Representative Expenditures: 

Addressing the 

Neglected Dimension 

of Fiscal Capacity 

ADVISORY COMMSSION ON I INTERGOVERNMENTAL RELATIONS I 

December 1990 

ROBERT W. RAFUSE, JR. 

M-174 

An Information Report 
U.S. Advisory Commission on 

Intergovernmental Relations 

1111 20th Street, NW 

Suite 2000 

Washington, DC 20575 

(202) 653-5640 

FAX (202) 653-5429 

il Advisory Commission on Intergovernmental Relations 
Executive Summary 

Formulas by which federal grants to state and local 

governments are allocated have included a measure of the 

fiscal capacities of the states for more than half a century. 

For most of that time, the measure has been a matter of 

considerable controversy. The fii programs taking account 

of fiscal capacity enacted during the Great Depression relied 

on per capita personal income for this purpose, and that 

measure reigned supreme for decades thereafter. 

Indeed, no other indicator of fiscal capacity appeared 

in federal legislation until the Alcohol, Drug Abuse, and 

Mental Health Block Grant was reauthorized in 1987. 

That law substituted the per capita value of a new variable 

called total taxable resources for per capita income in the 

allocation formula. 

Fiscal Capacity and Per Capita Personal income: 

The Problem 

Fiscal capacity is, in essence, an indicator of the 

relative fiscal well-being of all the governments in a state, 

as a group. (Fiscal capacity is also an attribute of the fiscal 

circumstances of an individual government. IIb simpllfy 

the discussion, references in this summary are limited to 

all governments in a state.) More spedkally, the fiscal 

capacity of a state is the potential ability of its governments 

to raise revenue from their own sources relative to the cost 

of their service responsibilities, allowing for revenues 

received from the federal government and other states. 

For decades, the controversy surrounding per capita 

personal income as a measure of fisml capacity focused on 

the validity of personal income as the indicator of 

revenue-raising ability. In 1962, the Advisory Commission 

on Intergovernmental Relations weighed into the debate 

with a report setting forth the Representative 2-w System 

@’IS) as a more comprehensive and realistic measure of 

revenue-raising ability. 

The RTS is, in essence, the average (or representative) tax system actually in use by the nation’s state and 

local governments. The estimated yield of that system in 

each state is a state’s “tax capacity.” That estimate, 

dividedby total population, is referred to as fiscalcapacity, 

following the established practice for personal income. 

Few questions were raised about the expression of 

these measures on a per capita basis until the past few 

years, when analysts began to challenge the implicit 

assumption of the convention that the costs of the service 

responsibilities of a state’s governments, or “needs,” 

depend only on the state’s total population. This report is 

about this issue. It presents an approach to the measure- ment of the relative public service needs of the states that 

is the expenditure-side analog of the RTS. 

Fiscal capacity relates to a state’s potential, not to the 

actual policies of its governments. Those policies determine 

the extent to which the state’s fiscal potential is being 

exploited, but not the potential itself. (Over time, a state’s 

actual policies may promote or depress its potential, but 

these interactions are tcu~ complex and too little understood 

to be taken into account empirically.) For this reason, the 

fundamental prerequisite for any measure of service 

costs-as of a measure of revenue-raising ability-is that it 

abstract as completely as possible from the actual tax and 

expenditure policies of any individual state. 

Sources of Variation 

in the Costs of Public Servlces 

Given that the actual policies of any one state are to be 

disregarded, variations in the costs of public services among 

the states depend on three general classes of factors: 

The range and types of services that must, by law, 

be provided. 

The prices of the inputs used to produce public 

services, such as wages and salaries, gasoline 

prices, and the cost of asphalt. 

Factors that determine the scope of the services 

provided, such as traffic and the miles of 

highways that must be maintained. 

rn 

Legal Requirements 

The services for which a jurisdiction is responsible are 

a key consideration in the cost of government at the local 

level, where obligations prescribed by state law vary 

among the states and among different types of local 

governments. At the state level, however, requirements 

imposed by the federal government apply uniformly 

throughout the nation, and the states are essentially free 

to offer whatever arrays of services they may choose. 

Their choices are, of course, embodied in policies, from 

which the analysis must abstract. Hence the first of the 

three types of factors is not germane in considering 

differences in the costs of public services that are not the 

result of the policies of the governments in a state. 

Prices 

The prices of the goods and services purchased by 

state and local governments vary with climate, with 

Advisory Commission on Inter- Mations iii 
distance from the point of production, between rural and 

urban areas, and as a consequence of state-local govern- ment policy. For example, state laws relating to the 

compensation of public employees vary widely, with major 

consequences for the costs of public services. Cost 

differences traceable to the policies of state and local 

governments must be abstracted from, however. 

'Ibo little information is available on the prices paidby 

the states and localities to permit estimation of a 

comprehensive index of the relative input costs of 

governments in all of the states. It is possible, however, to 

estimate the differences among the states in the cost of 

employee compensation. This cannot be accomplished by 

looking at actual payments to state and local employees 

because those payments reflect policy as well as underlying economic realities. Rather, the reference must be to 

the relative compensation state and local governments 

must pay to compete effectively in the market. The closest 

approximation to this magnitude is the statewide average 

earnings of full-time employees of a given age, sex, and 

level of educational attainment. 

Such estimates are developed for the first time in this 

report using data from the 1980 census on average 

earnings in each 'state. The estimates of differences in 

employee earnings are, in turn, used to compute a 

quasi-index of relative input costs for each major function. 

The index assumes that unit costs other than employee 

compensation are uniform around the nation. 

A separate index is developed for each function 

because employee compensation, which averages about 

half of all state-local outlays, varies dramatically among 

functions. That compensation, for example, accounts for 

8lpercent of outlays for police and corrections but only 13 

percent of expenditures for public welfare. Hence all of 

the estimates of representative expenditures presented in 

this report are adjusted for differences among the states 

in the cost of employee compensation. 

Scope of Services 

This leaves the factors that influence the amount or 

mpe of public services that must provided, and it is 

accounting for their variability that is the primary purpose 

of the representative expenditure approach. 

Estimating 

Representative Expenditures 

The RTS achieves policy neutrality by estimating the 

yield in each state of a standard revenue system. Given 

the representative system, the key issue is the definition of 

the base of each tax and estimation of its value in each state. 

The representative expenditure approach parallels 

that of the RTS. The crucial step is the identification of 

the best possible measure of the workload for each of the 

major categories of state-local expenditures. A state's 

workload for a service indicates its relative need for 

butlays on that function, IIb ensure that the workload 

measures are independent of the actual policies of the 

governments in a state, such program-client variables as 

enrollment in public schools and the number of people 

receiving welfare benefits are not used. 

The workload measures for the categories of expendi- tures analyzed separately in this report are identified in 

iv ACMW commision on lntergovemmental ~e~ations 

Exhibit 1. They are derived from review of the literature 

and consultation with authorities in each functional area. 

Given the workload measure for a function, the 

representative expenditure per unit of workload is 

calculated by dividing the total of actual state and local 

outlays for the service by the U.S. total for the workload 

measure. A state's representative expenditure for the 

function is then arrived at by multiplying the representa- tive outlay per unit by the state's workload. The result is 

an estimate of how much it would cost the governments in 

a state to provide the national-average (representative) 

level of the service. 

Exhibit 1 

Workload Measures 

for Representative Expenditures 

1. Elementary and Secondary Education 

The workload measure is the wighted sum of three 

population groups: (1) children of elementary-school age 

(5-13) net of enrollment in private elementary schools, (2) 

youth of secondary-school age (14-17) net of private 

secondary enrollment, and (3) the population under 18 

living in households with incomes below the poverty line. 

The weights are, respectively, 0.6, 1.0, and 0.25. 

2. Higher Education 

The measure is the weighted sum of the population in 

the age groups 14-17,18-24,Z-34, and 35 and older. Each 

weight (1.32percent, 22.44 percent, 4.16 percent, and 0.83 

percent, respectively) is the full-time-equivalent number of 

students in the age gmup emlled in institutions of higher 

education nationwide as a proportion of the total population 

in the age group. 

3. Public Welfare 

The workload measure is the population living in 

households with incomes below the poverty line. 

4. Health and Hospitals 

The measure is the sum of the equally weighted 

percentage distributions of (1)pemns age 16-64 with work 

disabilities, (2) the population living in households with 

incomes be10.w 150 percent of the poverty line, and (3) the 

total population. 

5. Highways 

The workload measure is the weighted sum of the 

percentage distributions of two variables: (1) vehicle-miles 

traveled, and (2)lane-miles of streets and roads other than 

those on federally controlled land. The first is weighted 

0.825, the second 0.175. 

6. Police and Corrections 

The measure is the sum of the equally weighted 

percentage distributions of (1) the population age 18-24, (2) 

the number of murders committed, and (3) the total 

population. 

7. All Other Direct General Expenditures 

The workload measure is total population. 
Results of the Analysis 

mle ES-1 shows the actual general expenditures of 

state and local governments in the 50 states and the District 

of Columbia for the 10 major functions. The information is 

expressed in per capita terms indexed to U.S. averages to 

facilitate comparisons among the states. mtal actual 

spending for all functions ranges from 71 percent of the per 

capita national average in Arkansas to 371 percent in Alaska. 

The estimates of representative expenditures, adjusted for differences in input costs, are presented in 

nble ES-2 for the same 10 functions, also on a per capita basis indexed to the national average. Total population is 

the workload factor for the functions shown in columns 

&11. The breakout is presented to provide greater insight 

into the differences among the states than would be possible 

if the four were combined in a single, “all-other” categoly. 

Although the same workload is used for all four 

categories, the adjustment for differences in employee 

compensation is performed separately for each, in recognition of the varying importance of those costs. Interest on 

general debt is a somewhat peculiar category because it 

includes no employee compensation. As a consequence, the 

per capita representative expenditure in every state is 

identical to the U.S. average (the indexed value is 100.0). 

The range in the estimates of representative expendi- tures is much smaller than that in actual outlays: from a low 

of 85 in New Hampshire to a high of 121 in Alaska. New 

Hampshire’s unadjusted index of representative expendi- tures is 91. Unit labor costs in that state are only 86 percent 

of average, however, so the cost of producing nationalaverage public services is the lowest in the country. 

(Employee compensation accounts for approximately 46 

percent of state-local outlays in New Hampshire. Hence 

the state’s overall unit-cost index is (0.46 x 0.86 = 0.40) + 

0.54 = 0.94. That index times the state’s unadjusted index 

of representative expenditures yields its adjusted index: 

0.94~ 91 - 85.) 

Alaska’s position at the high end, on the other hand, 

is attributable largely to its extremely high unit labor 

costs, which are 134 percent of the U.S. average. Its index 

of representative expenditures unadjusted for those costs 

is only 103. me calculation is (0.52~ 1.34 = 0.67) + 0.48 = 1.17; and 1.17 x 103 = 121.) 

If the adjustment for input-costs were not made, 

production of the national-average level of public services 

would be most costly per capita in Mississippi, whose 

unadjusted index of representative expenditures is 122, 

and least costly in Connecticut, whose unadjusted index is 

88. Allowing for labor costs only 84 percent of the national 

average in Mississippi but 109 percent in Connecticut 

moderates their respective indices of representative 

expenditures to 113 and 92. 

’Igble ES-3 displays the ratios of actual expenditures 

to the representative estimates for each of the functions. 

Mississippi’s below-average actual spending and above- average needs yield a ratio of only 67 percent, at the 

bottom of the list of states, when consideration is given to 

both dimensions. Alaska remains at the top of the list, 

though with a ratio of 306 percent as a result of its high 

representative costs. 

A variety of general findings can be drawn from the 

estimates in libles ES-1 to ES-3 as well as from others 

discussed in the text. 

It is clear that population is an inferior measure of the 

relative cost to the governments of a state of providing a 

standard level of public services. Its use in a measure of 

fiscal capacity systematically overstates the capacities of 

states below the national average and understates the 

capacities of states above the national average. Fiscal 

disparities among the states are significantly larger than 

most measures available until now have suggested. 

The differences among states in the cost of providing a 

common level of public services are substantial. They are 

smaller, however, than the differences in own-revenueraising ability, by all measures currently available. 

High public service costs tend to be associated with 

low revenue-raising ability, 

The actual spending of three out of four states with 

fiscal capacities below the national average is less than 

their representative expenditures. 

The existing federal grant system, taken as a whole, 

tends to worsen fiscal disparities among the states. 

Therefore, the failure to allow for federal grants in a 

measure of state fiscal capacity results in systematic 

understatement of the magnitudes of fiscal disparities. 

Caveats and Advice on Interpreting the Results 

Three points deserve special emphasis in interpreting 

the results of the analysis. First, no implication should be 

drawn that the representative outlays are in any sense 

correct or “needed” in any absolute sense. The estimates 

merely show how much it would cost each state to provide 

the national-average level of each service. 

Second, the estimates assume that every government 

produces the representative level of each service with the 

same efficiency. In other words, a given level of spending 

per capita (adjusted for differences in compensation 

costs) buys the same level of service in every state. Hence 

no inferences about operating efficiency can be drawn 

from the relationship between actual spending for a 

function and the representative expenditures. 

Third, and a closely related point, the estimates are 

silent on the issue of performance. A dollar of spending 

(adjusted for differences in unit costs) in one state is 

assumed to yield the same quantity and quality of a service 

as it does in every other state. Although we know that 

public services are not of equal quality per dollar spent 

everywhere in the nation, it is, regrettably, impossible to 

take this into account because credible measures of 

performance are not available. 

Representative Expenditures 

and the Fiscal Capacities of Local Governments 

The representative expenditure approach outlined in 

this report and used to estimate the fiscal capacities of the 

states is equally ap liable, with appropriate adaptation, 

within a particular state. In fact, the approach, in 

combination with representative revenue methods, has 

been applied by ACIR staff in a recently completed analysis 

of Hawaii’s state-local fiscal system. The approach also has 

been adapted for a study of the fd capacities of the 23 

counties and the City of Baltimore in Maryland, and is 

currently being applied in developing estimates of the fiscal 

capacities of a sample of 40 municipalities in the Chicago 

metropolitan area. 

Advisory Commission on intergovernmentel Relatkna v 

to analysis of the F iscal capacities of local governments 
Table ES-I 

Indices of the Actual Direct General Expenditures of State and Local Governments 

Per Capita, by Function, 1986.87 

Education Health Police Environ- Interest Govern- Primary and and menr on mental 

and Public Hospi- Correc- and General Adminis- All 

State Total Secondary Higher Welfare tals Highways tions Housing Debt tration Other 

United States 

Standard Deviation 

Alabama 

Alaska 

Arizona 

Arkansas 

California 

Colorado 

Connecticut 

Delaware 

District of Columbia 

Florida 

Georgia 

Hawaii 

Idaho 

Illinois 

Indiana 

Iowa 

Kansas 

Kentucky 

Louisiana 

Maine 

Maryland 

Massachusetts 

Michigan 

Minnesota 

Mississippi 

Missouri 

Montana 

Nebraska 

Nevada 

New Hampshire 

New Jersey 

New Mexico 

New York 

North Carolina 

North Dakota 

Ohio 

Oklahoma 

Oregon 

Pennsylvania 

Rhode Island 

South Carolina 

South Dakota 

Tennessee 

Tk!eXaS 

Utah 

Vermont 

Virginia 

Washington 

West Virginia 

Wisconsin 

Wyoming 

(1) 

100.0 

25.8 

77.3 

370.7 

104.4 

71.0 

11 3.9 

105.6 

108.9 

111.3 

192.3 

87.6 

89.3 

105.4 

77.5 

93.8 

80.5 

93.6 

92.8 

77.7 

91.9 

92.2 

102.9 

111.5 

107.9 

122.2 

75.5 

77.0 

107.3 

92.3 

104.6 

83.3 

113.0 

100.3 

145.2 

77.4 

107.9 

90.7 

82.5 

104.6 

87.5 

103.8 

79.0 

94.7 

77.4 

86.5 

94.8 

102.4 

89.4 

103.4 

84.7 

105.9 

164.7 

(2) 

100.0 

19.6 

65.3 

283.8 

108.3 

82.9 

99.8 

112.9 

105.7 

102.6 

120.1 

89.0 

96.7 

73.8 

77.8 

90.9 

89.2 

90.9 

98.9 

68.7 

80.0 

96.5 

97.9 

98.6 

113.9 

116.5 

73.6 

84.6 

122.2 

100.1 

89.8 

93.7 

117.4 

105.2 

133.6 

88.8 

101.5 

97.7 

90.5 

113.6 

98.3 

92.5 

88.1 

87.9 

67.1 

103.3 

loo. 1 

110.3 

98.4 

105.7 

96.0 

107.8 

183.5 

(3) 

100.0 

25.3 

104.5 

174.1 

137.8 

81.1 

122.0 

117.3 

63.9 

161.1 

55.7 

54.5 

76.7 

108.9 

114.2 

92.0 

115.6 

150.0 

122.6 

89.9 

84.1 

82.5 

106.9 

71.2 

130.3 

135.5 

91.2 

90.0 

92.1 

125.7 

79.8 

72.2 

83.7 

120.1 

87.1 

119.2 

157.9 

98.5 

94.6 

122.9 

52.7 

82.7 

108.0 

95.0 

84.4 

103.9 

153.1 

131.6 

109.6 

120.1 

76.0 

134.1 

162.0 

(4) 

100.0 

42.2 

47.8 

168.6 

65.2 

69.1 

124.1 

85.1 

112.3 

65.6 

272.7 

52.0 

63.6 

86.6 

51.7 

102.5 

77.5 

91.9 

65.0 

82.1 

71.8 

129.8 

94.2 

155.0 

140.3 

145.7 

64.4 

66.0 

92.9 

79.1 

49.3 

77.8 

106.5 

66.7 

194.8 

59.9 

106.8 

118.9 

78.7 

64.6 

112.7 

151.6 

55.1 

66.3 

76.1 

48.2 

71.0 

105.3 

57.2 

95.5 

81.9 

148.0 

70.5 

(5) 

100.0 

34.5 

138.8 

104.5 

53.8 

74.0 

114.9 

88.3 

88.2 

63.0 

207.4 

103.5 

184.6 

79.1 

83.3 

67.3 

90.8 

107.0 

85.1 

55.5 

125.2 

49.9 

48.4 

118.8 

122.7 

110.4 

138.4 

93.7 

63.2 

113.2 

82.2 

52.4 

74.6 

86.6 

168.7 

86.7 

70.7 

87.8 

89.1 

75.2 

55.3 

84.1 

125.8 

51.8 

11 3.4 

80.4 

74.5 

41.9 

94.3 

83.7 

61.8 

73.4 

225.5 

(6) 

100.0 

37.7 

81.2 

518.3 

169.5 

99.7 

65.8 

116.0 

118.3 

127.1 

87.2 

81.6 

92.6 

63.7 

117.2 

102.6 

82.2 

146.7 

146.2 

115.9 

106.2 

112.4 

120.3 

77.5 

82.5 

146.9 

98.1 

88.2 

177.0 

132.5 

130.0 

121.8 

111.0 

148.4 

99.7 

75.3 

156.8 

82.2 

94.0 

107.1 

100.8 

77.3 

62.3 

161.8 

89.4 

112.2 

100.1 

158.1 

118.0 

116.2 

124.6 

121.4 

306.7 

(7) 

100.0 

40.3 

61.8 

226.8 

134.1 

47.4 

149.4 

103.9 

91.8 

103.5 

445.1 

116.6 

822 

106.1 

61.3 

93.6 

57.1 

62.5 

67.3 

58.4 

85.2 

60.8 

124.6 

97.4 

108.1 

77.0 

49.2 

75.3 

62.9 

61.3 

150.0 

67.0 

116.3 

97.1 

163.6 

80.0 

45.2 

88.6 

64.8 

87.9 

72.2 

82.6 

75.2 

57.6 

67.7 

77.6 

83.8 

56.5 

90.6 

92.2 

37.9 

87.0 

105.7 

(8) 

100.0 

31.6 

67.2 

368.2 

102.0 

59.8 

126.5 

109.5 

97.3 

112.5 

276.3 

111.0 

77.4 

154.1 

85.1 

100.6 

68.2 

78.8 

66.3 

77.1 

99.9 

102.8 

130.5 

122.4 

78.3 

124.3 

59.7 

71.6 

117.3 

70.8 

112.1 

71.5 

114.7 

89.2 

140.5 

59.9 

96.2 

83.1 

87.1 

103.0 

70.9 

83.9 

66.6 

76.0 

74.4 

92.7 

95.9 

78.5 

99.5 

124.3 

67.1 

110.3 

145.8 

(9) 

100.0 

67.9 

79.4 

1,048.7 

113.9 

62.9 

87.9 

121.8 

134.2 

211.1 

183.1 

100.5 

56.7 

141.1 

45.6 

93.4 

53.3 

66.2 

108.6 

103.3 

145.9 

91.0 

113.9 

107.9 

72.4 

151.3 

60.9 

66.7 

124.1 

74.5 

142.6 

115.2 

146.2 

129.9 

149.9 

44.8 

96.3 

71.4 

80.3 

150.2 

106.4 

155.0 

61.2 

107.8 

64.7 

107.0 

93.7 

100.0 

67.6 

74.2 

103.7 

82.2 

195.1 

(10) 

100.0 

35.2 

73.6 

502.5 

119.5 

60.1 

124.8 

138.2 

125.8 

138.9 

254.3 

109.3 

85.8 

145.7 

79.3 

89.9 

70.9 

82.4 

106.6 

75.9 

84.2 

81.6 

100.2 

110.7 

98.0 

109.7 

65.2 

68.6 

114.8 

75.9 

153.4 

84.6 

119.0 

114.3 

132.5 

74.9 

87.0 

86.5 

77.7 

120.3 

82.1 

106.1 

63.3 

85.2 

68.7 

76.4 

109.1 

110.9 

102.5 

102.0 

82.8 

87.6 

163.3 

(11) 

100.0 

51.0 

78.6 

665.7 

77.4 

48.5 

139.1 

82.8 

153.1 

99.2 

205.1 

91.0 

68.7 

163.7 

63.8 

103.2 

69.8 

57.6 

72.4 

69.9 

81.1 

83.9 

112.0 

144.3 

95.0 

102.8 

53.7 

56.8 

93.2 

69.5 

139.7 

72.4 

140.5 

74.1 

173.6 

63.4 

135.1 

67.1 

57.1 

112.2 

93.5 

123.3 

66.2 

155.8 

77.4 

59.2 

73.4 

106.3 

63.1 

108.0 

89.1 

77.1 

113.7 

Source: Bble €3-1. 

vi Advisory Commission on Intergovernmental Relations 
Table ES-2 

Indices of the Estimates of Representative State-Local Expenditures Per Capita, 

Adjusted for Input-Cost Differences, by Function, 1986.87 

Educat ion Health Police Environ- Interest GovernPrimary and and ment on mental 

and Public Hapi- Corn- and General Adminis- All 

State Total Secondary Higher Welfare tals Highways tions Housing Debt tration Other 

United States 

Standard Deviation 

Alabama 

Alaska 

Arizona 

Arkansas 

California 

Colorado 

Connecticut 

Delaware 

District of Columbia 

Florida 

Georgia 

Hawaii 

Idaho 

Illinois 

Indiana 

Iowa 

Kanaaa 

Kentucky 

Maine 

Maryland 

MaJJachusetts 

Michigan 

Minnesota 

Miasksippi 

Missouri 

Montana 

Nebraska 

Nevada 

New Hampshire 

New Jersey 

New Mexico 

New York 

North Carolina 

North Dakota 

Ohio 

Oklahoma 

Oregon 

Pennsylvania 

Rhode Island 

South Carolina 

South Dakota 

Xmnessee 

mas 

Utah 

Wnnont 

Viinia 

Washington 

West Virginia 

Wisconsin 

Wyoming 

bUkM 

(1) 

100.0 

6.4 

108.8 

121.3 

102.6 

106.0 

101.3 

98.1 

91.7 

96.1 

102.9 

92.6 

108.6 

89.6 

100.1 

102.4 

99.3 

95.8 

98.4 

108.3 

110.4 

89.0 

97.0 

87.3 

108.3 

98.0 

113.3 

100.2 

102.0 

96.2 

95.9 

85.4 

93.1 

110.6 

95.3 

98.6 

105.2 

99.9 

103.8 

97.9 

90.4 

85.8 

103.3 

104.7 

103.5 

109.7 

104.9 

89.1 

98.6 

98.6 

102.7 

94.2 

102.2 

(2) 

100.0 

11.9 

107.9 

150.2 

103.0 

105.2 

101.1 

101.1 

89.7 

87.1 

73.0 

79.1 

109.9 

85.5 

113.0 

105.8 

106.6 

97.0 

96.2 

108.5 

110.1 

83.4 

94.8 

81.4 

115.2 

99.0 

112.9 

95.0 

100.0 

90.6 

95.3 

82.1 

92.3 

112.1 

89.6 

96.6 

96.6 

105.0 

106.2 

99.2 

85.6 

77.9 

102.9 

91.4 

100.6 

120.8 

140.7 

82.5 

96.1 

101.6 

109.1 

93.7 

113.5 

(3) 

100.0 

6.0 

94.9 

1 30.3 

97.2 

88.4 

103.6 

102.2 

105.1 

105.1 

98.7 

86.5 

99.9 

102.2 

86.4 

106.4 

101.6 

94.5 

94.4 

101.0 

105.6 

85.8 

108.2 

101.6 

111.0 

101.8 

91.8 

95.1 

86.7 

91.5 

97.6 

93.8 

104.1 

93.1 

100.2 

94.9 

91.6 

101.5 

95.0 

94.0 

97.8 

97.7 

97.0 

83.3 

94.8 

102.6 

97.4 

90.6 

105.2 

100.9 

94.2 

100.0 

93.3 

(4) 

100.0 

21.1 

145.5 

92.8 

110.6 

144.8 

96.0 

84.6 

59.3 

91.7 

140.7 

103.9 

127.9 

81.1 

104.3 

100.7 

86.9 

90.1 

89.9 

135.7 

145.2 

91.4 

77.0 

69.3 

95.8 

85.2 

181.7 

108.8 

100.9 

94.8 

73.5 

60.4 

71.1 

146.4 

98.5 

111.8 

110.3 

93.6 

102.9 

89.2 

76.6 

73.8 

125.5 

146.3 

126.4 

114.3 

86.4 

84.5 

90.8 

82.5 

116.2 

77.9 

65.9 

(5) 

100.0 

8.9 

115.5 

104.6 

104.9 

117.7 

102.8 

92.1 

83.5 

95.5 

117.4 

99.3 

112.4 

83.5 

93.5 

101.6 

94.3 

88.2 

89.9 

120.4 

119.1 

88.7 

94.5 

84.1 

109.7 

90.7 

124.2 

102.8 

91.1 

86.3 

89.6 

77.2 

89.2 

108.5 

97.8 

100.6 

88.4 

101.8 

104.7 

101.8 

92.3 

88.4 

104.7 

96.8 

110.3 

101.6 

87.1 

84.2 

96.5 

98.8 

114.5 

85.3 

78.1 

(6) 

100.0 

21.6 

117.5 

113.8 

112.3 

111.4 

93.7 

110.1 

97.0 

109.1 

58.4 

89.1 

119.1 

73.4 

119.1 

84.4 

102.8 

120.3 

145.7 

105.8 

87.5 

108.5 

93.2 

81.4 

104.6 

122.9 

106.7 

114.4 

186.7 

146.8 

122.0 

102.3 

85.2 

137.7 

65.1 

101.7 

223.9 

90.1 

137.9 

111.4 

80.2 

69.4 

109.6 

193.0 

108.1 

115.6 

100.3 

118.2 

109.6 

108.1 

94.5 

113.1 

197.4 

(7) 

100.0 

16.3 

97.4 

140.9 

94.3 

86.2 

113.7 

90.0 

92.2 

89.9 

204.8 

101.3 

110.9 

85.8 

68.7 

108.3 

90.1 

71.0 

79.9 

96.5 

115.9 

63.7 

112.5 

77.6 

128.8 

78.6 

96.2 

96.0 

71.9 

73.1 

97.3 

71.3 

90.5 

98.6 

113.3 

90.6 

65.0 

92.8 

92.0 

85.1 

87.4 

77.4 

96.1 

60.3 

97.0 

116.4 

77.9 

66.6 

97.9 

90.4 

81.5 

80.4 

71.7 

(8) 

100.0 

2.5 

97.0 

111.7 

99.1 

95.4 

102.0 

100.1 

103.0 

100.3 

98.7 

97.0 

98.1 

98.9 

95.3 

103.5 

100.2 

98.3 

98.3 

99.2 

100.9 

92.6 

102.1 

98.7 

104.2 

100.9 

94.7 

98.7 

95.3 

96.5 

99.4 

95.5 

102.9 

96.3 

100.4 

95.7 

95.6 

101.5 

98.2 

99.5 

100.1 

97.7 

95.8 

92.5 

97.4 

100.9 

98.4 

93.2 

99.4 

101.2 

98.0 

99.7 

98.8 

(9) 

100.0 

0.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

(10) 

100.0 

4.9 

94.3 

122.6 

98.3 

91.0 

103.9 

100.1 

105.9 

100.6 

97.5 

94.3 

96.3 

97.8 

90.9 

106.7 

100.4 

96.7 

96.6 

98.5 

101.8 

85.8 

104.0 

97.5 

108.1 

101.7 

89.8 

97.5 

90.9 

93.3 

98.8 

91.3 

105.6 

92.9 

100.8 

91.7 

91.6 

102.9 

96.5 

99.0 

100. 1 

95.6 

91.8 

85.6 

94.9 

101.8 

97.0 

86.8 

98.9 

102.3 

96.1 

99.3 

97.7 

(11) 

100.0 

2.0 

97.7 

109.1 

99.3 

96.4 

101.6 

100.1 

102.4 

100.2 

99.0 

97.7 

98.5 

99.1 

96.3 

102.7 

100.2 

98.7 

98.7 

99.4 

100.7 

94.3 

101.6 

99.0 

103.2 

100.7 

95.9 

99.0 

96.3 

97.3 

99.5 

96.5 

102.2 

97.2 

100.3 

96.7 

96.6 

101.1 

98.6 

99.6 

100.1 

98.2 

96.7 

94.2 

98.0 

100.7 

98.8 

94.7 

99.5 

100.9 

98.4 

99.7 

99.1 

Source: Thble B-3. 

Advisory Commission on Intergovernmentel Reletions vll 
Table ES-3 

Actual Direct General Expenditures of State and Local Governments 

as Percentages of Representative Expenditures Adjusted for Input-Cost Differences, 

by Function, 1986-87 

state 

~~~ 

Edufation Health Police Environ- Interest GovernPrimary and and ment on mental 

and Public Hospi- Correc- and General Adminis- All 

Total Secondary Higher Welfare tals Highways tions Housing Debt tration other 

United States 

Standard Deviation 

Alabama 

Alaska 

Arizona 

Arkansas 

California 

Colorado 

Connecticut 

Delaware 

District of Columbia 

Florida 

Georgia 

Hawaii 

Idaho 

Illinois 

Indiana 

Iowa 

Kansas 

Kentucky 

Louisiana 

Maine 

Maryland 

Massachusetts 

Michigan 

Minnesota 

Mississippi 

Missouri 

Montana 

Nebraska 

Nevada 

New Hampshire 

New Jersey 

New Mexico 

New York 

North Carolina 

North Dakota 

Ohio 

Oklahoma 

Oregon 

Pennsylvania 

Rhode Island 

South Carolina 

South Dakota 

'ILnnessee 

PXiS 

Utah 

Vermont 

Virginia 

Washington 

West Virginia 

Wisconsin 

Wyoming 

(1) 

100.0% 

25.6 

71.0 

305.7 

101.8 

67.0 

112.4 

107.6 

118.8 

115.8 

186.9 

94.6 

82.2 

117.6 

77.5 

91.6 

81.1 

97.7 

94.3 

71.7 

83.3 

103.5 

106.0 

127.7 

99.6 

124.7 

66.6 

76.8 

105.2 

95.9 

109.1 

97.5 

121.4 

90.7 

152.4 

78.5 

102.6 

90.8 

79.5 

106.9 

96.8 

121.1 

76.4 

90.5 

74.7 

78.9 

90.3 

114.9 

90.7 

104.9 

82.4 

112.4 

161.2 

(2) 

100.0% 

21.9 

60.5 

188.9 

105.2 

78.8 

98.7 

111.6 

117.9 

117.9 

164.4 

112.6 

87.9 

86.3 

68.8 

85.9 

83.7 

93.7 

102.7 

63.4 

72.7 

115.6 

103.2 

121.1 

98.9 

117.8 

65.2 

89.0 

122.2 

110.5 

94.2 

114.2 

127.1 

93.8 

149.2 

91.9 

105.0 

93.1 

85.2 

114.5 

114.9 

118.8 

85.6 

96.1 

66.7 

85.6 

71.1 

133.6 

102.4 

104.0 

88.0 

115.1 

161.7 

(3) 

100.0% 

24.6 

110.1 

133.6 

141.7 

91.8 

117.7 

114.8 

60.8 

153.2 

56.5 

63.0 

76.8 

106.5 

132.2 

86.5 

113.7 

158.6 

129.8 

89.0 

79.7 

96.2 

98.8 

70.0 

117.3 

133.2 

99.3 

94.6 

106.3 

137.4 

81.7 

77.0 

80.4 

129.0 

87.0 

125.6 

172.5 

97.0 

99.6 

130.8 

53.9 

84.6 

111.4 

114.1 

89.0 

101.3 

157.1 

145.3 

104.2 

119.0 

80.7 

134.1 

173.6 

(4) 

100.0% 

52.9 

32.8 

181.6 

59.0 

47.7 

129.3 

100.6 

189.4 

71.5 

193.8 

50.1 

49.8 

106.8 

49.6 

101.7 

89.2 

102.0 

72.3 

60.5 

49.4 

142.0 

122.4 

223.6 

146.4 

171.0 

35.4 

60.7 

92.0 

83.5 

67.1 

128.8 

149.9 

45.5 

197.8 

53.6 

96.9 

127.0 

76.5 

72.5 

147.1 

205.3 

43.9 

45.3 

60.2 

42.2 

82.2 

124.6 

63.0 

115.8 

70.5 

189.9 

107.0 

(5) 

100.0% 

33.9 

120.2 

99.9 

51.3 

62.9 

111.8 

95.9 

105.6 

66.0 

176.6 

104.2 

164.2 

94.7 

89.1 

66.2 

96.3 

121.2 

94.7 

46.1 

105.1 

56.2 

51.2 

141.3 

111.8 

121.8 

111.4 

91.2 

69.3 

131.1 

91.8 

67.8 

83.6 

79.8 

172.5 

86.2 

80.0 

86.2 

85.1 

73.9 

59.9 

95.1 

120.2 

53.5 

102.8 

79.1 

85.5 

49.8 

97.8 

84.7 

54.0 

86.1 

288.5 

(6) 

100.0% 

33.8 

69.1 

455.6 

151.0 

89.5 

70.2 

105.4 

121.9 

116.5 

149.4 

91.5 

77.8 

86.8 

98.3 

121.5 

80.0 

122.0 

100.3 

109.6 

121.3 

103.6 

129.0 

95.2 

78.9 

119.6 

91.9 

77.0 

94.8 

90.2 

106.5 

119.0 

130.3 

107.8 

153.1 

74.1 

70.0 

91.2 

68.2 

96.1 

125.7 

111.4 

56.9 

83.9 

82.7 

97.0 

99.8 

133.8 

107.7 

107.4 

131.8 

107.3 

155.3 

(7) 

100.0% 

27.9 

63.5 

160.9 

142.2 

55.0 

131.3 

115.4 

99.5 

115.1 

217.3 

115.1 

74.1 

123.7 

89.2 

86.4 

63.3 

88.0 

84.1 

60.6 

73.5 

95.4 

110.8 

125.5 

83.9 

97.9 

51.1 

78.4 

87.5 

83.8 

154.1 

93.9 

128.5 

98.5 

144.4 

88.3 

69.6 

95.5 

70.5 

103.4 

82.5 

106.7 

78.3 

95.6 

69.8 

66.6 

107.6 

84.7 

92.6 

102.0 

46.5 

108.2 

147.4 

(8) (9) 

100.0% 100.0% 

29.9 

69.3 

329.6 

102.9 

62.7 

123.9 

109.4 

94.4 

112.2 

279.9 

114.4 

78.9 

155.8 

89.3 

97.3 

68.0 

80.2 

67.4 

77.7 

99.0 

110.9 

127.8 

123.9 

75.2 

123.2 

63.0 

72.5 

123.2 

73.4 

112.8 

74.8 

111.4 

92.6 

139.9 

62.5 

100.6 

81.9 

88.7 

103.5 

70.8 

85.8 

69.6 

82.1 

76.4 

91.8 

97.4 

84.3 

100.1 

122.9 

68.4 

110.7 

147.6 

67.8 

79.4 

1,048.7 

113.9 

62.9 

87.9 

121.8 

134.2 

211.1 

183.1 

100.5 

56.7 

141.1 

45.6 

93.4 

53.3 

66.2 

108.6 

103.3 

145.9 

91.0 

113.9 

107.9 

72.4 

151.3 

60.9 

66.7 

124.1 

74.5 

142.6 

115.2 

146.2 

129.9 

149.9 

44.8 

96.3 

71.4 

80.3 

150.2 

106.4 

155.0 

61.2 

107.8 

64.7 

107.0 

93.7 

100.0 

67.6 

74.2 

103.7 

82.2 

195.1 

(10) 

100.0% 

30.7 

78.1 

409.8 

121.5 

66.1 

120.1 

138.0 

118.9 

138.1 

260.7 

115.9 

89.1 

149.0 

87.3 

84.3 

70.5 

85.2 

110.3 

77.0 

82.8 

95.1 

96.3 

113.5 

90.7 

107.9 

72.6 

70.4 

126.3 

81.3 

155.2 

92.7 

112.7 

123.1 

131.4 

81.6 

95.0 

84.1 

80.5 

121.5 

82.0 

111.0 

68.9 

99.5 

72.4 

75.0 

112.5 

127.7 

103.7 

99.7 

86.1 

88.2 

167.2 

(11) 

1OO.W 

48.1 

80.4 

610.4 

77.9 

50.3 

137.0 

82.8 

149.6 

98.9 

207.1 

93.1 

69.7 

165.2 

66.2 

100.6 

69.7 

58.3 

73.4 

70.3 

80.6 

89.0 

110.2 

145.7 

92.0 

102.2 

56.0 

57.3 

96.7 

71.4 

140.3 

75.0 

137.4 

76.3 

173.0 

65.6 

139.8 

66.3 

57.9 

112.7 

93.5 

125.5 

68.5 

165.4 

79.0 

58.8 

74.3 

112.2 

63.4 

107.0 

90.5 

77.3 

114.8 

Sources: Bbles Es-1 and €3-2. 

viii Advisory Commission on Intergovernmental Relations 
Preface and Acknowledgments 

This report adds a new dimension to the Advisory 

Commission on Intergovernmental Relations’ contribu- tions to measuring the fiscal capacities of state and local 

governments. Until now, measures of fiscal capacity have 

been expressed on aper capita basis. That is, the measures 

relate their evaluations of the revenue-raising potential 

of the states and local governments to the total population 

of a state. This convention effectively assumes that 

population is the important determinant of the “needs” of 

that state for public services. This assumption has long been 

criticized on the ground that, for example, the number of 

poor people living in a state is a much better indicator of the 

need for welfare programs than is total population. 

This report responds to the criticism by marshaling 

the best available information on the demographic and 

other relevant characteristics of the states to identify a set 

of measures of a state’s relative needs. The measures, 

developed for ten major categories of public services, 

include allowance for estimated differences among the 

states in the unit cost of employee compensation. 

Special care should be exercised by readers in 

drawing conclusions from, or making specific use of, the 

estimates of representative expenditures, especially in 

comparisons with actual spending. Particular attention 

should be paid to the observations throughout the text 

regarding the possible limitations of the measures and 

the reliability and currency of some of the data. This 

report is intended to promote discussion and analysis of 

the important issue of the comparative measurement of 

government spending, as ACIR’s numerous reports on 

public revenue systems-those on the Representative 

Thx System, in particular-have promoted constructive 

discussion of the financing of government. 

It is especially important to emphasize that the 

measures should not be interpreted as implying or 

necessarily supporting judgments about the performance 

or quality of government in any state. Performance cannot 

be judged by a government’s level of spending alonethough it can hardly be considered without reference to 

spending. The quality of a government’s performance is a 

matter of the relationship between the amount of its 

spending and the results achieved, a relationship commonly referred to as the efficiency (or effectiveness) of a 

government’s operations. We have to be concerned about 

what the children graduated from our public schools have 

learned, not just about how much is appropriated for 

teachers’ salaries and classroom construction. 

The report is silent on the issue of the results of 

government-the quality of performance, if you will- and no such implications should be read into the findings. 

The report offers estimates of the amount it would cost in 

each state to provide the national average level of public 

services if governments in every state were equally 

efficient. Outlays for a service that are lower than the 

estimate of a state’s representative level of expenditure 

for that service do not necessarily imply that the quality of 

the service actually delivered is below average. The 

information would be consistent with a situation in which 

the governments in the state are, on the whole, more 

efficient than average. In other words, the reality might be 

that services of average quality, perhaps even better than 

average, are being delivered in the state at a cost that is 

below the national average. 

The author and principal investigator for this study is 

Robert W. Rafuse, Jr., Senior Fellow at ACIR. We would 

like especially to express appreciation to the U.S. 

Department of the Tkeasury for its support of this 

research, which builds on work initiated by Dr. Rafuse 

during the Tkeasury studies of federal-state-local relations when the author was Deputy Assistant Secretary, 

State and Local Finance. 

We would like to thank the participants in a critics 

session on a draft of the report in March 1989, which 

yielded an array of constructive advice: Robert H. Aten, 

Manufacturers’ Alliance for Productivity and Innovation; 

John C. Camevale, U.S. Office of National Drug Control 

Policy; John R. Coleman, Port lbbacco, Maryland; Philip 

M. Dearborn, Maryland Commission on State Tmxes and 

Xu Structure; Robert Dinkelmeyer, U.S. General Accounting Office; Jerry C. Fastrup, U.S. General Accounting Office; Jay Ladin, Maryland Commission on State 

lbes and ’Ihx Structure; Hany G. Meyers, U.S. Office of 

Management and Budget; Vic Miller, Federal Funds 

Information for the States; Vincent Munley, Lehigh 

University; Will S. Myers, National Education Association; 

Max B. Sawicky, Economic Policy Institute; and Michael 

Springer, US. Department of the 2easury. Camevale, 

Fastrup, and Sawicky were particularly generous with their 

time in follow-up conversations on a variety of issues. 

Special thanks are due to Douglas H. Clark (FederalProvincial Relations Division, Department of Finance, 

Government of Canada) for enthusiastic encouragement 

Advisory Commission on Intergovernmental Relations Ix 
and trenchant comments from his special perspective 

north of theborder; Steven D. Gold (Center for the Study 

of States, Rockefeller Institute, State University of New 

York at Albany), whose complimentary 1989 article in 

State Legisratures prompted numerous inquiries about the 

study; Harold A. Hovey (publisher of State Policy Reports), 

whose suggestions were instrumental in shaping the 

analysis; Robert D. Reischauer (Congressional Budget 

Office), who suggested the approach used to compute the 

adjustment for differences among the states in unit input 

costs; John Shannon (The Urban Institute); Esther 

Shepherd (Population Estimates Branch, Population 

Division, U.S. Bureau of the Census), for special 

tabulations of school-age population for age groups not 

normally published; and Dennis Zimmerman (Congres- sional Research Service). 

A draft of this report was circulated to officials of all 

the states for review. In addition to acknowledgments on 

particular points appearing in the report, a number of 

officials whose contriiutions were “above and beyond. . .” 

deserve special mention: Dave Clark (Office of Manage- ment and Budget, State of North Dakota), Nancy Reuss 

(Management and Intergovernmental Systems, Budget 

Division, New York State), Henry Thomassen (Economic 

Advisor to the Governor of Georgia), Joseph LaFace 

(Economic Analysis and ’&x Research, Department of 

Finance and Administration, State of Arkansas), Ron 

Lanoue (Fiscal Affairs Division, Executive Office for 

Administration and Finance, Commonwealth of Massa- chusetts), Benjamin W. Mokry (Office of Policy Development, Department of Finance and Administration, State 

of Mississippi), Brad Pierce (Division of Policy, Office of 

Management and Budget, State of Alaska), Richard 

Drennon (Florida Advisory Council on Intergovernmental Relations), and Carol Meyers and Walter Davis 

(Department of Finance and Revenue, Government of 

the District of Columbia). 

Finally, at ACIR, we wish to thank Carol Cohen, who 

was always available to chat as the work progressed and who 

read the entire manuscript at one stage or another of its 

preparation and offered innumerable constructive com- ments; Clay Dursthoff, who almost always knows where the 

numbers are to be found; Joan Casey, who helped in 

rounding up especially elusive information sources and 

preparing the manuscript for publication; and Pamela 

Reynolds, who was there with word proCessing assistance. 

John Kincaid 

Executive Director 

Robert D. Ebel 

Director, Government Finance Research 

x Advisory Commission on Intergovernmental Relations 
Contents 

Chapter1.1 ntroduction .......................................................................................... 1 

What Is Fiscal Capacity? ...................................................................................... 1 

3 

OverviewoftheReport ....................................................................................... 3 

5 

7 

7 

Representative Expenditures: Basic Concepts ..................................................................... 8 

The Workload Measures ....................................................................................... 9 

1 . Elementary and Secondary Education ....................................................................... 10 

2 Higher Education ......................................................................................... 10 

3 . Public Welfare ........................................................................................... 12 

4 . Health and Hospitals ...................................................................................... 13 

5 .Highways ................................................................................................ 13 

6 . Police and Corrections .................................................................................... 15 

7 . All Other Expenditures .................................................................................... 15 

Variation in Public Input Costs ................................................................................. 16 

Chapter 4-Estimates of Representative Expenditures ............................................................... 19 

ActualExpenditures ........................................................................................... 19 

The Estimates of Representative Expenditures .................................................................... 21 

23 

25 

Fiscal Capacity Measures Reflecting Representative Expenditures Compared with Population ........................... 25 

An Alternative Statement of the Results ......................................................................... 29 

Disregarding Federal Grants ................................................................................. 29 

Taking Federal Grants into Account ........................................................................... 29 

Review of the Report by State Officials ......................................................................... 

Chapter2-The Variability of the Costs of Public Services ............................................................ Chapter 3-The Representative Expenditure Approach ............................................................... The Representative Tax System ................................................................................. 

Actual Outlays Compared with Representative Expenditures ........................................................ Recapitulation: The Regional Dimension ........................................................................ 

Chapter 5-Graphic Presentation of the Results by State ............................................................. Alabama .................... 36 Kentucky .................... 44 NorthDakota ................ Alaska ....................... 36 Louisiana .................... 45 Ohio ........................ Arizona ...................... 37 Maine ....................... 45 Oklahoma ................... Arkansas ..................... 37 Maryland .................... 46 Oregon ...................... California .................... 38 Massachusetts ................ 46 Pennsylvania ................. Colorado ..................... 38 Michigan ................... 47 Rhode Island ................. Connecticut .................. 39 Minnesota ................... 47 South Carolina ............... 

District ofColumbia ........... 40 Missouri ..................... 48 Tennessee .................... 

Hawaii ....................... 41 Nevada ...................... 50 Vermont ..................... Idaho ........................ 42 NewHampshire .............. 50 Virginia ..................... Illinois ....................... 42 New Jersey .................. 51 Washington .................. Indiana ...................... 43 New Mexico ................. 51 West Virginia ................ Iowa ......................... 43 NewYork ................... 52 Wisconsin .................... Kansas ....................... 44 North Carolina ............... 52 Wyoming .................... Chapter 6-Concluding Observations .............................................................................. 

Appendix A-Data Used for Estimation of Representative Expenditures ............................................... 1 . Elementary and Secondary Education ...................................................................... 2 Higher Education ........................................................................................ 3 . Public Welfare ........................................................................................... 4 . Health and Hospitals ..................................................................................... 5 . Highways ............................................................................................... 6 . Police and Corrections .................................................................................... 7 . All Other Direct General Expenditures ..................................................................... 

Delaware ..................... 39 Mississippi ................... 48 SouthDakota ................ 

Florida ....................... 40 Montana .................... 49 Texas ........................ Georgia ...................... 41 Nebraska .................... 49 Utah ........................ 

35 

53 

53 

54 

54 

55 

55 

56 

56 

57 

57 

58 

58 

59 

59 

60 

60 

61 

63 

65 

65 

66 

66 

66 

67 

67 

67 

AppdkB-BackgroundDataand Detail .......................................................................... 69 

Appendix C-Variation in the Cost of the Goods and Services Used by State and Local Governments 

to Produce Public Services 91 

92 

92 

94 

100 

Advisory Commission on intergovernmental Relations Xi 

.......................................................................... Measuring Input Costs: Conceptual Issues ....................................................................... An Index of the Prices Paid by State and Local Governments ...................................................... An Approach to Identifying Differences in Unit Labor Costs ...................................................... Estimating ............................................................................ a Unit-Input Cost Index 
Appendix D-Technical Discussion of the Representative Approaches to the Measurement of Fiscal Capacity 

and Comparison with ExportA4justed Income and Regression Approaches ............................... 105 

The Representative A proaches ................................................................................ 106 

Regression-Based Approaches to the Estimation of Public Service Costs ............................................. 108 

109 

Bradbury. Ladd. Perrault. Reschovsky. and Yinger on Local Government Needs in Massachusetts .................... 110 

111 

General Services ......................................................................................... 112 

Police ................................................................................................... 112 

Fire .................................................................................................... 113 

The Export-Adjusted P ncome Approach to the Measurement of Own-Revenue-Raising Ability ......................... 106 

Auten’s Estimates of Local Expenditure Needs in New York ..................................................... 

Ladd and Yinger on Measurement of the Fiscal Health of the Nation’s Cities ...................................... 

. 

Exhibits and Tables 

Exhibit 1 

Exhibit 2 

Table 1 

Table 2 

Table 3 

Table 4 

Table 5 

Table 6 

Table 7 

Table 8 

Table 9 

Table 10 

Table 11 

Table 12 

Table 13 

Table 14 

Table B-1 

Table B-2 

Tbble B-3 

Table B4 

Table B-5 

Table B-6 

Table B-7 

Table B-8 

Table B-9 

Table B-10 

Table B-11 

Table 8-12 

Table 8-13 

Table 8-14 

Table B-15 

Table 8-16 

Table B-17 

Table B-18 

Table B-19 

Table C-1 

Table C-2 

Table C-3 

Table C-4 

Table C-5 

Table C-6 

Table D-1 

Table 0-2 

Workload Measures for Representative Expenditures ..................................................... 9 

Comparison of Indices of Fiscal Capacity Calculated Using Resident Population and Input-Cost-Adjusted 

Representative Expenditures .......................................................................... 28 

Trend in Full-Time-Equivalent Enrollment in Higher Education. by A e. 1970-87 ............................ 10 

Actual lTE Enrollments in Public and Private Institutions of Higher hucation. by State. Compared 

with Enrollments Expected on the Basis of National-Average Propensities. Fall 1987 .......................... 11 

The Incidence of Poverty by Major Census Region in 1979 and 1987 ....................................... 12 

Average Annual Rates of Growth in Public Road and Street Mileage. Surfaced or Paved. 1904-87 .............. 13 

Direct General Expenditures by State and Local Governments: Functions Included in the “All Other” 

Category for Which the Workload Measure is Resident Population. 1986-87 ................................. 16 

Relative Costs of producing Public Servi~: Index of Unit Labor Costs and Implicit Index of All In t Costs. 1987 ... 17 

1ndices.of the Actual Direct General Expenditures of State and Local Governments Per Capita, by &n&n. 1!?86-87 . 2ll 

Indices of the Estimates of Representative State-Lmal Expenditures Per Capita Adjusted for Input-Cmt 

22 

Actual Direct General Expenditures of State and Local Governments as Percentages of Representative 

Expenditures Adjusted for Input-Cost Differences. by Function. 1986-87 .................................... 24 

Indices of Actual and Representative Expenditures and the Ratio of the Two. by Census Region. 1986-87 ....... 25 

Indices of Fiscal Capacity with Public-Service Costs Accounted for by Population and by Representative 

Expenditures Unad‘usted and Adjusted for Differences in the Unit Costs of Producin hblic Services. 1987 .... 26 

of Federal Grants .................................................................................... 30 

Gap between “Needs” and Revenue-Raising Ability in 1987. with No Account Taken of Federal Grants. 

Per Capita and Relative to Representative Expenditures .................................................. 31 

Calculation of the Gap Between “Needs” and Revenue-Raising Ability in 1987. with Account Taken 

of Actual Federal Grants .............................................................................. 

Direct General Expenditures of State and Local Governments. by Function. 1986-87 ......................... 70 

Direct General Expenditures of State and Local Governments. by Function. Per Ca ita. 1986-87 ............... 71 

Representative State-Local Expenditures b Function. 1986-87. Adjusted for Input$ost Differences ............ 72 

Representative StateLocal Expenditures by &ridon. Per Capita, 1986-87. Adjusted for Inputat Differences ...... 73 

Measures of Revenue-Raising Ability. 1986 or 1987 ....................................................... 74 

Derivation of a Workload Measure for Public Welfare. 1987 ............................................... 75 

Derivation of Estimates of the Number of Persons in Pove . 1987 ......................................... 76 

Derivation of Estimates of the Number of Children in Poverty. 1987 ........................................ 78 

Derivation of a Workload Measure for Elementary and Secondary Education. 1987 ........................... 79 

Enrollment in Elementary and Secondary Schools. Public and hvate. 1986 and 1987 ......................... 80 

Enrollment in Element and Secondary Schools. Public and Private. Fall 1980 ............................. 82 

84 

Derivation of a Workload Measure for Higher Education. 1987 ............................................ 86 

Derivation of a Workload Measure for Health and Hospitals. 1987 ......................................... 87 

Derivation of a Workload Measure for Highways. 1987 .................................................... 88 

Data Relatin to Highways. 1987 ....................................................................... 89 

Derivation ofa Workload Measure for Police and Corrections. 1987 ........................................ 90 

Mean Annual Earnings of Males 45-54 Years Old Who Worked 40 or More Weeks in 1979. by Years 

Indices of the Mean Annual Earnings of Males 45-55 Years Old Who Worked 40 or More Weeks in 1979. 

Labor-In ut-Cost Index Derived from Mean Annual Earnings of Males 45-54 Years Old Who Worked 40 

Payrolls of State and Local Governments. by Function. October 1986 Related to Direct General Expenditures. 

Payroll and Total Employee Compensation Costs as Percentage of All Direct General Expenditures by State 

Differences, by Function. 1986-87 ....................................................................... 

. 

Calculation of the Oap between “Needs” and Revenue-Raising Ability in 1987. with rf o bunt Taken 

331 

Derivation of Estimates of the Number of Persons under 15 3 Percent of the Poverty Level. 1987 ............... 77 

Trend in Population and ”t; i her Education Enrollment. by Age. Fall 1970-87 ................................ Trend in Higher Education knrollrnent. by Age. Fall 1970-87 .............................................. 85 

of Educational Attainment ............................................................................ 96 

by Years of Educational Attainment .................................................................... 98 

by Function. 1986-87 (dollar amounts in millions) ........................................................ 101 

and Local Governments. by Function. 1987 .............................................................. Inputat Indices for Major Functions. 1986-87 ......................................................... 103 

Calculation of Ladd-Yinger-Equivalent Overall Index of Standardized and Actual Fiscal Health. 1987 .......... 

or More Leeks in 1979. by Years of Educational Attainment. 1986 Weights (populations in thousands) ......... 99 

102 

107 

114 

Sources of the Own General Revenues of Local Governments Fiscal Year 1981-82 ........................... 

xii Advisory Commission on intergovernmental Relations 
Chapter 7 

Introduction 

More than a quarter-century ago, the Advisory Commission on Intergovernmental Relations published an information report setting forth a new approach to the 

measurement of the fiscal capacities of state and local 

governments.’ That report, prepared by Selma J. Mushkin 

and Alice M. Rivlin, developed the concept and presented 

preliminary estimates of the yield in each state in 1960 of a 

Representative ’Itur System (RTS). Subsequent Commission reports have refined the approach and updated the 

estimates; the most recent are for 19#L2 

Since the introduction of the RTS, estimates of per 

capita representative tax collections have come to be recognized by the technical community with virtual unanimity as a major improvement on per capita personal income 

as a measure of the fiscal capacities of state and local governments. The approach has not escaped criticism, however. Wo general types have been most important. 

The first type of criticism challenges the underlying 

logic of the RTS as a measure of the potential ability of 

state and local governments to raise revenues from their 

own sources, and questions the appropriateness and a m - 

racy of some of the methods used to estimate representative collections. The issues raised by this type of criticism 

‘Advisory Commission on Intergovernmental Relations, Masum of State and Local Fiscal Capaciw and Tm Effort 

(Washington, DC, 1962). 

2Advisory Commission on Intergovernmental Relations, 1988 

State Fiscal Capacity and Efirt (Washington, DC, 1990). This 

report also presents estimates of the yield of a Representative 

Revenue System (RRS) that includes-in addition to 27 

categories of taxes in the RTS-such nontax revenues of state 

and local governments as user charges and rents and royalties. 

Total RRS revenues amount to 89 percent of the total general 

revenues of the states and localities from own sources reported 

by the Bureau of the Census for 1987-88. The discrepancy 

exists because the RRS does not include interest earnings ($47 

billion), revenues from the sale of property ($1 billion), and 

miscellaneous revenues totaling approximately $19 billion; see 

U.S. Department of Commerce, Bureau of the Census, 

Government Finances in 1987-1988 (Washington, Dc, 1990) 

mle 6. To simphfy the win, only the RTS is referred to in 

the remainder of the present report the argument would not be 

signi6cantly different if the references weere to the RRS. 

of the RTS deserve serious consideration, but they lie 

outside the scope of this report.3 

The second criticism is that the RTS is flawed as a 

measure of fiscal capacity because it assumes implicitly that 

the costs of the service responsibilities of state and local 

governments depend solely on population. This report can 

be Viewed as a direct response to the second criticism. In 

essence, the estimates of representative expenditures 

yielded by the approach outlined in this report are intended 

to be an improved measure of the relative public service 

costs of the states. As such, their use-in lieu of 

population-in combination with the estimates of reve- nue-raising ability produced by the RTS (or other measure) 

would be a slgnrficant refinement of the measurement of the 

fiscal capacities of state and local governments. 

What Is Fiscal capacity? 

A brief review of the concept of fiscal capacity and the 

RTS approach to measuring it is in order at this point to 

establish the context of the present study. “Fiscal 

capacity” is most usefully defined as the potential ability 

of a state or local government to raise revenues from its 

own sources relative to the cost of its service responsibili- ties, with appropriate allowance for revenues received 

from other governments! 

The concept of the costs of the public service 

responsibilities of a government is difficult to define in the 

abstract. It is perhaps best understood as the common 

meaning of the term “needs,” which is used in this report 

as a synonym for relative public service costs. A rigorous, 

general definition of “need” or “needs” appears to have 

eluded the English language, howe~er.~ 

jFor a review of these issues, see U.S. Department of the 

?feasury, Office of State and Local Finance, Fedeml-StateLocal Fiscal Relations: Report to the President and the Congms 

(Washington, DC, 1985), Chapter VIII; and Stephen M. Bm, 

“Improved Measures of State Fiscal Capacity: Short-Term 

Changesin the PCI and RTS Indices,” in Robert W. Rafuse, Jr. 

(4.1 Fedeml-State-Local Fiscal &latiom: Technical Paper, 

Vol. I (Washington, DC U.S. Department of the lkasury, 

Office of State and Local Finance, 19861 pp. 187-261. 

neasury, Fcdeml-State-Local Relations, p. 207. 

5The definition of ‘‘need” by the American Heritage Dictionary 

of the English hguug@, for example, boils down to “some- thing required or wanted“ (Boston: American Heritage, 

Houghton Mifflin Company, 1975) p. 878. 

Advisocy Commission on Intergovernmental Relations 1 
Three general approaches to an operational definition of public service responsibilities suggest themselves: 

What the people “want”, 

What the people are willing to pay for, and 

What the experts say we ought to have. 

The first approach is better suited to the rhetoric of 

demagogues than to the demands of empirical analysis. 

In a democracy, of course, the wishes of the voters are 

the ultimate considerations on an issue, and the obliga- tion of elected officials is to be responsive to those 

wishes. In the end, however, this approach yields little 

more than a rationale for saying that-on the assump- tion that the system is working effectively-whatever a 

government is actually spending for public services is 

what the people want. This conclusion is not very help- ful; it certainly does not reflect the common under- standing of “needs” as something quite different from 

actual spending by every individual government. 

The second approach draws on the economic notion 

of effective demand, as opposed to wishes or wants. But 

this approach, like the first, threatens to reduce to the 

judgment that, if democratic government is working 

responsively, the public services actually provided must be 

the services the voters are willing to pay for. Again, we 

have no basis for an independent, evaluative definition of 

“needs.” Another problem with this approach derives 

from the dependence of effective demand on the existing 

distribution of income and wealth among the voters. One 

thing the concept of needs certainly comprehends is that 

they are independent of means. 

The third approach is perhaps the most common. It 

relies on normative definitions of “needs,” typically as 

prescribed by experts as the “correct,” “proper,” or 

“optimal” number of teachers per 100 pupils, square miles 

of parkland per 100,OOO population, or traffic lanes per 

1,OOO vehicles per hour. 

The history of the measurement of revenue-raising 

ability demonstrates the essential problem with a norma- tive approach. For several decades preceding the develop- ment of the RTS strategy in the early 196Os, measurement 

of the revenue-raising potential of state and local govern- ments relied on estimation of the yield in each state of a 

model, or ideal, tax system.6 The difficulty with this approach 

was that there was no shortage of competing ideas about 

model tax systems. Since each system could weight 

economic stocks and flows differently, each would produce a 

different set of estimates of relative revenue-raising abilities. 

The Same problem arises with the normative approach 

to the evaluation of needs. In some fields, prevailing 

standards reflect a strong consensus of experts. In other 

areas, however, major controversies rage among the 

technicians. An attempt to defme a single set of need 

standards for the entire range of public services viewed by 

one or another expert or interest as essential to the agenda 

6An early example of this approach is a study that estimated the 

yield in each state of a variation on a model tax system 

developed by the National Tax Association in the 19%; see 

Mabel Newcomer, An Index of the Tqaying Ability of State 

and Local Governments (New York: Columbia University, 

Teachers College, 1935). 

of government in the United States would be an invitation to 

endless debate, with negligible prospects for ultimate 

agreement. 

The answer is a purely positivistic approach, following 

the general strategy of the WS. By this approach, public 

service responsibilities are whatever all state and local 

governments in the nation, collectively, have demon- strated them to be by their actual fiscal decisions. It 

follows that the total cost of those responsibilities is equal 

to the total actual outlays of all states and local 

governments. This strategy offers an objective basis for 

quantitative analysis of the relative costs of the public 

service responsibilities of the states. A keyattniute of the 

approach, it must be emphasized, is that the analysis 

abstracts completely from the actual policies of any 

individual government and from the actual policies of all 

the governments, as a group, in any particular state. 

The yield of the Representative lhx System, referred 

to as “tax capacity,” is an indicator of the potential ability 

of all the governments in a state, as a group, to raise 

revenue from their own sources. When the estimate of tax 

capacity is divided by the population of the state, the 

resulting per capita yield of the HIS becomes an estimate of 

the state’s fiscal capacity. These estimates are customarily 

presented as an index, with the national average set at 100.’ 

Until recently, this practice of expressing tax capacity 

on a per capita basis was generally viewed as a 

mathematical convention whose purpose was to facilitate 

comparisons among the states. Some analysts, however, 

including Mushkin and Rivlin in their 1962 report, have 

long recognized that dividing estimates of representative 

tax yields by population has significant analytical implica- tions. As Mushkin and Rivlin note, 

. . . to express capacity on a per capita basis . . . implies that a State’s . . . public expenditure 

needs vary directly with its population. . . . The use of population as the sole indicator of 

needs for public services clearly leaves much to 

be desired! 

‘The per capita yield of the RTS in a state is divided by 

national average yield, and the result multiplied by 100. 

the 

Advisory Commission on Intergovernmental Relations, M a - sum of State and Local Fiscal Capacity and Effort, p. 9. Other 

analysts explicitly acknowledging the implication of expressing 

fiscal capacity measures on a per capita basis include George E 

Break, who observes in the first version of his study of 

intergovernmental finance that, 

. . . population, used as a divisor in . . . measures of 

fiscal capacity,. . . serves as a rough measure of. . . need for public services. Intergovernmental FkcalRelations in the United States (Washington, DC The 

Brooking Institution, 1967) p. 117. 

In a major updating and extension of the RTS approach in the 

mid-l970s, D. Kent Halstead notes, in explaining his presenta- tion of results in per capita terms, that tax . . . capacity. . . is most meaningful if it is related to 

public needs . The proxy chosen to express public 

needs is simple population count. (Emphasis in the 

original.) Tw Wealth in Filty States (Washington, DC 

U.S. Department of Health, Education and Welfare, 

National Institute of Education, 1!378), p. 7. 

Halstead reports the results of an “introductory effort” to develop 

“more exact comparative measures of relatiw public service re- quirements” in an appendix to this report. 

2 Advisory Commission on Intergovernmental Relations 
The problem is that the costs of the public service 

responsibilities of state and local governments depend 

on numerous important factors in addition to popula- tion. Although some of these factors cannot be taken 

into consideration because the data that would be 

required are not available, others certainly can be 

brought into the picture. The objectives of this report 

are to show how this can be done and to present the 

results of an effort to do SOP 

Review of the Report by State Officials 

A special procedure was followed in the production of 

this report at the request of ACIR’s Commissioners at the 

time they approved publication. A draft of the executive 

summary was sent to the governor, speaker of the house, 

and president of the senate of each state (and to the mayor 

and council chair of the District of Columbia) with a 

request for their review and comment. 

The letter accompanying the executive summary 

indicated particular interest in comments relating to 

special circumstances in a state that might help account 

for any unusual or especially striking aspects of the 

representative expenditure estimates or their relationships 

to actual spending levels. The letter also mentioned the 

Commissioned intent that comments on the findings 

relating to individual states be inmporated into the report. 

Responses were received from the governors of 24 

states, the house speakers of 3, and the senate presidents 

of 2 states. Responses going beyond acknowledgment of 

receipt of the materials were received from 13 governors, 

1 speaker, and 1 senate president. 

Ifthereisacommon themeof thecomments, it is that 

the representative approach is a significant improvement 

on conventional expenditure analysis performed with 

reference only to total resident population. Though an 

attempt isnot made to summarize or synthesize the entire 

set of comments here, specific observations, suggestions, 

and cautionary notes appear in the text or as footnotes 

wherever in the report they are most germane. 

A review of the recent technical literakm in the United States 

appears in Appendix D. An especially interesting collection of 

papers on the measurement of government expenditure 

needs, with particular emphasis on experience in Europe, 

appears in Gordon Cameron and Jurgen Lotz (eds), Measuring 

Local Government l5penditure Neeh: The Copenhagen Work- shop, Urban Management Studies (Pans: Organisation for 

Economic Cooperation and Development, 1981) 

Overview of the Report 

Chapter 2 of this report reviews the principal consider- ations that account for the variability of the costs of public 

services among governments. That discussion is followed in 

Chapter 3 by a summary of the basic logic of the 

representative expenditure approach and of the specific 

methods used to develop estimates of representative 

expenditures for the ten major categories of state-local 

outlays. 

The estimates themselves are presented in Chapter 4 

and compared with actual spending levels in the states. 

Regional differences in the estimates are also explored in 

this chapter. The index is used to determine the 

consequences for estimates of state fiscal capacities of 

using representative expenditures rather than population 

alone as the measure of the cost of the public services 

provided by state and local governments. The analysis 

considers four different measures of revenue-raising 

ability: resident personal income, RTS, gross state 

product (GSP), and total taxable resources m). Chapter 4 also expresses the results as gaps between 

the representative expenditures of a state and the 

revenues that would be raised if the state’s governments 

were to exert a national-average level of fiscal effort. The 

implications of the existing distribution of federal 

grants-in- aid for the revenues available to state and local 

governments in each state are also considered in the 

context of the gap analysis. 

Chapter 5 consists of a set of graphs, one for each 

state, portraying the estimates of representative expenditures on a per capita basis for the ten major functional 

categories. The estimates are related to a state’s actual 

per capita spending and to the U.S. average for each 

function. Some concluding observations and suggestions 

for potentially productive lines of further research are 

presented in Chapter 6. 

Details on the sources of the data used to derive the 

estimates of representative expenditures appear in 

Appendix A. A set of tables showing the data and 

calculations underlying the estimates is provided in 

Appendix B. Appendix C discusses differences among 

governments in input costs and summarizes the method 

used to derive an index of the variation in such costs 

among the states. 

Appendix D presents a technical description of the 

representative expenditure and revenue approaches and 

compares them with other methods of arriving at 

estimates of the elements of measures of fiscal capacity. 

Advlsory Commission on lntergovemmmtal Relations 3 
4 Advisory Commission on Intergovernmental Relations 
Chapter 2 

The Variability of the Costs 

of Public Services 

As noted earlier, the expression of a measure of fiscal 

capacity in per capita terms assumes that variation in 

population is the only source of differences in the costs of 

public services among areas. This assumption is not 

entirely wrong. Population undoubtedly is the most 

important factor in the variation in public service costs. 

The difference, for example, between the $85 billion 

spent in 1986-87 by the state and local governments in 

Californiaand the $1.5 billion spent by the state, counties, 

and towns in Vermont is accounted for largely by the fact 

that nearly 28 million people live in California and fewer 

than 600,OOO live in Vermont. 

Three general classes of factors are responsible for 

variation in the costs of public services among governments and areas:' 

H The range and types of services a jurisdiction 

must, by law, provide. For example, the law 

in some states requires county governments 

to deliver medical services to all poor 

persons who meet certain specified condi- tions. 

H The prices of the inputs used to produce 

public services, such as wages and salaries, 

gasoline prices, and the cost of asphalt. 

Factors that determine the scope of the 

services provided, such as the number of 

pupils in public schools. 

H 

The types of services a jurisdiction is responsible for 

providing are central considerations in the cost of 

government at the local level, where obligations prescnied by state law vary substantially among states and 

among different types of local governments. At the state 

level, however, requirements imposed by the federal 

government are relatively insignificant. The states (col- lectively with their local governments) are essentially free 

to offer-or not to offer-any service not reserved to the 

'It is important to remember that the concern here is only with 

differences in mts that are not attributable to the policies of 

the governments serving an area. 

federal government by the Constitution or proscribed by 

the Congress. Such federal requirements as do exist apply 

uniformly throughout the nation, so they should not be an 

important source of variation in costs. Thus, this class of 

factors is not germane in considering variations in the 

costs of public services among the states. 

The prices of the goods and services used by state and 

local governments vary with climate, with distance from 

the point of production, between rural and urban areas, 

and as a consequence of state and local policy. For example, 

state laws relating to the compensation of public employees 

range widely, with major consequences for the costs of 

producing public services. As discussed in the next section, 

however, a central premise of the analysis and measurement 

of fiscal capacity is that differences among jurisdictions and 

states that are traceable to state or local policies must be 

abstracted from if the estimates are to be of much use. 

In general, unfortunately, information on the prices 

paid by states and localities is not currently compiled by any 

agency in sufficient detail to permit estimation of a 

comprehensive index of the relative input costs paid by 

governments in all of the states. It is possible, however, to 

estimate the approximate differences among the states in 

the basic cost of employee compensation. Such compensa- tion accounts for roughly half of all direct general 

expenditures by state and local governments, and probably is 

more variable among the states than the costs of most goods 

purchased. Employee compensation also varies dramatically 

among functions as a proportion of total outlays. 

Therefore, a fairly good handle on the variation in 

unit costs can be gained by an index that weights relative 

costs of employee compensation at their actual proportion of total outlays and assumes that the unit costs of all 

other inputs are uniform throughout the country. The 

estimates of representative expenditures presented in 

Chapter 4 are adjusted for differences in unit input costs 

using an input-cost index discussed in Chapter 3 and 

considered in detail in Appendix C. 

This leaves the factors that influence the amount or 

scope of public services provided. Population, as noted 

earlier, is unquestionably the simplest and most common 

variable used for this purpose. It is clear, however, that 

population is not a very good indicator for many types of 

Advisory Commission on lntergovemmentel Relations 5 
public services. An obvious example is education. The 

costs of elementaly and secondaly education are more 

closely related to the number of school-age children than 

to the size of the entire population. The heart of the 

representative expenditure approach is the identification 

of the measures for specific categories of public services 

that are better than total population. The approach is 

discussed in detail in the next chapter. 

An additional source of differences in the costs of 

public services among governments and areas is the 

efficiency with which labor and materials are managed to 

produce those services. The cost of producing a given 

quantity and quality of a service is lower for an efficient 

government than it is for an inefficient one. Important as 

efficiency is to good government, few types of data are in 

shorter supply than information on the overall efficiency 

of different governments. Fortunately, this is not a 

problem for the present analysis. Efficiency clearly is a 

matter of government policy and, as a consequence, is an 

issue that must be abstracted from here. This means that 

the estimates of the costs of providing the representative 

level of services assume that the average efficiency of 

government is roughly the same in all states. 

It follows from this that observations in this report to 

the effect that the costs of some or all public services are 

lower in one state than in another should not be 

understood to refer to the relative efficiency of government operations in the states. In the present analysis, the 

costs of providing the representative levels of services 

vary among the states only because of differences in 

workload or differences in unit input costs that are beyond 

the control of state and local governments. 

6 Advisory Commission on Intergovernmental Relations 
Chapter 3 

The Representative Expenditure 

Approach 

The concept and the methods used to estimate 

representative expenditures for the 50 states and the 

District of Columbia owe a great deal to the Representa- tive ’hx System (RTS). Because considerable familiarity 

with the KIS has been achieved during the quarter century 

or so since it was first put forward, the basic logic of the 

representative expenditure approach may be most easily 

understood by reference to the IITS. Thus the discussion 

begins with a brief recapitulation of some of the essential 

elements of the KTS. 

The Representative Tax System 

The relative tax capacity of a state is defined by the 

RTS as the revenue the state and its local governments 

would raise if they were to apply a set of taxes and tax rates 

“representative” of actual policies prevailing, on average, 

throughout the nation. The basic rationale for such a 

prototypical, or hypothetical, tax approach is to ensure 

that the revenue estimate is independent of the actual tax 

policies of the governments in any particular state. This 

”policy neutrality” is an essential attribute of any element 

of a measure of the fiscal potential-as opposed to the 

actual behavior-of the governments in a state. 

The most recent RTS estimates are derived using a 

system with 27 categories of taxes accounting for 100 

percent of all state-local tax collections reported by the 

Governments Division of the U.S. Bureau of the Census 

for 1987-88.’ Specific taxes account for 26 of the 

categories, the 27th category--“other taxes”-is the 

residual portion of the Census total of state-local tax 

revenues. It accounts for somewhat less than 4 percent of 

total tax collections in 1987-88. 

‘Advisory Commission on Intergovernmental Relations, 1988 

State Fkcd Capacity and Efirf (Washington, DC, 1990). Until 

the RTS was revised for the report published this year, it did 

not include taxes accounting (1986-87) for a little more than 4 

percent of all state and local tax revenues. These taxes were 

not included on the grounds that they are rarely used or are 

levied on bases for which there are no adequate data or clearly 

plausible proxies. Among those excluded were license taxes on 

certain occupations and businesses, documentary and 

stock-transfer taxes, and severance taxes on forest products, 

fish, and oysters. 

The “bases” of the 27 categories of taxes for the 50 

states and the District of Columbia are the central 

element of the RTS. The RTS base for a tax is a prototype 

that may or may not be the actual, statutory base in any 

state. For example, the total federal income tax liability of 

a state’s residents (adjusted for the deductibility of state 

and local taxes) is the RTS base for individual income 

taxes. The federal liability is actually the base for state 

income taxes only in Rhode Island and Vermont? 

Selection of the KI’S base for a tax is a judgment call, 

but the objective is to match as closely as possible the 

distribution among the states of the typical statutory base. 

In the case of the new category of “other taxes,” there isby 

definition no typical statutory base, so the KI’S base is 

defined as resident personal income. The options are 

constrained to data published annually and separately for 

all the states, although older data have to be used in a few 

cases. This facilitates regular updating of the estimates 

and minimizes the complexity of the analysis. 

The RTS “rate” applied to each of the 27 RTS bases to 

calculate the estimates of representative tax collections is 

a national average. It, too, is a prototypical rather than 

statutory rate. That is, the KI’S rate is the ratio of the 

actual collections of all state and local governments for 

the category to the national total of the WS base.3 This 

zAdvisory Commission on Intergovernmental Relations, Sign$cant Featum of Fiscal Federalism, 1990, Volume 1 

(Washington, DC, 1990), Table 16. 

’In the case of ad valorem taxes, the RTS “rate” is a flat 

percentage, even though the statutoryrates of the corporation 

income taxes of many states are graduated. For unit taxes, the 

“rate” is a dollar amount per unit taxed-per pack, per gallon, 

per barrel, per license. As noted earlier, the RTS base for the 

individual income tax is the (adjusted) federal liability of a 

state’s residents. Use of a flat RTS “rate” in this case implies 

that the representative rate structure mirrors the graduation in 

the rate structure of the federal tax. This may make more sense 

today that it once did. The reduction in the graduation of the 

federal rate structure since 1981 has been so severe as to make 

it resemble many state structures of a decade ago. The 

problem is that, in the interim, a number of states have been 

busy degraduating their own rate structures. This means that 

the flat RTS rate may still very much overstate the actual 

degree of graduation in the rate structures of today’s state 

income taxes. 

Advisory Commission on Intergovernmental Relations 7 
use of national-average rates can be viewed as a method of 

weighting the various tax bases in accordance with actual 

relative reliance on them by states and localities around 

the country. 

Representative Expendltures: Bask Concepts 

The representative expenditure approach closely paral- lels that of the RTS. The parallel is not perfect because of an 

important asymmetry between revenues and expenditures 

that is embodied in the accounts of the Governments 

Division of the U.S. Bureau of the Census, which are the 

source of the fiscal data used in the analysis. That is, revenue 

sources are inherently more discrete conceptually (and 

legally) than are expenditure functions or categories. 

Although there is room for dispute at the margin 

concerning the Census Bureau’s classification of some 

revenues, on the whole there is no disagreement about 

whether the governments of a state do or do not levy an 

individual income tax, or a general sales tax, or a tax on the 

transfer of stocks (as New York State once did). The 

cornerstone of the Kl3 is the judgment, with respect to 

each tax for which data are reported separately by Census, 

whether the tax is relied on by the governments of enough 

states to warrant its inclusion in a “representative” 

state-local tax system. 

On the expenditure side, on the other hand, the issue 

of “representativeness”-in a sense analogous to whether 

reliance on a particular tax is or is not “representative” of 

actual practice throughout the nation-is moot. At the 

level of aggregation considered in the present report, 

every function in the Census accounts is representative in 

this sense because outlays are recorded for every state for 

every f~nction.~ 

Given the set of functions determined to be representative (all functions, at the level of aggregation considered 

here), the crucial step in the representative expenditure 

approach is the identification of the best possible measure 

of the workload for each f~nction.~ This is equivalent to 

the identification of prototypical tax bases in the RTS. The 

workload measure may be as simple as total population or 

more complex, comprising multiple variables equally or 

unequally weighted. The measures are derived from reThe annual Census reports on government finances display 

estimates for 29 categories of direct general expenditures by 

states and localities. Of these, no outlays are reported for 

transit subsidies (0.04 percent of total outlays) in 22 states, 

water transportation and terminals (0.3 percent of outlays) in 

12 states, and veterans’ services (0.02 percent) in 3 states. NO 

spending for other education and air transportation is 

reported for the District of Columbia. U.S. Department of 

Commerce, Bureau of the Census, Government Finances in 

1987-1988 (Washington, DC, 1990) Table 29. 

“Workload” is Robert D. Reischauer‘s term in his pioneering 

analysis of state and local expenditures during the years 

1962-72, Rich Governments--Poor Governments: Determining 

the Fiscal Capmi& and Revenue Requirements of State and 

Local Governments, Brooking Staff Paper, unpublished, 1974, 

Chapter 2. The state-local sector as a whole-rather than 

individual governments or states-is the subject of Reischauer’s study. Workload can also be referred to as “needs.” See 

Harold A. Hovey’s representative expenditure estimates for 

the states in “Fiscal Capacity, Tax Effort, and ‘Need,’ ” State 

review of the literature and consultation with authorities 

in particular functional areas. Where possible, as with the 

KI’S, the workload measures are limited to variables for 

which data for all states are available annually. 

A general consideration of overriding importance in the 

selection of workload measures is that they be independent 

of the policies of the governments in any particular state. As 

discussed later, this argues against use of such programclient Variables as enrollment in public schools and the 

number of persons receiving welfare benefits. It also means 

that the analysis must abstract from the important issue of 

how efficiently public services are produced. 

Given the workload measure for a function, the 

representative expenditure per unit of workload can be 

calculated by dividing the total of actual state-local 

outlays for the category by the U.S. total for the workload 

measure. The resulting average cost per workload unit is 

equivalent to the national-average tax “rate” in the RTS. 

As the representative tax yield for a state can be 

calculated by multiplying the value of the state’s base by 

the RTS tax rate, so the representative expenditure for a 

state can be derived by multiplying the state’s workload 

measure for a function by the national-average expenditure 

per unit of workload? This preserves the mix of actual 

expenditures by all state and local governments as a group. 

It is important to emphasize that the estimates of 

representative expenditures-like the tax yields gener- ated by the RTS-are of relative and not absoluteinterest. 

They indicate how much it would cost a state to provide 

the average level of public services that actually prevailed 

nationwide in the year for which the estimates are 

calculated. A key assumption here is, as noted earlier, that 

the representative level of outlays results in roughly the 

same service level in every state-in other words, that 

government is of approximately equivalent efficiency in 

every state. 

Reference as the basis for the analysis to service 

levels actually provided on average by state and local 

governments throughout the nation is not intended to 

imply that the representative levels are necmady correct 

or “needed” in any absolute sense. Indeed, the approach 

explicitly abstracts from debates about whether the na- 

~ 

policy Repom 3 (July 1985): 10-20. The approach outlined in 

this report draws heavily on Robert W. Rafuse, Jr., “A 

Representative Expenditure Approach to the Measurement 

of the Cost of the Service Responsibilities of States,” in Rafuse 

(4.1 Fedeml-State-Local Fiscal Relatiom: Technical Papers, 

Volume I (Washington, DC U.S. Department of thelhasury, 

Office of State and Local Finance, 19861 pp. 133-86. That 

paper presents estimates of representative expenditures for 

the states for 1983-84 that are very similar, conceptually, to 

those for 1986-87 in the present report. 

A more straightfod way of descn’bing the calculation is that 

the national total of actual state and local outlays on a function is 

distriited among the states in proportion to the values of its 

workload measure. Similarly, the RTS distriiutes the national 

total of actual collections of a tax among the states in praportion 

to the RTS base for that tax Viewed from this perspectiw, it is 

clear that the RTS tax “rates” and the costs per workload unit are 

mathematically superfluous. Nonetheless, reference to them is 

helpful in explaining the logic of the procedure. 

8 Advlsory Comm’lsslon on Intergovernmental Relations 
Ejrhibit 1 

Workload Measures 

for Representative Expenditures 

1. Elementary and Secondary Education 

The workload measure is the weighted sum of three 

population groups: (1) children of elementary-school age 

(5-W) net of enrollment in private elementary schools, (2) 

youth of secondary-school age (14-17) net of private 

secondary enrollment, and (3) the population under 18 

living in households with incomes below the poverty line. 

The weights are, respectively, 0.6, 1.0, and 0.25. 

2. Higher Education 

The measure is the weighted sum of the population in 

the age groups 1417,18-24,2544, and 35 and older. Each 

might (L32 percent, 2244 percent, 4.16 percent, and 0.83 

percent, rnpectivdy) is the full-timeequivalent number of 

students in the age group enrolled in institutions of higher 

education nationwide as a proportion of the total population 

in the age group. 

3. Public Welfare 

The workload measure is the population living in 

households with incomes below the poverty line. 

4. Health and Hospitals 

The measure is the sum of the equally weighted 

percentagedistributionsof(1)persons age 16-64withwork 

disabilities, (2) the population living in households with 

incomes below 150 percent of the poverty line, and (3) the 

total population. 

5. Highways 

The workload measure is the weighted sum of the 

percentage distributions of two variables: (1)vehicle-miles 

traveled, and (2)lane-miles of streets and roads other than 

those on federally controlled land. The first is weighted 

0.825, the second 0.175. 

6. Police and Corrections 

The measure is the sum of the equally weighted 

percentage distributions oE (1) the population age 18-24, 

(2) the number of murders committed, and (3) the total 

population 

7. All Other Direct General Expenditures 

The workload measure is total population. 

tion’s governments are spending “enough” for education 

or infrastructure, and whether what is being spent is being 

managed efficiently. 

It follows that the analysis should not be viewed as 

providing a comprehensive framework for addressing 

some of the most important issues of public spending 

policy. The representative approach is intended to 

promote understanding of the reasons why relative levels 

of public-expenditures differ among the states and to 

improve the quality of the information base on which the 

debates on issues of efficiency and sufficiency can 

proceed. The approach is not intended to substitute for 

careful analysis of governmental performance or efficien- cy, which requires intensive consideration of results 

actually achieved in relation to the level of spending for 

each specific program or function. 

The Workload Measures 

The functions for which specific workload measures are 

developed and estimated in this report are: (1) elementary 

and secondary education, (2) higher education, (3) public 

welfare, (4) health and hospitals, (5) highways, and (6) police 

and corrections. The six functions account for nearly 70 

percent of the total direct general expenditures of state and 

local governments.’ The estimates of representative outlays 

for all other functions are derived using total resident 

population as the workload measure. 

The specific workload measure for each expenditure 

category is described briefly in Exhibit 1. The basic 

considerations underlying the selection of the measures 

are discussed in the remainder of this section.* 

‘U.S. Department of Commerce, Bureau of the census, 

Government Finances in 1986-87 (Washington, DC, 1988) Table 

29. As defined by the Census Bureau, direct expenditures are 

payments to suppliers, employees, and all other final recipients of 

government outlays except other governments General acpenditurn are all outlays but those by governrnentavwd liquor 

stores, insurance trust systems, and utilities 

In a letter to John Kincaid (Executive Director, ACIR), dated 

February 7, 1990, commenting on a draft of the executive 

summary of this report, L Edward Lashman, Jr. (Secretary, 

Executive Office for Administration and Finance, Commonwealth of Massachusetts) notes: 

I am aware of the many uncertainties and value 

judgements inherent in this sort of social science ex- ercise. My worry is that many in policy making posi- tions will not recognize the very tentative nature of 

the current research results. The . . . cost indices 

could readily find their way into the substantive arena such as through use in distribution formulas for 

grants in aid. Given the state of the art as described 

in your draft, such a use of the results would be sig- nificantly premature. 

Because of this reality, I strongly suggest that. . . [the report] highlight the chief alternative specifica- tions, rather than displaying only one, supposedly 

definitive, index for each variable , . . [and] provide 

suitable cautions about the limits of the research. 

The research has undoubtedly explored a vari- ety of formulations of the individual cost indices. 

Each amalgam may have different theoretical pluses 

and minuses, and each may have widely different re- sults. . . . providing multiple results, with cautions in 

the text, are necessary precautions. 

Lashman’s understanding is correct that a variety of options 

for the workload measures was explored in the course of work 

on this report. Many of these are discussed in this section; ad- ditional discussion of the options can be found in Rafuse, ‘24 

Representative Expenditure Approach. . . ,” Practical consid- erations of publication cost, as well as the logic of encouraging 

readers to focus on a particular set of workload measures in 

order to facilitate understanding of the conceptual approach, 

respectively, preclude and argue against publication of the variety of estimates of representative expenditures that would be 

yielded by even the “chief’ option specifications for each 

workload measure. In fact, with a fewexceptions, workload in- dices and estimates of representative expenditures were not 

actually calculated for measures other than those described 

below in Exhibit 1. It should go without saying that judgments 

about the appropriatenes, from whatever pen-, of the estimates of representative expenditurn for any or all states were 

new a consideration in the selection of a workload measm. 

Advisory Commission on intergovernmental Relations 9 
1. Elementary and Secondary Education 

In fiscal years ending between July 1,1986, and June 

30,1987, elementary and secondary education accounted 

for 24 percent of the direct general expenditures of state 

and local governments. The workload measure for this 

function is a weighted average of the elementary (5-13) 

and secondary (14-17) school-age populations, in both 

cases adjusted to exclude enrollment in private schools, 

with special allowance for the number of children living in 

households with incomes below the poverty line. 

The weights (1) adjust for the lower cost per student 

of elementary education, which is assumed to be 60 percent 

of the cost per student of secondary education, and (2) allow 

for the higher cost of the compensatory and remedial 

programs that pupils from poverty households tend to 

require more often than pupils from other households? 

Population data are used because enrollment and 

average-daily-attendance (ADA) data are strongly influenced by the attendance requirements of state law. 

Variations in dropout rates account for much of the 

difference between school-age population and enroll- ment. Use of enrollment data would imply that states with 

depressed enrollments because of high dropout rates 

have lower need for expenditures for public education. 

Moreover, state definitions of enrollment and attendance 

differ, raising questions about the comparability of the 

available data. On balance, the influence of state policy on 

enrollment and ADA makes them both poor candidates 

for a workload measure. 

Adjustment for enrollment in private schools seems 

advisable because the importance of private institutions 

varies significantly among the states. In 1987, just under 12 

of every 100 kids of elementary-school age were enrolled in 

private schools. The proportions in individual states ranged 

from 192 percent of the national average in Delaware to less 

than 8 percent in Utah.'O F'rivate schools, in fact (as their 

proponents often point out), diminish the number of pupils 

that must be provided for in the public system. 

The argument against adjustment for private enrollment is that it is affected by the quality of publicprograms, 

a matter of policy from which the workload measure 

should abstract. Though the quality of public schools is 

undoubtedly a factor in private enrollment, considerations other than current educational policy (family 

tradition and the religious, ethnic, and racial mix of the 

population) are probably much more important in many 

areas of the country. In view of these considerations, 

subtraction of private enrollment from school-age population would seem to be desirable in arriving at a workload 

measure for elementary and secondary education. 

2. Higher Education 

More than 9 percent of the direct general expen- ditures of state and local governments in 1986-87 were 

The school-aid formulas of many of the states apply weights of 

roughly 1.25 to children in households below the poverty line; 

the equivalent of that weighting is used here. Richard Salmon, 

Christina Dawn, Steven Lawton, and Thomas Johns (eds), 

School Finance Progmms of the United States and Canada, 

1986-87 (Blacksburg: Amencan Education Finance Association 

and Virginia Polytechnic Institute and State University, 1988) 

lo See Table B-12. 

allocated to higher education. The workload measure for 

this function is the population in various age groups 

weighted by the proportion of those in each group who 

were actually enrolled (full-time equivalent) in an 

institution of higher education in the fall of 1987. 

A simpler measure would be the population of 

traditional college age, say, 18-24. The problem with this is 

that it would neglect the remarkable shift in recent 

decades in the age mix of students attending institutions 

of higher education. The shift is readily apparent in 'Ihble 

1. Although the proportion of those in the 18-24 age 

bracket enrolled in higher education declined somewhat in 

the 197% the slippage was more than recovered by 1987. 

The frequency of enrollment of those 14-17 declined fairly 

steadily, while that of individuals older than the traditional 

college ages rose sharply during the 1970s and has since been 

sustained at a frequency close to that reached in 1980. 

These trends have been accentuated by the evolution 

of the age profile of the population as the baby-boom 

generation has matured. Thus, columns 4-6 of nble 1 

show the steep decline in the proportion of full-timeequivalent enrollment accounted for by the 18-24 age 

group-from 78 percent in 1970 to 68 percent in 1987. At 

the same time, the representation of those over 24 soared 

from 18 percent of total enrollment at the beginning of 

the period to 30 percent in 1987. These trends appear 

likely to continue, with significantly different patterns 

around the country. Hence it is essential that the 

workload measure for higher education incorporate the 

capacity to capture these shifts'. 

At first glance, it might seem desirable to account 

somehow for differential patterns of enrollment of a 

state's residents in out-of-state institutions and in private 

institutions in-state, because both tend to reduce needs in 

some states and raise them in others. However, the 

out-of-state enrollment propensities of residents are 

surely influenced by the actual policies of a state 

regarding the quality and availability of public higher 

education. They are, therefore, not a suitable candidate 

Table 1 

lkend in Full-Time.Equivalent Enrollment 

in Higher Education, by Age, 1970.87 

FTE Enrollment as Percentage Distribution 

Percentaee of Powlation - gf FTE Enrollment 

Age 1970 1980 1987 1970 1980 1987 

(1) (2) (3) (4) (5) (6) 

Total 4.51% 4.89% 4.62% 100.02 100.0% 100.0% 

14-17 1.56 1.39 1.32 3.7 2.6 2.2 

18-24 22.22 21.03 22.44 78.2 72.0 67.6 

25-34 3.45 4.37 4.16 12.7 18.5 20.1 

3s + 0.43 0.63 0.83 5.4 6.9 10.2 

Note: Full-time equivalents arc estimated by assuming that three 

part-time students equal one full-time student. Part-time 

enrollment in 1987 isassumed to be the same proportion of the 

total enrollees in each age group as in 1983. 

Sources: 'Ihbles B-13 and B-15. 

10 Advisory Commission on Intergovernmental Relations 
for a policy-neutral workload measure. In any event, the 

necessary data are not available. 

Data on enrollment in private institutions are 

available by state, and might be used as similar information is in the workload measure for elementary and 

secondary education.'l The contribution of private institutions to lessening the workload for public higher 

education is arguable, however. nble 2 compares actual 

enrollments in each state with the enrollments in public and 

pxivate institutions that could be expected on the basis of 

national-average enrollment propensities Q%le 1, column 

3). The states are sorted by the ratio of actual to expected 

enrollment in private institutions, which ranges from the 

District of Columbia (891 percent) to Nevada (2 percent). 

A regional pattern is clearly apparent at the ex- tremes. All seven of the states with the highest ratios of 

actual to projected private enrollment also have be- low-average ratios of enrollment in their public institutions, and all are located in the northeastern part of the 

country. The eight states with the lowest private ratios, by 

contrast, are all in the West or South, though two (Alaska 

and Nevada) also have below-average public ratios. 

Apattern in the intervening data, however, is difficult 

to discern, and the reasons come easily to mind.'* Most 

private colleges and universities draw their students from 

national or regional markets. Most limit enrollment of 

"I am indebted to Bany H. Stern (until recently Director, 

Office of Liaison Services, U.S. Department of Justice, and 

former Secretary of Labor and Industry, Commonwealth of 

Pennsylvania) for discussions that encouraged me to look in 

some detail at the variation in public and private enrollments 

among the states. 

12An overall negative relationship between the ratios for public 

and private institutions exists and is statistically significant. A 

simple regression comprehending the 50 states and the 

District of Columbia, with the public ratio the dependent 

variable and the private ratio the independent, is: 

Y = 112.3-0.098 X 

(-4.6) 

The t-statistic in parentheses indicates that theX coefficient is 

significant at the99pemnt level. The R2 is 0.31, quite high for 

a regression of this type. If the District of Columbia is dropped 

from the regression on the reasoning that its major private 

universities (American, Catholic, Gallaudet, Georgetown, 

George Washington, and Howard) are clear examples of 

institutions drawing predominantly on a national-even 

international-market, the result is: 

Y = 114.9 - 0.129 X 

(-3.2) 

As expected, the R2 drops to 0.17, but the X coefficient 

remains negative and significant at the 99 percent level. When 

the top seven and bottom eight states are excluded from the 

regression, however, the reason why a systematic relationship 

between the two ratios for the remaining 36 states is difficult to 

see is clear there is no statistically significant (linear) one. The 

regression results are: 

Y = 107.4- 0.058 X 

(-0.6) 

The R2 plunges to 0.009, and the t-statistic indicates that the 

coefficient of the X variable, although still negative, is not 

significantly different from zero. 

Table 2 

Actual FTE Enrollments 

in Public and Private Institutions of Higher Education, 

by State, as Percentages of Enrollments ExDected 

on the Basis of Nathal-Average PropenGties, 

Fall 1987 

State All Public Private 

District of Columbia 

Massachusetts 

Rhode Island 

Vermont 

New York 

New Hampshire 

Pennsylvania 

Utah 

Iowa 

Connecticut 

Missouri 

Illinois 

Minnesota 

Idaho 

United States 

Ohio 

Tennessee 

South Dakota 

Maine 

Indiana 

North Carolina 

Nebraska 

Delaware 

Wisconsin 

South Carolina 

Georgia 

Kentucky 

Oregon 

Hawaii 

Oklahoma 

Michigan 

Florida 

Virginia 

California 

Washington 

New Jersey 

Maryland 

Colorado 

Alabama 

Texas 

Louisiana 

Kansas 

Arkansas 

West Virginia 

Montana 

Mississippi 

North Dakota 

Arizona 

Wyoming 

Alaska 

New Mexico 

Nevada 

(1) 

247% 

140 

145 

124 

113 

104 

100 

129 

125 

92 

98 

107 

111 

10 1 

100 

97 

85 

99 

79 

93 

97 

123 

109 

121 

82 

71 

82 

111 

88 

103 

102 

n 

95 

109 

106 

88 

107 

95 

89 

82 

117 

74 

85 

99 

88 

127 

114 

108 

71 

98 

69 

m 

(2) 

34% 

75 

88 

92 

82 

74 

72 

115 

117 

73 

87 

103 

110 

98 

100 

97 

82 

100 

74 

94 

99 

134 

120 

136 

85 

71 

85 

125 

94 

115 

115 

81 

106 

123 

120 

73 

98 

124 

111 

102 

94 

139 

83 

99 

118 

104 

156 

144 

138 

90 

127 

91 

(3) 

891% 

336 

3 17 

2% 

207 

193 

183 

171 

150 

149 

129 

114 

108 

100 

97 

95 

94 

93 

92 

91 

89 

75 

74 

74 

72 

72 

69 

68 

66 

65 

65 

64 

64 

62 

62 

58 

56 

49 

49 

49 

48 

46 

43 

39 

38 

38 

25 

14 

14 

9 

2 

im 

Source: U.S. Department of Education, Office of Educational Re- search and Improvement, National Center for Education Sta- tistics, Dig~sr of Education Sraristics, 1989 (Washington, DC, 

1989), Bbles 167 and 168. 

Advisory Commission on Intergovernmental Relations 11 
students from the same state in the interestsof diversityof 

student backgrounds. It is clear that-in contrast to the 

situation with elementary and secondary schools, whose 

enrollments are highly circumscribed geographicallyfurther research is needed on the extent to which 

enrollments in private institutions in a state can legiti- mately be viewed as reducing the need for public spending 

for higher education in that state.13 

3. Public Welfare 

In 1986-87, public welfare accounted for 12percent of 

the direct general expenditures of state and local 

 government^.'^ The workload measure for this function is 

the number of persons living in households with incomes 

below the poverty lie. 

The chief conceptual problem with this measure is 

that it does not take into account differences in the cost of 

living among the states. This means that a dollar of 

welfare benefits is assumed to be worth the same to the 

recipient in every part of the country. Using an approach 

such as that discussed in Appendix C, it would be possible 

to adjust for these differences, but time has not permitted 

an adjustment to be incorporated in the present analysis. 

The most important practical shortcoming of the . workload measure is the unavailability of data for most 

states for years other than decennial census years. The 

sample used in the March Current Population Survey, the 

source of annual estimates of the number of poor people in 

the nation as a whole, is too small (roughly 60,OOO 

households) to permit statistically reliable estimates to be 

calculated for any subnational areas but the four major 

Census regions.” 

The approach used in the present study to deal with this 

problem involves extrapolation (to July 1,1987, the refer- 

”In a letter to the author, dated January 29, 1990, Richard 

Drennon (Legislative Analyst, Florida Advisory Council on 

Intergovernmental Relations) suggests that an effort be made 

to extend the analysis to account for the importation and ex- portation of public expenditures. To the extent that out-ofstate tuition, though generally considerably higher than 

in-state, does not cover the full costs of the education, a state’s 

taxpayers are subsidizing the out-of-state student. In Drennon’s terms, the subsidy portion of the state’s outlay-s for high- er education provided to the out-of-state student is being 

exported. By definition, the subsidy being exported must be 

imported somewhere else, although the identity of the import- ing location is not an unambiguous issue, given the transitional 

residential status of many students in colleges and universitia. 

Though an attempt is not made to pursue this avenue of inquiry 

in this report, higher education is an espeually intriguing function 

for such an effort 

l4 The category “public welfare” in the Census accounts includes 

all costs associated with the “support of and assistance to 

needy persons contingent upon their need.” It specifically 

includes payments of cash assistance, payments made directly 

to private purveyors for such services as medical care and 

burials, and outlays by publicwelfare institutions. The costs of 

services provided to needy persons by state-local hospitals and 

health agencies are included in the function “health and 

hospitals.” Census, Government Finances in 1986-87, p. 120. 

‘5Estimate~ are also compiled and published for residence by 

type of area: in metropolitan areas over and under 1 million, 

inside and outside central cities in such areas, and outside 

metropolitan areas. 

12 Advisory Commission on Intergovernmental Relations 

ence date for all demographic data used here) of the Census 

estimates of poverty populations in 1979.16 Many extrapola- tion methods are available, the most obvious being to apply a 

state’s 1979 poverty ratio to its 1987 population. This would 

produce an arguably better estimate of the 1987 poverty 

population than direct use of the 1979 figure because it 

would take into munt the considerable diversity in 

population growth rates among the states. It would assume, 

however, that poverty rates remained constant (or changed 

at the same pace) throughout the nation between 1979 and 

1987, which we how not to be true. 

A better approach, and the one used for this report, 

involves use of the limited annual estimates of poverty 

rates for subnational areas that are available for the four 

major Census regions. The regions’ rates in 1979 and 1987, 

together with the percentage changes in those rates, 

appear in Tmble 3. Specifically, a state’s ratio of persons in 

poverty in 1979 is projected to change at the same rate 

between 1979 and 1987 as the rate of change in the ratio 

for the Census region in which the state is situated (the 

percentage change shown in column 3 of Tmble 3).” 

Table 3 

The Incidence of Poverty by Major Census Region 

in 1979 and 1987 

Region 1979 1987 Change 

(3) 

United States 12.1% 13.4% + 10.7% 

Northeast 

Midwest 

South 

West 

Source: ’lhble B-7. 

10.9 10.9 - 

10.2 12.6 + 23.5 

15.0 15.8 + 5.3 

11.0 12.6 + 14.6 

16The decennial Census in April 1980 asked respondents about 

their incomes in the preceding calendar year. Hence the 

estimates of poverty populations produced by the 1980 Census 

relate to persons who were living in households with incomes 

below the poverty line in 1979. 

171n a letter to John Kincaid (Euecuti~? Director, ACIRX dated 

January 29, 1990, commenting on a draft of this report, Len 

McComb (Director, Oh of Financial Management, State of 

Washington) takes note of the extrapolation method 

0bserVaS: 

Because Washington is included in the West census 

region, the CPS data used to calculate poverty rates 

for Washington is heavily influenced by the largest 

western state, California. Since the poverty rates in 

Washington and California vary, the three workloads in the report that are based upon poverty levels . . . are affected more heavily by poverty trends in 

California than in Washington. 

Washington has recently prepared annual poverty 

estimates for the state and each of itscounties. Yet, be- cause similar estimates are not available for all other 

states, the poverty level calculation that is used in the 

report most likely cannot be refined until the results of 

the 1990 census are published. 

and 
It is important to recall, in this connection, that no ad- justment for differences in the cost of living among the 

states or within states is provided for in current federal 

welfare programs-Food Stamps, Aid to Families with 

Dependent Children, Medicaid. Nor do the official esti- mates of the poverty population published by the Bureau 

of the Census take such differences into account. 

4. Health and Hospitals 

This function accounted for a little less than 9 percent 

of the direct general expenditures of the states and local 

governments in 1986-87. The workload measure for health 

and hospitals combines three variables: (1) the number of 

persons in the age range most commonly participating in the 

labor force (16-64) with a work disability, that is, a condition 

that limits the kind or amount of work they can do; (2) the 

population in households with incomes below 150 percent of 

the poverty line; and (3) the total population.lS 

A serious problem in developing a workload measure 

for health and hospitals is that very few data are available 

by state on a timely and regular basis. Illness rates, 

work-loss days, and restricted-activity days are distriiuted 

among the states in rough proportion to total population. 

The only major study of these factors by state was 

completed in 1976. Its findings generally confirm the 

proportionality distribution.19 

Indices of bed-days or hospitalization rates would be 

influenced by state policies to a degree that would make 

them unacceptable as variables in a workload measure. In 

view of these considerations, total population is the first 

of the three variables in this workload measure. 

The work-disability variable is intended as a rough 

proxy for the relative extent to which a state’s economy is 

associated with injuries or illnesses that may increase the 

demands on its public health and hospital programs. It is 

not at all clear how credible the variable is for this 

purpose, but the information necessary for a better 

variable does not appear to be available. 

The premise underlying the inclusion in the measure 

of the number of individuals in households with incomes 

under 150 percent of the poverty level is that such persons 

are much more likely than those with higher incomes to 

qualify for and to rely on publicly supported health and 

hospital services.zo 

In his letter to the author, Richard Drennon of Florida ob- serves that the 

. . , health and hospitals measum do not include age as 

a factor. This affects the Florida expenditure picture 

for this category as Florida has a large elderlypopulation. The direction of this bias is a subject of some 

debate since the elderly who migrate to Florida bring 

financial and medical insurance fesoufces with them. 

l9 U.S. Department of Health, Education, and Welfare, State& 

timates of Disability and Utilimlwn of Medical Services (Washington, DC, 1976). 

MAlthou~ the Census aaxlunts do not break out state and local 

upenditum under Medicaid, which finances health Services for 

bincome rsons, federal grants for the program in federal fjscal year 1 98r amounted to nearly half of total state and local outlays for health and hospitals in 1986-87. The estimate of federal 

grants to the states for Medjcaid is from Office of Management 

and Budget, Historical Tabla, Budget of the United States Gov- ernment, 1990 (Washington, DC, IW), Table l2.3. 

5. Highways 

Outlays for the construction and maintenance of the 

nation’s system of roads and streets amounted to slightly 

less than 8 percent of the total direct general expenditures 

of state and local governments in 1986-87. The workload 

measure for this function is the weighted sum of the 

percentage distributions among the states of: (1) the miles 

traveled by motor vehicles in 1987, and (2) the number of 

miles of lanes of streets and roads in the nation, other than 

those located on federally controlled land, on December 31, 

1987. The two variables are weighted in rough proportion to 

their contributions to highway deterioration over time. 

It is commonly observed that the cost of constructing 

a mile of urban road is very high, primarily because of the 

expense of right-of-way acquisition. At the same time, 

however, there tend to be many fewer miles of highways 

per capita in urban than in rural areas. Moreover, a mile of 

rural highway is not necessarily cheaper to build than one 

of uhn. In mountainous areas, for example, construction 

costs can be extremely high (and population per square mile 

very low). No easy answer to this conundrum is available. 

Fortunately, none really is needed, for initial construction is 

no longer a major element of the cost of U.S. highways. 

The nation’s system of streets and roads is largely in 

place. This is apparent in the steady decline in the rate of 

increase in the total mileage of surfaced highways during the 

past three decades (see Bble 4). As a consequence, 

expenditures for entirely new construction are a relatively 

minor component of total state-local outlays for highways. 

Table 4 

Average Annual Rates of Growth 

in Public Road and Street Mileage, Surfaced or Paved, 

1904.87 

Period Surfaced’ Pavedl 

(1) (2) 

1904-25 5.48% n.a. 

1925-40 6.26 n.a. 

1940-50 222 n.a 

1950-60 2.81 4.66% 

1960-70 1.43 3.03 

1970-79 .72 1.82 

1980-87 .89 

1981-87 .52 - n.a. -not available 

‘Surfaced mileage includes all paved roadways as well as graded 

and drained roads with surfaces of mixed soil, gravel, crushed 

stone, slag, and similar materials. 

*Paved mileage includes all roadways with, at a minimum, a bituminous surface course suitable for occasional heavy loads. 

Note: Reporting of mileage of “surfaced” roads was discontinued in 

1979; reporting of “paved” roads was initiated in 1980. The 

two series are estimated for later and earlier years, respectively, 

by adding mileage reported to be surfaced by “gravel or stone” 

to total paved mileage in 1981 and 1987, and by subtracting re rted mileage surfaccdwith ‘‘soil, ravel, or stone” from te 

tarurfaced mileage in the yean 1980-79. 

Sources: 1904-1985 -U.S. Department of Itansportation. Federal 

Hi hway Administration, Highway Statistics: Sum to I985 d shington, DC, 1987), lsblu M-203, HM-212, and M-2DO; 

1987-Highway Statistics, 1987 (1988), ’IBble HM-12. 

- 

Advisory Commission on Intergovernmental Relabions 13 
From this it follows that the costs incurred by state and 

local governments for highways are largely a function of the 

outlays required to maintain the existing system. These costs 

arise from two basic sources: deterioration resulting from 

traffic and deterioration that is independent of traffic. 

The costs attributable to tra€fii can be approximated by 

the vehicle-miles traveled in a state. This assigns equal 

weight to a mile traveled by evey type of vehicle. The 

problem is that heavy trucks do far more damage than 

automobiles. Clearly, the traffic variable ought to weight 

travel by large trucks much more heavily than travel by other 

vehicles.21 Regrettably, the available data do not permit this 

to be done for the entire nation with acceptable reliability?* 

The costs of deterioration attributable to time and the 

weather can be approximated by the stock of streets and 

roads in a state. This stock is measured reasonably well by 

the lane-miles that state and local governments are 

responsible for maintaining. This argues for excluding 

lane-mileage on federally controlled land that is maintained by federal agencies.23 

As for the weighting of the two variables, it is hard to 

quarrel with a recent report of the U.S. General 

Accounting Office, which concludes that 

. , . factors need to be weighted according to the 

components of highway deterioration to reflect 

relative preservation requirements. Deterioration is determined by use, which can be measured 

by VMT or motor fuel sales, and by factors 

unrelated to use, such as weather and time. The 

factor reflecting the extent of the system to be 

preserved should be weighted by the share of road 

In fact, the critical variable in damage to roads is the weight of 

a vehicle per axle, which is measured by engineem in “esals” 

(equivalent standard axle loads). The damaging power of a 

vehicle rises extremely rapidly with its weight per axleroughly as the third power of that weight. 

Thus, for example, the rear axle of a typical [two 

axle] thirteen ton van causes over 1,000 times as 

much structural damage as that of a car. . . . For all 

practical purposes, structural damage to roads is 

caused by trucks and buses, not by cars. 

Kenneth A. Small, Clifford Winston, and Carol A. Evans, 

Road Work: A New Highway Pricing and Investment Policy 

(Washington, DC The Brooking Institution, 1989), p. 11. 

22The 1982 Cost Allocation Study by the Federal Highway Ad- ministration estimates that the heaviest trucks cause 18 times 

as much road-damage cost per mile traveled as “lighter” ve- hicles. See the discussion of the available measures of 

heavy-truck travel in U.S. Department of Transportation, Fed- eral Highway Administration, Section 137 Studies: CIimare 

and Apportionment, and Interstate 4R Apportionment (Wash- ington, DC, 1983), pp. IV-23-26. 

Estimates of lane-mileage by state were published by the 

Federal Highway Administration for the first time in 1985. 

Unfortunately, the information is limited to nonlocal highways. The necessary estimates of local lane-mileage are 

derived for the present study from the published data using 

two assumptions: (1) all “local” mileage is two lane, and (2) all 

mileage on federally controlled land is two lane and would be 

classified in FHA reports as local if it were not reported 

separately. 

14 Advisory Commission on Intergovernmental Relations 

deterioration that is unrelated to use. The factor 

reflecting the level of highway use should be 

weighted by the share of deterioration that is 

use-related.24 

The GAO report eschews recommendations for specific 

weights. However, an appendix to the report observes that 

Discussions with DOT officials and their cost 

allocation study of May 1982 suggest that the vast 

majority of deterioration is use-related, which 

implies that theweight onVMTshouldbe . . .[in] 

the range 0.7 to 0.95.*5 

Accordingly, weights of 0.825 and 0.175, respectively, are 

assigned to vehicle-miles traveled and lane-miles for the 

workload measure for highways. These reflect the mid- point of the range cited by GAO. 

For some state and local governments, snow removal is 

a major element of outlays for highways. Maintenance costs 

are also exceptionally high for pavement and structures 

whose deterioration is accelerated by the use of salt and the 

freeze-thaw cycle. These costs amount to 25-40 percent of 

the road and streets budgets of municipalities located in 

areas with substantial annual snowfall.26 

24U.S. General Acownting Office, Highway Funding: Fedeml 

Distribution Formulm Should Be Changed (washington, Dc, 

1986) p. 31. The current formula for the apportionment of 

federal funds under the Intentate 4R Program, established in 

1981, assigns intentate lane-mileage and vehicle-miles traveled 

on the interstate system weights of 55 peroent and 45 percent, 

respebvely. 

25 Ibid., p. 67. Small, Winston, and Evans argue that the effects of 

axle weight, age, and weather 

. . . are mainly interactive-it is weathering of the 

pavement in conjunction with heavy axles that 

causes the problems. . . . Hence aging and weather- ing leave a pavement more vulnerable to damage by 

heavy loads, thereby raising the extra maintenance 

cost caused by those loads. (p. 20) 

%Rafuse, ‘A Representative Expenditure Approach . . . ,” p. l58, 

note 40. Two state officials who submitted comments on a draft of 

the executive summary of this qort urge the inclusion of a vari. 

able relating to weather conditions in the workload meawe for 

highways. In a letter to John Kincaid, dated February 14,1990, 

hvis N . Dodak (Speaker of the HQW, State of Mxhgan) qpests taking into munt “predominant weather conditions” as 

well as “the major type of vehicle use (i.e., trucks versus can)” 

In his letter to Kincaid, Edward Lashman of Massachusetts comments that 

ACIR should consider the addition of data on 

weather conditions (particularly freeze thaw cycle 

related information such as heating degree days). 

Weather is an important factor in increasing road 

maintenance, in addition to vehicle miles traveled 

and lane miles of roads. 

. . . ACIR should explore Federal Highway Adminis- tration’s data on the cost to completion of the Inter- state system. The state share of such projects will 

constitute a significant capital expenditure in com- ing years; ACIR could convert the state share figures 

into an annualized capital expenditure stream for index [workload measure] purposes. 

Lashman further suggests, in this connection, that 
Unfortunately, the data required to construct a stateby-state index of snowfall are not available. If they were, it is 

not obvious how such an index would deal with the extreme 

variability of the climate in some of the larger states. In 

California, for example, winter conditions are arperienced 

only in relatively unpopulated areas of the state. 

A recent report to the Congress by the Federal 

Highway Administration specifically addresses the need 

for and feasibility of introducing weather factors into the 

formulas for federal highway grants. The report acknowledges the importance of weather as a cost factor in 

construction, but concludes that 

. . . no single surrogate can represent all of the 

combined effects of temperature and moisture, 

let alone their interactions with traffic and soil. 

'Ibo many different weather-related mechanisms 

act upon a highway to capture them all within a 

single measure (or even a limited number of 

measures).27 

Moreover, 

Because of this interdependence among 

factors affecting highways, the impacts of weather cannot be identified in an absolute sense, e.g., 

all weather-related effects on highways can not 

be represented by some percentage of design or 

repair costs.28 

In sum, it is clear that-for the present analysis-no good 

method is currently available for adjusting the workload 

measure to take into account the unquestionably significant 

cost implications of the climatic variation across the nation. 

6. Police and Corrections 

In 1986-87, police and corrections accounted for 6 

percent of the direct general expenditures of state and 

local governments. The workload measure is the sum of 

the equally weighted percentage distributions among the 

states of the population 18-24 years old, the number of 

murders, and the total population.zg 

The overall crime rate (crimes reported to the police) 

in each state from the FBI's Uniform Crime Report is 

published annually. Regrettably, the rate is heavily 

influenced by actual police practices, reporting proce- 

*'Federal Highway Administration, Section 137 Studia, pp. 1-6 

211 bid., p. 111-4. 

and 1-7. 

In his letter to the author, Richard Drennon comments that 

. . . measures related to Police and Corrections ex- penditures may need further refinement. The male 

population age 18-34 may be better than population 

age 18-24 as a Florida expenditure indicator. Statis- tics, such as number of armed robberies, from the 

FBI Uniform Crime Report may represent a more 

sensitive expenditure demand than number of mur- ders committed. Additionally, the resident popula- tion for Florida does not account for the transient or 

tourist population. The direction and magnitude of 

the influence upon police and corrections expendi- tures for Florida using your indicators is unknown. 

dures, and expenditures for protective services. These are 

all elements of pl&y from which a wurkloird mgj~~g 

must abstract. 

Because they are relatively free of reporting biases and 

the variability of police practices, victimization rates would 

be preferable to crime rates. However, the sample of the 

National Crime Survey conducted by the Bureau of the 

Census is not large enough to permit estimates for every 

state. The reporting of murders is minimally subject to the 

problems that contaminate rates for other crimes. The 

number of murders (the reported data include nonnegligent 

manslaughter) can probably be regarded as a good indicator 

of the relative level of violent behavior in a state.30 

In 1986, nearly one-third of all those arrested were 

18-24 years old, though persons in this age group made up 

less than 12 percent of the pop~lation.~~ This age group is 

commonly used as an indicator of an area's potential for a 

wide range of serious crimes.3z 

Many police responsibilities have little to do with 

crime. They include such tasks as accident investigation, 

traffic control, and enforcement of municipal safety and 

parking ordinances. The police effort required for these 

activities probably depends overwhelmingly on the size of 

an area's population, so this variable is included in the 

workload measure for this function. 

The number of murders and the size of the 18-24 

population can also serve as crude indicators of the 

relative costs of corrections, on the assumption that these 

costs are directly related to the incidence of serious crime. 

This abstracts, as the measure should, from the large 

differences among the states in policies relating to 

corrections-including judicial practices, statutory sentencing rules, and parole procedures. 

7. Ail Other Expenditures 

The direct general expenditures of state and local 

governments for all functions other than those discussed 

in the preceding pages account for roughly 32 percent of 

total outlays. Tible 5 shows the entire detail available in 

the Census accounts for these expenditures. With the 

exception of interest on general debt, which is well over 6 

percent of state-local general expenditures, none of the 

remaining functions accounts for more than 2 percent. In 

the case of interest, resident population is arguably the 

only reasonable candidate for the workload measure. 

For a number of the individual functions displayed in 

Tible 5, workload measures more directly relevant than 

resident population readily suggest themselves-the 

In his letter, Edward Lashman of Massachusetts notes 

The murder rate is in some cases a poor proxy for 

the owall lexl of crime. For example, many North- east states have kr murder rates than the rest of the 

nation, but higher overall rates of violent or nonviolent 

&me. ACIR should use such a broader measwe. 

31 U.S. Department of Commerce, Bureau of the Census, Stalktical Abstmct of the United States, 1988 (Washington, DC, 

1987), pp. 13 and 165. 

32For example, see Burt Solomon, "Fewer Teenagers Means 

Fewer Crimes," Nutional Journal 18 (March 8,1986): 553. 

Advisoty Commission on Intergovernmental Relations 15 
Table 5 

Direct General Expenditures 

by State and Local Governments: 

Functions Included in the “All Other” Category 

for Which the Workload Measure is Resident Population, 

1986-87 

Percentage 

Amount of Total 

Function/Su bfunction (millions) Outlays 

(1) (2) 

Total for the ‘Ill Other’’ Category $206,004 31.5% 

Environment and Housing, Subtotal 53,805 8.2 

Agriculture 3,242 .5 

Natural Resources 6,496 1.0 

Parks and Recreation 10,978 1.7 

Housing and Community 

Development 11,766 1.8 

Sewerage 14,862 2.3 

Sanitation Other’than Sewerage 6,462 1.0 

Interest on General Debt 41,816 6.4 

Governmental Administration, 

Subtotal 34,895 5.3 

Financial Administration 12,841 2.0 

Judicial and Legal 10,106 1.6 

General Public Buildings 4,853 .7 

Other Governmental Administration 7,096 1.1 

All Other, Subtotal 75,487 

Other Education 9,636 

Libraries 3,274 

Employment Security Administration 2,752 

Veterans’ Services 129 

Air Transportation 4,876 

Parking Facilities 757 

Water Pansport and Terminals 1,744 

Transit Subsidies 244 

Fire Protection 10,910 

Protective Inspection and Regulation 4,420 

Miscellaneous Commercial Activities 297 

General Expenditure, N.E.C. 36,448 

*Less than 0.05 percent. 

11.6 

1.5 

.5 

.4 

.8 

.1 

.3 

1.7 

.7 

5.6 

L 

8 

* 

Note: Detail may not add to totals because of rounding. 

Source: U.S. Department of Commerce, Bureau of the Census, Government Finances in 1986-87 (Washington, DC, 1988), ’hbles 

22 and 29. 

number of resident veterans, for example, for veterans’ 

services. On the whole, however, resident population is 

not an unreasonable measure for virtually all the 

functions identified in Thble 5. Therefore, in lieu of an 

effort to disaggregate further, the outlays for all of the 

functions are distriiuted among the states in proportion 

to total resident population. 

In response to inquiries about the substantial differ- ences among some of the states in drafts of this report that 

displayed only the total for the entire “all-other” category, 

16 Advisory Commission on Intergovernmental Relations 

a fourfold break of the category is presented. This 

approach sheds light on the sources of the often large 

differences in spending for the functions for which 

specific workload measures are not developed. The break 

displayed throughout is: 

rn Environment and housing; 

rn Interest on general debt; 

rn Governmental administration; and 

rn Allother. 

Variation in Public input Costs 

Differences in the prices governments pay to acquire 

the resources they use are second in importance only to 

differences in workloads in explaining the variation 

among the states in the costs of public service responsibili- ties. Unfortunately, no measure of the variation in 

average unit costs among the states is currently available 

from any source. This section reports the results of an 

effort to develop and estimate a measure of relative input 

prices. The measure is used to adjust the estimates of 

representative expenditures for differences in the unit 

costs of public inputs among the states.33 

The approach estimates an index of relative labor 

costs using detailed information on individual earnings 

in each state from the 1980 Census of Population. 

Although the data are earnings in calendar year 1979, 

the basic economic realities underlying them change 

veryslowly, so the resultsare interesting despite theage 

of the data used. Moreover, should the approach pass 

muster with readers of this report, the findings of the 

1990 Census will be available in the next few years, so 

more timely estimates of relative earnings could be 

available fairly soon. 

The premise of the approach is that differences in 

the average earnings of full-time employees-controlling for sex, age, and education-are a good indicator of 

relative unit labor costs for all employers, including 

governments, in an area or state. Average earningsvary 

for many reasons, including differences in the cost of 

living, the power of labor unions, and the capital 

available per worker. 

The prices of some factors of production almost 

certainly vary more substantially than labor costs-land, 

for example, in rural and urban areas. The prices of most 

goods (computers, pencils, police cars) are set in nationwide markets, however, varying only with transportation 

costs and with the intensity of competition among local 

suppliers. Indeed, the prices of many goods may be lower 

in urban than in rural areas, when dealer competition is 

taken into consideration, thus partially offsetting differences in land prices. Unfortunately, the unavailability of a 

systematic body of information on the variation in these 

prices permits no better assumption than that, on balance, 

they do not vary significantly among the states. 

Given these considerations, an overall index of unit 

input costs can be calculated by weighting the index of 

33A detailed discussion of these issues appears in Appendix C. 
Table 6 

Relative Costs of Producing Public Services: 

Index of Unit Labor Costs and Implicit Index 

of All Input Costs, 1987 

Unit Labor Implicit Index 

Rank and State Cost Index of Input Costs 

United States 

Standard Deviation 

1. Alaska 

2 Michigan 3. Illinois 

4. Connecticut 

5. NewJersey 6. M land 

7. Cagornia 8. Ohio 

9. Washington 10. Taras 

11. Louisiana 

12 Minnesota 

W. NewYork 

14. Delaware 

15. Indiana 

16. Colorado 

17. Pennsylvania 18. Wisconsin 

19. Oregn 20. Virpnia 

21. Nevada 

22 Kentucky 23. Arizona 

24. Hawaii 

25. Wyoming 26. Missouri 

27. District of Columbia 

28. Massachusetts 

29. Utah 

30. Iowa 

31. Kansas 

32 Oklahoma 

33. Geor ’a 

34. Westtir ‘nia 

35. RhodeIsEnd 

36. Tennessee 

37. Florida 

38. Alabama 

39. Nebraska 

40. NewMexico 

41. South Carolina 

42 North Carolina 

43. NorthDakota 

44. New Hampshire 45. Arkansas 

46. Idaho 

41. Montana 

48. Mississippi 49. Vermont 

SO. Maine 

51. South Dakota 

(1) 

100.0 

7.5 

134.4 

111.9 

109.7 

108.5 

108.1 

105.7 

105.5 

103.9 

1029 

1023 

102.1 

102.0 

100.7 

100.3 

100.1 

99.6 

99.6 

98.4 

97.9 

97.7 

97.6 

97.2 

96.8 

96.0 

95.8 

95.6 

95.6 

95.6 

94.7 

94.3 

94.2 

94.0 

93.7 

93.4 

926 

91.6 

90.6 

90.6 

89.1 

88.4 

86.8 

86.6 

86.4 

86.0 

85.6 

85.3 

85.3 

83.7 

79.0 

77.1 

17.4 

(2) 

100.0 

3.6 

117.5 

106.2 

105.0 

104.4 

104.2 

103.1 

103.0 

102.2 

101.8 

101.4 

101.4 

101.3 

100.7 

100.5 

100.4 

100.2 

100.2 

99.6 

99.4 

99.2 

99.2 

99.0 

98.8 

98.4 

98.3 

98.3 

98.2 

98.2 

97.7 

97.7 

97.6 

97.5 

97.3 

97.2 

96.8 

96.3 

95.9 

95.9 

95.2 

94.9 

94.0 

93.9 

94.2 

93.6 

93.5 

93.2 

93.5 

92.7 

90.4 

89.6 

90.1 

Note: The implicit index for all costs is a weighted average of the 

unit-cost index for each function. The weights are the estimates 

of representative expenditures. In otherwords, the index for a state is the estimate of its total, price-adjusted, representative 

expenditures divided by the estimate of its unadjusted repre- sentative expenditures (multiplied by 100). 

Sources: lhblea A-2A (Scaled), A-2U, and C-3. 

labor costs and the implicit index of all other costs (in 

which every state has a value of 100) by the proportions of 

the direct general expenditures of state and local 

governments paid for the two types of factors of 

production. 

Employee compensation accounts for a different 

share of outlays for each function: the range is from 81 

percent for police and corrections to zero for interest 

on general debt.34 Therefore, separate weights reflecting 

the specific ratios are used to calculate an input-cost index 

for each function. 

The index of unit labor costs appears in column 1 of 

Xble 6, and the weighted average of the index for each 

category of general expenditures is shown in column 2. 

The range in labor costs is from 77 percent of the U.S. 

average in South Dakota to 134 percent in Alaska. The 

range in the index of all input costs is roughly half 

that-from 90 in South Dakota to 118 in Alaska.35 The 

values of the index for 17 states lie above the national 

average.% The states in nble 6 are ranked by the index of 

unit labor costs. 

A general measure of the variability in the cost 

indices is the standard deviation, which is shown in the 

second line of Thble 6 for both indices.37 These statistics 

indicate that the variability in unit labor costs is relatively 

small among the states. Although only 30 of the 51 lie 

between 92.5 and 107.5 (the range denoted by the 

standard deviation), the 30 include most of the most 

populous states, so the population-weighted standard 

deviation is somewhat smaller than it would be if each 

state were weighted equally in the calculation. The 

standard deviation for the implicit index of all input costs 

is roughly half that for the labor-cost index, the 

relationship expected given the way it is calculated (see 

footnote 36). 

34 See Appendix C. .. 

3sSee Appendix C for a discussion of some reasons why this 

estimate may understate the amount by which unit input casts 

in Alaska exceed averages for the nation as a whole. 

36The values of the overall index for five states in the 

neighborhood of the national average are statistical anoma- lies. That is, the implicit index for a state is an average of its 

labor cost index and an “index” for all other inputs whose 

value is 100 for every state. This implies that a state’s overall 

index must lie between its labor mt index and 100, yet this 

result does not quite obtain in the cases of the states ranked 

13-17. The discrepancies appear to lie within such small 

bounds as to be attributable to rounding, however. 

37The standard deviation of a set of data is the square root of the 

mean of the squared differences between the individual 

observations and their mean. It indicates the average 

variability of the data about the mean. The larger the standard 

deviation, the larger is the dispersion in the data. If the 

distribution of the observations resembles a normal curve, 

roughly two-thirds of the observations (34 states) lie within 

one standard deviation above and one standard deviation 

below the mean. Weighting the state values by population in 

calculating the standard deviation dampens the influence of 

the extreme values of Alaska and a few other small states. 

Advlsoty Commlsslon on Intergovernmental Relations 17 
18 Advisory Commission on Intergovernmental Relations 
Chmter 4 

Estimates 

of Representative Expenditures 

This chapter presents estimates of representative 

expenditures for state and local governments in the 50 

states and the District of Columbia and compares them 

with the actual outlays of those governments in fiscal 

years ending between July 1, 1986, and June 30, 1987.’ 

The estimates of representative expenditures are 

adjusted to allow for the estimated variation in input 

costs. The estimates are employed to consider the 

implications for a set of measures of state fiscal capacity if 

they, rather than resident population, are used as the 

indicator of the relative costs of the service responsibilities of the states. 

The final section of the chapter expresses the estimates 

of fiscal capacity as the gaps between the revenues a state’s 

governments would raise if they had a national-average tax 

system and the costs of providing a national-average level 

of publicservices. nKo sets of gap estimates arepresented: 

the first abstracts from federal grants; the second 

considers the total amount of federal grants actually 

received by the governments in each state. 

Actual Expenditures 

lhble 7 summarizes the actual direct general expendi- tures of state and local governments in 1986-87, by 

function. The information is expressed in per capita terms 

and indexed to the national average to facilitate comparisons among the states. Display of the estimates in this 

form focuses attention on relative spending for each 

function; no information is conveyed about relative 

spending among the functions or about the absolute size 

of the outlays. (The exhibits in the first two lines of the 

table provide perspective on these aspects: they display 

the percentage distribution of total outlays among the 10 

functions and the per capita magnitude of the spending on 

each.)The data underlying Tmble 7 appear in Appendix B. 

A number of governments whose fiscal years end on August 31 

or September 30 are treated by the Census Bureau as though 

their years ended on the preceding June 30. The August 

exceptions are the state government of Texas and that state’s 

school districts. The September exceptions are the state 

governments of Alabama and Michigan, the District of 

Columbia, and the school districts of Alabama. 

The variability of government spending across the na- tion is well known, but the extent of the variation is 

brought home by nble 7. The range in total expenditures 

isvery large: from 71 percent of the per capita national average in Arkansas to 371 percent in Alaska, which is in a 

class by itself. The state with the second highest outlays per 

capita is Wyoming, at 165 percent of the national average. 

It is interesting to note that the range has decreased 

significantly in the past few years. In 1983-84, barely three 

years earlier, Arkansas’ spending was virtually the same 

relative to the national average (at 70 percent), but 

Alaska’s was 406 percent, and Wyoming’s 183 percent.* 

The steep declines in relative spending in Alaska and 

Wyoming are due largely to the plunge in the value of oil 

and gas production during the period, which sharply 

curtailed state revenues from that source. 

The ranges in expenditures for the individual functions 

are, as would be expected, wider in every case than the 

ranges in the total. On the low side, in the case of public 

welfare, three states (Alabama, Nevada, and h) spend 

less than half the national average per capita. At the Same 

time, the spending of four states (Alaska, Massachusetts, 

New York, and Rhode Island) and the District of Columbia 

exceeds 150 percent of the per capita average. 

No state’s outlays are under half the national average 

for education. Alabama’s spending is the lowest, at 65 

percent of the U.S. average, for elementary and second- ary education-the actual outlays of Alaska and Wyoming 

are more than 1.5 times higher than the average. 

Pennsylvania, at 53, sets the low end of the range for 

higher education. Alaska is at the top of the range, 

followed closely by Wyoming, Delaware, Iowa, North 

Dakota, and Utah-all with per capita outlays more than 

50 percent above the national average. 

Maine, Maryland, and Vermont spend less than half 

the per capita national average for health and hospitals, 

while the District of Columbia and Wyoming spend more 

than twice that average. 

*Robert W. Rafuse, Jr., ‘A Representative Expenditure 

Approach to the Measurement of the Cost of the Service 

Responsibilities of the States,” in Rafuse (ed.), Fedeml-SlateLocal Fiscal Relations: Technical Papem, Vol. I (Washington, 

DC US. Department of the Treasury, Office of State and 

Local Finance, 1986). p. 161. 

Advisory Commission on Intergovernmental Relatlon8 19 
Table 7 

Indices of the Actual Direct General Expenditures of State and Local Governments Per Capita, by Function, 1986.87 

Health Police Environ- Intertst Govern- All 

Edu- and and ment on mental Other 

State Total Secondary Higher Welfare tals Highways tions Housing Debt tration turn 

Primary and Public Hospi- Correc- and General Adminis- Expendi- 

(1) 

Scale Exhibit: 

Percent 100.0% 

Per Capita $2,685 

United States 

Alabama 

Alaska 

Arizona 

Arkansas 

California 

Colorado 

Connecticut 

Delaware 

District of Columbia 

Florida 

Georgia 

Hawaii 

Idaho 

Illinois 

Indiana 

Iowa 

Kansas 

Kentucky 

Louisiana 

Maine 

Maryland 

Massachusetts 

Michigan 

Minnesota 

Mississippi 

Missouri 

Montana 

Nebraska 

Nevada 

New Hampshire 

New Jersey 

New Mexico 

New York 

North Carolina 

North Dakota 

Ohio 

Oklahoma 

Oregon 

Pennsylvania 

Rhode Island 

South Carolina 

South Dakota 

Tennessee 

Texas 

Utah 

Yermont 

Virginia 

Washington 

West Virginia 

Wisconsin 

Wyoming 

Standard Deviation 

100.0 

25.8 

370.7 

104.4 

71.0 

113.9 

105.6 

108.9 

111.3 

192.3 

87.6 

89.3 

105.4 

93.8 

80.5 

93.6 

92.8 

77.7 

91.9 

92.2 

102.9 

111.5 

107.9 

122.2 

75.5 

107.3 

92.3 

104.6 

83.3 

113.0 

100.3 

145.2 

77.4 

107.9 

90.7 

82.5 

104.6 

87.5 

103.8 

79.0 

94.7 

77.4 

86.5 

94.8 

102.4 

89.4 

103.4 

84.7 

105.9 

164.7 

77.3 

77.5 

77.0 

(2) 

24.0% 

$644 

100.0 

19.6 

65.3 

283.8 

108.3 

82.9 

99.8 

112.9 

105.7 

102.6 

120.1 

89.0 

96.7 

73.8 

77.8 

90.9 

89.2 

90.9 

98.9 

68.7 

80.0 

96.5 

97.9 

98.6 

113.9 

116.5 

73.6 

84.6 

122.2 

loo. 1 

89.8 

93.7 

117.4 

105.2 

133.6 

88.8 

101.5 

97.7 

90.5 

113.6 

98.3 

92.5 

88.1 

87.9 

67.1 

103.3 

100.1 

110.3 

98.4 

105.7 

96.0 

107.8 

183.5 

(3) 

9.2% 

$247 

100.0 

25.3 

104.5 

174.1 

137.8 

81.1 

122.0 

117.3 

63.9 

161.1 

55.7 

54.5 

76.7 

108.9 

114.2 

92.0 

115.6 

150.0 

122.6 

89.9 

84.1 

82.5 

106.9 

71.2 

130.3 

135.5 

91.2 

90.0 

92.1 

125.7 

79.8 

72.2 

83.7 

120.1 

87.1 

119.2 

157.9 

98.5 

94.6 

122.9 

52.7 

82.7 

108.0 

95.0 

84.4 

103.9 

153.1 

131.6 

109.6 

120.1 

76.0 

134.1 

162.0 

(4) 

12.3% 

$329 

100.0 

42.2 

47.8 

168.6 

65.2 

69.1 

124.1 

85.1 

112.3 

65.6 

272.7 

52.0 

63.6 

86.6 

51.7 

102.5 

91.9 

65.0 

82.1 

71.8 

129.8 

94.2 

155.0 

140.3 

145.7 

64.4 

66.0 

92.9 

79.1 

49.3 

77.8 

106.5 

66.7 

194.8 

59.9 

106.8 

118.9 

78.7 

64.6 

112.7 

15 1.6 

55.1 

66.3 

76.1 

48.2 

71.0 

105.3 

57.2 

95.5 

81.9 

148.0 

70.5 

77.5 

(5) 

8.7% 

$234 

100.0 

34.5 

138.8 

104.5 

53.8 

74.0 

114.9 

88.3 

88.2 

63.0 

207.4 

103.5 

184.6 

79.1 

83.3 

67.3 

90.8 

107.0 

85.1 

55.5 

125.2 

49.9 

48.4 

118.8 

122.7 

110.4 

138.4 

93.7 

63.2 

113.2 

82.2 

52.4 

74.6 

86.6 

168.7 

86.7 

70.7 

87.8 

89.1 

75.2 

55.3 

84.1 

125.8 

51.8 

113.4 

80.4 

74.5 

41.9 

94.3 

83.7 

61.8 

73.4 

225.5 

(6) 

8.0% 

$214 

100.0 

37.7 

81.2 

5 18.3 

169.5 

99.7 

65.8 

116.0 

118.3 

127.1 

87.2 

81.6 

92.6 

63.7 

117.2 

102.6 

82.2 

146.7 

146.2 

115.9 

106.2 

1124 

120.3 

82.5 

146.9 

98.1 

88.2 

132.5 

130.0 

121.8 

111.0 

148.4 

99.7 

75.3 

156.8 

82.2 

94.0 

107.1 

100.8 

77.3 

623 

161.8 

89.4 

112.2 

100. 1 

158.1 

118.0 

116.2 

124.6 

121.4 

306.7 

77.5 

177.0 

(7) 

6.3% 

$170 

100.0 

40.3 

61.8 

2.26.8 

134.1 

47.4 

149.4 

103.9 

91.8 

103.5 

445.1 

116.6 

82.2 

106.1 

61.3 

93.6 

57.1 

62.5 

67.3 

58.4 

85.2 

60.8 

124.6 

97.4 

108.1 

77.0 

49.2 

75.3 

62.9 

61.3 

150.0 

67.0 

116.3 

97.1 

163.6 

80.0 

45.2 

88.6 

64.8 

87.9 

72.2 

82.6 

75.2 

57.6 

67.7 

77.6 

83.8 

56.5 

90.6 

92.2 

37.9 

87.0 

105.7 

(8) (9) 

8.2% 6.4% 

$221 

100.0 

31.6 

67.2 

368.2 

102.0 

59.8 

126.5 

109.5 

97.3 

112.5 

276.3 

111.0 

77.4 

154.1 

85.1 

100.6 

68.2 

78.8 

66.3 

99.9 

102.8 

130.5 

122.4 

78.3 

124.3 

59.7 

71.6 

117.3 

70.8 

112.1 

71.5 

114.7 

89.2 

140.5 

59.9 

96.2 

83.1 

87.1 

103.0 

70.9 

83.9 

66.6 

76.0 

74.4 

92.7 

95.9 

78.5 

99.5 

124.3 

67.1 

110.3 

145.8 

n. 1 

$172 

100.0 

67.9 

79.4 

1,048.7 

113.9 

62.9 

87.9 

121.8 

134.2 

211.1 

183.1 

100.5 

56.7 

141.1 

45.6 

93.4 

53.3 

66.2 

108.6 

103.3 

145.9 

91.0 

113.9 

107.9 

72.4 

151.3 

60.9 

66.7 

124.1 

74.5 

142.6 

115.2 

146.2 

129.9 

149.9 

44.8 

96.3 

71.4 

80.3 

150.2 

106.4 

155.0 

61.2 

64.7 

107.0 

93.7 

100.0 

67.6 

74.2 

103.7 

82.2 

195.1 

107.8 

(10) 

5.3% 

$143 

100.0 

35.2 

73.6 

502.5 

119.5 

60.1 

124.8 

138.2 

125.8 

138.9 

254.3 

109.3 

85.8 

145.7 

79.3 

89.9 

70.9 

824 

106.6 

75.9 

84.2 

81.6 

100.2 

110.7 

98.0 

109.7 

65.2 

68.6 

114.8 

75.9 

153.4 

84.6 

119.0 

114.3 

132.5 

74.9 

87.0 

86.5 

120.3 

82 1 

106.1 

63.3 

85.2 

68.7 

76.4 

109.1 

110.9 

102.5 

102.0 

82.8 

87.6 

163.3 

77.7 

(11) 

11.5% 

$3 10 

100.0 

51.0 

78.6 

665.7 

48.5 

139.1 

82.8 

153.1 

99.2 

205.1 

91.0 

68.7 

163.7 

63.8 

103.2 

69.8 

57.6 

724 

69.9 

81.1 

83.9 

112.0 

144.3 

95.0 

102.8 

53.7 

56.8 

93.2 

69.5 

139.7 

72.4 

140.5 

74.1 

173.6 

63.4 

135.1 

67.1 

57.1 

112.2 

93.5 

123.3 

66.2 

155.8 

59.2 

73.4 

106.3 

63.1 

108.0 

89.1 

113.7 

77.4 

77.4 

n. 1 

Sources: Tkbles B-1 and B-7. 

20 Advisory Cornhission on Intergovernmental Relations 
South Carolina’s outlays are the lowest per capita for 

highways, but they are 62percent of the national average. 

Alaska’s spending for highways tops five times the 

national average, while Wyoming’s index is 307. West 

Vi spends only 38 percent of the average for police and 

Cmrections, the lowest ratio for any state for any function.’ 

The District of Columbia sets the high end for this function, 

with outlays exceeding 445 percent of the national average. 

Alaska’s per capita outlays for interest on general debt 

are far and away the highest for any state for any 

function-at more than 10 times the national average. This 

level of spending is especially interesting in light of the 

interest earned by Alaska’s governments, which amounts to 

more than 26 times the national per capita average and is 

nearly twice the amount of the state’s payments of interest 

on general debt.3 At less than 45 percent of the national per 

capita average, North Carolina’s outlays for this function are 

lower than those of any other state. 

State and local expenditures in the “all-other” 

categoty range from a spare 49 percent of the national 

average in Arkansas to 666 percent in Alaska? 

A more general measure of the variability in per 

capita expenditures is the standard deviation? The 

population-weighted standard deviation of each index is 

shown in the second line of Gble 7 and of each state table 

’US. Department of Commerce, Bureau of the Census, 

Government Finances in 1986-87 (Washington, DC, 1988) pp. 

46 and 48; and Table B-7. 

‘The treatment by the Governments Division in the Census 

mn$ of special institutions in two states is questioned in a 

letter to the author by Dave Clark, Executive Budget Analyst, 

0- of Management and Budget, State of North Dakota 

Qanuary 26,1990). The Bank of North Dakota and the State Mill 

and Elevator are both commercial entities owned and operated 

by the state government. In South Dakota, an apparently large 

cement plant is owned by the state government In the Census 

accounts for both states, these publicly owned enterprises 

classi6ed as miscellaneous commercial activities, and their total 

outlays are, as a consequence, beated as general expenditures of 

the two state governments. The effect is that North and South 

Dakota rank first and mnd among the states in total outlays for 

this function 

A report prepared by the Office of Management and 

Budget, State of North Dakota, argues that these institutions in 

both states are “unique. . . public enterprises whose expenditures 

should not be counted as general state spending”-A Cornpun*- 

mn of Per Capita State and Local Government Ependitum in 

Norih Dakota to Sunvunding States for Fiscal Year 1987 

(Bismarck, lW), p. 12 If this treatment were adopted by Census, 

the effect mld be to reduce North Dakota’s index for per capita 

“all othef‘ expenditures in Table 5 from l35 to 82 South Dakota’s 

indexwwildbe reduced fmm 156 to 146. 

In a letter to the author, dated January 11, 1990, Brad 

Pierce (Policy Analyst, Division of Policy, Office of Manage- ment and Budget, Office of the Governor, State of Alaska) 

suggests that 

If the all other expenditures category includes Per- manent Fund dividend appropriations from the 

state’s $10 billion public savings account, they should 

probably be removed since PFDs have nothing to do 

with provision of public services. 

See footnote 36, Chapter 3, for a definition of the standard de- viation and a discussion of its interpretation. 

in the remainder of this report. This measure indicates 

that per capita outlays are most disparate among the 

states for interest on general debt. The second most 

disparate function is “all other” expenditures, a result that 

is difficult to interpret given the open-ended nature of 

that category. The third largest standard deviation-by a 

tiny margin-is for public welfare, and the fourth largest 

is for police and corrections. The least variability in per 

capita spending is for elementary and secondary education-the standard deviation is only 20. 

The Estimates of Representatlve Expenditures 

The estimates of representative expenditures, adjusted 

for input-cost differences, are presented in nble 8.‘j As in 

the case of actual outlays just considered, the estimates are 

expressed as indices of per capita values, with the national 

average equal to 100. The range in the index for the total of 

the estimates is far smaller than that in actual outlays. 

The state whose cost of implementing the represen- tative level of total spending per capita would be highest is 

Mississippi. The per capita outlays of the governments in 

that state would have to exceed the U.S. average by more 

than 13 percent in order for it to provide the national- average level of public services. The per capita cost of the 

average level of services is lowest in New Hampshire (85 

percent of the national average), followed closely by 

Rhode Island (86), Massachusetts (87), Maine and 

Vermont (89), and Hawaii and Pennsylvania (90).’ In 

addition to Mississippi, the indices of only three states 

(Alaska, Louisiana, and New Mexico) exceed 110.* 

From a different perspective, the standard deviation of 

the index of total representative expenditures is sigmficantly 

less than one-third that in actual outlays. However, the 

standard deviation of the index for highways is more than 60 

percent of that in actual outlays for the function, as is the 

standard deviation for elementary and secondary education. 

Three considerations account for the relatively minor 

variation in the overall index of representative expenditures. The first is the absence of variation among the 

states in per capita outlays for the last four categories of 

expenditures- the analysis assumes that per capita 

representative outlays (unadjusted for unit-cost differences) are the same in all states for each of these 

categories. Hence the only variation in the per capita 

estimates for these functions is that attributable to 

input-cost differences, which are nonexistent for interest 

on general debt. The four functions accounted for 32 

percent of actual state-local outlays in 1986-87. 

The second consideration is that the variation in the 

workload measures for the other six functions is smaller 

than that in the indices for actual expenditures. In other 

words, factors in addition to differences in the “need” for 

public services enter into the determination of the actual 

‘jThe dollar estimates underlying the indices appear in Table 

B-4, in Appendix B. 

’Note that this reference to per capita “cost” relates to “needs” 

rather than to the efficiency with which services are delivered 

by the governments in a state. 

See Appendix C for a discussion of some reasons why the index 

may understate the cost of the representative level of public 

services in Alaska. 

Advisory Commission on Intergovernmental Relations 21 
Table 8 

Indices of the Estimates of Representative State-Local Expenditures Per Capita 

Adjusted for Input-Cost Differences, by Function, 1986.87 

Health Police Envlmn- Interest Govern- All 

n and and ment on mental Other 

Primary and Public Hospi- Correc- and General Adminis- Expend1 

State Total Secondary Higher Welfare tals Highways tbns Housing Debt tration turea 

United States 

Alabama 

Alaska 

Arizona 

Arkansas 

California 

Colorado 

Connecticut 

Delaware 

District of Columbia 

Florida 

Georgia 

Hawaii 

Idaho 

Illinois 

Indiana 

Iowa 

Kansas 

Kentucky 

Louisiana 

Maine 

Maryland 

Massachusetts 

Michigan 

Minnesota 

Mississippi 

Missouri 

Montana 

Nebraska 

Nevada 

New Hampshire 

New Jersey 

New Mexico 

New York 

North Carolina 

North Dakota 

Ohio 

Oklahoma 

Oregon 

Pennsylvania 

Rhode Island 

South Carolina 

South Dakota 

Tennessee 

Texas 

Utah 

Vermont 

Virginia 

Washington 

West Virginia 

Wisconsin 

Wyoming 

Standard Deviation 

(1) 

100.0 

6.4 

108.8 

121.3 

102.6 

106.0 

101.3 

98.1 

91.7 

96.1 

102.9 

92.6 

108.6 

89.6 

100. 1 

1024 

99.3 

95.8 

98.4 

108.3 

110.4 

89.0 

97.0 

87.3 

108.3 

98.0 

113.3 

100.2 

102.0 

96.2 

95.9 

85.4 

93.1 

110.6 

95.3 

98.6 

105.2 

99.9 

103.8 

97.9 

90.4 

85.8 

103.3 

104.7 

103.5 

109.7 

104.9 

89.1 

98.6 

98.6 

1027 

94.2 

102.2 

(2) 

100.0 

11.9 

107.9 

150.2 

103.0 

105.2 

101.1 

101.1 

89.7 

87.1 

73.0 

79.1 

109.9 

85.5 

113.0 

105.8 

106.6 

97.0 

96.2 

108.5 

110.1 

83.4 

94.8 

81.4 

115.2 

99.0 

112.9 

95.0 

100.0 

90.6 

95.3 

82 1 

92.3 

112.1 

89.6 

96.6 

96.6 

105.0 

106.2 

99.2 

85.6 

77.9 

102.9 

91.4 

100.6 

120.8 

140.7 

82.5 

96.1 

101.6 

109.1 

93.7 

113.5 

(3) 

100.0 

6.0 

94.9 

130.3 

97.2 

88.4 

103.6 

102.2 

105.1 

105.1 

98.7 

86.5 

99.9 

1022 

86.4 

106.4 

101.6 

94.5 

94.4 

101.0 

105.6 

85.8 

108.2 

101.6 

111.0 

101.8 

91.8 

95.1 

86.7 

91.5 

97.6 

93.8 

104.1 

93.1 

100.2 

94.9 

91.6 

101.5 

95.0 

94.0 

97.8 

97.7 

97.0 

83.3 

94.8 

102.6 

97.4 

90.6 

105.2 

100.9 

94.2 

100.0 

93.3 

(4) 

100.0 

21.1 

145.5 

92.8 

110.6 

144.8 

96.0 

84.6 

59.3 

91.7 

140.7 

103.9 

127.9 

81.1 

104.3 

100.7 

86.9 

90.1 

89.9 

135.7 

145.2 

91.4 

77.0 

69.3 

95.8 

85.2 

181.7 

108.8 

100.9 

94.8 

73.5 

60.4 

71.1 

146.4 

98.5 

111.8 

110.3 

93.6 

1029 

89.2 

76.6 

73.8 

125.5 

146.3 

126.4 

114.3 

86.4 

84.5 

90.8 

82.5 

116.2 

77.9 

65.9 

(5) 

100.0 

8.9 

115.5 

104.6 

104.9 

117.7 

1028 

92 1 

83.5 

95.5 

117.4 

99.3 

112.4 

83.5 

93.5 

101.6 

94.3 

88.2 

89.9 

120.4 

119.1 

88.7 

94.5 

84.1 

109.7 

90.7 

124.2 

102.8 

91.1 

86.3 

89.6 

77.2 

89.2 

108.5 

97.8 

100.6 

88.4 

101.8 

104.7 

101.8 

92.3 

88.4 

104.7 

96.8 

110.3 

101.6 

87.1 

84.2 

96.5 

98.8 

114.5 

85.3 

78.1 

(6) 

100.0 

21.6 

117.5 

113.8 

112.3 

111.4 

93.7 

110.1 

97.0 

109.1 

58.4 

89.1 

119.1 

73.4 

119.1 

84.4 

102.8 

1a.3 

145.7 

105.8 

87.5 

108.5 

93.2 

81.4 

104.6 

122.9 

106.7 

114.4 

186.7 

146.8 

122.0 

1023 

85.2 

137.7 

65.1 

101.7 

223.9 

90.1 

137.9 

111.4 

80.2 

69.4 

109.6 

193.0 

108.1 

115.6 

100.3 

118.2 

109.6 

108.1 

94.5 

113.1 

197.4 

(7) 

100.0 

16.3 

97.4 

140.9 

94.3 

86.2 

113.7 

90.0 

92.2 

89.9 

204.8 

101.3 

110.9 

85.8 

68.7 

108.3 

90.1 

71.0 

79.9 

96.5 

115.9 

63.7 

112.5 

77.6 

128.8 

78.6 

96.2 

96.0 

71.9 

73.1 

97.3 

71.3 

90.5 

98.6 

113.3 

90.6 

65.0 

92.8 

92.0 

85.1 

87.4 

77.4 

96.1 

60.3 

97.0 

116.4 

77.9 

66.6 

97.9 

90.4 

81.5 

80.4 

71.7 

(8) 

100.0 

25 

97.0 

111.7 

99.1 

95.4 

102.0 

100. 1 

103.0 

100.3 

98.7 

97.0 

98.1 

98.9 

95.3 

103.5 

100.2 

98.3 

98.3 

99.2 

100. 9 

92.6 

102.1 

98.7 

104.2 

100.9 

94.7 

98.7 

95.3 

96.5 

99.4 

95.5 

102.9 

96.3 

100.4 

95.7 

95.6 

101.5 

98.2 

99.5 

100. 1 

97.7 

95.8 

92.5 

97.4 

100.9 

98.4 

93.2 

99.4 

101.2 

98.0 

99.7 

98.8 

(9) 

100.0 

0.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100. 0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

(10) 

100.0 

4.9 

94.3 

122.6 

98.3 

91.0 

103.9 

100. 1 

105.9 

100.6 

97.5 

94.3 

96.3 

97.8 

90.9 

106.7 

100.4 

96.7 

96.6 

98.5 

101.8 

85.8 

104.0 

97.5 

108.1 

101.7 

89.8 

97.5 

90.9 

93.3 

98.8 

91.3 

105.6 

92.9 

100.8 

91.7 

91.6 

102.9 

96.5 

99.0 

100. 1 

95.6 

91.8 

85.6 

94.9 

101.8 

97.0 

86.8 

98.9 

102.3 

96.1 

99.3 

97.7 

(11) 

100.0 

20 

97.7 

109.1 

99.3 

96.4 

101.6 

100. 1 

1024 

100.2 

99.0 

97.7 

98.5 

99.1 

96.3 

102.7 

100.2 

98.7 

98.7 

99.4 

100.7 

94.3 

101.6 

99.0 

103.2 

100.7 

95.9 

99.0 

96.3 

97.3 

99.5 

96.5 

102.2 

97.2 

100.3 

96.7 

96.6 

101.1 

98.6 

99.6 

100. 1 

98.2 

96.7 

94.2 

98.0 

100.7 

98.8 

94.7 

99.5 

100.9 

98.4 

99.7 

99.1 

Sources: Dble B-3. 

22 Advisory Commission on Intergovernmental Relations 
levels of spending. These factors include, as discussed earlier, differences in the unfathomable complex of variables 

commonly referred to as voter tastes for public services. 

The third reason for the modest variability in the 

index of total representative expenditures is that, for 

many states, the values of the indices for different 

functions are offsetting. That is, a state’s high “needs” for 

one type of public service are often offset by a belowaverage workload for another. 

Abstracting from the functions displayed in columns 

8-11 of ’Itible 8, the indices of only one state exceed 100 for 

all functions. That state is Texas, whose overall index (at 

110) places it fifth in the nation. The relative needs of six 

states exceed the national average for all but one of the 

functions. They are Alaska and Michigan (public welfare), 

Georgia (higher education), Illinois and Louisiana (high- ways), and Kentucky (police and corrections). 

The indices of two states are under 100 for all 10 

functions: Pennsylvania and Rhode Island. The needs of 

Massachusetts and New Jersey are below the national 

average for all functions but higher education. The needs 

of seven states (Iowa, Kansas, Maine, Nebraska, Nevada, 

New Hampshire, and Vermont) would be entirely below 

the national average were it not for their exceptional 

highway needs? 

Actual Outlays Compared 

with Representative Expenditures 

able 9 shows the relationship between each state’s 

actual outlays in 1986-87 and the estimates of the levels of 

spending that would be necessary for the state to deliver 

the representative level of service. For the nation as a 

whole, actual and representative expenditures are, by 

deliition, identical-that is, the percentages are 100 for all 

functionS. Overall, the ranges and standard deviations are 

similar to their values for actual expenditures in mle 7. 

At the top of the scale is Alaska, with actual outlays 

nearly 306 percent of the level needed to deliver nationalaverage seMm. Second highest is Wyoming, at 161, 

followed closely by New York, at 152. Wyoming is the only 

state spending more than enough to deliver representative 

sed levels for every function, The ratios for four states 

exceed 100 for all but one function. They are Alaska (health 

and hospitals), the District of Columbia and New York 

(higher education), and Minnesota (police and corrections). 

At the bottom is Mississippi, whose actual total 

expenditures are less than 67 percent of its representative 

total, although its outlays for health and hospitals 

significantly exceed those necessary to provide nation- al-average services. It is interesting to note that, although 

Mississippi has the lowest ratio for total outlays, none of 

its ratios for individual functions is lowest. 

91n a letter to the author, dated January 20, 1990, Richard 

Drennon (Legislative Analyst, Florida Advisory Council on 

Intergovernmental Relations) suggests that 

. . . when the relative cost of living in rural versus ur- ban settings in Florida is considered, . . . [population 

in households with incomes below the poverty line] 

probably overstates the public welfare representa- tive arpenditure level. 

Three states are under 100 percent for all 10 

functions: Arkansas, Missouri, and Oklahoma. Georgia 

would share this distinction if its actual outlays for health 

and hospitals did not exceed (by more than 64 percent) 

those necessary to deliver representative services. Six 

other states also fall short of 100 for all but one function. 

They are Idaho, Indiana, and North Carolina (higher 

education); Ohio (public welfare); and Mississippi and 

Tennessee (health and hospitals). 

It is important to note that a state whose actual 

outlays are lower than the estimate of its representative 

level is not necessarily delivering a level of public services 

that is below the national average. As explained earlier, 

the analysis does not take into account possible differences among the states in the efficiency of government, 

nor does it recognize special circumstances that may 

increase or decrease the cost in a particular state of 

delivering the representative level of services.1o A state 

with actual spending below its representative level maybe 

sufficiently more efficient than the national average that 

the quantity and quality of the public services it actually 

delivers equal or even exceed the national average.” 

lo An example of such special circumstances is mentioned in a 

letter, dated January 29, 1990, to John Kincaid (Executive 

Director, ACIR) from Len McComb (Director, Office of 

Financial Management, State of Washington): 

Washington has a relatively extensive feny system. 

The costs for the feny system are included in the total 

highway expenditures that the report uses to deter- mine the workload for this category. The inclusion 

of ferry expenditures in this category results in the 

actual highway expenditures for Washington to be 

shown in the report at a level above the representa- tive amount. 

“In a letter to the author, dated January 22,1990, Patricia A. 

Woodworth (Director, Office of Planning and Budget, Office 

of the Governor, State of Florida)comments that Florida’s low 

ratio of actual to representative expenditures for higher educa- tion (63 percent) is attributable to enrollments in public institutions that are much below those implied by national average 

enrollment propensities, and that the state’s actual ’’support of 

higher education per FTE student” exceeds the national average 

by more than 13 percent She cites actual FTE enrollment of 

223,747 in 1986-87,55 percent of the 408,30 yielded by applying 

national average propensities (see Table El.5) Combined, the 

tw ratios exceed 62 percent (113 0.5% almost identical to, and 

hem mnlirming. the figure reported in Table 7. 

Woodworth also observes that 

. . . Florida’s rating in your report might be better 

[than the 50 percent ratio shown in Table 7 for 

public welfare] if more recent data were available 

for analysis. Participation rates in Florida in Med- icaid and AFDC have increased somewhat since 

fiscal year 1986-87. As a consequence of outreach 

efforts and expansion of coverage the percent of 

Florida’s population participating in Medicaid in- creased from 4.5 percent in 1986-87 to 5.7 percent 

in 1989-90. The analogous figures for AFDC are 

2.4 percent and 2.6 percent, respectively. The im- plication of these improved participation rates is 

that Florida’s public welfare expenditures should 

now be higher for a given “workload” of popula- tion living under the poverty level. 

Advisory Commlsslon on Intergo- fbhtknw 23 
Table 9 

Actual Direct General Expenditures of State and Local Governments 

as Percentages of Representative Expenditures Adjusted for Input-Cost Differences, 

by Function, 1986.87 

Health Police Environ- Interest Govern- All 

and and ment on mental Other 

Primary and Public Hospi- Corn- and General Adminis- Expend1 State Total Secondary Higher Welfare tals Highways tions Housing DeM tration turn 

United States 

Alabama 

Alaska 

Arizona 

Arkansas 

California 

Colorado 

Connecticut 

Delaware 

District of Columbia 

Florida 

Georgia 

Hawaii 

Idaho 

I1 1 in o i s 

Indiana 

Iowa 

Kansas 

Kentucky 

Louisiana 

Maine 

Maryland 

Massachusetts 

Michigan 

Minnesota 

Mississippi 

Missouri 

Montana 

Nebraska 

Nevada 

New Hampshire 

New Jersey 

New Mexico 

New York 

North Carolina 

North Dakota 

Ohio 

Oklahoma 

Oregon 

Pennsylvania 

Rhode Island 

South Carolina 

South Dakota 

Tennessee 

Texas 

Utah 

Vermont 

"Virginia 

Washington 

West Virginia 

Wisconsin 

Wyoming 

Standard Deviation 

(1) 

100.0% 

25.6 

71.0 

305.7 

101.8 

67.0 

112.4 

107.6 

118.8 

115.8 

186.9 

94.6 

82.2 

117.6 

77.5 

91.6 

81.1 

97.7 

94.3 

71.7 

83.3 

103.5 

106.0 

127.7 

99.6 

124.7 

66.6 

76.8 

105.2 

95.9 

109.1 

97.5 

121.4 

90.7 

152.4 

78.5 

102.6 

90.8 

79.5 

106.9 

96.8 

121.1 

76.4 

90.5 

74.7 

78.9 

90.3 

114.9 

90.7 

104.9 

82.4 

112.4 

161.2 

(2) 

100.0% 

21.9 

60.5 

188.9 

105.2 

78.8 

98.7 

111.6 

117.9 

117.9 

164.4 

112.6 

87.9 

86.3 

68.8 

85.9 

83.7 

93.7 

102.7 

63.4 

72.7 

115.6 

103.2 

121.1 

98.9 

117.8 

65.2 

89.0 

122.2 

110.5 

94.2 

114.2 

127.1 

93.8 

149.2 

91.9 

105.0 

93.1 

85.2 

114.5 

114.9 

118.8 

85.6 

96.1 

66.7 

85.6 

71.1 

133.6 

102.4 

104.0 

88.0 

115.1 

161.7 

(3) 

100.0% 

24.6 

110.1 

133.6 

141.7 

91.8 

117.7 

114.8 

60.8 

153.2 

56.5 

63.0 

76.8 

106.5 

132.2 

86.5 

113.7 

158.6 

129.8 

89.0 

79.7 

96.2 

98.8 

70.0 

117.3 

133.2 

99.3 

94.6 

106.3 

137.4 

81.7 

77.0 

80.4 

129.0 

87.0 

125.6 

172.5 

97.0 

99.6 

130.8 

53.9 

84.6 

111.4 

114.1 

89.0 

101.3 

157.1 

145.3 

104.2 

119.0 

80.7 

134.1 

173.6 

(4) 

100.0% 

52.9 

32.8 

181.6 

59.0 

47.7 

129.3 

100.6 

189.4 

71.5 

193.8 

50.1 

49.8 

106.8 

49.6 

101.7 

89.2 

102.0 

72.3 

60.5 

49.4 

142.0 

122.4 

223.6 

146.4 

171.0 

35.4 

60.7 

92.0 

83.5 

67.1 

128.8 

149.9 

45.5 

197.8 

53.6 

96.9 

127.0 

76.5 

72.5 

147.1 

205.3 

43.9 

45.3 

60.2 

42.2 

82.2 

124.6 

63.0 

115.8 

70.5 

189.9 

107.0 

(5) 

100.0% 

33.9 

120.2 

99.9 

51.3 

629 

111.8 

95.9 

105.6 

66.0 

176.6 

104.2 

164.2 

94.7 

89.1 

66.2 

96.3 

121.2 

94.7 

46.1 

105.1 

56.2 

51.2 

141.3 

111.8 

121.8 

111.4 

91.2 

69.3 

131.1 

91.8 

67.8 

83.6 

79.8 

172.5 

86.2 

80.0 

86.2 

85.1 

73.9 

59.9 

95.1 

120.2 

53.5 

102.8 

79.1 

85.5 

49.8 

97.8 

84.7 

54.0 

86.1 

288.5 

(6) 

100.0% 

33.8 

69.1 

455.6 

151.0 

89.5 

70.2 

105.4 

121.9 

116.5 

149.4 

91.5 

77.8 

86.8 

98.3 

121.5 

80.0 

122.0 

100.3 

109.6 

121.3 

103.6 

129.0 

95.2 

78.9 

119.6 

91.9 

77.0 

94.8 

90.2 

106.5 

119.0 

130.3 

107.8 

153.1 

74.1 

70.0 

91.2 

68.2 

96.1 

125.7 

111.4 

56.9 

83.9 

82.7 

97.0 

99.8 

133.8 

107.7 

107.4 

131.8 

107.3 

155.3 

(7) 

100.0% 

27.9 

63.5 

160.9 

142.2 

55.0 

131.3 

115.4 

99.5 

115.1 

217.3 

115.1 

74.1 

123.7 

89.2 

86.4 

63.3 

88.0 

84.1 

60.6 

73.5 

95.4 

110.8 

125.5 

83.9 

97.9 

51.1 

78.4 

87.5 

83.8 

154.1 

93.9 

128.5 

98.5 

144.4 

88.3 

69.6 

95.5 

103.4 

82.5 

106.7 

78.3 

95.6 

69.8 

66.6 

107.6 

84.7 

92.6 

102.0 

46.5 

108.2 

147.4 

70.5 

(8) (9) 

100.0% 100.0% 

29.9 

69.3 

329.6 

102.9 

62.7 

123.9 

109.4 

94.4 

112.2 

279.9 

114.4 

78.9 

155.8 

89.3 

97.3 

68.0 

80.2 

67.4 

77.7 

99.0 

110.9 

127.8 

123.9 

75.2 

123.2 

63.0 

72.5 

123.2 

73.4 

112.8 

74.8 

11 1.4 

926 

139.9 

625 

100.6 

81.9 

88.7 

103.5 

70.8 

85.8 

69.6 

82.1 

76.4 

91.8 

97.4 

84.3 

100. 1 

122.9 

68.4 

110.7 

147.6 

67.8 

79.4 

1,048.7 

113.9 

62.9 

87.9 

121.8 

134.2 

21 1.1 

183.1 

100.5 

56.7 

141.1 

45.6 

93.4 

53.3 

66.2 

108.6 

103.3 

145.9 

91.0 

113.9 

107.9 

72.4 

151.3 

60.9 

66.7 

124.1 

74.5 

142.6 

115.2 

146.2 

129.9 

149.9 

44.8 

96.3 

71.4 

80.3 

150.2 

106.4 

155.0 

61.2 

107.8 

64.7 

107.0 

93.7 

100.0 

67.6 

74.2 

103.7 

82.2 

195.1 

(10) 

100.0% 

30.7 

78.1 

409.8 

121.5 

66.1 

120.1 

138.0 

118.9 

138.1 

260.7 

115.9 

89.1 

149.0 

87.3 

84.3 

70.5 

85.2 

110.3 

82.8 

95.1 

96.3 

1l3.5 

90.7 

107.9 

72.6 

70.4 

126.3 

81.3 

155.2 

92.7 

112.7 

123.1 

131.4 

8 1.6 

95.0 

84.1 

80.5 

121.5 

820 

111.0 

68.9 

99.5 

72.4 

75.0 

1125 

127.7 

103.7 

99.7 

86.1 

88.2 

167.2 

n.o 

(11) 

100.0% 

48.1 

80.4 

610.4 

77.9 

50.3 

137.0 

828 

149.6 

98.9 

207.1 

93.1 

69.7 

165.2 

66.2 

100.6 

69.7 

58.3 

73.4 

70.3 

80.6 

89.0 

110.2 

145.7 

920 

102.2 

56.0 

57.3 

96.7 

71.4 

140.3 

75.0 

137.4 

76.3 

173.0 

65.6 

139.8 

66.3 

57.9 

112.7 

93.5 

125.5 

68.5 

165.4 

79.0 

58.8 

74.3 

112.2 

63.4 

107.0 

90.5 

114.8 

77.3 

Sources: lhbles 7 and 8. 

24 Advisory Cammission on Intergovernmental Relations 
Recapltulatlon: The Reglonal Dlmenslon 

‘Qble 10 provides summary statistics for the eight 

Census regions for the estimates discussed so far. (See 

’IBble 11 for a display of the states in each region.) The 

regions are arrayed in the table by the index of per capita 

representative expenditures adjusted for differences in 

unit input costs in column 3. The ratio of actual to 

representative expenditures (column 4) underlines the 

striking pattern that is apparent in the first two columns. 

There is a very strong inverse relationship between needs 

and actual expenditures. In other words, the higher the 

cost of a national-average level of public services, the 

more likely it is that the level of services actually provided 

will fall short of that average. 

In the New England states, the representative level of 

services could be provided at a cost of roughly 88 percent 

of the national average. Actual per capita outlays in New 

England, however, are 6 percent higher than average. As 

a result, the public services enjoyed by the typical resident of 

New England are, on average, 2.0 percent above the national 

average. In the Southwest states, on the other hand, the 

representative level of services costs 108 percent of the 

national average. Actual outlays, however, are more than 10 

percent below. As a consequence, the level of public seMces 

delivered in the typical state in the Southwest is more than 

17 percent below the national average. 

Fiscal Capacity Measures 

Reflectlng Representative Expendltures 

Compared with Population 

Measuresof the fiscal capacities of the 50 statesand 

the District of Columbia for four measures of own-revenueraising ability are presented in nble 11. The measures 

are personal income, RTS, gross state product (GSP), and 

Table 10 

Indices of Actual and Representative Expenditures 

and the Ratio of the Wo, by Census Region, 

1986.87 

Actual as Actual Representative Percentage 

Expen- of Adjusted 

ditures Unadjusted Adjusted Representative 

(1) (2) (3) (4) 

UnitedStates 100.0% 100.0% 100.0% 100.0% 

New England 105.8 

Mideast 119.3 

Plains 96.0 

Far West 115.0 

Rocky Mountain 103.4 

Great Lakes 95.7 

Southeast 83.1 

Southwt 89.3 

90.2 

92.6 

100.8 

98.0 

103.0 

98.4 

106.2 

107.8 

88.4 

93.9 

98.7 

100.5 

100.6 

101.7 

102.5 

108.0 

119.7 

127.1 

97.3 

114.4 

1028 

94.1 

81.1 

82.7 

Note: 

Sounxs: 7hble.d 7,8, and 9. 

The regional indices are population-weighted means. 

total taxable resources (’T’I’R).l2 For each measure of 

revenue-raising ability, a fiscal capacity index is shown 

with the relative costs of service responsibilities ac- counted for (1) by population and by representative 

expenditures (2) unadjusted and (3) adjusted for variation 

in unit input costs.13 The information is arrayed by Census 

region to facilitate comparisons among neighboring 

states. The population-weighted means of the indices of 

fiscal capacity and the standard deviations of the indices 

are shown for each region. 

For a given state, the relationship between the index 

calculated using population and those using representa- tive expenditures is the same for all four measures of 

revenue-raising ability. For example, Mississippi’s index 

of representative expenditures per capita, unadjusted for 

unit input costs, is 122. Adjusted, the index is only 113 

because the cost per unit of the inputs used to produce 

public services is more than 7 percent below the national 

average (see ThbIe 6). 

To calculate Mississippi’s fiscal capacity indices using 

representative expenditures rather than population, the 

four population-based indices of fiscal capacity are 

divided by the state’s two indices of per capita representa- tive expenditures (and the results are multiplied by 100).14 

These calculations reduce the four population-based 

indices of fiscal capacity for Mississippi shown in Table 11 

by 18 and 12 percent, respectively. 

The opposite effect is apparent in the case of 

Connecticut, whose index of per capita representative 

expenditures unadjusted for input prices is 88. Adjusted, 

however-because unit input costs are more than 4 percent 

higher than the national average-the state’s representative 

expenditure index is 92. Here the use of representative 

expenditures results in fiscal capacity indices for all four 

measures of revenue-raising ability that are 14 and 9 

percent higher, respectively, than the corresponding 

population-based indices. 

I2The estimates of personal income and RTS are for 1987; those 

for GSP and TTR are for 1986. See Table B5. A useful discussion 

of these measufes appears in Max B. S-, ‘Appendix A: 

Alternative Measures of Fiscal Capacity and Their Uses,” in 

Advisory Commission on Intergovernmental Relations, Mmur 

ing State Fiscal Capacity, 1987 Edition (Washington, DC, 1987) 

l3 The indices shown in Table 11 are not really measures of fixal 

capacity, as that concept is defined in Chapter 1 of this report, 

because revenues received from the federal government (and 

from state and local governments in other states) are not taken 

into consideration. The indices are more properly referred to 

as measures of own-revenue-raising ability relative to expenditure needs. An analysis of the fiscal capacities of the states 

taking into account actual amounts of federal grants received 

appears later in this chapter. 

14This is the same, mathematically, as dividing a state’s total 

personal income (or RTS tax capacity, or GSP, or TTR) by its 

total representative expenditures and indexing the resulting 

ratio to the ratio of the national totals of the same data. The 

calculation described in the text divides one index of per capita 

values by another index of per capita values. Since the same 

population is used to calculate the two per capita amounts that 

are indexed, the numerator and denominator of the fiscal 

capacity fraction are both divided by the same amount, and 

population therefore cancels. 

pp. 107-20. 
Table 11 

Indices of Fiscal Capacity with Public-Service Costs Accounted for by Population and by Representative Expenditures 

Unadjusted and Adjusted for Differences in the Unit Costs of Producing Public Services, 1987 

Pe-ome Re- Tax system Gross &ate Product e Resources 

Representative 

Expenditures Exwnditures 

Representative Representative Representative 

nditures Exwndituns 

Input- Input- Input- Input 

Popula- Not cost Popula- Not Cost Popula- Not Cost Popula- Not Cost 

Region and State tion Adjusted Adjusted tion Adjusted Adjusted tion Adjusted Adjusted tion Adjusted Adjusted 

United States 

New England 

Connecticut 

Maine 

Massachusetts 

New Hampshire 

Rhode Island 

Vermont 

Mideast 

Delaware 

District of Columbia 

Maryland 

New Jersey 

New York 

Pennsylvania 

Great Lakes 

Illinois 

Indiana 

Michigan 

Ohio 

Wisconsin 

Plains 

IOWa 

Kansas 

Minnesota 

Missouri 

Nebraska 

North Dakota 

South Dakota 

Standard hidion 

Standard hiatwn 

Standard Deviatwn 

Standard Deviation 

Standard Deviation 

(1) 

100.0 

15.2 

119.3 

15.3 

137.4 

90.1 

123.7 

113.2 

100.5 

92.4 

114.4 

11.5 

107.8 

132.1 

117.1 

131.5 

116.3 

98.3 

98.2 

5.7 

106.2 

89.9 

99.4 

94.4 

95.2 

94.9 

5.9 

92.0 

97.7 

102.9 

94.9 

926 

84.0 

81.1 

(2) 

100.0 

21.0 

132.8 

20.9 

156.5 

90.7 

139.1 

124.0 

113.4 

93.7 

123.5 

12.7 

112.7 

126.2 

124.4 

147.3 

122.9 

108.8 

99.9 

6.2 

108.9 

90.9 

97.5 

%.6 

100.7 

94.1 

9.4 

93.7 

97.0 

106.3 

93.0 

91.6 

75.2 

69.8 

(3) 

100.0 

19.4 

134.9 

16.1 

149.8 

101.2 

141.6 

132.6 

117.2 

103.7 

121.6 

10.8 

112.2 

128.4 

120.6 

141.3 

122.0 

108.6 

96.7 

5.2 

103.7 

90.5 

91.8 

94.5 

101.1 

96.1 

7.3 

95.9 

99.3 

105.0 

94.7 

96.2 

79.9 

77.5 

(4) 

100.0 

14.9 

1228 

14.4 

139.1 

96.9 

126.8 

l23.0 

95.8 

1027 

107.1 

10.6 

123.5 

122.1 

108.8 

122.3 

108.0 

92.3 

92.7 

3.9 

97.3 

87.1 

95.3 

91.0 

87.9 

92 1 

7.4 

83.5 

93.4 

103.9 

91.0 

90.6 

89.9 

78.3 

(5) 

100.0 

19.8 

136.6 

19.7 

158.5 

97.5 

1427 

134.7 

108.1 

104.2 

115.6 

11.6 

129.1 

116.6 

115.6 

137.0 

114.1 

1022 

94.3 

3.8 

99.8 

88.1 

93.4 

93.1 

92.9 

91.3 

10.2 

85.1 

92.7 

1M.4 

89.3 

89.6 

80.5 

67.4 

(6) 

100.0 

18.3 

139.0 

15.1 

151.8 

108.8 

145.3 

143.9 

111.7 

115.3 

113.9 

9.9 

128.4 

118.7 

112.1 

131.4 

113.4 

102.0 

91.3 

2.9 

95.0 

87.7 

87.9 

91.1 

93.3 

93.2 

8.2 

87.1 

94.9 

106.0 

90.8 

94.1 

85.5 

74.8 

(7) 

100.0 

17.8 

110.4 

13.6 

127.2 

85.0 

113.9 

103.7 

89.7 

91.8 

110.5 

26.4 

106.4 

265.0 

98.6 

116.7 

117.2 

88.8 

96.6 

5.4 

104.4 

88.8 

96.4 

94.2 

92.5 

95.2 

6.2 

88.5 

99.3 

103.2 

94.9 

95.5 

90.9 

79.6 

(8) 

100.0 

20.6 

122.9 

18.5 

144.9 

85.6 

128.2 

113.6 

101.3 

93.1 

118.8 

23.9 

111.2 

253.0 

104.8 

130.8 

123.9 

98.3 

98.2 

6.0 

107.1 

89.8 

94.5 

96.4 

97.8 

94.3 

9.3 

90.1 

98.6 

106.7 

93.0 

94.5 

81.4 

68.5 

(9) 

100.0 

18.8 

124.9 

14.0 

138.8 

95.5 

130.5 

121.4 

104.6 

103.0 

117.1 

24.3 

110.6 

257.6 

101.7 

125.4 

123.0 

98.1 

95.1 

5.1 

101.9 

89.4 

89.0 

94.4 

98.2 

96.4 

7.3 

923 

101.0 

105.4 

94.7 

99.2 

86.5 

76.1 

(10) 

100.0 

15.0 

113.4 

14.1 

130.5 

86.2 

117.5 

106.2 

94.6 

91.5 

111.9 

17.2 

104.4 

198.8 

106.9 

121.9 

117.0 

93.0 

97.7 

5.6 

105.4 

89.2 

98.7 

94.7 

93.8 

95.0 

6.0 

89.8 

99.7 

1028 

94.6 

94.7 

88.1 

80.2 

(11) 

100.0 

19.4 

126.3 

19.3 

148.6 

86.8 

1322 

116.3 

106.8 

928 

120.5 

15.7 

109.2 

189.9 

113.6 

136.6 

123.6 

103.0 

99.3 

6.0 

108.1 

90.2 

96.8 

%.9 

99.1 

94.3 

9.2 

915 

99.0 

106.3 

92.7 

93.7 

78.9 

69.0 

(12) 

100.0 

17.7 

128.3 

14.7 

1423 

%.9 

134.5 

124.3 

110.3 

102.7 

118.8 

15.3 

108.6 

193.3 

110.2 

131.0 

122.7 

102.9 

96.1 

5.0 

102.9 

89.9 

91.1 

94.8 

99.5 

96.2 

7.2 

93.7 

101.4 

104.9 

94.3 

98.4 

83.7 

76.6 
TdIe 11 (cont.) 

Indices of Fiscal Capacity with Public-Service Costs Accounted for by Population and by Representative Expenditures 

Unadjusted and Adjusted for Differences in the Unit Costs of Producing Public Services, 1987 

Pe Income Svstem CRepresentative Representative Representative Representative ItUreS nditures rcs 

Input- Input- Input- Input 

Popula Not Cost Popula Not Cost Popula- Not Cost Popula- Not cosc 

Region and State tion Adjusted Adjusted tion Adjusted Adjusted tion Adjusted Adjusted tion Adjusted Adjusted 

Southeast 

Alabama 

Arkansas 

Florida 

Georgia 

Kentucky 

Louisiana 

Mississippi 

North Carolina 

South Carolina 

Tennessee 

Virginia 

West Virginia 

Southwest 

Arizona 

New Mexico 

Oklahoma 

TexaS 

Rocky Mountain 

Colorado 

Idaho 

Montana 

Utah 

Wyoming 

Far West 

Alaska 

California 

Hawaii 

Nevada 

Oregon 

Washington 

Standard Deviation 

Standard hiation 

Standanl Deviation 

Standard Deviation 

(1) 

87.3 

12.3 

74.3 

100.7 

92.4 

77.9 

74.1 

66.5 

86.0 

77.5 

83.2 

106.7 

71.2 

87.9 

4.5 

92.5 

76.7 

81.1 

89.6 

85.9 

11.7 

100.7 

76.7 

79.8 

73.4 

82 1 

110.9 

7.9 

117.8 

115.1 

101.2 

105.7 

90.7 

100.8 

n. 1 

(2) 

83.2 

16.5 

68.0 

65.6 

104.3 

82.8 

71.2 

68.0 

54.4 

81.9 

70.6 

107.4 

67.3 

81.5 

5.6 

89.1 

65.8 

76.1 

829 

83.6 

15.2 

102.8 

71.4 

73.1 

68.4 

79.0 

113.1 

7.5 

114.1 

117.1 

111.1 

109.4 

92.0 

104.0 

77.4 

(3) 

86.1 

16.8 

70.9 

70.1 

108.8 

85.1 

71.9 

67.1 

58.7 

87.2 

75.0 

80.4 

108.2 

69.3 

81.3 

4.7 

90.2 

69.3 

78.1 

81.7 

85.4 

13.8 

102.6 

76.6 

78.2 

70.0 

80.4 

110.1 

6.7 

97.2 

113.7 

1129 

110.2 

926 

102.2 

(4) 

89.3 

12 1 

75.3 

73.8 

104.6 

94.2 

79.0 

86.1 

65.0 

89.5 

78.8 

83.8 

102.8 

77.2 

97.4 

3.7 

99.5 

86.6 

93.2 

99.1 

98.9 

20.3 

111.0 

76.9 

86.5 

79.0 

136.6 

114.6 

l2.9 

168.5 

117.1 

113.2 

140.6 

92.4 

98.5 

(5) 

85.1 

16.6 

66.4 

65.1 

108.4 

84.4 

722 

79.1 

53.2 

85.3 

71.7 

78.0 

103.4 

73.0 

90.3 

5.1 

95.9 

74.3 

87.5 

91.7 

96.2 

22.5 

113.4 

71.6 

79.3 

73.5 

13 1.4 

116.9 

12.3 

163.2 

119.1 

124.3 

145.4 

93.8 

101.7 

(6) 

88.1 

16.9 

69.2 

69.6 

113.0 

86.7 

72.9 

78.0 

57.4 

90.8 

76.3 

81.0 

104.2 

75.1 

90.1 

4.1 

97.0 

78.3 

89.7 

90.4 

98.2 

21.3 

113.2 

76.8 

84.9 

75.3 

133.7 

113.6 

10.2 

139.0 

115.6 

126.3 

146.6 

94.4 

99.9 

(7) 

87.6 

9.3 

78.1 

76.7 

87.4 

97.0 

82.0 

95.1 

69.8 

91.7 

76.1 

86.7 

103.4 

72.3 

loo. 1 

6.8 

93.4 

91.8 

86.7 

104.6 

96.5 

17.3 

104.2 

75.6 

85.6 

83.0 

132.4 

112.3 

17.9 

211.6 

113.7 

104.3 

115.5 

87.9 

100. 1 

(8) 

83.1 

12.0 

68.9 

67.7 

90.6 

87.0 

75.0 

87.4 

57.1 

87.4 

69.2 

80.7 

104.1 

68.4 

92.7 

6.6 

90.0 

78.7 

81.4 

96.8 

93.8 

19.1 

106.4 

70.4 

78.5 

77.3 

127.4 

114.4 

16.6 

205.0 

115.7 

114.6 

119.5 

89.2 

103.3 

(9) 

86.0 

11.6 

71.8 

72.4 

94.4 

89.4 

75.7 

86.2 

61.6 

93.0 

73.7 

83.7 

104.9 

70.4 

925 

4.8 

91.1 

83.0 

83.5 

95.4 

95.7 

17.9 

106.2 

75.5 

84.0 

79.1 

129.6 

111.1 

12.4 

174.5 

1123 

116.4 

120.5 

89.8 

101.5 

(10) 

87.2 

9.7 

77.8 

76.2 

93.6 

94.5 

79.4 

85.8 

68.1 

88.4 

76.6 

84.4 

104.2 

72.3 

95.1 

5.2 

93.3 

84.9 

85.3 

98.3 

92.5 

13.4 

104.2 

76.1 

83.2 

79.0 

109.9 

111.8 

11.7 

166.8 

114.5 

102.9 

110.3 

89.4 

101.3 

(11) 

82.9 

13.5 

68.6 

67.3 

97.0 

84.7 

72.6 

78.8 

55.7 

84.2 

69.7 

78.5 

104.9 

68.4 

88.1 

5.7 

89.9 

72.8 

80.1 

91.0 

89.9 

16.4 

106.4 

70.9 

76.3 

73.6 

105.7 

114.0 

10.7 

161.5 

116.5 

113.0 

114.1 

90.7 

104.6 

(12) 

85.9 

13.5 

71.5 

71.9 

101.2 

87.0 

73.3 

77.7 

60.1 

89.6 

74.1 

81.5 

105.8 

70.4 

87.9 

4.2 

91.0 

76.8 

82.1 

89.7 

91.8 

14.8 

106.2 

76.1 

81.6 

75.3 

107.5 

110.8 

7.8 

137.5 

113.1 

114.8 

115.0 

91.3 

102.8 

Swrces: 'Ihbles 8 and B-5; and U.S. Department of Commerce, Bureau of the Census, State pbpulotion and Household Estimates, with Age, Sex, and Components of Change, 1981-87, Current Population 

Reports, (Washington, DC, 1988), 'Eibles 5 and 6. 
Exhibit 2 

Comparison of Indices of Fiscal Capacity Calculated Using Resident Population 

and Input-Cost-Adjusted Representative Expenditures 

Population Index Is: 

ReDresentative ExDenditure Index 

Above Average Below Average 

Higher than Index Calculated 

Using Representative Expenditures 

District of Columbia 

Illinois 

Alaska 

California 

Michigan 

Missouri 

North Dakota 

South Dakota 

Alabama 

Arkansas 

Georgia 

Kentucky 

Louisiana 

Mississippi 

South Carolina 

Tennessee 

West Virginia 

Arizona 

New Mexico 

Oklahoma 

Texas 

Idaho 

Montana 

Utah 

Wyoming 

Lower than Index Calculated 

Using Representative Expenditures 

Connecticut 

Maine 

Massachusetts 

New Hampshire 

Rhode Island 

Vermont 

Delaware 

Maryland 

New Jersey 

New York 

Pennsylvania 

Wisconsin 

Minnesota 

Florida 

Virginia 

Colorado 

Hawaii 

Nevada 

Washington 

Indiana 

Ohio 

Iowa 

Kansas 

Nebraska 

North Carolina 

Oregon 

Source: nble 11. 

The relationship apparent in the cases of Mississippi 

and Connecticut is a general one. That is, the use of 

population (rather than representative expenditures) to 

calculate a measure of fiscal capacity tends systematically 

to understate the capacities of states that are above the 

national average and to overstate the capacities of those 

below it. This is quite apparent in Exhibit 2, which arrays 

the states by the relationship between the estimate of 

fiscal capacity using the unit-cost-adjusted index of 

representative expenditures and the estimate calculated 

using resident population. 

The population-based measure overstates the fiscal 

capacities of 21 of the 28 states whose capacities are below 

the national average by the representative expenditure-based index. At the same time, the population-based 

measure understates the fiscal capacities of 19 of the 23 

states whose capacities are above the national average 

when representative expenditures are used in calculating 

the measure. 

Statistical confirmation of this relationship can be 

found in the standard deviations of the indices for the 

nation as a whole. For every measure of revenue-raising 

ability, the standard deviations are higher when representative expenditures are substituted for population. This 

indicates that the effect of the substitution is to widen the 

spread of estimates of fiscal disparities among the states. 

It is interesting to note that the relationship between 

the standard deviations is not apparent for every region 

28 Advisory Commission on Intergovernmental Relations 
for every measure of revenue-raising ability. For example, 

the standard deviations for the Far West are lower in both 

cases for the indices calculated using representative 

expenditures. The standard deviation also is lower for both 

indices using representative expenditures for the Mideast 

for the GSP and lTR measures of revenue-raising ability. 

An Alternative Statement of the Results 

An alternative to indices as a vehicle for the results of 

the analysis is to calculate the gap between a state’s total 

representative expenditures, expressed as a dollar 

amount, and its revenue-raising ability, similarly expressed. The revenue-raising potential of a state is 

calculated by distributing the national total of the direct 

general expenditures of state and local governments 

among the states in proportion to the distribution of a 

measure of revenue-raising ability.15 

This approach has several advantages over index 

numbers. The most important is that the gap is a dollar 

estimate of the difference between the fiscal capacity of a 

state and the national average. With this measure, it is 

possible to estimate the effectiveness of federal grant 

programs-existing or proposed-in reducing disparities 

in fiscal capacities among the states. The analysis can be 

conducted by ignoring existing federal grants or by taking 

them into account in calculating the gaps. Both approaches are explored in the next few pages. 

Dlsregarding Federal Grants 

Abstracting from federal payments to state and local 

governments, a state’s gap is the difference between (a) its 

total cost of providing the representative level of public 

services, adjusted for input costs, and (b) the total revenue 

that would be raised if the state were to exploit its 

revenue-raising potential at the national-average rate. 

The estimates of “needs” and potential revenues for 

all the states and the District of Columbia add, by 

construction, to $653.6 billion.16 This is the national total 

of direct general expenditures by state and local governments in FY 1986-87. The gap for a state may be positive 

or negative; the national sum of the gaps is zero. This 

underlines the inherently relative nature of the measurement of fiscal capacity. 

A state’s gap is positive if its cost of the representative 

level of public services exceeds the revenues it could raise 

with the national-average level of fiscal effort. Such a 

state has a fiscal capacity below the national average. A 

state with a negative gap has an above-average fiscal 

capacity. It could finance an average level of services with 

below-average fiscal effort, or better-than-average services with average effort. 

~~ 

15This procedure ensures that, for the nation as a whole, total 

revenues equal actual direct general expenditures. For exam- ple, the RTS estimates of the “tax capacities” of the states in 

1985-86 cannot be used directly because their sum is only 59 

percent (and the RRS estimates of “revenue capacities,” 76 

percent)of the total general expenditures of all state and local 

governments in that year. 

*6The estimates of representative expenditures appear in Table 

B-3; those of own revenue-raising ability in Table B-5. 

The estimates of the state gaps are shown in Xible 12. 

Estimates of the revenues each state could raise with an 

average fiscal effort appear in columns 2-5 for the four 

measures. Columns 6-9 show the amounts of the gaps for 

the four measures, given the estimates of representative 

expenditures in column 1. For the nation as a whole, the 

sum of the (positive and negative) gaps is zero, since total 

revenues equal total outlays by construction. 

The sums of the positive gaps are of special interest, 

however. They are estimates of the outlays that would be 

required under a perfectly designed federal grant program 

to raise the fiscal capacity of evey state to the national 

average.” The average of these magnitudes suggests that 

this objective could have been achieved in 1986-87 at a total 

cost of roughly $46 billion (40 percent of the total of $115 

billion of federal grants paid in that year). The same 

calculation could be done for any fraction or multiple of the 

national average level of fU capacity that might be 

postulated as a policy objective. 

Comparison of the size of a state’s gap, positive or 

negative, with its representative expenditures and reve- nue-raising ability makes possible a variety of interesting 

insights into its flscal situation. For example, by the KlX 

measure of revenue-raising ability, Connecticut’s gap is 

negative $4,0!42million. Relating this to the state’s represen- tative expenditures indicates that, with average fiscal effort, 

Connecticut could finance outlays 52 percent higher than 

the national average ($4,092/$7,906). It is interesting to note 

that the state’s actual outlays of $9,394 million are only 19 

percent above its representative level.lS It follows that 

Connecticut’s actual fiscal effort is well below the national 

average-nearly 22 percent below, in fact ($9,394/$11,998). 

Alternatively, Connecticut could fmance the representative 

level of expenditures with fiscal effort of less than 66percent 

of the national average ($7,906/$11,998). 

At the other extreme, Mississippi, with a gap (by the 

RTS measure) of $3,406 million, has the weakest fiscal 

capacity in the nation. To finance the representative 

level of expenditures, Mississippi would have to exert a 

fiscal effort 74 percent higher than the national average 

($3,406/$4,581). Conversely, limiting its fiscal effort to 

the national average would produce revenue sufficient 

to finance only 57 percent of the representative level of 

spending ($4,581/$7,987). Mississippi’s actual outlays 

($5,319 million) are 67 percent of that level. Hence its 

actual fiscal effort is more than 16 percent higher than 

the national average ($5,319/$4,581). 

Bble 13 presents the gaps in terms that facilitate 

direct comparisons among the states: columns 1-4 

display the gaps on a per capita basis, and columns 5-8 

show them as percentages of the representative 

expenditures of each state. 

Taking Federal Grants Into Account 

‘Ib this point, the analysis has abstracted from the 

federal grant system and its implications for the relative 

17The analysis at this point is assuming that there are no other 

federal grants. 

Actual expenditures appear in Table El. 

Advisory Cammission on Intergovernmental Relations 29 
Table 12 

Calculation of the Gap between “Needs” and Revenue-Raising Ability in 1987, with No Account ’Men of Federal Grants 

(millions) 

~~ - 

Revenue-Raising Ability: Total General Gap between “Needs” and 

Revenue Re-ltV .. .. .. Total 

Representative Personal Personal 

state Expenditures Income RTS CSP TTR Income RTS GSP TTR 

United States 

Alabama 

Alaska 

Arizona 

Arkansas 

California 

Colorado 

Connecticut 

Delaware 

District of Columbia 

Florida 

Georgia 

Hawaii 

Idaho 

Illinois 

Indiana 

Iowa 

Kansas 

Kentucky 

Louisiana 

Maine 

Maryland 

Massachusetts 

Michigan 

Minnesota 

Mississippi 

Missouri 

Montana 

Nebraska 

Nevada 

New Hampshire 

New Jersey 

New Mexico 

New York 

North Carolina 

North Dakota 

Ohio 

Oklahoma 

Oregon 

Pennsylvania 

Rhode Island 

South Carolina 

South Dakota 

Tennessee 

Texas 

Utah 

Vermont 

Virginia 

Washington 

West Virginia 

Wisconsin 

Wyoming 

Sum of Positive Gaps 

(1) 

$653,608 

11,926 

1,710 

9,325 

6,796 

75,242 

8,682 

7,906 

1,663 

1,718 

29,883 

18,138 

2,607 

2,682 

31,856 

14,747 

7,294 

6,541 

10,841 

13,224 

2,838 

11,817 

13,726 

26,764 

11,174 

7,987 

13,733 

2,215 

4,118 

2,593 

2,425 

19,172 

4,455 

45,619 

16,977 

1,898 

28,921 

9,123 

7,161 

28,990 

2,271 

9,502 

1,993 

13,496 

49,436 

4,734 

1,312 

15,627 

12,015 

534 

12,160 

1,345 

(2) 

$653,608 

8,457 

1,661 

8,407 

4,767 

85,513 

8,910 

11,846 

1,865 

2,207 

32,500 

15,434 

2,944 

2,055 

33,032 

13,349 

6,999 

6,496 

7,796 

8,877 

2,872 

14,256 

19,442 

24,565 

11,730 

4,686 

13,000 

1,733 

3,963 

2,859 

3,214 

27,085 

3,090 

55,668 

14,810 

1,516 

27,333 

7,124 

6,634 

3 1,494 

2,660 

7,131 

1,544 

10,847 

40,378 

3,312 

1,360 

16,915 

12,280 

3,627 

12,292 

1,081 

(3) 

$653,608 

8,253 

2,376 

9,048 

4,730 

86,966 

9,825 

11,998 

2,135 

2,040 

33,760 

15,732 

3,291 

2,061 

30,266 

12,937 

6,356 

7,904 

10,320 

3,089 

13,248 

19,944 

23,536 

11,842 

4,581 

12,474 

1,880 

3,876 

3,803 

3,490 

25,202 

3,488 

51,712 

15,414 

1,622 

26,346 

8,187 

6,760 

29,575 

2,536 

7,249 

1,490 

10,928 

44,687 

3,563 

1,512 

16,291 

12,006 

3,930 

11,346 

1,797 

(4) 

$653,608 

8,577 

3,052 

8,304 

4,933 

83,237 

9,227 

11,015 

1,825 

4,489 

27,713 

16,049 

3,013 

2,054 

32,693 

13,242 

6,835 

6,623 

8,285 

11,605 

2,702 

11,929 

18,014 

23,895 

11,792 

4,963 

13,025 

1,897 

4,135 

3,029 

2,888 

24,132 

3,680 

56,561 

15,743 

1,674 

27,459 

7,767 

6,436 

28,622 

2,371 

6,974 

1,528 

11,278 

47,326 

3,744 

1,347 

16,241 

12,113 

3,751 

11,994 

1,820 

(5) 

$653,608 

8,542 

2,405 

8,292 

4,898 

83,850 

9,222 

11,295 

1,792 

3,369 

29,688 

15,624 

2,971 

2,069 

33,018 

13,3 15 

6,941 

6,648 

8,023 

10,468 

2,740 

12,934 

18,577 

24,458 

11,747 

4,843 

12,981 

1,843 

4,101 

2,891 

2,957 

25,207 

3,404 

56,437 

15,164 

1,621 

27,601 

7,643 

6,547 

29,995 

2,501 

7,020 

1,539 

10,976 

44,485 

3,565 

1,342 

16,377 

12,258 

3,757 

12,159 

1,511 

(6) 

so 

51,647 

3,470 

49 

9 18 

2,029 

(10,271) 

(229) 

(3,940) 

(202) 

(488) 

(2,617) 

2,704 

(337) 

627 

(1,176) 

1,398 

296 

45 

3,045 

4,347 

(34) 

(2,440) 

(5,716) 

2,m 

(556) 

3,302 

734 

482 

156 

(266) 

(789) 

(7,912) 

1,366 

(10,048) 

2,167 

382 

1,587 

1,999 

527 

(2,504) 

(390) 

2,371 

449 

2,649 

9,058 

1,421 

(48) 

(1,287) 

(265) 

(131) 

1,608 

264 

(7) 

$0 

48,114 

3,673 

(666) 

277 

2,066 

(1,143) 

(472) 

(322) 

(37877) 

(684) 

(11,725) 

(4,092) 

2,407 

621 

1,589 

1,811 

938 

332 

2,937 

2,904 

(25 1) 

(1,431) 

(6,218) 

3,228 

(668) 

3,406 

139 

335 

242 

(1,209) 

(1,065) 

(6.029) 

967 

(6,092) 

1,562 

276 

2,575 

936 

401 

(586) 

(265) 

2,253 

502 

2,567 

4,749 

1,171 

(2oc9 

(664) 9 

1,304 

8 15 

(453) 

$0 $0 

40,411 43,294 

3,349 3334 

(1,343) (6%) 1,021 1,032 

1,863 1,897 

(7,996) (8,608) 

(546) (540) (3,109) (3,389) 

(163) (130) 

(2,771) (1,651) 2,170 195 

2,090 2,514 

(406) (364) 628 6 13 

(837) (1,162) 1505 1,432 

459 353 

(82) (108) 2,555 2,818 

1,619 2,756 

137 98 

(113) (1,118) 

(4,288) (485 1) 2,870 2,307 

(618) (573) 3,024 3,144 

708 753 

(4,960) (6,035) 775 1,051 

(10,942) (10;818) 

1,234 1,813 

1,461 1,320 

1,355 1,480 

725 614 

367 (1,006) 

(loo) (231) 

224 271 

2,527 2,482 

464 454 

2,218 2,519 

2110 4.951 

.990 1;169 

(613) (749) 

(35) (30) 

(98) (243) 

Note: 

Sources: 1 -Thble B-3. 

Columns 2-5 show the total revenue that each state could raise if it were to exploit its own-revenue-raising potential at the national-average rate, 

abstracting from federal payments to the states and localities, as indicated by each of the four measures of revenue-raising ability. 

2-5-Bble B-5. 

6-9-Column 1 less columns 2-5, respectively. 

30 Advisory Commission on Intergovernmental Relations 
Table 13 

Gap between "Needs" and Revenue-Raising Ability in 1987, with No Account Taken of Federal Grants, 

Per Capita and Relative to Representative Expenditures 

(dollar amounts in millions) 

state 

~~ 

Per Q&a As Ph 

Personal Personal 

Income RTS GSP TTR Income RTS GSP TTR 

United States 

Alabama 

Alaska 

Arizona 

Arkansas 

California 

Colorado 

Connecticut 

Delaware 

District of Columbia 

Florida 

Georgia 

Hawaii 

Idaho 

Illinois 

Indiana 

IOWa 

Kansas 

Kentucky 

Louisiana 

Maine 

Maryland 

Massachusetts 

Michigan 

Minnesota 

Mississippi 

Misfouri 

Montana 

Nebraska 

Nevada 

New Hampshire 

New Jersey 

New Mexico 

New York 

North Carolina 

North Dakota 

Ohio 

Oklahoma 

Oregon 

Pennsylvania 

Rhode Island 

South Carolina 

South Dakota 

Tennessee 

TexaS 

Utah 

Vermont 

Virginia 

Washington 

West Virginia 

Wisconsin 

Wyoming 

Sum of Positive Gaps 

(1) 

$0.00 

212 19 

849.82 

92.52 

271.10 

849.68 

(371.28) 

(69.35) 

(1,227.02) 

(314.10) 

(785.31) 

(217.67) 

434.66 

(311.18) 

628.13 

(101.53) 

252.71 

104.32 

17.98 

816.95 

974.53 

(28.47) 

(538.00) 

(976.28) 

239.10 

(130.91) 

1,257.85 

143.77 

595.61 

97.73 

(263.98) 

(746.79) 

(1,031.33) 

910.48 

(563.72) 

337.85 

568.34 

147.18 

611.00 

193.60 

(209.8 1) 

(395.13) 

692.24 

63299 

545.60 

539.52 

846.10 

(88.30) 

(218.03) 

(58.36) 

847.45 

(27.33) 

538.56 

(2) 

$0.00 

197.68 

899.59 

(1,268.62) 

81.88 

865.13 

(423.84) 

(1,274.48) 

(5 17.3 1) 

(322.5 1) 

386.80 

(63 1.95) 

622.42 

137.23 

327.36 

331.00 

134.18 

787.94 

650.97 

(315.53) 

350.90 

(157.32) 

1,297.58 

246.80 

414.27 

151.80 

(1,200.82) 

(1,007.71) 

(785.91) 

644.88 

(34 1.78) 

243.64 

410.90 

238.75 

286.15 

147.35 

(49.07) 

657.79 

708.45 

528.81 

282.89 

697.05 

(365.49) 

(112.41) 

1.97 

687.25 

169.44 

(923.89) 

(346.93) 

(733.66) 

(211.28) 

(1,062.0 1) 

(268.97) 

(3) 

$0.00 

166.03 

820.28 

(2,557.58) 

301.54 

780.29 

(289.04) 

(165.56) 

(968.28) 

(252.76) 

(4,455.25) 

180.46 

335.85 

(374.52) 

629.43 

(72.30) 

272.16 

161.94 

(33.15) 

685.66 

362.87 

115.17 

(24.84) 

(732.36) 

311.95 

(145.63) 

1,152.10 

138.73 

393.63 

(432.60) 

(437.89) 

(646.53) 

516.61 

(613.84) 

19243 

333.37 

135.50 

414.27 

266.10 

30.78 

(101.62) 

737.93 

654.71 

4%. 78 

125.67 

589.38 

(64.03) 

(103.89) 

(21.61) 

778.50 

34.47 

(970.42) 

(10.68) 

(4) 

$0.00 

177.87 

628.86 

(1,325.20) 

304.88 

794.57 

(311.17) 

(163.92) 

(1,055.42) 

(201.21) 

(2,653.80) 

16.21 

404.08 

614.50 

(100.34) 

258.98 

124.6 1 

756.17 

617.86 

82.57 

(246.42) 

(828.48) 

250.75 

(134.85) 

1,197.85 

147.47 

459.52 

11.09 

(295.86) 

(503.27) 

(786.57) 

700.61 

(606.89) 

282.64 

411.50 

122.41 

452.44 

225.36 

(84.26) 

(233.98) 

724.65 

640.18 

518.90 

294.90 

695.57 

(335.74) 

(43.57) 

(55.46) 

(126.90) 

(53.58) 

778.50 

.21 

(338.38) 

(5) 

0.0% 

7.9 

29.1 

2.8 

9.8 

29.9 

(13.7) 

(2.6) 

(12.2) 

(28.4) 

(8.8) 

(129) 

(3.7) 

(49.8) 

14.9 

23.4 

9.5 

4.1 

.7 

28.1 

32.9 

(1.2) 

(20.6) 

(5.0) 

(41.6) 

8.2 

41.3 

5.3 

21.8 

3.8 

(10.3) 

(32.6) 

(41.3) 

30.7 

12.8 

20.1 

5.5 

21.9 

7.4 

(8.6) 

(17.2) 

25.0 

22.5 

19.6 

18.3 

30.0 

(22.0) 

(3.7) 

(8.2) 

(22) 

(1.1) 

30.7 

19.6 

(6) 

0.0% 

7.4 

30.8 

(39.0) 

3.0 

30.4 

(15.6) 

(13.2) 

(51.8) 

(28.4) 

(18.7) 

(26.3) 

(13.0) 

13.3 

23.2 

5.0 

12.3 

12.9 

5.1 

27.1 

22.0 

(8.8) 

(12 1) (45.3) 

(6.0) 

12.1 

42.6 

9.2 

15.1 

5.9 

(46.6) 

(43.9) 

(31.4) 

21.7 

(13.4) 

9.2 

14.6 

8.9 

10.3 

5.6 

(2.0) 

(11.7) 

23.7 

25.2 

19.0 

9.6 

24.7 

(15.3) 

(4.2) .1 

24.9 

6.7 

(33.7) 

(7) 

0.0% 

6.2 

28.1 

(78.5) 

11.0 

27.4 

(10.6) 

(6.3) 

(39.3) 

(9.8) (161.3) 

7.3 

11.5 

(15.6) 

23.4 

(2.6) 

10.2 

6.3 

(1.3) 

23.6 

12.2 

4.8 

(1.0) 

(31.2) 

10.7 

(5.5) 

37.9 

5.2 

14.4 

(.4) (16.8) 

(19.1) 

(25.9) 

17.4 

(24.0) 

7.3 

11.8 

5.1 

14.9 

10.1 

1.3 

(4.4) 

26.6 

23.3 

16.4 

4.3 

20.9 

(2.7) 

(3.9) 

(-8) 

(35.4) 

28.2 

1.4 

(8) 

0.0% 

6.6 

28.4 

(4.7) 

11.1 

27.9 

(11.4) 

(6.2) 

(42.9) 

(7.8) 

(96.1) 

.7 

13.9 

(13.9) 

22.9 

(34 

9.7 

4.8 

(1.6) 

26.0 

20.8 

3.5 

(9.5) 

(35.3) 

(5.1) 

8.6 

39.4 

5.5 

16.8 

.4 

(11.5) 

(21.9) 

(31.5) 

23.6 

(23.7) 

10.7 

14.6 

4.6 

16.2 

8.6 

(3.5) 

(10.2) 

26.1 

22.8 

18.7 

10.0 

24.7 

(2.3) 

(4.8) 

(2.0) 

28.2 

(12.3) 

*Less than 0.05 percent 

Sources: Thbles 11 and 12. 

Advisory Commission on Intergovemmenbil Relations 31 
fiscal capacities of the states. Federal grants could be 

introduced into the analysis in a variety of ways. It is 

convenient-and does no great violence to reality-to 

assume that federal grants are revenue for state and local 

governments that is independent of their abilities to raise 

funds from their own sources. On this assumption, a 

state’s overall revenue-raising ability can be defined as the 

amount of federal grants its governments receive plus its 

share (defined by a measure of what has to this point been 

referred to as revenue-raising ability) of the total cost to 

all state and local governments of financing the actual 

level of direct general expenditures net of federal grants. 

In other words, a state’s overall revenue-raising 

potential is the sum of the actual federal grants it receives 

and what can be called its “own-revenue-raising ability.” 

Estimates of the gaps between “needs” and the revenues 

yielded by national-average fiscal effort, given the actual 

distribution of federal grants in 1986-87, appear in Wle 14. l9 

It is interesting to compare the results for Connecticut and Mississippi when federal grants are taken into 

account. The total revenues available to Mississippi if its 

governments were to exert national-average fiscal effort 

(again using the RTS measure) are $508 million larger 

(compare Thble 14, column 4, with Thble 12, column 3). 

Since representative expenditures remain the same, this 

means that Mississippi’s gap drops by the same amount. 

A somewhat curious situation now obtains because 

the national-average level of state-local fiscal effort-and 

hence the yield of that level of effort in each state-is 

lower when federal grants are brought into the picture. 

That is, state and local governments as a group have to 

raise from their own sources only the portion of their 

expenditures that is not financed by the federal grants. 

The own revenues produced by the national-average 

level of own-revenue-raising effort in Mississippi total 

$3,775 million-$806 million less than Mississippi’s 

governments would have collected at national-average 

effort in the absence of the federal aid. As a result, to raise 

the additional $2,898 million needed to finance its represenl9 The essential difference between Tables 12 and 14 is that the 

national total distributed among the states by the measures of 

revenueraising ability in Table l2 is $653.6 billion. The amount 

distributed by the four measures in Table 14 is $538.6 billion (the 

total of Table l2 minus $115.0 billion of federal grantsj To each 

state’s share of the national total of own-=venue-raising ability is 

added the actual amount of federal grants reoeived by the state. 

The result is its overall mnue-raising ability. 

tative level of spending (that is, the state’s gap in Tmble 14, 

column 8), an increase in the fiscal effort of Mississippi’s 

governments of 77 percent would be required (rather than, 

as mentioned earlier, the 74 percent rise in effort needed 

when the analysis disregards federal grants-in-aid). 

Alternatively, Mississippi could finance 64 percent of 

the national-average level of services with average fiscal 

effort, compared with only 57 percent of the level in the 

absence of federal grants. However, since, as noted 

earlier, the state’s actual spending is only 67 percent of its 

representative level, it is clear that when account is taken 

of federal grants Mississippi’s own-revenue-raising effort 

exceeds the national average by only 6 percent.” 

The overall revenue-raising ability of Connecticut is 

somewhat diminished, relatively speaking, by the federal 

grant system. Its total revenues (by the mS) with average 

fiscal effort are $738 million lower when grants are taken 

into consideration (but this still is $3,354 million more than 

needed to finance its representative expenditures). ?his 

implies that the state would have to exert an ownrevenue-raising effort of roughly 66 percent of the national 

average to finance its representative expenditures.21 Anoth- er way of expressing this result is that average effort would 

yield sewices 42 percent higher than the national average. 

’Wing these two states alone, the results suggest that 

the federal grant system in 1986-87 tended to reduce fiscal 

disparities. When all 50 states and the District of Columbia 

are taken into account, however, the evidence in Wles 12 

and 14 is inconclusive. Two of the four measures of 

own-revenue-raising ability suggest that federal grants tend 

to worsen disparities to a very minor degree (the sums of the 

positive gaps for these measures-GSP and TI’R-are, on 

average, slightly larger when federal grants are taken into 

account than when they are ignored); the other two 

measures suggest the opposite conclusion. It is clear that the 

federal grant system does little to mitigate underlying fiscal 

disparities among the states. 

“Mississippi’s actual expenditures total $5,319 million. Netting 

federal grants of $1,314 million leaves $4,005 million to be 

financed by own revenues. This level of actual own revenues is 

only 6 percent larger than the yield in Mississippi of the national 

average level of own (RTS) effort-$3,?75 million (s@%J milbn, 

from column 4 of Table 14, less federal grants of $Ul4 million) 

21 Connecticut’s representative expenditures total $7,906 mil- lion, its federal grants $1,373 million, leaving $6,533 million to 

be financed from own sources. This requirement amounts to 

66 percent of the state’s own-revenue-raising ability, which is 

$9,887million ($11,260 million, from column 4of Table 14, less 

actual federal grants). 

32 Advisory Cornhission on Intergovernmental Relations 
Table 14 

Calculation of the Gap Between “Needs” and Revenue-Raising Ability in 1987, 

with Account Taken of Actual Federal Grants 

(millions) 

Total Total Revenue-Raising Ability: Federal 

Federal Represen- Grants Plus Own General Revenue Gap between “Needs” and 

Grants- tative Dimbuted bv Wure 

in-Aid Expendi- Personal Personal 

Revenue- .. 

Stnk 1986-87 Income RTS GSP TTR Income RTS GSP TTR tuns 

(1) (2) 

United States $114,996 $653,608 

Sum of Positive Gaps 

Alabama 

Alaska 

Arizona 

Arkansas 

California 

Colorado 

Connecticut 

Delaware 

District of Columbia 

Florida 

Georgia 

Hawaii 

Idaho 

Illinois 

Indiana 

Iowa 

Kansas 

Kentucky 

Louisiana 

Maine 

Maryland 

Massachusetts 

Michigan 

Minnesota 

Mississippi 

Missouri 

Montana 

Nebraska 

Nevada 

New Hampshire 

New Jersey New Mexico 

New York 

North Carolina 

North Dakota 

Ohio 

Oklahoma 

Oregon 

Pennsylvania 

Rhode Island 

South Carolina 

South Dakota 

Tennessee 

TexaS 

Utah 

Vermont 

Virginia 

Washington 

West Virginia 

Wisconsin 

Wyoming 

1,742 

560 

1,176 

1,017 

14,390 

1,429 

1,373 

3 18 

1,393 

3,668 

2,756 

528 

423 

5,147 

2,210 

1,227 

900 

1,588 

2,735 

683 

2,210 

3,118 

4,721 

2,274 

1,314 

1,854 

565 

677 

396 

388 

3,423 

697 

12,472 

2,382 

423 

4,541 

1,277 

1,482 

5,648 

551 

1,352 

405 

2,131 

5,600 

894 

362 

2,264 

2,444 

988 

2,418 

459 

11,926 

1,710 

9,325 

6,796 

75,242 

8,682 

7,906 

1,663 

1,718 

29,883 

18,138 

2,607 

2,682 

31,856 

14,747 

7,294 

6,541 

10,841 

13,224 

2,838 

11,817 

13,726 

26,764 

11,174 

7,987 

13,733 

2,215 

4,118 

2,593 

2,425 

19,172 

4,455 

45,619 

16,977 

1,898 

28,921 

9,123 

7,161 

28,990 

2,271 

9,502 

1,993 

13,496 

49,436 

4,734 

1,312 

15,627 

12,015 

5,234 

12,160 

1,345 

8,711 8,544 

1,929 2,518 

8,104 8,632 

4,945 4.915 

84,858 86;056 

8,772 9,526 

11,134 11,260 

1,854 2,077 

3,212 3,074 

30,450 31,489 

15,474 15,720 

2,954 3,241 

2,116 2,121 

32,367 30,088 

13,211 12,871 

6,994 6,465 

6,253 6,016 

8,012 8;lOl 

10,050 11,239 

3,050 3,229 

l3,958 13,127 

19,139 19,553 

24,964 24,116 

11,941 12,033 

5,175 5,089 

12,567 12,134 

1.993 2.114 

31942 31871 

2,753 3,530 

3,037 3,264 

25,742 24,191 

3,243 3,571 

58.345 55.085 

14:587 15:085 

1,672 $759 

27,065 26,251 

7.147 8.023 

6;~ i;os3 

31,601 30,020 

2,744 2,641 

8,810 8,782 

3,075 2,542 

8,019 8,010 

5,082 5,053 

82,983 83,487 

9,033 9,029 

10,450 10,680 

1,822 1,794 

5,093 4,170 

26,506 28,133 

15,981 15,631 

3,011 2,976 

2,115 2,128 

32,088 32,356 

13,122 13,182 

6,860 6,947 

6,357 6,378 

8,415 8,199 

12,298 11,361 

2,910 2,941 

12,040 12,868 

17,962 18,426 

24,412 24,876 

11,992 11,954 

5,404 5,305 

12,588 12,551 

2.128 2.084 

41085 41056 

2,893 2,779 

2,768 2,825 

23,310 24,195 

3,730 3,502 

59.082 58.980 

3:355 14I879 

1,802 1,759 

27,169 27,285 

7.678 7.575 

6,786 61878 

29,235 30,366 

2,505 2,613 

7,099 7,137 

1,665 1,673 

11,425 11,177 

44,600 42,258 

3,979 3,832 

1,472 1,468 

15.647 15.759 

121426 12i545 

4,084 4,084 

12,302 12,438 

1,959 1,704 

(7) 

$0 

49,637 

3,215 

(219) 

1,221 

1,851 

(9,616) 

(90) (3,229) 

(192) 

(1,494) 

(567) 

2,664 

(348) 

565 

(511) 

1,536 

300 

288 

2,829 

3,174 

(212) 

(5,413 

1,801 

2,8 12 

1,167 

222 

176 

(767) 

(6,570) 

1,213 

(12,726) 

2,390 

226 

1,856 

1,976 

212 

(2,612 

2,273 

3 15 

29426 

10,562 

1,110 

(171 

1,258 

(4731 

(8) 

$0 

47,155 

3,383 

(808) 

693 

1,881 

(10,814) 

(414) 

2,418 

(634) 

561 

1,767 

1,877 

829 

525 

2,740 

1,985 

(391) 

(1,310) 

(5,827) 

2,648 

(859) 

2,898 

1,600 

10 1 

247 

(5,019) 884 

(9,466) 

1,892 

138 

2,669 

1,100 

108 

(1,031 

2,176 

359 

2,359 

7,011 

903 

(323 

1,008 

393 

(596) 

(3701 

(9) 

$0 

41,591 

3,116 

(1,366) 

1,306 

1,714 

(7,741) 

(35 1) (2,544) 

(159) 

(3,375) 

3,377 

2,157 

(404) 

566 

(232) 

1,625 

434 

183 

2,426 

926 

(71) 

(4,236 

2,353 

(8 18) 2,584 

1,145 

87 

34 

(4,138) 726 

(13,462) 1,621 

96 

1,752 

1,445 

375 

2,402 

328 

2,070 

4,836 

754 

(2%] 

88 

&I 

(160) 

(20) 

(411) 

1,150 

[%{ 

(10) 

$0 

44,430 

3,145 

(833) 

1,315 

1,742 

(8,246) 

(347) 

(2,775) 

(132) 

(2,451) 

1,750 

2,507 

(370) 

554 

(500) 

1,565 

347 

162 

2,642 

1,863 

(103) 

(1,052) 

(4,700) 

1,889 

(780) 

2,683 

1,182 

13 1 

62 [%I 

(5,023) 953 

(13,360) 

2,098 

139 

1,635 

1,548 

283 (lg3 

2,365 

320 

2,3 19 

7,178 

901 [;%I (530 

1,150 

Note: The national-average level of own-revenue-raising effort is that required to raise just enou h revenue to finance the actual level of direct eneral 

expenditures b state and local governments net of the portion assumed to be financed %y federal grants actually received, that is, sh8.612 

million ($653,l08 million- $114,996 million). The estimates of total revenue-raising ability in columns 2-5 are the sum of each state’sown-reve- nue-raising ability by the four measures plus actual federal grants received, from column 1. 

Sources: 1-U.S. Department of Commerce, Bureau of the Census, Gowmment Finances in 1986-87 (Washington, DC, 1988), %able 29. 

Z-Thble B-3. 

3-6-Bble B-5. 

7-10-Column 2 less columns 3-6, respectively. 

Advlsory Commission on Intergovernmental Relatlons 33 
34 Advisory Commission on Intergovernmental Relations 
Chaoter 5 

This section includes abar chart for each state and the 

District of Columbia illustrating the results of the 

ana&s& For each of the lUfunctiona1 mlegories of d?ect 

general expenditures, the first bar shows the state’s 

representative level of outlays, the second its actual 

expenditures, and the third the national average level of 

spending. 

The exact dollar amount of the per capita expendiG rap h i c Present atio-n 

of the Results by State 

tures plotted in the graphs in this section can be calculated 

by dividing the total expenditures (actual and representative)h Dbks B -1 and B-3 by the resjdentpopulatjon of a 

state, which appears in nble B-7. 

The estimates of representative expenditures displayed in the graphs are the estimates discussed in 

Chapter 4, that is, they are adjusted for differences among 

the states in unit input costs. 

Advisory Commission on Intergovernmental Relations 35 
Alabama 

2800 

2400 

Direct 

General 2000 

Expenditures 

Capita 

Per 1600 

1200 

800 

400 

0 

State and Local Expenditures by Function, 1986-87 

Representatlve 

H Actual 

U.S. Average 

Total Elemen- Higher Publlc Health Highways Police Environ- interest Govern- All 

taryand Educa- Welfare and and ment on mental Other 

Secondary tlon Hospi- Correo and General Admln- ExpenEducatlon tab tions Housing Debt istration dltures 

Alaska -1s- State and Local Expenditures by Function, 1986-87 

2800 

2400 

Direct 

General 2000 

Expend- itures 

Per 1600 Capita 

1200 

800 

400 

0 

Representatlve 

Actual 

U.S. Average 

Total Elemen- Higher Public Health Highways Police Environ- Interest Govern- All taryand Educa- Welfare and and ment on mental Other 

Secondary tion HospE Correc- and General Admin- ExpenEducation talS tions Housing Debt lstratlon ditures 

36 Advisory Cornhission on Intergovernmental Relations 
Arizona 

Direct 

General 

Expenditures 

Per 

capita 

$3200 

2800 

2400 

2000 

1600 

1200 

800 

400 

0 

State and Local Expenditures by Function, 1986-87 

Representative 

Actual 

U.S. Average 

Total Elemen- Higher Public Health Highways Police Environ- Interest Govern- All 

taryand Educa- Welfare and and ment on mental Other 

Secondary tion H08pl- Correc- and General Admin- ExpenEducatlon talr Hons Housing Debt istratlon diturer 

Arkansas 

$ 3200 

2800 

2400 

Direct 

General 2@)0 

Expenditures 

Per 

Capita '600 

1200 

800 

400 

0 

State and Local Expenditures by Function, 1986-87 

Kl Representative 

U.S. Average 

Total Elemen- Higher Publk Health Highways Police Envlron- Interest Govern- All 

taryand Educa- Welfare and and ment on mental Other 

Secondary tion Hospi- Correo- and General Admin- ExpenEducatlon talr tionr Housing Debt lotration dituros 

Advisory Commission on Intergovernmental Relations 37 
California 

State and Local Expenditures by Function, 1986-87 

$3200 1 

Direct 

General 

Expenditures 

Per 

Capita 

Total Elemen- Hlgher Public Health Highways 

taryand Educa- Welfare and 

Secondary tion HOSPC 

Education tals 

Representative 

Actual 

U.S. Average 

Police Environ- Interest Governand ment on mental 

Correc- and General Admlntions Housing Debt istration 

All 

Other 

Expen- ditures 

Colorado 

State and Local Expenditures by Function, 1986-87 

$ 3200 

2800 

2400 

Direct 

General 2000 

Expenditures 

Per 

Capita '600 

1200 

800 

400 

0 

Representative 

Actual 

US. Average 

Total Elemen- Higher Public Health Highways Police Environ- Interest Govern- All 

taryand Educa- Welfare and and ment on mental Other 

Secondary tion Hospi- Correc- and General Admin- ExpenEducation tais tions Housing Debt istration ditures 

38 Advisory Commission on Intergovernmental Relations 
Connecticut 

State and Local Expenditures by Function, 1986-87 

Direct 

General 

Expenditures 

Per 

Capita 

$ 3200 

2800 

2400 

2ooo 

1600 

1 200 

800 

400 

0 

I 

Representative 

Actual 

U.S. Average 

Total Elernsn- Higher Public Health Highways Pollce Envlron- Interest Govern- All 

taryand Educa- Welfare and and ment on mental Other 

Secondary tion Hospi- Correc- and General Adrnin- ExpenEducation talS Uonr Houslng Debt istration diturer 

Delaware 

$ 3200 

2800 

2400 

Direct 

General 

Expenditures 

Per 

Capita 1600 

1200 

800 

400 

0 

State and Local Expenditures by Function, 1986-87 

Representative 

Actual 

U.S. Average 

Total Elemen- Higher Public Health Highways Police Environ- Interest Govern- All 

taryand Educa- Welfare and and ment on mental Other 

Secondary tion Hospl- Correc- and General Admln- ExpenEducation tdr tionr Housing Debt lstration dltures 

Advisory Commission on Intergovernmental Reletions 39 
District of Columbia 

State and Local Expenditures by Function, 1986-87 

Direct 

General 

Expend- Rurer 

Per 

Caplta 

2800 

2400 

2Ooo 

1600 

1200 

800 

400 

0 

Floric 

$3200 

2800 

2400 

Direct 

General 

Expendlturer 

1 200 

800 

Representative 

Actual 

U.S. Average 

Total Elemen- Higher Publlc Health Hlghwayr Police Envlron- Interest Govern- All 

taryand Educa- Welfare and and ment on mental Other 

Secondary tlon Hospl- Correc- and General Admln- Expen- Educatlon talr tlonr Houslng Debt istratlon diturei 

a 

State and Local Expenditures by Function, 1986-87 

Representative 

Actual 

US. Average 

0 

Total Elemen- Higher Publlc Health Hlghwayr Police Envlron- Interest Govern- Ail 

taryand Educa- Welfare and and ment on mental Other 

Secondary tlon Horpl- Correc- and General Admln- Expen- Educatlon talr tlonr Housing Debt lstration diturer 

40 Advisory Cornhission on intergovernmental Relations 
Georgia 

$ 3200 

2800 

2400 

Direct 

General 2000 

Expenditufer 

Per 1600 Capita 

1200 

800 

400 

0 

State and Local Expenditures by Function, 1986-87 

Representative 

Actual 

U.S. Average 

Total Elemen- Higher Publlc Health Highways Pollce Envlron- Interest Govern- All 

taryand Educa- Welfare and and ment on mental Other 

Secondary tion HOSPI- Correc- and General Admln- Expen- Educatlon talr tlonr Houslng Debt istration diturer 

Hawaii 

$ 

2800 

2400 

Dlrect 

General 

Expenditures 

Per 

capita 1600 

1200 

400 

0 

State and Local Expenditures by Function, 1986-87 

Representative 

U.S. Average 

Total Elemen- Hlgher Publlc Health Hlghwayr Police Envlron- Interest Govern- All 

taryand Educa- Welfare and and ment on mental Other 

Secondary tlon Ho~pl- Correo- and General Admln- ExpenEducatlon talr tionr Hourlng Debt lrtratlon diturea 

Advisory Commission on Intergovernmental Relations 41 
Idaho 

State and Local Expenditures by Function, 1986-87 

Dlrect 

General 

Expendltures 

Per 

Capita 

2800 

2400 

2000 

1600 

1 200 

800 

400 

0 

Representatlve \ 

Total Elemen- Hlgher Publlc Health Highways Police Environ- Interest Govern- All 

taryand Educa- Welfare and and ment on mental Other 

Secondary tion HOSPI- Corrac- and General Admin- Expen- Education tats tlons Housing Debt istratlon ditures 

Illinois 

$ 3200 

2800 

2400 

Direct 

General 2000 

Expend- itures 

Per 

Capita 1600 

1 200 

800 

400 

0 

State and Local Expenditures by Function, 1986-87 

Representative 

Actual 

U.S. Average 

Total Elemen- Higher Publk Health Highways Police Envlron- Interest Govern- All 

taryand Educa- Welfare and and ment on mental Other 

Secondary tlon Hospl- Correc- and General Admin- Expen- Education tats tions Housing Debt istration dlturer 

42 Advisory Commission on Intergovernmental Relations 
Indiana 

Dlrect 

General 

Expenditures 

Per 

Capita 

$ 3200 

2800 

2400 

2000 

1600 

1200 

800 

400 

0 

State and Local Expenditures by Function, 1986-87 

Representative 

rn Actual 

US. Average 

Total Elemen- Hlgher Publlc Health Hlghwayr Pollce Envlron- Interest Govern- All 

taryand Educa- Welfare and and ment on mental Other 

Secondary Uon Haspi- Correc- and General Admln- ExpenEducatlon talS Won8 Housing Debt lstration diturer 

Iowa 

Dlrect 

General 

Expenditures 

Per 

Capita 

$ 3200 

2800 

2400 

2Ooo 

1600 

1200 

800 

400 

0 

State and Local Expenditures by Function, 1986-87 

rn 

Representative 

Actual 

U.S. Average 

Total Elemen- Higher Publlc Health Highways Pollce Envlron- Interest Govern- All 

taryand Educa- Welfare and and ment on mental Other 

Secondary tion HO8pl- Correc- and General Admin- ExpenEducation talr Uonr Hourlng Debt lstratlon diturer 

Advisory Commission on Intergovernmental Relaths 43 
Kansas 

$3200 

2800 

2400 

Direct 

General 2oOO 

Expend- itures 

Capita Per 1600 

1200 

800 

400 

0 

State and Local Expenditures by Function, 1986-87 

Representative 

Actual 

U.S. Average 

Total Eiemen- Higher Public Health Highways Police Envlron- interest Govern- All 

taryand Educa- Welfare and and ment on mental Other 

Secondary tion Hospi- Correc- and General Admin- ExpenEducation tats tions Houslng Debt Istratlon ditures 

Kentucky 

State and Local Expenditures by Function, 1986-87 

$32001 

Direct 

General 

Expenditures 

Per 

capita 

44 Advisory Cornhission on Intergovernmental Relations 
r 

Louisiana 

State and Local Expenditures by Function, 1986-87 

$ 3200 

Dire& 

General 

Expend- itures 

Per 

Capita 

Total Elemen- Hlgher 

tary and EducaSecondary tion 

Educatlon 

Public 

Welfare 

Health Hlghways 

and 

Hospltals 

Representative 

w Actual 

U.S. Average 

Police Envlron- Interest Govern- All 

and ment on mental Other 

Correc- and General Admin- Expen- tlons Housing Debt lstratlon ditures 

Maine 

State and Local Expenditures by Function, 1986-87 

2800 

2400 

Direct 

General 

Expenditures 

Per 

Capita l600 

1200 

800 

400 

0 

Representative 

1 Actual 

U.S. Average 

Total Elemen- Hlghw PuMk Health Highways Pollce Envlron- Interest Govern- All 

taryand Educe Weifare and and ment on mental 0th~ 

Secondary tion Hotpi- Corrsc- and General Admln- ExEducation tals tions Housing Debt lstratlon dituret 

Advisory Commission on lntergovemmental Relations 45 
Mary 

Direct 

General 

Expend- lturer 

Per 

capita 

and 

2800 

2400 

2000 

1600 

1200 

800 

400 

0 

State and Local Expenditures by Function, 1986-87 

Representatlve 

Actual 

U.S. Average 

Total Elemen- Higher Publk Health Highways Polfce Envlron- Intenst Govern- All 

taryand Educa- Welfare and and ment on mental Other 

Secondary tion Ho~pl- Correc- and General Admin- ExpenEducation tal. tionr Housing Debt lrtration dlturer 

Massachusetts 

2800 

2400 

Direct 

General 

Expend- itures 

Per 

Capita l6O0 

1200 

400 

0 

State and Local Expenditures by Function, 1986-87 

Representatlve 

Total Elemen- Higher Public Health Highways Pollco Envlron- Interest Govern- All 

taryand Educa- Welfare and and ment on mental Other 

Secondary tion Hospl- Correc- and General Admln- ExpenEducation tal. tionr Housing Debt lttration ditunr 

46 Advisory Commission on Intergovernmental Relations 
Michigan 

Direct 

General 

Expenditures 

Per 

Capita 

$3200 

2800 

2400 

2OOo 

1600 

1200 

800 

400 

0 

State and Local Expenditures by Function, 1986-87 

Representatlve 

Actual 

Total Elemen- Higher Publk Health Hlghwayr Police Environ- Interest Govern- All 

taryand Educa- Welfare and and ment on mental Other 

Secondary tlon Hospl- Correc- and General Admln- ExpenEducatlon tal. tlons Hourlng Debt lstratlon ditures 

Minnesota 

$ 3200 

2800 

2400 

Direct 

General 2000 

Expenditures 

1200 

800 

400 

0 

State and Local Expenditures by Function, 1986-87 

Representative 

Actual 

U.S. Average 

Total Elemen- Higher Publk Health Highways Pollce Environ- Interest Govern- All 

taryand Educa- Welfare and and ment on mental Other 

Secondary tion Hospl- Correc- and General Admln- ExpenEducation talr tlons Hourlng Debt Istratlon dltures 

Advisory Commission on lntergovmmental Relations 47 
Mississippi 

State and Local Expenditures by Function, 1986-87 

$ 3200 

2800 

2400 

Direct 

General 2000 

Expenditures 

Per 1600 capita 

1200 

800 

0 

m 

Representatlve 

Actual 

U.S. Average 

Total Elemen- Hlgher Publlc Health Highways Pollce Envlron- lnterert Govern- All 

taryand Educa- Welfare and and ment on mental Other 

Secondary tion HOSpl- Correc- and General Admln- ExpenEducaUon talr tions Housing Debt lstratlon dltures 

I Missouri 

2800 

2400 

Direct 

General 2000 

Expenditures 

Per 

Caplta 1600 

1200 

400 

0 

State and Local Expenditures by Function, 1986-87 

Representatlve 

Total 

Actual 

U.S. Average 

Elemen- Higher Publlc Health Highways Pollce Envlron- Interest Govern- taryand Educa- Welfare and and ment on mental 

Secondary Uon Hospl- Correc- and General Admln- Education tals tlons Housing Debt lstratlon 

All 

Other 

Expen- diturer 

48 Advisory Commission on intergovernmental Relations 
Montana 

Direct 

General 

Expend- itures 

Per 

Capita 

$3200 

2800 

2400 

2000 

1600 

1200 

800 

400 

0 

State and Local Expenditures by Function, 1986-87 

Representatlve 

w Actual 

US. Average 

Total Elemen- Higher Publlc Health Hlghwayr Pollce Envlron- Interest Govern- All 

taryand Educa- Welfare and and ment on mental Other 

Secondary tion HOSPI- Correc- and General Admln- ExpenEducation talr Uonr Housing Debt irtratlon diturer 

Nebraska 

$ 3200 

2800 

2400 

Dlrect 

General 2000 

Expenditures 

Per 

Capita l6O0 

1200 

0 

State and Local Expenditures by Function, 1986-87 

Representatlve 

Actual 

U.S. Average 

Total Elemen- Hlgher Publlc Health Hlghwayr Pollce Envlron- interest Govern- All 

taryand Educa- Weliarr and and ment on mental Other 

Secondary Uon Ho~pl- Correc- and General Admin- ExponEducation tala Uonr Houoing Debt istratlon dlturer 

Advisory Commission on Intergovernmental Relations 49 
Nevada 

State and Local Expenditures by Function, 1986-87 

Direct 

Genera I 

Expenditures 

Per 

Capita 

2800 

2400 

2000 

1 600 

1200 

800 

400 

0 

Representative 

I 

Actual 

Total Elemen- Higher Public Health Highways Police Environ- Interest Govern- All 

taryand Educa- Welfare and and ment on mental Other 

Secondary tion HOSPI- Correo and General Admin- ExpenEducation tais tions Housing Debt istration ditures 

New Hampshire 

$3200 

2800 

2400 

Direct 

General 2000 

Expenditures 

Per 

Capita 1600 

1200 

800 

400 

0 

State and Local Expenditures by Function, 1986-87 

Representative 

Actual 

U.S. Average 

Total Elemen- Higher Public Health Highways Police Environ- Interest Govern- All 

taryand Educa- Welfare and and ment on mental Other 

Secondary tion Hospl- Correc- and General Admin- ExpenEducation talS tions Housing Debt lstration ditures 

50 Advisory Commission on Intergovernmental Relations 
New Jersey 

Direct 

General 

Expenditures 

Per 

Capita 

$ 3200 

2800 

2400 

2000 

1600 

1200 

800 

400 

0 

State and Local Expenditures by Function, 1986-87 

Representative 

Actual 

Total Elemen- Higher Public Health Highways Pollce Envlron- Interest Govern- All 

taryand Educa- Welfare and and ment on mental Other 

Secondary tion Hospl- Correc- and General Admin- ExpenEducation tais tions Housing Debt istration ditures 

New Mexico 

Direct 

General 

Expenditures 

Per 

Capita 

$ 3200 

2800 

2400 

2Ooo 

1600 

1200 

800 

400 

0 

State and Local Expenditures by Function, 1986-87 

[3 Representative 

Actual 

U.S. Average 

Total Elemen- Higher Public Health Highways Police Envlron- Interest Govern- All 

taryand Educa- Welfare and and ment on mental Other 

Secondary tion Hospl- Correc- and General Admin- ExpenEducation talr tions Housing Debt lotration diturer 

Advisory Commission on intergovernmental Relations 51 
New York 

State and Local Expenditures by Function, 1986-87 

$ 3200 

2800 

2400 

Direct 

General 2000 

Expenditures 

Per 1600 Capita 

1200 

800 

400 

0 

Representative 

Total Elemen- Higher Public Health Highways Police Environ- Interest Govern- All 

taryand Educa- Welfare and and ment on mental Other 

Secondary tion Hospi- Correc- and General Admin- ExpenEducation tais tions Housing Debt lstration ditures 

North Carolina 

State and Local Expenditures by Function, 1986-87 

$ 3200 

2800 

2400 

Direct 

General 2000 

Expenditures 

Per 

Capita '600 

1200 

800 

400 

0 

Representative 

Actual 

U.S. Average 

Total Elemen- Higher Public Health Highways Pollce Environ- Interest Govern- All 

taryand Educa- Welfare and and ment on mental Other 

Secondary tion Hospi- Correc- and General Admin- ExpenEducation talS tlona Housing Debt lstration diturer 

52 Advisory Cornhission on intergovernmental Relations 
North Dakota 

State and Local Expenditures by Function, 1986-87 

2800 

2400 

Direct 

General 2OOO 

Expenditures 

Per 1600 Capita 

1200 

800 

400 

0 

Representative 

Actual 

U.S. Average 

Total Elemen- Higher Public Health Highways Police Envlron- Interest Govern- Ail 

taryand Educa- Welfare and and ment on mental Other 

Secondary tion Hospl- Correo and General Adrnin- ExpenEducatlon tais tlons Housing Debt lstration ditures 

Ohio 

$ 3200 

2800 

2400 

Direct 

General 

Expenditures 

1200 

400 

0 

State and Local Expenditures by Function, 1986-87 

Representative 

Actual 

U.S. Average 

Total Elemen- Higher Public Health Highways Pollce Envlron- Interest Govern- All 

taryand Educa- Welfare and and ment on mental Other 

Secondary lion Hospl- Correc- and General Admin- ExpenEducation tals tions Housing Debt istration ditures 

Advisory Commlsslon on Intergovernmental Relations 53 
Oklahoma 

Direct 

General 

Expenditures 

Per 

Capita 

$ 3200 

2800 

2400 

2000 

1 600 

1200 

800 

400 

0 

State and Local Expenditures by Function, 1986-87 

Representative 

Actual 

U.S. Average 

Total Elemen- Higher Publlc Health Highways Pollce Environ- Interest Govern- All 

taryand Educa- Welfare and and ment on mental Other 

Secondary tlon Hospl- Correc- and General Admin- ExpenEducation tals tions Housing Debt istratlon diturer 

Oregon 

State and Local Expenditures by Function, 1986-87 

$ 3200 

Direct 

General 

Expenditures 

Per 

Capita 

Total Elemen- Higher 

tary and EducaSecondary tion 

Education 

Public 

Welfare 

Health 

and 

HospC 

tals 

Representative 

Actual 

U.S. Average 

Govern- All 

mental Other 

Adrnin- Expenlrtratlon diturer 

Highway6 Police 

and 

Correctlonr 

Environ- Interest 

ment on 

and General 

Houslng Debt 

54 Advisory Commission on Intergovernmental Relations 
Pen nsy Ivan i a 

Direct 

General 

Expenditures 

Per 

Capita 

$ 3200 

2800 

2400 

2Ooo 

1600 

1 200 

800 

400 

0 

State and Local Expenditures by Function, 1986-87 

Representatlve 

Actual 

U.S. Average 

Total Elemen- Hlgher Public Health Hlghways Pallce Envlron- Interest Govern- All 

taryand Educa- Welfare and and ment on mental Other 

Secondary tlon Ho~pl- Correc- and General Admln- ExpenEducation tals Uons Housing Debt lstration ditures 

Rhode Island 

2800 

2400 

Direct 

General 

Expenditures 

1200 

400 

0 

State and Local Expenditures by Function, 1986-87 

Representative 

Actual 

U.S. Average 

Total Elemen- Higher Public Health Highways Police Envlron- Interest Govern- All 

taryand Educa- Welfare and and ment on mental Other 

Secondary tion HospC Correc- and General Admin- ExpenEducation tala Uon8 Houslng Debt lstration ditures 

Advisgr Commission on Intergovernmental Reletions 55 
South Carolina 

$3m 

2800 

2400 

Direct 

General 2oOo 

Expend- lturer 

Per 1600 capita 

1200 

800 

400 

0 

State and Local Expenditures by Function, 1986-87 ~~ 

a Representative 

Actual 

U.S. Average 

Total Elemen- Hlgher Public Health Highway8 Pollce Envlron- Interest Govern- All 

taryand Educa- Welfare and and ment on mental Other 

Secondary tlon HOSPI- Correc- and General Admln- ExpenEducatlon tala Uonr Houslng Debt lstratlon dlturer 

South Dakota 

$- 

2800 

2400 

Direct 

General 2000 

Expend- Iturea 

1 200 

800 

400 

0 

State and Local Expenditures by Function, 1986-87 

m Representative 

Actual 

U.S. Average 

Total Elemen- Higher Public Health Hlghwayr Pollce Envlron- Interest Govern- All 

taryand Educa- Welfare and and ment on mental Other 

Secondary tlon Hospi- Correc- and General Admin- ExpenEducatlon tat8 tlona Housing Debt lstratlon diturer 

56 Advisory Commission on Intergovernmental Relations 
Tennessee 

$ 3200 

2800 

2400 

Direct 

General 2000 

Expenditurer 

Per 1600 Caplta 

1200 

800 

400 

0 

State and Local Expenditures by Function, 1986-87 

Representative 

Actual 

Total Elemen- Hlgher Public Health Highways Police Environ- Interest Govern- Ail 

tary and Educa- Welfare and and ment on mental Other 

Secondary tlon HOSPI- Correc- and General Admin- ExpenEducation talr tlonr Houslng Debt istration diturer 

Texas 

$- 

2800 

2400 

Direct 

General 2000 

ExpenditUf08 

Per 

Capita 1600 

1200 

800 

400 

0 

State and Local Expenditures by Function, 1986-87 

Representative 

Actual 

Total Elemen- Higher Public Health Highways Police Envlron- lnterert Govern- All 

taryand Educa- Welfare and and ment on mental Other 

.Secondary tlon HO8pi- Correc- and General Admln- ExpenEducatlon tal. tlonr Hourlng Debt lrtratlon dlturor 

Advlsary Commission on Intergovernmental Relations 57 
Utah 

Direct 

General 

Expenditures 

Per 

Capita 

$ 3200 

2800 

2400 

2000 

1 600 

1200 

800 

400 

0 

State and Local Expenditures by Function, 1986-87 

Representative 

Actual 

U.S. Average 

Total Eiemen- Higher Public Health Highways Police Envlron- Interest Govern- All 

taryand Educa- Welfare and and ment on mental Other 

Secondary tion Ho~pi- Correc- and General Admln- EyenEducation tdS tionr Housing Debt lstration ditures 

Vermont 

2800 

2400 

Dlrect 

General 2000 

Expenditures 

Per 

Capita '600 

1200 

400 

State and Local Expenditures by Function, 1986-87 

Q Representatlve 

Actual 

U.S. Average 

0 

Total Elemen- Higher Public Health Highways Police Envlron- Interest Govern- All 

taryand Educa- Welfare and and ment on mental Other 

Secondary Uon HospE Correc- and General Admin- ExpenEducation talr Uons Housing Debt lstration diturer 

58 Advisory Commission on Intergovernmental Relations 
Vi r g i n i a 

State and Local Expenditures by Function, 1986-87 

$ 3200 

2800 

2400 

Direct 

General 2OOO 

Expenditures 

Capita Per 1600 

1200 

800 

400 

0 

Representative 

Actual 

U.S. Average 

Total Elemen- Higher Public Health Highways Police Envlron- Interest Govern- All 

taryand Educa- Welfare and and ment on mental Other 

Secondary tlon HOSpi- Correc- and General Admin- ExpenEducation tals tions Housing Debt lstratlon ditures 

Washington 

2800 

2400 

Direct 

General 2000 

Expenditures 

Per 

Capita 1600 

1200 

400 

0 

State and Local Expenditures by Function, 1986-87 

Representative 

Actual 

U.S. Average 

Total Elemen- Higher Public Health Highways Police Envlron- interest Govern- All 

taryand Educa- Welfare and and ment on mental Other 

Secondary tion HospC Correc- and General Admln- ExpenEducation tab dons Housing Debt lstration diture6 

Advisory Commission on Intergovernmental ReWow 59 
West Virginia 

2800 

2400 

Dlrect 

General 2000 

Expendltures 

Capita Per 1600 

1200 

800 

400 

0 

State and Local Expenditures by Function, 1986-87 

Representative 

Actual 

U.S. Average 

Total Elemen- Higher Public Health Highways Police Envlron- Interest Govern- All 

taryand Educa- Welfare and and ment on mental Other 

Secondary tion Ho~pi- Correc- and General Admln- ExpenEducation tals dons Houslng Debt lstration ditures 

Wisconsin 

State and Local Expenditures by Function, 1986-87 

$ 3200 

2800 

2400 

Direct 

General 2000 

Expenditures 

Per 

Capita 1600 

1 200 

800 

400 

0 

Representative 

Actual 

U.S. Average 

Total Elemen- Hlgher Public Health Hlghways Police Envlron- Interest Govern- Ail 

laryand Educa- Welfare and and ment on mental Other 

Secondary tion Hos~C Correc- and General Admin- Expen- Education lalS tions Houslng Debt istratlon ditures 

60 Advisory Commission on Intergovernmental Relations 
Wyoming 

$ 3200 

2800 

2400 

Direct 

Genera 20()0 

Expend- itures 

1600 Per 

Capita 

1200 

800 

State and Local Expenditures by Function, 1986-87 

Representative 

Actual 

U.S. Average 

0 

Total Elemen- Hlgher Publlc Health Hlghways Police Envlron- Interest Govern- All 

tary and Educa- Welfare and and ment on mental Other 

Secondary tion HOSPI- Correc- and General Admin- ExpenEducation talr tlons Housing Debt lstration ditures 

Advisory Commission on Intergovernmental Relations 61 
62 Advisory Commission on Intergovernmental Relations 
1. Population is an inferior measure of the relative 

cost to a state of providing a standard level of public ser- vices. Its use in a measure of fiscal capacity systematically 

overstates the capacities of states below the national average and understates the capacities of states above the na- tional average. Fiscal disparities among the states are significantly larger than most measures available until now 

have suggested. 

2. The differences among the states in the cost of pro- viding a common level of public services are substantial, 

but they are smaller than the differences in own-revenueraising ability, by all the measures currently available. 

3. High public service costs tend to be associated with 

low revenue-raising ability. 

4. The actual spending of three out of four states with 

Concluding Observations 

fiscal capacities below the national average is less than 

their representative expenditures. 

5. The existing federal grant system, taken as a 

whole, tends to worsen fiscal disparities among the 

states. Therefore, the failure to allow for federal grants 

in a measure of fiscal capacity results in systematic un- derstatement of the magnitudes of fiscal disparities 

among the states. 

6. Aperfectly targeted federal grant program could 

guarantee every state a fiscal capacity at the national av- erage at a cost equivalent to less than half that of the 

current system. The payment to a state under such a 

program would be just sufficient-when combined with 

the revenues its governments could raise if they, collec- tively, were to exert national-average fiscal effort -to 

finance its representative level of expenditures. 

Advisory Commission on Intergovernmental Relations 63 
64 Advisory Commission on Intergovernmental Relations 
Appendix A 

Data Used for Estimation 

Expenditure Category, Data Element, and Source 

of Representative Ex pen d it u res 

Dates for Estimates 

PreDared in 

1986 1989 

1. Elementary and Secondary Education 

Population aged 5-13, by state 

Population aged 14-17, by state 

U.S. Department of Commerce, Bureau of the Census, Statistical Abstmct 

of the United States, 1986 (Washington, DC, 1985), Table 29. 

Population aged 5-13, by state 

Population aged 14-17, by state 

Special tabulations prepared by the U.S. Bureau of the Census, Population Division, 

Population Estimates Branch (November 1988). 

Enrollment in private elementary schools, by state 

Enrollment in private secondary schools, by state 

Statistical Abstmct of the United States, 1986, Table 212. 

Statistical Abstmct of the United States, 1982-83 (1982), Table 220. 

Enrollment in private elementary schools, by state 

Enrollment in private secondary schools, by state 

Statkticd Abstmct of the United States, 1982-83, Table 220. 

U.S. Department of Education, National Center for Education Statistics, 

U.S. Department of Education, National Center for Education Statistics, 

Population under 18 living in households with incomes below the poverty line, by state. 

Digest of Education Statistics, 1988 (Washington, DC, 1988), Tables 32,44, and 49. 

Pmjectionr of Education Statistics to 1997-98 (Washington, DC, 1988), Table 1. 

Statistical Abstmct of the United States, 1986, Tables 29,765, and 767. 

Population under 18 living in households with incomes below the poverty line, by state. 

U.S. Department of Commerce, Bureau of the Census, 1980 Cem of Population, Volume 1, 

U.S. Department of Commerce, wlreau of the Census, State Population and Household 

Characteristics of the Population, Chapter C, Geneml Social and Economic Characteristics, 

Part 1, United States Summary (Washington, DC, 19831 Table 245. 

Estimates, with Age, Sex, and Components of Change: 1981-87 (Washington, DC, 19SS), 

Tables 5 and 6. 

(Wshington, DC, 1988), Table 5. Regional totals: all related persons under age 18 living 

in households below the poverty level in 1986. 

U.S. Department of Commerce, mau of the Census, Money Income and Poverty Status in the 

United States: 1987 (Advance Data from the March 1988 Cumnt Population Survey) 

(Mshington, DC, 1988), Table 18. U.S. total: all related persons under age 18 living 

in households below the poverty level in 1987. 

U.S. Department of Commerce, Bureau of the Census, Poverty in the United States: 1986 

7/V84 

7/1/84 

“Fall 83” 

“Fall 83” 

“Fall 87” 

“Fall 87” 

“1984” 

‘( 1987 

Advisory Commission on intergovernmental Relations 65 
Expenditure Category, Data Element, and Source 

Dates for Estimates 

PreDared in 

1986 1989 

2. Higher Education 

Population aged 14-17, by state 

Population aged 18-24, by state 

Population aged 25-34, by state 

Population aged 35 and older, by state 

Population aged 14-17, by state 

Statistical Abstract of the United States, 1986, Table 29. 

Special tabulations prepared by the US. Bureau of the Census, Population Division, 

Population Estimates Branch (November 1988). 

Population aged 18-24, by state 

Population aged 25-34, by state 

Population aged 35 and older, by state 

State Population and Household Estimates, with Age, Sex,and Components of Change: 1981-87, 

FTE students enrolled in institutions of higher education as percentage of U.S. total population aged: 

Tables 5 and 6. 

14-17 

18-24 

25-34 

35 and older 

Unpublished estimates of total enrollment in 1984 by the National Center for Education Statistics. 

Statistical Abstract of the United States, 1986, Tables 29 and 255. 

FTE students enrolled in institutions of higher education as percentage of US. total population aged: 

14-17 

18-24 

25-34 

35 and older 

Pmjections of Education Statistics to 1997-98, Table 8. 

Digest of Education Stafistics, 1988, Table 119. Historical data for 1970-85. 

3. Public Welfare 

Total population living in households with incomes below the poverty line, by state 

Total population living in households with incomes below the poverty line, by state 

Statistical Abstract of the United States, 1986, Tables 765 and 767. 

1980 Census of Population, Volume 1, Chapter C, Part 1, Table 245. 

State Population and Household Estimates, with Age, S-and Components of Change: 1981-87, 

Poverty in the United States: 1986, Table 5. 

Money Income and Poverty Status in the United States: 1987, Table 18. Only regional totals 

Tables 5 and 6. 

are available for 1987. 

4. Health and Hospitals 

Number of persons aged 16-64 with work disabilities, by state 

Unpublished tabulation by the USBureau of the Census from the 1980 Census 

of the proportion of the noninstitutional population aged 16-64 with a work disability. 

Number of persons aged 16-64 with work disabilities, by state 

1980 Census of Population, Volume 1, Chapter C, Part 1, Table 245. 

State Population and Household Estimates, with Age, Sq and Components of Change: 1981-87, 

Tables 5 and 6. 

Population aged 16-64, by state 

Population aged 16-64, by state 

Statistical Abstract of the United States, 1986, Table 29. 

State Population and Household Estimates, with Age, Ser, wid Components of Change: 1981-87, 

Tables 5 and 6. 

Total population living in households with incomes below 150 percent of the poverty line, by state 

Unpublished tabulation by the U.S.Bureau of the Census from the 1980 Census of the 

number of persons in households with incomes below 150 percent of the poverty line. 

7/V84 

71 lf84 

7/1/84 

7/V84 

7/U87 

7/1/87 

7/1/87 

71 1/87 

“Fall 84” 

“Fall 84” 

“Fall 84” 

“Fall 84” 

Fall 87 

Fall 87 

Fall 87 

Fall 87 

“ 1984” 

“1987” 

“1984” 

“1987” 

7/1/84 

71 V87 

“1984” 

66 Advisory Commission on Intergovernmental Relations 
Expenditure Category, Data Element, and Source 

a 

Dates for Estimates 

1986 1989 

4. Health and Hospitals (cont.) 

US. Department of Commerce, Bureau of the Census, Chamcteristics of the Population below 

the Poverty Level: 1983, Current Population Reports, Series Pa, No. 147 (February 198% 

Table 7. US. total: All persons below 150 percent of the poverty level in 1983. 

Total population living in households with incomes below 150 percent of the poverty line, by state 

1980 Census of Population, Volume 1, Chapter C, Part 1, Table 245. 

State Population and Household Estimates, with Age, Sar, and Components of Chmge: 1981-87, 

Poverty in the United States: 1986, Table 4. U.S. totals: all persons below 125 percent and 150 

Money Income and Poverty Status in the United States: 1987, Table 17. US. totals: all persons 

Tables 5 and 6. 

percent of the poverty level in 1986. 

below 125 percent of the poverty level in 1986 and 1987. 

Total population, by state 

Total population, by state 

Statistical Abstract of the United States, 1986, Table 29. 

State Population and Household Estimates, with Age, Sex, and Components of Change: 1981-87, 

Tables 5 and 6. 

5. Highways 

Vehicle-miles traveled, by state 

US. Department of Transportation, Federal Highway Administration, Highway Statistics, 1984 

(Washington, DC, 1985), Table VM-2. 

Vehicle-miles traveled, by state 

Lane-miles of streets and roads net of lane-mileage on federally controlled land, by state 

Lane-miles of streets and roads net of lane-mileage on federally controlled land, by state 

Highway Statistics, 1987 (1988), Table VM-2. 

Highway Statistics, 1984, Tables HM-20 and HM-60. 

Highway Statistics, 1987, Tables HM-20 and HM-60. 

6. Police and Corrections 

Population aged 18-24, by state 

Population aged 18-24, by state 

Statistical Abstmct of the United States, 1986, Table 29. 

State Population and Household Estimates, with Age, Sex, and Components of Chmge: 1981-87, 

Tables 5 and 6. 

Number of murders committed, by state 

Number of murders committed, by state 

Statistical Abstmct of the United States, 1986, Table 281. 

US. Department of Justice, Federal Bureau of Investigation, Crime in the United States-1987 

(Washington, DC, 1988), Table 4. 

Total population, by state 

Total population, by state 

Statistical Abstmct of the United States, 1986, Table 29. 

State Population and Household Estimates, with Age, Sex, and Components of Change: 1981-87, 

Tables 5 and 6. 

7. All Other Direct General Expenditures 

Total population, by state 

Total population, by state 

Staristical Abstmct of the United States, 1986, Table 29. 

State Population and Household Estimates, with Age, Sq and Components of Change: 1981-87, 

Tables 5 and 6. 

“1987” 

7/1/84 

71 1/87 

1984 

1984 

1987 

1987 

1984 

1987 

7/VM 

7/ V87 

7/1/84 

7/1/87 

Advisory Commission on Intergovernmental Relations 67 
68 Advisory Commission on Intergovernmental Relations 
Appendix B 

Background Data and Detail 

This appendix consists of a set of 18 tables providing 

details on the estimates of representative expenditures and 

the data used to calculate the workbad measure for each 

function. Where data have been extrapolated or otherwise 

adjusted from original sources, the calculations involved are 

displayed and, if necessary, explained in footnotes. 

Advisory Commission on Intergovernmental Relations 69 
Table B-1 

Direct General Expenditures of State and Local Governments, by Function, 1986.87 

(millions) 

Health Police Environ- Interest Govern- Education and and ment on mental 

Primary and Public Hospi- Corn- and General Adminis- All 

State Total Secondary Higher Welfare tals HighwaF tions Housing Debt trntion Other 

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) 

United States $653,608.3 

Alabama 8,472.8 

Alaska 5,226.7 

Arizona 9,490.4 

Arkansas 4,553.0 

California 84,581.5 

Colorado 9,345.3 

Connecticut 9,393.6 

Delaware 1,925.3 

District of Columbia 3,211.3 

Florida 

Georgia 

Hawaii 

Idaho 

Illinois 

Indiana 

Iowa 

Kansas 

Kentucky 

Louisiana 

Maine 

Maryland 

Massachusetts 

Michigan 

Minnesota 

Mississippi 

Missouri 

Montana 

Nebraska 

Nevada 

New Hampshire 

New Jersey 

New Mexico 

New York 

North Carolina 

North Dakota 

Ohio 

Oklahoma 

Oregon 

Pennsylvania 

Rhode Island 

South Carolina 

South Dakota 

Tennessee 

Texas 

Utah 

Vermont 

Virginia 

Washington 

West Virginia 

Wisconsin 

Wyoming 

28,270.5 

14,912.2 

3,066.3 

2,078.0 

29,169.9 

11,956.5 

7,126.2 

6,169.5 

7,775.6 

11,013.4 

2,937.6 

12,527.4 

17,525.5 

26,662.1 

13,930.2 

5,319.2 

10,552.8 

2,330.9 

3,949.9 

2,829.4 

2,365.1 

23,280.6 

4,041.1 

69,520.5 

13,324.9 

1,946.3 

26,255.4 

7,249.1 

7,653.4 

28,049.8 

2,749.3 

7,263.6 

1,803.5 

10,086.8 

39,016.7 

4,276.2 

1,506.6 

14,166.9 

12,602.1 

4,313.3 

13,666.5 

2,167.6 

$156,781.7 $60,240.3 

1,718.6 1,056.1 

959.8 226.2 

2,363.0 1,154.6 

1,275.2 479.5 

17,778.0 8,354.1 

2,395.9 957.1 

2,186.6 507.8 

425.7 256.8 

481.2 85.8 

6,892.5 1,622.4 

3,874.2 1,181.3 

514.5 291.9 

500.1 282.0 

6,778.7 2,638.4 

3,178.2 1,582.3 

1,658.8 1,051.8 

1,577.1 751.2 

1,650.3 829.3 

2,299.1 928.9 

737.8 242.4 

2,858.9 1,199.5 

3,718.1 1,031.7 

6,749.9 2,965.9 

3,187.4 1,424.2 

1,245.0 592.4 

2,?79.2 1,136.8 

636.9 184.5 

1,027.9 495.9 

582.4 198.8 

638.0 188.9 

5,799.6 1,589.6 

1,016.3 445.8 

15,343.4 3,844.1 

3,669.0 1,892.1 

439.1 262.6 

6,785.7 2,627.6 

1,907.6 766.2 

1,992.9 828.4 

7,560.3 1,556.4 

587.4 201.7 

1,944.4 915.6 

401.3 166.7 

2,098.3 1,013.9 

11,176.1 4,316.9 

1,083.1 636.4 

389.2 178.4 

3,740.7 1,602.2 

3,088.3 1,348.6 

1,173.3 357.0 

3,337.6 1,594.9 

579.1 196.5 

$80,089.7 $56,971.4 $52,199.3 $41,321.8 $53,805.2 $41,816.2 $34,895.4 $75,487.2 

641.8 

291.2 

726.1 

543.2 

11,292.3 

923.2 

1,186.6 

139.1 

558.1 

2,058.7 

1,302.9 

308.8 

169.9 

3,904.5 

1,410.4 

857.0 

529.5 

1,006.2 

1,053.4 

507.2 

1,405.3 

2,986.9 

4,247.0 

2,035.7 

556.3 

1,108.2 

247.3 

414.9 

163.4 

270.5 

2,688.6 

329.0 

11,422.5 

1,263.2 

236.2 

4,219.6 

847.2 

579.3 

4,424.7 

491.9 

620.8 

154.6 

1,215.6 

2,664.8 

392.6 

189.8 

1,110.9 

1,426.6 

5 11.2 

2,341.5 

113.7 

1,326.4 

128.4 

426.7 

413.6 

7,441.2 

681.3 

663.1 

94.9 

301.9 

2,911.3 

2,688.9 

200.6 

194.6 

1,823.6 

1,175.8 

709.4 

493.5 

484.3 

1,307.0 

138.6 

5l3.7 

1,628.6 

2,641.4 

1,097.7 

850.2 

1,119.0 

119.7 

422.2 

193.8 

129.6 

1,339.4 

303.9 

7,038.1 

1,301.7 

111.3 

2,215.3 

682.4 

479.7 

1,544.7 

194.0 

1,008.8 

86.0 

1,289.1 

3,158.1 

292.9 

53.8 

1,303.2 

889.2 

274.2 

826.2 

258.6 

711.1 

583.6 

1,230.8 

510.6 

3,904.5 

819.8 

814.5 

175.6 

116.4 

2,103.8 

1,235.5 

147.9 

250.7 

2,548.7 

975.0 

891.6 

776.1 

926.5 

1,015.9 

286.2 

428.6 

202.1 

770.8 

192.2 

7,014.7 

581.2 

500.4 

113.1 

470.0 

2,380.6 

868.4 

195.1 

103.8 

1,839.5 

535.8 

300.5 

282.7 

369.8 

645.3 

122.4 

1,169.6 959.4 

973.1 968.4 

1,628.2 1,689.0 

1,337.9 554.8 

552.0 219.1 

964.7 652.0 

307.0 86.4 

452.8 165.8 

280.7 256.4 

276.0 120.2 

1,826.0 

477.5 

3,811.6 

1,035.6 

226.0 

1,900.2 

659.7 

625.5 

2,580.7 

163.5 

457.9 

246.1 

930.4 

4,039.5 

360.5 

185.9 

1,494.4 

1,130.7 

506.8 

1,251.8 

322.2 

1,514.3 

247.3 

4,952.0 

871.4 

51.6 

1,622.1 

360.1 

406.5 

1,462.7 

138.2 

437.5 

69.3 

558.2 

2,211.3 

239.1 

52.5 

908.2 

710.6 

122.0 

710.1 

87.9 

606.9 

427.3 

763.3 

315.5 

7,733.2 

797.5 

690.3 

160.2 

379.9 

2,949.2 

1,064.4 

368.8 

187.8 

2,576.4 

833.8 

493.8 

3626 

634.9 

984.7 

269.6 

1,308.0 

1,583.6 

1,592.7 

1,166.5 

346.5 

807.8 

209.8 

249.6 

249.6 

167.0 

1,944.5 

295.9 

5,536.2 

848.7 

142.9 

1,980.8 

630.2 

620.0 

1,870.6 

182.8 

504.6 

119.0 

798.5 

3,440.9 

356.0 

95.2 

1,298.8 

1,247.0 

281.2 

1,172.3 

157.9 

557.2 

945.9 

662.7 

257.9 

4,177.1 

689.6 

740.4 

233.6 

195.7 

2,076.6 

430.8 

378.2 

580.0 

205.9 

4,950.5 

653.0 

579.2 

128.3 

226.8 

1,883.9 

606.4 765.3 

262.4 226.3 

78.1 113.5 

1,858.0 1,493.4 

506.3 561.9 

322.5 334.7 

461.9 378.5 

661.2 405.5 

1,117.9 538.6 

185.6 138.9 

887.1 

1,085.6 

1,144.8 

1,103.9 

274.9 

584.6 

172.5 

204.1 

246.7 

209.2 

1,926.8 

334.8 

4,589.9 

493.8 

111.2 

1,322.2 

451.4 

702.8 

2,182 1 

2626 

651.3 

929.3 

1,292.6 

667.7 

245.5 

502 1 

133.1 

173.4 

221.4 

128.2 

1,309.2 

245.8 

3,385.1 

688.5 

83.9 

1,337.9 

364.7 

469.9 

1,404.7 

150.0 

360.0 310.7 

131.3 86.6 

540.0 478.1 

3,087.6 1,838.0 

270.4 262.8 

94.1 87.1 

685.2 867.8 

578.2 663.4 

338.0 2251 

678.8 603.6 

164.2 114.7 

995.3 

1,083.9 

812.4 

359.3 

11,936.0 

846.7 

1,524.7 

198.1 

395.6 

3,391.3 

1,324.8 

550.0 

197.5 

3,708.5 

1,196.9 

506.0 

556.3 

807.4 

1,122.6 

308.8 

1,574.6 

2,620.2 

2,710.5 

1,354.4 

437.4 

898.4 

233.8 

343.5 

436.2 

237.4 

3,342.6 

344.9 

9,597.6 

1,261.0 

281.6 

2,244.0 

579.7 

948.3 

3,463.0 

703.4 

342.6 

1,164.7 

3,083.6 

3824 

180.6 

1,155.3 

1,519.4 

524.4 

1,149.8 

172.8 

377.1 

Sources: U.S. Department of Commerce, Bureau of the Census, Government Finances in 1986-87 (Washington, DC, 1988), Thble 29. 

70 Advisory Commission on Intergovernmental Relations 
Table B-2 

Direct General Expenditures of State and Local Governments, by Function, Per Capita, 1986-87 

(millions) 

State 

Health Police Environ- Interest GovernEducation and and ment on mental 

Primary and Public Hospi- Correc- and General Adminis- All 

Total Secondary Higher Welfare tals Highways tions Housing Debt tration Other 

United States 

Alabama 

Alaska 

Arizona 

Arkansas 

California 

Colorado 

Connecticut 

Delaware 

District of Colun 

Florida 

Georgia 

Hawaii 

Idaho 

Illinois 

Indiana 

Iowa 

Kansas 

Kentucky 

Louisiana 

Maine 

Maryland 

Massachusetts 

Michigan 

Minnesota 

Mississippi 

Missouri 

Montana 

Nebraska 

Nevada 

New Hampshire 

New Jersey 

New Mexico 

New York 

North Carolina 

North Dakota 

Ohio 

Oklahoma 

Oregon 

Pennsylvania 

Rhode Island 

South Carolina 

South Dakota 

Tennessee 

Texas 

Utah 

Vermont 

Virginia 

Washington 

West Virginia 

Wisconsin 

Wyoming 

11 

(1) 

$2,68534 

2,075.14 

9,955.54 

2,802.83 

1,906.62 

3,057.57 

2,835.33 

2,925.44 

2,989.62 

ia 5,162.88 

2,351.37 

2,396.69 

2,831.30 

2,082.20 

2,518.55 

2,161.73 

2,514.54 

2,491.71 

2,086.29 

2,468.83 

2,474.82 

2,762.37 

2,993.25 

2,898.05 

3,280.78 

2,026.37 

2,067.97 

2,881.25 

2.477.98 

2j809.75 

2,237.55 

3,034.49 

2,694.09 

3,900.17 

2,077.80 

2,896.27 

2,434.67 

2,215.49 

2,809.62 

2,350.02 

2,788.35 

2,120.76 

2,543.77 

2,077.62 

2,323.95 

2,545.33 

2,749.23 

2,399.54 

2,777.01 

2,273.75 

2,843.03 

4,423.76 

(2) 

$644.14 

420.92 

1,828.23 

697.88 

534.01 

642.66 

726.92 

680.97 

661.08 

773.57 

573.28 

622.66 

475.10 

501.12 

585.28 

574.62 

585.33 

636.95 

442.79 

515.38 

621.58 

630.41 

635.03 

733.69 

750.67 

474.29 

544.63 

787.25 

644.83 

578.31 

603.58 

755.94 

677.50 

860.78 

572.12 

653.48 

629.24 

583.02 

731.61 

633.41 

595.78 

567.70 

566.02 

432.19 

665.68 

644.70 

710.22 

633.59 

680.54 

618.50 

694.31 

1,181.74 

(3) 

$247.50 

258.67 

430.84 

341.00 

200.8 1 

302.00 

290.39 

158.15 

398.77 

137.88 

134.95 

189.86 

269.49 

282.54 

227.80 

286.08 

37 1.15 

303.40 

222.52 

208.22 

204.24 

264.50 

176.21 

322.38 

335.42 

225.67 

22277 

228.06 

311.08 

197.38 

178.75 

207.20 

297.19 

215.66 

295.04 

390.81 

243.66 

234.17 

304.12 

130.40 

204.59 

267.32 

235.09 

208.85 

257.13 

378.83 

325.62 

271.37 

297.17 

188.20 

331.79 

400.99 

(4) 

$329.05 

157.19 

554.67 

214.45 

227.48 

408.21 

280.09 

369.54 

215.99 

897.3 1 

171.23 

209.41 

285.10 

170.24 

337.12 

255.00 

302.41 

213.87 

269.98 

236.14 

427.26 

309.87 

5 10.15 

461.63 

479.44 

211.92 

217.17 

305.66 

260.26 

162.26 

255.93 

350.44 

219.36 

640.81 

196.98 

35 1.48 

391.28 

258.91 

212.65 

370.70 

498.91 

181.25 

218.00 

250.38 

158.72 

233.67 

346.41 

188.17 

314.37 

269.47 

487.10 

23 1.98 

(5) 

$234.07 

324.85 

244.63 

126.03 

173.19 

268.99 

206.71 

206.51 

147.39 

485.37 

242.15 

432.16 

185.20 

195.03 

157.45 

212.58 

250.34 

199.30 

129.96 

292.98 

116.78 

113.28 

278.15 

287.11 

258.52 

323.88 

219.27 

147.92 

264.88 

192.43 

122.62 

174.58 

202.59 

394.84 

165.57 

205.42 

208.55 

176.09 

129.41 

196.74 

294.55 

121.24 

265.52 

188. il 

174.36 

98.11 

220.73 

195.94 

144.56 

171.87 

527.77 

202.98 

(6) 

$214.46 

174.15 

1,111.54 

363.51 

213.80 

141.15 

248.71 

253.66 

27260 

187.07 

174.98 

198.58 

136.57 

251.24 

220.06 

176.28 

314.59 

313.46 

248.60 

227.73 

241.14 

257.90 

166.19 

176.97 

315.10 

210.28 

189.05 

379.54 

284.06 

278.78 

261.15 

238.01 

318.31 

213.84 

161.48 

336.25 

176.20 

201.63 

229.64 

216.21 

165.84 

133.68 

347.10 

191.63 

240.61 

214.59 

339.16 

253.13 

249.16 

267.14 

260.40 

657.65 

(7) 

$169.77 

104.96 

385.01 

227.63 

80.50 

253.58 

176.33 

155.83 

175.65 

755.67 

198.01 

139.57 

180.17 

104.02 

158.82 

96.88 

106.03 

114.17 

99.22 

144.66 

103.16 

211.55 

165.39 

183.59 

130.68 

83.48 

127.77 

106.78 

104.00 

254.62 

113.69 

197.38 

164.88 

277.81 

135.87 

76.81 

150.42 

110.07 

149.25 

122.54 

140.15 

127.74 

97.81 

114.97 

131.71 

142.33 

95.83 

153.83 

156.60 

64.32 

147.72 

179.42 

(8) 

$221.06 

148.65 

813.92 

225.42 

132.12 

279.55 

241.95 

214.99 

248.72 

610.83 

245.30 

171.07 

340.55 

188.15 

222.45 

150.76 

174.26 

146.46 

170.36 

220.73 

227.14 

288.42 

270.47 

173.12 

274.72 

131.98 

158.3 1 

259.38 

156.59 

247.89 

158.01 

253.46 

197.26 

310.59 

132.34 

212.62 

183.68 

19260 

227.60 

156.72 

185.37 

147.32 

167.90 

164.47 

204.95 

211.89 

173.64 

219.99 

274.80 

148.23 

243.88 

322.27 

(9) 

$171.80 

136.46 

1,801.71 

195.70 

108.01 

151.00 

209.22 

230.57 

362.74 

314.62 

172.72 

97.46 

242.34 

78.27 

160.42 

91.54 

113.80 

186.56 

177.40 

250.60 

156.40 

195.61 

185.42 

124.44 

260.00 

104.71 

114.56 

213.17 

128.05 

245.01 

197.96 

25 1.15 

223.20 

257.50 

165.47 

122.61 

137.95 

258.02 

182.82 

266.36 

105.12 

185.25 

111.23 

183.91 

160.94 

171.72 

116.06 

127.41 

178.19 

141.21 

335. w 

77.00 

(10) 

$143.37 

105.51 

720.38 

171.29 

86.23 

178.96 

198.13 

180.38 

199.15 

364.57 

156.69 

123.00 

m.95 

113.74 

128.95 

101.58 

118.09 

152.87 

108.81 

120.74 

117.00 

143.62 

158.72 

140.50 

157.26 

93.51 

98.39 

164.55 

108.77 

219.91 

121.31 

170.65 

163.89 

189.91 

107.36 

124.79 

124.07 

111.45 

172.52 

117.69 

152.17 

90.70 

122.09 

98.48 

109.48 

156.40 

158.97 

146.99 

146.20 

118.68 

125.57 

234.11 

(11) 

$310.14 

243.77 

2,064.62 

239.93 

150.48 

431.48 

256.89 

474.84 

307.54 

635.99 

282.07 

212.93 

507.83 

197.86 

320.20 

216.40 

178.55 

224.69 

216.64 

251.65 

260.13 

347.22 

447.51 

294.62 

318.97 

166.64 

176.05 

288.95 

215.47 

433.15 

224.55 

435.68 

229.93 

538.43 

196.63 

419.00 

208.09 

348.13 

290.13 

382.43 

205.38 

483.27 

239.90 

183.67 

227.62 

329.56 

195.69 

334.82 

276.46 

239.19 

352.70 

in. 16 

Sources: 'Ihbles B-1 and B-7. 

Advisory Commission on Intergovernmental Relations 71 
Table B-3 

Representative State-Local Expenditures by Function, 1986-87, Adjusted for Input-Cost Differences 

(millions) 

State 

Health Police Environ- Interest hemE-n and and ment on mental 

Primary and Public Hospi- Correc- and General Adminis- All 

Total Secondary Higher Welfare tals Highways tions Housing Debt tration Other 

(1) 

United States $653,608.3 

Alabama 11,926.4 

Alaska 1,709.6 

Arizona 9,324.7 

Arkansas 6,795.8 

California 75,241.7 

Colorado 8,681.7 

Connecticut 7,905.6 

Delaware. 1,662.5 

District of Columbia 1,718.2 

Florida 

Georgia 

Hawaii 

Idaho 

Illinois 

Indiana 

Iowa 

Kansas 

Kentucky 

Louisiana 

Maine 

Maryland 

Massachusetts 

Michigan 

Minnesota 

Mississippi 

Missouri 

Montana 

Nebraska 

Nevada 

New Hampshire 

New Jersey 

New Mexico 

New York 

North Carolina 

North Dakota 

Ohio 

Oklahoma 

Oregon 

Pennsylvania 

Rhode Island 

South Carolina 

South Dakota 

Tennessee 

Texas 

Utah 

Vermont 

‘Virginia 

Washington 

West Virginia 

Wisconsin 

Wyoming 

29i882.8 

18,138.2 

2,606.9 

2,681.8 

3 1,855.6 

14,747.1 

7,294.2 

6,540.5 

10,840.8 

13,223.9 

2,838.3 

11,816.6 

13,725.9 

26,764.5 

11,173.9 

7,987.5 

13,733.3 

2,215.0 

4,118.4 

2,593.5 

2,424.6 

19,172.1 

4,455.3 

45,619.3 

16,976.7 

1,897.6 

28,920.6 

9,122.9 

7,161.3 

28,989.6 

2,270.7 

9,501.7 

1,992.6 

13,495.7 

49,435.9 

4,733.7 

1,311.5 

15,627.5 

12,015.0 

5,234.1 

12,160.1 

1,344.7 

(2) (3) 

$156,781.7 $60,240.3 

2,838.7 959.4 

508.0 169.2 

2,245.8 814.7 

1,618.4 522.2 

18,020.6 7,095.4 

2,146.4 833.9 

1,855.4 835.5 

361.2 167.6 

2927 151.9 

6,123.9 2,573.9 

4,405.9 1,538.8 

596.4 274.0 

726.4 213.3 

7,889.3 3,050.1 

3,798.2 1,391.3 

1,770.5 663.1 

1,535.0 578.7 

2,604.8 931.4 

3,163.3 1,165.6 

638.0 252.0 

2,769.8 1,214.7 

3,070.2 1,472.8 

6,827.4 2,528.0 

2,706.5 1,069.6 

1,909.2 596.6 

3,122.3 1,201.4 

521.2 173.6 

930.1 360.9 

618.0 243.3 

558.7 245.4 

4,561.7 1,976.5 

1,083.3 345.6 

10,284.2 4,419.3 

3,991.9 1,507.0 

418.3 152.3 

7,291.8 2,709.3 

2,239.2 769.1 

1,740.2 633.4 

6,582.0 2,888.1 

494.6 238.3 

2,271.2 822.0 

417.5 146.1 

3,144.4 1,139.6 

13,059.2 4,262.4 

1,522.5 405.1 

291.3 122.8 

3,653.6 1,537.4 

2,970.8 1,132.9 

1,333.5 442.4 

2,899.9 1,189.3 

358.2 113.1 

(4) (5) (6) (7) (8) (9) (10) (11) 

$80,089.7 $56,971.4 $52,199.3 $41,321.8 $53,805.2 $41,816.2 $34,895.4 $75,487.2 

1,954.1 

160.3 

1,231.7 

1,137.9 

8,736.1 

917.7 

626.5 

194.4 

287.9 

4,110.3 

2,618.0 

289.1 

342.4 

3,839.1 

1,581.1 

840.0 

732.4 

1,664.5 

2,13 1.4 

357.1 

1,148.3 

1,335.8 

2,900.1 

1,190.5 

1,569.3 

1,826.9 

268.7 

497.0 

243.5 

210.0 

1,793.9 

722.7 

5,775.0 

2,358.5 

243.9 

3,3226 

1,107.8 

799.3 

3,007.5 

239.6 

1,414.0 

341.4 

2,018.7 

6,3126 

477.6 

152.4 

1,763.5 

1,232.3 

725.4 

1,232.8 

106.3 

1,103.5 

128.6 

831.3 

657.9 

6,656.8 

710.8 

627.9 

143.9 

171.0 

2,794.4 

1,029.0 

128.1 

815.3 

570.7 

5,560.7 

777.9 

668.1 

150.7 

77.9 

2,298.6 

1,637.3 1,589.1 

211.7 170.4 

218.4 255.0 

2,753.2 2,097.4 

1,220.5 1,219.5 

585.2 730.9 

520.9 773.6 

1,050.4 845.3 

1,243.3 837.4 

246.5 276.2 

1,003.1 

1,152.9 

2,361.8 

901.0 

763.0 

1,227.6 

172.6 

322.2 

211.1 

191.1 

1,602.1 

380.9 

4,078.9 

1,509.9 

139.1 

2,569.0 

802.2 

649.1 

2,579.5 

204.0 

839.4 

160.6 

1,253.5 

3,992.9 

342.5 

107.9 

1,332.9 

1,049.8 

508.2 

959.5 

89.6 

906.5 

1,022.5 

2,064.4 

1,119.0 

600.7 

1,252.2 

323.9 

501.9 

263.5 

232.0 

1,401.6 

442.9 

2,488.8 

1,398.2 

322.7 

2,083.6 

968.0 

650.6 

2,052.7 

146.7 

804.7 

293.5 

1,125.5 

4,1629 

361.2 

138.9 

1,387.5 

1,052.5 

384.6 

1,166.2 

207.5 

675.3 

125.6 

542 1 

349.4 

5,341.8 

503.6 

502.7 

98.3 

216.3 

2,068.6 

1,171.6 

157.8 

116.4 

2,128.9 

846.0 

341.6 

336.0 

610.7 

877.4 

128.4 

866.3 

771.7 

2,0121 

566.7 

428.9 

831.8 

98.7 

197.9 

166.4 

128.0 

1,178.9 

251.1 

3,429.5 

986.4 

74.2 

1,699.3 

510.9 

393.4 

129.5 

558.7 

72.6 

799.5 

3,319.0 

2223 

62.0 

981.1 

696.6 

262.4 

656.2 

59.6 

1,771.9 

875.9 

129.6 

741.9 

503.4 

6,240.1 

729.1 

731.3 

1428 

135.7 

2,579.1 

1,348.9 

236.7 

210.2 

2,648.6 

1,225.4 

615.8 

537.8 

817.7 

995.1 

243.1 

1,023.4 

1,277.7 

2,118.8 

946.7 

549.7 

1,113.7 

170.4 

340.1 

221.2 

223.2 

1,745.1 

319.4 

3,957.5 

1,356.9 

142.1 

2,419.2 

710.3 

599.1 

2,640.2 

213.0 

725.1 

145.0 

1,044.9 

3,746.4 

365.5 

1129 

1,297.5 

1,014.9 

410.9 

1,058.9 

107.0 

701.5 

90.2 

58 1.7 

410.3 

4,752.5 

566.3 

551.6 

110.6 

106.9 

2,065.6 

1,068.9 

186.1 

171.5 

1,989.8 

950.2 

486.9 

425.4 

640.3 

766.4 

203.9 

551.9 

92.3 

477.2 

311.7 

4,122.5 

473.2 

487.3 

92.9 

87.0 

1,625.1 

858.8 

15 1.8 

130.0 

1,771.1 

796.4 

392.9 

343.1 

526.5 

650.8 

146.0 

779.1 676.3 

1,005.9 818.6 

1,580.6 1,425.6 

729.5 618.9 

451.0 338.1 

876.7 713.7 

139.0 105.4 

273.8 213.2 

173.0 142.7 

181.6 138.4 

1,237.2 

177.6 

1,043.0 

714.0 

8,715.2 

1,022.8 

1 ,O 19.3 

200.2 

191.0 

3,643.2 

1,900.9 

3329 

298.2 

3,688.1 

1,718.4 

867.3 

757.6 

1,149.1 

1,393.3 

347.1 

1,429.2 

1,797.8 

2,945.8 

1,325.6 

780.9 

1,567.1 

241.7 

481.1 

310.8 

316.4 

1,318.1 

257.7 

3,062.3 

1,101.8 

115.5 

1,8527 

562.1 

468.0 

2,050.6 

169.4 

1,161.5 2,432.8 

199.8 451.9 

843.3 1,922.8 

1,590.3 3,382.9 

4528 1,000.6 

386.7 841.5 

1,713.3 3,703.6 

135.2 300.4 

2,577.0 5,546.9 

88.2 mi.4 

588.4 450.9 

121.8 87.0 

834.1 660.6 

2,884.4 2,450.9 

288.6 233.5 

94.2 68.2 

1,014.3 836.9 

325.9 261.4 

825.8 684.6 

84.2 68.6 

n9.6 665.4 

1,027.4 

207.2 

1,475.0 

5,245.0 

5 14.7 

161.0 

1,822.8 

1,420.2 

579.2 

1,486.8 

150.5 

Sources: See text. 

72 Advisory Commission on Intergovernmental Relations 
Table B4 

Representative State-Local Expenditures by Function, Per Capita, 1986.87, Adjusted for InputXost Differences 

(millions) 

State 

Health Police Environ- Interest GovernEducation and and ment on mental 

Primary and Public Hospi- Correc- and General Adminis- All 

Total Secondary Higher Welfare tals Highways tions Housing Debt tration Other 

United States 

Alabama 

Alaska 

Arizona 

Arkansas 

California 

Colorado 

Connecticut 

Delaware 

District of Columbia 

Florida 

Georgia 

Hawaii 

Idaho 

Illinois 

Indiana 

Iowa 

Kansas 

Kentucky 

Louisiana 

Maine 

Maryland 

Massachusetts 

Michigan 

Minnesota 

Mississippi 

Missouri 

Montana 

Nebraska 

Nevada 

New Hampshire 

New Jersey 

New Mexico 

New York 

North Carolina 

North Dakota 

Ohio 

Oklahoma 

Oregon 

Pennsylvania 

Rhode Island 

South Carolina 

South Dakota 

Tennessee 

TexaS 

Utah 

Vermont 

Virginia 

Washington 

West Virginia 

Wisconsin 

Wyoming 

(1) 

$2,685.34 

2,920.99 

3,256.33 

2,753.91 

2,845.83 

2,719.94 

2,634.02 

2,462.02 

2,581.56 

2,762.44 

2,485.47 

2,915.17 

2,407.11 

2,687.15 

2,750.44 

2,666.27 

2,573.83 

2,641.57 

2,908.71 

2,964.33 

2,391.16 

2,605.64 

2,344.30 

2,909.18 

2,631.64 

3,042.84 

2,691.23 

2,738.01 

2,583.67 

2,575.45 

2,293.89 

2,498.98 

2,970.21 

2,559.29 

2,647.24 

2,823.85 

2,681.8 1 

2,788.17 

2,628.95 

2,428.75 

2,302.94 

2,774.23 

2,8 10.42 

2,779.75 

2,944.54 

2,817.65 

2,393.27 

2,646.93 

2,647.65 

2,759.15 

2,529.67 

2,744.27 

(2) 

$644.14 

695.24 

967.69 

663.25 

651.43 

651.23 

577.82 

560.86 

470S2 

509.35 

708.11 

550.73 

727.88 

681.17 

686.72 

624.75 

619.95 

698.90 

709.09 

537.50 

610.76 

524.37 

742 1 1 

637.43 

727.33 

611.85 

644.21 

583.53 

613.68 

528.57 

594.59 

677.74 

722.21 

576.95 

622.47 

622.52 

676.17 

684.37 

638.83 

551.44 

501.63 

663.12 

588.84 

647.67 

777.85 

906.24 

531.54 

618.83 

654.66 

70297 

603.26 

731.05 

(3) 

$247.50 

234.99 

322.37 

240.60 

218.69 

256.49 

253.01 

260.19 

260.24 

244.25 

214.09 

247.32 

253.01 

213.73 

263.34 

251.54 

233.97 

233.73 

249.91 

261.28 

212.27 

267.85 

251.55 

274.78 

251.91 

227.29 

235.43 

214.54 

226.42 

241.60 

232.18 

257.62 

230.37 

247.93 

235.00 

226.60 

25 1.23 

235.07 

232.52 

241.97 

241.70 

240.00 

206.07 

234.72 

253.88 

241.15 

224.16 

260.40 

249.64 

233.21 

247.40 

230.92 

(4) 

$329.05 

478.60 

305.39 

363.77 

476.50 

315.81 

278.43 

195.10 

301.88 

462.93 

341.87 

420.77 

266.90 

343.07 

331.47 

285.86 

296.39 

295.80 

446.60 

477.79 

300.88 

253.20 

228.14 

315.23 

280.38 

597.84 

358.01 

332 14 

311.82 

241.76 

198.66 

233.83 

48 1.8 1 

323.98 

362.89 

308.11 

338.56 

293.43 

251.97 

242.97 

412.84 

481.46 

415.79 

376.00 

284.31 

278.05 

298.69 

271.55 

382.40 

256.46 

216.90 

367.77 

(5) 

$234.07 

270.26 

244.90 

245.52 

275.52 

240.64 

215.65 

195.54 

223.47 

274.89 

232.42 

263.15 

195.51 

218.84 

237.71 

220.67 

206.51 

210.39 

281.85 

278.70 

207.69 

221.18 

196.91 

256.71 

212.19 

290.67 

240.56 

213.30 

202.11 

209.68 

180.8 1 

208.83 

253.93 

228.83 

235.44 

207.01 

238.22 

245.16 

238.28 

216.11 

206.91 

245.08 

226.56 

258.18 

237.83 

203.86 

196.97 

225.76 

231.34 

267.92 

199.61 

182.91 

(6) 

$214.46 

252.03 

243.97 

240.79 

238.98 

201.02 

236.02 

208.05 

233.95 

125.18 

191.19 

255.40 

157.35 

255.47 

181.09 

220.48 

257.92 

312.45 

226.82 

187.72 

232.68 

199.88 

174.63 

224.39 

263.53 

228.83 

245.39 

400.39 

314.90 

261.65 

219.44 

182.69 

295.27 

139.63 

218.03 

480.27 

193.21 

295.83 

238.86 

171.98 

148.81 

234.95 

413.90 

231.82 

247.96 

215.02 

253.46 

235.02 

23 1.93 

202.75 

242.61 

423.42 

(7) 

$169.77 

165.40 

239.25 

160.09 

146.30 

193.10 

152.80 

156.57 

152.58 

347.73 

172.05 

188.29 

145.69 

116.66 

183.81 

152.96 

120.55 

135.71 

163.85 

196.69 

108.13 

191.02 

131.81 

218.70 

133.47 

163.38 

163.00 

122.00 

124.17 

165.24 

121.06 

153.66 

167.41 

192.40 

153.81 

110.36 

157.58 

156.13 

144.41 

148.45 

131.34 

163.13 

102.36 

164.67 

197.69 

132.3 1 

113.10 

166.18 

153.50 

138.32 

136.5 1 

121.69 

(8) 

$221.06 

214.51 

246.93 

219.11 

210.80 

225.57 

221.22 

227.76 

221.72 

218.24 

214.51 

216.80 

218.53 

210.62 

228.68 

221.56 

217.28 

217.22 

219.39 

223.06 

204.79 

225.66 

218.22 

230.31 

222.96 

209.43 

218.25 

210.60 

213.39 

219.71 

211.12 

227.47 

21293 

222.02 

211.58 

211.43 

224.33 

217.07 

219.94 

221.20 

216.03 

211.70 

204.55 

215.23 

223.15 

217.59 

205.97 

223.65 

216.63 

220.29 

218.38 

2ig.n 

(9) 

$171.80 

171.80 

171.81 

171.80 

171.80 

171.80 

171.80 

171.80 

171.80 

171.80 

171.80 

171.80 

171.80 

171.80 

171.80 

171.80 

171.80 

171.80 

171.80 

171.80 

171.80 

171.80 

171.80 

171.80 

171.80 

171.80 

171.80 

171.81 

171.80 

171.80 

171.80 

171.80 

171.80 

171.80 

171.80 

171.80 

171.80 

171.80 

171.80 

171.80 

171.81 

171.80 

171.81 

171.80 

171.80 

171.80 

171.81 

171.80 

171.80 

171.80 

171.80 

171.80 

(10) 

$143.37 

135.17 

175.77 

140.93 

130.51 

149.03 

143.57 

151.76 

144.20 

139.83 

135.17 

138.03 

140.20 

130.29 

152.92 

143.99 

138.64 

138.56 

141.28 

145.88 

122.98 

149.14 

139.81 

154.95 

145.76 

128.80 

139.85 

130.26 

133.76 

141.67 

130.92 

151.39 

133.18 

144.57 

131.50 

131.31 

147.47 

138.38 

141.96 

143.55 

137.07 

131.65 

122.69 

136.07 

145.98 

139.02 

124.47 

141.75 

146.62 

137.82 

142.41 

140.00 

(1 1) 

$3 10.14 

303.02 

338.25 

308.03 

298.98 

315.05 

310.31 

317.43 

310.86 

307.08 

303.02 

305.51 

307.39 

298.79 

318.43 

310.68 

306.03 

305.96 

308.32 

312.32 

292.44 

315.15 

307.05 

320.20 

312.21 

297.49 

307.09 

298.76 

301.79 

308.67 

299.34 

317.11 

301.30 

311.18 

299.84 

299.67 

313.70 

305.80 

308.92 

310.29 

304.68 

299.97 

292 19 

303.80 

312.41 

306.36 

293.74 

308.73 

3 12.96 

305.32 

309.31 

307.22 

Sources: lsbles B-3 and B-7. 

Advisory Commission on intergovernmental Relations 73 
Table B-5 

Measures of Revenue-Raising Ability, 1986 or 1987 

(dollar amounts in millions) 

State 

- Resident Personal RTS Tax Gross state Total Taxable 

Percentage Percentage 

1987 -- 

Percentage Percentage 

Amount Distribution Amount Distribution Amount Distribution Amount Distribution 

(1) 

United States $3.768.125 

Sum of Detail 

Alabama 

Alaska 

Arizona 

Arkansas 

California 

Colorado 

Connecticut 

Delaware 

District of Columbia 

Florida 

Georgia 

Hawaii 

Idaho 

Illinois 

Indiana 

Iowa 

Kansas 

Kentucky 

Louisiana 

Maine 

Maryland 

Massachusetts 

Michigan 

Minnesota 

Mississippi 

Missouri 

Montana 

Nebraska 

Nevada 

New Hampshire 

New Jersey 

New Mexico 

New York 

North Carolina 

North Dakota 

Ohio 

Oklahoma 

Oregon 

Pennsylvania 

Rhode Island 

South Carolina 

South Dakota 

Tennessee 

Texas 

Utah 

Vermont 

Virginia 

Washington 

West Virginia 

Wisconsin 

Wyoming 

3;768;124 

48,753 

9,576 

48,466 

27,481 

492,989 

51,369 

68,291 

10,751 

12,722 

187,365 

88,977 

16,972 

11,847 

190,430 

76,961 

40,348 

37,450 

44,945 

51,174 

16,558 

82,190 

112,085 

14 1,6 18 

67,624 

27,013 

74,945 

9,992 

22,845 

16,484 

18,529 

156,145 

17,812 

320,930 

85,382 

8,738 

157,580 

41,069 

38,245 

181,565 

15,337 

41,110 

8,900 

62,533 

232,783 

19,095 

7,840 

973 15 

70,795 

20,907 

70,862 

6,231 

(2) 

100.oooO% 

100.oooO 

1.2938 

0.2541 

1.2862 

0.7293 

13.0831 

1.3633 

1.8 123 

0.2853 

0.3376 

4.9724 

2.3613 

0.4504 

0.3144 

5.0537 

2.0424 

1.0708 

0.9939 

1.1928 

1.3581 

0.4394 

2.18 12 

2.9746 

3.7583 

1.7946 

0.7169 

1.9889 

0.2652 

0.6063 

0.4375 

0.4917 

4.1438 

0.4727 

8.5170 

2.2659 

0.2319 

4.1819 

1.0899 

1.0150 

4.8184 

0.4070 

1.0910 

0.2362 

1.6595 

6.1777 

0.5068 

0.2081 

2.5879 

1.8788 

0.5548 

1.8806 

0.1654 

(3) 

$396,673.9 

396,673.0 

5,009.0 

1,441.8 

5,490.9 

2,870.6 

52,779.7 

5,962.9 

7,281.5 

1,295.8 

1,238.1 

20,489.1 

9,547.4 

1,997.5 

1,250.6 

18,368.5 

7,851.1 

3,857.6 

3,767.8 

4,797.0 

6,263.1 

1,874.8 

8,039.9 

12,103.9 

14,284.1 

7,186.9 

2,780.4 

7,570.4 

1,140.9 

2,352.6 

2,307.9 

2,118.0 

15,294.8 

2,116.9 

31,383.6 

9,354.9 

984.1 

15,989.3 

4,968.4 

4,102.6 

17,949.2 

1,539.0 

4,399.3 

904.5 

6,632.4 

27,120.2 

2,162.2 

917.5 

9,887.1 

7,286.5 

2,385.4 

6,885.6 

1,090.8 

(4) 

100.~% 

99.9998 

1.2627 

0.3635 

1.3842 

0.7237 

13.3056 

1.5032 

1.8356 

0.3267 

0.3121 

5.1652 

2.4069 

0.5036 

0.3153 

4.6306 

1.9792 

0.9725 

0.9499 

1.2093 

1.5789 

0.4726 

2.0268 

3.0514 

3.6010 

1.8118 

0.7009 

1.9085 

0.2876 

0.5931 

0.5818 

0.5339 

3.8558 

0.5337 

7.9117 

2.3583 

0.2481 

4.0308 

1.2525 

1.0343 

4.5249 

0.3880 

1.1090 

0.2280 

1.6720 

6.8369 

0.5451 

0.2313 

2.4925 

1.8369 

0.6013 

1.7358 

0.2750 

(5) 

$4,191,705 

4,191,705 

55,007 

19,575 

53,253 

3 1,633 

533,816 

59,177 

70,639 

11,706 

28,791 

177,729 

102,922 

19,320 

13,170 

209,666 

84,922 

43,836 

42,472 

53,m 

74,426 

17,326 

76,504 

115,526 

153,240 

75,626 

31,830 

83,534 

12,163 

26,521 

19,426 

18,s 18 

154,765 

23,603 

362,736 

100,961 

10,733 

176,102 

49,814 

41,278 

183,559 

15,205 

44,727 

9,802 

72,328 

303,s 10 

24,008 

8,636 

104,155 

24,096 

76,922 

11,673 

77,683 

(6) 

100.oooO% 

100.oooO 

1.3123 

0.4670 

1.2704 

0.7547 

12735 1 

1.4118 

1.6852 

0.2793 

0.6869 

4.2400 

2.4554 

0.4609 

0.3142 

5.0019 

2.0260 

1.0458 

1.0132 

1.2676 

1.7756 

0.4133 

1.8251 

2.7561 

3.6558 

1.8042 

0.7594 

1.9928 

0.2902 

0.6327 

0.4634 

0.4418 

3.6922 

0.563 1 

8.6537 

2.4086 

0.2561 

4.2012 

1.1884 

0.9848 

4.3791 

0.3627 

1.0670 

0.2338 

1.7255 

7.2407 

0.5728 

0.2060 

2.4848 

1.8533 

0.5749 

1.8351 

0.2785 

(7) 

$4,191,705 

4,191,705 

54,783 

15,426 

53,181 

31,414 

537,742 

59,143 

72,434 

11,493 

21,605 

190,393 

100,199 

19,05 1 

13,265 

2 11,749 

85,390 

443 14 

42,638 

51,449 

67,130 

17,574 

82,949 

119,135 

156,85 1 

75,332 

3 1,060 

83,248 

11,821 

26,298 

18,543 

18,961 

161,655 

21,833 

361,942 

97,250 

10,396 

177,007 

49,013 

41,989 

192,365 

16,042 

45,O 19 

9,868 

70,394 

285,289 

22,863 

8,605 

105,027 

78,614 

24,096 

77,978 

9,687 

(8) 

1OO.oooO% 

100.oooO 

1.3069 

0.3680 

1.2687 

0.7494 

12.8287 

1.4109 

1.7280 

0.2742 

0.5154 

4.5422 

2.3904 

0.4545 

0.3 165 

5.0516 

2.0371 

1.0620 

1.0172 

1.2274 

1.6015 

0.4193 

1.9789 

2.8422 

3.7419 

1.7972 

0.7410 

1.9860 

0.2820 

0.6274 

0.4424 

0.4524 

3.8565 

0.5209 

8.6347 

2.3201 

0.2480 

4.2228 

1.1693 

1.0017 

4.5892 

0.3827 

1.0740 

0.2354 

1.6794 

6.8060 

0.5455 

0.2053 

2.5056 

1.8755 

0.5749 

1.8603 

0.2311 

Sources: 1 -Survey of Current Business, August 1988, 'Cible 1, p. 30. 

3-Advisory Commission on Intergovernmental Relations, 1986 State fiscal Capacity and EAporf (Washington, DC, 1989), p. 12: ACIR, 1988 

State Fiscal Cmaciw and Effort (1990). 0. 32. The estimates shown in this table are means of the estimates for 1986 and 1988; estimates were not irepared by-AClR for lG87. 

5-Survey of Current Business, May 1988, pp. 38-45. 

7-Unpublished estimates prepared by Michael Springer, U.S. Department of the 'Reasury, Office of Economic Policy. 

74 Advisory Commission on Intergovernmental Relations 
Table B-6 

Derivation of a Workload Measure for Public Welfare, 1987 

(populations in thousands) 

Pers<uls in Pave@ 

1979 Total Under 18 

198'1 Total Under 18 Workload Measure 

State 

United States 

Alabama 

Alaska 

Arizona 

Arkansas 

California 

Colorado 

Connecticut 

Delaware 

District of Columbia 

Florida 

Georgia 

Hawaii 

Idaho 

Illinois 

Indiana 

Iowa 

Kansas 

Kentucky 

Louisiana 

Maine 

Maryland 

Massachusetts 

Michigan , Minnesota 

Mississippi 

Missouri 

Montana 

Nebraska 

Nevada 

New Hampshire 

New Jersey 

New Mexico 

New York 

North Carolina 

North Dakota 

Ohio 

Oklahoma 

Oregon 

Pennsylvania 

Rhode Island 

Sum of Detail 

South Carolina 

South Dakota 

Tennessee 

Texas 

Utah 

Vermont 

Virginia 

Washington 

West Virginia 

Wisconsin 

Wyoming 

(1) 

27,393 

27,393 

720 

42 

35 1 

424 

2,627 

285 

243 

68 

113 

1,287 

884 

92 

117 

l,23 1 

5 16 

286 

232 

626 

765 

14 1 

405 

532 

946 

375 

587 

582 

94 

163 

69 

75 

689 

226 

2,299 

840 

79 

1,089 

394 

274 

1,210 

94 

500 

113 

736 

2,036 

148 

59 

611 

396 

287 

398 

36 

(2) 

10,026 

10,026 

271 

15 

12% 

154 

947 

91 

93 

25 

38 

427 

342 

35 

43 

478 

189 

94 

73 

230 

307 

50 

143 

193 

361 

118 

244 

196 

32 

53 

21 

24 

278 

91 

877 

299 

27 

401 

132 

85 

426 

33 

195 

41 

263 

791 

57 

20 

216 

128 

102 

139 

11 

(3) 

32,546 

32,547 

802 

62 

502 

470 

3,519 

373 

251 

79 

117 

1,688 

1,071 

118 

142 

1,538 

641 

343 

299 

678 

862 

149 

463 

545 

1,159 

482 

650 

745 

111 

205 

99 

87 

720 

298 

2,341 

974 

10 1 

1,341 

453 

325 

1,221 

98 

584 

143 

828 

2,554 

195 

64 

7 18 

498 

297 

501 

43 

(4) 

12,830 

12,834 

3 10 

29 

211 

1,535 

140 

92 

30 

43 

583 

429 

52 

61 

684 

263 

127 

112 

251 

361 

50 

164 

186 

494 

17 1 

282 

288 

43 

77 

35 

27 

275 

138 

878 

349 

41 

563 

164 

114 

418 

33 

232 

59 

302 

1,089 

94 

21 

2.54 

186 

106 

199 

16 

in 

(5) 

100.00% 

100.00 

247 

.19 

1.54 

1.45 

10.81 

1.14 

.24 

.36 

5.19 

3.29 

.36 

.43 

4.73 

1.97 

1.05 

.92 

2.08 

2.65 

.46 

1.42 

1.67 

3.56 

1.48 

2.00 

229 

.34 

.63 

.30 

.27 

2.21 

.91 

7.19 

2.99 

.3 1 

4.12 

1.39 

1.00 

3.75 

.30 

1.79 

.44 

2.54 

7.85 

.60 

.m 

2.20 

1.53 

.91 

1.54 

.13 

.n 

~~ 

- 

Sources: 1 & 2-US. Department of Commerce, Bureau of the Census, 1980 Cews of Population, Volume 1, Characteristics of the Population, Chapter C. General Social and Economic Characteristics, Part 1, United States Summary (Washington, X, 1983), Dble 245. 

3-Table 8-7, column 6. 

4-Bble B-9, column 6. 

5-Percentage distribution of column 3. 

Advisory Commission on Intergovernmental Relations 75 
Table 8-7 

Derivation of Estimates of the Number of Persons in Poverty, 1987 

(populations in thousands) 

Region and State 

1979 1987 

Total Povertv Total Pw in Povertv 

Population Number Percent Population Number Scaled Percent 

United States 

Sum of Detail 

Northeast 

Connecticut 

Maine 

Massachusetts 

New Hampshire 

New Jersey 

New York 

Pennsylvania 

Rhode Island 

Vermont 

Illinois 

Indiana 

Iowa 

Kansas 

Michigan 

Minnesota 

Missouri 

Nebraska 

North Dakota 

Midwest 

Ohio 

South Dakota 

Wixonsin 

South 

Alabama 

Arkansas 

Delaware 

District of Columbia 

Florida 

Georgia 

Kentucky 

Louisiana 

Maryland 

Mississi pi North Zarolina 

Oklahoma 

South Carolina 

Tennessee 

Texas 

Virginia 

West Virginia 

West 

Alaska 

Arizona 

California 

Colorado 

Hawaii 

Idaho 

Montana 

Nevada 

New Mexico 

Oregon 

Utah 

Washington 

Wyoming 

(1) 

226,549 

32,547 

49,136 

3,108 

1,125 

5,737 

921 

7,365 

17,558 

11,864 

947 

511 

58,868 

11,427 

5,490 

2,914 

2,364 

9,262 

4,076 

4,917 

1,570 

653 

10,798 

691 

4,706 

75,372 

3,894 

2,286 

594 

638 

9,746 

5,463 

3,661 

4,206 

4,217 

2,521 

5,882 

3,025 

3,122 

4,591 

14,229 

5,347 

1,950 

43,173 

402 

2,718 

23,668 

2,890 

965 

944 

787 

800 

1,303 

2,633 

1,461 

4,132 

470 

(2) 

27,393 

32,547 

5,343 

243 

141 

532 

75 

689 

2,299 

1,210 

94 

59 

6,010 

1,23 1 

5 16 

286 

232 

946 

375 

582 

163 

79 

1,089 

113 

398 

11,285 

720 

424 

68 

113 

1,287 

884 

626 

765 

405 

587 

840 

394 

500 

736 

2,036 

611 

287 

4,755 

42 

35 1 

2,627 

285 

92 

117 

94 

69 

226 

274 

148 

396 

36 

(3) 

12.1% 

10.9 

7.8 

12.5 

9.3 

8.2 

9.4 

13.1 

10.2 

9.9 

11.6 

10.2 

10.8 

9.4 

9.8 

9.8 

10.2 

9.2 

11.8 

10.4 

12.1 

10.1 

16.3 

8.5 

15.0 

18.5 

18.5 

11.5 

17.8 

13.2 

16.2 

17.1 

18.2 

9.6 

23.3 

14.3 

13.0 

16.0 

16.0 

14.3 

11.4 

14.7 

11.0 

10.4 

12.9 

11.1 

9.9 

9.5 

12.4 

12.0 

8.6 

17.3 

10.4 

10.1 

9.6 

7.7 

(4) 

243,399 

50,277 

3,211 

1,187 

5,855 

1,057 

7,672 

17,825 

11,936 

986 

548 

59,538 

11,582 

5,531 

2,834 

2,476 

9,200 

4,246 

5,103 

1,594 

672 

10,784 

709 

4,807 

83,885 

4,083 

2,388 

644 

622 

12,023 

6,222 

3,727 

4,46 1 

4,535 

2,625 

6,413 

3,272 

3,425 

4,855 

16,789 

5,904 

1,897 

49,699 

525 

3,386 

27,663 

3,296 

1,083 

998 

809 

1,007 

1,500 

2,724 

1,680 

4,538 

490 

(5) 

32,546 

5,476 

251 

149 

544 

87 

719 

2,338 

1,219 

98 

63 

7,499 

1,539 

642 

343 

299 

1,159 

482 

746 

205 

10 1 

1,342 

143 

501 

13,287 

799 

468 

78 

117 

1,680 

1,066 

675 

858 

460 

647 

969 

45 1 

58 1 

824 

2,542 

714 

295 

6,285 

62 

503 

3,525 

373 

118 

142 

111 

99 

298 

326 

195 

499 

43 

(6) 

32,546 

5,476 

251 

149 

545 

87 

720 

2,341 

1,221 

98 

64 

7,499 

1,538 

641 

343 

299 

1,159 

482 

745 

205 

101 

1,341 

143 

50 1 

13,287 

802 

470 

79 

117 

1,688 

1,071 

678 

862 

463 

650 

974 

453 

584 

828 

2,554 

7 18 

297 

6,285 

62 

502 

33 19 

373 

118 

142 

111 

99 

298 

325 

195 

498 

43 

(7) 

13.4% 

10.9 

7.8 

12.6 

9.3 

8.2 

9.4 

13.1 

10.2 

9.9 

11.6 

12.6 

13.3 

11.6 

12.1 

12.1 

126 

11.3 

14.6 

12.8 

15.0 

12.4 

a. 1 

10.4 

15.8 

19.6 

19.6 

12.2 

18.8 

14.0 

17.1 

18.1 

19.2 

10.2 

24.7 

15.1 

13.8 

17.0 

17.0 

15.1 

12.1 

15.6 

12.6 

11.9 

14.8 

12.7 

11.3 

10.9 

14.2 

13.8 

9.9 

19.9 

12.0 

11.6 

11.0 

8.9 ~ ~ ~~ 

‘sources: 1 & 4-US. Department of Commerce, Bureau of the Census, Stare Population and Household Esrimures, with Age, Sex, and Componenrs of 

Change, 1981-87, Current Population Reports (Washington, DC, 1988), ’Eibles 5 and 6. 

2-Bble B-6, column 1. 

5 -Regional totals from U.S. Department of Commerce, Bureau of the Census, Money Income and Poverty Status in The United Stores: 1987 

(Advance Dora from the March 1988 Current Population Survey), Current Population Reports (Washington, DC, 1988), Table 15. For 

each state in a region, the number is the percentage in column 7 applied to column 4. 

6-The direct estimates for the states in a region are scaled to the actual regional total in column 5. 

7-For regional totals: [column 5kolumn 41. For each state in a region, the percentage is that in column 3 (for 1980) multiplied by its region’s 

ratio in 1987 (column 7) divided by its region’s ratio in 1980 (column 3). 

76 Advisory Commission on Intergovernmental Relations 
Table B-8 

Derivation of Estimates of the Number of Persons under 150 Percent of the Poverty Level, 1987 

(populations in thousands) 

1979 1987 

Total r 150% of Poverty Total Pe-er 150% of Povem 

Region and State Population Number Percent Population Number Scaled Percent 

United States 

Sum of Detail 

Northeast 

Connecticut 

Maine 

Massachusetts 

New Hampshire 

New Jersey 

New York 

Pennsylvania 

Rhode Island 

Vermont 

Illinois 

Indiana 

Iowa 

Kansas 

Michigan 

Minnesota 

Missouri 

Nebraska 

North Dakota 

Ohio 

South Dakota 

Wisconsin 

Alabama 

Arkansas 

Delaware 

District of Columbia 

Florida 

Georgia 

Kentucky 

Louisiana 

Malyland 

Mississi pi 

North tarolina 

Oklahoma 

South Carolina 

Rnnessee 

Texas 

Virginia 

West Virginia 

Alaska 

Arizona 

California 

Colorado 

Hawaii 

Idaho 

Montana 

Nevada 

New Mexico 

Ore on 

utat 

Washington 

Wyoming 

Midwest 

South 

West 

(1) 

226,546 

226,549 

49,136 

3,108 

1,125 

5,737 

921 

7,365 

17,558 

11,864 

947 

511 

58,868 

11,427 

5,490 

2,914 

2,364 

9,262 

4,076 

4,917 

1,570 

653 

10,798 

691 

4,706 

75,372 

3,894 

2,286 

594 

638 

9,746 

5,463 

3,661 

4,206 

4,217 

2,521 

5,882 

3,025 

3,122 

4,591 

14,229 

5,347 

1,950 

43,173 

402 

2,718 

23,668 

2,890 

96 5 

944 

787 

800 

1,303 

2,633 

1,461 

4,132 

470 

(2) 

49,135 

49,135 

9,639 

441 

29 1 

1,027 

157 

1,208 

3,968 

2,242 

184 

121 

10,872 

2,045 

983 

5 39 

452 

1,667 

705 

1,082 

316 

153 

1,933 

202 

795 

19,763 

1,215 

752 

120 

176 

2,339 

1,530 

1,069 

1,228 

713 

963 

1,570 

738 

896 

1,285 

3,529 

1,128 

511 

8,861 

73 

631 

4,899 

532 

183 

229 

179 

134 

394 

513 

295 

727 

72 

(3) 

21.7% 

19.6 

14.2 

25.9 

17.9 

17.0 

16.4 

22.6 

18.9 

19.4 

23.7 

18.5 

17.9 

17.9 

18.5 

19.1 

18.0 

17.3 

22.0 

20.1 

23.5 

17.9 

29.3 

16.9 

26.2 

31.2 

32.9 

20.2 

27.6 

24.0 

28.0 

29.2 

29.2 

16.9 

38.2 

26.7 

24.4 

28.7 

28.0 

24.8 

21.1 

26.2 

20.5 

18.2 

23.2 

20.7 

18.4 

19.0 

24.3 

22.7 

16.7 

30.2 

19.5 

20.2 

17.6 

15.3 

(4) 

243,400 

243,399 

50,277 

3,211 

1,187 

5,855 

1,057 

7,672 

17,825 

11,936 

986 

548 

59,538 

11,582 

5,531 

2,834 

2,476 

9,200 

4,246 

5,103 

1,594 

672 

10,784 

709 

4,807 

83,885 

4,083 

2,388 

644 

622 

12,023 

6,222 

3,727 

4,461 

4,535 

2,625 

6,413 

3,272 

3,425 

4,855 

16,789 

5,904 

1,897 

49,699 

525 

3,386 

27,663 

3,296 

1,08 3 

998 

809 

1,007 

1,500 

2,724 

1,680 

4,538 

490 

(5) 

54,573 

58,427 

9,880 

454 

269 

983 

157 

1,300 

4,223 

2,203 

177 

115 

13,566 

2,783 

1,160 

621 

542 

2,097 

872 

1,348 

370 

182 

2,427 

258 

907 

23,270 

1,405 

824 

138 

206 

2,956 

1,875 

1,187 

1,510 

810 

1,139 

1,705 

793 

1,022 

1,450 

4,472 

1,257 

520 

11,711 

116 

935 

6,558 

694 

220 

264 

207 

185 

555 

606 

364 

928 

81 

(6) 

54,573 

54,573 

9,228 

424 

25 1 

918 

146 

1,214 

3,945 

2,057 

165 

107 

12,672 

2,600 

1,084 

5 80 

506 

1,958 

814 

1,259 

346 

170 

2,267 

24 1 

847 

21,735 

1,313 

769 

129 

192 

2,761 

1,752 

1,109 

1,411 

757 

1,064 

1,593 

74 1 

955 

1,354 

4,177 

1,174 

486 

10,939 

108 

873 

6,126 

648 

205 

246 

193 

172 

518 

566 

340 

867 

75 

(7) 

22.4% 

18.4 

13.2 

21.2 

15.7 

13.8 

15.8 

22.1 

17.2 

16.8 

19.5 

21.3 

22.4 

19.6 

20.5 

20.4 

21.3 

19.2 

24.7 

21.7 

25.3 

21.0 

34.0 

17.6 

25.9 

32.2 

32.2 

20.0 

30.9 

23.0 

28.2 

29.7 

31.6 

16.7 

40.5 

24.8 

22.6 

27.9 

27.9 

24.9 

19.9 

25.6 

22.0 

20.7 

25.8 

22.1 

19.7 

18.9 

24.7 

23.9 

17.1 

34.5 

20.8 

20.2 

19.1 

15.4 

Sources: 1 & 4-Table B-7, columns 1 and 4, respectively. 2- Column 3 column I]. 

5 U.S. total is 1986 increased by the rcenta e increase in 1987 in the number of persons in households with incomes below 125 percent of 

the poverty level. The estimates oKhe num%er of rsons below 125 percent in 986 and 1987 are from U.S. Department of Commerce, 

Bureau of the Census, Money IncomeandpqveriY Earns in the United States: 1987 (Advance Lktafrom the March 1988 Current Population 

Survey), Current Population Re rts (Washin ton, DC, 1988), Bble 17. The estimate of persons below 150 percent in 1986 is from 

U.S. Bureau of the Census, Eve@ in the Jnited States: 1986, Current Population Reports yashington, DC, 1988), Bble 4. The 

preliminary estimate for each state is the ratio for its re ion of the number of persons below 1 0 percent to the number of rsons m the estimated number of rsons in poverty in the state in 1987 (Em Bble 

E2, column 6). The regional estimates are the sums orthose for the states in eacEegion. 

6-The regional totals are scaled to the U.S. total; the estimates for the states in a region are scaled to the total for the region. 

7-[Column 6kolumn 41. 

3- Li ble B-16, column 5. 

erty in 1980 (from Bble B-7, column 2) multiplied 

Advisory Commission on Intergovernmental Relations 77 
Table 8-9 

Derivation of Estimates of the Number of Children in Poverty, 1987 

(populations in thousands) 

1980 1987 

Total Under 18 in Pov- Total 

er Scaled Percw 

(5) (6) (7) 

United States 

Sum of Detail 

Northeast 

Connecticut 

Maine 

Massachusetts 

New Hampshire 

New Jersey New York 

Pennsylvania 

Rhode Island 

Vermont 

Illinois 

Indiana 

Iowa 

Kansas 

Michigan 

Minnesota 

Missouri 

Nebraska 

North Dakota 

Ohio 

South Dakota 

Wisconsin 

Alabama 

Arkansas 

Delaware 

District of Columbia 

Florida 

Georgia 

Kentucky 

Louisiana 

Maryland 

Mississi pi North Zarolina 

Oklahoma 

South Carolina 

Tennessee 

TexaS 

Midwest 

South 

Virginia 

West Virginia 

West 

Alaska 

Arizona 

California 

Colorado 

Hawaii 

Idaho 

Montana 

Nevada 

New Mexico 

Oregon 

Utah 

Washington 

Wyoming 

63,758 

63,758 

13,083 

823 

322 

1,490 

258 

1,991 

4,688 

3,123 

243 

145 

16,921 

3,244 

1,618 

826 

649 

2,752 

1,172 

1,363 

447 

19 1 

3,095 

206 

1,358 

21,638 

1,162 

671 

166 

143 

2,359 

1,646 

1,083 

1,33 1 

1,168 

815 

1,658 

855 

942 

1,298 

4,306 

1,475 

560 

12,116 

13 1 

791 

6,389 

809 

276 

307 

232 

215 

418 

723 

540 

1,139 

146 

10,026 

10,026 

1,992 

93 

50 

193 

24 

278 

877 

426 

33 

20 

2,170 

478 

189 

94 

73 

36 1 

118 

196 

53 

27 

401 

41 

139 

4,180 

271 

154 

25 

38 

427 

342 

230 

307 

143 

244 

299 

132 

195 

263 

791 

216 

102 

1,683 

15 

128 

947 

91 

35 

43 

32 

21 

91 

85 

57 

128 

11 

15.7% 

15.2 

11.3 

15.5 

12.9 

9.3 

14.0 

18.7 

13.6 

13.4 

13.7 

12.8 

14.7 

11.7 

11.4 

11.2 

13.1 

10.1 

14.4 

11.9 

14.2 

13.0 

19.7 

10.3 

19.3 

23.3 

23.0 

15.3 

26.3 

18.1 

20.8 

21.2 

23.1 

12.2 

30.0 

18.0 

15.4 

20.3 

18.4 

14.6 

18.2 

13.9 

11.8 

16.2 

14.8 

11.3 

12.7 

14.0 

13.6 

9.7 

21.7 

11.7 

10.6 

11.2 

7.6 

20.7 

63,543 

12,072 

756 

303 

1,336 

266 

1,831 

4,360 

2,851 

229 

140 

15,677 

3,035 

1,469 

732 

650 

2,459 

1,111 

1,309 

424 

187 

2,837 

195 

1,269 

22,378 

1,116 

648 

162 

136 

2,704 

1,736 

996 

1,316 

1,125 

791 

1,628 

893 

941 

1,251 

4,984 

1,460 

49 1 

13,416 

172 

9 19 

7,302 

874 

286 

306 

225 

253 

447 

686 

629 

1,169 

148 

12,830 

12,834 

1,979 

92 

51 

186 

27 

275 

878 

418 

33 

21 

3,078 

684 

263 

128 

112 

494 

17 1 

288 

77 

41 

563 

59 

199 

5,125 

309 

177 

29 

42 

58 1 

427 

251 

360 

163 

281 

348 

163 

231 

301 

1,086 

2.53 

106 

2,653 

29 

2 12 

1,540 

140 

52 

61 

43 

35 

138 

114 

94 

187 

16 

12,830 

12,834 

1,979 

92 

50 

186 

27 

275 

878 

418 

33 

21 

3,078 

684 

263 

127 

112 

494 

17 1 

288 

77 

41 

563 

59 

199 

5,125 

3 10 

177 

30 

43 

583 

429 

251 

36 1 

164 

282 

349 

164 

232 

302 

1,089 

254 

106 

2,653 

29 

211 

1,535 

140 

52 

61 

43 

35 

138 

114 

94 

186 

16 

20.2% 

16.4 

12 1 

16.7 

13.9 I 

10.0 

15.0 

20.1 

14.7 

14.4 

14.8 

19.6 

22.5 

17.9 

17.4 

17.2 

20.1 

15.4 

22.0 

18.2 

21.7 

19.8 

30.1 

15.7 

22.9 

27.6 

27.3 

18.2 

31.2 

21.5 

24.6 

25.2 

27.4 

14.5 

35.5 

21.4 

18.3 

24.5 

24.0 

21.8 

17.4 

21.6 

19.8 

16.8 

23.0 

21.1 

16.1 

18.1 

20.0 

19.3 

13.7 

30.9 

16.7 

15.0 

16.0 

10.8 

Sources: 1 & 4-US. Department of Commerce, Bureau of the Census, State Population and Household Estimates, with&, Sex, and Componentsof 

Change, 1981-87, Current Population Reports (Washington, DC, 1988), 'hbles 5 and 6. 

2-'hbIe Bd, column 2. 

5-Regional totals are estimates for 1986 [from US. Department of Commerce, Bureau of the Census, Poverty in the United States: 1986, 

Current Population Reports (Washington, DC, 1988), Bble 5, adjusted to 1987 by the change from 1986 in the overall rate for the entire 

country. The U.S. total for 1987 is from Bureau of the Census, Money Income and Poverzy Status in the United States: 1987, Advance Data 

from the March 1988 Current Population Survey (1988), 

'hble 18. For each state in a region, the number is the percentage in column 7 applied to column 4. 

region's ratio in 1987 (column 7) divided by its region's ratio in 1980 (column 3). 

6-The direct estimates for the states in a region are scaled to the actual regional total in column 5. 

?'-For the regional totals: [column 5/column 41. For each state in a region, the percentage is that in column 3 (for 1980) multiplied by its 

78 Advisory Commission on Intergovernmental Relations 
Table B-10 

Derivation of a Workload Measure for Elementary and Secondary Education, 1987 

(populations in thousands) 

State 

~~~~ 

School-Age Children Weighled Net 

School-Age Enrollment Population Under 18 School-Age 

Population in Private Schools Net of Private Living in Pooaon 

Poverty Workload 

5-13 14-17 Elementary Secondary Elementary Secondary 1987 Number Measure 

United States 

Alabama 

Alaska 

Arizona 

Arkansas 

California 

Colorado 

Connecticut 

Delaware 

District of Columbia 

Florida 

Georgia 

Hawaii 

Idaho 

Illinois 

Indiana 

Iowa 

Kansas 

Kentucky 

Louisiana 

Maine 

Maryland 

Massachusetts 

Michigan 

Minnesota 

Mississippi 

Missouri 

Montana 

Nebraska 

Nevada 

New Hampshire 

New Jersey 

New Mexico 

New York 

North Carolina 

North Dakota 

Ohio 

0 klahom a 

Oregon 

Pennsylvania 

Rhode Island 

South Carolina 

South Dakota 

Tennessee 

Texas 

Utah 

Vermont 

Virginia 

Washington 

West Virginia 

Wisconsin 

Wyoming 

Sum of Detail 

(1) 

30,823 

30,824 

553 

80 

437 

323 

3,486 

419 

356 

78 

61 

1,267 

847 

138 

158 

1,484 

729 

371 

321 

500 

650 

147 

527 

621 

1,198 

544 

397 

641 

113 

2 10 

122 

127 

868 

218 

2,088 

788 

94 

1,392 

440 

343 

1,376 

109 

462 

97 

6 18 

2,412 

332 

67 

693 

570 

25 1 

625 

76 

(2) 

14,467 

14,467 

268 

32 

195 

152 

1,514 

187 

186 

37 

29 

625 

412 

59 

64 

690 

350 

165 

137 

238 

281 

73 

265 

326 

596 

244 

183 

299 

48 

92 

54 

63 

450 

95 

1,024 

402 

38 

672 

195 

153 

692 

55 

223 

40 

305 

1,070 

113 

33 

346 

257 

123 

288 

29 

(3) 

3,664 

3,590 

50 

5 

34 

14 

439 

28 

43 

18 

12 

170 

63 

28 

4 

243 

72 

38 

27 

49 

128 

7 

69 

68 

140 

71 

34 

93 

6 

26 

6 

10 

150 

14 

406 

44 

9 

183 

13 

19 

251 

20 

42 

9 

42 

144 

3 

3 

54 

43 

8 

133 

3 

(4) 

1,229 

1,195 

11 

0 

11 

4 

126 

8 

33 

6 

6 

57 

26 

10 

2 

76 

20 

12 

8 

18 

36 

9 

28 

43 

51 

16 

18 

28 

1 

11 

1 

10 

55 

5 

123 

12 

2 

63 

4 

8 

97 

8 

8 

2 

27 

30 

4 

4 

19 

14 

3 

23 

0 

(5) 

27,159 

27,234 

503 

75 

403 

309 

3,047 

391 

3 13 

60 

49 

1,098 

784 

110 

154 

1,241 

657 

333 

294 

45 1 

522 

140 

458 

553 

1,058 

473 

363 

548 

107 

184 

116 

117 

718 

204 

1,682 

744 

85 

1,209 

427 

324 

1,125 89 

420 

88 

576 

238 

329 

64 

639 

527 

243 

492 

73 

(6) 

13,238 

13,272 

257 

32 

184 

148 

1,388 

179 

153 

31 

23 

568 

386 

49 

62 

614 

330 

153 

129 

220 

245 

64 

237 

283 

546 

228 

165 

27 1 

47 

81 

53 

53 

395 

90 

901 

390 

36 

609 

19 1 

145 

595 

47 

215 

38 

278 

1,040 

109 

29 

327 

243 

1% 

265 

29 

(7) 

12,830 

12,834 

3 10 

29 

211 

177 

1,535 

140 

92 

30 

43 

583 

429 

52 

61 

684 

263 

127 

112 

251 

361 

50 

164 

186 

494 

17 1 

282 

288 

43 

77 

35 

27 

275 

138 

878 

349 

41 

563 

164 

114 

4 18 

33 

232 

59 

302 

1,089 

94 

21 

254 

186 

106 

199 

16 

(8) 

32,741 

32,822 

636 

84 

479 

378 

3,601 

448 

363 

75 

63 

1,372 

963 

128 

170 

1,530 

790 

385 

334 

554 

648 

160 

553 

661 

1,304 

555 

453 

672 

122 

211 

13 1 

130 

895 

247 

2,129 

924 

97 

1,475 

488 

368 

1,374 

109 

525 

105 

699 

2,673 

330 

72 

774 

605 

292 

611 

n 

(9) 

99.75% 

100.00 

1.94 

0.26 

1.46 

1.15 

10.97 

1.36 

1.11 

0.23 

0.19 

4.18 

2.93 

0.39 

0.52 

4.66 

2.41 

1.17 

1.02 

1.69 

1.97 

0.49 

1.68 

2.01 

3.97 

1.69 

1.38 

2.05 

0.37 

0.64 

0.40 

0.40 

2.73 

0.75 

6.49 

2.82 

0.30 

4.49 

1.49 

1.12 

4.19 

0.33 

1.60 

0.32 

2.13 

8.14 

1.01 

0.22 

236 

1.84 

0.89 

1.86 

0.23 

Sources: 1 & 2-S cia1 tabulations prepared by the U.S. Bureau of the Census, Population Division, Population Estimates Branch, November 1988. 

3 & 4-Gle B-11, columns 11 and 12. 

5-[Column 1 - column 3). 

6-[Column 2 - column 41. 

7-Bble B-9, column 6. 

8-[0.6 (column 5) + column 6 + 0.25 (column 7)]. 

9-Percentage distribution of column 8. 

Advisory Commission on Intergovernmental Relations 79 
Table B-11 

Enrollment in Elementary and Secondary Schools, Public and Private, 1986 and 1987 

(thousands) 

Percentage of Total 

Enrollment in Public Enrollment in Fall 1986 Public Institutions, 

Institutions in 1980 Public Institutions Public Institutions Scaled Private Institutions 

s Enrollment in Fall 1987 

3 

3 

ti’ g. state Elementary Secondary Total Elementary Secondary Total Elementary. Secondary Elementary Secondary Elementary Secondary 

s 

g United States 

ca Sum of detail 

2 

% Alabama 

- 

3 

Alaska 3 

Arizona 

ansas 

California 4 Colorado 

Connecticut 

Delaware 

District of Columbia 

Florida 

Georgia 

Hawaii 

Idaho 

Illinois 

Indiana 

Iowa 

Kansas 

Kentucky 

Louisiana 

Maine 

Maryland 

Massachusetts 

Michigan 

Minnesota 

Mississippi 

Missouri 

Montana 

Nebraska 

Nevada 

New Hampshire 

New Jersey 

New Mexico 

New York 

North Carolina 

North Dakota 

(1) 

88.42% 

91.32 

94.04 

92 14 

95.64 

87.76 

93.23 

88.11 

78.87 

84.12 

87.38 

9295 

80.74 

97.21 

83.67 

90.13 

89.60 

91.80 

90.14 

82.07 

95.13 

87.03 

89.14 

88.84 

87.32 

91.43 

85.70 

94.42 

87.88 

95.10 

91.56 

83.29 

93.27 

80.93 

94.53 

90.42 

(2) 

90.86% 

94.87 

100.00 

94.12 

96.98 

91.35 

95.50 

81.04 

83.83 

78.80 

89.57 

92.58 

83.46 

97.20 

87.95 

93.86 

92.66 

93.93 

91.56 

85.37 

87.83 

88.66 

86.07 

91.67 

93.47 

88.45 

89.73 

97.28 

87.92 

97.22 

84.10 

86.69 

94.87 

87.56 

%.46 

94.12 

(3) 

39,837.5 

39,837.5 

733.7 

108.0 

534.5 

437.4 

4,378.0 

558.4 

468.8 

94.4 

85.6 

1,607.3 

1,096.4 

164.6 

1,825.2 

966.8 

481.3 

416.1 

642.8 

795.2 

211.8 

675.7 

833.9 

1,681.9 

711.1 

498.6 

800.6 

153.3 

267.1 

161.2 

163.7 

1,107.5 

28 1.9 

2407.7 

1,085.2 

208.4 

118.7 

(4) 

27,403.7 

27,403.7 

519.0 

78.0 

371.4 

306.9 

3,045.7 

386.3 

321.8 

64.8 

62.5 

1,120.9 

778.0 

113.3 

149.6 

1,249.3 

653.6 

323.5 

291.6 

446.9 

580.8 

143.7 

456.0 

559.4 

1,108.8 

479.1 

356.1 

549.3 

107.6 

185.3 

112.2 

109.9 

7423 

191.0 

1,713.5 

748.5 

83.9 

(5) 

12,433.8 

12,433.8 

214.8 

30.0 

163.1 

130.6 

1,3323 

172.1 

147.0 

29.6 

23.2 

486.4 

3 18.4 

51.4 

58.8 

575.8 

313.2 

157.8 

124.5 

195.9 

214.4 

68.1 

219.7 

274.5 

573.1 

2320 

1426 

251.3 

45.8 

81.9 

49.1 

53.8 

365.1 

90.9 

894.3 

336.8 

34.8 

(6) 

40,200.1 

40,200.1 

730.5 

105.5 

567.2 

437.0 

4,469.9 

560.2 

464.0 

95.7 

87.7 

1,663.6 

1,159.5 

165.9 

212.4 

1,798.0 

965.2 

478.9 

421.1 

642.7 

795.3 

210.0 

680.1 

823.6 

1,673.8 

716.3 

505.6 

8021 

153.9 

2.68.1 

165.1 

164.2 

1,105.6 

287.2 

2,593.1 

1,084.8 

118.5 

0 

27,653.2 

27,663.1 

516.7 

76.2 

394.1 

306.6 

3,109.6 

387.6 

318.5 

65.7 

64.0 

1,160.2 

822.7 

114.1 

152.5 

1,230.8 

6526 

321.9 

295.1 

446.8 

580.9 

142.5 

459.0 

552.5 

1,103.5 

482.6 

361.0 

550.4 

108.0 

186.0 

114.8 

110.3 

741.1 

194.6 

748.1 

83.8 

1,703.9 

(8) 

12,546.9 

Q537.0 

213.8 

29.3 

173.1 

130.5 

1,360.3 

172.7 

145.5 

30.0 

23.7 

503.4 

336.7 

5 1.8 

59.9 

567.3 

312.7 

157.0 

126.0 

195.9 

214.5 

67.5 

221.1 

271.1 

570.3 

233.7 

144.6 

251.7 

45.9 

822 

50.2 

53.9 

364.5 

926 

889.2 

336.7 

34.7 

(9) 

27,983.0 

27,983.0 

522.7 

77.1 

398.7 

310.1 

3,145.6 

392.0 

322.2 

66.4 

64.7 

1,173.6 

8322 

115.5 

154.2 

1,245.0 

660.1 

325.6 

298.5 

452.0 

587.6 

144.1 

464.3 

558.9 

1,116.3 

488.2 

365.2 

556.7 

109.2 

188.1 

116.2 

11 1.5 

749.6 

196.9 

1,723.6 

756.8 

84.7 

(10) 

12,217.0 

12,217.0 

208.4 

28.6 

168.7 

127.1 

1,325.6 

168.3 

141.8 

29.2 

23.1 

490.6 

328.2 

50.5 

58.4 

552.8 

304.7 

153.0 

122.8 

190.9 

209.0 

65.8 

215.5 

264.2 

555.8 

227.7 

140.9 

245.3 

44.8 

80.1 

49.0 

525 

355.2 

90.3 

866.5 

328.1 

33.8 

(11) 

3,664.5 

3,589.7 

49.7 

4.9 

34.0 

14.1 

438.7 

28.5 

43.5 

17.8 

12.2 

169.5 

63.1 

27.5 

4.4 

243.0 

72.3 

37.8 

26.7 

49.4 

128.4 

7.4 

69.2 

68.1 

140.2 

70.9 

34.2 

92.9 

6.5 

25.9 

6.0 

10.3 

150.4 

14.2 

406.1 

43.8 

9.0 

(12) 

1,228.8 

1,195.2 

11.3 

0.0 

10.5 

4.0 

125.5 

7.9 

33.2 

5.6 

6.2 

57.1 

26.3 

10.0 

1.7 

75.7 

19.9 

12.1 

7.9 

17.6 

35.8 

9.1 

27.6 

42.8 

50.5 

15.9 

18.4 

28.1 

1.3 

11.0 

1.4 

9.9 

54.5 

4.9 

123.1 

12.0 

2.1 
Table B-11 (cont.) 

Enrollment in Elementary and Secondary Schools, Public and Private, 1986 and 1987 

(thousands) 

Percentage of Total 

Institutions in 1980 Public Institutions Public Institutions 

Enrollment in Fall 1987 

Enrollment in Public Enrollment in Fall 1986 Public Institutions, 

Scaled Private Institutions 

State Elementary Secondary Total Elementary Secondary Total Elementary Secondary Elementary Secondary Elementary Secondary 

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) 

Ohio 86.95 90.03 L793.5 1,208.1 585.4 1,789.5 1,205.4 584.1 1,219.4 569.2 183.0 63.0 

Oklahoma %.93 97.97 593.2 417.3 175.9 598.7 421.2 177.5 426.0 173.0 13.5 3.6 

Oregon 94.34 94.34 449.3 308.5 140.8 455.9 313.1 142.8 316.7 139.2 19.0 8.4 

Pennsylvania 80.94 85.80 1,674.2 1,064.6 609.6 1,656.4 1,053.3 603.1 1,065.4 587.7 250.9 97.3 

Rhode Island 8241 84.66 l34.3 91.4 42.7 134.1 91.4 42.7 92.4 41.6 19.7 7.5 

South Carolina 91.26 95.64 611.6 427.8 183.9 6 14.9 430.1 184.9 435.0 180.2 41.7 8.2 

South Dakota 91.40 93.82 125.5 89.4 36.1 126.5 90.1 36.4 91.1 35.4 8.6 2.3 

TaraS 94.43 %.85 3.209.5 2,317.5 892.1 3,350.7 2,419.4 931.3 2,447.4 907.5 144.4 29.5 

Tennessee 93.36 89.74 8 18.1 577.0 241.0 819.3 577.9 241.4 584.6 235.2 41.6 24.9 

Utah 99.03 %.n 416.0 308.4 107.6 418.7 310.4 108.3 314.0 105.5 3.1 3.5 

Vermont 95.44 86.83 92 1 63.4 28.7 93.5 64.4 29.2 65.1 28.4 3.1 4.3 

West Virginia 96.77 %.91 351.8 243.5 108.3 344.2 238.3 106.0 241.0 103.3 8.1 3.3 

Wisconsin 79.59 91.82 767.8 509.6 258.2 772.0 512.4 259.6 518.3 253.0 1329 22.5 

Wyoming 95.84 100.00 101.0 72.2 28.7 98.5 70.5 28.0 71.3 27.3 3.1 - 

Virginia 92.74 93.88 975.1 673.2 301.9 979.3 676.1 303.2 683.9 295.4 53.5 19.3 

Washington 92.58 94.27 761.4 521.3 240.1 775.8 531.2 244.6 537.3 238.4 43.1 14.5 

~ Sources: 1 --Ible B-12 [column 7/column 61. n 

5 

a 

t7 

3 

s 

5 

8 

2--Ible B-12 [column ll/column lo]. 

3-6-U.S. Department of Education, National Center for Education Statistics, D&stofEducutiOn Stutistics, 1988 (Washington, DC, 1988), able 32. An estimate of total enrollment in Massachu7-[(Column 4/column 3) column 61. 

8 -[Column 6 - column 71. 

9 & 10-columns 7 and 8, respectively, scaled to national totals from U.S. Department of Education, National Center for Education Statistics, hjechns of Educuhn S~atistics to 1997-98 

(Washington, DC, 1988), 'Ifible 1. 

11 -[(Column 9/column 1) - column 91. 

12--((Column lO/column 2) - column lo]. 

setts is not show separately; the amount appearing above is implicit in the published national total. 

3 
Table B-12 

Enrollment in Elementary and Secondary Schools, Public and Private, Fall 1980 R3 

g (thousands) 5 

s 

t? 

jj. state 

s (1) (2) (3) (4) (5) (6) 0 (8) (9) (10) (11) (12) (13) (14) 

s 45,940 40,978 4,962 3,925 1,037 31,288 27,665 2,925 698 14,652 13,313 1,OOO 264 339 

997 255 339 - United States $ Sum of detail 45,944 40,982 4,962 3,923 1,039 31,292 27,666 2,926 700 14,652 13,3 16 

822 759 63 24 39 578 528 20 30 244 231 4 6 9 (a 

90 86 4 2 2 64 60 2 2 26 26 0 0 0 3 Alabama 

554 5 14 40 31 9 387 357 24 6 167 157 7 2 3 3 Alaska 

Arkansas 466 448 18 10 8 3% 3 10 8 6 142 138 2 2 2 Arizona 

ti; California 4,632 4,118 5 14 413 10 1 3,146 2,761 3 16 69 1,486 1,357 97 24 32 

581 546 35 24 11 401 374 19 8 180 172 5 2 3 

532 88 79 9 413 364 45 4 m7 168 34 4 5 B Colorado 

122 99 23 16 7 72 57 11 4 50 42 5 2 3 3 Connecticut 620 

District of Columbia 121 100 21 15 6 84 71 10 3 37 29 5 2 3 

Delaware 

Florida 1,715 1,510 205 116 89 1,192 1,042 89 61 523 468 27 21 28 

202 165 37 23 14 136 110 17 9 66 55 6 4 5 

m 203 6 4 2 148 144 3 1 61 59 1 1 1 

Total Enrollment Elementan Sc hools Secondarv Schools 

3 Private Private Private 

Total Public Total (8) + (12) (3)-(4) Total Public A B Total Public A C D 

co. 

E 

Georgia 1,152 1,069 83 27 56 798 742 20 36 353 327 7 14 19 

Hawaii 

2,333 1,984 349 332 17 1,596 1,335 249 12 738 649 83 4 6 Idaho 

Indiana 1,155 1,055 100 80 20 786 708 63 15 370 347 17 4 6 Illinois 

Iowa 

Kansas 

Kentucky 

Louisiana 

Maine 

589 534 55 51 4 392 35 1 38 3 198 183 13 1 2 

450 416 34 29 5 308 283 22 3 142 133 7 1 2 

670 70 58 12 5 15 464 43 8 225 206 15 3 4 

937 159 120 39 663 544 92 27 274 234 2a 9 12 

241 223 18 12 6 16 1 153 6 2 80 70 6 3 4 

740 778 

857 751 106 83 23 566 493 59 14 291 258 24 7 9 

843 754 89 74 15 552 482 59 11 291 272 15 3 4 

1,160 1,022 l38 123 15 758 676 75 7 402 346 43 6 8 

11 14 

11 14 

Maryland 

Massachusetts 

Michigan 

Minnesota 

2,075 1,863 212 17 1 41 1,379 1,225 127 27 696 638 44 

Mississippi 527 477 50 16 34 36 1 330 11 20 166 147 5 

Missouri 

Montana 

Nebraska 

Nevada 

New Hampshire 

New Jersey 

New Mexico 

New York 

North Carolina 

North Dakota 

970 844 

164 156 

3 19 280 

157 150 

188 167 

1,476 1,244 

289 27 1 

3,451 2,871 

1,187 1,129 

128 117 

126 

8 

39 

7 

21 

230 

18 

580 

58 

11 

115 

6 

35 

5 

17 

207 

13 

490 

17 

9 

11 662 

2 112 

4 215 

2 106 

4 122 

23 984 

5 199 

90 2,27 1 

41 83 1 

2 85 

567 

106 

189 

10 1 

112 

820 

186 

1,838 

786 

77 

87 8 309 277 

5 1 51 50 

24 2 104 91 

4 1 50 49 

9 1 65 55 

150 14 49 1 426 

10 3 90 85 

372 61 1,180 1,033 

14 31 356 343 

7 1 43 40 

28 3 4 

1 0 0 

11 1 2 

1 0 0 

8 2 2 

57 6 8 

3 1 2 

118 2229 

3 7 10 

2 0 1 
Table B-12 (cont.) 

Enrollment in Elementary and Secondary Schools, Public and Private, Fall 1980 

(thousands) 

Total Enrollment Elementaw Sc hools Secondarv Schools 

Private Private Private 

State Total Public Total (8) + (12) (3)-(4) Total Public A B Total Public A C D 

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (W (13) (14) 

Ohio 2,225 1,957 268 244 24 1509 132 18 1 16 716 645 63 6 8 

Oklahoma 594 578 16 10 6 412 399 8 5 183 179 2 1 2 

Oregon 492 464 28 21 7 338 3 19 15 4 154 145 6 2 3 

Pennsylvania 2,311 1,909 402 348 54 1,521 1,231 255 35 790 678 93 14 19 

Rhode Island 178 148 30 26 4 115 95 18 2 63 53 8 1 2 

South Carolina 669 6 19 50 14 36 467 426 12 29 202 193 2 5 7 

South Dakota 140 129 11 8 3 93 85 6 2 47 44 2 1 1 

Tennessee 926 854 72 35 37 645 602 23 20 281 252 12 13 17 

Texas 3,049 2,900 149 115 34 2,170 2,049 95 26. 879 85 1 20 6 8 

Utah 349 343 6 4 2 252 250 2 0 96 93 2 1 1 

Vermont 103 95 8 7 1 69 66 3 0 33 29 4 0 0 

Virginia 1,085 1,010 75 43 32 758 703 33 22 327 307 10 8 10 

Washington 8 13 757 56 38 18 556 5 15 29 12 257 242 9 4 6 

West Virginia 396 383 13 8 5 279 270 6 3 117 113 2 1 2 

Wisconsin 993 83 1 162 153 9 663 528 128 7 330 303 25 2 2 

Wyoming 101 98 3 2 1 73 70 2 1 2a 28 0 0 0 

A: 

B 

8 c: 

2. D: 

g 

Enrollment in private elementary and secondary schools as reported by U.S. Department of Education, National Center for Educational Statistics, that is, excluding enrollment in 

“combined elementary and secondary schools and other schools.” 

Enrollment in private “combined elementary and secondary schools and other schools” apportioned to primary schools as the residual amount remaining of the total after the 

apportionment to secondary schools (column 5 - column 14). 

Enrollment in private “combined elementary and secondary schools and other schools” apportioned to secondary schools by secondary schools’ actual share of total enrollment in 

exclusively elementary or secondary (private) schools in each state [(column l2/column 4) column 51. 

Enrollment reported in column 13 scaled to 339, the enrollment implicit in the estimate reported for Fall 1980 for private secondary schools in Digest ofEducation Statistics, 1988, 

Table 44 [in other words, the total enrollment in private secondary schools reported for Fall 1980 in Table 44 (1,339) less the enrollment other than in “combined” schools shown in 

column 12 (l,OOO)]. 

D 

3 

2 

Sources: 3-U.S. Department of Education, National Center for Education Statistics, Dig& ofEducufion S&fisfics, 1988 (Washington, DC, 1988), ’Jhble 49. 

7,8,11, and 12-U.S. Department of Commerce, Bureau of the Census, StatisticalAbstractof the Unitedstates, 1982-83 (Washington, DC, 1982), ’Ihble 220. The U.S. total for public secondary $l 

3 

schools is the amount reported in Dig& of Education Stntistics, 1988, able 44. 

3 

t 
Table 8-13 

Wend in Population and Higher Education Enrollment, by Age, Fall 1970-87 

(thousands) 

Y 

h 

Enrollment in Institutions of Higher Education 9 Resident PoDulation Aee 14 and Older Total Full-Time Eauivalent 

4/1/70 7/1/75 4/1/80 7/1/85 7/1/87 1970 1975 1980 1985 1987 1970 1975 1980 1985 1987 3 1: Age 

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (W (14) (15) 

s 

s 

2 Total 149,399 165,424 179,038 190,622 194,654 8,580 11,185 12,096 12,250 12,545 6,739 8,289 8,763 8,801 8,995 $ 

14-17 15,851 17,125 16,247 14,865 14,797 259 278 247 235 210 248 254 226 214 195 

18-24 23,714 27,735 30,022 28,500 27,107 5,937 6,783 7,313 6,916 7,036 5,268 5,843 6,314 5,988 6,082 

!i 25-34 24,923 31,314 37,082 42,027 43,315 1,561 2,741 3,114 3,214 3,276 859 1,561 1,621 1,741 1,804 2 3 35 + 84,911 89,250 95,687 105,230 109,435 823 1,383 1,422 1,885 2,023 364 632 603 858 914 

P 

z. s Total Enrollment as Percentage Percentage Distribution of 

- 

z 

of Pooulation. bv Ape Grow Total Enrollment bv Aee v) 

Age 1970 1975 1980 1985 1987 1970 1975 1980 1985 1987 

(16) (17) (18) (19) (20) (21) (22) (23) (24) (25) 

Total 5.74% 6.76% 6.76% 6.43% 6.44% 100.0% 100.0% 100.0% 100.0% 100.0% 

14-17 1.63 1.62 1.52 1.58 1.42 3.0 2.5 20 1.9 1.7 

18-24 25.04 24.46 24.36 24.27 25.96 69.2 60.6 60.5 56.5 56.1 

25-34 6.26 8.75 8.4 7.65 7.56 18.2 24.5 25.7 26.2 26.1 

35 + 0.97 1.55 1.49 1.79 1.85 9.6 12.4 11.8 15.4 16.1 

FTE Enrollment as Percentage 

of PoDulation. bv Age Grow 

Percentage Distribution of 

FTE Enrollment bv Aee 

Age 1970 1975 1980 1985 1987 1970 1975 1980 1985 1987 

(26) (27) (28) (29) (30) (31) (32) (33) (34) (35) 

Total 4.51% 5.01% 4.89% 4.62% 4.62% 100.0% 100.0% 100.0% 100.0% 100.0% 

14-17 1.56 1.48 1.39 1.44 1.32 3.7 3.1 26 24 2.2 

18-24 2222 21.07 21.03 21.01 22.44 78.2 70.5 72.0 68.0 67.6 

25-34 3.45 4.98 4.37 4.14 4.16 127 18.8 18.5 19.8 20.1 

35 + 0.43 0.71 0.63 0.82 0.83 5.4 7.6 6.9 9.8 10.2 

sources: 1 -US. Department of Commerce, Bureau of the Census, Statistical Abstract of the United States, 1988 (Washington, DC, 1987), ’Ifible 20. 

2-StatisticaIAbstrad of he United States, 1986 (1985), Bble 29. 

3-5-U.S. Department of Commerce, Bureau of the Census, State hpk&n andHouschold Estimates, with Age, Sex, and Components ofChnge: 1981-87 (Whshington, DC, 1988), nble 5; and 

unpublished tabulation for the 14-17 age group supplied by the U.S. Department of Commerce, Bureau of the Census, Population Division, Population Estimates Branch, November 1988. 

6-l0-’Ifible B-14, columns 1-5. 

l-lS-’hble B-14, columns 16-20. 
Table B-14 

Wend in Higher Education Enrollment, by Age, Fall 1970-87 

(thousands) 

Total Enrollment Full-Time Enrollment Part-Time Enrollment 

1970 1975 1980 1985 1987 1970 1975 1980 1985 1987 1970 1975 1980 1985 1987 

Total 

14-17 

18-19 

20-21 

2224 

25-29 

w34 

Total 

14-17 

18-24 

25-34 

Sum of Detuil 

35 + 

35 + 

(1) 

8,581 

8,580 

259 

2,600 

1,880 

1,457 

1,074 

487 

823 

8,580 

259 

5,937 

1,561 

823 

(2) 

11,185 

11,185 

278 

2,786 

2,243 

1,754 

1,774 

%7 

1383 

11,185 

278 

6,783 

2,741 

1383 

(3) 

12,097 

12,096 

247 

2,901 

2,423 

1,989 

1,871 

1,243 

1,422 

12,096 

247 

7,313 

3,114 

1,422 

(4) 

12,247 

12,250 

235 

2,600 

2,383 

1,933 

1,953 

1,261 

1,885 

12,250 

235 

6,916 

3,214 

1,885 

(5) 

12,544 

12,545 

210 

2,764 

2,224 

29048 

1,947 

1,329 

2,023 

12,545 

210 

7,036 

3,276 

2,023 

5,815 6,841 7,098 

5,817 6,841 7,097 

242 242 216 

2,406 2510 2580 

1,647 1,854 2,060 

881 1,008 1,174 

407 692 610 

100 279 264 

134 256 193 

5,817 6,841 7,097 

7,075 7,219 

203 188 

2,322 2,450 

1,975 1,847 

1,227 1,308 

695 724 

310 344 

345 359 

7,077 7,220 

7,077 7,220 

242 242 216 203 188 

507 971 874 1,005 1,068 

134 256 193 345 359 

4,934 5,372 5,814 5,524 5,605 

(11) 

2,766 

2,765 

17 

194 

233 

576 

668 

388 

689 

2,765 

17 

1,003 

1,056 

689 

(12) 

4,344 

4,344 

36 

276 

390 

746 

1,082 

687 

1,127 

4,344 

36 

1,412 

1,769 

1,127 

(13) (14) 

4,999 5,172 

4,999 5,172 

31 ' 32 

320 278 

364408 

815 705 

1,261 1,258 

979 951 

1,229 1,540 

4,999 5,172 

31 32 

1,499 1,391 

2,240 2,209 

1,229 1,540 

(15) 

5,325 

5,325 

22 

3 14 

377 

740 

1,223 

985 

1,664 

5525 

22 

1,43 1 

2,208 

1,664 

Total FTE E nrollment Full-Time Enrollment Part-Time FTE Enrollment 

Age 1970 1975 1980 1985 1987 1970 1975 1980 1985 1987 1970 1975 1980 1985 1987 ~ 

(16) (17) (18) (19) (20) (21) (22) (23) (24) (25) (26) (27) (28) (29) (30) 

6,739 8,289 8,763 8,801 8,995 5,817 6,841 7,097 7,077 7,220 922 1,448 1,666 1,724 1,775 

248 254 226 214 195 242 242 216 203 188 6 12 10 11 7 

2,471 2,602 2,687 2,415 2,555 2,406 2510 2,580 2,322 2,450 65 92 107 93 105 

1,725 1,984 2,181 2,111 1,973 1,647 1,854 2,060 1,975 1,847 78 130 121 136 126 

1,073 1,257 1,446 1,462 1,555 881 1,008 1,174 1,227 1,308 192 249 272 235 247 

25-29 630 1,053 1,030 1,114 1,132 407 692 610 695 724 223 361 420 419 408 

30-34 229 508 590 627 672 100 279 264 310 344 129 229 326 317 328 

35 + 364 632 603 858 914 134 256 193 345 359 230 376 410 513 555 

s 

8 Total 

3 

# Total 6,739 8,289 8,763 8,801 8,995 5,817 6,841 7,097 7,077 7,220 922 1,448 1,666 1,724 1,775 

2 18-24 5,268 5,843 6,314 5,988 6,082 4,934 5,372 5,814 5,524 5,605 334 471 500 464 477 

$ 14-17 248 254 226 2 14 195 242 242 216 m3 188 6 12 10 11 7 

P 

2 25-34 859 1,561 1,621 1,741 1,804 507 971 874 1,005 1,068 352 590 747 736 736 

35 + 364 632 603 858 9 14 134 256 193 345 359 230 376 410 5l3 555 

f 

8 

Sour-: 14,6-9, and 11-14-U.S. Department of Education, National Center for Education Statistics, Digest of Educution Statistics, 1988 (Washington, DC, 1988), Pble 119. 

5, 10, and 15-U.S. Department of Education, National Center for Education statistics, Projectionr of Education Statistics to 1997-98 (Washington, DC, 1988), Pble 8. 

26-30-Columns 11-15 divided by 3. 
Table B-15 

Derivation of a Workload Measure for Higher Education, 1987 

(populations in thousands) 

State 

CoW-Aee pw 1. 1987 

14-17 18-24 25-34 35 + 

Sum of PNumber Workload Measure 

United States 

Alabama 

Alaska 

Arizona 

Arkansas 

California 

Colorado 

Connecticut 

Delaware 

District of Columbia 

Florida 

Georgia 

Hawaii 

Idaho 

Illinois 

Indiana 

Iowa 

Kansas 

Kentucky 

Louisiana 

Maine 

Maryland 

Massachusetts 

Michigan 

Minnesota 

Mississippi 

Missouri 

Montana 

Nebraska 

Nevada 

New Hampshire 

New Jersey 

New Mexico 

New York 

North Carolina 

North Dakota 

Ohio 

Oklahoma 

Oregon 

Pennsylvania 

Rhode Island 

South Carolina 

South Dakota 

Tennessee 

Texas 

Utah 

Vermont 

Virginia 

Washington 

West Virginia 

Wisconsin 

Wyoming 

Sum of Detail 

(1) 

14,467 

14,467 

268 

32 

195 

152 

1,514 

187 

186 

37 

29 

625 

4 12 

59 

64 

690 

350 

165 

137 

238 

281 

73 

265 

326 

596 

244 

183 

299 

48 

92 

54 

63 

450 

95 

1,024 

402 

38 

672 

195 

153 

692 

55 

223 

40 

305 

1,070 

113 

33 

346 

257 

123 

288 

29 

(2) 

27,107 

27,107 

466 

63 

373 

264 

3,006 

366 

355 

76 

67 

1,202 

737 

129 

106 

1,278 

628 

307 

267 

433 

526 

135 

532 

684 

1,060 

470 

3 13 

552 

85 

174 

106 

122 

843 

17 1 

1,983 

754 

75 

1,182 

359 

275 

1,291 

113 

416 

78 

543 

1,882 

194 

65 

7 14 

484 

208 

542 

53 

(3) 

43,3 15 

43,318 

701 

103 

602 

374 

5,331 

676 

536 

118 

13 1 

1,891 

1,107 

197 

170 

2,070 

976 

494 

444 

65 1 

817 

201 

8 12 

1,078 

1,642 

780 

430 

876 

143 

281 

206 

195 

1,256 

262 

2,988 

1,145 

125 

1,862 

575 

5 13 

2,oo 1 

175 

619 

121 

848 

3,151 

308 

102 

1,089 

873 

316 

850 

106 

(4) 

109,435 

109,327 

1,800 

188 

1,491 

1,103 

12,024 

1,381 

1,563 

288 

288 

6,227 

2,642 

471 

4 18 

5,199 

2,457 

1,302 

1,115 

1,647 

1,802 

547 

2,067 

2,755 

4,038 

1,884 

1,090 

2,366 

358 

716 

442 

475 

3,741 

621 

8,494 

2,887 

286 

4,904 

1,445 

1,249 

5,792 

469 

1,449 

3 14 

2,214 

6,771 

550 

240 

2,642 

2,012 

882 

2,147 

74 

(5) 

8,984.0 

8,983.2 

152.2 

a.4 

123.7 

86.0 

1,016.1 

124.2 

117.4 

24.8 

23.3 

408.3 

238.8 

41.8 

35.2 

425.2 

206.5 

102.4 

89.4 

141.1 

170.7 

44.2 

173.8 

225.5 

347.6 

156.8 

99.6 

183.9 

28.6 

57.9 

36.7 

40.3 

278.4 

55.7 

653.3 

246.1 

24.9 

392.3 

119.0 

95.4 

430.2 

37.3 

134.1 

25.7 

179.5 

623.7 

62.4 

21.3 

232.0 

165.0 

68.8 

178.6 

17.3 

(6) 

100.01% 

100.00 

1.69 

.23 

1.38 

.% 

11.31 

1.38 

1.31 

.28 

.26 

4.55 

2.66 

.47 

.39 

4.73 

2.30 

1.14 

1.00 

1.57 

1.90 

.49 

1.93 

2.51 

3.87 

1.75 

1.11 

2.05 

.32 

.64 

.41 

-45 

3.10 

.62 

7.27 

2.74 

.28 

4.37 

1.33 

1.06 

4.79 

.41 

1.49 

-29 

2.00 

6.94 

.69 

.24 

2.58 

1.84 

.77 

1.99 

.19 

Sources: 1 -Special tabulations prepared by the U.S. Department of Commerce, Bureau of the Census, Population Estimates Branch, Population 

Division, November 1988. 

2-4-U.S. Department of Commerce, Bureau of the Census, Stare Population and Household Estimates, wirh Age, Sex, and Componenfs of 

Change, 1981-87 (Washington, DC, 1988), Bbles 5 and 6. 

5 -Sum of (1.32 rcent of column l), (22.44 percent of column 2), (4.16,percent of column 3), and (0.83 percent of column 4); each weight is 

theestimategeFTEnumberofpersons in theagegroupenrolledin institutionsof highereducationasapercentageof the total populationon 

July 1,1987, from able B-13, column 30. 

6-Percentage distribution of column 5. 

88 Advisory Commission on Intergovernmental Relations 
Table B-16 

Derivation of a Workload Measure for Health and Hospitals, 1987 

(populations in thousands) 

Florida 

Georgia 

Hawaii 

Idaho 

Illinois 

Indiana 

Iowa 

Kansas 

Kentucky 

Louisiana 

Maine 

Maryland 

Massachusetts 

Michigan 

Minnesota 

Mississippi 

Missouri 

Montana 

Nebraska 

Nevada 

New Hampshire 

New Jersey New Mexico 

New York 

North Carolina 

North Dakota 

Ohio 

Oklahoma 

Oregon 

Pennsylvania 

Rhode Island 

South Carolina 

South Dakota 

Tennessee 

TeXaS 

Utah 

Vermont 

Virginia 

Washington 

West Virginia Wisconsin 

Wyoming 

Poou-er 150% Povertv Total Population 

Rate 

Work

P0Q-d -Disabled Pooulation 16

Percentage Percentage Percentage 

-64. 1987 -a 

Workload State 1980 Number Disabled Distribution 1980 1987 Number Distribution Number Distribution Measure 

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) 

Sum of Detail 157,626 13,441 100.00 54,573 100.0 243,399 100.00 100.00 

Alabama 10.6 2,599 275 2.05 31.2 32.2 1,313 2.41 4,083 1.68 204 

Arizona 9.1 2,139 195 1.45 23.2 25.8 873 1.60 3,386 1.39 1.48 Arkansas 12.7 1,471 187 1.39 32.9 32.2 769 1.41 2,388 .98 1.26 California 8.2 18,212 1,493 11.11 20.7 22.1 6,126 11.22 27,663 11.37 11.23 

Colorado 7.2 2,216 160 1.19 18.4 19.7 648 1.19 3,296 1.35 1.24 

Connecticut 6.5 2,126 138 1.03 14.2 13.2 424 .78 3,211 1.32 1.04 

Delaware 7.9 427 34 .25 20.2 20.0 129 .24 644 .26 .25 

United States 8.5% 157,628 13,398 99.70% 21.7% 22.4% 54,573 100.00% 243,400 100.0% 100.00% 

Alaska 5.4 35 1 19 .14 18.2 20.7 108 .a 525 .22 .19 

District of Columbia 9.9 424 42 .31 27.6 30.9 192 .35 622 .26 .31 

9.9 7,509 743 5.53 24.0 23.0 2,761 5.06 12,023 4.94 5.18 

10.4 

5.9 

8.7 

7.3 

8.0 

7.2 

7.6 

11.4 

9.6 

9.7 

8.0 

7.3 

9.3 

7.0 

11.8 

9.1 

8.1 

7.0 

7.8 

7.5 

6.9 

8.2 

7.7 

9.7 

6.7 

8.8 

10.8 

9.9 

8.5 

8.6 

9.8 

7.6 

10.4 

7.6 

7.5 

8.5 

8.4 

8.8 

123 

6.8 

6.1 

4,075 

719 

611 

7,504 

3,574 

1,769 

1,562 

2,398 

2,809 

763 

3,066 

3,895 

5,997 

2,732 

1,609 

3,249 

509 

999 

676 

704 

5,089 

953 

11,706 

4,242 

415 

6,954 

2,063 

1,746 

7,688 

642 

2,232 

435 

3,161 

10,726 

969 

360 

4,004 

2,971 

1,206 

3,057 

3 13 

424 

42 

53 

548 

286 

127 

119 

273 

270 

74 

245 

284 

558 

19 1 

190 

296 

41 

70 

53 

53 

35 1 

78 

901 

411 

28 

6 12 

223 

173 

653 

55 

219 

33 

329 

8 15 

73 

31 

336 

261 

148 

208 

19 

3: 15 

.32 

.40 

4.08 

2.w 

.95 

.88 

2.03 

2.01 

.55 

1.82 

2.12 

4.15 

1.42 

1.41 

2.20 

.3 1 

.52 

.39 

.39 

2.61 

.58 

6.71 

3.06 

.21 

4.55 

1.66 

1.29 

4.86 

.41 

1.63 

.25 

245 

6.06 

.54 

.23 

250 

1.95 

1.10 

1.55 

.14 

28.0 28.2 

19.0 18.9 

24.3 24.7 

17.9 22.4 

17.9 19.6 

18.5 20.5 

19.1 20.4 

29.2 29.7 

29.2 31.6 

25.9 21.2 

16.9 16.7 

17.9 15.7 

18.0 21.3 

17.3 19.2 

38.2 40.5 

22.0 24.7 

22.7 23.9 

20.1 21.7 

16.7 17.1 

17.0 13.8 

16.4 15.8 

30.2 34.5 

22.6 22.1 

26.7 24.8 

23.5 25.3 

17.9 21.0 

24.4 22.6 

19.5 20.8 

18.9 17.2 

19.4 16.8 

28.7 27.9 

29.3 34.0 

28.0 27.9 

24.8 24.9 

20.2 20.2 

23.7 19.5 

21.1 19.9 

17.6 19.1 

26.2 25.6 

16.9 17.6 

15.3 15.4 

1,752 

a5 

246 

2,600 

1,084 

580 

506 

1,109 

1,411 

251 

757 

9 18 

1,958 

8 14 

1,064 

1,259 

193 

346 

172 

146 

1,214 

5 18 

3,945 

1,593 

170 

2,267 

741 

566 

2,057 

165 

955 

241 

1,354 

4,177 

340 

107 

1,174 

867 

486 

847 

75 

3.21 

.38 

.45 

4.76 

1.99 

1.06 

.93 

2.03 

2.58 

.46 

1.39 

1.68 

3.59 

1.49 

1.95 

231 

.35 

.63 

.32 

.27 

222 

.95 

7.23 

2.92 

.3 1 

4.15 

1.36 

1.04 

3.77 

.30 

1.75 

.44 

2.48 

7.65 

.62 

.a 

2.15 

1.59 

.89 

1.55 

.14 

6,222 

1,083 

998 

11,582 

5,531 

2,834 

2,476 

3,727 

4,461 

1,187 

4,535 

5,855 

9,200 

4,246 

5625 

5,103 

809 

1,594 

1,007 

1,057 

7,672 

1,500 

17,825 

6,413 

672 

10,784 

3272 

2,724 

11,936 

986 

3,425 

709 

4.855 

16,789 

1,680 

548 

5,904 

4,538 

1,897 

4,807 

490 

2.56 

.44 

.41 

4.76 

2.27 

1.16 

1.02 

1.53 

1.83 

.49 

1.86 

2.41 

3.78 

1.74 

1.08 

210 

.33 

.65 

.41 

.43 

3.15 

.62 

7.32 

2.63 

.28 

4.43 

1.34 

1.12 

4.90 

.41 

1.41 

.29 

1.99 

6.90 

.69 

.23 

243 

1.86 

.78 

1.97 

.20 

2.97 

.38 

.42 

4.53 

2 13 

1.06 

.94 

1.87 

2.14 

SO 

1.69 

2.07 

3.84 

1.55 

1.48 

-33 

.60 

.37 

.36 

2.66 

.72 

7.09 

2.87 

.26 

4.38 

1.45 

1.15 

4.51 

.37 

1.59 

.33 

2.31 

6.87 

.62 

.22 

2.36 

1.80 

.92 

1.69 

.16 

2.20 

Sources: 1 -Unpublished tabulation by U.S. Bureau of the Census from the 1980 Census. Percentage of the noninstitutional population 16-64 years 

of age with a “work disability.” 

2-U.S. Department of Commerce, Bureau of the Census, State Population and Household Estimates, with Age, Sex, and Components of 

Change, f98f-87, Current Population Reports, Series P-25, No. 1024 (Washington, DC, 1988), Isbles 5 and 6. 

3-[Cohrnn 1 column 21.5 -u.s. Department ofcommerce., Bureau of thecensus, 1980 Censusofhpulution, Volume 1, Charactekticsof 

thehpulation, Chapter C, GenemlSocial andEconomicCharactetistics, Part 1, UnitedStatesSumma~(ington, DC, 1983),lhble 245. 

6-Isble B-8, column 7. 

7-Isble B-8, column 6. 

9-Bble B-7, column 4. 

11 -[(Column 4 + column 8 + column 10)13]. 

Advisory Commiwlon on IntergovemM Relations 87 
Table B-17 

Derivation of a WorkIoad Measure for Highways, 1987 

State 

1987 

Percentage 

Miles Distribution 

1987 

Perrentap 

Miles Distribution 

.. 

Workload 

Measure 

United States 

Alabama 

Alaska 

Arizona 

Arkansas 

California 

Colorado 

Connecticut 

Delaware 

District of Columbia 

Florida 

Georgia 

Hawaii 

Idaho 

Illinois 

Indiana 

Iowa 

Kansas 

Kentucky 

Louisiana 

Maine 

Maryland 

Massachusetts 

Michigan 

Minnesota 

Mississippi 

Missouri 

Montana 

Nebraska 

Nevada 

New Hampshire 

New Jersey 

New Mexico 

New York 

North Carolina 

North Dakota 

Ohio 

Oklahoma 

Oregon 

Pennsylvania 

Rhode Island 

South Carolina 

South Dakota 

Tennessee 

Texas 

Utah 

Vermont 

Virginia 

Washington 

West Virginia 

Wisconsin 

Wyoming 

Sum of Detail 

(1) 

7,624,454 

7,624,454 

180,493 

24,108 

91,682 

153,212 

325,195 

143,877 

42,249 

11,505 

2,668 

215,701 

219,815 

8,542 

69,708 

281,870 

189,729 

229,287 

270,135 

142,445 

120,620 

44,514 

60,172 

71,008 

245,916 

268,374 

147,249 

244,369 

130,450 

186,454 

63,814 

29,749 

73,174 

98,642 

234,961 

189,416 

173,174 

235,297 

228,639 

108,553 

240,359 

12,528 

13 1,066 

145,238 

172,384 

615,908 

68,194 

28,786 

137,439 

148,485 

69,317 

223,581 

74,403 

(2) 

lOO.~% 

1OO.oooO 

2.3673 

.3 162 

1.2025 

2.0095 

4.2652 

1.8871 

5541 

.1509 

.0350 

2.8291 

2.8830 

.1120 

.9 143 

3.6969 

2.4884 

3.0073 

3.5430 

1.8683 

1.5820 

3338 

.7892 

.9313 

3.2254 

3.5199 

1.9313 

3.2051 

1.7109 

2.4455 

3370 

.3902 

.9597 

1.2938 

3.0817 

2.4843 

2.2713 

3.0861 

2.9988 

1.4238 

3.1525 

.1643 

1.7190 

1.9049 

2.2609 

8.0781 

.8944 

.3776 

1.8026 

1.9475 

.9091 

2.9324 

.9759 

(3) 

1,924,327 

1,924,327 

37,426 

3,900 

3 1,729 

18,306 

226,301 

26,968 

26,775 

6,086 

3,368 

93,639 

60,293 

7,218 

8,119 

75,756 

44,122 

20,808 

20,561 

30,320 

30,599 

10,766 

36,493 

42,305 

75,706 

35,167 

20,173 

43,379 

8,074 

13,091 

8,396 

9,167 

57,071 

15,116 

98,002 

54,600 

5,681 

79,157 

3 1,606 

23,332 

78,626 

6,003 

30,224 

6,209 

42,126 

151,186 

12,679 

5,039 

54,834 

38,520 

13,742 

40,196 

5,367 

(4) 

1OO.oooO% 

1OO.oooO 

1.9449 

2027 

1.6488 

-95 13 

11.7600 

1.4014 

1.3914 

,3163 

,1750 

4.8661 

3.1332 

.3751 

.4219 

3.9368 

22929 

1.0813 

1.0685 

1.5756 

1.5901 

395 

1.8964 

2.1984 

3.9342 

1.8275 

1.0483 

2.2542 

.4196 

.6803 

.4363 

.4764 

2.9658 

.7855 

5.0928 

2.8374 

.2952 

4.1135 

1.6424 

1.2125 

4.0859 

.3120 

1.5706 

,3227 

2.189 1 

7.8566 

.6589 

,2619 

2.8495 

2.0017 

.7141 

20888 

,2789 

(5) 

100.W6 

100.00 

2.02 

.22 

1.57 

1.14 

10.45 

1.49 

1.24 

.29 

.15 

4.5 1 

3.09 

.33 .s1 

3.89 

2.33 

1.42 

1.50 

1.63 

1.59 

S6 

1.70 

1.98 

3.81 

2.12 

1.20 

2.42 

.65 

.99 

.51 

.46 

2.61 

.87 

4.74 

2.78 

.64 

3.93 

1.88 

1.25 

3.92 

.29 

1.60 

.60 

2.20 

7.90 

.70 

.28 

2.67 

1.99 

.75 

2.24 

.40 

Sources: 1-Bble B-18, column 8. 

3-US. Department of Tkansportation, Federal Highway Administration, Highway Stahrics, 1987 (Washington, DC, 1988) Bble VM-2. 

5-[0.175 (column 2) + 0.825 (column 4)]. 

88 Advisory Commission on Intergovernmental Relations 
Table B-18 

Data Relating to Highways, 1987 

Private Net 

Motor Vehicle Licensed Total Mileage, 12\31/87 Federally Local 

Registration. Driwrs Controlled Mileage 1987 

State 1987 1987 Total Rural Urban Mileage (3)-(6) Total Nonlocal ha1 

(1) 

United States 176,046,592 

Sum of Detail 175,338,792 

Alabama 3,504,551 

Alaska 346,719 

Arizona 2,385,893 

Arkansas 1,424,737 

California 19,937,942 

Colorado 2,999,191 

Connecticut 2381,522 

Delaware 582,908 

District of Columbia 258,967 

Florida 10,464,480 

Georgia 

Hawaii 

Idaho 

Illinois 

Indiana 

Iowa 

Kansas 

Kentucky 

Louisiana 

Maine 

Maryland 

Massachusetts 

Michigan 

Minnesota 

Mississippi 

Missouri 

Montana 

Nebraska 

Nevada 

New Hampshire 

New Jersey 

New Mexico 

New York 

North Carolina 

North Dakota 

Ohio 

Oklahoma 

Oregon 

Pennsylvania 

Rhde Island 

4,961,180 

679,116 

920,446 

3,651,300 

2,660,011 

2,161,790 

2,650,045 

2,847,474 

909,884 

3,275,580 

3,845,758 

6,025,474 

3,132,579 

1,734,097 

3,685,020 

632,026 

1,281,605 

790,554 

861)245 

5,393,976 

1,255,911 

9,469,062 

4, 775,762 

637,091 

8,424,705 

2,833,866 

2,198,594 

7,550,032 

646, 185 

7,570,397 

South Carolina 

South Dakota 

Tennessee 

TexaS 

Utah 

Vermont 

Virginia 

Washington 

West Virginia 

Wisconsin 

Wyoming 

2,329,854 

659,090 

3,%7,03 1 

11,934,041 

1,094,000 

435,701 

4,550,014 

3,772,918 

1,l36,812 

3,046,842 

464,814 

(2) 

161,818,461 

161,8 18,445 

2,773,636 

300,000 

2,272,863 

1,657,795 

18,562,926 

2,310,349 

2,346,660 

4623 14 

388,835 

8,593,062 

4,215,283 

628,027 

690,893 

7,186,070 

3,590,173 

1,842,538 

1,678,418 

2,338,005 

2,614,425 

870,716 

3,009,476 

3,944,206 

6,378,723 

2,471,180 

1,775,864 

3,471,458 

604,05 1 

1,069,140 

719,058 

785,591 

6,022,080 

1,037,634 

10,029,037 

4,318,723 

434,046 

7,402,416 

2,163,148 

2,027,554 

7,684,l36 

647,887 

2,195,348 

485,367 

3,156,826 

11,153,472 

1,005,942 

402,088 

4,053,303 

3,156,743 

1,303,404 

3248,206 

339,150 

(3) (4) 

2,661,796 2,172,542 

2,661,796 2,172,542 

58,659 48,564 

6,926 5,579 

62,582 55,062 

49.754 44.969 

101;301 58,891 

49,209 41,652 

12,823 6,049 

667 - 73,811 51,374 

70,148 55,804 

3,775 2,698 

2,586 1,672 

58,652 57,266 

98.934 76.825 

601638 48i838 

70,466 65,178 

89,905 83,627 

46,523 41,609 

39,972 31,205 

13,317 11,882 

18,939 10,513 

21,008 8,060 

76,567 59,050 

90,691 80,887 

49,012 44,069 

84,267 73,583 

48,636 46,906 

62,984 59,382 

36,658 34,438 

10,019 8,591 

23,349 7,564 

41,908 38,393 

74,092 48,590 

63,313 50,610 

61,041 59,976 

77,286 56,299 

76,535 68,437 

68,866 63,119 

81,030 63,088 

4,098 947 

42,376 35,937 

48,216 47,082 

57,175 46,300 

202,770 142,018 

37,985 33,911 

9,386 8,790 

43,292 33,199 

55,682 44,693 

22,925 21,024 

75,647 66,098 

25,395 24,244 

(5) 

489,254 

489,254 

10,095 

1,347 

7,520 

4,785 

44,410 

7,557 

6,774 

1,077 

667 

22,437 

14,344 

914 

1,386 

22,109 

11,800 

5,288 

6,278 

4,914 

8,767 

1,435 

8,426 

12,948 

17,517 

9,804 

4,943 

10,684 

1,730 

3,602 

2,m 

1,428 

15,785 

3,515 

25,502 

12,703 

1,065 

u3,987 

8,098 

5,747 

17,942 

3,15 1 

6,439 

1,134 

10,875 

60,752 

4,074 

596 

10,093 

10,989 

1,90 1 

9549 

1,151 

(6) 

212,556 

212,556 

935 

34,941 

1,494 

l3,837 

7,144 

3 

- 

- 

- 

- 

984 

100 

37,633 

3 18 

118 

483 

587 

178 

430 

116 

1,672 

338 

709 

7,877 

133 

w,994 

141 

39 

6,429 

1,973 

684 

29 

20 

41,312 

992 

598 

1,956 

559 

964 

17353 

80 

1,725 

8,006 

1,414 

337 

3,921 

- 

- 

- 

- 

- 

(7) 

2,449,240 

2,449,240 

57,724 

6,926 

27,641 

48,260 

87,464 

42,065 

12,823 

667 

738 1 1 

69,164 

2,486 

21,019 

98,616 

60,638 

70,348 

89,905 

46,040 

39,385 

13,139 

18,509 

20,892 

76,567 

89,O 19 

48,674 

83,558 

40,759 

62,851 

22,664 

9,878 

23,310 

35,479 

74,092 

61,340 

60,357 

76,515 

27,554 

80,038 

4,098 

46,260 

56,616 

201,806 

20,632 

9306 

41,567 

47,676 

21,511 

75,310 

21,474 

3,772 

77,257 

41,m 

(8) 

7,624,454 

7,624,454 

180,493 

24,108 

91,682 

153,212 

325,195 

143,877 

42,249 

11,505 

2,668 215,701 

219,815 

8,542 

69,708 

281,870 

189,729 

229,287 

270,135 

142,445 

120,620 

44,514 

60,172 

71,008 

245,916 

268,374 

147,249 

244,369 

130,450 

186,454 

63,814 

29,749 

73,174 

98,642 

234,961 

189,416 

173,174 

235,297 

228,639 

108,553 

240,359 

12,528 

131,066 

145,238 

172,384 

615,908 

68,194 

28,786 

137,439 

148,485 

69,317 

223,581 

74,403 

(9) (10) 

2,725,974 4,898,480 

2,725,974 4,898,480 

65,045 115,448 

10,256 13,852 

36,400 55,282 

56,692 96,520 

150,267 174,928 

59,747 84,WO 

16,603 25,646 

3,961 7,544 

1,334 1,334 

68,079 147,622 

81,487 138,328 

3,570 4,972 

27,670 42,038 

84,638 197,232 

68,453 121,276 

88,591 140,696 

90,325 179,810 

50,365 92,080 

18,236 26,278 

23,154 37,018 

29,224 41,784 

92,782 153,134 

90,336 178,038 

49,901 97,348 

77,253 167,116 

48,932 81,518 

60,752 125,702 

18,486 45328 

9,993 19,756 

26,554 46,620 

27,684 70,958 

a6,m 148,184 

66,736 122,680 

52,460 120,714 

80,783 154,514 

75,609 153,030 

53,445 55,108 

80,283 160,076 

4,332 8,196 

47,510 83,556 

52,718 92,520 

59,152 113,232 

212,296 403,612 

26,930 41,264 

10,174 18,612 

54,305 83,134 

53,133 95,352 

26,295 43,022 

31,455 42,948 

41,850 78,770 

72,961 150,620 

Sources: 1-U.S. Department of Ttansportation, Federal Highway Administration, Highway Statistics, 1987 (Washington, DC, 1988) able MV-1. 

2-Ibid., Bbk DL-1. 

4 & 5 -Ibid., Pble HM-20. 

6-Ibid., Bble HM-50. 

9-Ibid., Bble HM-60. 

lO-[Column 7 21. 

Advisory Commission on Intergovernmental Relations 89 
Table B-19 

Derivation of a Workload Measure for Police and Corrections, 1987 

(populations in thousands) 

ter Population Total Population 

Percentage Percentage Percentage Workload 

State Number Per lOOK Number Per lOOK Distribution Number Distribution Number Distribution Measure 

1986 1987 Led 18-24 

(1) 

United States 20,613 

Sum of Detail 20,613 

Alabama 409 

Alaska 46 

Arizona 307 

Arkansas 191 

California 3,038 

Colorado 230 

Connecticut 148 

Delaware 31 

District of Columbia 194 

Florida 1,371 

Georgia 

Hawaii 

Idaho 

Illinois 

Indiana 

Iowa 

Kansas 

Kentucky 

Louisiana 

Maine 

Maryland 

Massachusetts 

Michigan 

Minnesota 

Mississippi 

Missouri 

Montana 

Nebraska 

Nevada 

New Hampshire 

New Jersey 

New Mexico 

New York 

North Carolina 

North Dakota 

Ohio 

Oklahoma 

Oregon 

Pennsylvania 

Rhode Island 

South Carolina 

South Dakota 

Tennessee 

Texas 

Utah 

Vermont 

Virginia 

Washington 

West Virginia 

Wisconsin 

Wyoming 

686 

51 

32 

1,023 

329 

51 

108 

248 

575 

23 

401 

208 

1,032 

105 

295 

464 

24 

50 

121 

23 

399 

170 

1,907 

515 

7 

595 

269 

178 

659 

34 

29 1 

28 

50 1 

2,258 

53 

11 

411 

223 

114 

149 

27 

(2) 

8.55 

10.10 

8.65 

9.36 

8.06 

11.25 

7.04 

4.64 

4.90 

31.04 

11.72 

11.25 

4.79 

3.19 

8.86 

5.98 

1.79 

4.39 

6.66 

12.78 

1.96 

8.99 

3.57 

11.29 

2.49 

11.24 

9.16 

2.94 

3.13 

12.51 

2.24 

5.23 

11.49 

10.72 

8.14 

1.03 

5.54 

8.14 

6.59 

5.54 

3.49 

8.61 

3.96 

10.44 

13.53 

3.19 

2.03 

7.09 

5.00 

5.95 

3.12 

5.33 

(3) 

20,096 

20,096 

380 

53 

253 

182 

2,924 

19 1 

156 

33 

225 

1,371 

735 

52 

31 

967 

307 

59 

110 

280 

496 

30 

436 

173 

1,m 

112 

269 

423 

33 

55 

85 

32 

35 1 

152 

2,016 

5 19 

10 

630 

244 

153 

642 

35 

3 18 

13 

444 

1,959 

55 

15 

437 

256 

92 

168 

10 

(4) 

8.26 

9.3 1 

10.10 

7.47 

7.62 

10.57 

5.80 

4.86 

5.12 

36.17 

11.40 

11.81 

4.80 

3.11 

8.35 

5.55 

2.08 

4.44 

7.51 

11.12 

2.53 

9.61 

296 

12.22 

2.64 

10.25 

8.29 

4.08 

3.45 

8.44 

3.03 

4.58 

10.13 

11.31 

8.09 

1.49 

5.84 

7.46 

5.62 

5.38 

3.55 

9.29 

1.83 

9.15 

11.67 

3.27 

2.74 

7.40 

5.64 

4.85 

3.50 

2.04 

(5) 

100.00% 

100.00 

1.89 

.26 

1.26 

.91 

14.55 

.95 

.78 

.16 

1.12 

6.82 

3.66 

.26 

.15 

4.81 

1.53 

.29 

.55 

1.39 

2.47 

.15 

2.17 

.86 

5.59 

.56 

1.34 

2.10 

.16 

.27 

.42 

.16 

1.75 

.76 

10.03 

2.58 

.05 

3.13 

1.21 

.76 

3.19 

.17 

1.58 

.06 

2.21 

9.75 

.27 

.07 

2.17 

1.27 

.46 

.84 

.05 

(6) 

27,107 

27,107 

466 

63 

373 

264 

3.006 

366 

355 

76 

67 

1,202 

737 

129 

106 

1,278 

628 

307 

267 

433 

526 

135 

532 

684 

1,060 

470 

313 

552 

85 

174 

106 

122 

843 

171 

1,983 

754 

75 

1,182 

359 

275 

1,291 

113 

416 

78 

543 

1,882 

194 

65 

714 

484 

208 

542 

53 

(7) 

100.00% 

100.00 

1.72 

.23 

1.38 

.97 

11.09 

1.35 

1.31 

.a 

.25 

4.43 

2.72 

.48 

.39 

4.71 

232 

1.13 

.98 

1.60 

1.94 

SO 

1.96 

2.52 

3.91 

1.73 

1.15 

2.04 

.3 1 

.64 

.39 

.45 

3.11 

.63 

7.32 

2.78 

.28 

4.36 

1.32 

1.01 

4.76 

.42 

1.53 

.29 

200 

6.94 

.72 

.24 

2.63 

1.79 

.77 

2.00 

.20 

(8) 

243,400 

243,399 

4,083 

525 

3,386 

2,388 

27,663 

3,296 

3,211 

644 

622 

12,023 

6,222 

1,083 

998 

11,582 

5,531 

2,834 

2,476 

3,727 

4,461 

1,187 

4,535 

5,855 

9,200 

4,246 

2,625 

5,103 

809 

1,594 

1,007 

1,057 

7,672 

1,500 

17,825 

6,413 

672 

10,784 

3,272 

2,724 

11,936 

986 

3,425 

709 

4,855 

16,789 

1,680 

548 

5,904 

4,538 

1,897 

4,807 

490 

(9) 

100.00% 

100.00 

1.68 

.22 

1.39 

.98 

11.37 

1.35 

1.32 

.26 

.26 

4.94 

2.56 

.44 

.41 

4.76 

2.27 

1.16 

1.02 

1.53 

1.83 

.49 

1.86 

2.41 

3.78 

1.74 

1.08 

2.10 

.33 

.65 

.41 

.43 

3.15 

.62 

7.32 

2.63 

.2a 

4.43 

1.34 

1.12 

4.90 

.41 

1.41 

.29 

1.99 

6.90 

.69 

.23 

2.43 

1.86 

.78 

1.97 

.20 

(10) 

lOO.a)?Zl 

100.00 

1.76 

.24 

1.34 

.95 

12.33 

1.22 

1.14 

.24 

.54 

5.40 

2.98 

.39 

.32 

4.76 

2.04 

.86 

.85 

1.51 

208 

.38 

200 

1.93 

4.43 

1.35 

1.19 

2.08 

.27 

.52 

.41 

.35 

2.67 

.67 

8.22 

2.67 

.20 

3.98 

1.29 

.96 

4.29 

.33 

1.51 

.21 

2.07 I 

7.86 

.56 

.18 

2.41 

1.64 

.67 

1.60 

.15 

Sources: 1 & 3-US. Department of Justice, Federal Bureau of Investigation, Crime in the United States, 1987 (Washin ton, DC, 1988, Table 4. 

2-[Column l/(POP86/100)]. Population on July 1,1986, from U.S. Department of Commerce, Bureau of the $ensus, Stute Populution and 

Household Estimates, with&, Ser, andComponents ofchange, 1981-87, Current Population Reports (Washington, DC, 1988, 'hbles 5 and 

6. 

4-[Column 3/(POPS7/100)]. Population on July 1, 1987, from column 8. 

6-'Eible B-15, column 2. 

8-Bble B-7, column 4. 

10-[(Column 5 + column 7 + column 9)/3]. 

90 Advisory Commission on Intergovernmental Relations 
Appendix C 

Variation in the Cost of the Goods 

and Services Used by State and Local 

Governments to Produce Public Services 

Thecost of thegoodsand servicesgovernmentsbuyin 

order to produce public services is one of the most 

controversial issues in public finance. In the media, 

attention usually focuses on the honesty and efficiency of 

the procurement process- the $435 Pentagon hammer, 

for example, or whether procedures prescribed by state 

law were used in the award of a contract by a county 

highway department. Though the efficiency of govern- ment procurement is an undeniably important object of 

public attention, it is not the dimension of the cost of 

government that is relevant here? 

In essence, the issue for present purposes can be stated 

as follows: if all governments managed their procurement 

with roughly comparable honesty and efficiency, how much 

variation would remain in the average unit costs paid by 

jurisdictions in the different states of the union? 

In a 1986 paper on the costs of the public service 

responsibilities of state and local governments published 

in conjunction with the Treasury studies of feder- al-state-local fiscal relations, the author argued that the 

’ Herbert Block, Herblock through the Looking Glass (New York: 

W.W. Norton & Co., 1984), p. 67. 

Efficiency is a consequence or attribute of the actual policies of 

a government. The central logic of the measurement of represen- tative expenditures and fiscal capacity reqh that the analysis 

abstract from a government’s actual policies Hence efficiency is 

not a relevant consideration in the present contart. 

Ray D. Whitman, “Cost as a Factor in Federal Grant Alloca- tions,’’ in Robert W. Rafuse, Jr. (ed.), Fedeml-State-Local Fis- cal Relations, Technical Papers, Vol. I1 (Washington, DC: U.S. 

Department of the Treasury, Office of State and Local Fi- nance, September 1986), pp. 941-86. 

4At the time the series was discontinued in 1982, the Bureau of 

Labor Statistics (BLS)was publishing estimates of the relative 

cost of living in 25 metropolitan areas in the continental 

United States, Alaska, and Hawaii and for a small sample of 

nonmetropolitan urban areas in each of the four major Census 

regions. (Until 1978, the estimates were available for 40 

metropolitan areas and a sample of non-metro urban areas in 

the four Census regions.) These estimates, known as the 

“family” or “standard” budget series, were published for 

market baskets of consumer goods and services representing, 

for each aredregion, three different standards of living. 

Since 1982, the BLS has published estimates of two 

consumer price indices-one for all urban consumem and one 

for all urban wage earners-for the four Census regions and 

unavailability of necessary data offered no alternative to 

assuming uniformity across the nation in the cost of the 

goods and services purchased by the states and localities 

to produce public services. 

Commentators on that paper did not take issue with 

the assumption. Perhaps the novelty of the estimates had 

something to do with the absence of such a challenge. 

Moreover, the Treasury technical papers included a 

review of the literature on the variation in input costs 

among states and region^.^ It concluded that the cause 

was hopeless even if the Reagan Administration had not 

abandoned the preparation of estimates of the relative 

cost of living in metropolitan areas? 

This time around, however, critics of an early draft of 

this report urged that an attempt be made to deal with the 

input-cost issue. They argued that the credibility of the 

effort would be undermined by the patent unrealism of an 

assumption that input costs are the same, say, in Alaska as 

in Mississippi. Hence the analysis reported this appendix 

was launched. 

for 15 metropolitan areas; see, for example, Monthly Labor 

Review, January 1989, Table 31. Unfortunately, these estimates 

only track the rate of change in the axt of the two market baskets 

of mnsumer goods and services in each area That is, the i& 

reveal whether consumer prim are rising more rapidly in the 

Boston am or the San Frandakland area, but not in which 

the absolute cost of living is higher. The reason is that the base 

(100) for the indices is the average cost of the applicable market 

basket in each area during the years 1982-84. 

Even if the family budget series had not been discontin- ued, the information, even prior to 1978, constituted an inade- quate base for credible estimates of relative living costs in all of 

the states. No estimates whatsoever were available for 22 

states, for example, or for rural areas in any states. Despite 

these obstacles, Stephen M. Bana developed a method of ex- trapolating the available BLS estimates to generate a cost-ofliving index for each of the 50 states and the District of 

Columbia (Equalization and Equity in Geneml Revenue Shar- ing: An Analysis OfAItemative Dktribution Formular; Part I: Alternative Interstate Distribution Formulas, prepared for the 

National Science Foundation, 1975). Barro’s method subse- quently was adapted and extended by Frederich J. Grasberger 

in Fomula Evaluation Pmject, Final Rqwtt, Developing and 

Applying Analytical Tools to Evaluate the Dktributional and 

Equalization Effkcts of Fedeml Gmnt-in-Aid Fonndar and to 

Impmve Formula Pegomuutce (Rochester, New York Center 

for Governmental Research, 1980). 

Advisory Commission on Intergovernmentel Relatione 91 
The estimates of relative input costsare derived using 

data from the 1980 Census of Population, the most recent 

information available in adequate detail for each state. 

The underlying economic reality is probably sufficiently 

stable that the results shed considerable light on the likely 

implications of taking account of differences in input costs 

in the measurement of fiscal capacity. The data are tooold 

for use in the implementation of federal programs, 

however (though equally ancient data continue to be used 

in a number of federal grant formulas). Should the 

general approach be deemed reasonable in concept, the 

impending availability-within, perhaps, two years-of 

the results of the 1990 Census of Population may make 

serious consideration of the approach for program 

purposes an appealing proposition. 

Measuring input Costs: Conceptual issues 

The outlays by state and local governments to 

purchase the goods and services they use to produce a 

given quantity and quality of a public service differ for at 

least five reasons: 

The prices paid per unit of the inputs purchased are 

different-per gallon of number 2 fuel oil, for 

example, or per hour for a newly credentialed CPA 

for a government’s accounting department. Land is 

much more expensive in urban than in rural areas. 

2. The quantities and mixes of the inputs used vary, 

for reasons of climate and other factors beyond 

the control of the officials of a jurisdiction. For 

example, fuel oil (or other source of energy) for 

heating is a major factor in the production of 

elementary education in Maine. It is of negligible 

interest to the school administrator in Florida, 

however, to whom electricity for air conditioning is a matter of serious importance. 

3. Goods and services are not employed with the 

same efficiency by all governments. Installation 

of a mile of curb and gutter may require 20 

laborer-hours in one city and only 18 in another 

where supervision is more rigorous and effective, 

or where work rules incorporated in collective 

bargaining agreements are less constraining. 

4. The productivity of labor varies because of 

differences in the amount of capital available per 

worker. Construction of a mile of curb and gutter 

requires many fewer laborer hours where appro- priate machinery and equipment are available 

than where the work is done largely by hand. 

1. 

5. The optimum scale of production-the level at 

which the average cost of a unit of output is at a 

minimum-varies considerably from service to 

service. All governments are not large enough to 

produce all services at their most efficient scale. 

At the same time, some governments are so large 

that their production of certain services is at a 

scale that exceeds the optimum? 

The third, fourth, and fifth sources of differences in 

the cost of the goods and services purchased by state and 

local governments have their roots in the policies of 

individual jurisdictions. For this reason, differences trace- able to these sources are disregarded in the present analysis 

for reasons discussed in the second chapter of this report. 

Ideally, a measure of the relative cost of the inputs 

used by the states and localities would take into 

consideration differences of the second type: input mix. In 

Alaska, for example, the absence of roads between many 

population centers means that such services as education 

and governmental administration require air travel to an 

extent unparalleled in any other state.6 

Unfortunately, the information base necessary for a 

systematic attempt to take account of differences in the 

production functions of state and local governments in 

different areas of the country does not exist. Given the 

complexity of the issues involved, it seems unlikely that 

the necessary information will be available in the 

foreseeable future. 

This leaves the first reason for differences in input 

costs-variation in the unit prices of the goods and 

services purchased. The measurement of unit input costs 

is discussed in the next section. 

An Index of the Prices Paid 

by State and Local Governments 

The standard approach to the estimation of differ- ences in the prices faced by purchasers in different 

areas-as of changes in the general price level over 

time-begins by defining a standard “market basket” of 

the goods and services customarily purchased by the class 

of buyers in which one is interested. 

In the immediate instance, the buyers are state and 

local governments. The reference must be to the mix of 

goods and services purchased by state and local govern- ments as a group because the purchases of any particular 

government reflect an array of policy decisions from 

which the analysis must abstract.’ For the same reason, 

reference cannot be to the prices actually paid by a 

particular government, or even by all governments in a state, 

*The scale at which a public service is produced and delivered is 

a matter on which the decisionmakers of a government often 

have a significant range of options-the scale need not be dic- tated by the size of the jurisdiction. Techniques are available 

for achieving optimum production scale whatever the size of a 

government. For example, the amount of a service to be deliv- ered may be too small to enable a government to achieve all 

possible economies of scale. In some such cases, the govern- ment may be able to realize the scale economies by arranging 

with a neighboring jurisdiction for joint production of the ser- vice. In other cases, a government may be able to capture scale 

economies by contracting for performance of the service by 

another government (perhaps a special district) or by a private 

firm. Large governments can usually manage to avoid disecon- omies of scale by decentralizing production. A useful survey of 

92 Advisory Cornhission on Intergovernmental Relations 

research on these issues appears in William E Fox, Size Econo- mies in Local Government Services: A Review, Rural Develop 

ment Research Report No. 22 (Washington, DC U.S. 

Department of Agriculture, Economics, Statistics, and Coop 

eratives Service, 1980). 

Example mentioned in a letter to the author from Brad Pierce, 

Policy Analyst, Division of Policy, Office of Management and 

Budget, Office of the Governor, State of Alaska (January 11, 

’For an analysis similar to that undertaken here but performed 

for local governments in a particular state, the appropriate 

class of buyers would be all localities, or all local governments 

of a given type, in the state. 

1990). 
because some of the most important of these pricesteachers’ salaries, for example-are affected by the policy 

decisions of the governments involved. 

With rare exceptions, as when the courts become 

involved in eminent domain takings, the states and 

localities buy goods and services in the competitive 

market. Nonetheless, many governments, especially 

larger ones, have the power to influence some of the 

prices they actually pay. Often, the effect is the payment of prices higher than those prevailing in the market. This 

may be the result of collective bargaining agreements or 

of a belief that higher-than-market prices will buy 

better-than-average teachers, or support services, or 

dealer responsiveness. These consequences of state and 

local policy decisions must be abstracted from. 

This can be accomplished in concept by referring to 

the actual behavior of governments as a group only for the 

purpose of defining the market basket. The actual price of 

each component of the market basket is ascertained for 

each area or tracked over time. Then the cost of the 

market basket as a whole is derived by calculating a 

weighted total of the prices of the individual components of the basket for each area or time period. The weights are 

the relative quantities of the gods and services that are 

regularly bought by the typical purchaser! Finally, the 

cost of the market basket is converted to an index, with a 

value of 100 assigned to the average for all areas, or to the 

cost of the basket for a given area in a base period. 

An alternative to the fixed-weight market basket is the 

variable-weight approach familiar to those acquainted with 

the national income and product accounts. In this approach, 

actual expenditures by state and local governments for goods 

and services during a period are revalued in as fine detail as 

possible using appropriate price indices. This yields an 

estimate of the value of the purchases at the prices that 

prevailed during a base period. Division of the currentdollar 

expenditures by the estimates of their value at the prices of the 

base period yields an “implicit price deflator.” 

In addition to being available in the income accounts only 

for state and local governments as a group, an implicit price 

deflator is not available for state-local expenditures other than 

direct purchases of goods and services. (After a year or so 

delay, annual estimates of currentdollar expenditures are 

published for state governments as a group and all localities, 

but separate constantdollar estimates-and the correspond- ing implicit price deflators-are not published.) 

For example, transfer payments by state and local 

governments to individuals (that is, cash payments made other 

than in exchange for currently rendered services) cannot be 

valued in the manner described above. The goods and services 

for which the payments are spent by their recipients (except 

for amounts that may be saved) are recorded in the national 

income acwunts as personal consumption, which-in the 

aggregate-is analyzed separately. Hence an overall implicit 

price deflator for all direct expenditures by state and local 

governments is not available in the income accounts. 

The approach relied on by many analysts is to use the im- plicit price deflator for personal consumption expenditures to 

deflate the total of all state-local outlays other than purchases. This is a convenient expedient because transfer payments ac- count for the remainder of state-local expenditures. Actually, 

transfers currently account for more than the remainder be- cause of a curious feature of the income accounts. Of the major 

categories of statelocal expenditures, only purchases and trans- fers currently appear as positive amounts; the entries for the other categories happen to be negative (see the tabulation below of 

data for 1989). The practical consequence of this is that the deflaThe analogy to the underlying logic of the Represen- tative Tix System and the estimates of representative 

expenditures should be apparent. The obvious way to 

arrive at a market basket for an index of the prices paid by 

state and local governments would be to look at the 

quantities of the specific goods and services actually 

purchased by all states and localities. The resulting 

“representative” market basket would identify both the 

data to be collected and the weights to be used to compute 

the value of the index for each jurisdiction or state. 

Actually, a full-blown accounting for differences in 

input costs among the states would entail the calculation 

of multiple price indices-perhaps as many as there are 

separate functions for which representative-expenditure 

estimates are prepared. The reason why a separate index 

might be required for each function is that the mix of 

inputs actually used to produce some types of services 

(even if the same mix is assumed to be used by all 

governments around the country) is drastically different 

from the mix characteristic of other services. 

Consider, for example, the diversity of payroll costs as 

a proportion of the total direct general expenditures of 

state and local governments for four function^:^ 

H public welfare-10 percent; 

H highways-22 percent; 

H 

H police protection-70 percent. 

elementary and secondary education-53-66 per- cent;1° and 

tor for total state and local expenditures calculated by this method 

somewhat overnights the deflator for purchases relative to that 

for personal consumption expenditures. 

Amount Percent 

Total Expenditures $702.5 100.0% 

Purchases of goods and services 625.6 88.9 

Transfer payments to persons 145.9 20.7 

Net interest paid less dividends received (49.3) (7.0) 

Subsidies less current surplus 

of government enterprises (18.8) (2.7) 

Note: Detail does not add to totals because of rounding. 

Source: Survq, of Cumnt Business, July 1990, Table 3.3. 

US. Department of Commerce, Bureau of the Census, Public 

Employment in 1986-87 (Washington, DC, 1988) Table 4; and 

Government Finances in 1986-87 (1988), Table 29. The Census 

wlreau publishes estimates of the gas payrolls of state and local 

governments by state, by function, and by type of government for 

the month of October each year. Gross payrolls include all 

salaries, wages, fees, and commissions actually paid to employees 

during the month. They do not include deferred compensation or 

the value of homing, meals, and other in-kind compensation. 

Hence the Census data are roughly equivalent to the current 

money earnings of state and local employees 

To compare the payroll data with fml-year expenditures, the October estimates must be annualized. For most 

functions, the annual equivalents can be approximated by 

multiplying the monthly payroll estimates by 12. However, 

most instructional employees in education (and a few in other 

functions) are paid on a nine- or ten- month basis, presumably 

including the month of October. A smaller monthly multiplier 

must be used to approximate annual payroll in these cases. 

lo The ratio depends on whether October payrolls for instruc- tional employees are assumed to be one-ninth or one-twelfth 

of total, annualized payrolls. 

Advisory Commission on Intergovernmental Relations 93 
In the case of public welfare, the bulk of the outlays 

fund cash payments for income support of program 

beneficiaries. Only 10 percent of expenditures for this 

function is for the purchase of the services of the 

government employees who administer the programs. 

Because most public welfare involves the direct payment 

of money to eligible persons and families, it is different 

from all other functions, which involve the production of 

services whose value to society can only be measured by the cost of the inputs used to produce them.” 

The cost to state and local governments of a dollar paid 

to a beneficjay is $1 (abstracting from the effect of federal 

matching grants, which is to reduce the price from $1 to the 

level of the share of the cost not financed by federal funds). 

The value of a dollar of cash assistance to the program 

beneficiary, on the other hand, is not the Same everywhere 

in the country. That value depends on the cost of living in 

one area compared with that in another. A complicating 

factor is the likelihood that the cost living for low-income 

program beneficiaries does not vary around the country in 

precise proportion to the cost of living for the middleincome government employees administering the program. 

In elementary and secondary education, the bulk of 

expenditures by state and local governments are for the 

salaries of teachers and support staff. The other outlays are 

for such purposes as the construction and maintenance of 

school buildings, instructional materials, and libraries. The 

mix clearly is entirely different from that for public welfare. 

In the case of highways, payroll is only 22 percent of 

total outlays. The other major objects of expenditure are 

machinery and equipment, paving materials, and the 

purchase of the services of construction contractorsagain, an entirely different mix of inputs. Payroll accounts 

for an even-larger share of expenditures for police than 

for elementaly and secondary education, and other 

outlays for the police function are for purposes that 

l1 An exception is the rare case when a service produced by gov- ernment is sold at a market price in a competitive market. In 

such cases, of course, the value of a unit of the output is its mar- ket price. For a discussion of these issues of the valuation of 

government output, see W. Irwin Gillespie, “Effect of Public 

Expenditures on the Distribution of Income,” in Richard A. 

Musgrave (ed.), Essays in Fiscal Federalism (Washington, DC: 

The Brookings Institution, 196.5) pp. 122-86. 

l2 Whitman speculates that such an effort would cost more than the 

compilation of the consumer price index, a central element of the 

nation’s economic data base (“Cost as a Factor. . . ,” p. 977). 

l3 I am indebted to Robert D. Reischauer for insisting that the 

input-cost issue be addressed and for suggesting the general 

approach outlined in this section. He, of course, bears none of 

the responsibility for the specific details of my execution of his 

advice. 

14The derivation of this estimate is explained below. 

l5 In a letter to John Kincaid (Executive Director, ACIR), dated 

February 7,1990, commenting on a draft of this report, L Ed- ward Lashman, Jr. (Secretary, Executive Office for Adminis- tration and Finance, Commonwealth of Massachusetts) 

argues that 

The use of average employee earnings from the 

1980 Census is problematic for two reasons. These data 

are 10 years old; relative wage rates have shifted dra- matically in the last 10 years because of disparate 

growth trends in regional economies. Second, state- wide average wages also differ because of differing inbear little resemblance to textbooks or paving materials. 

Tahnical niceties aside, however, deference must be 

paid to two harsh realities; together, they preclude 

implementation of a representative market basket ap- proach. First, information is not available in sufficient detail 

on the specific goods and services actually purchased by the 

states and local governments-in the aggregate, to say nothing of specific functions-to permit the specification of 

anything more than the most rudimentary market basket. 

The discussion of the input mix for various functions in the 

past few paragraphs tests the outer limits of the detail of 

information currently available. More importantly, even if a 

crude market basket were defined, data on the actual prices 

paid by governments around the country for the items in the 

basket are not currently collected, and an effort to do so 

would be extremely expensive.12 

In fact, the only currently feasible strategy for 

identifying the differences among the states in the input 

costs of public services is an effort to estimate the 

variation in the labor-cost component of expenditures. A 

method of accomplishing this is outlined in the next 

section. The results of this analysis are used in the final 

section to calculate a set of overall indices of unit input 

costs on the assumption that costs other than employee 

compensation do not vary among the states. 

An Approach to Identifying Differences 

in Unit Labor Costs13 

The total cost of employee compensation amounts to 

roughly half of the total direct general expenditures of 

state and local go~emments.’~ This section summarizes a 

method of estimating the differences in the unit cost of 

that compensation among the states using data on 

individual earnings from the 1980 Census of Population. 

The data are, regrettably, the most recent available in the 

detail necessary for the approach.15 

dustry mix; however, thesewying mixes maybe irrele- vant for state and local government hiring needs. 

Both problems could possibly be solved by use 

of Labor Department data on payrolls and employ- ment, which are far more current than the Census 

data. ACIR could choose an appropriate skill mix or 

industry mix to proxy the state and local labor force 

(e.g., government looks more like service industries 

than like manufacturing or retail trade; government 

employs a higher proportion of professional and 

technical workers). At a minimum, the 1980 Census 

data could be “aged” through use of Bureau of Eco- nomic Analysis state personal income data 

In a telephone conversation with the author on February 1, 

1990, Ron Lanoue (Capital Planning Manager, Budget Bureau, Commonwealth of Massachusetts) suggested that the es- timates of the relative costs of employee compensation 

derived from earnings in 1979 be aged using the regional and 

metropolitan area cost of livinglconsumer price indices pub- lished by BLS. The problems with these BLS data and the 

work undertaken by Barro in 1975 and Grasberger in 1980 to 

develop methods for overcoming them are discussed in footnote 4 above. An attempt to adapt their methods to implement 

Lanoue’s suggestion, especially given the changes in its statis- tical program implemented by BLS in 1982, would have re- quired far more resources than were available for the present 

study. Moreover, the likely improvement in the reliability of 

the estimates of the variation in employee compensation costs 

among the states would probably not have been sufficient to 

warrant the effort, particularly in light of the impending avail- ability of information on 1989 earnings from the 1990 Census. 

94 Advisory Commission on Intergovernmental Relations 
The basic idea underlying the approach is fairly 

straightforward. It is that-controlling for sex, age, and 

educational attainment-differences among the states in 

the average earnings of all full-time employees are a reasonably good indicator of relative unit labor costs.16 An index of these differences is an appropriate device for 

adjusting the labor-cost component of the estimates of 

representative expenditures for the variation in these 

costs among the states. 

Variation in the cost of living is the most important 

source of differences in average earnings among the 

states, and hence in the unit labor costs of state and local 

governments. Other factors include the power of labor 

unions in a state and the amount of capitd available per 

worker. 

It is important to remember that cost of living is more 

than a matter of the prices of consumer goods and 

services. Cost of living comprehends the mix of consumption as well as prices paid per unit. For example, 

transportation costs boost the prices of many'consumer 

goods in Hawaii to levels significantly higher than those 

on the Mainland. However, the supremely temperate 

climate of the Islands, coupled with a lifestyle arguably 

more felicitous even than that of California, combine for a 

cost of living that may actually be lower than the U.S. 

average. Moreover, the climate and lifestyle of the Islands 

may be worth enough to many individuals that they are 

willing to accept lower real cash incomes in exchange for the 

nomonetary benefits. 

The unavailability of data relating to the other factor 

costs of state and local governments means that those 

costs must be assumed, for purposes of this analysis, to be 

uniform among the states. This is not an unreasonable 

I6The reference is to the earnings of all employees rather than 

the employees of state and local governments because the 

earnings of public employees are strongly influenced by the 

policies of the governments for which they wrk, and abstraction 

from policy is a key consideration in this analysis. In any event, 

earning data from the 1980 Census are not available separately 

for government employees, nor are the published data on the 

earning of government employees available broken down by the 

demographic characteristics of the employees. 

It is not likely that state and local governments employ a 

large enough proportion of the labor force in any state that 

their compensation policies are a serious influence on overall 

levels of earnings. For example, of the five states with the 

highest numbers of full-timeequivalent state-local government employees per 10,OOO population, FTE government 

workers were 18 percent of total employment in October 1986 

in Alaska and Wyoming. The ratios are 14 percent in Nebraska 

and New York, and 8 percent in the District of Columbia. The 

U.S. average is a little less than 12 percent. Public Employment 

in 1986, Tables 7 and 12; and Employment and Eumings, 

December 1986, Tables B-4 and B-8. 

"An intensive search of possible sources of information on 

some of these factors of production might well establish the 

availability of sufficient reliable data to permit development of 

additional cast indices. These would make it possible to 

increase the proportion of the outlays of state and local 

governments for which input-cost adjustments could be made. 

Such an effort, however, would require resources and time far 

beyond those available for the present study. 

assumption for a significant portion of the purchases of 

those governments-particularly for such goods as motor 

vehicles, computers, and related equipment and supplies 

that are traded in competitive national markets. Uniformity is a questionable assumption, however, for energy 

and land costs, among others." 

IQble C-1 shows for each state the mean annual 

earnings of male residents, 45-54 years of age, who worked 

40 or more weeks in lm, at each of seven levels of 

educational attainment. No weighty analytical considerations dictate the choice of this particular set of data. The 

distinguishing characteristic of the earnings of males 45-54 

years of age is that they are higher, on average, than those of 

any other demographic group. The information in columns 

1-8 of Thble C-1, indexed to the U.S. average, is displayed in 

able C-2 to facilitate comparisons among the states. 

To calculate an index of unit labor costs from these 

data, a set of weights is needed. In order to abstract from 

the actual mix of employment in each state, a single set of 

national weights is used to calculate the index.18 Two 

options are available: (1) the national totals of the 

numbers of comparable individuals at each level of 

educational attainment in 1979, from the Census; and (2) 

the number of such persons at each level of educational 

attainment in 1986, as determined by the Current 

Population Survey. The two sets of weights are shown in 

the first few rows of Tmble C-3. The percentage distribution of the 1986 data is used as the weights for the earnings 

data for each state. The weighted average of the earnings 

for each state appears in column 1 of nble C-3. The index 

of the state averages in column 1 to the national average is 

shown in column 9, which is the desired index of unit labor 

Examples of three areas where research on input costs 

could have asubstantialpayoff in improved reliability of the 

estimates of representative expenditures are cited in the 

letter from Edward Lashman of Massachusetts comment- ing on a draft of this report: 

It is unreasonable to expect (as does this analy- sis) that AFDC and EA recipients are receiving 

equivalent services by equal dollar welfare grants if 

rent levels are vastly different. 

.*. 

ACIR should include interstate health care cost 

data. The literature on comparative hospital and 

physician costs is extensive, and it demonstrates that 

significant differences do exist. 

8.8 

In any capital construction program (e.g., high- ways, environment and housing), interstate varia- tions in construction costs are significant. These data 

are available from such private seMces as EW. 

Dodge/McGraw Hill. 

'*Note that the first column of Table C-1 is the equivalent of a 

weighted average of the mean earnings at each level of educa- tional attainment, where the weights are the actual number of 

employed men at each level in each state. Therefore, the first 

column of Table C-2 is, effectively, an index of unit labor costs 

constructed using each state's own rather than national-average weights. 

Advisory Commission on Intergovernmental Relations 95 

I 
8 

D 

a 

Table C-I 

Mean Annual Earnings of Males 45-54 Years Old Who Worked 40 or More Weeks in 1979, by Years of Educational Attainment 

5. 

Elempntarv Hi&&hool colleee 

s 

$? 

% 

3 state Total 0-7Years 8Years 13Years 4Years 1-3 Years 4 Years 5+ Years 516Years 7+ Years 5-6 Years 7+ Years 

cn. 

0 

3 

s United States 

3 Alabama 

Alaska $ Arizona 

Arkansas 3 California 

Colorado 5 Connecticut 

(D Delaware 

District of Columbia 

2 Florida 

Georgia 

Hawaii 

Idaho 

Illinois 

Indiana 

Iowa 

Kansas 

Kentucky 

Louisiana 

Maine 

Maryland 

Massachusetts 

Michigan 

Minnesota 

Mississippi 

Missouri 

Montana 

Nebraska 

Nevada 

New Hampshire 

New Jersey 

New Mexico 

New York 

North Carolina 

North Dakota 

Ohio 

Oklahoma 

Oregon 

Pennsylvania 

Rhode Island 

- 

(1) 

$23,084 

19,835 

33,366 

23,118 

18,255 

25,932 

24,657 

26,527 

23,375 

24,384 

20,883 

20,488 

22,957 

20,305 

25,293 

22,423 

21,306 

22,102 

20,506 

Q63 1 

17,305 

25,367 

22,923 

25,796 

23,757 

17,989 

21,654 

20,280 

20,368 

23,012 

20,103 

25,658 

20,722 

23,611 

18,280 

19,182 

23,5so 

21,942 

23,591 

22,245 

20,470 

(2) 

$14,045 

12,737 

26,562 

13,855 

12,351 

14,918 

15,459 

16,440 

13,680 

13,415 

12,847 

12,095 

14,161 

14,086 

16,028 

16,536 

15,574 

15,244 

l3,836 

15,256 

12,761 

15,293 

13,738 

19,003 

15,188 

10,869 

14,218 

16,219 

13,646 

16,1#1 

14,050 

15,104 

12,300 

13,557 

11,229 

13,955 

16,837 

14,261 

17,002 

15,161 

13,225 

(3) 

$16,399 

14,329 

29,504 

18,859 

12,753 

18,828 

17,903 

15w 

14,529 

14,584 

14,098 

14,250 

16,398 

15.036 

18,337 

17,424 

16,243 

15,253 

15,653 

16,524 

W,408 

17,15 1 

15,091 

19,725 

16,388 1aw 

16,381 

16,782 

14,859 

18,686 

17,105 

15,756 

15,156 

W,146 

14,346 

18,093 

15W 

18,420 

16,505 

14,255 

14,305 

(4) 

$17,978 

15,487 

29,088 

17,851 

14,458 

18,972 

17,911 

1738 

15564 

15,690 

16,232 

18,223 

17,803 

19,760 

18,735 

17,952 

17,343 

18,744 

14,342 

18,214 

16,709 

20,953 

18,739 

14,590 

17,570 

18,117 

16,616 

19,953 

15,157 

17,169 

17,049 

14m 

16,491 

19,029 

16,583 

17,572 

15,906 

20,076 

17x36 

18,670 

m, 180 

(5) 

$m,m 

18,870 

3 1,564 

20,754 

17,604 

22,479 

21,080 

20,386 

19,734 

17,653 

18,651 

18,911 

20,661 

18,433 

22,562 

19,554 

193 19 

19,979 

21,356 

16,132 

21,614 

19,229 

23,209 

17,339 

19,758 

19,098 

18,502 

18,306 

21,614 

18,800 

20,022 

17,212 

18,670 

21,509 

19,865 

21,564 

19,855 

18,308 

m,96o 

20,728 

20,475 

(6) 

$23,903 

21,282 

33,628 

22,774 

20,049 

25,190 

23,501 

25,631 

23,233 

21,772 

21,296 

22,484 

229023 

20,957 

26,012 

24,340 

22,824 

23,427 

23,144 

24,679 

19,360 

25,761 

23,005 

27,532 

25,641 

19,810 

22,830 

19,757 

21,946 

24,053 

21,411 

26,341 

21,021 

24,067 

24,560 

21,864 

23,029 

23,584 

21,592 

20,983 

20,244 

(7) 

$33,342 

30,253 

36,096 

30,433 

28,945 

33,521 

32,934 

40,071 

35,225 

31,668 

29,395 

3&475 

30,492 

27,642 

37,115 

33,204 

3 1,848 

32,479 

32,278 

35,165 

25,300 

34,975 

32,491 

36,682 

34,675 

28,739 

32,085 

26,538 

29,375 

29,16 1 

27,802 

37,014 

28,614 

34,437 

29,103 

27,788 

34,010 

31,501 

31,402 

33,523 

32,386 

(8) 

$37,432 

34,320 

41,207 

35,048 

33,007 

37,893 

35260 

43.83 1 

40,029 

43,578 

35,544 

35,401 

35,171 

27,813 

40,706 

35,419 

33,327 

32,725 

36,772 

35,820 

27,463 

40,021 

36,572 

40,148 

36,583 

31,112 

34,948 

27,75 1 

31,912 

35w 

30,591 

41,203 

3 1,262 

39,729 

34% 

30,744 

38,769 

34,507 

32,190 

39,000 

36530 

(9) 

$3338 

28,853 

37,777 

30,644 

27,651 

33,791 

33,569 

42,296 

35,OW 

37306 

29,952 

30243 

29,936 

25,985 

37,3 14 

29,642 

28,580 

29,018 

29,805 

3 1,162 

22,3 18 

36,780 

33,996 

35334 

31,356 

25,671 

30,685 

24,859 

28,068 

28,712 

27,915 

37,995 

28m 

35,502 

28,842 

28,436 

33,642 

31,725 

29,726 

34,133 

33,63 1 

(10) 

$41,864 

40,500 

44,979 

39,573 

39,m 

42,543 

37,169 

45,717 

44,401 

48,052 

41,758 

41,541 

41,048 

30,m 

44,524 

41,963 

38,657 

36,526 

44,164 

41,023 

32,927 

42,832 

39333 

45,660 

43,167 

36,170 

39,464 

31,130 

35,717 

42,321 

33,611 

44,572 

34,m 

43,620 

39,275 

33338 

445 10 

37,622 

35,OW 

43325 

39,172 

(11) 

514,276 

5,959 

902 

6,129 

2,803 

73,806 

8,729 

11,488 

1,515 

1,880 

19,299 

9,372 

2,299 

5030 

25,140 

9,473 

5,192 

5,252 

4,663 

6,480 

1,660 

13,%7 

16,895 

19,849 

10,427 

2,975 

8,908 

1,563 

2,848 

1,590 

5042 

21,873 

2,890 

46,235 

8,289 

1,155 

21,545 

6,366 

6,046 

1,668 

20,497 

(12) 

473,809 

5,271 

820 

5,965 

2,387 

65,106 

7,735 

9,353 

1,738 

2,636 

17,367 

7,872 

2,048 

1,246 

22,334 

8,364 

4,624 

5,122 

4,395 

5,801 

1563 

16,101 

15,765 

17,334 

8277 

3w 

8,410 

1,338 

2,877 

1,513 

1,810 

20,828 

3,061 

50232 

8,540 

1,028 

19,238 

5,684 

23,066 

1830 

5,277 
Table C-1 (cont.) 

Mean Annual Earnings of Males 45-54 Years Old Who Worked 40 or More Weeks in 1979, by Years of Educational Attainment 

Me- h ibit: Collew Attainment .. 

StaC lbtpl 0-7Years 

Elementarv 

8Yem 1-3Years 

Hieh School 

4Years 1

collere 

-3 Years 4 Years 5+ Years 

Mean 

5/6 Years 

Earniner 

7+ Years 

1979 - 

5-6 Years 'I+ Years 

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (1 1) (12) 

South Carolina 18,313 11,516 13,004 15,533 17,466 19,820 29,491 34,310 29,678 38,912 3,753 3,?78 

South Dakota 17,143 11,859 12,823 14,689 16,337 17,903 25,383 27,907 24,956 30,483 1,036 1,187 

Tennessee 19,572 12,051 14,170 15,800 18,917 22,925 30,124 33,884 29,413 38,686 7,298 6,794 

TexaS 23,521 13,348 16,228 18,467 20,833 23,837 35,043 38,638 34,894 43,666 34,452 25,649 

Utah 23,573 15,659 16,656 19,465 21,546 22,496 29,550 30,301 28,018 33,200 4,170 3,284 

Vermont 18,213 12,621 14,472 14580 17,006 19,397 26,843 26,001 24,029 28,636 1,138 852 

Virginia 22,740 13,612 15,047 16,794 19,981 23,270 32,826 37,438 34,341 41,054 17,303 14,821 

Washington 25,270 18,723 20,604 21,391 22,814 23,822 31,482 34,838 31,904 38,524 11,577 9,217 

Wisconsin 22,386 16,903 17,554 18,488 20,359 23,495 32,194 36,143 32,422 40,041 8,381 8,001 

Wyoming 23,077 16,724l 19,015 19,651 21,343 24,253 29,955 29,442 26,151 34,294 1,247 846 

Sources: 1-7,9-12, U.S. totals-U.S. Department of Commerce, Bureau of the Census, 298UCemus of POpuutiOn, Vol. 1, C/&?ruc&stksof the hpulution, Chapter D,De&iled Popurcltion Chamaerirtics, 

1-7.9-12, States-2980 Census of Population, W. 1, C~mcze~cs of the Popuhzliwz, Chapter D, Detailed Population Charactektics, Part 6, [State] (1983), Thble 237. 

8-Mean of columns 9 and 10, weighted by columns 11 and 12, respectively. 

West Virginia 20,612 14,983 16,378 18,854 20,313 21,751 28,216 33,798 27,163 40,427 5222 5224 

Part 1, United States Summary, Section A: United Staies, 'Eibles 253-310 (Washington, DC, 19841, 'Ihble 296. 

D Q 

4 

0 

J 
Table C-2 

Indices of the Mean Annual Earnings of Males 45-55 Years Old Who Worked 40 or More Weeks in 1979, 

by Years of Educational Attainment 

State Total 0-7Years 

Elementan 

8 Years 1-3 Years 4 Years 

I 

1

- 

-3 Years 4 Years 5 + Years 

United States 

Alabama 

Alaska 

Arizona 

Arkansas 

California 

Colorado 

Connecticut 

Delaware 

District of Columbia 

Florida 

Georgia 

Hawaii 

Idaho 

Illinois 

Indiana 

Iowa 

Kansas 

Kentucky 

Louisiana 

Maine 

Maryland 

Massachusetts 

Michigan 

Minnesota 

Mississippi 

Missouri 

Montana 

Nebraska 

Nevada 

New Hampshire 

New Jersey 

New Mexico 

New York 

North Carolina 

North Dakota 

Ohio 

Oklahoma 

Oregon 

Pennsylvania 

Rhode Island 

South Carolina 

South Dakota 

Tennessee 

TaraS 

Utah 

Vermont 

Virginia 

Washington 

West Virginia 

Wisconsin 

Wyoming 

(1) 

100.0 

85.9 

144.5 

100. 1 

79.1 

112.3 

106.8 

114.9 

101.3 

105.6 

90.5 

88.8 

99.5 

88.0 

109.6 

97.1 

923 

95.7 

88.8 

98.0 

75.0 

109.9 

99.3 

111.7 

102.9 

93.8 

87.9 

88.2 

99.7 

87.1 

111.2 

89.8 

102.3 

79.2 

83.1 

102.0 

95.1 

102.2 

96.4 

88.7 

79.3 

74.3 

84.8 

101.9 

102.1 

78.9 

98.5 

109.5 

89.3 

97.0 

100.0 

77.9 

(2) 

100.0 

90.7 

189.1 

98.6 

87.9 

106.2 

110.1 

117.1 

97.4 

95.5 

91.5 

86.1 

100.8 

100.3 

114.1 

117.7 

110.9 

108.5 

98.5 

108.6 

90.9 

108.9 

97.8 

135.3 

108.1 

77.4 

101.2 

115.5 

97.2 

114.8 

100.0 

107.5 

87.6 

96.5 

80.0 

99.4 

119.9 

101.5 

121.1 

107.9 

94.2 

82.0 

84.4 

85.8 

95.0 

111.5 

89.9 

96.9 

133.3 

106.7 

120.3 

119.0 

(3) 

100.0 

87.4 

179.9 

115.0 

77.8 

114.8 

109.2 

96.6 

88.6 

88.9 

86.0 

86.9 

100.0 

91.7 

111.8 

106.3 

99.0 

93.0 

95.5 

100.8 

81.8 

104.6 

92.0 

m.3 

99.9 

76.0 

99.9 

102.3 

90.6 

113.9 

87.2 

104.3 

96.1 

92.4 

80.2 

87.5 

110.3 

96.9 

112.3 

100.6 

86.9 

79.3 

78.2 

86.4 

99.0 

101.6 

88.2 

91.8 

125.6 

99.9 

107.0 

116.0 

(4) 

100.0 

86.1 

161.8 

99.3 

80.4 

111.7 

105.5 

99.6 

96.2 

86.6 

87.3 

90.3 

101.4 

99.0 

109.9 

104.2 

99.9 

96.5 

95.9 

104.3 

79.8 

101.3 

92.9 

116.5 

104.2 

81.2 

97.7 

100.8 

92.4 

111.0 

84.3 

103.8 

95.5 

94.8 

82.8 

91.7 

105.8 

92.2 

112.2 

97.7 

88.5 

86.4 

81.7 

87.9 

102.7 

108.3 

81.1 

93.4 

119.0 

104.9 

102.8 

109.3 

(5) 

100.0 

91.8 

153.6 

101.0 

85.7 

109.4 

102.6 

99.2 

96.0 

85.9 

90.8 

92.0 

100.5 

89.7 

109.8 

102.0 

95.1 

95.0 

97.2 

103.9 

78.5 

105.2 

93.6 

112.9 

100.9 

84.4 

96.1 

92.9 

90.0 

99.6 

89.1 

105.2 

91.5 

97.4 

83.8 

90.8 

104.7 

96.7 

104.9 

96.6 

89.1 

85.0 

79.5 

92.0 

101.4 

104.8 

82.8 

97.2 

111.0 

98.8 

99.1 

103.9 

(6) 

100.0 

89.0 

140.7 

95.3 

83.9 

105.4 

98.3 

107.2 

97.2 

91.1 

89.1 

94.1 

92.1 

87.7 

108.8 

101.8 

95.5 

98.0 

96.8 

103.2 

81.0 

107.8 

96.2 

115.2 

107.3 

829 

95.5 

82.7 

91.8 

100.6 

89.6 

110.2 

87.9 

100.7 

87.8 

84.7 

1027 

91.5 

96.3 

98.7 

90.3 

82.9 

74.9 

95.9 

99.7 

94.1 

81.1 

97.4 

99.7 

91.0 

98.3 

101.5 

(7) 

100.0 

90.7 

108.3 

91.3 

86.8 

100.5 

98.8 

12Q.2 

105.6 

95.0 

88.2 

97.4 

91.5 

82.9 

111.3 

99.6 

95.5 

97.4 

96.8 

105.5 

75.9 

104.9 

97.4 

110.0 

104.0 

86.2 

96.2 

79.6 

88.1 

87.5 

83.4 

111.0 

85.8 

103.3 

87.3 

83.3 

102.0 

94.5 

94.2 

100.5 

97.1 

88.5 

76.1 

90.3 

105.1 

88.6 

80.5 

98.5 

94.4 

84.6 

96.6 

89.8 

(8) 

100.0 

91.7 

110.1 

93.6 

88.2 

101.2 

94.2 

117.1 

106.9 

116.4 

95.0 

94.6 

94.0 

74.3 

108.7 

94.6 

89.0 

87.4 

98.2 

95.7 

73.4 

106.9 

97.7 

107.3 

97.7 

83.1 

93.4 

74.1 

85.3 

94.4 

81.7 

110.1 

83.5 

106.1 

91.2 

82.1 

103.6 

92.2 

86.0 

104.2 

97.6 

91.7 

74.6 

90.5 

103.2 

81.0 

69.5 

100.0 

93.1 

90.3 

96.6 

78.7 

Source: Bble C-1. 

98 Advisory Commission on Intergovernmental Relations 
Table C-3 

Labor-Input-Cost Index Derived from Mean Annual Earnings of Males 45.54 Years Old 

Who Worked 40 or More Weeks in 1979, by Years of Educational Attainment, 1986 Weights 

(populations in thousands) 

State 

Index 

of Unit 

Elementarv Hiehool Col Labor 

Total 0-7 Years 8 Years 1-3 Years 4 Years 1-3 Years 4 Years 5 + Years COStS 

United States 

weights, 1979 

Weights, 1986 

Alabama 

Alaska 

Arizona 

Arkansas 

California 

Colorado 

Connecticut 

Delaware 

District of Columbia 

Florida 

Georgia 

Hawaii 

Idaho 

Illinois 

Indiana 

Iowa 

Kansas 

Kentucky 

Louisiana 

Maine 

Maryland 

Massachusetts 

Michigan 

Minnesota 

Mississippi 

Missouri 

Montana 

Nebraska 

Nevada 

New Hampshire 

New Jersey 

New Mexico 

New York 

North Carolina 

North Dakota 

Ohio 

Oklahoma 

Oregon 

Pennsylvania 

Rhode Island 

South Carolina 

South Dakota 

Tennessee 

Texas 

Utah 

Vermont 

Virginia 

Washington 

West Virginia Wisconsin 

Wyoming 

Percentage Dktribution 

Percentage Distribution 

(1) 

$24,166 

8,726 

99.9973% 

8,291 

100.oooo% 

21,889 

32,475 

23,393 

20,675 

25,503 

24,079 

26,217 

24,244 

23,106 

21,890 

22,636 

23,201 

20,618 

26,519 

24,191 

22,794 

22,774 

23,482 

24,683 

18,711 

25,532 

23,101 

27,049 

24,650 

20,228 

23,111 

20,610 

21,521 

23,586 

20,782 

26,121 

21,372 

24,342 

20,933 

20,883 

25,097 

22,726 

23,662 

24,074 

22,386 

20,972 

18,634 

22,124 

24,710 

22,893 

19,098 

23,606 

24,876 

22,581 

23,778 

23,150 

(2) (3) 

$508 $653 

685 594 

7.8512% 6.8089% 

300 330 

3.6184% 3.9802% 

461 

961 

501 

447 

540 

559 

595 

495 

485 

465 

438 

5 12 

5 10 

580 

598 

564 

552 

50 1 

552 

462 

553 

497 

688 

550 

393 

5 14 

587 

494 

583 

508 

547 

445 

49 1 

406 

505 

609 

5 16 

6 15 

549 

479 

417 

429 

436 

483 

567 

457 

493 

677 

542 

6 12 

605 

570 

1,174 

75 1 

508 

749 

713 

630 

578 

580 

561 

567 

653 

598 

730 

694 

647 

607 

623 

658 

534 

683 

601 

785 

652 

496 

652 

668 

591 

744 

569 

681 

627 

603 

523 

571 

720 

633 

733 

657 

567 

5 18 

5 10 

564 

646 

663 

576 

599 

820 

652 

699 

757 

(4) (5) 

$1,834 $7,657 

1,343 2,957 

15.3945% 33.8863% 

846 3,089 

10.2038% 37.2573% 

1,580 

2,968 

1,821 

1,475 

2,049 

1,936 

1,828 

1,764 

1,588 

1,601 

1,656 

1,859 

1,817 

2,016 

1,912 

1,832 

1,770 

1,759 

1,913 

1,463 

1,859 

1,705 

2,138 

1,912 

1,489 

1,793 

1,849 

1,695 

2,036 

1,547 

1,905 

1,752 

1,740 

1,519 

1,683 

1,942 

1,692 

2,059 

1,793 

1,623 

1,585 

1,499 

1,612 

1,884 

1,986 

1,488 

1,714 

2,183 

1,924 

1,886 

2,005 

7,030 

11,760 

7,732 

6,559 

8,375 

7,854 

7,595 

7,352 

6,577 

6,949 

7,046 

7,698 

6,868 

8,406 

7,809 

7,285 

7,272 

7,444 

7,957 

6,010 

8,053 

7,164 

8,647 

7,723 

6,460 

7,361 

7,115 

6,893 

7,628 

6,820 

8,053 

7,004 

7,460 

6,413 

6,956 

8,014 

7,401 

8,034 

7,397 

6,821 

6,507 

6,087 

7,048 

7,762 

8,027 

6,336 

7,444 

8,500 

7,568 

7,585 

7,952 

(6) (7) (8) 

$3,981 $4,452 $5,589 

1,250 908 988 

14.3240% 10.4089% 11.3235% 

1,381 1,107 1,238 

16.6566% 13.3518% 14.9319% 

3,545 

5,601 

3,793 

3,339 

4,196 

3,914 

4,269 

3,870 

3,626 

3,547 

3,745 

3,668 

3,491 

4,333 

4,054 

3,802 

3,902 

3,855 

4,111 

3,225 

4,291 

3,832 

4,586 

4,271 

3,300 

3,803 

3,291 

3,655 

4,006 

3,566 

4,388 

3,501 

4,009 

3,495 

3,372 

4,091 

3,642 

3,836 

3,928 

3,596 

3,301 

2,982 

3,819 

3,970 

3,747 

3,231 

3,876 

3,968 

3,623 

3,913 

4,040 

4,039 

4,819 

4,063 

3,865 

4,476 

4,397 

5,350 

4,703 

4,228 

3,925 

4,336 

4,071 

3,691 

4,956 

4,433 

4,252 

4,337 

4,310 

4,695 

3,378 

4,670 

4,338 

4,898 

4,630 

3,837 

4,284 

3,543 

3,922 

3,894 

3,712 

4,942 

3,820 

4,598 

3,886 

3,710 

4,541 

4,206 

4,193 

4,476 

4,324 

3,938 

3,389 

4,022 

4,679 

3,945 

3,584 

4,383 

4,203 

3,767 

4,298 

4,000 

5,125 

6,153 

5,233 

4,929 

5,658 

5,265 

6,545 

5,977 

6,507 

5,307 

5,286 

5,252 

4,153 

6,078 

5,289 

4,976 

4,886 

5,491 

5,349 

4,101 

5,976 

5,461 

5,995 

5,462 

4,646 

5,218 

4,144 

4,765 

5,278 

4,568 

6,152 

4,668 

5,932 

5,097 

4,591 

5,789 

5,152 

4,807 

5,823 

5,455 

5,123 

4,167 

5,059 

5,769 

4,525 

3,883 

5,590 

5,202 

5,047 

5,397 

4,396 

(9) 

100.0 

90.6 

134.4 

96.8 

85.6 

105.5 

99.6 

108.5 

100.3 

95.6 

90.6 

93.7 

96.0 

85.3 

109.7 

100.1 

94.3 

94.2 

97.2 

102.1 

77.4 

105.7 

95.6 

111.9 

102.0 

83.7 

95.6 

85.3 

89.1 

97.6 

86.0 

108. 1 

88.4 

100.7 

86.6 

86.4 

103.9 

94.0 

97.9 

99.6 

926 

86.8 

n. 1 

91.6 

102.3 

94.7 

79.0 

97.7 

1029 

93.4 

95.8 

98.4 

Sources: 1-6-The weights are the U.S. total number of full-time male workers with earnings, age 45-54, with the indicated level of educational 

achievement. The 1986 weights are from U.S. Department of Commerce, Bureau of the Census, Monq Income offfouseholds, Families, 

andPenonsinthe Unitedstates; 1986, Current Population ReportsOhashington, DC, 1988),'Eible 36. The 1979 weightsare from Bureauof 

the Census, 1980 Censlrs of Population, Vol. 1, Chamctetistics of the Population, Chapter D, Detailed Population Characteristics, Part 1, 

United States Summary, Section A: United States, 'lhbles 253-310 (Washington, DC, 1984) 'Ihble 296. 

I-8-"he entries are columns 2-8, 'Eible C.2, multiplied by the 1986 percentage weights; column 1 is the sum of the entries in columns 2-6. 

9-Column 1 indexed to the U.S. average. 

Advisory Commission on Intergovernmental Relations W 
costs for each state. The values of the index range from a 

low of 77 in South Dakota and Maine to 134 in Alaska.19 

Alaska's value is no surprise, but Michigan's position 

as the state with the second highest value (112) may be. 

This result is probably more attributable to the strength of 

the union movement in the state than to the cost of living. 

Whether earnings are high in Michigan because of the in- fluence of unions or the cost of living is not important for 

purposes of the present analysis, however. The index of 

unit labor costs indicates that the costs of compensation 

for the public employees of state and local governments in 

the state are likely to be well above the national average. 

Another Surprise maybe Hawaii, with an index value of 

%. Conventional wisdom (contirrned by BLS estimates and 

a number of studies in the 1970s) has long identified Hawaii 

as the state with a cost of living second only to that of Alaska.20 Two obsemtions are in order. First, it maybe that the 

cost of living Hawaii is not as high as earlier estimates indicated because the market basket of goods and services used 

by the BLS in preparing the estimates for the family budget 

series for Honolulu failed to account adequately for the special characteristics of the life style in the state. The more important reason for the plausibility of the estimate that 

average earnings in Hawaii are only % percent of the U.S. 

average, however, is that, as noted earlier, the nonmonetary 

benefits of living and working in the state make people willing to accept lower real cash incomes than they would demand for comparable work elsewhere. 

Estimatlng a UnR-Input Cost Index 

As mentioned above, the information necessary to estimate the variability of unit costs among the states for inputs other than labor is not available. Nonetheless, the 

index of unit labor costs can be used to calculate an overall 

input-cost index on the assumption that all nonlabor costs 

are uniform throughout the nation. The key issue in computing this index is the proportion of direct general expenditures accounted for by employee compensation.21 

The foundation for the effort to determine this proportion is the estimates of state and lccal government payrolls 

published annually by the Bureau of the Census. The estimates for October 1986 by function appear in the first column of able C-4. As noted earlier, the October numbers 

must be annualized to put them on a basis comparable with 

In his letter to the author, Brad Piem okm that this estimate 

overstates the relative level of earnings in Alaska because 1979 

, . , was just after the %wAlaska pipeline was com- pleted and earnings in the entire economy were grossly 

inflated. The 1990 census will undoubtedly yield more 

representative data. 

*'See the review of studies by Barro and Grasberger, in Whitman. This view impelled the Congress in 1976 to authorize a 

special supplement to the federal Revenue Sharing payments 

for which Alaska and Hawaii qualified under the general for- mulas. The supplement was repealed in 1980. 

21 It is, of course, the variability in this proportion from function 

to function that makes this effort necessary. If the proportion 

were the same for all functions, the index of unit labor costs 

wuld be identical to the overall index calculated in this section. 

the Census estimates of direct general expenditures. This is 

accomplished by multiplying the monthly payrolls for instructional employees in education and all employees in nat- ural resources by 10. The assumption underlying this 

procedure is that, on average, these employees are paid on a 

ten-month basis and that October is one of the ten months. 

The payrolls for all other functions are multiplied by 12. 

A minor problem is that the timing of the payroll in- formation is not as well aligned as it might be with 

state-local fiscal years. In particular, the annualized pay- rolls in column 2 of 'hble C-4 understate fiscal year out- lays in a period of rising spending because October is an 

early month of the typical fiscal year. To bring the two sets 

of data into better alignment, the annualized October 

payrolls are projected to January 1987, which is the ap- proximate midpoint of the 1986-87fiscal year for stateand 

local governments. The rate of growth used for the projec- tion is the increase in total direct general expenditures from 

1985-86 to 1986-87: slightly more than 8.3 percent. The quar- terly compounding rate implicit in that rise (2.015 percent) is 

used for the projections, which appear in column 3. 

The resulting ratios of payroll costs to direct general 

expenditures are shown in column 6 of Thble C-4. The 

overall ratio is slightly under 39percent. The range is from 

zero percent for interest on general debt to 84 percent for 

social insurance administration. 

The expenditures of state and local governments for 

employee compensation include more than the outlays classified in the Bureau of the Census accounts as payrolls. As 

noted above, payroll outlays are roughly equivalent to the 

current money eamhgs of state-local employees. As such, 

they do not include the current expenditures by state and local governments for such labor costs as: 

rn 

life insurance; 

w health and hospital insurance; 

rn unemployment insurance; 

rn employee retirement plans; 

rn federal Social Security taxes; 

uniform allowances; 

rn bonuses; and 

rn severance pay. 

The most recent available report by the Bureau of the 

Census on the costs incurred by the states and localities 

for these purposes estimates that they amount to rough1 

This translates to roughly Bpercent of payrolls (0.2210.78 

= 0.28). Tmble C-4 indicates that payrolls account for 39 

workers compensation or disability insurance; 

22 percent of total costs for employee compensation. 22; 

22 U.S. Department of Commerce, Bureau of the Census, 1982 

Censusof Governments, Volume 3, Public Employment, No. 3, 

Compendium of Public Employment (Supplement) (Washing- ton, DC, 1985), p. viii. This estimate includes only a portion of 

the costs of employees' paid vacation and sick leave. The Cost 

of leave used by employees during the October payroll period 

on which the Census estimates is based is included in gross 

payroll. Leave accrued but not paid is a liability of a govern- ment from a balance-sheet perspective, but not a current ex- penditure. Hence the liability is not a currently paid labor cost 

and is not recorded as a direct general expenditure. 

100 Advisory Conlmission on Intergovernmental Relations 
Table C4 

Payrolls of State and Local Governments, by Function, October 1986 

Related to Direct General Expenditures, by Function, 1986.87 

(dollar amounts in millions) 

Annual Payroll as Pms Direct Percentage of Direct 

October General 

Function 1986 October January 1987 Expenditures October January 1987 

(1) (2) (3) (4) (5) (6) 

General Functions, Total $22,095 $248,015 $253,012 $653,608 37.9% 38.7% 

Education 

Higher Education 31,120 31,747 60,m 51.7 527 

Elementary and Secondary Schools 90,316 92,136 156,782 57.6 58.8 

Local Libraries 119 1,428 1,457 3,274 43.6 44.5 

Other Education 187 2,244 2,289 9,636 23.3 23.8 

Public Welfare 677 8,124 8,288 80,090 10.1 10.3 

Hospitals 1,737 20,844 21,264 40,108 52.0 53.0 

Health 499 5,988 6,109 16,864 35.5 36.2 

Social Insurance Administration 197 2,364 2,412 2,88 1 82 1 83.7 

Instructional Employees 1,426 14,260 

Other Employees 1,405 16,860 

Other Employees 1,848 22,176 

Instructional Employees 6,814 68,140 

Social Services and Income Maintenance 

Transportation 

Highways 956 11,472 11,703 52,199 22.0 22.4 

Air Transportation 56 672 686 4,876 13.8 14.1 

Water Transportation 29 348 355 1,744 20.0 20.4 

Parking Facilities n.a. - - 757 - - 

Transit Subsidies n.a. - - 244 - - 

Police Protection 1,410 16,920 17,261 24,684 68.5 69.9 

Fire Protection 603 7,236 7,382 10,9 10 66.3 67.7 

8,556 8,728 16,637 51.4 525 - - 4,420 

Correction 713 

Protective Inspection and Regulation n.a. - 

Natural Resources 322 3,2m 3,285 9,738 33.1 33.7 

Parks and Recreation 306 3,672 3,746 10,978 33.4 34.1 

Housing and Community Development 177 2,124 2,167 11,766 18.1 18.4 

Sewerage 205 5460 2,5 10 14,862 16.6 16.9 

Sanitation Other than Sewerage 189 2,268 2,314 6,462 35.1 35.8 

Governmental Administration 1,434 17,208 17,555 34,896 49.3 50.3 

Interest on General Debt n.a. - - 41,816 - - 

General Expenditure, N.E.C. n.a - - 36,746 - - 

All Other and Unallocable. 786 9,43 1 9,621 - - - 

Exhibit: 

Local Utilities 959 11,508 11,740 65,509 17.6 17.9 

245 2,931 8.2 8.4 

Insurance Trust n.a. - - 50,815 - - 

Total All Other and Unallocable 822 - - - - 

Public Safety 

- 

Environment and Housing 

State Liquor Stores 20 240 

n.a.-not available. 

A portion of “total all other and unallocable” payrolls ($822 million) proportionate to published payroll amounts shown in column 1 is allocated to 

general functions. For total direct general expenditures, this category includes amounts for the five functions for which payroll estimates are shown as 

not available in column 1. 

Sources: 1 -US. Department of Commerce, Bureau of the Census, Public Employment in 1986 (Washington, DC, 1988), Thble 4. 

2-Column 1 multiplied by 12 except for instructional employees in education and employees in natural resources, in which cases column 1 is 

multiplied by 10. 

3-Assumes one uarter’s growth at the annual rate of increase in the total direct general expenditures of state and local governments from 

1985-86 to 1386-87. 

4-U.S. Department ofCommerce, Bureau of the Census, Government Finces in 1986-87 (Washington, Dc, 1988), Thble 29. 

5 -Column Z/column 4. 

6-Column 3kolumn 4. 

Advisory Commission on Intergovernmental Relations 101 
Table C-5 

Payroll and Total Employee Compensation Costs 

as Percentage of All Direct General Expenditures 

by State and Local Governments, by Function, 

1987 

Employee 

Function Payrolls Compensation 

(1) 

Education 

Primary and secondary 58.8% 

Higher 52.7 

Public welfare 10.0 

Highways 22.4 

Police and corrections 62.9 

Environment and housing 26.1 

Interest on general debt - 

General administration 50.3 

All other 20.2 

Sources: Thble C-4 and see text. 

Health and hospitals 48.1 

75.3% 

67.5 

12.8 

61.6 

28.7 

80.5 

33.4 

64.4 

25.9 

- 

percent of the direct general expenditures of the states 

and localities. It follows that the total costs of employee 

compensation amount to approximately half of all direct 

expenditures (0.39 1.28 = 0.50). Bble C-5 shows the 

ratios of payroll and employee compensation to total direct general expenditures for each of the 10 functional 

categories considered in this report. 

The ratio, r, in column 2 of Bble C-5 for each function can be viewed as the weight to be assigned to the value of a state’s index of labor costs, with the ratio (1-r) the 

weight to be assigned to the uniform index (100 for all 

states) in the calculation of an overall index of the unitinput costs of state and local governments. 

The resulting indices are shown in able C-6. 

102 Advisory Commission on Intergovernmental Relations 
Table C-6 

Input-Cost Indices for Major Functions, 1986-87 

Inout-Cost Index 

Health Police Environ- Interest Govern- All 

Education and and ment on mental Other 

State Index Secondary Higher Welfare tals Highways tions Housing Debt tration turn 

Unit 

Labor 

Cost Primaryand Public Hospi- Correc- and General Adminic ExpendiUnited States 

Alabama 

Alaska 

Arizona 

Arkansas 

California 

Colorado 

Connecticut 

Delaware 

District of Columbia 

Florida 

Georgia 

Hawaii 

Idaho 

Illinois 

Indiana 

Iowa 

Kansas 

Kentucky 

Louisiana 

Maine 

Maryland 

Massachusetts 

Michigan 

Minnesota 

Mississippi 

Missouri 

Montana 

Nebraska 

Nevada 

New Hampshire 

New Jersey 

New Mexico 

New York 

North Carolina 

North Dakota 

Ohio 

Oklahoma 

Oregon 

Pennsylvania 

Rhode Island 

South Carolina 

South Dakota 

Tennessee 

Texas 

Utah 

Vermont 

Virginia 

Washington 

West Virginia 

Wisconsin 

Wyoming 

(1) 

100.0 

90.6 

134.4 

96.8 

85.6 

105.5 

99.6 

108.5 

100.3 

95.6 

90.6 

93.7 

96.0 

85.3 

109.7 

100. 1 

94.3 

94.2 

97.2 

102 1 

77.4 

105.7 

95.6 

111.9 

102.0 

83.7 

95.6 

85.3 

89.1 

97.6 

86.0 

108.1 

88.4 

100.7 

86.6 

86.4 

103.9 

94.0 

97.9 

99.6 

92.6 

86.8 

77.1 

91.6 

102.3 

94.7 

79.0 

97.7 

1029 

93.4 

98.4 

95.8 

(2) 

100.0 

92.9 

125.9 

97.6 

89.1 

104.2 

99.7 

106.4 

100.2 

96.7 

92.9 

95.2 

97.0 

88.9 

107.3 

100.1 

95.7 

95.7 

97.9 

101.6 

83.0 

104.3 

96.7 

109.0 

101.5 

87.7 

96.7 

88.9 

91.8 

98.2 

89.5 

106.1 

91.3 

100.5 

89.9 

89.8 

102.9 

95.5 

98.4 

99.7 

94.5 

90.0 

82.8 

93.6 

101.7 

96.0 

84.2 

98.3 

102.2 

95.1 

98.8 

96.8 

(3) 

100.0 

93.6 

123.2 

97.8 

90.2 

103.7 

99.8 

105.7 

100.2 

97.0 

93.6 

95.7 

97.3 

90.1 

106.6 

100. 1 

96.2 

96.1 

98.1 

101.4 

84.8 

103.8 

97.0 

108.1 

101.4 

89.0 

97.1 

90.1 

92.6 

98.4 

90.5 

105.5 

92.2 

100.5 

91.0 

90.8 

102.6 

96.0 

98.6 

99.7 

95.0 

91.1 

84.5 

94.3 

101.5 

96.4 

85.8 

98.4 

102.0 

95.6 

98.9 

97.2 

(4) 

100.0 

98.8 

104.4 

99.6 

98.2 

100.7 

100.0 

101.1 

100.0 

99.4 

98.8 

99.2 

99.5 

98.1 

101.2 

100.0 

99.3 

99.3 

99.6 

100.3 

97.1 

100.7 

99.4 

101.5 

100.3 

97.9 

99.4 

98.1 

98.6 

99.7 

98.2 

101.0 

98.5 

100. 1 

98.3 

98.3 

100.5 

99.2 

99.7 

100.0 

99.1 

98.3 

97.1 

98.9 

100.3 

99.3 

97.3 

99.7 

100.4 

99.2 

99.8 

99.5 

(5) 

100.0 

94.2 

121.2 

98.0 

91.1 

103.4 

99.8 

105.2 

100.2 

97.3 

94.2 

96.1 

97.5 

91.0 

106.0 

100. 1 

96.5 

96.5 

98.3 

101.3 

86.1 

103.5 

97.3 

107.3 

101.2 

90.0 

97.3 

90.9 

93.3 

98.5 

91.4 

105.0 

92.9 

100.4 

91.8 

91.6 

102.4 

96.3 

98.7 

99.8 

95.5 

91.9 

85.9 

94.8 

101.4 

96.8 

87.1 

98.6 

101.8 

96.0 

99.0 

97.4 

(6) 

100.0 

97.3 

109.9 

99.1 

95.9 

101.6 

99.9 

102.4 

100. 1 

98.7 

97.3 

98.2 

98.9 

95.8 

102.8 

100.0 

98.4 

98.3 

99.2 

100.6 

93.5 

101.6 

98.7 

103.4 

100.6 

95.3 

98.7 

95.8 

96.9 

99.3 

96.0 

102.3 

96.7 

100.2 

96.2 

96.1 

101.1 

98.3 

99.4 

99.9 

97.9 

96.2 

93.4 

97.6 

100.6 

98.5 

94.0 

99.3 

100.8 

98.1 

99.5 

98.8 

(7) 

100.0 

92.4 

127.7 

97.4 

88.4 

104.5 

99.7 

106.8 

100.3 

96.5 

924 

94.9 

96.8 

88.2 

107.8 

100. 1 

95.4 

95.4 

97.7 

101.7 

81.8 

104.6 

96.5 

109.6 

101.6 

86.9 

96.5 

88.2 

91.2 

98.1 

88.7 

106.5 

90.7 

100.6 

89.2 

89.1 

103.1 

95.2 

98.3 

99.7 

94.1 

89.4 

81.6 

93.2 

101.8 

95.8 

83.1 

98.1 

1024 

94.7 

98.7 

96.6 

(8) 

100.0 

96.9 

111.5 

98.9 

95.2 

101.8 

99.9 

1028 

100. 1 

98.5 

96.9 

97.9 

98.7 

95.1 

103.3 

100.0 

98.1 

98.1 

99.1 

100.7 

925 

101.9 

98.5 

104.0 

100.7 

94.6 

98.5 

95.1 

96.3 

99.2 

95.3 

1027 

96.1 

100.2 

95.5 

95.5 

101.3 

98.0 

99.3 

99.9 

97.5 

95.6 

924 

97.2 

100.8 

98.2 

93.0 

99.2 

101.0 

97.8 

99.5 

98.6 

(9) 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

100.0 

(10) 

100.0 

93.9 

122.1 

97.9 

90.7 

103.6 

99.8 

105.5 

100.2 

97.2 

93.9 

95.9 

97.4 

90.5 

106.3 

100. 1 

96.3 

96.3 

98.2 

101.4 

85.5 

103.6 

97.2 

107.7 

101.3 

89.5 

97.2 

90.5 

93.0 

98.5 

91.0 

105.2 

92.6 

100.5 

91.4 

91.3 

102.5 

96.2 

98.7 

99.8 

95.3 

91.5 

85.3 

94.6 

101.4 

96.6 

86.5 

98.5 

101.9 

95.8 

99.0 

97.3 

(11) 

100.0 

97.6 

108.9 

99.2 

96.3 

101.4 

99.9 

102.2 

100. 1 

98.9 

97.6 

98.4 

99.0 

96.2 

102.5 

100.0 

98.5 

98.5 

99.3 

100.6 

94.2 

101.5 

98.9 

103.1 

100.5 

95.8 

98.9 

96.2 

97.2 

99.4 

96.4 

102.1 

97.0 

100.2 

96.5 

96.5 

101.0 

98.5 

99.5 

99.9 

98.1 

96.6 

94.1 

97.8 

100.6 

98.6 

94.6 

99.4 

100.8 

98.3 

99.6 

98.9 

Note: 

Sources: ’Ihbles C-3 and C-5. 

Thevalue of a state’s inputcost index for a given function is thevalue of the state’s unit-laborcost index multiplied by the U.S. average ratio of 

employment costs to total direct eneral expenditures for the function (r) plus the quantity (1 - r) multiplied by 100. The ratio r for each 

function appears in column 2 of kble C-5. 

Advisory Commission on Intergovernmental Relations 103 
104 Advisory Commission on Intergovernmental Relations 
Technical Discussion of the Representative 

to the Measurement of Fiscal Capacity and 

with Export-Adjusted Income and Regression 

The fiscal system of a state is horizontally balanced 

when the fiscal capacity of each local government is 

adequate to enable it to provide some specified levels of 

the services for which it is responsible without excessive 

tax rates.l Another way of saying the same thing is that 

horizontal balance exists when disparities in the fiscal 

capacities of local governments do not exceed some 

reasonably acceptable levels. For purposes of this discus- sion, fiscal capacity is defined as the potential ability of a 

local government to raise revenue from its own sources 

relative to the costs of its service responsibilities (fiscal 

needs), with ap ropriate allowance for revenue the 

The levels of services that are the reference standard, 

or the criterion of fiscal need, are a matter of value 

judgment within a state. In one state, they may be 

minimally acceptable levels. In another, the specified 

levels may be the average for all localities in the state, or 

some fraction or multiple (say, 1.25) of the average. 

The definition of “excessive” tax rates is also a matter 

that policymakers in a state must decide. As with service 

levels, the criteriafor tax rates can be expressed in relative 

or absolute terms-for example, in relation to the average 

of rates for all localities in the state, or by reference to the 

tax rates prevailing in neighboring states. 

The constitutions or statutes of two of the great federal 

nations of the world include definitions of standards that 

bear a strong resemblance to the concept of horizontal 

balance outlined here. The constitution of Canada 

provides that horizontal balance (as the condition is 

referred above) exists when 

. . . provincial governments have sufficient 

revenues to provide reasonably comparable 

levels of public services at reasonably compara- bie levels of taxation. 

locality receives P rom other governments. 

For convenience of exposition, the discussion in this appendix 

relates to the finances of local governments in a state. With a few 

exceptions, the points made apply with equal validity in analytical 

comparisons of state-loml fiscal systems among the states. 

’Subsection (2), Section 36 of Part I11 of the Constitution Act, 

1982, quoted by Thomas J. Courchene, Equalization Payments: 

Past, Present and Future, Federal Provincial Relations Series, 

Special Research Report (Ottawa: Ontario Economic Coun- cil, 1984), p. 3. 

Appendix D 

Approaches 

Comparison 

Approaches 

In the case of Australia, Section 13(3) of the States 

(Personal Income ’Itur Sharing) Amendment Act, 1978, 

defines horizontal balance as a situation in which each 

state in the Commonwealth would be able 

. . . to provide, without imposing taxes and charges 

at levels appreciably different from the levels of 

taxes and charges imposed by the other States, 

government serviCes at standards not appreciably 

different from the standards of the overnment 

The finances of a particular local government can be 

services provided by the other States. B 

said to be in balance when: 

where 

ENi = ORRAi + F4 + SA, (1) 

ENi (expenditure need) is the total cost to the ith local 

government of providing a specified level of 

public services, 

ORRAi (own revenue-raising ability) is the total 

revenue local government i could raise from its 

own sources if it implemented a specified 

revenue system, 

FAi is the total amount of federal aid actuallyreceived 

by the ith local government, and 

SA; is the total amount of fiscal assistance actually 

received by the ith locality from its state 

government. 

This concept of balance can be distinguished from the 

actual status of a local government’s budget, which is balanced when 

(2) 

where 

AEi is the total of the actual expenditures by local 

AORi is the total revenue the local government 

AEi = AORj + FAj + SAj 

government i, and 

actually raises from its own sources. 

3Commonwealth Grants Commission, Report on Slate Tm 

Sharing Entitlements, 1981: Main Report (Canberra: Australian 

Government Publishing Services, 198l), p. 18. 

Advisory Commission on intergovernmental Relations 105 
For all local governments in the state as a group, 

ZENi= ZAEi (3) 

(4) 

and 

ZORRAi = ZcAEi - ZFA, - ZSAi 

’Lb focus attention on the issue of horizontal balance, 

local governments collectively are assumed to be operat- ing with balanced budgets, that is: 

CAE$ = CAORi + ZFAi + ZSA, 

It follows that, for all local governments as a group, 

(5) 

ZENi ZORW + ZFA, + ZSA, (6) 

This appendix compares the representative ap- proaches to the measurement of own revenue-raising 

ability and public service costs with the export-adjusted 

income approach to revenue-raising ability and with 

various methods that rely on regression analysis to amve 

at estimates of relative expenditure needs. 

The Representative Approaches 

The “representative” approaches to expenditure need 

and own revenue-raising ability offer operational defiitions 

of 44w~ed” levels of need and own re~enue.~ 

The representative expenditure approach yields 

estimates of what it would cost each local government to 

provide the statewide average (representative) level of 

each public service for which local authorities in the state 

are responsible. That is, the total expenditure need of the 

ith local government is defined as 

ENi = Wa-1 WbwLbi + s.. + KWLni (7) 

where Wa is the statewide average (representative) cost per 

unit of workload of providing service a and wL,i is the 

workload of local government i for service a. 

In an analogous manner, the representative revenue 

approach defines the total own-revenue-raising ability of 

the ith local government as 

ORRAi = taBai + fbBbi + e. + f” hi (8) 

where f. is the statewide average (representative) rate 

for tax (or other revenue source) a and Bai is the base of 

tax a that is accessible to taxation by local government i. 

The Export-Adjusted Income Approach 

to the Measurement 

of Own-Revenue-Raising Ability 

The representative approach is not the only method 

available for estimating revenue-raising p~tential.~ The 

In addition to the present report, see Advisory Commission on 

Intergovernmental Relations, 1988 State Fiscal Capacity and 

Effort (Washington, DC, 1989). 

For a general discussion of the options for measurement of 

revenue-raising ability, see U.S. Department of the Treasury, 

Office of State and Local Finance, Fedeml-State-Local Fivcal 

Re1ations:Report to the President and the Congress (Washington, 

DC, 1985), Chapter VIII. The most useful recent discussion of 

an export-adjusted income approach appears in Helen E Ladd 

and John Y inger, America’s Ailing Cities: Fiscal Health and the 

Design of Urban Policy (Baltimore: Johns Hopkins University 

Press, 1989), pp. 45-77. 

chief alternative to the representative method, the exportadjusted income approach, defines the specified level of 

own revenue as the yield of a revenue system with two 

basic characteristics: (1) it imposes a standard burden on 

the residents of each local government, defined as a 

uniform percentage of their total income; and (2) it 

maximizes the taxes collected from nonresidents, that is, 

the tax yields that are “exported.” 

Under this approach, the own-revenue-raising ability 

of the ith local government can be written as 

where 

ORRA, = K*Yi (1 + ei) (9) 

K* is a standard tax burden on the income of the 

residents of each local government, 

Yi is the total income of the residents of local 

government i, and 

q is amount of taxes collected by the ith local 

government from nonresidents per dollar of 

taxes paid by the government’s residents. 

Equation 9 can be shown to be equivalent to the representative definition of own-revenue-raising capacity in 

the simple case in which local governments have only one 

revenue source (a) at their disposal. In this case, the defi- nition of representative revenue-raising capacity can be 

written as a special case of equation 8: 

ORRAi = fa Bai (10) 

The base of tax a accessible to local government i, B,i, can 

be segmented between the base attniutable to residents 

(R) and the base attributable to nonresidents (E): 

Substituting for Bai in equation 10, 

ORRAi = EaB; + faBz (11) 

The total own-revenue-raising capacity of local government i is the sum of the yield of its tax at the 

representative rate, f., that would be paid by residents 

and the yield that would be exported to nonresidents. 

In the export-adjusted income approach, K* is 

defined as the amount of tax paid by residents as a 

proportion of their total income, that is, 

This expression can be rewritten as 

faBz = K*Yi (13) 

and as 

Substituting for faBs in equation 11 from equation 13, 

ORRAi = K’Yil + faB: (15) 

106 Advisory Commission on lntergovemmental Relations 
Substituting for fa in equation 15 from equation 14 yields 

(16) Kay. 

Bai 

ORRAi = K*Yi + (+)B: 

Rewriting: 

Factoring, 

In the export-adjusted income approach, B$/B: = epi . Therefore, 

ORRAi = K*Yi(l + eai) (19) 

which is equivalent to equation 9. 

When local governments are allowed to raise revenues 

from more than one source, however, the representative 

and the export-adjusted-income approaches are no longer 

equivalent. This can be seen by considering a system in 

which localities have access to two revenue sources, a and 

b. From equation 8, the representative approach defines 

the own revenue-raising potential of the ith local 

government as 

ORRAi = faBai + fbBbi (20) 

In the export-adjusted-income approach, the expres- sion for the own revenue-raising potential of government 

i is considerably more complicated: 

Subject to the constraint that 

that is, that the total taxes paid py residents of the locality 

equal the standard burden (K Yi) . Unfortunately, the tax rates of the local government 

cannot be identified by observation-as in the representa- tive approach, where the statewide average effective rate 

is used. Rather, the rate for each tax must be identified 

that maximizes the revenue collected from nonresidents, 

subject to the burden-on-residents constraint. The rates 

that satisfy this requirement are likely to differ from 

government to government because the export ratios for 

the taxes depend on the nature and mix of activity in a 

local economy. Export ratios will not be the same, for 

example, for a community with a regional shopping mall, a 

community with a major factory, and a bedroom suburb. 

An important consideration in identifying the revenue-maximizing rates is that the sizes of the bases 

themselves can be expected to be influenced by the tax rates 

selected. This is, of course, a problem with the representative approach as well. 

Theoretically, with enough reliable information, the 

identification of the revenue-maximizing rates and the 

yields they would generate would be a straightforward 

maximization exercise. In fact, the necessary estimates of 

the responsiveness of bases to tax rates are not available, 

so the approach cannot be implemented without major 

simplifying assumptions.6 These assumptions may, in fact, 

make the export-adjusted-income approach essentially 

equivalent to the representative approach. 

The method actually used by Ladd and Yinger 

focuses on the estimation of an overall export ratio for 

each city. Given that ratio, the own-revenue-raising ability of 

a government can be calculated directly from the total 

income of the jurisdiction’s residents, using equation 9. 

The overall export ratio for a city is calculated as the 

weighted average of separate estimates for three “standard‘‘ taxes: a real property tax, a general sales tax, and an 

earnings tax. The respective weights are 50 percent, 25 

percent, and 25 percent. 

The authors offer no explanation for their choice of 

these weights. As Xible D-1 shows, the weights are 

substantially at variance with the actual reliance of local 

governments on the major sources of own revenue. The 

magnitude of the variance raises serious questions about the 

results. Of course, Ladd and Yinger do not purport to be 

using a “representative” approach, so the discrepancy 

between actual practice and their weights cannot be faulted 

on the ground that the weights are not representative. The 

alternative, however, is a normative perspective, and the 

authors do not indicate that this is their approach. Hence, 

why those weights? 

Setting aside the issue of the rationale for the 

weights, the methods used to derive the individual export 

ratios deserve brief consideration. 

Property Tax. From the literature, Ladd and Yinger 

postulate assumptions about the incidence among eco- nomic groups of a tax on each of eight classes of property. 

Owner-occupied housitg 100 percent on owners. 

Table D-1 

Sources of the Own General Revenues 

of Local Governments, 

Fiscal Year 1981-82 

Revenue Source 

Weights 

Used All 

byLadd Local Cities 

and Govern- Over 

Mnger ments 200,000 

(1) (2) (3) 

Property Tax 50.0 48.3 30.1 

Total Own General Revenue 100.0% 100.0% 100.0% 

Individual Income Tax 25.0 3.1 14.0 

General Sales Tax 25.0 6.3 11.7 

All Other 42.3 44.2 

Sources: U.S. Department of Commerce, Bureau of the Census, Governmental Fmces in 1981-82 (Washington, DC, 1983), lsble 

4, and Ciw Government Fnances in 1981-82 (1983). Table 2; 

and Ladd and Yinger, America‘s Ailing Cities, p. 48. 

See Ladd and Yinger, America’s Ailing Cities, pp. 70 and 71. 

Advisory Commission on Intergovernmental Relations 107 
m 

rn 

Rental housing, single family: not identified. 

Rental housing, 2-4 Unit sbuctum: not identified. 

Rentai housing, 5 or more unit structum: 80 percent 

on renters, 20 percent on landowners. 

Commercial, real and personal: 42 percent to 

consumers, 38percent to workers, and 20percent 

to landowners. 

m Industrial, real and personal: 14 percent to 

consumers, 75 percent to workers, and 11 percent 

to landowners. 

rn Vaant, acreage, and other: not identified. 

State-assessed: not identified. 

Given these assumptions, the authors develop esti- mates separately for each city of the proportion of the in- dividuals in each group that lives outside of the city. 

Owner-occupiers and renters obviously live in the city, for 

example. Consumers and workers are apportioned on the 

basis of such factors as the size of a city relative to its met- ropolitan area and the share of wages and salaries paid to 

commuters. 

The incidence assumptions and location estimates 

are then combined to calculate the proportion exported 

of each city’s actual property tax base in each of the 

eight classes. The ratio of the sum of the bases exported 

for all eight classes to the aggregate “resident” base is 

the city’s export ratio for the standard property tax. 

Ladd and Yinger estimate that the average export ratio 

for 78 major cities in 1982 was 0.52. In other words, a 

standard property tax would collect 52 cents from 

nonresidents for every $1.00 paid by city residents. 

Sales Tax. Ladd and Yinger assume that local sales 

taxes are shifted entirely to consumers in higher prices. 

Therefore, all that is necessary to calculate the export ra- tio is an estimate of the proportion of total retail sales in a 

city made to purchasers other than residents. 

The proportion is derived by estimating total retail 

spending by residents as the sum of three, separately 

derived components. The components are goods bought 

in food and drug stores, food and drink consumed in 

restaurants, and all other taxable items. The estimates are 

calculated by multiplying the total money income of a 

city’s residents by estimates of their average propensities 

to consume each of the three categories of goods and 

services. The propensities are ratios of total retail sales in 

each SMSA to total income in the SMSA, adjusted in 

undisclosed ways 

. . . (using coefficients estimated from a multivariate regression equation) for differences 

between city and SMSA income and purchases by 

tourists.’ 

The undisclosed adjustments are the key to the 

analysis because observed retail sales in the numerator 

of the propensity ratio presumably include purchases by 

nonresidents. This being the case, the undisclosed adjust- ments are the key to the estimating process. It seems a bit 

strange to suggest that the propensities are used to estimate 

’Ibid., p. 74. 

108 Advisory Chimission on Intergovernmental Relations 

the split between resident and nonresident retail sales, when 

the process of estimating the propensities themselves 

apparently embodies the method used to partition resident 

from nonresident purchases. 

In view of this, Ladd’s and Yinger’s concern that the 

estimates of export ratios for the standard sales tax may be 

too low because the “approach ignores the possibility that 

city residents might shop outside the city” seems genuinely 

curious. If the approach in fact assumes that city residents 

shop only in the city, the export ratio would indeed be 

underestimated, seriously. Unfortunately, in the absence of 

information on the procedures actually used by the authors 

to estimate resident propensities to consume, it is impossible 

to evaluate the problem. 

Ladd and Yinger estimate an average export ratio for 

the standard sales tax in their 78 cities in 1982 of 0.21, less 

than half that for the property tax. 

Earnings Tax. The base of the standard earnings tax is 

all employee earnings in a city-by nonresidents as well as 

residents-and the full burden of the tax is assumed to be 

borne by the worker. As estimates of earnings in central 

cities by nonresidents are available from the decennial 

census, the ratio of these estimates to total earnings in a 

city is the desired export ratio for the earnings tax. 

The average export ratio for the standard earnings tax 

in the 78 cities studied by Ladd and Yinger is 1.27-well 

over $1.00 would be collected from nonresidents for each 

$1.00 of this tax collected from residents. 

Regression-Based Approaches 

to the Estimation of Public Service Costs 

State and local government spending varies from 

state to state and among localities for a wide range of 

reasons extending from differences in voter preferences 

to differences in the incidence of poverty. A substantial 

technical literature has developed since World War I1 

applying regression analysis in an attempt to identify the 

relative importance of the many “determinants” of the 

variation in state-local spending. 

The early studies tended to be naive, correlationhunting exercises motivated by little more than a desire to 

identify the variables that “explain” relative levels of state 

and local expenditures. By the 1970s, the focus had 

narrowed to an effort to estimate the “stimulative” effects 

of grants-in-aid on the spending of recipient governments. The usual method of analysis was a multiple 

regression with one of the independent variables the level 

of funding for the grant program whose impact was to be 

estimated. As for the quality of this work, it is interesting 

to note that, as recently as 1977, Gramlich was con- strained to point up the 

. . . various conceptual and technical problems 

with the studies-lack of an underlying theory of 

the behavior of state and local governments, lack 

of any attempt to distinguish the different effects 

of different typesof grants, lack of any attempt to 

deal with the possible simultaneous causation of 

grants and expenditures.* 

Edward M. Gramlich, “Intergovernmental Grants: A Review 

of the Empirical Literature,” in Wallace E. Oates (ed.). The 

Political Economy of Fiscal Fedemlism (Lexington, Massachu- setts: D.C. Heath Co., Lexington Books, 1977), p. 219. 
Auten’s Estimates of Local Expenditure Needs 

In New York 

In an article published in 1974 but not included in 

Gramlich’s review, however, Auten ushered in a generation of more sophisticated analysis that has re nded to 

~~~~~~“f3” ~kzd~ 

on consumer utility maximization theory, Auten postu- lates a model in which local public expenditures are a 

function of three classes of factors: (1) revenue-raising 

ability (including individual income, wealth, ability to ex- port taxes, and intergovernmental payments); (2) cost 

factors (the concentration of poverty, population density, 

and other socio-demographic variables); and (3) community preferences for public services. The resulting expenditure function has this general form: 

e = f (a, c, d) (22) 

where: 

e is per capita local expenditures, 

a is a vector of variables relating to revenue-raising 

c is a vector of socioeconomic (need) factors, and 

d is tastes and preferences for public services. 

Auten estimates this expenditure function separately 

for nine major functional categories of local government 

spending using multiple regression.1° The coefficients of 

the a variables indicate the average response of expendi- tures to differences in revenue-raising ability.ll The a 

variables are the equivalent of an individual’s income in 

the standard theory of consumer demand-that is, the 

quantity of a good or service demanded is hypothesized to 

increase, other things equal, as income rises. 

The coefficients of the c variables show the way per 

capita spending by the sample governments responds, on 

average, to differences in socioeconomic and demographic 

conditions. The d variable is assumed to be subsumed in the 

standard error-term of the regression. That is, Auten’s 

model assumes that differences in expenditures not directly 

associated with the a and cvariables are attributable to voter 

ability, 

9Gerald E. Auten, “The Distribution of Revenue Sharing 

Funds and Local Public Expenditure Needs,” Public Finance 

Quarten‘y 2 (July 1974): 32-75 

‘OThe dependent variables in the regressions are the total 

outlays by all local governments providing services to a 

representative sample of 104 school district areas in New York 

State. The independent variables are fiicaI/emnomic/demographic attributes of the geographic areas of the districts. 

l1 Auten actually uses what might be characterized as a prepack- aged vedor of Mliables measuring revenue-raising ability, that is, 

he uses a measufe developed for another study. The measure b a 

weighted avemge of median family income and the market values 

of five classes of real property-residential, commercial, indus- trial, seasonal, and other. The weights are dented from 

regression analysis in which the income and property values an? 

the independent variables and the dependent variable is the total 

per capita revenues from ovh~ sourax of all local governments 

serving each school district area 

tastes and preferences. Hence the model does not include 

explicit variables reflecting public preferences. 

The coefficient of each independent variable in a 

regression of this type is an estimate of the response of the 

dependent variable (local expenditures per capita) to a 

unit change in the independent variable if there were no 

cdange any offhe ofher w~%ks ?Z& means fkaf 

estimates of the expenditure “needs” of each community 

can be calculated by using the regression equation to 

predict per capita expenditures with the actual values of 

the c variables and the mean values of the a variabIes. Use 

of the mean values of the a variables controls for 

differences in revenue-raising ability (as a factor influencing 

the quantity of public services demanded, not as a factor 

affecting need). 

Auten retains in his regressions all c variables that are 

significantly different from zero at the 10 percent level. 

Unfortunately, he does not display the t-values, so a more 

rigorous criterion cannot be applied in the following 

listing of the c variables in each of his regressions: 

General government: population growth rate, 

proportion of the total market value of real 

property accounted for by seasonal and resort 

property. 

Public safety: population per square mile in the 

county in which the district is located, population 

per square mile in the district, proportion of the 

total market value of real property accounted for by 

commercial property, crime rate, old housing as 

proportion of the total, population growth rate. 

Highways: square miles of district area, area of 

the county in which the district is located, 

population per square mile in the district, 

population density of the district squared, pro- portions of the total market value of real 

property accounted for by (a) commercial and (b) 

seasonal and resort property. 

Sanitation: proportion of the total market value 

of real property accounted for by industrial and 

commercial property, population per quare mile 

in the district, population density of the district 

squared, proportion of the total market value of 

real property accounted for by residential property. 

Health: AFDC children as percentage of total 

population, square miles of district area, propor- tion of the population of the county in which the 

district is located that lives in urban areas. 

Recreation: population per square mile in the 

county in which the district is located, population 

growth rate, proportion of the total market value 

of real property accounted for by seasonal and 

resort property. 

Welfare: proportion of the population of the 

county in which the district is located that lives in 

urban areas, low-income families as percentage 

of total, proportion of adult residents not having 

completed high school. 

Schools: number of low-achievement pupils as 

percentage of total, public school enrollment as 

proportion of total population. 

Advisory Commission on Intergovernmental Relations 109 
Other: population growth rate, population per 

square mile in the district, population density of 

the district squared. 

The incompleteness of Auten’s conceptual framework is exemplified by his failure even to mention differences in the unit prices of inputs as factors in the variation in 

spending needs among localities. Another problem is his 

treatment of tastes and preferences. As Fastrup observes: 

By modelling [these considerations] . . . as part of 

the error term, this approach biases the coefficients of the socio-demographic variables to the 

extent the are correlatedwith the excluded taste 

variables. 72 

Bradbury, Ladd, Perrault, Reschovsky, and Yinger 

on Local Government Needs in Massachusetts 

These problems with Auten’s approach are significantly clarified in a 1984 article by Bradbury and 

associates.13 They begin by observing that the literature 

on the determinants of state and local expenditures 

assumes that voters are concerned about budgetary 

outlays. In fact, they remind us that-as Bradford, Malt, 

and Oates had pointed out a decade and a half earlierl4-voters’ primary concerns rekite to levels of services, 

or ‘Tial’’ outputs: the safety of the streets, for example, and 

the quality of the air. 

The levels of public services actually delivered depend, 

in part, on what public employees actually do-that is, on 

the number of police patrols and the number of smokestack 

emission inspections. These activities can be characterized 

as “intermediate” outputs.15 The cost of these intermediate 

outputs depends, in turn, on the amounts spent for the 

inputs used, the sophistication of the available technology, 

and the efficiency with which the outputs are produced. The 

inputs include police officers and air-quality inspectors, 

communications systems, squad cars, and equipment 

for monitoring smokestack emissions. For a given 

standard of technology and operating efficiency, the 

”Jerry C. Fastrup, “Estimating the Cost of Local Public 

Services,” February 25, 1990, processed, p. 5. 

13Katherine L Bradbury, Helen E Ladd, Mark Perrault, 

Andrew Reschovsky, and John Yinger, “State Aid to Offset 

Fiscal Disparities Acrw Communities,” National Tax Journal 

37 (June 1984): 151-70. 

14David E Bradford, R. A. Malt, and Wallace E. Oates, “The 

Rising Cost of Local Public Services: Some Evidence and 

Reflections,” National Tar Journal 22 (June 1969): 185-202. 

”Bradford et al. refer to these as “direct produced” outputs 

@. 186). 

“The relevant prices in this context are the opportunity costsof 

the inputs, that is, their value in the best alternative 

employment (see Appendix C). The relevant prices are not 

necessarily those actually paid by local officials, for they may 

pay more than the minimum necessary to purchase inputs of 

given quality, perhaps as a result of collective bargaining 

agreements with public employee unions. For studies finding 

significant effects of unionization on the wages of local public 

employees, see Roger W. Schmenner, “The Determination of 

1 10 Advisory Commission on Intergovernmental Relations 

relationship between amounts spent and the intermediate 

outputs depends on the prices paid per unit for the inputs.16 

The final output resulting from a given number of 

police patrols or emissions inspections depends on the 

environment in which the intermediate outputs are 

produced-in which the public employees are working. In 

the cases of public safety and air quality, the important 

aspects of the environment include the proportion of a 

community’s population in age groups with high propensities to commit crimes, the nature of the community’s 

economy, and climatic conditions. 

A given level of public safety requires more-frequentthan-average police patrols, for example, in a community 

with an unusually high proportion of 18-25 year-old 

residents. Achievement of a given standard of air quality 

requires more emissions inspections than average in a 

communitywith a lot of heavy industry, or that frequently 

experiences such climatological phenomena as temperature inversions. 

These two types of variables-the prices of inputs, 

which can be designated as P, and environmental factors 

(C)-can be thought of as the major influences on the 

supply of public services. The next question is what 

variables determine demand. 

The demand for a public service, like that for a 

private good, depends on the price of the service to the 

voter as well as his or her income and preferences. The 

tax price of a public service depends, unlike the 

situation in the market for a private good, on the overall 

revenue-raising ability of the community. The reason is 

that it is the total amount of revenue raised by a given 

taxrate (not just the amount of tax paid by theindividual 

voter-purchaser) that determines how much of a service 

the community can purchase at that tax rate. If the 

service is a pure public good (safe streets and air quality, 

for example), the amount produced is by definition the 

amount available to be consumed by every resident of 

(or visitor to) the community.17 

Overall revenue-raising ability can be characterized as the sum of potential revenue from own sources 

Municipal Employee Wages,” Review of Economics and 

Statistics 55 (February 1973): 83-90; Ronald G. Ehrenberg and 

Gerald S. Goldstein, ‘h Model of Public Sector Wage 

Determination,” Journal of Urban Economics 2 (July 1975): 

222-45; and Orley C. Ashenfelter, “The Effects of Unioniza- tion on Wages in the Public Sector: The Case of Firefighters,” 

Industrial and Labor Relations Review 24 (January 1971): 

191-202; all discussed by Robert €? Inman, “The Fiscal 

Performance of Local Governments: An Interpretative 

Review,” in Peter Mieszkowski and Mahlon Straszheim (eds.), 

Current Issues in Uhun Economics (Baltimore: Johns Hopkins 

University Press, 1979), pp. 302-4. 

If the seMce is not a pure public good, an additional resident or 

visitor reduces the quantity (or quality) of the final service 

available to each consumer. Streets and roads, for example, are 

not pure public goods because as the number of persons using 

them increases they become congested, travel times increase, and 

the quality of the final seMce they provide diminishes. The 

analyses of public services discussed in this appendix essentially 

assume that all the senices under consideration are pu~ public 

goods. Some efforts ha% been made to deal explicitly with the 

congestion problem; see Fastrup, “Estimating the Cmt of Local 

Public Services,” pp. 8-14. 
(V) and actual state and federal aid (A). The income and 

preferences of the voter can be designated as D, fordemand. 

Bken together, the five categories of variables 

identified in the preceding paragraphs constitute the 

simple model estimated for Massachusetts cities and 

towns by Bradbury and her associates: 

The dependent variable (e) is total operatin expenditures 

The model is estimated as a simple linear relationship 

between e and each of 19 independent variables.19 @cause 

of the unavailability of the neceSSafy data, no variable 

representing P is included.) For purposes of discussion, the 

nine environmental-cost variables are especially interesting: 

e = f(V,A,P,C,D) (23) 

per capita, including spending for schools. 9, 

Population density: resident population divided 

by square miles of area; 

Full-time-equivalent pupils (weighted by values 

specified in the major state aid program) per capita; 

Number of crimes reported per 1,ooO inhabitants; 

Fraction of year-round housing units built before 

1940; 

Number of state and federal government em- ployees per capita by place of work; 

Number of employees in trade and services per 

capita; 

Number of employees in manufacturing per 

capita; 

‘*Note that the dependent variable is outlays per capita, not 

some composite measure of service levels. The authors 

concede that their approach 

. . . is apractical compromise not an ideal solution. In 

particular, it provides better estimates of the impact 

of environmental cost factors on spending than on 

local publicservices. (Bradburyet al., StuteAid.. . , 

The approach can hardly be faulted for this compromise. Respectable measures of final outputs are available for very few 

government services. There is, therefore, no practicable alternative to the authors’ assumption that expenditures are a reasonable proxy for service levels. 

I9In addition to 9 C (environmental) variables, the model 

includes 2 variables designed to measure V (own-revenueraising ability): total equalized property tax valuation per 

capita and total actual collections of nonproperty tax revenues 

per capita. (Acrual collections are a questionable measure of 

revenue raising potential.) Both these variables are significantly different from zero at the 1 percent level. The model 

includes two variables each for federal and state aid. The 

coefficients for both state aid variables and for federal 

Revenue Sharing are significant at the 1 percent level; that for 

all other federal aid is not significant at the 5 percent level. 

The model includes two variables intended to reflect voted 

resources and preferences: the pqortion of the resjdent 

population age 65 and older and resident personal income per 

capita The income variable is sigmfhnt at the 1 percent level; 

the elderly variable has the srpected Sign (negatix) but k not 

statistically significant. The last two variables in the model are 

included to reflect the influence of the rate of change in resident 

population; neither variable is sigrdcant at the 5 percent h1. 

p. 155) 

w 

Percentage of resident population with income 

below the poverty line; and 

Local road mileage per registered vehicle. 

Of the nine variables, only the first five turn out to be sign& 

cantly different from zero at the 5 percent level or better. 

Ladd and Yinger on Measurement of the Fiscal 

Health of the Nation’s Cities 

At the time the articleby Bradbury and associates was 

published, three of the authors-Bradbury, Ladd, and 

Yinger-were engaged in a project funded bya grant from 

the US. Department of Housing and Urban Develop- ment that involved considerable refinement of the 

analytical methods used in the Massachusetts analysis. 

Ladd and Yinger continued this work and eventually 

published the results in an important volume discussed 

earlier.20 The Ladd-Yinger study develops estimates of 

“standardized expenditure need” for a sample of 86 

central cities located throughout the nation. These 

estimates are then used in conjunction with estimates of 

revenue-raising ability, discussed earlier in this appendix, 

to arrive at a measure of the “standardized fW health” of 

each of the cities. The estimates are also used, dong with 

data on actual flows of intergovernmental aid, to calculate a 

measure of the “actual” fiscal health of each city. 

In Ladd’s and Y inger’s analysis, 

A city’s standardized fiscal health is the differ- ence between its [own] revenue-raising capacity 

and its standardized expenditure need, expressed 

as a percentage of its capacity.21 

For purposes of the calculation, standardized need is 

set “so that, on average, cities exactly use up their 

revenue-raising capacity.”22 The gaps between own 

revenue-raising ability and need calculated by Ladd and 

Yinger are very similar to those displayed in nble 9 of the 

present report-that is, the estimates of gaps between 

representative expenditures and revenue-raising abiity 

abstracting from federal grants-in-aid. Expressed as a 

percentage of revenue-raising ability (with no account taken 

of federal grants), the gap indicator of fiscal capacity 

presented in Chapter 4 would be roughly equivalent to 

Ladd’s and Yinger’s measure of standardized fiscal health. 

The authors’ measure of actual fiscal health extends 

the analysis to allow for (1) actual amounts of intergovernmental aid received, (2) differences in city service 

responsibilities and revenue-raising authority, and (3) 

differences in the tax burdens imposed by overlying local 

governments and the states. The estimates are scaled and 

calibrated in complex ways that need no discussion here: 

their effect is to ensure that the difference between total 

receipts and expenditure need is zero for the average city. 

For purposes of comparisons among the states-the 

object of the present report-differences in service reAmerica’s Airing Cities. 

Ibid., p. 103. 

22 Ibid., p. 104. 

Advisoly Commission on intergovernmental Relatians 11 1 
responsibilities and revenue-raising authority are immaterial, as discussed in Chapter 2. Moreover, the taxes imposed 

by the only government that overlies the states are 

necessarily uniform throughout the nation. Hence Ladd’s 

and Yinger’s measure of actual fiscal health is quite similar 

to the concept of fiscal capacity used in the present report, 

and the calculation parallels that reported in mle 14. 

Reversing the sign of the gap as it is calculated in 

Chapter 4 and expressing the result as a percentage of 

revenue-raising capacity (measured by the RTS) produces 

an index of the actual health of state-local fiscal systems 

that ranges from -57for Mississippi to + 44for the District. 

of Columbia. The range of values for the index of actual 

fiscal health estimated by Ladd and Yinger for 1982 is 

from -80 for Los Angeles to +56 for Hollywood, 

Florida.23 The significantly wider range of the estimates 

for cities than for the states is consistent with expecta- tions, given the more diversified nature of the economies 

and homogeneity of the socioeconomic characteristics of 

the states as compared with central cities. 

The results of the present report are restated as 

indices of fiscal health in nble D-2 on page 114. The 

comparisons of the indices without and with federal grants 

in columns 7-9 provide some interesting insights into the 

distributive impacts of the federal grant system. The 

health indices of the dozen least healthy state-local fiscal 

systems is improved by federal grants, but there is very 

little apparent pattern in the effect of federal grants on 

the fiscal health of the other states. 

The estimates of standardized expenditure need are 

derived by Ladd and Yinger by estimating by multiple 

regression a model of the determinants of per capita city 

expenditures using data for 1967,1972,1977, and 1982 for 

the 86 cities.24 The analysis produces cost indices for 

three categories of services: fire, police, and general (all 

other). Each index measures a city’s relative cost of 

providing the indicated category of service given its input 

prices and environmental factors, and controlling for differences in service responsibilities, institutional characteristics, and variables of the types V, A, and D, discussed 

above.25 

The value of a city’s cost index for each of the 

categories, weighted by national-average per capita spending 

for the category in 1972 (net of average user fees collected 

231bid., pp. 210-11. 

24Again, as in the analysis by Bradbury et al., the dependent 

variable is per capita spending rather than a measure of final 

output or service levels. As the authors observe: 

The final outputs of city services, such as 

learning and protection from crime and fire, are 

difficult if not impossible to measure. Therefore we 

cannot directly measure the impact of environmental 

factors on the level of final outputs. Nevertheless, we 

can indirectly measure these impacts by analyzing city 

expenditure. (bid., p. 82) 

25The authors refer to this aspect of the analysis as “carefully 

controlling for service responsibilities and service quality” (ibid.). 

Service responsibilities are handled explicitly in the analysis. It is 

difficult to see, hmr, how the other variables in the model can 

be characterized as controlling for “service quality.” 

11 2 Advisory Commission on Intergovernmental Relations 

for the services in the category), is the estimate of the city’s 

standardized expenditure need, that is 

. . . the amount it must spend to obtain a 

standardized service quality for a standardized 

package of service responsibilities.26 

A city’s cost index is derived from a cost function of 

this general form: 

where: 

rn Cj is the cost per unit of service quality in city j, 

rn Ij is an input cost index for city j, 

rn Xj is the value of the ith environmental cost 

factor in city j, and 

rn c and the ai’s are estimated parameters. 

The input cost measure for general and police 

services is the average wage in manufacturing in the state 

in which city j is located. For fire services, Ij is a consumer 

price index excluding taxes and housing. The coefficients 

of the input-cost variable in the general and police 

regressions are not significantly different from zero, but 

the coefficient of the price-index variable in the fire 

regression is significant at the 1 percent level. 

The statistically significant environmental variables and 

the values of their coefficients are different for the three 

categories of services, as the following summay indicates. 

General Services27 

rn Resident population; 

rn Population density; 

rn 

I 

rn 

Police28 

Percentage of housing units over 20 years old: 

City’s population as percentage of its SMSAs; and 

Private employment in the city as percentage of 

its resident population. 

rn Resident population; 

261bid., p. 79. 

*’The environmental cost variables not significantly different 

from zero in the regression for general services are: poverty 

population; government employment as a proportion of 

private employment; and the ratios to the assessed value of 

owner-oocupied housing of the assessed values of the following 

classes of property: rental housing, property used in retail and 

wholesale trade, property used in the production of services, 

industrial property, and vacant land and state-assessed property. 

28 The environmental cost variables not significantly different 

from zero in the regression for police services are: population 

density, percentage of housing units over 20 years old, 

percentage of housing units in single-unit buildings, the 

unemployment rate, government employment as a proportion 

of private employment; and the ratios to the assessed value of 

owner-occupied housing of the assessed values of the 

following classes of property: rental housing, property used in 

retail and wholesale trade, property used in the production of 

services, industrial property, and vacant land and stateassessed property. 
m Percentage of population below the poverty line; 

City's population as percentage of its SMSA's; and 

Private employment in the city as percentage of 

its resident population. 

Fire= 

Percentage of housing units over 20 years old; 

Private employment in the city as percentage of 

its resident population; 

Assessed value of property used in production of 

services as proportion of assessed value of 

owner-occupied housing; and 

Assessed value of industrial property as proportion 

of assessed value of owner-occupied housing. 

The environmental cost variables not significantly different 

from zero in the regression for fire services are: the log of 

resident population, population density, percentage of housing units in single-unit buildings, the poverty population, the 

city's population as percentage of its SMSA's, government 

employment as a proportion of private employment; and the 

ratios to the assessed value of owner-occupied housing of the 

assessed values of the following classes of property: rental 

housing, property used in retail and wholesale trade, and 

vacant land and state-assessed property. 

Advisory Commission on Intergovernmental Relations 11 3 
Y 

0 

United States 

z 3 Alabama 

Alaska 

Arizona 

Arkansas $ California 

p Colorado 

if Delaware 

a Florida 

Georgia 

Hawaii 

Idaho 

Illinois 

Indiana 

Iowa 

Kansas 

Louisiana 

Maine 

Maryland 

Massachusetts 

Michigan 

Minnesota 

Mississippi 

Missouri 

Montana 

Nebraska 

Nevada 

New Hampshire 

New Jersey 

New Mexico 

New York 

North Carolina 

North Dakota 

Ohio 

Oklahoma 

Oregon 

Pennsylvania 

Rhode Island 

Connecticut 

District of Columbia 

Kentucky 

Table 0-2 

Calculation of Ladd-Yinger-Equivalent Overall Indices of Standardized and Actual Fiscal Health, 1987 

(dollar amounts in millions) 

Standardized Fiscal Health 

Abstractinr from Fe deral Grants 

Actual Fiscal Health ed by In dex of Fieal th 

Considering Federal Grants Stdardized Actual 

RTS RR4 RTSGap Health RTSRRA RTSGap Health state Health State Health Change 

(1) (2) (3) (4) (5) (6) (7) (8) (9) 

- - - $653,608 SO $65 3,608 $0 United States United States - - 

(39.6) Connecticut 34.1 District of Columbia 44.1 28.3 

32.1 4.1 

Massachusetts 31.2 Wyoming 30.7 5.5 

8,253 3,673 (44.5) 8,544 3,383 

28.0 2,518 (808) 32.1 Nevada 31.8 Alaska 

8,632 693 (8.0) 

2,376 (666) 

9,048 277 (3.1) 

9,825 (1,143) 11.6 9,526 (844) 11,998 (4,092) 34.1 11,260 (3,354) 

2,135 (472) 22.1 2,077 (414) 

2,040 (322) 

30.5 Massachusetts 29.8 (1.4) 

86,966 (11,725) 13.5 86,056 (10,814) 12.6 Alaska 28.0 Connecticut 29.8 (4.3) 

8.9 Wyoming 25.2 Nevada 26.5 (5.3) 

29.8 New Jersey 23.9 New Hampshire 25.7 (4.8) 

20.0 Delaware 22.1 New Jersey 20.7 (3.2) 

15.8 3,074 (1,356) 44.1 Hawaii 20.8 Delaware 

11.5 31,489 (1,606) 5.1 District of Columbia 15.8 Hawaii 19.6 (1.2) 

13.5 Vermont 18.4 5.2 

13.2 NewYork 17.2 5.4 

(26.4) New York 11.8 Rhode Island 14.0 3.6 

30,266 1,589 (5.3) 30,088 1,767 (5.9) Colorado 11.6 California 12.6 (.9) 

12,937 1,811 (14.0) 12,871 1,877 (14.6) Florida 11.5 Maine 12.1 4.0 

6,356 9 38 (14.8) 6,465 829 (12.8) Maryland 10.8 Maryland 10.0 (.8) 

Rhode Island 10.5 Colorado 8.9 (2.8) 

7,904 2,937 (37.2) 8,101 2,740 (33.8) Maine 8.1 Minnesota 7.1 1.5 

10,320 2,904 (28.1) 11,239 1,985 (17.7) Minnesota 5.6 Florida 5.1 (6.4) 

3,089 (251) 8.1 3,229 (391) 12.1 Virginia 4.1 Pennsylvania 3.4 1.5 

13,248 (1,431) 10.8 13,127 (1,310) 10.0 Pennsylvania 2.0 Washington 2.6 2.7 

23,536 3,228 (13.7) 24,116 2,648 (11.0) Arizona (1.5) 4.4 

7.1 Illinois (5.3) Wmnsin (3.3) 3.8 

(57.0) Kansas (5.4) Montana (4.8) 13.0 

4,730 2,066 (43.7) 4,915 1,881 (38.3) New Hampshire 

20.0 (2.2) 

33,760 (3,877) 

15,732 2,407 (15.3) 15,720 2,418 (15.4) California 

20.8 3,241 19.6 Vermont (634) (30.1) 2,121 561 

3,291 (684) 2,061 621 

6,208 332 (5.4) 6,016 525 (8.7) 

19,944 (6,218) 31.2 19,553 (5,827) 29.8 Washington (.1) Virginia -4 (3.7) 

11,842 (668) 4,581 3,406 

12,474 1,259 (10.1) 12,134 1,600 (13.2) Oregon (5.9) Illinois (5.9) (4 

2,114 101 (4.8) Nebraska (6.2) Nebraska (6.4) (4 

3,803 (1,209) 31.8 3,530 (937) 

3,490 (1,065) 30.5 3,264 (840) 

25,202 (6,029) 23.9 24,191 (5,019) 20.7 North Carolina (10.1) Ohio (10.2) (.4) 

3,488 967 (27.7) 3,571 884 (24.8) ThS 

(3.1) Oregon 

5.6 12,033 (859) (74.3) 5,089 2,898 

1,880 335 (17.8) 

3,876 242 (6.2) 3,871 247 (6.4) Wisconsin (7.2) North Dakota (7.9) 9.2 

26.5 Ohio (9.8) Arizona (8.0) (5.0) 

25.7 Missouri (10.1) Kansas (8.7) (3.4) 

(10.6) Michigan (11.0) 2.7 

51,712 (6,092) 11.8 55,085 (9,466) 17.2 Oklahoma (11.4) North Carolina (12.5) (2.4) 

15,414 1,562 (10.1) 15,085 1,892 (12.5) Michigan (13.7) Iowa (12.8) 1.9 

1,622 276 (17.0) 1,759 138 (7.9) Indiana (14.0) Missouri (13.2) (3.1) 

26,346 2,575 (9.8) 26.251 2,669 (10.2) Iowa (14.8) Oklahoma (13.7) (2.3) 

8,187 936 (11.4) 8,023 1,100 (13.7) Georgia (15.3) Indiana (14.6) (.6) 

6,760 401 (5.9) 7,053 108 (1-5) North Dakota (17.0) Georgia (15.4) (.1) 

2.0 30,020 (1,031) 3.4 Montana (17.8) Texas (16.5) (5.9) 

10.5 2,641 (370) 14.0 Tennessee (23.5) Louisiana (17.7) 10.5 

29,575 (586) 

2,536 (265) 
Table 0-2 (cont.) 

Calculation of Ladd-Yinger-Equivalent Overall Indices of Standardized and Actual Fiscal Health, 1987 

(dollar amounts in millions) 

Standardized Fiscal Health Actual Fiscal Health Ranked bv Index of Fiscal fIeal th 

Abstractine from Fedrra I Grants Considerine Federal Grants Smdardized Actual 

State RTSRRA RTSGap Health RTS RRA RTSGap Health State Health State Health Change 

(1) (2) (3) (4) (5) (6) (7) (8) (9) 

South Carolina 7,249 2,253 (31.1) 7,326 2,176 (29.7) New Mexico (27.7) Tennessee (21.2) 2.3 

South Dakota 1,490 502 (33.7) 1,633 359 (22.0) Louisiana (28.1) South Dakota (22.0) 11.7 

Tennessee 10,928 2,567 (23.5) 11,137 2,359 (21.2) Idaho (30.1) Utah (23.6) 9.3 

Texas 44,687 4,749 (10.6) 42,425 7,011 (16.5) South Carolina (31.1) West Virginia (23.8) 9.3 

Utah 3,563 1,171 (32.9) 3,830 903 (23.6) Utah (32.9) New Mexico (24.8) 3.0 

18.4 West Virginia (33.2) Idaho (26.4) 3.7 

.4 South Dakota (33.7) South Carolina (29.7) 1.4 

2.6 Kentucky (37.2) Kentucky (33.8) 3.3 

(23.8) Arkansas (43.7) Arkansas (38.3) 5.4 

Alabama (44.5) Alabama (39.6) 4.9 

Mississippi (74.3) Mississippi (57.0) 17.4 

13.2 1,608 (296) 

4.1 15,689 (61) 

12,338 (323) 

11,767 393 (3.3) 

Vermont 1,512 (200) 

Virginia 16,291 (664) 

Wshington 12,006 9 (4 

Wisconsin 11,346 815 (7.2) 

4,226 1,008 

1,940 (596) 30.7 

West Virginia 3,930 1,304 (33.2) 

Wyoming 1,797 (453) 25.2 

Note: The index of fiscal health is the RTS gap, with the sign reversed, divided by RTS revenue-raising ability (RRA), multiplied by 100. 

Sources: 1 & 2-Thble 12. 

4 & 5-Thble 14. 
116 Advisory Commission on intergovernmental Relations