, pp. 15-16. 

52 COGs and Intergovemntental Coopemtion, p. 3. 

53 Refereniiiini Handbook, p. 24. 

54 COGs and Intergovemrnerital Coopemtion, p. 5. 

55 McDonald and Trafford, only parts of which are in Allegheny 

County, are not included in this count. 

56 Only four boroughs have been incorporated from portions of 

townships in Allegheny County since 1945: Pleasant Hills and 

Whitehall (1943, Baldwin (1960J and Pennsbury Village (19n) 

36 U.S. Advisory Commission on Intergovernmental Relations 
57 It is also possible for an entire township to incorporate as a 

borough. Second class townships received new powers following World War 11. 

'' In 1937, the formation Of first Class townships Was given impetus when the state legislature provided protection from annexation not available to second class townships. The special rule 

required voter approval for any annexation of township territory. See Boundary Change Rules, p. 2. 

59 Boiindary Change Rules, pp. 18-19. 

60 COG^ I~~~~~~~

" Referendum Handbook, pp. 1-5. 

62 Fofiy-one of the 58 home rule charters adopted throughout 

the state contain provisions for initiative and referendum. bid. 

63 Constitution Of Pennsy1vania9 Section '. 64 Constitution of Pennsylvania, Article 111, Section 32. 

U.S. Advisory Commission on Intergovernmental Relations 37 
38 U.S. Advisory Commission on Intergovernmental Relations 
Municipal Services: 

Police, Streets, Fire Protection 

This chapter turns from a discussion of general patterns of metropolitan organization and governance in Allegheny County to the organization for provision and 

production of specific municipal services-police protection, street and street-related services, and fire protection.' The basic patterns are somewhat different between 

police and street services, and quite different between 

these services and fire protection. There are numerous instances of interlocal cooperation and coordination. 

The arrangements for basic service provision in the 

county are highly noncentralized. Police and street services are provided by municipalities, the county, and the 

state, virtually all by public departments. Fire services 

throughout most of the suburban county are organized by 

relatively small voluntary associations. Volunteer departments provide and produce fire services in all municipalities except Pittsburgh, McKeesport, and Wilkinsburg, 

which have municipal departments. There are relatively few 

intergovernmental contracts and few joint production units 

for direct services, although some experimentation with joint 

production is under way, especially for street services. 

The situation is quite different with respect to indirect 

or adialy services (e.g., communications, purchasing, and 

training), for which there are contractual, cooperative, and 

even centralized production arrangements. Many local departments that supply direct services report cooperation with 

neighboring departments, especially for fire services (more 

than 90 percent in a 1982 sample of fire chiefs).2 Cooperative 

efforts also were reported by more than 50 percent of a sample of police chiefs, and approximately 25 percent of a sample of public works director^.^ Individuals interviewed for 

this study indicated that interjurisdictional cooperation has 

become more widespread in response to efforts by a number 

of organizations in the county. 

POLICE SERVICES 

Of the 130 municipalities in Allegheny County, all but 

one made provision for local police service in 1987. The 

predominant organization is a municipal police department (see able 4.1). Sixty municipalities maintain 58 police departments composed entirely of full-time officer^.^ 

Three of these 60 municipalities, Pine and Marshall Townships and Bradford Woods Borough, operate a combined 

full-time department, the first such organization created 

Table 4.1 

Police Service Provision in Allegheny County Municipalitiesa 

hmnicipal Number of Municipalities With: 

Population Number of Municipal Full-Time Mixed Part-Time Con tract 

Category Municipalities Population Department Department Department Policing 

0-1,OoO 12 6,270 1 1 

1-2,Ooo 18 26,770 4b 10 

2-5,OOO 39 135,210 1IC 25 

5-10,OOO 31 238,710 20 11 

lO-u1,OoO 14 191,790 10 3 

20-55,M)o 13 386,770 13 0 

Pittsburgh 1 387,490 1 0 

2 8 

4 0 

3 0 

0 0 

0 Id 

0 0 

0 0 

Totals 128 1,373,010 60" 50 9 sd 

'Excluding McDonald and Trafford. 

bIncludes one municipality served by a joint police department. 

lncludes two municipalities served by a joint police department. 

"Includes one municipality served by Pennsylvania State Police. 

lncludes three municipalities served by a single joint department. 

Sources: 1987 police strength from Pennsylvania State Police. 

1986 population estimates from Pennsylvania State University. 

U.S. Advisory Commission on Intergovernmental Relations 39 
in Pennsylvania (in 1969) and still one of the few examples. 

An additional 50 municipal departments employ full-time 

and part-time officers, while nine departments have only 

part-time officers. Contracting for basic police services is 

uncommon. Eight small municipalities, none with populations exceeding 600, contracted with neighboring munici- palities for police services in 1987. One municipality, 

Clairton, made no provision for police services, relying instead on the State Poli~e.~ 

Police services are produced by 117 municipal police 

departments, the Allegheny County Police Department, 

the Pennsylvania State Police, the Housing Authority of 

the City of Pittsburgh, the Port Authority of Allegheny 

County, and several college and university campus police 

forces! The number of independent producers of police 

services is substantially Iarget than that laud in mast 

metropolitan counties. In a 1975 survey of 80 metropolitan 

areas, for example, the highest number of police patrol 

producers of all types in a single area was 91, while the me- dian number was 13.’ Allegheny County has roughly nine 

police departments per 100,000 citizens, 50 percent higher 

than in the median metropolitan area in 1975. 

The explanation for the large number of police departments is that Allegheny County has many more municipalities than most metropolitan counties in the United 

States,s and 93 percent of them have a local police department. Nationwide, almost all county and municipal governments produce at least some police services through a 

police department. In a 1982 study, 96 percent of more 

than 1,600 responding communities organized their crime 

preventiodpatrol services either wholly or in part with local government employees? 

Local observers offered hypotheses to explain the 

persistence of this choice in Allegheny County. One factor 

they identified is the “weak mayor” form of borough government. In Pennsylvania boroughs, the mayor is not a 

member of the governing council1o and has few functional 

responsibilities, but is responsible for day-to-day operation of the police department. If a borough contracted 

with a neighboring government for police service, or entered into a joint production arrangement, the mayor 

could lose this responsibility but might oversee a contractual 

arrangement. According to several local informants, mayors 

tend to oppose joint police ventures. Nevertheless, the plausibility of this factor as an explanation for the lack of joint 

ventures is limited by the lack of political power typically associated with the position of mayor in most boroughs. 

Another explanation offered by local observers is the 

unwillingness of municipal police chiefs to surrender their 

authority by becoming supervisors in a larger, merged department. The Pine-Marshall-Bradford Woods joint police department, the only one in the county, was created at 

a time when Bradford Woods had one officer and Mar- shall had none. It was relatively easy to expand the Pine 

Township Police Department to include Bradford Woods 

while avoiding controversy over who would be the police 

chief-the chief of the PineTownship department was the 

obvious choice.” 

In 1983, the Allegheny Valley North Council of Governments, with assistance from the Pennsylvania Department of Community Affairs, developed a plan for an 

Allegheny Valley Regional Police Department.I2 The plan 

has not been implemented. Obstacles are said to include 

concerns about loss of local control by borough mayors, 

township commissioners and supervisors, and their constituents; an inability to agree on a process for selecting a 

chief; differences in union contracts; and differences in 

pension plan provisions and extent of full funding.13 

The Allegheny County Police Department has 220 

full-time officers, four times as many as the largest municipal 

department outside Pittsburgh. The county police patrol 

countyparks and the airports. They are also, in effect, a “major case squad,” investigating serious crimes in the jurisdic- tions of municipal departments on invitation of a local chief 

of police. The county poke supply back-up to municipal 

hces when reqneskd, qe&&u;rd seaices o\he~ than investigations (especially a hostage negotiation team called 

PASS).14 and narcotics and organized crime investigations. 

The availability of these specialized services from the 

county police was offered as a third explanation of why 

small municipalities maintain their own police depart- ments. An additional explanation, not cited by local ob- servers, lies in Pennsylvania law. There is no legal 

requirement that municipalities provide police protection 

or that there be full-time police department^.'^ The State 

Police can and do provide police service for municipalities choosing not to organize a municipal department. 

Many of the smaller municipal police departments in 

Allegheny County rely extensively on part-time officers, with few or even no full-time officers. Amunicipality may establish a police department at very low cost, 

and supplement its effort with services from the county 

police or the state police as needed. 

All of these conjectures must be considered explana- tions as to why Allegheny County is not atypical. Given a 

set of provision units, production arrangements in a sense 

require no special explanation because they are not variant. The borough mayor explanation is peculiar to Pennsylvania, while the police chief explanation potentially 

would apply anywhere. Both can be considered short-term 

political costs. The availability of county supp1ementa.y 

police services is not so much an obstacle to joint ventures 

as it is a substitute. It is not a cost of joint action, but a factor that reduces the potential benefit of joint action. The 

statutory explanation refers to a lack of special legal incentive to engage in joint action, but there is nothing atypical 

in this, either. The choice of production arrangements for 

basic police services in Allegheny County, like the choice 

made throughout the United States, is predominantly that 

of locally organized police forces which, in turn, have 

back-up and supplementary service available to them from 

neighboring and overlapping jurisdictions. 

Jurisdiction Size and Costs Per Capita 

Most of the municipal police jurisdictions in Allegheny 

County are small, and so are their police departments. Of 

the 117 municipal police departments, only 38 employed 

more than 10 full-time officers in 1987, and only 12 (including Pittsburgh) employed 25 officers or more mble 4.2). 

Still, most full-time police officers are employed by, and 

40 US. Advisory Commission on Intergovernmental Relations 
Table 4.2 

Police Service Production by Allegheny County Municipalitiesa 

Dpartment Percent Number of Percent of Number of 

Size of County Percent of Full-time Full-time Part-Time 

(full-time) Population Population Departments Officers Officers Officers 

Part-time only 14,990 1 % 8% 0 0% 63 

4- 10 253,050 18 43 336 15 106 

1-3 45,070 3 17 39 2 118 

11-24 331,410 24 22 374 17 15 

25-55 329,140 24 9 397 18 1 

Pittsburgh 387,490 28 1 1,063 48 0 

Totals 1,361,150 98 100 2,209 100 303 

.Excluding McDonald, Trafford, and Clairton. 

Sources: 1987 police strength from Pennsylvania State Police University. 

1986 population estimates from Pennsylvania State. 

Table 4.3 

Police Department Characteristics 

Full-Time Part-Time 

Department Officers Officers Per Capita 

Part-Time 

Value in Median DeDartment: 

Size per 1,000 per 1,000 Expenditurea 

Only - 4.30 $26 

1-3 0.81 2.40 52 

4-10 1.40 0.23 55 

11-24 1.21 0.00 50 

25-55 1.35 0.00 58 

Pittsburgh 2.74 0.00 98 

1 a See note 18. 

Percent of 

Part-Time 

Officers 

21% 

39 

35 

5 

0 

0 

100 

most Allegheny County residents receive police services 

from, the larger departmcnts. Nearly one-half (48 percent) 

of the full-time municipal police officers work in Pittsburgh, and an additional 35 percent work in departments 

with more than ten full-time officers. Three-fourths of the 

county’s population reside in arcas served by departments 

with more than ten full-time officers.“ 

The smaller departments augment their service delivery capacity by employing part-time officers. In 1987, there 

were 303 part-time officers employed in the county, and 

virtually all of them worked in departments with ten or 

fewer full-time officers and municipalities with populations of less than 5,000.17 

Per capita police expenditures of Allegheny County 

municipalities in 1985 ranged from a low of $15 to a high of 

$323 per year.“ The countywide average was $65 per capita, while the population-weighted median expenditure 

was $50. Per capita costs in Pittsburgh were $98. Eleven 

small municipalities, either wealthy residential communities or industrial enclaves, had per capita police costs higher 

than Pittsburgh’s in 1985, but their combined population 

was less than 1.5 percent of the county total. 

When compared with other metropolitan citykounties of similar size, Allegheny County has substantially 

fewer police officers and spends less for police services. 

The 2,209 officers employed by municipalities in the 

county, divided by the estimated population in 1986, yield 

a ratio of 1.62 officers per 1,000 residents. If the Allegheny 

County police are added, the ratio increases to 1.78 per 

1,000 residents. By way of comparison, St. Louis and St. 

Louis County, Missouri, with approximately the same 

population as Allegheny County, employ 3,607 officers, 

with a ratio of 2.54 officers per 1,000 inhabitants.” The 

City of St. Louis had nearly 4 officers per 1,000 residents, 

compared to the City of Pittsburgh’s 2.74.” The ratio of 

officers to citizens in St. Louis County (which does not include St. Louis) was 1.93 per 1,000. In Allegheny County 

outside Pittsburgh, with county police included, the ratio 

is 1.40 per 1,000. Total local expenditures per capita for police services in 1982-$62-ranked the county 18th among 

the 21 American counties with resident populations exceeding one The county was also 18th out of 21 

in reported serious crime rates in 1983 (only Nassau and 

Suffolk Counties in New York and Middlesex County, 

New Jersey, reported lower numbers).” 

The number of full-time and part-time officers per 

1,000 inhabitants, and the per capita cost of police services 

for the median Allegheny County municipal police department in several size ranges are shown in Table 4.3. For 

those municipal departments outside Pittsburgh that employ 

full-time police, the median cost per capita is roughly $55. 

For municipal departments in St. Louis County, the comparable median cost was roughly $85 per capita. 

Police Service Expenditures 

and Population Served 

Some of the small municipalities in Allegheny County 

had the highest per capita expenditures for police services 

in 1985, while other small municipalities had the lowest 

(Figure 4.1). The variation in per capita expenditure decreases with increased population, but it is difficult to 

discern an overall pattern indicating economies or diseconomies related to the number of residents. The simple re- lationship between per capita expenditures and municipal 

population (shown as a solid line in Figure 4.1) is virtually 

flat.23 Figure 4.2 shows average police expenditures in small 

U.S. Advisory Commission on Intergovernmental Relations 41 
Figure 4.1 

Per Capita Police Service Expenditures in Suburban Municipalities, 1985 

30 0 

2 250 

$ 

8 150 

& 

200 

.s 

vr 400 m 

2 

50 

0 

0 10 20 30 40 50 60 

1985 Population Estimate (thousands) 

See note 18. 

Table 4.4 

Per Capita Expenditure Elasticities 

and Partial Coefficients for Police Services 

in Suburban Municipalities’, 1985 

Log-Linear 

Elasticities 

Resident Population (1,000s) 

Per Capita Income (1,000s) 

Tax Price 

Per Capita Intergovernmental Aid 

Employment to Population Ratio 

Density (1,000s per square mile) 

Percent of Housing Built 

Percent of Families with Incomes 

Percent Change in Population 

Intercept 

R2 (adjusted) 

before 1940 

below Poverty Level 

1980-1985 

-0.052 

(1.692) 

1.182. 

-0.444, 

(3.32) 

-0.015 

(8.3) 

(0.21) 

(4.37) 

0.170* 

0.097+ 

(2.68) 

0.002 

0.018+ 

(2.36) 

0.003 

(0.78) 

(1.78) 

0.57 

(1.21) 

-3.411 

120 suburban municipalities. 

(t statistic for parameter estimates). 

Significant at p < .001. 

+ Significant at p < .05. 

Linear 

Partials 

-0.050 

(0.51) 

2.794: 

(5.77) 

-0.009 

(1.66) 

0.134 

(1.76) 

26.4: 

(4.14) 

1.875 + 

(2.54) 

0.081 

(0.81) 

0.095 

0.299 

9.616 

(0.87) 

0.48 

(0.24) 

(1.50) 

jurisdictions to be higher than in somewhat larger ones. 

The jurisdictions with fewer than 2,000 residents in 1985 

had police expenditures per capita and per $1,000 of local 

personal income that were, on average, substantially higher than those of larger jurisdictions. However, the data for 

places below 2,000 population are highly skewed by the 

presence of two small communities-Neville Township 

and Sewickley Heights-that have very high per capitapolice expenditures (see Figure 4.1). Above 2,000 residents, 

the data suggest limited size economies-average per capita expenditures and average expenditures per $1,000 of 

personal income generally decline with increasing municipal size, but these effects are small. Further, these data do 

not take account of differences in revenue base, tax price, 

or service conditions among suburban police jurisdictions, 

nor do they account for differences in service quality. 

Econometric analyses of per capita expenditures and 

population, adjusting for differences in revenue base, tax 

price,24 and service conditions, demonstrate little support 

for significant returns to population size among suburban 

police departments (data used in these analyses and data 

sources are listed in the Appendix). The model used for 

these analyses-developed in greater detail in Chapter 

6-posits per capita expenditures to be positive functions of 

resident income and intergovernmental aid, and to be negatively related to tax price. Per capita expenditures also are 

expected to be higher in municipalities with large employment to population ratios, higher population density, older 

housing stock, and a larger poverty population. ?able 4.4 

presents coefficients from regression analyses of the model, 

including both elasticities from a log-linear estimate and partial effects from a linear specifi~ation.~~ 

The most consistent predictors of per capita municipal police expenditures are resident per capita income, tax 

price, and the ratio of employment to population. Municipalities with higher income residents spend more for police services than those whose residents have lower 

incomes. So, too, do municipalities with higher ratios of 

42 U.S. Advisory Commission on Intergovernmental Relations 
Figure 4.2 

Municipal Police Expenditures Per Capita and Per $1,000 Personal Income, 1985 

d 2 P%mn P2,m 

$ *s,= 

2 c10,m 610,mo 

*G" 10-a0,m, 10-a0,o.m0 

3 *soarm E 

% 9,- $ PI¶rav(E prtuarpl 

tx 0 el0 W c30 $40 SSD 80 *XI a 00 $100 0 (1 $2 U 14 )8 $7 CB S8 $10 

Per Capita Per $1,000 Income 

See note 18. 

employment to resident population, a measure of both 

revenue raising potential and increased per resident ex- penditure required to produce police services for a large 

daytime population. Municipalities with higher tax prices 

spend less per capita on police services. Per capita police 

expenditures are higher in more densely populated communities, and those with a higher proportion of families 

with incomes below the poverty level. Each of these factors has been identified with higher levels of demand, and 

the sign of their coefficients is as expected. The coefficients for population change are consistent with a hypothesis that expenditure change tends to lag behind 

population change, although these coefficients lack statistical significance. 

Significant negative coefficients for residential population in the estimates would indicate lower per capita 

costs in larger jurisdictions. The estimates reported in 

'kble 4.4 do not provide evidence of significant size economies, however.26 The coefficients for resident population-while negative-are small in magnitude. The 

partial effect is a reduction of 5 cents per capita for each 

1,000 resident increase. It is not significantly different 

from zero by statistical test. 

cers, only 5 produce their own dispatch services, and one 

of these does so in conjunction with another department 

Wble 4.5). The remaining 24 very small departments con- tract for dispatch services, often from a center that serves 

many smaller departments. Xvo of the larger joint dispatch centers are organized by Shaler Township, which 

dispatches for nine police departments and a large number of fire and rescue companies, and by the Twin Rivers 

Council of Governments, which dispatches 14 police departments, 22 fire companies, and ll ambulance/rescue 

companies. There are other joint centers serving smaller 

numbers of departments. A similar trend is found arnong 

larger departments. Departments with 4 to 24 full-time 

officers also tend to be dispatched by contractual or combined dispatch centers, or to dispatch for other departments in addition to their own. Only the largest 

departments are likely to operate their own independent 

dispatch centers. 

Cooperative and contractual dispatch arrangements 

have become increasingly common in recent years. During 

the 1970s, funds from the federal Law Enforcement Assistance Administration (LEAA) were available to departService Components 

If per capita police expenditures declined with population, the configuration of many small jurisdictions in Allegheny County could be charged with inefficiency in that 

service. The data do not reveal significant returns to population size, however. Police expenditures are relatively low 

and, after adjustment for variation in revenue base, tax 

price, and service conditions, are unrelated to jurisdiction 

population. Because some components-radio communications, training, sophisticated investigation, and crime 

lab, for example-require technologies with obvious scale 

economies in production, these results require further explanation. Small jurisdictions should incur relatively high 

costs if they produce these services for themselves. 

Perhaps the best explanation of why there were no significant.relationships of jurisdiction size and per capita expenditures is that, for the most part, components of police 

services where scale economies would be expected are not 

produced by most of the smaller departments. Of the 29 

municipal departments with fewer than four full-time offiTable 4.5 

Pol ice Dispatch Arrange men ts 

for Allegheny County Police Departments 

Receive 

Dispatch Dispatch Dispatch 

Own Own via Contract 

Municipal Department and Other or Combined 

Departments Only Departments Center 

Part-time only 1 0 8 

1 to 3 full-time 3 1 16 

4 to 10 ful1,time 11 9 30 

11 to 24 full-time 6 10 10 

25 to 55 full-time 6 4 1 

Pittsburgh 1 - - 

I Totals 28 24 65 

Sources: 1987 police strength from Pennsylvania State Police 

Dispatch arrangements from Marshall Bond, Intergovernmental Cooperation Program 

US. Advisory Commission on Intergovernmental Relations 43 
ments that wished to upgrade their communications 

equipment. LEAA funding was often contingent on the 

creation of joint dispatch centers. A 1982 sample of police 

departments in the county reported 41 percent of the departments involved in a cooperative dispatch arrangements. Currently, 56 percent of the departments-65 out 

of 117-either receive dispatch service from another department or joint center or provide this service to one or 

more neighboring departments.*’ This increase cannot be 

explained by federal funding incentives (LEAA was no 

longer in existence). Instead, the examples of the earlier 

centers apparently encouraged additional departments to 

create centers or join existing ones. 

Training, which exhibits obvious economy of scale in 

production, is organized by county government (with reimbursement from the state) for municipal departments outside Pittsburgh. Pittsburgh operates its own 

training academy. Crime lab services also are organized 

by county government. The availability of investigative 

services from the county police allows smaller departments to put more of their personnel resources into patrol and immediate response?* 

Complex police service systems, such as Allegheny 

County’s, that combine many small departments producing patrol and immediate response with overlapping arrangements for services exhibiting economies of scale in 

production have been shown to be technically efficient ina 

comparative study of policing in U.S. metropolitan areas.29 This does not mean that all police departments in 

the county are efficient, or that efforts to improve police 

service delivery through linkages are unwarranted. What 

we can say is that the system does not appear to suffer 

from inefficiency related to the size of jurisdictions. 

This finding may provide an additional explanation 

for the choice of arrangements in Allegheny County. In 

the face of political and administrative obstacles to the 

creation of joint police departments, the absence of obvious, significant economic payoffs from increased jurisdiction size helps to account for the lack of public 

entrepreneurship in promoting mergers of police departments or seeking interlocal contracting. Without economic pressure to change production arrangements, political 

and administrative factors can be expected to dominate. 

Cooperative Production Arrangements 

As in most metropolitan areas, police departments in 

Allegheny County supply mutual patrol back-up, generally on an informal, as-requested basis.30 This is facilitated 

for many municipal departments by shared dispatch arrangements. Allegheny County government is a major 

partner in local police cooperation, regularly supplying 

personnel to augment municipal patrol officers during 

special events and in emergencies. The county, as noted 

above, supplies training and crime lab facilities. 

Other cooperative investigative teams also operate in 

the county. The South Hills Investigative Task Force links 

the nine communities of Baldwin Township, Bethel Park, 

Carnegie, Dormont, Greentree, Mt. Lebanon, Scott 

Township, South Park Township, and Whitehall. The task 

force has been in operation since 1985 and focuses on narcotics-related investigation^,^^ using officers from its 

member departments. The second Cooperative Police Investigation Team has been organized by Elizabeth Borough, Elizabeth Township, Glassport, and McKeesport, 

with a similar focus on undercover narcotics investigations. In 1982, nearly 60 percent of police chiefs surveyed 

in the county reported that thcir dcpartments were involved in cooperative investigative 

Cooperative investigative teams are not always easily 

established. Special factors cited for South Hills included 

municipal managers in each community with control over 

their police departments, which was important in overcoming any political difficulties. In the McKeesport area, 

police chiefs have met regularly for a number of years under sponsorship of the Twin Rivers COG, and their departments share a common dispatch center. In contrast 

with these successes, municipal departments in the area 

surrounding Wilkinsburg have not been able to agree on 

formation of a cooperative team. Wilkinsburg is surrounded on two sides by large municipalitics-Pittsburgh 

and Penn Hills-that have sufficient resources to conduct 

independent investigations, and on the remaining sides by 

wealthier communities that do not perceive sufficient 

crime problems to warrant joining in cooperative efforts. 

An emerging area of coopcration is receipt of citizens’ 

calls for police, ambulance, and emergency medical service. 

At present, Allegheny County does not have an areawide 

911 emergency system. Callers must know the jurisdictional 

location to select the correct telephone number. 

A task force organized by the Intergovernmental 

Cooperation Program has presented a report addressing 

the need for a countywide 911 system. This report was prepared by a local advisory board in conjunction with a national consulting firm. The proposed system would 

remove the need to know one’s jurisdictional location 

when requesting emergency service. A call to 911 from any 

part of the county would connect a person to a dispatcher 

in the correct jurisdiction. Municipal police departments 

would retain dispatch responsibilities if they chose to do 

so, but would have access to video screen displays of telephone number and location information through a primary integrated Public Safety Answering Point (PSAP).33 

This system, if implemented, also holds the possibility of 

developing a countywide information network. 

Other aspects of police service for which significant 

cooperation is reported include apprehension, detainment, disaster planning, special squads, educational services, traffic control, crime reporting, and juvcnile 

services.34 This cooperation helps maintain the viability of 

the numerous small police dcpartmcnts. 

Police Services -A Summary 

Outside Pittsburgh, arrangements for the production 

of police services form a complex pattcrn that can be ex- plained as a configuration of variables. The elements of 

this pattern seem to fit together in a comprehensible way. 

One element is relatively low expcnditures for police ser- vices, with variations related to community fiscal capacity 

and service conditions. This element is consistent with a 

reliance on police departments that are quite small with a 

44 U.S. Advisory Commission on Intergovernmental Relations 
Figure 4.3 

Per Capita Street Service Expenditures in Suburban Municipalities, 1985 

120 2 3 1oo.g 

XIC 

t@ cd 80 

.el 

u 60 

% 

$: 

2 

!d 

In m 40 

20 

0 

0 10 20 30 40 50 60 

1985 Population Estimate (thousands) 

See note 39. 

relatively high percentage of part-time officers. The absence of police contracting and full functional consolidation can be explained by a relatively low demand for police 

services compared to many other metropolitan areas-reported crime rates in the county are low for large counties-coupled with the absence of economies of scale in 

police patrol beyond the very smallest departments. 

Cooperative relationships for auxiliary services are common, facilitated by the availability of the county government to produce those service components that exhibit 

significant economies from large scale. 

STREET SERVICES 

Responsibility for the provision of highways, streets, 

and roads in Allegheny County is divided among the Commonwealth of Pennsylvania (1,873 miles), Allegheny 

County government (370 miles), and all municipalities 

(3,707 miles).35 Production responsibility for the maintenance of state highways is vested in the Pennsylvania Department of Transportation (PennDOT), District ll, 

which includes Beaver and Lawrence counties in addition 

to Allegheny. County production responsibilities are divided between the county departments of Engineering 

and Construction and Maintenan~e.~~ Municipal production is carried on mainly by municipal street departments 

or public works department^.^' 

County and Municipal Street Production 

County highway provision responsibilities have di- minished over the years due to state preemption, leaving a 

fragmented pattern of roads rather than a coherent system. In effect, the county government is the residual road 

provider. The county also owns and maintains some 275 

bridges (spans greater than 8 feet in length), including 

most of the large spans in Pittsburgh’s downtown triangle. 

The Department of Maintenance, with an annual budget 

of about $24 million, is responsible for maintaining roads 

and bridges, all county buildings and parks, and two county 

airports. Although the department contracts out for surface treatment, it maintains a large in-house production 

capability, including heavy equipment and technical personnel, greatly exceeding any other municipal operation 

outside Pittsburgh. The department is placing incr2ased 

emphasis on preventive maintenance, including crack 

sealing of road surfaces (100 miles completed in 1988). 

Street service expenditures in the county are roughly 

comparable to those in metropolitan counties of a similar 

size. In 1982, the county ranked 10th in per capita highway 

expenditures among the nation’s 21 counties with populations exceeding one million.38 Figure 4.3 depicts the range 

of per capita expenditures in 1985 for street services in Allegheny County municipalities outside Pittsburgh. The 

lowest per capita expenditure was $14 in Braddock. The 

highest was $134 in Thornburg. Small municipalities had 

both the highest and the lowest per capita expenditures 

for street services. The population-weighted average expenditure outside Pittsburgh was just under $50 per capita, while Pittsburgh spent $85 per 

Street Service Costs and Population Served 

Bivariate comparisons of jurisdiction size and street 

service costs per capita and per $1,000 personal income 

show a slight decline in costs with increasing population 

served (Figure 4.4).40 Multivariate analyses of this rela- tionship yield mixed and statistically insignificant results 

wble 4.6). The elasticity of per capita street expenditures 

in relation to population is positive, indicating higher per 

capita expenditures in larger jurisdictions. The partial co- efficient for resident population is negative, indicating 

lower per capita expenditures for them. In neither specification does resident population help explain much of the 

variation in per capita expenditures. Much more impor- tant factors are per capita income and intergovernmental 

aid, which are both positively related to spending, and tax 

price, which is negatively related. 

US. Advisory Commission on Intergovernmental Relations 45 
Figure 4.4 

Municipal Street Service Expenditures Per Capita and Per $1,000 Personal Income, 1985 

Cooperation in Street Services and Public Works 

Allegheny County, acting through its Department of 

Development and its associated Authority for Improvement 

in Municipalities (AIM), has actively stimulated cooperative 

street and public works ventures. One such project, which 

also involved the COGs, is the sewer maintenance and 

cleaning (SMAC) program. Using funds made available by 

AIM, the Department of Development purchased television 

equipment to allow inspection of sewer lines from the inside 

and “sewervactor” equipment to remove blockages. The 

Table 4.6 

Per Capita Expenditure Elasticities 

and Partial Coefficients for Street Services 

in Suburban Municipalities,’ 1985 

Log-Linear Linear 

Elasticities Partials 

Resident Population (1,000s) 0.053 

(1.492) 

Per Capita Income (1,OOOs) 0.801* 

(5.13) 

Tax Price -0.470* 

(3.12) 

Per Capita Intergovernmental Aid 0.262+ 

(3.11) 

Employment to Population Ratio 0.016 

(0.35) 

Density (1,oooS per square mile) -0.010 

(0.25) 

Percent of Housing Built 0.006 

before 1940 (2.76) 

Percent of Families with Incomes -0.006 

below Poverty Level (0.76) 

Percent Change in Population -0.005 

1980-1985 (0.93) 

(0.88) 

R2 (adjusted) 0.35 

Intercept. -1.725 

123 suburban municipalities. 

(t statistic for parameter estimates) 

* significant at p < .001. 

+ significant at p < .05. 

-0.198 

(1.88) 

1.667+ 

(3.18) 

-0.013+ 

(2.24) 

0.382* 

(4.60) 

19.7+ 

(2.94) 

-0.205 

(0.26) 

0.131 

(1.20) 

(1.28) 

-0.547 

-0.270 

(1.25) 

32.5+ 

(2.70) 

0.45 

equipment is available for rental by municipalities from the 

COGS for a fee that covers operating costs. 

Basic municipal street services are produced through 

in-house capabilities, supplemented by private contractors for special construction or reconstruction projects,41 

joint production of street sweeping through COGs, and 

other forms of mutual aid. The county Department of 

Maintenance supplies general back-up, mainly in the form 

of equipment sharing. Twenty percent of public works directors, surveyed by ACCD in 1982, reported cooperation 

in road repair a~tivities.~~ 

A somewhat different pattern is emerging among a 

group of distressed municipalities in the Mon Valley that 

are members of the Turtle Creek COG. Some of these 

communities own equipment but cannot afford to hire operators. In other places, the situation is reversed. With staff 

support from the COG, five small municipalities formed a 

joint public works team in 1987 that pools personnel, equipment, and materials to perform crack sealing on local streets. 

The county Department of Maintenance contniuted a 

pick-up truck, and the chief maintenance engineer, Paul Ostrowslu, trained the work crew. Rankin, one of the municipalities, had begun crack sealing its streets five years earlier, 

and was able to supply experience and leadership. 

With the help of small grants from the Intergovernmental Cooperation Program (ICP) and the Pennsylvania 

Department of Community Affairs (DCA), Turtle Creek 

COG was able to employ Ostrowski on a part-time basis. 

ICP and DCA are also funding a COG-wide street inventory and condition assessment to provide an information 

base for future joint activities. A street improvement project 

has been implemented in the tiny Borough of Wall, combining Community Development Block Grant funds with 

in-kind support from the Department of Maintenance. 

Allegheny Valley North COG is experimenting with 

another innovation, the RIDER program, developed by 

the Southwest Pennsylvania Regional Planning Commission to set priorities for repairs that will preserve roadways 

in good condition, while identifying lower quality roadways that need extensive rebuilding. The RIDER street 

rating instruments and computer programs are available 

through the COG office. 

Much of the cooperation between the county Department of Maintenance and the municipalities is on a proj46 U.S. Advisory Commission on Intergovernmental Relations 
Figure 4.5 

Per Capita Fire Expenditures in Suburban Municipalities, 1985 

1985 Population Estimate (thousands) 

See note 49. I 

cd 

.r( c1 3 30 

u - 

CI 

k 20 

u-l 

m 

4 

m 

0 

0 10 20 30 40 50 

X X 

X 

ect-by-project basis. Ostrowski described one such project 

in detail in The.Pennsyl~anian.4~ West Elizabeth Borough, a 

member of the Steel Valley COG, had a stormwaterdrainage problem caused by upstream activities and the nonenforcement of building and grading ordinances. Solving the 

problem required cooperation from PennDOT, Jefferson 

Borough (not a COG member), and Allegheny County. 

Both the Department of Maintenance and the Steel 

Valley COG helped arrange and supported the cooperative effort. In another recent example, the Department of 

Maintenance reconstructed an access road to a school in 

the North County, and Northgate School District agreed 

to assume responsibility for its maintenance. 

An interesting example of contracting in public works 

links numerous municipalities with PennDOT to remove 

snow and ice from state highways that pass through their 

jurisdictions. This arrangement would appear to save 

PennDot a substantial investment in extra work crews, 

while allowing the municipalities to recapture part of the 

cost of providing a needed service. Until recently, a similar 

arrangement operated between the county Department of 

Maintenance and 45 municipalities. Instead of cash, the 

department furnished municipalities with salt in exchange 

for removing snow and ice from county roads. The arrangement was suspended in 1988 because some municipalities were not meeting county standards. 

There is a perception among local leaders that cooperative ventures are more feasible for street services and infrastructure maintenance than for some other services. Street 

and sewer maintenance are viewed as “safe,” that is, less 

likely to stir citizen complaint than, for example, police. Yet, 

in a 1982 survey conducted by ACCD, roughly twice as many 

municipalities reported cooperation in police services as in 

public works services.44 This is consistent with findings in the 

St. Louis County study. The most plausible explanation for 

different levels of cooperation in street and police services 

lies in the different nature of service production. 

FIRE SERVICES 

Fire services in Allegheny County are organized for 

the most part by volunteer fire companies. There are ap- proximately 250 companies and approximately 20,000 volunteer fire, rescue, and EMS personnel45 serving about 

two-thirds of the county population. Many municipalities 

are served by more than one volunteer company (in one 

case, seven). Only the cities of Pittsburgh, McKeesport, 

and Wilkinsburg have full-time paid departments, al- though several cities have some paid fire 

The volunteer fire companies raise the bulk of their 

funds through public solicitations, carnivals and other 

public events, and social functions. Many municipalities 

purchase and maintain equipment, supply fire station facilities, provide the volunteers with fuel and other supplies, 

carry liability and other insurance, and provide cash subsidies. Some municipalities pay volunteer fire fighters an 

hourly wage when they are actively fighting fi~es,~’ and 

some employ full-time drivers. Still, local governments 

supply remarkably little funding for fire protection. In 

1982, the county ranked 19th in per capita expendituresfor 

fire protection among the 21 U.S. counties having one million or more residents.a 

Total 1985 fire protection expenditures by municipalities in the county were $39 an average expenditure of $27.60 per capita.5O Seventy-five percent of the 

total was spent by the Pittsburgh Fire Department. Outside Pittsburgh, the average fire expenditure per capita in 

1985 was just under $10. Only six communities, including 

Pittsburgh, reported fire expenditures of $25 per capita or 

more (Figure 4.5).’l 

These data understate the cost of fire protection because they do not include funds raised and expended by 

the volunteer companies. No data are available to estimate 

these funds, but it is reasonable to assume that adding them 

to the public total would yield a fire expenditure less than 

that of equivalent areas using fully paid fire departments. 

U.S. Advisory Commission on lnterclovernmental Relations 47 
By local accounts, Allegheny County is well protected 

by its volunteer and paid fire fighters. The absolute number of fire fighters exceeds by a very significant margin the 

number found in comparable areas that rely predominantly 

on paid fire department^.^^ 

Local informants reported that the amount and quality 

of equipment are also quite sub~tantial.~~ The Mon-Yough 

Fire Defense Council, one of eight fire associations outside Pittsburgh, maintains 81 first-line fire and rescue ve- hicles, which are operated by the council’s 69 member 

organizations. If the other fire associations (see “Cooperation in Fire Protection” below) are similarly equipped, the 

number of fire and rescue vehicles in Alle-gheny County is 

more than double that in St. Louis County. The 

Mon-Yough Council members alone have approximately 

half the number of vehicles found in all of St. Louis City and 

County.54 One could argue (and several persons did so argue) that the system of volunteer fire companies, with its 

competition to have the latest or the largest engines and other equipment, yields overinvestment in equipment. 

Local fire fighters are trained by the county Fire 

Training Academy, which reports that both paid and volunteer companies maintain high standards. No data were 

available on fire insurance @SO) rates in the county, and no 

comparisons with other similarly sized areas could be made. 

Cooperation in Fire Protection 

The fire companies (and many rescue and emergency 

medical services) outside Pittsburgh are organized into 

eight fire associations or fire defense councils, some of 

which include companies in adjacent counties. Mutual aid 

arrangements are common. In a 1982 survey of fire chiefs, 

93 percent reported cooperation in fire fighting,55 including first-response arrangements. The association members and a number of companies maintained by large 

corporations engage in joint training exercise^.^^ 

Fire, ambulance, and emergency rescue dispatch for 

many companies is supplied through centers within the 

fire associations. In several instances (e.g., in the Lower 

Allegheny Association and the Mon-Yough Fire Defense 

Council), they use the same dispatch centers as for police. 

Mon-Yough Regional Fire Dispatch serves 64 companies, 

the Shaler Township Communications Center serves 29 

companies, and the South and West Fire Dispatch Centers serve 54 companies using four base station^.^' 

The fire associations also publish equipment lists that 

make it easier to share with neighboring companie~.~’ Allegheny County, working with the associations, has organized hazardous materials response units in five regions. 

SUMMARY 

There are interesting differences in the patterns of 

delivery of police, street, and fire services in Allegheny 

County compared to other major metropolitan areas. The 

most obvious difference is the large number of production 

units- 117 municipal police departments and county police, approximately 250 fire departments, and 130 street 

and public works departments. 

Police service expenditures and the number of personnel are significantly lower than in similarly sized areas, 

as are reported crime rates. Public fire protection costs are 

also much lower, although including funds raised and expended by the volunteer fire companies would, if they 

could be calculated, reduce the difference. The number of 

fire fighters is much higher than commonly found elsewhere. Street service expenditures are roughly comparable with those in other metropolitan counties. 

There is no statistical evidence that the large number 

of police and street service producers contributes to excessive costs, or that the costs might be lowered by jurisdictional consolidations of small municipalities. The system 

of many small volunteer fire companies may result in overinvestment in equipment, but data were unavailable to assess production costs for this service. 

There is relatively little intergovernmental contracting 

for service components delivered directly to citizens-basic 

police patrol, for example. Intergovernmental contracting is 

found for some auxiliary service components, especially dispatch. Municipal cooperation is common for a number of 

components of police services, and is growing for street services, facilitated by the Councils of Governments and the 

county government. Cooperation is the rule among volunteer fire companies. Allegheny County government is a significant partner in interlocal cooperation, as is the Greater 

Pittsburgh Chamber of Commerce’s Intergovernmental 

Cooperation Program. The county government produces a 

variety of services that enhance the viability of the smaller 

production units of individual municipalities. 

One should not conclude, however, that service production arrangements in Allegheny County are perfect, or 

that improvements are not possible. Although there is no 

need for systematic, across-the board consolidation of service, further differentiation that includes consolidation of 

production for some service components may be appropriate. Efficient arrangements vary, depending on municipal 

circumstances. The county structure allows for experimentation with alternative service arrangements, such as 

the joint public works team in the Turtle Creek COG. 

These efforts can identify potential improvements in efficiency and effectiveness of service production while minimizing the potential for unintended inefficiencies 

associated with large-scale reform projects. 

Pennsylvania’s strong tradition of local autonomy has 

not prevented interlocal cooperation in producing service 

components, allowing the capture of economies of scale 

and enhancing coordination. Respect for jurisdictional autonomy can make negotiation of these agreements a pnckl; 

task, and the structure of local governments in Pennsylvank 

makes it a task frequently subject to delay or veto. Still, the 

prevalence of such agreements in the county belies the characterization of “Balkanization” often made of jurisdictionally fragmented areas. The prospects for additional 

interlocal functional cooperation and coordination in the 

county appear favorable, especially as the councils of governments experiment with new responsibilities, and the 

supportive efforts of county government and thehtergov. 

ernmental Cooperation Program bear further fruit. 

Notes 

These services and education were selected for study becaust 

(1) they are services most commonly provided by local govern 

48 U.S. Advisory Commission on Intergovernmental Relations 
ments in the United States, (2) in most local governments, they 

account for the majority of local spending and employment, 

and (3) to permit consistency and comparison with Metmpolitan Otganization: The St. Louis Case (Washington, DC: U.S. 

Advisory Commission on Intergovernmental Relations, 1988). 

* Allegheny Conference on Community Development and 

Consortium for Public Administration Field Services, To 

Cooperate or Not to Cooperate: A Repod on Intergovernmental 

Cooperation in Allegheny County mttsburgh, 1982), Exhibit J3-4. 

Ibid., Exhibits B-3 and B-2. 

This count does not include McDonald or Trafford Boroughs, 

only portions of which lie wjthin Allegheny County. To be included in this count, a municipality had to have employed at least 

four full-time officers. Those with fewer than four full-time officers were included in the mixcd full-time and part-time category 

regardless of whether they employed part-time officers. 

Clairton disbanded its paid police department in 1985 when it 

was declared a “distressed community” under Pennsylvania’s 

Act 47. Braddock is now (1988) receiving Pennsylvania State 

Police service also, while retaining one full-time and several 

part-time officers in its own department. 

Production of police services by the Pennsylvania State Police, 

the Pittsburgh Housing Authority, the Port Authority, and col- lege campus police forces are not discussed in this report. 

’ Elinor Ostrom, Roger B. Parks, and Gordon P. Whitaker, Patterns of Meiropolitan Policing (Cambridge, Massachusetts: Ballinger Publishing Company, 1978), p. 77. 

* ACIRs study of St. Louis County, Missouri, found 62full-time 

municipal police departments serving 89 independent munici- palities, with many small municipalities contracting for basic 

police service from the countypolice or an adjacent municipal- ity. In this respect, St. Louis County is atypical of most metro- politan counties. The extensive contracting for police services 

in St. Louis is the result of a Missouri statute requiring all mu- nicipalities in the county with 400 or more residents to provide 

full-time police service. Because many municipalities are too 

small to support a force of four or more full-time officers (the 

number necessary to provide around-the-clock coverage), con- tracting is chosen as a means to comply with the statute. Metmpolitan Olganization, Chapter 4. 

Carl E Valente and Lydia D. Manchester, Rethinking Local 

Services: Examining Alternative Delivety Appmaclies. Management Information Service Special Report No. 12 (Washington, 

DC: International City Management Association, 1984). 

lo The mayor may attend council meetings and participate in discussions, but has no vote on matters before the council. See 

Christine Altenburger, Kevin Kearns, and B. Guy Peters, 

“Strengthening Pennsylvania Local Governments: Implications 

for the Mon Valley,” a paper presented at the University of Pittsburgh President’s Conference on the Mill Towns, May 54,1988. 

*’ A 1986 survey of elected officials, administrators, police chiefs, 

and police officers in the South Hills provides some support 

for these explanations. Borough mayors and township commissioners consistently preferred the “status quo”-independent departments-to several merger options and to 

contracting. Police chiefs were more willing to entertain limited mergers or contracting, however, and police Officers generally favored limited mergers while opposing contracting for 

police service. See Robert Flaherty, “What is the Most CostEffective Way of Providing Police Protection to the Citizens of 

Baldwin Township, Castle Shannon, Dormont, and Mt. Lebanon?” University of Pittsburgh, Graduate School of Public and 

International Affairs, January 13, 1986. 

l2 A Strategy for Cooperation: Ears 2 and 3 (Pittsburgh: Intergovernmental Cooperation Program, April 1985), p. 17. 

l3 The question of pension plan funding was cited as a hindrance 

to functional consolidations in all areas of municipal service. 

Communities with fully funded systems are reluctant to combine functional departments with neighbors whose pensions 

are partially funded because this could require partial assump- tion of the unfunded liability. The state is forbidden constitutionally to assume any local government debts and is unable to 

assist functional combinations by removing this obstacle. 

l4 PASS stands for Police Anti-Sniper Squad. Sce Sandra E 

Donovan, “Special Police Unit Won’t ‘PASS’ Out on Hostage 

Attempts,” The TirneslBeaver Newspapers, August 28, 1988. 

This contrasts sharply with Missouri law bearing on St. Louis 

County, where all municipalities with 400 or more residents 

are required to provide full-time police protection. This provision accounts for much of the interjurisdictional contracting 

for police services in St. Louis. Twenty-nine of Allegheny 

County’s police departments would be forced to increase their 

full-time employment or consider contracts for basic police 

services if Pennsylvania had a similar law. See ACIR, Metropolitan Organizaiion, p. 56. 

l6 This skewed pattern, with most police departments relatively 

small, while most police officers work in larger departments 

and most citizens reside in the jurisdictions of larger depart- ments, is common in American metropolitan areas. See Ostrom, Parks, and Whitaker. 

l7 This reliance on part-time police has been challenged in Pcnnsylvania. A decision in Monroe County found that state law 

“gives no arrest authority to ‘regular part-time’ or ‘casual parttime’ police officers.” A similar case, involving an arrest for 

drunken driving made by a part-time officer employed by 

North Braddock, was being litigated in Allegheny County at 

the time of our research. If the Monroe County precedent 

were tobe accepted, substantial pressure for joint and contrac- tual police services might be placed on small municipalities in 

Allegheny County. 

l8 Comparisons of total police expenditures and expenditures 

per capita among municipalities in Allegheny County must be 

approached with caution. Most of the expenditure data in this 

report were obtained from the Municipal Statistics and Records 

Division, Bureau of Lucal Government Services, Department 

of Community Affairs (DCA), Commonwealth of Pennsylvania. 

They are preliminary tabulations of data reported by municipalities. A recent study by the Pennsylvania Economy League, 

Western Division, found inconsistencies in the ways that municipalities categorized expenditures, leading the league to believe that police expenditures are underreported, perhaps by a 

significant amount (personal communication from Boyd Messenger, Manager, Public Safety Programs, Pennsylvania Economy League, July 5, 1989). Further, the data obtained from 

DCA for municipalities with populations in excess of 25,000 

differ to some extent from data reported for these same municipalities by the U.S. Bureau of the Census in the 1985 Government Finance series. Thus, the comparisons reported here 

should be read as suggestive of general patterns, with specific 

intermunicipal comparisons unwarranted. 

l9 ACIR, Meimpolitari Organization, pp. 57-58. 

2o St. Louis City’s high ratio of officers to citizens reflects in part 

the way the police have been governed historically. In St. 

Louis, a board of police commissioners, appointed by the governor, determined police staffing levels and submitted a mandatorybudget to the city. While this arrangement has changed 

somewhat as a result of Missouri’s Hancock tax limitation 

amendment, the city’s ratio of officers to citizens continues to 

be among the highest of large American cities. 

21 US. Department of Commerce, Bureau of the Census, Slate 

and Metmpoliian Area Data Book, 1986 (Washington, DC, 

1987). The caution in note 18 above may apply here as well, 

although the Census Bureau uses different methods for its exUS. Advisory Commission on Intergovernmental Relations 49 
penditure estimates than the reports used by the Department 

of Community Affairs. 

22 Census, State and Metrvpolitan Area Data Book, 1986. 

23 Regressing per capita expenditures on population size yields 

an intercept of approximately $59 and a slope of negative 5 

cents per 1,000 population. 

24 Tax price is computed as the ratio of the median value of an 

owner-occupied home in a given community to that communi- ty’s market value of all real property. It is the “price” for community services that the median homeowner would pay if all 

services were financed by property taxes. 

25 The regressions are based on data from 120 suburban munici- palities. Eliminated prior to the analyses were two municipali- ties only partially located in the county, three with 

extraordinarily high per capita incomes, one industrial enclave, and three municipalities reporting negligible expendi- tures for police services in 1985. The inconsistencies in 

reporting police expenditures cited in note 18 are of less con- cern for these econometric analyses. Unless underreporting is 

correlated significantlywith size of population served. it simply 

serves to increase error variance in the coefficient estimates. 26 These models do not account directly for variations in the 

quality or quantity of police services, although population 

served is a rough proxy indicator for service quantity. No ac- ceptable indicators of service quality are available. 

27 1982 data from Allegheny Conference, To Cooperate or Not to 

Coopemte, Exhibit B-3. Current data from Marshall Bond, Intergovernmental Cooperation Program. 

28 See Ostrom, Parks, and Whitaker, especially Tables 5-9 and 

5-10, pp. 89-90. This study of policing practice by departments 

in 80 metropolitan areas shows that smaller departments 

deploy substantially higher proportions of their sworn personnel for on-street duties than do larger departments. 

29 See Roger B. Parks, “Metropolitan Structure and Systemic 

Performance: The Case of Police Service Delivery,” in Kenneth Hanf and The0 A. J. Toonen, eds., Policy Implementation 

in Federal and Unitary States (Dordrecht, The Netherlands: 

Martinus Nijhoff Publishers, 1985), pp. 161-191. 

30 The 1982 survey of police chiefs in the county reported that 

“the majority of cooperative arrangements in police services 

are mutual aid agreements with other municipalities.” Allegheny 

Conference, Exhibit B-3. 

31 See Charles J. Lee, Jr., Cooperative Investigative Team @ormont, Pennsylvania: South Hills Investigative Task Force, 

Progress Report, January 1988). 

32 Allegheny Conference, To Cooperate or Not to Cooperate, Ex- hibit B-3. 

33 The county’s topography is such that a numberof such PSAPs 

would be required to reach all department’s patrol units. 

34 Allegheny Conference, To Cooperate or Not to Coopemte, Ex- hibit B-3. “Significant cooperation” as used here means that at 

least 25 percent of the chiefs surveyed in 1982 reported that 

their department cooperated with at least one other depart- ment in the service component named. 

35 Allegheny County Department of Maintenance. Number of 

miles rounded to the nearest mile. 

36 These two departments were created in 1978 by dividing the 

Department of Public Works. 

37 Indeed, the principal function served by the original municipalities in the county-townships, the precursor to today’s second class townships-was the building and maintenance of 

roads. Township organization still reflects that earlier emphasis, and boroughs and cities continue the model of production 

by a local government bureau. 

38 Census, State and Metropolitan Area Data Book, 1986. 

39 These data, like those for policing, were provided by the Pennsylvania Department of Community Affairs (see Note 18). It 

was not possible to determine whether they exhibit inconsistencies in reporting, but the possibility suggests a need for cautious interpretation of municipal comparisons. 

40 A population-weighted regression of per capita street service 

expenditures on municipal population indicates an intercept 

of approximately $49 and a negative slope of 20 cents per 1,000 

residents. This regression line is shown on Figure 4.3. 

41 The Borough of Churchill departs from this pattern, relying on 

a long-standing contractual relationship with aprivate firm for 

the production of public works maintenance. 

42 Allegheny Conference. 

43 Paul Ostromki, “Intergovernmental Cooperation Spells C-OG,” Pennsylvanian, May 1988, pp. 4-5, 12. 

44 Compare Allegheny Conference, To Cooperate orNot to Coop- erate, Exhibits B-2 and B-3. 

45 These numbers are approximate because there is no authoritative central registry of volunteer fire companies. The estimate 

was provided by Merrill Parker, director of the county’s Fire 

Training Academy. The numbers include volunteer compan- ies and personnel that supply rescue and EMS services in addi- tion to or instead of fire prevention and suppression. 

46 Wilkinsburg recently has been declared a distressed city under 

provisions of Pennsylvania’s Act 47. The Pennsylvania Economy 

League was appointed by the state Department of Community 

Affairs to develop a recovery plan for Wilkinsburg. The recovery plan, adopted by the borough, recommended that the paid 

fire department be maintained for the immediate future, within certain budget constraints, and provided for a communitybased task force to recommend possible service delivery 

efficiencies. That task force has recommended continuation of 

a paid fire department, togcther with exploration of alternatives over time (personal communication, Boyd Messenger, 

Pennsylvania Economy League, July 5,1989). Citizens of Wilkinsburg voiced substantial support for their paid fire fighters 

at the meeting where the recovery plan was first presented. 

Communities with a combination of paid and volunteer fire 

fighters include Mt. Lebanon, Bellevue, and Camegie. 

47Thi~ practice may be discontinued as a consequence of the 

1985 Amendment to the FairLaDorStarzdardsAct as it bears on 

municipal employees, many of whom are also volunteer fire 

fighters. If a municipality pays one of its employees while acting as a volunteer fire fighter, the hours paid are counted as a 

part of the employee’s work week and, thus, may require the 

payment of overtime or the granting ofcompensatory time off. 

48 Census, State arid Metropolitan Am Data Book, 1986. 

49 Data from preliminary tabulations of local government financial statistics supplied by the Municipal Statistics and Records 

Division, Bureau of Local Government Services, Pennsylvania 

Department of Community Affairs. As with police and street 

expenditures, these data should not be used for specific inter- municipal comparisons (see Note 18). 

50 The comparable publicexpenditure for fire protection services 

in St. Louis City and County in 1985 was $75 million, for a per 

capita average of $52.85, nearly double that of Allegheny 

County. See ACIR, Metropolitan Otgaiiization. 

51 The upward sloping regression line shown in Figure 4.5 most 

likely does not indicate diseconomies ofscale. Rather, it is likely that larger municipalities make relatively larger contributions to their volunteer fire companies and/or employ more 

fire fighters in-house. 

52 Compare Allegheny County’s 20,000 volunteer fire fighters tc 

the 1,859 full-time fire fighters in St. Louis City and County, ar 

50 U.S. Advisory Commission on Intergovernmental Relations 
area with virtually the same population. Many fire protection 

districts in St. Louis County utilize some volunteer fire fighters, but the number falls well below the number in Allegheny 

County. In part, this difference is attributable to the requirements of volunteer fire companies. Since it is difficult to prepare schedules to ensure that a given number of volunteer fire 

fighters will be available whenever a fire should occur, companies must include many more fire fighters than would a paid 

department, which could make such schedules. The St. Louis 

data are from ACIR, Metropalitan Organization. 

"Severalpersons we inferviewed stated that the amount of fire 

equipment in Allegheny County exceeded that in the entire 

state of Maryland. While the factual basis of this statement 

could not be ascertained, the evidence points to a very large 

equipment complement in the county. 

54 1988 Fiw, Ainbulance, and Rescue Companies Roster Book 

(McKeesport, Pennsylvania: Mon-Yough Fire Defense Coun- cil, 1988). For St. Louis, see ACIR, Metropolitan Organization, 

pp. 78-79. If the Mon-Yough Council's equipment roster is typ- ical of other county fire associations, there are approximately 

300 first-line fire and rescue vehicles in Allegheny Countyoutside the City of Pittsburgh. The number identified in St. Louis 

County was 130. 

s5 Allegheny Conference, To Cooperate or Not to Cooperate, Ex- hibit B-4. 

56 In 1982,74percent ofthe fire chiefssurveyed reported mperation in training activities. Ibid. 

57 Data from PennJyJvania Scanner Guide supplied by Marshall 

Bond, Intergovernmental Cooperation Program. 

58 For example, the Mon-Yough Fire Defense Council RosterBook. 

U.S. Advisory Commission on Intergovernmental Relations 51 
52 U.S. Advisory Commission on Intergovernmental Relations 
ChaDter 5 

Public Education 

INTRODUCTION on the eastern and western edge of Pittsburgh, respectively. 

School districts in Pennsylvania, like municipalities, 

are classified into five population groups. Philadelphia 

and Pittsburgh are each classified separately. Second class 

districts must have populations between 30,000 and 

500.000, and third class districts between 5,000 and 30,000. 

Districts with populations under 5,000 are fourth class. 

Three questions are often asked about the organiza- areas: 

rn Are small, separately organized school districts 

able to draw on expertise and specialized services 

that can be produced only on a larger scale? 

t

i

on of public education in fragmented 

Are small school districts associated with rela- tively poor school performance? 

Does fragmentation cause serious fiscal dispari- ties in the provision of education? 

Relatively little is known about how the institutional characteristics of a metropolitan school system translate into 

school performance. After introducing school district organization in Allegheny County, this analysis focused on 

four relationships among districts: (1) organizational linkages, (2) specialized production arrangements, (3) performance patterns, and (4) fiscal patterns. 

SCHOOL DISTRICT ORGANIZATION 

The 43 school districts in Allegheny County differ in 

many important respects, beginning with size. The Pittsburgh district, with more than 40,000 students, is the largest. The other 42 districts range in average daily 

membership (ADM) from 913 in Cornell to 7,925 in Penn 

Hills. Eleven districts have an ADM of fewer than 2,000, 

and 24 districts have fewer than 3,000. 

For the most part, the 42 suburban districts serve predominantly white, middle-income communities. Thxty-five 

districts are 90 percent or more white; none has a majority 

nonwhite population. Only the Upper St. Clair District 

has a median household income over $30,000 per year. 

Five districts have median household incomes of less than 

$15,000, and 20 districts range between $18,000 and 

$22,000 per year. To some extent, these figures fail to reflect the substantial diversity among communities resulting in part from different ethnic and racial concentrations. 

Some districts have substantial poverty rates, seven of 

them at more than 10 percent. The districts also vary in the 

proportion of the population with a high school education. 

rn 

School districts are governed by nine-member boards of 

school directors elected to four-year overlapping terms. 

Although separately governed, the initial establish- ment of school districts in Pennsylvania largely followed 

municipal incorporation. The state policy was that each 

municipality would have its own school district, with two 

exceptions: (1) the creation of new fourth class districts 

had to be approved by state officials and (2) for many years, 

voters in contiguous areas could petition the court of com- mon pleas to create an “independent” school district (independent of municipal organization). Under current law, 

state approval is required for creation of third class districts 

as well, and independent districts may be created only for the 

purpose of merging with an adjoining district.2 Annexation 

automatically changes school district bo~ndaries.~ 

Before 1961, school district consolidations could take 

place only at the initiative of school directors or district 

voters, and required concurrent approval in the districts. 

“Union” districts were created in this manner. In the 

196Os, however, the state legislature created a special procedure to consolidate school districts, requiring a review 

of all districts with pupil populations under 4,000 and consolidation of all districts with pupil populations under 

2,500. (These are pupil populations measured by average 

daily membership, not total populations used to classify 

school districts.) The procedure, which is no longer in effect, was for county boards of education to prepare consol- idation plans, which were then approved by the state 

Council of Basic Education. School districts that were 

consolidated in this manner are, in a literal sense, “creatures of the state.” The state law was later modified to al- low consolidation by joint agreement between school 

boards, eliminating the requirement for voter appr~val.~ 

ORGANIZATIONAL LINKAGES - - 

Poverty and edu&tibnal background are useful as indica- tors of the schools’ service conditions. Pittsburgh, with a 

poverty rate of more than 16 percent, is one of five districts 

in the county with relatively difficult service conditions. 

The others are Clairton and Duquesne, both located in 

the Mon Valley, plus Wilkinsburg Borough and Sto-Rox, 

The existence of a large number of autonomous local 

school districts does not mean that each district must “go it 

alone” in arranging for the full complement of elementary 

and secondary education services. The 43 districts in Al- legheny Countyare supplemented by (1)joint service agreements, known as jointures; (2) intermediate units, one for 

U.S. Advisory Commission on Intergovernmental Relations 53 
the Pittsburgh district and one for the suburban districts; and 

(3) two independent consortia, one in the southwest hills 

area and the other in the Mon Valley. These interorganizational arrangements create opportunities for specialized ser- vice production that otherwise would be unavailable. 

size) and ability to pay. District contributions computed 

for Fiscal 1988-89 range from a low of $5,827 for Clairton 

Jointures 

A jointure is a voluntary cooperative arrangement 

among school districts created and governed by the district 

boards of directors. Jointures maintain facilities for spe- cial education in four areas (Eastern, South Central, 

Southeastern, and Western), and maintain facilities for 

and provide vocational-technical education in three areas 

(Forbes Road East, Parkway West, and Steel Center). The 

Northern Area Special Purpose Schools jointure is the 

only one that provides special education facilities and 

vo-tech education. 

The jointures are suppfemented organizationally (at 

least initially) by municipal authorities. also created jointly 

by some school districts to finance (through revenue bonds), 

construct, equip, and furnish the specialized facilities. 

The basic governing document of a jointure consists 

of legally binding Articles of Agreement, whereby school 

districts agree to establish a “joint school system” for limited purposes for a stipulated period of time (e.g., 40 years). 

The governing body is a board of school directors consisting of the members of the district boards. Annual approval 

of the operating budget is required by a majority of the 

board and two-thirds of the participating school districts. 

Most other policy decisions are made by a joint school 

committee, with at least one representative from each 

member district board. The committee either organizes its 

own production unit (vocational-technical schools) or contracts with the Allegheny Intermediate Unit (special education centers and the Steel Center vo-tech services). 

Although one of the district superintendents must serve 

as the superintendent of record for the jointure, supervisory responsibility rests with a full-time director. In the 

Northern Area jointure, the superintendent of record 

serves as chairperson of a professional advisory committee 

of the district superintendents. 

Jointures bring school district personnel together on a 

regular basis to discuss common concerns. In the North- ern Area jointure, for example, regular meetings are held 

among the superintendents, principals, counselors, and 

personnel directors. The latter group has organized a consortium to operate a shared substitute teacher program. 

Intermediate Units 

The 29 intermediate units throughout Pennsylvania, 

established in 1971 as successors to county school systems, 

are, unlike jointures, creatures of the state. Like jointures, 

they are governed by member school districts. Intermedi- ate units have a broad range of functions, the basic one being to act as a channel of communication between the 

state Department of Education and the school districts. 

Other functions typically include producing numerous 

auxiliary services as well as direct services to special education students. Because of its importance as an organizational overlay in the suburban county, this analysis focused 

54 US. Advisory Commission on Intergovernmental Relations 
State and federal funding for AIU programs is complex, involving some 60 separate program budgets. The 

various “pots of money” range in size from a few thousand 

dollars to the exceptional children’s program with more 

than $33 million. Many of the budgets commingle funds 

from more than one source. 

Not surprisingly, AIU has a substantial administrative 

apparatus organized in four major divisions plus finance. 

The executive director is assisted by an associate and three 

assistant executive directors and a finance director. Some 

29 program officers report to these second-tier supervisors or to the executive director. 

Because public education is regulated extensively by 

the state, the intermediate units are used as a mediating 

structure by state and local officials. NU regularly supplies information on how to comply with state mandates. 

Local districts and the state view this as an important service. Given the governance structure of AIU, its officials 

tend to view themselves as representatives of the districts, 

not as agents of the state Department of Education. 

AIU is a complex intergovernmental institution. 

Created by the state, it is governed by local districts. Much 

of its institutional structure and many of its responsibilities are determined by state law. It operates in a collegial 

manner, however, and is often used to create and administer limited-purpose, voluntary consortia of some subset of 

districts. Administratively, AIU is much larger than any of 

its member districts, yet its direct service responsibilities 

are limited mostly to special education. Importantly, AIU 

has no supervisoly authority over local school districts. It is a 

service organization that districts may use at their discretion, 

although the districts’ financial contributions are mandatory. 

Independent Consortia 

The Mon Valley Educational Consortium is a community-based organization serving 20 school districts in three 

counties. Unlike jointures and intermediate units, this 

consortium was formed by a local citizen initiative and remains formally independent of school district organization. Founded in 1985 as the McKeesport Education 

Consortium of schools, businesses, and communities, the 

organization served only the McKeesport area district. Its 

initial projects included a community newsletter and an 

alumni association, both designed to foster greater community awareness of school activities. Since its expansion 

in 1987, the consortium serves 10 districts in Allegheny 

County (Clairton, Duquesne, East Allegheny, ElizabethForward, McKeesport, South Allegheny, Steel Valley, 

West Jefferson Hills, West Mifflin, and Woodland Hills) 

and 10 districts in Washington, Westmoreland, and 

Fayette counties. The original 16-member governing 

board was expanded to 26 community representatives. 

School districts participate at their own initiative, and district superintendents meet twice each year. 

The consortium raises funds for specific projects from 

the local communities and foundations. The staff is 

small-3.5 positions including the executive director and a 

secretary. Instead of seeking to increase its in-house production capabilities, the organization concentrates on 

building linkages between schools and other organizations. 

An annual program called Great Ideas makes small 

grants to teachers (up to $300), schools (up to $1,500), and 

one district (up to $10,000), offering opportunities to try 

out new ideas. The teacher projects are reviewed by a committee of business people and educators in each district. A 

Partnership on Education program pairs schools with businesses and government agencies, including the McKeesport Daily News, U.S. Bureau of Mines, Alcoa Research 

Center, and a general hospital, to engage in joint teaching. 

The South Hills Area School Districts Association 

(SHASDA) originated in 1969 when 12 superintendents 

began regular meetings. Although the number has grown 

to 16, the organization remains informal. Expenses are 

shared on a voluntary basis, and the staff consists of a secretary. Much of SHASDA’s activity is political, focusing on 

working closely with the area’s 13 state legislators. Personnel directors from the member districts maintain a data 

bank for use in collective bargaining. Since 1978, SHASDA has sponsored a spring conference for school board 

members, administrators, and students. A parallel association-Student SHASDA-was started in 1981. Motivated by a desire to improve relationships in interscholastic sports competition, the group organizes student 

visits and social events. 

SPECIALIZED PRODUCTION ARRANGEMENTS 

Two types of services comprise or contribute to public 

education: 

1) Direct services to students, including classroom 

teaching, transportation, school lunches, and 

counseling. 

2) Indirect or auxiliary services to the producers of 

direct services, including building maintenance, 

curriculum development, and in-service training. 

In Allegheny County, most direct services are produced by school districts. Special education is produced in 

large part by the Allegheny Intermediate Unit in coordination with school districts. Vocational-technical education is produced mostlyby separate schools organized and 

governed through jointures. AIU is the dominant producer of auxiliary services other than building maintenance. 

School districts produce some auxiliary services, depending on district size and wealth, and jointures and independent consortia are increasingly active. Interorganizational 

arrangements are important in producing special education and vo-tech education and for all auxiliary services. 

These areas are discussed below. 

Special Education 

Students with mental, physical, and multiple handicaps-the major special education program-either are 

enrolled in five special education centers provided by jointures (approximately 1,100 students) or receive special 

services in regular schools (24,000 students, including 

those with specific learning disabilities). All of the centers 

are staffed and operated by AIU, although the buildings 

are owned and maintained by jointures. AIU also supplies 

the majority of special education teachers in the regular 

schools. In some cases, the state subsidy plus the district 

US. Advisory Commission on Intergovernmental Relations 55 
contribution is used to enroll handicapped students in private schools (e.g., schools for the blind or for autistic children). AIU evaluates all special education students. 

School districts may hire their own special education 

teachers and receive the state subsidy directly or request 

the service from MU. Riverview District, for example, 

staffs all of its special education classes. Two considerations led to this choice: (1) the ability of the district to 

control the classroom and (2) a desire to preserve local 

teaching positions in the face of declining district enrollments. The major cost associated with this option is the 

need to submit paperwork to the state for reimbursement. 

AIU estimates that roughly 20 percent of the state subsidy 

in its jurisdiction is being spent directly by school districts 

and encourages its member districts to assume as much responsibility as possible in view of limited state funding. In 

the majority of cases, however, an AIU teacher, hired and 

supervised by AIU, works in a district classroom under the 

control of a building principal. This arrangement depends 

on a high level of coopexationbetween school districts and 

MU, and it frequently works well. Sometimes, there are 

difficulties in scheduling (working hours for. AIU and district teachers may not coincide) and participation of AIU 

teachers in in-service education. 

Special education also includes services for the hearing 

impaired and for socially and emotionally disturbed students, 

as well as a gifted and talented program. AIU supplies technical assistance to regular classroom teachers and, in some 

cases, teachers who move from school to school. 

Vocational-Technical and Alternative Education 

Arrangements for the production of vocational-technical education are considerably more straightforward 

than for special education. Three of the four area vo-tech 

schools are operated by jointures. The Steel Center program is operated by AIU, and McKeesport operates its 

own program. 

The vocational program provided by the Northern 

Area jointure serves as an illustration. Nine school districts make up the jointure, formed in 1966: Avonworth, 

Deer Lakes, Fox Chapel, Hampton Area, North Allegheny, 

Northgate, North Hills, Pine-Richland, and Shaler Area. 

The joint school committee operates the Alfred W. Beattie Area Vo-Tech School, which offers a wide range of programs for the 11th and 12th grades, including business, 

graphic communications, health services, mechanics, culinary arts, and cosmetics. In 1984-85, Beattie had an ADM 

of 1,099 students for three hours each day at a per-pupil 

cost of $1,710. Like other vo-tech schools in the county, 

Beattie has experienced a serious decline in enrollments. 

In 1987-88, the ADM was down to 793 and per-pupil cost 

was $2,881, a 68.5 percent increase in three years. 

To support the jointure, each school district is billed 

based on the number of students in the vo-tech school, 

making up nearly 90 percent of operating revenues. The 

state subsidy for vocational education accounts for less 

than 10 percent of funding. The administrative budget, 

which includes support services for the board, building 

maintenance, and capital costs, is shared by the districts in 

proportion to their share of the total assessed valuation of 

the area. This amount has been declining due to a decrease in capital costs. Each district is responsible for 

transporting its students. 

In 1987-88, the Northern Area jointure established an 

alternative high school, also located in the Beattie facility. 

The program is intended for students “not receptive to or 

profiting from existing school program^."^ Student quotas 

were allocated to each district based on its share of the total ADM in grades 10-12. Operating costs were allocated 

among the districts on the basis of student participation, 

but the method was changed to a student quota basis, thus 

giving each district an incentive to use its quota. Enrollment in the fall of 1988 was 81 students. Parkway West 

jointure also has introduced an alternative high school. 

Auxiliary Services 

The Allegheny Intermediate Unit supplies a wide 

range of indirect services to schools and school districts. 

AIU resources include an exten~~~ef~~~(ui~e~~i~and 

delivery service, and a learning resource center that 

houses instructional materials and a professional library. 

AIU offers in-service credit courses for continuing professional education. An evening and summer program was 

developed to emphasize classroom issues, and was made 

available to Pittsburgh and to private school educators. 

AIU also supplies consulting services for curriculum management and instructional support. AIU also organizes 

administrative consortia for joint purchasing, natural gas, 

health insurance, and workers’ compensation. 

Small school districts seem tobe especially dependent 

on AIU for indirect services, often pooling money they 

have received from the state to have AIU organize joint 

programs. Larger districts may depend on AIU to develop 

service options. Out of the six district superintendents interviewed for this study, only one expressed reservations 

about the value of AIU, arguing that it was too large and 

not sufficiently responsive to the districts. The others 

cited AIU support and services as beneficial or essential. 

One alternative and potential complement to reliance on AIU is greater use of jointures and independent 

consortia organized by the districts or, as in the case of the 

Mon Valley Education Consortium, by local citizen 

groups. The Northern Area jointure operates a substitute 

teacher service. The South Hills Area School District Association coordinates in-service training. The Mon Valley 

consortium complements the regular AIU support services. 

Summary 

Allegheny County school districts are not limited to 

those functions that each is capable of performing separately. Especially outside of Pittsburgh, the 42 suburban 

school districts can be looked on as the basic building 

blocks in a system of organization that extends across district boundaries. The purpose of these organizational linkages is to arrange for the expertise and specialized services 

often thought to be lacking in a fragmented area. Jurisdictional fragmentation provides a base for interorganizational efforts. 

The specific arrangements vary. Both jointures and 

intermediate units are aptly named. Jointures are created 

from the ground up, so to speak, and represent a horizon56 U.S. Advisory Commission on Intergovernmental Relations 
I 

Table 5.7 

Service Conditions Model Explaining School District County Performance levels 

on “TELLS” Tests, Allegheny County 

(Shown: Unstandardized Regression Coefficients and T scores, N =43.) 

Reading Math 

1984-85 1985-86 1984-85 1985-86 

Poverty Rate -.0187 -.0213 -.0123 -.om 

Percentage of Population High School Grads .0037 .ooa .008 1 .ooa 

Percent of Population over Age 65 .0030 .003 1 .0040 

(4.38) (5.63) (7.36) (3.88) 

(3.33) (2.30) (2.88) (5.34) 

(2.23) (1.02) (1.22) (1.45) Standard Error .0555 ,0481 .0527 .0711 

R2 .7503 .8484 3004 .6934 

tal linkage that joins two or more districts in common efforts. Intermediate units are created from the top down 

and assume a role in the vertical linkage between school 

districts and the state. Yet, intermediate units are locally 

governed and often serve as organizational umbrellas for 

voluntary joint efforts among a limited number of districts. Automatic funding by state action is one of the 

strengths of AIU that also makes it less dependent on its 

immediate clientele, the school districts. Smaller and 

poorer districts clearly have more to gain from the services 

available from AIU, but larger and richer districts are not 

free to withdraw their support and therefore have incentives to participate. At the same time, the two voluntary 

consortia represent entrepreneurial efforts that go beyond what AIU has been willing and/or able to provide by 

way of support. The basic point remains that there are numerous feasible alternatives to what David Tyack called 

“the one best system”6 (a single consolidated school district) in the metropolitan organization of public education. 

PERFORMANCE PATTERNS 

The Effect of District Size 

School and school district consolidation have become 

part of the folklore of progressivism in American public 

education. Despite empirical results to the ~ontrary,~ education and public administration professionals often assume that smaller districts are associated with poorer 

school performance. Consolidation efforts continue in 

many states and communities, with public policy (though 

perhaps not public opinion) often firmly on their side. 

Pennsylvania promoted district consolidation as recently 

as two decades ago. Therefore, it is useful to examine the 

nature of the relationship between school district size and 

school performance in a fragmented metropolitan area such 

as Allegheny County. Because there is no convincing model 

that relates school characteristics to school performance,” 

this analysis is exploratory and its conclusions tentative. 

Test results from a statewide program, Testing for Essential Learning and Literacy Skills (TELLS), can provide 

a limited measure of student performance aggregated by 

district. Competency tests in reading and mathematics are 

administered in Pennsylvania’s 501 school districts in the 

3rd, 5th, and 8th grades. Students who score 16 or more 

percentage points below the national median on either 

test are eligible for remedial help. In this analysis, the percentage of 8th grade students found not eligible for remedial help is used as an indicator of aggregate student 

achievement in each district. This indicator measures the 

degree to which students, aggregated by district, reach a 

minimum level of achievement by the 8th grade. It does not 

measure the degree of student achievement above a minimum level. Nonetheless, minimum standards measure a 

basic and important dimension of student performance. 

Ideally, an analysis of school district performance 

would use multiple indicators, including average or median scores on standardized achievement tests, graduation 

rates, college placement, and expressions of satisfaction 

or dissatisfaction by students and parents. The analysis 

here is based on a single indicator, but it is a useful one in 

many respects. Whatever local preferences may be for 

educational performance, it seems reasonable to compare 

school districts on the criterion of a minimum level of academic performance by as many students as possible. Ex- cept where noted, all 43 school districts in the county are 

included in the analysis, using TELLS test scores for the 

1984-85 and 1985-86 school years. 

The Effect of Service Conditions 

If student achievement is used as an indicator of 

school district performance, then that performance is determined mainly by service conditions, specifically students’ social background? In this analysis, a school 

district’s service conditions are measured by (1) the poverty rate, controlling for the percentage of a district’s population over age 65,’” and (2) the percentage of adults who 

have graduated from high school. Both of these variables 

are strongly and independently related to 8th grade test 

performance.” As shown inlhble 5.1, the three variables together explain approximately 75 percent of the variance in 

test performance levels among the 43 districts for both years. 

Service conditions, as measured here, are by and large 

beyond the control of a school district. Given the strong 

effect of service conditions on student performance, 

school performance cannot be equated with student performance (neither can they be divorced). An indicator of 

school performance can be derived by comparing actual 

U.S. Advisory Commission on Intergovernmental Relations 57 
levels of student performance with the levels predicted by 

a service-conditions model. The difference between actual and predicted student performance levels can be in- terpreted as a rough index of school performance or 

effectiveness.12 This approach is used in the discussion of 

district size effects. 

The Effect of Per-Pupil Expenditures 

Some of the unexplained variance in the service-conditions model can be explained by adding total expenditures per student. Districts that spend more money per 

student tend to have a higher percentage of students who 

do not require remedial help in the 8th grade, controlling 

for service conditions. The additional amount of the variance explained, between 2 and 3 percent, is not substantial. 

The Effect of School District Size 

School district size alone, measured by average daily 

membership, has a low positive association with student 

performance among the 42 suburban districts (i.e., larger 

districts tend to have larger percentages of 8th grade stu- dents performing at or above the minimum standard in 

reading and math in 1984-85 and 1985-86).13 When considered jointly with service conditions, however, the coeffi- cients relating size to the four performance indicators 

become negative in three of the four cases (i.e., the larger 

the districts the lower the performance), but the coeffi- cients are weak and not significant. Overall, size does not 

appear to have a significant linear effect on performance 

when service conditions are contr01led.l~ 

School district size, nevertheless, has been an issue of 

great concern and considerable controversy in Pennsylva- nia. State policy during the 1960s sought to consolidate all 

districts with pupil populations under 4,000 and required 

consolidation of all districts with pupil populations under 

2,500. By the early 1970s, a wave of school consolidations 

had been completed throughout the state. Thirty of the 42 

school districts in suburban Allegheny County are a product of consolidation. 

Since the period of consolidation, enrollments in the 

county have declined overall, leaving 20 school districts 

(including 14 consolidated districts) with an average ADM 

of less than 2,500, and 11 districts (including 7 consolidated districts) with less than 2,000. Eleven more districts 

have pupil populations between 2,500 and 4,000. The creation of Woodland Hills district is the only school consolidation that has occurred recently, and that was by federal 

court order to effect racial desegregation. If the state criteria used during the consolidation period were applied 

today, almost half of the county's school districts would be 

required to consolidate, and as many as two-thirds would 

be considered or consolidation. 

The effectiveness of individual school districts in 

mee;ing minimum standards can be compared by computing a residual for each district after controlling for service 

conditions. First, the service-conditions model (shown in 

nble 5.1) is used to predict a performance score for each 

district; then, the difference between the observed and 

predicted scores is calculated. The difference is the residual. Districts with positive residuals are doing better than 

service conditions predict and are considered more effective. Districts with negurive residuals are not doing as well 

as service conditions predict and are considered less effective. The residuals are thus used to estimate the effectiveness of school districts in educating students from 

communities with various conditions for 1ea1ning.l~ 

The approach used here is to examine the effective- ness of the smallest districts in the county, individuallyand 

as a group, compared to the others. The set of smallest dis- tricts-designated as Group I-was determined by com- puting the mean pupil population of all districts with fewer 

than 2,500 pupils (the cut-off for mandated consolidation) 

and defining the set as those districts with pupil popula- tions below the mean (1,765 pupils). Group I is composed 

of nine districts, ranging in size from 913 to 1,610 students. 

Group I1 has 11 districts, ranging from 1,911 to 2,486 stu- dents. Together, Groups I and I1 comprise those districts 

that would have been required to consolidate under state 

criteria. Group 111 also has 11 districts with between 2,500 

and 4,000 pupils, the additional districts that would have 

been considered for consolidation. Group 4 has 11 dis- tricts, with pupil populations over 4,000. This group would 

not have been affected by the state consolidation criteria. 

The fourgroupsare compared in Table 5.2 Notice that 

the average observed scores for Groups I and I1 are in the 

70 percent range, while Groups I1 and IV fall in the 80 per- cent range, seeming to indicate that bigger is better. The 

difference in observed scores, however, does not take into 

account differences in service conditions. The mean 

scores predicted by the service-conditions model follow a 

similar pattern. This means that Groups 1 and I1 tend to 

have less favorable service conditions. The difference be- tween the predicted and the observed scores, averaged for 

each group, is the average residual. Comparing the residu- als across groups is a meaningful way of comparing effec- tiveness of school districts in different size categories. 

Group 1-the smallest districts-displays the two 

largest positive residuals (one in reading and one in math) 

and compares favorably to all the other groups. Group 

11-the next smallest districts-performs least well, having the largest negative residuals (two in reading, one in 

math). Group 111-districts between 2,500 and 4,000 pu- pils-is in second place, with consistently positive residuals. Group IV-the largest districts outside Pittsburgh-is 

in third place, with three out of four residuals negative. 

Although the linear relationship between district size and 

effectiveness across the full range is inconsistent (negative 

between Groups I and 11, positive between Groups I1 and 

111, and negativebetween Groups111 and IV), the smallest 

districts as a group are relatively most effective. 

School districts in Groups I and I1 would face consolidation under previous state rules. Such a requirement, 

however, would not be congruent with patterns of TELLS 

performance. The smallest school districts in the county 

tend to perform at least as well as districts in larger size 

groups, and often perform better, using minimum standards of reading and mathematics as indicators. Yet, the 

relationship of size to performance is inconsistent. This 

sort of relationship is incongruent with an automatic size 

threshold rule for consolidation. Rather, existing performance patterns suggest that consolidation proposals 

ought to be judged on a case-by-case basis. 

58 U.S. Advisory Commission on Intergovernmental Relations 
Table 5.2 

School District Effectiveness, Measured by Difference between Observed and Predicted Performance Levels 

on “TELLS” Tests, by Size Groups 

(Pittsburgh shown separately, N=43) 

School Districts 

Eighth Grade Test Year 

Group I: 

Districts with fewer than 1,765 pupils (N=9) 

Reading 84-85 

Math 84-85 

Reading 85-86 

Math 85-86 

Group II: 

Districts with 1,765 to 2,500 pupils (N= 11) 

Reading 84-85 

Math 84-85 

Reading 85-86 

Math 85-86 

Group 111: 

Districts with 2,501 to 4,000 pupils (N=ll) 

Reading 84-85 

Math 84-85 

Reading 85-86 

Math 85-86 

Group nT: 

Districts with more than 4,000 pupils (N= 11) 

Reading 84-85 

Reading 85-86 

Math 84-85 

Math 85-86 

Pittsburgh: 40,599 pupils 

Reading 84-85 

Math 84-85 

Reading 85-86 

Math 85-86 

A B A - B 

Score’ Score2 Residual’ 

Observed Predicted 

79.3 

75.9 

76.0 

79.0 

77.6 

76.1 

78.2 

73.7 

87.4 

87.1 

87.4 

84.6 

85.3 

86.3 

86.9 

84.0 

60.9 

58.3 

76.9 

64.2 

n. 1 + 2.2 

75.5 + 0.5 

76.4 -0.3 

75.2 + 3.8 

79.1 -1.6 

77.8 -1.7 

78.7 -0.5 

76.2 -2.5 

86.6 + 0.9 

86.2 + 1.0 

86.5 + 0.9 

84.5 4- 0.2 

86.5 -1.2 

86.0 + 0.2 

87.6 -0.7 

85.0 -1.0 

60.8 +0.1 

57.0 + 1.3 

63.1 + 13.7 

57.3 + 6.9 

Average of percent not eligible for remediation. 

Observed score - predicted score = residual. Numbers may not subtract precisely due to rounding. 

’ Scores predicted from serviceconditions model shown in Table 5.1 averaged over school districts in each group. 

From the evidence presented here, school district 

consolidation alone is unlikely to have an appreciably favorable impact on district effectiveness.16 Only to the extent that consolidation is tied to other changes is increased 

effectiveness likely. One possibility is that consolidation 

would result in an increase in spending per student. If increasing the district size increases the taxbase per student, 

and if taxpayers are willing to increase spending accordingly, the positive relationship between expenditure per 

student and student performance suggests some possibility of better performance as a result. Note in able 5.2 that 

the performance of the Pittsburgh district, much larger 

than any other in the county, is consistently positive. Pittsburgh also spends much more per pupil than other districts with similar service conditions. Outside Pittsburgh, 

there is no significant relationship between district size 

and total spending per pupil. Again, it would appear that 

consolidation proposals can be judged only on a 

case-by-case basis.” 

It bears repeating that both small and large districts 

may excel in other ways not measured by the indicators 

used here. The districts with small negative residuals but high 

observed scores are, without doubt, excellent school districts in 

many respects. Minimum performance standards, nevertheless, reflect a basic public policy concern. This concern 

is especially relevant to those districts that face difficult 

service conditions-that have larger numbers of students 

who tend to perform below a minimum standard due to social background. 

NORTHCATE SCHOOL DISTRICT: 

A CLOSER LOOK 

To press the exploratory analysis of school district effectiveness still further, individual district residuals were 

US. Advisory Commission on Intergovernmental Relations 59 
examined to search for consistently superior districts. 

Large positive residuals for reading and math for both years 

are uncommon.’* The most consistent top performer was 

Northgate School District, the ninth smallest district in the 

county. Its residuals and (actual scores) are shown below: 

Reading 84-85 + 10.15 (94.0) 

Reading 85-86 + 4.54 (87.5) 

Math 84-85 3- 12.36 (96.6) 

Math 85-86 -6.69 (91.7) 

The 1984-85 scores were more than two standard errors 

above the predicted scores for that year, but the 1985-86 

scores fell just within a single standard error. 

Northgate serves about 1,550 students who live in a 

1.5 square mile area, adjacent to the northwest comer of 

Pittsburgh. All students reside within walking distance of 

one of two elementary schools (K-6) or the one juniorsenior high school, and either walk or arrange their own 

transportation. The school district boundaries exactly 

overlay Avalon and Bellevue boroughs. Private schools 

enroll 13 percent of the district’s elementary students and 

3 percent of the secondary students. The district professional staff consists of a superintendent, buildings and 

grounds coordinator, and director of computer services, 

with offices in an old Victorian house. 

There was a separate school district for each borough 

until 1971, when the state mandated consolidation. Separate high schools were maintained until 1976. Bellevue 

contested the consolidation in court, but lost. Avonworth, 

also a candidate for inclusion in the Northgate district, 

avoided the state mandate. 

Northgate can be described as a low-income, white 

community with an average poverty rate and average 

school spending. Its median household income of $14,777 

ranks it 37th out of the 43 districts. The poverty rate of 6.57 

percent is close to the countywide average. Whites make 

up 98.09 percent of the population. An assessed valuation 

per student of $34,306 puts Northgate in 29th place in the 

county, but total expenditures per student of $5,256 put it 

in 20th place, close to the mean. As shown in Table 5.3, 

Northgate raises somewhat more local revenue than predicted from the size of its revenue base. About two-thirds 

of its revenues are raised locally. The district millage rate 

has been increased every year since 1980. In 1996, the district will become debt free, and it has begun a preventive 

maintenance program to forestall another bond issue. 

In an interview, James C. Manley, Northgate superintendent, stressed three factors in accounting for the district’s success. One is related to the district’s small 

population and area, enabling students to walk to school 

and keeping school close to home. By holding down class 

size as well (a factor that is independent of district size), 

the schools are able to maintain a learning environment in 

which teachers know students and their families. School 

A second factor cited is that the district employs 1.5 

school psychologists, which enables Northgate to analyze 

student performance without a four-five month wait. The 

district has its own learning disability program in the elementary schools, but relies on the Allegheny Intermediate 

Unit for the secondary school program. MU personnel 

are treated as part of the district staff. 

A third factor is the conservative cultural climate of 

the community. Churches remain strong, and the North 

Borough Ministerial Association continues to perform a 

baccalaureate for graduating seniors. Families continue to 

regard education as important. Yet, the district also has a 

significant number of transient and single-parent families 

whose children often require special attention. The district makes a strong effort to stay in close touch with its 

community, publishing an annual scholastic calendar 

packed with information about school programs and services, and distributing a weekly column, “From the Superintendent’s Desk,” to the two local newspapers. Many of 

these columns are devoted to reinforcing a sense of pride 

in the achievements of Northgate students and residents. 

The explanation offeredby the Northgate superintendent is consistent with recent theoretical conjectures and 

research findings of James B. Coleman on school effectiveness.Ig Coleman distinguishes three schoolkommunity factors that affect performance: 

1) physical capital-buildings, equipment, and ma- terials in the schools, and books, materials, and a 

quiet place to study at home; 

2) human capital-skills and talents of teachers, ad- ministrators, and parents; and 

3) social capital-trust, goodwill, communication, 

and reciprocity. 

Coleman’s theory, together with Superintendent Manley’s assessment of his district, affords a tentative explanation of why Northgate is consistently a top performer, 

controlling for service conditions. The service-conditions 

model contains a measure of physical capital (poverty rate) 

and human capital (high school graduation), but not social 

capital. Except for one human capital factor (school psychologists), the superintendent’s assessment focused on 

the accumulated social capital in Northgate. It follows that 

Northgate would perform better than predicted by indicators of physical and human capital only. Because social 

capital draws on relationships between the community and 

school personnel, it cannot be treated exclusively as an 

in-school attribute or a community attribute. It is a product of interactions between schools and community. The 

ability of schools to function as an effective part of the communities they serve appears to be an important variable. 

PATTERNS OF PROVISION 

discipline is good, according to Manley. Vandalism of 

school property amounts to only about $100 in damage 

each year. Manley also noted that Northgate has never 

had a teachers’ strike, and characterized the relationships 

among teachers, the administration, and the community 

as based on underlying trust. 

How Much Disparity? 

Provision for public education in Pennsylvania, as 

throughout most of the United States, is a joint responsibility of local school districts and the state. In Pennsylvania, direct state aid provides 45.6 percent of total school 

district spending (plus 8 percent in retirement fund aid). In 

GO U.S. Advisory Commission on Intergovernmental Relations 
part, state funding is intended to compensate for inadequate fiscal resources in some localities. Whether remaining patterns of disparity should be attributed to local 

patterns of organization or state aid policies and formulas 

or both is ambiguous. 

Often, state education funds are accompanied by extensive regulation, so much so that the function of specifying what is to be provided, and often how, has been 

preempted by the state. Pennsylvania is no exception. 

Most of the district superintendents interviewed in Allegheny County cited the timely information about state 

requirements and advice on how to comply with them as 

an especially beneficial service of the Allegheny Intermediate Unit. The details of state regulation, however, lie beyond the scope of this study. The focus here is on fiscal 

patterns among the 43 school districts in the county, as affected by patterns of state assistance. 

State Assistance 

The distribution of most state financial assistance to 

school districts is based on complicated formulas that take 

into account such factors as number of students (technically, average daily membership), population density, local 

tax effort, and the percentage of pupils in households receiving Aid to Families with Dependent Children (AFDC). 

The Equalized Subsidy for Basic Education, the largest state education aid program, consists of a base amount 

with economic supplements for qualifying districts. The 

base is calculated by multiplying an aid ratio that reflects 

district wealth (measured by the market value of taxable 

property and personal income) by (1) an educational expense factor established by the state legislature and (2) 

WADM-average daily membership indexed to give 

greater weight to secondary students. Aid ratios in Al- legheny County range from 0.15 in Fox Chapel and Quaker Valley to 0.63 in Clairton. Pittsburgh’s aid ratio is 0.36. 

One of the two economic supplements is given to districts where at least 10 percent of ADM are students who 

receive AFDC. The amount of the supplement depends on 

the actual percentage, ranging from $100 to $500 per AFDC 

pupil. The second supplement is available to districts where 

the local tax effort exceeds the median effort statewide, and 

it vanes from 1 percent to 5 percent of instructional expenditures according to district population per square mile. Large 

densely populated districts, such as Plttsburgh, are treated as 

exceptional cases and receive a supplement equal to 19 percent of instructional expenditures. This special subsidy is reflected in the total amount of aid distributed. 

In addition to using formula-based calculations, the 

legislature has constrained the distribution of aid by imposing ceilings and floors. In 1985-86, no district received a 

subsidy increase of more than 8.45 percent or less than 2 

percent over the previous year. Each district is guaranteed 

at least 80 percent of its subsidy. The subsidy ceiling tends 

to work against districts that are growing rapidly, while the 

floor cushions the effect of declines in enrollment. Small 

and needydistricts, defined as those with an aid ratio of 0.5 

or greater and an ADM of 1,500 or less, receive an additional $50 per pupil from the amount appropriated for the 

state basic subsidy program but added to the individual district’s allotment. Thus, the small district supplement directly reduces the amount available to other districts. 

The other major state assistance programs are for special and vocational education. The special education subsidy 

is intended to cover fully the added costs incurred by a district for the conduct of a state-approved program. Districts 

are to receive the difference between the cost of a regular 

education and the cost of special education perpupil.2O Some 

of these funds are distributed directly to intermediate units, 

which operate most special education programs. 

State support for vocational programs is considerably 

less than for special education. The vocational education 

subsidy is determined by a formula similar to that used for 

the basic subsidy. With some exceptions, the state pays an 

amount equal to 21 percent of the actual instructional expense for students attending vo-tech schools (or 17 percent in approved school district programs) multiplied by 

an aid ratio based on either market value of district property or personal income (but no less than 0.375). 

Other state subsidies provide small amounts of support for programs such as health services, driver education, food services, and pupil transportation, 

Variation in local Provision 

Given the pattern of state support, school districts in 

Allegheny County vary in the percentage of revenue 

raised locally from a low of 51.9 percent in South Allegheny 

to a high of 88.2 percent in Quaker Valley. Overall, Allegheny county schools raise approximately 67.4 percent 

of their total revenues from local sources (61.2 percent for 

Pittsburgh). 

Allegheny County suburban school districts rely predominantly on real estate taxes; Pittsburgh does so to a 

much lesser extent. In 1983-84, the suburban districts 

raised 83.3 percent of their revenues from the real estate 

tax, 12.9 percent from the earned income tax and other 

Act 511 sources, and the remainder from miscellaneous 

sources, including fees. Pittsburgh raised 54.2 percent from 

the real estate tax and 34.5 percent from Act 511 sources. 

The revenue base of the school districts, measured by 

the market value of taxable real estate per student 

(WADM),21 accounts for 83 percent of the variance in local revenues raised per pupil by all of the districts, reflecting their predominant reliance on real estate taxes (except 

Pittsburgh). The property tax base is used, as shown in 

Xble 5.3, to predict a revenue amount for each district. 

The difference between the actual amount of revenue 

raised and the amount predicted by real estate values 

yields an index of local tax effort, expressed in dollars per 

student (WADM), also shown in Table 5.3.This difference 

is the residual amount unexplained by real estate values. 

Districts with positive residuals dig more deeply into their 

pockets, so to speak, than districts with negative residuals. 

Five districts have negative residuals and eight have positive residuals that exceed one standard error ($294). Pittsburgh is included among the districts with a high tax 

effort.22 Most of the districts with low levels of local revenue not only have a low tax base but also make a relatively 

low tax effort. Note, however, that the two districts with 

the highest predicted local revenues-Fox Chapel and 

US. Advisory Commission on Intergovernmental Relations 61 
Quaker Valley-also have large negative residuals; yet 

both still manage to rank very high (one is in first place) in 

actual local revenue raised per student. 

The 43 districts vary considerably in total expenditures per student (from all revenue sources), rangingfrom 

$2,990 in South Park to $5,881 in Cornell. Pittsburgh issecond highest at $5,256 per student. The countywide mean 

(averaged by students, not districts) is $4,446. Omitting 

Table 5.3 

Local Tax Effort, Allegheny County School Districts 

Ranked by Actual Local Revenue 

(in dollars per pupil in average daily attendance) 

School District 

South Allegheny 

Elizabet h-Fonvard 

South Park 

Plum Boro 

Sto-Rox 

Clairton City 

Duquense City 

Deer Lakes 

Highlands 

West Allegheny 

McKeesport Area 

Penn Hills 

Wilkinsburg Boro 

est. Jefferson Hills 

South Fayette 

East Allegheny 

Hampton Township 

Northgate 

Carlynton 

Moon Area 

Woodland Hills 

Baldwin- Whitehall 

Shaler 

North Allegheny 

Steel Valley 

Brentwood Boro 

Keystone Oaks 

Pine-Richland 

Riverview 

Gateway 

North Hills 

Montour 

Bethel Park 

Allegheny Valley 

Avonworth 

Pittsburgh 

Upper St. Clair 

West Mifflin Area 

Quaker Valley 

Chartiers Valley 

Cornell 

Mt. Lebanon 

Fox Chapel Area 

A 

Actual 

Local 

Revenue 

$1,670 

1,795 

1,829 

1,851 

1,977 

2,087 

2,117 

2,121 

2,136 

2,211 

2,226 

2,304 

2,421 

2,755 

2,817 

2,857 

2,937 

2,944 

2,951 

3,005 

3,028 

3,034 

3,047 

3,086 

3,164 

3,181 

3,230 

3,258 

3,283 

3,348 

3,380 

3,398 

3,470 

3,522 

3,529 

3,636 

3,715 

3,715 

3,909 

3,910 

4,104 

4,216 

4,223 

B 

Predicted 

Local 

Revenue 

$2,003 

2,004 

2,311 

2,011 

1,990 

2,072 

2,380 

2,265 

2,221 

2,477 

2,390 

2,397 

2,431 

2,832 

3,002 

2,702 

2,900 

2,7 16 

2,839 

2,619 

3,224 

2,966 

2,933 

3,359 

3,188 

2,951 

3,336 

3,403 

2,913 

3,298 

3,698 

3,455 

3,110 

3,679 

3,199 

3,15 1 

3,399 

3,502 

4,340 

3,558 

4,086 

3,215 

4,8 14 

* + / More Than One Standard Error ($294) 

** +/ More Than Two Standard Errors ($588) 

A-B 

Residual 

-332 * 

-209 

-482 * -160 

-13 

15 

-263 

-144 

-85 

-266 

- 164 

-93 

-10 

-77 

-185 

155 

37 

228 

112 

386* 

-196 

68 

115 

-273 

-23 

229 

- 105 

-145 

370 * 

50 

-3 18 * -57 

359 

-157 

330 * 

485 * 

316. 

213 

-432 * 

352 * 

18 

941** 

-591** 

Pittsburgh, the mean falls to $4,020. The standard deviation (a measure of dispersion) is $478 per student, or 

11.89 percent of the mean.23 Because Pittsburgh is so different from most other districts in the county, the distribution of spending levels for the suburban districts is 

examined separately and shown in Figure 5.1 

The distribution is fairly symmetrical, with 71 percent 

of the student population in districts that lie within one 

standard deviation of the mean. Of the remaining students, 16 percent might be characterized as relatively advantaged (19,071 students in five districts) and 14 percent 

as relatively disadvantaged (18,610 students in seven districts). If Pittsburgh were included in the analysis, the result would be a sharply asymmetrical distribution with the 

40,038 students in the central city added to the small group 

of advantaged students from the suburbs. 

Among the 42 suburban districts, there is no statistically significant relationship between district size, measured by ADM, and expenditures per student. One of the 

arguments made for school district consolidation is that 

access to a wider tax base will increase school revenues. 

Although this relationship may hold in individual cases, it 

does not hold in Allegheny County as a general rule. An 

alternative, partly contradictory, argument sometimes is 

made that small districts choose to remain small in order 

to preserve a wealthy enclave and spend more per student 

on fewer students. From this argument, one might expect 

the highest spending districts to be among the smallest, 

but in Allegheny County this is not the case. While the argument may hold in individual cases, there is no pattern to 

suggest a general tendency in that direction. 

Disparities 

One of the greatest sources of concern with highly 

fragmented or differentiated metropolitan areas is the potential for disparities in service provision among separate 

jurisdictions. Although disparity is often taken simply to 

mean an inequality among jurisdictions measured by variation on a single variable, a more interesting approach is to 

view disparity as a relationship between inequalities on 

different but related variables. The basic disparity of interest is actually an intradistnct relationship-a disparity between the problems faced by a school district and its fiscal 

capacity to respond to those problems. 

Consider the relationship between revenues per student and the percentage of low-income students. The 

school districts in a metropolitan area vary with respect to 

each of these characteristics: they are unequal. Disparity 

is more, however. It can be viewed as a relationship between these two inequalities, specifically, a combination 

of low revenues per student and a high percentage of 

low-income students. In this case, a negative coefficient 

would indicate disparity-a high score on one is associated 

with a low score on the other-and the degree of disparity 

in indicated by the size of the coefficient. 

The concern with disparity is usually with extreme differences among jurisdictions. Thus, one approach is to compare the jurisdictions at the extreme ends of related 

distributions. In this way, substantially more advantaged and 

substantially less advantaged jurisdictions can be identified. 

62 U.S. Advisory Commission on Intergovernmental Relations 
Figure 5.7 

Variations in Per Student Spending 

(Allegheny County school districts outside Pittsburgh) 

Standard Deviations from Mean of $4,020 

Standard Deviation = $478 

I 

U.S. Advisory Commission on Intergovernmental Relations 63 
Four sets of variables are used to identify and assess 

disparity: 

An index of local revenue capacity. Variation in local revenues is clearly one potential contributor 

to a disparity between service conditions and service capacity. As discussed above, the revenue 

base of local school districts in Pennsylvania consists mostly of the market value of taxable real estate. The local revenue levels predicted from the 

districts' property taxbase, shown innble 5.3, are 

used here as an index of local revenue capacity. 

This index permits a direct comparison between 

revenue capacity and spending. 

Patterns of state and federal assistance. Variation in 

state and federal aid to local districts may serve to 

reduce inequality in local fiscal capacity, although 

there also is a potential for increasing the inequality. 

Total spendingperstudent, reflecting the aggregate 

pattern of local, state, and federal revenues for 

each district. (See Figure 5.1) 

Service conditions. Another possible contributor 

to disparity is variation in student social backgrounds, which, as discussed above, is a major actor in determining the service conditions faced by 

schools. The predicted performance levels on 

TELLS 8th grade reading and math exams can be 

used as an index of service conditions, measured 

in terms of the predicted impact on performance. 

Scores for 1984-85 and 1985-86 are averaged for 

this purpose. The index permits a direct comparison between expected and actual performance. 

nbles 5.4 and 5.5 display the scores on each variable 

for ten districts at the ends of each distribution, including 

those districts that lie more than one standard deviation 

above or below the mean. The latter districts are considered as the most disadvantaged Wble 5.4) or advantaged 

Wble 5.5) on each variable. The interesting relationships 

are those between the fiscal variables (revenue capacity, 

intergovernmental aid, and total spending) and service 

conditions. 

As can be seen in nble 5.4, nearly all the districts that 

are among the most disadvantaged in local revenue capacity remain the most disadvantaged in total spending. Patterns of state and federal assistance do little to alter the 

relative position of the most disadvantaged districts. Still, 

state assistance in particular tends to flow in greatest 

amounts to districts that are lowest in revenue capacity, 

with the exception of Pittsburgh. 

Turning to Xible 5.5, two of the four districts with 

greatest revenue capacity are absent among the districts 

highest in total spending. These two districts-Quaker 

Valley and North Hills-are among the districts having 

the lowest tax effort in the county. Moon Township, while 

below average in revenue capacity, is the only district to 

lead Pittsburgh in tax effort and, for this reason, is found 

among the highest spending districts. Despite a below average tax effort, Woodland Hills combines a better than average revenue capacity with better than average state and 

federal aid to join the group of highest spending districts. 

Fiscal disparity depends on cumulative disadvantages 

between fiscal conditions and service conditions. Table 5.4 

shows a considerable overlap between those districts lowest in revenue capacity and those most disadvantaged by 

service conditions. Duquesne, Sto-Rox, and Clairton are 

among the most disadvantaged in terms of predicted performance in reading and math, as well as in revenue capacity. McKeesport, also among the most disadvantaged on 

both service condition indicators, lies just inside one standard deviation below the mean in the fiscal Capacity indicator. Wilkinsburg, disadvantaged in the reading indicator, is 

also well below average in revenue capacity. Steel Valley is 

close to the average. Only Pittsburgh among the districts 

most disadvantaged by service conditions is also among 

the highest spending districts @able 5.5). In terms or numbers of disadvantaged students, the greatest number by far 

are serviced by the Pittsburgh district. 

Comparing service conditions to total spending, the 

greatest disparities are found in Duquesne and Clairton, 

both located in the economically depressed Mon Valley. 

Both districts are Socially disadvantaged, and both lie more 

than 1.75 standard deviations below the mean in total 

spending per student. Yet their levels of state assistance 

are well within a single standard deviation of the mean. 

Federal aid to Allegheny County schools is oriented 

more toward assisting districts with relatively poorer social 

conditions, while state aid gives more dollars per student 

to districts with low revenue capacity. The districts that are 

most disadvantaged by federal aid, including Pittsburgh, 

are all considered to be socially disadvantaged. Those 

most advantaged by state aid are considered to be disadvantaged in terms of revenue capacity, Pittsburgh excepted. Given the strong association between social 

disadvantage and performance, federal aid seems to be 

more closely related to improving performance, while 

state aid is more closely related (though not entirely) to 

achieving greater fiscal equity. The much larger amount of 

state aid gives the state distribution system greater weight 

in determining the overall financial position of each district. 

In sum, fiscal and social inequalities among school 

districts in Allegheny County are only partially cumulative. In several cases, low revenue capacity and low total 

spending combine with difficult service conditions. In 

Pittsburgh, where the greatest number of disadvantaged 

students live, local revenue capacity, local tax effort, and 

state aid combine to avoid a potential disparity between 

resources and needs, at lest comparcd to other districts. 

SUMMARY 

Public education in Allegheny County joins a large 

number of relatively small school districts (outside Pittsburgh) to a rich an3 varied array of organizational ties and 

overlays. School districts tend to be community based, reflecting their historical tie to municipal incorporation. 

Since the school district consolidations of the 1960s, however, most districts now serve more than one municipality. 

There is a strong tradition of cooperation among the 42 

64 U.S. Advisory Commission on Intergovernmental Relations 
Table 5.4 

Disparities among School Districts in Allegheny County- Potentially Disadvantaged Districts 

(dollars per pupil) 

Revenue Capacitv Total SDendinE 

Predicted 

Local 

District Revenue District Spending 

South Park 2,777 

Duquense City 3,033 

Sto-Rox 1,990 

South Allegheny 2,003 

Elizabeth-Forward 2,004 

Plum Boro 2,011 

Clairton City 2,072 

Highlands 2,221 

c Deer Lakes 2,265 vr * South Park 2,3 11 $. Duquense City 2,380 0 

4 

A 

(-1 SD) 

b' 

McKeesport Area 2,390 

0 

3 

2,963 - 2 [mean] 

(-2 SD) 

South Allegheny 3,113 

Plum Boro 3,124 

Clairton City 3,140 

Elizabeth-FOM 3,309 

Highlands 3,479 

(-1 SD) 

Sto-Rox 3,606 

West Jefferson Hills 3,664 

Deer Lakes .3,666 

[mean] 4,446 

Intergovernmental Aid Service Conditions 

Predicted 

State Federal Math 

District Aid District Aid District Score* District 

Pittsburgh 329 

(+3 SD) 

Pittsburgh 1,962 Duquense City 228 Duquense City 55.8 (48.9) Duquense City 

Sto-Rox 217 Sto-Rox 56.7 (52.1) Clairton 

Clairton 56.8 (65.0) Sto-Rox 

Pittsburgh 

(+2 SD) (+2 SD) (-2 SD) (-2 SD) 

Plum Boro 1,565 Clairton City 196 Pittsburgh 60.2 (70.6) Wilkinsburg Boro 

Deer Lakes 1,526 Wilkinsburg Boro 187 McKeesport 69.4 (64.3) McKeesport 

Elizabeth-Forward 1,521 McKeesport Area 173 Steel Val. 

West Allegheny 1,488 

Sto-Rox 1,479 

(+1 SD) ( + ISD) (-1 SD) (-1 SD) 

South Allegheny 1,456 Steel Valey 139 Steel Valley 71.2 (72.3) Highlands 

Wilkensberg Boro 1,451 Moon Area 131 Highlands 71.8 (71.3) Woodland Hills 

McKeesport 1,418 Woodland Hills 121 Wilkinsburg Boro 725 (63.0) Cornell 

Shaler 1,397 East Allegheny 104 Cornell 73.0 (63.6) South Fayette 

[mean] 1,184 [mean] 84 [mean] 81.0 [mean] 

Predicted 

Reading 

Score* 

54.8 (57.6) 

56.1 (58.8) 

58.3 (56.6) 

58.9 (59.6) 

68.5 (57.6) 

70.1 (69.2) 

71.3 (76.9) 

73.4 (77.3) 

74.5 (72.0) 

76.0 (71.8) 

74.0 (74.8) 

81.6 

*Actua! Score in Parenthesis. 
h 

1. 

0 

v1 

Revenue Capacity 

Predicted 

Local 

District Revenue 

2. [mean] 2,963 a 

Mt. Lebanon 3,275 

5 North Allegheny 3,359 

$ Upper St. Clair 3,399 

a Chartiers Valley 3.558 

i Allegheny Valley 3,679 

2 

E 

P 

0 

a - 

m s Montour 3.455 

- 

z. (+ 1 SD) 0 

VI J North Hills 3.698 

Cornell 14,086 

(+2 SD) 

Quaker Valley 4,340 

Fox Chapel Area 4,814 

Table 5.5 

Disparities among School Districts in Allegheny County - Potentially Advantaged Districts 

(dollars per pupil) 

Total SDendinP Intergovernmental Aid Service Conditions 

Predicted Predicted 

State Federal Math Reading 

District Spending District Aid District Aid District Score* District Score* 

[mean] 4,446 [mean] 1,184 [mean] 84 [mean] 81.0 [mean] 81.6 

Chartiers Valley 4,363 Chartiers Valley 978 Quaker Valley 41 West Jefferson Hills 87.9 (89.6) Plum Boro 87.9 (85.0) 

Quaker Valley 4,400 Montour 930 Plum Boro 40 Brentwood Boro 88.7 (89.6) West JeKerson Hills88.0 (87.5) 

Avonworth 4,433 North Hills 920 Bethel Park 38 Gateway 88.8 (90.1) Moon Area 88.0 (94.6) 

Bethel Park 4,480 North Allegheny 32 North Hills 89.1 (87.9) North Hills 88.9 (87.3) 

Hampton Township 31 Hampton Township 89.2 (88.8) Hampton Tmahip 89.6 (92.4) 

Pine-Richland 29 Pine-Richland 89.6 (94.5) Pine-Richland 90.3 (90.5) 

Mt.. Lebanon 27 

West Allegheny 28 

(+1 SD) (-1 SD) (-1 SD) (+1 SD) (+1 SD) 

Mt. Lebanon 4,509 Fox Chapel Area 893 Elizabeth Forward 16 Bethel Park 93.5 (88.1) North Allegheny 92.2 (95.8) 

Woodland Hills 4,546 North Allegheny 870 Upper St. Clair 15 North Allegheny 94.0 (94.5) Bethel Park 93.0 (90.5) 

Moon Area 4,690 Cornell 869 Upper St. Clair 99.3 (96.9) Mt. Lebanon 98.0 (96.1) 

Fox Chapel Area 4,943 Allegheny Valley 868 Mt. Lebanon 100.0 (97.6) Upper St. Clair 98.6 (95.6) 

Upper St. Clair 782 

Mt. Lebanon 760 

(+2 SD) (-2 SD) 

Pittsburgh 5,256 Quaker Valley 480 

Cornell 5,322 

*Actual Score in Parenthesis. 
suburban districts. A notable example is jointures for the 

provision of vocational-technical education and facilities 

for special education. The Allegheny Intermediate Unit 

serves all the districts outside Pittsburgh, producing direct 

services for special education students (and vo-tech students in one case), plus a range of indirect services. Most 

recently, the Mon Valley Consortium was launched to foster school improvement in an economically depressed 

portion of the county. 

The jointures and AIU represent contrasting institutional approaches. Jointures are organized,under terms of 

state law, but are set up at the initiative of local districts 

and are governed by them, without any intervening process of election and representation. AIU, in contrast, was 

established by state law and, while governed locally, elects 

a governing board from among school directors. With respect to vo-tech education, jointures bill school districts 

for services. MU receives its funds directly from the state, 

and each school district’sportion is deducted from its state 

aid allocation. AIU is more autonomous than jointures in 

governance and finance. 

A key question in the evaluation of a public economy 

is the extent to which public entrepreneurship is able to 

emerge as a spur to innovation. Evidence of entrepreneurship is found in AIU and in jointures. The recent organization of administrative consortia within AIU and the 

development of alternative high schools by two jointures 

are important instances of entrepreneurship. Perhaps the 

most prominent example is found in the work of the Mon 

Valley Education Consortium. In this instance, a citizen 

entrepreneur-acting from outside the school systemhas put together an organization that ties together 20 districts in three counties, forming a network that links 

schools with communities in efforts to nurture classroom 

and school improvement. 

For many years, school district consolidation has been 

assumed to have automatic benefits. One of the benefits-access to expertise and specialized academic support 

services-is available to Allegheny County districts by virtue 

of AIU and other consortia. Jointures produce specialized 

educational services, another presumed consolidation 

benefit. Moreover, as this analysis shows, small school districts in Allegheny County cannot be presumed from their 

small size to be inadequate on at least one important indicator of school performance: the number of 8th grade pupils who perform at minimum achievement levels. 

Automatic minimum size thresholds for school district 

consolidation do not fit comfortably with the inconsistent 

relationship of district size to performance. 

An analysis of disparities across school districts between revenue capacity and spending per student and service conditions yields mixed conclusions. For the vast 

majority of students in the county at the extreme low end 

of the service conditions distribution, there is no obvious 

disparity. This is due to the spending level of the Pittsburgh district that results from a combination of local revenue capacity, tax effort, and state aid. Serious disparities 

nevertheless remain, affecting small numbers of disadvantaged students in a few small suburban school districts. 

The Duquesne and Clairton school districts are the most 

severely limited in their capacity to respond to their relatively poor service conditions, as measured by students’ 

social background. Compared to total county spending on 

education, the amount of money necessary to address 

these remaining disparities would be quite small. 

The cause of these remaining fiscal disparities is ambiguous. If schools were funded exclusively or predominantly from local dollars, one might accurately attribute 

the cause to jurisdictional fragmentation. Yet roughly 

one-third of the revenue available to Allegheny County 

schools comes from the state, allocated by state formulas. 

One of the purposes of state aid is to correct for financial 

disparities. Failure to do so might be attributed to the way 

in which state aid is allocated among districts. In the case 

of schools, this conclusion is at least as plausible as the 

common argument that fragmentation is to blame for fiscal disparities. 

Notes 

The policy connecting the formation of school districts to municipal incorporation dates to an act of the state legislature in 

1911.24 Pennsylvania Statutes 2-201, 2-241. 

Ibid., 2-201, 242.1. 

Ibid., 2-226. 

4 Ibid., 2-224. 

Northern Area Special Purpose Schools, Articles of Agreement: Alternative High School (July 1, 1981). 

’ David B. Tyack, The One Best System: A History of American 

Urban Education (Cambridge, Massachusetts: Harvard Uni- versity Press, 1974). 

’See, for example, Herbert J. Kiesling, A Study of Coxt and 

Qiiality of New Yo& Scliool Districts (Washington, DC: US. 

Department of Health, Education, and Welfare, Office of 

Education, 1970); and William A. Niskanen and Mickey Levy, 

“Cities and Schools: A Case for Community Government in 

California,” Working Paper No. 14 (Berkeley: University of 

California, Graduate School of Public Policy, 1974). 

* Robert E. Klitgaard and George R. Hall, ‘A Statistical Search 

for Unusually Effective Schools,” in William B. Fairly and 

Frederick Mosteller, eds., Statistics and Public Policy (Reading, 

Massachusetts: Addison-Wesley, 1977, p. 5. 

This widely accepted premise can be traced to the so-called 

Coleman Report of 1966. See James B. Coleman et al., Equalify ofEdircational Oppo~unity (Washington, DC: U.S. Department of Health, Education, and Welfare, Office of Education, 

1966). See also Harvey A. Averch et al., How Efiecfive Is 

Scholiiig? (Santa Monica: The Rand Corporation, 1972). 

lo The sign of the zero-order relation between percentage over 

age 65 and performance is negative, but the sign becomes positive in the service condition model. 

For poverty rate, r = -0.880 and -0,875 for 1984-85 and 1985-86 

test scores, respectively. For percentage of high school graduates, r = 0.839 and 0.801, respectively. The correlation between poverty and high school graduation is -0.769. 

l2 This intcrpretation assumes that the serviceanditions model 

is correctly specified and should be viewed with caution. Sort- ing out the effects of community context from the effect of 

in-school activities on student performance presents difficulties. The service-conditions model used here, while it explains 

a large percentage of the variance in student Performance levels, no doubt fails to capture all of the effects of community. 

Presumably, there is also some degree of school-community 

interaction, especially over the long term (i.e., good schools 

U.S. Advisory Commission on Intergovernmental Relations 67 
bujld strong mmmunjtjes and strong communities help sustain good schools). Some of the effect attributed here toschool 

effectiveness may in fact be linked to other community attrib- utes or to the joint effects of school and community. The more 

limited model is used here to avoid overcontrolling in ways 

that would not allow the in-school effects to be detected. For a 

discussion and application of this approach to identifylng effective schools, see Klitgaard and Hall, pp. 51-86. 

l3 The correlation coefficients (and associated probabilities) re- lating ADM to each of the performance indicators for the 42 

suburban districts are as follows: Reading 1984-85, r = + .20 

(.19); Math 1984-85 = + .32 (.04); Reading 1985-86, r = .33 

(.03); Math 1985-86, r = + .20 (.20). Adding Pittsburgh to the 

analysis changes three of the four coefficients from positive to 

negative, but none of the relationships are statistically signifi- cant. 

l4 One possibility is that size has a nonlinear or threshold effect. 

Logically, it is possible that none of the districts outside Pittsburgh are large enough to make a significant difference in per- formance, but this contingency cannot be examined from the 

Allegheny County data alone. The possibility is nonetheless 

rather unlikely considering the evidence from large-scale 

empirical studies. See Note 6. 

l5 One potential problem with a comparison of residuals is that 

districts that have relatively low predicted scores have more 

“room” to do better, so to speak, than districts with high pre- dicted scores. To take an extreme example, a district with apredicted score of 99.9 can have a positive residual of only 0.1, 

while its negative residuals can be much larger, potentially 

99.9. For this problem to affect the analysis by truncating the 

positive residual for a district, it would be necessary to have an 

observed score of 100 percent. No such score occurs. The re- gression model does predict perfect scores in three instances, 

but each time the district performance is somewhat less than 

perfect, resulting in relatively small negative residuals. 

l6 This conclusion pertains only to performance up to 8th grade. 

An asseseaent of high school performance would require additional data. 

l7 It can sfill be argued that consolidation may have an important 

economic benefit if it lowers the cost per pupil of producing 

education. Lower costs of producing education do not necessarily imply lower expenditures. Unfortunately, this sort of 

analysis is difficult if not impossible to conduct. Education is a 

multidimensional good. The indicator of performance used 

here measures only one, albeit an important dimension. Even 

assuming that all of the relevant dimensions can be measured, 

collapsing them into a single indicator would require assigning 

weights to the various dimensions. Arguments for local control 

of education rest in part on a presumption that different com- munities have different preferences for the various dimensions of the complex good called education. In other words, 

different communities would assign different weights todifferent dimensions. Clearly, any given school district would rationally seek to produce the greatest possible amount of, 

education for its level of expenditures. Comparing the degree 

to which they succeed in doing so is problematic. If preferences 

vary among districts, it is also possible that different size dis- tricts may be appropriate. The approach taken here is more 

modest. Small districts that spend more or less average 

amounts per pupil are capable of achieving high levels of performance in meeting minimum standards, controlling for a 

highly relevant aspect of the local service conditions. Surely 

the consolidation of such districts should be approached with 

great caution and not be assumed to be desirable on the basis 

of enrollment figures alone. This point addresses a pertinent 

issue of public policy, namely, how to go about making deci- sions on school district consolidation. Nothing in this discussion should be construed to mean that any particular 

consolidation proposal would necessarily be unwise. 

l8 In general, one can expect the smallest districts to appear more 

erratic in performance from year to year for statistical reasons. 

The small per pupil populations in each district increase the 

likelihood that the 8th grade populations in any one year will 

be above or below average. Small districts are more likely than , 

large districts to experience wider variation in test scores from 

year to year. This does not mean that small districts are less 

consistent educationally than large districts, only that the overall effect of service conditions on small districts is more variable. 

l9 See James B. Coleman, “Social Capital in the Creation of Human Capital,” American Jounial of Sociology 94 Supplement 

(1989): pp. S95-Sl20. See also Coleman and T B. Hoffer, Public and Private Schools: nze Impact of Communities (New York: 

Basic Books, 1987). 

2o The procedure is for the state to allocate money directly to special education centers and for each district to pay tuition to the 

state equal to the cost of educating a regular student. The actual amount of money available for distribution is determined 

by an annual allocation in the governor’s budget. In practice, 

school districts have accepted a larger percentage of fhe oper- ating cost than apparently prescribed by state law. Emerging 

litigation is challenging this practice. 

21 Weighted average daily membership. See discussion of state 

aid formulas. 

22 Given Pittsburgh’s heavier reliance on Act 511 taxes, property 

values may underestimate the city’s actual revenue base. 

23 This yields a coefficient of variation of 11.89 percent. In other 

words, the “average” distance of students from the mean is just 

under 12 percent of the mean. 

68 US. Advisory Commission on Intergovernmental Relations 
r- - 

The Political Economv 

INTRODUCTION 

This chapter presents an analysis of fiscal relationships among governmental units in Allegheny County. 

Four broad questions are examined: 

Is there a relationship between population and 

expenditures for public services among the many, 

relatively small municipal governments? 

What is the distribution of per capita revenue 

among municipalities and how is variation in revenue related to jurisdictional socioeconomic 

characteris tics? 

What is the distribution of residential taxburdens 

among municipalities and how is variation in tax 

burden related to jurisdictional socioeconomic 

characteristics? 

What is the distribution in per pupil revenue 

among school districts and how is variation in 

per-pupil revenues related to district socioeconomic characteristics? 

The first question addresses governmental efficiency, 

while the other three are related to fiscal equity. Answers 

to these questions provide limited information on these issues. Analyses based on revenue and expenditure data 

alone cannot be definitive-measures of service and of citizens’ preferences are also needed-but patterns of fiscal 

relationships can indicate efficiency and equity problems. 

Economic development issues are considered briefly, 

including recent efforts to address the serious decline in 

heavy manufacturing in parts of the county and its surrounding region, and to facilitate economic restructuring. 

POPULATION SERVED 

AND MUNICIPAL EXPENDITURES 

An important evaluative criterion for local government 

systems is efficiency in producing public services. Complex, 

fragmented systems like Allegheny County often are alleged 

to be inefficient because they contain many small municipalities that are unable to capture scale economies if they produce services by themselves, and to coordinate efforts 

through interjurisdictional production arrangements. 

Those who make this argument commonly claim that 

productive efficiency could be enhanced by consolidating 

of Allegheny Counti 

small municipalities. The resulting larger municipalities 

should, by this argument, exhibit lower per capita expenditures for a given service level than municipalities with 

smaller populations. On the other hand, most economic 

analyses of population size economies for local government services have not found this relationship.2 

Those who fault the production capacity of small jurisdictions miss the important distinction made in Chapter 1 

between service provision and service production. Many 

communities are too small to efficiently organizeproduction of a service or a service component. But efficient production may still be possible by arrangement with a larger 

scale producer, or jointly with other communities through 

contracting, multijurisdictional production, or overlapping production districts. A community also can be too big 

to organize production efficiently if it has a large, inefficient bureaucracy. In such a case, services can be provided 

more efficiently by contracting with smaller, competitive 

producers. The scale of provision need not and often 

should not match the scale of production. There is, therefore, no reason to anticipate significant population size 

economies for local government services. 

The relationship between municipal population and 

service expenditures is affected by a variety of factors, including (1) returns to scale in production (positive and 

negative); (2) availability and choice of production arrangements sensitive to returns to production scale for 

small and large provision units; (3) returns to scale in consumption, including both non-rivalry and congestion ef- fects; (4) externalities associated with population size; and 

(5) political effects of interest groups and municipal bureaucracies that vary with population size. The empirical 

relationship between per capita expenditures and population is, therefore, better termed “returns to population 

size” to distinguish it from returns to production scale or 

the more common usage, “economies of scale.”3 

To estimate the empirical relationship between per 

capita municipal expenditures and population in Allegheny 

County, we specify a reduced-form model including four 

exogenous variables-local personal income per capita 

[Y], intergovernmental aid received per capita [A], the tax 

price paid for services by the median resident [t]‘, and pop- ulation [nJSThe model can be written in constant elasticity form as: 

E/n = bo * ybl * Ab2 * tb3 * nb4, 

where b1 through b4 are elasticities of spending with respect 

to income, aid, tax price, and population, respectively. The 

U.S. Advisory Commission on Intergovernmental Relations 69 
elasticity of spending with respect to a particular independent variable is the percentage change in per capita expenditure associated with a 1 percent change in that variable. 

Income, intergovernmental aid, and tax price are variables commonly associated with demand for public services, while population is commonly associated with 

service cost or supply. In this reduced-form model, obtained by combining multiple equations representing service production, cost, demand, and other factors, the 

elasticities cannot be interpreted directly in supply, demand, or cost terms, but represent their combined effects? Still, those interested in what affects public service 

spending in Allegheny County and, especially, whether 

there are indications of returns to population size, will find 

estimates of the coefficients informative. 

%king logarithms of both sides of the equation and 

adding additional environmental factors to account for 

their effects, if any, on service costs, yields a log-linear es- timating equation: 

log (Eh) = log bo + bl log Y + b2 log A 

+ b3 log t + b4 log n + XbjSj 

where the Sj are the added factors. Conventional expectations for coefficient estimates in a model like this are bl, 

b2 > 0, per capita spending higher as per capita income or 

per capita aid is higher, and b3 c 0, per capita spending 

lower as the tax price paid by residents is higher. It ispossible to develop thcse expectations from economic theory, 

but for our purposes ordinary intuition should suffice. 

Higher income and/or higher per capita intergovernmental aid increase the budget available for purchase of local 

public services, and higher spending should be expected. 

A higher tax price for services reduces demand for them, 

with lower spending expected. 

The expected sign of b4, per capita expenditure elasticity with respect to population size, is ambiguous for reasons noted above. Population size in this model, therefore, 

is treated as an environmental cost factor similar to other 

Sj factors, but without specification of its anticipated relationship to per capita expenditures. If our empirical estimate of b4 turns out to be negative, this would indicate 

increasing returns to population size or-in everyday language-the possibility of reducing expenditures by combining governments and increasing the population served 

by each remaining municipality. If the empirical estimate 

is positive, decreasing returns to population size are indicated-suggesting that combining governments could increase rather than reduce expenditures. 

Expectations for other environmental cost factors, bj, 

j > 4, depend on the particular Sj variables selected for 

inclusion. In the present analysis, five socioeconomic fac- tors are considered-population density, the ratio of employment in a municipality to residential population, 

percentage of housing built before 1940, percentage of 

families living below the poverty level, and percentage 

change in jurisdiction population from 1980 to 1985. Low 

density should be associated with higher expenditures for 

dispersed facilities, transportation, and coordination, while 

high density should be associated with higher expenditures due to crowding effects. A high ratio of employment 

to population indexes a need to provide services for significant numbers of nonresidents and is expected to have a 

positive association with per capita expenditures. Thepercentage of housing built before 1940 is a proxy for deteriorating housing and infrastructure age, and is expected to 

be positively associated with expenditures. The poverty 

variable measures the relative size of a city’s disadvantaged population and also is expected to be associated positively with expenditures. Population growth may require 

increased expenditures to extend services or it may allow 

spreading of service costs across additional residentsmost likelyboth. Per capita expenditures may also be higher (lower) in shrinking (growing) communities if changes 

in service levels lag behind changes in population size. Because of these mued possibilities, no expectation for the 

sign of the population change coefficient is specified. 

In Chapter 4, this model was used to explore whether 

returns to population size (increasing or decreasing) were 

indicated in police and street service expenditures. Here, 

we examine whether returns to population size are indicated across a broader range of “common” service expenditures-common in the sense that most municipalities in 

the county spend significant amounts in the categories included. Common expenditures for this purpose are com- puted by exclusion, calculated as total reported expenditures 

in 1985 minus expenditures for public service enterprises, 

sewer and sanitation services, refuse collection, and fire 

services. Expenditures in these latter categories were excluded because of significant variation in funding. 

Coefficient estimates for the model are listed inTable 

6.1.’ The first column contains elasticity estimates from 

the log-linear model. The second column presents coefficient estimates from a linear-additive, rather than loglinear form of the model. That is, the same variables are 

used for estimating purposes, but without the logarithmic 

transformation of the base model. The coefficients in column two, therefore, are tobe interpreted as partial effects 

rather than elasticities. They represent the dollar change 

in per capita expenditures associated with a one unit 

change in each independent variable, holding the other 

variables constant. 

The coefficient estimates show per capita expenditures for common local services to be positively related to 

income and intergovernmental aid, and negatively related 

to tax price, as anticipated above. These effects are significant both in magnitude and by statistical test in either 

model specification. Among environmental cost factors, 

the ratio of employment to residential population in a municipality has a strong, positive association with per capita 

expenditures in both specifications. Population density, 

percentage of housing built prior to 1940, and percentage 

of the population living in poverty have modest positive 

elasticities, but only the percentage of housing built prior 

to 1940 shows a significant, positive partial effect. Change 

in municipal population from 1980 to 1985 shows no effect 

in the log-linear specification, but has a significant negative partial effect. There is no indication of returns to population size in either equation estimates. Population 

elasticity and partial effects are small and not statistically 

significant. In other words, after accounting for important 

70 U.S. Advisory Commission on Intergovernmental Relations 
Table 6.7 

Per Capita Expenditure Elasticities 

and Partial Coefficients 

for Common local Services 

in Suburban Municipalities', 1985 

Log-Linear Linear 

Elasticities Partials 

Resident Population (1,000s) 

Per Capita Income (1,000s) 

Tax Price 

Per Capita Intergovernmental Aid 

Employment to Population Ratio 

Density (1,000s per square mile) 

Percent of Housing Built 

before 1940 

Percent of Families with Incomes 

below Poverty Level 

Percent Change in Population 

Intercept 

R2 (adjusted) 

1980-85 

0.006 

0.968* 

-0.340* 

(0.26)Z 

(9.79) 

(3.56) 

0.176. 

(3.30) 

0.092+ 

(3.16) 

0.059+ 

(2.28) 

0.003+ 

(2.11) 

0.013' 

(2.40) 

-0.002 

(0.64) 

-2.209 

(1.78) 

0.59 

0.447 

(1.03) 

10.9. 

(9.02) 

-0.028+ 

(2.30) 

0.407' 

(2.10) 

64.9. 

(4.30) 

1.428 

(0.45) 

0.674' 

(2.74) 

0.530 

(0.54) 

-1.090+ 

(1.93) 

8.483 

(0.30) 

0.56 

* 123 suburban municipalities. Common expenditures ex- clude those for public service enterprises, sewers and sani- tation, refuse collection, and fire protection. 

* (t-statistic for parameter estimates) 

Significant at p < .001. 

+ Significant at p < .05. 

factors other than population size, per capita expenditures 

are unrelated to jurisdiction population. 

This finding of .no size effect on local expenditures 

among Allegheny County's municipalities implies that, in 

part because of overlapping structures and the availability 

of services from the county (see Chapters 2 and 4), they do 

not suffer generally from inefficiencies related to size. 

This does not mean that all municipalitiesare equally efficient. Communities of the same size have different per 

capita expenditures, indicative of differences perhaps in 

service preferences but also in efficiency. Our analyses 

demonstrate only that per capita expenditures are not related to jurisdiction size and that the vstem of small mu- nicipalities in the county exhibits neither positive nor 

negative returns to population size. 

Some additional caveats are in order. First, there are 

no indicators of service quality in our analyses. If, for example, service quality increases systematically with the 

number of persons served, then a finding of relativelyconstant per capita expenditure across communities of different population size indicates size economies-quality is 

higher in larger communities while per person expenditure remains the same. The reverse is true if service quality decreases systematically with number of persons 

served. In this latter case, relatively constant per capita expenditures across communities of different population 

size would indicate diseconomies of size, as service quality 

is lower in larger communities for a given per capita expenditure. Without quality indicators, these possibilities 

could not be addressed. 

We should also note that scholars at the Center for 

Public Financial Management at Carnegie Mellon University in Pittsburgh present analytic results at odds with 

those in this section. In a recent paper, they use a curvilinear regression of 1980 municipal expenditures on 1980 

population to estimate the expenditure/population size 

relationship, not accounting for differences in income, tax 

price, intergovernmental aid, or other factors. They report 

returns to population size, with an estimated optimal com- munity size in Allegheny County of approximately 12,000 

residents and estimated savings of 7.45 percent of 1980 ex- penditures had all suburban municipalities been this opti- mal size. Taking into account county topography and the 

possibility of consolidating adjacent municipalities while 

meeting some reasonable socioeconomic criteria, the Carnegie Mellon researchers estimate an optimal configuration of 65 municipalities to have afforded savings of 1.65 

percent of 1980 expenditures? 

The Center's estimation approach differs from ours 

by its failure to include variables associated with service 

demand or supply other than population size. We attempted to replicate their result by adding a curvilinear 

term to our estimating equations, but failed to obtain a 

similar effect. Neither population size nor its square were 

related to per capita expenditures in our models that included income, tax price, intergovernmental aid, and envi- ronmental cost factors. We also attempted but failed to 

replicate the curvilinear relationship using 1985 population and population squared alone to estimate 1985 expenditures. In our estimate, population and population squared 

were related positively to expenditures? We have no explanation for this latter difference from the Center's results.lo 

MUNICIPAL FISCAL VARIATIONS 

Fiscal variations (i.e., significant differences in the 

amounts of revenue raised by different jurisdictions) are 

virtually inevitable in complex local public economies. 

These variations result partially from differences in revenue sources that can be tapped for local purposes, but they 

also reflect differences in costs of public services and the 

willingness of citizens to tax themselves for public service 

provision. Fiscal variations demonstrate inequality-per 

capita amounts of revenue raised are not equal across 

communities. Whether fiscal variations also demonstrate 

inequity requires careful consideration. 

Unequal amounts of public revenues raised by two 

otherwise comparable communities suggest a difference 

in preferences for public services between the two communities. Given the same revenue base and cost of public 

services, a community that raises greater revenues exhibits a stronger preference for services than does its neighbor that raises lesser revenues. If each community had 

access to revenue bases with similar characteristics (e.g., 

resident incomes, taxable property, etc.), the fact that they 

raised different revenues would be no cause for concern. 

U.S. Advisory Commission on Intergovernmental Relations 71 
Table 6.2 

Factors Explaining Variation in Per Capita Own Source Revenues [R,] of Suburban Municipalities’, 1985 

Equation I: Per Capita Income ly,] 

R, = 48.7 + 12.6 * Yp RZ = 0.34 

(2.56) (8.05) 

Equation 11: Per Capita Income BPI and Per Capita Market Value of Nonresidential Property [NR,] 

Ro = 23.6 -k 12.3 * Y, + 7.03 * NR, R’ = 0.47 

(1.34) (8.76) (5.51) 

123 suburban municipalities. Own-source revenues exclude intergovernmental aid and revenues from public service enterprises. 

Figures in parentheses are t-statistics for the regression coefficients. 

Indeed, it could be an advantage because citizens could 

choose between a high tax, high service community and a 

low tax, low service community. 

Just as all individuals or households do not have the 

same incomes, all communities do not have access to comparable revenue bases. Some are home to residents with 

high taxable incomes, others have large amounts of taxable real property. Some have both, some have neither. 

Communities differ on factors that affect the cost of pro- viding public services-large, nonresident working or 

shopping populations, for example-and the revenue 

raised. Communities differ in their citizens’ preferences 

for public services and willingness to pay for them. These 

differences can confound analyses that attempt to link 

revenue bases to revenues actually raised. Still, explora- tion of this linkage and how it relates to other community 

characteristics can be informative. One can ask, for example, whether there are patterns of cumulative advantage 

or disadvantage across communities by analysis of how 

municipal revenues and revenue bases are related to citizen and community characteristics. 

In search of patterns of cumulative advantage or disadvantage, we examine variations in two fiscal indicators. 

The first is per capita own-source revenue of suburban 

municipalities; the second, the percentage of household 

income represented by earned income and real estate 

taxes imposed by municipalities on their residential 

households. We relate variations in each of these indicators to variations in revenue bases available to the municipalities and to additional socioeconomic characteristics. 

Variation in Own-Source Revenues 

Own-source revenues of suburban municipalities in 

1985 ranged from less than $90 per capita in Wall, South 

Versailles, Fawn, Frazer, West Elizabeth, and Forward to 

more than $400 per capita in Thornburg, Fox Chapel, Edgeworth, Rosslyn Farms, Neville, and Sewickley Heights. 

Per capita own-source revenues are associated significant- ly with two indicators of municipal revenue base-per capita income (r = 0.59) and per capita market value of real 

property (r = 0.63).” Given the municipalities’ reliance 

on revenue from the earned income and real estate taxes 

(see Chapter 2), these associations are to be expected. The 

two revenue base indicators are correlated highly across 

the municipalities (r = 0.73), but this correlation masks an 

additional distinction between residential and nonresi- dential property. Per capita market value of residential 

property is correlated so stronglywith per capita income (r 

= 0.90) as to be virtually indistinguishable from it in statistical analyses.” Per capita value of nonresidential proper- ty, on the other hand, is unrelated to per capita income (r 

= 0.04), but is associated significantly with per capita 

own-source revenue (r = 0.38). 

Variation in per capita income across the suburban mu- nicipalities accounts for 34 percent of the variation in their 

own-source per capita revenue wble 6.2, Equation I). This 

represents the direct effect of income on revenue through 

the earned income tax and income’s indirect effects through 

real estate taxes on residential property, other taxes, and 

charges. Adding per capita value of nonresidential property 

to the estimating equation increases the variance explained 

to 47 percent (Equation 11). This latter indicator captures direct revenue effects of real estate taxes on nonresidential 

property and indirect effects from other taxes and charges 

associated with the use of nonresidential property. 

The strength of these two indicators in explaining 

own-source revenues and their statistical independence 

from one another suggest their use to classify suburban 

municipalities. Communities can be categorized as having 

low or high personal income and, separately, as having low 

or high nonresidential property value, based on whether 

their income and property values fall below or above the 

median values for county municipalities. Arraying the two 

categorization schemes orthogonally yields a four-fold 

typology of municipalities: 

Group I: 34 communities with low per capita income 

and low nonresidential property values, home to 

19 percent of the suburban population. 

Group 2: 28 communities with low per capita income 

but high nonresidential property values, with 16 

percent of the suburban population. 

Group 3: 27 communities with high per capita income 

but low nonresidential property values, with 28 

percent of the suburban population. 

Group 4: 34 communities with high income and high 

nonresidential property values, with 37 percent of 

the suburban population. 

The first group of municipalities is disadvantaged with 

72 US. Advisory Commission on Intergovernmental Relations 
Table 6.3 

Average Per Capita Revenues by Source for Suburban Municipalities in Each Revenue Base Group', 1985 

Average Average Average Average 

Group 1 Group 2 Group 3 Group 4 

Total Own Sotrrce 

Per Capita $147 $195 $209 $233 

Standard Deviation (55) (55) (67) (87) 

Per Capita $28 $26 $53 $50 

Standard Deviation (8) (8) (16) (23) 

Eamed Income Tax 

Miscellaneoiw CharPeslOtiier 

Per Capita $42 $59 $43 $58 

Standard Deviation (36) (42) (29) (35) ' 123 suburban municipalities. 

Average Average Average Average 

Group 1 Group 2 Group 3 Group 4 

Real Estate Tax 

$68 $97 $98 $102 

(27) (39) (56) (6 1) 

$8 $14 $15 $22 

(6) (10) (8) (19) 

Total Other Tar 

Iniemovemmental Revenue 

$30 $39 $25 $24 

(18) (29) (21) (6) 

respect to both revenue bases and indeed raises smaller 

revenues, averaging $147 per capita from own sources 

Wble 6.3). The fourth group has advantageous revenue 

bases and raises an average of $233 per capita from own 

sources. Groups 2 and 3 occupy middle grounds, with averages of $196 and $209 per capita, respectively. 

The groups differ in their per capita revenues by major source mble 6.3). Per capita revenues from the real 

estate tax in Group 1 communities average two-thirds of 

those in the other groups, each of which averages about 

$100 per capita. Average revenues from the earned income tax differ across groupson the income dimensionbut 

are not related to presence or absence of nonresidential 

property (Group 3 and Group 4 municipalities had nearly 

twice the per capita revenues from this tax as did those in 

Groups 1 and 2 communities). Average per capita revenues from other taxes are positively related to both income and nonresidential property values. Average per 

capita revenues from charges and miscellaneous sources 

are related somewhat to the value of nonresidential proper- ty, but not, on average, to differences in per capita income. 

Intergovernmental aid revenues per capita tend to be 

slightly higher in lower income communities, but not 

those with the least advantageous revenue bases. Communities in Group 2-where average incomes are low but 

nonresidential property values are high-obtain more intergovernmental aid per capita on average than do their 

less advantaged Group 1 neighbors. This reflects the fact 

that aid is distributed to support infrastructure development and other purposes in addition to redistribution. 

Indicators of community characteristics less directly 

related to community revenue bases show, not surprisingly, substantially weaker associations with per capita 

own-source revenue Fable 6.4). Among the simple correlations, only those with percentage of families living below 

poverty in 1979 (r = -0.21) and ratio of employment to resident population (r = 0.39) are significant statistically or 

substantively. The partial correlation and regression coefTable 6.4 

Relationships of Community Characteristics with Per Capita Own Source Revenues in Suburban Municipalities', 

1985 

Community Revenue Characteristic 

Relationship with Per Caoita Own Source Revenue 

Zero-Orde? Partial3 (t-statistic) 

Correlation Correlation Regression4 Coefficient 

Percent of Families with Incomes below Poverty Level 

Percent Minority Population 0.00 

Percent Population over 65 Years Old 

Density (1,000s per square mile) 

Percent of Housing Owner Occupied 

-ox+ 

0.01 

-0.04 

0.11 

-0.03 

-0.07 

Percent of Housing Built before 1940 

Percent of Housing Built after 1970 

Employment to Population Ratio 0.39* 

123 suburban municipalities. 

* Pearson correlation with per capita own-source revenue. 

0.19+ 

0.21+ 

O.B* 

0.25* 

-0.27* 

0.34* 

-0.34' 

0.28* 

2.51' 

1.43+ 

2S9+ 

4.89+ 

-1.13+ 

0.87' 

-1.79' 

81.0+ 

(2.12) 

(3.20) 

(2.36) 

(2.86) 

(3.08) 

(3.92) 

(3.88) 

(3.13) 

Pearson partial correlation controlling for per capita income and per capita market value of nonresidentii. property. 

Regression coefficient when added to equation including per capita inmme and per capita market value of nonresidential property. 

* Significant at p < .001. 

+ Significant at p < .05. 

US. Advisory Commission on Intergovernmental Relations 73 
ficients-alternative means of attempting to adjust for per 

capita income and nonresidential property value differences-reveal additional statistically significant effects. 

After adjustment for differences in the principal variables affecting own-source revenue-per capita income 

and market value of nonresidential property-per capita 

revenue tended to be higher in communities with greater 

percentages of poor, nonwhite, and elderly residents, 

communities that were more densely populated and had 

older housing stock, and communities that were significant employment centers. Again, after this adjustment, 

per capita own-source revenues were lower in communities with greater percentages of owner-occupied housing 

and newer housing stock. However, all of these relationships are substantively modest and the variables considered add little to our explanation for variations in per 

capita own-source revenue. 

Own-source per capita revenues of suburban municipalities in 1985 were principally a function of two revenue 

base indicators-residents’ per capita income and per capita market value of nonresidential property. As these indicators of revenue base exhibit wide variation across the 

municipalities, so too do the own-source revenues they 

raise. In 1985, intergovernmental aid served to reduce 

overall revenue variation slightly, but left a number of 

communities with per capita revenues well below those of 

their neighbors in the county. Nineteen percent of the 

suburban population resided in 34 communities-identified above as “Group 1”-that had especially low values 

for revenue base indicators, correspondingly low 

own-source revenues, and received about average per capita intergovernmental revenue. If Allegheny Countians or 

citizens of Pennsylvania were to consider this evidence of 

inequity in the county’s fiscal system and chose to remedy 

it by subsidizing Group 1 communities, the cost would not 

be overly high. Additional aid averaging $57 per capita targeted to Group 1 communities would have been required 

in 1985 to bring their total per capita revenues up to the 

average in Groups 2 and 3. In total, this would have cost 

$10.5 million, an increase of 36 percent in overall intergovernmental aid to county suburbs, or about 5.5 percent of 

own-source revenues of the suburban municipalities. 

Variation in Household lax Costs 

The two principal municipal taxes raised directly from 

households in Allegheny County are the earned income 

tax and the real estate tax on residential property (see 

Chapter 2). All municipalities in Allegheny County impose an earned income tax, which is collected from residents of a community regardless of where their incomes 

are earned. Dividing total earned income tax revenues of a 

municipality by the number of households it contains 

yields an estimate of the cost to an average household rev- enue from this tax.13 

The highest estimated per household cost from the 

earned income tax in 1985 was $446 in Fox Chapel. Other 

communities with high per household costs from this 

tax-over $300-included Thornburg, Ohara, Upper St. 

Clair, Sewickley Heights, and Pittsburgh. Residents of 

each of these communities except Pittsburgh had incomes 

in 1985 substantially above the county average, and this is 

reflected in their high per household earnings tax costs. 

Pittsburgh’s high per household cost results from its significantly higher earned income tax rate-a factor that 

also explains in part the higher costs estimated for Ohara 

and Upper St. Clair. 

Communities with low estimated costs per household 

from the earned income tax are the Mon Valley communities of Homestead, Rankin, Duquesne, Clairton, and 

Braddock-each of which raised less than $40 per household from this source in 1985. The lowest was that of 

Homestead, $26 per household. 

The real estate tax is collected from residential and 

nonresidential property. To estimate the per household 

cost of the real estate tax for an average household in each 

community, the community’s revenue from the real estate 

tax was first multiplied by the proportion of its assessed 

valuation which is residential, and then divided by the 

number of households in the community.14 

The highest estimated per household costs from the 

residential real estate tax-more than $500-were in Ben 

Avon Heights, Fox Chapel, Rosslyn Farms, Thornburg, 

Edgeworth, and Sewickley Heights (highest at $1,003 per 

household). The lowest per household costs from real estate taxes-less than $70-were in Sewickley Hills (lowest 

at $39), Forward, Haysville, Liberty, Plum, and Braddock. 

An estimate of the dollar cost paid directly in municipal taxes by an average household in each community may 

be made by adding the average household cost of the 

earned income tax to the average household cost of the 

real estate tax.ls To increase comparability across municipalities, household costs were adjusted upward to include 

the cost of trash collection where this appeared not to be a 

tax supported service.16 

The lowest estimated total costs per residential 

household for earned income, real estate taxes, and trash 

collection and disposal-less than $150-were in Haysville, Braddock, Forward, Wall, Liberty, West Elizabeth, 

and East Pittsburgh. The highest total costs per household-greater than $1,000-were in Rosslyn Farms, Edgeworth, Thornburg, Fox Chapel, and Sewickley Heights. 

Pittsburgh’s total cost per average household of $630 was 

among the highest in the county. In addition to the five 

communitics listed above, only two other municipalities 

had computed total costs higher than Pittsburgh. 

Household Cost Burdens 

With the exception of Pittsburgh, estimated per 

household dollar costs from the earned income and real 

estate taxes and trash charges were roughly proportional 

to average household income.” This indicates that, across 

suburban municipalities, household tax and trash costs are 

neither progressive (imposing higher rates on the wealthy) 

nor regressive (higher rates on the poor). The data do not 

allow us to examine the possibility of progressive or regressive tax and cost structures within municipalities. 

A variable perhaps more relevant for assessing relative advantage and disadvantage than the estimated dollar 

cost paid by an average household is the percentage of 

household income required to pay that estimated cost. For 

ease of reference, we call this percentage the household 

74 US. Advisory Commission on Intergovernmental Relations 
Table 6.5 

Relationships of Community Characteristics with Household Cost Burdens in Suburban Municipalities', 1985. 

Community Revenue Characteristic 

Percent of Families with Incomes below Poverty Level 

Percent Minority Population 

Percent Population over 65 Years Old 

Density (1,000s per square mile) 

Percent of Housing Owner Occupied 

Percent of Housing Built before 1940 

Percent of Housing Built after 1970 

Employment to Population Ratio 

Per Capita Value of Nonresidential Property 

Per Capita Intergovernmental Aid 

Relationshb with Household Cost Burden 

Zero-Ordes Partial3 (t-statistic) 

Correlation Correlation Regression4 Coefficient 

-0.02 

0.04 

0.22' 

0.30* 

-0.10 

0.29* 

-OM* 

-0.06 

-0.19' 

0.26' 

0.04 

0.04 

0.24' 

0.34' 

-0.15' 

0.34* 

-0.43* 

-0.06 

-0.19' 

0.26' 

123 suburban municipalities. 

Pearson correlation with household cost burden (percent of household income). 

Pearson partial correlation controlling for average household income. 

Regression coefficient when added to equation including average household income. 

* Significant at p < .001. 

+ Significant at p < .05. 

0.002 

0.001 

0.005' 

0.027* 

0.003 

0.004* 

-0.009* 

-0.045 

-0.011' 

0.003' 

(0.47) 

(0.49) 

(2.10) 

(3.92) 

(1.69) 

(3.95) 

(5.28) 

(0.66) 

(2.12) 

(3.03) 

cost burden. By this measure, the highest household burdens were in Pittsburgh (2.5 percent of average household 

income) and McKeesport (1.75 percent), followed by West 

Homestead, Rosslyn Farms, Heidelberg, Osborne, Edgewood, and Pennsbury Village, all over 1.4 percent. The 

lowest cost burdens-less than 0.7 percent-were in 

Bradford Woods, Haysville, Aleppo, Pine, Sewickley 

Hills, East Pittsburgh, Forward, Braddock, and Marshall. 

High burdens were found in both upper and lower income 

communities, as were low burdens. 

The average household cost burden in the suburban 

county in 1985 was 0.98 percent of household income, and 

nearly 80 percent of the suburban population resided in 

communities with cost burdens between 0.7 and 1.1 percent.'* About 21 percent of the suburban population resided in communities with burdens above this range, and 2 

percent in communities with burdens below it. 

Household cost burdens were related to some municipal socioeconomic characteristics and not to others Wble 

6.5). Neither the percentage of families living below the 

poverty level nor the percentage of residents who were 

nonwhite showed any relationship to cost burdens. Burdens were higher in communities with higher percentages 

of elderly residents, older housing stock, and that were 

more densely populated. Burdens tended to be lower 

where housing stock and, most likely, infrastructure were 

newer and where a larger percentage of residents owned 

their own homes. The ratio of employment to population 

was unrelated to household cost burdens, but those communities with higher per capita market values of nonresidential property tended to have somewhat lower burdens, 

suggesting that they may be able to shift some costs away 

from residential households. 

Intergovernmental aid in 1985 was targeted to some 

extent on communities with relatively higher household 

burdens. Percentage burden and total aid per capita correlated at a modest level of 0.26. The 31 municipalities with 

burdens in excess of 1.1 percent of average household income received an average of $42 in state-federal nonhighway aid and $16 in county aid per household, while the 9 

communities with burdens less than 0.7 percent of income 

received an average of $31 per household in state-federal 

nonhighway aid and no aid from the county. 

Patterned Inequalities? 

Variation in per capita own-source revenue was found 

to be closely related to variation in per capita income and 

per capita market value of nonresidential property in suburban municipalities. Municipalities that had either residents with higher incomes or higher value nonresidential 

property, or both, raised greater own-source revenues 

than did municipalities with smaller values for these revenue bases. Variation in the dollar cost imposed on residential households was found to be even more closely related 

to variation in income. Municipalities whose residents had 

higher incomes collected more revenue from the earned 

income tax, the residential real estate tax, or both. 

Variation in both fiscal indicators exhibits income 

neutrality. Communities whose residents have higher incomes have access to greater own-source revenues, but 

their residents contribute larger amounts to those 

own-source revenues. The system is one of "market equity" in this sense. Taxable nonresidential property is unrelated to residents' incomes, although it contributes 

significantly to own-source revenues and is related to lower costs for residential households. Low-income and 

high-income communities alike benefit fiscally from taxable nonresidential property. 

Patterns of fiscal variation with other community attributes, controlling for income and nonresidential property 

differences across communities, indicate that poor and minority populations are slightly advantaged-per capita 

U.S. Advisory Commission on Intergovernmental Relations 75 
own-source revenues are related positively to the percentage of poor and minority residents in a community, but 

household cost burdens are not. Communities with older 

housing stock, that are more densely populated, and that 

have a higher percentage of elderly residents are somewhat disadvantaged. Their per capita own-source revenues tend to be a bit higher than predicted by resident 

incomes and nonresidential property, but so too are 

household cost burdens. Their higher revenues presumably derive from the higher burdens paid by residential 

households, and probably reflect at least in part higher 

service costs. Conversely, communities with newer housing stock and a higher percentage of owner-occupied 

housing tend to have lower per capita own-source revenues than predicted by income and nonresidential property, but also to have lower household cost burdens. These 

patterns may reflect lower service costs and/or stronger 

resistance by homeowners to costs imposed on residential 

households. 

None of the fiscal patterning with socioeconomicvariables other than income is particularly strong. The only 

significant “patterned inequality” is that communities 

whose residents have higher incomes tend to have greater 

own-source revenues to spend for services. The communities most disadvantaged by this patterning are those identified earlier in “Group 1”-communities that combine 

low resident personal income with small nonresidential 

property bases. The intergovernmental aid system in the 

county does not reduce their disadvantage by much. To do 

so, aid would have to be increased by more than $10 million-a 36 percent increase, with that increase targeted on 

group one communities. 

Pittsburgh: A Special Case 

Pittsburgh is among the most advantaged communities in terms of per capita own-source revenues. Only Sewickley Heights and Neville Township scored higher on 

this indicator in 1985. But the estimated per household 

cost burden in Pittsburgh, 2.5 percent of average household income, is substantially higher than that found in any 

suburban municipality. It cannot be determined from this 

analysis why this burden is so high. One part of the explanation may be that the city is permitted to tax real property 

at different rates for buildings and land, thus enhancing its 

ability to export a larger portion of its real estate tax collections than accounted for by the estimate. Pittsburgh included 43 percent of the market value of nonresidential 

property countywide in 1985, also suggesting a high export 

potential. To the extent that this is true, our estimate of 

Pittsburgh’s household cost burden from the real estate 

tax is overstated. Even with a reduced estimate for its real 

estate burden, however, its total household burden would 

remain high due to its high earned income tax rate. Because all the municipalities in the county impose earned 

income taxes, Pittsburgh cannot tax directly the earnings 

of nonresident workers, relying instead on the occupational 

privilege tax of $10 per worker as its only direct tax on nonresidents employed in the city.19 

One factor that may help to account for Pittsburgh’s 

high household burden is the added per resident cost for 

public services that results from its status as the major employment, shopping, and entertainment center of the 

county. With just under 30 percent of the county population in 1985, employment in Pittsburgh was roughly half the 

county total. Pittsburgh employs substantially more police 

personnel per resident than do most county municipalities, 

and has one of the few full-time paid fire departments. In 

addition, salaries and fringe benefits for public employees in 

Pittsburgh, although not the highest in the county, are in the 

upper range. The city’s large number of public employees, 

combined with their relatively high salaries and fringe benefits, makes delivery of basic public services relatively more 

expensive in per resident terms. In 1985, the city’s expenditures for general administrative services were 63 percent of 

the county total, 44 percent for police, 75 percent for fire services, and 43 percent for streets and highways. Pittsburgh 

also has access to extraordinary revenue sources that may 

help compensate for (or perhaps even stimulate) its high setvice expenditures. Its Act 511 revenues other than the 

earned income tax were $49 million in 1985,W percent of the 

municipal total from these taxes. Much of that $49 million 

must result from taxes paid by nonresidents. Real estate revenues were $93 million, more than half of the county total. 

More than half of real estate revenue came from nonresidential property, and much of the tax on nonresidential 

property is almost certainly exported to nonresidents. 

The city received two-thirds of the state and federal 

nonhighway aid distributed in the county in 1985. Its aid 

revenue of roughly $330 per household contrasts sharply 

with the average in the suburban county of $39 per household, an advantage of 8.5 to 1. Average households in 

Pittsburgh pay a higher percentage of their incomes in 

taxes than do average households in the suburban county, 

but revenues from nonresident sources are markedly 

higher in Pittsburgh as well. Thus, Pittsburgh’s status as 

the county’s central city is unlikely to be the principal explanation for its high household burden. It is certainly true 

that the city and its residents would be much worse off fiscally if it were not for the large number of nonresidents 

who are employed there and who use Pittsburgh’s shopping, entertainment, and other facilities. 

What may be a more significant factor is the wider 

array of public services provided by Pittsburgh. The city’s 

library expenditures in 1985 were 56 percent of the total 

spent by all municipalities; parks and recreation, 68 percent; and health, more than 80 percent. 

It may also be that Pittsburgh suffers to some extent 

from diseconomies of size, incurring extra costs because of 

its large public bureaucracies. There are several municipalities in Allegheny County that have higher ratios of employment to resident population than Pittsburgh,*’ yet all 

of their residential tax burdens are substantially lower. 

This suggests that Pittsburgh’s status as a major employment 

center alone cannot explain its high household burden. 

VARIATION IN PER-PUPIL SCHOOL REVENUES 

There was much less variance in school district revenues in 1984-85 than in municipal revenues. The South 

Park district had the lowest revenues per average daily 

membership (ADM), $3,105 per ADM.*’ Pittsburgh had 

76 U.S. Advisory Commission on Intergovernmental Relations 
Table 6.6 School 

Revenue Variations in Allegheny County 

Percent of Average 

Daily Membership 

(ADMI 

City of Pittsburgh 23.5% 

County Districts 76.5 

Number of Districts 

Eleven Lowest in Revenues per ADM 25.2 

Next Ten 24.3 

Next Eleven 25.0 

Ten Highest in Revenues per ADM 25.5 

Percent 

of Total Revenues Average Revenues 

per ADM per ADM 

69.9 $4,221 

Variations in County Districts 

21.2 $3,559 

23.4 $4,072 

26.2 $4,434 

29.1 $4,807 

30.1% $5,939 

Range of 

Revenues 

- 

$3,105-$5,175 

$3,105-$3,770 

$3,816-$4,345 

$4,361-$4,5 12 

$4,528-$5,175 

the highest revenues per ADM at $5,939. This yields a ra- tio of 1.9 to 1 between the highest and lowest per ADM 

revenues, contrastingwith a ratio of 10.2 to 1 for municipal 

per capita revenues. 

Bble 6.6 summarizes variation in revenues per ADM 

among county school districts. The Pittsburgh school dis- trict is better funded than any other district in the county. 

Its revenues per ADM are about 40 percent higher than 

the average in suburban districts, and 15 percent higher 

than the best funded suburban district, Fox Chapel Area. 

Among school districts outside Pittsburgh, the range 

of variation in revenues per ADM is from $3,105 in South 

Park to $5,175 in Fox Chapel Area. When grouped into 

quartiles on the basis of average daily membership, the 11 

districts with the lowest revenues receive about threequarters as much revenue as the ten districts with the 

highest revenues. 

Total suburban school district revenue per ADM and 

revenue per ADM raised locally are both linked tightly to 

the market value of real property per ADM (r = 0.82 for 

total revenue and r = 0.92 for revenue raised locally). 

These linkages of revenue with property value in suburban school districts are much stronger than similar linkages in suburban municipalities (see above). Variation 

in market value of real property per ADM across subur- ban districts explains 84 percent of the variation in their 

local revenues per ADM.22 

Median household income in each district is also re- lated to suburban school's local revenue per ADM (see 

nble 6.7), but the relationship is much weaker than 

among municipalities and becomes insignificant once vari- ation in property values is ~ontrolled.~~ Other district 

characteristics related to local revenues per ADM are the 

percentage of families with incomes below the poverty 

level and the percentage of minority residents in the district. Both characteristics are negatively related to district 

revenues (and to one another with r = 0.75), but as the 

partial correlations and regression coefficients show, the 

negative relationship is explained by poor and minority 

residents in districts where property values are lower. Af- ter adjustment for property value differences, the per- centage of residents who are elderly is related positively to 

local revenues per ADM. 

The simple correlations of aid from federal and state 

sources with local revenues per ADM indicate compensatory funding-suburban districts raising lower amounts of 

revenue locally receive higher amounts of aid. The federal 

aid correlation becomes insignificant once property value 

Table 6.7 

Relationships of Suburban School District Characteristics with Local School Revenues per Average Daily Membership,' 

1985 

Community Revenue Characteristic 

RelationshiD with Per CaDita chvn Source Revenue 

Zero-Ordes partial3 (t-statistic) 

Correlation Correlation Regression4 Coeficient 

Median Household Income 0.34' 0.03 1.90 (0.19) 

Percent of Families with Incomes below Poverty Level -0.42' 0.04 3.48 (0.26) 

Percent Minority Population -0.26 0.04 1.67 (0.27) 

Percent Population over 65 Years Old 0.08 0.32' 21.4' (2.10) 

Federal Aid per ADM -0.36' 0.16 0.92 (0.98) 

State Aid per ADM -0.83' -0.35' -0.70' (2.35) 

42 suburban school districts. 

Pearson correlation with local revenue per ADM. 

Pearson partial correlation controlling for market value of real property per ADM. 

Regression coefficient when added to equation including market value of real property per ADM. 

* Significant at p < .001. 

+ Significant at p < .05. 

U.S. Advisory Commission on Intergovernmental Relations 77 
variation is controlled, but the state aid relationship does 

not. State aid to school districts flows more toward those 

raising smaller local revenues even after control for their 

local property base. Federal and state aid per ADM to the 

Pittsburgh district is substantially higher than the suburban 

average-$329 versus $78 per ADM from federal sources, 

and $1,962 versus $1,165 per ADM from state sources. 

METROPOLITAN PROBLEM SOLVING: 

ECONOMIC DEVELOPMENT ISSUES 

Metropolitan problem solving is often viewed as difficult in jurisdictionally fragmented areas. One such problem is economic development, which has been on the 

agenda of decisionmakers at all levels in Allegheny County 

for many years. The approach to economic problems in this 

jurisdictionally fragmented area, therefore, is instructive. 

In recent years, Allegheny County, like the rest of 

Southwestern Pennsylvania, has been undergoing dramatic 

economic change. The county and the region’s economic 

base and employment in heavy manufacturing-principaincipally ~ ~ ~I 

p--ry metks-has declin& significanly, while employment in the service sector, especially corporate services, 

has exhibited significant gr0wth.2~ This restructuring of 

the local economy has caused serious fiscal distress in 

many municipalities, especially in the mill towns of the 

Man Valley, the Youghiogheny, and lhrtle Creek. At the 

same time, communities in other parts of the county have 

seen growth in high technology and service employment. 

The county and region have not developed a single, comprehensive approach to this restructuring. Rather, several 

local initiatives are under way, networked in ways consistent with the “partnership approach” that characterizes 

metropolitan problem solving in the area.25 

In 1981, the Allegheny Conference on Community 

Development formed an Economic Development Committee “. . . to develop a unified economic strategy backed 

by broad consensus: not a ‘quick fix’ or an attempt to pose 

simplistic answers for current problems, but a forward-looking strategy that could position this region 

strongly for the remainder of the century, and lay a foundation for the next.’’26 The Committee “. . . articulated a 

strategy based on the principles of balanced growth, a 

long-term perspective, reliance upon the marketplace 

with a supportive role for government, and coordination 

of separate efforts rather than central planning.”*’ It recommended ten initiatives-among them efforts to enhance the growth of high technology, focus resources on 

emerging companies, provide export trade assistance, increase tourism, and support job training programs. 

A second step was Strategy 21, a proposal developed 

in 1985 by a consortium of officials from Pittsburgh, Allegheny County, and the county’s two major universities, 

Pittsburgh and Carnegie Mellon. The proposal requested 

funding from the state for airport modernization, advanced biotechnology and manufacturing centers to be 

built by the universities, and transportation improvements 

in the Mon Valley and across the southern part of the 

county.z8 Many of the proposed projects are under way, 

with some lag in transportation improvements. 

In 1986, the Allegheny County commissioners 

created the Mon Valley Commission, which developed a 

set of “Priority Actions” to revitalize this former center of 

the steel industry.% In 1988, the Regional/Urban Design 

Assistance Team convened a multidisciplinary group from 

the Mon Valley area and other regions confronting similar 

problems.30 

Many different proposals and initiatives have 

emerged from these and related efforts aimed at improving the county’s economy. Some are well under way, while 

others remain in the planning stage, and still others have 

been superseded. Although significant economic restructuring has taken place, it is premature to evaluate the success of the county’s efforts. 

What is most interesting from the perspective of this 

study is the philosophy of local governance that informed 

these efforts. Those working to improve the economy of 

Allegheny County appear to take for granted the continuation of the county’s jurisdictional structure, including its 

many relatively small municipalities. Rather than seeing a 

reduction in jurisdictional fragmentation as a necessary 

yrecursor to economic chane and imp$ovement, existinq 

municipalities are seen as potential contributors to their 

own betterment. Opportunities for functional cooperation, 

coordination, and even consolidation are identified and recommended, but these recommendations show respect for 

the local base afforded by long-standing communities, and 

seek to build on thisbase through wrdhated effects orga- nized by councils of governments and other consortia. 

The operative approach to metropolitan problemsolving in Allegheny County is “partnership” between adjacent communities confronting similar problems, between the public and private sectors, and between 

municipalities and overlying governmental and quasi- governmental bodies. It is a prescription that respects citizens’ attachments to their local communities, while 

drawing attention to prospects for cooperative ventures to 

resolve selected problems of broader scale. 

SUMMARY 

The analyses of fiscal relationships among Allegheny 

County municipalities and school districts provide insights 

into the efficiency and equity of the jurisdictionally fragmented system. 

1) The analysis of returns to population size yielded 

no evidence of a relationship between per capita 

service costs and jurisdictional population. This 

finding, we believe, is a result of the quite significant array of finctional coordination, cooperation, and consolidation found in the county. 

Groups of municipalities have joined together to 

arrange production of service components 

through a variety of functional overlays, while retaining jurisdictional autonomy. The finding of no 

returns to population size is not evidence that all 

municipalities are equally efficient or that efforts 

to enhance functional ties and overlays are not 

needed, but it does indicate that the sysfem of 

fragmented jurisdictions does not engender substantial inefficiency. 

78 U.S. Advisory Commission on Intergovernmental Relations 
2) The analyses of fiscal distributions found a strong 

relationship between resident income and municipal own-source revenues. While this relationship is consistent with a standard of “market 

equity,” it is a disadvantage for some low income 

communities that do not have access to otherrevenue sources, especially taxable nonresidential 

property. Older, more densely populated communities, too, appear somewhat disadvantaged by 

the county’s fiscal system. A further indication of 

potential fiscal disadvantage is the significantly 

higher cost burden on residential households in 

Pittsburgh compared to suburban municipalities. 

This is true in spite of the extraordinary revenues 

accruing to Pittsburgh by virtue of its large nonresident employment and itscentral city shopping 

and entertainment locus. Pittsburgh’s higher burdens result in part from differences in the selvices it 

provides and the ways services are financed, and 

may reflect size diseconomies, although this could 

not be verified by the empirical analysis. 

3) Patterned inequalities also were found among 

suburban school districts in the county, resulting 

from the strong linkage between revenues available to a district and the market value of real 

property. Resident income, poverty status, and 

racial characteristics are correlated with property 

values in suburban districts, so revenues per average daily membership are lower in districts with 

larger poor and minority populations. State and 

federal efforts to equalize school revenues have 

not been fully successful in the suburban county-state aid is much better targeted to low revenue districts than is federal aid. Students in 

Pittsburgh are relatively advantaged compared to 

students in other districts where advantage is indexed by revenues per average daily membership 

and aid from state and federal sources. 

4) Allegheny County’s approach to metropolitan 

economic development problem solving emphasizes partnership among a wide variety of stakeholders, including the many local governments. 

This approach differs from those that place a 

priority on reducing the number of jurisdiction^.^^ 

In Allegheny County, consortia of local jurisdictions, operating through COGS and other collaborative ventures, are expected to play important 

roles in economic restructuring, especially in the 

most distressed areas. How these efforts develop, 

and with what success, are important topics for 

future research. 

Notes 

See, for example, Committee for Economic Development, Reshaping Government in Metropolitart Areas (New York, 1970). 

* See William E Fox, Jerome M. Stam, W. Maureen Godsey, and 

Susan D. Brown, Economies of Size in Local Government: An 

Annotated Bibliogmpl;ry, Rural Development Research Report 

No. 9 (Washington, DC: US. Department of Agriculture, Emnomics, Statistics, and Cooperative Services, 1979); Robin Barlow, “City Population and Per Capita City Government 

Expenditures,” Research in Population Economics 4 (1982): 

49-82; and Werner Z. Hirsch, Urban Econonlics (New York 

Macmillan Publishing Company, 1984). 

See John Yinger, “On Fiscal Disparities across Cities,”Joumal 

of Urban Economics 19 (May 1986): 316-337, especially 322. A 

variant, “returns to population scale,” is used by William 

David Duncombe in Evaluation of Factors Affecting the Cost of 

Public Services with an Application for Fire Pmtection, Ph.D. 

Dissertation, Syracuse University, 1989. 

Tax price for each community is computed by dividing the esti- mated median value of ownersccupied housing by the market 

value of all real property per household. 

Input factor costs, often included in a model of this form, are 

not included here. We assume that Allegheny County approxi- mates a single market for input factors and, therefore, that fac- tor costs are approximately constant countywide. 

For an example of how a reduced-form model of this type is 

obtained, see Barlow, pp. 71-76. ’ The model is estimated with data from 123 suburban munici- palities. Six suburban municipalities are excluded from the 

analyses of suburban fiscal patterns. McDonald and Trafford 

have only a small portion of their populations residing in Al- legheny County; Neville Township is a predominantly indus- trial island; and residents of Edgeworth, Fox Chapel, and 

Sewickley Heights have per capita incomes so high as to make 

their experience atypical. Data for all analyses can be found in 

the Appendix. 

Malachy Carey, Ashok Srinivasan, and Robert P. Strauss, “Op- timal Consolidation of Municipalities: An Analysis of Alterna- tive Designs” (Pittsburgh: Center for Public Financial 

Management, Carnegie Mellon University, August 3, 1989). 

The OLS estimate for this model is: 

EXP = 51,124 + 157 * POP + 2.06E-4 * POP’, 

with an adjusted R2 of 0.84. Only the POP coefficient is signifi- cant. Its t-statistic is 9.7, while the t-statistics for the intercept 

and population squared are approximately 0.5. 

lo A second paper from the Center reports substantial cost sav- ings that might be available to several small communities in 

the Steel Valley COG if they were to consolidate with their 

neighbors, and suggests this to be evidence of “potential econ- omies of scale for small jurisdictions” more generally. See Bev- erly S. Bunch and Robert P. Strauss, “Consolidation of Small 

Governments: Can It Help Distressed Municipalities?” (Pitts- burgh: Center for Public Financial Management, Carnegie 

Mellon University, January 29, 1990). Their results are based 

on detailed analysis and forecasting of revenues and expendi- tures of nine municipalities, and indicates that seven of the 

nine could benefit from consolidation-two would be made 

worse off. We were unable to conduct similar analyses for all 

county municipalities and, thus, cannot relate our statistical re- sults to the results reported in their paper. 

l1 Market value of real property is that established by the state 

Tax Equalization Board and represents a uniform measure of 

taxable valuation. 

12Per capita income [Y] explains 80 percent of the variance 

across municipalities in per capita residential property value 

[R]. The OLS equation linking the two variables is: 

The t-statistics for the intercept and slope terms are 6.2 and 

27.2, respectively. 

l3 These earned income burden estimates assume that all house- holds in a given community pay the tax. Actually, municipali- ties are authorized to exempt persons earning less than $5,000 

from the tax. It was not possible to determine which municipalR = 4.7 + 1.39*Y 

U.S. Advisory Commission on Intergovernmental Relations 79 
ities allowed this exemption. Where it is allowed, the burden 

on households actually paying the earned income tax would be 

higher than the estimates used here. 

l4 This method yields per household cost estimates that may be 

higher than actual costs in municipalities where a significant 

portion of residential property is owned by nonresident landlords. If they are not able to include the full tax cost as a part of 

their rents, then the cost estimate for residential households 

made here should be reduced by the amount these nonresidents pay. No data were available to make such a correction, 

but we believe its effect would be small for most communities. 

Katherine L Bradbury and Helen E Ladd estimate that 

roughly 15 percent of property taxes on multifamily rental 

properties are paid by nonresident landlords in large Amencan cities-“Changes in the Revenue Raising Capacity of US. 

Cities, 1970-82,” New England Economic Review (MarcNApnl 

1985): 20-37. No comparable estimates are available for small 

municipalities. 

This estimate understates households’ tax costs somewhat by 

not including per household estimates for the variety of additional taxes levied by county municipalities (see Chapter 2). 

The incidence of these additional taxes-in particular the extent to which they are paid directly by households-could not 

be determined from the data available to us. For most municipalities, however, the dollar amounts raised by these additional taxes are small, and their inclusion would not change our 

estimates significantly. 

l6 Fifty-nine communities with significant expenditures for trash 

collection and disposal in 1985 reported no revenues for this 

service, indicating that it was paid for with tax revenues. No adjustment in per household dollar cost was made for these com- munities. Another 30 communities reported significant 

revenues for this service, indicating that the municipality col- lected a fee or service charge for collection and disposal. For 

these, per household trash revenues were added to the dollar 

cost computed for taxes. It was assumed that trash collection 

and dispaal in communities that reported neither expenditures nor revenues for this service was arranged by households 

using private haulers. In the absence of actual cost data, it was 

assumed that fees charged by private haulers were roughly 

comparable to the average charged by municipalities, and this 

amount ($16.50 per capita) was added to household tax costs. 

l7 The correlation between dollar cost and average household income in suburban municipalities was 0.82. Regressing esti- mated dollar cost [DC] on average household income [AHI] 

yielded the equation: 

with t-statistics of 1.00 and 15.9 for the regression coefficients 

and two-thirds of the variance in estimated dollar mts across 

the municipalities explained. 

Note that these data reflect 1985 burdens on residentialptvpeity 

only. A recent report of burdens in communities in the Steel 

Valley COG reported significantly higher total burdens, but 

did not distinguish between residential and nonresidential 

property. An important point made in that report, however, is 

that burdens, undoubtedly including residential burdens, have 

increased since 1985 as communities have increased tax rates 

and obtained court-approved excess levies. See Robert I! 

DC = -22.0 + 0.0105 * AH1 

Strauss and Beverly S. Bunch, The Fiscal Position ofMunicipa1- 

ities in the Steel Valley Council of Governments (Pittsburgh 

Center for Public Financial Management, Carnegie Mellon 

University, 1987), pp. 22-23. 

l9 Several persons interviewed for this research stated that the 

difference in earnings tax rate between Pittsburgh and its suburbs has contributed significantly to Pittsburgh’s population 

loss in recent years, as city residents relocate to reduce their 

earnings tax burden. 

2o Neville Township, Green Tree, East Pittsburgh, Harmar, Letsdale, Homestead, Collier, and Ohara all had ratios in 1985 that 

exceeded Pittsburgh’s 0.79 persons employed per resident. 

21 Average daily membership is a formula-based measure of 

school district enrollment (see Chapter 5). 

22 The OLS estimate for the relationship is: 

$LOC/ADM = 587 + 21.2 * $MKT/ADM 

with market value measured in thousands of dollars. The tstatistic for the intercept is 3.50 and for the slope, 14.6, both 

statistically significant with 42 observations. 

23 Median household income in 1979 is used here, rather than 

1985 per capita income used in the analysis of municipal ownsource revenues. The latter was unavailable for school districts. Use of 1979 income with 1984-85 revenues partially 

explains the weaker relationship. The correlation of median 

household income with market value of real property per 

ADM is 0.36. 

24 Ralph L Bangs, “Restructuring of the Regional Economy. 

1983-1987,” in Ralph L Bangs and Vijai F! Singh, eds., The 

State of the Region: Economic, Demographic and Social Trends 

in Southwestern Pennsylvania (Pittsburgh: University of Pittsburgh, Center for Social and Urban Research, 1988), pp. 1-17, 

and Table 1-3, p. 107. 

25 Roger S. Ahlbrandt, Jr., “Regional Responses to Structural 

Change,” in Bangs and Singh, pp. 29-53. This section draws 

heavily on Ahlbrandt’s account. 

2b James E. Lee and Konrad M. Weis, A Stmtegy for Growth: An 

Economic Development Pmgram for the Pittsburgh Region 

(Pittsburgh: Allegheny Conference on Community Develop 

ment, 1984), p. 2. Quoted in Ahlbrandt, p. 30. 

City of Pittsburgh, County of Allegheny, University of Pitts- burgh, and Carnegie Mellon University, Strategy 21: Pit& 

bu~gh/Aileglieny County Economic Development Strategy to 

Begin the 21st Century (Pittsburgh: Office of the Mayor, 1985). 

29 Mon Valley Commission, Report to the Allegheny Coirrity Board 

of Comrnissio~iers fortlie Economic Revitalization of the Moilongaliela, Yoiigliioglieny, and lirrtle Creek Valleys (Pittsburgh, 

1987). 

30 Regional/Urban Design Assistance Team, Remaking the Monongaliela Valley (Pittsburgh: American Institute ofArchitects, 

31 Contrast, for example, the recommendations for governmen- tal consolidation to foster economic development cited in 

ACIRs study of St. Louis, Metropolitan Organization: 77ie St. 

Loiris Case. 

27 Ahlbrandt, p. 31. 

1988). 

80 US. Advisory Commission on Intergovernmental Relations 
Chapter 7 

Governing a Metropolitan County 

The jurisdictional fragmentation of Allegheny 

County is both long standing and, for large American 

counties, record setting. Most of the county’s 130 munici- palities were established by World War I. For a time, the 

city of Pittsburgh was able to expand unilaterally, and it ab- sorbed the community of Allegheny over the objections of 

residents. Eventually, however, the rules governing con- solidation of municipalities disallowed further expansion 

without the consent of the affected citizenry. As the Bureau of the Census counts governmental units, Allegheny 

is the most fragmented of the counties in the United 

States with more than a million population. Allegheny 

County has four cities, 84 boroughs, 42 townships, 43 

school districts plus two intermediate education units, and 

149 municipal authorities. This does not include the 

county’s estimated 250 volunteer fire companies, eight 

councils of governments or nine education “jointures” 

that provide for special and vocational-technical education. If a high “density” of governmental units per person 

is thought to equate with a jurisdictional “jungle” or 

“thicket” through which citizens wander in a vain search 

for local services, Allegheny County should be marked 

with huge signs warning away unsuspecting visitors-and 

potential residents. 

Jurisdictional fragmentation, however, does not necessarily lead to functional fragmentation. A metropolitan 

area is fragmented jurisdictionally to the extent that it 

contains numerous independent political jurisdictions. It 

is fragmented functionally to the extent that integral governmental functions and services are uncoordinated. 

Newcomers to Allegheny County need not fear that they 

are entering a land where local government has spun out 

of control. To the contrary, there is a wide range of options 

among diversely governed local communities, knit together in various ways that make for discernible patterns of 

metropolitan organization. 

A focus on jurisdictional fragmentation implies that 

the appropriate model for understanding local government organization is the single city. As Daniel J. Elazar 

points out, however, “the metropolitan area is far from being a single city. Rather it is increasinglybecoming a large, 

relatively low density urban region concentrated around 

several commercial, industrial, and cultural nodes, divided politically to give expression to diverse interests and 

groups.” He continues: 

The organization of government in . , . metropolitan regions cannot be based upon the single 

city model. Rather, it must be based on an understanding of what is appropriately local within the 

region and what requires regionwide treatment. 

In those fields requiring regionwide treatment, 

the question must then be asked, how is that 

treatment thus provided? By some multipurpose 

governmental unit? By a congeries of single purpose units, each with boundaries tailored to its 

particular “service-shed” under local control? By 

similar congeries of state-sponsored governmental units or agencies functioning as arms of the 

state government? Or by a division of areawide 

responsibilities among existing local units on a 

contractual basis? 

There is no single answer to be found to this 

question suitable for all or even a majority of metropolitan regions. Rather, each must develop its 

own answer in light of its own situation.’ 

Clearly, metropolitan areas need to be understood in 

much different terms than single cities. The purpose of 

this chapter is to review, and within limits evaluate, the 

patterns of metropolitan organization and governance 

that characterize Allegheny County. 

FU N CTI 0 N AL PAT1 ER N S 

0 F M ETROPO 1 I TAN 0 RC A N I ZATl 0 N 

The term “metropolitan” as used here refers not to a 

comprehensive metropolitan government, which does not 

exist in Allegheny County, but to structures of organization and governance that embrace multiple local governments. Metropolitan governance in this sense is 

intergovernmental and multigovernmental. Rather than 

being imposed from above, it emerges out of processes of 

interaction among local citizens and officials as they address specific problems. Capabilities for collective action 

are created and used at different scales-as broad and formal as the Commonwealth of Pcnnsylvania and as small 

and informal as a volunteer fire company. The working relationships of metropolitan organization cross jurisdictional 

boundaries, linking small units with one another and with 

larger, overlying units, and formal institutions of government with informal community associations. 

The following functional patterns are identified and 

discussed below: 

A metropolitan legal framework or a body of rules ~OVerning the formation and the powers of local government that applies countywide. 

A heavy reliance on communiv-based organization, 

reflected outside Pittsburgh in a large number of 

U.S. Advisory Commission on Intergovernmental Relations 81 
small municipalities with numerous elected officials and volunteer fire companies, and inside Pittsburgh by a multitude of neighborhood associations. 

An overlying county government that functions as an 

“umbrella,” never as the “ground-level” jurisdiction*Two intermediate units Serve much the Same 

function in public education. 

of the boards of school directors. Still fresh in the minds of 

citizens are the school district consolidations mandated by 

the state legislature in the late 1960s. 

A key feature of the legal framework that applies to 

Allegheny County is uniform statewide legislation for 

classes of local governments. This means that the powers 

of the state legislature are used to discriminate among local governments as townships, boroughs, and cities of vaMultiple ties and overlays that connect jurisdictions, 

both vertically and horizontally. Voluntary councils of governments and jointures in the case of 

school districts produce direct and indirect services and coordinate selected activities among 

primary jurisdictions. Municipal authorities also 

serve as a mechanism for joint production. Contractual arrangements with public and private 

vendors separate provision from production in selected service components. 

A Metropolitan Legal Framework 

Metropolitan governance depends on a common legal 

framework that establishes the terms and conditions under which various local government units can be formed 

and modified, and operate in relation to one another.2The 

rules for the legal framework-here termed a “local government constitution”-constitute the first level of metropolitan governance. Without an ability to make rules 

that apply across governmental units, the constitution of a 

metropolitan area could accurately be described as Balkanized. Moreover, the nature of the legal framework is a 

basic factor influencing the character of governance that 

emerges in a metropolitan area. 

Municipalities and school districts are the primary local 

jurisdictions in Pennsylvania. Rules bearing on their formation and modification govern the entry and exit of basic provision units into the local public economy. Rules that specify 

local government powers determine the range of intergovernmental actions. Fiscal rules, in particular, often attempt 

to take into account potential interdependencies among local governments. Adding to or subtracting from the powers 

of local governments, or classes of local governments, often 

has implications for metropolitan relationships. 

The body of rules governing the formation and modification of local governments in Pennsylvania was described in Chapter 3. Because townships have municipal 

status and Allegheny County is entirely incorporated, 

rules for the formation of local governments are mainly of 

historic interest, but they do explain the number and variety of municipalities. It is the ability of communities to 

keep their local governments-or to modify them as they 

see fit-that commands greater attention today. The 1968 

Pennsylvania Constitution extended home rule to all municipalities that choose to frame and adopt a charter. 

Municipal consolidation is also firmly in the hands of 

citizens. The only procedure available is the initiative and 

referendum, requiring concurrent majorities in the affected municipalities. The General Assembly is free to 

prescribe different rules to govern consolidation, but has 

not chosen to do so since the adoption of the 1968 constiI tution. School districts can be consolidated by agreementrying population, but not to discriminate on the basis of 

their location in a particular metropolitan county. Although Allegheny County is the only county of its class, 

the municipalities within its borders are treated like other 

municipalities of the same class across the state (Pittsburgh is the only city in its class). Whether, under the 

Pennsylvania Constitution, it would be feasible to do 

otherwise is unclear. Perhaps the legislature could distinguish townships, boroughs, third class cities, and home 

rule municipalities within a second class county as separate subclasses. The existing legislative practice, however, 

is to consider only statewide legislation. 

Sometimes, statewide rules can have a differential or 

a heightened impact in a large metropolitan area. Perhaps 

even more salient than the local metropolitan impact of 

statewide changes, however, is the incapacity they create 

for adjusting relationships selectively. Metropolitan problem solving often may depend on changing the basic rules. 

An inability to adjust those rules reduces the level of local 

investment in metropolitan decisionmaking. The Allegheny 

League of Municipalities, while it represents all local governments, including the county government, cannot build 

a countywide consensus for changes specific to Allegheny 

because the necessary state legislation is not available. 

The league’s legislative program consists entirely of efforts to modify the state code as it affects municipalities 

across the state. 

The state constitution and laws supply the legal 

framework that affords local communities of varying geographical dimensions a range of organizational options. 

The framework is also one that has not been adjusted to 

the particular circumstances of Allegheny County. At the 

level of basic rules, metropolitan governance in Allegheny 

County is driven by statewide perspectives and concerns. 

Com m u n ity- Based Organization 

The citizens of Allegheny County have chosen to rely 

on forms of organization that are closely tied to geographic communities, most of which have deep historical roots3 

This is most readily apparent in the large number of small 

municipalities outside Pittsburgh and in the volunteer fire 

companies that serve nearly all of these municipalities. The 

rules of municipal incorporation outside Pittsburgh allow for 

the greatest and most explicit reliance on community-based 

organization. Even within Pittsburgh, however, citizens tend 

to identlfy strongly with historic neighborhoods and to sustain active neighborhood organizations. The suburban school 

districts, despite forced consolidations, also retain strong 

community identification. Using the powers available to 

them, citizens seem to have maximized their reliance on 

community-based organizations to serve, where possble, as 

the primary units of local government. 

82 U.S. Advisory Commission on Intergovernmental Relations 
Community-based organizations cannot, acting 

alone, solve all the problems that beset a metropolitan 

area. They can, nevertheless, provide an important base 

on which other, more encompassing, efforts can bc built. 

For example, as this study was in progress, nearly every 

municipality in Allegheny County was struggling with increased costs of solid-waste collection. Various responses 

were under consideration, including in some cases an imposition of user fees. Other municipalities were thinking 

about service modifications, such as moving from 

back-door to curbside collection. One small borough in 

the Mon Valley developed an in-house collection service 

in the face of escalating prices charged by contract vendors. The corollary of community-based organization is 

community responsibility and self-reliance- the recognition that to some significant extent communities must 

solve their own problems. 

An Overlying County Government 

The fundamental importance of an overlying 

county government is readily apparent in Allegheny 

C~unty.~ The county is not a metropolitan government, 

able to treat other units as subordinates. The county 

government is best understood as a broader, not a higher government. By virtue of full municipal incorporation, the county government is exclusively an overlying 

unit, never the primary jurisdiction. This allows the 

county government to concentrate on issues that transcend municipal boundaries. 

The county government is concerned primarily with 

the delivery of state-mandated services (this report is 

not centrally concerned with the important role of 

county government as an administrative unit of the 

state). As a local jurisdiction, the county government 

takes on five basic roles: 

m 

The provision of certain countywide services, 

such as an arterial highway network and a county 

park system. 

Provision and production of service components 

that benefit from economies of scale or 

broad-based coordination, such as police and fire 

training, the investigation of serious crimes, and 

forensic analyses. 

Planning, information gathering, and facilitating 

coordination, including an important problem-solving component for problems that spill 

over municipal boundaries. 

Funding for innovative municipal initiatives and 

ventures that take on an interlocal character. 

The provision of back-up services to municipalities or councils of governments, as needed. 

Each role depends on cooperation with individual 

municipalities or associations of municipalities. Frequently, the county government is an important element in a 

broad metropolitan effort, one that includes foundations, 

universities, and major employers. Sometimes, a county 

official functions as a public entrepreneur who brings together interested parties, collects and distributes information, negotiates agreements, and follows up with 

implementation. Other times, county officials participate as 

members of organizational networks initiated elsewhere. 

Multiple Ties and Overlays 

In between the 130 municipalities and 43 school districts in Allegheny County, and the single overlying 

county government, there are numerous interorganizational ties and multiorganizational overlays. The most visible are eight councils of governments and, in public 

education, two intermediate units. Both within and outside these organizational umbrellas can be found other bilateral and multilateral arrangements-including school 

jointures and consortia, mutual aid agreements, and intergovernmental contracts. 

Councils of Governments 

Unlike bilateral or multilateral cooperative efforts 

limited to particular functions, a multifunctional COG 

creates a new source of public entrepreneurship? A COG 

executive director has incentives to look for ways to serve 

member municipalities and to find common ground for 

cooperation. Several of Allegheny County’s COGs are 

slowly expanding their fee-for-service role, particularly 

’Thrtle Creek Valley and Twin Rivers. The voluntary nature of COGs equips them for this task. Instead of planning in the abstract what functions might be performed 

more efficiently on a larger scale, a COG approaches this 

question on an incremental basis. Only to the extent that 

cost savings and/or productivity improvements are demonstrated will municipalities tend to participate. In this 

way, a transfer of functions to COGs is likely to generate 

benefits that exceed costs. 

COGs also potentially decrease the transaction costs 

of coordination by bringing municipal representatives together on a regular basis and, by creating a small set of 

similar organizations countywide, create more favorable 

conditions for the diffusion of innovations. The payoff 

from this sort of investment is long term. Current efforts 

to create new forms of intergovernmental cooperation in 

street maintenance and solid waste disposal, and efforts at 

the diffusion of previous innovations will determine 

whether the COGS can have a general, positive effect 

throughout the county. 

The COGS serve as a useful organizational link between county government and more than 100 small municipalities. Clearly, the county government faces a problem in 

being able to communicate effectively with the municipal 

governments. COGS substitute in part for an expanded 

county-municipal liaison agency. Some of the COGs (to a 

certain extent all of them) emphasize grantsmanship. From 

this perspective, the COGs serve a useful “middleman” 

function. Much of this role is also absohed with the distribution of knowledge and information, whether by word of 

mouth, memoranda, or seminars and workshops. 

In conjunction with the county government, the eight 

COGs also contribute to countywide coordination and problem solving. As a production unit, a COG tends to serve a 

U.S. Advisory Commission on Intergovernmental Relations 83 
wider clientele than its own membership. Many COG projects and innovations, such as the anticipated solid waste disposal site being developed by Char-West COG, have 

countywide implications. Thus, the COGs, by linking a large 

number of small municipalities with the county government, 

seme as vehicles for metropolitan problem solving. 

It is also possible to overestimate the importance of 

the COGs to the development of intergovernmental 

cooperation. Many cooperative ventures preceded the 

formation of the COGs, such as the joint purchasingcouncil now operated by SHACOG, and new forms of cooperation still are being developed. COGs are useful, or 

convenient, but they are neither a necessary nor sufficient 

condition for cooperative ventures. Sixteen municipalities 

in the county-among them Pittsburgh-do not participate in COGs. Often, all members do not participate in all 

COG activities. The existence of a COG is not a substitute 

for the entrepreneurial initiative and cooperation of local 

government officials and citizens. 

There is a question as to how well the COGs will be 

able to survive the gradual erosion of federal support for 

local governments. Much of the work of COGs has been 

absorbed in the administration of the Community Development Block Grant (CDBG) program. Some part of the 

interest of county government in the COGs also derives 

from the need to implement the county’s portion of 

CDBG through many municipalities. There seems to be 

some tendency, moreover, to replace professionals with 

nonprofessionals when vacancies occur in COG executive 

directorships. This does not always lead to a decline in 

entrepreneurial initiative or in effectiveness. In general, 

the COGs seem to be adapting to the new, more stringent 

financial environment by becoming more self-reliant and 

developing new service capabilities. 

In sum, the COGs clearly make a positive contribution to the development of the local public economy in Al- legheny County. They have increased the potential for 

public entrepreneurship and decreased the costs of coordination, both among municipalities and between municipalities and the county government. Moreover, they have 

done so at remarkably low cost to taxpayers. 

Intermediate Units, Jointures, and Consortia 

An intermediate unit (IU) is more like a county government-indeed IUs replaced county boards of education-than like a COG, although 1Us are governed by 

representatives of the member units rather than by separately elected officials.6 Still, IUs do not exist at the pleasure 

of their members, but at the discretion of the General Assembly. The Allegheny Intermediate Unit (MU), which 

covers the suburban districts outside Pittsburgh, fils a role 

analogous to county government in relation to school districts, producing certain areawide services and auxiliary service components, engaging in planning and information 

gathering, and assisting school districts in various ways. Jointures, on the other hand, are more like COGs, particularly in 

the case of the single multifunctional jointure in the North 

Hills. Created and governed by member districts, jointures 

produce vocational-technical education and build and maintain facilities for special education services produced by MU. 

I 

FUN CTI ONAL EVALUATI 0 N 

This study relies mainly on process rather than performance criteria to evaluate metropolitan functional arrangements. The criteria identify key processes that link 

structures of governance with performance-self-determination and citizen choice, representation and accountability, public entrepreneurship, coordination, and metropolitan 

problem solving. Each of these criteria is discussed below. 

Self-Determination and Citizen Choice 

The commitment to local self-determination in Al- legheny County is so strong that “metropolitanism” is 

nearly taboo as a subject for public discussion. The basic 

rules of association in Pennsylvania-those bearing on incorporation, annexation, and consolidation-generally 

rely on local self-determination and are presently determined by the state constitution. The General Assembly, 

however, has the authority to substitute itsown rules. Historically, important breaches of the principle of self-determination have occurred in the development of the region. 

Pittsburgh was built on nonconsensual mergers with adjoining municipalities. The sharp reduction in the number 

of school districts in the late 1960s and early 1970s was dictated by state authorities. Most recently, a federal court ordered a suburban school consolidation in order to promote 

racial integration. Despite their strong attachments to their 

communities, Allegheny County residents continue to be ex- posed to the possibility of legal mandates that would impose 

new jurisdictional arrangements without local consent. 

The home rule capabilities created by the 1968 Pennsylvania Constitution are potentially an important enhancement of local self-determination and citizen choice. 

Historically, Pennsylvania has not relied heavily on the initiative and referendum. The principal forms of local government-boroughs and second class townships-were 

fashioned by state law rather than by local choice. Any municipality is now free to adopt a home rule charter and thus 

to create its own form of government. Even if local officials are reluctant to consider basic changes, the initiative 

power creates a potential for change over the long term. 

As a political community, Allegheny County seems to 

be strongly committed to local self-determination. The 

county government, in particular, has not pursued initiatives 

that would rob municipalities of any of their basic prerogatives. Instead, county agencies, such as the Department of 

Development and Department of Maintenance, participate 

with municipalities as initiators or partners in a range of improvement efforts. There seems to be a common recognition 

that continued improvement in public services depends 

more on sustained cooperation than preemptive leadership. 

As a result, municipal officials are not required continually 

to defend their independent authority. 

Representation and Accountability 

The large number of locally elected municipal officials, coupled with relatively small jurisdictions outside 

Pittsburgh, would appear to enhance the representation 

of citizen interests. Besides the formal apparatus of elections, heavy reliance on citizen volunteers-especially in 

fire protection-may have a constraining effect on the 

84 U.S. Advisory Commission on Intergovernmental Relations 
conduct of municipal government. Volunteer fire fighters 

tend to be politically active and influential in their communities. Other community organizations become involved in the support of volunteer fire companies. An 

infrastructure of community-based organizations has 

been understood since Alexis de Tocqueville’ to strengthen local governance and increase community well-being. 

As the research on this project progressed, the role of 

the borough mayor in local representation and accountability emerged as something of a puzzle. As explained in 

Chapter 2, the mayor has little political power but is the 

most visible local official, who regularly attends the meetings and gatherings of community organizations. The mayor might be viewed as an important link between borough 

hall and the citizens. Unlike council members (including 

the usually powerful council president), the mayor ordinarily has an office at the borough hall. Although political 

leadership commonly resides with the council president, 

greater community prestige attaches to being mayor. 

Is it possible that the position of borough mayor tends to 

insulate the council and its president from criticism? Do local citizens blame the mayor when things go wrong even 

though the mayor may have little responsibility for policy or 

administration? Or are council members attentive to expressions of concern by the mayor because he is perceived as one 

who is in touch with the community, not to mention well regarded? In the latter case, a mayor could have considerable 

influence on some occasions without overtly exercising political power. The scope of this research was sufficient to raise, 

but not to answer, these questions. Whether the position of 

borough mayor contributes to or detracts from citizen representation and accountability is, nevertheless, an interesting 

puzzle that merits further research. 

Another caveat on citizen representation and accountability concerns procedures for excess property tax 

levies. If a municipality, other than one of the home rule 

municipalities, reaches its statutory rate limit, it is allowed 

to levy in excess of the limit only by securing judicial determination of need, not electoral authorization. Presumably, 

expenditures in excess of revenues constitutes a need. If ex- cess levies had to be approved by citizens voting in a referendum, greater pressure might be exerted on elected officials 

to find ways of saving money when the budget is tight. Fiscal 

controls, such as citizen referenda, have been found to be 

positively associated with the use of efficiency enhancing 

mechanisms, such as contracting for services.8 

Service contracts are relatively uncommon in Allegheny County (see Chapter 4), suggesting that local 

officials in some of the smaller municipalities may not 

be as hard pressed to search out more efficient ways of 

producing services, Connecting the lack of direct citizen 

control over tax rates with the low level of municipal 

service contracting, however, is purely speculative with 

respect to Allegheny County. 

Competition 

Competition among service producers is presumed to 

be beneficial, giving provision units more alternatives and 

coaxing better and more efficient efforts from producers. 

Relatively little competition exists in Allegheny County 

because there is little contracting for service production. 

The tendency of municipalities to produce direct services 

in-house inhibits the development of competitive alternatives. The separation of provision and production, noted 

as a basic feature of metropolitan organization in St. Louis 

County, is observed only among the very smallest units in 

Allegheny County, where municipalities turn to in-house 

production at a low size threshold. 

Coordination, Metropolitan Problem Solving, 

and Public Entrepreneurship 

These three criteria have a strong interrelationship in 

Allegheny County. Intergovernmental coordination and 

problem solving derive from a process of public 

entrepreneurship, which when successful may produce results equivalent to more formal coordination and/or problem solving. The structure of Allegheny County affords 

many opportunities for ongoing public entrepreneurship, 

both in county government and among local communities. 

The basic patterns of public entrepreneurship in Allegheny County link those in county government with 

those in municipalities and COGS, and municipal entrepreneurs join with their counterparts in neighboring communities. Sources of entrepreneurship in county 

government include officers in the Department of Development, the Authority for Improvements in Municipalities, the Department of Planning, and the Department of 

Maintenance. With the encouragement of the board of 

county commissioners, individuals in these departments 

have established working relationships with local officials 

throughout the county. Their entrepreneurship is frequently matched by that of COG directors. Municipal officials and managers also pursue initiatives in relation to 

nearby communities, sometimes under the auspices of a 

COG. Municipal cooperation does not necessarily depend 

on the efforts of overlying organizations, but can and does 

emerge from the initiative of individual municipalities. 

In public education, the Allegheny Intermediate Unit 

(NU) is a source of entrepreneurship in the development of 

functional consortia among school districts. Other consortia 

have been formed, however, at the initiative of district superintendents and, in the case of the Mon Valley Education 

Consortium, at the initiative of a private citizen. School district jointures, organized initially to provide for vocational 

and/or special education, also have begun to display 

entrepreneurial capabilities, organizing such joint ventures 

as alternative schools and a substitute teacher pool. 

Substantial interlocal coordination is found in all four 

service areas-police, fire, streets, and education-investigated in this study. Coordination, like entrepreneurship, 

involves both overlapping and nonoverlapping jurisdictions. County government agencies and joint production 

units formed among municipalities contribute to the coordination of service production-for example, when municipal police patrol local streets but respond to calls 

through a joint dispatch center that serves several municipalities and rely on county police for investigative services. 

Or when a school district operates a school for students, 

including some who need special education services, but 

relies on the Allegheny Intermediate Unit to supply a speU.S. Advisory Commission on Intergovernmental Relations 85 
cia1 education teacher, the delivery of the service depends 

on coordination. For the most part, coordination becomes 

routine once the arrangements have been established. 

Parallel to coordination is “alternation,” dividing service production responsibilities for different segments of a 

shared jurisdiction. Alternation is a substitute for coordination, for example, when county police take responsibility for traffic patrol on county roads, as well as patrolling 

county parks, while municipal police assume all other patrol responsibilities. The municipal and county police 

avoid duplication of effort by alternating between different parts of their common jurisdiction. More coordination 

is apparent in police and fire services than in streets, 

where there is greater alternation among state, county? 

and municipal producers. By and large, the county Department of Maintenance maintains county roads and municipal street departments maintain municipal streets. 

Yet, some of the more innovative and highly coordinated 

arrangements are being developed in street services. Even 

where basic responsibilities are divided on the principle of 

alternation, specific projects may require coordination. 

Many local government observers in Allegheny 

County report that cooperation is difficult to attain, largely because of political jealousies in different local jurisdic- tions and a lack of trust among communities. This 

perception exists alongside widespread patterns of cooperation in the functions studied for this report. 

It may be that local observers are referring to failures 

in cooperation for functions not examined in this study, or 

to unwillingness to enter into full functional consolidation 

of services, rather than unwillingness to cooperate in other forms. Clearly, local officials resist full functional consoli- dation of service production, just as they resist jurisdictional 

consolidation that would merge provision units. 

Local officials also tend to be somewhat skeptical of 

the net benefits claimed for more limited joint ventures, 

but many have entered into a variety of interlocalcooperative arrangements. A skeptical attitude-having to be 

shown-can be defended as a responsible orientation to 

the public’s business if the skeptic can be satisfied by a reasonable argument supported by evidence. 

The high level of public entrepreneurship observed in 

both county and municipal governments for the services 

examined in this report is associated with ongoing joint ef- forts to solve problems. The most visible effort is the mobili- zation of local talent to address the economic problemsfaced 

by communities in the Mon Valley. Far from being ignored in 

their plight, Mon Valley municipalities find that they have to 

choose among competing joint ventures and sponsors. In 

another effort, the county planning department is spear- heading the formation of a storm water drainage district 

among municipalities in the North County. West of Pittsburgh, an intergovernmental body has been created to ad- dress issues of development surrounding the Pittsburgh 

International Purport. Both the drainage district and air- port-area venture involved county initiatives undertaken in 

collaboration with COGS and local municipalities. 

County government entrepreneurship tends not to be 

preemptive of local responsibilities. Municipalities re- main basically self-reliant even as they act jointly with 

county government. In the Mon Valley, state and county’ 

agencies are searching for ways to assist local municipali- ties without displacing them. Community self-reliance 

also depends on local entrepreneurship. The Mon Valley 

borough of Braddock, for example, experienced a period 

of poor management in addition to economic decline, 

leading eventually to an application for state designation 

as a distressed community. The initiative for dealing with 

the local crisis, however, came from within the borough, 

where voters elected a new council pledged to address the 

community’s fiscal troubles. Even as limited forms of as- sistance are made available, the primary responsibility for 

solving the problems rests with the borough. Indeed, out- side assistance is likely to be contingent on a demonstrated 

willingness in the local community to face up to problems. 

Allegheny County government and Pittsburgh city 

government enjoy a relationship that is mainly comple- mentary rather than competitive. Visitors who amve at 

the Pittsburgh International Airport are greeted by huge 

signs erected by the county commissioners proclaiming 

that Pittsburgh is the “most livable” city in America. Pitts- burgh and Allegheny County officials participated side by 

side in the extensive public-private partnerships that or- chestrated the well-known “Pittsburgh Renaissance.” Be- cause the jurisdiction of Allegheny County overlies 

Pittsburgh, in contrast to the nonoverlapping jurisdictions 

of St. Louis City and St. Louis County, county officials 

have an incentive to contribute to development in the 

Pittsburgh Triangle, rather than seeking to attract reve- nue-generating businesses to the suburbs. The result is a 

more balanced approach to economic development 

throughout the metropolitan area. 

One puzzle that remains unsolved is the fiscal relation- ship between Pittsburgh and the suburban municipalities. 

Pittsburgh’s extraordinarily large daytime population 

undoubtedly creates service demands that Pittsburgh 

residents largely must shoulder. Of course, high-value 

property in the Triangle owes its value in great part to its 

ability to attract workers, shoppers, concert-goers, and 

sports enthusiasts from throughout the area. High-value commercial property is generally thought to be a 

profit maker for cities, generating revenues that exceed 

expenditures. Yet, Pittsburgh residents have relatively 

large tax burdens (see Chapter 6), encouraging the 

movement of residents to the suburbs. 

F I SCAL EVA LU AT I ON 

In addition to the process criteria discussed above, 

this study used two criteria based on fiscal relationships: 

production efficiency and fiscal equity. Two of the most 

common criticisms of jurisdictionally fragmented metro- politan areas are that (1) numerous small local govern- ments are inefficient due to their inability to capture 

economies of scale and (2) fragmentation of the tax base 

leads to a mismatch of resources and needs among local 

jurisdictions. The results of the fiscal analysis, described in 

detail in Chapter 6 (portions of the analysis are also found 

in Chapters 4 and S), are summarized here, together witha 

discussion of policy implications. 

Production Efficiency 

Relatively little evidence was found of uncaptured returns to population size in the production of services by 

86 US. Advisory Commission on intergovernmental Relations 
municipalities and school districts. Controlling for service 

conditions, total expenditures per capita (per student in 

the case of school districts) are not related to size of populations served. This finding also holds for separate analyses of police, street, and education services. 

A lack of systematic evidence pointing to uncaptured 

returns to population size does not prove that there are no 

economies remaining to be captured. It does establish, 

however, that relatively small production units are not 

necessarily inefficient for many service components, and 

that many in fact are relatively efficient, enough so that 

there is no significant statistical association between size 

of population served and per capita spending. Numerous 

opportunities may remain to improve the efficiency of service production in Allegheny County, and some of these 

opportunities may entail the consolidation of production 

units. Across-the-board consolidation of municipalities or 

school districts, however, is unlikely to improve efficiency. 

Instead, the method most likely to do so is to extend the 

basic approach already used in Allegheny County: to en- courage public entrepreneurs to seek out new arrangements for producing selected service components that are 

likely to exhibit limited economies of scale. 

Equity 

The most serious apparent inequity among taxpayers 

in Allegheny County is the relatively heavy tax burden 

shouldered by residents of Pittsburgh, related in part to 

the city’s larger daytime population. In municipal jurisdictions outside Pittsburgh, tax burdens are roughly proportional to income. Fiscal relationships, indexed by the real 

estate and earned income tax burdens on average households in each community, slightly favor jurisdictions with 

newer, owner-occupied housing over more densely populated jurisdictions with older housing stock and elderly 

residents. Overall, the fragmentation that is reflected in 

the large number of suburban municipalities in the county 

is not associated with significant inequities, using income 

neutrality as an indicator of distributional equity. 

Fiscal disparity, defined as a mismatch of resources 

and problems, is a somewhat different matter. Some mu- nicipalities and school districts in the county are seriously 

distressed. Pennsylvania law allows the designation of municipalities and school districts as distressed communities, 

facilitating their financial assistance and recovery contin- gent on local initiative in addressing problems. Allegheny 

County government provides both financial and in-kind 

aid, preserving local self-reliance while making available 

some resources from the wider state and region. 

In public education, the mismatch of resources and 

problems is most apparent for a few small suburban school 

districts with large proportions of students in poverty. The 

Pittsburgh school district does not face a similar disparity, 

due in part to state aid formulas that favor urban districts. 

Poverty and the attendant educational problems are not 

confined to central cities, and school districts outside 

Pittsburgh with high poverty rates are arguably the most 

seriously disadvvtaged in the metropolitan area. 

SUMMARY 

Academic and professional literature in public administration, political science, planning, and public finance is 

filled with standard descriptions of metropolitan areas 

that almost invariably cite an assortment of problems said 

to derive from fragmentation. Allegheny County fits part 

of the standard description: it contains a large number of 

small, independent, often overlapping jurisdictions. Al- legheny County also has problems, but they are not nearly 

as severe, or as endemic, as the literature on metropolitan 

areas would lead one to expect. Some of the problems 

widely thought to be inherent in metropolitan fragmentation are not found at all. 

Little evidence was found to indicate that the county’s 

collection of boroughs, townships, and third class cities are 

too small to arrange for and efficiently produce traditional 

police, fire, street, and school services to citizens. Neither is 

there evidence of destructive intergovernmental conflict. 

With few exceptions, fragmentation outside Pittsburgh does 

not generate systematic inequities among taxpayers. The 

major outlier in an analysis of fiscal equity is Pittsburgh, 

Some problems exist because of effects that spill over municipal borders-drainage problems in the North Hills, airport 

development problems in the western county, economic development problems in the Mon Valley. All of these problems, however, are being vigorously addressed. 

A major reason why jurisdictional fragmentation does 

not create insuperable barriers to coordination and prob- lem solving in Allegheny County is the availability of the 

county government as an overlying jurisdiction. Because 

the county is fully incorporated, the jurisdiction of the 

county government is exclusively an overlay, a complementary rather than competitive political jurisdiction. 

County officials are free to concentrate their energies on 

providing and producing a limited number of services and 

otherwise relating in productive ways to municipal governments. Considerable attention has been given to addressing problems that spill over municipal borders and to 

assisting distressed communities. 

Still, citizens and local government officials in Al- legheny County face a number of challenges that will continue to test their ability to adapt to change and to develop 

new patterns of organization and governance. Some of these 

challenges require at least a countywide perspective and may 

involve changes in state legislation (e.g., possible inequities 

in state school aid formulas). Others depend on developing 

new structures for municipal cooperation (e.g., to plan for 

recycling or to secure limited economies of scale in public 

works maintenance). Communities in the Mon Valley will 

continue to exhibit signs of distress as they struggle to cope 

with economic decline. In the case of municipalities and 

school districts that have become seriously distressed fmlly, 

a key challenge is to learn to help such communities without 

displacing community initiative and self-reliance. 

Throughout urban and metropolitan America, one 

basic challenge is to foster and maintain active and effec- tive communities with sufficient social capital to solve 

problems. The distinction between provision and production can aid in this process. Communities can continue to 

function as effective provision units, even while employing production units that are connected to borough or 

township hall by a contractual relationship. Good local 

government provides for its community, but does not nec- essarily produce all its services in-house. The organizational challenge is to build multilevel approaches to 

service provision and production that enable communities 

U.S. Advisory Commission on Intergovernmental Relations 87 
to make effective choices, as well as to draw on the re- sources of a wider region when pressed by circumstances 

beyond their control. 

The most prominent organizational features of Allegheny County are not functional fragmentation, inef- ficiency, and inequity, but public entrepreneurship, 

community-based organization and voluntarism, and in- tergovernmental problem solving. By extending these patterns of organization to new problems and opportunities 

as they arise, Allegheny County can continue to build a 

productive local public economy. 

Notes 

I 

' Daniel J. Elazar, Building Cities in America: UrSanizution and 

Suburbanization in a Frontiersociety (Philadelphia: Temple University, Center for the Study of Federalism, 1987) pp. 219-220. 

Chapter 3 provides a detailed description of the legal frame- work for local government in Allegheny County. 

Chapter 2 provides a more detailed description of municipal 

governments. Volunteer fire companies are discussed in Chap- ter 4, and school districts in Chapter 5. 

Chapters 2 and 3 describe Allegheny County government further. 

Councils of governments are described further in Chapter 2. 

'See Chapter 5 for a fuller description of cooperative arrange- ments in education. 

'See Alexis de Tqueville, Democmcy in America. 

See U.S. Advisory Commission on Intergovernmental Rela- tions, The Olganization of Local Public Economies (Washing- ton, DC, 1987), Chapter 2. 

88 U.S. Advisory Commission on Intergovernmental Relations 
Data and Data Sources 

The data used for the analyses in Chapters 4 and 6 of 

this report are listed in Tables A-1 through A-4 of this appendix. Sources used are as follows: 

Population Estimates (1 980 and 1984), 

Per Capita Income (1 985), and land Area 

Diskette User’s Data Express, DUDES 1 and 3, obtained from the Pennsylvania State Data Center, The 

Pennsylvania State University at Harrisburg, The Capitol 

College, Middletown, PA 17057. 

Population and Housing Characteristics 

(1 979 and 1980) 

U.S. Bureau of the Census, 1980 Census of Population and Housing, Summary Tape File 3A (Pennsylvania), 

1982. 

Extract of data for Allegheny County prepared by the 

Pennsylvania State Data Center, The Pennsylvania State 

University at Harrisburg, The Capitol College, Middletown, PA 17057. 

Revenue and Ex enditure Data for 1985, 

Market Value o P Property in 1985 

Preliminary tabulations of 1985 local government financial statistics for Allegheny County, obtained from the 

Municipal Statistics and Records Division, Bureau of Local Government Services, Department of Community Affairs, Commonwealth of Pennsylvania, Harrisburg, PA 

17120. These data should be used with caution, as explained in Note 18 to Chapter 4. The per capita figuresare 

computed using 1984 population estimates (see above). 

Percent ResidentiaVNon-Residential (1 986) 

Community Profiles for Municipalities in Allegheny 

County, prepared from data for 1986 supplied by the Department of Planning, Allegheny County, by the Pennsylvania Economy League, Inc., Western Division, Two 

Gateway Center, Pittsburgh, PA. Per capita data are computed using 1984 population estimates (see above). 

Population, Number of Households, 

and Employment Estimates (1 985) 

Cycle 4 estimates produced by the Southwestern 

Pennsylvania Regional Planning Commission, 200 First 

Avenue Pittsburgh, PA. 

Household Burdens from Real Estate Tax, 

Earned Income Tax, and Waste Collection and Disposal 

Computed using data from sources above; see Chapter 6 for details. 

U.S. Advisory Commission on Intergovernmental Relations 89 
Table A-1 

Population, Households, Land Area, Income, and Poverty Data 

Land 

Po~ulation Households Area 

Municipality (1980) (1984) (1985) 

Pittsburgh 423,959 

Third Class Cities 

Clairton 12,188 

Duquesne 10,094 

Boroughs 

Aspinwall 3,284 

Avalon 6,243 

Baldwin 24,714 

Bell Acres 1,307 

Ben Avon 2,3 14 

Ben Avon Heights I 398 

Blawnox 

Brackenridge 

Braddock 

Braddock Hills 

Brentwood 

Bridgeville 

Carnegie 

Castle Shannon 

Chalfant 

Cheswick 

Churchill 

Coraopolis 

Crafton 

Dormont 

Dravosburg 

East McKeesport 

East Pittsburgh 

Edgewood 

Edgeworth 

Elizabeth 

Emsworth 

Etna 

Forest Hills 

Fox Chapel 

Franklin Park 

Glassport 

Glenfield 

Haysvile 

Heidelberg 

Homestead 

Ingram 

Jefferson 

Leetsdale 

Lincoln 

McKees Rocks 

Millvale 

Mt Oliver 

Munhall 

North Braddock 

Oakdale 

Oakmont 

Liberty 

1,653 

4,297 

5,634 

2,556 

11,859 

6,154 

10,099 

10,164 

1,119 

2,336 

4,285 

7,308 

7,623 

11,275 

2,511 

2,940 

2,493 

4,382 

1,738 

1,892 

3,074 

4,534 

8,198 

5,049 

6,135 

6,242 

246 

117 

1,606 

5,092 

4,346 

8,643 

1,604 

3,112 

1,428 

8,742 

4,772 

4,576 

14,535 

8,711 

1,955 

7.039 ,- 

Osborne 529 

Pennsbury Village 798 

Pitcairn 4,175 

Pleasant Hills 9,604 

Plum 25,390 

Port Vue 5,316 

Rankin 2,892 

402,583 

12,258 

9,782 

2,984 

6,087 

24,029 

1,254 

5228 

363 

1,693 

4,097 

5,018 

2,546 

11,291 

5,899 

9,585 

1,113 

2,187 

4,163 

6,959 

7,718 

11,118 

2,444 

2,807 

2,490 

4,412 

1,817 

1,716 

3,093 

4,284 

8,125 

4,836 

6,273 

5,930 

258 

129 

1,688 

4,780 

4,257 

8,533 

1,499 

3,030 

1,454 

8,459 

4,634 

4,360 

14,095 

8,290 

2,161 

6,806 

5 15 

644 

4,175 

9,217 

25,318 

5,165 

2,658 

9,677 

397,237 

10,681 

9,256 

3,061 

5,758 

23,449 

1,254 

2,399 

358 

1,492 

4,166 

4,623 

2,521 

10,991 

5,719 

9,618 

9,63 1 

1,007 

2,117 

3,958 

6,544 

7,283 

10,493 

2,235 

2,706 

2,198 

4,117 

1,675 

1,645 

2,880 

4,359 

7,405 

5,617 

8,468 

5,489 

214 

110 

1,394 

4,681 

4,002 

8,834 

1,516 

2,870 

1,353 

7,287 

4,216 

4,109 

13,280 

7,666 

1,809 

6,523 

511 

756 

3,806 

9,379 

25,958 

4,838 

2,529 

(1985) 

159,002 

4,502 

3,815 

1,394 

2,724 

8,461 

448 

882 

13 1 

655 

1,685 

1,944 

1,127 

4,460 

2,376 

4,05 1 

3,650 

396 

834 

1,399 

2,782 

2,986 

4,187 

941 

1,111 

945 

1,597 

609 

678 

1,203 

1,790 

2,784 

1,754 

2,646 

2,114 

88 

38 

592 

2,242 

1,623 

3,025 

585 

1,077 

453 

3,035 

1,818 

1,659 

5,252 

3,048 

6 13 

2,567 

187 

467 

1,603 

3,401 

8,182 

1,756 

1,006 

(sq. mi.) 

55.1 

2.7 

1.8 

0.4 

0.6 

5.5 

5.4 

0.4 

0.2 

0.3 

0.5 

0.6 

1.0 

1.5 

1.1 

1.3 

1.6 

0.2 

0.5 

1.4 

1.3 

1.1 

0.8 

0.9 

0.4 

0.4 

0.6 

1.4 

0.3 

0.5 

0.7 

1.5 

7.8 

14.6 

1.6 

0.8 

0.1 

0.3 

0.6 

0.4 

16.6 

0.9 

1.5 

4.9 

1.0 

0.6 

0.3 

2.3 

1.5 

0.4 

1.6 

0.4 

0.1 

OS 

2.8 

29.7 

1.2 

0.4 

Per Capita 

Income 

(1979) (1985) 

6,845 

6,540 

6,239 

9,353 

7,994 

7,696 

12,882 

9,867 

14,827 

7,289 

6,591 

4,824 

7,049 

7,797 

8,092 

7,699 

7,907 

7,3 15 

8,856 

15,473 

7,201 

7,743 

7,187 

7,032 

7,049 

6,941 

9,012 

24,749 

6,956 

7,271 

6,162 

9,326 

26,577 

10,223 

6,738 

6,25 1 

4,163 

6,800 

5,765 

7,037 

7,994 

7,274 

7,480 

7,201 

6,238 

5,856 

6,182 

7,753 

5,813 

7,145 

9,685 

11,338 

15,612 

6,708 

9,758 

7,397 

6,752 

5,377 

9,998 

9,154 

7,899 

14,356 

11,405 

10,798 

17,842 

13,636 

20,795 

11,791 

8,913 

6,663 

10,259 

11,060 

11,624 

10,808 

11,485 

10,554 

12,662 

21,813 

10,380 

11,107 

10,279 

9,348 

9,608 

10,188 

133 13 

39,055 

10,137 

10,219 

8,776 

13,412 

42,009 

14,298 

8,803 

9,192 

6,026 

9,162 

7,551 

10,114 

10,357 

10,142 

9,604 

10,254 

9,143 

8,206 

8,830 

9,818 

7,824 

10,141 

14,184 

15,905 

22,706 

9,176 

13,210 

10,592 

8,738 

7,285 

Household 

Income 

(1979) (1985) 

17,173 

16,345 

15,389 

20,823 

18,383 

22,241 

37,618 

25,820 

43,084 

16,786 

16,596 

11,584 

16,108 

19,612 

19,745 

18,353 

20,896 

19,155 

23,573 

44,580 

16,700 

19,303 

18,079 

17,167 

17,528 

16,424 

23,396 

66,022 

17,282 

18,963 

15,412 

25,606 

84,913 

33,619 

17,766 

15,635 

15,464 

16,428 

12,065 

17,626 

24,068 

19,3 10 

20,583 

21,492 

14,976 

14,109 

15,558 

19,973 

15,222 

21,769 

2,640 

34,767 

26,087 

16,3 12 

27,470 

23,742 

19,453 

13,205 

24,978 

21,718 

19,165 

31,523 

24,108 

29,926 

49,942 

37,089 

56,829 

26,858 

22,037 

15,845 

22,948 

27,256 

27,979 

25,66 1 

30,305 

26,838 

32,141 

61,713 

24,417 

27,091 

25,760 

22,203 

23,402 

23,697 

34,836 

107,417 

24,595 

24,464 

21,371 

35,674 

134,529 

45,758 

22,857 

22,353 

17,444 

21,574 

15,765 

24,939 

30,246 

26,283 

25,593 

30,626 

21,952 

19,030 

21,870 

24,825 

19,678 

29,927 

36,043 

43,462 

36,757 

21,787 

36,429 

33,604 

24,074 

18,314 

Percent 

Below 

Poverty 

(1979) 

16.5 

17.3 

17.9 

4.4 

5.1 

4.0 

3.4 

5.1 

1.3 

8.3 

13.2 

29.8 

10.5 

4.8 

4.6 

8.3 

5.0 

9.4 

4.1 

1.8 

8.0 

6.3 

6.0 

6.0 

9.4 

15.6 

4.7 

2.4 

7.6 

5.3 

6.6 

1.6 

2.2 

2.0 

6.3 

12.8 

0.0 

8.0 

22.8 

7.4 

5.0 

6.6 

4.9 

4.3 

16.7 

12.9 

10.4 

6.4 

12.3 

5.2 

6.2 

1.6 

2.5 

9.5 

3.4 

3.8 

7.0 

25.6 

90 U.S. Advisory Commission on intergovernmental Relations 
Table A-1 (cont.) 

Population, Households, Land Area, Income, and Poverty Data 

Land 

PoDulation Households Area 

Municipality (1980) (1984) (1985) 

Boroughs (cont.) 

Rosslyn Farms 521 

Sewickley 4,778 

Sewickley Heights 899 

Sewickley Hills 419 

Sharpsburg 4,351 

Springdale 4,418 

Swissvale 11,345 

Tarentum 6,419 

Turtle Creek 6,959 

Verona 3,179 

Versailles 2,150 

Wall 989 

West Elizabeth 808 

West Homestead 3,128 

West Mifflin 26,322 

West View 7,648 

Whitaker 1,615 

White Oak 9,480 

Wilkinsburg 23,669 

Wilmerding 2,421 

Thornburg 526 

First Class Townships 

AlePPO 

Baldwin 

Collier 

Crescent 

East Deer 

Elizabeth 

Hamson 

Kennedy 

Leet 

Neville 

North Versailles 

Reserve 

Robinson 

Ross 

Scott 

Shaler 

South Fayette 

South Versailles 

Springdale 

Stowe 

Wilkins 

1,134 

2,680 

5,063 

2,862 

1,658 

16,269 

13,252 

7,159 

1,854 

1,416 

13,294 

4,306 

9,416 

35,102 

20,413 

33,694 

9,707 

425 

1,918 

9,202 

8.472 

Second Class Townships 

Fawn 

Findlay 

Forward 

Frazer 

Harmar 

Kilbuck 

Marshall 

Moon 

North Fayette 

Ohio 

Pine 

South Park 

2,899 

4,573 

4,335 

1,509 

3,461 

1,219 

2,594 

20,935 

7,35 1 

2,072 

3,908 

13,535 

499 

4,765 

868 

456 

4,065 

4,252 

11,402 

6,347 

489 

6,709 

3,087 

1,976 

989 

759 

2,901 

25,396 

7,634 

1,564 

9,649 

22,729 

2,252 

1,206 

2,636 

4,889 

2,687 

1,559 

16,231 

12,678 

7,3 17 

1,896 

1,312 

13,010 

4,308 

9,413 

35,039 

19,272 

32,933 

9,610 

389 

1,804 

8,826 

8,399 

2,878 

4,949 

4,360 

1,493 

3,345 

1,107 

2,878 

20,463 

7,917 

2,111 

4,464 

14.652 

484 

4,245 

852 

485 

3,939 

4,327 

11,430 

5,814 

499 

6,127 

2,938 

1,926 

864 

765 

2,779 

24,501 

7,148 

1,507 

9,325 

22,997 

2,046 

1,338 

2,586 

4,998 

2,755 

1,423 

15,597 

12,202 

6,964 

1,847 

1,166 

12,748 

4,724 

9,565 

35,262 

19,851 

32,543 

10,191 

372 

1,723 

8,417 

8,131 

2,700 

4,407 

4,264 

1,334 

3,265 

1.033 

2,821 

22,267 

8.40 1 

2,132 

4,411 

13,701 

(1985) 

175 

1,891 

303 

165 

1,739 

1,717 

4,669 

2,374 

153 

2,568 

1,144 

8 17 

333 

278 

1,075 

8,962 

2,819 

578 

3,477 

10,481 

940 

5 12 

897 

1,464 

911 

594 

5,291 

4,742 

2,427 

584 

559 

4,801 

1,650 

3,116 

13,151 

7,266 

10,835 

3,364 

137 

662 

3,373 

3,194 

924 

1,534 

1,592 

468 

1,317 

257 

979 

7,424 

3,026 

695 

1,409 

4.943 

(sq. mi.) 

0.6 

1.0 

7.4 

4.4 

0.5 

0.9 

1.2 

1.2 

0.4 

1.0 

0.5 

0.5 

0.4 

0.2 

0.9 

14.2 

1.0 

0.3 

6.5 

3.1 

0.4 

1.9 

0.5 

12.8 

2.1 

2.2 

15.8 

7.1 

5.5 

1.7 

1.4 

8.2 

2.0 

15.9 

13.6 

4.0 

11.1 

21.2 

1.0 

2.3 

1.9 

2.6 

13.7 

32.8 

18.9 

9.4 

5.9 

2.6 

15.5 

24.1 

25.6 

6.8 

17.0 

9.1 

Per Capita 

Income 

(1979) (1985) 

18,119 

9,434 

30,036 

10,115 

6,356 

7,202 

7,096 

6,173 

16,5 19 

6,991 

6,682 

7,810 

6,292 

6,671 

7,761 

7,637 

7,323 

6,901 

9,068 

7,359 

6,556 

12,514 

7,680 

6,48 1 

7,844 

6,775 

7,894 

735 1 

8,281 

7,995 

8,343 

7,726 

7,144 

8,221 

9,388 

9,166 

7,999 

7,127 

6,561 

7,083 

6,652 

9,263 

6,831 

7,298 

6,874 

6,920 

735 1 

8,781 

8,423 

9,049 

7,692 

8,254 

9,538 

7,941 

24,473 

13,557 

41,757 

14,116 

10,115 

10,116 

10,321 

8,456 

23,658 

9,661 

9,638 

10,759 

8,119 

8,884 

10,074 

9,822 

10,877 

9,396 

12,036 

10,679 

8,864 

19,747 

10,920 

9,403 

10,565 

9,134 

10,301 

10,204 

11,346 

11,159 

10,934 

10,105 

10,070 

11,455 

13,592 

13,119 

11,592 

9,728 

9,107 

9,652 

9,659 

13,250 

9,791 

10,354 

9,072 

9,549 

10,982 

12,854 

13,989 

12,631 

10,662 

13,253 

13,367 

11,011 

Household 

Income 

(1979) (1985) 

50,956 

21,635 

85,993 

30,587 

15,279 

18,688 

17,407 

15,054 

54,923 

16,934 

17,675 

18,682 

16,807 

19,770 

20,395 

21,223 

19,000 

18,243 

24,28 1 

16,525 

14,580 

32,944 

23,283 

21,123 

23,879 

16,505 

233 14 

19,966 

24,897 

26,05 1 

18,032 

20,653 

21,159 

25,217 

25,421 

24,239 

23,724 

21,475 

17,769 

19,413 

16,877 

23,900 

20,250 

22,217 

20,353 

20,673 

18,758 

32,685 

25,310 

26,478 

21,567 

33,400 

30,247 

23,854 

67,685 

30,433 

117,416 

41,492 

22,9 11 

25,493 

25,266 

20,709 

77,159 

23,050 

24,752 

25,363 

21,066 

24,447 

26,042 

26,852 

27,580 

24,498 

32,279 

23,431 

19,293 

51,604 

3 1,482 

32,lO 1 

31,950 

21,882 

30,366 

26,257 

32,556 

35,292 

22,807 

26,832 

28,831 

35,163 

36,444 

35,842 

34,817 

29,470 

24,728 

25,121 

24,103 

33,731 

28,610 

29,746 

24,298 

27,219 

27,226 

51,666 

40,309 

37,884 

29,601 

40,655 

41,847 

30,520 

Percent 

Below 

Poverty 

(1979) 

1.4 

7.5 

9.0 

8.3 

8.1 

5.9 

7.3 

14.4 

0.6 

9.8 

9.1 

3.4 

8.6 

7.9 

12.1 

6.6 

4.4 

5.2 

3.4 

13.8 

12.1 

4.4 

4.5 

5.3 

3.1 

6.9 

3.2 

7.3 

5.3 

2.4 

6.5 

6.8 

3.3 

4.1 

3.9 

3.4 

4.0 

7.4 

9.1 

4.0 

14.3 

3.5 

2.5 

3.6 

4.9 

4.4 

5.8 

3.2 

4.0 

4.5 

5.5 

0.0 

3.3 

4.3 

U.S. Advisory Commission on Intergovernmental Relations 91 
Table A-1 (cont.) 

Population, Households, Land Area, Income, and Poverty Data 

Land Per Capita 

PoDulation Households Area Income 

Municipality (1980) (1984) (1985) (1985) (Sq. mi.) (1979) (1985) 

Home Rule Municipalities 

McKeesport 3 1,012 

Bellevue 10,128 

Bethel Park 34,755 

Bradford Woods 1,264 

Green Tree 5,722 

Monroeville 30,977 

Whitehall 15,143 

McCandless 26,191 

Mt. Lebanon 34,414 

Ohara 9,233 

Penn Hills 57,632 

Upper St Clair 19,023 

Hampton 14,319 

Indiana 6,080 

Richland 7,749 

West Deer 10,897 

28,853 

9,646 

34,407 

1,339 

5,691 

30,470 

14,671 

25,897 

33,633 

9,279 

56,072 

18,992 

14,667 

6,300 

8,472 

10,971 

27,639 

9,521 

35,029 

1,362 

5,578 

31,572 

14,424 

27,548 

35,115 

8,931 

55,743 

18.088 

14,731 

6,012 

7,537 

10,926 

11,102 

4,463 

11,859 

435 

1,993 

11,459 

6,771 

9,248 

13,472 

2,872 

19,211 

5,898 

4,867 

1,983 

2,747 

3,774 

6.6 6,433 

1.0 7,771 

11.7 9,269 

0.9 13,014 

21 9,861 

19.5 8,924 

17.4 10,544 

6.0 12,811 

7.1 11,159 

19.0 7,643 

9.7 13,866 

16.3 9,194 

17.6 8,582 

14.7 8,177 

29.0 7,307 

3.3 10,606 

8,628 

11,234 

13,452 

21,283 

13,766 

12,784 

14,716 

15,325 

19,174 

17,160 

10,670 

21,377 

12,875 

12,715 

11,498 

10,032 

Household 

Income 

(1979) (1985) 

16,071 

16,913 

27,782 

41,516 

27,945 

25,216 

26,879 

3 1,662 

34,115 

24,719 

223 17 

47,322 

28,678 

26,18 1 

25,258 

21,875 

21,480 

23,966 

39,734 

66,638 

38,528 

35,223 

3 1,349 

45,650 

49,977 

53,362 

30,960 

65,559 

38,969 

38,549 

31,547 

29,043 

Percent 

Below 

Poverty 

(1979) 

14.4 

7.5 

2.4 

3.7 

2.2 

4.2 

4.0 

3.6 

2.4 

2.8 

5.1 

1.2 

3.5 

5.5 

2.9 

5.5 

92 U.S. Advisory Commission on Intergovernmental Relations 

I' 

1; 
Table A-2 

Population and Housing Characteristics, Density, Population Change, Property Value and Type 

Municipality 

Pittsburgh 

Third Class Cities 

Clairton 

Duquesne 

Boroughs 

Aspinwall 

Avalon 

Baldwin 

Bell Acres 

Ben Avon 

Ben Avon Heights 

Blawnox 

Brackenridge 

Braddock 

Braddock Hills 

Brentwood 

Bridgeville 

Carnegie 

Castle Shannon 

Chalfant 

Cheswick 

Churchill 

Coraopolis 

Crafton 

Dormont 

Dravosburg 

East McKeesport 

East Pittsburgh 

Edgewood 

Edgeworth 

Elizabeth 

Emsworth 

Etna 

Forest Hills 

Fox Chapel 

Franklin Park 

Glassport 

Glenfield 

Haysvile 

Heidelberg 

Homestead 

Ingram 

Jefferson 

Leetsdale 

Lincoln 

McKees Rocks 

Millvale 

Mt Oliver 

Munhall 

North Braddock 

Oakdale 

Oakmont 

Osborne 

Pennsbury Village 

Pitcairn 

Pleasant Hills 

Plum 

Port Vue 

Liberty 

Percent of 

PoDulation 

Nonwhite 

(1980) 

24.9 

28.0 

23.5 

0.6 

1.2 

0.9 

0.1 

3.9 

0.0 

0.1 

2.5 

47.8 

15.8 

0.3 

4.2 

2.2 

0.9 

0.5 

0.1 

1.5 

12.3 

1.6 

0.4 

0.2 

1.1 

4.5 

1.7 

2.2 

7.9 

3.7 

0.1 

1.3 

2.6 

1.9 

0.3 

2.9 

9.6 

1.4 

37.5 

2.8 

2.9 

5.5 

1.5 

0.4 

9.6 

0.1 

1.6 

0.7 

14.6 

3.3 

c.9 

3.1 

2.8 

0.9 

1.5 

2.9 

0.0 

Over 65 

(1980) 

16.0 

17.2 

18.1 

19.5 

20.9 

9.9 

8.4 

13.5 

w. 1 

15.1 

19.9 

18.4 

19.0 

17.5 

17.7 

18.1 

11.8 

15.0 

12.8 

11.7 

18.9 

13.2 

14.8 

17.8 

16.8 

17.9 

14.2 

15.5 

19.8 

14.3 

19.5 

14.0 

8.8 

7.7 

15.3 

16.3 

16.2 

19.0 

24.0 

16.0 

10.5 

16.7 

13.5 

8.7 

18.3 

18.5 

17.6 

17.5 

16.5 

9.4 

20.0 

13.0 

1.9 

14.9 

9.8 

5.3 

12.3 

Percent of 

Housing 

Built Built 

Before 

1940 

63.3 

58.8 

59.9 

62 1 

522 

122 

24.7 

72.5 

70.1 

51.6 

69.4 

75.9 

20.0 

38.0 

45.3 

55.2 

19.5 

50.4 

29.8 

7.5 

65.3 

61.3 

79.5 

42.7 

52.6 

70.6 

74.0 

55.8 

76.1 

44.3 

68.5 

39.8 

18.3 

16.3 

57.7 

74.0 

59.0 

54.9 

70.7 

53.3 

22.5 

67.3 

15.9 

27.6 

66.1 

79.2 

76.9 

47.8 

71.3 

51.0 

50.5 

57.6 

0.0 

77.6 

4.6 

13.9 

29.1 

in 

1970-80 

4.8 

2.7 

11.9 

6.7 

7.8 

9.9 

12.4 

24 

0.0 

8.6 

5.5 

1.9 

33.7 

4.3 

8.9 

10.1 

7.2 

0.6 

7.0 

7.0 

10.7 

10.6 

0.8 

1.2 

4.5 

8.1 

1.9 

3.8 

1.5 

18.7 

3.9 

4.8 

22.0 

28.9 

1.6 

0.0 

12.8 

4.1 

3.7 

10.2 

24.9 

0.2 

9.7 

9.1 

1.3 

2.5 

1.2 

2.9 

3.1 

15.7 

13.0 

2.9 

4.4 

2.3 

15.3 

29.2 

3.6 

Owner- Population 

Occupied 

(1980) 

51.2 

62.0 

58.3 

48.0 

47.8 

77.6 

91.7 

70.9 

94.6 

55.0 

64.0 

42.3 

57.4 

66.0 

68.0 

54.4 

63.3 

76.3 

81.7 

98.4 

59.6 

51.5 

56.4 

70.5 

65.4 

46.6 

63.4 

84.4 

60.4 

59.7 

61.6 

82.4 

94.6 

92.0 

68.1 

83.0 

71.8 

74.1 

40.6 

60.1 

80.8 

70.0 

89.1 

90.9 

5 1.9 

56.6 

58.7 

75.6 

64.9 

81.0 

54.6 

91.2 

79.8 

54.3 

76.0 

79.7 

83.8 

Density 

(1984) 

7,306 

4,540 

5,434 

7,460 

10,145 

4,369 

232 

5,570 

1,815 

5,643 

8,194 

8,363 

2,546 

7,527 

5,363 

7,373 

6,048 

5,565 

4,374 

2,974 

5,353 

7,016 

13,898 

2,716 

7,018 

6,225 

7,353 

1,298 

5,720 

6,186 

6,120 

5,417 

620 

430 

3,706 

323 

1,290 

5,627 

7,967 

10,643 

5 14 

1,666 

2,020 

297 

8,459 

7,723 

14,533 

6,128 

5,527 

5,403 

4,254 

1,288 

6,440 

8,350 

3,292 

852 

4,304 

Market 

PoDulation Value of 

dhange 

(percent) 

-5.0 

1980-84 

0.6 

-3.1 

-9.1 

-2.5 

-2.8 

-4.1 

-3.7 

-8.8 

2.4 

-4.7 

-10.9 

-0.4 

-4.8 

-4.1 

-5.1 

-4.8 

-0.5 

-6.4 

-2.8 

-4.8 

1.2 

-1.4 

-2.7 

-4.5 

-0.1 

0.7 

4.5 

-9.3 

0.6 

-5.5 

-0.9 

-4.2 

2.2 

-5.0 

4.9 

10.3 

5.1 

-6.1 

-2.0 

-1.3 

-6.5 

-2.6 

1.8 

-3.2 

-29 

-4.7 

-3.0 

-4.8 

10.5 

-3.3 

-2.6 

-19.3 

0.0 

-4.0 

-0.3 

-2.8 

Real Estate 

Per Capita 

(1985) 

14,503 

7,587 

9,701 

15,503 

11,120 

13,318 

26,159 

11,975 

28,3 13 

15,540 

7,915 

6,734 

15,183 

12,830 

14,635 

12,572 

12,205 

10,379 

15,830 

31,817 

12,458 

12,106 

10,159 

10,346 

10,203 

18,568 

15,112 

42,612 

10,864 

11,990 

11,181 

17,150 1 

45,229 

24,486 

8,356 

14,266 

17,582 

13,260 

10,93 1 

10,807 

16,290 

28,230 

11,859 

13,007 

8,140 

9,125 

7,492 

11,192 

6,021 

11,960 

15,292 

26,773 

21,074 

7,194 

19,022 

13,418 

8.822 

Percent 

of Real 

Estate 

Residential 

47.9 

64.8 

55.6 

78.2 

71.7 

87.8 

92.9 

96.5 

93.1 

60.5 

79.7 

39.7 

47.2 

81.4 

83.3 

72.0 

75.4 

87.2 

80.7 

77.3 

69.1 

77.0 

83.2 

69.3 

86.1 

27.5 

82.3 

95.7 

76.5 

83.0 

71.8 

85.3 

96.0 

93.6 

85.9 

72.2 

34.7 

81.0 

48.0 

82.2 

74.6 

46.3 

93.0 

87.5 

58.3 

75.4 

79.5 

80.2 

69.8 

88.0 

75.7 

89.8 

100.0 

81.3 

74.7 

83.3 

91.3 

U.S. Advisory Commission on Intergovernmental Relations 93 
Table A-2 (cont.) 

Population and Housing Characteristics, Density, Population Change, Property Value and 'Qpe 

Municipality 

Boroughs (cont.) 

Rankin 

Rosslyn Farms 

Sewickley 

Sewickley Heights 

Sewickley Hills 

Sharpsburg 

Springdale 

Swissvale 

Tarenturn 

Thornburg 

Turtle Creek 

Verona 

Versailles 

Wall 

West Elizabeth 

West Homestead 

West Mifflin 

West View 

Whitaker 

White Oak 

Wilkinsburg 

Wilmerding 

Percent of 

Pouulation 

Nonwhite 

(1980) 

44.7 

0.0 

15.6 

0.3 

1.4 

2.5 

0.0 

6.0 

1.3 

0.0 

0.5 

2.9 

2.0 

0.2 

2.3 

3.3 

6.7 

0.2 

0.7 

1.5 

38.1 

3.0 

First Class Townships 

Baldwin 0.5 

Collier 2.6 

Crescent 3.8 

East Deer 3.6 

Elizabeth 2.5 

Harrison 2.6 

Kennedy 0.7 

Leet 2.9 

Neville 0.6 

North Versailles 9.3 

Reserve 1.3 

Robinson 1.3 

Ross 1.9 

Scott 2.4 

Shaler 0.8 

South Fayette 6.2 

South Versailles 0.0 

Springdale 0.0 

Stowe 0.6 

Wilkins 1.8 

Second Class Townships 

Fawn 0.2 

Findlay 1.7 

Forward 0.2 

Frazer 0.3 

Harmar 0.0 

Kilbuck 2.3 

Marshall 0.0 

Moon 4.0 

North Fayette 1.7 

Ohio 4.9 

Pine 0.5 

South Park 4.6 

Aleppo 7.9 

Over 65 

(1980) 

18.3 

14.0 

19.4 

15.3 

6.0 

17.3 

15.0 

18.0 

16.4 

10.1 

17.9 

13.5 

19.2 

14.5 

11.9 

13.1 

11.8 

15.8 

17.2 

15.1 

17.5 

23.6 

6.8 

10.3 

18.8 

8.8 

20.8 

10.4 

15.9 

11.3 

7.9 

18.2 

11.0 

12.9 

8.0 

12.4 

16.3 

11.2 

14.2 

13.9 

11.2 

17.3 

11.9 

10.0 

8.5 

11.5 

10.4 

12.7 

24.8 

8.9 

5.4 

9.2 

8.9 

10.2 

5.6 

Percent of 

Housine 

Built Built 

Before 

1940 

54.3 

53.4 

59.9 

59.1 

25.9 

76.3 

57.6 

67.3 

72.3 

43.9 

53.1 

65.9 

45.0 

88.3 

57.5 

47.3 

17.6 

54.6 

57.4 

21.4 

52.8 

76.5 

17.2 

7.3 

33.2 

26.0 

63.4 

25.3 

43.6 

10.6 

37.0 

29.6 

15.7 

40.3 

17.1 

16.7 

13.8 

20.3 

27.1 

31.9 

41.0 

63.1 

21.0 

27.7 

32.0 

30.2 

20.1 

33.1 

29.1 

32.7 

7.6 

23.4 

12.5 

14.2 

14.2 

in 

1970-80 

4.3 

0.5 

1.5 

8.2 

34.7 

8.0 

0.5 

3.6 

6.2 

6.7 

8.7 

8.0 

18.6 

0.0 

17.3 

4.5 

12.5 

9.8 

1.6 

20.1 

8.7 

8.3 

52.3 

1.5 

8.4 

17.4 

4.3 

19.9 

9.4 

17.1 

22.2 

2.7 

21.8 

15.0 

24.6 

24.8 

13.4 

16.0 

39.2 

5.6 

12.7 

4.2 

12.6 

11.2 

33.6 

19.6 

10.8 

16.3 

7.2 

17.6 

30.3 

34.7 

16.9 

15.9.. 

51.6 

94 US. Advisory Commission on Intergovernmental Relations 

Owner- Pouulation 

Occupied 

(1980) 

45.2 

95.1 

47.9 

70.1 

87.9 

49.7 

68.2 

61.0 

53.6 

98.8 

56.9 

56.7 

60.0 

73.9 

67.2 

71.8 

82.4 

69.6 

78.3 

78.0 

41.7 

51.5 

87.6 

95.9 

84.6 

84.5 

71.7 

86.0 

72.3 

88.3 

86.2 

52.9 

74.4 

86.5 

84.7 

76.4 

68.0 

86.0 

76.8 

86.6 

84.3 

62.8 

69.5 

81.7 

81.2 

83.1 

86.9 

74.7 

93.1 

83.5 

68.1 

86.4 

89.9 

89.9 

76.0 

density 

(1984) 

6,645 

832 

4,765 

117 

104 

8,130 

4.724 

9,502 

5.289 

1,223 

6.709 

6,174 

3,952 

2,473 

3,795 

3,223 

1,788 

7,634 

5,213 

1,484 

7,332 

5,630 

635 

5,272 

382 

1,280 

709 

1,027 

1,786 

1,330 

1,115 

937 

1,587 

2,154 

592 

2,576 

4,818 

2,967 

453 

389 

784 

4,645 

3,230 

210 

15 1 

231 

159 

567 

426 

186 

849 

309 

3 10 

2453 

1,610 

Market 

Population Value of Percent 

Change 

(percent) 

1980-84 

-8.1 

-4.2 

-0.3 

-3.4 

8.8 

-6.6 

-3.8 

0.5 

-1.1 

-7.0 

-3.6 

-2.9 

-8.1 

0.0 

-6.1 

-7.3 

-3.5 

-0.2 

-3.2 

1.8 

-4.0 

-7.0 

6.3 

-1.6 

-3.4 

-6.1 

-6.0 

0.2 

-4.3 

2.2 

2.3 

-7.3 

-2.1 

0.0 

-0.0 

-0.2 

-5.6 

-2.3 

-1.0 

-8.5 

-5.9 

-4.1 

-0.9 

-0.7 

8.2 

0.6 

-1.1 

-3.4 

-9.2 

10.9 

-2.3 

7.7 

1.9 

14.2 

8.3 

Real Estate of Real 

Per Capita 

(1985) 

6,175 

40,029 

19,339 

58,532 

20,414 

10,901 

12,263 

9,639 

7,681 

28,711 

9,384 

11,332 

11,791 

8,272 

7,116 

15,843 

17,962 

14,787 

8,667 

14,085 

10,146 

14,352 

18,639 

14,266 

24,119 

10,538 

15,408 

12,551 

13,998 

16,538 

11,924 

52,607 

13,630 

9,606 

32,140 

18,212 

13,952 

14,564 

15,233 

9,925 

10,135 

9,642 

18,475 

12,577 

28,560 

11,213 

123 18 

26,9 10 

15,872 

28,044 

15,895 

13,758 

20,472 

21,397 

14,044 

Estate 

Residential 

53.5 

80.0 

72.5 

90.6 

97.7 

52.1 

69.0 

77.8 

71.1 

85.6 

57.1 

67.2 

62.6 

80.6 

62.6 

67.0 

54.0 

79.8 

92.0 

86.2 

71.8 

51.1 

85.0 

83.1 

45.3 

92.0 

51.9 

86.7 

73.7 

82.7 

95.5 

17.9 

69.3 

95.7 

48.3 

73.7 

78.3 

89.5 

74.5 

90.7 

87.3 

71.3 

68.5 

83.5 

37.1 

51.6 

90.4 

35.6 

95.0 

62.1 

67.0 

71.5 

89.9 

76.9 

88.5 
Table A-2 (cont.) 

Population and Housing Characteristics, Density, Population Change, Property Value and Qpe 

Percent of 

Population 

Nonwhite Over 65 

Municipality (1980) (1980) 

Home Rule Municipalities 

McKeesport 14.1 

Bellevue 2.3 

Bethel Park 2.2 

Bradford Woods 0.0 

Green Tree 25 

Monroeville 8.0 

Whitehall 0.4 

McCandless 1.8 

Mt. Lebanon 1.1 

Ohara 0.6 

Penn Hills 11.9 

Hampton 0.6 

Indiana 1.7 

Richland 1.6 

West Deer 0.8 

Upper St Clair 1.2 

17.9 

18.9 

8.5 

5.9 

13.4 

7.3 

15.1 

9.2 

16.4 

11.7 

9.7 

5.2 

6.9 

10.7 

9.1 

9.3 

Percent of 

Housiw 

Built Built Owner- Pooulation 

Before 

1940 

63.7 

56.9 

8.6 

27.0 

16.3 

8.0 

8.5 

6.7 

36.4 

24.1 

14.2 

5.1 

18.7 

36.5 

17.4 

35.6 

in 

1970-80 

5.2 

9.6 

23.9 

33.4 

8.5 

27.0 

11.6 

34.8 

5.8 

19.4 

13.0 

30.5 

31.5 

17.4 

2.3.4 

21.9 

Occupied Density 

(1980) (1984) 

60.0 4,372 

39.0 9,646 

80.0 2,941 

95.7 1,488 

88.6 2,710 

71.8 1,563 

71.7 4,446 

79.1 1,488 

73.0 5,606 

90.1 1,307 

83.1 2,95 1 

96.4 1,958 

87.1 900 

83.5 358 

86.0 576 

86.0 378 

Market 

Population Value of Percent 

Change Real Estate of Real 

1980-84 Per Capita Estate 

(percent) (1985) Residential 

-7.0 

-4.8 

-1.0 

5.9 

-0.5 

-1.6 

-3.1 

-1.1 

-2.3 

0.5 

-2.7 

-0.2 

2.4 

3.6 

9.3 

0.7 

8,564 

10,966 

18,708 

23,745 

34,428 

22,538 

18,446 

22,357 

20,832 

31,825 

123 18 

33,208 

20,960 

15,927 

21,417 

12,775 

76.8 

84.3 

75.4 

97.0 

38.2 

50.1 

86.4 

80.8 

87.9 

61.3 

84.5 

86.4 

83.6 

81.7 

75.3 

89.4 

US. Advisory Commission on Intergovernmental Relations 95 
Table A-3 

Per Capita Revenues and Expenditures, 1985 

Municipality 

Pittsburgh 

Third Class Cities 

Clairton 

Duquesne 

Boroughs 

Aspinwall 

Avalon 

Baldwin 

Bell Acres 

Ben Avon 

Ben Avon Heights 

Blawnox 

Brackenridge 

Braddock 

Braddock Hills 

Brentwood 

Bridgeville 

Carnegie 

Castle Shannon 

Chalfant 

Cheswick 

Churchill 

Coraopolis 

Crafton 

Dormont 

Dravosburg 

East McKeesport 

East Pittsburgh 

Edgewood 

Edgeworth 

Elizabeth 

Emsworth 

Etna 

Forest Hills 

Fox Chapel 

Franklin Park 

Glassport 

Glenfield 

Haysvile 

Heidelberg 

Homestead 

Ingram 

Jefferson 

Leetsdale 

Liberty 

Lincoln 

McKees Rocks 

Millvale 

Mt Oliver 

Munhall 

North Braddock 

Oakdale 

Oakmont 

Osborne 

Pennsbury Village 

Pitcairn 

Pleasant Hills 

Plum 

Port Vue 

Per Caoita Revenues in 1985-Excludin~ PSE’s 

Total 

727.53 

265.42 

214.13 

253.80 

201.29 

182.01 

239.26 

186.88 

349.09 

242.95 

179.00 

166.11 

230.54 

206.08 

227.84 

187.98 

186.69 

142.15 

240.07 

305.96 

301.19 

229.71 

237.97 

242.66 

169.64 

253.06 

274.71 

480.23 

307.04 

187.29 

222.61 

275.35 

460.74 

158.01 

133.08 

301.76 

125.55 

311.20 

246.96 

155.95 

288.77 

334.66 

123.74 

194.84 

218.47 

169.96 

199.47 

200.53 

141.40 

243.69 

261.08 

444.19 

368.93 

139.38 

337.03 

148.62 

173.38 

All Taxes 

497.44 

151.95 

125.32 

175.72 

146.29 

111.90 

197.58 

157.21 

312.03 

159.20 

83.96 

114.51 

183.82 

144.30 

175.56 

125.39 

135.40 

91.82 

134.49 

258.72 

150.46 

164.49 

140.38 

123.37 

114.42 

192.63 

218.10 

422.69 

106.74 

146.09 

130.95 

213.10 

368.52 

115.22 

89.00 

120.24 

77.70 

163.64 

152.5 1 

122.94 

143.88 

241.32 

57.90 

110.70 

122.38 

112.79 

120.50 

156.70 

106.49 

111.49 

148.19 

263.61 

334.83 

66.55 

177.10 

68.65 

104.03 

Real Estate 

TaX 

234.49 

126.39 

101.37 

120.58 

105.86 

71.69 

117.63 

100.04 

214.61 

111.25 

55.10 

73.10 

119.85 

102.45 

120.42 

84.71 

94.84 

56.29 

90.86 

136.62 

116.01 

92.74 

103.88 

71.54 

84.55 

161.70 

153.89 

304.06 

74.87 

102.70 

90.47 

125.37 

209.36 

29.26 

59.89 

73.63 

49.87 

99.98 

129.66 

81.43 

98.68 

199.25 

23.75 

71.92 

86.27 

75.18 

57.57 

125.68 

76.70 

65.60 

97.38 

188.44 

232.98 

46.00 

108.75 

24.02 

75.66 

Earned 

Income 

TaX 

139.89 

15.15 

14.35 

44.26 

32.19 

36.84 

59.94 

48.27 

78.23 

36.45 

21.80 

15.66 

22.95 

36.80 

32.62 

31.27 

36.29 

33.26 

39.42 

77.18 

26.71 

44.32 

32.27 

28.07 

25.74 

19.49 

48.46 

93.70 

27.14 

34.68 

28.04 

52.02 

139.38 

64.26 

21.61 

42.15 

18.10 

33.70 

12.69 

33.49 

36.63 

26.97 

29.23 

21.25 

22.99 

22.59 

47.86 

25.57 

19.10 

39.98 

42.37 

57.19 

86.06 

18.01 

46.39 

41.03 

27.64 

Total 

Miscellaneous 

230.27 

113.47 

88.80 

78.08 

55.00 

70.11 

41.68 

29.67 

37.06 

83.75 

95.04 

51.60 

46.72 

61.76 

52.31 

62.61 

51.27 

50.33 

105.59 

47.40 

150.80 

65.12 

97.59 

119.28 

55.22 

60.44 

56.64 

57.54 

200.30 

41.20 

91.66 

62.27 

92.29 

42.77 

44.07 

181.52 

47.85 

147.56 

94.41 

33.00 

145.01 

93.33 

65.84 

84.14 

96.09 

57.17 

78.97 

43.86 

34.93 

132.21 

112.96 

180.58 

34.10 

72.82 

159.83 

79.94 

69.34 

Intergovernmental 

Aid 

131.13 

18.63 

31.09 

6.56 

8.93 

9.94 

4.44 

8.14 

5.91 

12.24 

34.10 

19.72 

12.73 

13.12 

10.53 

8.29 

7.92 

25.50 

6.91 

4.72 

18.75 

17.94 

14.18 

30.00 

9.30 

17.45 

12.11 

4.00 

24.69 

11.08 

15.99 

21.33 

10.83 

6.13 

9.62 

21.29 

17.07 

39.58 

34.26 

9.91 

8.83 

28.80 

5.08 

44.72 

16.82 

14.70 

18.54 

11.66 

15.85 

47.90 

18.96 

111.92 

4.72 

10.85 

12.05 

9.11 

14.03 

Per Capita 

Exoenditures in 1985 

Total 

without 

PSEs Police Streets 

708.64 98.46 85.49 

247.64 36.61 40.53 

250.65 57.03 37.16 

219.02 

193.12 

179.84 

223.67 

196.48 

325.49 

278.69 

163.74 

184.50 

189.04 

198.16 

211.58 

194.74 

158.65 

155.05 

207.46 

245.29 

299.21 

206.92 

208.23 

224.68 

152.31 

257.21 

197.25 

448.84 

248.87 

180.31 

254.65 

247.40 

387.40 

128.72 

136.06 

257.17 

105.84 

235.15 

292.25 

146.82 

261.26 

330.46 

138.71 

188.77 

21 1.75 

158.30 

196.71 

187.42 

147.40 

177.22 

237.47 

262.95 

223.59 

159.01 

282.87 

135.76 

146.93 

57.28 

63.72 

34.39 

69.96 

67.50 

116.43 

81.88 

38.25 

60.30 

55.64 

61.90 

58.98 

68.47 

48.66 

28.03 

52.12 

98.17 

74.21 

51.40 

50.20 

50.74 

39.27 

91.54 

84.01 

123.25 

48.80 

50.62 

57.72 

56.43 

68.09 

23.55 

33.74 

56.88 

0.00 

80.24 

107.22 

49.50 

55.87 

101.43 

26.64 

40.59 

49.40 

44.90 

50.80 

49.88 

34.21 

57.17 

55.53 

63.87 

64.59 

45.82 

86.47 

31.16 

23.10 

5230 

44.43 

34.79 

72.06 

78.35 

106.15 

52.80 

44.43 

14.01 

48.83 

38.89 

47.69 

70.91 

34.58 

50.91 

32.07 

43.25 

45.48 

55.47 

36.47 

50.3 1 

44.16 

53.20 

39.86 

102.93 

45.61 

47.00 

37.83 

54.26 

92.93 

32.26 

26.27 

62.42 

33.95 

43.35 

52.24 

36.83 

43.88 

85.19 

29.91 

73.60 

55.85 

50.27 

43.87 

39.99 

42.58 

32.09 

41.26 

50.49 

22.94 

41.70 

36.24 

30.49 

30.70 

96 U.S. Advisory Commission on Intergovernmental Relations 
Table A-3 (cont.) 

Per Capita Revenues and Expenditures, 1985 

Per Capita 

Municipality 

Boroughs {cont.) 

Rankin 

Rosslyn Farms 

Sewickley 

Sewickley Heights 

Sewickley Hills 

S harpsburg 

Springdale 

Swissvale 

Tarentum 

Thornburg 

Turtle Creek 

Verona 

Versailles 

Wall 

West Elizabeth 

West Homestead 

West Mifflin 

West View 

Whitaker 

White Oak 

Wilkinsburg 

Wilmerding 

Per CaDita Revenues in 1985-Excludine PSE’s 

Total 

158.68 

518.04 

389.40 

832.37 

117.89 

246.11 

181.13 

167.54 

201.24 

447.98 

207.12 

179.57 

206.60 

91.59 

102.30 

282.82 

228.93 

214.47 

140.56 

227.67 

253.34 

401.67 

First Class Townships 

Aleppo 211.65 

Baldwin 185.22 

Collier 242.10 

Crescent 153.16 

East Deer 218.54 

Elizabeth 167.15 

Hamson 174.56 

Kennedy 227.74 

Leet 259.46 

Neville 745.48 

North Versailles 170.61 

Reserve 123.85 

Robinson 264.92 

Ross 145.71 

Scott 161.35 

Shaler 137.02 

South Versailles 107.91 

Springdale 194.73 

Stowe 159.91 

Wilkins 199.85 

Second Class Townships 

Fawn 100.65 

Findlay 365.10 

Forward 124.19 

Frazer 105.32 

Harmar 308.42 

Kilbuck 298.79 

Marshall 196.02 

Moon 151.79 

North Fayette 215.93 

Ohio 191.17 

Pine 139.21 

South Park 217.79 

South Fayette 235.21 

All Taxes 

94.94 

451.34 

232.75 

572.75 

79.84 

123.40 

76.04 

131.67 

89.56 

386.45 

123.52 

126.82 

140.55 

59.80 

75.81 

223.64 

179.54 

151.09 

91.49 

175.12 

162.54 

146.51 

143.62 

137.70 

184.49 

109.55 

110.27 

83.93 

124.24 

116.86 

159.76 

560.20 

124.49 

71.61 

208.99 

113.66 

120.35 

95.17 

118.24 

69.95 

87.80 

118.42 

160.87 

70.63 

126.88 

65.94 

69.21 

152.00 

121.61 

128.43 

114.88 

102.10 

140.90 

98.68 

109.55 

Real Estate 

Taw 

81.04 

336.71 

157.44 

393.45 

13.42 

73.90 

45.25 

97.90 

62.71 

271.28 

95.05 

96.86 

92.79 

37.23 

43.92 

191.40 

112.97 

108.11 

68.65 

110.78 

122.10 

107.13 

90.67 

76.57 

127.19 

75.16 

70.54 

42.16 

83.43 

53.82 

99.15 

487.77 

82.76 

36.76 

141.45 

52.21 

62.67 

43.70 

80.20 

43.80 

41.05 

84.91 

76.86 

39.22 

66.53 

32.51 

27.44 

115.96 

71.96 

60.88 

55.37 

36.37 

74.45 

34.42 

61.34 

Earned 

Income 

Taw 

11.22 

93.89 

42.51 

134.38 

57.53 

21.93 

22.62 

27.87 

17.90 

95.11 

24.23 

23.71 

25.54 

20.39 

23.30 

25.75 

32.07 

32.43 

21.10 

35.71 

26.55 

24.97 

39.83 

37.39 

24.91 

28.13 

29.53 

36.81 

28.75 

42.88 

47.33 

44.20 

28.56 

3251 

42.14 

42.77 

47.44 

46.98 

31.02 

22.81 

35.69 

25.13 

46.81 

25.16 

42.90 

27.17 

3272 

23.92 

40.46 

4236 

45.94 

44.63 

48.93 

38.72 

38.59 

Total 

Miscellaneous 

63.73 

66.70 

156.69 

259.62 

38.06 

122.71 

105.09 

35.86 

111.66 

61.53 

83.55 

52.75 

66.05 

31.79 

26.49 

59.18 

49.43 

63.34 

49.07 

52.56 

90.79 

255.15 

68.03 

47.52 

57.65 

43.61 

108.27 

83.22 

50.37 

110.93 

99.70 

185.29 

46.07 

52.24 

55.96 

32.05 

40.98 

41.82 

116.97 

37.96 

106.92 

41.51 

38.99 

30.02 

238.26 

58.25 

36.12 

156.39 

177.18 

67.59 

36.92 

113.83 

50.27 

40.53 

108.17 

Intergovernmental 

Aid 

17.06 

5.71 

14.32 

14.79 

3.47 

40.68 

6.15 

10.84 

20.32 

6.26 

31.84 

11.20 

11.39 

7.08 

7.38 

26.30 

18.75 

13.50 

20.74 

8.60 

36.43 

165.20 

4.18 

14.18 

21.70 

9.64 

21.45 

12.57 

15.43 

9.69 

16.23 

41.22 

21.21 

8.64 

16.36 

7.92 

8.99 

9.21 

21.98 

9.15 

14.51 

14.41 

11.10 

9.43 

27.69 

24.21 

9.45 

19.51 

12.01 

9.66 

9.26 

16.88 

10.37 

6.02 

13.46 

ExDenditures in 1985 

Total 

without 

PSEs Police 

173.83 47.88 

437.37 147.66 

369.14 117.92 

677.47 323.12 

104.61 44.33 

240.47 55.11 

199.56 34.87 

161.85 49.84 

212.42 39.25 

406.80 133.02 

211.85 50.58 

146.83 56.96 

193.41 51.15 

80.93 17.36 

108.36 34.13 

290.45 122.79 

213.05 45.71 

190.40 54.91 

136.06 34.05 

166.54 53.36 

234.60 58.88 

242.40 37.94 

223.82 79.90 

175.86 59.32 

212.08 63.17 

135.08 24.34 

280.89 71.14 

123.36 27.71 

177.43 50.18 

223.43 34.30 

229.73 58.36 

763.71 314.45 

193.05 30.24 

125.72 25.56 

222.48 66.90 

128.30 39.67 

157.62 52.39 

144.95 36.84 

184.08 37.11 

79.89 23.97 

159.65 19.32 

159.91 34.16 

180.30 66.97 

92.99 24.21 

326.75 75.90 

70.69 14.37 

92.07 0.15 

236.22 0.00 

222.52 138.73 

174.69 67.33 

132.17 39.67 

194.26 45.39 

189.53 53.46 

118.01 42.97 

199.62 52.74 

Streets 

36.33 

130.96 

62.96 

133.32 

17.56 

58.06 

51.26 

27.55 

50.26 

134.06 

50.45 

20.40 

59.62 

18.58 

24.49 

71.24 

50.00 

34.80 

30.04 

43.73 

35.87 

74.29 

52.25 

29.51 

64.64 

43.54 

99.61 

41.57 

46.64 

49.53 

46.77 

83.22 

87.39 

24.85 

68.67 

36.30 

37.05 

37.12 

57.24 

24.01 

43.15 

57.29 

50.75 

19.75 

111.83 

25.07 

41.79 

59.20 

19.20 

33.43 

30.08 

45.83 

59.76 

27.17 

26.04 

US. Advisory Commission on Intergovernmental Relations 97 
Table A-3 (conr.) 

Per Capita Revenues and Expenditures, 1985 

Jg PSE’s 

Municipality Total 

Home Rule Municipalities 

McKeesport 394.01 

Bellevue 218.99 

Bethel Park 235.86 

Bradford Woods 148.38 

Green Tree 350.48 

Monroeville 341.76 

Whitehall 210.07 

McCandless 179.94 

Mt. Lebanon 367.93 

Ohara 333.78 

Penn Hills 230.16 

Upper St Clair 371.52 

Hampton 265.02 

Indiana 164.16 

Richland 217.99 

West Deer 136.10 

Earned 

Real Estate Income 

All Taxes Tax Tax 

175.48 

154.82 

143.77 

114.04 

246.50 

249.75 

167.64 

144.40 

261.00 

227.63 

136.59 

258.96 

121.72 

113.85 

123.25 

90.08 

106.88 

88.94 

52.04 

31.94 

145.63 

79.12 

69.74 

61.35 

174.83 

103.29 

52.33 

107.86 

59.90 

67.29 

73.71 

46.76 

51.05 

55.25 

70.57 

72.06 

49.72 

59.89 

91.24 

56.56 

65.81 

107.84 

67.29 

117.81 

51.39 

35.96 

43.45 

36.47 

Total IntergovMiscell- ernmental 

aneous Aid 

218.50 99.32 

64.17 10.85 

92.12 13.55 

34.33 4.18 

103.99 16.68 

92.14 15.54 

42.42 6.28 

35.53 6.70 

106.91 11.95 

106.24 24.84 

93.61 29.99 

112.56 20.74 

143.24 10.18 

50.31 12.45 

94.71 11.44 

46.05 10.16 

Per Capita 

Exaenditures in 1985 

Total 

without 

PSEs Police Streets 

389.30 

213.11 

181.08 

140.01 

334.35 

303.21 

186.63 

119.25 

296.17 

275.89 

215.09 

311.86 

218.99 

147.16 

185.09 

139.39 

62.45 

60.23 

35.74 

43.95 

78.80 

54.38 

46.22 

41.85 

71.17 

63.29 

51.47 

66.84 

51.88 

42.35 

54.12 

32.92 

80.86 

53.75 

20.67 

39.63 

111.78 

75.13 

45.58 

37.50 

52.14 

71.94 

33.48 

71.48 

42.85 

49.22 

41.61 

45.35 

98 U.S. Advisory Commission on Intergovernmental Relations 
Table A4 

Employment, Household Burdens, 1985 

Municipality 

Pittsburgh 

Third Class Cities 

Clairton 

Duquesne 

Boroughs 

Aspinwall 

Avalon 

Baldwin 

Bell Acres 

Ben Avon 

Ben Avon Heights 

Blawnox 

Brackenridge 

Braddock 

Braddock Hills 

Brentwood 

Bridgeville 

Camegie 

Castle Shannon 

Chalfant 

Cheswick 

Churchill 

Coraopolis 

Crafton 

Dormont 

Dravosburg 

East McKeesport 

East Pittsburgh 

Edgewood 

Edgeworth 

Elizabeth 

Emsworth 

Etna 

Forest Hills 

Fox Chapel 

Franklin Park 

Glassport 

Glen field 

Haysvile 

Heidelberg 

Homestead 

Ingram 

Jefferson 

Leetsdale 

Liberty 

Lincoln 

McKees Rocks 

Millvale 

Mt Oliver 

Munhall 

North Braddock 

Oakdale 

Oakmont 

Osborne 

Pennsbury Village 

Pitcairn 

Pleasant Hills 

Plum 

Port Vue 

Emulovees ue r 1.000 Residents-1985 

Retail 

98.17 

67.03 

81.78 

58.15 

79.72 

27.76 

2.39 

24.18 

0.00 

32.84 

23.76 

41.10 

70.61 

73.61 

212.10 

126.12 

79.12 

9.93 

51.02 

7.33 

226.62 

70.58 

54.70 

54.59 

48.04 

34.12 

13.36 

59.10 

180.55 

35.07 

166.78 

38.08 

0.00 

9.57 

26.96 

65.42 

45.45 

102.58 

111.09 

49.48 

20.26 

136.54 

24.39 

74.65 

122.14 

56.45 

74.96 

19.35 

20.61 

18.79 

63.77 

0.00 

13.23 

40.20 

195.12 

20.19 

15.09 

Manufacturing 

38.76 

178.63 

11.13 

6.86 

19.80 

6.14 

0.00 

2.08 

0.00 

255.36 

39.61 

198.57 

0.00 

3.28 

52.63 

12.89 

4.78 

35.75 

24.09 

0.00 

14.06 

4.12 

3.91 

25.50 

26.61 

525.48 

126.06 

0.00 

1.22 

19.79 

9.41 

2.43 

0.00 

2.36 

98.74 

84.11 

0.00 

51.65 

550.52 

0.75 

50.60 

544.20 

5.57 

76.13 

8.51 

30.60 

3.65 

92.39 

163.32 

56.94 

144.57 

0.00 

0.00 

0.00 

15.89 

18.84 

3.31 

Government 

and 

Education 

121.28 

48.3 1 

37.17 

11.43 

39.94 

21.83 

18.34 

38.77 

0.00 

40.88 

31.20 

57.54 

26.18 

44.04 

30.60 

26.10 

38.83 

15.89 

49.13 

98.03 

45.39 

26.23 

52.80 

16.55 

3 1.78 

49.14 

24.78 

26.27 

55.32 

44.10 

25.69 

24.44 

47.71 

17.60 

31.15 

32.71 

0.00 

20.80 

66.01 

12.49 

56.49 

102.90 

72.82 

21.43 

52.70 

56.69 

48.67 

22.06 

48.40 

17.14 

53.35 

203.52 

1.32 

29.95 

39.34 

25.31 

10.54 

Other 

531.02 

72.56 

66.98 

39.53 

353.25 

36.42 

31.10 

8.34 

27.93 

159.52 

94.34 

269.74 

262.99 

101.81 

206.15 

134.75 

180.56 

55.61 

171.00 

536.38 

213.78 

368.80 

144.76 

405.37 

91.65 

874.43 

59.75 

79.40 

105.17 

98.26 

215.19 

156.92 

13.00 

29.88 

73.24 

182.24 

100.00 

129.84 

225.59 

38.73 

309.15 

327.84 

35.89 

48.78 

261.56 

599.86 

64.49 

58.66 

24.26 

19.35 

169.55 

178.08 

10.58 

47.56 

154.07 

63.18 

17.36 

Estimated Household Burdens From: 

Real Earned Trash 

Estate 

TaX 

260 

183 

128 

19 1 

148 

169 

302 

251 

54 1 

143 

103 

63 

119 

195 

230 

135 

178 

120 

181 

298 

177 

16 1 

202 

113 

168 

95 

308 

782 

13 1 

192 

149 

277 

638 

87 

127 

126 

48 

183 

118 

155 

209 

228 

58 

185 

112 

123 

106 

246 

128 

166 

175 

456 

366 

83 

2 16 

62 

186 

Income 

Tax 

349 

36 

35 

97 

68 

102 

168 

13 1 

214 

83 

54 

37 

51 

91 

79 

74 

96 

85 

100 

2 18 

63 

108 

81 

67 

63 

45 

125 

258 

66 

83 

68 

138 

446 

206 

56 

103 

52 

79 

26 

83 

107 

70 

78 

63 

55 

52 

119 

65 

48 

118 

108 

156 

139 

43 

128 

130 

76 

Collection 

/Disposal 

0 

20 

3 

52 

22 

0 

6 

0 

0 

35 

51 

0 

0 

0 

0 

7 

0 

6 

42 

0 

28 

0 

0 

3 

0 

0 

6 

0 

39 

0 

35 

0 

0 

5 

0 

0 

0 

7 

0 

7 

0 

0 

6 

6 

7 

30 

52 

0 

0 

76 

0 

0 

0 

42 

6 

64 

0 

Total 

Burden 

609 

239 

166 

340 

238 

271 

476 

382 

755 

261 

208 

100 

170 

286 

308 

216 

274 

21 1 

323 

5 16 

268 

270 

283 

182 

231 

140 

440 

1,040 

235 

275 

252 

415 

1,085 

297 

183 

228 

100 

270 

145 

244 

3 16 

298 

142 

254 

174 

206 

277 

3 10 

176 

360 

282 

612 

505 

167 

350 

255 

262 

Burden as 

Percent of 

Household 

Income 

2.44 

1.10 

0.87 

1.08 

0.99 

0.90 

0.95 

1.03 

1.33 

0.97 

0.94 

0.63 

0.74 

1.05 

1.10 

0.84 

0.90 

0.79 

1.01 

0.84 

1.10 

0.99 

1.10 

0.82 

0.99 

0.59 

1.26 

0.97 

0.96 

1.12 

1.18 

1.16 

0.81 

0.65 

0.80 

1.02 

0.58 

1.25 

0.92 

0.98 

1.04 

1.13 

0.55 

0.83 

0.79 

1.08 

1.27 

1.25 

0.89 

1.20 

0.78 

1.41 

1.37 

0.77 

0.96 

0.76 

1.09 

U.S. Advisory Commission on Intergovernmental Relations 99 
Table A4 (cont.) 

Employment, Household Burdens, 1985 

Municipality 

Boroughs (cont.) 

Rankin 

Rosslyn Farms 

Sewickley 

Sewickley Heights 

Sewickley Hills 

Shsrpsburg 

Springdale 

Swissvale 

Tarentum 

Thornburg 

Turtle Creek 

Verona 

Versailles 

Wall 

West Elizabeth 

West Homestead 

West Mifflin 

West View 

Whitaker 

White Oak 

Wilkinsburg 

Wilmerding 

First Class Townships 

Baldwin 

Collier 

Crescent 

East Deer 

Elizabeth 

Harrison 

Kennedy 

Leet 

Neville 

North Versailles 

Reserve 

Robinson 

Ross 

Scott 

Shaler 

South Fayette 

South Versailles 

Springdale 

Stow 

Wilkins 

Aleppo 

Emulovees uer 1.000 Residents-1985 I Government 

Retail 

7.91 

26.86 

130.27 

0.00 

14.43 

55.34 

45.76 

41.99 

78.95 

0.00 

53.21 

67.39 

100.21 

10.42 

78.43 

6931 

185.58 

121.71 

39.81 

49.44 

48.14 

72.34 

7.47 

38.28 

208.68 

10.53 

23.89 

20.90 

113.75 

50.40 

6.50 

24.87 

143.55 

16.72 

186.10 

137.46 

32.19 

29.16 

25.02 

8.06 

11.61 

22.93 

125.20 

Second Class Townships 

Fawn 20.37 

Findlay 56.27 

Forward 22.51 

Frazer 14.99 

Harmar 94.33 

Kil buck 11.62 

Marshall 161.29 

Moon 65.07 

North Fayette 73.44 

Ohio 12.20 

Pine 64.84 

South Park 19.78 

Manufacturing 

9.89 

289.26 

0.00 

0.00 

0.00 

97.99 

14.33 

36.13 

47.64 

0.00 

192.59 

84.41 

43.09 

4.63 

0.00 

391.51 

98.89 

2.24 

0.00 

3.22 

31.53 

30.30 

0.00 

15.85 

73.23 

9.44 

75.90 

12.89 

217.51 

0.00 

3.25 

1343.91 

9.73 

0.00 

30.21 

5.84 

7.76 

8.88 

34.44 

209.68 

0.00 

88.75 

12.67 

1.85 

41.07 

33.77 

15.74 

121.59 

11.62 

136.83 

21.96 

65.47 

9.85 

4.76 

0.22 

and 

Education 

12.65 

64.05 

77.27 

25.82 

2.06 

35.80 

67.71 

39.28 

45.41 

44.09 

36.23 

38.12 

47.25 

54.40 

0.00 

110.11 

46.41 

81.84 

0.00 

27.56 

49.22 

52.79 

7.47 

5.41 

128.05 

14.88 

91.36 

29.62 

43.35 

16.08 

8.12 

89.19 

33.18 

11.64 

36.17 

53.97 

28.01 

21.14 

15.31 

182.80 

15.09 

55.25 

19.06 

13.70 

64.44 

11.96 

10.49 

82.08 

0.00 

257.00 

90.22 

38.92 

46.44 

96.80 

35.91 

Other 

10.28 

289.26 

450.41 

39.91 

22.68 

408.99 

151.61 

77.17 

139.66 

26.05 

85.85 

169.16 

128.76 

54.40 

13.07 

132.42 

146.40 

113.46 

41.80 

71.85 

134.63 

177.91 

136.77 

157.00 

514.61 

42.11 

64.65 

46.36 

167.43 

131.96 

116.95 

855.06 

70.60 

67.10 

392.37 

135.24 

u37.04 

62.32 

265.23 

88.71 

78.93 

222.29 

362.32 

98.89 

263.44 

50.42 

29.99 

1092.50 

600.19 

219.07 

353.08 

70.71 

87.71 

120.61 

105.90 

Estimated Household Burdens From: 

Real Earned Trash 

Estate 

Tax 

100 

739 

236 

958 

38 

81 

75 

176 

102 

756 

12 1 

156 

129 

75 

72 

3 18 

163 

209 

159 

248 

176 

111 

198 

182 

192 

204 

84 

105 

152 

126 

293 

169 

147 

99 

205 

100 

128 

115 

175 

106 

91 

143 

128 

93 

69 

44 

69 

98 

272 

106 

106 

71 

202 

82 

145 

Income 

Tax 

28 

260 

95 

378 

169 

50 

57 

68 

44 

3 10 

58 

61 

60 

53 

64 

67 

88 

82 

55 

96 

58 

54 

104 

108 

85 

85 

71 

109 

74 

123 

150 

92 

76 

93 

129 

115 

130 

141 

94 

62 

93 

63 

119 

74 

123 

73 

93 

59 

163 

122 

138 

124 

150 

12 1 

107 

Collection 

/Disposal 

61 

0 

0 

6 

6 

33 

44 

0 

46 

0 

46 

0 

0 

6 

6 

0 

0 

0 

0 

0 

23 

0 

0 

0 

0 

33 

107 

6 

24 

6 

0 

0 

0 

24 

5 

6 

0 

5 

15 

6 

62 

0 

0 

6 

6 

6 

6 

7 

4 

6 

6 

44 

5 

5 

47 

Total 

Burden 

189 

999 

332 

1,341 

2 13 

163 

176 

244 

191 

1,066 

225 

217 

189 

134 

142 

384 

250 

291 

214 

343 

257 

165 

302 

290 

277 

322 

262 

220 

249 

254 

443 

26 1 

222 

216 

340 

220 

257 

262 

284 

174 

246 

206 

247 

172 

198 

123 

168 

164 

439 

234 

249 

238 

358 

208 

299 

Burden as 

Percent of 

Household 

Income 

1.03 

1.48 

1.09 

1.14 

0.51 

0.71 

0.69 

0.96 

0.92 

1.38 

0.98 

0.88 

0.75 

0.64 

0.58 

1.47 

0.93 

1.06 

0.88 

1.06 

1.10 

0.85 

0.58 

0.92 

0.86 

1.01 

1.20 

0.72 

0.95 

0.78 

1.25 

1.14 

0.83 

0.75 

0.97 

0.60 

0.72 

0.75 

0.96 

0.70 

0.98 

0.85 

0.73 

0.60 

0.67 

0.50 

0.62 

0.60 

0.85 

0.58 

0.66 

0.81 

0.88 

0.50 

0.98 

100 U.S. Advisory Commission on Intergovernmental Relations 
Table A-4 (cont.) 

Employment, Household Burdens, 1985 

Emplovees Per 1.000 Residents-1985 

Manu- and 

Government 

Municipality Retail facturing Education Other 

Home Rule Municipalities 

McKeesport 84.45 

Bellevue 72.79 

Bethel Park 73.42 

Bradford Woods 3.67 

Green Tree 67.41 

Monroeville 231.85 

Whitehall 19.55 

McCandless 66.43 

Mt. Lebanon 53.54 

Ohara 116.22 

Penn Hills 44.72 

Upper St Clair 124.17 

Hampton 79.29 

Indiana 7.49 

Richland 80.40 

West Deer 12.36 

26.09 

1.37 

5.17 

0.00 

21.33 

7.51 

4.30 

1.85 

0.00 

141.98 

3.79 

2.27 

9.10 

4.99 

47.90 

7.14 

88.57 

29.72 

40.05 

0.00 

280.39 

52.01 

50.26 

45.08 

38.25 

82.41 

35.30 

36.88 

38.90 

37.43 

45.24 

12.26 

249.83 

148.72 

103.57 

11.01 

1353.53 

339.54 

106.42 

185.53 

165.60 

495.24 

102.18 

118.53 

9 1.17 

179.47 

189.33 

48.42 

Estimated Household Burdens From: 

Real Earned 'kash 

Estate Income 

Tax TaX 

192 127 

145 118 

112 208 

96 226 

153 139 

105 165 

123 194 

143 168 

384 172 

194 335 

125 195 

284 36 1 

149 156 

163 109 

149 119 

119 106 

Collection 

/Disposal 

43 

0 

0 

5 

0 

0 

2 

6 

0 

0 

0 

0 

5 

5 

6 

6 

Total 

Burden 

363 

263 

321 

327 

292 

270 

3 19 

3 17 

556 

529 

320 

646 

3 10 

277 

274 

230 

Burden as 

Percent of 

Household 

Income 

1.69 

1.10 

0.81 

0.49 

0.76 

0.77 

1.02 

0.69 

1.11 

0.99 

1.03 

0.98 

0.79 

0.72 

0.87 

0.79 

U.S. Advisory Commission on Intergovernmental Relations 101 

Recent Publications of the 

U.S. Advisory Commission on Intergovernmental Relations 

Significant Features of Fiscal Federalism, 1992 Edition, Volume I, M-180, 1992. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 

State Taxation of Interstate Mail Order Sales, M-179, 1991. . , , . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 

Significant Features of Fiscal Federalism, 1991 Edition, 

$20 

$10 

$20.00 

. , . . . . . . . . , . , $22.50 

The Changing Public Sector: Shifts in Governmental Spending and Employment, M-178, 1991 . . . . . . . . . . . . . . . . . . $15.00 

Coordinating Water Resources in the Federal System: The Groundwater-Surface Water Connection A-118, 1991 . . $15.00 

Changing Public Attitudes on Governments and Taxes: 1990, S-20, 1991 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $10.00 

Interjurisdictional Tax and Policy Competition: Good or Bad for the Federal System?, M-177, 1991 . . . . . . . . . . . . . . $10.00 

State-Local Relations Organizations: The ACIR Counterparts, A-117, 1991 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $10.00 

Directory of State-Local Relations Organizations: The ACIR Counterparts, A-l17D, 1990 . . . . . . . . . . . . . . . . . . $2.00 

State Taxation of Telecommunications, A-116. 1990 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $10.00 

The Structure of State Aid to Elementary and Secondary Education, M-175. 1990.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . $10.00 

Representative Expenditures: Addressing the Neglected Dimension of Fiscal Capacity, M-174, 1990 . . . . . . . . . . . . . . $20.00 

Mandates: Cases in State-Local Relations, M-173, 1990 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $10.00 

1988 Fiscal Capacity and Effort, M-170, 1990 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $20.00 

State Constitutional Law: Cases and Materials, 1990-91 Supplement, M-172, 1990 . . . . . . . . . . . . . . . $7.00 

............ $10.00 

The Volume Cap for Tax-Exempt Private-Activity Bonds: State and Local Experience in 1989, M-171, 1990. . . . . . . . $7.50 

Significant Features of Fiscal Federalism, 1990 Edition, Volume I, M-169,1990 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $17.50 

Volume 11, M-169-11, 1990.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . , . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $17.50 

State and Local Initiatives on Productivity, Technology, and Innovation, A-114, 1990 . . . . . . . . . . . . . . . . . . . . . . . . . . . $25.00 

Local Revenue Diversification: Rural Economies, SR-13, 1990 . . . . . . . . . . . . 

State Taxation of Banks: Issues and Options, M-168, 1989. . . . . . . . . . . . . . . . 

A Catalog of Federal Grant-in-Aid Programs to State and Local Governments: Grants Funded FY 1989, 

Volume I, M-176, 1991.. . , . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . I . . . . . . . . . *. . . . . . . . . . . . . . . . . . . . . . . . Volume 11, M-176-11, 1991.. . . . . . . . . . . . . . .................. ..... 

Intergovernmental Regulation of Telecommunications, A-115, 1990 . . . . . . . . . . . . . . . . . . . 

M-167, 1989 . . . . . . .. t.. . ............ . .. . . . ........... . . .. . . .............................. $10.00 

$8.00 

$15.00 

$5.00 

$10.00 

........................ $10.00 

........................ $10.00 

Local Revenue Diversification: Local Sales Taxes, SR-12, 1989. . . . . . . . . . . . . . . . . . . . . . . . . . . . 

State Constitutions in the Federal System: Selected Issues and Opportunities for State Initiatives, A-113, 1989 . . . 

Residential Community Associations: Questions and Answers for Public Officials, M-166, 1989 . . . . . . . . . . . . . . . . . . 

Residential Community Associations: Prikate Governments in the Intergovernmental System? A-112, 1989 . . . . . . . 

Disability Rights Mandates: Federal and State Compliance with Employment Protections 

Hearings on Constitutional Reform of Federalism: Statem 

State and Federal Regulation of Banking: A Roundtable D 

Devolution of Federal Aid Highway Programs: Cases in State-Local Relations and Issues in State Law, M-160, 

State Constitutional Law: Cases and Materials, M-159, 1988,480 pp. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 

Local Revenue Diversification: Local Income Taxes, SR-10, 1988,52 pp. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 

Metropolitan Organization: The St. Louis Case, M-158, 1988, 176 pp. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . , . . . . . . . . . . 

Interjurisdictional Competition in the Federal System: A Roundtable Discussion, M-157, 1988, 32 pp. . . . . . . . . . . . . . 

State-Local Highway Consultation and Cooperation: The Perspective of State Legislators, SR-9, 1988, 54 pp. . . . . . 

Readings in Federalism-Perspectives on a Decade of Change, SR-11, 1989 . . . 

and Architectural Barrier Removal, A-111, 1989 . . . . . 

Government Association Representatives, M-164, 1989 .................. ..... $5.00 

$5.00 

$10.00 

$5.00 

$10.00 

$25.00 

$5.00 

$10.00 

$5.00 

5.00 

..... ...... $5.00 

......... $5.00 

$10.00 

..... . . . . . . . . . . . . . . 

Assisting the Homeless: State and Local Responses in an Era of Limited Resources, M-261, 1988 . . . . . . . . . . . . 

State Regulations of Banks in an Era of Deregulation, A-110, 1988, 36 pp.. . . , . . . . . . . . . . . . . . . . . . . . . . . 

The Organization of Local Public Economies, A-109, 1987, 64 pp. . . . . . . . . . . . . . . . . . . . . . . . . . . . 

Local Revenue Diversification: User Charges, SR-6, 1987,64 pp. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 

Devolving Selected Federal-Aid Highway Programs and Revenue Bases: A Critical Appraisal, A-108, 1987,56 pp. . .