THE MEASURE OF POVERTY 

A Report to Congress as Mandated by 

The Education Amendments of 1974 

April 1976 

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

For sale by the Superintendent of Documents, U.S. Government Printing Office 

Washington, D.C. 20402 - Price $3.60 

Stock No.017-046-00039-0 
THE UNDER SECRETARY OF HEALTH, EDUCATION. AND WELFARE 

WASHINGTON, D.C. 20201 

30 THE CONGRESS OF THE UNITED STATES: 

I am pleased to transmit the report on the measure of poverty, in 

compliance with Section 823 in Public Law 93-380. A Poverty Studies 

Task Force of the Subcommittee on Education for the Disadvantaged and 

Minorities under the Federal Interagency Committee on Education was 

established by the Assistant Secretary for Education to conduct the 

study. It examines methds by which the measure of poverty used in the 

allocation formula for Title I of the Elementary and Secondary Education 

Act of 1965 may be made more accurate and current. To explore the 

relevant areas in depth, the Task Force has had the support of many 

Federal agencies and departments, for which we are greatly indebted. 

The report discusses technical aspects of poverty measurement and lays 

out the administrative, analytical, statistical, and budgetary 

implications of alternative measurement schemes. We hope that this 

effort will assist Congress and the various components of the Executive 

Branch wllo are involved in deliberations about the measure of poverty 

not only for the Elementary and Secondary Education Act but also for 

other Federal programs ad for general analytical purposes. 

A series of Technical Papers will supplement the present report with 

more detailed and technical material. These will be issued by the 

Chairman of the Task Force as they become available. 

Sincerely, 

J-. 

"7- Under ecretar y 
CONTENTS 

FORWARDING LETTER ........................................................................................ iii 

PREFACE .................................................................................................. ix 

LIST OF MAPS ............................................................................................. xv 

EXECUTIVE SUMMARY ........................................................................................ xxi 

INTRODUCTION ............................................................................................. 1 

I . 

I1 . 

I11 . 

IV . 

v . 

VI . 

VII . 

THE FEDERAL POVERTY DEFINITION .. HISTORY AND APPLICATIONS .......................................... 5 

HISTORY .......................................................................................... 5 

STATISTICAL CONSTRUCTION ......................................................................... 7 

STATISTICAL SERIES ON POVERTY .................................................................... 11 

ADMINISTRATIVE USAGE OF POVERTY MEASURES ......................................................... 14 

CONCEPTS OF POVERTY MEASUREMENT .................................................................... 19 

SOCIAL AND CULTURAL CONCEPTIONS OF POVERTY .............................. ECONOMIC MEASURES OF POVERTY ............................................ SETTING A POVERTY LEVEL ................................................. Standards of Physical Needs. 22; Adjustments for Family Size and Compo 

Cost-of-Living Differences. 26; Updating the Standard. 27 

INCOME AND RESOURCES .................................................... Accounting Period . 29; Consumption Measures. 30; Wealth. 31; Taxes. 31 

Consumption Unit. 34; Choosing an Income Definition. 35 

DATA AVAILABILITY AND LIMITATIONS ......................................... 

........................ 19 

........................ 20 

........................ 21 

ition, 24; Geographic 

........................ 28 

In-Kind Income. 32; 

DATA FOR MEASURING NEEDS ......................................................................... 38 

Food. 38; Housing. 40; Other Needs. 44; Standards Based on Actual Consumption Data. 45; 

Geographic Equivalences. 48; Updating the Standards. 50 

DATA FOR MEASURING RESOURCES ..................................................................... 52 

Base Data: The Decennial Census. 52; Current Population Survey. 55; Administrative Records. 56; 

Unemployment Data. 57; The Job Market and Wage Rates. 60; Correcting Cash Income. 60; Adding 

Other Sources of Income. 62; Different Accounting Periods. 66 

CONSTRUCTING POVERTY MEASURES ...................................................................... 69 

RELATIVE MEASURES OF POVERTY ..................................................................... 69 

POVERTY LEVEL MARKET BASKET ...................................................................... 72 

ORSHANSKY UPDATE ................................................................................. 75 

ADJUSTMENTS FOR FAMILY SIZE AND COMPOSITION ...................................................... 78 

GEOGRAPHIC COST-OF-LIVING DIFFERENCES ............................................................ 81 

Components of Geographic Differences. 82; Data Sources for Measuring Geographic 

Differences. 83; Major Conceptual Problems. 85; Evidence of Geographic Differences. 86; 

Farm-Nonfarm Differences. 90; Attempts to Overcome Conceptual Problems and Data Limitations. 91 

UPDATING THE STANDARD ............................................................................ 91 

INCOME AND RESOURCES ............................................................................. 97 

General Limitations. 97; The Accounting Period. 97; Assets. 98; Taxes. 99; In-Kind Income. 100; 

Consumption Unit. 100 

ALTERNATIVE POVERTY COUNTS BASED ON AVAILABLE DATA ................................................. 103 

ALTERNATIVE POVERTY DEFINITIONS .................................................... THE NUMBER OF POOR. 1974 ........................................................... CHARACTERISTICS OF THE POOR . 1974 .................................................. Persons in Female-Headed Families. 115; Blacks. 115; School-Age Children. 115; El 

Families with Earnings . 119 

SUMMARY OF POVERTY COUNTS AND CHARACTERISTICS ...................................... DIFFERENCES OVER TIME .............................................................. GEOGRAPHIC DISTRIBUTION OF POVERTY ................................................. ANALYTIC AND STATISTICAL AGENDA ...................................................... ANALYTIC STUDIES ................................................................... Educational Disadvantage. 137; Setting a Poverty Level. 138; Income and Resources 

SURVNS ............................................................................. New Income Survey. 141; Geographically Sensitive Pricing Survey. 141; Low-Income Consumption 

Survey. 142; Household Food Consumption Survey. 142 

PROGRAM IMPACT ..................................................................................... 145 

GENERAL PROGRAM IMPACT ........................................................................... 145 

IMPACT ON TITLE I OF ESEA ........................................................................ 148 

Background . 148; Impact on Selected States . 150; Impact of Changing the Poverty 

Definition. 153; Impact of Updating the Poverty Count. 155; Impact of Changing the Allocation 

Formula. 158; Joint Impact of Changing the poverty Definition and Updating the Poverty 

Count . 160 
TABLES . 

Poverty Cutoffs in 1974 by Sex of Head. Size of Family. and Number of Related Children Under 

18 Years Old. by Farm-Nonfarm Residence ............................................................... 10 

Weighted Average Poverty.Cutoffs in 1974 by Size of Family and Sex of Head. by Farm-Nonfarm 

Residence ............................................................................................. 11 

1974 Orshansky Poverty Thresholds and Community Services Administration Income Eligibility 

Guidelines ............................................................................................ 16 

Weekly Cost of Food at Home. Estimated for 1974 Low-Cost Plan and 1964 Low-Cost Plan. 

September 1974 Prices ................................................................................. 41 

Comparative Data on Personal Income by Source. Selected Major Government.Statistica1 Series 

U.S., 1969 .......................................................................................... 61 

Median Income by Size of Family Unit for United States and Selected States. 1969 ...................... 71 

Comparison of Median Family Income and Official Poverty Cutoff for a Family of Four. 1959-1974 ........ 72 

Sensitivity Analysis of 1974 Poverty Cutoffs .......................................................... 76 

Size of the Poor Population Under Current and Revised Poverty Cutoffs. 1974 ........................... 77 

Revised Equivalence Scale for Urban Families of Different Size. Age. and Composition .................. 79 

Equivalence Matrix Implicit in Current Poverty Measure ................................................ 80 

Indexes of Comparative Costs Based on a Lower Budget for a Four-Person Family. Autumn 1974 ............ 87 

Family Budget and Fixed Weight Indexes of Family Living Costs. Autumn 1974 ............................ 88 

Comparison of the Consumer Price Index with Price Indexes for Special Groups. 1953-1975 ............... 93 

Distribution of Families by Number of Months in Poverty on a Monthly Basis by Poverty Status 

on an Annual Basis. 1970 .............................................................................. 99 

Powrty Status in 1974 Based on the Current Definition and a Definition Based on Household 

Income ................................................................................................. 101 

Comparison of Poverty Population Under Selected Alternative Definitions of Poverty. 1974 .............. 109 

Selected Characteristics of the Poverty Population Under the Current Definition. 1974 ................. 112 

Poverty Rates by Selected Characteristics for Alternative Poverty Definitions. 1974 ................... 113 

Distribution of the Poverty Population by Selected Characteristics for Alternative Poverty 

Definitions. 1974 ..................................................................................... 114 

Percent of Population in Poverty for Selected Alternative Poverty Definitions. by State. 1969 ......... 129 

Percent of Related Children Aged 5-17 Years in Poverty for Selected Alternative Poverty 

Definitions. by State. 1969 ........................................................................... 130 

Impact of Changes in the Allocation Formula on the Distribution of Title I Funds. 1975 ................ 151 

Impact of Alternative Definitions of Poverty on Allocation of Title I Funds. 1975 ..................... 152 

Comparison of Title I Funds That Would be Received Using 125 Percent and 150 Percent of the 

Present Poverty Line with the Amount That Would be Currently Received ................................. 154 

Comparison of Title I Funds That Would be Received Using a Single Poverty Line with the Amount 

That Would be Currently Received. 1975 ................................................................ 156 

Title I Funds to be Received by Each State in 1975 Using Current Allocation Formula and 

Alternative Estimates of Children in Poverty .......................................................... 157 

Comparison of Title I Funds That Would be Received Under Alternative Allocation Procedures 

with Amount That Would be Currently Received .......................................................... 159 

Title I Funds to be Received by Each State in 1975 Using the 1973 Count of Children in Poverty 

and a 25 Percent Increase in the Poverty Line ......................................................... 161 
FIGURES 

Average Annual Percent Change in the Cost of the Economy Food Plan and in the Consumer . 

Price Index (All Items and Food). 1959-1973 ............................................................ 12 

Number of Persons in Poverty and Percent of Population in Poverty, 1966-1974 .......................... 13 

Poverty Rates for Persons, Families, and Unrelated Individuals Under Alternative Poverty 

Measures, 1974.. ...................................................................................... 108 

Distribution of Poor Persons by Living Arrangements. Current Poverty Measure and Single-Dollar 

Poverty Cutoffs, 1974..... ............................................................................ 110 

Persons in Female-Headed Families: Poverty Rates and Percent of the Poverty Population Under 

Alternative Poverty Definitions, 1974 ................................................................. 116 

Black Persons: Poverty Rates and Percent of the Poverty Population Under Alternative Poverty 

Definitions, 1974 ..................................................................................... 117 

School-Age Children: Poverty Rates and Percent of the Poverty Population Under Alternative 

Poverty Definitions, 1974 .............................................................................. 118 

Elderly Persons: Poverty Rates and Percent of the Poverty Population Under Alternative 

Poverty Definitions, 1974 ............................................................................. 120 

9.\ Percent of Poor Families and Poor Unrelated Individuals Receiving Social Security Under 

Alternative Poverty Definitions, 1974....... .......................................................... 121 

Percent of Poor Families with Earnings and Percent of Poor Families with Head Working FullTime, Year-Round......... ............................................................................. 123 

Number of Persons in Poverty Under Alternative Poverty Definitions, for Selected Years, 

1967-1974.. ........................................................................................... 124 

Percent of Persons in Poverty Under Alternative Poverty Definitions, for Selected Years, 

1967-1974.... ......................................................................................... 127 

. . Regional Share of Poor Persons Under Alternative Poverty Definitions as a Ratio of ~egional 

Share Under Current Poverty Definition, 1969.... ...................................................... 131 

Regional Share of Poor School-Age Children Under Alternative Poverty Definitions as a Ratio 

of Regional Share Under Current Poverty Definition, 1969. ............................................. 134 

vii 
PREFACE 

Section 823 of the Education Amendments of 1974 (PL 93-380) requires a 

thorough study of the manner in which the relative measure of 

poverty for use in the financial assistance program authorized 

by Title I of the Elementary and Secondary Education Act of 1965 

may be more accurately and currently developed. 

The financial assistance program referred to is administered by the Commissioner of Education, through the Office of Education of the Department of 

Health, Education, and Welfare. A prominent feature of the program is the 

use of a formula prescribed by section 103 of the Elementary and Secondary 

Education Act for the annual distribution of Federal funds to school districts. The amount appropriated has increased from approximately $1 billion 

in 1966 to $1.6 billion in 1976. A significant factor in the formula is the 

number of school-age children 5 to 17 in poor families within each school 

district. 

I Incorporation of the Poverty Measure in Title I 

Prior to the enactment of the Education Amendments of 1974, the formula which was used to determine the amount of a grant for which a local 

educational agency was eligible (i.e., its "entitlement") under Title I was 

based, in part, on the number of children in families having an annual 

income of less than the "low-income factor." This factor was authorized to 

be $2,000. he low-income factor was $3,000 but was to be applied only 

when authorization using $2,000 was fully funded. This never happened, so 

$2,000 was the factor used until the 1974 Amendments.) The 1974 Amendments 

revised the Title I formula and specified a new measure of low-income -- 

the Federal government's official statistical definition of poverty (also 

known as the Orshansky poverty index, Social Security Administrat ion (SSA) 

poverty definition, the Census Bureau poverty lines, etc.) . Maps showing 

the geographic distribution of children aged 5 to 17 from families below the 

poverty level for the Title I formula, follow this Preface. 

The poverty level is only one element in the Title I formula. It is, 

however, a critical element and is the subject of this study, which addresses 

the accuracy and currency of the poverty measure. 

In addition to this study of the measure of poverty, the Education 

Amendments of 1974 mandated several other studies and special surveys which 

could make possible future improvements in the allocation formula and other 

aspects of the Title I programs. The following table shows the titles of 

these studies, the agency responsible for their conduct, and their due dates: 

Responsible Due 

- Study Agency - Date 

1. Study of purposes and effectiveness ~xtional Institute Sept. 1977 

of.compensatory education programs of Education 

(section 821) 
Study 

Responsible 

Agency 

Due 

- Date 

2. Survey and study for updating Secretary of Commerce Dec. 1976 (822a) 

number of children counted and Secretary of Health, June 1977 (822b) 

(section 822) Education, and We1 fare 

3. An evaluation of the Title I Commissioner of 

programs which is to include: Education 

(section 151) 

Findings to 

be reported 

as available 

Eva1 ua t ions describing and 

measuring program and project 

impact, the most comprehensive 

of which is the study of the 

sustaining effects of canpensatory 

education on basic cognitive skills. 

Development and publication of 

standards for pr~gram/~roject 

evaluation. 

Provision, where appropriate, 

for joint ~ederal/ state sponsored 

evaluations. 

Provision of technical assistance 

to State Education Authorities (SEAS). 

Development of a system for the 

gathering and dissemination of effective 

projects, practices, and evaluation result S. 

4. Survey of the numbers of Commissioner of 

economically and/or educationally Education 

disadvantaged children who do or 

do not receive Title I services. 

(section 417 (a)(2)) 

Fall 1977 

This "Participation Study" will be 

incorporated under the "Study of the 

Sustaining Effects of Compensatory 

Education on Basic Cognitive Skills ." 

(section 151) 

Related work has been mandated in two other recent legislative acts. 

In the Comprehensive Employment and Training Act, the Secretary of Labor 

is directed to develop and maintain comprehensive household budget data at 

different levels of living, including a level of adequacy. Any such review 

of the "level of adequacy" must necessarily be closely related to measures 
of poverty. Tne Housing and Community Development Act of 1974 makes the 

Secretary of the Department of Housing and Urban Development (HUD) responsible for adjustments in the poverty measure to reflect regional and 

area variations in the cost of living. The Conference Report accompanying 

it directs the Secretary to develop or obtain data with respect to the 

"extent of povertyi' by metropolitan areas and to submit such data to the 

Congress as part of a March 31, 1977 report. 

Scope and Performance of this Study 

Coverage of this study has been broadened to include implications 

of the findings of the study for the poverty-related programs of all affected 

Federal departments and agencies. The Title I program of the Elementary 

and Secondary Education Act is given the most detailed treatment, both to 

meet the legislatively-mandated specifications for the study and also to 

serve as a prime example of application of the concepts of poverty measurement to Federal programs. 

It is probable that a variety of poverty measures will continue to be 

used for statistical and administrative purposes within the Federal government. For this reason, an important objective of this report has been the 

full discussion and documentation of the major elements of currently used 

and potentially usable poverty measures. The material containing essential 

supporting documentation for this study has been assembled into technical 

papers. These have been written to stand alone as complete technical treatments of specific subjects. They may, therefore, be repetitive when compared 

to one another or to the text of the report. Similarly, within the text of 

the report, some redundancy may occur. In both cases, the repetition of 

material was considered to be beneficial from the point of view of completeness and clarity in the treatment of certain concepts. 

This study was performed under the direct guidance of the Poverty 

Studies Task Force of the Subcommittee on the Education of the Disadvantaged 

and Minorities, Federal Inter-Agency Committee on Education. Technical 

papers are being prepared at the request of, under the direction of, and 

subject to review by the Task Force members. The study draws on material 

in these papers, some of which have not been completed at the time of publishing this report. Some papers are primarily the work of one or two 

persons; these are attributed to their authors. Others result from the 

collective input of Task Force members or advisors and no specific attribution is given other than to the Task Force as a whole. 

References relevant to this report are too numerous for a separate 

listing. One can refer to Technical Paper 111, "Literature Review and 

Annotated Bibliography of Studies on the Measurement of Poverty" which 

contains a compilation of major sources and materials. Other pertinent 

references are cited throughout the report in footnotes and in the individual 

technical papers. The following listings show members of the Poverty Studies 

Task Force by appropriate Federal departments and agencies, those deserving 

special thanks, and the titles and authors of the technical papers. 
Federal Interagency Committee on Education 

Subcommittee on Education for the Disadvantaged and Minorities 

POVERTY STUDIES TASK FORCE 

Chairman 

Bette S. Mahoney 

Office of the Assistant Secretary 

for Planning and Evaluation 

Department of Health, Education, and Welfare 

f 

Co-Chairman for Education 

Abdul Khan 

Office of the Assistant Secretary for Education 

Department of Health, Education, and Welfare 

David Arnaudo 

Social and Rehabilitation Services 

Department of Health, Education, and Welfare 

Richard B. Clemmer 

Office of the Assistant Secretary 

for Policy Development and Research 

Department of Housing and Urban Development 

Genevieve 0. Dane 

Office of Education 

Department of Health, Education, and Welfare 

William Dorfman 

National Center for Educational Statistics 

Department of Health, Education, and Welfare 

Alan L. Ginsburg 

Office of the Assistant Secretary 

for Planning and Evaluation 

Department of Health, Education, and Welfare 

George E. Hall 

Social Statistics Branch 

Office of Management and Budget 

Stephen Hiemstra 

Food and Nutrition Service 

Department of Agriculture 

Paul T. Hill 

National- Institute for Education 

Department of Health, Education, and Welfare 

Eva Jacobs 

Bureau of Labor Statistics 

Department of Labor 

Jane Lampmann 

Office of the Assistant Secretary 

for Human Development 

Department of Health, Education, and Welfare 

Daniel Levine 

Bureau of the, Census 

Department of Commerce 

Nelson McClung 

Office of Tax Analysis 

Department of the Treasury 

June O'Neill 

Council of Economic Advisors 

Mollie Orshansky 

Social Security Administration 

Department of Health, Education, and Welfare 

Israel Putnam 

Community Services Administration 

Robert L. Rizek 

Agricultural Research Service 

Department of Agriculture 

Gooloo Wunderlich 

Office of the Assistant Secretary for Health 

Department of Health, Education, and Welfare 

xii 
Research kssistants 

Staff, Office of the Assistant Secretary 

for Planning and Evaluation 

George F. Grob, Staff Director 

Bernice Cravin 

Charlene Doyle 

Julie Jervey Mitchell 

Program Assistant 

Carolyn Solomon 

Special Thanks 

Department of Health, Education, and Welfare 

Philip Austin 

Lawrence Brown 

Walton Francis 

Martin Frankel 

Lawrence Haber 

Forrest Harrison 

Jane Lee 

W. Michael Mahoney 

Keith Melton 

Herman Miller 

Janice Peskin 

Paul Planchon 

David Sears 

Les Silverman 

Wray Smith 

Stan Stephenson 

John Todd 

Howard Tuckman 

Office of Management and Budget 

Joseph W. Duncan 

Milo B. Sunderhauf 

Secretarial and Clerical Assistants 

Vera Cotton 

Janice Donaldson 

Roseline B. Graves 

Diane Green 

Donna J. Milligan 

Louise Thornes 

Donna M. Saxty 

Department of the Treasury 

Gene Steuerle 

Department of Agriculture 

Thomas Carlin 

J. C. Chai 

Gary Perkins 

Betty Peterkin 

Department of Commerce 

Daniel Garnick 

Roger Herriot 

Richard Hornseth 

Jack McNeil 

Renee Miller 

Arno Winard 

Department of Labor 

Terry Finnegan 

Mark Sherwood 

Robert Stein 

Department of Housing and Urban Development 

Paul Gatons 

Mathematica, Inc. 

Connie Citro 

Jill King 

Diana Zentay 

The Institute for Research on Poverty, University of Wisconsin 

Killalea Associates, Incorporated 

Survey Research Center, University of Michigan 

Urban Systems Research & Engineering, Inc. 

xiii 
TECHNICAL PAPERS 

I. 

11. 

111. 

IV. 

v. 

VI. 

VII. 

VIII. 

IX. 

X. 

XI. 

XII. 

XIII. 

XIV. 

XV. 

XVI . 

XVI I. 

XVIII. 

Documentation of Background Information Mollie Orshansky 

and Rationale for Current Poverty Matrix Social Security Administration 

Administrative and Legislative Usages of Poverty Studies Task Force 

the Terms "Poverty ,I' "Low Income,'' and 

Other Related Items 

~ite;ature Review and Annotated 

Bibliography of Studies on the 

Measurement of Poverty 

Bureau of Labor Statistics Family 

Budgets Program 

The Consumer Price Index 

Wealth and the Accounting Period in 

the Measurement of Means 

In-kind Income and the Measurement of 

Poverty 

The 1972-73 Consumer Expenditure 

Survey 

Inventory of Federal Data Bases Related 

to the Measurement of Poverty 

(a) Non-Census Data Bases 

(b) Census Data Bases 

Effect of Using a Poverty Definition 

Based on Household Income 

Update of the Orshansky Index 

Food Plans for Poverty Measurement 

~eograpdic Differences and Relative 

Poverty 

Relative Measure of Poverty 

Analytic Support for Cost-of-Living 

Differentials in the Poverty Thresholds 

Implications of Alternative Measures 

of Poverty on Title I of the Elementary 

and Secondary Education Act 

The Sensitivity of the Incidence of 

Poverty to Different Measures of, 

Income: School-age Children and 

Families 

Characteristics of Low-Income 

Populations Under Alternative 

Poverty Definitions 

with assistance from Ellen Kraus 

Urban Systems Research 

and Engineering, Inc . 

Mark Sherwood 

Bureau of Labor Statistics 

Jill King 

Mathema~ica, Inc. 

Nelson McClung and Eugene Steuerle 

Department of the Treasury 

Janice Peskin 

Health, Education, and Welfare 

Jill King 

Mathematica, Inc. 

Connie Citro, Mathematica, Inc. 

Bureau of the Census 

Jack McNeil, Doug Sater, Arno Winard 

Bureau of the Census 

Mollie Orshansky ' 

Social Security Administration 

Betty Peterkin 

Department of Agriculture 

Jack McNeil 

Bureau of the Census 

Stanley Stephenson 

Health, Education, and Welfare 

Thomas Carlin 

Department of Agriculture 

Abdul Khan and Herman Miller 

Health, Education, and Welfare 

Survey Research Center 

University of Michigan 

Lawrence Brown 

Health, Education, and Welfare 

xiv 
MAPS 

1. Number of Children 5 to 17 Years Old elo ow the Poverty Level in 1969 

(By Counties of the United States) 

2. Percent of Children 5 to 17 Years Old Below the Poverty Level in 1969 

(By Counties of the United States) 
BUREAU OFME CMSUS 

UNmED STATES I CEDCW DIYISION 

1 1OQ) 

F7.W mnnm STATEl 

sop"1.t" 

BOUNDARIES 

Internotional County 

boundary boundary 

State 

boundary Extent 

of 

SMSA 
n 

BOUNDARIES 
EXECUTIVE SUMMARY 

The 1974 Amendments to the Elementary and Secondary Education Act 

included a mandate to the Department of Health, Education, and Welfare to 

study ways of improving the accuracy and currency of the present measure 

of poverty used in the formula that allocates funds authorized by Title I 

of the Act. This is a summary of the report of that study. 

Poor persons living in the United States in the 1970s are rich in 

contrast to their counterparts in other times and places. They are not 

poor if by poor is meant the subsistence levels of living common in some 

other countries. Nor are most poor like their counterparts in this country 

fifty or one hundred years ago. This country is concerned about poverty, 

its causes and correlates. It is willing to relieve the poverty 'of some 

of the poor and it wants to measure the effectiveness of its efforts to 

do so. None of this can be done without some idea of who is to be considered poor and who is not. 

The report deals with measuring the current status of the poor rather 

than with the causes or solutions to poverty.. A family is none the less 

poor for having arrived at that state of its own accord. Similarly, the 

fact that an individual could with modest and reasonable effort escape 

from poverty has nothing to do with whether he is currently poor. 

The current measure of poverty used in the allocation formula was 

originally developed by blollie Orshansky of the Social Security Administration in 1964 and was, with revisions, officially adopted in 1969 by 

the Office of Management and Budget as the Federal Government's official 

statistical measure of poverty. The measure is built around the Department 

of Agriculture's economy food plan of 1961 and the national average ratio 

of family food expenditures to total family af ter-tax income as measured 

in the 1955 Household Food Consumption Survey. It consists .of 124 separate 

poverty cutoffs differentiating families by size,.number of children, age 

and sex of head, and farm or nonfarm residence. Tne cutoffs are updated 

annually by changes in the Consumer Price Index. The weighted average 

poverty cutoff for a nonfarm family of four in 1974 was $5,038. According 

to the Census Bureau's report based on the March 1975 Current Population 

Survey, in 1974 there were approximately 24.3 million persons, or 12 

percent of the population, poor by this definition. 

The Orshansky poverty definition is widely used to measure the 

nation's progress in reducing the extent of poverty. It is also used as 

a statistical tool to identify the target populations of government programs 

that help the financially needy and to evaluate the effectiveness of such 

programs. In recent years it has been adapted for administrative purposes. 

The Title I program of the Elementary and Secondary Ed~cation Act provides 

one example of its administrative use. A different example is its use in the 

Head Start program where it plays a part in the determination of individual 

eligibility and the amount of government benefits provided to beneficiaries. 
The Orshansky matrix of poverty thresholds is not the only poverty 

or low-income measure used for statistical and administrative purposes. 

Other measures include dollar cutoffs unadjusted for family size; various 

percentiles of the income distribution; and various percentages of median 

family income. These measures have advantages and disadvantages which 

vary according to the spec'ific statistical, analytical, or administrative 

purposes intended. Each has subjective elements and limitations due to 

unresolved conceptual problems or scarcity of data. 

The study examines ( 1) regional, climatic, metropolitan, urban, 

suburban, and rural differences in the poverty measure, (2) differences 

due to family size and head of household, and (3) the availability of 

state and other subnational data more current than the decennial Census, 

including cost of living, cost of housing, labor market and job availability, prevailing wage rates, unemployment rates, income distribution, 

and the eligibility criteria for aid to families with dependent children 

(AFDC) under state plans approved for Title IV of the Social Security Act. 

The report reviews various topics; major discussion areas are: 

1. Measures of poverty used for national policy purposes require 

fundamental social, political, and ethical judgments which should 

reflect the following considerat ions : varying beliefs about the 

proper norms or standards of need which should be adopted; a well 

conceived purpose and reasoned use of the measure or measures; 

the implicit government policy, to redistribute income to or substantially assist those below the poverty line; and the necessity 

for periodically reviewing any poverty measure in light of changed 

perceptions of need, new data, resource limitations, changes in 

the demographic, composit ion, and social factors. 

The official measure of poverty has a number of limitations, some 

of which stem from the fact. that there are no commonly accepted 

standards of need, other than for food; even the Department .of 

Agriculture's measure of this standard is approximate. A multiplier which reflects the average ratio of income to food consumption is used as only a rough measure of nonfood requirements. In 

addition it, along with other measures discussed in this study, 

does not account for geographic differences in the cost of living 

or relative prices. Nor does it change over time with changes in 

the standard of living, although it is adjusted for changing prices 

to the extent they are captured by the Consumer Price Index. 

3. Various proposals have been made to change the official poverty 

measure,. The most commonly discussed include: revising it by 

using a more current USDA 'food plan and ratio of food expenditures 

to income from the 1965-66 Household Food Consumption Survey; 

simplifying it by removing the distinctions for farm residence, 

sex of head, or presence of children; making year-toyyear changes 

through a price index specially weighted for poor persons; 

xxii 
adjusting the definition of income for assets, taxes, and homeproduced goods and services; and measuring the effect of the 

subsidy programs which are now more available to the poor than 

they were when the measure was derived. 

4. There may be cost-of-living differences between regions, and 

among urban, suburban, and rural areas, but the extent and 

nature of these differences is difficult to identify accurately. 

Existing sources of data which are both accurate at the state 

and local level and available on a timely basis cannot provide 

a reliable proxy measure of poverty. Because cost-of-living 

differences across areas are not satisfactorily measured by 

existing data and because there is no agreement on the methodology for making such an adjustment, no geographic adjustment in 

the poverty threshold is made in the report. Nevertheless, even 

in the absence of demonstrated cost-of-living or price differences, some believe that national programs could contain provisions 

to overcome problems which could arise from the effects of local 

labor and housing markets, local extent of poverty, or other 

special circumstances. 

5. The development of a poverty definition based on a fully 

specified market basket of goods and services could provide a 

basis for varying the thresholds to account for differences in 

need due to variation in family size or composition. However, 

the lack of commonly accepted standards of need makes it 

difficult to construct a suitable poverty level market basket. 

Equivalence scales used to adjust the current poverty thresholds 

for family size and composition are based primarily on nutritional requirements and are not fully satisfactory. Alternative 

equivalence scales are examined in the report, but there is 

disagreement about their validity and in some cases they are 7 

quite arbitrary in their construction. Similarly, there are no 

generally accepted techniques for adjusting poverty cutoffs for 

other demographic characteristics such as health status or 

occupation. Unaddressed is the question of standards of poverty 

for the working poor compared with those dependent largely on 

public programs for support. 

Several findings related to changing the definition of poverty 

are : 

1. Commonly proposed changes in the definition of poverty would raise 

the poverty cutoffs and increase the number of persons who would. be 

counted as poor. However, there have also been a number of criticisms 

of the way in which the poor are counted, which, if valid, suggest 

that some persons are counted as poor who should not be. Commonly 

proposed alterations vary from a revision of the current definition on the basis of more recent family consumption patterns to 

xxiii 
P 

such entirely different approaches as specifying poverty in terms 

of some percentage of median income. Changes which lower the 

poverty-count, if the present poverty measure were not changed, 

include counting non-cash subsidies like food stamps as income 

and imputing income value to wealth when it does not generate 

interest, dividends, or rental income. 

I n c r e a s i n g . ' t h e poverty income cutoffs results not only in more 

persons and families being counted as. "poor," but also in a 

significantly different composition of the poor population. 

Increasing the poverty line results in a poverty popul'ation with 

proportionately more whites than at present, more working poor, 

an increased proportion of families with a male rather than a 

female ,head, slightly higher concentrations of the elderly, and 

slightly .lower concentrations of children. It'also causes a 

relative shift in the proportionate share of the poor population 

from the Southern fo other states and from less populated to more 

populated states. 

3. Since no accepted standards exist for nonfood items (housing: 

clothing, transportation, etc.), the current poverty threshold 

is derived by assuming that the appropriate ratio of expenditures 

on nonfood items to expenditures on food would be .that observed 

on the average in the United States. Based on more recent household food consumption data, the average proportion of income 

devoted to nonfood items and the corres'ponding multiplier to 'be 

applied to food costs are higher than in 'the current po.verty 

measure. Arguments have been made both for increasing and decreasing the multiplier. ~hese are related to: the assumption 

that food expenditures must not exceed the measured national 

average proportion of total income spent on food; differences in 

the statistical bases for. calculating the multiplier; and the 

income definition to be used. . 

Under the official poverty measurement system .(when backhated 

by the consumer Price Index), the number of poor families was' 

reduced from 18'.5 percent' in 1959 to 9.2 percent during 1974. 

Revising, the official poverty line on the, basis of current 

nutrition standards, food plans, food prices, and a higher . 

multiplier reflecting more recent overall consumption .data would 

raise the poverty line in real terms and .lessen the amount of 

progress shown in reducing the extent of poverty. A poverty line 

based on 50 percent of national median family income would . 

consistently show about 19 percent of all families as poor over 

the past fifteen years, although at ever higher real income 

levels. 

In-kind benefits from government and private sources have grown 

sharply during the past decade: Empirical evidence for 1974 and 

several earlier years indicates that, if food stamps were included 

xxiv 
as income and if the poverty thresholds were not changed, about 

5 to 15 percent of the poor (depending on the method of valuation 

used) would no longer be counted as poor. The number of poor 

children would be reduced more significantly than other groups of 

poor persons. Inclusion of the value of other in-kind subsidies 

such as .housing and health insurance would also reduce the number 

of poor counted by the present measure if the poverty thresholds 

were not changed. However, if the logic of the,existing measure 

is maintained, the ratio of after-tax income to food expenditures 

which is used in computing the poverty thresholds might be ' 

altered. Although it is difficult to agree on what value of inkind benefits to include as income, failure to do so excludes some 

of the fastest growing sources of income in the economy. 

6. Addition of unrealized or imputed income from assets (or even 

addition of stock of assets) to current income will also reduce 

the count of the poor if the poverty thresholds are not changed. 

The most dramatic reduction will occur for the self-employed, the 

aged, whites, and other groups in which the average net worth is 

higher than it is for the population, as a whole. However, many 

of the poor .have no sizable assets. Furthermore, if the poverty 

definition were revised maintaining its current logic, whether 

the number of poor would increase or decrease would depend on the 

distribution of such imputed income. 

Findings related to programs are: 

7. Except for a few programs, like child nutrition and food stamps, 

' . raising the poverty line (or lowering it) need not in itself 

increas'e (or decrease) the Federal budget, 'since in most programs 

a fixed amount of Federal funds is distributed. Federal revenues 

are linked to the poverty line to some extent through the minimum 

standard deduction for income taxes. The primary administrative 

effect of changing the poverty line (if administrative guidelines 

were to be similarly changed) is not necessarily a question of 

how much Federal money will be appropriated for the poor as of 

which -- low-income persons or areas will receive the appropriated 

. funds. 

8. With respect to Title I of the Elementary and Secondary Education 

Act, other elements of the distribution formula, such as the 

individual states' per-pupil expenditure rates, the size of their 

AFDC populations, the ''hold harmless" provision, and the failure 

to update the count.of children in poverty between the decennial 

Censuses, also have a significant effect on the proportionate 

share of funds which each state receives. If the funds were 

distributed solely on'the basis of the number of poor children, 

the distributional effects would be much sharper than those 

produced by any reasonable change in the poverty thresholds using 

the current formula of allocation of Title I funds. 

xxv 
This report does not recommend any particular changes in poverty 

measurement or concept. It shows that there are many alternatives possible, 

each with its own advantages and disadvantages. Unfortunately, many of the 

more conceptually desirable changes are among the most difficult to implement. There are options that would increase the poverty count; there are 

equally valid changes that would reduce it. It can be concluded that any 

poverty definition may be subject to valid criticism, and that any definition is inherently value laden. Nevertheless, there is an advantage in the 

continued publication of an official statistical series of a poverty measure 

as an index of national achievement in reducing the extent of poverty. 

xxv i 
INTRODUCTION 

Poor persons living in the United States in the 1970s are rich in contrast to their counterparts in other times and places. They are not poor 

if by poor is meant the subsistence levels of living common in some other 

countries. Nor are most poor like their counterparts in this country fifty 

or one, hundred years ago. This being so, why worry about poverty and its 

measure? The simple answer is that this country is concerned about poverty, 

its causes and coryelates. It is willing to relieve the poverty of some 

.of the poor and it wants to measure the effectiveness of its efforts to do 

so. None of this can be done without some idea of who is to be considered 

poor and who is not. 

It might appear a simple matter to define and measure poverty. After 

all, it is easy to describe a hypothetical situation with terms so harsh 

and stringent that most persons will agree they denote poverty. But agreement that all persons at and below some level are poor does not constitute 

agreement that persons above it are not poor. Poverty is not an "either-or" 

state or condition; it is also a matter of degree. 

Human beings vary in physical and mental ability. Some are favored 

with better physical or mental health than others. Their tastes differ 

and some suffer more from chance or bad luck than others. Moreover, all 

relationships involving human beings are continuous and have no sharp, 

obvious dividing lines. Thus, all poverty thresholds are necessarily subjective no matter how objective the empirical data used to derive them are. 

A point dividing a continuum is inherently subjective since one can always 

argue. that the point ought to be a little further to the right or to the 

left. 

Policy issues and causality often, get mixed up with the definition of 

poverty. Many people believe that poor people are people who deserve something, sympathy drily perhaps, but possibly some kind of assistance. Thus, 

when it is said that persons of a given type are not poor, what may be meant 

is that they do not deserve help or sympathy. And, when it is said that 

somebody is not "that poor," what may be meant is that that someone does not 

deserve "that" much help. The feeling that poor people necessarily deserve 

help inevitably leads to definitions- of poverty which reflect programmatic 

and policy issues. The definition of poverty is easily confound,ed by 

instilling into it a concern about the incentive effects of some program 

presumed to relieve. poverty. 

Whether and which of the poor deserve something from the rest is essentially a moral or ethical question. How much they deserve is partly subjective and partly ethical. How and whether they get it involves practical, 

economic, political and a host of other issues. Who is poor and who is not 

are canpletely subjective questions. Nonetheless, the concept of poverty 

can be, is, and should be defined without reference to cause, responsibility, 

or potential anti-poverty programs. It is precisely because ethical and 
subjective considerations inevitably enter into discussions of poverty that 

this is important. Such considerations make the discussion more complex 

and the issues more, difficult to resolve. 

The dictionary assigns to the word poverty a limited if imprecise 

meaning: lack of money or personal possessions. However, even a cursory 

review of the literature on poverty reveals that for many people the word 

has connotations broader or more narrow than the dictionary definition. 

For example, the dictionary does not limit -poverty to a condition arrived 

at or remained in involuntarily. A family is none the less poor for having 

arrived at that state of its own accord. Similarly, the fact that an individual could with modest and reasonable effort escape from poverty has nothing to do with whether he is currently poor. 

If poverty is the lack of money or personal possessions, then poverty 

must be measured with a scale of money and personal possessions. The scale 

itself does not define poverty since only at the very top can it be said 

that there is no poverty; every place else there is poverty relative to 

some other place except for the very bottom where there is complete poverty. 

To say that someone is poor merely because he occupies a place lower on the 

scale'than someone else (regardless of the complexities required to make 

such a statement) is not a sufficient definition. To say that someone is 

poor, then, must be to say that he lacks the money or possessions necessary 

to obtain some state or condition. A poverty threshold is the point on the 

scale of poverty below which people are deemed incapable of achieving this 

defined state; ,it has no intrinsic meaning apart from the state or condition 

it is meant to delimit. . 

Most people have an intuitive notion that there is a subgroup of the 

population that is poor; the 'term "the poor" can be used repeatedly without 

definition. But the criteria by which people distinguish the poor from. 

the rest are almost inevitably circular in reasoning: the poor are people 

who behave like poor people. This circular reasoning is hard to avoid. 

In general we all take "the poor" to be persons on the lower end of the 

measure of poverty; But how do we decide how far down? Where is the poverty 

threshold? What is the state of being poor? 

The further down on the scale of poverty, that is, the closer one 

. approaches mere physical subsistence: or the more limited the degree of , 

consumer choice assumed, the more likely it is that there will be agreement 

that people there and below are "poor ." This is so because there are several, perhaps many, possible senses of the word poor and persons on the lower 

end of the measure are more likely to fit one of these senses than persons 

further, up. Because of this, it is tempting to think that there is a consensus poverty threshold, a point on the scale of poverty below which people 

would be considered poor by almost everyone. Nonetheless, it is unlikely 

that a measure of poverty can be developed which will serve equally well 

for all purposes. Poverty can be defined in the abstract but whether someone 

is to be considered poor ultimately depends on who is asking the question and 

why he wants to know. Moreover, some measures suggest a requirement or a 
need that lasts just for a brief time but others relate to a phase or time 

of life and others could apply them over an entire lifetime. Persons turned 

away from hospital emergency clinics because they had neither cash nor 

evidence of insurance know one meaning of poverty. People who never have 

quite enough to make ends meet know another. 

Experts discussing poverty have distinguished between absolute and 

relative thresholds. An absolute threshold is a fixed bundle of goods 

and services that does not vary in mix, quantity or quality regardless 

of when ,or where it applied. Relative poverty changes directly with 

prevailing income. One reason for the focus on absolute versus relative 

poverty thresholds is to show that the level of living associated with being 

poor varies over time and from place to place. 

People have different living arrangements, they face different circumstances, live in different places and have different kinds of preferences 

and possessions. These differences create substantial problems in determining whether two persons are equally poor or in measuring the difference 

in their poverty. In some cases, they may involve matters .of taste which 

means that precise measurement is impossible. Such differences affect both 

the determination of where on the poverty scale a person belongs and the 

particular poverty threshold to apply to him. 

The problems of measuring poverty are the subject of this report. 

Chapter I, The Federal Poverty Definition, provides the background for the 

study. It briefly discusses the purposes of a Federal poverty measurement 

system, gives a brief history of the current official poverty line, describes 

its construction in detail, identifies available statistical series on the 

number of poor persons and their limitations, and describes the various 

current administrati,ve and legislative usages of poverty terminology. As a 

whole it introduces the key empirical issues connected with the current 

poverty measurement system to which this report is addressed. 

Chapter 11, Concepts of Poverty .Measurement, describes the concepts 

implicit in a poverty definition. It explores some a1 ternative conceptual 

definitions of poverty as well as some theoretical difficulties with defining standards of need, with constructing equivalence scales for family 

size and composit ion across geographic areas and over time , with measuring 

total resources availability, and with employing other normative measures. 

Chapter 111, Data Availability and Limitations, describes both the 

availability a(nd limitations of existing .data for making more current and 

accurate determination of poverty measures and estimating numbers of the 

poor once defined. The focus is on data sources.relevant to updating and 

modifying the current Orshansky measure, although data sources that could 

permit developing other kinds of measures are also reviewed. 

Chapter IVY Constructing Poverty Definitions, explains the kinds of 

poverty measures which can presently be constructed using available data 

and known conceptual frameworks. It also displays the available evidence 
for some concepts even when the data or theoretical constructs are not 

adequate for developing an alternative me,asure now. 

Chapter V, Alternative Poverty Counts Based on Available Data, describes alternative measures which are possible using existing data, indicating what the number and demographic characteristics of those counted 

as poor would be under each.. All alternative definitions are based on 

straight forward simplifications or adaptations of the official Federal 

statistical definition or on readily available income 8a.ta. The alternatives have been chosen to illustrate common usages o; concepts. Some of 

them are not recommended for adoption within Federal programs. 

Chapter VI, Analytic and Statistical Agenda, outlines the kinds and 

scope of research and survey activities which could lead to improved methods 

of measuring poverty. Time, cost, and utility are discussed in relation . 4 

to particular research and statistical programs. The interrelationship 

among major surveys, and necessary .planning around it, is also covered. 

Chapter VII, Program Impact, describes the impact of the alternative 

poverty indexes (developed in Chapter V) on Fed.eral poverty-related programs, particularly on the allocation of funds under Ti.tle I of the Elementary and Secondary Education Act. 
L THE FEDERAL POVERTY DEFINITION - HISTORY AND APPLICATIONS 

This study' deals with the Federal government's poverty measure. As 

required by Public Law 93-380, section 823, the study is aimed specifically 

at the measure of poverty used in the program of financial assistance 

authorized by Title I of the Elementary and Secondary Education Act of 1965. 

This measure is the Federal government's official statistical poverty index, 

and any recommendations concerning the index will affect all other programs 

which use it. Therefore, before examining its applications to the Title I 

education program, it is instructive to look at the concepts and background 

underlying this measurement system. 

This chapter describes the fundamental features of the Federal poverty 

line. First, it reviews the main historical events leading to adoption, by 

the Bureau of the Budget, of the Orshansky poverty index as thd official 

Federal statistical poverty definition. Second, it describes the economic 

concepts underlying the index and the data supporting its construction. 

Third, it summarizes the major statistical series published by the Census 

Bureau that are based on the poverty line. The final section summarizes the 

most common administrative and legislative usages of the Orshansky poverty 

measure (as well as of other measures that define low income or poverty). 

I 

As a whole, this chapter identifies the major issues that need to be 

resolved in meeting the requirements of section 823. The remainder of the 

report focuses on the resolution of these issues. 

History 

Concern with defining which persons and groups are poor goes back as 

far as the mid-nineteenth century. Congress has, from time to time, commissioned reports on the number of low-income families, their characteristics 

and their problems. 1/ Various Federal ,agencies have established data-gathering'activities witT a view toward setting standards of need in connection 

with specific programs. Some studies analyzed patterns of expenditure, but 

there was no official statistical poverty measure until the mid-1960s. The 

"War on Poverty" was announced January 8, 1964, in the president's Annual 

Message to the Congress on the state of the Union. In order to indicate 

the number and types of families that might be classified as "poor" under 

the various new anti-poverty programs, the Council of Economic Advisors 

(cEA), in its Annual Report 1964 issued in January of that year, designated 

as poor any family of two or more persons with an annual income of less 

than $3,000 or any person living alone (or with nonrelatives only) on less 

than $1,500. In assigning these as the critical thresholds, the Council 

cited a Social Security Administration (SSA) study appearing in the July 

1963 Social Security Bulletin which estimated $3,165 as the minimum income 

needed (in 1961) for a nonfarm family of two adults and two children. That 

study, "Children of the Poor" by ~ollie Orshansky, an economist with the 

Social Security ~dmin'istration, developed income criteria of need by- family 

size, but only -for families with children. 
In January 1965, the Social Security Bulletin contained another,article 

by Mollie Orshansky entitled, "Counting the Poor: ' Another Look at the Poverty 

Profile ," which updated and extended the. criteria to alL types of households. 

She used, as before, a ,concept of poverty based on budgets which can sustain. 

an adequate nutritional level. Instead of a single income cutoff like that 

cited by the Council, or'a measure which counts a constant proportion of the 

population, she used a slidiqg scale of income requirements for different 

family sizes and compositions. As an additional refinement, a lower income 

level was specified as the threshold for farm families. 

Using a special tabulation of 1963 incomes from the March 1964 Current 

Population Survey, Orshansky showed that, although the total number of poor 

persons was nearly the same as that obtained by using the CEA1s singledollar income cutoffs, the characteristics of the two populations differed 

greatly. Small families with requirements of less than $3,000 were no longer counted as poor. Larger families with many children and with requirements exceeding $3,000 were included. The number of children counted as 

poor increased substantially, while the number of childless couples, young 

and old, decreased. 

The Orshansky statistical definition appeared at a time when the need 

for a poverty measure was great: the Economic Opportunity Act of 1964 had 

recently been enacted. The Research Division of the Office of Economic 

Opportunity (0~0) adopted the Orshansky poverty neasure not only as a working tool for budget and planning purposes but also as an administrative 

guideline for program purposes. Political implications result from this. 

For example, the statistical differential for farm income could affect eligibility of farm communities and farm families for Federal financial assistance (although there is no evidence of the extent of the impact). 

The.Socia1 Security ~dministration continued to update the poverty 

thresholds annually for changes in food prices (as reflected in USDA estimates of economy food plan costs) and to apply each year's new thresholds 

to the Census Bureau income samples. At the request of the Council of Economic Advisors for trend data on poverty for its 1966 report, poverty counts 

were provided for all years back to 1959, the earliest date for which relevant Census Bureau data tapes were available. 

By 1968, there was concern about updating the poverty concept. The 

poverty cutoffs had been updated with the increasing price of the food bud- 

'get, but the cost of other consumer items as measured by the Consumer Price 

Index did not always change at the same rate. The 1960-61 BLS Consumer Expenditure Survey, published in 1965, suggested, that a smaller proportion of 

total income was spent on food 'than was reflected in the '195-5 Survey of 

Household.Food Consumption, which had been used for the original Orshansky 

calculations, althobgh methodo.logical differences in survey procedures 

blurred the difference. (Orshansky had noted the differences when she developed the poverty matrix.) In addition, the Department of Agriculture was 

pressing for lowering the differential between farm and. nonfarm poverty lines. ' 
The poverty measures, and the poverty population they delineated, remained quasi-official numbers until..August 1969, when the Budget Bureau 

designated them as the official statistical series to be published regularly by the Census Bureau. Agreement was reached by a Federal Interagency 

Committee headed by the Bureau of the Budget to continue the SSA index (Orshansky matrix) in order to have a stable measure for evaluation purposes, 

but to incorporate two modifications. One was to move the thresholds for 

1963 incomes forward by the annual average changes for all items in the 

Consumer Price Index (for urban middle-income families), rather than by the 

December-to-December changes in the price of the economy market basket of 

foods. The other was to set the poverty thresholds for farm residents at 

85 percent of the nonfarm thresholds, instead of the original 70 percent. 

In 1971, a new Technical Committee on Poverty Statistics met to discuss 

various proposals for changes in terminology and ,definitions of the poverty 

line and related statistics. The committee produced a report, Administrative and Legislative Use of the Terms "Poverty" and "Low Income", and agreed 

to a new definition of poverty areas. Because a complete technical review 

required considerable expenditure, it was not undertaken by the committee at 

that time. 

A more complete review was undertaken in 1973. At that time, three 

subcommittees were formed to study the poverty threshold, the measurement 

of non-cash income, and the improvement of the measurement of cash income. 

The consolidated report by the subcommit~ee chairmen recommended one immediate change in the threshold -- that the differential for farm and nonfarm 

families be eliminated. The recommendation was not adopted by the Office 

of Management and Budget (OMB). In addition, the consolidated report recommended that no other changes be made in the threshold until a new food plan 

incorporating revised nutritional standards became available. Substantial 

improvements in reporting cash income and non-cash income could not be made 

at that time. The subcommittee recommended a substantial research program 

to accomplish a major revision in the poverty thresholds after the proposed 

1975-1976 Food Consumption Survey. 

An edited collection of early publications dealing with the Orshansky 

poverty index is provided in Technical Paper I to this report. It includes 

a summary of the research recommendations of the technical committee just 

cited and.a detailed account of the-statistical construction of the poverty 

index, which is described next. 

Statistical Construction 

The SSA (Orshansky) index provides a range of income cutoffs adjusted 

by such 'factors as family size, age and sex of family head, number of children under 18 years old, and farm-nonfarm residence. Families and unrelated 

individuals are then classified as above or below the. poverty level and also 

by the amount of their income shortfall. The index is an attempt to specify 

in dollar terms a minimum level of income adequacy for families of different 

types in keeping with American consumption patterns. 
Orshansky developed her index from an estimate of the outlay with which 

American households with low incomes might provide household members with 

diets meeting nutritiohal goals as established by the National Academy of 

Sciences-National Research Council in the Recommended Dietary Allowances 

(RDA). Specifically, Orshansky's thresholds were based on the cost for 

the Department of Agriculture's economy food plan, originally developed in 

1961 as the least costly of the USDA's family food plans at four ievels of 

cost -- economy, low-cost , moderate-cost, and liberal. 21 The economy plan 

specified, for men, women, and children of different ages, quantities of 11 

different food groups that together made up a nutritious diet. The plan 

reflected both the RDA and food use of low-income households surveyed in 

the USDA's 1955 Household Food Consumption Survey. Between 1961 and 1967, 

the cost of foods in the economy plan was estimated annually. In 1967 

procedures for costing the food plans were revised to reflect food use from 

the USDA's 1965-66 survey. Because of demographic problems with the 1965-66 

data for very low-income households, however, the cost of the economy plan 

was estimated at 80 percent of the low-cost plan between 1968 and July 1975, 

when the plan was replaced by the thrifty food plan (see Technical Paper 

XII). The USDA economy plan specified quantities of food for 20 age-sexcategories, reflecting each category's nutritional and caloric requirements. 

Costs for any family could be figured by totaling costs for plans for the 

age and sex of family members and adjusting the total by economy-of-scale 

factors for families of different sizes. 

Orshansky used the costs for the plan to estimate costs for 62 different family types, classified on the basis of sex and age of head, number of 

persons in the family, and number of related children under 18. The final 

step in producing the Orshansky dollar cutoffs whs to add to. the food 

costs an es'timate of the additional income needed to purchase necessities 

other than food; this estimate was based on the inverse of the percent of 

incane an average American family deyoted to food expenditures as reported 

in the 1955 Household Food Consumption Survey.. 

The proportion of income expended for necessities -- for food, in . 

particular -- is indicative of the relative well-being of both individuals 

and the society in which they live. The 1955 survey reported an average of 

one dollar for food outlay to three dollars of family income. Using this 

ratio, Orshansky set the poverty level for families of three or more 

persons at three times the cost of the economy food plan for that size and 

type of family. For smaller families and persons residing alone, slightly 

higher multiples were used to compensate for the relatively higher fixed 

expenses of these smaller households. 

It should be noted that the'income definition used in the Household 

Food Consumption Survey is income after taxes. The poverty cutoffs, 

however, are applied 'to before-tax income. Generally, the poor do not pay 

Federal income taxes. However, some poor families do pay state income 

taxes, and those who work usually pa$ a 5.85 percent Social security tax 

on their earnings. These taxes are excluded in the Household Food 

Consumption Survey. 
Finally, the SSA poverty cutoffs allowed for the fact that farm families customarily obtain housing and food as part of the farm business operation, rather than by direct expenditure. On the bgsis of data available at 

that time, a farm family was assumed to need only 70 percent as much cash to 

maintain a canparable level of living as a corresponding nonfarm family. 

Hence, proportionately lower poverty thresholds were set for farm families 

than for nonfarm families, resulting in 124 thresholds in all. The 1969 

Federal Interagency Committee changed the farm-nonfarm differential to 

85 percent. There was a lack of conclusive evidence on which to substantiate the earlier farm-nonfarm differential or to revise it. However, USDA 

studies of equivalent levels of living based on the 1961-62 Consumer 

Expenditure Survey and the increasing number of farm residents who derive 

much of their income from nonfarm work supported the Agriculture Department's contention that the 70 percent figure was unjustifiably low. 

Table 1 shows the entire set of 0rshaniky poverty indexes for income 

in 1974. Because it is impractical to use the entire set of 124 poverty 

lines for anything other than Census surveys or computerized analytical 

studies, the Census Bureau publishes the indexes in a simplified form as 

weighted average cutoffs. The simplified version of Table 1 is displayed 

in Table 2. For many purposes it is inconvenient and unnecessary to 

consider 77 weighted average cutoffs, since it would be more convenient 

to refer to only one number for each family size. Frequently cited cutof fs are the weighted average threshold for a nonfarm family of four and 

for an elderly person living alone, which in 1974 were $5,038 and $2,364, 

respectively, as indicated in Table 2. For 1975 these cutoffs are estimated to be $5,500 and $2,580, respectively. 

The SSA thresholds were originally developed in terms of 1963 incomes 

and prices. Subsequently adjusted only for price changes, they were extended forward without 'modification through 1967 and backward to 1959. These 

changes were originally based on changes in .the December cost of the economy food plan market basket. During the late 1960s, the cost of the economy 

food plan did not increase as much as overall prices: Thus, price changes 

between 1959 and 1968 were not the same as changes in the poverty threshold. 

As a result of deliberations of the ~'ederal Interagency Committee in 1969, 

annual adjustments in the low-incane thresholds were thereafter based on 

average annual changes in the Consumer Price Index (CPI) . 

In recent years, changes in the CPI may not, however, have reflected 

all the changes in the living costs incurred by the poor. For example, 

the poor tend to spend a higher proportion of their income on food than 

the total population. Between 1972 and 1973, the cost of the food component of the CPI increased considerably more than the total CPI (14.5 

percent compared to 6.2 percent). Figure 1 illustrates the annual changes 

between 1959 and 1975 in the cost of the economy food plan, compared to 

the changes in the CPI for all items and for only the food component. 
Table 1. Poverty Cutoffs in 1974 by Sex of Head, Size of Family, and 

Number of Related Children Under 18 Years Old, by Farm-Nonfarm Residence 

NONFARM 

Size of Family Unit 

Male Head 

1 Person (Unrelated Individual): 

Under 65 years 

65 Years and Over 

2 Persons: 

Head Under 65 Years 

Head 65 Years and Over 

3 Persons 

4 Persons 

5 Persons 

6 Persons 

7 or More Persons 

Number of Related Children Under 18 Years Old 

Female Head 

1 Perion (Unrelated Individual) : 

Under 65 Years 

65 Years and Over 

2 Persons: , 

Head under 65 Years 

Head 65 Years and Over 

3 Persans 

4 Persons 

5 Persons 

6 Persons 

7 or More Persons 

None 6 

FARM 

5 

Male Head 

1 Person (Unrelated Indiv 

Under 65 Years 

65 Years and Over 

2 Persons:, 

Head Under 65 Years 

Head 65 Years and Over 

3 Persons 

4 Persons 

5 Persons 

6 Persons 

7 or More Persons 

Female Head 

idual) : 

$2,258 

2,030 

1 Person (Unrelated Individual): 

Under 65 Years 

65 Years and Over 

2 Persons: 

Head Under 65 Years 

Head 65 Years and Over f 

3 Persons 

4 Persons 

5 Persons 

6 Persons 

7 or More Persons 

SOURCE: U.S. Bureau of the Census, "Characteristics of the Population Below the Poverty Level: ' 

1974," Current Population Reports, Series P-60. No. 102, Table A-2. 
Table 2. Weighted 'Average Poverty Cutoffs in 1974 

by Size of Family and Sex of Head, by Farm-Nonfarm Residence 

* 4 Persons 

5 Persons 

6 Persons 

7 or 'More personsa 

Size of Family Unit 

SOURCE: U.S. Bureau of the Census, "Characteristics of the Population Below the Poverty Level: 

1974." Current Population Reports, Series P-60, No. 102, Table A-2. 

a Represents an average for families with 7 or more persons. 

Statistical Series on Poverty 

1 Person (Unrelated Individual) $2.487 $2,495 $2,610 $2,413 $2,092 $2,158 $2,029 

14 to 64 Years 2,557 2,562 2,658 2,458 2,197 2,258 2,089 

65 Years and Over 2,352 2,364 2,387 2,357 2,013 2;030 2,002 

2 Persons 3,191 3,211 3,220 3,167 2,707 2,711 2,632 

Head 14 to 64 years ' 3,294 3,312 3,329 3,230 2,819 2,824 2,706 

Head 65 Years and Over 2,958 2,982 2,984 2,966 2,535 2,535 2,533 

3 Persons 3,910 3,936 3,957 3,822 3,331 3,345 3,133 

Total 

Since 1968, the Census Bureau has regularly published information on 

the number and characteristics of poor persons and poor families, using the 

concept, of poverty operationalized by Orshansky in the matrix of 124 poverty 

thresholds. The number of poor persons from 1966 to 1974 and the percent of 

the population in each of these years is shown in Figure 2. , 

The major data source provid'ing annual poverty counts is the Current 

population Survey conducted in March of each year by the Census Bureau. In 

addition, the Decennial Census provides detailed information on the lowincome populat.ion at 10-year interyals. Both sources make available data 

'on many characteristics of the. poverty population, including age, race, 

. sex, education, weeks worke.d, and family type; these are published in the 

Current Population Reports P-60 series-31 and in Chapter D, "~etailed 

~haracteristics," of Volume I of the 1970 Census of Population. Selected 

characteristics of persons and families below the poverty level in 1969 are 

presented in Chapter C for each of the states, counties, SMSAs, urbanized 

areas, and urban places having a population of 2,500 or more. - 41 

-- - 

Nonfarm .- 

Male Female 

Head Head 

Farm .- Male Female I Head Head 
Average 

Annual 

Percent 

Change 

15 

16 

13 

12 

11 

10 

9 

8 

7 

6 

5 

4 

3 

2 

1 

0 

-1 

-2 

-3 

Key: - = CPI, all items ---- 7 CPI, food 

......... = Economy Food Plan 

- 

- 

- 

- 

- 

- 

- 

- 

- 

- 

- 

- 

- 

- 

- 

7 

- 

- 

- 

1959 1960 196.1 1962 1963 1964 1965 1966 1967 1968 1969 1970 1971 1972 1973 1974 

60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 

SOURCE: U.S. Bureau of the Census, "Characteristics of the Low-Income Population: 1973,'' Current Population Reports, Series P-60. 

No. 98 (January 1975).Table A-4. 

Bureau of Labor Statistics, Monthly Labor Review (June 1974, June 1975).(Provided 1973-74 percent changes.) 

Note: In 1969 the official poverty cutoff was updated by price changes in the total CPI rather than the economy food plan. 

a The Department of Agriculture has continued to prepare and ma'ke avai-lable data on the economy food 

plan through July 1975. The composition in the plan changed in 1966 so that comparable data are not available after 1966-67. 

Figure 1. Average Annual Percent Change 

in the Cost of the Economy Food Plan and in the 

Consumer Price Index (All Items and Food), 1959-1973 
Number of Persons in Poverty 

Percent of 15 

Population 

10 

5 

0 

Percent of Population in Poverty 

12.6 12.5 

11.9 ' 

t L 

11.1 11.6 

Source Legend: -- U.S. Bureau of the Census, "Characteristics of the LowIncome Population: 1373," Carrent Population Reports, 

Series P-60, No. 98 (January 1975). 

-- U.S. Bureau of the Census, 1970 Census of Population, Vol. 

I, pof Chap. D, "Detailed 

Characteristics." 

Figure 2. Number of Persons in Poverty 

and Percent of Population in Poverty, 1966-1974 
As Figure 2 shows, the 1970 Census and the 1970 Current Population 

Survey (CPS) yield different estimates of the poverty population for 1969; 

the number reported in the Census is 27.4 million poor persons, compared 

with 24.1 million in the CPS. The apparent inconsistency has two explanations. Although both surveys use a similar concept of income and the same 

definition of poverty, the income collected in the CPS by trained interviewers is more accurate than the less detailed income reported by selfenumeration in the 1970 Census. Further.more, college students, who are 

generally enumerated at their family home in the CPS, are enumerated at 

their college residence in the Decennial Census, tending to increase the 

number of low-income persons in that data source. 5/ It is more important, 

however, to recognize the limitations shared by bo-fh the Census and the CPS 

as sources of data for measuring the low-income population. In both surveys 

there is an undercount of persons, and some sources of income are known to 

be substantially underreported. This underreporting is particularly true, 

among sources of income affecting the poor, the Social Security and welfare . payments. The number of poor persons would be substantially reduced below 

both CPS and Census estimates if underreporting did not occur in these 

surveys. This is discussed further in Chapter 111, Data Availability and 

Limitations. 

The most important practical difference between the Current Population 

Survey and the Decennial Census is the fact that the CPS cannot yield valid 

estimates of the poverty population at the state level. The annual March 

CPS, while nationally representative, can provide poverty counts only for 

the ten Federal regions on the basis of its sample of about 47,000 households. The Decennial Census, on the other hand, does provide information 

on the poverty population for states and for Standard Metropolitan Statistical Areas ( SMSAS) having a population of 250,000 or more. - 4/ 

A more detailed discussion of these data bases and their limitations 

for measuring poverty is contained in Chapter. -111, Data Availability and 

Limitations, and in Technical Paper.IX, Inventory of Federal Data Bases ., 

Related to the Measurement of Poverty. 

Administrative Usage of Poverty Measures 

Many Federal programs are designed to help the poor (needy, low-income, 

disadvantaged) and use a poverty measure or income eligibility standard for 

administrative purposes. Although the Orshansky measure, which was originally developed as a statistical measure, has been widely adopted, it is 

not the only administrative measure of poverty used. Moreover, the official measure is usually modified to some degree, and frequently it is used 

in conjunction with still other criteria. Often programs use different 

definitions of income, increasing diversity st ill further. Such variation 

in Federal administrative practice occurs because of the broad spectrum of 

objectives covered by these programs. 

Federal programs .for the poor differ in design. Some programs are 

devised to aid areas and some are devised to aid families or individuals 
directly. In the former case, the poverty measure is used in an allocative formula to distribute the appropriation, typically a fixed amount, 

among the subunits of the nation,designated by the legislation. In the 

second type of program, a poverty cutoff may be used as an income eligibility criterion for individual applicants. 

Title I of the Elementary and Secondary Education Act, as amended, is 

an example of a program using a poverty measure as part of an allocative 

formula. The appropriated funds are distributed partly on the basis of the 

number of poor school-age children in each county. Where county boundaries 

are not coterminous with school districts, county amounts are then suballocated to the school districts by state departments of education. Children 

living in school attendance areas which have an incidence of poverty as high 

as or higher than the district-wide average are eligible for Title I services. Children are selected for participation on the basis of educational 

deficiencies, regardless of family income. . 

The Community Services Administration (CSA), fornerly the Office of 

Economic Opportunity, provides an example of administrative use of the 

Orshansky measure for determining income eligibility. Uniform income eligibility standards are issued for poverty-related programs administered by 

CSA. Based directly on the official Federal poverty measure, these guidelines eliminate many of the distinct ions and smooth some of the ,remaining 

variations. The CSA poverty thresholds allow for variations by family size, 

with equal increments for additional family members. Cutoffs for farm 

families are 15 percent below those for nonfarm families. In addition, 

two major geographic variations are partly taken into account by raising 

these thresholds by 25 percent for Alaska and by 15 percent for Hawaii. 

The CSA th,resholds are updated annually according to the change in the 

Consumer Price Index. Table 3 presents the 1974 CSA poverty cutoffs for 

the continental United States, along with the comparable weighted average 

cutoffs from the Orshansky system from which these were derived. For 

each of the weighted Orshansky averages in Table 3, the numbers in 

parentheses indicate the range of variation across all other thresholds 

for the same family size. 

The basic dichotomy between allocative and eligibility .uses is not 

necessarily exclusive, for a single legislative act may contain both an 

allocative formula for distributing fixed program funds and eligibility 

criteria for determining which individuals in' each area are entitled to i 

receive assistance. Furthermore, entirely different poverty measures may 

be used in the various stages of one program, as with the Comprehensive 

Employment and Training Act (CETA). The measure of poverty used for distributing CETA funds is a single-dollar threshold, with the allocation based 

partly on the number of families in an area with an income below that level. 

At the local level, however, individual eligibility is determined in part by 

an income criterion based on a modified Orshansky measure and in part on 

such other factors as unemployment or underemployment. 
Table 3. 1974 Orshansky Poverty Thresholds and 

Community Services Administration Income Eligibility Guidelines 

Community Services 

Administration Orshansky Poverty Measure 

Family Size I onf farm^ I arm^ I Nonfarm I Farm . 

1 person $2590 , $2200 $2495(2358:~659)~ $2092(2004-2260) 

2 persons 3410 2900 3211(2948-3724) 2707(2506-3165) 

3 persons ' 4230 3600 3936(3568-4223) 3331(3033-3590) 

4 persons 5050 4 300 5038(4900-5252) 4302 (4165-4465) 

5 persons 5870 5000 5950(5781-6232) 5057(4914-5298) 

' 6 persons 6690 5700 6699(6457-7087) 5700(5489-6024) 

SOURCE: Federal Register, Vol. 40, No. 132 (July 9, 1975). p. 28794. 

U.S. Bureau of the Census. "Characteristics of the Population 

Below the Poverty Level: 1974,".Current Population Reports. 

Series P-60, No. 102, Table A-2. 

a All States except Alaska and Hawaii. The thresholds for Alaska 

are 25 percent higher. and those for Hawaii are 15 percent higher. 

Figures in parentheses indicate the 'range of variation across the 

thresholds in the measure. 

In many cases the Orshansky thresholds are used but in a modified form. 

The most common variations of the Orshansky measure are scaling the thresholds by a multiplicative factor, as is done, for example, in child nutrition 

program-s. Another common adaptation is to include status, as a recipient of 

welfare, in conjunct ion with the thresholds, to identify, target populations. 

This may be done to avoid penalizing those states whose higher welfare 

benefits may have brought many families out of poverty, or to insure that 

benefits which may lead to self-sufficiency are provided to welfare families. 

Thus, a person may be 'eligible for benefits in a program either by the fact 

that his family income falls below the poverty cut-off or because he is in 

a family receiving welfare payments. In addition, various characteristics 

of the recipient, such as employability, are sometimes used to determine 

categorical eligibility., 

Measures of poverty or income eligibility and concepts of need other 

than the Orshansky measure are also used in Federal programs. A singledollar threshold that is unchanged for family size is currently used as an 

eligibility criterion in the College Work-Study program authorized by the 

Higher Education Act of 1965. This type of measure is also used in the 

a1 locat ion formula of the Comprehensive Employment and raini in^ Act and was 
used in the allocation of funds under'Title I of the Elementary and Secondary 

Education Act until 1974. 

Another measure of income eligibility is one based on some percentage 

of median income. Title XX of the Social Security Act (social services) 

adopted 80 to 115 percent of median family income in each state as its 

standard. Title I1 of the Housing and Community Development Act of 1974 

uses 50 and 80 percent of median family income in the "area" as its eligibility,criteria. The use of standards based on median income is a relatively new development in Federal programs, although there is precedence 

in social service programs. 

Finally, administrative and legislative references abound in terms that , 

target Federal programs to the "disadvantaged," "needy," "dependent," I I economically disadvantaged," and "individuals whose income and resour'ces 

are insufficient." In many such references, the terms are employed without 

definition. The various administrative and legislative uses of poverty 

terminology are described more completely in Technical Paper 11. 

There are several arguments in favor of using an official poverty 

measure. Determining public policy, setting program goals, and evaluating 

program success all benefit from the external referent provided by an 

official measure, even if the measure is altered to fit programs. It 

a1 lows canparisons over time. Also, various Federally funded programs 

are required by law to identify their target populations in terms of lowincome status or extent of poverty in terms of this official poverty matrix. 

There may be value, however, in updating or revising the present measure. 

Moreover, publication of more than one series of poverty statistics may be 

desirable. There are advantages, both statistical and administrative, to 

other concepts. 

Quite obviously, it is easier to agree that some official measure of 

poverty is useful than it is to agree on its precise definition and applicability to specific uses. Conceptual, statistical, and administrative 

constraints interact in a very complicated way; In attempting to establish 

as sound a methodology as possible, one must accept at the outset that no 

poverty measure will be purely scientific, free of value'judgments. 

Even if the most fundamental principles of "well-being" and "poverty" 

were clearly articulated and universally agreed upon, some debate would 

continue about whether or not any one poverty measurement series could or 

should be used as an index of national achievement, as a source of statistical data for the design and evaluation of programs, and as an administrative parameter in Federal programs. The focus of this report is on 

definitions which can be used to help policy makers design and evaluate 

programs. However, the current administrative uses cannot help but. 

affect the analyses in this report. 
NOTES TO CHAPTER I 

1. See, for example, Low-Income Families and Economic Stability, 

Staff of the Subcommittee on Low-Inccme Families, Joint Committee on the 

Economic Report (washington, D. C.: Government Printing Office, 1949). . 

2. See E. Cofer, E. ~rossman, and F. Clark, Family Food Plans and 

Food Costs. U.S. Devartment of Agriculture. HERR 20 (November 1962). 

3.. See, in particular, Series P-60, Nos. 54, 68, 76, 81, 86, 91, 

95, 98, and 102. 

4. Further ,information on data availability from the 1970 Census is 

contained in Low-Income Data from the 1970 Census, Data Access Description, 

No. 29, Collection, Evaluation, and Processing Series CEP-7 (May 1972). 

5. Another difference between the'two surveys does not affect their 

differential poverty counts. The CPS excludes the institutional population 

and all members of the Armed Porces living in barracks. Although the Census 

includes these groups, the institutional populations are not included in 

the poverty universe. because of the difficulty of classification by income. 
11. CONCEPTS OF POVERTY MEASUREMENT 

The term poverty connotes a large and complex set of economic, social 

and psychological conditions.l/ Most people would probably agree that anyone who does not have enough Tesources to cover their perception of his 

needs is "poor" and that needs could include food stuffs if a person were 

hungry or medical services if his health were poor. Beyond this basic 

not ion of poverty people have different individual views and philosophies. 

Poverty definitions serve two quite different functions for public 

policy purposes: first, they allow program administrators to identify 

individuals or families that require and are eligible for help. Second, 

they are essential to policy makers in the design and evaluation of 

program,s to help the poor. Often the,sane definition can serve both 

purposes. But, there are situations in which it is more appropriate to 

separate the two. For examplej in determining whether a family is eligible for medical assistance, a definition might include some measure of 

the family's "medical needs" compared with its available resources. On 

the other hand, for designing programs to meet medical needs, it may not 

be necessary to identify medical needs by individual family; aggregate 

statistics may be all that is necessary. 

The impetus for undertaking a study on the measurement' of poverty 

came from Congressional concern over the allocation of funds distributed 

to school districts under provisions of Title I of the Elementary and 

Secondary Education Act. The Title I $formula reflects the Congressional 

view that poverty and education are related and allocates proportionately 

more funds to school districts with higher incidences of poverty. 

Resources are given to those schools whose attendance areas have concentrations of children from low-income families so that local school 

programs can be developed for those children who have need of special 

' educational assistance. 

A "thorough evaluation and study of compensatory education programs'' 

is being undertaken by the National Institute of Education (NIE) under the 

instructions of section 821 of the Education Amendments of 1974 (P.L. 93- 

380). The study is to be completed by September 30, 1977 -- in time to 

provide Congress with information during its deliberations on the reauthorization of Title I. The NIE study will be a comprehensive examination 

of educational disadvantage. In contrast, the present study is on poverty 

measures, one of which is used in the Title I allocation formula. 

Social and Cultural Conceptions of Poverty 

Some social scierit ists would like, to use general "social indicators" 

as measures of poverty. Attention has been focused on ways, other than 

lack of money, in which the poor differ from the rest of socie~y -- on 

now the poor compare with the rest of society in terms of "well-being," 

"quality of life," and "social health." Some of the indicators which I 
have been examined are adult and infant mortality, morbidity, nutrition 

and malnutrition, literacy and educational levels, housing, and neighborhood conditions (such as overcrowding and criminal victimization). 

It is not so much a non-economic measure of poverty which is desired, 

but a conception of poverty that goes beyond simple economic notions. The 

causes, correlates, and solutions to the problems of poverty cannot be 

limited to economic ones. However, economic attributes never correlate 

perfectly and sometimes correlate quite poorly with the psychological and 

cultural behavioral patterns often thought of as characteristic of the 

poor. Therefore, social indicators which are meant to be a measure of the 

"quality of life" of the' poor cannot be limited to the poor. It may be 

possible for further research using a variety of economic measures of 

. . poverty to provide more insight into the relation between lack of 

resources and quality of life. 

I Economic Measures of Poverty 7 

Economic definitions of poverty can be formulated in two rather different ways. In one, poverty is defined specifically in terms of what the 

overall population has. These are usually called relative definitions. A 

purely relative measure defines a fixed percent of the population as poor. 

A quasi-relative measure defines the poor.as those whose income is below a 

fixed percent of the median income. A commonly proposed purely relative 

definition is the lowest quintile or quartile. A commonly proposed quasirelative definition of poverty would set the'threshold at 50 percent of 

.median income. 

In the second type of definition, poverty is defined in terms of a 

family's ability to purchase a specified market basket of goods and services. These are usually called absolute definitions because the cost of 

the market basket is determined objectively and serves as the threshold. 

However, the composition of the market basket is subjective and represents 

a judgment about some minimally acceptable level of living. Since this 

judgment varies with the general standard of living, absolute definitions 

of poverty .are meaningful only with reference to a given period and place. 

Underlying many conceptions of poverty is some notion of the ideal 

(or at least an acceptable) shape of 'the income distribution. Formal 

expressions of some minimally acceptable amount of' inequality go as far 

back as Plato, who suggested that in an ideal society no man should be 

more than four times richer than any other (The ~aws). A modern dayphilosopher, John Rawls, has suggested that a ju~stincome distribution 

would be that which people would selec't if they did not know in advance 

where on the distribution they would be. He believes that the amount of 

inequality that would be acceptable would be that amount which would 

produce the greatest amount of well-being for the least advantaged. 21 

Rawls' work was widely acclaimed when first' published but has latelybeen receiving extensive theoretical criticism. 
Poverty need not, however, be conceived of in ethical, terms. It can 

also be simply a notion of what it takes to "get along," without regard to 

any obligation to those who have less than that. Over the years Gallup 

polls have included questions on the minimum amounts of money needed 

by families to get along. These questions address only the bottom portion 

of, and not the entire, income distribution; they do not address issues 

of redistribution. They also do not consider the difference between 

what people think they, themselves, would consume and what they would 

be willing to be taxed for in order to provide for others. 

A fundamental decision in any of the poverty definitions is how to 

determine the level of the threshold, that is, the level below which 

people are designated poor. This is clearly the case in the absolute 

definition. However, the fixed percent in the purely relative definition 

or the fixed percent of the median in a quasi-relative definition must 

also be arbitrarily chosen. Those measures based on community views are 

to some extent free from this difficulty. 31 The Council of Economic 

Advisors Report in 1964 chose 20 percent, but justified it by referring ---- 

to a study using a market basket approach. The quasi-relative definition 

most frequently used is 50 percent of the median income, chosen in 1967 

by Victor Fuchs as an arbitrary but reasonable number. 41 It was at - about the same level as the Orshansky level in 1959. 

The relative definitions arose largely in response to difficulties 

inherent in revising an absolute level to reflect growing aff luence. Even 

when an absolute threshold is adjusted for changes in the level of prices, 

a diminishing proportion of the population is classified as poor when income 

shifts upward due to increases in real productivity over time.' 'Purely relative measures, on the other hand, are criticized because the poverty population will be the same fixed percent whether examkned in different places 

or at different times, even though the level in real terms will be different. 

Similarly, a definition which is a fraction of the median income has been 

criticized because, although it does allow for the possibility of diminishing 

or eliminating poverty, this will happen only if the income distribution 

changes. Since the overall income distribution has not changed measurably 

during this century, analyses using this measure differ little from those 

using a purely relative measure. 

For all economic definitions, setting the level of poverty and defining 

income are required. 

Setting a Poverty Level 

Needs can be defined as what is required to survive or to get along 

at a "minimum standard" compared to the rest of society. Until the last 

two centuries, nations generally had little choice except to define it 

in terms of survival; only a small proportion of the population did much 

better than subsist. But typical levels of living improved in the last 

two centuries, and some people began to look at poverty as a comparative 

state. Adam Smith in 1776 (wealth of Nations) wrote: ---- - 

, 

2 1 
By necessaries I understand not only the commodities which 

are indispensably necessary for the support of life, but 

whatever the custom of the century renders it indecent for 

creditable people, even of the lowest order, to be without. 

By the 20th century, this view of poverty as a comparative state 

gained considerable support in the United States. The budgets prepared 

by the Bureau of Labor in 1907 mark a distinct turning point in the concept of poverty: budgets were devised to meet "minimum standards" (i .e., 

subsistence) as well as a "fair standard" -- to include goods needed for 

the "development and satisfaction of human attributes.'' It is to be 

noted, however, that more recent budgets developed by the BLS since 1948 

for a city worker's family have not centered on the concept of poverty 

but on various levels of living for a year-round full-time worker in the 

United States. > 

Most Americans today would probably agree that a poverty standard 

ought to include the ability to satisfy needs in addition to those 

necessary for survival. However, just what the minimum standard should 

be is subject to considerable debate. 

I Standards of Physical Needs 

Two alternative techniques were used in early studies to calculate 

resources needed to. achieve 'subsistence: surveys of actual expenditures 

o£ the poor, and the "pricing out" of 'a hypothetical market basket. Both 

techniques have survived to some extent today, but only the latter is 

discussed here in depth. The former,'surveying actual expenditures, 

requires some notion of the total level of resources considered adequate, 

which i's often derived from a consideration of the total resource distribution. Development of a hypothetical market basket requires the 

determination of those commodities or goods in specified amounts to be 

included in the market basket. Currently, state welfare agencies use 

this approach as one consideration in determining the size of payments. 

The problem with determining a measure using the hypothetical market 

basket approach is that there is currently no objective method for determining all needs. The two components most often considered are food and 

housing . 

Nutritional standards exist from several sources. Some of the more 

prominent are: Recommended Dietary Allowances, Eighth Edition, National 

Academy of Sciences (RDA); Handbook of Human Nutritional Requirements, 

Food and Agricultural Organization of the United Nations (FAO); and 

Standards for Evaluation of Daily Dietary Intake used in the Health and 

Nutrition Examination Survey United States 1971-72 (HANES Survey). These 

standards specify amounts of nutrients for various age-sex combinations. 

The standards can be translated into combinations of foods that might be 

expected to sustain life and good health. Furthermore, it is possible to 

examine diets and measure the actual intake of nutrients of individuals 

or subgroups of the population. But, it is important to note that even 
the nutritional standards -- that is, the amount recommended for optimal 

consumption or to avoid consequences of nutritional deficiency -- are nqt, 

without question. Many countries use lower standards and even in this 

country there is disagreement as to whether the margin of safety is set 

too high. 

Moreover, adequate nutrition can be obtained from diets varying 

widely in- quality and cost. The determination of which foodstuffs and in 

what -quantity constitute an appropriate diet even when empirically based 

requires some arbitrary assumptions. Finally, studies have shown that, 

even at upper income levels, 30 percent or more do not consume "nutrit ionally adequate" diets -- diets that ,provide recommended amounts of all 

nutrients considered. 

There are no commonly accepted standards of need for housing. It is 

important to distinguish here between housing standards and standards of 

- need for housinn. - There is no lack of housing - standards such as building - codes which define acceptable methods of construction and materials or 

home inspection criteria us'ed in connection with private or Federally 

supported loans.. Housing standards also pertain to the existence of 

facilities (toilet, bath, sink, electricity), to the level of maintenance 

(both structural and sanitary), and to occupancy. 

t 

None of these housing standards, however, are widely accepted as a 

standard of need. They do not tell what kind or how much housing is 

necessary for the basic health of occupants, although there may be some 

relationship. Currently, there is little agreement about the character 

of a threshold description of housing, without which families are considered to be deprived or poor. Despite this, the Housing and Community 

Development Act of 1974 refers to "decent, safe, and sanitary dwellings," 

but without setting standards. 

One of the reasons why standards of need for shelter are so difficult 

to construct is that differences due to climate, to type of residential 

area (farm-nonfarm, inner city-suburb), t.0 type of dwelling (high-rise 

apartment., duplex, single family dwelling, mobile home), and to type of 

financial arrangement (renting, buying, joint ownership) require highly 

flexible standards of need. For example, most Northern residences need 

heating systems, some Southern residences do not. 

A good example of the theoretical problems associated with standards. 

of need for housing is the "number of rooms" component sometimes used for 

snalyt ical purposes. By this definition, a house or apartment is considered 

substandard if the number of rooms is less than 1.01 rooms per occupant. 

(Previous definitions used 2.0 and then 1.5 occupants per room). While 

this may appear reasonable for small families,, it is not when applied 

to large families. 

Nonetheless, it may yet be possible to develop a standard of need 

for housing based, perhaps, on minimum floor space per person and on 
existence of basic facilities like running water, power, and on the maintenance of acceptable temperatures. 

For other categories bf basic needs, there are no generally accepted 

scientific standards. Thus, to measure poverty using such an approach 

requires either resolving the conceptual problems involved in determining 

such standards, or using less rigorously defined notions of deprivation. 

Chapter 111, Data Availability and Limitations, describes the significant 

surveys and statistical series which are applicable to the subject of 

standards. In Chapter IVY we explore those alternatives which can be 

derived from existing data. 

Adiustments for Familv size and Com~osition 

Thus far, we have discussed family needs as though all families were 

alike or could be averaged. The needs of individuals or families clearly 

depend on their circumstances, as well as on the ethical or normative 

principles of society in general. One normative principle calls for 

equal treatment for families enjoying equal well-being. In the case 

of poverty, equal well-being is usually interpreted as economic wellbeing. Unfortunately, the only straightforward application of such a 

principle is that families which are identical in every relevant respect 

should be treated equally. Although some theoretical work in consumption 

economics has been directed to determining equivalent incomes for families 

that differ in size and composition, its application is constrained both 

because of theoretical and data limitations. 

Recently, there has been some question of whether tax and poverty 

programs ought to consider the need differences of particular family 

groups. The argument against adjustments has taken two forms. First, 

there has been concern that coupling tax deductions or income maintenance payments to family size provides incentives for having larger 

families. Empirical evidence on this issue is li~ited and conflicting, 

and no definite resolution is possible at present. 

The second, more subtle, argument against making such adjustments 

comes from the comparatively new theory of "human capital" in economics. 

It argues that, to a large extent, family configurations can be viewed 

as the result of a rational, deliberate choice, in which the costs and 

benefits of family size are weighed and optimal familial relations are 

decided. Decisions on living arrangements -- like whether a woman marries, 

lives alone or lives with her grown children -- are considered the re,sult, 

to a significant degree,, of the same rational procedure conventionally 

assumed to explain a consumer's choice between apples and oranges. To the 

extent that one believes that the decision to marry or to have children 

is the result of deliberate choice, small families may not. be better off 

than large families with equal incomes. The human capital argument does 

not state that family physical needs are not greater the more persons 

there are, but that non-monetary benefits may balance the greater physi-' 

cal needs. 
This position has been attacked on two basic grounds. First, the 

assumption of rationality and control in decisions of marriage and 

children has been challenged. Second, the argument assumes that a family 

is somehow better off for having achieved its status voluntarily. Most 

opponents have concentrated on the ironic inconsistency that some members 

of the family may not have been volunteers. 

The majority view is that poverty budgets should be keyed, to some 

extent, to family size and composition. Determining the nature and size 

of adjustments, however, is no easy matter. First, the particular 

attributes of family structure which create need differences must be 

identified. Family size is the first and most obvious candidate: some 

needs such as food and clothing increase with family size. Indeed, most 

state welfare departments, as well as the Federal income tax system, allow 

adjustments for family size. Age, both of children and of the head of the 

household, also appears to influence need. Employment status of the head 

of household, mother's employment status (and child care needs), and 

residence are also suggested as possible determinants of need. 

Both the relevant attributes and the size of the adjustment to be 

made for each particular attribute need to be determined. The basic 

problem here, and one which has occupied social scientists and policymakers since Engel's work in the nineteenth century, is to quantify 

equivalent living scales for families of different types. - 51 

The simplest technique available to adjust budget requirements for 

differences in family size is a simple linear expansion: each individual 

is assumed to have equal "needs" -- needs which are independent of either 

his own characteristics or the characteristics of the family unit to 

which he belongs. The linear expansion technique assumes that. needs are 

constant. across individuals; only the number of people and not the type, 

of people is relevant to budget requirements, and there are no economies 

of scale. 

Empirically, however, it has been determined that needs do vary with 

individual characteristics, particularly with age and sex. In addition, 

the linear expansion technique does not take into account the degree to 

which sqme conskption goods, like television sets and automobiles, are 

shared without proportionate increases in costs as family size increases. 

While the old adage that "two can live as cheaply as onet' is no doubt an 

expression of romantic optimism, the empirical evidence does indicate real 

savings from shared expenses. \ 

Early consumption studies sugge,sted that the percentage of income a 

family would spend on a particular group of goods would change as the 

level of the family's income changed. For some goods -- termed necessities -- the percentage would decline as income level increased. In 

general, then, two equivalently canposed families with different incomes 

would spend different percent ages on given items ; the higher-income 

family would, in general, spend a smaller percentage of its budget on 
necessities such as food. Some current "equivalent. income" .techniques 

assume that families which spend equal proportions of their income on 

food have attained equal levels of living. 61 - 

There are several problems with this technique. The underlying 

assumption of equivalence is arbitrary. Also, it assumes that the degree 

of. satisfaction achieved is independent of the absolute level of expenditure (or consumptidn). There is no empirical evidence or theoretical 

basis to support such an assumption. Furthermore, the results are sensitive to the commodity chosen for the index. Percentage of income spent 

on food has frequently been used in the past; however, the proportion of 

income spent on housing may be as good a measure 6f well-being and leads 

t'o quite different equivalence scales. The scaling indzx will differ 

depending on which commodity is used. .Chapter 111 describes the consumption surveys which can be used to derive equivalence scales. chapter IV 

further examines the equivalence scales presently used. 

The equivalence scale underlying the current poverty matrix is 

different from those described above. It attempts to derive the equivalence Scale on the basis of need rather than actual expenditures. Food 

costs for families of different age-sex compositibn (family types) were 

derived by "costing out" food needs based on nutritional requirements 

(for men, women, and children of different ages) suggested by the 

National Research Council; this allows consideration of age and sex 

differences in need. A multiplier was then applied to the food require- 

'ments to reflect nonfood needs. . he assumption that for certain family 

sizes the equivalence scale for nonfood items is the same as for food 

items has been criticized. Other ch'apters discuss this methodology in 

much more detail, and Chapter IV examines the implications of updating 

the matrix' using the same methodology and more current data. 

- Geographic Cost-of-Living Differences, 

Many people believe that the cost of living varies across geographic. 

areas. Income levels do vary significantly from region to region and 

.. between rural and urban areas, but the extent of variation in the cost of 

liv'ing is difficult to determine. Technical Paper XV, Analytic Support 

for Cost-of-Living Differentials in the Poverty Thro,sho.lds, Technical Paper 

IVY The Bureau of Labor Statistics Family Budget Program, and Technical 

Paper XIII, Geographic Differences and Relative Poverty discuss this in 

more detail. To show why this issue is so problematical, some basic conceptual problems are presented below. If' prices do vary from place to 

place, then,obviously the price of a fixed market basket of goods and 

services would also vary. But, if taste preferences also vary from place . 

to place, the fixed market basket may not be an appropriate indicator of 

the cost of living.' "Needs" vary, especially those which are related to 

climate or the particular economies and diseconomies coming from dense or 

sparse population. Also: some goods are not available uniformly. The 

variations in quality and availability of medical service and of publicly 
provided goods and services are examples of striking variation among 

geographic areas. 

The fact that in a given area the notion of what is considered poor 

depends upon the general level of living of the area itself qoses a special 

dilemma in attempting to measure geographic variations in the cost of 

living. A standard of need determined on a national basis may appear 

unduly generous in local areas if the local cost is less than the national 

average. If a large proportion of a local population would be considered' 

poor under a national definition, if is easy to believe that the national 

definition is somehow unfounded. For that reason, a national standard 

benefit level could cause problems. For example, when the Senate Finance 

Committee debated the proposed Family Assistance Plan in the early 1970s, 

committee members were very disturbed that a benefit of $2,400 for a 

family of four meant 35 percent of Mississippi's population would be 

eligible while ,only 7 percent of Illinois' would be. Within a state it 

is also important to consider how a program benefit may distort levels of 

living between those who are eligible and those who are not. Accordingly, 

although cost-of-living differences from place-to-place are hard to define 

and even harder to measure, it is sometimes expedient to administer a 

program differentially to accommodate differences in prevailing local wage 

rates or costs of specific items such as housing or medical care. 

With any geographically defined deflator there arises the problem of 

boundaries. Conceptually one could imagine a perfectly continuous function defined on the basis of U.S. latitudes and longitudes. But the 

practical alternatives have the drawback of treating neighbors on different sides of the SMSA, state, or regional boundaries quite differently. 

This is not a severe problem if the objective is limited to aggregate 

measures in which the inequities roughly balance out. But if the poverty 

indicators are used to determine whether individual persons or famil.ies 

are eligible for various programs or benefits, inequities might arise. 

One would want to avoid making one individual eligible for particular 

benefits when a neighbor across the street -- which serves as a boundary 

-- is ineligible but equally poor. 

U~dating the Standard 

.Although it may be desirable to change the level of any poverty measure from time to time, no regular changes for differences in prices are 

required for the relative measures of poverty mentioned in the section 

above on Economic Measures of Poverty. They are ivplicitly updated both 

for combined changes in the price level and for changes in general 

levels. No such implicit adjustment occurs for the absolute definitions. 

The cost of the market basket used by the absolute measures must be adjusted to account for changes in prices over time. The most appropriate 

way to adjust for prices is to determine the prices of each of the commodities in the market basket. To the extent that such pricing cannot be 

done, price indexes not based on the specified market basket are often 

used. 
Index numbers suffer from several limitations for updating poverty; 

one of these comes from the so-called "aggregation problem." Index 

numbers are usually derived from observing what goods are consumed by a 

group of different individuals. These goods are then used to represent 

what a "typical" consumer buys or to represent a "typical" market basket. 

To t.he extent that there may be significant differences across individuals, 

price changes that affect commodities differentially will have different 

effects on individuals. If groups of families have substantially different consumption patterns, one might wish to use several price indexes, 

appropriate for particular subgroups of society. Two final limitations 

arise with currently published price indexes: the market basket may be 

restricted to private goods and services, omitting such things as public 

goods and services, leisure, and goods received in kind; and accounting 

for changes in the quality of goods over time is difficult. 

Price changes over time may lead to changes in the cost of living 

which are not reflected in a price index. A basic postulate of consumer 

or welfare economics is that individuals purchase goods in order to maximize their satisfaction, subject to the constraints imposed by their 

incomes and the existing price levels. The extent to which a price change 

of a single good will affect an individual's welfare depends on his preferences and on the size of the price change. For most individuals, an 

increase in the relative price of a good causes the individual to change 

his purchases of that good (and those goods that are complementary to it) 

and to increase his purchases of 'substitute goods. That is, a change in 

the price of a good probably alters the market basket that is purchased, 

i.e., a change in relative prices is likely to alter expenditure patterns. 

Thus, the weights attached to goods in the market basket prior to price 

changes may no longer be appropriate. 

Income and Resources 

Poverty levels are generally compared to income or resource levels. 

Within a money economy there is a strong tendency to confine the notion 

of income to those receipts which are in the form of money or are "payments 

in kind" for production of goods and services to be used for or by someone 

else. Such income does not include the returns for goods and services 

provided for oneself. Resources include both those which produce money 

earnings and the rest of our accumulated stock, to which cooking utensils 

and houses both belong. Whether items produced or used at home should be 

counted as income, or the associated stock of consumer goods counted as 

resources, depends on the purpose for which the definition is to be used. 

The well-being of families also differs depending on whether the income 

reported is for a month or for a period of five years, on the existence of 

both financial and non-financial assets or in-kind income, on the receipt 

of lump sum income, and on the composition of the consumption unit. 

For analytic convenience, issues associated with setting the poverty 

level have been separated here from those associated with measuring income . or resources to be compared with that level. However, the poverty threshold 
and the income measure should be consistent with one another. For example, 

if medical needs are included in determining the poverty threshold then 

medical resources like insurance or medical assistance programs should 

be included in the income measure. Similarly, if some value of assets is 

included in the income measure, the need for assets should be reflected 

in the threshold. Practically, it may be more convenient to omit some 

items from both the threshold and resource measure than to include them. 

If the definition of income were changed to include the value of in-kind 

benefits, for example, and if the logic of the existing measure were 

maintained, the ratio of after-tax income to food expenditures which is 

used in canputing the poverty thresholds might be altered. Similarly, 

whether or not the number of poor would change if unrealized or imputed 

incane from assets were added to current income would depend on the 

distribution of such imputed income. 

Accounting Period 

Except where interest is specifically in emergency or special situations, poverty will usually be perceived in terms of an individual's 

ability to sustain a particular status for some period of time. The 

particular duration, whether it is to be a week, month, year or lifetime, 

depends on the particular purpose the definition of poverty ismeant to 

serve, since the variation in the flow of income an individual receives 

during any given period affects his well-being during the period. Consider the following streams of earnings: 

Period 

1 2 3 

A $ 300 $ 300 $ 300 

B 1500 -0 ,1500 

C 1000 1000 1000 

D 3000 -0- . -0- 

In any one period it is clear who is best off and who is worst off for the 

period. If, however, we were in the middle of the second period and had 

no knowledge of or ability to predict future earni'ngs beyond the second 

period, we could say, one, that C was currently better off than all others 

and, two, for the two periods C is better off than A and B. Whether A is 

better off in period 2 than D depends on whether equal weight should be 

given to all parts of the two periods. If we were at the beginning of the 

three periods and assumed that each of the four individuals knew what his 

own earnings pattern would be, our perspective would be different still. 

Person D would have the highest consumption. potential since he could invest part of his earnings early in the period and enjoy the interest later. 

Person A would have the least consumption potential; his three-period 

incane is less than the first-period income of any of the others. Whether 

B and C are financially equal would depend on whether the'cost to B of 

borrowing against his third-period income is greater than the interest 
possible on savings from his first-period income. Whether B is actually 

better off than C will depend on the value of his leisure in the second 

year, and the value of leisure is a matter of taste.. 

This illustration was pre'sented in terms of consumption potential 

and financial well-being; the four persons were assurned to be alike in 

all respects other than income; and why the wage patterns varied.was not 

addressed. Well-being depends on ,the perceived "voluntariness" of the 

irregularity. Someone who voluntarily goes without income for a year 

because he is taking a trip around the world is considered better off. 

than someone with an identical income pattern who has lost his job, even 

if he chose his occupation knowing there would be long periods of unempl open t . I 

The Census definition of income is limited to "regular" cash income 

and does not include receipts from insurance policies, capital gains, and 

the like, but does not adjust for unexpected losses like loss of income 

due to illness or unemployment. Counting the poor using the Census 

definition means that in any one survey year, people'who are earning 

below their normal level will be included in the low-income group., while 

those who are temporarily earning much more than they usually do will not 

be counted in the low-income group to which they normally belong. 

The size of the poverty population will vary significantly depending 

upon the time period of income required to be considered poor. If we 

examine monthly' income fluctuations, the poor population will be higher 

than if we examine annual incomes. The appropriate accounting period 

depends in part on the aim' of the measure. If the measure is to help 

design'research which will measure the intergenerational transfer of 

income to different groups, lifetime income is likely to be the appropriate period. Analysis of basic education or inheritance taxat ion are 

examples. On the other hand, for designing programs which deal with 

emergencies or temporary low income, like temporary unemployment, a 

shorter accounting period is more appropriate. 

Consumption Measures 

Measuring money spent on consumption rather than money income has 

frequently been offered as an alternative definition of well-being because 

it eliminates much of the transitory phenomenon of unexpected gains or 

losses manifest in current income figures. In other words, consumption 

stands as a proxy for long-run income. Available data indicate that 

replacing income with consumption as a poverty,measure may have significant 

effects on the poverty count. since at very low inccmes, expenditures 

for consumption more often than not exceed income, a current income measure 

produces higher poverty counts than a consumption measure. In particular, 

a consumption measure would reduce the number of young poor, who are 

frequently ,suffering only temporary poverty, and the number of aged poor 

who can maintain consumption by drawing upon savings. 
Wealth 

Wealth is also proposed as an alternative measure of well-being 

because.people who possess wealth have a kind of security not available 

to people without it at canparable income levels. Wealth not only provides income but is, itself, a resource which may be consumed. To the 

extent that we could heasure "human capital" as well, wealth would give 

us a clearer picture of lifetime income. Studies of the effects of a 

wealth and asset measure on the number and canposition of the poor 

population reveal that, with the exception of the aged, people poor in 

income are in general also poor in wealth. Thus, a wealth based measure 

would reduce poverty somewhat for all groups and especially for the aged. 

A wealth measure would also significantly alter the distribution of 

economic status for the entire U.S. population, by showing even more 

people in the upper income brackets. 

The use of a wealth measure, or a measure combining wealth and 

income, poses many technical problems in addition to those of properly 

assessing the value of an individual's wealth, choosing the appropriate 

interest rate, and arriving at a fair period of time for annuitization 

and differences in the liquidity of.assets. Even with an income measure 

of poverty, many sources of income are unrealized (for example, appreciation in the value of property or business) and can be best estimated or 

imputed only by knowledge of the wealth underlying the income. Investments in owned homes or automobiles also yield in-kind income. Exclusion 

of such income will bias estimates of aggregate income downward and distort income over time and across households. Such problems should not 

obscure the need to consider more than just current cash income in 

assessing a person's financial status. Financial well-being depends on 

more than just current income. Technical Paper VI, Wealth and the 

Accounting Period in the Measurement of Means discusses these issues. 

I 

Taxes 

A measure of income might aim at a "disposable" income, including 

cash and in-kind benefits. However, tax payments may be as important as 

transfers in modifying gross income to achieve a totai resource measure. 

The incidence of taxation, or who actually pays the tax, is both theoretically and empirically a very difficult issue. Thus, .although the 

incidence of personal income taxes may be relatively straight forward, 

the incidence of corporate income, excise, or payroll taxes is not. To 

the extent that taxes represent user charges for ser.vices provided by 

governments, it would be appropriate to' ignore taxes only if the services 

were also ignored. Unfortunately, it is difficult to evaluate these 

incidences and services, and survey data are unlikely to help. Chapter 

I11 discusses the availability and limitations of data from the Internal 

Revenue Service. 
In-Kind Income 

Individuals in our society receive a multitude of in-kind income, 

that is, benefits that take a non-cash form. 7/ These benefits or subsidies may be provided by the government or tFe private sector. Examples 

of government in-kind benefits range from in-kind transfers (such as food 

stamps or Medicare) to investments in human capital (such as education) 

to subsidies within the tax system (such as interest and property tax 

deductions for homeowners). In the private sector, in-kind benefits 

such as health insurance or free housing may be provided by employers or 

may be entirely dependent on individual choices (such as owner-occupied 

housing or home-grown food). 

In-kind subsidies are now sizable in absolute terms. Moreover, they 

have grown sharply over the past decade in breadth and size. Outlays in 

the food stamp program have risen from less than $100 million in 1965 to 

$4.6 billion in fiscal year 1975. Medicare and Medicaid, which were 

not legislated until 1965, now cost more than $25 billion a year, and 

the employer-provided portion of private health insurance is estimated 

to total about $20 billion annually. Deduction of mortgage interest 

and property taxes on owner-occupied homes is estimated to cost about 

$10 billion a year in lost tax revenues. 

To exclude in-kind benefits from income calculations clearly biases 

aggregate income downward. Even more important, however, to ignore in-kind 

income distorts income comparisons over time and across households. The 

rise in in-kind transfers to low-income households during the past 

decade has been several times that of cash public assistance transfers. 

Fringe benefits have also been rising relative to wages and salaries. 

Ironically, this rise in in-kind benefits, many of them specifically 

aimed at reducing poverty, makes the current 'income measure used with 

the poverty line increasingly obsolete as a poverty performance measure, 

since it explicitly excludes the very programs instituted to reduce or 

alleviate poverty. It has. been estimated that if food stamps were counted 

as income, the number of poor would decrease by 5 to 15 percent in 1974. 

Incorporating Medicare and Medicaid would also reduce the poverty count 

substantially, if the definition of poverty remained unchanged. Public 

housing, free school lunches, "Meals on Wheels" for the aged, legal aid, 

neighborhood health centers, and a long list of other in-kind social programs are other sources of resources for the poor. While other programs, 

such as government subsidies to public universities, benefit the middle 

and upper classes much more than the poor, and a systematic inclusion 

of in-kind benefits might not have a major impact on the overall income 

distribution, under any definition of poverty other than a purely relative 

one (and to some extent under a relative definition), inclusion of 

in-kind benefits could reduce the poverty count and would change the demographic composition of the poor. 

Unfortunately, the incidence of in-kind benefits is particularly 

uneven across households. Not 'only do the various types of government 
and private in-kind benefits apply to prescribed, and often different, 

segments of the population, but also the incidence of each type of inkind income across the potentially eligible population varies. For 

example, many low-income households are excluded from eligibility for 

Medicaid, and most are excluded from public housing; and employerprovided health and life insurance in 1970 covered two-thirds of nonof £ice employees in non-union establishments but 97 percent in union 

establishments. Hence, the accurate attribution of in-kind benefits to 

income would involve substantial data collection and manipulation. 

How these in-kind benefits should be valued is an important issue in 

the measurement of income and poverty. Typically, published data on the 

amounts of in-kind income provided through various programs are shown in 

terms of the providers' costs or outlays. For example, among government 

in-kind transfers, it is the cost to the government (i.e., program outlays exclusive of administrative costs) that is equated with recipient 

"benefits." However, the value to the recipient may not necessarily equal 

outlays by the government. 

The argument for valuing in-kind income differently from government 

outlays is based on a notion of the cash inco~me a family would accept in 

lieu of its in-kind income to leave 'it just as well off (a "willingness 

to pay" measure). It is usually assumed that a household receiving income 

in the form of cash will spend that income on its most preferred bundle of 

goods (including savings). In-kind income, however, is provided in the 

form of a particular good or set of goods. After receipt of the in-kind 

income, then, the household's bundle of goods may include more (or in some 

cases less) of the particular good than it would choose if given cash. By 

not permitting the household to exercise complete freedom in the choice of 

a bundle of goods, that bundle with the in-kind component may be worth 

less to the household than if it had been given an equivalent in cash. 

Receipt of in-kind income may influence the recipient's choice of a 

bundle of goods by constraining consumption amounts directly and/or 

altering the relative prices faced by the recipient. Programs like food 

stamps and public housing set amounts of food and housing, respectively, 

that must be consumed if program benefits are to be enjoyed. Partially 

or fully subsidized health benefits, on the other hand, normally leave 

amounts of health care consumed up to individual recipients, although it 

does alter the prices faced by the recipient. 

In order to treat in-kind income consistently with cash income as 

perceived by the recipient -- which does allow families full choice over 

how to spend income -- the provider cost of in-kind subsidies might be 

reduced (or, in rare cases, perhaps increased) to equal their cash 

equivalent value to individual families. The cash equivalent value of 

in-kind subsidies will generally fall between zero and 100 percent of 

provider outlays. It will be greater than 100 percent if it can be provided by the government more efficiently than the private sector and if 

the recipient would have purchased at least the amount provided. It will 
not be negative as long as potential recipients are not forced to participate. Moreover, observation that recipients. purchase greater amounts of 

the good on the market than is provided through the in-kind subsidy is a 

sufficient condition for valuation equal to provider cost. 

The recipient's valuation does not reflect the full value of inkind benefit s to 'society, however. The taxpayer, the employer, or 

society at large may indirectly benefit from the provision of the inkind income. The government ascribes a value to the benefits which is 

at least equal to the outlay. It is precisely because the public's 

valuation may be greater than the recipient's valuation that in-kind 

benefits are provided in the areas of health, housing, and nutrition. 

There is disagreement about whether the recipient's valuation of inkind benefits should determine their income value. Work is being undertaken to explore and evaluate methods of valuing in-kind benefits for 

the purpose of incorporating them in income statistics. 

Consumption Unit 

So far we have discussed income without any discussion of the unit 

receiving the income. The basic units used in the current statistics on 

poverty are families and unrelated .individuals. Under the current ,definition, the poverty status of a person 14 years of age or older who does 

not live with someone to whom he or she is related 'is determined entirely 

by his own income. ' The poverty status of ,a person who does live with one or 

more relatives is determined by the income of that person plus the income 

of those relatives with whom he or she lives. Thus, persons whose own 

incane is below the poverty line would be counted as poor if they 'lived 

alone, but not if they lived with relatives possessing enough income for 

a1 1. Aged "other relatives1' and mother-child subfamilies are important 

examples . 

There are, of course, good reasons for choosing families and unrelated individuals as the basic units. There are traditional and legal 

bonds which cause families to ex'ist as economic entities. Bonds between 

or among unrelated individuals 6ho share' a single residence are generally 

much weaker. 

However, for poverty identification, when c&npar ing income against 

some consumption norm, the unit which shares consumption activities seems 

most relevant. Although many consumption units coincide exactly with 

families and unrelated individuals, there are many instances in which the 

consumption unit.does not. For example, although the bond may be weaker, 

households made up of unrelated individuals may share in most of the 

benefits of economies of scale that characterize the economic situation 

of families : sharing appliances, sharing he'ating and plumbing equipment, 

and purchasing and preparing foods. in large quantities. In some cases, 

too, the bond existing between a family and an unrelated individual or 

between unrelated individuals is as strong as a family bond. Unmarried 
couples who live together would presumably regard themselves as a single 

economic unit, and it is likely that many families who have unrelated 

individuals living with them consider that individual part of the family 

for economic purposes. It is for these reasons that in Chapter IV we 

examine some different definitions of economic units for defining poverty. 

I Choosing an Income Definition 

The choice of a conceptual definition of income or resources frequently depends on the purpose for which it is to be used. For instance, 

if we are concerned with examining the necessity for providing income 

during a brief period of unemployment, the income concept used may have 

a relatively short accounting period where only liquid assets and in-kind 

income (replacing short-term consumption) are incorporated at full value. 

On the other hand, for a program of .compensatory education, a predicted 

lifetime income concept may be more appropriate. Like the poverty concept itself, many alternatives are conceptually available for use. 
NOTES TO CHAPTER I1 

1. This chapter .draws heavily without further citation on material 

prepared by Urban Systems Research and Engineering, Inc., and duplicated 

in Technical Paper 111. 

2. John Rawl's, A Theory of Justice (Cambridge: Harvard University 

Press, 1971). 

3. Robert Kilpatrick, "The Income Elasticity of the Poverty Line," 

Review of Economics and Statistics (Cambridge: Harvard University Press, 

1973), pp. 327-332. 

4. Victor R. ~uchs , "Redefining Poverty and Redistributing Income ,I1 

Public Interest, No. 8 (New York 1967). 

1 5. E. Engel, "Die Productions- und Consumptions-verhaltnisse 'des 

Konigreichs Sachsen" (1857), Reprinted in ISI' Bull. 9, Appendix and 

"Die Lebenskosten Belgischer Arbeiter-Familien Fruher und ~etzt" (1895), 

IS1 Bull. 9, p. 1. 

6. Harold W. Watts, "The Iso-Prop Index: An Approach to the Determination' of Differential Poverty ~hresholds ," ~ournii of Human Resources, 

111 (Madison, Winter 1967), pp. 3-18, and U.S. Department of Labor, Bureau 

of Labor Statistics, "Estimating Equivalent Incomes or Budget Costs by 

Family Type ,I1 Monthly Labor Review -( l960), or "Revised ~~uivalence incomes 

or Budget ~ost-.~. Bureau of Labor Statistics Bulletin, 

1570-2 (Washington, D.C.: Government Printing Office, November 1968). 

7. The subject of in-kind benefits is discussed in greater detail 

in "In-kind Income and the Measurement of Poverty," by Jan Peskin, to 

be issued as a Technical Analysis Paper of the Office of Income Security, 

Department of Health, e ducat ion, and Welfare, and included as Technial 

Paper VII of this report. 
111. DATA AVAILABILITY AND LIMITATIONS 

As Chapter I1 makes evident, there are a number of concepts of 

poverty,, each with its own theoretical advantages and limitations. 

For any definition to be of practical use, it must be capable of 

objective measurement. There must be data available to construct and 

apply the measure, data whose appropriateness and reliability can be 

assessed. 

Chapter 11 focused primarily on economic measures of poverty. 

Whatever the relative theoretical merits of other concepts of poverty, 

econani6 measures have the decided practical advantage. Although the 

construction of economic measures is limited by data appropriateness 

and reliability, there is more data available to support the construction 

and use of economic poverty measures than alternative ones. In fact, 

all poverty measures developed for Federal government use to date are . 

based on some concept of economic status or need. 

This chapter reviews and evaluates existing data sources that can 

be used in connection with various economic poverty measures. It initially 

considers data bearing on measurement of needs, and then on measurement 

of resources. A comprehensive guide to available Federal data bases and 

canputer files pertaining to aspects of .poverty measurement is provided 

in Technical Paper IX: There are also technical papers providing detailed 

coverage of the Consumer Price Index, the BLS Family Budgets Program, 

the 1972-1973 Consumer Expenditure Survey, and the Agriculture ~epartment ' s 

food plans. 

In evaluating the usefulness of each data source for its intended 

purpose, the following criteria should .be considered : 

First, the data source should be an appropriate or valid indicator of 

what it purports to measure. For example, a data source that,provides 

information solely on consumption practices with respect to food, housing, 

transportation, or other basic commodities by different types of families 

is a less valid indicator of need than a data source that establishes 

varying physiological requirements for different food nutrients. 

Second, the data source should be reliable to the level of detailed 

differentiation of the population which is desired. Because most current 

data on characteristics of the population are obtained from sample surveys 

rather than from complete census counts, efforts must be made to ensure 

that samples are sufficiently large and representative of the population 

or universe being estimated. The sample size and design affect the size 

of confidence intervals for particular population subgroups and determine 

the reliability of estimates of population parameters. -Data reliability 

can also be affected by non-sampling errors, such as misreporting by 

respondents,or mistakes in editing or coding. 
Third, the data.for things that are changing rapidly shduld be 

obtained relatively frequently. For example, while data on prevailing 

food consumption patterns have been collected at intervals of approximately 

ten years, data on family income are collected annually. 

.Data for Measuring Needs I 

Most economic measures of poverty are based on some minimum level of b 

living. In general, needs are defined and then expressed in cost terms 

so that they can be canpared to resource levels, or to capabilities of I 

purchasing goods and services. People,counted as poor are people without 

the income or resources necessary to attain the specified level of living. 

The following discussion evaluates data sources available for defining 

different needs. Obj'ect ively based standards of need are described first. 

Then more'subjective standards are presented. Data on food are examined 

first, because food is the cornerstone of the presently used Orshansky 

poverty measure and because it is a most basic need. 

- Food 

- 

The National Academy of Sc iences-Na t ional Re search Council has 

established Recommended Dietary Allowances (RDA) for 17 different food 

elements or nutrients (e.g., iron, calcium, vitamin A) for 20 age-sex 

groups (e.g., children aged 1 to 3 years, men aged 35 to 55, nursing 

mothers). The RDA are revised about every 5 years to reflect new knowledge of human nutrition. For example, the RDA released in 1958 and 

reflected in the economy food plan used for the Orshansky measure were 

revised subsequently in 1963, 1968 and again in 1974.. Although the 

acceptance of the RDA is attested by their role in the 1974 food plans 

of the U.S. Department of Agriculture, there are other sources of 

nutritional standards. Among these are the standards set by the Food and 

Agricultural Organization (FAo) of the United Nations in its Handbook of 

Human Nutritional Requirements and the standard for evaluation of Daily 

Dietary Intake used in the U.S. Public Health ~er;ice and Nutrition 

~xamination Survey (HANES) of 1971-1973. 

The RDA, and other nutritional standards mentioned above, are 

research-based standards of need. However, the specification of the 

nutritional standards 'has an element of subjectivity because 'knowledge 

about nutritional needs and variation in needs among individuals is 

incomplete. Levels are usually set to cover .what are believed to be the 

requirements for nutrients for almost all people. Thus, "even if a person 

habitually consumes less than the recommended. amounts o'f some nutrients, 

his diet is not necessarily inadequate for those nutrients." 1/ - 

The FA0 and HANES standards for some nutrients are lower than the . RDA; yet food plans based on FA0 and %NES.standards are only slightly 

less costly than those based on 'the RDA. (See Technical Paper xII.) The 

RDA in 1974 are substantially different from those in 1958 -_ higher for 

some nutrient's and lower for others -- and the RDA were specified in 1974 
for some nutrients not covered in 1958. Food plans based on the 1974 RDA 

are more costly for some age-sex categories and less costly for others 

than plans based on the earlier RDA. 

A large number of food items of different nutritidnal composition are 

available at widely different costs. Therefore, diets at widely different 

levels of cost can be developed, each providing recommended amounts of 

nutrients but some being more palatable than others. Food ,plans are 

developed by the U.S. Department of Agriculture incorporating not only the 

KDA but also actual consumption patterns of families at different spending 

levels. Hence the actual food plans incorporate a major subjective cost 

element and are not the minimum cost of .obtaining the RDA. The economy 

food plan used in the Orshansky measure, which resulted in costs averaging 

75 to 80 percent of the low-cost plan, reflected food selections and costs 

from the 1955 Survey of Household Food Consumption conducted by the USDA. 

The Agricultural Research Service has recently revised its low-cost, 

moderate-cost, and liberal food plans, and has just finished replacing the 

economy food plan with the "thrifty1' plan, to incorporate new nutrition 

' 

standards and more current food preferences, based on data from the 1965-66 

Survey of Household Food Consumption. This is the most recent such survey. 

It is expected to be repeated within the next couple of years. This would 

permit another revi'sion of the basic food plans. - 2/ 

Both the 1955 and 1965-66 surveys collected data or! the amounts and 

costs of foods and beverages used at home during the seven days preceding 

the interview. Over 15,000 households were selected for each survey to 

represent metropolitan areas, cities of various sizes, and rural farm and 

nonfarm areas in all parts of the United States except Alaska and Hawaii. 

Information collected on the household itself included age, sex, height, 

weight, status in household of persons eating out of household food 

supplies, the number of meals eaten at home and away by each member, plus 

the age, race, education, and employment status of the homemaker. Family 

income information was also collected. The sample was designed to provide 

information separately for urban, rural nonfarm and farm families) in the 

four Census regions. Only housekeeping households are included.: families 

or individuals that take all of their meals outside the home are not 

interviewed. The surveys measure food consumption at the level at which 

foods come into the kitchen; in other words, the data represent food as 

cooked and served rather than as actually eaten by each household member 

or guest. The 1965-66 survey obtained information on a day's food intake 

for each individual in about half the households interviewed in the Spring. 

Assessment of the reliability of the .data indicates that, for the 1965 

survey at least, the sample was reasonably representative of housekeeping 

households in the U.S. on key family characteristics dimensions. The 

sample size, which is close to l/g,OOO of the universe of households for 

the Spring portion of the sample, is more than adequate for reliable estimates by size of household or for different age-sex groups. 

The Orshansky measure used a 1961 economy food plan based on the 1958. 

RDA and consumption data from the 1955 household survey. In describing 
its 1974 plans, the Department of Agriculture indicated several reasons 

for revising the old plans. First, the 1974 RD'A differed ~ubstant~ally 

from the 1958 RDA. Second, the nutritive value of some foods changed. 

For example, many ready-to-eat cereals are now fortified with more vitamins and minerals. Third, actual food consumption patterns changed at al.1 

income levels as evidenced in the 1965 survey. Finally, shifts in relat ive food prices occurred over the ten years. Thus, several foods used 

generously in the 1964 low-cost plan, such as dry beans and potatoes, 

increased markedly in price and were relatively more costly in 1974. 

The percentage of family income spent on food was lower in the 1965 study 

than in 1955. 

The USDA now estimates the cost of food at home each month based on 

the food plans at four levels of cost for 12 different age-sex categories 

6 and pregnant and nursing women. Costs as published assume that individuals 

are living in four-person families. Scale adjustments for family size of 

one person up to seven or more are suggested to a1 low for economies that 

large families have over small ones in buying and using food. 

Table 4 displays :the total weekly cost in September 1974 prices under 

the low-cost plan for comparable age-sex groups as specified in 1974 versus 

1964. For as many as 8 of the 18 categories, the 1974 food plan indicates 

lower costs than does the 1964 plan. Technical paper'xll explains the 

details of the food plans. 

Housing 

Some effort has gone into developing standards for basic housing 

needs, but definitive standards comparable to the RDA or the Department 

of Agriculture food plans do not exist. The American Public Health 

Association (APHA) developed housing recommendat ions that are currently 

incorporated, along with recommendations of the U.S. Public Housing 

Administration in the Bureau of Labor Statistics family budgets. An 

unfurnished f'ive-room unit with a canplete private bath is recanmended 

for a four-person family living in a rental unit, while a five-room or 

six-room house with 1 or 1-112 baths is recanmended for'the same 

family living in their own home. Both the rental unit and the owned home 

must be in sound structural condition; have a fully equipped kitchen, hot 

and cold running water, electricity, central or other installed heat; be 

located in neighborhoods free £ran hazards or nuisances; and provide 

access to public transportation, schools, grocery stores, and play space 

for children. 31 - 

An obvious problem with the APHA housing standards is the lack of 

specificity of many components, such as "sound structural condition" or 

absence of "hazards or nuisances." Assuming that relevant data for such 

canponents are available in the first place, considerable subjectivity is 

necessarily involved in deciding which housing units in a given cmmunity 

meet the standards for purposes of setting cost levels and making substitutions where none can be found. 
Table 4. Weekly Cost of Food at Home, Estimated for 1974 Low-Cost Plan 

and 1964 Low-Cost Plan, September 1974 Prices 

1974 Low- 1964 LowSex-Age Group Cost Plan Cost Plan 

Families : 

Family of 2, 20-54 yearsa $26.70 $26.50~ 

Family of 2, 55 or morea 23.60 21.60 

Family of 4, preschool 

childrenb 37.70* 38.20e 

Family of 4, school 

childrenC 45.60 44. 7oe 

Individuals :d 

Child: 

7 months to 1 year 

1-2 years 

3-5 years 

6-8 years 

9-11 years 

Male : 

12-14 years 

15-19 years 

20-54 years 

55 years and over 

Female : 

12-19 years 

20-54 years 

55 years and over 

Pregnant 

Nursing 

SOURCE: Betty Peterkin, "U.S. Department of Agriculture Family Food 

plans, 1974" (December 1974), Tables 4 and 5. 

Indicates instances where the 1974 food plan cost is lower than 

the cost for the 1964 food plan. 

Ten percent added for family size adjustment. 

Man and woman, 20-54 years; children, 1-2 and 3-5 years. 

Man'and woman, 20-54; children 6-8 and 9-11 years. 

The costs given are for individuals in 4-person families. For 

individuals in other size families, the following adjustments are 

suggested: 1-person--add 20 percent; 2-person--add 10 percent; 

3-person--add 5 percent; 5-person--subtract 5 percent; 6-or-moreperson--subtract 10 percent. 

Man and woman, 20-35 years; children as in 1974 plan. 

Costs represent averages for more detailed age groups represented 

in the 1964 plan. 

The Census Bureau has faced similar problems in its attempts over the 

past few decades to define a standard of housing quality. Beginning with 

the first Census of Housing in 1940, data have been available on the size 

of housing units (number of rooms), and the Census Bureau has always used 

as one measure of acceptable housing the ratio of rooms to the number of 
household residents. The Bureau has also at tempted to define standard 

versus substandard housing 'units on the basisVof their plumbing facilities 

and structural condition. Complete private plumbing facilities in standard housing are defined to include piped hot and cold water, inside flush 

toilet, and a bathtub or shower for exclusive use of the occupants. 

Structural condition has been much harder to define. In the 1940 Census, 

units were classified on the basis of enumerator observation as "not 

needing major repairs" or as "needing major repairs." In 1950, the 

classification was changed to "not dilapidated" versus "dilapidated," 

while in 1960 three categories were recognized: "sound," "deter'iorating," 

and "dilapidated." In 1970, the concept of structural condition was 

abandoned, because studies had shown that evaluation of. housing condition 

by enumerators was very unreliable, even though some 40 percent of the . households were personally interviewed. 41 - 

Nevertheless, the Decennial Census of Housing is one of the richest 

sources of information on the nation's housing stock. The 1970 Census, 

for example, included 49 items on housing, of which 16 were asked on a 100 

percent or complete count basis and the remainder on very large systematic 

samples of households (20 percent, 15 percent, or 5 percent samples, 

depending on the question). Many of the components of the APHA standard 

are ascertained by the Census, such as number of rooms, number of bathrooms (also bedrooms), kitchen facilities, plumbing facilities, and 

heating equipment. Other items are included which could be candidates 

for a revised housing standard as well, such as passenger elevator for 

highrise apartments, air conditioning, and appliances such as washing 

machine and dryer. The Census also includes data on home value and rent, 

as well as utility expenses (the latter for renters only). 

The sample size of the Census is more than adequate for determining 

cost levels for different size families. But the Census data do not 

include data on neighborhood conditions or availability of services, 

which are two of the components of the APHA standard, nor, since 1960, 

on the structural condition of the unit. Moreover, the data collected 

on items such as heating or plumbing equipment do not ascertain whether 

the facilities are in working order, an important consideration in 

determining whether a housing unit satisfies basic needs requirements. 

Finally, because a multitude of characteristics relating essentially to 

consumer preferences, such as wooded lot, and brick, wood, or stone 

construction, are not ascertained in the Census, the value and rent 

figures from the Census would reflect such characteristics as well as 

those, incorporated in any standard of need, however defined. This is 

also true of utility expenses which, in any case, are reported only for 

renters. ,Hence, it may be difficult to cost out housing that meets only 

a basic set of needs. 

~eginning in 1973, the Census Bureau has conducted for the Department 

of Housing and Urban Development an Annual Housing Survey (AHS). The national AHS sample comprises 76,000 housing units designed to be representative 

of important population groups, housing categories, and principal geographic 
sections of the country. (This sample size amounts to about 1/1,000 of ' 

urban households and 11500 of rural households which are over-represented 

in the sample.) Also, about 140,000 units are being surveyed annually in 

one of three different groups of 20 metropolitan areas on a rotating basis. 

The AHS includes data similar to the Census on financial and structural characteristics of housing units and their amenities, including 

number of rooms and bedrooms, kitchen facilities, plumbing facilities, 

heating equipment and fuel, basement, airconditioning, elevator, and major 

appliances. Data are also collected as in the Census on housing value and 

rent plus utility expenses which, beginning in 1974, are asked of homeowners as well as renters. In addition, the AHS ascertains how well 

facilities such as the heating, plumbing, and electrical systems actually 

work and, similarly, the dependability of services such as water supply, 

sewage disposal, and trash and garbage collection. Such household problems as leaky roofs and basements, holes in wa1,ls and ceilings, broken 

steps, and peeling paint and plaster are also identified. 

The AHS also inquires into the environment of the neighborhood in 

which the housing unit is located. Factors considered include the 

presence of abandoned, vacant, or run-down buildings; heavy street 

traffic; and street or neighborhood crime. Households are also asked to 

judge the adequacy of their neighborhood public services. Finally, the 

AHS includes data on the size, composition, and income of the household w 

residents themselves. The survey also directs questions specifically to 

recent movers, in an attempt to view the characteristics of their 

previous house and neighborhood in relation to their decision to move. 

The Annual Housing Survey is a very comprehensive~source of data 

which may be useful for analyzing housing needs and expenses .for different 

kinds of families. The sample size appears more than adequate for this 

purpose. Problems of data reliability similar to those with the Census 

data will be present to some degree. For example, respondents' evaluations about trash in the street, street traffic, or neighborhood crime 

may vary considerably. However, since the survey is repeated annually 'by 

a trained interviewer staff and since the questionnaire items are very 

specific, more reliable data will probably be produced, particularly as 

experience is.gained wirh respect to standards of need for housing. 

Many problems of theory and value judgment remain. For one thing, 

except for heating and a very minimum degree of structural soundness, 

there is no physiological basis for a housing standard. For example, for 

some persons, keeping cool may be as essential to health and comfort as 

keeping warm, but there are no standards for this factor. There is no 

"need" for a room for each person in the same way that there is a need 

for a certain amount of vitamin C. Housing needs may be as much a function of the level of living of a society at a particular time and of what 

its people believe is needed as they are of objectively measurable needs. 

Hence, considerable subjectivity must inevitably enter a definition of 

standard housing. Furthermore, it is difficult to determine a cost level 
for standard housing that is not ' contaminated by clearly irrelevant characteristics. Also, cost may not be related to condition. Another problem 

is lack of adequate information on the availability of the supply of standard 

housing (generally, and to disadvantaged groups -- such as minorities, 

families with many children, and others facing discriminat ion in the marketplace). The Annual ~o'using Survey will provide a more complete and current 

source of data to aid in resolving these and other problems associated with 

defining a standard for housing to be used in measuring poverty. Like 

the Food Survey, however, the Housing Survey unfortunately concentrates bn 

only one category of expenditure and cannot take account of how preferences 

modify "needs" as consumers trade off one category of living against another. 

Other Needs 

Very little work has been directed toward developing minimum standards for basic .needs bes-ides food and housing, such as clothing, trans- , 

portation, and education. As noted before, the current Orshansky poverty 

measure multiplies food costs by a factor of three to develop a total 

income. leve 1. 

The only systematic work by a Federal agency on standards for other 

needs has been in connection with the Bureau of Labor Statistics (BLS) 

family budgets, first issued in 1948. In 1967, the BLS developed three 

budget levels -- lower," "intermediate," and "higher" -- for a four- O 

person urban family with an employed huiband aged 38, his nonworking 

wife, and two children aged 8 and 13, and for a retired couple with both 

husband and wife aged 65 or older. The intermediate budget was designed 

to represent a "modest but adequate" standard of living, and costs for 

this budget were then scaled to produce the other two budgets. The 

budgets are periodically updated for price changes in the broad components of the Consumer Price Index (CPI). The BLS also developed 

equivalence scales based on patterns of food expenditures, to use in 

determining budget costs for different kinds of families as percentages 

of the base four-person family. These equivalence scales were for 

different family types by age of head, number of persons in the family, 

and number and age of children. 

None of the BLS budgets, including the lower one, was intended to be 

an absolute standard of need, much less a poverty standard. They are not 

based on minimum quantities or prices of necessary goods and services, but 

rather are descriptive of relative levels of living. 51 They apply to the 

family of a year-round full-time worker with 15 yearso£ work experience. 

In Autumn 1974, the lower BLS budget for a four-person family was $9,198 or 

more than 80 percent higher than the 1974 weighted average, nonfarm poverty 

threshold of $5,038. The Orshansky poverty matrix was based on the 

Department of Agriculture's economy food plan. The BLS budgets use the 

low, intermediate, or liberal cost food plans. 

BLS techniques have technical limitations and do not result in 

objectively derived .standards. 'BLS budgets u.se the various food plans 
2 

for food-at-home, expenditures; they incorporate the aforementioned APHA 

housing standards; they include utility company estimates of the electricity 

and utility services required for specified appliances; they adjust heating 

(but not cooling) fuel requirements for differences in climate; and they 

include insurance costs for major medical illnesses. Since objectively 

defined standards are not available for such components of the budgets as 

clothing, house furnishings, transportation, personal care, household 

operation, reading, recreation, tobacco, education, gifts and contributions, { 

and miscellaneous expenses including work expenses and taxes, the BLS used 

a technique that tried to rely on consumer purchases as the basis for 

. these budgets. 61 - 

The BLS family budgets involve a multitude of subjective decisions 

by the budget makers. They must decide which family types and manners 

and levels of living to represent; which data sources are most appropriate 

for deriving the budget quantities; and most importantly, how to interpret actual family consumption in terms of standards. The end result is 

a mixture of generally accepted standards, quasi-standard s , and preferences. The incorporation of consumption data for needs other than food 

and shelter is especially troublesome, because the notions of standards 

and basic ne'eds have beenlost and themethodology for quantifying 

consumer interest in a commodity is not satisfactory. 

It is clear from the BLS experience with family budgets'that devel- 

-oping minimum standards of need for items other than food and perhaps 

,housing is a very difficult business. To develop a canplete poverty 

budget, not only would additional data about consumption patterns be 

needed, but also data on society's beliefs about the need for such items 

as recreation or household furnishings. The judgment of professionals 

in the field might also cane into play. ~ven then the resulting standards for the various items could not be described as being objectively 

derived or scientifically rigorous. 

The Department of Agriculture publishes some clothing budgets. 71 ' 

These are not based on prior standards as are the food plans, but ,on . average family food spending levels of. the USDA food pl'ans, modified to 

accommodate comparable levels of living in all areas. 

I Standards Based on Actual Consumption Bata 

The 1960-61 Consumer Expenditure Survey, a joint effort by the BLS 

and the Department of Agriculture, resulted in the acquisition of almost 

14,000 usable questionnaires, representing a 1/4,000 sample of households. 

The BLS collected data from households and from nonfarm residents in 

rural portions of metropolitan areas; the USDA collected data from rural 

households outside metro areas and from farm operators inside these areas. 

The only groups excluded were the institutional population 'and on-post 

military personnel. 
- 

Each household in the sample was interviewed once in 1961 or 1962 and ' 

asked to recall expenditures for such items as automobiles and app'liances 

fo,r the preceding year and for food and related items for the preceding 

week. The levels of expenditures requested were very complete. The 1960-61 

CES also obtained an inventory of major durable goods and property owned 

at the beginning of. the reference year as well as information on financial 

assets and liabilities and detailed spurces of income for the preceding 

year. 

Clearly, the CES is a very detailed source of information on consumption patterns of U.S. families. The sample size of the 1960-61 survey is 

adequate for analysis of differing patterns among broad family size and 

\ composition categories, although it is admittedly weak for simultaneously 

considering a number of factors such as age, income, work status, family . size and locality. There is evidence that the reliability of the expenditure data collected varies with the-importance and cost of the item, 

and the frequency of purchase since expenditures are more readily and 

accurately recalled for expensive items such as appliances than for small 

items such as cleaning and laundry supplies. 

The BLS and the Census Bureau are currently processing a new Consumer \ 

Expenditure Survey. The 1972-73 CES is similar in content to previous 

surveys, although the data collection methods radically depart from . 

previous procedures. The sample size has also been enlarged, and c,overage 

has been extended to all families, urban and rural, farm and nonfarm, in a 

"single" survey. This has obviated' the need for a joint BLS-USDA effort. 

However, the new procedure makes it more difficult to associate all income 

and'expenditure items in a single year for a single family. 

The l'singlell 1972-73 CES is actually two related but separate surveys, 

the Quarterly Survey and the Diary Survey. In the Quarterly Survey, a , total of 20,000 families were interviewed, 10,000 in each year, for a 

l/3,OOO sample of the universe in all. Each family was interviewed five 

times over a 151nonth period beginning in January of 1972 or 1973. In the 

Diary Survey, a total of about 20,000 additional families were' interviewed, 

10,000 in each year, and each family was asked to caplete a two-week diary 

of all expenditures in those two weeks. Interviewing was spread fairly 

evenly over the two years to incorporate *seasonal variations. Two surveys 

were used to avoid the recall problem mentioned earlier. The Quarterly 

Survey was designed to collect information on larger and more easily 

recalled expenditures, while the Diary Survey was designed to gather 

information on smaller and less easily recalled expenditures. Also, the 

Diary Survey, unlike the Quarterly Survey, recorded expenditures daily. 

Specifically, the Quarterly Survey. obtained expenditures for major 

appliances, real' estate, motor vehicles, and other expensive or infrequently purchased 'items on a twelve-month recall basis; expenditures for 

relatively expensive items such' as furniture and small kitchen appliances 

on a six-month recall basis; and expenditures on frequently purchased or 

relatively inexpensive items such as clothing and utilities on a. quarterly 
basis. Global estimates for food and beverage expenditures were also 

obtained in quarters two through five. Furthermore, the Quarterly Survey 

obtained an inventory of durable goods and property assets, detailed 

information on financial assets and liabilities, and detailed information . 

on annual incane by type. 

The Diary Survey, in contrast, focused on expenditures for small, 

frequently purchased items (although respondents were asked to record all 

purchases to prevent any confusion about what items should be included). \ The major expenditure components for which the Diary Survey was designed 

were food, household supplies, personal care products, and non-prescription drugs. As in the Quarterly Survey, the information was requested 

in extremely great detail. For example, respondents were requested to 

specify cuts of meat, kinds of milk, types of flour, net weights or 

volumes, and conditions of foods (e.g., fresh, frozen, canned, dried, or 

packaged). More than 1,700 different codes were developed to classify 

the expenditures for analysis. The Diary Survey also obtained demographic and socio-economic characteristics of the consumer unit as, did 

the Quarterly and the 196e61 CES. The Diary Survey also collected 

annual income data, but in less detail than in the Quarterly. 

Only the preliminary results have been ~ublished from the Diary 

Survey. The new procedures used should have improved the completeness 

and accuracy of each type of expenditure reporting, but it may now be 

more difficult to relate expenditures for one category with those for 

another. Moreover, the enlarged sample size for each portion should 

permit more reliable analyses of spending patterns for different types 

and income levels of families. 

However, estimates of family characteristics equivalences are 

limited. It is particularly important to note that the two samples from 

the Diary and Quarterly Surveys cannot 'simply be cmbined to make a total 

sample of 40,000 over the two years,, since neither survey obtained complete information on all expenditures. Complicated statistical matching 

procedures would be required to .impute missing data on one of the surveys 

using the information on the other. Technical Paper VIII describes the 

1972-73 CES in more detail and evaluates its usefulness for poverty 

measurement. 

Only a few other data sources are available for developing standards 

and family characteristics equivalences for other basic needs. One is 

the 1973 Farm Family Living Expenditures Survey conducted by the USDA, 

which obtained detailed expenditure data similar to that obtained by the 

CES, from 2,500 families interviewed at three points during the year. 

Although the 1972-73 CES included the farm population, the 1973 USDA 

survey represented a larger sample, about 1/1,000, permitting a more 

reliable analysis of this group. Comparison with data from a previous 

1955 Farm Family Survey shows substantial changes in spending patterns, 

suggesting that a poverty standard explicitly identifying one or more 

categories of need would look quite different in 1973 when compared to 1955. 
In 1969-1970, the Department of Transportation conducted a Nationwide 

Personal Transportation Study, which obtained extensive information from 

approximately 6,000 households ( 11 10,000 of the universe) on pat terns of 

automobile use for trips to work, to school, for shopping, and other 

travel. These data could possibly be used to analyze standards of, need. 

for transportation based on household size, number of earners, school 

children, availability of public transportation, and other factors. 

Geographic Equivalences 

Whether basic needs vary by geographic residence and, if so, whether 

such variations should be incorporated into a measure of poverty is an 

. important issue in the development of new or revised poverty measures. 

. The .current Orshansky measure does not recognize any geographic differences of need, but does differentiate income differences between farm and 

nonfarm households. 

Geographic equivalences pose troubling theoretical and judgmental 

problems, just as do family characteristics equivalences. As discussed 

in Chapter 11, geographic variations in expenditures can be present as a 

result of many factors including actual physical differences in need due 

to climate or other factors, differences in preferences, availability of 

goods, variation in ,prices, or long-standing differences in income and 

prevailing usage levels. Attempting to establish that geographic price 

differences are present to a significant degree involves a number of 

analytical decisions. For example, one must decide which kinds of 

geographic areas are most valid to examine as illustrating the range of 

prices and costs; whether to cost out the same "market basket" for each 

.area; or whether to vary the contents because of physical factors or 

preference differences. 

Unfortunately, the extent and nature of geographic differences in 

cost of living cannot be determined at the present time, because available data are inadequate. The same criteria (validity, reliability, and 

frequency of collection) which were outlined in the previous section for 

evaluating data sources on family characteristics equivalences apply to 

sources on geographic equivalences. It appears that the criterion of 

reliability -- or sample size -- is especially critical for geographic 

differences, because by definition geographic analysis must be for 

populations smaller than the national total. 

Because available data are not adequate to determine geographic 

differences in needs, it is not surprising that no generally accepted 

standards of need have yet been developed that include geographic equivalences. The .BLS family budgets described previously have been costed out 

in 44 different metropolitan and nonmetropolitan areas (all of which are 

urban, however) for the four regions ,of dthe U.S. The cost for the lower 

budget for a faniily of four in the Spring of 1970 varied considerably from 

a low of $6,150 in the nonmetropolitan urban areas of the South to highs 

of $8,597 in Honolulu, Hawaii and .$lo ,788 in ~nchorage, Alaska. However, 
the places for which budgets are priced do not represent accurately or 

adequately the range of prices within regions or other areas; nor were 

they so chosen in the first place. The budget components themselves 

recognize some geographic differences, both physical and preferential. 

Heating fuel and clothing requirements vary according to climatic differences; transportation requirements vary according to size of place and the 

availability of mass transportation; and the market basket for each region 

assumes some regional differences in food consumption practices such as 

the preference for pork rather than beef in the South. Taxes are also 

varied to reflect state and local tax regulations. . Given all of the judgments involved in the derivation of the budgets, however, these differences 

cannot be accepted hs differences of need or cost-of-living expenses. 

The only other existing standards that incorporate geographic variations are the AFDC eligibility standards set by each of the states. Each 

state determines a standard of need which it uses to identify families 

with dependent children who are eligible for prograrn benefits. These 

standards vary considerably by state. For example, as of July 1974, $184 

was allotted per month ($2,208 annually) &r a family of four in ~orth' 

Carolina, while $456 per month ($5,472 annually) was allotted for a family 

of four in Wisconsin. Not all states pay their full needs standards to 

recipients. The standards may appear at first glance to represent a 

basis for determining geographic equivalences, particularly as a number of 

similarities in concept and method of determination are present among the 

states. However, there are also significant dissimilarities in concept, 

methodology, and as noted above, in dollar level. The differences are so 

great that the standards can be viewed only as guidelines for what each 

state believes is feasible for spending on its welfare program. 

Much remains to be done in developing geographic equivalences for 

poverty measurement that can be generally accepted. Generally, the data 

sources available are the same as those for family characteristics 

equivalences and standards of need; namely, the 1960 and 1970 Decennial 

Censuses of Housing, the Annual Housing Survey for housing and utility 

costs. and needs, the 1960-61' and 1972-73 Consumer Expenditure Surveys for 

all items of consumption, the 1955 and 1973 Farm Family Living Expenditure 

' Surveys fo-r farm household consumption, the 1969-70 Nationwide Personal 

Transportation Study, for transportation needs, and the vari0u.s Household 

Food Consumption Surveys. 

None of these existing data sources is of sufficient size and quality 

to support the kind of detailed analysis that would be required to establish valid geographic equivalences. Such an analysis would have to 

examine various types of geographic areas to spot major' differences and 

analyze all major expenditure categories for the several types of families 

and income levels within each area. Existing data sources are inadequate 

to support a geographic analysis by family type with additional categorization by income level and expenditure class. 
Updating the Standards 

An independent re-derivat ion of the curient poverty thresholds each 

year is impractical. Some means of updating these thresholds each year 

is necessary to take account of changing prices. Originally, the Social 

Security Administration revised the Orshansky poverty measure by the 

annual increment in the economy food budget. In 1969, the Consumer Price 

Index (CPI) was adopted for the annual adjustment. 

The Consumer Price Index is a monthly statistical measure of the 

average change in prices of goods and services purchased by urban wage 

and clerical workers. This series has been part of an on-going program 

by the Bureau of Labor Statistics since the early twentieth century. 

Although over the years there have been many changes in scope ,* coverage, 

frequency, and publication format, the index has remained a measure of 

change in the cost of a fixed market basket of goods and services. This 

section describes the construction of the current series, which is based 

on revisions introduced in January 1964. The BLS is currently undertaking 

a set of revisions, to be instituted in April 1977, which are based 

partially on the 1972-73 Consumer Expenditure Survey. 

The CPI is a weighted aggregative index number with fixed annual 

weights. The weights represent the expenditures (price multiplied by 

quantity) of items purchased and are commonly referred to as the "market 

basket" of goods and services. The quantities remain constant, except 

for revisions which occur about every ten years. Generally, those items 

are repriced at regular intervals, and the aggregate cost of the market 

basket is compared from one period to another or to the cost in a 

selected base period. 

The market basket of quantities represents all the goods and services 

purchased: food, clothing, shelter, transportation, fuel, drugs, dentist 

and doctor fees, recreation, furniture, appliances, haircuts, etc. All 

taxes on the purchase of commodities, i.e., sales, excise, and real estate 

taxes, are included, but income and other personal taxes are not. For the 

current CPI, the composition of the market basket was determined on the 

basis of expenditure patterns reported in the Consumer Expenditure Survey 

con'ducted in 1960-61. Only the responses of urban consumer units with at 

least one wage earner or clerical worker were used, and the sample included 

4,860 such families. 

The expenditure information collected in this survey was extremely 

detailed. Over 1,800 items were recorded, although the impossibility of 

pricing all items individually caused a sample of about 400 items to be 

selected for.the market basket. After classifying the detailed items 

into 52 broad expenditure classes representing groupings of items serving 

similar human needs, individual items were selected randomly with a 

probability directly proportional to their importance in the budget. 
Prices for the CPI are obtained in 56 representative urban areas 

,(stratified by region and size class) by personal visit to a representative sample of nearly 18,000 stores and service establishments where 

wage and cletical workers buy goods and services. This includes chain 

stores, independent grocery, department, and specialty stores, and repair 

and service shops in both the central city and suburbs. Where possible, 

these outlets are gen,erally represented by their sales volume. Rental 

rates are obtained from about 40,000 tenants twice a year.' The BLS uses 

mail questionnaires to obtain data on streetcar and bus fares, newspaper 

prices, and prices of certain other items which do not require a personal 

visit. For a number of items such as home purchase, college tuition, 

and magazine subscription, data collected by other government agencies 

or private organizations are used. 

Prices are collected in each of the 56 urban locations at intervals 

ranging fran once a month to once every three months, with a few items 

surveyed semiannually or annually. Because food prices change frequently 

and foods are a significant part of total spending, food pricing is 

conducted every month in each urban area. Except for food items, the 

number of price quotations obtained in each city is quite small (usually 

4 and at most 81, while the number of food stores visited ranges from 10 

to a maximum of 80 (the latter in New. York City). At the national level, 

however, this still represents a significant number of quotations. 

The BLS attempts to ensure that the index reflects only changes in 

prices and not in quantity or quality. The BLS price reporters are, 

consequently, provided with detailed specifications for each item to be 

priced, such as canned Bartlett pears or home permanent refills. Moreover, the reporters are instructed to price exactly the same item in the 

same stores each time. When it is necessary to substitute for a specified item, its price is carefully spliced into the index to avoid 

affecting the overall index. 

As a general index for updating .the poverty thresholds or for other 

purposes, the Consumer Price Index has a number of limitations. While it 

represents the average movement of prices for a fixed market basket of 

goods and services, it does not necessarily represent the change in the 

actual costs of day-to-day living of urban wage and clerical workers. As 

prices change, families may adjust their consumption patterns, substituting 

less costly items or performing services such as home repairs themselves. 

The change in relative prices also causes a change in purchases. These 

shifts in consumption patterns are not captured by the CPI, because the . 

market basket remains unchanged. 

Second, the CPI cannot be used to study intercity differences in 

either prices or living costs. Although it is published separately for 23 

of the 56 urban areas, the CPI measures only time-to-time price change in 

a given area. 
A feature.of the CPI which is sometimes cited as a limitation from' 

the standpoint of its use as a means of updating the poverty measure is 

the fact that it is based on expenses of one particular group of consumers, 

urban wage and clerical workers. The experience of this group is not 

necessarily representative of the price changes faced by the low-income 

population. The expenditure pattern of poor families is in general more 

heavily weighted to necessities such as food and shelter. Also, the items 

purchased to satisfy these needs may be of l'ower quality or may not be the. 

same as those purchased by urban wage and clerical workers. Moreover, lowincome families, frequently confined to the central city without adequate 

transportation, do not generally shop in the same stores as suburban 

families with their own automobiles. 

Data for Measuring Resources 

The data most frequently used to determine resources for comparison 

with needs are the previous year1-s income data from the Decennial Census 

or the Cur rent Population Survey. Embodied , i n . t h e incane concept employed 

in these data series are several judgments which affect the concept's usefulness for measuring resources. A more canprehensive comparison of the 

differences in income definitions and its components is found in Technical 

Paper IX, Inventory of Federal Data Bases Related to the Measurement of 

Poverty. 

First, the Census series restrict the definition of income to - cash 

income, excluding in-kind income such as food stamp bonuses, the imputed 

rental value of a home, or special benefits to workers such as subsidized 

health insurance. Second, the Census concept of cash income includes only 

regular sources of income excluding lump-sum income such as capital gains, 

prize money, and in general any one-t ime receipts. Third, the Census 

concept measures income over a year (the calendar year just prior to the 

Census or CPS survey date), excluding any data on income in previous years 

and any data on income variations within that year. The Census concept 

includes both private and public sources of money income, including such 

transfer payinents as Social Security, Veterans benefits, and AFDC payments. 

It asks for all sources before taxes or other payroll deductions. 

Base Data: the Decennial Census 

The Decennial Census of Population and Housing is by design the most 

comprehensive of all government statistical series in terms of population 

coverage. A canplete (100 percent) count of the population in 50 states, 

the District of Columbia, Puerto Rico, and the U.S. possessions is 

attempted to acquire basic demographic ,characteristics (age, sex, race, 

household relationship, marital status) and dwelling unit attributes. 

Also, such other characteristics as income, education, occupation, and 

marital history are collected by taking very large systematic samples 

of the population (25 percent in 1960 and 20 percent, 15 percent, or 5 

'percent in 1970, depending on the questions asked). The only population 

group excluded from the census is that of foreig'n citizens temporarily 
visiting or traveling in the U.S. or living on the premises of an embassy, 

legation, etc. Resident aliens are enumerated, as are U.S. citizens 

abroad for an extended period. 

Each person enumerated is counted as an inhabitant of his or her 

usual place of abode. Also, persons temporarily away from their usual 

place of residence (e.g., in a hospital or on vacation) are allocated to 

their homes. Certain groups are allocated to a place of residence according to special rules. For instance, college students, inmates of institutions, and Armed Forces personnel in barracks or on harbored vessels are 

enumerated as inhabitants of the place where they currently reside; they 

are not enumerated as inhabitants of'their families' abodes. 81 This . 

treatment may overestimate poverty among unrelated individuals in some 

areas. For example, the poverty status of college students living in 

dormitories is determined by their families' income, but the poverty 

status of those living in non-dormitory housing is determined by their \ 

own income. To the extent that students draw on their families' 

resources, their own income may not be a good indicator of their poverty 

status. 

The very large sample size for the household canposition and income 

information (100 percent for the former and 20 percent for the latter, in 

1970) suggests that estimates of the currently defined poverty population 

are reliable for narrowly defined distributions of characteristics and 

for fairly small geographic areas. More reliable estimates might still 

be desired, however, for smaller geographic areas such as many counties, 

urban places, or school districts. 

Aside £ran the fact that it is conducted only once every ten year;, 

there are other problems in obtaining complete coverage, including the 

unskilled nature of the Census field staff (most interviews and coders 

are hired on a short-term, part-time basis), the mobility and lack of 

permanent residence of a signifi~ant portion of the population, and some 

persons' resistance to being enumerated. Obviously, these problems are 

canpounded by the canplexities of enumerating and processing results for 

over 200 million individuals. ' 

About 2.5 percent of the population is missed in the Census enumeration, constituting the so-called "undercount ." The undercount varies 

systematically by age, race, and sex, with black males aged 25 to 34 

being most frequently overlooked. For black males aged 25 to 34, the 

undercount is as high as 18.5 percent of the population. 91 The undercoqt is an especially serious problem when measuring poverty because 

the groups with the greatest disadvantages are often the groups with the 

highest undercounts. 

There are alSo problems in achieving full coverage of individual populat ion characteristics, as a s-igni ficant number of enumerated persons fail 

either to report certain characteristics or to report them correctly. The 

Census Bureau has developed sophisticated editing procedures for imputing 
missing data for household and person records. These procedures attempt . I to all-ocate the."bestt' response for a person based on other information on 

record, or, if this is not possible, based on answers furnished by other 

persons living in the same area and possessing similar characterist,ics. 

Use of these procedures has improved the Census series, although all . 

editing procedures incorporate some bias. 

Of course, the most important variable (fr.om the point of view of 

poverty measurement) affected by misreporting is family and persons' 

incane. Each Decennial Census obtains information on income for the 

calendar year, preceding the Census date ( 1969 for 'the 1970 census). A11 

persons 14 years, or older are asked to report regular money income of six r 

types : 

(1) Wages or- salary income before deductions for taxes, pensions, 

union dues, etc. 

(2) Net money income from self-employment in a business, 

professional practice, or partnership. 

4' 

(3) Net money income from self-employment on a farm. 

(4) Social Security or Railroad Retirement Act income including 

Medicare premiums but not reimbursements for payments made by 

respondents for medical care covered by Medicare. 

(5) Public assistance or welfare income. 

(6) All other regular income including dividends, interest, estate 

incane, net rental income, pensions, alimony, unemployment 

benefits, etc. 

. . I here are many problems associated with income reporting in the 

Census. For example, many persons rely on recall rather than on records 

of wages paid, bank interest, etc. Even persons checking their records 

may be uncertain of what is being asked. Also, it is sometimes difficult 

to acquire accurate information on family income because families in 

existence as of April 1 of the Census year are requested to report income 

for the previous year, even though some recent members might not have been 

part of the family in that year, or even though some members might have 

left before the Census date. 

f 

For all of these reasons, incane data in t,he Census suffer considerably 

from underreporting and misreporting and require the most editing of all 

Census items. Even after editing, there is substantial underreporting, 

particularly from sources other than wage and salary income (especially 

public assistance. and property income such as interest, dividends, and 

rent). 
Current Population Survey 

A number of sources are available for annually updating the Decennial 

Census income data. No one source is completely satis factory, however, 

primarily because the sample size is too small to support state or smaller 

area estimates or because detail on household composition is limited or 

missing. 

One canmonly used data source for updating the Census is the Current 

Population Survey (CPS) conducted monthly by the Bureau of the Census to 

obtain figures on employment for the Bureau of Labor Statistics. The 

extensive information in the March Income Supplement, otherwise known as 

the Annual Demographic File, is available for annual updating of poverty 

counts. + 

The Current Population Survey closely resembles the Decennial Census 

in population coverage. However, unlike the Census, the CPS excludes 

inmates of institutions and Amed Forces personnel living on base if their 

families are not present. Also, the CPS excludes U.S. citizens livingabroad or residents of Puerto Rico or.of the U.S. possessions. Furthermore, household relationship definitions differ in one way. In the CPS, 

college students living away from home are enumerated as family members 

at their families' home rather than as unrelated individuals living in 

different areas. This is probably a more realistic treatment for the 

purpose of measuring poverty. 101 The CPS also suffers the same handicap 

as the Census with respect to changes in family composition between the 

income year and the reporting period. 

Income concepts in the CPS resemble those in the Census, except that 

in the latter there are fewer income types. For instance, as of March 

1975, the CPS identified 11 income types while the Census identified only 

6. Prior to March 1975, the CPS had divided "other income" into 3 categories so that it still included 2 more types than did the Census. In the 

CPS personal interviews by experienced enumerators reduce misconceptions, 

help respondents in checking their records, etc. However-, about the same 

proportion of persons in the CPS as in the Census (12 to 16 percent) 

furnish incomplete incane data that must be corrected in the editing 

process. 111 Income underreporting is also serious for certain income 

types as discussed later in the section on Correcting Cash Incane. 

The most important difference between the censLs and CPS from the 

standpoint of comprehensively measuring poverty is that data in the CPS 

is collected from a systematic clustered sample limited to 45,000 interviewed households (about 130,000 persons) in the 50 states and the 

District of Columbia. The CPS incurs a substantial degree of sampling 

error, even for regional estimates. This is particularly so for poverty 

estimates, because the CPS is designed to be representative of the entire 

household population and not only low-income groups. Beginning with the 

March 1976 file, the sample size will be increased to about 55,000 interviewed households. However, even with this larger sample, the CPS is 
still not designed to provide valid estimates of poverty it the state 

level. 

Administrative Records' 

Other sources of annual income data for states and smaller areas 

based on administrative records rather than surveys are available. For 

instance, the Bureau of Economic ~nal~sis (BEA) , Department of Commerce, 

estimates per-capita personal income for the nation, states, and counties 

on an annual basis. The BEA incwe concept is much more comprehensive 

than the Census or CPS. - 121 It includes, for example, several sources of 

in-kind incane. However, the direct usefulness of the BEA series for 

measurement of poverty is severely limited by the absence of any data on 

fiamily size or canposition or data permitting determination of quantities 

besides average income in a geographic area. Also, because BEA obtains 

its income figures 'from business establishments and administrative, 

records, obtaining estimates of fhily and per-capita personal income is 

c anplicated , since incane earned by workers living in jurisdictions other 

than those in which they work must be properly allocated to places of 

residence. For these reasons income distributions estimated by the BEA 

may be less reliable than aggregate or per-capita income estimates. 

Problems also affect the usefulness of the annual Internal Revenue 

Service (IRS) Statistics of Income series. This series is based on a 

11300 sample of Federal income ta returns filed by single persons and 

married couples in the 50 states, the District of Columbia, and Puerto 

Rico. Persons who made under '$600 of yearly non-self-employment income 

(under $1,200 if 65 or older) or under $400 of self-employment income are 

not required to file, although many of them file to obtain tax rebates. 

The master file contains a limited amount of information on all returns. 

The IRS concept of adjusted gross income (AGI), before deductions and 

exemptions, differs in a number of ways from both the BEA series and the 

Census 02 CPS. For example, the AGI, , like the CPS, excludes such income 

sources as wages in-kind. Unlike the CPS, however, the AGI excludes a 

large proportion o f . t r a n s f e r iricme, such as Social Security and public 

assistance, and includes some capital gains. - 131 

Moreover, for direct use in poverty measurement, the IRS data suffer 

from the fact that household and personal relationship data are not. 

obtained and often cannot be inferred from the information reported on 

the tax forms. The inadequacy of such a procedure for poverty measurement purposes is sugge'sted by the fact that married couples may file 

jointly or separately and that children or relatives.wil1 be included as 

dependents on the head's return only in certain situations. Also, 

persons wholly dependent on public tfansfers such as Veterans payments, 

AFDC, or Social Security are likely to be poor, but since their income is 

tax,exempt they are not included in the IRS data base. 
Finally, several agencies in HEW compile periodic data from administrat ive records for particular kinds of income received by participants 

in their respective transfer programs. For example, the Social Security 

Administration (ssA) provides quarterly data on earnings and industry of 

workers subject to social security payroll taxes up to the taxable limit 

of $14,100. Wages over the limit must then be estimated. Furthermore, 

no information on other income sources is contained in this series, nor 

are there data on household composition. Moreover, the SSA earnings 

series excludes all persons whose income canes from other than employment 

sources and, among employed workers, many Federal, state, and local 

government employees, workers covered under the Railroad Retirement Act, 

and person with insufficient earnings (mainly some self-employed persons, 

farm workers, and domestics). - 141 

Other program statistics have similar drawbacks. The National Center 

for Social Statistics (NCSS) publishes monthly data by state on the number 

and amount of AFDC and General Assistance payments. The SSA publishes similar data on Social Security beneficiaries and on payments under the new 

Supplemental Security Incane program for the aged and disabled, although 

these data are simple aggregates of payments by state and do not provide 

information on household relationships or on family income characteristics 

of recipients. 

Since 1967, NCSS has conducted biennial surveys of AFDC case records, 

obtaining substantial information on household size and composition, 

family income, and many other Census-type variables. The 1973 AFDC Survey 

consists of about 32,000 records, representing about a 1 percent sample 

of case-worker records in the 50 states, the District of Columbia, Puerto 

Rico, and the Virgin Islands. 151 This sample, along with supplements, 

permits reliable estimates of welfare income in all but the smallest states. 

The sample is based on case records rather than on personal interviews; the 

information on other than welfare income, particularly on earnings, may be 

less reliable than survey data. In some cases the information may reflect 

the financial status of a family in one particular month, for example, when 

the family first applied for welfare, and thus not reflect any subsequent 

changes in the family's situation. 

Unemployment Data 

Some have suggested using unemployment data as a source of current 

data on poverty in small areas. In spite of a conceptual link between 

unemployment and poverty, the two populations are not identical. 

Data at the national level (from the Cu~rent Population survey) 

indicate a lack of overlap between the unemployed and the poor, as defined 

in official government statistics. Of 5.1 million poor family heads, only 

450,000 (about 9 percent) were unemployed at the time of the survey in 

March 1975, while 643,000 poor family heads (about 12.6 percent) experienced 
unemployment during the previous year. This is because many poor 

adults are not in the labor force and are not counted as unemployed. 

A view equating poverty and unemployment may stem from the 1930s, 

when the unemployed were mostly family breadwinners, and when more than 

25 percent, of the labor force was unemployed. .Undoubtedly, there are 

instances today of poverty resulting from prolonged unemployment; for 

example, Detroit has been described by some writers as reminiscent of the 

.Great Depression. For the vast majority of the labor force, however, the 

situation is quite. different today, even in a c'mparatively deep recession 

such as that in 1975. I 

There are several reasons why the officially defined poverty and 

unemployment populations do not significantly overlap, stemming frm a 

fundamental difference in purpose for measuring these populations. 

Basically, the poverty measure is used to isolate those who have inadequate income fir their needs, while the unemployment measure is concerned 

with those who want to work but cannot find jobs; there is no reference 

to economic need or hardship, the heart of the poverty definition. More 

specifically , the measures differ for the following reasons : ( 1) periods 

of unemployment are cushioned by unemployment insurance and other s'pcial 

programs and earnings of other family members; (2) periods of unemployment 

are usually too short to cause a family's income to fall below the poverty 

line; (3) poverty is counted on an annual basis, while unemploynent 

depends upon activity in a given'week of the month; (4) poverty data 

relate to the economic situation of entire families (and unrelated individuals) while unemployment data relate to the employment status of 

individuals, regardless of their family situation; and (5) unemployment 

data excludes many of the poor who are not able to work, since those not 

in the labor force are excluded. These reasons are discussed more fully 

below. 

First, many unemployed receive Unemployment Compensation. Under this 

program they may receive up to 40 percent of gross earnings, although 

there is considerable variation by state. In 1974 and 1975, unemployment 

insurance programs covered more than two-thirds of all jobless workers. 

Moreover, some unemployed workers in selected labor unions are also 

entitled to Supplemental Unemployment Benefits. For example, it was 

reported that during the first several months of layoffs, auto workers 

were receiving 95 percent of their' previous take-home pay through a 

canbination of Unemployment Compensation and Supplemental Unemployment 

Benefits. 

BLS studies also show that nearly a third of the unemployed in 

families had another family member in the labor force working full time 

(usmlly a working wife) . These women and, occasionally , children 

usually account for no more than a fourth of family income when both 

husband and wife are working. When added to Unemployment Compensation, 

however, these earnings help keep a family from falling below the poverty 

line. 
Second, the unemployed tend to experience short terms of unemployment; the average length of a single spell of unemployment has been five 

to seven weeks. For the family to fall below the poverty line, a family 

head would have to be unemployed for a very long period of time to exhaust 

all possible benefits and have no other family earners. This rarely occurs, 

as is suggested by the fact that the 1974 median family income for 2.8 

million unemployed family heads in March 1975 was $10,200. This was $4,600 

less than that of employed workers but $3,500 more than that of persons 

not in the labor force. The poverty line for a four-person family averaged 

about $5,038 in 1954. 

1 

A third reason for the limited overlap of the poverty and unemployment populations is that poverty is counted on an annual basis, while 

unemployment depends on status during a fixed one-week reference period. 

A family would consequently have to be both unemployed and poor for an 

entire year to be counted. For reasons discussed above, it is doubtful 

that many families with working members would deplete their resources to 

the extent that the family's income would fall below the comparatively 

low threshold of the official poverty line. 

Fourth, since unemployment data are for individuals only, they 

include many secondary earners in non-poor families. For example, anyone 

16 years of age and over who is not disabled can be counted as unemployed, 

even if the family head and other family members are working. A special 

study in March 1975 showed that nearly three fourths of the unemployed 

were in families where the head had a full-time job. Another source 

revealed that, in the second quarter of 1975 when the unemployment rate 

was close to 9 percent, 5 million of the 8 million unemployed were not 

household heads, but rather wives, grown children, or other immediate 

relatives of the family head. On the other hand, poverty status is 

determined by family size as well as income. A family head may be 

employed and still be poor if his earnings are low and family size is . 

large. 

Fifth, unemployment is defined in a way to exclude persons most 

likely to be in the poverty population. The Department of Labor classifies anyone as unemployed if he or she had no work in the week of the 

interview, sought. full-time or part-time work in the four weeks before 

the interview, or was temporarily laid off from work during that time and 

was available for work during the week of the interview. Those working 

a-re, of course, classified as employed. Those not working and not looking 

for work, however, are classified as "not in the labor force." This last 

classification includes the very population disproportionately represented 

in the poverty statistics: the aged, female heads of families, and the 

disabled. Although increasing Social Security payments and, to a lesser 

extent, AFDC have been responsible in recent years for pushing some 

persons with these characteristics above the poverty line, the aged and 

female-headed families are still disproportionately included among the 

officially poor. This Labor ~e'~artment classification also excludes the 
unemployed who have given up looking for work and dropped out of the labor 

force -- a group disproportionately composed of blacks and women. 

The Job Market and Waee Rates 

The unreliability of unemployment data as an indicator of poverty also 

applies to sources of information relating to the labor market, sources 

of job availability, and prevailing wage rates. 

Labor market information is not pinpointed to the, needs of. unemployed 

poor family heads or family members; it usually provides general information 

on job availability and does not specify the generally unskilled jobs for 

which the poor person is qualified. The nationwide system of state public 

employment services offices has a system of computerized job banks. Many 

of the listed jobs call for skills that .the poor person does not possess. 

Some of the unskilled jobs may be unfilled because they offer unsatisfactory 

wages, working conditions, and fringe benefits. 

Prevailing wage surveys obtain - informat ion on average hourly or weekly 

earnings for only a limited number of specific. white-collar or blue-collar 

occupations in 82 areas of the country. These earnings are obtained for 

full-time weekly workers, exclude premium pay, and are not obtained for all 

industries. The major aim of the area wage survey program is to describe ' 

the level and movement of wages in the labor market. Relatively low weekly 

or hourly earnings for a particular individual do not necessarily. indicate 

that, on an annual basis, family income is around or below the poverty level. 

The preceding discussion establishes that there are no currently available substitutes for the income data in the CPS for national or regional 

estimates of poverty or for the Decennial Census for estimates at the level 

of states or smaller areas. The study mandated by section 822b of P.L. 

93-380 will discuss some other statistical procedures which have recently 

been formulated to develop current state estimates of the number of families 

and children in poverty. These procedures result, however, in figures 

representing total counts and lacking detailed characteristics. A number 

of the data sources described can be used to correct the substantial 

underreport ing occurring in the Census and the CPS. 

Correctine Cash Income 

The various administrative income series have more complete reporting 

by income types than do other surveys. For example, covered employers are 

obliged by law to report payroll tax information on earnings of employers 

to Social Security, 'and the law is ,backed by stiff penalties. In contrast, 

penalties for failure to cooperate with the Census or CPS enumeration are 

slight and rarely imposed. 

Table 5 provides canparative data for personal income by type 

from the 1970 Census 20 percent sample, the March 1970 CPS, the 1969 IRS 

Statistics of Income, the 1969 SSA earnings series, the 1969 BEA personal 
Table 5. comparative Data on Personal Income by Source, 

Selected Major Government Statistical Series U. S:; 1969 

Income Source 

Wages and Salary 

Self-employment: 

Nonfarm 

Farm 

(Subtotal 

Self-employment) 

Other income: 

Social Security 

Property (dividends, 

interest, net 

rental) 

Public assistance 

Public pensions, unemployment insurance, 

veterans' payments 

All other 

(Subtotal 

Other income) 

1970 Census 

20% 5 

bil. $ 

(1) 

March 1970 CPS~ 

1 ratio to 

1969 IRS 

Statistics 

2f IncomeC 

bil. $ 

(5) 

$ 498.9 

44.1 

3.6 

(47.4) 

N.A. 

38.0 

N.A. 

N.A. 

18.4 

(56.4) 

$ 603.0 

1969 SSA 

Earninis Series 

bil. $ 

(6) 

$ 455.68 

48.5 

N.A. 

N.A. 

N.A. 

N. A. 

N.A. 

(-) 

j 504.1 

1969 BEA 

Personal 

Incomee 

bil. $ 

(7) 

$ 509.0 

50.5 

16.4 

(66.9) 

33.0 

106.4 * 

10.4~ 

49.2 

(199.0) 

CPS Comparable 

~enchmark~ 

bil. $ 

(8) 

$ 490.0 

48.9 

12.9 

(61.8) 

27.5 

64.9 

6.9 

16.0 

10.3 

(125.6) 

Note: N.A. (not available) means data for this income source not collected in this series. 

Means data for this income source not shown separately in this series but lumped with all 

other income. 

U.S. Bureau of the Census, Census of Population: 1970, Vol..l, Chap. D, Detailed 

Characteristics, pt. 1, U.S. Summary, Table 257. 

UYS. Bureau of the Census, "Income in 1969 of Families and Persons in the United States," 

Current Population Reports, Series P-60, No. 75 (December 1970), Table 61. 

Internal Revenue Service, Statistics of Income--1969, Individual Income Tax Returns 

(l97l), Table 1.3. 

U.S. Department of Health, Education, and Welfare, Social Security Administration, 

Social Security Bulletin, Annual Statistical Supplement (1969), Table 34. 

U.S. Department of Commerce, Bureau of Economic Analysis, Survey of Current Business, 

Vol. 50, No. 7 (July 1970), Table 2.1. 

Estimated benchmarks using the same definitions as in the CPS, calculated from 1969 

BEA data for earnings and property income and from 1969 HEW data for transfers. SOURCE: 

Memo from Mitsui Ono to Roger Herriot, U.S. Bureau of the Census (Washington, D.C., July 6, 

1970). Note: Because the benchmarks are comparable to the CPS, which excludes most persons 

in group quarters, one would expect the census income ratios in column 2 to be higher than 

the CPS ratios in column 3. . P 

Includes estimated wages and salary income above the taxable limit. 

Includes unemployment insurance and veterans' payments only. Public pension income is 

included with all other income. 

Ratio is calculated to the total of property, public pension, and all other income in 

colm 8 ($91.2 billion). 
income estimates, and benchmarks from the BEA and HEW programs which use 

definitions comparable to those in the CPS. Compared to the benchmark., 

Census and CPS clearly obtain very acceptable reporting of wage and salary 

income and reasonably good reporting of self-employment income, although 

other items are substantially underreported. Thus, Census obtains only 

67 percent of public assistance income, and the CPS obtains only 73 percent. 

Only 42 percent of property income (dividends, interest, net rental) is 

obtained from the CPS. 

Procedures developed for correcting income reported in the CPS on an 

aggregate basis could be applied to the Census as well, based on comparison 

with administrative sources such as the IRS and SSA series. The Treasury 

Department and HEW are also attempting to derive an alternative methodo,logy 

for improving CPS income data which correct income at the individual or 

micro level. 161 This micro methodology still does not produce reliable 

intercensal pGerty est hates for states or smaller areas. 

Adding Other Sources of Income 

' 

.As stated before, the Census (and CPS) concept of income is limited 

to regular cash receipts. The concept excludes in-kind benefits' such 

as food stamps, excludes non-regular sources'of income such as prize 

money, and excludes any income value that might be attributed to nonfinancial assets such as homes. On the other hand, it includes Federal 

and state personal income and Social ~ecuriG payroll taxes. 

If the valuation issues raised in Chapter I1 can be resolved, 

it is still necessary to determine whether data are currently available 

to permit expanding the concept of income beyond regular cash receipts. 

Although it is doubtful that such data are currently available, they might 

be in the future. The following discussion considers ways in which inkind income and the value of assets present difficult problems in data 

collection. Obtaining information on lump-sum income to add to gross 

income and on taxes to subtract from gross income is relatively straightforward, although not devoid of problems. 

In-Kind Income 

Food stamps are of particular interest among the various types of 

in-kind income. Beginning in 1972, the CPS included a supplement on b 

receipt of food, stamps and other transfer benefits during the preceding 

month and the preceding year. The August 1974 CPS supplement estimated 

that 3,489,000 househol-ds including 11,680,000 persons received food stamps 

in July 1974. The most recent food stamp supplement was administered in 

December 1975. The data have several drawbacks, the most important of 

which is that they underestimate the number of recipients. Compared to 

USDA monthly figures, the 1974 CPS supplement estimated only 80 percent of 

the total number of recipients. Moreover, the food stamp supplements, like 

the March, CPS, provide relatively unreliable estimates at or below the 

state level, since they are based on a fairly small sample size. 
Data from the Panel Study of Income Dynamics (otherwise known as the 

Michigan Longitudinal survey) on food stamp recipients by year from 1968- 

1974 appear to be somewhat closer to USDA counts than the CPS supplements. 

The Panel Study is a continuing longitudinal survey of about 5,000 families 

that began in 1968 and has been repeated each year since then. Originally 

sponsored by the Office of Economic Opportunity, it is now sponsored by 

HEW, and is actually conducted by the Survey Research Center of the University of Michigan. The Panel Study includes data on several other 

sources of in-kind income such as the value of food produced at home, 

free clothing or food and free medical care through Medicaid or other 

sources. Certain uses of the data are difficult, however, because of the 

sample size of around 5,000 families. Almost half of the sample comprises 

families with incomes below the 1966 poverty level. It overrepresents the 

low-income population by about five to two, but still produces only a 

1/8,000 sample of this universe', while providing a 1/12,000 sample of the 

remainder of the population. Over 'time, the lack of representativeness 

becanes more and more limiting. 

In November 1973 the Department of Agriculture canmissioned a special 

survey of about 7,200 households certified as eligible to participate in 

either the food stamp or food canmodity distribution program. The survey, 

carried out in early 1974 by the Chilton Research Service; included 

information on other in-kind benefits such as subsidized housing, special 

food programs for school children and pregnant women, and Medicare and 

Medicaid benefits. The survey size was initially small, representing 

about 11700 of the combined program universe, and suffered from consider able 

nonresponse (the aggregate response rate was 63 percent). oreo over, there 

are indications that many respondents were unaware of several programs in 

which they participated, e.g., special school milk programs for their 

children. Thus, the' extent of in-kind benefits may again have been underestimated. - 171 

Consumption or expenditure surveys such as the 1960-61 and 1972-73 

CES have collected some data on in-kinc! income on a one-time basis -- the 

most canmonly collected data being the estimated value of food produced 

at home and food stamp benefits. The BEA personal income series also 

includes several sources of in-kind income, including such private sources 

as wages in-kind and the value of bank services, as well as some public 

sources. ,All these data sources suffer from such problems as small sample 

size for subnational estimates and lack of periodicity in the case of 

the expenditure surveys. 

In general, except for food stamps, very little data have been collected on in-kind sources of income. Moreover, the data which have been 

collected reflect. considerable underreporting , have been obtained in an 

inconsistent fashion, and indicate respondent. confusion about actual receipt. 

of in-kind incane. This suggests that canparisons among the different 

surveys will be complicated and that correction of the survey data would 

require canbining them with data obtained from administrative records. The 

Survey of Income and Education -- mandated by Section 822a of P.L. 93-380 -- 
will provide information on receipt df food stamps, Medicare, Med 

and public housing, although reporting problems will arise again. 

Value of Assets 

icaid , 

Attempting to add a value for assets to income, particularly for 

non-cash assets such as property, presents a formidable proble4. Even 

if all of the knotty judgmental issues such as the appropriate time period 

over which to amortize assets could be resolved, 'there would still be 

problems in obtaining reliable data about assets. 

The 1970 Decennial Census contains data on the current market value 

of owner-occupied homes and on the presence of durable goods such as 

automobiles, household appliances, and TVs, as well as on household ownership of a second (vacation) home. No ,data were collected on financial 

assets such as bank accounts, stocks, or bonds, and the only asset in 

the Census for eich a dollar figure is determined is an owner-occupied 

home. Even here, the data are not complete, because the only homeowners 

asked 'to report a value are those living in a single-family house which 

is not on a farm and which is not.used for a business or profession. 

Obviously, this excludes owners of apartments, mobile homes, etc. Moreover, the value reported may not be entirely realistic, since it is the 

respondent's own estimate of the burrent worth of his home. i 

The CPS does not collect any asset data, but since 1973 the Annual 

~ousing Survey has included questions similar to those in the 1970 

Census on home value, presence of automobiles and household appliances, 

and ownership of a second home. For example, the AHS (beginning with 

the 1974, survey) represents 1/1,000 of urban households and 11500 of 

rural households, while the CPS represents only about 1/1,300 of the 

population. Asset data in the AHS suffer from the same limitations 

as those in the Census, however, since the universe is restricted for 

the home value question and dollar values are absent for the other items. 

The 1972-73 Consumer Expenditure Survey and the 1973 Farm Family 

Living Expenditure Survey both obtained extensive data on property holdings 

(including purchase price as well as current market value of the family's 

home, other real property, and property improvements) and on durable goods 

and vehicles (including an inventory of items already owned plus those 

purchased during the survey year). Neither of these surveys is conducted 

very often (the latest CES was in 1960-61 and the latest Farm Family 

Survey was in l955), and both have small sample sizes. Moreover, the 

Farm Family Living Expenditure Study provides meager information on financial assets. Information on such assets is requested in detail in the . 

CES, but since responses to such questions are frequently unreliable, 

the usefulness of the CES asset data remains to be assessed. 

The 1966-67 Survey of Economic Opportunity .(SEO) also attempted 

to obtain complete assets information. The.SEO, in which approximately 

30,000 households were interviewed in 1966 and again in 1967, was designed 
to supplement information regularly collected in the CPS March Income 

Supplement relating to economic well-being. Thus, the SEO included data 

on dimensions of economic status such as housing, assets, and liabilities 

that were not usually obtained between censuses. The survey attempted 

to overrepresent low-'income families. This was done by selecting about 

12,000 cases in nonwhite areas assumed to be heavily low-income and by 

selecting the remaining cases to represent the entire population. The 

resulting sample represented about 1/ 500 of the nonwhite universe and 

1/3,500 of the white universe. 181 

The list of assets covered in the SEO is unusually complete: market 

value of the home, other real estate, own business or farm; money in banks; 

current value of government bonds; current value of stocks, bonds, or other 

private industry investments; personal loans to others, including mortgages 

and very small loans; number of cars and trucks and their value; and value 

of all other assets including airplanes, boats, oil royalties, patents, 

etc., but excluding personal belongings such as jewelry or furniture. 

Data on the following kinds of debts were also obtained: money owed for 

a car or truck; money owed to stores (excluding regular 30-day charge 

accounts) ; money owed to companies for utilities, etc. ; money 

owed for medical care; money owed to banks; and all other debts owed to 

other persons or lenders. The asset data in the SEO are less than reliable, 

and are not identified by state but only by region and for the 12 largest 

SMSAs. The sample size is too small for reliable state estimates. The 

heavy overrepresentation of nonwhite households cannot contribute to 

reliable estimates, since nonwhites comprise only about 10 percent of the 

population. 

One other source of asset data, the 1963-64 Survey of Financial 

Characteristics of Consumers, is unsuitable for poverty measurement. 

Conducted by the Bureau of the Census for the Board of Governors of the 

Federal Reserve System, the survey is inadequate as a source of poverty 

data both because of its very small sample size (2,557 completed interviews 

in all) and because it was purposely designed to overrepresent the segments 

of the population that were expected to have sizable amounts of wealth. 

Thus, 464 families with 1962 incomes of $25,000 or nore were included 

for a sampling rate of about 1/6,000, while 757 families with incomes below 

$5,000 were included for a sampling rate of less than 1/30,000. Also, 

despite intensive efforts to obtain complete and reliable information, 

comparison of the survey results with administrative totals indicates 

substantial underreporting. Thus, the survey obtained only 70 percent 

of the value of corporate stock, 60 percent of the value of installment 

debt, 50 percent of savings accounts, 47 percent of U.S. Government 

securities, and 40 percent of state and local government securities. 

Estimates of the value of corporate securities other than stock, mortgage 

debt, and noninstallment debt were much better (90 percent or higher in 

each case), and underreporting appeared much more prevalent among highincome than lower-income groups. - 19/ 
The Survey of Incane and Education will provide limited information 

on assets. It will include values of owned homes (and outstanding mortgages 

on such homes) and the ,amounts of certain liquid assets where total val'ues 

of these hssets are below $5,000 for any household. 

This review suggests, then, that reliable asset data are hard to 

obtain. Attempts at acquiring such data are discouraged by the length 

of the questionnaire required to ensure canpleteness and accuracy of the 

information, and by the absence of any agreement on how to incorporate the 

value of assets into a measure of total resources that can be canpared 

with needs standards. The general absence of reliable asset data is 

particularly unfortunate because eligibility criteria in many programs 

include a limit on asset holdings. For example, eligibility criteria of 

the food stamps program includes consideration of financial assets and 

other than personally needed property, but excludes such assets as a home 

and durable goods, the latter items being considered essential for living. 

Different Accounting Periods 

The accounting period probl'em is that of choosing'an appropriate 

time span for measuring resources to determine poverty status. The 

time span affects the status obtained. For example, when the Census 

and CPS measures income for the calendar year preceding the date of 

enumeration, it overlooks income .fluctuations within the year and ignores 

patterns of income receipt over periods longer than a year. 

Data frun Incune Maintenance Experiments conducted in Seattle, Washington; Denver, Colorado; and Gary, Indiana are a source of information on 

monthly incane trends. 201 These experiments attempt to study the work 

responses and other behavioral changes among families receiving a guaranteed 

monthly income payment, and the work responses and behavioral changes among 

a set of control families. The sample sizes in these experiments are small, 

ranging from about 2,700 families in Denver to about 1,600 in Gary, and are 

of course not intended to be nationally representative. The samples were 

designed to overselect low-income households in their respective areas, 

with female-headed families making up the bulk of the Gary sample. Thus, 

the data are not directly useful for developing nationwide measures of 

short-term poverty, although they (and the evidence from the New Jersey 

experiment) do suggest that there are substantial dithin-year income changes 

among the poor. 

Data frun the ~anel'stud~ of Income Dynamics, which has followed the 

same 5,000 families for more than five years, indicate that the "hard-core" 

poverty population -- that is, families and persons with persistently low 

incomes -- is both smaller than the total poverty population at any one 

point in time and markedly different in canposition. - 211 

The Panel Study is currently the only source of national data on 

family incane histories. The Incane Maintenance Experiments, which follow 

families for at least three to five years, are also .a' source of across-year 

trends for particular sites. 
NOTES TO CHAPTER I11 

1. National Academy of Sciences-National Research Council, Recommended 

Dietary Allowances 1974, 8th ed. (1974). 

2. For a description of the new low-cost, moderate-cost, and liberal 

food plans, see Betty Peterkin, "USDA Family Food Plans, 1974," paper 

presented at the 1975 National Agricultural Outlook Conference, Washington, 

D.C., December 12, 1974. The new. thrifty food plan is described in U.S. 

Department of Agriculture, Agricultural Research Service, Consumer and 

~obd Economics Institute, The Thrifty Food Plan (September 1975). The 

cost for this plan is estimated independently based on a market basket 

of foods, and not as a percentage of the cost for the low-cost plan, as was 

the procedure between 1968 and July 1975. The thrifty plan costs work out 

to about 77 percent of the new low-cost plan on the average, but the relationship varies depending on the sex and age of the individuals and the time 

of the estimate. 

3. Mark Sherwood, Bureau of Labor Statistics (BLS) Family Budgets 

Program, Technical Paper IV to this report. 

4. U.S. Bureau of the Census, Delineation of Problem Housing Areas, 

Data Access Description, No. 28 (May 1972). 

5. U.S. Department of Labor, Bureau of Labor Statistics, Handbook of 

Methods. Ch. 9. "Family Budgets," BLS Bulletin 1711 (revised 19721, p. 70. 

6. Basically, this technique consisted of locating the incane class 

in which maximum income elasticity occurred for a given group of consumption 

items. The average numbers and kinds of items purchased at this income 

level became the basis for the intermediate budget. Generally, income 4 

classes below and above the classes used for the intermediate budget were 

the source of quantities for the lower and -higher budgets. 

7. See "Clothing Budgets for Children from USDA: Annual Costs at 

Three Levels in Four Regions," Home Economics Journal, Vol. 1, No. 3 arch 

1973) and Virginia Britton, USDA Clothing Budgets: Annual Costs (Summer 

1974). 

8. See U.S. Bureau of the Census, 1970 Census Users' Guide, Part 1 

(October 19701, p. 93. 

9. See also Jacob S. Siegel, "Estimates of Coverage of the Population 

by Sex, Race, and Age in the 1970 Census," Demography, Vol. 11 (~ebruary 

19 74), pp. .l-23. 

10. For CPS population coverage and concepts, see any of the U.S. Bureau 

of the Census Current Population Reports, Series P-60, Consumer Income. 
11. Moreover, incane underreporting in the CPS, as well as in the 

Census, appears to be increasing. See Mitsuo Ono and Herman P. Miller, 

'"~ncane Nonresponses in the Current Population Survey,'' Proceedings of the 

Social Statistics Section. American Statistical Association. 1969. 

12. A detailed canparison of the BEA and Census income concepts is 

provided in Herman P. Miller, Income Distribution in the United States, a 

1960 Census Monograph (Washington, D. C. : Government Printing Office, 19661, 

pp. 172-190. 

13. See ~nternal Revenue Service, Statistics of Income -- 1973, 

Individual Income Returns, Sec. 7'(19757. 

14. U.S. Department of Health, Education; and Welfare, Social Security 

Administration. Social Security Bulletin. Annual Statistical Supplement. . . - 1973, pp. 5-6. 

15. See U.S~ Department of Health, ducati ion, and Welfare, Social and 

Rehabilitation Service, National Center for Social Statistics, Findings of 

the'1973 AFDC Study, Pts. I-IV (1974). 

16. See Frederick J. Scheuren and Barbara Tyler, "~atched Current 

Population Survey and Social Security Data Bases," Review of Public Data 

- Use, Vol. 3, No. 3 (July 19751, pp. 7-10. 

17. U.S. Congress, Senate, Committee on Agriculture and Forestry, 

Food Stamp Program: A Report in Accordance with Senate Resolution 58 

7~~1~ 21, 1975). 

18. ~xecutivb Office of the President, Office of Economic Opportunity, 1967 Survey of Economic Opportunit'y Codebook. 

19. Dorothy S. Projector and Gertrude S. Weiss, Survey of Financial 

Characteristics of Consumers, Federal Reserve Technical Paper (August 

19661, Technical Note. 

20. Raymond J. Uhalde, Analysis of Multiple Benefits Receipt Among 

the Low Income Population (Washington, D. C.: Mathematica, Inc., 

Decenber 19741, Ch. I. Similar experiments conducted in four cities 

in New Jersey and Pennsylvania from 1968 to 1972 and in two rural sites 

also obtained monthly incane data, but for much smaller samples than the 

Seattle, Denver, and Gary experiments. 

21. See U.S. Department of Health-, Education, and Welfare, Office of 

the Assistant Secretary for Planning and Evaluation, Office of Income . 

Security Policy, The changing ~conomic Status of 5000 American Families : 

Highlights from the Panel Study of Income Dynamics (May 19741, Ch. 11. 
IV. CONSTRUCTING POVERTY MEASURES 

Preceding chapters have discussed some alternative measures of poverty 

and issues related to their use. As shown, data limitations and conceptual 

problems restrict the number of alternatives that would be possible to 

construct at this time. This chapter discusses measures that could be constructed using available data and known conceptual frameworks. It generally 

follows the outline of Chapter 11, but its emphasis is on realistic alternatives rather than on all measures that are theoretically desirable. First, 

the empirical effects, advantages, and disadvantages of relative and fractionof-the-median measures are examined and contrasted with the current measure. 

The chapter then considers possible variations of the current measure, such 

as use of a new or different food plan, a different formula for expanding 

food costs to total family living needs, or different adjustments to poverty 

measures to reflect differences by geographic regions and over time. Finally, 

it describes the impacts of different definitions of income and the use of a 

household rather than a family as the reference unit. 

Relative Measures of Poverty 

Economic measures of poverty are either absolute, and do not vary automatically with changes in income, or they are relative and change directly 

with the prevailing income. Absolute measures clearly require judgmental 

decisions and construct ion from consumption patterns or standards that are 

not always currently available. Selection and reevaluation of a fixed percentile for the purely relative measure and a fixed percent of median family 

income for the quasi-relative measure also require judgmental decisions on 

selecting the percentile or percentage of median income that best divides 

poor from non-poor. Although methods for establishing such levels are 

subject to theoretical differences and wide disagreement, it should be noted 

here that analysts frequently use the lowest quintile or quartile and fifty 

percent of median family income. 

Unlike the purely relative concept, measures using a percentage of 

median family income theoretically allow reduction or even elimination of 

poverty, since every family could have income exceeding some specific percent of national median family income. Use of a poverty line based on 

median income would show progress only if efforts were directed at redistributing rather than increasing incomes in general. Using this measure, 

national efforts to overcome poverty would appear to be unsuccessful unless 

the incomes at the lower end of .the income distribution increased at a 

faster rate than incomes in general. 

However, this theoretical possibility has not happened. For the 

past 15 years, a poverty line set at 50 percent of median family cash income 

would have resulted in an almost constant poverty rate for families, and 

thus would have resembled a purely relative cutoff set at the lowest quintile of the family income distribution. This does not mean that there has 

been little income redistribution in the past 15 years. Some recent poverty 

programs have redistributed benefits in the form of in-kind transfers 
like food stamps. Furthermore, it is clear from annual income statistics 

that the composition of households at the bottom of the distribution is 

now different. By and large, families of workers, particularly working 

men, have moved out of the lowest quintile (or quartile) while families 

dependent more on transfer payments than on earnings -- the aged and 

female heads of large families -- have not. The income distribution would 

be different if in-kind income, housing, medical insurance, and benefits 

from private sources were counted as income; if some value of assets were 

included; or if adjustments for taxes were made. 

When using fraction-of-the-median definitions, it is important to 

determ'ine ,£run which median family income a given percentage is to be 

taken. For example, since the median family income in 1969 for a family 

of four was $10,782 and for all families was $9,586, a definition based 

on the median family income for a family of four (as in Titl'e XX of the 

Social Security Act) would yield a different threshold than would one 

based on the median family income .for - all families (as in Title I1 of the 

Housing and Community Development Act of 1974). Furthermore, definitions 

based on the median family income in the nation or in each state (as in 

,Title XX of the Social Security Act) or in each metropolitan area (as in 

Title I1 of the Housing and Community Development Act) will also have 

different results. 

It is sometimes suggested that relative definitions of poverty have 

the advantage ofi enabling natural adjustments of the poverty lines for 

family size or other characteristics. For example, if the poverty line 

is set at 50 percent of median family income, the poverty line for a fourperson family can be set at 50 percent of the median family incane for 

four-person families, and similarly for other family sizes. Table 6, 

which shows median family income in 1969 by family size in a few states 

'and in. the nation as a whole, illustrates the problems with this method. 

It is usually presumed that larger families need more income, but in every 

instance displayed in the table the families of seven or more have lower 

incanes than four-person families. 

Similar problems arise if the median income for various subgroups of 

the low-income population is used as a basis for poverty lines. For example, 

the median incane for families in 1969 was $9,586, while that for unrelated 

individuals was only $2,489; If 50 percent of median family.income were used 

as a poverty line for persons living in families, and 50 percent of median 

income for unrelated individuals were used for persons living alone, the 

poverty lines in l969'would have been $4,795 and $1,245, respectively. A . 

definition of poverty based on dir.ect estimates of needs rather than on the 

relative place in the income distribution may have a different relationship. 

Unlike the current poverty matrix which results in a fluctuating 

but downward tre,nd in the poverty counts, a relative measure would have 

shown'a constant rate of poverty. For example, between 1959 and 1974, the 

number of families defined as poor under the current measure declined 

frm 18.5 percent to 9.2 percent of the population. One reason for this 
Table 6. Median Income by Size of Family Unit for United States and Selected States, 1969 

(~ndex, U.S. median income for a family of four = 100.00) 

- - 

Size of Family Unit 

UNITED STATES 

State 

Number .................. 51,168,599 

Median income .... .do1 .. 9,586 

Index ................. 88.9 

Nm YORX 

~otal~ 

milies 

Number .................. 4,609,638 

Median income .... .do1 .. 10,609 

Index ................. 98.4 

ILLINOIS 

Number .................. 2,794,194 

Median income .... .do1 .. 10,957 

Index ................. 101.6 

1 

Person 

CALIFORNIA 

3 

Persons 

2 

Persons 

Number .................. 5,001,255 

Median income ..... do1 .. 10,729 

Index ................. 99.5 

NORTH CAROLINA 

Number .................. 1,292,466 

Median income ..... do1 .. 7, 770 

Index ................. 72.1 

4 

Fersons 

MISSISSIPPI 

5. 

Persons 

Number .................. 534,444 

Median income ..... do1 .. 6,068 

Index ................. 56.3 

6 

Persons 

SOURCE: U.S. Bureau of the Census. 1970 Census of Population, Vol. I, Characteristics of the Population, Chap. D, "~etailed ~haracteristics." 

Part 1, U.S. Summary. Tables 250 and 251, and Parts 6, 15, 26, 34, and 35, Tables 198 and 199. 

7 

Persons 

8 

Persons 

a Excludes family units of 1 person. 

9 

Persons 

10. Persons 

or Mre 
difference is the changing relationship between the absolute and relative 

measures of poverty. As shown in Table 7, the current' poverty cutoff for 

a nonfarm family of four has steadily declined, as a percentage of the 

median income for a four-person family between 1959 and 1974. The present 

poverty line for ,a (nonfarm) four-person family adjusted only for price 

changes has declined to 34 percent of median income for four-person families in 1974 -- down from approximately 49 percent in 1959 and 44 percent 

in 1963, the poverty base year. Clearly this reflects an increase in real 

income, but it also suggests that the standards on which the current 

poverty cutoff are based may need to be reevaluated. 

Table 7. Comparison of Median Family Income and 

Official Poverty Cutoff for a Family of Four, 1959-1974 

SOURCE: U.S. Bureau of the Census, Current Population Reports, 

Series P-60: for median income, see annual reports on 

mone income of families and persons; for poverty . . cutoffs, see annual reports on the poverty population. 

Year 

poverty Level Market Basket 

Setting and updating both absolute and relative measures require some 

method for determining a basic level of need. As noted in Chapter 11, 

Median Income 

for a 4-person 

Family 

(U.S.) 

Poverty 

Cutoff for a 

&-Person Family 

(Nonfarm) 

Poverty 

Cutoff ae a 

Percentage of 

&dim Income 
there are conceptual problems in using a full market basket approach for 

setting such a level. since standards of need based on scientifically 

measurable consumption units are not available. Furthermore, as is discussed in Chapter 111, AFDC state budgets and BLS Family Budgets are 

unacceptable as poverty cutoffs. It should be added that the Orshansky 

measure was developed using the particular construction of a nutrition 

base and a multiplier. precisely because of the difficulty of setting 

standards given the data base and conceptual problems. 

The Department of Agriculture uses the Recommended Dietary Allowances 

as the basis for nutritional goals for its food .plans. Other nutritional 

standards could be used as a basis for food plans for use in the Orshansky 

measure. In an analysis which was prepared for this study and which is 

summarized in technical paper XII, the USDA used two other standards to 

construct a variety of food plans for 12 age-sex categories and determined 

the cost of such plans. It was found that the plans developed to meet the 

three different standards (and take into account food consumption patterns 

of survey households with relatively low food costs) had similar costs. 

Thus, the choice of nutritional standards does not necessar,ily affect the 

poverty thresholds. The composition of food plans can. however, significantly affect poverty cutoffs. because plans can be more or less liberal 

in the use of delicacies. high-quality meats, and other expensive foods, 

and in making assumptions about spoilage or waste. 

It should be noted that while a majority of survey households who 

spent less on food than the cost for the USDA's least costly food plan 

did not have diets that provided recommended amounts of nutrients, such 

households did not necessarily suffer from a nutritional deficiency. As 

has been stated earlier. not everyone requires the amounts of nutrients 

specified in the RDA. Furthermore, the USDA's least costly food plan is 

not the lowest-cost adequate diet that could be developed. It is intended 

to be reasonably palatable and is characterized by certain aesthetic 

aspects of foods that people desire. Expenditures for waste and nonnutritious foods are not eliminated from the food plans. The amounts of 

expensive types of foods such as meats are restricted in the plan, while 

whole-grain and enriched breads and cereals and dry beans. which provide ' 

many important nutrients at low cost, are included in large amounts; 

Nutritious plans at lower cost could be developed, but such plans would 

deviate further than the USDA plan from the food consumption patterns 

of U.S. households. The same subjective factors which enter into the 

setting of a poverty line enter into the selection of a food plan intended 

to be used for poverty measurement. 

The cost of the thrifty plan (estimated using 1965-66 prices) is low 

when compared to the cost of food reported as used by survey households in 

the 1965 Household Food Consumption Survey. Only 10 percent of the 1965-66 

survey households used food costing less than the thrifty plan. Preliminary food expenditures reported from the 1972-73 Consumer Expenditure 

Survey, although not completely comparable. are lower than costs of food 
reported as used by households in the 1965-66 Food Consumption Survey, 

updated to 1972-73 levels. Expenditures ,reported in the 1972-73 Expenditure 

Survey for the average family of four were $30 a week for food at home 

and $40. for food at home and away from home. These expenditures fall 

between the cost for the USDA's low-cost plan and moderate-cost plan in 

1972-73 for'a four-person family composed of a couple and'two elementary ' 

school children ($33 and $42, respectively). The costs for the food plans 

cover food for all meals and snacks for the week, but assume that all 

food is prepared at home. Also, the plans are designed to provide 

nutritious diets, and the nutritional quality of foods covered by 1972-73 

expenditures is not known. 

Since no accepted standards of need exist for nonfood items (housing, 

clothing, transportation, etc.), the current poverty threshold is derived 

by assuming that the appropriate ratio of expenditures on nonfood items 

to expenditures on food would be that observed on the average in the 

United States. The 1955 Food Consumption Survey found that average food 

expenditures made up one third of total income after taxes. Thus, the 

cost of the economy food plan was multiplied by three to obtain the poverty 

standard. The largest component of the poverty cutoffs is, then, set 

by this multiplier. A slightly different ratio is used for one-person 

and two-person families, since their total consumption requirements and 

fixed costs are believed to be significantly different from those for 

larger families. Income after Federal income taxes was used as a proxy 

for expenditures so that income for total expenditures- could be compared 

to necessary food expenditures. Of course, income allows for saving as 

well as consumption. 

The appropriate multiplier is a question of judgment, and multipliers 

higher or lower may be 'reasonable. Some people have questioned, for instance, 

the judgment implicit in assuming that food expenditures must not exceed 

the average proportion of total income .spent on food if total income is to. 

provide adequate amounts of clothing, shelter ,. and other nonfood items. 

The problem is that, as family income increases, the proportion. of income ' 

spent on food goes down. According to the Consumer Expenditure Surveys, at 

the lowest family incokes, upwards of 50 percent of cash income is observed 

to be spent on. food. Thus, very poor families may forego some nonfood 

expenditures to maintain an adequate diet. ' The average family, however, 

. spends a much smaller proportion of its income on food than families that ' 

would be at the poverty line under the current measure. And, over time, 

as average family income increases, the proport ion Pevoted to food continues to decline, while there is an increase in the proportion of nonfood 

items (presumably including more luxuries). Many believe, therefore, that 

it would be better co base the multiplier on the proportion of income 

spent on food by those below the average, .although the precise level is ' 

difficult to determine. 

On the other hand, a higher multiplier has been suggested because 

surveys other than the 1955 Food Consumption Survey, from which the 3:l 

ratio is derived, indicate a higher ratio of nonfood to food expenditures 
for the average American family. For example, a ratio of 3.4: 1 is derived 

from the 1965 Food Consumption Survey, possibly indicating a general rise 

in the standard of living since 1955. More significantly, the Consumer 

Expenditure Surveys of 1960-61 and 1972-73 seem to indicate that the ratio 

exceeds 5:l. One reason for this discrepancy may be the underreporting of 

income in the 1955 Household Food Consumption Survey because income information was measured globally for the entire household, not for household 

members separately. Data for 1965 are likely to be less valid. The household was asked only to specify an income class representing household income 

after taxes in 1965, but to specify total income and deductions in 1955. 

The Consumer Expenditure Surveys, on the other hand, obtained income by 

detailed source so that income figures are likely to be more reliable and 

less likely to be underreported. At. the same time, the food expenditure data 

may be less reliable in the Consumer Expenditure Surveys. 

Another issue relating to the mu1 tiplier involves an irkonsistenc ' 

between income definitions. The multiplier is based on the after-tax 

income-to-food expenditure ratio. Thresholds thus derived are compared to 

before-tax Census income. 

Orshansky Update 

It is evident that many critical judgments significantly affect the 

level of the current poverty lines. These judgments pertain to: the level 

of food plans considered as adequate, the multiplier relating total income 

requirements to the cost of the food, the appropriateness of before-tax or 

after-tax income, the setting of thresholds for representative family . types within the range of requirements for similarly composed families, 

and adjustment of the cutoffs for very large or small families. To 

understand how significant these judgments can be, one need only consider 

the implications of using the low-cost food plan rather than the economy 

food plan and using a 5:l rather than the 3:l multiplier. These two 

changes, both within the range of reasonable judgment and based on 

statistical interpretations, would more than double the official poverty 

thresholds and include about one-third of the population as poor. 

In Technical Paper XI of this study, Mollie Orshansky constructed 

alternative poverty cutoffs taking into account many of these factors. 

More than twelve setsof poverty cutoffs are constructed, and the characteristics of the poverty populations, identified by using these cutoffs 

are examined. 

Table 8 illustrates the effect which some of these factors can have 

on the poverty cutoffs. Four sets of revised cutoffs are shown, compared 

to the official weighted average poverty cutoffs for 1974. The revised 

cutoffs are based on the revised low-cost food plan, two versions of 80 

percent of the revised low-cost 'food plan, and the thrifty food plan. In 

the current official poverty matrix a single cutoff is assigned to families of seven or more persons with a specified number of children, by sex 

bf head. This cutoff was an aver.age cutoff for larger families (representing about eight .persons). One of the revised sets of cutoffs using 

80 percent of the low-cost food plan (Condensed Family Size) uses this 
Table 8. Sensitivity Analysis of 1974 Poverty Cutoffs 

IOfficial 1 Revised Povertv Cutoffs Based on: 

I 

1 Person 

Weighted 

Average 

Under 65 Years $2,557 

65 Years or Over 2,352 

2 Persons 

Head under 65 3,294 

Head 65 or Over 2,958 

3 Persons 3.910 

4 Persons 5,008 

5 Persons 5,912 

6 Persons 6,651 

7 Persons 

8 Persons 

9 Persons 8,165~ 

10 Persons 

11 Persons or More 

SOURCE: Based on analysis performed by ~ollie Orshansky (see Technical 'paper XI). 

Family Size Level l%lncreasea Level 1 %increasea 'Level 1 %increasea ILevel 1 %1ncreasea 

-. 

Note: Sensitivity analysis based on indicated food plan and an income:food expenditure ratio of 3.4:l. 

80% Low-Cost Plan 

Condensed Fam. Size 

d a Percent increase over the 1974 official weighted average cutoff. 

Represents an average for families with 7 or more persons. 

Thrifty Plan. 

same convention. The other sets of revised cutoffs show separate dollar 

levels for the larger families. up to size eleven. Each set of cutoffs 

used an income-to-food ratio of 3.4:1, derived from the 1965 Food Consumption Survey. As the table illustrates, all of the new poverty thresholds exceed their comparable official weighted average 1974 cutoffs, 

although the increase is not the same for each family size and is much 

smaller for families with three to six members. This differential 

increase partly relates to the differential adjustment of the RDA for 

adults and children between 1958 (the basis for the economy planin the 

current formula) and 1974 (the basis for the revised food plans). Another 

reason' is that, compared with' 1955, the, 1965 survey indicated a larger 

drop in the percentage of income spent on food for two-person families 

than for all famXlies, so that the multipliers are different. 

Poverty cutoffs based on the low-cost food plan are included for 

several reasons. First, they illustrate the significant impact which the 

level o£ the food plan can have on the poverty cutoffs. Second, they demonstrate the effect which a change in the poverty cutoffs would have on 

the "near poor" cutoffs which are based on the low-cost food plan (the Census Bureau publishes counts of those at 12.5 percent of the poverty level). 

Finally, the cutoffs based on the revised low-cost plan approximate the 

effect of using the thrifty food plan with a higher income-to-food ratio. 

The reason is that, for all family sizes except persons living alone, the 

low-cost food plan is approximately 27 percent higher than the thrifty 

food plan. Therefore, poverty cutoffs' based, on the low-cost food plan and 

I 

80% Low-Cost Plan Low-Cost Plan 
The revised poverty lines illustrated here center about the USDA 

food plans of December 1974 -- a time when food prices were abnormally 

high relative to other commodities. Accordingly, poverty cutoffs were 

also constructed from 1972 food plans and updated to 1974 by the allitems CPI. This is discussed later in this chapter in the section, 

Updating the Standard. 

The change in the poverty cutoff based on the thrifty food plan and 

a 3.4:l multiplier for a four-person family ($6,366) is 43 percent of the 

1974 median income for four-person families ($14,7471, just about what it 

was for the current poverty line in its base year 1963. similar comparisons for the current cutoffs are: 49 percent in 1959, 42 percent in 1964, 

and 34 percent in 1974. 

Table 9 displays variations in the size of the "poverty population" 

associated with each of the poverty cutoffs shown in Table 8. With the 

revised cutoffs based on the thrifty food plan, there are 8.7 million 

poor families in 1974, equal to 15.6 percent of all families. An examination of the characteristics of the poverty population using these 

updated cutoffs is included in Technical Paper XI. The impact of using 

the new measures can be approximated, however, by examining the different 

levels of the current poverty measure explored in Chapter V. Because of 

the differences in the food plans, the levels examined in Chapter V may 

show a slightly different distribution by family type than will those 

based on the revised cutoffs discussed here. 

Table 9. Size of the Poor Population 

Under Current and Revised Poverty Cutoffs, 1974 

( In mil 1 ions) 

U.S. 

Population 

The Poor 

Using 

Official 

Poverty 

Cutoffs 

-- - 

Using Revised Poverty cutoffsa 

80% of 

Low-Cost 

80% of 

Family Size Plan 

Persons 209.3 24.3 39.2 39.9 41.4 55.4 

Families 55.7 5.1 8.8 8.7 9.0 12.8 

Unrelated 18.9 4.8 8.4 8.2 !.4 9.2 

Individuals 

Children 49.8 7.5 10.4 11.1 11.6 15.4 

Ages 5-17 

In Families 

Source: Special Tabulations from the March 1975 Current Population Sufvey. 

a Revised cutoffs are identified by the food plans, as in Table IV-3. Revision of the 

cutoffs, however, involves factors other than food plans. 
Adjustments for Family Size and Composition 

As noted in Chapter 11, a measure which is used to equilibrate 

standards of need for different family size and composition is called an ' 

equivalence scale. The most extensively developed equivalence scale 

published by the Federal government is that which the Bureau of Labor 

Statistics uses in connection with its Family Budget series. Technical 

Paper IV, which includes a description of the scale, concludes that 

because of technical shortcomings in the derivation, it should not be 

used for adjusting poverty standards for family size and composition. 

It is presented here to illustrate some problems encountered in the construction of equivalence scales. The BLS equivalence scale is illustrated 

in Table 10. 

Early consumption studies suggested that the percentage of income a 

family spends on particular goods changes as the family's income changes. 

With necessities such as food, the percent of income spent on such goods 

declines as the income increases. Thus, two, otherwise equivalent families 

with different incomes would spend different percentages of their income 

on food. This is the' basis for an assumption that families spending equal 

proportions of their incane on food are living at equivalent levels in all 

ways. This basic assumption is 'used in the construction of the BLS 

equivalence scale. Furthermore, in developing the scale, smoothings and 

replotting of data were. performed because the actual data used did not 

initially fit basic preconceptions that a scale should increase with 

.family size, other variables held constant. The arbitrariness of the 

basic assumption and 'the peculiar behavior of the data have caused the 

Bureau of Labor Statistics to alert users to the limitations of its 

equivalence scale. 

The current poverty measure consists of a matrix of cutoffs for 124 

different family sizes and types. Sixty-two of these cutoffs, by family 

size, age and sex of head, and number of related children under 18, were 

separately derived on the basis of different nutritional requirements, 

except that one-person household criteria were derived from the two-person 

relationship rather than fran the food requirements, because of considerat ions and limitations discussed in Technical Paper XI. In addition, a 

downward adjustment for farm residence was made to account for the noncash 

incane of home-grown food, increasing the number of cutoffs to 124. '~n 

equivalence scale can be derived from these cutoffs by using the poverty 

line in the current poverty measurement system for a four-person, twochild, male-headed, nonfarm family as the base set at' 100, and then 

indexing all other poverty lines for the remaining 123 family types in 

relation to this base. Table 11 shows the derived equivalence scale which 

could be used to adjust other poverty lines for family size and type. As 

finely adjusted as the poverty thresholds are, however, it is still necessary to make approximations in assigning the thresholds to various types 

of families. For example, a threshold is assigned to a (nonfarm) fiveperson female-headed family with three children. There are many such 

families; the range of children's ages can be great, and the two adults 

can be young or old, male or female. 
Table 10. Revised Equivalence Scale 1/ 

for Urban Families of Different Size, Age, and-composition 

(4-person family-husband, age 35 to 54, wife, 2 children, older 6 to 15=100) 

-- 

I Age of head 

Size and type of family2 

One person ............................... 

Two persons: average3. ...................... Husband and wife .......................... One parent and child ........................ 

Three persons: average3 ...................... Husband, wife, child under 6. .................. Husband, wife, child 6-15 .................... Husband, wife, child 16-17.. .................. Husband, wife, chi Id 18 or over ................. One parent, 2 children ........................ 

Four persons: average3 ...................... Husband, wife, 2 children, (older under 6) .......... Husband, wife, 2 children, (older 6-15) ............ Husband, wife, 2 children, (older 16-17) .. , ........ Husband, wife, 2 children, (older 18 or over) ........ One parent, 3 children ....................... 

Five persons: average3 ...................... Husband, wife, 3 children, (oldest under 6) ......... Husband, wife, 3 children, (oldest 6-15) ........... Husband, wife, 3 children, (oldest 16-17) .......... Husband, wife, 3 children, (oldest 18 or over) ....... One parent, 4 children ...................... 

Six persons or more: averoge3 .................. Husband, wife, 4 children or more, (oldest under 6) .... Husband, wife, 4 children or more, (oldest 6-15) ...... Husband, wife, 4 children or more, (oldest 16-17) ..... Husband, wife, 4 children or more, (oldest 18 or over) . . One parent, 5 children or. more ................. 

SOURCE: Bureau of Labor Statistics. Revised Equivalence Scale for Estimating Eql 

(November 1968). derived from BLS Survey of Consumer Expenditures, 1960. 

.lent Incomes or Budlet Costs by Family Type, Bull. No. 1570-2 

'The scale values shown here are the percentages of the cost of goods ond services for family consumption of the base family 

(4 persons--husband, oge 35-54, wife, 2 children, older child 6-15 years) required to provide the some level of living for urbon 

families of different size, age, and composition. 

2~usbond-wife and one-parent fomilies with their own children (including adopted and stepchildren) present, but with no other 

persons living with the family. 

'~cale volues for individual family types weighted by the number of fomilies of each type in the universe. The overages include 

some types for which values were not shown separately becouse of the small number of such fomilies in the sample. 

4Revi sed. 
Table 11. Equivalence Matrix Implicit in Current Poverty Measure 

NONFARM 

- FARM 

Size of Family Unit 

Male Head 

Person (Unrelated Individual): 

Under 65 years 

65 Years and Over 

Persons : 

Head Under 65 Years 

Head 65 Years and Over 

Persons 

Persons 

Persons 

Persons 

or More Persons 

Number of Related Children Under 18 Years Old 

Female Head 

Person (Unrelated Individual): 

Under 65 Years 

55 Years and Over 

Persons : 

Head Under 65 Years . 

Head 65 Years and Over 

Persons 

Persons 

Persons 

Persons 

or More Persons 

None 

Male Head 

4 

Person (Unrelated Individual) :, 

Under 65 Years 

65 Years and Over 

Persons : 

Head Under 65 Years 

Head 65 Years and Over 

Persons 

Persons 

Persons 

Persons 

or More Persons 

1 5 6 

Female Head 

2 3 

Person (Unrelated Individual): 

Under 65 Years 

65 Years and Over 

Persons : 

Head Under 65 Years 

Head 65 Years and Over 

Persons 

Persons 

Persons 

Persons 

or More Persons 

SOURCE: Mollie Orshansky, Office of'Research and Statistics, Social Security Administration 
Some argue that modern computer technology can handle more detailed 

thresholds. Statistical definitions of poverty could conceivably be based 

on tailor-made food plans for .each family, fitting the age and sex of 

every family member. Another view holds that such fine distinctions are 

not meaningful, since nutritional standards and food plans are themselves 

only approximations subject to error. Moreover, it is hard to believe 

that families themselves can and do adjust spending patterns this incremental 1 y. 

Simplification of the standards by eliminating some of the size and 

composition differences in the poverty lines has been proposed. One reason 

for this is that the differences, which are based on nutritional requirements, cannot be representative of total income requirements. It is not 

likely that total consumption patterns vary by family size and composition 

in the same way that nutritional requirements do, or that variations for 

other basic needs can be as precisely measured as nutritional needs. 

Moreover, a simplified structure would more closely approximate common 

administrative income eligibility standards, which make distinctions only 

for family size. Chapter V discusses the statistical results of progressively reducing the number of thresholds by eliminating distinctions based 

on residence, sex of head, and the presence of children. Further significant details about the construction of the poverty thresholds are to be 

found in Technical Papers I and XI. 

It is possible to use Table 11 to derive equivalence scales with less 

sophistication. For example, one can eliminate the farm/nonfarm difference 

and use only the nonfarm portion of the table. Similarly, one can eliminate 

differences for sex of head by using only the male-headed, nonfarm portion. 

It is not possible, however, to derive a set of adjustment factors for 

family size alone from this table. Such factors must be derived from 

weighted average poverty cutoffs which are published each year by the Census 

Bureau in its series on the characteristics of low-income families (Current 

Population Reports, Series P-60). The weighted cutoffs for 1974'are displayed in Chapter I, Table 3. Equivalence scales derived from the annual 

tables of weighted cutoffs vary slightly from year to year because the 

tables are based on current numbers of U.S. families of each type. Similar 

tables can be derived based on the number of poor families. 

Equivalence scales derived from the poverty matrix are useful for 

analytical purposes -- chiefly to compare alternative poverty cutoffs with 

the official ones. They are used in this way in Chapter V, which compares 

the size and composition of poverty populations under alternative poverty 

measures. 

Geographic Cost-of-living Differences 

One of the most troublesome concepts of poverty measurement is that 

of geographic cost-of-living differences. Because of Congressional interest 

in the subject, as noted in section 823 of the Education Amendments of 1974, 

as well as because of concern about the problem among technicians, this 
study directed considerable effort inpan analysis of possibilities for 

incorporating such differences in a poverty measure. Data sources examined 

include: the BLS Family Budget series, state standards of need for the 

program of Aid to Families with Dependent Children, the 1960 and 1970 

Decennial Censuses of Housing, the Current Population Surveys, the 1955 

and 1973 Farm Family Living Expenditure Surveys, the Consumer Price Index, 

the 1955 and 1965 Household Food Consumption Surveys, and the 1960-61 

and 1972-73 Consumer Expenditure Surveys. In addition, economic literature 

and related government studies on the subject were reviewed, and special 

studies were undertaken to see if data limitations or conceptual problems 

could be overcome. Material relevant to the subject of geographic differences will be found in: Technical Paper 111, Literature Review and Annotated Bibliography; Technical Paper IV, The Bureau of Labor Statistics 

Family Budgets Program; Technical Paper VIII, The 1972-73 Consumer Expenditure 

Survey; Technical Paper V, The Consumer Price Index; Technical Paper XIII, 

Geographic Differences and Relative Poverty; Technical Paper XV, Analytic 

Support for Cost-of-Living Differentials in the Poverty Thresholds; 

Technical Paper IX, Inventory of Federal Data Bases Related to the Measurement of Poverty; and Technical Paper XIV, Relative ?leasure of Poverty. 

'The conclusion of this extensive analysis is that although there may 

be geographic differences in the cost of living, there is' no known way to 

make satisfactory geographic adjustments .to the poverty cutoffs. Significant problems stem from both unresolved conceptual is'sues discussed in 

Chapter I1 and from data limitations discussed in Chapter 111. ' Research 

and statistical activities that might lead to a resolution of some of the 

problems are discussed in Chapter VI. The major lines of argument leading 

to the negative finding are reviewed here in some detail. 

Components of .Geonravhic Differences 

Because it is necessary to deal simultaneously with many overlapping 

and interdependent subjects, it is helpful to describe the elements involved in an analysis of geographic difference~. The major components are 

residential classification, elements of expense, the types of economic , 

measures, and levels of living. 

Residential or Geographic Classification , 

A variety of residential or geographic variations can be explored in 

a study of geographic differences. For example, political boundaries such 

as states or counties, incorporated places with different population densities, and regions like the North or South are most often the bases for 

residential classification. Sometimes the type of industry, such as farming, 

forms the basis of the definition. In other instances, geographic characteristics such as high plains, mountains, or coastal plains or climatic 

characteristics constitute the definition. In addition, sometimes the classification is based on where people live, sometimes on where they work, and 

sometimes on,where they buy goods and services. Unfortunately, these 

classification systems are not mutually exclusive. For example, a Standard 
Metropolitan Statistical Area (SMSA) is a county or group of contiguous 

counties that contains at least one city of 50,000 inhabitants or more, 

I or "twin cities" with a combined population of 50,000 or more. A nonmetropolitan area is one that is not within a SMSA. The metropolitan classification differs technically from the urban-rural classification. The urban 

population consists of all persons living in places of at least 2,500 

inhabitants incorporated as cities, villages, boroughs, and towns. The rural 

population includes all persons living outside urban areas. The rural 

population can be divided into two groups, the rural farm population, which 

includes rural people residing on farms, and rural nonfarm people. When the 

terms farm and nonfarm are used as a dichotomy, the nonfarm population 

includes the rural nonfarm and urban groups. But, rural people can be 

found in SMSAs. In the various studies, some data are presented using 

one classification system, and some another. This is an inherent, almost 

unavoidable, problem when a variety of data is used. 

Elements of Expense 

Elements of expense such as food, shelter, transportat ion, medical 

services, and clothing are useful for cataloging prices and expenditures 

by residential category. All such expenditure categories need to be 

explored in order to adjust poverty cutoffs for resid~ntial differences. 

Types of Economic Measures 

Frequently, two different phrases are incorrectly used interchangeably 

to describe geographic differences. The first is differences in cost of 

living, which describes differences in the style of living between areas 

and includes both differences in the prices paid for particular items and 

the kinds and quantities of goods purchased. The second is differences in 

price, which describes how the prices of a fixed market basket vary between 

areas. When one argues that it is cheaper to live in one place than another, 

it is important to know if he is referring to the different life styles or 

different prices in the two places. Cost of living may appear to be low in 

an area because comsumption or expenditures there are generally lower than 

in other areas. However, this may result from low prevailing income levels 

and not from differences in prices. 

Levels of Living 

Geographic differences in living costs appear to vary by level of 

living. Differences in the cost of new houses, no matter how great, may ' 

not affect the poor. Similarly, regional differences in the cost of the 

liberal food plan may not be relevant to a study of geographic differences 

in living costs faced by the poor. 

Data Sources for Measuring Geographic Differences 

The lack of data constitutes the major obstacle in analyzing the 

nature and degree of geographic cost-of-living differences. It is 

commonly but mistakenly believed that there is a government cost-of-living 
index for almost all cities. Practically speaking, only one statistical 

series provides current data about differences in living costs, the Family 

Budget series -published by the Bureau of Labor Statistics. Because of the 

special significance of this series for dealing with questions of poverty 

measurement in general and with geographic differences in parti'cular, this 

study examined its concepts and coverage. Significant technical and conceptual problems were encountered in considering its potential use in 

poverty measurement. These stem from the use of expenditure and consumption patterns in making regional modifications in the market basket, and 

from limitations in the availability and comparability of pricing data. 

Technical Paper IV discusses fully the conceptual and technical problems 

encountered. 

It is important to note that; however strong or weak its conceptu2l 

basis, the BLS series covers only 44 cities, and obviously some states are 

not represented. Even for states with cities included in the series, the 

level of living in the state as a whole may not be represented by the 

average cost of living of the particular city or cities covered. The 

Family Budget series provides no way to measure the differences in level 

of living between a city and a rural area; the cost of living in a city 

that is included in the series cannot be construed as being typical of 

the cost of living in rural areas away from the city. 

The cities in the Family .Budget series are grouped by regions, but 

the cost of living in the cities cannot be construed as being typical 

of living costs in the region. Significant differences occur among the 

indexes for cities within each region. 

The Consumer Price Index is frequently but incorrectly cited to show 

geographic variations in prices. The CPI measures average changes in the 

prices of goods and services usually bought by urban wage earners and 

clerical workers. It is based on prices of approximately 400 items selected 

to represent the movement of prices of all goods and services purchased 

by such workers. Prices are obtained in 39 major statistical areas and 

17 smaller cities. There is no index for small towns or. rural areas. 

Furthermore, the CPI does not measure absolute price differences among 

the cities; it measures only changes over the base 1967 prices in each 

city. Some of the price data collected for use 'in the CPI may be useful 

for analyzing cost-of-living differences, but an adequate analysis would 

require additional collection of price data and the prior completion 

of significant analytical studies supporting the construction of a povertylevel market baskec. Additional information about the CPI is included in 

Technical Paper V. 

Another data source that, on the surface, would seem to offer some 

assistance in incorporating geographic differences into poverty measurement 

are the standards used by.'the states in the program of. aid to families with 

dependent children. An examination of these standards was made, for this 

study to determine if they might be adapted for this use. These standards 

are, however, not comparable with one another. They exhibit great variations 
because of varying assumptions about family needs. State AFDC standards 

are also affected by state attitudes towards welfare spending as influenced, for example, by fiscal situations. The manner of constructing 

and maintaining these standards in each state is described in Technical 

Paper 111. 

The study also examined the major Federal data bases to determine if 

they might be used for adjusting the poverty cutoffs for geographic differences. Important aspects of the geographic sensitivity of the Consumer 

Expenditure Surveys are discussed in Technical Paper VIII; the other major 

data sources are described briefly in Chapter 111 and in detail in Technical Paper IX. 

Major Conceptual Problems 

The conceptual problems encountered in dealing with geographic differences in living .costs are serious. A generally accepted market basket 

of goods and services representative of the needs of the poor in various 

geographic areas has not yet been developed. Moreover, there are inherent 

difficulties in deriving such a market basket due to differences id tastes 

as well as needs. Ideally, one would want to ensure that an individual 

would derive equal satisfaction from the various market baskets priced 

in different geographic areas. One example of the difficulties in ensuring 

equal satisfaction is given in the food component of the BLS budget. 

Regional variations are incorporated into the food-at-home component based 

upon regional consumption patterns as reflected in the U.S. Department 

of Agriculture's 1965 Household Food Consumption Survey. Larger weights 

are given to pork and lard in the South than in the Northeast, compared 

to larger weights for beef and but'ier in the Northeast versus the South. 

In order to argue that these weight variations based upon regional 

consumption pat terns are valid for use in a geographic cost-of-living 

index, the following questions would need to be answered. Would a representative individual be equally satisfied with either the Southern or 

the Northeastern market baskets of food when the Southern basket contains 

more pork and lard and less beef and butter than the Northeastern basket? 

Or is it the case that the different consumption patterns in the Northeast 

and South might reflect differences in real incomes? 

Without belaboring the point, it may be helpful to examine another 

example, given by the weight va'riations between the metropolitan and nonmetropolitan areas' market baskets in the intermediate budget for house 

furnishings. The market basket for persons living in metropolitan areas 

contains 1.44 sheets (i.e., the family purchases on the average 1.44 

sheetsfye&) and the market basket for persons living in nonmetropolitan 

areas contains 1.30 sheets. There are probably many factors explaining 

why the empirical data show such a difference in spending patterns. For 

whatever reason, in order to use the family budget indexes to make 

cost-of-living comparisons, it is necessary to assume that an individual 

living in a nonmetropolitan area would be just as satisfied replacing his 

sheets less frequently than if he lived in a larger area and replaced his 
sheets more'frequently. The intent of presenting the above two examples is 

to point out the theoretical problems and the implications of arbitrarily 

using consumption or expenditure data in the family budgets to adjust the 

area market baskets in order to make geographic cost-of-living comparisons. 

Evidence of Geographic Differences 

Evidence of geographic differences in living costs is sketchy and 

inconsistent. As noted previously, the most prominent1 y mentioned source 

of data is the Bureau of Labor Statistics' Family Budgets. As stated 

earlier, these Budgets have certain inherent limitations which preclude . their use as accurate measures of cost-of-living differences. They are 

published' quarterly for 44 urban areas in terms of two hypothetical families 

and three levels of living. . One family is a four-person, family with a 

fully-employed father aged 38, a non-working wife, and two children aged 

13 and 8; the other is a retired couple. The three levels of living are 

high, intermediate, and low. The total cost of the budgets is based on a 

market basket of goods and services theoretically consumed by the hypothetical families; the content of the baskets is based partly on needs standards, 

partly on observed consumption patterns, and partly on judgments by the BLS 

staff. 

Table 12 indicates 'the range of the lower budget and shows that extreme 

variations occur in only a few cases. Two cities -- Honolulu and Anchorage 

-- obviously constifute special cases, and are thus omitted in commenting 

on the table. Using the U.S. average urban cost as a base of 100, the 

range for the total budget is -from 88 in Austin to 108 in Boston and in 

San Francisco-Oakland. For food, the range is from 89 in Austin to 112 in 

New York-Northeastern New Jersey. For transportation, the range is from 

84 in the New York area to 104 in Buffalo.; but in the nonmetropolitan 

urban areas in the nation as a whole it is 123. The index for medical 

care ranges from 84 in Green Bay to 122 in Los Angeles-Long Beach. 

Personal.income taxes range from 66 in Austin to 131 in Boston. 

~hese budgets are based on different market baskets. in each city. 

Table 13 shows family budget index numbers which result when there is no 

adjustment for regional consumption patterns, availability of public 

transportation, and climatic variations. The effect is to reduce interarea differentials in consumption costs between the highest and lowest 

costs. 

The, factors in Table 13 are based on the intermediate budgets. It 

can be observed by comparing them to factors in Table 12 that inter-city 

variations are smaller .at the lower than at the intermediate budget level. 

Thus, the measurement of geographic differences depends on the budget 

level. There is no publi,shed statistical series showing geographic 

differences at the poverty level, as currently defined. 

For this study, differences in living cpsts were examined, based on 

readily available comsumption data, by the Economic Research Service of 
Table 12 . Indexes of Comparative Costs 

Based on a Lower Budget for a Four-Person Family. Autumn 1974 - 1/ 

(U . S. urban average cost=100) 

Area 

Urban United States .................................... Metrapohtan areas' .................................. Nonmetropolitan areas ' ............................... 

Northeast: 

Boston Mass . ........................................ BuHalo . N.V. ..................................... Hartford . Cann ...................................... Lancarter . Pa ........................................ New York.Northeastern. N.J ...................... .Phdadelphta . Pa .. N.J ................................ P~ttsburgh . Pa .................................... Portland Maine . .................................... Nonmetropolitan areas* ............................... 

North CentratCedar Rapads . Iowa .................................. Champangn.Urbana . Ill ............................... Ch~cago . Ill .. Northwestern Ind .......................... Clncmnati . Ohio-Ky-lnd ............................... Cleveland . Ohio ....................................... Oaylon . Oh80 ......................................... Oetro~t . Mich ......................................... Green Bay, Wis ....................................... Ind~anapolns.Ind ..................................... Kansas City . Mo .Kans ................................ M~lwaukee . Wis ............ Mmneapol~s.St . Paul . Mmn ........................... St LOUIS . Mo .. Ill ........................... -.... 

Wtchlta, Kans ........................................ Nonmetropot~tan areas' ............................... 

South 

Atlanta . Ga ........................................... 

Austin . Ter .......................................... Balt~more . Md ..................... 

Baton Rouge . La .................................... Dallas . Te ........................................... Du1ham.N.C ......................................... Houston . Te: ......................................... Nashwlle . Tenn ...................................... Orlando . Fla .......................................... Washmgton . O.C..Md .. Va .............................. Nonmetropolitan areas ' ............................... 

West: 

Bakersfneld . Cald .................................... Denver . Colo 

Lor Angeles-Long Beach . Calil .......................... San Doego . Calif ..................................... San Franc~sco.OakIand. Calif ........................... Seattle.Everett . Wash .......................... Honolulu . Hawa~i 

Nonmetropolitan areas' ................... ....... 

Anchorage . Alaska ........................................ 

.. 

lotal 

conlimption 

.. 

IW 

101 

95 

106 

101 

108 

98 

106 

100 

% 

104 

98 

95 

lo3 

104 

95 

100 

96 

99 

95 

99 

99 

99 

99 

97 

96 

97 

95 

91 

100, 

93 

94 

97 

95 

94 

98 

104 

91 

% 

98 

. 104 

102 

108 

107 

I20 

98 

143 

- 

. 

ram 

100 

101 

94 

104 

101 

105 

102 

112 

108 

101 

102 

100 

91 

98 

103 

102 

IW 

101 

103 

91 

97 

102 

94 

98 

102 

97 

95 

% 

89 

95 

% 

90 

94 

95 

91 

91 

102 

91 

94 

98 

98 

97 

102 

104 

120 

95 

122 

- SOURCE: Bureau of Labor Statlecies . Monthly Labor Review (June 1975) . 

The lamdy consnstr 01 an employed husband . age 38. a wile not employed outside 

the homr. an 8-year-old girl . and a I3.year-old boy . 

8 Housmg includes shelter . housefurnishings and household operations . The hiphe* 

budget also mcludes an allowance for lodging away lrom home clty . 

1 Renter costs include average conlract rent plus the cost of required amounts of 

heating luel. gas. electr~clty . water. specified equipment. and Insurance on household 

contents . 4 The average costs ol automobile owners and nonowners in th lower budget were 

welghted by the lollow~ng proportions of families: Boston . Chocago . New Yolk. and 

phlladelphla . 50 percent lor hlh automobdr owners and nonowners; all other metropolltan areas. 65 percent lor automobde owners . 35 percent lor nonownars; nonmetropolltan are as. IW percent for automob~le owners . The mtermediale budgetproport~ons 

are . Boston . New York . Ch~cago . and Phdadelphia . 80 percent for owners . 20 percent 

lor nonowners; Baltimore . Cleveland . Detro~t . 10s Angales . Pinsburgh . Ln Francouo . 

. 

Food 

at 

tome 

. 

IW 

101 

96 

105 

101 

105 

I03 

Ill 

107 

LOO 

102 

102 

90 

99 

104 

103 

97 

102 

102 

92 

98 

102 

94 

98 

103 

97 

98 

% 

88 

94 

97 

87 

95 

93 

91 

90 

101 

92 

94 

98 

97 

95 

102 

104 

124 

97 

. 

127 

Cat of family consumption 

.. 

"toobile 

men 

. 

LOO 

103 

92 

118 

106 

105 

94 

107 

I11 

95 

97 

95 

89 

94 

120 

95 

102 

93 

99 

93 

101 

99 

94 

97 

105 

95 

90 

94 

97 

IW 

96 

98 

92 

% 

95 

95 

102 

91 

102 

97 

I07 

106 

110 

104 

I15 

93 

. 

119 

. 

loth 

ing 

. 

1W 

101 

94 

98 

I11 

107 

103 

IW 

95 

95 

101 

95 

111 

115 

100 

99 

106 

99 

101 

107 

97 

I01 

106 

IW 

94 

99 

99 

% 

100 

97 

96 

93 

93 

94 

103 

90 

93 

89 

97 

I17 

104 

106 

112 

113 

101 

105 

I22 

. 

. 

Peronal 

care 

. 

IW 

103 

87 

101 

101 

I21 

96 

101 

IW 

I01 

IW 

82 

106 

99 

108 

95 

I19 

98 

108 

I04 

101 

112 

106 

107 

105 

104 

89 

104 

102 

101 

104 

103 

107 

I06 

I8 

91 

% 

87 

102 

98 

98 

99 

112 

106 

113 

91 

. 

123 

. 

Mical 

.re ' 

. 

1W 

103 

87 

% 

88 

96 

85 

110 

101 

87 

95 

89 

88 

98 

105 

87 

98 

88 

103 

84 

102 

97 

94 

93 

88 

95 

83 

95 

95 

110 

87 

114 

106 

105 

89 

106 

104 

86 

110 

94 

122 

I18 

111 

106 

105 

91 

. 

157 

. 

Ither 

amill 

conurnp . lion' 

... 

IW 

104 

81 

106 

106 

112 

92 

114 

105 

I01 

lo8 

81 

101 

99 

108 

104 

105 

I08 

104 

98 

107 

I02 

103 

104 

99 

101 

83 

106 

102 

101 

lo3 

104 

I03 

99 

I04 

103 

107 

81 

91 

98 

% 

95 

LO3 

103 

LO6 

79 

I W 

- 

. 

Perional 

lcome 

axes 

St Louis . and Washington . O.C. with popvlations of 1.4 mdlion or more in 1960 . 95 pcrcrnt for automobile owners and 5 percent lor nonowners: all other areas . 100 perCtnt lor automobile owners . The higher budget weight is 100 percent lor automobile 

Owners m all areas . 

' In total medical care . the average costs of medical lnsurance were weighted 

by thr lollowmg proportions: 30 percent lor families paying full cost ol insurance. 26 

percent for lamher paying half costs; 44 percent lor lamhes covered by noncontrlbutory Insurance plans (paid by employer) . 

' Other lamity mnsumptjon includes average Costs for readong. recreation. tobacco 

products . alcoholic beverages . educatton and mixellanrous expenditures . 

AS defmd in 1M1 . For a detailed descr8ption of these and previous geopraph . lcal boundarms . we the 1967 ed~tion of Standard Metropolitan Statistical Areas . prepared by the Onice of Management and Budget . * Places with POpulatlOn of 2.500 to 9.W. 
Table 13. Family Budget and Fixed Weight Indexes 

of Family Living Costs, Autumn 1974 

I Family budget indele! 

Index 1 IAIea 

U.S. urban average costs .......... $14.333 I 

Total cost 

(Including 

Income 

and ~oclal 

Urban Un.ted Stales .............. 1W 

Metmpol~lan awas I... ...... 102 

Nonmet#opoldan areasa ....... 90 

Northeast: 

Boston. Mass ................ Bunalo, N.Y ................. Harlfo~d. Conn ............... Lancasler. Pa ................ New York-Northearlern N.1.:. 

Philadelphia. Pa.-N.J ......... Ptttsburph. Pa ............... Portland. Maine .............. Nonrnetropolitan areas * ...... 

:onsump. 

on cats 

- 

lndex 2 

$10.781 

IW 

102 

91 

I14 

105 

111 

98 

111 

,101 

% 

104 

99 

97 

102 

104 

97 

103 

95 

I01 

% 

I W 

98 

101 

- 

117 

107 

108 

99 

116 

103 

97 

103 

99 

North Central: 

Cedar Rapids, Iowa ........... Champaign-Urbana, 111 ........ Chicago, Ill.-Northwestern Ind. 

Cincinnati. Ohio-Ky.-lnd ...... Cleveland. Ohio .............. Oayton. Ohio ................. Detroit. Mich ................. Green Bay. Wis ............... Indianapolis, Ind .............. Kansas City. Mo.-Kans ........ Milvauhee. Wis .............. 

I Family budget fndexe 

98 

102 

103 

96 

102 

93 

IW 

99 

99 

97 

105 

lion 

costs 

adjusted 

fW 

cllmale 

-- 

Conrumc 

llon cost 

not 

adjustr 

for cllmate ' 

- 

Total cm 

Area (lncludln 

Income 

and soclz 

security 

tarn): 

M~nneapolis-St. Paul. Minn ... 

St. Louis. Mo .- Ill ............ Wichita, Kans ............... Nonmstropol~tan areas. ...... 

,"th' 

Atlanta. Ga ................. Austin. Tei ................. Balt~more. Md .............. Baton Rouce. -. La ............. Dallas. Ter ................. Durham. N.C ................ I Houston. Ter ............... Nashville. Tenn ............. 1 Orlando. Fla. ............... Washmgton. D.C.-Md.-Va .... Nonmetrowlitan areas' ...... 

est: 

Bakersf~eld. Csld ............ Denver. Colo ................ Lor Angeles-Low Beach. 

Cald ..................... San Oiego. Cald ............. San Francmo-Oakland. Calif. 

Seattle-Everell. Wash ........ Nonmetropolitan arras '...... lnolulu. Hawaii ................ ~chorage. Alaska ............... 

Consump 

tlon 

cmtl 

adjurted 

for 

cllmate ' 

Index 3 

98 

97' 

93 

93 

94 

91 

99 

95 

95 

98 

94 

95 

94 

102 

90 

91 

95 

99 

98 

105 

1M 

91 

115 

132 

- SOURCE: Bureau of Labor Statistics, Monthly Labor Review (June 1975). 

I Indexes reflect dlnrrences in average pricer. varialions in budget items and These Indexes calculated from costs of constanl markel basket for urban family of 4 

quant~ty we~ghtr associated wtth ddferences In food consumplion patterns. climate. pnsonr. reflect only average price levels md climatic rsquirsmants. 

availabtlity of public Iransportat~on. and life styles in metropolitan and nonmetropoltlan calculated from costs of market basket for ,,,ban family of persons, N~ areas. Total cosl indexes also renect differences in Federal. Slate, and local income lax adjuslmEnls made for climate, lndeler ,meet only dinerenca in avsrage price rsquirements. levels. 

Consumplion costs equal tolal cosl minus personal income tales, social se,curity I defined in lwl, F~~ detailed drscription of these pmgnphical boundarin, tares. and olhsr nonconsumption items. These indexes renecl all remaining sources standard ~~~~,,~~li~~~ ~t~tl~ti~,l A~~~~; E~~~~~,~~ ofice of the preridont, of variatm. Burwu of the Budpel. 1967. 

The bud weigh1 slrvclvre excludes repion, transportation, and city sire variations. . places 2,500 lo 50.0~ inhabitants, 

the Department of Agriculture. The following summary is excerpted 

the report, which is reproduced as Technical Paper XV: 

Analysis of the 1965 Household Food Consumption Survey 

suggests that the key issue concerning differentials in food 

expenditures between urban and rural areas was home-produced 

food. This, of course, was the central argument for the 

original farm differential in the current poverty threshold. 

Producing food at home does involve costs, both direct cash 

outlays and indirect opportunity costs, or the income possib'ilities foregone by committing land, labor, or capital 

resources to home production. Two 'pricing systems were used 

in an attempt to capture these costs. When home-produced food 

was valued at retail 

for the same food in 

prices, or what 

a retail store, 

would have been sperit 

there was only a 7 to 8 

from 
percent difference in expenditures between urban and rural 

families. Valuing food at farm prices increases the differential between urban and rural nonfarm families to 10 percent, 

and to 20 percent between urban and farm families. 

The meager data available suggest that there is no appreciable difference in clothing .expenditures between urban and 

rural families. For example, all families have access to 

clothing of similar quality at similar prices through mailorder catalogs. Families in rural areas also shop in stores 

similar to those used by urban families. Data are not available to isolate the effect of urbanization on clothing needs. 

Regional variations in clothing expenditures also appear to be 

minimal. The only available survey data (as of July 1975) for . 

answering this question are from the 1960-61 CES, which are 

quite outdated. Part of the lack of regional variations in 

clothing expenditures can be attributed to the wide climatic 

.variations within regions. 

Housing was one area in which considerable residential 

variation occurred both by region and by urbanization. In 

terms of shelter (rents and value), there was little difference in median outlays between many rural areas and urban 

places of 2,500 to 50,000 population. Within some regions, 

rural housing was more costly than in central city areas. 

Among regions, housing outlays tend to be lower in the South. 

Median values and rents appear to be about 20 percent higher 

in metro. than in nonmetro areas. However, rental units are 

less prevalent outside cities. Financing arrangements also 

affect ownership costs. In rural areas, repayment periods 

are shorter and interest rates are higher on home loans. 

Housing outlays for maintenance, repairs, and improvements are lower in nonmetro areas. However, these expenditures are not always lower tnan similar outlays in central 

cities of SMSAs, particularly in the Northeast and West. 

Utility costs are also an important factor in housing differentials. Rural households heat more often with L-P gas, a 

high price fuel, and less often with natural gas. There is 

little information, however, on how this might affect housing 

differentials. 

There is little hard evidence that transportation costs 

are considerably higher in rural areas. Rural households do 

travel more miles, but with less stop and go driving, they 

tend to get better mileage. The biggest difference in the 

transportation situation between rural and urban families 

is the lack of public transportation in rural communities. 

The lower tax rates evidenced in nonmetro areas appear 

to carry with them lower quantity and quality community 

services, especially those special services vitally important 

to low-income people. Research in this area is sketchy, but 

one recent study suggests that the real costs of services in 

rural America are much higher than direct outlays might suggest. Health care is a good example. The shortage of 
physicians is more acute in rural areas; patients tend to 

drive longer distances to obtain health services, emergency 

health services are more likely to be deficient, work-related 

injury rates are higher, and a comprehensive approach to health 

care delivery is less likely to be present. 

The Department of Health, Education, and Welfare and the Federal 

Energy Administration explored the effect of rising home-heating costs 

on the lower inc.ome population. The results showed large variations in 

home-heat ing expenses paid by households in di f ferent areas. Also, 

energy price increases varied. These variations are due to differences 

in climate, housing characteristics, and types and prices of fuel used. 

.Living costs can appear to be lower in rural than nonrural areas as 

a result of confusing farm with rural residence, and cost of living with 

source o£ income. Farm residents are often assumed to save money by home 

production of food. But many nonfarm families in rur'al and nonrural areas 

' also grow food. Special 'studies reported in Technical Paper XV show that 

, for each income class rural food expenditures were lower, although there 

did not appear to be differences in food prices. . . 

\ Living costs appear to be lower in the Southern region than in other 

regions. Differelices may stem from income and expenditure patterns rather 

than prices. Income levels are generally lower and poverty rates higher 

. in the South than elsewhere. It should be added that differences in 

living costs.between cities within a region, even within the same state, 

are frequently quite significant. 

.Shelter costs seem to be lower in rural areas and in the Southern 

region than elsewhere. The pattern is less clear when comparimg shelter' 

costs in rural and metropolitan areas to those in small cities and in 

central city areas of SMSAs. Patterns then vary among the regions. The . lower rural .and Southern cost of housing may be due to d'ifferences in 

quality or characteristics of the housing. 

Farm-Nonf arm Differences 

The Orshansky measure does not recognize any geographic differences 

except for the differences between farm and nonfarm households. The 

poverty thresholds for farm families are set at 85 percent of the nonfarm 

threshold for each family type. - (until 1969, the farm thresholds were only 

70 percent of the nonfarm.) This distinction is not based on measured di fferences of need but rather on assumed cost savings from home-produced food. 

With greater home .production of. food in nonfarm areas. and less on farms, 

this difference may diminish significantly. Furthermore, there is some 

question about the appropriateness of singling ,out income differences based 

on home production of food when other income differences like employee and 

in-kind benefits may represent significant income advantages to nonfarm 

families. A Federal Technical Committee in 1973 recommended that the farmnonfarm distinction be dropped from the official poverty matrix. 
The Census Bureau has recently redefined a farm as a food-producing 

property with annual food sales in excess of $1,000. Using this definition will significantly reduce the number of farm households counted as 

poor in Census tabulations. (Many of them will be counted as poor under 

the nonfarm residence classification.) 

Attempts to Overcome Conceptual Problems and Data Limitations 

In addition to examining the BLS Family Budgets and the state welfare 

standards of need, other studies were undertaken to aid in overcoming 

limitations of existing data sources. 

Data used by the BLS for the Family Budget series were compared with 

annual data collected by the Department of Agriculture for use in computing 

the index prices for farmers. However, quality control was a serious problem in comparing data for items priced by both agencies. Furthermore, the 

number of items which did match, given the quality control problem, was 

too small to support the derivation of valid global results. This attempt 

to match the two data sources is described in Technical Paper XV. 

A common notion is that living costs are highly correlated with 

prevailing incane levels. Thus, a person may be willing to live in a city 

with high housing or transportation costs if he knows that his income is 

higher than it would be if he moved to another city. Likewise, prices may 

be higher because incomes are higher. The correlation between living 

costs and incane was tested in a study reported in Technical Paper XIII. 

The two data sets were not strongly correlated; only forty percent of the 

variation in income levels was statistically explained by the cost of living 

data. The test of correlation was repeated by comparing the median family 

incane in the cities to the cost of housing (as measured by the shelter 

cmponent in the BLS family budgets). Again, the correlation between the 

two data sets was not strong. The relatively low correlation and limitations in the budget data used for verification indicate that Census median 

incane should not be used for a measure of cost-of-living differences 

without further study. 

Updating the Standard 

It may be desirable to change the level of any poverty measure from 

time to time. Relative measures appear to have an implicit mechanism for 

updating but, like the absolute definitions, the level must be revalidated. 

One possible method of updating the current poverty matrix, discussed 

earlier in this chapter, is to use more recent data on food consumption 

and nutritional needs than were used in the original construction. Such 

consumption surveys have been conducted at approximately ten-year intervals 

and nutrition standards are revised only once every five years. Therefore, 

a simples and more practical method of updating more frequently is 

require.d. .Initially the poverty cutoffs were updated by the annual 

percentage increase in the cost of the economy food plan calculated by 

the Department of Agriculture using food prices paid by survey households 
updated by changes in prices of about 100 foods collacted monthly by the 

BLS. ' Since 1969 the poverty cutoffs have been increased each year by the 

annual percentage increase in the Consumer Price Index. 

The use of the Consumer Price Index as the updating mechanism for the 

poverty lines has been the subject of some disagreement among analysts. 

Those favoring it cite its convenience (it is readily available) and widespread acceptance as an index of rising living' costs. Those objecting to 

it note that it is based on consumption patterns of urban wage and clerical workers and on price changes of goods and services purchased by such 

workers. These may differ from consumption patterns of, and price changes 

affecting, the poor, since it is believed that the poor spend greater proportions of their incomes on food and housing. It has been proposed that a 

special index, a poor person's index, be constructed by reweighting the 

price changes for food, housing, and other items in the Consumer~Price Index. 

Since consumption patterns also differ according to other demographic characteristics such as age, race, and sex, there have also been proposals to 

create.price indexes for special subcomponents of the poverty population 

or of the population as a whole, such as the aged or the aged poor. 

Table 14 shows examples of special price indexes which have been 

crudely constructed to examine the distributional impacts of inflation. 

Technical Paper V contains a more complete discussion of these ' 

indexes, including a description of the methodology used for their construction. As shown in Table 14, the special price indexes were generally 

very close to the Consumer Price Index until 1972, with some tendency for 

the price indexes for the low-income groups to rise at a slower rate prior 

to 1967. During the recent period of rapid inflation, however, when price 

increases for food and housing outpaced the increases for other items, the 

price indexes for the low-income groups increased at a faster rate than the 

Consumer Price Index or the price index for the wealthy (families with 

incomes above $10,000 in 1960-61). 

In the absence of direct information, current attempts to construct 

measures of price changes directly affecting the poor (e.g., Table 14) have 

consisted of reweighting expenditure categories to allow for the fact that 

families with low incomes must allot larger shares of their funds to 

necessities such as food and housing than households less restricted by 

lack of funds. As a general rule, differences in actual i'tems brought and 

in point of purchase -- that is, individual items selected and kind of 

store patronized -- may be more important in the overall price picture than 

the weights attached to family living categories. But the recent disparate 

rise in prices of food compared to prices of other commodities reveals 

another difficulty in settling on and updating a poverty reference standard 

-- namely what is an appropriate starting point? 

While a suitable price index for the poor may require a different 

market basket -- or at least a different assignment of category weights -- 

than for the population at large, the impact on the poor of price changes 
Table 5. Comparison of Consmr Price Index with 

Price Indexes for Special Groups, 1953-1975 

I I Price Index for: 

Income 

Consumer 

Price 

Index 

SOURCE: Monthly Labor Review (August 1975). Tables 22 and 23 for Consumer Price 

Index. 

Unpublished study by the Social Security Administration for the price index 

for the low-income retired. 

All 

Poor 

Robinson G. Hollister and John L. Palmer, "The Impact of Inflation on the 

Poor and the Implicit Tax of Inflation and Unemployment: Some Policy Impli-. 

cations," in Kenneth E. Boulding and Martin Pfaff, ed., Redistribution to 

the Rich and Poor: The Grants Economics of Income Distribution (Belmont, 

California: Wadsworth Publishing Co., 1972), Tables 4 and 5 for the other 

price indexes, 1953 to 1967. 

John L. Palmer and Michael C. Barth, "The Impacts of Inflation and Unemployment: With Emphasis on the Lower Income Population," Technical Analysis 

Paper No. 2, Office of Income Security Policy, Office of the Assistant Secretary for Planning and Evaluation, Department of Health, Education, and 

Welfare (October 1974), Table 2, for the price index for all poor and for 

wealthy, 1967 to 1973. 

Aged 

Poor 

a Adjusted for Medicare 

Calculated from expenditure weights reported in above sou;ces and component price 

indexes in Monthly Labor Review (August 1975), Table 23. 

Average for January-June 1975. 

Rural 

NonAged 

Poor 

Rural i::y Aged Aged White White 

Poor Poor 
over a specified time period can still be approximated adequately by an 

index for the general population. such as the CPI. It is essential, however, 

that the prices for different commodities move up or down at approximately 

the same rate. Food prices play a larger role in the spending of the poor, 

because food outlays normally comprise a larger share of total outlays for 

low-income families than for other families. It is also apparent that increases in outlays for non-food items because of higher rent prices or costs 

of a medical emergency, for example, may cause a family to spend less on food. 

Over long periods the food component of the Consumer Price Index has 

moved at more or less the same pace as the bundle of remaining items. 

However, for a variety of'reasons, in recent years the food component has 

escalated much faster, reaching a peak in the period 1973-74. Trends in 

food and non-food components of the CPI are illustrated below. 

Year Indexes (1963=100) ---- Year-to-Year Change (percent) ---------------------- 

All Items Food Nonfood All Items Food Nonfood 

1959 95.2 95.5 94.9 0.8 -1.6 1.9 

Late in 1974 the U.S. Department of Agriculture revised its low-cost 

food plan. Late in 1975 the Department replaced the economy food plan, 

formerly 80 percent of the cost of the low-cost plan, with a new thrifty 

food plan. Since these food plans are more adapted to the food consumption patterns of families with limited amounts to spend than are the 

moderate or liberal food budgets, these plans are more suitable for use 

in developing a poverty criterion. The costs of these plans for families 

of different size, estimated as of December 1974, provided one basis for 

updating and refining the official measure in use for the year 1974. On 

the other hand, the estimated costs of these plans, based on family food 

patterns and choices in 1965, were affected already by the exceptionally 

high prices of food prevailing in 1974. 

In order to analyze the effect of these high prices on the development 

of revised Orshansky poverty lines, the revised low-cost plan was priced 

back to December 1972, when food prices stood in a more typical relationship 

to other prices. In the case of the new thrifty plan, which did not exist 

prior to September 1975. an approximated equivalent was also priced back 
to December 1972. By December 1975, the food plan costs showed signs 

of dropping back to a smaller annual rate of increase. Trends in the 

cost of the revised USDA food plans are as follows: 

Monthly Cost Per-Person Year-to-Year Change (percent) -------- 

Thrifty Low-Co s t Thrifty Low-Co s t 

Equivalent P 1 an -----------.----- Equivalent ------- P 1 an 

Dec. 1972 $28.09 $36.45 ---- ---- 

Dec. 1973 34.48 43.85 22.7 20.3 

Dec. 1974 39.40 50.17 14.3 14.4 

Dec. 1975 40.96 53.00 4.0 5.6 

While food prices particularly affect the poor, trends in cost of 

homeownership are more important to the nonpoor than to the poor, who 

largely rent their housing. Also, in recent years, the costs of homeownership have increased much more than the costs of rent, in spite of the fact 

that the trends in these costs have been similar for long periods. By 1975, 

the normal relationship between trends in food and nonfood costs, and 

between rent and homeownership appears on the way to being restored. Still, 

it is difficult to determine the longrun impact of energy costs on prices, 

and the way in which these will affect the poor and nonpoor segments of the 

population. 

It is clear that the Orshansky poverty measure, using the cost of a 

food plan as iats core, will be higher if priced out at 1974 costs before 

applying the multiplier, than it would be if the food prices of 1972 were 

used as the base and the measure moved forward by the change in the overall 

CPI. The first procedure, illustrated in Table 8, would incorporate the 

recent escalation of food permanently into the measure. The latter would 

understate the food cost situation in 1974, but would subsequently reflect 

a more typical relationship between food and nonfood price trends. The 

pending revisions in the CPI based on 1972-73 expenditure patterns, when 

completed in 1977, may render both options obsolete. 

Calculating the new poverty lines on the basis of the new food plan 

costs at 1974 prices is tantamount to computing income cutoffs priced as 

of 1972 and moving them forward year by year corresponding to changes in 

the food plan cost estimates, .a procedure originally used with the present 

poverty line but abandoned in favor of change in the all-items CPI. It 

happens also to be true that 1974 was an unusual year in that median real 

income of American families declined by about four percent from 1973, one 

of the largest single year declines since income data were first collected 

in the CPS in 1947. 

Developing the updated criteria for 1974 by using 1972 food plan costs 

and moving them forward to 1974 by applying the 17.9 percent change in the 
average'all-items CPI from 1972 to 1974 is one way to avoid distorting the 

income needs criteria with the atypical food price spiral or the decline 

in income. Until the CPI itself is revised on the basis of a more current 

market basket, the present index -- based on expenditure patterns prevailing 

in 1960-61 -- may parallel the market basket of a low-income family more 

closely than originally intended. 

Such alternative calculations of a revised poverty matrix and their 

resultant effect on the poverty counts appear in Technical Paper XI. The 

figures below illustrate the lower poverty lines resulting from the use of 

1972 rather than 1974 as the base year. Based on the thrifty plan equivalent cost in 1972, and raised by 17.9 percent to conform to the rise in the 

monthly average rise in the CPI between 1972 and 1974, the new poverty cutoff for 1974 for a two-person family with an elderly head is $3,644, or 23 

percent more than the currently used figure of $2,958. By contrast. when 

derived directly from the 1974 thrifty food plan itself; the 1974 poverty 

line for an elderly couple, as shown in Table 8, is $4,324 or 46 percent 

higher than the current official measure. 

Poverty Income Criteria in 1974 Based on: ------------------------------ 

Official Thrifty Plan 80 percent of Low-Cos t 

Criterion -- or Equivalent Low-Cost Plan Plan ------------------------------------- 

Elderly couple 

4-Person family 

Per sons 

Families 

Unrelated 

individuals 

Children 5-17 

in families 

$2,958 $3,644 $3,791 $4,739 

5,008 5,344 5,544 6,930 

Population Counted Poor in 1974 (millions) 

24.3 31.4 32.6 0 44.3 

5.1 6.6 6.9 9.9 

Obviously, the total number of households or persons counted poor for 

the year 1974 decreases too, if the lower new poverty lines are used, but 

the count still continues substantially above the 24.3 million identified 

as poor by the unrevised official measure now in use. 

It'is sometimes proposed that the poverty cutoffs be updated separately by geographic area. This might appear feasible since the Consumer 

Price Index is published for 24 different cities, the nonmetropolitan 

areas of four regions and five "size of place" areas. However, the city 

indexes are not comparable because they are based on different market 

baskets for each city, and the regional indexes at most reflect price 

increases within smaller cities but not the rural areas. 
Income and Resources 

General Limitations 

poverty measurement can be affected by changing the definition of 

income. This chapter explores empirically the effects of some changes 

in income definition. Attention initially focuses on the Census ~ureau's 

definition of income, which is currently used in connection with the 

Orshansky poverty matrix. 

The Bureau of the Census uses a measure of regular, total, beforetax, money income. It includes money earned by labor and through property 

ownership, as well as funds received from government cash transfer programs 

(such as Social Security, veterans' payments or AFDC), ~rivate pensions 

and annuities, and alimony and regular contributions from persons not in 

the household. It does not include irregularly received lump sum income, 

such as capital gains, tax refunds, earned income tax credit, and prize 

money, and it does not include income from illegal sources like theft. 

It also excludes in-kind income, employer-paid fringe benefits, the value 

of assets not providing current income streams, imputed services from 

owner-occupied housing and consumer durables, home production (such as 

child care services), and undistributed corporate profits. The Census 

also measures income over the time period of a year and excludes data on 

income in previous years as well as data on income variations within a 

ye ar . 

It is difficult to modify the definition of income for statistical 

purposes given the general lack of regularly collected income or resource 

information associated with social and demographic characteristics in any 

form other than that used by the Census Bureau in its income definition. 

Thus, changes in the definition of income for statistical purposes could 

require either an expanded Current Population Survey (which is unlikely 

because the March CPS questionnaire is already very long) or the use of 

arbitrary imputation techniques involving computer simulations with 

various data sources. 

The Accountinn Period 

Although measures of income are currently based on annual information 

which does not allow for pre-year or intra-year fluctuations, measures 

based on information collected more or less frequently would also have 

problems. For example, measures based on informat ion collected over 

periods as short as a month would be very sensitive to temporary income 

changes, while measures based on information collected over periods longer 

than one year would incorporate recall difficulties. 

The effect of the accounting period on the count of the poor population is considerable. In general, a short accounting period includes 

more people with large variance in income over time while a long accounting period includes fewer people but relatively more people with steady 
but low incanes. Technical Paper VI, which used the University of Michigan 

Panel Survey data, found that a one-year accounting period produces a 

7ignificant increase in the number of self-employed among the poor when 

compared with multi-year periods. Only about 3-112 percent of the selfemployed were poor under a fi~e-~ear accounting period, but 16 percent 

were poor for at least one year of the five years with an annual definit ion. No other group experienced increases of this magnitude, however. 

The groups with the greatest incidence of poverty, such as nonwhites, the 

aged, and female-headed families, show the smallest increases in poverty 

rates with a shortened accounting period. 

The study also found that 31 percent of those who were poor in 1972, 

using an annual definition, would have been considered non-poor if a fiveyear definition had been used. On the other hand, 17 percent of those 

poor under the f ive-year definition would have been non-poor in 1972. 

One source of data on monthly fluctuations in income is the records 

of the income maintenance experinent s, which provide payments to lowincane families. With these data it is possible to illustrate the 

potential impact of using monthly, rather than annual, income to define 

poverty. Table 15 shows the number of months different families, whose 

annual income in 1970 (prior to receiving income supplement payments) was 

above or below the poverty cutoff, were poor on a monthly basis in one 

experimental site (~enver) . (~ecause these data reflect monthly adjustments for family size as well as income, 1.4 percent of poor families are 

portrayed as having spent no months in poverty and 0.4 percent of the nonpoor families are portrayed as having spend 12 months in poverty.) These 

data show that people with annual incomes below the poverty cutoff were 

most likely to be in poverty over half of the 12 months and 85 percent of 

them were poor for 6 months or more. Only 52 percent were in poverty all 

12 months. On the other hand, 70 percent of the non-poor families were 

never poor on a monthly basis and 88 percent were in poverty 3 months or 

less. Nearly 96 percent were below poverty 6 months or less, and about 

3 percent were in poverty 6 months or more. 

Assets 

The lack of any regularly conducted survey dealing with assets also 

makes it exceedingly difficult to adopt a wealth or asset concept for 

statistical purposes. Including assets in the definition of income would 

decrease the number of poor counted if no compensating change were made 

in the threshold. 

Technical Paper VI, prepared for this study on the basis of the 

University of Michigan Panel Study, which followed 5,000 families for 

six years, shows that the inclusion of income from imputed rent from 

homeownership reduced the annual size of the poverty population by about 

16 percent. When incane was defined to include all liquid assets, the 

poverty population was reduced by 18 percent. When a definition of 

income was used that included net worth available to meet consumption 
v able 15. Distribution of Families by Number of Months in Poverty 

on a Monthly Basis by Poverty Status on an Annual Basis, 1970 

Poor 100% 1.4 1.2 1.8 0.7 2.6 3.2 3.9 6.3 6.5 8.6 5.5 6.2 52.1 

Annual 

Poverty 

Status 

Nonpoor 100% 70.1 7.3 6.3 4.7 3.6 2.2 2.1 1.2 1.1 0.6 0.2 0.1 0.4 

SOURCE: Special tabulations of families in the Denver Income Maintenance Experiment. 

a Poverty status based on a monthly accounting period. 

Total 

requirements, 41 percent of thoge poor under the current income definition became non-poor. 

When one looks at the effect on various groups, the self-employed 

and, the aged had a far greater incidence of poverty under a simple income 

definition than they did when the definition included other kinds of 

wealth. Nonwhites, families with school-age children, and the employed 

but non-self-employed were affected least when net worth was included in 

the income definition; these groups are the least likely to have assets. 

Number of Months in povertya 

Taxes 

012 

Federal income taxes have only a minor statistical impact on poverty 

measurement. This is because Federal tax liability was revised to exclude 

most persons counted poor by the current measures. The standard deduction 

of $1,300 coupled with a $750 exemption for each family member results in 

exempting a large proportion of the earned income of the poor. 

3456789101112 

Technical Paper XVII discusses the result of using income, from which 

Federal inccme taxes have been subtracted, as a measure of income. Aftertax income does increase the number of people counted as poor, but the 

increase is not very great. Demographic characteristics of this larger 

group are highly correlated with those of the poverty population with the 

standard before-tax concept. 

One important tax affecting the poor is the payroll deduction for 

Social Security benefits. A computer simulation using the March 1975 

Current Population Survey estimates that excluding from income the 5.85 

percent tax on earnings would have increased the number of officially 

poor by 1.27 million persons in 1974. These calculations do not include 

the impact of .the earned income tax credit (enacted in 1975). Below the 
level of the Federal tax systems, the incidence of state and local taxes 

(property, income, sales, gasoline) varies significantly and is difficult 

to determine. 

InAKind ' Income 

Estimates of poverty reduction for food stamps are generally better 

than for other in-kind benefits. Inclusion of the bonus value of food 

stamps in income reduced the poverty population in 1974 or earlier years 

by about 5 to 15 percent. Furthermore, families with large numbers of 

children would be affected.more than other family types because of their 

higher rates in the food stamp program. 

Technical Paper VII describes a number of studies which evaluate 

the effects of in-kind income on poverty counts. These studies suggest 

that poverty counts will be reduced significantly if in-kind transfers 

are included in household income and no change is made in the poverty 

threshold. 

Consumption Unit 

Under current practice, the poverty status of a person 14 years of 

age or older who does not live with a relative is wholly determined by 

the income of that person. The poverty status of a person who lives with 

one or more relatives is determined by the income of that person plus the 

incane of those relatives with whom he or she lives. Because income 

questions are not asked of persons under 14 years of age, unrelated individuals in this age group have neither family income nor income of their 

own, and are excluded from the poverty universe. Table 16 indicates what 

would happen to poverty counts if the current family concept were replaced 

with a household concept, i.e., all household members treated as if they 

were related. The table shows that about one million unrelated individuals who are now considered poor would not be considered poor under the 

household concept. The revised concept would also shift about half a 

million family members from poor to non-poor. The use of a household concept implicitly assumes that all household members pool their resources. 

The results of this analysis depend on the amount of pooling of resources 

and consequent economies of scale under various living arrangements. The 

assumption is most reasonable in the case of young unrelated individuals 

living with a family, but it may not be as reasonable for certain other 

living arrangements, e .g. , several unrelated individuals living together. 

Technical Paper X contains a more complete treatment of this subject. In 

addition, the notion of "potential for independent living on one's own 

incane" has been used by Orshansky and the Social Security Administration.. 

There are about 1.3 million other relatives living in non-poor families 

who would be classified as poor if they were unrelated individuals. 
Table 16. Poverty Status in 1974 Based on the Current Definition 

and a Definition Based on Household Income 

(In millions) 

Persons by Age, Sex, Relationship to 

Head of Household, and Household Composition 

I I Poor By 

Poor By Definition I Difference 

Current I Based On I In Number I I Poverty Household Of Poor 1 1 1 ~efiniton 1 Income Persons 

(2) (3) 1 (3)-(2) 

All persons (except unrelated individuals under 14 yrs. of age) 209,343 

All unrelated individuals . - . . . - . . . . . . . . . . . 19,100 

Under14yearsofage. . . . . . . . . . . . . . . . . . . 2 29 

14 years of age and older. . . . . . . . . . . . . . . . . 18,872 

All unrelated individuals 14 years of age and older: 

14to17 ......................... 14 8 

, 18 to 24 . . . . . . . . . . . . . . . . . . . . . . . . . 2,817 

25 to 64 . . . . . . . . . . . . . . . . . . . . . . . . . 9,413 

65 and older . . . . . . . . . . . . . . . . . . . . . . . 6,493 

Males : 

Livingwith afamily. . . . . . . . . . . . . . . . . 560 

Living with unrelated individuals . . . . . . . . . . 2,413 

~i~i~~ alone. . . . . . . . . . . . . . . . . . . . . 4,918 

Females : 

Livingwith a family' ' ' ' ' " . ' ' ' - - . - ' . 336 

Living with unrelated individuals . - . . . - . - - 1,634 

~i,,i,,~ alone. . . . . . . . . . . . . . . . . . . . . 9,021 

SOURCE: Special tabulation of the March 1975 Current Population Survey. 
ALTERNATIVE POVERTY COUNTS BASED ON AVAILABLE DATA 

This chapter investigates the effect of some alternative poverty 

measures on the statistical description of poor populations. 11 It deals - 

with the poverty cutoffs, not with the definition of income. In Chapter 

IV, it was shown that modifying the income definition by including some 

cash equivalent value of in-kind benefits or assets would lower the 

poverty count if the poverty cutoffs were not simultaneously changed to 

be consistent with the new income definition. Similarly, poverty counts 

would be reduced if underreporting of cash income were corrected in the 

Census and CPS surveys, or if irregular cash income were counted. However, these commonly proposed changes to the definition of income cannot 

be incorporated into the poverty measure without modifying the Census or 

CPS surveys or developing new surveys from which to derive a poverty 

count. Furthermore, the statistical effect of these modifications is not 

approximated by simple adjustments of the poverty cutoffs, such as by 

lowering than, because subgroups of the poor population are affected 

differently by changes in the income definition. For example, the income 

of the elderly would probably be raised more by the inclusion of the 

value of assets than would the income of young family heads. 

The change which is most canmonly proposed in connection with the 

poverty cutoffs is to raise them. This reflects a presumption that the 

standard of living, however defined, has risen in this country since 

the official poverty level was originally established. Also, it is not 

generally believed that U.S. citizens need less now than they did in the 

past. These notions are implicit in such proposals as: revising the 

Orshansky matrix on the basis of current food plans and consumption 

patterns; identifying the lowest quintile of the income distribution 

as the poverty income level; setting the poverty level at 50% of median 

income; using public opinion polls to determine a generally accepted 

level of income adequacy; or using the lower BLS family budget as a 

poverty budget. Similarly, most administrative adaptations of the poverty line in Federal programs have the effect of enlarging the population 

of program beneficiaries beyond those identified as poor by the official 

poverty measure. 

However, not all canmonly proposed changes to the poverty cutoffs 

or income definition can be linked simply to higher or lower poverty 

counts. For example, if the thrifty food plan were used as a basis for 

the poverty cutoffs, but without simultaneously raising the ratio of 

incane-to-food costs, the cutoffs for some families would be lowered 

and others raised. Similarly, if poverty cutoffs were annually updated 

using a price index based on food or on items in a special poor person's 

index, rather than on the Consumer Price Index, the poverty cutoffs 

could be higher in some years and lower in others than the current 

cutoffs. Presumably, geographic adjustments to the poverty cutoffs would 

raise them in some places and lower them in others; removing the current 

adjustment for farm residence would raise the poverty counts only 
slightly. Simplifying the current poverty matrix by removing distinctions 

for sex of head and presence of children would affect the poverty status 

of families according to sex and age of family members. If Federal or 

state and local income taxes, Social Security payroll deductions, or. 

other taxes were excluded from the income definition (and the poverty 

cutoffs were not simultaneously changed), the poverty count would be 

increased, although this could be offset if the Federal tax credit for 

earned income were counted as income. Changing the definition of family 

or using households rather than families as accounting units could raise 

or lower the count depending on the change made. Applying a recently 

proposed index of employment and earnings inadequacy and a price index 

for the elderly might cause poverty counts of these groups to differ from 

counts under a single national poverty measure. 

It is not. practical to describe here the statistical effects of. 

adopting all of the variously proposed alternative measures. Of the 

many possibilities, the analysis here considers four groups of definitions 

totalling 13 specific alternatives '(the current poverty measure and 12 

others selected for analysis by the Poverty Studies Task Force). These 

were selected because : they can be studied with readily accessible data; 

they are similar to administrative poverty measures or income eQigibility 

criteria currently used in Federal programs; and they can be used to' 

approximate the effects of adopting some concepts discussed in the earlier 

chapters. 

Alternative Poverty Definitions 

The four broad groups of alternatives are: simple proportionate 

increases or decreases of the current poverty matrix, simplifications 

of the current poverty matrix, single-dollar thresholds, and relative 

measures based on median income. The current poverty measure was also 

included to provide a point of reference against which the other measures 

could be compared. . 

The first group consists of four matrixes derived by multiplying 

each of the cutoffs in the official poverty matrix for 1974 (shown in 

Chapter I, Table 1) by 75 percent, 125 percent, 150 percent, and 200 

percent. One reason for the selection of these cutoffs was to demonstrate 

the importance of the level of the poverty thresholds, compared to that 

of adjustments for residence and family composition (analyzed in the next 

set oi a1 ternatives). in determining the poverty population. Also, some 

Federal programs, such as those of the Department of Agriculture, define 

eligibility on the basis of simple proportional increases in the official 

poverty cutoffs. Furthermore, as noted earlier, many commonly proposed 

poverty measures have the effect of raising the poverty income levels. 

The statistical effect of such changes can be approximated by reference 

to one of the higher sets of poverty cutoffs included here. A poverty 

line set at 75 percent of the current threshold is also shown. This 

information is provided to identify those groups of people who are most 

severely in need. Furthermore, in making administrative adaptations of 

the poverty line, program administrators may desire to raise income . . 
eligibility criteria above the poverty line in some places and lower the 

criteria below the poverty line in other places, in order to accommodate 

variations in local labor markets, local prices, the extent of poverty, or 

other conditions. Simple scalings of the 1974 poverty cutoffs for a nonfarm 

male-headed family of four with two children are as follows: 

75% of 125% of 150X of 200% of 

Current Current Current Current Current 

Measure Measure Measure Measure -- -- Measure 

The second group consists of three progressive simplifications of 

the current poverty measure. These were studied because it .has been argued 

that the various adjustments for residence and family composition are not 

accurate or necessary. Also, most administrative uses of the poverty 

measure as an eligibility criterion do not incorporate all of the refinements in the current poverty matrix. For example, the income eligibility 

guidelines of the Community Services Administration are based on family 

size and farm-nonfarm residence, but not on sex of head or number of 

children under 18. Other administrative guidelines include distinctions 

only for family size. For this analysis, first the farm-nonfarm differential was eliminated by using the nonfarm thresholds of, the current 

poverty matrix. Next, the distinction based on sex of the head was 

eliminated by using the nonfarm male-headed family thresholds. Finally, 

the distinctions for the number of related children under 18 were eliminated 

by using weighted average thresholds for each family size category. 

Simplified poverty cutoffs in 1974 are shown below. For non.farm and 

male-headed family cutoffs, see Table 1. 

Famil y-Size 

and Type 

1 Person 

Under 65 

Over 65 

2 Persons 

Head under 65 

Head over 65 

3 Persons 

4 Persons 

5 Persons 

6 Persons 

7 or more Persons 

1974 Weighted Average 

Povertv Cutoffs 

The third group consists of two single-dollar poverty thresholds, 

which are invariant with respect to family size. The first, the low 
threshold, was $3,220 for all families; that amount was chosen because 

it yielded a poverty count equal to the nu6ber of poor persons derived 

by the current measure in 1969 £rom the 1970 Census of Population. The 

high threshold is the average weighted threshold for a nonfarm family 

of four in the current poverty' matrix, equal 'to $5,038 in 1974. 

Such measures serve as a point of reference to illustrate the effect 

of variations for family size on the composition of the poor. Singledollar cutoffs are sometimes used for analytical purposes or as administrative criteria for distributing Federal funds. The Comprehensive 

Employment and Training Act, for example, distributes manpower revenuesnaring funds to local governments in part (by a weighting factor of 12.5 

percent) based on the number of families in each unit of a government's 

jurisdiction with an income less than a fixed amount; and a $2,000 threshold 

was used for distributing Title I funds under the Elementary and' Secondary 

Education Act until 1974. Although in this analysis the high threshold 

(like the current measure) was varied over time by the annual rise in the 

Consumer Price Index, the low threshold was held constant at $3,200 over 

the eight-year period of analysis, 1967-1974. Thus, the low threshold also 

illustrates the effect of a poverty measure which is not annually updated. 

Single-dollar cutoffs in 1974 are presented below. 

Low Cutoff High Cutoff 

The fourth group consists of three different relative measures of 

poverty. Each measure is based on 50 percent of some median income. Fifty 

is an arbitrary percentage which was selected because it is frequently 

used in discussions of relative poverty measures. The interest in these 

measures is primarily in their behavior over time and their relationship 

to the more conventional measure(s1 updated by the Consumer Price Index. 

The first relative measure examined was a double threshold distinguishing between families and unrelated individuals: for families, 

the poverty threshold was set at 50 percent of median family income 

($6,418 in 1974, or 50 percent of $12,836); for unrelated individuals, 

the threshold was set at 50 percent of the median income for unrelated 

individuals ($2,220 in 1974, or 50 percent of $4,439). This large 

difference in the thresholds for these two groups of people reflects 

the fact that unrelated individuals as a group receive much lower incomes 

than families. 

The remaining,two relative measures considered use 50 percent of a 

base median income and adjust it for fam.ily size by using the equivalence 

scales implicit in the current poverty measure. (~hese equivalence scales 

are described in Chapter IV and are illustrated in Table 11.) In one 

106 
case, the base median income is that for all families ($12,836 in 1974); 

in the other, the median income is that for a nonfarm family of four with 

a male head and two children ($14,004 in 1974). In both cases, 50 percent 

of the base median .income was assumed to represent the poverty threshold 

for the typical family of four just described, and the equivalence scale 

was used to calculate the comparable cutoffs for the 123 other family sizes 

and types. Income eligibility criteria based on median income have been 

included in recently enacted legislations, such as Title 11 of the Housing 

and Community Development Act of 1974 and Title XX of the Social Security 

Act. Those definitions, however, use local median incomes rather than 

the national median. Title XX requires the median income for each state 

to be used in establishing its income eligibility standard, and the housing 

Act uses median income for a metropolitan area in establishing the income 

eligibility level for the area. National median incomes' in 1974 were as 

fo 1 lows : 

All families $12,836 

Male-he aded 

Nonfarm families of four 

Wi th two children 

Unrelated individuals $ 4,439 

The effect of the alternative measures on the size of the poverty 

population in 1974, based on the March 1975 Current Population Survey, 

is described in the next section. 

The Number of Poor, 1974 

Figure 3 illustrates the effect of the 13 definitions of poverty 

on the size of the poverty population. Portrayed as the first bar on 

these graphs, the current poverty measure provides the basis of canparison for the other measures. 

Successively scaling the current poverty thresholds by 75 percent, 

125 percent, 150 percent, and 200 percent has the largest impact on the 

number of poor persons and poor families, and the poverty population is 

largest for 200 percent of the current measure. A pattern of increase is 

observed with the upward shifts: for every 5 percent increase in the 

current cutoffs, approximately two million persons are added to the poverty 

population, and the percent of the population counted as poor increases one 

percentage point. This pattern was also observed for the downward shift to 

75 percent of the current measure. As shown in Table 17, the number of 

poor persons rises from 14.5 million with 75 percent of the current measure, 

or 6.9 percent of the population to 69.4 million, or 33.1 percent of the 

population with 200 percent of the current measure. The comparable poverty 

rates for families are slightly lower, 5.5 percent and 28.8 percent. 
40 

Persons in Poverty I w w w w v ZL, C ca m - 4 mu ca .3 dm 0.7 0 .a a a, es 

'2 '3 k. 

Current Scalinn Simplifications Single- Relative 

of Current Dollar Poverty 

Measure Cutoffs ' Measures 

Measure of Current 

Measure 

Current 

Measure 

30 

20 U C

w 

h 

a 

a 

10- 

Scaling Simplifications Single- Relative 

of Current of Current Dollar Poverty 

Measure Measure Cutoffs Measures 

Unrelated Individuals in Poverty 

- 

28.8 

- 

- 

- 

17.9 

' 13.3 

Current 

Measure 

75% 4 N 0 

Scaling 

of Current 

Measure 

Families in Poverty 

Simplifications 

of Current 

Measure 

- - 

13.5 

SingleDollar 

Cutoffs 

5 

Relative 

Poverty 

Measures 

- 

19.6 

' C 

a + m x rn 

"7 ow 2 

SOURCE: Special tabulations by the Census Bureau from the March 1975 Current Population Survey. 

9.3 9.4 

c e L? 2 

Figure 3. Poverty Rates for Persons, Families, and Unrelated Individuals 

Under Alternative Poverty Measures, 1974 

16.1 14.0 - 

u;"? 

5: 

2: 

9.6 

3- 2. 

2s A$ 

5s 

.7 

v 

* - 
Table 17. Comparison of Poverty Population 

Under Selected Alternative Definitions of Poverty,. 1974 1 1 Pe;~,ie;o;~lpoor 

Alternative Definition Percent of 

Thresholda (millions) . Population 

Current measure $ 5,038 24.3 11.6% 

75% of current measure 3,779 14.5 6.9 

125% of current measure 6.298 34.6 16.5 

150% of current measure 7,557 45.2 21.6 

200% of current measure 10,076 69.4 33.1 

SOURCE: Special tabulations by the Census Bureau from the March 1975 Current 

Population Survey. 

a Weighted average threshold for a nonfarm family of four. 

Compared to the current measure, the progressive siapli fications 

of the current measure have little impact on the size of the poverty 

population. Eliminating the farm-nonfarm differential raises the poverty 

rate slightly to 11.7 percent, as 70,000 farm families and 19,000 unrelated individuals living on farms (a total of 274,000 persons) are added 

to the poverty population. An additional 612,000 persons are counted as 

poor when the higher thresholds for male-headed families are substituted 

for the thresholds assigned to female-headed families in the Orshansky 

matrix, raising the poverty rate to 12.0 percent. In the final simplification, the variations based on number of related children under 18 

were omitted. The number of poor unrelated individuals is therefore 

unaffected. The number of poor persons and the number of poor families 

decreases slightly, and the poverty rates are virtually the same, 12.0 

percent and 9.4 percent, as in the previous simplification. Additional 

analysis of the effect of progressive simplifications of the cutoffs is 

found in Technical Paper XI, which deals with updating and revising the 

current poverty measure on the basis of current food plans and consumption 

pat terns. 

The poverty count resulting from the low single-dollar threshold 

($3,200) is 17.4 million persons, considerably lower than the population 

defined by the current measure -- 24.3 million in 1974 -- and the lowest 

of any of the alternatives, with the exception of 75 percent of the 

current measure. However,' the impact on families differs greatly from 

the impact on unrelated individuals. Far more unrelated individuals 

are poor under this definition, and far fewer families. With the high 

single-dollar poverty threshold ($5,038). a much larger number of persons 

are included in the poverty population, 32.7 million. Compared to the 

current poverty measure, this,difference is due entirely to the family 
size equivalences, as many more small families (two and three persons) 

and unrelated individuals are counted as poor with the high singledollar cutoff. This poverty measure produces the largest number of poor 

unrelated individuals, about 10.5 million. Although the number of both 

poor families and poor unrelated individuals increases, this poverty 

population is comprised of a smaller proportion of persons living in 

families than the current poverty population, as shown in Figure 4. 

Unrelated 

ndlvidual 

Living 

in 

Families 

Current 

Poverty 

Measure 

Unrelated 

!ndividualt 

41.9 

58.1 

Living 

in 

Families 

Lor: 

SingleDollar 

Cutoff 

Unrelated 

ndividual. 

32.2 

67.8 

Living 

in 

Families 

High 

SingleDollar 

C"t0ff 

SOURCE: Special tabulations by the Ceosua Bureau from the 

hrch 1975 Current Population Survey. 

-Figure 4. Distribution of Poor Persons by Living Arrangements, 

Current Poverty Measure and Sing le-Dollar Poverty Cutoffs, 19 74 

The three relative poverty measures based on 50 percent of median 

incane all produce higher poverty counts than the current measure. Although two measures -- 50 percent of median income unadjusted for family 

size except by families and unrelated individuals, and 50 percent of 

median family income adjusted by the equivalence scale implicit in the 

current poverty matrix -- produce almost identical counts of poor persons 

(about 36 million), the former poverty population has more families and 

fewer unrelated individuals than the latter. Reflecting the very low 

median income of unrelated individuals and the resulting lower cutoff in 

the first instance, $2,220 compared to $3,192, fewer unrelated individuals 
are counted as poor when 50 percent of their own median income is used. 

On the other hand, the adjusted 50 percent of median family income loses 

more two-person and three-person families than it gains five-or-moreperson families, compared to the unadjusted 50 percent median income 

measure, so that the number of poor families falls. This comparison 

provides another illustration of the effect of equivalence scales on 

poverty counts. Finally, using 50 percent of the median income of the 

base case family (nonfarm, two-child family of four with a male head) 

adjusted for family size produces a poverty population almost as large 

as that with 150 percent of the current poverty measure, 41.2 million. 

The reason is that the cutoff for the base case family is very similar 

for each measure, $7,002 compared to $7,500; consequently, the full poverty 

matrixes are very similar. 

In summary, the largest impact on the size of the poverty population 

results £ran large increments in the level of the current thresholds. 

Of all the alternatives considered, the poverty population is largest 

when 200 percent of the current poverty measure is used, but even 150 

percent of the current measure yields a higher absolute poverty count 

than the other measures. Because of their small family size and generally 

low income, unrelated individuals are an exception; the high singledollar threshold generates the largest number of poor unrelated individuals. Using 75 percent of the current measure produces the smallest 

poverty population for both persons in families and unrelated individuals. 

Characteristics of the Poor, 1974 

An important consideration in analyzing the alternative definitions 

of poverty is the composition of differing poverty populations. Knowing 

precisely who is counted as poor is as important as knowing the number 

of poor. This section explores the impact of the various poverty definitions on the characteristics of the poor in 1974. As general background 

to this discussion, a brief description of the current poverty population 

is provided. 

Under the current poverty measure, the poverty population has a 

greater proportion of the elderly, female-headed families, blacks, the 

poorly educated, and unrelated individuals (especially elderly unrelated 

individuals) than the general population. For example, 46 percent of 

poor families are headed by a female, and children in female-headed 

families are about 6 times as likely to be poor as children in maleheaded families (52 percent vs. 9 percent). Blacks are more than 3 

times as likely as whites to be poor; blacks comprise almost one-third 

of the poor population, compared to only 11 percent of the total population. About 16 percent of the elderly are poor, compared to a poverty 

rate of 12 percent for the general population, and the elderly constitute 

14 percent of the poverty population. Only one-third of poor persons over 

14 years have a high-school diplcma. Although about two-thirds of poor 

families receive some earnings, employment tends to be unstable; only 19 
percent of poor family heads have full-time, year-round employment. 

Table 18 summarizes some of these characteristics. 

Table 18. Selected Characteristics of the Poverty Population 

Under the Current Definition, 1974 

Characteristic 

Percent of Percent of / poverty I Total 

Population Population 

Persons 

Black 30.8% 11.4% 

Elderly 13.6 10.1 

Living in female-headed family 35.3 11.1 

Families 

Female-headed 46.0 13.0 

Received earnings 62.1 88.9 

Head worked full-time, year-round 19.2 61.4 

SOURCE: Special tabulations from the March 1975 Current Population Survey. 

The summary discussion in this section is intended to highlight the 

major impacts of the alternative definitions on the composition of the 

poor. Several specific characteristics were selected for this illustrat ion : female-headed families, the elderly, blacks, and the working poor. 

Separate consideration has also been given to school-age children because 

of the focus of this study on Title I of the Elementary and secondary 

Education Act. The poverty rates and the canposition of the poor by a 

more complete set of characteristics are provided in Tables 19 and 20. 

To simplify the following descriptions, several generalizations 

can be made about the observed trends in the alternative poverty populations. Those definitions which most alter the size of the poverty 

population also have the greatest effect on the characteristics of the 

poor. As the current poverty measure is successively scaled by 75 percent, 

125 percent, 150 percent, and 200 percent, the poverty rate for each 

subgroup increases but at a different rate. The canposition of the ever 

larger poverty population approaches that of the total population. 

Progressive simplifications of the current measure, on the other hand, 

have negligible impact on the composition of the poor, as is evident 

in each of the accompanying figures, and for the most part will be ignored 

in this analysis. The single-dollar thresholds, which are invariant with 

respect to family size, change the canposition of the poor to a large 

extent because of their differential screening of large and small families. 
Table 19. Poverty Rates by Selected Characteristics 

for Alternative Poverty Definitions, 1974 

I I I I Simplificarions of [Single-mllar I 

Scaling of Current Measure 

Characteristics 

I Current Measure I cutoffs I Relative Measures 

Persons 

Total .............. 

Nonfarm 

Living arrangements: 

In families ...... Male headed .... Female headed . . Unrelated individuals ......... 

Race: 

White ............ Black ............ Other ............ 

Hale 

Nonfarm 

Age : 

Under 5 years . . . . 5-17 years ....... 18-64 yearsa . . ... . 65 years 6 over . . 

Families 

Total .............. 

Age 

(I Sire 

Sex of head: 

Hale ............. Female ........... 

Presence of children: 

None ............. he or more ...... 

Low 

Employment status 

of head: 

employed ......... Unemployed ....... Not in civilian 

labor force ..... 

Source of income:b 

Earnings ......... Social Security .. Public assistance. 

High 

Unrelated Individuals 

Total .............. 

50% 11 S . Mediah 

Unadj . 

Sex: 

Male ............. Female ........... 

Employment status: 

Employed ......... Unemployed ....... Nor in civilian 

labor force ..... 

Source of income:b 

Earnings ......... Social Security .. Public assistance. 

SOmce: Special tabulations by the Census Bureau from the mrch 1975 Current Population Survey 

a Includes a small number of heads, wives, and unrelated individuals 14-17 years of age. 

A family or unrelated individual may have more than one source of income. Consequently, the totals for these categories exceed the numbers 

of families and unrelated individuals. 
Table 20. Distribution of the Poverty Population 

by Selected Characteristics for Alternative Poverty Definitions, 1974 

Persons 

Number (in thousands). 209,343 

Living arrangements: 

- I" families ........ 91.0% 

. ' Male headed .. .. ... 79.9 . . 

. . Female headed ..... 11.1 

Unrelated 

individuals ....... 9.0 

Relative Measures 

Race: white.. . . . . . . . . . . . . . 87.1 

Black ............... 11.3 

Other....... ....... 1.6 

Single Dollar 

Cutoffs 

- Age: under 5 years.. . . . . . 7.6 

5-17 years.... ...... 23.8 

18-64 years a ....... 58.5 

-. 65 years and over... 10.1 

50% &-PersonMedian Family. 

Adj. 

50% U.S. 

Median, unadj. 

Lou 

,Simplifications of 

Current Measure 

Families 

Number (in chousnnds) . 55,712 

Current 

' characceriscics Measure 50% U.S. 

Median Family, 

Adj. 

High 

sealing of Current Measure 

Sex of head: 

-.,-vale ................ 87.0 

Female.... .......... 13.0 

Total 

Population Age Nobfarm and Sire 

. Presence of children: 

None. ............... 43.8 

One or mare......... 56.2 

Male 

200% Nonfarm 

. . Employment status of . head: - Employed .. .. . ... .. . 72.5 

< Unemployed ......... 5.0 

Not in civilian . labor force ....... 22.4 

75% 150% 

Source of income:b 

"nmings ............ 88.9 

Social Security ..... 21.8 

Public assistance... 7.8 

125% 

. . Unrelated Individuals 

' 'Number (in thousands). 18,872 

,$ex: 

.. Male....... ......... 41.8 

Female. ............. 58.2 

Employment status: . . Employed ......,..... 51:2 

. Unemployed .......... 4.9 . .Not in civilian 

labor force ........ 43.9 

Source of income:b 

Earnings ............ 61.5 

Social Security ..... 37.0 

Public assistance... 8.8 

SOURCE: Special tabulations by the Census Bureau from the Harch 1975 Current Population Survey. 

a Includes a small number of heads, wives, and unrelated individuals 14-17 years of age. 

A family or unrelated individual may have more than one source of income. Consequently, the torale for these categories exceed the numbers of families and unrelated individuals. 
In general, because the relative poverty measures adjusted for family size 

and composition are similar in 1974 to those resulting from an upward 

scaling of the current measure by 25 to 50 percent, their poverty populations are similar in size and composition. 

Persons in Female-Headed Families 

As shown in Figure 5, the poverty incidence for persons in femaleheaded families rises from 3,7 percent to 64 percent as the poverty 

thresholds are doubled. At the same time, this group falls from 35 

percent to 22 percent of all poor persons; thus, more male-headed families 

and family members are added as the poverty group expands. Female-headed 

families and family members are, however, still greatly overrepresented 

in the poverty population. Decreasing the poverty thresholds to 75 

percent of the current measure lowers the incidence of poverty to 24 

percent and raises the proportion of persons in female-headed families to 

39 percent of the poor. Eliminating the male-female distinction in the 

current poverty measure increases the poverty rate for members of femaleheaded families slightly, from 37 to 39 percent. The low single-dollar 

threshold significantly lowers the poverty rate for this group to 20 

percent, and both single-dollar thresholds decrease their share of the 

poor to about 27 percent. The effects of the relative poverty measures 

are similar to the 25 percent and 50 percent increases in the current 

poverty measure, reducing persons in female-headed families to about 30 

percent of the poor. 

Blacks 

Figure 6 shows that the measures have an impact on blacks similar 

to that on persons in female-headed families. lacks as a percentage 

of the poor fall from 31 percent to 21 percent as the current poverty 

thresholds are raised by 100 percent ; black poverty incidence almost 

doubles, rising from 32 percent to 62 percent. 

School-Age Children 

The poverty rates for children aged 5 to 17 years under' the alternative poverty definitions, and their representation in the poverty 

population, are displayed in Figure 7. Although the poverty rates follow * 

a pattern similar to those for blacks and persons in female-headed 

families, they are at a much lower level, reaching 39 percent at 200 

percent of the current measure. School-age children are not as overrepresented in the poverty population as the other subgroups. Under the 

current definition they comprise 31 percent of the poverty population, 

compared with 24 percent of the general population. Only the three sizeinvariant poverty thresholds '-- $3,200, $5,038 and 50 percent of unadjusted 

median family income -- significantly affect their representation among the 

poor. Because these three measures reduce the number of large families 

relative to unrelated individuals, poor school-age children drop to as low 
Poverty Rate 

Current Scaling Simplifications Single- Relative 

Poverty 

Eleasures Measure of Current of Current 

Measure Measure 

Persons in FemaleHeaded Families in 

Total Population 

n 

Poverty Population 

I I I Ln 

Relative 

Poverty 

Measures 

Simplifications 

of Current 

Measure 

SingleDollar 

Cutoffs 

United Current 

States Eleasure 

Scaling 

of Current 

Measure 

SOURCE: Special tabulations by the Census Bureau from the March 1975 Current Population Survey. 

Figure 5. Persons in Female-Headed Families : 

Poverty Rates and Percent of the Poverty Population 

Under A1ternativ.e Poverty Definitions, 1974 
Poverty Rate 

Simplifications 

of Current 

Measure 

Current Scaling 

Measure of Current 

Measure 

Single- Relative 

Dollar Poverty 

Cutoffs Measures 

Blacks in 

Total Population Poverty Population 

United Current 

States Measure 

Scaling Simplifications 

of Current of Current 

Measure Measure 

Single- Relative 

Dollar Poverty 

Cutoffs Measures 

SOURCE: Special tabulations by the Census Bureau from the March 1975 Current Population Survey. 

Figure 6. Black Persons: 

Poverty Rates and Percent of the Poverty Population 

Under Alternative Poverty Definitions, 1976 
Poverty Rate 

Current 'Scaling 

Measure of Current 

Measure 

Simplifications Single- Relative 

of Current Dollar Poverty 

Measure Cutoffs Measures 

School-Age 

Children in 

Total Population 

'21.2 

$ w-7 . 23 . 

07- 

3,. 

*g Zh 

C 

Poverty Population 

16.7 

" . .u 

"Im 

;s 

W a om "72 

Ilnited Current 

States Measure 

' 

Scaling 

of Current 

Measure . , 

15.6 

-3 

w WN DO.-l 

4 07 I"$ Low 

:31. 0: ...... 

...... ..... 

...... ..... 

...... ..... 

...... ..... 

...... ..... 

............ ..... ..-........ ...... 

...... ..... 

..... ..I........ ..... 

...... ..... 

...... ..... 

...... ..... 

...... ..... 

..... 

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

...... ..... 

..... 

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

...... ..... 

...... ..... 

...... ..... 

..... 

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

Simplifications Singleof Current Dollar 

Measure Cuyffs 

11.9 

z 

31.7 

Wsgg rnNln0 P-.+r(N 

SOURCE: Special tabulations by the Census Bureau from the March 1975 Current Population Survey. 

31.0 

w 

Figure 7. . School-Age Children: 

31.0 31.0 

w 

Eg;: 

SZ-3 

c3w 

224" 

Relative 

Poverty 

Measures 

Poverty Rates and Percent of the Poverty Population 

Under Alternative Poverty Definitions, 1974 

7 

22.8 

% d 

u 

w 2 v w 

.LI "I", 

., 3" Wm u 

oc m3 

- 

16.8 

4 h 

29.2 

$: 

'd ", 

~r> 

ga < - "I- 

.X 33 d 

XE om 

lncr 

- 

18.1 

5 + 

Z 

28.8 

C 

.r( 

uu 

2: 

C, 0" 

g2 

D.- I X u.+ + 

we om

knl* 
as 17 percent of poor persons. For all other measures, they remain at 

28 to 32 percent of the poor. 

Elder 1 y 

Figure 8 exhibits several slightly different patterns for the 

elderly (persons aged 65 or more) with respect to the alternative poverty definitions. Their poverty rates increase as the current poverty 

measure is successively raised, but at a faster rate, from 16 percent 

to 50 percent. Consequently, the elderly comprise a slightly higher 

percentage of the poverty population at 125 percent and 150 percent of 

the current measure, 16 percent compared to 14 percent, and decline only 

slightly to 15 percent at 200 percent of the current measure. These small 

differences are not statistically significant. As the poverty thresholds 

are raised, many elderly whose Social Security and pension income is only 

marginally higher than the current thresholds are "recaptured" as poor. 

When the poverty threshold is lowered to 75 percent of the current measure, 

the poverty rate for the elderly declines to 7 percent and their share of 

the poverty population is reduced to 10 percent. As with school-age 

children, the three invariant poverty thresholds significantly affect 

the representation of the elderly in the poverty population. This effect 

is in the opposite direction of that on the children, however, because 

of the elderly's preponderance in small one-person or two-person families. 

The elderly rise to 29 percent of the poverty population for the low 

single-dollar threshold ($3,2001, and are only a slightly lower proportion 

for the high single-dollar threshold (27 percent). For the unadjusted 

relative poverty measure, 50 percent of median income for families or 

unrelated individuals, the elderly constitute about one-fifth of the 

poor, compared to only 10 percent of the' total population. Closely 

rel?ted to this is the effect of the alternative poverty definitions 

on families and unrelated individuals receiving Social Security. A 

very similar pattern is evident in Figure 9, although the impact of 

the single-dollar thresholds is not as pronounced as for the elderly. 

Families with Earnings 

As noted earlier, about two-thirds of all families who are poor 

under the current measure receive some earnings. This proportion increases to almost three-quarters when these cutoffs are raised by 100 

percent, but it is still considerably lower than the percentage of all 

families in the general population with earnings, which is about 90 

percent. The proportion of poor families with earnings is lowest using 

the single-dollar thresholds, which are invariant with respect to family 

size. The work patterns of the poor tend to be unstable, and only 19 

percent of poor family heads under the current definition worked full-time, 

year-round, in 1974, compared to 61 percent of all family heads. Raising 

the poverty cutoffs captures more and more working poor. They represent 

22 percent of all poor families at 125 percent of the current measure, 

25 percent at 150 percent, and they rise to 34 percent of poor families 

at poverty cutoffs equal to 200 percent of the current measure. These 

results are illustrated in Figure 10. 
Poverty Rate 

Current Scaling 

Measure. of ~urient 

Measure 

Elderly Persons 

in Total 

Population 

Simplifications Singleof Current Dollar 

Measure Cutoffs 

Poverty Population 

Relative 

Poverty 

Measures 

United Current Scaling Simplifications Single- Relative 

States Measure of Current of Current Dollar Poverty 

Measure Measure Cutoffs Measures 

SOURCE: Special tabulations by the Census Bureau from the March 1975 Current Population Survey. 

Figure 8. Elderly Persons: 

Poverty Rates and Percent of the Poverty Population 

Under A1 t ernat ive Poverty Definitions, 1974 
Families With 

Social Security in &or Families 

Total Population With Social Security 

I I 50 n 

United Current Scaling 

States Measure of Current 

Measure 

Simplifications Singleof Current Dollar 

Measure Cutoffs 

Re la t ive 

Poverty 

Measures 

Unrelated 

Individuals With 

Social Security in Poor Unrelated Individuals 

Total Population With Social Security 

n I 60 

United Current 

States Measure 

Scalina 

of Current 

Measure 

Simplifications 

of Current 

Measure 

SingleDollar 

Cutoffs 

SOURCE: Special tabulations by the Census Bureau from the March 1975 Current Population Survey. 

Relative 

Poverty 

Measures 

Figure 9. Percent of Poor Families and Poor Unrelated Individuals 

Receiving Social Security Under Alternative Poverty Definitions, 1974 
Summary of Poverty Counts and Characteristics 

The effect of the alternative poverty definitions on the number and 

characteristics of those who would be counted as poor is substantial in 

some cases. The composition of the poor varies the most with two basic 

changes in the poverty definition: first, large increments in the level of 

the thresholds, and second, elimination of the variations by family size. 

The large increases in the poverty population resulting from successively 

raising the current poverty thresholds by 25 percent, 50 percent, and 

: 100 percent are accompanied by a shift in the composition of the poverty 

population to resemble more closely the overall population. Even at 200 

percent of the current poverty measure, however, the poverty population is 

still disproportionately comprised of blacks, female-headed families, and 

the elderly. The invariant poverty thresholds, on the other hand, produce 

a poverty with proportionately fewer families (especially large 

families), more unrelated individuals, fewer female-headed, and more elderly. 

The simplifications of the current poverty measure, by eliminating 

distinctions for sex of head, farm residence, and presence of children, 

have a negligible effect on both the size and composition of the poverty 

population. 

Differences Over Time 

Poverty definitions differ in the manner in which they are updated 

over time. All measures based on the current definition are updated each 

year by the annual percentage increase in the Consumer Price Index. The 

relative measures, based on median income, are updated each year as income 

levels change. Only one of the poverty measures analyzed, the $3,200 

single-dollar threshold, was invariant over time. This sect ion considers 

changes in the effect of the different poverty measures over time, with a 

view to determining the stability of the patterns observed in the 1974 

data. Attention is focused particularly on the behavior of the poverty 

populations for the time-invariant and the relative measures of poverty. 

Figure 11 illustrates how the size of the poverty population under 

each measure has varied over the period 1967 to 1974, based on special 

tabulations from the March Current Population Surveys for 1968, 1970, 

1972, 1974, and 1975. Between 1967 and 1974, the total population 

increased by almost 15 million persons, and the poverty population under 

the current definition dropped from almost 28 million to 24 million. The 

descent was not smooth, however, with slight increases occurring between 

1969 and 1971 and between 1973 and 1974; these increases coincided with 

rises in the national unemployment rate, from 3.5 percent to 5.9 percent 

and from 4.9 percent to 5.6 percent, respectively. It should be remembered, however, that for small areas there is little relationship between 

unemployment and poverty (See Chapter 111 for a more detailed discussion 

- of unemployment data.) This same trend was reflected in the three progressive simplifica.tions of the current measure (note that it is impossible to 
Families With 

Earnings in 

Total Population Poor Families With Earnings 

n I 1 

United Current Scaling 

States Measure of Current 

Measure 

Simplifications Single- Relative 

of Current Dollar Poverty 

Measure Cutoffs Measures 

Families With Head 

Working Full-Time 

year-Round in Poor Families With 

Total Population - Head Working Full-Time Year-Round 

I 1 

United Current Scaling Simolifications .- ~-- Sinele- Relative 

States Measure of Current of Current Dollar Poverty 

Measure Measure Cutoffs Measures 

SOURCE: Special tabulations by the Census Bureau from the March 1975 Current Population Survey. 

Figure 10. Percent of Poor Families with Earnings 

and Percent of Poor Families with Head Working Full-Time, Year-Round 
Persons 

(in millions) 

Total Population 

200% Current Measure 

.I502 Current Measure 

- 50% 4-Person Median Family Income, Adj. 

50% U.S. Median Family Income, Adj. 50% U.S. Median Income, Unadj. 

-CLCC---------d 

Male Nonfarm Family of 4 

(High Single-Dollar Cutoff) 

Current Measure 

1967 1969 1971 1973 ' 1974 

SOURCE: Special tabulations by the Census Bureau from the March Current Population survey for 1968, 1970. 1972. 1974. and 1975. I 

Figure 11. Number of Persons in Poverty 

Under Alternative Poverty Definitions, for Selected Years, 1967-1974 
distinguish these measures on the graph because of their close similarity), 

and, at successively higher positions, in the four scalings of the current 

measure (75 percent, 125 percent, 150 percent, and 200 percent). The 

poverty counts from the relative measures, based on median income, exhibited 

much less variation over time. For 50 percent of the median inccme for 

four-person families, adjusted, the counts were virtually invariant, and 

for 50 percent of median family income, adjusted, only slightly more change 

over time was apparent. With the unadjusted 50 percent of median income, 

the number of poor persons steadily increased over time. Finally, as 

expected, the invariant threshold of $3,200 resulted in a large and steady 

fall in the number of poor persons from 29 million in 1967 to 17 million 

in 1974. This illustrates what would happen if poverty cutoffs were not 

adjusted for rising prices or a rising standard of living. 

The poverty rates for different subgroups of the population under 

the alternative poverty definitions were also examined over the sane 

e ight-year period, 1967 through 1974. There are two general differences 

in the trends for the subgroups canpared to the overall trends for the 

general population discussed above. The poverty rates under the relative 

measures were not as stable and constant for the subgroups over the period, 

although the difference was not consistent among the subgroups. Both 

upward and downward trends were observed, in addition to greater variability in both directions from one year to the next. A second difference 

was that the poverty rates of the subgroups at successively higher levels 

of the current thresholds, especially 200 percent of the current measure, 

did not exactly mirror the pattern over time of the poverty rates with the 

current measure. Both of these differences indicate that the income 

distribution of subgroups of the population is not as regular and stable 

as the income distribution of the population as a whole. Also, they may 

reflect changes in the canposition of the population as a whole. 

The largest differences from the general pattern of alternative 

poverty rates over time were observed among the elderly and persons in 

female-headed families. For the elderly, the poverty rates under all 

poverty definitions displayed a strong and steady downward trend from 

1967 to 1974. With the current measure, for example, the poverty rates 

fell from 30 percent in 1967 to 16 percent in 1974. The decline over 

the period was about 10 to 15 percentage points for variants of the current measure, a somewhat smaller but still a steady decline for the relative measures, and a much larger decline (about 45 percentage points) for 

the constant single-dollar threshold of $3,200. This improvement in the 

economic position of the elderly is largely a result of increases in Social 

Security benefits after 1970, and, to a lesser extent, larger and more 

widespread private pensions, 

The percentage of persons in female-headed families counted as poor 

under the current measure declined slightly from 39 percent to 37 percent 

over the period, Most of this decline occurred after 1971. However, the 

number of female-headed families has increased with time. This subgroup 

is distinguished by the behavior of its poverty rates under the relative 
measures. The percent of persons in female-headed families classified as 

poor rose sharply from 1967 to 1969 under all three relative measures, and 

continued to rise until 1973 for the two measures based on 50 percent of 

median family income, adjusted and unadjusted for family size, From 1973 

to 1974, the poverty rate fell under each of the relative measures. This 

pattern of a rising poverty rate to 1973, followed by a drop, was even more 

pronounced for families receiving public assistance under the relative 

measures . 

The poverty rates for other subgroups examined -- blacks, families 

with earnings, and school-age children -- were generally similar to the 

trends observed for the overall population in Figure 12. Blacks experienced a larger drop in their poverty incidence between 1967 and 1969 than 

did the general population, and the decline occurred under a1 1 alternative 

definitions. 

The largest change over time in the canposition of the alternative 

poverty populations also occurred for the elderly and persons in femaleheaded families. Persons in female-headed families steadily increased as 

a percentage of the poverty population under all alternative measures. 

While growing from 9 to 11 percent of the general population, this group 

rose from 25 percent of the poverty population under the current measure 

in 1967 to 35 percent in 1974. Gains of 5 to 10 percentage points were 

made under the alternative measures. Families receiving public assistance 

experienced an even larger growth over the period, from 4 percent to 8 

percent of all families and from 21 percent to 40 percent of poor families 

under the current measure. 

Elderly persons, on the other hand, were generally a declining 

segment of the poverty population, reflecting their overall decline in 

poverty incidence. The trend was not steady, and between 1967 and 1969 

the elderly increased as a percentage of the poor. Under the current 

measure they fell from 19 percent of the poor in 1967 to 14 percent in 

1974, and their representation in most alternative poverty populations 

dropped by 2 to 5 percentage points over the period. The only exception 

was 200 percent of the current poverty measure; in this case the elderly 

increased as a percentage of these poverty populations. 

Accompanying these trends were much smaller changes in the representation of other groups in each of the alternative poverty populations. 

Families with earnings declined from 1967 to 1974 as a percent of poor 

families, largely as a result of the dramatic growth in poor families 

with public assistance. Blacks and school-age children, who were each 

about 30 percent of the poverty population under the current measure, 

maintained a fairly stable representation in each of the alternative 

poverty populations over the period. 

Although some rather large changes in poverty incidence and in the 

composition of the poor occurred over the eight-year period, the differences between two adjacent years were not large. 
Percent of 

Persons in 

Poverty 

150% rurrent Measure 

50% 4-Person Median Family Income, Adj. 

\ - 

-\ 

-\ 50% U.S. Median Family Income, Adj. 

-... -... ... \% -.,.- --,ow-- -..- - 50% U.S. Median Income, Unadj. 

->=- 4- 125% Current ~easure- s. -) ./ - ... -...- ... - ... ...#... -... Male Nonfarm Family of 4 

(High Single-Dollar Cutoff) 

Simplification of Current Measure 

Current Measure 

$3,200 Threshold 

(Low Single-Dollar Cutoff) 

1967 1969 1971 1973 1974 

SOURCE: Special tabulations by the Census Bureau from the March Current population Survey for 1968, 1970. 

1972, 1974, and 1975. 

Figure 12. Percent of Persons in Poverty 

Under Alternative Poverty Definitions, for Selected Years, 1967-1974 
Geographic Distribution of Poverty 

The preceding sections have dealt with the impact of the thirteen 

poverty definitions at the national level, based on tabulations from the 

March Current ~o~ulation Surveys. Although the CPS is geographically 

representative, the sample size of about 47,000 households is not large 

enough to yield statistically reliable estimates of the number of poor at 

the state level; this point has been further elaborated in Chapter 111. 

Therefore, in order to investigate the impact of the definitions on the 

geographic distribution of the poor, it was necessary to use the One 

Percent Sample of the 1970 Census of Population, which contains over 6 

million households. This section discusses data for the poverty population by states in 1969. 

Concern about the geographic distribution of poverty arises from the 

manner in which funds are distributed under Title I of the Elementary 

and Secondary Education Act. The formula a1 locates available funds according to the number of school-age children in families with incomes below 

the appropriate poverty cutoffs. Thus, the relevant criterion is a 

state's - share of the pool of eligible children (i.e., of the national 

count of poor, school-age children). Therefore, the analysis in this 

section is concerned with changes in the share of the total poverty 

population from the - share existing under the current poverty measure. 

The discussion is prlmarlly at the regional level, with differences 

for individual states noted. For the interested reader, poverty rates 

for the entire population in 1969 are reported by state in Table 21 and 

for school-age children in Table 22. Technical Paper XVIII contains a 

more detailed analysis of the share at the state level. 

Figure 13 illustrates the changes in the share of poverty for each 

region under the alternative poverty definitions. In each case, the bar 

on the graph represents the region's share of the poverty population 

under each definition relative to its share under the current definition. 

As an aid in canparing effects, we introduce the notion of a share 

ratio, defined as a region's percentage of the nation's poor population 

resulting from an alternative measure divided by its percentage resulting 

£ran the current definition. (Both percentages are based on the same 

year, 1969.) A ratio of 1.0 indicates that a region's share is unchanged 

by the alternative measure; a ratio smaller than 1.0 indicates a decreased 

share. For example, the Northeast contains 17.9 percent of the 27.4 

million poor persons in the United States under the current definition 

in 1969; raising the current poverty thresholds by 25 percent results 

in a poverty population of 37.5 million persons, of which 18.4 percent 

reside in the Northeast. Therefore, the share ratio for the Northeast 

under the upward scaling of the current measure by 25 percent is 1.03 

(18.4117.9). 

Several broad regional patterns emerge from Figure 13. The South's 

share of poor persons generally decreases, or remains unchanged, for 

every alternative poverty measure, with the exception of. 75 percent of the 
Table 21. Percent of Population in Poverty 

for Selected Alternative Poverty Definitions, by State, 1969 

UNITED STATES 

State 

Alabama 

Alaska 

Arizona 

Arkansas 

California 

Colorado 

Connecticut 

Delaware 

Oist. of Col. 

Florida 

Universe 

(000s) 

Georgia 

Hawaii 

Idaho 

Illinois 

Indiana 

Iowa 

Kansas 

Kentucky 

Louisiana 

Maine 

Current 

Measure 

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 

Scaling of Current Measure 

South Carolina 

South Dakota 

Tennessee 

Texas 

Utah 

Relative Measures 

50% US. 50% 4-Person 

YI% US. Median Median 

Wdian, Family, Family, 

Unadj. Adj 1 Adj. 

Simplifications of 

Current Measure 

SingleDollar 

Cutoffs 

Vermont 

Virginia 

Washington 

West Virginia 

Wisconsin 

Wyoming 

75% NonfarmNonfarm Low 

- 

SOURCE: Special tabulations by the Census Bureau from the 1:100 Sample of the 1970 Census of Population. 

125% 150% High 

Male 

200% Age &Size 
Table 22. Percent of Related Children Aged 5-17 Years in Poverty 

for Selected Alternative Poverty Definitions, by State, 1969 

I I I Scaling of Current Measure I Simplifications of I ooliar I Relative Measures 

Universe Current Current Measure 

(000s) Measure 

Male Age 

75% 125% 150% 200% Nonfarm Nonfarm h Size 

UNITED STATES 

Alabama 

Alaska 

Arizona 

Arkansas 

California 

Colorado 

Connecticut 

Delaware 

oist. of C0l. 

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 Caroliria 

North Dakota 

Ohio 

Oklahoma 

Oregon 

Pennsylvania 

Rhode Island 

South Carolina 

South Dakota 

Tennessee 

Texas 

Utah 

Vermont 

Virginia 

Washington 

West Virginia 

Wisconsin 

Wyoming 

SOURCE: Special tabulations by the Census Bureau from the 1:100 Sample of the 1970 Census of Po~ulation. 
Share ''I5 

Ratio 

1.10 Northeast 

Share 1.15 1 

Ratio 

1.10 1 North Central 

Share 1 -. 

Ratio 

1.00 

.90 

.85 

v South 

Share 

Ratio 

1.05 West 

.95 

.90 

Scaling 

of Current 

Measure 

Simplifications Singleof Current Dollar 

Measure Cutoffs 

Relative 

Poverty 

Measures 

SOURCE: Special tabulations by the Census Bureau from the 1:100 Sample of the 1970 

Census of Population. 

Figure 13. Regional Share of Poor Persons 

Under Alternative Poverty Definitions as a Ratio of 

Regional Share Under Current Poverty Definition, 1969 
current measure. In this situation, the South's share increases slightly. 

Conversely, the other regions generally increase their share of the poverty population, The share of poverty in the North Central region 

increases under every alternative measure. 

These regional changes, for the most part, are not large. Significant changes (5 percent or more) from the share of poverty under the 

current measure occur only when the current poverty matrix is raised by 

50 percent or LOO percent or when the single-dollar thresholds are used. 

The progressive simplifications of the current measure has a negligible 

impact on the regional distributions of poverty. Both single-dollar 

thresholds reduce the South's share of poor persons by 9 percent, increase 

the North Central's by 9 percent, and increase the West's and the Northeast's by about 6 to 7 percent. Raising the current poverty matrix by 

100 percent decreases the South's share by 13 percent, increases the 

Northeast's and North Central's shares by 12 to 13 percent, and increases 

the West's share by 6 percent. 

These broad regional patterns obscure some differences at the state 

level. For example, by using 75 percent of the current measure, Mississippi 

increases its share of the poverty population more than does the South as 

a whole, while Delaware, Oklahoma, and Texas decrease their shares. Not 

a1 1 Southern states consistently reduce their share of the poverty 'population for the other 11 alternative poverty measures, as does the South as a 

whole.. 

Several alternatives increase the positions of Florida, Maryland, 

Oklahoma, and Virginia, although usually only slightly. Several Southern 

states have greater losses than does the South as a whole. Three states 

in the North Central region experience a significant loss (i.e., larger 

than 5 percent of their present share.of the national poverty population): 

North Dakota under both the $3,200 single-dollar cutoff and 75 percent 

of the current measure, and Iowa and Minnesota under 75 percent of the 

current measure. Other states in this region experience slight losses 

for some alternatives, and the pattern of significant gains varies among 

the states for the different alternatives. Several Northeastern states 

experience significant losses at 75 percent of the current measure. 

Rhode Island is the only exception to the general rise in the share of 

the poor in the Northeast states under the other alternatives; its share 

is reduced consistently, although significantly only once. New York 

does not exhibit a significant gain or loss in its share of the poor under 

any alternative studied. A mixed pattern is observed among the states 

in the Western region, with more states experiencing a relative decline 

in their share of poverty than in the Northeast and North Central regions. 

However, few of these losses are significant. New Mexico and Arizona 

are the most consistent losers under the alternatives, and Idaho, Montana, 

and Wyoming the most consistent and significant gainers in the West. 

Technical Paper XVIII provides detailed supporting tables of the effect 

of the alternative poverty measure on each state's share of the poor. 
Similar patterns of regional changes are apparent for poor schoolage children in Figure 14. In all regions except the West, the gains and 

losses are generally larger and more significant than in Figure 13. Two 

important differences from the geographic distribution of poor persons 

just described can be noted. First, with the two single-dollar thresholds, 

the South's share of poor school-age children does not significantly 

decrease. Also under these two poverty measures, fewer' North Central, 

Northeastern, and Western states experience an increase in their share of 

poor school-age children than experience an increase in their share of all 

poor persons. 

Second, the relative measures based on median incane, which have very 

little impact on the geographic distribution of the tot a1 poverty population, do affect the geographic distribution of poor school-age children. 

Under these definitions of poverty, the South's share of poor school-age 

children declines relative to its share under the current poverty measure. 

Many Southern states experience significant losses; only the District 

of Columbia significantly increases its share of poor school-age children 

with the unadjusted 50 percent of median income, and only Delaware does 

so with the two adjusted relative measures. States in the North Central, 

Northeast, and Western regions generally increase their share of poor 

school-age children under these relative measures, frequently significantly. The relative measure defined as 50 percent of the median income 

of a nonfarm family of four with a male head and two children (adjusted 

for family size and composition with the equivalence scale in the current 

poverty matrix) produces the largest regional differences of these three 

measures. Under this measure, the South's share of poor school-age children is reduced by 7 percent; the share in the North Central and Northeast 

regions is increased by 10 percent and 8 percent, respectively. Only the 

West does not appreciably change its share under this measure. 

In addition to the regional patterns, it can be observed that the 

more populated states as a group increase their share of poor persons more 

than other states as the poverty lines are increased. When the poverty 

lines are set at 150 percent of the official thresholds, the national poverty rate is increased by 10.4 percentage points; however, over half of 

this increase is attributable to low-income persons living in the eleven 

most populated states. As a group, these states contain 48 percent of the 

poverty population under the current poverty thresholds and 51 percent of 

the poverty population under the thresholds set at 150 percent of the 

current thresholds. 
Share 

Ratio 

Northeast 

1.10 Share 

West 

.95 

m 

.90 - Z 

Z 0 

1.25 

1.20 

1.15 

1.10 

1.05 

Scaling Simplifications Single- Relative 

of Current of Current Dollar Poverty 

Measure Measure Cutoffs Measures 

SOURCE: Special tabulations by the Census Bureau from the 1:100 Sample of the 1970 

Census of Population. 

Figure .l4. Regional Share of Poor 'School-Age Children 

Under A1 ternat ive poverty Definitions 

as a Ratio of Regional Share Under Current Poverty Definition, 1969 

- 

- 

0 . 

1.250 

- 

- - 

North Central 

- 

1.127 

1.053 

1.00 - 

.995 

.95 - 

.90 - wmoo 

,5 ,. m .N .* h 3 

0 -l 10 

;/ N 

NNN 

em :, 3 

M 

:/ d 
NOTE TO CHAPTER V 

1. This chapter draws heavily from an analysis found in Technical 

Paper XVIII, Characteristics of Low-Income Populations Under ~lternative 

Poverty Definitions,,prepared by Lawrence Brown. 
VI. ANALYTIC AND STATISTICAL AGENDA 

In. Chapter IV, it was noted that some poverty definitions cannot be 

constructed from existing data. Even modest increments to existing surveys 

and statistical series may not provide the data needed to make geographic 

adjustments to the poverty cutoffs; to establish or routinely update the 

poverty cutoffs on the basis of housing, transportation, medical, and 

other needs of the poor; to more accurately measure income and to measure 

in-kind income other than food stamps; or to count and characterize the 

poverty population in small areas (school districts, cities, counties) at 

time intervals of less than ten years. Moreover, analytic studies must 

be undertaken before such surveys can be used in measuring poverty or for 

such other purposes as modifying the administrative structure of- social 

programs or performing economic impact analyses. This chapter describes 

research and statistical activities which could lead to improved poverty 

measurement. The importance attached to particular types of poverty 

definitions or their attributes will determine whether such efforts should 

be pursued. 

It is difficult to predict the cost and time necessary to canplete 

research and statistical projects. Effective projects depend on cooperat ive efforts among Federal departments, agencies and other components of 

government and the private sector. Furthermore, the analytic studies 

discussed here are more likely to be useful for improving our poverty 

measure if they are performed in consultation with those performing 

poverty-related analyses and program administration. The major Federal 

executive departments and agencies involved in poverty measurement and in 

the analytic and statistical activities discussed in this chapter are 

represented on the Poverty Studies Task Force which prepared this report. 

For surveys bearing on poverty measurement, the Federal departments, 

state and local governments, and the public generally depend on Federal 

statistical agencies, particularly on the Bureau of Labor Statistics and 

the Bureau of the Census. I 

1 Analytic Studies 

I Educational Disadvantage 

The Preface discussed significant on-going research related to identifying and characterizing poor and needy children eligible for assistance 

under Title I of the Elementary and Secondary Education Act (as amended), 

as well as to evaluating the effectiveness of compensatory education programs. This research will make it possible to compare economic need and 

educational disadvantage, to test the feasibility of alternative techniques 

to estimate the numbers of poor children within counties and school districts, and to simulate the effects of alternative allocative criteria and 

formulas on the Title I program. These studies will aid in assessing the 

importance of analytic studies and survey efforts for Title I purposes. 
Settine a Povertv Level 

Public Policy on Poverty Levels 

The selection and use of one or more poverty levels for programmatic 

purposes is essentially a policy judgment. Analyses could sharpen the 

intuition of public officials by arraying the implications of various 

approaches. Some of the key issues that are susceptible to policy 

analysis are: given program objectives, what population de finit ions are . 

most appropriate? What are the implications of constructing poverty lines 

for program purposes di f ferentl y for the employable and unemployable, aged 

and young, healthy and disabled? If an absolute need standard is derived, 

which programs designed to help the needy are now serving or not serving 

them? 

Scientific Standards 

The development of accepted standards of need for shelter, transportation, medical care, clothing, and other essential elements of expense 

might eliminate some of the subjectivity in current definitions. If the 

relationships between these expenses and good health, safety and other 

seemingly objective norms could be established, such standards could be 

combined with price and income data for reasonably comparing the extent 

of poverty from place to place and over time. Unfortunately, even such 

rigorously defined standards would be based in part on judgment. For 

example, good health and safety cannot be defined absolutely, and equally 

nutritious food plans can be constructed for a very wide range of cost 

levels. Although it is unlikely that rigorously defined standards of need 

can be developed in the near future, the potentials of such standards suggest that efforts might be directed towards resolving the relevant analyt ic 

issues. 

Market Basket Studies 

Lacking scientific standards, more arbitrary and subjective market 

baskets or multipliers might be developed. 1tems not listed might be 

assigned a cost dictated by analytic techniques which generally depend on 

preconceived notions of an adequate total income level. An example is the 

Department of Agriculture' s thrifty food plan which chooses and prices 

food items after examining actual food buying patterns as well as nutritional standards. -The cost of shelter might be set by stipulating a 

percentile in the distribution of market values for rental units of a . 

given size, and medical care could be priced at prevailing rates of 

medic a1 insurance . 

An examination of consumption and: expenditure pat terns of families 

with incomes near the currently defined poverty cutoffs might prove a useful description of the style of life which can be supported at low-income 

levels. A similar analysis could be made of expenditure patterns of those 

components of t,he population which are disproportionately represented in the 
low-income levels, such as the elderly, minorities, families with a disabled head, and female-headed families. This could contribute to an 

understanding of the specific needs of these groups as compared to the 

population as a whole. Such analyses, however, would be difficult with 

currently available expenditure data. 

Standards Based on Consensus 

Setting an income level to divide the poor from the non-poor necessarily involves significant elements of subjectivity. The problem can be 

approached systematically, however, so that the subjectivity is documented 

explicitly rather than implicitly. Some believe that the use of public 

opinion methods might also assist in determining a consensus on the 

appropriate level. One might also appraise the various legislative and 

administrative eligibility criteria and program benefit levels to determine 

whether an implicit consensus about the overall level of need can be derived from them. However, the latter approach might be misleading because 

such levels were never intended to be used for such a purpose, because 

they are widely and sometimes deliberately inconsistent, and because 

virtually all methods of weighting them are arbitrary. 

Adjustments for Family Size and Composition 

The development of a complete market basket of goods and services as 

a poverty threshold would provide a basis for varying the bundle by family 

size and composition. Without such a market basket, other methods for 

determining equivalent incomes must be used. Both the relevant attributes 

and the size of adjustments need to be determined. Because no currently 

proposed methodology (including the current procedure) is completely satisfactory, an examination of both theoretical and empirical constructions 

of equivalence scales is desirable. 

Geographic Cost-of-Living Differences 

The limitations in the analysis of geographic cost-of-living differences have been discussed in earlier sections of this report. A range of 

survey activities to overcome the scarcity of data is discussed later in 

this chapter, and analytic studies which must be performed before geographic variation can be introduced are described below: 

1. An analysis of the feasibility of undertaking data collection on 

a scale necessary to derive accurate estimates of geographic differences 

for policy and administrative purposes. 

2. An assessment of the reliability of alternative methodologies 

for developing equivalent levels of satisfaction, development of a theoretical or empirical framework for assessing the basic reasons underlying 

observed differences in living costs across geographic divisions or 

boundaries, and an analysis of how differences in the choice of goods 

affect expenditures in different areas. The analysis should include an 
assessment of the effect on area differences in living costs due to 

unavailability or significantly lower quality of services such as major 

health facilities or public services. 

3. An analysis of price differences between areas based on a lowincome level market basket (since there is evidence that geographic price 

differences vary according to the cost level of market basket choices). 

4. An exploration of special problems associated with surveying the 

prices faced by the low-income population such as comparing goods of 

different age, quality and characteristics. 

5. An analysis of the administrative and economic impact of adjusting 

poverty lines .for geographic differences and the degree to which ruralurban, interregional and other population migrations are affected. 

Updating the Poverty Cutoffs 

All types of poverty definitions require periodic updating for changes 

in prices over time. A special poor person's price index may be better 

than currently available indexes if the appropriate market basket items are 

identified and priced. The techniques for developing such an index currently exist. The required expanded expenditure and price surveys are 

discussed later in this chapter. 

Income and Resources 

A New Income Survey, which is described later in this chapter, would 

provide more accurate information on income and resources. Such information might also allow alternative income and resource definitions using 

different accounting periods or "income items" not possible with current 

data. In addition to new survey information, several analytic studies 

are required if the definition of income is to be altered. These include 

a study of the proper valuation of in-kind benefits, of means of collecting 

household information on benefits other than food stamps, of after-tax 

income, of possible adjustments for wealth, and ,of the development of a 

methodology for collecting information about yealth. 

Surveys 

Analytic studies may indicate that geographically sensitive and more 

accurate thresholds cannot be developed without a geographically sensitive 

pricing suryey, a low-income consumption survey, a household food consumption survey, and an expanded income survey. However, there is no way to 

assure tnat new surveys can correct all of the difficulties of' deriving 

such thresholds. Each of the surveys is expensive either on a one-time or 

recurring basis, but the costs depend on the amount of geographic and other 

detail required. The initial costs are greater, of course, than those of 

repeating the survey. It should be added tnat such surveys would be useful 

for purposes other than improved poverty measurement. Defining the appropriate survey package therefore requires more analytical work. 
New Income Survey 

The specific objectives of a New Income Survey might be to provide: 

(1) more accurate estimates of the income distribution by reducing the 

underreporting of cash incomes at the extremes of the income distribution 

and by including as much non-cash income and unr.ealized income from assets 

as possible as part of the income estimates; (2) the collection of intrayear income information to obtain data that more closely approximate 

accounting periods associated with some Federal programs and to minimize 

respondents' recall difficulties ; and (3) the measurement of assets and 

various criteria of need so that better estimates of the number of persons 

eligible for participation in major programs can be made and so that a 

relationship between wealth, income, and poverty can be better assessed. 

It is also desirable, although expensive, to collect longitudinal data and 

data capable of producing statistically reliable state or other subnational 

area estimates of key characteristics. 

A New Incane Survey would be helpful in overcoming limitations in 

existing data sources by providing more accurate and detailed statistics 

on income, assets, and eligibility for and participation in major Federal 

transfer programs. In addition to providing more accurate estimates of 

the poverty population, the survey data could provide information for 

assessing the impact of pres'ent and proposed Federal programs. 

Estimates of the annual cost of such a survey range .between $10 and 

$15 million. The two main factors associated with total cost are the size 

of the longitudinal canponent and the capability of producing reliable 

subnat ional estimates. A survey capable of producing nationally representative data and which includes a relatively small longitudinal panel 

would cost about $5 million. The higher funding levels could yield state 

estimates and would contain a larger longitudinal canponent. 

Initial development of such a survey is now being undertaken within 

the Office of the Assistant Secretary for Planning and Evaluation in the 

Department of Health, Education, and Welfare. Expansion of the survey to 

produce state estimates could take place after 1980. The planning and 

design work associated with the Survey of Income and Education which was 

legislatively mandated by PL 93-380, section 822, has served as a useful 

stimulus for the development of the income survey. 

Geographically Sensitive Pricing Survey 

A geographically sensitive pricing survey would provide price data 

for canparing the prices of such items as food, shelter, clothing and 

medical services, between geographic areas and over time. The data 

collected frm the pricing survey, in conjunction with data from a proposed low-income consumption survey, may enable such comparisons to be 

based on the market baskets of goods and services purchased by the lowincome population. The survey probably could be an augmentation -- in 

terms of area coverage, reference population, and additional price data 
necessary for inter-area canparisons -- of the BLS Consumer Price Index 

price collection program. 

 he poverty line or income standards cannot be adjusted for differences in living costs or price levels among areas and for area changes in 

living costs or price levels over time, until reliable consumer price data 

are collected by geographic area. On an area basis, such data may also 

aid in analyzing price behavior in different geographic areas during 

periods of unusual changes in economic conditions, and in evaluating the 

differential economic impact of Federal programs. 

The BLS Consumer Price Index price collection program could probably 

serve as the basic vehicle for collecting time series data for the pricing 

survey. Research and testing must be per formed, however, before attempting 

to add areas such as "rural areas" to the program and before attempting to 

integrate the collection and compilation of the consumer price data necessary for inter-area canparisons. 

The cost of a geographically sensitive pricing survey could be very 

high -- some multiple of the BLS survey depending on the degree of detail 

planned. The BLS revised CPI program (which will estimate price indexes 

for 2 types of families for the urban U.S., for 28 major urban areas, and 

12 areas classified by region and size of area) costs approximately $40 

million for the revision process al.one and $7 million annually to maintain 

a monthly pricing program. 

Low-Income Consumption Survey 

A low-incane consumption survey resembles the consumer expenditure 

surveys which collect data on actual expenditures of American families and 

which have been conducted approximately every ten years by the Bureau of 

Labor Statistics. These surveys differ primarily in sample size and composition. The survey could probably supplement the new BLS continuing 

consumer expenditure survey, however, which is currently being planned and 

which is tentatively scheduled to begin in fiscal year 1979. Research 

could begin immediately on developing a sample and survey design appropriate for collecting information on low-income families living in specified 

areas. Although the cost of such a survey cannot be estimated at this . 

time, it is estimated that the BLS continuing consumer expenditure survey 

program will cost $6 million annually to maintain and would have to be 

expanded considerably in size to provide accurate break-outs by income and 

family size. It might also be important to mount separately or concomitantly surveys of families participating in specific programs like food 

stamps, AFDC, unemployment insurance or others, to see the impact of such 

programs on consumption patterns. The educational characteristics of 

children frm low-income families might be another important component .' 

Household Food Consumption Survey 

A nationwide study of household food consumption that provides detailed 

information on the kinds and- amounts. of foods used and prices paid for foods 
by the total household and the food intake of individuals within the 

household is required for the development of realistic standards of food 

needs, such as the Department of Agriculture food plans. The most recent 

such study was conducted in 1965-66. A new study is being planned for 

1977 at an estimated cost of $5 million. 

Summary 

Funding all of these activities could lead to more accurate and current definitions of poverty. The costs are high, however, and decisions 

on whether any of them should be undertaken depend on the value attached 

to the analytical or administrative uses to be made of the data. The 

greatest expense would be incurred in developing sufficient information 

to permit counting the poor by state more frequently than once every ten 

ye ars . 
VII. PROGRAM IMPACT 

This chapter examines the effects on Federal programs of changing the 

poverty measures and updating the poverty count. The precise impacts of 

changes in poverty measurement are difficult to estimate, since they will 

depend in large part upon subsequent decisions within the legislative and 

executive branches. A full discussion of the factors that would affect 

these decisions is beyond the scope of this study. The following discussion is therefore presented for illustrative purposes. The first part 

describes in general terms the effects of a change on all major Federal 

poverty-related programs, assuming that no offsetting changes in law or 

regulation were made. The second part presents the results of a quantitative analysis of the effects on the program of financial aid authorized by 

Title I of the Elementary and Secondary Education Act of 1965 as amended by 

the Education Amendments of 1974. 

General Program Impact 

It is important at the outset to distinguish between changes in the 

officially designated poverty matrix and changes in one of the specific 

administrative income eligibility standards or poverty measures that: can 

be developed through the adaptation of the existing data series. Changing 

the officially designated poverty matrix could affect the way both the 

government and the general public view poverty, which could in turn affect 

how the nation sets its goals in attempting to eliminate or reduce the 

extent of poverty. 

It is helpful when considering the direct impact of a change in the 

official poverty series, to' distinguish between programs that identify 

poverty of the target population by means of the official series from programs that use other income tests or income levels to identify the target 

population. Such programs as the food stamp program, Title I1 of the 

Housing and Community Development Act of 1974, the Supplemental Security 

Incme Program, Aid to Families with Dependent Children, Title XX of the 

Social Security Act, and Medicaid belong to the latter category. Except 

for the food stamp program, which partially uses the official poverty 

series, a change in the series would have no direct impact on these programs as they are currently defined. An indirect impact may result from 

the fact that many planners at both the Federal and state levels instinctively look to the Federal poverty matrix for guidance in setting the 

income levels for such programs or in interpreting how effectively these 

programs reach needy populations. 

There are many reasons why income transfer programs, such as Aid to 

Families with Dependent Children and Supplemental Security Income, are 

not tied directly to the poverty line. Program parameters such as benefit 

reduction (tax) rates or basic benefits or allotments determine levels of 

incane at which persons are no longer eligible for program benefits. The 

setting of these parameters will depend upon specific program goals such 

as the provision of work incentives. Imposing a cutoff of benefits at the 
poverty line independent of the parameters of the program produces a sudden 

decrease in benefits as a person's income reaches the poverty line. This 

effect, often called a "notch," may cause serious inequities or adversely 

affect work incentives. Most importantly, the purpose of a program may 

not be congruent with the Federal statistical definition of poverty. Moreover, there is no consensus among the public, or even among selected groups, 

that poverty generally should be eliminated regardless of cost. 

The following programs refer directly to the official poverty matrix: 

Title I of the Elementary and Secondary Education Act, 'Title I of the 

Housing and Community Development Act of 1974, the Community Services Act 

of 1974 (formerly the Economic Opportunity Act), the Comprehensive Employment and Training Act, the food stamp program, and the child nutrition 

programs of the Department of Agriculture. In addition, some health 

programs, particularly those relating to mental health and community 

health centers, and some education programs use poverty cutoffs which are 

related to the official poverty lines through administrative guidelines. 

These programs would probably be affected by a change in the offioial 

poverty statistical series. 

For these programs, two kinds of effects need to be examined: first, 

potential changes in the Federal budget and second, potential changes in 

tne characteristi-cs of the recipients of program benefits. The latter 

kind of change would generally have a greater impact and it can be gauged 

from the discussion in Chapter V of the statistical characteristics of poor 

populations under alternative poverty definitions. Only in a few large 

programs would the Federal budget be greatly affected. 

In order to understand this impact, it is necessary to recall the 

distinction made in Chapter I between programs that use a formula for the 

distribution of Federal funds and those that establish eligibility criteria 

based on the income levels. Programs with a formula for the distribution 

of funds based on the official poverty line are Title I of the Elementary 

and Secondary Education Act, Title I of the Housing and Community Development Act of 1974, and grants made to Community Melital Health Centers 

with disproportionate poverty populations in health citchment areas. A 

modification of the official poverty line would not result in a changed 

Federal budget for these programs because the standards affect the distribution of an amount of money which is fixed by authorization and appropriation. 

The poverty matrix determines the relative share of the appropriated amount 

that each state or unit of government receives. 

Similarly, tne Comprehensive Employment and Training Act distributes a 

fixed amount of funds to general-purpose governments partly on the basis of 

the number of families with incomes less than a certain amount. The funds 

are then used by the local governments to establish employment and training 

programs to serve needy individuals. A change in the threshold might change 

the composition of the population benefited but would not affect total 

expenditures. 
The following programs use the poverty series as a basis for establishing income eligibility for program assistance: food s,tamp program, 

child nutrition programs of the Agriculture Department, Title I1 of the 

Housing and Community Development Act of 1974, programs sponsored by the 

Community Services Act of 1974, the local use of funds from the Comprehensive Employment and Training Act, and various locally administered 

health and education programs. Except for the child nutrition program and 

possibly the food stamp program, the budgetary impact of a change in the 

official poverty matrix would not be great, but it is almost impossible to 

predict accurately for three reasons. First, the number of people participating in a program differs from the number of people who are eligible. 

Although the participation rate is difficult to predict, 'since it varies 

from place to place and time to time, it probably would not increase at 

the same rate as would the poverty line. Second, the eligibility criterion 

for participation in these programs is seldom based exclusively on the 

poverty thresholds. Normally, other eligibility criteria, for example, 

those relating to the employability characteristics under the Comprehensive 

Employment and Training Act, come into play. Some of these programs make 

welfare recipients automatically eligible for benefits. Finally, in some 

cases, the poverty thresholds are used to distribute to eligible persons 

limited Federal funds on a first-come, first-served basis or on a most-inneed basis. An example is the Comprehensive Employment and Training Act. 

Local governments use these funds to establish employment and training programs for eligible participants. Eligibility is based partly on the poverty 

income guidelines (as well as on other criteria) and partly on the basis of 

the amount of funds made available to them. Another example is the Community Action Agencies, which adopt the income eligibility guidelines 

published by the Community Services Administration (formerly the Office of 

Economic Opportunity) to distribute services to needy persons. 

In some programs, eligibility is open-ended, in that the benefits are 

provided to all eligible persons requesting them; such programs would force 

the Federal budget upward if the poverty line were .increased. The child 

nutrition programs of the Department of Agriculture, for example, would be 

affected significantly by an increase in the poverty line. A 25 percent 

increase in the poverty line could result in an increase of more than 30 

percent in the program budget under current law. 

A smaller effect would occur in the food stamp program because its 

income eligibility criteria already generally exceed the poverty lines for 

most family sizes. There would be a much more significant effect on the 

food stamp program if it were re-defined primarily on poverty criteria 

such as in recently proposed legislation and regulations. Obviously, the 

structure of the poverty guidelines would then be a most crucial program 

parameter. 

Generally, most of the open-ended programs are the income or in-kind 

transfer welfare programs. As mentioned earlier, these generally do not 

use the poverty matrix either for setting the incom? eligibility standards 

or the benefit levels. 
Impact on Title I of ESEA 

Background 

The Elementary and Secondary Education Act as enacted in 1965 provided 

for allocating funds to counties according to a formula that defined the 

children to be counted and the payment rate. The formula children included 

chcldren aged 5 to 17 in families with incomes under $2,000 in the 1960 

Census, all children in families with AFDC payments of $2,000 or more, as 

well as foster and institutionalized children. The payment rate was set 

at 50 percent of the state expenditure per pupil or 50 percent of the 

national average expenditure per pupil,, whichever was higher. 

Several years after the law was put into effect, it was observed that 

the formula was allocating an unexpectedly large share of the funds to the 

large urban states. Two factors canbined to bring about this result. The 

poverty population (children in families with incomes under $2,000 in 1959) 

was fixed, while the AFDC population grew each year because of rising 

payments and mushrooming caseloads, so that in 1972 the AFDC component 

constituted more than 50 percent of the eligible population canpared with 

10 percent of the total in 1965. The large urban states generally set 

higher welfare payment levels and broadened eligibility for welfare, which 

automatically increased their share of the formula funds. ~urin~ this 

seven-year period, for example, California, New Jersey, and New York more 

than doubled their percentage of the national total of Title I funds. 

The increased payments to large urban states were also due in part to 

the payment rate. Since spending per pupil in these states is characteristically higher than the national average, the effect was to systematically 

allocate higher Title I payments to the larger states. Therefore, both 

elements in the allocation formula -- the definition of the formula children 

and the payment rate -- gave benefits to the urban states that were higher 

than expected. T 

In 1974, the present allocation formula was adopted after considerable 

debate. An attempt was made to correct some of the more severe defects in 

the earlier formula, but the basic allocation procedure remained much the 

same. Children identified by the formula comprised the following three 

groups: children 5 to 17 in poor families as defined in the 1970 Census, 

two-thirds of the children in families rece iving AFDC payments exceeding 

the poverty line, children institutionalized either because of neglect or 

delinquency, and children in foster homes supported with public funds. 

The payment rate was also revised. Theminimum rate was set at 40 

percent of 80 percent (i.e., about one-third) of the national average expenditure per pupil, and the maximum rate was set at 40 percent of 120 percent 

(i.e., about one-half) of the national average. In addition, each county 

was guaranteed a payment of at least 85 percent of the payment received in 

the preceding year, a provision referred to as the "floor" and as the "hold 

harmless" provision. I 
An analysis of the impact of changing the poverty definition was 

carried out by calculating the allocation of $1.5 billion in Title I funds 

in 1975 under the 13 definitions of poverty defined in Chapter V. (Data 

were from the-one percent sample of the 1970 Census.) A concomitant change 

was made in the AFDC population above the poverty line to reflect the change 

in the level of the poverty definition. All 13 poverty concepts were 

tested, and 5 of them are discussed here in detail: the current measure, 125 

and 150 percent of the current measure, a single poverty threshold based 

on half of the national median family income, and a single poverty threshold 

based on the poverty threshold for a nonfarm family of four. The results 

for most of the other poverty definitions fall somewhere within the range of 

the 5 presented here. 

i 

There is good reason to be concerned about allocating Title I funds 

in 1975 on the basis of the 1970 Census estimates of the number of poor 

children in each state. During the past few years, the nation has suffered 

a recession which has undoubtedly affected some parts of the country more 

than others. The current allocation formula assumes that the distribution 

of poor children by state is the same today as it was in 1970, which is 

unlikely. To test this assumption, allocations based on the 1970 Census 

estimates were compared with the allocations based on estimates of the 

number of poor children by state for 1973, the most recent year for which 

such estimates could be made. Two estimates for 1973 were used: one by 

the Bureau of the Census and the other by the Regional Economic Analysis 

Division (READ) of the Department of Commerce. The methods used are described in a paper by Herman Miller and Abdul Khan, "Methodology for Estimating the Number of Children in Poverty for States and Counties," to be 

published in the near future by the Bureau of the Census. 

In analyzing the impact of revised poverty definitions and of updating 

the count, the basic tabulations were performed assuming that the current 

allocation formula was unchanged. In order to identify separately the 

effects of various canponents of the formula, additional tabulations were 

made to explore the impact of: the hold harmless provision (the 85 percent 

floor); omitting the AFDC children; and omitting the AFDC children and the 

CEPP factor. The use of current expenditures per pupil (CEPP) as a basis 

for allocating Title I funds is a very important element in the current 

formula, As noted above, the eligible population in each state is multiplied by 40 percent of CEPP in the state (with a minimum of about one-third 

of the national average and a maximum of about one-half of the national 

average) to arrive at the dollar entitlement for each state. A measure of 

the effect of CEPP can be obtained by comparing the amount each state would 

receive if funds were allocated only on the basis of the number of poor 

children, with the amount the state receives using both CEPP and the number 

of poor children. As will be noted subsequently, CEPP has a much greater 

influence on the allocation of Title I funds than any of the other factors 

in the present formula. 

The results of the analysis of the impact on the Title I program of 

changing the definition of poverty, and taking into account the other 

factors just naned, are presented in several stages: 
. A sketch of the results based on five states representing 

differences in various regions and in size of population. 

. A detailed analysis for all states of the impact of changing 

the definition of poverty. 

. A detailed analysis for all states of the impact of updating 

the 1970 Census estimate of the number of poor children. 

. An analysis of the impact of revising the allocation formula. 

. An analysis of the joint impact of changing the poverty definition 

and simultaneously updating the 19 70 Census count . 

I Impact on Selected States 

Before turning to the detailed tables, it is useful to consider how 

changes in the definition of poverty or in the various components of the 

Title I formula might affect the allocation of funds in 1975. One large 

state was selected for each region of the country (California, Illinois, 

New York, and North ~arolina), and Mississippi was selected as a low-income 

Southern state. An examination of the detailed figures for these five 

states provides a better understanding of the more canprehensive analysis 

presented later in this chapter, of the results for all states. Table 23 

shows the impact on the allocation of funds for these five states of 

changes in the formula, of updating the count of poor children, and of 

retaining or eliminating the hold harmless provision. Similar data are 

shown in Table 24 for the same states, measuring the impact of a change in 

the poverty definition. 

Column 3 of Table 23 indicates that, under the current formula, New 

York received $191.0 million in Title I funds in 1975. Using the same 

foxmula without the floor, New York would have received only $169.9 million 

(column 1). Indeed, in 1975 the floor served to take a little away from 

most other states and give it to New York. Note that three of the other 

five states would have received slightly more funds without the floor than 

\ with it. \ 

. A canparison of columns 1 and 2 shows the impact of updating the count 

'of poor children. If the current formula had been used, but only the count 

ofpoor children updated, New York would have received $194.5 million rather 

than $169.9 million. This same change would increase the funds going to 

California, but it would have decreased the funds going to Illinois, North 

Carolina, and Mississippi. A more detailed examination of the data for 

all states will show that such a change would in fact increase the allocation to nearly all of the largest states, largely reflecting a redistribution of poor children among states during recent years. 

An examination of column 1, lines 1 through 3 for each state shows the 

impact of other changes in the allocation formula on the Title I allotments. 
Table 23. Impact of Changes in the Allocation Formula 

on the Distribution of Title I Funds, 1975 

(Millions of dollars) 

State and Allocation 

Formula 

New York: 

b Current formula 

CEPP and Poverty only 

Poverty only 

Illinois: 

Current formula b 

CEPP and Poverty only 

Poverty only 

California: 

b Current formula 

CEPP and Poverty only 

Poverty only 

North Carolina: 

b Current formula 

CEPP and Poverty only 

Poverty only 

Mississippi: 

b Current formula 

CEPP and Poverty only 

Poverty only 

Allocations W 

1970 CIP~ 

hout Floor 

1973 CIP 

Allocat ior 

1970 CIP 

With Floor 

197.3 CIP 

$ 197.7 

193.0 

187.6 

74.5 

69.2 

66.8 

133.9 

126.3 

. 118.8 

45.1 

46.2 

48.8 

33.4 

35.0 

37.7 

SOURCE: Special tabulations prepared by the National Center for Education Statistics. 

a CIP represents the number of children in poverty. 

The current formula evidences CEPP, the number of children in AFDC families 

with incomes above the poverty line, and the number of children in poverty. 

Estimated actual allocation in 1975. 

Under the current formula, New York would have received $159.9 million, 

assuming no floor. If the AFDC population with incomes above the poverty 

line were excluded from the formula, the allocation of funds to New York 

would have dropped sharply to $131.5 million. If the funds were alloted 

only on the basis of the number of poor children, New York's allotment 

would again have been cut sharply to $102.5 million. Changes of a similar 

nature may be noted for Illinois and California. The picture is quite 

different, however, in North Carolina and Mississippi. These Southern 

states would receive substantial increases in funds if the allocation were 

based entirely on the count of poor children.. These differences largely 

'reflect the higher expenditures per pupil in the larger states and their 

more generous AFDC payments. 
Table 24-. Impact of Alternative Definitions of Poverty 

on Allocation of Title I Funds, 1975 

(~il lions of dollars) 

New York: 

d 

Current formula 

CEPP and Poverty only 

Poverty only 

Single Poverty Line 

b $4795 1 $374; 

State and Allocation 

Formula 

Illinois: 

d 

Current formula 

CEPP and Poverty only , 

Poverty only 

Current 

Povertye 

Concept 

California: 

Current formula d 

CEPP and Poverty only 

Poverty only 

125% of 

Current 

Poverty 

Line 

North Carolina: 

150% of 

Current 

Poverty 

Line 

d 

currdnt formula 

CEPP and Poverty only 

Poverty only 

Mississippi: 

d 

Current formula 

CEPP and Poverty only 

Poverty only 

SOURCE: Special tabulations prepared by the National Center for Education Statistics. 

a These figures differ from the corresponding figures in Table VII-1 because 

they are based on tabulations for states, whereas the data in Table VII-1 

are based on county tabulations summarized to state levels. 

50% of the U.S. median family income in 1969. as indicated by the 1970 

Census. 

Weighted average poverty threshold for nonfarm 4-person family in 1969. 

The current formula includes CEPP, the number of children in AFDC families 

with incomes above the poverty line, and the number of children in poverty. 

Table 24 shows the impact of a change in the poverty measure on the 

allocation of Title I funds among the. 5 states. Five different poverty 

concepts are considered: The current poverty concept, 125 percent and 150 

percent of the current poverty line, a single poverty threshold based on 

one-half of thz U.S. median family income in the 1970 Census ($4,795), and 

a single poverty threshold based on the poverty threshold for a nonfarm 

four-person family in 1969 ($3,748). The two single poverty thresholds 

were selected to show the differential impact of vastly simplified poverty 

concepts selected at different points on the income distribution. 
If the current allocation formula is used, but the poverty line is 

increased by 125 percent or 150 percent, New York would have an appreciable reduction in funds. This is primarily because the influence of the 

AFDC add-on would disappear. The other 4 states, however, would not be 

as significantly affected. An examination of the figures for all states 

will show that most of them would not be appreciably affected by such a 

change in the poverty concept. More significant is the fact that a 

simplified poverty concept based on half the U.S. median family income, 

without adjustment for family size and canposition or farm-nonfarm 

residence, would also not appreciably change the allocation of Title I 

funds among any of the states shown in Table 24 (except New York) , nor, 

as we shall see later, would it appreciably change the amount of funds 

received by most states. In other words, we could achieve largely the 

same distribution of Title I funds we now have by using other poverty 

concepts. 

A single poverty threshold selected somewhat lower on the income 

distribution (column 5) would alter the allocation of funds appreciably, 

primarily because of its impact on the AFDC population. If the poverty 

threshold for'a nonfarm family of four persons were used as the single 

poverty threshold for all families, New York would receive $188.6 million 

rather than $173.3 million. Illinois and California would also have 

substantial gains if such a change were made, whereas North Carolina and 

Mississippi would have slight reductions. The reason for these changes . 

is that as the poverty line is lowered, more AFDC families are included 

in the eligible population. Such families are disproportionately located 

in the high-income Northern states. It is especially significant that 

excluding the AFDC population from the formula (i.e., allotting funds 

on the basis of CEPP and poverty only), would not cause the amount of 

funds received by each state (except ~ississippi) to vary appreciably 

under any of the poverty definitions. 

Impact of Changing the Poverty Definition 

Table 25 shows, for each of the 50 states and the District of Columbia, a comparison of the Title I funds received under the current 

poverty concept with the funds that would be received if the poverty 

line were increased by 25 percent or 50 percent, and commensurate changes 

were made in the number of AFDC children above this new poverty line. 

For purposes of analysis, four different groupings of states have 

been established, based on size: (a) the 12 largest states -- these states 

have over 5 million inhabitants and receive about 55 percent of the 

Title I funds; (b) 12 moderately large states -- these states have 3-5 

million inhabitants and receive about 25 percent of the Title I funds; 

(c) 14 moderately small states -- these states have 1-3 million inhabitants and receive about 15 percent of the Title I funds; and (dl the 13 

smallest states -- these states each have less than 1 million inhabitants 

and receive about 5 percent of the Title I funds. 
Table 25. Comparison of Title I Funds 

That Would be Received Using 125% and 150% of the Present Poverty Line 

with the Amount That Would be Currently Received 

 illi ions 'of dollars; assumes a total allocation of $1.5 billion) 

12 Largest States 

State 

California 

New York 

Pennsylvania 

Texas - 

Illinois 

Ohio 

Michigan 

New Jersey 

Florida 

Massachusetts 

Indiana 

North Carolina 

12 Moderately Large States 

Current 

Definition 

(1) 

Missouri 

Virginia 

Georgia 

Wisconsin 

Tennessee 

Maryland 

Minnesota 

Louisiana 

Alabama 

Washington 

Kentucky 

Connecticut 

14 Moderately Small States 

Increased Poverty Line 

125% 150% 

(2) (3) 

Iowa 

South Carolina 

Oklahoma 

Kansas 

Mississippi 

Colorado 

Oregon 

Arkansas 

Arizona 

West Virginia 

Nebraska 

Utah 

New Mexico 

Maine 

13 Smallest States 

Absolute Chanee 

(2-1) (3-1) 

Rhode Island 

Hawaii 

New Hampshire 

Idaho 

Montana 

South Dakota 

North Dakota 

Delaware 

Nevada 

Vermont 

Wyoming 

Alaska 

Washington, D.C. 

SOURCE: Special tabulations prepared by the National Center for Education Statistics. 

154 

Relative Chanee 

2x10~ 

1 

3x100 

1 
A 25 percent increase in the poverty line would produce a sharp 

reduction in the funds going to several of the large states and, with a 

few exceptions, would redistribute these funds to the rest of the country. 

The big losers would nearly all be concentrated in the 12 largest states. 

They include New York, with a cut of $20 million or 12 percent; Illinois 

(-$6 million or 7 percent); Michigan (-$6 million or 9 perkent); 

California (-$4 million or 3 ~ercent); and New Jersey (-$2 million or 4 

percent). Three other states would have losses of $1 million (~ouisiana, 

Alabama and ~ississi~~i). Most of the other states' would receive s1Yght 

to moderate gains. 

With few exceptions, the pattern described above would prevail if 

the poverty line were raised by 50 percent. In most cases the changes 

resulting from a 50 percent increase are in the same direction, but larger 

than those resulting from a 25 percent increase. 

Table 26 shows for each state the change in the allocation of funds 

if the poverty concept were based on two different single thresholds: 

one-half the U.S. median family income in 1969 ($4,795) and the poverty 

threshold for a nonfarm family of four persons in 1969 ($3,748). If the 

higher threshold were used, the results would be very similar to those 

obtained using the current concept. The allocations to only 7 states 

would differ by more than 10 percent of the present allocation, and most 

of these differences would be in the smaller states, representing relatively small amounts of money. If the lower threshold were used, most of 

the largest states would have gains in funds, largely at the expense of 

Southern states. Included among the heavy losers would be Texas, Florida, 

North Carolina, Missouri, Virginia, Georgia, Tennessee, Louisiana, 

Alabama, Kentucky, South Carolina, and Mississippi. The reason for this 

change, as previously explained, is that the lower poverty line would 

include more of the AFDC children among the eligible population under 

the Title I allocation formula. Most of these children live in the large 

Northern states. 

Impact of Updating the Poverty Count 

Table 27 shows the amount of Title I funds each state would receive 

in 1975 with no change in the allocation formula, with a replacement of 

the 1970 Census estimate of the number of school-age children in poverty 

with the Census estimate for 1973, and with a replacement of the 1970 

Census estimate with the estimate for 1973 prepared by the Regional 

Economic Analyses Division (READ). The first three columns of this 

table show the funds, in millions of dollars each state would receive, 

assuming a total allocation of $1.5 billion. Column 4 shows the ratio 

between the amount received using the READ estimate of poor children in 

1973 and that received under the current formula; column 5 replaces the 

READ estimate with the Census estimate for 1973. 

These data show that the substitution of current estimates of children in poverty for the 1970 Census estimates, with few exceptions, 
Table 26. Comparison of Title I Funds 

That Would be Received Using a Single Poverty Line 

with the Amount That Would be Currently Received, 1975 

 illio ions of dollars; assumes a total allocation of $1.5 billion) 

12 Largest States 

California 

New York 

Pennsylvania 

Texas 

Illinois 

Ohio 

Michigan 

New Jersey 

Florida 

Massachusetts 

Indiana 

North Carolina 

12 Moderately Large States 

State 

Missouri 

Virginia 

Georgia 

Wisconsin 

Tennessee 

Maryland 

Minnesota 

Louisiana 

Alabama 

Washington 

Kentucky 

Connecticut 

Current 

Poverty 

Definition 

(1) 

Single Poverty Line Difference 

14 Moderately Small States 

Ratio 

$4,795 a 

(2) 

(2-1) 

Iowa 

South Carolina 

Oklahoma 

Kansas 

Mississippi 

Colorado . Oregon 

Arkansas 

Arizona 

West Virginia 

Nebraska 

Utah 

New Mexico 

Maine 

x 100 1 $3,748 

(3) 

(3-1) 

13 Smallest States 

-? x 100 1 

Rhode Island 

Hawaii 

New Hampshire 

Idaho 

Montana 

South Dakota 

North Dakota 

Delaware 

Nevada 

Vermont 

Wyoming 

Alaska 

Washington, D.C. 

SOURCE: Special tabulations prepared by the National Center for ducat ion Statistics. 

a 504 of 1969 U.S. median family income as indicated by the 1970 Census. 

Weighted average poverty threshold for nonfarm 4-person family in 1969. 
Table 27. Title I Funds to be Received by Each State in 1975 

Using Current Allocation Formula and 

Alternative Estimates of Children in Poverty 

 illio ions of dollars; assumes a total allocation of $1.5 billion) 

State 

12 Largest States 

Current Allocation Formula 

Using 1969 Estimates of 

Children in Poverty 

(1) 

California 

New York 

Pennsylvania 

Texas 

Illinois 

Ohio 

Michigan 

New Jersey 

Florida 

Massachusetts 

Indiana 

North Carolina 

Current Allocation Formula 

Using 1973 Estimates of 

Children in Poverty 

READ Census Bureau 

estimates estimates 

(2) (3) 

12 Moderately Large States 

Missouri 

Virginia 

Georgia 

Wisconsin 

Tennessee 

Maryland 

Minnesota 

Louisiana 

Alabama 

Washington 

Kentucky 

Connecticut 

14 Moderately Small States 

Iowa 

South Carolina 

Oklahoma 

Kansas 

Mississippi 

Colorado 

Oregon 

Arkansas 

Arizona 

West Virginia 

Nebraska 

Utah 

New Mexico 

Maine 

13 Smallest States 

Rhode Island 

Hawaii 

New Hampshire 

Idaho 

Montana 

South Dakota 

North Dakota 

Delaware 

Nevada 

Vermont 

Wyoming 

Alaska 

Washington, D.C. 

SOURCE: Special tabulations prepared by the National Center for Education Statistics. 

15 7 
transfers funds from the smaller rural states to the large industrial 

states. Although there are some differences between the Census Bureau and 

the READ estimates, both sets of data support\this conclusion. This change 

undoubtedly reflects the fact that the slow economic growth experienced in 

the United States between 1969 and 1973 had a much greater negative impact 

on the large industrial states than it had on the smaller ones. As a 

result, relatively more of the nation's poor children in 1973 were located 

in the large states than was the case in 1969. There is no logical basis 

for retaining the 1970 Census count of children in poverty in the allocation formula. This procedure was used because it was not considered 

likely that up-to-date county estimates of children in poverty would be 

available. The data in Table 27 suggest that if more recent data were 

available, the Title I funds received by most of the larger states would 

increase considerably. 

Focusing attention on the Census estimates for t*he 12 largest states 

in Table 27, we find that 'two states would receive reductions in funds 

if the current estimates of children in poverty were used (Texas and 

North Carolina), one state would have no change (Pennsylvania), one state 

would have a mall increase (Ohio), and eight states would have increases 

ranging from 5 to 22 percent (Florida, New York, Indiana, Illinois, 

Michigan, Massachusetts, California, and New Jersey). 

The picture is somewhat different among the 12 moderately large 

states, those with 3-5 million inhabitants. Among these states, we find 

only three with substantial gains in Title I funds if current estimates of 

children in poverty were used (Connecticut, Washington, and ~aryland) , and 

seven states with losses (~issouri, Virginia, Georgia, Kentucky, Tennessee, 

~ouisiana, and Alabama). 

One of the 14 moderately small states with 1-3 million inhabitants 

(Arizona) would gain in Title I funds if the current estimates of children 

in poverty were used. Each of the other states in this group would lose 

funds. The losses would be less than 10 percent ,in Oklahoma, Colorado, 

Oregon, and Maine; between 10 and 20 percent in Iowa, South Carolina, 

Kansas, Mississippi, Arkansas, Nebraska, Utah, and New Mexico; and greater 

than 20 perc,ent in West ~ir~inia. 

The estimates shown in Table 27 for the 13 smallest states are considered too weak to be analyzed meaningfully because of the very small 

size of the CPS sample in those states. Reasonably reliable estimates for 

these states will not be available until after the Survey of Income and 

Education is canpleted in 1976. Y aImpact of Changing the Allocation Formula 

. . In contrast to the relatively minor changes that can be noted in most 

states if the poverty line is increased even by as much as'50 percent, very 

sharp changes can be noted in most states if the basic allocation formula 

itself is changed. Table 28 shows the change that would take place if the 
Table 28. Comparison of Title I Funds 

That Would be Received Under Alternative Allocation Procedures 

with the Amount That Would be Currently Received 

No Change in Poverty Definition; No Change in Allocation Formula; 

States Olange in Allocation Formula to Increase in Poverty Line by: 

Poverty onlya 25 percent 50 percent 

12 Largest States 

California 

New York 

Pennsylvania 

Texas 

Illinois 

Ohio 

Michigan 

New Jersey 

Florida 

Massachusetts 

Indiana 

North Carolina 

12 Moderately Large States 

Missouri 

Virginia 

Georgia 

Wisconsin 

Tennessee 

Maryland 

Minnesota 

Louisiana 

Alabama 

Washington 

Kentucky 

Connecticut 

14 Moderately Small States 

Iowa 

South Carolina 

Oklahoma 

Kansas 

Mississippi 

Colorado 

Oregon 

Arkansas 

Arizona 

West Virginia 

Nebraska 

Utah 

New Mexico 

Maine 

13 Smallest States 

Rhode Island 

Hawaii 

New Hampshire 

Idaho 

Montana 

South Dakota 

North Dakota 

Delaware 

Nevada 

Ve mn t 

Wyoming 

Alaska 

dasbington, O.C. 

106 

108 

LOO 

107 

10 1 

107 

104 

97 

97 

98 

103 

102 

SOURCE: Special tabulations prepared by the National Center for Education Statistice. 

Note: Each column represents a ratio of the amount that wuld be received using the specified 

definition to the amount that would be received under the current definition. 

a The numerator of the ratio shown in this col- represents the amount each state would 

receive if the current poverty definition were used; but the allocation was baaed only 

on the number of poor children and not on the current formula. The denominator represents 

the amount each state could receive using the current definition of poverty and the current 

allocation formula. 
current allocation formula were replaced with a formula that allocates 

Title I funds solely on the basis of the number of children in poverty 

as reported in the 1970 Census. If such a change were made, most large 

industrial states would receive a sharp reduction in Title I funds, and 

most smaller rural states would receive a sharp increase in such funds. 

This change is due largely to the elimination of current expenditures per 

pupil from the allocation formula. Using CEPP to determine funding tends 

to transfer funds from those states with large proportions of poor children to those that make relatively large expenditures per capita on 

education. 

Among the 12 largest states, three would have reductions of 20 to 30 

percent (~assachusetts, Pennsylvania, and ~llinois); and three would have 

reductions of 30 to 40 percent (New York, Michigan, and New Jersey). The 

three states in this group that would gain the most are in the South: 

Florida, with a gain of 22 percent, and North Carolina and Texas, each 

with gains of 32 percent. 

Changes of a similar magnitude would be found among the 12 moderately 

large states. The 7 Southern states in this group would all have gains 

ranging from 20 to 40 percent, whereas 5 states (only one of which is in 

the south) would have substantial losses. Among the 12 moderately small 

states, all but Oregon would have an increase in funds. Among the 13 

smallest states, about half would gain, and half would lose funds. 

Of all the factors considered, it appears that the allocation formula 

itself, and particularly current expenditures per pupil, exerts the 

greatest impact on the allocation of Title I funds. The greatest change 

in the allocation of funds among states would take place if the funds were 

allotted on the basis of the number of children in poverty rather than 

according to the present formula. If the present formula is retained, an 

increase in the poverty line would have a relatively minor impact on the 

allocation of Title I funds; .however, an updating of the number of children 

in poverty would appreciably increase the funds going to the larger states 

and would decrease those funds going to the smaller states. 

Joint Impact of Changing the Poverty Definition and 

Updating the Poverty Count 

In the preceding sections, attention was focused on the impact of 

a change in the definition of poverty or an update in the count of poor 

children. We shall now examine the impact of a joint change in these 

variables. Table 29, column 3, shows the Title I allotments to each state 

in 1975, assuming a 25 percent increase in the poverty line and using the 

1973 estimated number of poor children. These figures are compared with 

the amounts each state would receive if the current formula were used with 

the 1969 estimate of poor children, and if the current formula were used 

with the 1973 estimate of poor children. 
Table 29. Title I Funds to be Received by Each State in 1975 

Using the 1973 Count of Children in Poverty and 

a 25 Percent Increase in the Poverty Line 

 illio ions of dollars; assumes a total allocation of $1.5 billion) .. . 

12 Largest States 

California 

New York 

Pennsylvania 

Texas 

Illinois 

Ohio 

Michigan 

New Jersey 

Florida 

Massachusetts 

Indiana 

North Carolina 

State 

12 Moderately Large States 

Current 

Formula, 

1969 Estimate 

of CIP a 

(1) 

1973 Estimate of CIP 

Current Current Formula 

Formula Using 125% of 

Poverty Line 

(2) (3) 

Missouri 

Virginia 

Georgia 

Wisconsin 

Tennessee 

Maryland 

Minnesota 

Louisiana 

Alabama 

Washington 

Kentucky 

Connecticut 

Difference 

(2-1) (3-1) 

14 Moderately Small States 

Iowa 

South Carolina 

Oklahoma 

Kansas 

Mississippi 

Colorado 

Oregon 

Arkansas 

Arizona 

West Virginia 

Nebraska 

Utah 

New Mexico 

Maine 

13 Smallest States 

Rhode Island 

Hawaii 

New Hampshire 

Idaho 

Fontana 

South Dakota 

North Dakota 

Delaware 

Nevada 

Vermont 

Wyoming 

Alaska 

Washington, D.C. 

SOURCE: Special tabulations prepared by the National Center for Education Statistics. 

a CIP represents children in poverty. 16 1 
The change in both variables would, with some important exceptions, 

have the same impact as that previously described for updating of the 

poverty count alone. That is, there would be a transfer of funds from 

the small states to the large ones. Among the 12 largest states, 8 would 

receive an increase in funds, the same number as that previously noted 

for a change in the poverty count albne. New York, an important except ion, 

would have gained considerably £run an update of the poverty count alone, 

but would lose slightly if both variables were changed at the same time. 

Illinois and North Carolina would also lose considerably if both variables 

were changed at the same time. The gains for the other large states were 

largely offset by declines in most of the 12 moderately large states and 

in nearly all of the moderately small states. On the other hand, most of 

the 13 states with less than 1 million inhabitants would gain as a result 

of this change; however, these changes are subject to large errors of 

estimation. 

* US. GOVERNMENT PRINTING OFFICE : I976 0-214-412