Low Benefit Recipiency in State

Unemployment Insurance Programs

by

 Wayne Vroman

The Urban Institute

June 2001
Acknowledgements

This is a final report prepared under a task order contract with the Office of Workforce

Security of the U.S. Department of Labor. John Trutko and Steve Woodbury participated in the

site visits to states described in Chapter VI. Several professional staff in the states visited

provided valuable information. The state staff who helped during the project are too numerous to

thank individually. If there are errors in the site visit summary, however, the responsibility is not

theirs. Edgar Lee provided helpful research assistance. 

Many staff at the Office of Workforce Security (OWS) of the Employment and Training

Administration contributed importantly to the report. Several OWS staff provided helpful

comments on the first draft of the report. Esther Johnson, Chief of the Division of Research and

Reporting, provided support throughout the project. Crystal Woodard, the OWS technical

representative, was helpful during all stages of the project. Opinions expressed in this report are

those of the author and do not necessarily reflect the opinions of the U.S. Department of Labor or

the Urban Institute. 
Table of Contents

Page

 Executive Summary i

 Introduction 1

 I. Background 3

 II. Time Series and Interstate Variation in Recipiency 8

Aggregate Measures of Recipiency 8

Recipiency in National Time Series Data 9

Interstate Variation in Benefit Recipiency 14

III. Low Benefit Recipiency: An Accounting Framework 22

An Accounting Identity Decomposition of the WBTU Ratio 22

The Four Accounting Identity Ratios in National Data 26

Accounting Identity Ratios by State 28

Geographic Patterns of Low Recipiency 33

Indicators of UI Administrative Activities 36

Recipiency and Administrative Measures for Six Groups of States 40

Summary 43

IV. Measurement Issues 44

Key Definitions 44

Partial Unemployment Benefits 46

State Border Issues 50

Reason for Unemployment 63

Unemployment Duration 68

 V. Determinants of the Accounting Identity Ratios 78

Determinants of the Application Rate, the ICNU Ratio 78

Determinants of Repeat Applications, the NICIC Ratio 84

Determinants of the First Payment Rate, the FPNIC Ratio 89

Relative Duration in UI Benefit Status, the ADUIAD Ratio 93

Summary of the Regression Analysis 102
Table of Contents (continued)

VI. State Site Visits 104

Selection of States for Visits 105

Administrative Diversity 108 

Information to Claimants About UI Benefits 111

Claims Filing, Specialized Claims and Claimants in Special

Circumstances 115

Factors in Initial Eligibility 120

Continuing Eligibility, Appeals and Claimant Satisfaction Surveys 128

Summary 134

VII. Regression Analysis of Three UI Administrative Variables 136

Monetary Eligibility Rates 137

Separation Determinations 142

Evidence of Stringency in UI Program Administration 148

Summary 153

 VIII. Summary and Conclusions 155

 

References 162

List of Abbreviations 164
List of Tables

Page

Table II-1 Summary of Aggregate Recipiency Ratios, 1967 to 1998 15

Table II-2 Average WBTU Ratios by State for Selected Periods, 1967 to 1998 18

Table III-1 Summary of Average UI Flows, States Sorted by Average 

WBTU, 1977 to 1998 29

Table III-2 Indicators of Administrative Activities, States Sorted by Average

WBTU, 1977 to 1998 37

Table III-3 Average Recipiency Measures and Administrative Measures for

Six Groups of UI Programs, 1977 to 1998 41

Table IV-1 Partial Weeks and STC Weeks as a Percentage of Total Weeks 

Compensated, 1998 48

Table IV-2 Intrastate and Interstate Weeks Compensated by State, 1996, 1997 

and 1998 51

Table IV-3 Estimated Effect of Commuter Claims on IUTU Ratios in Three 

States, 1998 and 1999 57

Table IV-4 Prevalence of Combined Wage Claims, 1996-1998 60

Table IV-5 Total Unemployment and Job Loser Unemployment by State, 

1978-1999 Averages 65

Table IV-6 Measures of Average Unemployment Duration, 1950 to 1999 70

Table V-1 Determinants of ICNU, the Ratio of Initial Claims to New Spells of

Unemployment 81

Table V-2 Determinants of NICIC, the Ratio of New Initial Claims to Initial 

Claims 85

Table V-3 Determinants of FPNIC, the Ratio of First Payments to New Initial 

Claims 90

Table V-4 Determinants of Average Duration in UI Benefit Status, ADUI 95

Table V-5 Determinants of Average Unemployment Duration in CPS Data, 

AD and ADPUB 98

Table V-6 Determinants of Relative Unemployment Duration, ADUIAD 100

Table VI-1 States Considered and States Selected for Site Visits 106 

Table VI-2 Information About Unemployment Insurance Benefits Available to 

Unemployed Workers 113

Table VI-3 Main Methods of Claims Filing, Specialized Claims and Claimants 

in Special Circumstances 116

Table VI-4 Monetary and Nonmonetary Provisions Affecting Entry Eligibility 121

Table VI-5 Determinants of Continuing Eligibility, Appeals and Claimant 

Satisfaction Surveys 129
Table VII-1 Factors Related to Monetary Eligibility Rates 140

Table VII-2 Determination Rates for Voluntary Quits and Misconduct 145

Table VII-3 Comparison of Average Errors for Monetary Eligibility and 

Separation Determinations by State and Division 149

List of Charts and Maps

Chart II-1 IUTU Ratios and WBTU Ratios, 1947 to 1999 10

Chart II-2 IUTU Ratios and WBTU Ratios, Five Year Averages, 1947 to 1999 11

Chart II-3 Ratio of Weeks Paid to Weeks Claimed, 1947 to 1999 13

Chart II-4 Average WBTU Ratios by Time Period, States Sorted by WBTU 

Ratio 1967-98 19

Chart III-1 Accounting Identity Ratios, National Data, 1967 to 1998 27

Chart IV-1 Actual and Simulated Application Rates 69

Chart IV-2 Average Unemployment Duration, Centered Five Year Averages,

 1952 to 1997 74

Chart IV-3 Indices of Duration and Exhaustions, 1950-1999 76

Chart VII-1 Monetary Eligibility, 1967 to 1999 138

Chart VII-2 States with Durational Penalties 143

Map 1 WBTU Ratios, 1967-1998 Average 21

Map 2 Rates of Inflow into Benefits 34

Map 3 Low Recipiency in Three Groups of States 35
i

Executive Summary

When workers become unemployed they often apply for and receive Unemployment

Insurance (UI) benefits. Across the United States, there is wide variation from state to state in UI

application rates, the rate of first payments to applicants and duration in UI benefit status. The

project studied the explanation for the wide interstate variation in the receipt of UI benefits. In

addressing this question, particular interest centered on states where recipiency is significantly

lower than the national average.

Several factors operative in the states could explain why recipiency is so varied. The

project focused on two broad sets of factors: 1) differences in state labor markets and 2)

differences in aspects of UI programs such as their statutes, administrative activities and methods

filing for benefits. The analysis found both sets of factors contributed to differences in the receipt

of UI benefits across states. 

Considering the findings from all parts of the project, three main conclusions are drawn. 1)

Variation in UI benefit recipiency can be productively studied, and the analysis indicated that low

recipiency is systematically linked to variables that reflect UI statutes and administrative

operations as well as differences in features of state labor markets, e.g., unionization. 2) Varying

rates of inflow into benefit status generally have larger effects on overall benefit recipiency than

variation in duration of benefit receipt. The application rate (applications as a share of new onsets

of unemployment) and the first payment rate (first payments as a share of new initial claims), two

of the three inflows studied, are most closely linked to overall recipiency as measured by the

WBTU ratio (weekly UI beneficiaries as a proportion of weekly unemployment). 3) The

misconduct determination rate has an especially large effect on all three ratios linked to inflows

into UI benefit status. Developing a more detailed understanding of why misconduct

determination rates are so varied across states would seem to be especially important.

The research documents variation in UI recipiency rates examining two state-level

measures, IUTU ratios (weekly UI claimants as a proportion of weekly unemployment) and

WBTU ratios (weekly UI beneficiaries as a proportion of weekly unemployment). Focusing

primarily on WBTU ratios, it summarizes state-level data for the years since 1967. Long run

averages of WBTU ratios exceed 0.40 in some states while in others WBTU ratios have averaged

less than 0.20. The patterns of low (or high) recipiency are shown to persist in individual states

for multiyear periods. Low (or high) recipiency is also shown to have a clear regional pattern.

Among the states with low recipiency, three distinct patterns were identified. 1) In five

widely dispersed states, low recipiency is associated with both a low inflow rate into benefits and

short benefit duration. 2) In nine states, mainly in the southwest, the inflow into benefits is very

low but duration is long, higher than the national average. Because the inflow rate is so low, the

result is low recipiency. 3) In five southeastern states, the inflow into benefits is average but

benefit duration is very short, partly because recipients are still job-attached. Employer filing is

common in these states, and it has a large effect on the pattern of UI recipiency. It is associated

with high application rates, low first payment rates, short benefit duration and low determination
ii

rates for voluntary quits and misconduct. These consequences all follow from a situation where

many claimants are still job-attached. In states with a significant volume of employer filing, the UI

program experiences an especially fast flow-through of claimants compared to other states.

The project followed two approaches in studying the explanation for low recipiency.

Inferences are drawn from multiple regressions and related analyses and from information

gathered during site visits conducted in nine states. Because the methodologies used in the two

approaches are so different, exact comparisons of their findings are somewhat difficult to make.

However, the two approaches did yield some common findings. The regressions and the site visits

identified aspects of UI statutes, program administration and methods of claims filing that

significantly affect recipiency.

While a wide array of factors related to UI programs cause interstate differences in

recipiency, two are most important. 1) The inflow into benefit status is particularly sensitive to the

rate at which UI agencies make determinations on the issue of misconduct. High misconduct

determination rates are systematically associated with low inflows into UI benefits. 2) Duration in

benefit status is sensitive to agency activities that reflect the frequency of nonseparation

determinations and the frequency of eligibility reviews. In states where these activities occur with

high frequency, benefit duration is significantly shorter than in other states. In summary, data

reflecting aspects of UI administrative activities are systematically linked to the likelihood of

receiving UI benefits and to the duration of benefits. 

The regression analysis, one of the two research approaches, was conducted using an

accounting framework developed within the project. The regressions used pooled state-year data

and examined three ratios related to the inflow into benefit status and a fourth ratio linked to

unemployment duration. The regressions included both macro-labor market variables and

variables reflecting UI statutes, administrative activities and methods of filing for benefits. The

labor market variables and the UI variables both made important contributions to the explanation

of interstate variation in recipiency.

The regressions explaining the application rate, the inflow variable with the widest range

of interstate variation, found it depends heavily on the misconduct determination rate. Methods of

filing initial claims other than in-person filing were found to increase application rates with the

biggest effect caused by employer filing. The base period earnings requirement and the partial

benefits share also made significant contributions to explained variation. The repeat application

rate was found to depend on the misconduct determination rate as was the first payment rate (first

payments as a proportion of new initial claims). Also important in explaining interstate variation in

the first payment rate were the net liable-agent claims differential, the monetary eligibility

proportion and the misconduct denial rate. 

For explaining inflows into benefit status, the largest effect was found for the misconduct

determination rate. High misconduct determination rates were associated with low application

rates, low repeat application rates and low first payment rates. In short, all three facets of claimant

inflows into benefits were reduced by a high misconduct determination rate. 

Relative unemployment duration, i.e., duration of UI benefits relative to overall

unemployment duration, was strongly linked to potential UI benefit duration, the partial benefits

share, the nonseparation determination rate, the nonseparation denial rate, the rate of eligibility
iii

reviews and the proportion of continued claims filed by employers. The negative effects of the

nonseparation determination rate and the eligibility review rate on relative duration show that

active administration of continuing claims significantly shortens average duration. 

The preceding findings were all drawn from multiple regressions that also included large

and significant effects of macro and labor market variables, e.g., capacity utilization, the job loser

share of new unemployment spells and the unionization rate. Even controlling for obvious factors

in the macro-labor markets of the states, UI program variables had important effects on all aspects

of UI recipiency. 

While the findings of the site visits were more qualitative than quantitative, several

patterns were identified that differentiated four high recipiency states from five low recipiency

states. Seven specific findings were the following. 1) High recipiency states have made much

more accommodation to non-English speakers in filing for UI benefits. 2) Requirements for

monetary eligibility are generally easier to satisfy in high recipiency states. This encompasses

lower monetary thresholds (measured relative to the average weekly wage), the absence of added

monetary requirements, having alternative earnings requirements, offering an alternative base

period (monetary eligibility based on more recent earnings than used in standard eligibility

determinations) and offering short-time compensation (or worksharing which allows some work

and receipt of benefits in the same week). Monetary eligibility proportions averaged 0.90 in the

four high recipiency states but only 0.81 in the five low recipiency states while the national

average proportion was 0.86. 3) Rates of adjudication on separation issues, both quits and

misconduct, are generally lower in states with high recipiency. 4) Quits are more likely to be

compensated in high recipiency states. 5) Disqualifying and deductible income denials are less

frequent in high recipiency states. 6) Eligibility reviews generally occur less frequently in high

recipiency states while penalties for failure to meet reporting requirements have more “teeth” in

low recipiency states. 7) Rates of employer appeals of nonmonetary determinations are much

lower in high recipiency states, less than half the rate of appeals in low recipiency states. While the

separate contributions of these individual factors are difficult to estimate, all operate to reduce

recipiency in the states with low recipiency.

The research also addressed the issue of UI administrative stringency using three

administrative measures important in determining the inflow of claimants into benefit status: the

monetary eligibility proportion, the voluntary quit determination rate and the misconduct

determination rate. These were examined with a series of multiple regressions. The patterns of

average residuals from the regressions were then compared. Probably the most important finding

of this analysis was that low benefit recipiency, as signaled by the WBTU ratio, was negatively

associated both with the voluntary quit determination rate residuals and with the misconduct

determination rate residuals. In other words, low benefit recipiency was systematically associated

with higher than expected determination rates for both voluntary quit and misconduct issues. 

In conducting the research for the project, several questions were encountered that

seemed fruitful areas for further research. The final chapter identifies and briefly discusses some

suggested topics for further research.
Introduction

This report examines the following question: why does the receipt of unemployment

insurance (UI) benefits vary so widely across individual states within the United States? Especially

strong interest centers on states where UI recipiency has been and remains very low. To the

extent that research on this question is successful, it will improve our understanding of this

phenomenon and will identify changes that could increase UI recipiency rates. 

The report has eight chapters. Chapter I introduces the topic and briefly discusses earlier

research. Chapter II reviews aggregate time series evidence on UI recipiency and describes

patterns of interstate variation. Chapter III introduces an accounting framework to help in

understanding why recipiency varies so widely across states. Chapter IV investigates several

measurement issues related to UI recipiency. Chapter V reports the results of a multiple

regression analysis of recipiency carried out within the accounting framework introduced in

Chapter III. Chapter VI summarizes the findings of site visits conducted in nine states. States

were visited to develop a better understanding of differences in UI administrative processes and

statutes, and, more important, to identify key differences in laws and program administration that

contribute to low recipiency. Chapter VII conducts a regression analysis of three key measures of

UI administration: the monetary eligibility rate, the voluntary quit determination rate and the

misconduct determination rate. It finds evidence of linkages between both determination rates and

low UI benefit recipiency. Chapter VIII gives a summary of the findings, draws conclusions and

makes suggestions for future research.

The principal conclusions of the investigation can be stated at the outset. 1) Differences in

laws and administrative practices make an important contribution to interstate differences in UI

recipiency rates. States with low recipiency have requirements in the areas of monetary eligibility

and nonmonetary eligibility that, on average, are more difficult to satisfy than are the 

requirements in states with high recipiency. 2) No single factor seems to be the key which

differentiates states with low recipiency from states with high recipiency. Rather, it appears

several different factors combine to produce low recipiency. Individual factors are found to be

differentially important when overall recipiency is broken down into four constituent parts.

Factors related to entry into benefit status are distinguishable from factors that affect UI benefit
2

duration. 3) Of all the explanatory factors that contribute to low recipiency, the misconduct

determination rate makes the largest single contribution. States with high misconduct

determination rates have especially low levels of recipiency. The misconduct determination rate

operates through three channels of UI recipiency: the application rate; the repeat application rate;

and the ratio of first payments to new initial claims. All three are systematically lower in states

with above-average levels of misconduct determinations.
1

 See for example Wandner and Stengle (1997)

2

 An illustration of time series variation in IUTU ratios between 1947 and 1996 is given in

Chart 1 of Vroman (1998). See also Charts II-1 and II-2 in Chapter II of this report. 

3

Chapter I. Background

The fraction of unemployed workers who receive benefits from the state unemployment

insurance (UI) programs in the U.S. varies widely from year to year and from state to state. The

most common indicator of benefit recipiency is often termed the IUTU ratio, a shorthand

reference to the ratio of insured unemployment (IU, the number with active claims or in receipt of

benefits) to total unemployment (TU, the total number unemployed including new entrants into

the labor force, labor force reentrants and job leavers as well as job losers). While the IUTU ratio

is the most widely used indicator of UI benefit recipiency, other measures also exist.1 One

indicator, the WBTU ratio (the ratio of weekly UI beneficiaries to weekly unemployment), is

accorded special prominence in the present research. 

The IUTU ratio has displayed a wide range of variation through time and across states.

During the 1950s the IUTU ratio averaged roughly 0.50 nationwide. Two subsequent time

periods witnessed major reductions in the IUTU ratio. The ratio declined by roughly ten

percentage points between 1960 and 1967. This reduction has been attributed mainly to the

change in the demographic mix of unemployment with the influx into the labor force of young

workers of the baby boom generation and increased labor force participation of adult women,

groups that have below-average UI recipiency rates. The second period of reduced recipiency

occurred in the early 1980s, a reduction due in part to problems of state trust fund insolvency

which were widespread between 1980 and 1985. Since the mid 1980s, the nationwide IUTU ratio

has been quite stable, in the 0.30-0.36 range, with a higher level observed in 1991, a recession

year.2 Chapter II reviews national developments in recipiency over the past 50 years.

Systematic measurement of IUTU ratios at the state level has been possible only since the

late 1960s. Starting in 1967, the monthly household labor force survey (the Current Population
3

 The derivation of these estimates is described in Vroman (1992).

4

 There is probably sizeable variation in recipiency within states. The report does not

address this issue. 

4

Survey or CPS) was restructured to produce representative estimates of total unemployment and

unemployment rates for the nine major census divisions and for ten large states. State

unemployment and labor force detail in CPS was subsequently expanded to 30 states in 1970 and

to all states in 1976. This project utilizes estimates of total unemployment by state developed by

the principal investigator and extending back to 1967 for all states.3 Thus the maximum available

time series of annual data by state is the 33 years from 1967 to 1999.

For as long as measurements have been possible, IUTU ratios have been observed to differ

markedly from one state to the next. One illustration of this interstate variability is given in Chart

5 of a recent report by Vroman (1998). For the years 1967, 1977, 1987 and 1996 IUTU ratios in

three states (Massachusetts, New Jersey and Pennsylvania) all ranged between 0.40 and 0.70

while in three other states (Texas, Florida and Virginia) the corresponding ratios ranged between

0.15 and 0.25. Chapter II examines this interstate variability in greater detail.4

Two of the primary objectives of state UI programs are: 1) to provide short-term

protection against wage loss due to unemployment; and 2) to provide automatic or built-in

stability to the macro economy through automatic increases in total payouts during recessions.

Both objectives are more successfully achieved when IUTU ratios are higher and the

countercyclical payouts from UI trust funds are larger.

This project examined the factors that affect UI benefit recipiency in the states. Interest

centered particularly on situations of low recipiency and the explanation of low recipiency.

However, to better understand low recipiency, the analysis encompassed all state programs so

that low recipiency was examined within a comparative framework that also included states with

high benefit recipiency. 

Concern about low UI recipiency has been present for nearly two decades. The U.S.

Department of Labor supported two large investigations of this topic in the 1980s. Reports by

Burtless and Saks (1984) and Corson and Nicholson (1988) focused on the explanation for the
5

decline in recipiency in the early 1980s. Other researchers such as Blank and Card (1991), Bassie

and McMurrer (1997), and Wandner and Stengle (1997) have also explored this issue. The most

recent analysis of UI recipiency was undertaken by Wittenburg, et.al. (1999). A selected review

of earlier research was undertaken in the present project, and this review influenced the project’s

data collection activities. Wittenburg, et.al. (1999) reviews this literature. 

The approach of most of the earlier literature has had a time series orientation. Within

pooled state-by-year data, the explanatory variables that entered the specifications included

variables from state labor markets, state UI program variables and other factors such as taxation

of UI benefits, the changing geographic distribution of the U.S. labor force, the solvency of UI

trust funds and unionization.

Because the preceding studies have not been fully successful in explaining time series and

interstate variation in benefit receipt, the U.S. Department of Labor has also supported two other

projects that conducted interviews with unemployed persons in the monthly household labor force

survey (CPS). In 1989-1990 and again in 1993, special supplements to the CPS were mounted.

For unemployed persons in outgoing rotation groups, a set of additional questions was asked that

probed issues of application for and receipt of UI benefits. Reports that summarize these

investigations were authored by Vroman (1991), Horvath (1996), and Wandner and Stettner

(2000). These studies utilize micro data to investigate reasons for nonfiling, information not

routinely available in studies that utilize time series data by state from the CPS and from UI

program data. Two main reasons for nonfiling revealed by these studies were: 1) “did not work

enough” and 2) “quit last job,” respectively monetary and nonmonetary reasons that disqualify

persons from eligibility during their current spells of unemployment. 

These studies based on CPS micro data also were helpful in showing differences in receipt

of UI benefits according to the reason for unemployment (job loser, job leaver, reentrant, and new

entrant) and unemployment duration. Job losers and those with long duration were more likely to

receive benefits than others. While these studies are helpful for understanding the nonfiler

phenomenon, e.g., only about half of job losers file for benefits and much higher proportions of

nonfilers are observed for other “reasons for unemployment,” the underlying data bases were too
5

 Some detail at the level of the nine census divisions are displayed in Vroman (1991). 

Table 8 of this report also shows varying rates of interstate claims by region. In 1989 the highest

rates of interstate claims occurred in the South and Mountain divisions (six to nine percent) while

the lowest rates occurred in the New England and the Mid Atlantic divisions (two to three

percent). 

6

 See Table 5 in Vroman (1998).

6

small to support a state level analysis.5 Thus, reasons for low recipiency in individual states could

not be systematically examined in these data.

Low benefit recipiency especially among low-wage workers was examined by the

Advisory Council on Unemployment Compensation (ACUC) (1996). The Council identified

several situations leading to nonreceipt of benefits among persons who quit jobs for personal and

family reasons, part-time workers, and workers paid low wage rates with low base period

earnings. The ACUC made several recommendations for increasing access to benefits, and these

recommendations continue to be actively discussed within the U.S. Department of Labor. 

Nonstandard employment is an important and growing phenomenon in the U.S. labor

market. A growing number of workers work either short hours or in situations where the

traditional long-term employment relationship does not pertain. An analysis by Vroman (1998),

developed a taxonomy of nonstandard employment situations, examined their prevalence, and

noted receipt of UI benefits by workers in nonstandard situations. The scope of this analysis

covered part-time work, independent contractors, temporary help, and other contingent workers.

Among temporary help employees, occurrences of unemployment are frequent, and receipt of UI

benefits is below-average. Part-time workers also have below-average recipiency rates. The other

groups generally did not have low recipiency rates.6

The low rate of UI benefit recipiency continues to be a major policy concern at the U.S.

Department of Labor (DOL). The Government Performance and Results Act (GPRA) as applied

to DOL includes a performance measure related to UI recipiency. For Fiscal Year 2000, the UI

program was to achieve an increase in the share of the unemployed receiving UI benefits. Lowwage and part-time workers are two groups of special concern. 

During the year 2000 the National Association of State Workforce Agencies (NASWA)
7

led an effort involving business, labor, state agencies, U.S. Department of Labor and other

interested groups to develop a “consensus” package of UI/ES program reforms. The package

addressed concerns about financing, benefits and program administration. Two proposed changes

in UI benefit availability would require states to adopt an Alternative Base Period (or ABP,

effectively recognizing more recent earnings than in the usual base period) and to improve access

to benefits among part-time workers. If these proposed changes were enacted, they would raise

UI recipiency. Chapter VI of this report discusses the ABP and benefit availability for part-time

workers in the states selected for site visits.
7

 Regular UI refers to the program that can pay up to 26 weeks of benefits in most states.

It is state financed. Other UI payments not considered here include payments from the programs

for federal employees (UCFE), ex-servicemen (UCX) and long-term benefits paid through the

Federal-State Extended Benefits program (EB), and periodic emergency federally-financed benefit

programs (most recently EUC, Emergency Unemployment Compensation).

8

Chapter II. Time Series and Interstate Variation in Recipiency

Aggregate Measures of Recipiency

To characterize low benefit recipiency it will be helpful to introduce three measures of

unemployment and unemployment benefit status. Each of the three can be measured as a weekly

average for a given year. 

TU = the weekly average of total unemployment. This is most often measured as the simple

average of the twelve estimates from the monthly household labor force survey (CPS). 

IU = the weekly average of the number of regular UI claimants.7 This number includes both

persons in UI benefit status and persons who have been determined eligible for benefits

but have not received a first payment. 

WB = the weekly average of the number of regular UI beneficiaries. This number excludes

persons serving a waiting period and persons serving disqualification periods. It shows the

actual weekly number of recipients.

By convention among researchers, the most common measure used to characterize UI

benefit recipiency has been the ratio of IU to TU, hereafter IUTU. Literally, this ratio shows the

number of persons actively claiming regular UI benefits as a proportion of the number

unemployed as measured in the CPS. 

Note that in terms of strict accuracy, the ratio of WB to TU shows the fraction of the

unemployed actually receiving benefits. In recent years, the ratio of WB to IU has averaged 0.88-

0.90 so that use of the IUTU ratio to characterize benefit recipiency exaggerates actual recipiency

by about 10 percent. When the IUTU ratio is, say, 0.36, the WBTU ratio will be about 0.32-0.33.
8

 Exhaustees from the so called regular UI program may subsequently receive benefits

from the Federal-State Extended Benefit (EB) program or from an emergency federal program

such as Emergency Unemployment Compensation (EUC) which paid benefits between late 1991

and early 1994. As noted earlier, the present research does not address payments from these

programs or from the programs for federal employees (UCFE) or ex-servicemen (UCX).

9

 Data from CPS special supplements of 1989-1990 and 1993 suggest about half of job

losers collect UI benefits compared to only 0.10-0.15 of job leavers and labor force reentrants. 

9

While some researchers have been sensitive to the distinction between IU and WB, IUTU has

been used most often as the indicator of benefit recipiency. 

Recipients who exhaust UI benefits may remain unemployed and continue to be measured

in the CPS, i.e., included in TU. In contrast, exhaustees do not enter either IU or WB. One reason

for decreases in IUTU and WBTU ratios in later stages of recessions is that exhaustions reduce

the numerators of both ratios.8

Note also that a third ratio can be generated from these variables. The WBIU ratio

explicitly shows the ratio of persons receiving UI benefits to persons claiming benefits (or weeks

paid to weeks claimed). To the extent that claimants are in the waiting week or serving a

disqualification, they are measured in IU but not in WB and cause the WBIU ratio to be smaller

than 1.0.

Recipiency in National Time Series Data

Charts II-1 and II-2 display IUTU and WBTU ratios for the years 1947 to 1999. The

annual ratios in Chart II-1 show how volatile the ratios can be from year to year. Each of the

peaks (1949, 1952, 1954, 1958, 1960, 1971, 1975, 1980, 1982 and 1991) identifies a recession

year when the ratios rise. The increases mainly reflect a change in the composition of

unemployment during recessions. Job losers constitute an increased share of the unemployed and

of the claimant pool during recessions, and because they have the highest recipiency rate,9 this

causes the IUTU and WBTU ratios to rise.

Clearly both ratios in Chart II-1 were much higher during the early years than during more

recent years. To help make this point more clearly, Chart II-2 shows centered five year averages

of these same two ratios. This chart which removes cyclical variation via averaging
47

54

5867

75

82

91

99

0.2

0.25

0.3

0.35

0.4

0.45

0.5

0.55

0.6

Proportions

IUTU - Annual WBTU - Annual

Chart II-1. IUTU Ratios and WBTU Ratios,

1947 to 1999
49

54

5867

75

82

91

97

0.25

0.3

0.35

0.4

0.45

0.5

0.55

Proportons

IUTU - 5 Yr Avg WBTU - 5 Yr Avg

Chart II-2. IUTU Ratios and WBTU Ratios,

Five Year Averages, 1949 to 1997
10 This discussion will not attempt to be more precise on the exact size of the reductions in

IUTU and WBTU ratios (absolute or percentage) during these two periods. Earlier research has

made differing estimates. Probably the most elaborate accounting for the decline of the early

1980s was made by Corson and Nicholson (1988). Note that the decline of the early-to-mid 1960s

can be documented, but lack of data on TU by state before 1967 makes it impossible to test

hypotheses about this earlier decline using state-level data. 

11 Between 1980 and 1989 the national IUTU ratio averaged 0.333 whereas it averaged

0.343 between 1990 and 1999. The corresponding averages for WBTU were 0.291 and 0.304. 

12 Other explanatory variables were the unemployment rate and the unemployment rate

lagged one year. The sample period was 1967 to 1998 for 51 jurisdictions, the 50 states plus the

District of Columbia, for a sample size of 1632 observations. The implied elasticities of the

declines were 12.7 percent in IUTU but only 8.1 percent for WBTU. 

12

shows the large reductions of the early-to-mid 1960s and of the late 1970s-early 1980s. During

these two relatively short periods of time, both ratios declined by roughly 0.08-0.11 or some 15-

20 percent.10

Note in Chart II-2 that some recovery in the five year ratios occurred in the late 1960s, in

the late 1980s and again in the late 1990s. The time series for the IUTU and WBTU ratios shown

in both charts provides a more nuanced picture than suggested by assertions that the declines have

been a persistent phenomenon in all periods. In fact, average recipiency has been somewhat higher

in the 1990s than in the 1980s.11 

One factor not obvious in Charts II-1 and II-2 is that the ratio of beneficiaries (or weeks

paid) to claimants (or weeks claimed) has been higher in the 1980s and 1990s than in earlier

decades. Chart II-3 helps to illustrate this point showing annual data and five year averages of

WBIU ratios between 1947 and 1999. The ratios during the 1980s and 1990s have varied

between 0.87 and 0.90, considerably higher than during earlier decades.

One implication of high levels of the WBIU ratios is that the decline in IUTU ratio during

the early 1980s was larger than the decline in the WBTU ratio. This was confirmed when these

ratios were examined using time series multiple regressions. The coefficient on a 1981-1998

dummy variable was -0.046 in the IUTU regression but only -0.025 in the WBTU regression.12

An analysis of the decline in recipiency based on the IUTU ratio would show a larger decline than

an analysis based on the WBTU ratio. 
47

5867

75

82

91

99

0.81

0.82

0.83

0.84

0.85

0.86

0.87

0.88

0.89

0.9

Proportions

WBIU - Annual WBIU - 5 Yr Avg

Chart II-3. Ratio of Weeks Paid to Weeks Claimed,

1947 to 1999
13 Chart VII-1 of Chapter VII shows that the proportion of claimants who were monetarily

eligible declined sharply during 1975-1977.

14 Part of the explanation for higher WBIU ratios is the increased prevalence of durational

penalties since the late 1970s. Relatively fewer claimants served fixed and variable duration

penalties (included in IU but not in WB) during the 1980s and 1990s. See Chart VII-2 of Chapter

VII for counts of states with durational penalties from 1965 to 1999. 

14

Chart II-3 shows especially low WBIU ratios during the mid 1970s. These low ratios

coincide with the timing of the Supplemental Unemployment Assistance (SUA) program of 1975-

1978. This emergency program allowed claimants who were not eligible for regular UI benefits to

claim and receive special benefit payments. To be eligible for SUA, however, applicants had to

apply for regular UI benefits. There appear to have been enough applicants for SUA (included in

IU but not WB) to lower the overall WBIU ratio by roughly two or three percentage points.13

Chart II-3 also shows that the WBIU ratio increased by several percentage points after the

late 1940s and then decreased by even more between the early 1960s and the mid 1970s. The

explanation of these patterns lies beyond the scope of the current project. What is relevant for the

project is that since 1982 the WBIU ratio has been higher in every year than during nearly every

year of the previous three decades.14 

Interstate Variation in Benefit Recipiency

Table II-1 summarizes UI benefit recipiency by state using the three aggregate ratios

previously examined in national data, IUTU, WBIU and WBTU. The fifty states plus the District

of Columbia are arrayed in alphabetical order. For each state the table displays averages of the

three indicators over the 32 years from 1967 to 1998. 

The bottom six rows of Table II-1 provide national summaries and summaries for the

states with highest and lowest recipiency. Because the focus of the project is interstate variation in

recipiency, all entries in the summary rows as well as individual state detail are simple averages.

For a given state, each year between 1967 and 1998 was treated equally. For the national

summaries, each state was treated equally even though their economic importance
Table II-1. Summary of Aggregate Recipiency Ratios, 1967 to 1998

State IUTU WBIU WBTU

ALABAMA 0.299 0.843 0.252

ALASKA 0.533 1.048 0.563

ARIZONA 0.269 0.773 0.208

ARKANSAS 0.354 0.765 0.271

CALIFORNIA 0.410 0.885 0.363

COLORADO 0.246 0.728 0.180

CONNECTICUT 0.464 0.952 0.443

DELAWARE 0.352 1.012 0.357

DIST OF COL 0.379 0.989 0.376

FLORIDA 0.225 0.732 0.164

GEORGIA 0.257 0.870 0.224

HAWAII 0.420 0.875 0.368

IDAHO 0.397 0.757 0.301

ILLINOIS 0.379 0.883 0.333

INDIANA 0.268 0.829 0.223

IOWA 0.355 0.886 0.314

KANSAS 0.353 0.885 0.312

KENTUCKY 0.314 0.880 0.275

LOUISIANA 0.274 0.869 0.239

MAINE 0.454 0.852 0.384

MARYLAND 0.335 0.836 0.280

MASSACHUSETTS 0.517 0.879 0.454

MICHIGAN 0.385 0.839 0.321

MINNESOTA 0.385 0.883 0.339

MISSISSIPPI 0.269 0.760 0.205

MISSOURI 0.400 0.794 0.316

MONTANA 0.352 0.809 0.284

NEBRASKA 0.328 0.853 0.279

NEVADA 0.411 0.903 0.371

NEW HAMPSHIRE 0.326 0.806 0.263

NEW JERSEY 0.490 0.953 0.467

NEW MEXICO 0.269 0.774 0.208

NEW YORK 0.443 0.923 0.408

NORTH CAROLINA 0.320 0.815 0.262

NORTH DAKOTA 0.364 0.849 0.311

OHIO 0.310 0.820 0.254

OKLAHOMA 0.269 0.789 0.212

OREGON 0.434 0.829 0.360

PENNSYLVANIA 0.481 0.888 0.427

RHODE ISLAND 0.600 0.878 0.526

SOUTH CAROLINA 0.302 0.792 0.239

SOUTH DAKOTA 0.238 0.736 0.175

TENNESSEE 0.358 0.818 0.291

TEXAS 0.200 0.831 0.167

UTAH 0.310 0.830 0.256

VERMONT 0.490 0.862 0.422

VIRGINIA 0.193 0.840 0.163

WASHINGTON 0.449 0.843 0.378

WEST VIRGINIA 0.316 0.837 0.264

WISCONSIN 0.441 0.869 0.382

WYOMING 0.279 0.848 0.240

U.S.- 51 Programs 0.358 0.849 0.307

Top 13 - WBTU 0.473 0.911 0.431

Bottom 13 - WBTU 0.252 0.794 0.201

Top 13 - Col. Sort 0.478 0.930 0.431

Bottom 13 - Col. Sort 0.251 0.770 0.201

Top 13/ Bottom 13 1.908 1.207 2.148
15 Interstate claims are discussed in Chapter IV.

16 The same point can be made using correlation coefficients. The simple correlation

between the IUTU and WBIU ratios in Table 1 is 0.557 and is highly statistically significant. As

would be expected, the correlation between IUTU and WBTU is even higher (0.971). 

16

 differs widely. Thus the thirteen states with the highest IUTU ratios between 1967 and 1998 had

an average of 0.478 while the 13 with the lowest ratios had an average of 0.251. For the “typical”

state in the high recipiency group the IUTU ratio was 1.908 times the ratio for the “typical” state

in the low recipiency group.

It may be surprising to some readers that the WBIU ratios also vary measurably across

states. While the national average was 0.849 during these 32 years, averages for the highest 13

and lowest 13 states were 0.930 and 0.770 respectively. Typically, states with waiting periods of

less than one week have higher WBIU ratios. Some states like Alaska and Delaware have high

ratios because of interstate claims activity.15

Because IUTU ratios vary widely across states and because most weeks claimed are paid,

it is not surprising that the WBTU ratios in Table II-1 also display wide interstate variation. While

the national average WBTU was 0.307, the averages for the highest 13 and lowest 13 states were

0.431 and 0.201 respectively. This high-to-low contrast in 13 state averages of WBTU ratios is

even larger than for IUTU ratios (2.148 versus 1.908). On average, the states with low IUTU

ratios also have low WBIU ratios. The product of IUTU and WBIU produces wider relative

variation across states than the variation associated with IUTU alone.

This point is made in a second way in the six summary lines at the bottom of Table II-1.

The summaries display ratios for the states with the highest and lowest WBTU ratios for each of

the three overall indicators of recipiency (the second and third lines of the summary lines). In the

13 states with the highest WBTU ratios, the WBIU ratios as well as the IUTU ratios are generally

above-average.16

While the data in Table II-1 are dramatic, the volume of state detail makes it difficult to

absorb the information by simply viewing the numbers. To focus attention on interstate

differences more sharply, it will be helpful to concentrate on just a single indicator of recipiency

and to arrange states according to that indicator, not alphabetically as in Table II-1. 
17 Readers who object to using TU in measuring recipiency rates would be skeptical of

both the IUTU and WBTU ratios. See Wandner and Stengle (1997).

18 The nine divisions and their numeric identifiers in Table II-2 are as follows: New

England(1), Mid Atlantic(2), East North Central(3), West North Central(4), South Atlantic(5),

East South Central(6), West South Central(7), Mountain(8) and Pacific(9).

17

The indicator selected is the WBTU ratio. This has been less commonly used in studies of

recipiency than the IUTU ratio, but it has been selected for two reasons. First, it accurately

measures recipiency since only weeks compensated enter the numerator of the ratio.17 Second, as

will be seen in Chapter III, it can be decomposed into constituent parts that are of analytic

interest. The importance of this second point will become apparent in Chapter III. As a practical

matter, IUTU and WBTU are very closely related. Thus in Table II-1 the simple correlation

between IUTU and WBTU was 0.971.

Table II-2 displays summary data on WBTU ratios by state for selected time periods. The

states are arranged in sort order according to the average ratio for the full 32 year period 1967 to

1998. When the states are sorted in this manner, the full range of variation of WBTU ratios is

amply displayed. Averages below 0.20 characterize five states while averages above 0.40

characterize eight states.

Perhaps as surprising as this wide range of interstate variation is the comparative stability

of state-level WBTU ratios. Averages are displayed for three subperiods: 1967 to 1980, 1981 to

1988 and 1989 to 1998. This stability is illustrated in Chart II-4 which shows the three sets of

ratios by subperiod. The three sets of averages display the same overall profile. State-level WBTU

ratios have shown persistent differences for as long as measurements have been possible.

Persistence in low rates of recipiency is also illustrated in the two final columns in Table

II-2. These show respectively the number of years WBTU ratios were below 0.20 and 0.25 in

each state. The maximum number is 32, i.e., each year from 1967 through 1998. States with the

lowest average WBTU ratios also have had the largest number of years where their ratios fell

below these two fixed threshold indicators of low recipiency. 

Low recipiency has a strong regional component. Table II-2 identifies the nine “Census

Divisions” commonly used in regional analysis.18 Note that the first nine states at the top of the
Table II-2. Average WBTU Ratios by State for Selected Periods, 1967 to 1998

Years Years

State Fips Div 1989-98/ Below Below

1967-98 1967-80 1981-88 1989-98 1977-98 1967-80 0.200 0.250

ALASKA 2 9 0.563 0.570 0.554 0.562 0.606 0.987 0 0

RHODE ISLAND 44 1 0.526 0.578 0.481 0.490 0.493 0.848 0 0

NEW JERSEY 34 2 0.467 0.530 0.419 0.417 0.426 0.787 0 0

MASSACHUSETTS 25 1 0.454 0.484 0.433 0.430 0.424 0.890 0 0

CONNECTICUT 9 1 0.443 0.489 0.352 0.450 0.404 0.920 0 0

PENNSYLVANIA 42 2 0.427 0.454 0.376 0.428 0.416 0.943 0 0

VERMONT 50 1 0.422 0.419 0.408 0.438 0.421 1.046 0 0

NEW YORK 36 2 0.408 0.463 0.355 0.375 0.368 0.809 0 0

MAINE 23 1 0.384 0.414 0.339 0.378 0.365 0.914 0 0

WISCONSIN 55 3 0.382 0.371 0.335 0.436 0.394 1.176 0 0

WASHINGTON 53 9 0.378 0.375 0.327 0.423 0.366 1.128 0 0

DIST OF COL 11 5 0.376 0.374 0.359 0.392 0.380 1.047 0 1

NEVADA 32 8 0.371 0.417 0.306 0.358 0.343 0.859 0 0

HAWAII 15 9 0.368 0.366 0.352 0.385 0.362 1.053 0 0

CALIFORNIA 6 9 0.363 0.369 0.368 0.349 0.358 0.947 0 0

OREGON 41 9 0.360 0.342 0.328 0.411 0.367 1.202 0 0

DELAWARE 10 5 0.357 0.358 0.342 0.368 0.350 1.028 0 1

MINNESOTA 27 4 0.339 0.355 0.316 0.337 0.333 0.949 0 1

ILLINOIS 17 3 0.333 0.371 0.285 0.317 0.323 0.855 0 2

MICHIGAN 26 3 0.321 0.354 0.254 0.329 0.304 0.929 1 3

MISSOURI 29 4 0.316 0.368 0.256 0.290 0.286 0.789 0 4

IOWA 19 4 0.314 0.341 0.266 0.315 0.305 0.925 0 5

KANSAS 20 4 0.312 0.316 0.340 0.286 0.314 0.905 0 5

NORTH DAKOTA 38 4 0.311 0.302 0.347 0.293 0.330 0.971 0 7

IDAHO 16 8 0.301 0.278 0.317 0.321 0.317 1.154 0 5

TENNESSEE 47 6 0.291 0.324 0.233 0.290 0.275 0.893 1 8

MONTANA 30 8 0.284 0.294 0.278 0.275 0.288 0.937 0 11

MARYLAND 24 5 0.280 0.300 0.268 0.262 0.262 0.873 0 7

NEBRASKA 31 4 0.279 0.288 0.272 0.271 0.270 0.939 0 9

KENTUCKY 21 6 0.275 0.302 0.237 0.266 0.272 0.878 3 13

ARKANSAS 5 7 0.271 0.262 0.246 0.303 0.281 1.156 1 14

WEST VIRGINIA 54 5 0.264 0.293 0.255 0.231 0.270 0.788 2 18

NEW HAMPSHIRE 33 1 0.263 0.341 0.210 0.194 0.211 0.569 13 16

NORTH CAROLINA 37 5 0.262 0.263 0.259 0.263 0.261 1.000 4 16

UTAH 49 8 0.256 0.286 0.266 0.206 0.250 0.723 3 18

OHIO 39 3 0.254 0.258 0.245 0.257 0.261 0.997 4 18

ALABAMA 1 6 0.252 0.285 0.212 0.236 0.239 0.829 3 17

WYOMING 56 8 0.240 0.193 0.325 0.236 0.267 1.221 9 20

SOUTH CAROLINA 45 5 0.239 0.243 0.239 0.235 0.239 0.968 5 19

LOUISIANA 22 7 0.239 0.262 0.272 0.181 0.232 0.693 7 19

GEORGIA 13 5 0.224 0.219 0.239 0.219 0.231 0.998 12 26

INDIANA 18 3 0.223 0.257 0.196 0.198 0.202 0.771 14 22

OKLAHOMA 40 7 0.212 0.247 0.211 0.164 0.189 0.665 16 24

ARIZONA 4 8 0.208 0.217 0.200 0.201 0.193 0.924 16 28

NEW MEXICO 35 8 0.208 0.227 0.209 0.179 0.190 0.788 17 27

MISSISSIPPI 28 6 0.205 0.200 0.210 0.207 0.212 1.034 18 27

COLORADO 8 8 0.180 0.149 0.219 0.193 0.197 1.302 20 31

SOUTH DAKOTA 46 4 0.175 0.212 0.154 0.140 0.165 0.661 24 28

TEXAS 48 7 0.167 0.145 0.181 0.188 0.179 1.295 28 32

FLORIDA 12 5 0.164 0.162 0.143 0.185 0.164 1.141 28 31

VIRGINIA 51 5 0.163 0.156 0.175 0.165 0.176 1.060 27 30
1

1121314151

0.1

0.2

0.3

0.4

0.5

0.6

Avg. WBTU Ratio

1967-80 1981-88 1989-98

Chart II-4. Average WBTU Ratios by Time Period,

States Sorted by WBTU Ratio 1967-98
19 One of the multiyear averages in Table II-2 covers the years 1977 to 1998. Data from

this time period will be examined in Chapter III. 

20 Maps were created for all the WBTU averages shown in Table II-2. However, the map

showing averages for the 32 years 1967 to 1998 is the only map displayed in this report. 

21 In fact, site visits were conducted in five of the ten states where WBTU ratios averaged

less than 0.200 during 1989-1998.

20

table are all from divisions 1,2, and 9: the North East and the Far West. Conversely thirteen of the

fifteen states with the lowest ratios are from divisions 5, 6, 7 and 8: the South and the Rocky

Mountains. These geographic contrasts are observed in all data displayed in Table II-2.19

Geographic contrasts in UI recipiency are also vividly illustrated with maps. Map 1 shows

the WBTU averages during 1967-1998 for the lower 48 states (Alaska, Hawaii and the District of

Columbia are not shown). The color coding progresses from white for the highest WBTU ratios

to black for the lowest (below 0.20). Note the concentration of darker colors in the South and

Rocky Mountain states while whites are found mainly in the North East and along the West coast.

The map provides yet another representation of regional contrasts.20

Map 1 is also helpful in identifying states that are unusual relative to adjacent states. Over

the full 1967-1998 period, New Hampshire, Indiana, South Dakota and Virginia had low

recipiency compared to neighboring states while Arkansas and Wisconsin had high recipiency.

Persistently low recipiency has characterized certain states such as Colorado, Florida,

South Dakota, Texas and Virginia. For the ten year period 1989-1998 these five states plus New

Mexico, Oklahoma, Indiana, Louisiana and New Hampshire all had average ratios below 0.20.

This point is illustrated in Table II-2 in the low WBTU ratios for the full 32 years and the most

recent ten year sub-period. All of these states had at least ten years with WBTU ratios below

0.20. These same states also stand out in Map 1. Since the project is particularly concerned with

the explanation for low recipiency, it is especially important to examine these states in greater

depth.21
 Map 1. WBTU Ratios,

1967-1998 Average

0.200

0.250

0.300

0.350

0.576
22

Chapter III. Low Benefit Recipiency: An Accounting Framework

Low benefit recipiency can arise from several possible sources. Three obvious ones are: 1)

low application rates by unemployed workers, 2) low rates of awards to claimants and 3) short

durations in benefit status. These and possibly other factors could be of differing importance from

one state to the next. The starting point for disentangling different potential explanations is

provided by an accounting identity which identifies four distinct aspects of benefit recipiency. 

An Accounting Identity Decomposition of the WBTU Ratio

To help identify factors that lead to low benefit recipiency, the definitions given in Chapter

II need to be rewritten. The starting point is the WBTU ratio as shown in Tables II-1 and II-2 of

Chapter II. 

The components of the WBTU ratio can be expressed as follows. 

(1) TU = NU*AD/52

where NU is new spells of unemployment in a year (measured in the CPS as 12 times the

average monthly number unemployed less than 5 weeks), and 

AD is the average duration of the new spells, (in weeks and measured as 52*TU/NU).

AD/52 is average duration per spell expressed as a fraction of the year. 

(2) WB = IC*(NIC/IC)*(FP/NIC)*ADUI/52

where IC is initial claims (new plus additional initial claims) for UI benefits,

NIC is new initial claims for UI benefits,

FP is first payments of UI benefits (payments that signal the start of a benefit year), and

ADUI is average duration in benefit status (total weeks compensated as a ratio to first

payments. ADUI/52 is average duration per first payment measured as a fraction of the

year. 

Using terms on the right hand side of (1) and (2) and taking the ratio of (2) to (1) yields: 

(3) WBTU = (IC/NU)*(NIC/IC)*(FP/NIC)*(ADUI/AD)

The left hand side of expression (3) has WBTU, the indicator of benefit recipiency to be
22 Given the low numbers of unemployed job leavers and reentrants who receive benefits,

some have also advanced a recipiency measure that compares recipients with the number of job

losers. See Wandner and Stengle (1997). 

23

emphasized in this project. To repeat, WBTU is the weekly number of UI beneficiaries expressed

as a ratio to weekly unemployment as measured in the CPS.22

The right hand side of expression (3) shows the four explicit ratios that combine to

determine the WBTU ratio. For convenience, each will be referred to using capital letters but

dropping the division symbols appearing in expression (3).

The first term (ICNU) is the take-up rate or application rate. It shows the number who file

for benefits as a fraction of all new occurrences of unemployment. Historically, this has averaged

about 0.50 nationwide but with considerable variation across individual states. Knowledge about

people who do not file for benefits is limited, but so called “nonfilers” or “self denials,” i.e.,

people who do not file either because they believe they are ineligible or for other reasons, are

thought to be an important phenomenon. Many people do not file when they perceive they are not

eligible either due to monetary reasons (insufficient earnings and/or weeks worked in the base

period) or nonmonetary reasons (e.g., voluntarily quitting the last job). 

The second term in (3) (NICIC) shows the importance of additional claims relative to new

initial claims. To date, this has not been the subject of much research. During 1998, new initial

claims totaled about 10 million while additional initial claims totaled more than 6.5 million. Thus,

filing for benefits more than once a year is a major phenomenon in UI programs.

The third-right hand term in (3), (FPNIC), shows the fraction of new initial claims that

result in a benefit payment. This first payment ratio is less than unity partly because some people

find jobs while in the waiting week and/or the disqualification period. More important, however,

are the denials for both monetary and nonmonetary reasons. The national (FPNIC) ratio has

varied between 0.73 and 0.78 in recent years, and it also varies widely across states.

The final term in expression (3) is the ratio of the two unemployment duration measures.

Note that ADUI appears in the numerator of this ratio. States that closely monitor continuing

eligibility and/or states that have relatively less generous UI potential duration provisions could

have low average durations even though duration from the CPS (AD) is not unusually low. One
23 See U.S. Department of Labor, Employment and Training Administration (1995).

24

indication of less generous duration provisions is a low level of potential duration among those

found to be monetarily eligible for benefits. State-level information on potential duration is

available from ETA-218 reports (monetary eligibility reports) and from so called Handbook

data.23 Potential benefit duration is found to be important in the regressions of Chapter V.

All of the elements defined in expressions (1), (2) and (3) are measured at the state level in

CPS data or in federally required reports submitted by the state UI programs to the Office of

Workforce Security. Thus, the four right hand ratios in equation (3) can be derived for each state

and can be extended into the past for more than twenty years. An analysis of low UI benefit

recipiency, as signaled by a low WBTU ratio (and a low IUTU ratio), can thus decompose a low

overall ratio into the product of its four constituent parts. A low WBTU ratio in a state may arise

from different combinations of the four factors shown on the right-hand side of expression (3). 

Some additional comments about this accounting framework should be made. First, there

is a key issue about the timing of data availability. State data on WBTU, WBIU, IUTU as

examined in Chapter II are available back to 1967. However, new spells of unemployment by

state have been measured in the CPS only since 1977. Thus the right-hand elements of equation

(1), e.g., NU and AD extend back only to 1977. Consequently, the ICNU and ADUIAD ratios in

expression (3) are available only starting in 1977.

Second, accounting identity (3) has a mixture of unemployment timing measures. Some

measures pertain to individual spells of unemployment while others refer to unemployment during

a full year (where many individuals experience more than a single spell). Two of the ratios, ICNU

and FPNIC, have the same kind of timing measure in both numerator and denominator. Both

elements of ICNU are measured on a per spell basis whereas both elements in FPNIC are

measured on a benefit year basis. In contrast, NICIC has a benefit year measure in the numerator

(new initial claims) but a per-spell measure in the denominator (new plus additional initial claims).

Finally, ADUIAD has a benefit year measure in the numerator (average weeks per first payment)

but a per-spell measure in the denominator (average weeks per occurrence).

The latter two mixed measures are unavoidable since monthly CPS data measure
24 There are annual CPS unemployment data that measure unemployment on both a perperson and per-spell basis, so called work experience data collected in March of each year. The

retrospective unemployment question classifies respondents into three groups: one spell, two

spells and three or more spells. The duration measures in the work experience data do provide

estimates of annual duration of unemployment per person, combining all spells. Because these

data are collected but once a year, state detail has even more statistical noise than the monthly

unemployment data by state. Work experience data do not distinguish unemployment by reason.

There is also concern that work experience data may understate the number of unemployment

spells of short duration. These data are included in the discussion of Table IV-6 in Chapter IV.

25

unemployment per spell.24 Of the two mixed measures, the NICIC ratio does not appear to pose

measurement problems since its components are routinely reported by states to the national Office

of the Workforce Security (ETA 5159 data). However, more than a single issue arises in

considering the ratio of the two average duration measures.

If one reexamines expression (3), observe that the first three terms on the right hand side

pertain to spells of unemployment (ICNU, NICIC and FPNIC, measured on a mixture of per spell

and per person bases). The product of the three shows first payments as a ratio to new spells of

unemployment. This triple product can be termed the inflow rate. A high inflow rate indicates that

a large proportion of new unemployment spells are compensated. 

The final ratio in expression (3), (ADUIAD), is the ratio of two average duration

measures. Both ADUI and AD are empirical derivations affected by “adding up” constraints.

ADUI has annual weeks compensated in the regular UI program in its numerator, as noted in the

explanation below expression (2). AD has annual weeks of unemployment (from the CPS) in its

numerator, as noted in the explanation below expression (1). 

Two factors affect the measures of unemployment duration used in the present

investigation. Both ADUI and AD are affected by the calendar year accounting framework that

has been adopted. For individuals measured as unemployed in the CPS and for UI beneficiaries,

unemployment experiences cross annual calendar year boundaries. If this crossing occurred at the

same rate each year, it would not raise questions, but undoubtedly it is more important in years of

high unemployment than in years of low unemployment. Also, for both CPS and UI program

measures of unemployment, unemployment may extend past the point where measurement stops.

In other words, the CPS measures incomplete spells of unemployment, i.e., duration up to the
25Note also that ICNU and ADUIAD display more year-to-year variation than the other

two series. This pattern would be expected since the denominators of both ICNU and ADUIAD

are based on samples whereas the data in NICIC and FPNIC are based on universe counts.

26

time of the survey, not the full spell of joblessness. In UI benefit data, claimants disappear after

exhausting benefits, but their spells of unemployment may extend for several more weeks past

exhaustion. Thus average duration in both measures is affected by two types of truncation,

truncation due to the calendar year accounting framework and truncation due to unemployment

that extends beyond the end point of measurement of the spell. Additional discussion of truncation

in measuring unemployment duration is reserved for Chapter IV. 

To say the least, the preceding considerations suggest there is both noise as well as

conceptual ambiguity in the ADUIAD ratios to be examined in this report. The other three ratios

on the right hand side of expression (3) have straightforward interpretations. Of these three ratios,

it should also be noted that the ICNU ratio contains more statistical “noise” than the NICIC and

FPNIC ratios. The latter are based on universe counts in data reported by state UI programs

whereas NU is from the CPS which has rather small samples for individual states. To help control

for this noise, the summary data to be examined initially will be displayed as national aggregates

and as multiyear averages.

 

The Four Accounting Identity Ratios in National Data

Chart III-1 displays the four ratios from expression (3) in national data over the period

from 1967 to 1998. Individual years are shown along with averages for two multiyear periods on

the right hand side of the chart, 1967 to 1980 (1H) and 1981 to 1998 (2H). Years of high

unemployment like 1975-1976, 1980-1982 and 1990-1992 are obvious. For both ICNU and

FPNIC, the ratios are higher in recession years than in other periods.25 For NICIC, however, the

ratio is lower in years of high unemployment. There is also a cyclical pattern for ADUIAD which

declined during 1975-1976, 1981-1982 and again during 1990-1992. 

When the 1967-1980 and 1981-1998 averages are compared, note the stability in both

NICIC and FPNIC. These aspects of UI application-receipt processes were, on average, stable

between the two sub periods. In contrast, ICNU and ADUIAD were both lower during the latter
67

7379

86

9298

1H2H

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

Ratios

ICNU NICIC FPNIC ADUIAD

Chart III-1. Accounting Identity Ratios,

National Data, 1967 to 1998
26 The NICIC averages were 0.565 for both sub periods while the FPNIC average was 

actually somewhat lower during 1967-1980, 0.733 versus 0.748 during 1981-1998.

27One factor contributing to a long term decrease in ADUIAD is shorter potential benefit

duration in some states. In 1967, nine regular UI programs could pay benefits for more than 26

weeks. This number had decreased to two in 1985 (Massachusetts and Washington). 

28

of the two sub periods. The multiyear average of ICNU in national data declined from 0.564 in

1967-1980 to 0.514 in 1981-1998 or by about 9 percent. For ADUIAD the corresponding decline

was about 7 percent from 1.455 to 1.353. Using this accounting framework, the decline in UI

recipiency appears to have had components related to initial applications for benefits and to

average duration in benefit status. In contrast, the repeat claims ratio (NICIC) and the first

payments to new applications ratio (FPNIC) were stable over the two sub periods.26

Coincident with the decline in the ADUIAD ratio of the past two decades has been a

noticeable lengthening of average unemployment duration. Duration measures from the CPS and

from UI program data both show that unemployment duration has been increasing. Because

unemployment duration from the CPS has increased more than duration as measured in UI

program data, the decrease in the ratio of ADUI to AD noted in Chart III-1 is due to larger

increases in the denominator (AD) than the increases in the numerator (ADUI).27

This interesting development is examined in Chapters IV and V of this report. The final

section of Chapter IV studies several measures of unemployment duration, in both CPS and UI

data. A regression analysis of unemployment duration is undertaken in Chapter V. 

To conclude, the ratio of the two duration measures is the least transparent of the four

ratios on the right-hand side of expression (3). This ambiguity comes from ambiguities inherent in

the two underlying duration measures, ADUI and AD. The final section of Chapter IV discusses

the measurement of unemployment duration in more detail.

 

Accounting Identity Ratios by State

Table III-1 displays averages by state for the four right-hand ratios from expression (3).

Also shown is the product of the four, the WBTU ratio. The final column of data shows the

inflow rate, the product of ICNU, NICIC and FPNIC. This will be emphasized in a later section
Table III-1. Summary of Average UI Flows, States Sorted by Average WBTU, 1977 to 1998

State FIPS Div ICNU NICIC FPNIC ADUIAD WBTU Inflow

Rate

ALASKA 2 9 0.802 T 0.470 B 1.058 T 1.541 T 0.606 T 0.399 T

RHODE ISLAND 44 1 0.980 T 0.526 B 0.800 1.249 0.493 T 0.412 T

NEW JERSEY 34 2 0.616 T 0.646 T 0.803 1.349 0.426 T 0.319 T

MASSACHUSETTS 25 1 0.632 T 0.559 0.861 T 1.406 0.424 T 0.304 T

VERMONT 50 1 0.610 0.551 0.911 T 1.397 0.421 T 0.306 T

PENNSYLVANIA 42 2 0.789 T 0.453 B 0.861 T 1.362 0.416 T 0.308 T

CONNECTICUT 9 1 0.692 T 0.629 T 0.812 1.167 B 0.404 T 0.353 T

WISCONSIN 55 3 0.701 T 0.504 B 0.886 T 1.267 0.394 T 0.313 T

DIST OF COL 11 5 0.443 0.737 T 0.831 1.501 T 0.380 T 0.271 T

NEW YORK 36 2 0.579 0.566 0.776 1.466 T 0.368 T 0.254

OREGON 41 9 0.668 T 0.457 B 0.834 1.447 0.367 T 0.254

WASHINGTON 53 9 0.607 0.492 B 0.767 1.595 T 0.366 T 0.229

MAINE 23 1 0.832 T 0.539 0.689 B 1.237 0.365 T 0.309 T

HAWAII 15 9 0.579 0.526 B 0.834 T 1.464 T 0.362 0.254

CALIFORNIA 6 9 0.619 T 0.563 0.680 B 1.529 T 0.358 0.237

DELAWARE 10 5 0.596 0.456 B 1.020 T 1.297 0.350 0.277 T

NEVADA 32 8 0.532 0.546 0.843 T 1.417 0.343 0.245

MINNESOTA 27 4 0.422 B 0.567 0.935 T 1.496 T 0.333 0.224

NORTH DAKOTA 38 4 0.505 0.596 0.805 1.385 0.330 0.242

ILLINOIS 17 3 0.460 0.621 0.745 1.524 T 0.323 0.213

IDAHO 16 8 0.612 0.441 B 0.900 T 1.311 0.317 0.243

KANSAS 20 4 0.473 0.589 0.811 1.416 0.314 0.226

IOWA 19 4 0.497 0.603 0.852 T 1.211 B 0.305 0.255

MICHIGAN 26 3 0.613 0.603 0.683 B 1.223 0.304 0.252

MONTANA 30 8 0.476 0.569 0.827 1.296 0.288 0.224

MISSOURI 29 4 0.646 T 0.519 B 0.709 1.226 0.286 0.238

ARKANSAS 5 7 0.577 0.543 0.723 1.256 0.281 0.227

TENNESSEE 47 6 0.613 0.541 0.687 B 1.228 0.275 0.227

KENTUCKY 21 6 0.576 0.587 0.725 1.145 B 0.272 0.245

NEBRASKA 31 4 0.413 B 0.611 0.819 1.319 0.270 0.207

WEST VIRGINIA 54 5 0.414 B 0.695 T 0.891 T 1.056 B 0.270 0.257 T

WYOMING 56 8 0.390 B 0.581 0.767 1.526 T 0.267 0.174 B

MARYLAND 24 5 0.427 0.618 0.753 1.344 0.262 0.199

OHIO 39 3 0.518 0.571 0.735 1.219 B 0.261 0.217

NORTH CAROLINA 37 5 0.877 T 0.472 B 0.645 B 1.002 B 0.261 0.267 T

UTAH 49 8 0.332 B 0.633 T 0.833 1.448 0.250 0.175 B

SOUTH CAROLINA 45 5 0.729 T 0.535 B 0.595 B 1.062 B 0.239 0.232

ALABAMA 1 6 0.558 0.566 0.762 1.005 B 0.239 0.240

LOUISIANA 22 7 0.351 B 0.639 T 0.690 B 1.491 T 0.232 B 0.155 B

GEORGIA 13 5 0.481 0.683 T 0.715 1.008 B 0.231 B 0.235

MISSISSIPPI 28 6 0.466 0.527 B 0.702 1.243 0.212 B 0.173 B

NEW HAMPSHIRE 33 1 0.441 0.642 T 0.866 T 0.872 B 0.211 B 0.245

INDIANA 18 3 0.454 0.614 0.661 B 1.114 B 0.202 B 0.185 B

COLORADO 8 8 0.307 B 0.651 T 0.750 1.339 0.197 B 0.150 B

ARIZONA 4 8 0.296 B 0.630 T 0.676 B 1.559 T 0.193 B 0.126 B

NEW MEXICO 35 8 0.259 B 0.609 0.727 1.688 T 0.190 B 0.115 B

OKLAHOMA 40 7 0.335 B 0.656 T 0.651 B 1.344 0.189 B 0.143 B

TEXAS 48 7 0.237 B 0.694 T 0.686 B 1.595 T 0.179 B 0.113 B

VIRGINIA 51 5 0.426 0.568 0.673 B 1.108 B 0.176 B 0.163 B

SOUTH DAKOTA 46 4 0.337 B 0.624 0.658 B 1.193 B 0.165 B 0.138 B

FLORIDA 12 5 0.236 B 0.691 T 0.723 1.404 0.164 B 0.118 B

U.S.- 51 Programs 0.530 0.579 0.777 1.320 0.301 0.233

Top 13 - WBTU 0.688 0.548 0.838 1.383 0.418 0.310

Bottom 13 - WBTU 0.356 0.633 0.706 1.304 0.195 0.158

Top 13 - Col. Sort 0.737 0.664 0.902 1.536 0.418 0.315

Bottom 13 - Col. Sort 0.333 0.491 0.667 1.089 0.195 0.148

Top 13/ Bottom 13 2.213 1.353 1.351 1.411 2.137 2.126
30

of the chapter. All data in Table III-1 are averages for the 22 years 1977 to 1998. Note also the

ordering of the states, i.e., sorted in descending order by the average WBTU ratio. Top-to-bottom

the range of WBTU ratios exceeds three to one (from 0.606 down to 0.164).

As in earlier tables, Table III-1 has a large volume of information. To help reduce the

information to a more manageable scale, two types of summaries are also included. First, a three

way division of state-level ratios appears next to each column of data. Each column has been

divided into high (T), medium and low (B) with counts of 13, 25 and 13 respectively. The choice

of 13 is admittedly arbitrary but it reflects a compromise between selecting just a few extreme

outliers and placing too many states in the extreme categories. As it is, note the range of variation

in the WBTU ratios within both the top group (from 0.606 to 0.365) and the bottom group (from

0.232 to 0.164). This ranking procedure was applied to each column, and the Ts and Bs identify

the top 13 and bottom 13 when each column was sorted from high to low.

Second, summary measures emphasizing differences between the top 13 and bottom 13

states appear in the six bottom rows of Table III-1. In addition to the national averages, there are

two averages for the top 13 and the bottom 13 states. One average is based on sorted data in each

column (Col. Sort) and one based on the top and bottom 13 states sorted according to WBTU

ratios. The former gives an idea of the variation within each column regardless of the linkage to

the overall WBTU ratio while the latter shows how each indicator matches up with the top 13 and

bottom 13 states when ranked by WBTU ratios. All averages are simple averages that assign

equal weights to each state. 

A convenient starting point is the bottom entry in the WBTU column of Table III-1. This 

shows the average ratio of WBTU for the top 13 states relative to the bottom 13. This ratio,

2.137, shows that, on average, UI recipiency was more than twice as likely in the top 13 states

than in the bottom 13 states. 

The other bottom line ratios give a clear sense of how much variation was present in the

four individual accounting identity ratios and in the inflow ratio during 1977-1998. Among the

four ratios in expression (3), variation in ICNU (initial claims relative to new spells) was by far the

largest. The top 13 had an average ratio of 0.737 compared to 0.333 for the bottom 13. This ratio

of ratios, 2.213, indicates that filing for UI benefits is more than twice as likely in high application
28 Alaska, Rhode Island, New Jersey, Massachusetts, Pennsylvania, Connecticut,

Wisconsin, Oregon and Maine.

29 The explanation for the negative association between NICIC and WBTU is

straightforward. If a new initial claim is denied there cannot be a subsequent additional claim. A

later application for UI benefits would be again be classified as a new initial claim.

31

states than in low application states. Compared to this dispersion in application rates, the other

three ratios from expression (3) display more modest ranges of variability. All three Top

13/Bottom 13 ratios lie between 1.351 and 1.411. Ratios of repeat claims, first payment rates and

relative unemployment duration all display much less state-to-state variation than the rate at which

newly unemployed persons file for regular UI benefits. 

Note the wide range of variation in the inflow ratios, i.e., the Top 13/Bottom 13 ratio is

2.126. In states with high inflow rates a new spell of unemployment is more than twice as likely to

be compensated than in states with low inflow rates. Interstate variation in the inflow rate is much

wider than the variation in relative unemployment duration, i.e., a Top13/Bottom 13 ratio of

2.126 versus 1.411 for ADUIAD. 

Each of the four accounting identity ratios also displays an association with the overall

WBTU ratio. While the product of the four equals WBTU (by derivation in expressions (1), (2)

and (3)), each shows a definite individual association with WBTU. This is apparent in two ways.

First, note the number of Ts and Bs in the top 13 rows and bottom 13 rows for each of the four

ratios. Nine states with the highest ICNU ratios are among the 13 with the highest average

WBTU ratios.28 Eight with the lowest ICNU ratios are from the 13 with the lowest WBTU ratios.

A similar pattern is apparent for the FPNIC ratios as well. In contrast, high NICIC ratios are

associated with low WBTU ratios. Six with Bs fall into the highest WBTU group of 13 while

eight with Ts fall into the lowest WBTU group of 13. An aspect of low recipiency is a low

number of additional claims relative to new initial claims.29

The second indicator of association with the overall WBTU ratio is the level of the second

and third summary lines at the bottom of Table III-1 relative to the national averages. For both

ICNU and FPNIC, the averages for states with top WBTU ratios are significantly above their

national averages, e.g., 0.688 compared to 0.530 for ICNU and 0.838 compared to 0.777 for
32

FPNIC. Conversely, the averages of ICNU and FPNIC are noticeably below average for the 13

states with the lowest WBTU ratios. Note also that the NICIC ratio is below average for the 13

states with the highest WBTU ratio, i.e., 0.548 compared to the national average of 0.579. 

A convenient way to describe the associations between the individual components in

expression (3) with the overall WBTU ratio is in terms of correlations. Pairwise correlations

between each of the four series and WBTU in Table III-1 were as follows: ICNU -- +0.723,

NICIC – -0.468, FPNIC – +0.645 and ADUIAD – +0.187. The first three of these correlations

were highly significant when tested at the 0.01 level under a one sided test. 

While it simplifies the situation somewhat, the information on the four ratios as presented

in Table III-1 suggests that factors related to attempted entry into UI benefit status (ICNU) and

favorable decisions on new initial claims (FPNIC) carry most of the explanatory power for the

observed interstate differences in WBTU ratios. These associations with the WBTU ratio were

also explored with a set of multiple regressions. Regressing WBTU on the three component ratios

of ICNU, NICIC and FPNIC “explained” 0.810 of the interstate variation observed in Table III-1.

Regressing WBTU on just ICNU and FPNIC explained 0.783 of the variation. The descriptive

regressions indicated that ICNU and FPNIC were both very important factors in explaining

interstate variation in WBTU while NICIC was only of marginal importance and ADUIAD had

insignificant explanatory power. 

The final column of Table III-1 shows inflow rates into benefit status (first payments as a

proportion of new unemployment spells) measured as the product of the three inflow measures

from the left-hand columns. There is a striking association between state-specific inflow rates and

WBTU ratios. Ten of thirteen states with highest WBTU ratios are from the thirteen with highest

inflow rates. Conversely, eleven of the thirteen states with the lowest WBTU ratios are from the

thirteen with the lowest inflow rates. Thus 21 of the 26 states found at the extremes of the WBTU

distribution were also at the extremes of the inflow rate distribution. 

Interstate variation in UI recipiency, as reflected in average WBTU ratios, is closely

associated with interstate variation in the ratio of first payments to new spells of unemployment.

The correlation between the inflow rate and the WBTU ratio in Table III-1 is 0.893. Interstate

variation in UI recipiency is much more closely linked to variation in the inflow rate than to
33

variation in relative benefit duration.

Geographic Patterns of Low Recipiency

Map 2 helps to focus on the geographic variation in inflow rates. It identifies the thirteen

states with the highest and the lowest inflow rates from Table III-1. Ten of the thirteen with the

lowest inflow rates are contiguous, stretching in an arc from Mississippi to South Dakota. Across

the thirteen low inflow states, the inflow rates ranged from 0.185 (Indiana) down to 0.113

(Texas) and averaged 0.148. This average compares to a national average of 0.233 across all 51

programs and an average of 0.315 for the 13 states with the highest inflow rates. 

All thirteen states with the lowest inflow rates have below-average recipiency as signaled

by WBTU ratios. However when low inflow rates and low WBTU ratios are examined jointly,

interesting geographic patterns emerge.

Low benefit recipiency can arise in three distinct ways: 1) a low rate of inflow into benefits

with average relative benefit duration (relative to unemployment duration), 2) an average inflow

rate with short relative benefit duration, or 3) a combination of a low inflow rate and low relative

benefit duration. In fact, all three patterns are present in states with low recipiency. However, two

of the patterns exhibit a clear geographic concentration. 

For the period 1977-1998, 27 of the 51 programs had WBTU ratios that fell below the

national average of 0.301 displayed in Table III-1. Map 3 identifies three groups of states with

differing patterns of low recipiency. A group of five are characterized by average inflow rates but

short benefit duration. These are five contiguous states in the southeastern U.S.: North Carolina,

South Carolina, Georgia, Alabama and Tennessee. Their inflow rates range from 0.267 down to

0.227 compared to the national average of 0.233. All five are also characterized by short relative

duration (ranging from 1.002 up to 1.228 compared to the national average of 1.320). In these

states low recipiency is associated with short benefit duration. Part of the reason for the short

duration in these states is that the claimant population includes a large share of job-attached

workers. This feature of these UI programs enters the later analysis of Chapters V and VI.

The second group of states is a group of nine from the 13 with the lowest inflow rates

(Map 2), but they all have above-average relative unemployment duration. Eight of the nine are
Map 2. Rates of Inflow Into Benefits

Highest 13

Other 25

Lowest 13
Map 3. Low Recipiency in Three Groups of States

Avg. Inflow, Low Relative Duration

All Other States

Low Inflow, High Relative Duration

Other Lowest 13 WBTU Ratios
30 Determination rates are measured in this project according to standard definitions.

Determination rates for voluntary quit and discharge are measured as a proportion of new spells

of unemployment (new intrastate initial claims times the proportion monetarily eligible plus

additional intrastate claims plus interstate liable claims). Determination rates for nonseparation

issues are measured per ten claimant contacts. Claimant contacts are the sum of new spells (as just

defined) plus intrastate weeks claimed plus interstate liable weeks claimed. 

36

located in a block that extends from Louisiana to Colorado. Florida is the ninth. All have aboveaverage relative UI benefit duration and five are from the 13 with the highest relative duration

(Arizona, Louisiana, New Mexico, Texas and Wyoming). Despite the long duration in benefit

status in these states, the inflow rate is so low that they exhibit very low WBTU ratios. 

The remaining five states with the lowest WBTU ratios have low ratios through a

combination of below-average inflow rates (except for New Hampshire) and uniformly belowaverage relative unemployment duration. These are widely dispersed around the country, e.g.,

New Hampshire, Virginia, Indiana, Mississippi and South Dakota. 

The three groups combined account for 19 of the 27 programs where the WBTU ratio

was below the national average during 1977-1998. They generate low recipiency through varying

combinations of low inflow rates and low relative unemployment durations. The three groups

combined include the seventeen states with the lowest WBTU ratios in Table III-1 plus Wyoming

and Tennessee that respectively rank 20th and 24th from the bottom. Map 3 clearly illustrates that

low recipiency rates in the southeast and southwest have quite distinct origins. 

Indicators of UI Administrative Activities

Interstate variation in UI recipiency undoubtedly has several causes. Among these, the

administrative actions of state UI programs in making eligibility determinations are of particular

interest. Showing an association between administrative decisions and low recipiency would be of

interest to UI administrators, public policy analysts and the research community. 

Table III-2 presents state-level information on five types of administrative decisions that

can affect the receipt of UI benefits. These are: 1) monetary eligibility proportions, 2) voluntary

quit determination rates, 3) misconduct determination rates, 4) determination rates on

nonseparation issues30 and 5) appeals per separation determination. The administrative processes
Table III-2. Indicators of Administrative Activities, States Sorted by Average WBTU, 1977 to 1998

State FIPS Div Prop. Vol. Quit Misconduct Non Sep. Appeals Per WBTU

Mon. Elig. Det. Rate Det. Rate Det. Rate Sep. Det

ALASKA 2 9 0.835 0.089 0.046 T 0.257 0.090 T 0.606 T

RHODE ISLAND 44 1 0.918 T 0.077 0.050 T 0.226 0.167 T 0.493 T

NEW JERSEY 34 2 0.879 0.063 T 0.078 0.261 0.216 0.426 T

MASSACHUSETTS 25 1 0.941 T 0.068 T 0.067 0.187 0.212 0.424 T

VERMONT 50 1 0.893 0.087 0.062 T 0.099 T 0.181 0.421 T

PENNSYLVANIA 42 2 0.865 0.040 T 0.041 T 0.353 B 0.285 B 0.416 T

CONNECTICUT 9 1 0.826 0.085 0.117 0.284 0.275 B 0.404 T

WISCONSIN 55 3 0.929 T 0.080 0.062 T 0.283 0.132 T 0.394 T

DIST OF COL 11 5 0.719 B 0.107 0.198 B 0.151 T 0.312 B 0.380 T

NEW YORK 36 2 0.957 T 0.060 T 0.078 0.434 B 0.192 0.368 T

OREGON 41 9 0.818 B 0.101 0.096 0.400 B 0.130 T 0.367 T

WASHINGTON 53 9 0.869 0.084 0.059 T 0.340 0.193 0.366 T

MAINE 23 1 0.725 B 0.075 0.062 T 0.463 B 0.197 0.365 T

HAWAII 15 9 0.968 T 0.113 0.095 0.295 0.126 T 0.362

CALIFORNIA 6 9 0.803 B 0.090 0.093 0.319 0.102 T 0.358

DELAWARE 10 5 0.931 T 0.048 T 0.069 0.125 T 0.275 B 0.350

NEVADA 32 8 0.923 T 0.146 B 0.172 B 0.197 0.214 0.343

MINNESOTA 27 4 0.949 T 0.088 0.096 0.257 0.212 0.333

NORTH DAKOTA 38 4 0.792 B 0.086 0.070 0.224 0.243 B 0.330

ILLINOIS 17 3 0.834 0.088 0.113 0.211 0.255 B 0.323

IDAHO 16 8 0.854 0.078 0.062 T 0.407 B 0.094 T 0.317

KANSAS 20 4 0.825 0.120 0.136 B 0.275 0.232 0.314

IOWA 19 4 0.874 0.137 B 0.091 0.214 0.250 B 0.305

MICHIGAN 26 3 0.928 T 0.095 0.068 0.211 0.087 T 0.304

MONTANA 30 8 0.836 0.120 0.063 T 0.127 T 0.099 T 0.288

MISSOURI 29 4 0.813 B 0.098 0.143 B 0.325 0.170 0.286

ARKANSAS 5 7 0.871 0.091 0.087 0.204 0.211 0.281

TENNESSEE 47 6 0.859 0.035 T 0.054 T 0.033 T 0.246 B 0.275

KENTUCKY 21 6 0.847 0.052 T 0.064 T 0.103 T 0.260 B 0.272

NEBRASKA 31 4 0.942 T 0.476 B 0.204 B 0.776 B 0.058 T 0.270

WEST VIRGINIA 54 5 0.899 0.072 T 0.067 0.109 T 0.210 0.270

WYOMING 56 8 0.788 B 0.094 0.090 0.362 B 0.216 0.267

MARYLAND 24 5 0.827 0.131 B 0.130 0.319 0.216 0.262

OHIO 39 3 0.908 T 0.044 T 0.077 0.266 0.081 T 0.261

NORTH CAROLINA 37 5 0.858 0.041 T 0.051 T 0.130 T 0.190 0.261

UTAH 49 8 0.900 T 0.138 B 0.132 B 0.667 B 0.150 T 0.250

SOUTH CAROLINA 45 5 0.803 B 0.038 T 0.091 0.116 T 0.190 0.239

ALABAMA 1 6 0.819 0.051 T 0.067 T 0.465 B 0.307 B 0.239

LOUISIANA 22 7 0.803 B 0.167 B 0.179 B 0.240 0.229 0.232 B

GEORGIA 13 5 0.897 0.072 0.156 B 0.161 T 0.148 T 0.231 B

MISSISSIPPI 28 6 0.802 B 0.081 0.101 0.224 0.206 0.212 B

NEW HAMPSHIRE 33 1 0.872 0.099 0.093 0.435 B 0.168 0.211 B

INDIANA 18 3 0.824 0.158 B 0.093 0.170 T 0.196 0.202 B

COLORADO 8 8 0.930 T 0.287 B 0.148 B 0.478 B 0.203 0.197 B

ARIZONA 4 8 0.863 0.137 B 0.150 B 0.492 B 0.175 0.193 B

NEW MEXICO 35 8 0.870 0.126 B 0.111 0.131 T 0.297 B 0.190 B

OKLAHOMA 40 7 0.754 B 0.126 B 0.151 B 0.120 T 0.281 B 0.189 B

TEXAS 48 7 0.849 0.150 B 0.248 B 0.307 0.206 0.179 B

VIRGINIA 51 5 0.811 B 0.062 T 0.089 0.264 0.176 0.176 B

SOUTH DAKOTA 46 4 0.742 B 0.115 0.104 0.447 B 0.216 0.165 B

FLORIDA 12 5 0.831 0.145 B 0.176 B 0.304 0.233 B 0.164 B

U.S.- 51 Programs 0.856 0.104 0.102 0.279 0.196 0.301

Top 13 - WBTU 0.860 0.078 0.078 0.288 0.199 0.418

Bottom 13 - WBTU 0.834 0.133 0.138 0.290 0.210 0.195

Top 13 - Col. Sort 0.933 0.052 0.057 0.121 0.113 0.418

Bottom 13 - Col. Sort 0.782 0.179 0.169 0.475 0.271 0.195

Top 13/ Bottom 13 1.192 0.290 0.339 0.255 0.416 2.137
38

that generate these variables all may be important in determining initial receipt of benefits and/or

duration in benefit status. While other variables could also have been selected, e.g., denial rates

per determination, the five in Table III-2 all have clear relevance for UI benefit recipiency. The

table also shows the WBTU ratio in the final data column. All data are averages of annual data for

the 22 years 1977 to 1998. 

Table III-2 utilizes the same conventions as Table III-1 to summarize the data. Each

column was sorted, and the 13 highest and 13 lowest states were identified. Averages for these

two groups appear at the bottom of Table III-2, both for the column sort (Col. Sort) and for the

states with the highest and lowest WBTU ratios. Note that low and high are defined by the impact

of the administrative process on recipiency. Thus the highest monetary eligibility proportions are

identified with Ts. However, for rates of nonmonetary determinations and appeals, the lowest

averages are assigned Ts since a lower volume of these administrative decisions implies an

increased probability of payment.

Of the five separate administrative actions, relative variability across states is smallest for

the monetary eligibility proportion. The ratio of the average for the top 13 (0.933) to the average

for the bottom 13 (0.782) is only 1.192. The average eligibility proportion is only 19 percent

higher in the top 13 states compared to the bottom 13. The other Top 13/Bottom 13 ratios of

administrative activities in Table III-2 show much wider ranges of relative variation across states.

Observe in Table III-2 that the monetary eligibility averages for the states with top and

bottom WBTU ratios are quite similar, e.g., 0.860 and 0.834 respectively. There is no strong

association between average monetary eligibility proportion and average benefit recipiency as

signaled by the WBTU ratio.

The voluntary quit and misconduct determination rates vary widely across states. Both

determinations are roughly three times more frequent per new spell of unemployment in the

bottom 13 states compared to the top 13. The frequency of these determinations also is negatively

associated with the receipt of UI benefits. For example, the average rate of voluntary quit

determinations per new spell in the 13 states with the highest WBTU ratios was 0.078 compared

to 0.133 for the 13 with the lowest WBTU ratios. On average, states with above-average rates of

separation determinations per new spell (both voluntary quit and misconduct) have lower WBTU
31 See U.S. Department of Labor, Office of Workforce Security (2000).

39

ratios. Chapters VI and VII explore these differences in more detail while Chapter V examines the

quantitative importance of the differences using multiple regressions. Interstate differences in

determination rates for misconduct are found to be particularly important. 

Interstate variation in nonseparation nonmonetary determination rates is even wider than

for separation determinations. The average rate per ten claimant contacts in the top 13 states was

0.121 compared to 0.475 for the bottom 13 states. However, there is no obvious association

across states between these determination rates and WBTU ratios. The average nonseparation

determination rate was 0.288 for the 13 states with the highest WBTU ratios and 0.290 for the 13

with the lowest WBTU ratios. A similar pattern is also observed for the rate of appeals on

separation issues, i.e., wide interstate variation but no important association across states between

the rate of appeals and the WBTU ratio.

The administrative activities summarized in Table III-2 are some of the measures reviewed

by the national Office of Workforce Security in following state UI program operational

performance. The timeliness and accuracy of several administrative determinations are tracked.

Since 1998 quarterly reports on operational performance have been issued.31 Analysis of data in

these reports would suggest that states that score high on measures of administrative stringency

are often states with low benefit recipiency

The association between these five indicators of administrative actions in Table III-2 and

benefit recipiency can also be expressed in terms of correlations. When each of the five was

correlated with the WBTU ratio using the data in Table III-2, the correlations showed the

expected pattern. The five simple correlations with WBTU were: 1) proportion monetarily eligible

-- +0.222, 2) voluntary quit determination rate -- -0.251, 3) misconduct determination rate -- -

0.450, 4) nonseparation determination rate -- -0.101 and 5) appeals per separation determination -

- -0.154. Note that the last four correlations are all negative. However, the misconduct

determination rate was the only one of the five significantly associated with the WBTU ratio (at

the 0.01 level). 

The descriptive information in Table III-2 shows wide interstate variation for all five series
32 The eight are Montana, Missouri, Arkansas, Kentucky, Nebraska, West Virginia,

Maryland and Ohio.

40

that reflect UI administrative activities. For four of the five series (all except the proportion

monetarily eligible) determination rates in the 13 states with the highest determination rates are

more than twice as frequent as for the 13 states with the lowest determination rates. For the two

types of separation determinations, i.e., voluntary quits and misconduct, there is an association

between the determination rate and recipiency as indicated by the WBTU ratio. This association is

strongest between the misconduct determination rate and the WBTU ratio.

Recipiency and Administrative Measures for Six Groups of States

Table III-3 provides a summary of both recipiency measures and administrative measures

for UI programs combined into six groups, two groups with above-average recipiency and four

with below-average recipiency. The summaries use data from Tables III-1 and III-2 for six 

groupings of states: 1) Group 1 - the thirteen with the highest WBTU ratios, 2) Group 2 - the

other eleven with above-average WBTU ratios, 3) Group 3 - eight with below-average WBTU

ratios,32 4) Group 4 - five southeastern states with short benefit durations and low recipiency, 5)

Group 5 - nine (mainly southwestern) states with low inflow rates and low recipiency and 6)

Group 6 - the remaining five of the thirteen UI programs with the lowest WBTU ratios. Groups 4,

5 and 6 are the same states with low inflow rates and low WBTU ratios displayed in Map 3. All

data in Table III-3 are simple averages of state data from Tables III-1 and III-2. 

The motivation for making these groupings is to help identify systematic differences across

states when they are arranged by differing levels of recipiency. Note that the average WBTU

ratios follow a direct high-to-low progression from Group 1 through Group 6. National averages

for all measures appear in the bottom lines of Panels A and B.

The recipiency measures in Panel A have several noteworthy features. 1) Note the high

ICNU ratio for Group 4, the five southeastern states with short relative durations, 0.652

compared to 0.688 for the 13 with the highest WBTU ratios. The average application rate in these

states is 50 percent higher than for Group 6 and more than twice the application rate for Group 5

(the nine with low inflow but above-average relative duration). 2) The patterns of first
Table III-3. Average Recipiency Measures and Administrative Measures for Six Groups of UI Programs, 1977 to 1998

Panel A. UI Recipiency ICNU NICIC FPNIC Inflow ADUIAD WBTU

 Measures Rate

Group 1. Thirteen With 0.688 0.548 0.838 0.310 1.383 0.418

 Highest WBTU 

Group 2. Eleven With 0.537 0.556 0.828 0.243 1.388 0.331

 Above-average WBTU

Group 3. Eight with Below- 0.506 0.589 0.773 0.227 1.233 0.274

 average WBTU 

Group 4. Five South- 0.652 0.559 0.681 0.240 1.061 0.249

 eastern States

Group 5. Nine With Low 0.305 0.643 0.723 0.141 1.488 0.207

 Inflow Rates

Group 6. Other Five States 0.425 0.595 0.712 0.181 1.106 0.193

 With Lowest WBTU

U.S. - 51 Programs 0.530 0.579 0.777 0.233 1.320 0.301

Panel B. UI Administrative Prop. Vol. Quit Misconduct Non Sep. Appeals WBTU

 Measures Monetarily Determin. Determin. Determin Per Sep

Eligible Rate Rate Rate Determin.

Group 1. Thirteen With 0.860 0.078 0.078 0.288 0.199 0.418

 Highest WBTU 

Group 2. Eleven With 0.880 0.099 0.097 0.249 0.190 0.331

 Above-average WBTU

Group 3. Eight with Below- 0.868 0.135 0.104 0.279 0.163 0.274

 average WBTU 

Group 4. Five South- 0.847 0.047 0.084 0.181 0.216 0.249

 eastern States

Group 5. Nine With Low 0.843 0.152 0.154 0.344 0.221 0.207

 Inflow Rates

Group 6. Other Five States 0.810 0.103 0.096 0.308 0.192 0.193

 With Lowest WBTU

U.S. - 51 Programs 0.856 0.104 0.102 0.279 0.196 0.301
42

payment ratios (FPNIC) generally decreases as WBTU declines except that the five southeastern

states (Group 4) have the lowest ratios across all six groups. Low first payment rates as well as

short relative benefit duration both contribute to below-average recipiency in these five states. 3)

The low inflow rate for Group 5 (0.141) is less than half the inflow rate for Group 1. The next

lowest inflow rate is 0.181 for Group 6 while all other groups have averages that range upwards

from 0.227. 4) Groups 4 and 5 are also at the extremes of the relative duration averages. Long

relative benefit duration for Group 5 is unusual not only among states with below-average WBTU

ratios but even compared to Groups 1 and 2, states with above-average WBTU ratios.

Aspects of the administrative measures in Panel B are also noteworthy. 5) The monetary

eligibility averages are quite similar across the six groups with five of six between 0.843 and

0.880. 6) The five southeastern states (Group 4) have low separation determination rates for both

voluntary quit and misconduct. 7) For these same two issues the highest determination rates are

found in Group 5, the nine programs with very low inflow rates. The averages for both voluntary

quit and misconduct determination rates are roughly 50 percent above their respective national

averages. 8) Groups 4 and 5 are also found at the extremes of the nonseparation determination

rate averages as well. The five southeastern states have low determination rates on both

separation and nonseparation issues while these determination rates are high for the states in

Group 5 that have the lowest average inflow rates. 

These summary data displayed in both Tables III-2 and III-3 are suggestive of links

between state-level UI administrative actions and UI benefit recipiency rates. However, the

associations need to be examined within a more systematic framework than simple tabular

displays. Chapter V undertakes a regression analysis of the determinants of the four accounting

identity ratios introduced in expression (3) and displayed for each state in Table III-1.

Administrative measures such as those displayed in Table III-2 and III-3 are tested for their

effects on the accounting identity ratios along with other UI administrative factors as well as

factors operative in state labor markets.
43

Summary

The accounting framework developed at the start of this chapter allows one to view and

interpret low UI recipiency from a more nuanced perspective. If one were to examine WBTU

ratios directly, pairs of states such as Georgia and Mississippi, South Dakota and Florida and

Ohio and North Carolina would not be distinguishable because their long run WBTU ratios are so

similar (Table III-1). However, when elements of accounting relationship 3 are noted, these pairs

of states arrive at similar recipiency rates through quite differing combinations of factors relating

to benefit inflow and relative benefit duration. 

In fact, low recipiency is reached by varying combinations of low inflow rates and low

relative benefit durations. Referring to the groupings of states shown in Table III-3, one group

(Group 6) have both a low inflow rate and low relative duration. These five states are spread

widely across the country as shown in Map 3. A second group of states (Group 4) have average

inflow rates but very low relative durations. A third group (Group 5) have very low inflow rates

but lengthy relative durations. The latter two groups both exhibit strong geographic clustering, in

the southeast and southwest respectively. Absent the accounting framework developed in this

chapter, these differing patterns associated with low benefit recipiency could not be differentiated.

In the state UI programs, low recipiency is the result of three distinguishable patterns of inflow

rates and relative benefit durations. 
44

IV. Measurement Issues

As noted in Chapter II, the most common measure of UI recipiency is the IUTU ratio, the

ratio of insured unemployment (or active UI claimants) to total unemployment. In the present

project, greater emphasis is placed on the ratio of the average weekly number of UI beneficiaries

to total unemployment, the WBTU ratio. Since the IUTU ratio has been used most often in

previous research, both ratios are covered in this chapter.

The chapter examines five issues in measuring UI recipiency: 1) the exact definitions used

in measuring unemployment and the receipt of UI benefits, 2) partial benefits, 3) state border

issues, 4) the reason for unemployment and 5) unemployment duration. In all areas, we review

definitions, discuss the measures and display selected data as appropriate.

Key Definitions

Throughout the project emphasis is placed on the ratio of UI recipients (recorded in UI

program data) to total unemployment (measured in the monthly household labor force survey). It

should again be noted that certain unemployed persons who receive benefits through state UI

programs fall outside the scope of the project’s analysis. The exclusions extend to persons

compensated through unemployment compensation for federal employees (UCFE),

unemployment compensation for ex-servicemen (UCX), unemployment compensation for railroad

workers (RUI), federal state extended benefits (EB) and emergency federal programs, most

recently emergency unemployment compensation (EUC). The project’s scope, in other words, is

restricted to the so-called regular state UI program which in 51 of 53 jurisdictions can pay up to

26 weeks of UI benefits (30 weeks in Massachusetts and Washington). 

If we take the week as the time unit of measurement, most with unemployment are

unemployed for the full week. The full week unemployed constitute the majority of persons who

enter both the numerator and the denominator of the IUTU ratio and the WBTU ratio. However,

there are persons who within a given week experience both employment and unemployment.

Their treatment within the UI program data differs from their treatment in the household labor
45

force survey. This difference should be discussed starting with the household labor force survey.

The household survey (the Current Population Survey or CPS) conducted by the Census

Bureau for the Bureau of Labor Statistics is undertaken monthly and asks questions about labor

market activity of each household member aged 16 and older. Roughly 50,000 households are

surveyed, and the survey questions pertain to activities during the week that included the 12th of

the month (termed the reference week). Each household member is classified into one of three

mutually exclusive categories, e.g., employed, unemployed or not in the labor force. The first

question posed to each person is their principal activity during the reference week. All persons

(except family workers) who worked one or more hours during the reference week are classified

as employed. Family workers who work on a farm or for some other family business (but do not

receive a salary) are counted as employed only if they worked 15 or more hours during the

reference week. 

Thus if three persons worked for wages for one hour, ten hours and fifty hours, all three

would be classified as employed regardless of other activities during the reference week. One

differentiation that is made among the three situations is that the CPS distinguishes part-time

employment (fewer than 35 hours per week) from full-time employment (35 or more hours per

week). Thus the one-hour and ten-hour workers would be part-time while the fifty-hour worker

would be full-time.

Persons with no employment during the reference week may have experienced

unemployment. To be classified as unemployed, one has to have been able to work and available

to work during the reference week and to have engaged in some form of active work search

during that week or one of the preceding three weeks. Persons not meeting the criteria to be

classified as employed or unemployed during the reference week are classified as out-of-laborforce or economically inactive. Each month some 38 to 40 percent of persons 16 and older are

economically inactive.

In UI data, there are measures of claimants, eligible claimants, recipients and persons who

have exhausted entitlements. Insured unemployment (IU) counts unemployed persons who are

active claimants for benefits, most of whom are receiving benefits. Besides counting recipients, IU

also includes persons serving the waiting week and some serving fixed duration disqualification
46

periods. Weeks claimed and weeks compensated are both routinely measured. Most of the UI

program data used in this report are universe counts, not samples as in the CPS. 

After a person uses up their full UI benefit entitlement they are said to exhaust. The

program counts the number of exhaustees, but at that point the person is no longer actively

tracked in UI data. The treatment of exhaustees means that at the point of exhaustion a person

disappears from UI data but not from CPS data as long as he or she remains unemployed, i.e.,

seeking employment.

 

Partial Unemployment Benefits

A noteworthy situation with implications for IUTU and WBTU ratios occurs when a

worker experiences both employment and unemployment during the reference week. Such a

person could have received UI benefits that week even though that person would be classified as

employed in the CPS. The person would be included in the numerator but not in the denominator

of the IUTU ratio and the WBTU ratio.

It should also be noted that recipients of partial unemployment benefits have a larger effect

on IUTU and WBTU ratios than unemployed persons who receive a full week of UI benefits. The

partial unemployment beneficiary enters just the numerator of both ratios whereas the fully

unemployed beneficiary enters the numerator and the denominator of both ratios. This differential

effect has not been emphasized in earlier research. Its importance depends on the share of partial

beneficiaries within the population of UI recipients.

There are two possible ways an employed person could receive a UI benefit payment.

First, all states permit a beneficiary to have some earnings and still receive UI benefits. There is an

explicit partial benefit schedule that specifies a maximum earnings amount allowed with no loss of

benefits (termed the earnings disregard) and then a schedule that phases out benefits when

earnings exceed that amount. The earnings threshold is typically a fraction, e.g., one fourth or one

half, of the WBA (weekly benefit amount), and the phase-out is complete when earnings reach the

level of the WBA.

 Second, some states (18 in the year 2000) offer short-time compensation (STC) to

persons placed on short work schedules, say four-day or three-day schedules. STC benefits are
47

paid as a fraction of full weekly benefits with the fraction reflecting the proportionate reduction in

weekly hours. Thus people who work a four-day schedule would receive STC for the fifth day at

a rate of one fifth of the WBA for full unemployment. The payment of STC benefits is recorded in

standardized reports from the states. Reporting details include weeks claimed, weeks

compensated, equivalent (five day) weeks claimed and benefit payments. In all states with STC,

the payments constitute very small fractions of total weeks compensated and of benefit payouts.

Table IV-1 displays data by state showing the importance of partial UI benefits and STC

benefits in1998, each expressed as a percent of total weeks compensated. For STC benefits, the

table shows all weeks compensated and equivalent weeks, i.e., STC weeks compensated

measured as five-day weeks. 

The data clearly show how consistently small the STC program is in the 18 states where it

is offered. STC weeks compensated exceeded 1.0 percent of weeks compensated in six of the 18

states, and only in Rhode Island did STC weeks exceed 2.0 percent. Equivalent STC weeks

exceeded 0.5 percent of weeks compensated in just one state (again Rhode Island).

The small scale of STC in 1998 mirrors patterns observed in other years since the

programs were introduced. Reporting data extend back to 1982 for the first three states with STC

(Arizona, California and Oregon). Between 1984 and 1992 the number of states with STC

programs gradually expanded to 18 and has remained at 18 since 1992. Of 237 state-year

observations spanning the 1982-1999 period, STC equivalent weeks exceeded 1.0 percent of

weeks compensated just twice (Arizona in 1982 and 1985) and STC equivalent weeks exceeded

0.5 percent just 24 times. The small scale of STC shown in Table IV-1 is representative of the

STC programs’ experiences since their inception.

In contrast, partial unemployment benefits constituted a measurable share of weeks

compensated in 1998. The national average was 9.0 percent. So-called partials exceeded 20

percent of total weeks in four states (Maine, Montana, Nebraska and Wisconsin) with the highest

percentage occurring in Nebraska (37.3 percent). Note also that an additional 17 states had

percentages between 10.0 and 19.9 percent while just two had partial weeks of less than 4.0

percent of total weeks. Partial UI benefits are a reasonably common feature of UI programs.

It should be noted that some people with wages also collect full UI benefits for the same
Table IV-1. Partial Weeks and STC Weeks as a Percentage

 of Total Weeks Compensated, 1998

State Partial STC Equiv STC

Weeks Weeks Weeks

ALABAMA 4.8

ALASKA 9.2

ARIZONA 4.8 1.17 0.25

ARKANSAS 13.3 0.00 0.00

CALIFORNIA 6.0 1.11 0.22

COLORADO 7.2

CONNECTICUT 11.3 0.50 0.10

DELAWARE 15.3

DIST OF COL 9.1

FLORIDA 4.2 0.12 0.02

GEORGIA 9.2

HAWAII 13.3

IDAHO 14.7

ILLINOIS 6.3

INDIANA 4.9

IOWA 11.9 0.03 0.01

KANSAS 7.7 1.48 0.36

KENTUCKY 11.1

LOUISIANA 4.1 0.00 0.00

MAINE 20.3

MARYLAND 6.5 0.02 0.00

MASSACHUSETTS 8.0 0.21 0.06

MICHIGAN 0.0

MINNESOTA 10.5 0.07 0.02

MISSISSIPPI 7.6

MISSOURI 7.8 1.69 0.42

MONTANA 26.1

NEBRASKA 37.3

NEVADA 5.1

NEW HAMPSHIRE 7.2

NEW JERSEY 8.6

NEW MEXICO 3.1

NEW YORK 7.2 0.38 0.11

NORTH CAROLINA 14.6

NORTH DAKOTA 5.4

OHIO 4.7

OKLAHOMA 8.2

OREGON 19.7 0.18 0.04

PENNSYLVANIA 14.4

RHODE ISLAND 10.8 3.29 0.84

SOUTH CAROLINA 12.2

SOUTH DAKOTA 9.3

TENNESSEE 8.3

TEXAS 10.6 0.17 0.13

UTAH 15.2

VERMONT 11.8 1.16 0.35

VIRGINIA 9.6

WASHINGTON 17.6 0.36 0.04

WEST VIRGINIA 9.5

WISCONSIN 20.8

WYOMING 9.8

U.S. 51 Programs 9.0 0.34 0.08

Source: U.S Department of Labor, ETA-5159 Reports. 
49

week. This occurs when weekly wages fall below the earnings disregard of the partial benefit

schedule. There is no systematic measurement within UI programs of the prevalence of this

situation. Thus data on partial UI benefits as displayed in Table IV-1 understate the extent to

which people have wages and collect UI benefits in the same week. 

Because earnings disregards are very low in several states, it is believed that data on

partial UI benefits capture most situations of work and receipt of benefits during the same week.

However, five states in the year 2000 had earnings disregards that ranged from $50 to $100 per

week (Hawaii, Maryland, Ohio, Oklahoma, and West Virginia). A low-wage worker in these

states could work, say, from 8 to 16 hours, while receiving a full weekly benefit. Measuring this

phenomenon would be useful in showing the full extent of work and the receipt of UI benefits in

the same week. 

Partial UI benefits have grown in importance over the past three decades. In 1971 partial

benefits constituted only 6.0 percent of total weeks compensated. This percentage had increased

to 6.5 percent by 1978, to 7.7 percent by 1988 and (as noted) was 9.0 percent in 1998. Partial

benefits have been growing as a share of total UI benefits.

The main importance of partial UI benefits and STC benefits is to increase empirical

measures of UI benefit recipiency. Partial UI recipients and STC recipients are included in the

numerators of IUTU and WBTU ratios but not in their denominators. Thus a national WBTU

ratio of 0.33 would be reduced to about 0.30 if partial benefits and STC were excluded since they

account for nearly 10 percent of weeks compensated. 

A conclusion regarding partial benefits could be stated in two closely related ways. 1)

Persons who experience both employment and unemployment in a single week are treated

differently in UI program data from their treatment in the monthly household labor force survey.

Partial weeks of UI benefits are included in UI program data, but partial weeks of unemployment

do not enter CPS measures of unemployment because there is employment in the same week. 2)

Discussions of the WBTU and IUTU ratios frequently assume the underlying data fit within a

nested conceptual framework, i.e., assuming IU and WB are both subsets of TU. In actual fact, a

partially unemployed person can enter the numerator of both ratios but not be included in the

denominator. The low recipiency of some states would appear to be even lower if the numerators
50

included only full weeks of unemployment, i.e., if the IU and WB were nested within TU.

State Border Issues

State boundaries must be recognized in analyses of IUTU and WBTU ratios. Persons

measured as employed and unemployed in the household labor force survey are classified

geographically according to their state of residence. This rule is applied irrespective of where the

person works and/or the number and locations of jobs held. Thus the denominators of state-level

IUTU and WBTU ratios are unemployed persons classified by their state of residence.

Border issues do not arise in UI program data if all work during the base period is

confined to a single state in which the person files and continues to reside while receiving benefits

following a job separation. Such a situation is termed an intrastate claim, and it applies to full

weeks and partial weeks of unemployment.

Three separate situations involving UI benefits and state borders can be distinguished: 1)

interstate claims, 2) commuter claims and 3) combined wage claims (CWC). Each will be

discussed and supporting data will be displayed.

Interstate claims. Interstate claims arise when someone has worked in one state but is

temporarily or permanently located in another State and files for benefits from the latter state. The

state from which the claim is filed acts as the agent state for this interstate claim filed against the

UI program in the state where the claimant worked (the liable state). Should the person move

back to the liable state during the benefit year, the claim will change from an interstate to an

intrastate claim. The key point in interstate situations is that base period earnings occurred in a

state other than the state of residence at the time the week of unemployment is claimed. Benefit

eligibility determinations on interstate claims are issued under the liable state’s law. In most

cases, employers from the liable state are financially responsible for benefit charges which reduce

the liable state’s UI trust fund balance.

Situations involving interstate claims are relatively common. In 1998, about four percent

of initial claims and continued weeks claimed were filed as interstate claims. Table IV-2 shows

the state patterns in liable state and agent state claims activity for continued weeks claimed. The

standard measurement of continued weeks claimed and insured unemployment (continued weeks
Table IV-2. Intrastate and Interstate Weeks Claimed by State, 1996, 1997 and 1998.

Intrastate Interstate Interstate Agent - (Agent - Liable)/ (Intrastate + Agent)

State Agent Liable Liable Average

1998 1998 1998 1998 1998 1997 1996 1996-98

ALABAMA 1481 92 37 55 0.035 0.036 0.035 0.035

ALASKA 610 21 126 -105 -0.166 -0.183 -0.174 -0.174

ARIZONA 988 2 79 -77 -0.078 -0.039 0.035 -0.027

ARKANSAS 1309 53 54 -0 -0.000 -0.006 -0.001 -0.002

CALIFORNIA 18624 380 524 -144 -0.008 -0.013 -0.016 -0.012

COLORADO 812 56 60 -3 -0.004 -0.013 0.005 -0.004

CONNECTICUT 1565 37 99 -63 -0.039 -0.048 -0.044 -0.044

DELAWARE 287 28 43 -15 -0.047 -0.041 -0.116 -0.068

DIST OF COL 322 30 94 -64 -0.181 -0.139 -0.199 -0.173

FLORIDA 3593 272 163 109 0.028 0.030 0.028 0.029

GEORGIA 1612 105 67 38 0.022 0.015 0.022 0.020

HAWAII 634 23 52 -30 -0.045 -0.056 -0.056 -0.052

IDAHO 616 58 24 34 0.050 0.045 0.060 0.052

ILLINOIS 5300 88 231 -143 -0.026 -0.026 -0.024 -0.026

INDIANA 1505 103 65 38 0.024 0.024 0.026 0.025

IOWA 821 31 26 4 0.005 0.007 0.016 0.009

KANSAS 656 24 71 -47 -0.070 -0.066 -0.062 -0.066

KENTUCKY 1301 54 39 15 0.011 0.015 0.018 0.015

LOUISIANA 1085 95 46 49 0.041 0.023 0.025 0.030

MAINE 560 25 23 3 0.005 0.006 0.011 0.007

MARYLAND 1662 132 110 22 0.012 0.013 0.016 0.013

MASSACHUSETTS 3245 52 131 -79 -0.024 -0.036 -0.032 -0.030

MICHIGAN 4656 62 98 -36 -0.008 -0.008 -0.005 -0.007

MINNESOTA 1591 31 79 -48 -0.030 -0.025 -0.018 -0.024

MISSISSIPPI 911 63 39 24 0.025 0.022 0.020 0.022

MISSOURI 2046 101 66 35 0.016 0.005 0.006 0.009

MONTANA 388 36 13 22 0.053 0.033 0.061 0.049

NEBRASKA 337 15 30 -15 -0.043 -0.059 -0.063 -0.055

NEVADA 843 89 127 -37 -0.040 -0.056 -0.016 -0.037

NEW HAMPSHIRE 160 36 13 23 0.116 0.125 0.127 0.123

NEW JERSEY 4585 129 238 -109 -0.023 -0.028 -0.026 -0.026

NEW MEXICO 547 46 43 3 0.005 0.011 0.031 0.016

NEW YORK 8893 108 248 -140 -0.016 -0.019 -0.023 -0.019

NORTH CAROLINA 2532 89 116 -28 -0.011 -0.009 -0.006 -0.008

NORTH DAKOTA 173 13 8 4 0.024 -0.003 0.021 0.014

OHIO 3675 73 130 -57 -0.015 -0.016 -0.011 -0.014

OKLAHOMA 614 48 23 25 0.038 0.047 0.042 0.042

OREGON 2117 117 140 -23 -0.010 -0.014 0.009 -0.005

PENNSYLVANIA 7137 176 215 -39 -0.005 -0.010 -0.014 -0.010

RHODE ISLAND 658 32 25 7 0.010 0.034 0.021 0.022

SOUTH CAROLINA 1215 71 41 30 0.023 0.024 0.024 0.023

SOUTH DAKOTA 105 12 8 4 0.033 0.023 0.034 0.030

TENNESSEE 2097 84 73 12 0.005 0.007 0.006 0.006

TEXAS 5355 392 176 216 0.038 0.026 0.036 0.033

UTAH 466 23 26 -3 -0.005 -0.007 -0.001 -0.004

VERMONT 286 15 12 2 0.007 0.005 0.002 0.005

VIRGINIA 1138 115 93 22 0.017 0.015 0.016 0.016

WASHINGTON 3589 419 240 179 0.045 0.001 -0.014 0.010

WEST VIRGINIA 768 58 25 33 0.040 0.038 0.033 0.037

WISCONSIN 2593 68 84 -16 -0.006 -0.004 -0.003 -0.004

WYOMING 151 14 15 -1 -0.006 -0.010 -0.004 -0.006

U.S. - 51 Programs 108215 4295 4608 -313 -0.003 -0.007 -0.006 -0.005

 Source: ETA-5159 data. Data on weeks claimed measured in thousands.
52

divided by 52) is to add agent state claims to intrastate claims. In other words, IU as commonly

measured in each state includes the number of interstate agent claims filed from that state. 

Table IV-2 vividly illustrates that interstate activity is of much more importance to some

states than others. The four left-hand data columns summarize data for 1998. The net difference

between interstate agent and interstate liable weeks claimed is shown explicitly. In 1998, the

number of agent weeks claimed was greater than the number of liable weeks claimed by at least

100,000 for three states; Texas, Washington and Florida. However, for five states, California,

Illinois, New York, New Jersey and Alaska, the number of agent weeks claimed was less than the

number of liable weeks claimed by at least 100,000. All five of the latter group are northern

states, and except for Alaska they are also large states. Note that the aggregate difference

between agent weeks and liable weeks amounted to less than 0.3 percent of intrastate weeks, i.e.,

313,000 versus 108,215,000. 

In states where interstate agent weeks claimed exceed interstate liable weeks claimed,

interstate claims activity tends to increase the standard measures of weeks claimed and IU. The

three right-hand data columns in Table IV-2 show the differences between agent and liable weeks

claimed expressed as a proportion of the traditional measure of weeks claimed (intrastate plus

interstate agent weeks claimed). For the three years 1996, 1997 and 1998 this ratio exceeded

0.10 in just one state, New Hampshire. Its three year average of 0.123 was more than twice that

of the second highest average of 0.052 in Idaho. Generally, states where agent weeks claimed

exceed liable weeks claimed are most consistently found in the South (14 of 17). Whereas, liable

weeks claimed exceed agent weeks claimed for the majority of the Midwestern states (8 of 12)

and western states (9 of 13). For most states, the proportions are reasonably similar across the

three years, but wide variation is observed in a few, i.e., Washington, Arizona, North Dakota and

Delaware. Very large deficits are observed for Alaska and the District of Columbia while

persistent deficits are observed for several larger northern states; Ohio, New York, New Jersey,

Massachusetts, Illinois, Minnesota and Connecticut. These latter states are generally characterized

by high benefit levels. Each year there is a net outflow of monies from these states to other areas,

most typically to states in the South. 
53

State data on weeks compensated, in contrast to initial claims and weeks claimed, are

measured as the sum of intrastate plus interstate liable weeks compensated. Thus, following the

usual measurements of IU and WB, it is theoretically possible for WB to exceed IU for a state

with large amounts of liable claims and comparatively few agent claims. Alaska meets these

conditions. Its WBIU ratio in 1998 was 1.002, and the ratio exceeded 1.00 in 25 of the 27 years

between 1972 and 1998. 

Interstate claims involve two needs for information to flow between states. The eligibility

determinations for interstate initial claims made by liable states need information from claimants

such as address, the reason for the job separation and possibly the presence of disqualifying and/or

deductible income. Traditionally, agent states have gathered and conveyed this information to

liable states. Currently, most liable states obtain this information directly from the claimant using

what is termed remote initial claimstaking procedures, i.e., the claimant calls the liable state,

typically using a toll free number.

When an initial claim is filed or a week of unemployment is claimed, the liable state needs

to inform the agent state about the claims filed by persons residing in their state. The latter

information is conveyed from liable to agent states using the Interstate Statistical Data Exchange

(commonly referred to as LADT) via of the States’ interstate network called the Interstate

Connection (ICON). The LADT statistical record summarizes information about the individual

and the claim, i.e., identification of the agent and liable States, the benefit program type, the

effective date of the claim, the industry of the separating employer, personal characteristics of the

claimant and the claimant’s mailing address. 

The processing of interstate claims is changing with the advent of telephone claims filing.

Most States use remote claimstaking procedures for initial claims and require interstate claimants

to file by telephone directly with the liable state. This procedure has advantages since liable state

claims takers are most familiar with claims procedures and legal requirements of their own states.

Thus delays in information exchange are reduced and the accuracy of determinations may be

improved when the claimant deals directly with the liable state. At present, some 28 states take

interstate liable initial claims by telephone. After completing the claim, the liable state sends

information back to the agent state so that the claim appears along with other claims in the counts
54

of interstate claims filed from the agent state. With increasing reliance on remote claimstaking, the

administrative role of agent states in interstate claims diminishes.

To measure statewide and/or national totals of weeks claimed, one may add to intrastate

claims either interstate liable claims or interstate agent claims. Data for both are routinely

reported, as illustrated by the annual data summarized in Table IV-2. For both initial claims and

continued claims, statewide totals usually include interstate agent claims but the data user may

choose either agent or liable claims depending on the question at hand. 

Commuter claims. Commuter claims also involve state border issues. Commuters reside

in one state but work in an adjacent or nearby state and are usually tied to the labor market of that

state. When commuters experience unemployment, they file for UI in the state where they work

and search for work. In the UI claims data, commuter claims are counted as intrastate claims even

though the claimants reside in another state.

There is no single definition of a commuter that is used by all states. Individual states

differ in their treatment in at least three ways: 1) the distance from the border that denotes the

outer limit of commuting (interstate claims may be filed if beyond that distance), 2) the degree of

attachment to the cross-border labor market and 3) job search requirements for commuters. The

majority of commuters reside within fifty miles of their state’s border and search for work in the

adjacent state where they most recently worked. 

Measuring commuter claimants is accomplished through information exchange among the

states. The state to which the individual commutes to work and subsequently files claims reports

the claims information, separately from interstate claims information, to the claimant’s state of

residence. The data from these reports, that show counts of claimants that commuted into the

liable state, are also used to remove commuters from the statewide counts of intrastate claimants

when the data are being used for certain purposes. 

Historically, commuter information has been exchanged between states by mailing or

faxing hard copy reports or, in recent years, through the use of e-mail. These data are used in

the Local Area Unemployment Statistics (LAUS) program of the Bureau of Labor Statistics to

estimate unemployment rates for individual counties. Currently, a new method of exchanging

commuter information is being tested. Information on commuters’ weeks claimed is being
33 Stated in another way, the states do not report on commuter claims in the same way that

they report on interstate claims as summarized in Table IV-2. Several individual states have not

developed summary measures of commuter claims for inclusion in their LADT summary reports. 

For the week of December 4, 1999, for example, 30 of 53 UI programs reported on the number

of commuter claimants in the LADT summary reports. In New England, commuter claimant

counts were supplied by Connecticut, Massachusetts, Rhode Island and Vermont but not by

Maine and New Hampshire.

55

transmitted by some states using the LADT via ICON. Once a month, these states transmit

records of weeks claimed by commuters for the CPS reference week (the week that includes the

12th of the month) for the current reporting month and the preceding reporting month. When

States are operational on the new method and comfortable with the accuracy of the data, the 

electronic data exchange method will replace the manual method.

The data exchanges involving commuter claims are part of ongoing UI administrative

operations and LAUS operations. While sufficient for these needs, additional information on

commuter claims was needed for the present project. The statewide summary totals are gross

counts (commuters from other states included in intrastate claims) summed across all adjacent

states not the net difference between agent and liable claims for each state. To the extent that a

state has a net excess of commuter claims, i.e., its agent claims exceed liable claims (more of its

residents claim benefits in adjacent states than vice versa) this would lower recipiency measures

for that state. At the same time, commuting raises recipiency measures in states where liable

claims exceed agent claims. Thus the LADT summary reports that show only gross counts cannot

be used to show the net effect of commuters on measures of UI recipiency in individual states.

What is needed for each state is the net difference between the agent weeks and liable weeks

claimed by commuters.33

To pursue this question further, the project secured data on commuter claims from the UI

research offices in Massachusetts and Rhode Island. Monthly data on commuters were obtained

for 1998 and 1999 for each of their respective border states. The data pertained to both state

residents filing in the adjacent states and to adjacent state residents filing within these two states.

The objective was to adjust measures of recipiency to remove the effects of commuter claims.

Originally we hoped to obtain data from New Hampshire, but their information system did not
56

have ready data on commuters for all of 1998 and 1999. However, we were able to adjust New

Hampshire data using information obtained from Massachusetts. 

Table IV-3 summarizes information from three states (Massachusetts, Rhode Island and

New Hampshire) for 1998 and 1999. Panel A has LADT data while Panel B has ETA-5159 data

and Panel C displays measures of UI recipiency, (IUTU ratios) both levels and state ranks within

the 51 programs for which the data are available. All data are weekly averages. Line 2 of Panel A

shows total commuters while line 3 shows net commuter claims. Massachusetts has a deficit, i.e.,

fewer of its residents claim outside the state than out-of-staters claiming in Massachusetts, while

Rhode Island and New Hampshire have surpluses. Note that the New Hampshire data refer just to

the Massachusetts-New Hampshire pair and exclude information on its two other adjacent states

(Maine and Vermont). 

If commuting were ignored, the IUTU ratio would be too high in Massachusetts but too

low in Rhode Island and New Hampshire. Observe in Panel A that the net effect of commuting

summed across the three states is small (301 in 1998 and 263 in 1999) whereas the lowest net

effect for the six entries shown in line 3 is the 732 for Rhode Island in 1998. Line 5 shows how

intrastate weeks claimed should be adjusted in both Massachusetts and Rhode Island to remove

the net effects of commuting. For Massachusetts intrastate weeks would be lower while for

Rhode Island (and New Hampshire) intrastate weeks would be higher.

Panel B displays ETA-5159 data on intrastate and interstate weeks claimed. Line 8 shows

corrected estimates of intrastate weeks claimed. The line 8 entries were derived directly from the

product of lines 5 and 6 for Massachusetts and Rhode Island. Note the similarities between lines 3

and 7. Line 3 data were used as controls in deriving the estimates for New Hampshire shown in

line 7. The ratio between the Massachusetts “deficit” and the combined “surpluses” for Rhode

Island and New Hampshire from line 3 (0.837 in 1998) was used to derive the missing data for

New Hampshire. Once this estimate was derived, it was added to line 6 to yield the corrected

New Hampshire estimate shown in line 8.

Lines 9 and 10 show interstate agent and liable data from the ETA-5159 reports.

Massachusetts and New Hampshire exhibit strong contrasts in agent versus liable claims. For

Massachusetts liable weeks are more than twice agent weeks while the opposite is true for New
Table IV-3. Estimated Effect of Commuter Claims on IUTU Ratios in Three States, 1998 and 1999

1998 1999

Massa- Rhode New Hamp- Massa- Rhode New Hampchusetts Island shire chusetts Island shire

Panel A. LADT data - Annual averages of weeks claimed for the week of the 12th-a

 1. Total Intrastate Weeks 50693 9779 53234 9400

 Claimed

 2. Commuter Claims Filed 2248 345 58 2763 362 67

 In-State

 3. Net Effect of Commuter -1546 732 1115 -2011 960 1314

 Claims-b

 4. State Residents Intra- 49147 10511 51223 10360

 state Claims (lines1 + 3)

 5. State Residents to Total 0.970 1.075 0.962 1.102

 Intrastate Claims Ratio

 (line 4/line 1)

Panel B. ETA 5159 Data - Annual averages of weeks claimed

 6. Total Intrastate Weeks 62395 12648 3081 65280 12843 3045

 Claimed

 7. Estimated Net Effect of -1903 947 1327 -2466 1312 1478

 Commuter Claims-c

 8. Corrected Intrastate 60492 13595 4408 62814 14155 4523

 Weeks Claimed-c

 9. Interstate Agent Weeks 1000 611 693 962 312 659

 Claimed

10. Interstate Liable Weeks 2512 476 254 2166 438 271

 Claimed

11. Insured Unemployment 63395 13259 3774 66242 13155 3704

 (line 6 plus line 9)

12. Corrected Insured 61492 14206 5101 63776 14467 5182

 Unemployment (lines8 + 9)

13. Total Unemployment 109114 24343 18931 104780 20890 18068

Panel C. State measures of UI recipiency 

14. IUTU 0.581 0.545 0.199 0.632 0.630 0.205

15. Corrected IUTU 0.564 0.584 0.269 0.609 0.693 0.287

16. IUTU - State Rank 2 3 47 2 3 48

17. Corrected IUTU - State 3 2 38 3 1 34

 Rank

a - Data from special tabulations supplied by Massachusetts and Rhode Island. Comparable estimates for 

 New Hampshire were not available. Data displayed for New Hampshire were derived from information

 provided by Massachusetts.

b - Difference between state residents filing in adjacent states (agent) and out-of-state commuters filing in-state.

c - Estimated using lines 5 and 6 in Massachusetts and Rhode Island and line 3 for New Hampshire.
34 The national IUTU ratios in 1998 and 1999 were 0.348 and 0.364 respectively. New

Hampshire’s corrected ratios were less than 0.8 of the national ratio in both years. It should also

be noted that the New Hampshire estimates are the least firm. 1) Commuting data from Vermont

and Maine could not be included. 2) If commuters actually collected in New Hampshire, their

duration would probably be lower than in Massachusetts. The net effect of both considerations is

not clear, but the second alone would reduce the corrected estimate for New Hampshire.

58

Hampshire. Recall that insured unemployed is usually measured using interstate agent weeks

along with intrastate weeks. Since there are two estimates of intrastate weeks (lines 6 and 8),

Panel B shows the two corresponding estimates of IU in lines 11 and 12 respectively.

The effects of correcting for commuter claims are summarized in Panel C. Placing

commuters back into their state of residence reduces the IUTU ratio in Massachusetts and

increases it in both Rhode Island and New Hampshire. Because Massachusetts is so much larger

than the other two states, its IUTU ratio is least affected by these adjustments. The biggest effects

are found in New Hampshire where the IUTU ratio increases from 0.199 to 0.269 in 1998 and

from 0.205 to 0.287 in 1999. The bottom lines reinforce the preceding by showing state IUTU

rankings before and after the corrections for commuting. The IUTU ratio in New Hampshire is

affected the most. However, even after the corrections, New Hampshire still has an IUTU ratio

considerably below the national average in both years.34 

Four conclusions about the effects of commuter claims on recipiency measures can be

suggested. 1) Measures of recipiency in small states are likely to be more affected by commuting

than measures in large states. Lines 14 and 15 from Table IV-3 illustrate this point. Rhode Island

and New Hampshire ranked 43rd and 39th respectively (out of 51) in their levels of 1998 taxable

covered employment. Thus New Hampshire is probably at the extreme in terms of the size of the

effect of commuting on measured recipiency. 2) Patterns of net commuting may be similar to

patterns of agent/liable interstate claims for a given state. This is true for both Massachusetts and

New Hampshire. (Note Tables IV-2 and IV-3.) 3) For most states, the omission of a correction

for commuting probably has rather small effects. The previous three-state example was taken

from a geographic area (New England) where commuting across state borders is especially

prevalent. 4) More research on this topic would be helpful. From interstate claims data of Table

IV-2, it is clear that the District of Columbia, Maryland and Virginia would be a trio of states
35 To be an interstate CWC there must be base period earnings in two or more states.

Suppose a claimant satisfies the eligibility criteria of two other states (other than the state of

residence). There are two options in filing. First, select the preceding state with earnings and file

an interstate CWC claim. Second, select the third state. Under the second option, the person can

only use the earnings from the third state, and the claim becomes a regular interstate claim. 

59

worth examining. 

Combined Wage Claims. For measurable numbers of claimants, base period employment

and wages reflect jobs held in two or more states. When these claimants file for benefits, wages

are transferred from one state to another for use in the determination of benefit entitlement. The

term combined wage claims (CWC) is used to describe these situations. 

There are two types of CWC cases, intrastate and interstate. People typically file CWC

applications in their state of residence (although there is no requirement that residents file instate). If the claimant satisfies the state’s eligibility requirements, the person is compensated

under its statutory payment provisions. Although the person has wages from two or more states,

the benefit calculation provisions of the paying state (usually state of filing) determine the weekly

benefit amount, maximum duration and the replacement rate. When the CWC is filed under the

law of the State in which the claimant lives or commutes to work, the claim is termed an intrastate

CWC claim and that state is both the filing state and the paying state in CWC reporting. It is not

necessary that the person have in-state base period earnings to be an intrastate CWC claimant. 

The CWC rules require only that the person’s combined wages from all states satisfy the monetary

eligibility requirements of the filing state. 

Interstate CWC cases involve people applying for benefits in their state of residence, not

satisfying the state’s eligibility criteria, but qualifying on the basis of combining wages under the

law of another state where they have earnings. The administrative rule for determining the paying

state for an interstate CWC claim is that the paying state must be the last state where the claimant

worked in covered employment and satisfies that state’s eligibility criteria.35

Table IV-4 summarizes the importance of CWC activity by state for the three years 1996,

1997 and 1998. The three left hand data columns show CWC weeks as a proportion of total

weeks compensated. As a share of total weeks for the 50 states in the table, CWC weeks ranged
Table IV-4. Prevalence of Combined Wage Claims, 1996-1998

CWC Weeks/Total Weeks Compensated Interstate CWC Weeks/Total CWC Weeks

State 1998 1997 1996 1998 1997 1996

ALABAMA 0.025 0.029 0.028 0.045 0.052 0.049

ALASKA 0.029 0.026 0.031 0.147 0.122 0.142

ARIZONA 0.107 0.109 0.096 0.046 0.041 0.042

ARKANSAS 0.068 0.040 0.004 0.038 0.035 0.041

CALIFORNIA 0.018 0.018 0.017 0.048 0.051 0.056

COLORADO 0.023 0.023 0.023 0.113 0.110 0.101

CONNECTICUT 0.011 0.010 0.009 0.060 0.066 0.060

DELAWARE 0.012 0.012 0.012 0.000 0.000 0.000

FLORIDA 0.032 0.032 0.033 0.057 0.065 0.063

GEORGIA 0.032 0.032 0.031 0.011 0.012 0.013

HAWAII 0.016 0.015 0.016 0.110 0.132 0.135

IDAHO 0.069 0.067 0.070 0.043 0.046 0.054

ILLINOIS 0.004 0.004 0.004 0.055 0.065 0.049

INDIANA 0.019 0.019 0.030 0.044 0.050 0.045

IOWA 0.045 0.046 0.046 0.040 0.041 0.048

KANSAS 0.100 0.104 0.102 0.043 0.042 0.067

KENTUCKY 0.045 0.051 0.052 0.024 0.030 0.024

LOUISIANA 0.030 0.035 0.038 0.040 0.039 0.031

MAINE 0.012 0.021 0.031 0.007 0.033 0.051

MARYLAND 0.048 0.037 0.036 0.040 0.026 0.032

MASSACHUSETTS 0.006 0.006 0.006 0.040 0.043 0.039

MICHIGAN 0.010 0.012 0.011 0.050 0.060 0.079

MINNESOTA 0.209 0.048 0.046 0.054 0.099 0.082

MISSISSIPPI 0.030 0.036 0.033 0.051 0.052 0.051

MISSOURI 0.028 0.026 0.026 0.066 0.058 0.054

MONTANA 0.081 0.075 0.075 0.046 0.052 0.034

NEBRASKA 0.024 0.029 0.029 0.082 0.088 0.101

NEVADA 0.038 0.037 0.040 0.095 0.071 0.093

NEW HAMPSHIRE 0.201 0.106 0.140 0.134 0.132 0.037

NEW JERSEY 0.028 0.026 0.023 0.036 0.036 0.039

NEW MEXICO 0.049 0.057 0.051 0.063 0.025 0.049

NEW YORK 0.002 0.003 0.002 0.051 0.051 0.054

NORTH CAROLINA 0.038 0.043 0.035 0.110 0.084 0.067

NORTH DAKOTA 0.049 0.040 0.040 0.012 0.035 0.018

OHIO 0.033 0.033 0.031 0.040 0.042 0.044

OKLAHOMA 0.051 0.060 0.053 0.028 0.030 0.031

OREGON 0.045 0.050 0.053 0.077 0.071 0.067

PENNSYLVANIA 0.027 0.025 0.022 0.047 0.046 0.048

RHODE ISLAND 0.060 0.055 0.050 0.000 0.000 0.001

SOUTH CAROLINA 0.026 0.030 0.022 0.049 0.054 0.049

SOUTH DAKOTA 0.046 0.048 0.040 0.037 0.090 0.105

TENNESSEE 0.035 0.037 0.032 0.039 0.047 0.046

TEXAS 0.070 0.064 0.046 0.026 0.017 0.027

UTAH 0.045 0.052 0.067 0.033 0.054 0.061

VERMONT 0.042 0.042 0.044 0.075 0.086 0.089

VIRGINIA 0.033 0.036 0.036 0.058 0.032 0.055

WASHINGTON 0.068 0.067 0.062 0.068 0.074 0.076

WEST VIRGINIA 0.083 0.087 0.081 0.017 0.024 0.028

WISCONSIN 0.028 0.025 0.024 0.044 0.031 0.043

WYOMING 0.093 0.100 0.100 0.089 0.095 0.101

U.S. 50 States 0.032 0.029 0.027 0.049 0.048 0.051

Source: Data on weeks compensated from ETA-586 and ETA-5159 reports. District of Columbia data

 not available for all three years.
36 The data in Table IV-4 refer to 50 states. The District of Columbia, Puerto Rico and the

Virgin Islands are not included.

37The high percentage in Minnesota in 1998 reflects the one time effects of a large scale

work stoppage. The data for 1997 and 1996 are more typical of Minnesota’s usual experiences.

61

from 2.7 percent to 3.2 percent.36 The CWC shares are consistently highest in New Hampshire,

Arizona, Kansas and Wyoming, averaging from 10 to 13 percent of weeks compensated.37

Conversely averages of 1.0 percent or lower are observed for New York, Illinois, Massachusetts

and Connecticut. For most states, the three annual proportions are quite similar suggesting that

CWC activities constitute a stable component of most states’ workloads, at least for the three

years covered by Table IV-4. 

Interstate CWC weeks compensated averaged roughly 5.0 percent of total CWC weeks in

each of the three years. Four states (Alaska, New Hampshire, Colorado and Hawaii) had

interstate averages of at least 10.0 percent while three (Delaware, Rhode Island and Maine) had

averages below 1.0 percent. Again, the percentages were quite similar for most states across the

three years. The quantitative importance of interstate CWC payments is obviously small, i.e., 5.0

percent of a universe that represents 3.0 percent of all weeks compensated. 

It should be emphasized that claimants with earnings in two or more states do not always

file under the CWC program. Claimants that have sufficient base period earnings in a single state

or in more than one state, to qualify separately have a choice in selecting to file against wages

earned in a single state as an intrastate or interstate claim. Individual decisions in these situations

probably involve considerations such as the length of the waiting period, the maximum weekly

benefit, potential benefit duration and the treatment of other income in the individual states. Many

claimants will select the state with the highest expected benefit payments.

State Border Issues: Summary. A few comments about state border issues and recipiency

are appropriate. For two situations, interstate claims and CWC, the UI reporting system classifies

claimants by the state in which or from which the claim is filed. This is usually the state of

residence. Thus, in using the IUTU ratio as a measure of recipiency, regular interstate agent

claims and CWC intrastate claims generally enter the numerator on the basis of state of residence

just as they do for TU as measured by the CPS. CWC interstate claims, although of very small
62

quantitative importance, also generally classify people by state of residence. 

Commuter claims present a different situation. The data from Massachusetts, New

Hampshire and Rhode Island indicate that there can be measurable effects in an area where large

numbers of commuters cross state borders, states differ in size and there is one predominant

direction of commuting, e.g., into Massachusetts. When the IUTU ratios were “corrected” there

was a measurable increase in recipiency in New Hampshire. However, even with the corrections,

recipiency in New Hampshire was still well below the national average.

Because correcting for commuter claims cannot be readily done within existing UI and

LAUS reporting systems, this is a topic that requires additional data collection before a full

picture of its importance can be obtained. Assessing the importance of commuter claims will be

easier when the automated ICON commuter reporting has been implemented in all states. But

even then, an accurate assessment of the effects of commuting requires summaries of net cross

border commuting patterns for each state, something not contemplated at present in the ICON

summaries. Note that the required information is generated by LADT micro records within the

ICON system. However, these records need to be summarized in a manner different from that of

existing summary reports. 

The preceding also identified an important distinction between IUTU ratios and WBTU

ratios as measures of recipiency. The WBTU ratio is measured using interstate liable weeks

compensated. Liability and current residence differ in about 4 percent of weeks compensated, and 

it is possible for WB to exceed IU in a state where liable weeks greatly exceed agent weeks. For

Alaska and the District of Columbia liable claims are far larger than agent claims while New

Hampshire is at the opposite extreme. A number of states with low recipiency, especially in the

South, have many more agent weeks than liable weeks. However the same also applies to

Montana, Idaho and Washington where IUTU and WBTU ratios are typically high. 

Perhaps a final comment about New Hampshire should also be made. It shows up as high

on all three cross border measures of UI claims examined here. Being a small state next to a large

state with higher wages contributes to this situation. Also relevant is New Hampshire’s high

monetary eligibility requirements, unusual base period (a factor that will change after April 2001)
38 These are discussed in Chapter VI.

39 See Table 3A in Vroman (1991) for application rates in 1989-1990 and Wandner and

Stettner (2000) for application rates in 1993.

63

and its activist stance in monitoring continuing eligibility for benefits.38 Cross border commuting is

but one of several factors that contribute to low recipiency in New Hampshire. 

Reason for Unemployment

The monthly household labor force survey (CPS) distinguishes four different reasons for

unemployment: 1) job losers, 2) job leavers, 3) labor force reentrants and 4) new entrants into the

labor force. The first two are flows into unemployment by persons previously employed. The final

two are flows into unemployment by persons previously outside the labor force (or economically

inactive). Job loser unemployment arises from employer-initiated job separations. The CPS

distinguishes temporary from permanent job separations. Job leavers flow into unemployment

from their own decisions to leave (or quit) their jobs. Reentrants, the third category, are

individuals who have held jobs in the past, but subsequent to ending their previous job, have spent

time outside the labor force. All unemployed reentrants were either job losers or job leavers when

they left their last jobs. Because many unemployed reentrants were outside the labor force less

than twelve months, they often have base period earnings that satisfy UI monetary eligibility

criteria. New entrants usually have never worked in the past. For the decade of the 1990s the four

reasons for unemployment had the following average proportions: job losers -- 0.495, job leavers

-- 0.115, reentrants -- 0.302 and new entrants -- 0.088. 

Of the four “reason” categories, job losers are the group most likely to apply for and

receive UI benefits. Special supplements to the CPS have asked questions about application rates

by reason for unemployment. Nationwide, application rates for job losers fall into the 0.50-0.70

range while application rates for leavers and reentrants fall into the 0.10-0.15 range.39

Over the business cycle, the mix of unemployment by reason changes with the job loser

proportion increasing during recessions. Thus time series data show that IUTU and WBTU ratios

increase in recessions and fall during periods of economic recovery due partly to the changing 

mix of unemployment by reason. For the post-World War II years, this pattern for both ratios was
40 The terms “urgent, compelling and necessitous” for quitting are often included in

statutory language or administrative guidelines in states that compensate quits for good personal

reasons. In terms of the four reasons for unemployment, compensation may be paid to quitters

and to reentrants who may have quit before exiting the labor force.

64

shown earlier in Chart II-1 of Chapter II.

The mix of unemployment by reason also varies across the states. Because job losers are

so much more likely to apply for and collect UI benefits than the other unemployed groups,

interstate variation in job loser proportions may contribute to interstate variation in UI recipiency.

High recipiency in some states could reflect above-average job loser proportions. 

States undoubtedly vary in the share of job losers, job leavers and reentrants that apply for

and receive UI benefits. Some states recognize good personal reasons for quitting work40 and

allow payment of benefits in specified situations. Other states compensate job quitters only if the

quit was related to the job (or good cause restricted in the language of UI administrators). In

2000, only 15 UI programs recognized good personal reasons for quitting in making UI eligibility

determinations. State practices in this area undoubtedly vary more widely than suggested by the

presence or absence of this particular phrase in statutory language. Recipiency among job losers

probably also varies widely across the states.

Table IV-5 displays data on job loser proportions by state averaged for the 22 years 1978

to 1999. The states are arrayed by census division: eight of the nine standard census divisions with

the ninth (South Atlantic) division divided into northern and southern components. The first data

column in Table IV-5 shows proportions of annual weeks of unemployment accounted for by job

loser unemployment. The range in proportions is from 0.559 (New Jersey) to 0.369 (South

Dakota). The national average proportion was 0.485 for these years. For the top 13 states, the

simple average proportion of 0.525 was 27.1 percent higher than the average of 0.413 for the

bottom 13 states. The range and these averages both show that job loser proportions do vary

considerably across states.

The job loser proportions in the first data column of Table IV-5 refer to all weeks of

unemployment. These data are routinely available by state in so called geographic profile data,

first available for all states with detailed duration intervals in 1977. 
Table IV-5. Total Unemployment and Job Loser Unemployment by State, 1978-1999 Averages.

Census P Loser P Loser P Loser P Loser P Loser PLoser PMLoser PWLoser Sim Avg.

Division All New Spells Men Women All New Spells New Spells New Spells Applic. Applic.

Weeks New Spells New Spells Weeks Div Div Div Rate Rate

Connecticut N Eng 0.509 0.436 0.264 0.171 0.531 0.678

Maine N Eng 0.534 0.465 0.283 0.182 0.549 0.805

Massachusetts N Eng 0.531 0.436 0.271 0.165 0.532 0.630

New Hampshire N Eng 0.461 0.414 0.254 0.160 0.518 0.435

Rhode Island N Eng 0.541 0.481 0.272 0.209 0.559 0.985

Vermont N Eng 0.530 0.466 0.285 0.181 0.518 0.450 0.272 0.178 0.550 0.611

New Jersey M Atl 0.559 0.474 0.284 0.190 0.554 0.611

New York M Atl 0.523 0.454 0.278 0.176 0.542 0.565

Pennsylvania M Atl 0.540 0.462 0.302 0.160 0.540 0.463 0.288 0.175 0.547 0.785

Illinois EN Cent 0.506 0.416 0.265 0.151 0.519 0.454

Indiana EN Cent 0.493 0.419 0.257 0.161 0.521 0.447

Michigan EN Cent 0.487 0.430 0.285 0.145 0.528 0.605

Ohio EN Cent 0.507 0.422 0.282 0.139 0.523 0.508

Wisconsin EN Cent 0.513 0.449 0.289 0.160 0.501 0.427 0.275 0.152 0.539 0.709

Iowa WN Cent 0.459 0.381 0.256 0.125 0.498 0.502

Kansas WN Cent 0.440 0.375 0.240 0.134 0.495 0.470

Minnesota WN Cent 0.482 0.399 0.272 0.127 0.510 0.421

Missouri WN Cent 0.494 0.423 0.267 0.155 0.524 0.648

Nebraska WN Cent 0.391 0.347 0.221 0.126 0.478 0.409

North Dakota WN Cent 0.441 0.420 0.274 0.146 0.522 0.493

South Dakota WN Cent 0.369 0.338 0.185 0.153 0.440 0.383 0.245 0.138 0.473 0.328

Delaware S Atl-a 0.491 0.425 0.275 0.150 0.525 0.573

District of Columbia S Atl-a 0.455 0.390 0.225 0.165 0.504 0.419

Maryland S Atl-a 0.443 0.377 0.241 0.135 0.496 0.427

West Virginia S Atl-a 0.514 0.455 0.340 0.115 0.476 0.412 0.270 0.142 0.543 0.405

Florida S Atl-b 0.431 0.376 0.228 0.148 0.495 0.235

Georgia S Atl-b 0.420 0.382 0.212 0.170 0.499 0.481

North Carolina S Atl-b 0.435 0.389 0.215 0.174 0.503 0.892

South Carolina S Atl-b 0.462 0.412 0.235 0.177 0.517 0.734

Virginia S Atl-b 0.381 0.338 0.191 0.147 0.426 0.403 0.246 0.157 0.473 0.430

Alabama ES Cent 0.488 0.429 0.257 0.172 0.528 0.565

Kentucky ES Cent 0.465 0.402 0.266 0.135 0.511 0.566

Mississippi ES Cent 0.440 0.373 0.217 0.156 0.494 0.477

Tennessee ES Cent 0.475 0.398 0.231 0.167 0.467 0.386 0.233 0.153 0.509 0.617

Arkansas WS Cent 0.424 0.370 0.226 0.144 0.492 0.581

Louisiana WS Cent 0.464 0.406 0.274 0.132 0.514 0.353

Oklahoma WS Cent 0.426 0.370 0.245 0.125 0.492 0.335

Texas WS Cent 0.420 0.364 0.241 0.123 0.434 0.386 0.244 0.142 0.488 0.244

Arizona Mountain 0.424 0.375 0.250 0.126 0.495 0.301

Colorado Mountain 0.413 0.355 0.223 0.131 0.483 0.301

Idaho Mountain 0.499 0.460 0.304 0.156 0.546 0.615

Montana Mountain 0.447 0.388 0.266 0.122 0.503 0.470

Nevada Mountain 0.518 0.465 0.317 0.149 0.549 0.519

New Mexico Mountain 0.433 0.356 0.256 0.100 0.483 0.260

Utah Mountain 0.410 0.348 0.224 0.124 0.479 0.325

Wyoming Mountain 0.442 0.402 0.285 0.117 0.448 0.394 0.266 0.128 0.511 0.385

Alaska Pacific 0.495 0.444 0.323 0.121 0.537 0.766

California Pacific 0.507 0.459 0.293 0.166 0.545 0.617

Hawaii Pacific 0.429 0.368 0.250 0.119 0.491 0.578

Oregon Pacific 0.493 0.447 0.286 0.161 0.538 0.663

Washington Pacific 0.482 0.437 0.282 0.155 0.481 0.431 0.287 0.144 0.532 0.600

United States 0.485 0.416 0.264 0.153 0.485 0.416 0.264 0.153 0.520 0.536

State Averages

Mean 0.469 0.409 0.260 0.149 0.473 0.409 0.260 0.149 0.515 0.526

Variance 0.0020 0.0015 0.0010 0.0005 0.0006 0.0266

Std.Deviation 0.045 0.039 0.032 0.022 0.024 0.163

Coeff. of Variation 0.095 0.096 0.123 0.149 0.046 0.310

Source: Special tabulation of data from the monthly labor force survey conducted for the Bureau of Labor Statistics. 

 a - Four northern states of the South Atlantic division. b - Five southern states of the South Atlantic division.
41 The professional staff of BLS provided this tabulation.

66

Data on unemployment duration for the individual reasons show that duration is

systematically longer for job losers than for job leavers, reentrants and new entrants. Thus job

losers account for a higher proportion of all weeks of unemployment than their proportion of new

spells (onsets) of unemployment. 

This project approximates new spells of unemployment with counts of unemployment of

less than five weeks summed across the twelve months of each year. Annual new spells by reason

by state are not routinely published by BLS. However, new spells from the CPS provide the

logical metric for examining UI application rates (ICNU ratios). As noted, higher application rates

would be expected in states where the job loser proportion of new spells is above-average. 

To further examine this issue, the project secured a special tabulation of unemployment of

less than five weeks cross-classified by reason and gender.41 The second data column in Table IV5 shows average job loser proportions among estimated new spells by state for the same 22 years

1978 to 1999. 

The job loser proportions of new spells vary widely by state. The range in Table IV-5 is

from a high of 0.481 (Rhode Island) to a low of 0.338 (South Dakota) with a national average of

0.416. Job losers accounted for just over 40 percent of all new unemployment spells between

1978 and 1999. The ratio of the average job loss proportion for the highest 13 states was 0.460,

or 27.7 percent higher than the average proportion of 0.360 for the 13 lowest states.

Table IV-5 also shows the gender breakdown of new spells among job losers. The national

average proportions were 0.264 for men and 0.153 for women. Men accounted for more than 60

percent of job loser spells of unemployment between 1978 and 1999. Substantial interstate

variation by gender in these proportions is apparent.

Systematic differences in job loser proportions are observed across the census divisions.

Above-average proportions are observed in New England, Mid-Atlantic and East North Central

states. The converse holds for four divisions: West North Central, Southern South Atlantic, West

South Central and Mountain. Many states in the former three divisions have high recipiency while

many states in the latter four divisions have low recipiency. This again is suggestive of a possible
42 The new entrant proportion of new spells was assumed to be 0.10 in each state.

67

link between UI recipiency and the composition of unemployment by reason.

To pursue this question somewhat further, a simple simulation was executed using known

information on differences in UI application rates by reason for unemployment. A simulated

overall application rate was projected for each state assuming the job loser application proportion

was 0.70. This proportion was applied to the second data column in Table IV-5. The application

proportion was assumed to be 0.10 for both job leavers and reentrants and 0.00 for new

entrants.42 The resulting simulated application rates are displayed in the second column from the

right in Table IV-5. Simulated application rates ranged from a high of 0.559 (Rhode Island) to a

low of 0.473 (South Dakota). The simple average for the 51 programs was 0.515.

The final column of the table shows average application rates (ICNU ratios) for the 1978-

1999 period. In comparing actual with simulated UI application rates, three observations can be

made. 1) The actual application rates display much more variation than the simulated application

rates. The range of average application rates was from 0.985 (Rhode Island) to 0.235 (Florida).

For the 13 states with highest application rates the simple average was 0.733 whereas the lowest

13 had a simple average of 0.331. In contrast, the full range of simulated application rates was

only from 0.559 (Rhode Island) to 0.473 (South Dakota). Coefficients of variation for the two

series reinforce the contrast in their variability. The coefficient of variation for the simulated

application rates (standard deviation divided by the mean) at the bottom of Table IV-5 was 0.046

compared to 0.310 for the actual application rates. Relative variability was more than six times as

large for the actual application rates compared to the simulated rates. 2) There is an association

between the simulated application rates and the actual application rates. For the 13 states with

highest actual application rates, the simulated application rates averaged 0. 533 compared with a

simulated average of 0.495 for the 13 with the lowest actual application rates. 3) These

calculations are only suggestive, a gross (mutatis mutandis) comparison rather than a ceteris

paribus comparison which holds other factors constant. In Chapter V, the regression analysis

conducts formal tests for the effects of variation in job loser proportions on application rates. 
68

Chart IV-1 gives a visual display of the relative variability of the two application rates.

States are sorted from high to low according to the 1978-1999 average of the actual application

rate. The much wider variability of the actual application rates is vividly illustrated. 

Unemployment Duration

Several measures of unemployment duration are available from the household labor force

survey (CPS) and from UI program data. Table IV-6 displays eight series for the fifty years 1950

to 1999. Seven show average duration measured in weeks while the eighth, the UI exhaustion

rate, shows the percentage of claimants who entirely use up their entitlement to UI benefits. 

Seven series in Table IV-6 convey a common message which is clearly seen in the decade

averages at the bottom of the table. During the most recent two decades, i.e., the 1980s and the

1990s, unemployment duration was systematically longer than in the preceding three decades.

This is true for all four household labor force survey series and for three UI series (all but

potential duration). In contrast, note that average potential duration for UI recipients was little

changed in the 1980s and 1990s compared to earlier decades. The increase in the UI exhaustion

rate can be seen as a consequence of longer average benefit duration coupled with an unchanging

potential benefit duration. During the most recent two decades somewhat more than one third of

recipients have exhausted their UI benefits.

Nearly all the duration measures in Table IV-6 are affected by the phenomenon of

truncation. The measures are restricted in one or more ways, yielding an estimate that is lower

than the true duration of unemployment if it were followed to the end of each spell. Some

descriptive details of the individual duration measures may be helpful. 

The first two series, the mean and median monthly averages, measure the duration of

individual spells of unemployment. If a person experiences two or more spells in a given year,

these series show averages based on the duration of each individual spell measured from the onset

of unemployment up to the time of the labor force survey. In cases where the spell started in the

previous year, duration is still measured from the onset of the spell. The mean and median in

columns (1) and (2) respectively are both truncated in that the unemployment spells may extend

past the point of measurement in the labor force survey.
1

1121314151

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Proportions

Sim. Application Rate Actual Application Rate

Chart IV-1. Actual and Simulated Application Rates
Table IV-6. Measures of Average Unemployment Duration, 1950 to 1999.

 Household Labor Force Survey UI Program Data

Year Mean, Median, Mean, Mean, Actual Potential Actual Exhaustion

Monthly Monthly Project Work Duration, Duration Duration Rate - Pct.

Average, Average Estimate, Experience ADUI Exhaustees

ADPUB AD

(1) (2) (3) (4) (5) (6) (7) (8)

1950 12.1 NA 9.83 NA 13.02 21.1 19.3 35.6

1951 9.7 NA 7.57 NA 10.08 21.4 17.9 19.6

1952 8.4 NA 7.19 NA 10.44 22.0 19.3 21.2

1953 8.0 NA 6.96 NA 10.07 22.1 19.2 18.1

1954 11.8 NA 9.54 NA 12.79 22.4 20.0 26.8

1955 13.0 NA 9.26 11.97 12.44 22.7 20.3 28.2

1956 11.3 NA 8.44 12.77 11.39 23.0 20.0 21.0

1957 10.5 NA 8.80 13.39 11.52 23.4 20.5 20.4

1958 13.9 NA 11.38 15.86 14.78 23.5 21.7 32.0

1959 14.4 NA 10.23 13.95 13.09 23.6 21.7 28.8

1960 12.8 NA 9.71 14.26 12.68 24.0 21.4 23.7

1961 15.6 NA 11.31 14.78 14.77 23.9 21.8 33.3

1962 14.7 NA 10.19 14.21 13.07 23.9 21.6 26.7

1963 14.0 NA 10.07 14.13 13.29 24.1 21.6 25.8

1964 13.3 NA 9.67 13.25 13.02 24.2 21.9 24.7

1965 11.8 NA 8.96 11.57 12.00 24.1 21.3 21.8

1966 10.4 NA 7.92 10.31 11.27 24.2 21.1 18.4

1967 8.7 2.3 7.89 10.09 11.48 24.5 20.9 18.2

1968 8.4 4.5 7.66 9.64 11.62 24.3 21.2 19.5

1969 7.8 4.4 7.53 9.83 11.39 24.4 21.4 18.6

1970 8.6 4.9 8.29 12.50 12.31 24.6 22.1 20.0

1971 11.3 6.3 9.68 14.20 14.39 24.5 22.7 30.8

1972 12.0 6.2 9.44 13.57 14.20 24.3 22.7 31.2

1973 10.0 5.2 8.50 12.13 13.32 24.3 22.5 27.6

1974 9.8 5.2 8.58 12.35 12.58 24.4 22.4 24.5

1975 14.2 8.4 11.69 16.37 15.68 24.3 22.4 37.2

1976 15.8 8.2 11.28 15.94 14.89 24.0 22.6 37.6

1977 14.3 7.0 10.38 14.82 14.17 24.1 22.1 34.2

1978 11.9 5.9 9.38 13.87 13.32 24.5 22.5 26.6

1979 10.8 5.4 9.01 13.41 13.04 24.2 22.4 24.6

1980 11.9 6.5 10.04 15.79 14.84 24.3 22.7 30.5

1981 13.7 6.9 10.39 15.90 14.40 24.2 23.0 31.8

1982 15.6 8.7 11.92 18.17 15.85 24.3 23.2 35.8

1983 20.0 10.1 13.01 18.21 17.40 24.1 23.4 46.9

1984 18.2 7.9 11.05 16.73 14.30 23.7 22.8 33.4

1985 15.6 6.8 10.30 16.05 14.16 24.1 22.7 30.6

1986 15.0 6.9 10.35 16.42 14.47 23.9 22.9 32.0

1987 14.5 6.5 9.91 16.06 14.57 23.7 22.7 33.2

1988 13.5 5.9 9.42 15.27 13.70 24.1 22.7 28.6

1989 11.9 4.8 8.91 14.48 13.24 24.2 22.9 26.1

1990 12.0 5.3 9.35 15.06 13.43 24.1 23.1 26.6

1991 13.7 6.8 10.74 16.91 15.38 23.9 23.2 34.2

1992 17.7 8.7 12.34 17.94 16.21 23.7 23.3 41.3

1993 18.0 8.3 11.85 18.91 15.91 23.9 23.4 40.5

1994 18.8 9.2 12.70 17.22 15.44 23.7 23.2 49.9

1995 16.6 8.3 11.88 17.17 14.66 24.0 23.1 32.8

1996 16.7 8.3 11.91 17.24 14.82 24.0 23.2 34.0

1997 15.8 8.0 11.51 16.82 14.48 23.9 23.0 33.7

1998 14.5 6.7 10.26 16.36 13.79 23.7 22.2 30.8

1999 13.4 6.4 9.92 16.01 14.38 23.8 22.2 31.4

 Avg.

 1950s 11.3 NA 8.9 NA 11.96 22.5 20.0 25.2

 1960s 11.8 NA 9.1 12.21 12.46 24.2 21.4 23.1

 1970s 11.9 6.3 9.6 13.92 13.79 24.3 22.4 29.4

 1980s 15.0 7.1 10.5 16.31 14.69 24.1 22.9 32.9

 1990s 15.7 7.6 11.2 16.96 14.85 23.9 23.0 35.5

 Source: Bureau of Labor Statistics and Office of Workforce Security. All data in weeks except the exhaustion 

 rate. Average duration in work experience data derived by the author. NA - Information not available
43State level detail appears in various issues of the U.S. Department of Labor, Bureau of

Labor Statistics (1998).

71

Analyses of unemployment duration find that the escape rate from unemployment is linked

to the length of time an individual is unemployed. The longer a person is unemployed the more

likely he or she will remain unemployed in the following week. Thus for a given week, those

measured as unemployed include a disproportionate representation of persons with long spells.

This phenomenon, termed duration dependence, is manifest in Table IV-6 in the relative

magnitudes of the means and medians. The means, column (1), are uniformly much higher than

the medians, column (2), with mean/median ratios falling into the range between 1.7 and 2.5 for

32 of the 33 years where both averages are displayed.

Availability of means and medians by state from the CPS is a more recent phenomenon

than in national data. BLS first started to publish state-level means in the late 1970s and medians

are available only since 1994. All of these means and medians are based on calculations using

micro data. BLS publishes information on the underlying distributions, e.g., duration by weekly

intervals such as 1-4, 5-10, etc., as well as the means and medians.43

State-level estimates of mean unemployment duration were developed for the current

project. There are national estimates for years starting in 1950 (column (3)) and state estimates

from 1977. These means are measured as total annual weeks of unemployment (from monthly

labor force survey data) divided by estimated onsets of new unemployment spells (based on the

annual number of spells of less than five weeks duration). Unlike the means based on monthly

data, these means developed for the project do not have an underlying distribution by weeks of

unemployment, and they are affected by a different kind of truncation. All weeks of

unemployment occur in the reference year. There is no carryover of weeks from a previous year

as in the averages based on monthly data. 

 Some comparisons were made between the means based on monthly data (ADPUB,

column (1)) and the means used in the duration analysis of the present project (AD, column (3)).

The monthly average means were consistently larger than the project estimates of mean duration.

In the national data shown in Table IV-6, the 50 year averages were 13.1 for ADPUB and 9.9

weeks for AD. 
44 As of February 2001 BLS had not yet published the state duration data for 1999. The

project developed estimates of monthly average means by state from 1977 to 1981 using grouped

data on unemployment duration by intervals and a regression-based projection. From 1982

onward published BLS estimates were used. Details of estimating of the unemployment duration

means from 1977 to 1981 are available from the author. 

72

Monthly average means were also consistently larger in state-level comparisons spanning

1977 to 1998.44 For these 22 years, the simple averages of the state-level means were 13.8 for

ADPUB and 10.6 weeks for AD. However, the two series were highly correlated. A regression of

the project estimate on the monthly average mean yielded an adjusted R2 of 0.78. Of the two

series, there is much greater variation in the monthly average means (ADPUB) at the state level.

The two coefficients of variation for these 22 years were 0.29 for ADPUB and 0.20 for AD. It

appears that allowing weeks of unemployment from adjacent years enter into the measurement of

duration, acts to increase the relative variability of the measured unemployment duration. Because

the present project is focused on annual WBTU ratios and the four associated accounting identity

ratios, the project estimates of mean unemployment duration are of most relevance. However,

Table V-5 of Chapter V reports results of regressions explaining the two state-level estimates of

mean unemployment duration based on CPS unemployment data. 

Because the project estimates are not based on underlying distributions of unemployment

durations, questions about the accuracy of these means will remain. This fact of duration

measurement must be kept in mind in assessing the regression analysis of unemployment duration

reported in Chapter V. It has influenced our approach to analysis of duration. Several regression

relations were estimated using the mean derived from CPS data and the mean from UI data

(columns (3) and (5) in Table IV-6 respectively) as separate dependent variables.

Column (4) of Table IV-6 shows estimates of mean duration based on work experience

data. These data come from March supplements to the CPS which ask questions about

unemployment in the preceding calendar year. The data combine information on all spells during

the year in the estimate of unemployment duration. On average, 35 to 40 percent of those

reporting unemployment in a given year have two or more spells during that year. The truncation

in these duration data arises from the CPS survey question that restricts unemployment

experiences to the 52 weeks of the preceding year. 
73

Mean duration in work experience data was estimated by the project based on tabular

summaries of unemployment durations shown as interval data. The means can be derived starting

in 1955 when work experience data on unemployment in the previous year were first available.

These data are available as national estimates. No attempt was made to derive state-level

estimates of duration in work experience data.

Unemployment duration in the work experience data provide estimates of annual duration

summing across all spells of unemployment. Averages for the 1980s and 1990s fall into the 16-17

weeks range and are higher than the averages from the 1960s and 1970s. All four series based on

the CPS show longer average duration in the past two decades than in earlier years. 

Average duration in unemployment insurance data also increased during the 1980s and

1990s. The measurement of average actual duration (ADUI in column (5)) should be noted. It is

the ratio of weeks compensated in the year to first payments for that year. While actual duration

increased in these UI data, there was little change in potential duration (column (6)). All annual

averages between 1956 and 1999 fall into the 23.0 to 24.6 weeks range. Potential eligibility in the

UI program (column (6)) has not changed much in the past 40 years. Over the same period, actual

duration of exhaustees (column (7)) has increased somewhat, but the increase between, say, the

1960s and the 1990s has been much less than in CPS data. 

To help summarize long term developments in unemployment duration, two summary

charts were prepared. Chart IV-2 displays centered five year averages of three unemployment

duration indicators in national data. Two were introduced as part of the accounting identity

framework discussed in Chapter III (termed ADUI and AD and appearing respectively in columns

(5) and (3) of Table IV-6 ) plus average duration as reported by persons interviewed in the CPS

(ADPUB, from column (1) of Table IV-6). Five year averages were used to reduce the variation

present in the underlying annual data, a reflection of the sensitivity of unemployment duration to

the business cycle.

Three features in Chart IV-2 should be noted. 1) All three duration measures increase

when viewed over the full period and when traced from the late 1960s. 2) The long term increases

in the published averages from the CPS (based on column (1)) are even larger than for
52

59697989

97

6

8

10

12

14

16

18

20

Avg. Duration in Weeks

CPS - Pub Dur AD ADUI

Chart IV-2. Average Unemployment Duration,

Five Year Averages, 1952 to 1997
45 The 1950-1959 and the 1990-1999 averages that appear at the bottom of Table IV-6

were as follows: CPS published average duration - 11.3 and 15.7 weeks, the CPS measure used in

this project - 8.9 and 11.2 weeks and average duration in the regular UI program - 11.96 and

14.85 weeks. 

46 The average exhaustion rates for the 1970s, 1980s and 1990s were respectively 0.294,

0.329 and 0.360. Over the same period average potential duration for newly entitled persons was

practically unchanged (24.3, 24.1 and 23.9 weeks respectively) while average duration for

exhaustees increased (22.4 weeks, 22.9 weeks and 23.1 weeks respectively).

47 In fact, the UI duration data series all extend back to 1946 and some even further.

75

AD (based on column (3)), the CPS duration measure used in this project.45 3) Both CPS

measures are considerably higher in the 1990s than in the 1980s while ADUI (based on column

(5)) was at about the same level during these two most recent decades. People report lengthening

average unemployment duration in the CPS during the 1990s compared to the 1980s, but their

average duration in UI benefit status was roughly the same in the two decades, i.e., 14.69 weeks

between 1980 and 1989 versus 14.85 weeks between 1990 and 1999. While the UI duration

measure did not increase much between the two most recent decades, exhaustion rate data

suggest that average duration of unemployment for UI recipients has also increased over the last

three decades.46 These comments repeat earlier observations on the data displayed in Table IV-6.

The increase in the UI exhaustion rate apparent in Table IV-6 seems to reflect the increase

in actual UI duration relative to potential UI duration. The latter (column (6)) has remained

relatively stable. The increase in average duration relative to potential duration is plotted in Chart

IV-3. Note that the ratio of actual to potential duration was much higher in the last two decades

of this chart. In the 30 years between 1950 and 1979 the ratio equaled or exceeded 0.60 just five

times while it equaled or exceeded 0.60 in 13 of the final 20 years in the chart. The pattern for the

exhaustion rate is remarkably similar. The exhaustion rate exceeded 0.30 in just six of 30 years

between 1950 and 1979 but it exceeded the 0.30 threshold in 17 of 20 years from the 1980s and

1990s. 

All of the UI data in Table IV-6 (columns (5)-(8)) are available on an annual benefit year

(or work experience) basis, i.e., the information combines all spells for the year into the measure

of duration. These UI-reported series all have state-level detail that extend back to 1950.47 Thus
50

5969798999

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

Proportions

Act. Duration/Pot. Duration Exhaustion Rate

Chart IV-3. Indices of Duration and Exhaustions, 1950 to 1999
77

constraints on the starting dates of the estimation periods for examining the determinants of

unemployment duration arise from limitations in availability of CPS duration data, not from

limitations in UI duration data. The fact that unemployment duration increased less in UI data

than in CPS data during the 1980s and 1990s is undoubtedly linked to the truncation of UI

potential benefit duration at 26 weeks in all but two states.

The preceding descriptions of the various unemployment duration series are important

because all are affected by truncation in measurement. Of the four accounting identity ratios

developed in Chapter III, the three related to the inflow into UI benefit status (ICNU, NICIC, and

FPNIC) are easier to measure than the duration measure which compares UI benefit duration with

overall unemployment duration (ADUIAD). 
78

Chapter V. Determinants of the Accounting Identity Ratios

The framework for studying benefit recipiency introduced in Chapter III is new and as

such has not been the subject of earlier empirical analyses. This stands in contrast to earlier studies

where the IUTU ratio and (less often) the WBTU ratio have been examined. Like the earlier

analyses, the present analysis conducts multiple regressions using pooled data (state by year) that

span several years.

In reporting results from various regressions, it will be obvious that data availability

strongly affects the time periods covered. As noted in Chapter III, the ICNU and ADUIAD ratios

can be examined only starting in 1977. The other two ratios in expression (3), NICIC and FPNIC,

can be examined for the full 33 years from 1967 to 1999. Two other data constraints should be

noted. The ETA-207 reports only began recording nonmonetary determinations (on voluntary

quits, misconduct and nonseparation issues) in 1971. Even more limited is information from the

BAM measurement system on methods of filing initial claims and continued claims, i.e., only

available from 1988. Since the specifications that include determination rates and methods of

filing show that each make important contributions to explained variation, it is unfortunate these

variables are not available for longer time periods.

All regressions for this report are based on unweighted data. Each included data point has

the same weight regardless of state size. The results will be presented sequentially in the order of

appearance of the ratios on the right hand side of expression (3) from Chapter III.

Determinants of the Application Rate, the ICNU Ratio

The approach for examining the ICNU ratio and the other accounting identity ratios is to

specify regression relationships that include several factors relevant in explaining interstate

variation. These include factors from the state labor markets as well as several factors that reflect

the operation of the UI programs in the states.

Three economic factors of potential importance include the business cycle, the pattern of

job changing and unionization. The project assembled data on two national indicators of the
48 The final two peaks were 1989 and 1999. Between peaks potential real GDP was

assumed to grow at a constant geometric rate. Details on the derivation are available from the

author. 

49 See Hirsch, Macpherson and Vroman (2000).

79

business cycle. One was capacity utilization as reflected in the ratio of actual real GDP to

potential real GDP with the latter measured at cyclical peaks and smoothed for intermediate

years.48 The second cyclical indicator was the index of capacity utilization published by the

Federal Reserve Board (FRB). Both series are national time series. Of the two, the FRB capacity

utilization index consistently performed better than the real GDP-based measure. In this report,

results will be reported for regressions using the FRB index.

Job losers are much more likely to apply for and receive UI benefits than persons with

other reasons for unemployment (job leavers, labor force reentrants and new entrants). The share

of new spells is approximated with the job loser share of unemployment of less than five weeks

duration. As noted earlier, a special tabulation was obtained from BLS showing job loser

proportions. Unfortunately these CPS data extend only back to 1977. Variation in the job loser

proportion is linked both to the business cycle (increasing in recessions) and to interstate

differences in labor markets. As will be seen, the job loser proportions entered many regressions

with highly significant effects. 

Unionization is highly variable by state. A recent paper co-authored by the principal

investigator derived state-level estimates of unionization rates back to 1964.49 These estimates are

based on CPS data for years after 1976. Earlier estimates are based on a survey of unions

previously conducted every two years by the U.S. Department of Labor. 

From earlier research and a priori considerations, the expected signs of the coefficients for

each of these variables are known. Capacity utilization should have a negative coefficient. Low

capacity utilization would be expected to increase applications as the opportunity cost for

claiming benefits is lower in recession periods. The job loser proportion and unionization would

both be expected to have positive coefficients. The effect of unionization probably operates

directly through information dissemination, but there could also be an effect that operates though

statutory features that increase eligibility in states with high union density. 
50 Determination rates are measured as determinations relative to new spells of

unemployment where the latter reflects both new initial claims and additional initial claims. Denial

rates are measured as the ratio of denials to determinations. Because determinations are measured

only from 1971, a second measure of denials was used in regressions extending back to 1967,

e.g., denials as a ratio to new spells of unemployment.

80

Five variables reflecting UI programs in the states were tested for possible effects on the

application rate. 1) The share of weeks compensated for partial unemployment would be expected

to be positively associated with the application rate since those receiving partial benefits are

employed and do not appear in the denominator of the ICNU ratio. 2) The replacement rate,

average weekly benefits as a ratio to the average weekly wage, should also have a positive

association with the application rate. More would be expected to apply when benefit levels are

higher relative to past wages. 3) High base period earnings requirements would be expected to

lower applications. The proxy used here is the base period earnings requirement expressed as a

ratio to the state’s average weekly wage. 4) Determination rates and denial rates for misconduct

and voluntary quits could affect applications. If a UI program has above-average determination

rates and/or denial rates,50 this might deter persons from filing. 5) The method of filing could

affect applications. Compared to in-person filing, filing by telephone, by mail and employer filing

are all easier for the claimant. Thus as these alternative methods of filing are available, they could

raise application rates. Unfortunately, data on method of filing from Benefit Accuracy

Measurement (BAM) samples in the states are available only from 1988.

Table V-1 presents regression results for the ICNU ratio using two data periods 1977-

1999 and 1988-1999, with three regressions for each period. Each regression shows coefficients

and associated t ratios. Summary statistics appear in the five bottom lines of the table. 

The regression results shown in Table V-1 generally conform to expectations. The job

loser proportion enters with large and consistently positive coefficients. Unionization exerts a

positive and significant effect on the application rate in five of six regressions. Capacity utilization,

however, has an unexpected positive coefficient in the first three regressions which cover the

1977-1999 period. 

The various UI-related variables generally have expected signs for their coefficients. The

partial benefits share of weeks compensated has positive and highly significant coefficients in all
Table V-1. Determinants of ICNU, the Ratio of Initial Claims to New Spells of Unemployment.

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

Constant 0.088 -0.022 0.241 0.566 0.371 0.655

(0.6) (0.2) (1.8) (1.8) (1.2) (2.4)

Job Loser Share of New 0.701 0.732 0.592 0.814 0.820 0.601

 Unemployment Spells (11.5) (12.3) (10.2) (10.3) (10.5) (7.8)

Capacity Utilization - Fed. 0.342 0.360 0.193 -0.311 -0.281 -0.380

 Reserve Board Index (2.1) (2.3) (1.3) (0.9) (0.8) (1.2)

Unionization 0.369 0.359 0.310 0.502 0.617 0.320

(5.1) (5.1) (3.7) (4.2) (5.4) (2.2)

Partial Benefits, Share of 0.944 0.885 0.857 0.823 0.804 0.888

 Weeks Compensated (9.3) (9.0) (9.1) (7.0) (7.2) (8.6)

Replacement Rate - -0.183 -0.103

 (WBA/AWW) (2.1) (0.9)

Weeks for Minimum -0.0156 -0.0164 -0.0168 -0.0122 -0.0131 -0.0159

 Benefit Eligibility-a (5.7) (6.1) (6.4) (3.5) (3.8) (4.8)

Misconduct Determination -1.449 -1.516 -1.308 -1.152 -1.156 -1.004

 Rate - b (12.1) (15.8) (13.4) (7.1) (9.3) (8.1)

Misconduct Denial Rate - c 0.101 0.092 0.201 0.124 0.026 0.146

(2.5) (2.7) (5.5) (2.2) (0.6) (3.0)

Voluntary Quit Determination -0.085 0.035

 Rate - b (1.3) (0.4)

Voluntary Quit Denial Rate - c -0.033 -0.216

(0.8) (3.8)

Prop. Initial Claims 0.170 0.138 0.123

 Filed by Mail-d (3.7) (3.0) (2.8)

Prop. Initial Claims 0.075 0.072 0.069

 Filed by Telephone-d (2.7) (2.6) (2.6)

Prop. Initial Claims 1.029 1.028 0.976

 Filed by Employer-d (9.4) (9.5) (9.4)

Dummy Variables for No No Yes No No Yes

 Census Divisions

Adjusted R2 0.474 0.472 0.548 0.573 0.565 0.647

Standard Error 0.139 0.140 0.129 0.127 0.128 0.115

Mean Dep. Variable 0.527 0.527 0.527 0.519 0.519 0.519

Time Period 1977-99 1977-99 1977-99 1988-99 1988-99 1988-99

Sample Size 1173 1173 1173 612 612 612

 a -Base period earnings requirement divided by the state AWW. b - Determinations relative to new

 spells of unemployment. c - Denials per determination. d - Benefit Accuracy Measurement (BAM) data.
82

regressions. Applications for UI relative to new spells are consistently higher in states where

partial weeks represent a larger share of total weeks compensated. 

Two other UI variables also have expected effects. Weeks required for minimum benefit

eligibility has the expected negative coefficient. Its smallest t ratio across the six regressions is

3.5. In states where monetary eligibility requirements are higher, application rates are lower. 

The misconduct and voluntary quit nonmonetary determination variables have markedly

differing effects. Both were expected to have negative coefficients. The determination rate for

misconduct is highly significant in all equations and with a consistently negative coefficient. In

contrast, the determination rate for voluntary quits was not significant. Results for the voluntary

quit determinations are shown only for equations (1) and (4).

The nonmonetary determination variables yielded some surprises in Table V-1. First, note

that the misconduct coefficients are much larger and more significant than the voluntary quit

coefficients. Second, when misconduct denials were decomposed into the product of the

determination rate and denials per determination, the determination rate dominated in importance.

States where determinations on misconduct issues are below-average have much higher UI

application rates than other states. Third, the positive sign on the misconduct denial rate is

unexpected. It is positive in all six regressions and significant in five. The explanation for this

unexpected sign is not apparent. 

Recall from Chapter III that the difference in the average misconduct determination rate

for the high 13 states relative to the low 13 states as shown Table III-2 was -0.112 (0.057 less

0.169). Applying this difference to the determination rate coefficient in equation (1) (-1.449)

yields a point estimate of +0.162 for the difference in the average application rate between states

with low and high misconduct determination rates (holding other factors constant).

Equation (2) drops the nonsignificant UI variables and shows results retaining just the

partial benefits share, the weeks for minimum eligibility, the misconduct determination rate and

the misconduct denial rate. The adjusted R2 is essentially the same as for equation (1). The t ratios

for three UI variables range from 6.1 to 17.6 with the misconduct determination rate having the

largest t ratio. Again there is a “wrong”sign for the misconduct denial rate.

Equation (3) adds dummy variables for the census divisions. Note that the adjusted R2 is
51 See Needles, et.al. (2000). The impact effect suggested by this study did vary by state

but the general order of magnitude is an average increase of about 10 percent. 

52 Data collection in BAM focuses on the key week for investigations of benefit payment

accuracy. This length-biased sampling means that BAM samples have an over representation of

long duration claims. Hence, if employer-filed initial claims account for, say, 15 percent of weeks

claimed in BAM, they would represent a much higher share of all initial claims filed in a given

period, perhaps twice the BAM percentage. 

83

higher and that three slope coefficients on the macro-labor market variables change. The

coefficients for unionization and the job loser share are smaller in equation (3) than in (2) and

both have lower t ratios. 

Equations (4)-(6) provide evidence that different methods of filing have effects on the

application rate. As noted, filing by mail, telephone and employer filing are all more convenient

for the claimant than filing in person. Ease of filing seems to raise the application rate. All three

coefficients are positive and significant in each of the three regressions in Table V-1. Note that the

smallest of these coefficients is associated with telephone claims. The regressions suggest that

application rates will increase as workers increasingly file by telephone and the order of magnitude

is akin to that concluded by a recent study by Mathematica Policy Research, Inc.51

Perhaps the most interesting finding for method of filing relates to employer-filed claims.

For five southeastern states identified earlier in Map 3 of Chapter III (Alabama, Georgia, North

Carolina, South Carolina and Tennessee), BAM data show that the share of initial claims filed by

employers falls into the 0.10-0.25 range. Since these claimants on average collect for shorter

periods than other claimants (because they are job-attached), the proportions reported in BAM

data understate the importance of this method of filing.52 Note the large and highly significant

coefficients in Table V-1. Employer filing makes uniformly large contributions in these

regressions.

Equations (5) and (6) utilize a smaller set of UI variables for the 1988-1999 period with

divisional dummies added in equation (6). Again, the job loser share and unionization have smaller

and less significant coefficients when the divisional dummies are included. 

Overall, the regressions in Table V-1 explain a measurable share of total variation in the

application rate, over 45 percent in all equations and above 55 percent in three equations. The
84

coefficients on the variables generally have the expected signs. The only important exception is

the “wrong” sign for the misconduct denial rate. 

Of the most important variables, the job loser proportion, the partial benefits share, the

misconduct determination rate and employer filing of initial claims fall into the first rank of

significance followed in importance by the weeks for minimum eligibility, the misconduct denial

rate, filing by mail, filing by telephone and unionization. For the first four variables, the effects on

the application rate generally exceed 0.07 when the average values of these variables for the

highest 13 states and lowest 13 states are multiplied by the coefficients in Table V-1. The very

largest effect (for highest 13 versus lowest 13 states) is caused by the misconduct determination

rate where the projected effect exceeds 0.14 on average, and it exceeds 0.10 across all six

equations of Table V-1. High misconduct determination rates seem to exert a deterrent effect on

applications for UI benefits. 

Determinants of Repeat Applications, the NICIC Ratio

Table V-2 displays seven regressions explaining the NICIC ratio. This indicator of repeat

applications within benefit years is available back to 1967, and equation (1) displays results for the

full 33 years. The other regressions cover the periods 1971-1999 and 1988-1999. Equations (1),

(2) and (5) use denial rates measured relative to new UI spells while the other equations

decompose denials into the product of the determination rate and denials per determination.

Many of the variables tested in Table V-2 are the same as used in Table V-1. However,

the proportion monetarily eligible was also tested, and it entered some equations with a significant

negative coefficient.

Before examining the Table V-2 results, some discussion of the dependent variable and

expected signs for regression coefficients is needed. As noted, the NICIC ratio is an indicator of

repeat applications within a given benefit year. When more second and later applications occur,

these lower the NICIC ratio (because they increase its denominator but do not affect the

numerator). A higher ratio, in other words, means that comparatively fewer repeat applications

are filed. An important reason for fewer repeat applications is that when there are denials of new

initial claims there can be no repeat applications because benefit years are not established. 
Table V-2. Determinants of NICIC, the Ratio of New Initial Claims to Initial Claims.

(1) (2) (3) (4) (5) (6) (7)

Constant 0.338 0.260 0.173 0.238 0.349 0.248 0.285

(6.5) (4.7) (3.1) (4.6) (2.4) (1.8) (2.2)

Capacity Utilization - Fed. 0.303 0.428 0.414 0.361 0.419 0.341 0.357

 Reserve Board Index (5.4) (7.0) (7.0) (6.5) (2.4) (2.2) (2.4)

Unionization -0.111 -0.103 -0.045 -0.014 -0.098 0.056 0.060

(3.9) (3.4) (1.5) (0.4) (1.8) (1.1) (0.9)

Partial Benefits, Share of -0.452 -0.552 -0.525 -0.493 -0.568 -0.554 -0.542

 Weeks Compensated (10.7) (11.4) (11.3) (11.0) (9.9) (10.7) (10.9)

Proportion Monetarily -0.057 -0.073 -0.058 -0.036 -0.085 -0.046 -0.102

 Eligible (2.3) (2.8) (2.3) (1.5) (2.3) (1.4) (3.1)

Misconduct Denial Rate 1 - a 1.100 1.005 0.857

(9.2) (8.0) (5.4)

Misconduct Determination 0.576 0.519 0.658 0.647

 Rate - b (11.6) (10.3) (10.0) (9.0)

Misconduct Denial Rate 2 - c -0.042 -0.119 -0.129 -0.116

(2.6) (6.8) (5.4) (4.4)

Vol. Quit Denial Rate 1 - a 0.120 0.103 0.007

(3.2) (2.7) (0.2)

Vol. Quit Determination 0.067 0.179 -0.046 0.000

 Rate - b (2.5) (6.6) (1.2) (0.0)

Vol. Quit Denial Rate 2 - c 0.090 0.045 0.144 0.132

(5.5) (2.8) (5.7) (4.9)

Prop. Initial Claims -0.113 -0.132 -0.082

 Filed by Mail-d (5.0) (6.4) (3.9)

Prop. Initial Claims 0.039 0.022 0.023

 Filed by Telephone-d (2.8) (1.7) (1.9)

Prop. Initial Claims -0.203 -0.004 -0.060

 Filed by Employer-d (4.1) (0.1) (1.2)

Dummy Variables for No No No Yes No No Yes

 Census Divisions

Adjusted R2 0.242 0.269 0.332 0.415 0.346 0.474 0.538

Standard Error 0.076 0.073 0.070 0.066 0.063 0.057 0.053

Mean Dep. Variable 0.583 0.583 0.583 0.583 0.589 0.589 0.589

Time Period 1967-99 1971-99 1971-99 1971-99 1988-99 1988-99 1988-99

Sample Size 1683 1428 1428 1428 612 612 612

 a - Denials relative to new UI spells. b - Determinations relative to new UI spells.

 c - Denials relative to determinations. d - Benefit Accuracy Measurement (BAM) data.
86

Aspects of UI program administration can affect the NICIC ratio. In particular, when

(monetary and/or separation) denials of applications are more common, the number of new initial

claims will be high relative to all initial claims, increasing the NICIC ratio. Thus a lower monetary

eligibility proportion would be expected to raise this ratio while higher separation determination

rates (for both misconduct and voluntary quits) would also raise NICIC. 

The frequency of repeat applications may also have a cyclical component. Hence all

regressions in Table V-2 include the FRB capacity utilization index. Unionization is included for

similar reasons as in the analysis of the application rate. Unions provide information about the UI

program. High unionization might be expected to increase the volume of repeat applications.

Under this hypothesis, the unionization rate would be expected to have a negative coefficient.

The regressions also test for effects of method of claims filing. Methods that make filing

initial claims easier would also make it easier to file second and later claims in a given benefit year.

Thus the three methods of filing used in the analysis of the application rate are included in these

regressions as well. All three are expected to have negative coefficients. 

The Table V-2 results show that variation in capacity utilization is significantly associated

with rates of repeat claims filing. All seven coefficients on the FRB index are positive and the

coefficients are significant but clearly less significant in equations (5)-(7) which have a short

(twelve year) estimation period. When the economy is performing strongly, capacity utilization is

high and the NICIC ratio is high as repeat claims decrease proportionately more than new initial

claims. Unionization generally has small effects on the NICIC ratio. Only two of the unionization

coefficients had t ratios of 2.0 or larger.

Of the variables reflecting UI program measures, the two with the most significant effects

are the partial benefits share and the misconduct determination rate. In regressions where both are

included they uniformly have t ratios of 9.0 or larger. Throughout all equations in Table V-2, the

partial benefits share of weeks exhibits a negative coefficient in the range from -0.45 to -0.57 and

its t ratio is remarkably stable across the regressions. There is a strong association between the

importance of partial benefits and repeat claims. This is consistent with the idea that partial benefit

recipients collect for short periods and because they are less likely to exhaust, they file repeat

claims frequently. 
53 The possibility of a strong negative correlation between the determination rate and the

denial rate was investigated. However, the correlation between these two misconduct variables

during 1971-1999 was -0.14 and during 1988-1999 it was -0.12. Because these correlations are

quite small, this does not seem to explain the negative coefficients. 

87

Since the misconduct determination rate is only measured from 1971, it is instructive to

compare equations (2) and (3). The overall fit is better in (3) than in (2) with respective adjusted

R

2

s of 0.332 and 0.269. As in Table V-1 the determination rate for voluntary quits has much less

significance than the misconduct determination rate in explaining the NICIC ratio in Table V-2. 

While the proportion monetarily eligible has the expected negative coefficient, its size is

small and its significance level is modest. The coefficient ranges from -0.036 to -0.102, and of

seven t ratios, five exceed 2.0 but only one exceeds 3.0. Having high monetary eligibility rates

lowers the NICIC ratio (increases repeat claims) only modestly. 

Three methods of filing are tested in equations (5)-(7). Compared to their effects on the

application rate in Table V-1, their effects in Table V-2 are much smaller. The proportions of mail

claims and employer claims have the expected negative coefficients while telephone claims have

positive coefficients. The latter was not expected, but its coefficient is only of modest size. Of the

three methods of filing, filing by mail has the most consistently significant coefficient. 

Addition of census division dummies does improve the fit of these regressions but

otherwise the effects on other variables are generally small. The adjusted R2s in equations (4) and

(7) are respectively higher than in equations (3) and (6) by 0.083 and 0.064. When pairs of

coefficients are compared ((3) against (4) and (6) against (7)), no obvious patterns are observed.

Introducing regional dummies as additional controls did not affect the estimated effects of the

included variables in explaining variation in NICIC ratios. 

One surprise in the Table V-2 regressions is the sign on the misconduct denial rate

(misconduct denial rate 2, denials per determination). It enters four regressions with a negative

coefficient which always has a t ratio larger than 2.0 in absolute value. No ready explanation of

why higher denials per determination should reduce the NICIC ratio has been found.53 When the

determination rate and the denial rate are combined into a single variable (equations (1), (2), and

(5)), the effect is positive as expected. 
88

Note that decomposition of voluntary quit denials into a determination rate and a denial

rate (equations (3), (4), (6) and (7)) generally yields the expected positive coefficients for both

variables. Seven of eight coefficients are positive and six are statistically significant. As with the

analysis of applications, however, note in Table V-2 that the coefficient for the voluntary quit

determination rate is much smaller than for the misconduct determination rate. Simple averages

across the four equations that employ both determination rates are respectively 0.050 and 0.600. 

The pattern presented by the Table V-2 coefficients is that measures associated with

greater access to UI benefits have negative coefficients while those associated with lesser access

have positive coefficients. All seven coefficients on the share of partial benefit weeks are negative

as are the coefficients on the monetary eligibility proportion. All six coefficients for the

proportions filing by mail and by the employer are also negative. Thus the patterns of signs on the

coefficients in Table V-2 are largely opposite to that observed in Table V-1 (and opposite to the

patterns to be observed in Table V-3). As a rule, variables that increase the application rate (Table

V-1) also increase the repeat application rate, hence reduce the NICIC ratio.

One finding is common to the analysis of the application rate (Table V-1) and the repeat

application rate (Table V-2). The share of partial benefits in weeks compensated and the

misconduct determination rate have very large effects on both of these variables related to inflows

into UI benefit status. More new and repeat applications occur in states where partial benefits are

more prevalent and in states where misconduct determination rates are less prevalent.

These two variables have the largest effects of all explanatory variables on the repeat

application rate in Table V-2. The effects are estimated by multiplying the regression coefficients

by the difference between the averages for the top 13 states and bottom 13 states ranked by the

level of this variable. The average effect of top 13 less bottom 13 of the partial weeks variable

generally exceeds 0.04 and for the misconduct determination rate the average effect generally

exceeds 0.06. The misconduct determination rate has the largest effect of all explanatory variables

on repeat claims (NICIC) as well as the largest effect on initial claims (ICNU). 
89

Determinants of the First Payment Rate, the FPNIC Ratio

Several variables already introduced also entered the regression analysis of the first

payment rate. However, two additional variables that reflect institutional aspects of UI programs

were also tested, the waiting week and a variable showing the relative importance of liable versus

agent initial claims in the individual states.

The waiting week is a 0-1 variable equal to 1 when a state has a one week waiting period

and 0 when there is no waiting week. If there is a one week wait, the claimant will be less likely

collect a benefit because the wait provides a week within which to find a job. Thus the expected

sign of the waiting week coefficient is negative.

Certain states have provisions that make a 0-1 dichotomy an inadequate description of

their waiting week arrangement. Some states, more in the 1960s and 1970s than in the 1980s and

1990s, have provisions for retroactive payment of the waiting week after a set number of weeks

of benefits have been paid. The waiting week variable was assigned values between 0 and 1 in

these situations.

In the project, new and additional claims measure interstate claims on a state-of-residence

basis. In UI data reporting, however, first payments of interstate benefits are measured on a liable

basis. If a state had a much larger volume of liable than agent claims, it would increase its FPNIC

ratio because liable interstate claims would be included in the numerator of the ratio. To control

for this measurement effect, a net (liable - agent) interstate initial claim proportion was created.

Its numerator was the difference between liable and agent initial claims and its denominator was

the sum of intrastate claims plus interstate agent claims. It was expected to have a positive

coefficient. The method of filing initial claims is also included in the regressions.

Table V-3 shows results for the first payment ratio. All seven adjusted R2s exceed 0.3 and

two exceed 0.5. Several variables make highly significant contributions to explained variation.

Note there are four estimation periods in the table. The periods were chosen in recognition of

constraints on data availability and to match with data periods utilized in earlier regressions. 

Equation (1) was fitted for the full 33 years. Four explanatory variables have t ratios larger

than 10.0. Nearly all coefficients on individual variables in equation (1) enter with expected signs.

Capacity utilization has a negative sign while the net liable-agent proportion has
Table V-3. Determinants of FPNIC, the Ratio of First Payments to New Initial Claims.

(1) (2) (3) (4) (5) (6) (7)

Constant 1.100 1.032 1.074 0.734 0.719 0.827 0.852

(18.0) (15.6) (15.8) (8.2) (8.2) (4.6) (4.9)

Capacity Utilization - Fed. -0.798 -0.758 -0.762 -0.513 -0.478 -0.558 -0.536

 Reserve Board Index (11.6) (10.0) (10.0) (5.2) (5.0) (2.7) (2.7)

Job Loser Share of 0.252 0.259 0.234 0.249

 New Unemp. Spells (6.8) (6.9) (5.3) (5.3)

Waiting Week -0.016 -0.013 -0.014 -0.016 -0.030 -0.033 -0.038

(2.8) (2.2) (2.4) (2.6) (4.8) (4.4) (5.0)

Net Liable - Agent - Interstate 0.762 0.757 0.753 0.843 0.837 0.756 0.747

 Claims Proportion-a (16.4) (16.7) (16.6) (16.5) (16.1) (11.1) (10.6)

Proportion Monetarily 0.446 0.489 0.495 0.484 0.467 0.451 0.469

 Eligible (14.6) (15.6) (15.8) (14.2) (13.7) (10.7) (11.1)

Misconduct Denial Rate 1 - b -1.661 -1.736

(12.9) (13.3)

Misconduct Determination -0.582 -0.554 -0.490 -0.715 -0.828

 Rate - c (10.4) (9.2) (7.4) (9.0) (9.3)

Misconduct Denial Rate 2 - d -0.215 -0.196 -0.123 -0.163 -0.121

(10.4) (8.5) (4.7) (5.3) (3.5)

Vol. Quit Denial Rate 1 - b 0.215 0.253

(4.7) (5.5)

Vol. Quit Determination 0.148 0.229 0.142 0.155 0.183

 Rate - c (4.4) (5.7) (3.3) (3.2) (3.5)

Vol. Quit Denial Rate 2 - d 0.050 0.085 0.081 0.108 0.041

(2.4) (3.5) (3.2) (3.4) (1.2)

Prop. Initial Claims 0.123 0.148

 Filed by Mail-e (4.5) (5.2)

Prop. Initial Claims -0.016 -0.009

 Filed by Telephone-e (1.0) (0.5)

Prop. Initial Claims -0.500 -0.618

 Filed by Employer-e (8.3) (10.1)

Dummy Variables for No No No No Yes No Yes

 Census Divisions

Adjusted R2 0.342 0.381 0.379 0.426 0.469 0.552 0.593

Standard Error 0.094 0.091 0.091 0.086 0.082 0.074 0.071

Mean Dep. Variable 0.772 0.775 0.775 0.778 0.778 0.786 0.786

Time Period 1967-99 1971-99 1971-99 1977-99 1977-99 1988-99 1988-99

Sample Size 1683 1479 1479 1173 1173 612 612

 a - Ratio of (liable - agent) interstate initial claims to intrastate plus agent initial claims. b - Denials relative to

 new UI spells. c - Determinations relative to new UI spells. d - Denials relative to determinations. e - BAM data.
54 The high significance of he misconduct determination rate in Table V-3 repeats earlier

findings reported in Tables V-1 and V-2. In the present analysis of the FPNIC ratio, the denial

rate per determination is also highly significant. 

55 See Corson and Nicholson (1988) for a similar finding (using IUTU as the dependent

variable) and their discussion.

91

a positive sign as does the proportion with sufficient wage credits. From earlier results, the

negative effect of the misconduct denial rate was to be expected. 

Note across all equations the consistently negative effect of the waiting week. Since it has

a 0-1 range of variation, the estimated effect on the first payment rate can be estimated directly

from its coefficient. The size of the effect ranges from -0.013 to -0.038. Having a waiting week

reduces the first payment rate as expected.

The one surprise in equation (1) is the coefficient on the voluntary quit denial rate. The

sign is positive and the coefficient is significant with a t ratio of 4.7. In contrast, the misconduct

denial rate enters with the expected negative sign which is much larger in absolute value and with

much higher statistical significance.

Comparing equations (2) and (3) allows one to note the effects of separating the total

denial rate into its constituent parts, the determination rate and denials per determination. For

misconduct, both the determination rate and the denial rate enter equation (3) negatively and both

are highly significant. First payments are deterred both by a high misconduct determination rate on

new claims and by a high misconduct denial rate per determination. Note the consistently negative

pattern of coefficients for these two misconduct variables across the five equations in Table V-3

where both enter.54

The most perverse finding in Table V-3 is the consistent pattern of “wrong” signs on the

voluntary quit determination rate and denial rate variables. Of their twelve coefficients, all are

positive and all are statistically significant. The pattern of coefficients is the same whether the

determination rate and denial rate are combined (in (1) and (2)) or they are separated (in (3)-(7)).

While this finding is not new, it does raise questions of interpretation.55

One explanation that has been advanced for this finding in the past is that movement to

durational denials for voluntary quits reduced the UI application rate among job leavers. To the
56 Recall the time series pattern of WBIU displayed previously in Chart II-3. 

57 A similar argument can be made for durational denials reducing the application rate.

Recall from Chart III-1 that the ICNU ratio was higher during 1967-1980 than during 1981-1998.

92

extent that leavers generally have lower base period earnings than job losers, a change in the mix

of applicants towards a lower share of job leavers might be expected to raise the monetary

eligibility rate and raise the FPNIC ratio.56 Also, when such claimants were subjected to fixed and

variable length denials in the past, rather than durational denials, they may have found jobs during

the denial period, hence causing FPNIC to be lower.57 Some evidence in support of a change in

claimant behavior associated with a movement towards durational denials is presented in Table

VII-2 of Chapter VII. 

Regressions (4) and (5) have 1977-1999 estimation periods, coinciding with the

availability of data on the job loser proportion of new spells. Note that the job loser proportion

enters significantly. Note also that capacity utilization continues to have a significant effect on the

FPNIC ratio when the job loser proportion is included in the regression. 

The addition of census division dummies does little to alter the appearances of the

regressions. All variables are significant in equations (4) and (5) and all are significant in (6) and

(7) which were fitted for the shorter 1988-1999 period.

Equations (6) and (7) also include the three methods of filing initial claims introduced

previously, i.e., by mail, telephone and employer filing. Note that filing by mail increases the first

payment rate but filing by employer lowers the first payment rate. Both methods of filing are

highly significant, especially employer filing, where the t ratios are 8.3 and 10.1. 

Considering the results across the three tables, a most interesting pattern of the effect of

employer filing emerges. In the five southeastern states where this is prevalent, employer filing

significantly raises the application rate, increases the repeat application rate but lowers the first

payment rate. The effects on the application rate and the first payment rate are particularly large.

The negative effect on the first payment rate acts to offset much of the positive effect on the

application rate. This netting out causes the average inflow rate for these states to be roughly

equal to the national average (Group 4 in Table III-3). 
93

Considering the full set of seven regressions in Table V-3, most variables have expected

signs and nearly every slope coefficient meets the standard tests for statistical significance.

Probably more important, several variables have large effects, and the t ratios on their coefficients

are 10.0 and larger. The results are not sensitive to the inclusion of census division dummies. The

only “surprise” in these regressions is the consistent pattern of positive and significant coefficients

on the voluntary quit determination rate and voluntary quit denial rate.

Three variables have the largest effects on the first payment rate: the net interstate claims

proportion, the proportion monetarily eligible and the misconduct determination rate. For all three

variables, the effect on FPNIC of multiplying the average difference between top 13 states and

bottom 13 states times the regression coefficient exceeds 0.07. 

Relative Duration in UI Benefit Status, the ADUIAD Ratio

Compared to the other three accounting identity ratios on the right hand side of expression

(3), the ADUIAD ratio probably has the largest amount of statistical noise in its measurement.

Earlier discussions from Chapters III and IV identified several factors affecting the measurement

of both the numerator (ADUI) and the denominator (AD) of this ratio. Both unemployment

duration series are affected by truncation in their measurement.

National data for ADUI and AD were shown previously in columns (5) and (3)

respectively of Table IV-6. Both series in that table showed average unemployment duration to be

longer in the 1980s and 1990s than in earlier decades. 

Recognition of the issues in measuring ADUI and AD has influenced the approach used in

the regression analysis of relative unemployment duration. Several regressions that focused on

ADUI and AD individually were fitted before directly examining the ADUIAD ratio. 

As with the other accounting identity ratios from expression (3), this analysis is strongly

influenced by data availability. State-level information on ADUI is available from the late 1940s.

Some regressions were fitted that extended over the 33 years 1967 to 1999. Duration measures

from the CPS with state-level detail commence only in 1977. Thus the regression analysis of AD

and then of ADUIAD is only possible starting in 1977. 

The results to be reported are grouped into three sets of regressions, respectively
58 For the individual claimant payment of partial benefits implies more weeks of potential

eligibility since the weekly payment at less than a full weekly benefit causes a smaller reduction in

the potential entitlement. This effect is outweighed by the short duration in benefit status of

claimants who are job-attached. 

94

examining ADUI, AD and ADUIAD. As in earlier regressions, macro-labor market variables

constitute one set of explanatory factors while a second set are variables reflecting aspects of UI

laws and administration. 

In these regressions, the UI explanatory variables pertain to potential duration, continuing

eligibility and methods of filing continued claims. 1) Average potential duration would be

expected to have a positive effect on actual duration. 2) The partial benefits share of weeks

compensated is included in the specifications. As before, it is expected to have a negative

coefficient as more partial benefits imply more payments to people with employment and likely

shorter duration in benefit status.58 3) The effects of two types of ongoing administrative activities

are tested. One activity is nonseparation nonmonetary determinations, both determination rates

and denial rates. 4) The second is the frequency of eligibility reviews. In states where these

activities are more frequent (relative to weeks of continued claims), duration in benefit status

would be expected to be shorter. 5) Finally, there are tests for effects of filing continued claims by

mail, telephone and employer-filed claims. Unfortunately, these BAM data are available only from

1988. 

A new element in the analysis of unemployment duration is to test for lagged effects of the

cyclical variables. All regressions reported here include capacity utilization lagged one year as an

explanatory variable. As will be apparent, the lags typically have highly significant effects. Finally,

there are also tests for increases in unemployment duration in the most recent years. This is done

with 0-1 dummy variables that start in 1981 and in 1990. 

Table V-4 displays seven regressions explaining ADUI, i.e., UI benefit duration. Equation

(1) shows significant effects for all seven included variables and all coefficients have expected

signs. Capacity utilization (current and lagged) and unionization are both highly significant over

the 33 year estimation period. Both UI program variables, average potential duration and the

nonseparation denial rate, have highly significant effects. The dummies indicate that UI benefit
Table V-4. Determinants of Average Duration in UI Benefit Status, ADUI.

(1) (2) (3) (4) (5) (6) (7)

Constant 30.816 26.104 28.663 30.609 27.862 41.104 40.217

(17.8) (13.4) (14.7) (11.0) (10.8) (7.2) (8.0)

Capacity Utilization - Fed. -0.157 -0.141 -0.148 -0.109 -0.085 -0.076 -0.055

 Reserve Board Index (8.4) (7.2) (7.5) (3.7) (3.2) (1.2) (1.0)

Capacity Utilization - Fed -0.158 -0.109 -0.102 -0.169 -0.174 -0.327 -0.327

 Res. Board Index Lagged (8.7) (5.4) (5.1) (6.0) (6.9) (5.9) (6.7)

Job Loser Share of New 4.841 5.313 5.467 4.327

 Unemployment Spells (5.0) (5.9) (4.8) (3.9)

Unionization 9.335 11.584 10.739 9.389 9.393 3.918 4.681

(12.5) (14.2) (13.0) (8.7) (7.1) (2.5) (2.4)

Average Potential UI 0.280 0.267 0.232 0.206 0.254 0.205 0.196

 Benefit Duration (12.0) (10.7) (9.2) (7.1) (9.4) (5.5) (5.7)

Partial Benefits, Share of -9.210 -9.364 -8.768 -10.781 -2.237 -5.454

 Weeks Compensated (7.0) (7.2) (6.2) (8.3) (1.5) (4.0)

Nonseparation Denial -4.310 -4.272

 Rate 1 - a (8.6) (8.3)

Nonseparation Deter- -1.897 -1.466 -2.747 -3.067 -3.317

 mination Rate 1 - b (6.2) (4.2) (8.2) (6.8) (7.8)

Nonseparation Denial -3.190 -2.879 -3.417 -3.232 -2.840

 Rate 2 - c (9.6) (7.5) (9.1) (6.7) (6.1)

Eligibility Review Rate - d -0.759 -0.713 -0.597 -0.625

(6.9) (6.8) (4.7) (5.2)

Prop. Continued Claims 1.900 1.385

 Filed by Mail-e (3.5) (2.7)

Prop. Continued Claims 1.514 0.993

 Filed by Telephone-e (2.7) (1.9)

Prop. Continued Claims -16.942 -15.479

 Filed by Employer-e (10.7) (9.7)

1981 Dummy Variable 0.684 0.880 1.065 0.301 0.311

(4.4) (5.6) (6.7) (1.3) (1.5)

1990 Dummy Variable 1.084 1.186 1.253 1.010 1.049 0.264 0.456

(7.5) (8.1) (8.7) (6.3) (7.2) (1.0) (2.0)

Dummy Variables for No No No No Yes No Yes

 Census Divisions

Adjusted R2 0.370 0.377 0.391 0.416 0.535 0.536 0.639

Standard Error 2.106 2.077 2.052 2.024 1.805 1.740 1.534

Mean Dep. Variable 13.396 13.668 13.668 13.753 13.753 13.745 13.745

Time Period 1967-99 1971-99 1971-99 1977-99 1977-99 1988-99 1988-99

Sample Size 1683 1479 1479 1173 1173 612 612

 a - Denials per ten claimant contacts. b - Determinations per ten claimant contacts c - Denials per determination.

 d - Eligibility reviews per ten claimant contacts. e - Benefit Accuracy Measurement (BAM) data.
59 The 1981 dummy equals 1.0 in all years from 1981 while the 1990 dummy equals 1.0 in

all years from 1990. Compared to 1967-1980, duration as explained in equation (1) was 0.684

weeks longer during 1981-1989 and 1.768 (0.684 + 1.084) weeks longer during 1990-1999.

60 Eligibility reviews are available from ETA-5159 reports starting in 1981. The 1981 rates

of eligibility reviews by state were used to extend rates backward to 1977-1980. 

96

duration increased from 1981 and again from 1990 compared to the earlier 1967-1980 period.59

Equations (2) and (3) were fitted from 1971, and the importance of splitting the

nonseparation denial rate into a determination rate and denials per determination is apparent. Both

have highly significant negative coefficients in equation (3). Capacity utilization and unionization

again enter significantly, and the dummy variables for 1981 and 1990 show average duration to

have increased in the 1980s and again in the 1990s.

Equations (4) and (5) test for effects of the job loser proportion of new unemployment

spells and for effects of eligibility reviews. These variables are first available in 1977.60 Both enter

the regressions with expected signs and both are highly significant. Note that the addition of

census division dummies does not affect the coefficients on most variables. Note also that the

nonseparation determination rate and denial rate are more significant in (5) than in (4).

The method-of-filing variables make significant contributions in equations (6) and (7). The

contrasts among their coefficients are as expected. For both mail and telephone claims there is

greater convenience for the claimant compared to in-person filing. Thus positive coefficients are

to be expected. Employer-filed claims are usually made for job-attached workers, either working

part-time schedules or on temporary layoff. Hence, a negative coefficient is expected. Its size is

very large, and its t ratio is the highest of all variables in both equations (6) and (7). Note also that

the partial benefits share of weeks compensated has much reduced significance in these two

equations. To some extent, employer filing and the partial benefits share are measuring the same

phenomenon, i.e., payments to job-attached claimants who have short spells in benefit status.

Finally, adding census division dummies has small effects on the other coefficients.

Overall, the regressions in Table V-4 explain a large share of variation in UI benefit

duration. Macro and labor market variables are important as are several UI variables. Benefit

duration is longer when potential duration is longer, when fewer weeks of partial benefits are
61The averages of eligibility reviews per ten claimant contacts do not appear in any table

but were calculated as simple averages for two groups of 13 states from ETA-5159 data. 

62 Both calculations are the product of the regression coefficient and the average

difference between the top 13 and the bottom 13, e.g., 1.174 = 3.317*(0.475 - 0.121).

97

paid, when nonseparation determinations are less frequent, when there are fewer denials per

nonseparation determination and when eligibility reviews are less frequent. All of these effects are

in the expected direction. Finally, a high frequency of employer-filed claims is associated with

shorter UI benefit duration. 

Perhaps the most interesting finding in the Table V-4 regressions is evidence of sizeable

effects of active administration on duration in benefit status. High rates of determinations on

nonseparation issues and high rates of eligibility reviews both have measurable effects on duration.

Note in equation (7) that the regression coefficients for the nonseparation determination rate and

the eligibility review rate are -3.317 and -0.625 respectively. The top 13 and bottom 13 states had

average nonseparation determination rates of 0.121 and 0.475 per ten claimant contacts (Table

III-2) while the top 13 and bottom 13 had eligibility review rates of 0.130 and 0.806

respectively.61 The implied differential effect on duration between the top 13 and bottom 13 on

nonseparation determination rates was 1.174 weeks while the implied difference between the top

13 and bottom 13 on eligibility review rates was 0.422 weeks.62 The combined effects of these

two factors, each reflecting active administration of continuing UI eligibility, totals 1.60 weeks.

Since mean UI duration was 13.75 weeks (see Table V-4) the combined effect represents 11.6

percent of the overall mean, a sizeable impact on average duration in benefit status. 

Table V-5 displays six regressions to explain variation in the CPS-based measures of

average duration. The first measure is the one developed for this project (or AD) while the

second measure appears in BLS Geographic Profile publications (ADPUB). National data for

these two series were displayed earlier in columns (3) and (1) respectively of Table IV-6.

The specifications in Table V-5 include just macro-labor market controls plus dummy

variables for time periods (post-1981 and post-1990) and dummies for census divisions. In both

sets of equations, lagged capacity utilization has much larger effects on duration than current year

capacity utilization. Note also that the effects of lagged capacity utilization are much larger in
Table V-5. Determinants of Average Unemployment Duration in CPS Data, AD and ADPUB

AD AD AD ADPUB ADPUB ADPUB

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

Constant 23.110 30.793 29.795 40.878 45.527 43.526

(12.7) (13.8) (14.0) (11.5) (10.6) (10.62)

Capacity Utilization - Fed. -0.034 -0.071 -0.066 0.113 0.101 0.110

 Reserve Board Index (1.4) (3.0) (2.9) (2.4) (2.2) (2.5)

Capacity Utilization - Fed -0.190 -0.241 -0.240 -0.568 -0.611 -0.611

 Res. Board Index Lagged (8.5) (10.5) (11.2) (13.0) (13.8) (14.8)

Job Loser Share of New 12.026 9.161 8.282 21.073 13.368 12.710

 Unemployment Spells (16.7) (11.8) (11.0) (15.0) (8.9) (8.7)

Unionization 4.801 7.418 11.725 8.079 15.713 20.530

(6.7) (9.5) (11.1) (5.8) (10.4) (10.1)

1981 Dummy Variable -0.350 -0.098 0.952 1.226

(1.9) (0.6) (2.7) (3.7)

1990 Dummy Variable 1.239 1.396 2.201 2.365

(9.7) (11.6) (8.9) (10.2)

Div 2 - Mid-Atlantic 0.169 1.199

(0.7) (2.5)

Div 3 - East North Central -0.702 0.815

(3.4) (2.0)

Div 4 - West North Central -0.446 -0.373

(2.4) (1.0)

Div 5 - South Atlantic 0.738 2.025

(4.1) (5.9)

Div 6 - East South Central 0.255 1.667

(1.2) (4.1)

Div 7 - West South Central 0.242 1.396

(1.1) (3.2)

Div 8 - Mountain -0.904 -1.081

(5.0) (3.1)

Div 9 - Pacific -1.457 -1.617

(7.0) (4.0)

Adjusted R2 0.324 0.376 0.462 0.304 0.371 0.459

Standard Error 1.719 1.652 1.533 3.359 3.193 2.961

Mean Dep. Variable 10.541 10.541 10.541 13.709 13.709 13.709

Time Period 1977-99 1977-99 1977-99 1977-99 1977-99 1977-99

Sample Size 1173 1173 1173 1173 1173 1173

 AD - average duration as derived in the present project. ADPUB - average duration in BLS-LAUS data.
63 F tests at the .01 level yielded F’s of 4.52 and 21.9 compared to a tabular F of 2.53.

64 The greater noise in the ADUIAD ratio is also reflected in standard deviations. For the

the four factors on the right-hand side of relationship (3) from Chapter III, these were as follows

for the 1977-1999 period: ICNU - 0.192, NICIC - 0.082, FPNIC - 0.113 and ADUIAD - 0.234. 

99

equations (4)-(6). A similar pattern also holds for the job loser share and unionization. Since

ADPUB (means from BLS-LAUS data) exhibits more variation than AD (project estimates), the

standard errors are roughly twice as large in equations (4)-(6) vis-a-vis (1)-(3). 

In the four equations where the post-1990 dummy variable enters, it has a coefficient that

is large and positive. These are much larger in (5)-(6) than in (2)-(3), again because ADPUB has

fewer truncation constraints than AD. The lower significance of the post-1981 dummy should not

be surprising as only four years of earlier data (1977-1980) could be included in the estimation

period. The set of census division dummies make significant contributions in both equations (3)

and (6).63 In both sets of regressions note how the unionization coefficient is sensitive to the

inclusion of both the time period dummies and the census division dummies.

Overall, the fits in Table V-5 are reasonably good with adjusted R2s in the 0.30-0.46

range. Unemployment duration as measured in the CPS is significantly longer when capacity

utilization is low, the job loser share of new unemployment spells is high and unionization is high.

Duration was significantly longer in the 1990s than in earlier years.

Having examined separately the numerator and the denominator of the ADUIAD ratio, a

third regression analysis studied the ratio directly. Results appear in Table V-6. Compared to the

preceding analyses of three accounting identity ratios, this analysis gives clear evidence of more

noise in the estimated relationships. In Table V-6 the adjusted R2s are generally much lower than

in Tables V-1, V-2 and V-3. The standard errors of estimate in Table V-6 are uniformly larger

than their counterparts from these same three earlier tables. The standard errors in Table V-6 fall

into the 0.162-0.225 range whereas the counterpart ranges in Tables V-1, V-2 and V-3 are 0.116-

0.140, 0.053-0.076 and 0.078-0.094. Explaining relative unemployment duration was less

successful than explaining the other three accounting identity ratios. Part of the explanation for

the larger volume of noise in the ADUIAD ratio is the truncation in the measurement of

unemployment duration, in both the numerator and denominator of the ADUIAD ratio.64
Table V-6. Determinants of Relative Unemployment Duration, ADUIAD 

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

Constant 0.564 0.526 0.375 3.027 3.870 3.844

(1.9) (1.7) (1.4) (4.5) (6.3) (7.2)

Capacity Utilization - Fed. -0.0021 -0.0014 0.0006 -0.0416 -0.0490 -0.0461

 Reserve Board Index (0.6) (0.4) (0.2) (5.2) (6.9) (7.7)

Capacity Utilization - Fed 0.0128 0.0126 0.0122 0.0238 0.0207 0.0200

 Res. Board Index Lagged (4.1) (4.1) (4.8) (3.5) (3.4) (3.9)

Job Loser Share of New -0.582 -0.508 -0.450 -0.735 -0.510 -0.415

 Unemployment Spells (5.5) (4.8) (5.0) (5.4) (4.1) (3.5)

Unionization 0.628 0.275 -0.259 0.983 -0.029 -0.631

(5.9) (2.3) (1.9) (6.3) (0.2) (3.0)

Average Potential UI 0.006 0.015 0.005 0.012

 Benefit Duration (1.9) (5.4) (1.2) (3.2)

Partial Benefits, Share of -0.679 -0.883 -0.038 -0.372

 Weeks Compensated (4.4) (6.7) (0.2) (2.6)

Nonseparation Deter- 0.072 -0.155 -0.022 -0.170

 mination Rate 1 - a (1.9) (4.6) (0.5) (3.8)

Nonseparation Denial -0.100 -0.227 -0.107 -0.158

 Rate 2 - b (2.4) (6.0) (2.0) (3.2)

Eligibility Review Rate - c -0.071 -0.071 -0.062 -0.074

(6.0) (6.7) (4.5) (5.9)

Prop. Continued Claims 0.166 0.023

 Filed by Mail-d (2.8) (0.4)

Prop. Continued Claims 0.245 0.088

 Filed by Telephone-d (4.0) (1.6)

Prop. Continued Claims -1.769 -1.163

 Filed by Employer-d (10.3) (6.9)

1981 Dummy Variable 0.053 0.066 0.042

(2.1) (2.7) (1.9)

1990 Dummy Variable -0.047 -0.053 -0.062 -0.156 -0.243 -0.239

(2.7) (2.4) (4.3) (5.0) (8.5) (9.7)

Dummy Variables for No No Yes No No Yes

 Census Divisions

Adjusted R2 0.075 0.123 0.395 0.157 0.352 0.522

Standard Error 0.225 0.219 0.182 0.216 0.189 0.162

Mean Dep. Variable 1.324 1.324 1.324 1.305 1.305 1.305

Time Period 1977-99 1977-99 1977-99 1988-99 1988-99 1988-99

Sample Size 1173 1173 1173 612 612 612

 a - Determinations per ten claimant contacts b - Denials per determination. c - Eligibility reviews per

 ten claimant contacts. d - Benefit Accuracy Measurement (BAM) data.
65 The comparison involves equations (4) and (5) of Table V-4, equations (2) and (3) of

Table V-5 and equations (2) and (3) of Table IV-6.

101

Note that the macro-labor market variables (capacity utilization, the job loser share and

unionization) appear here as in the preceding two tables. Since their coefficients almost always

had the same algebraic sign in the Tables V-4 and V-5, their coefficients would be expected to be

smaller in Table V-6 due to a netting out of effects within the ADUIAD ratio. This expectation is

confirmed with the eight coefficients that can be compared.65 The reduction in significance in

Table V-6 was especially large for current capacity utilization and for unionization.

Two time periods were examined, each with three regressions. The approach for each trio

was first to fit a regression with just the macro-labor market variables. Variables reflecting UI

eligibility and administration were added in the second equation. Finally, the third equation added

the census division dummy variables.

Many of the UI variables are significant in Table V-6. Potential benefit duration enters

positively in four regressions, but it is significant only in specifications that also include the

dummies for census divisions. The nonseparation determination rate coefficient is negative and

significant in two of four regressions while the nonseparation denial rate coefficient is negative

and significant in all four. The rate of eligibility reviews enters all four regressions with negative

coefficients that have high significance, t ratios of 4.5 or larger. The mail claims and telephone

claims proportions generally have positive and significant coefficients while the employer-filed

claims proportion has very large negative coefficients. As in Table V-4, the significance of the

partial benefits share is sharply reduced when the employer-filed claims proportion also enters

(equations (5) and (6)).

Note that the post-1990 dummy variable enters all six equations of Table V-6 with a

significantly negative coefficient. During the 1990s, average unemployment duration as measured

in the CPS increased more than average duration in UI data when several other factors were held

constant.

To summarize, the analysis of relative unemployment duration (ADUIAD) proceeded

differently than the analysis of the other three accounting identity ratios on the right-hand side of

expression (3). Here, the numerator and denominator were first examined separately before their
102

ratio was studied. Macro-labor market variables and UI program variables both had a significant

effect on the ADUIAD ratio. A greater frequency of both nonseparation determinations and

eligibility reviews significantly reduced relative unemployment duration as did higher

nonseparation denial rates. While the method of claims filing was generally significant for the mail

claims and telephone claims proportions, the largest and most significant coefficients were those

for employer filing. Whereas it was previously found (Table V-1) that a higher rate of employer

filing raised the application rate but lowered the first payment rate (Table V-3), employer filing of

continued claims was associated with significantly lower actual duration (Table V-4) and relative

unemployment duration (Table V-6). Despite the greater noise in the underlying duration

variables, relative unemployment duration was found to be significantly affected by several

variables reflecting UI eligibility and administration. 

Finally, it is worth recalling from Chapter III that of the four ratios on the right-hand side

of accounting identity expression (3), ADUIAD has the lowest correlation with benefit recipiency

as measured by the WBTU ratio. Because of this low correlation with WBTU, making changes in

relative unemployment duration would have a less systematic impact on the states with low

WBTU ratios than the factors shown to affect the application rate, i.e., ICNU. 

Summary of the Regression Analysis

The preceding regression analysis represents a first analysis of the accounting identity

ratios derived in Chapter III. Probably the most important overall finding is that several highly

significant factors were identified that affect one or more of these four ratios. The ratios can be

productively examined with standard economist’s tools, i.e., multiple regressions using pooled

data. A number of explanatory variables had highly significant coefficients with expected signs in

the regressions reported in Tables V-1 to V-6.

Important and significant effects were found for both macro-labor market variables

(capacity utilization, the job loser proportion and unionization) and variables that reflect aspects

of UI programs in the states. The latter reflect UI program administration, statutes and methods

of applying for benefits. All were important in explaining one or more of the accounting ratios.

More testing of alternative specifications may be warranted and further data collection may also
66 For example, since the manufacturing sector’s share of employment varies widely by

state, its effects on application rates should be explored. 

103

be appropriate.66

 One finding present in three summary tables (V-1, V-2 and V-3) seems especially

important: the large effects of nonmonetary determinations related to misconduct. While

misconduct issues have about the same overall prevalence as voluntary quit issues, determinations

on misconduct consistently had much larger and more significant effects in each of Tables V-1, V2 and V-3. From Table V-1 it appears that the frequency of misconduct determinations is closely

linked to initial applications for benefits. Higher determination rates reduce UI applications. Since

the ICNU ratio has the greatest variation of the four accounting identity ratios (recall the

summaries at the bottom of Table III-1), finding what seems to be a deterrent effect of UI

administration seems particularly important. States where misconduct determination rates are very

high would seem especially worthy of more detailed analysis.

Since the FPNIC ratio is also significantly correlated with the overall recipiency ratio, two

findings in Table V-3 are encouraging. The monetary eligibility rate and the misconduct

determination rate both are very important determinants of the FPNIC ratio. Also, the misconduct

denial rate makes a large contribution which is clearly separate from the misconduct determination

rate. Low FPNIC ratios are found in states where monetary eligibility rates are low, misconduct

determination rates are high and misconduct denial rates (denials relative to determinations) are

high. Since the effects of misconduct determination rates have already been highlighted, further

analysis of states where the monetary eligibility rate is low also seems warranted. Some regression

analysis of administrative measures is conducted in Chapter VII.

 
104

Chapter VI. State Site Visits

Interstate differences in rates of UI recipiency among the unemployed can have several 

determinants. Of particular interest are the possible effects of different statutes and administrative

procedures present in the individual states. To investigate this possibility in some detail, the

project conducted site visits in nine individual states. Typically two members of the research team

participated in two days of meetings. This chapter summarizes the findings of the site visits.

The chapter is divided into seven sections. Part 1 describes how the individual states were

selected. Part 2 describes some of the administrative diversity among these states. Part 3 examines

issues related to claimant information about the UI program. This addresses three areas: 1)

information dissemination and advertising by the UI agency, 2) information provided by

employers and 3) alternative ways for claimants to make inquiries about UI benefits. Part 4

examines aspects of UI applications and procedures followed for specific groups of claimants and

types of claims. Part 5 reviews specific aspects of monetary and nonmonetary eligibility in these

states. Part 6 focuses on determinants of continuing eligibility and appeals and discusses the use of

claimant satisfaction surveys. Part 7 summarizes the most important findings.

Several contrasts were found that distinguish high recipiency from low recipiency states.

Among the most obvious of the contrasts were the following. 1) States with high recipiency are

much more likely to transact with claimants in languages besides English. 2) Among the states

visited, initial claims in high recipiency states were much more likely to be transacted over the

telephone than through in-person visits to local offices. 3) High recipiency states are generally

more likely to have monetary requirements that are easy to satisfy. 4) Rates of adjudication on

separation issues related to initial claims, both voluntary quits and misconduct, are generally lower

in states with high recipiency. 5) Compensation of persons who voluntarily leave jobs appears to

be more likely in high recipiency states. 6) Disqualifications for receipt of pension benefits and

severance pay are less likely in high recipiency states than in low recipiency states. 7) Rates of

employer appeals of nonmonetary determinations are lower in states with high recipiency and vice

versa. The preceding conclusions are all qualitative in nature. Their quantitative importance,
105

individually and collectively, was not assessed. 

Selection of States for Visits

Since the purpose of this project is to investigate the reason(s) for low recipiency, a key

factor in selecting states for visits was the ratio of beneficiaries to unemployment (termed the

WBTU ratio in Chapter II). Multiyear statewide averages of this ratio range from more than 0.40

to less than 0.20. Table III-1 shows state-level detail on WBTU ratios averaged for the 22 years

1977 to 1998. The WBTU ratios in both tables array the states from high to low.

If differences in the UI programs of the states contribute to differences in recipiency, it is

more likely the differences can be found by selecting states from the extremes of the distribution

of WBTU ratios. The strategy followed in selecting states for site visits was to choose from

among those with the highest and lowest recipiency. The thirteen with the highest and the thirteen

with the lowest WBTU ratios were considered for selection.

While several factors could contribute to interstate differences in UI recipiency, the project

considered two factors besides average recipiency rates: geography and the presence of employerfiled claims. When employers file claims, the individual almost always remains job-attached,

experiencing either a temporary layoff or a short work week. There is no need to search for work

in such situations (because there is a job waiting or the person remains employed), and the

duration of unemployment is likely to be much shorter than for a permanent separation. 

Table VI-1 arranges 32 states along the three dimensions previously noted: level of

recipiency (WBTU ratio), geography and presence of employer-filed claims. Employer-filed

claims are most important in five states located in the southeastern U.S.. These five are shown in

the final column of Table VI-1. 

The geographic detail in Table VI-1 appears in the left hand column. The Census Bureau

divides the county into nine divisions from New England to the Pacific. 

As noted earlier, UI recipiency has a strong regional component which is highlighted in

Table VI-1. The middle columns of the table identify by Census Division the 13 states with lowest

recipiency and the 13 (plus California) with highest recipiency. While California ranked 15th in its

average WBTU ratio during 1977-1998, it could be described as a near miss from the
Table VI-1. States Considered and States Selected for Site Visits

Census High Low Employer

Region WBTU WBTU Filed

Claims

New England Connecticut New Hampshire-S

Maine

Massachusetts-S

Rhode Island

Vermont

Mid Atlantic New Jersey

New York

Pennsylvania

East North Cent. Wisconsin-S Indiana-S

West North Cent. South Dakota

South Atlantic District of Columbia Florida-D Georgia

Georgia North Carolina-S

Virginia-S South Carolina

East South Cent Mississippi Alabama

Tennessee

West South Central Louisiana-S

Texas

Oklahoma-S

Mountain Arizona-D

Colorado

New Mexico

Pacific Alaska

California-S

Oregon

Washington

Total Number 14 13 5

Number Selected 3 5 1

S = State visited. D = Declined to participate in site visits.
67 John Trutko and Wayne Vroman visited Virginia, Louisiana, Indiana and California. In

Virginia and Louisiana, Crystal Woodard from the national office also participated in the

interviews. Jamie Bachinski and Estella Garcia from the USDOL regional office in San Francisco

participated in the site visit to California. Steve Woodbury and Wayne Vroman visited

Massachusetts and New Hampshire. Vroman undertook solo visits to Wisconsin, North Carolina

and Oklahoma. 

107

top 13. The ratio for Maine (ranked 13th) was 0.365 while California’s ratio was 0.358. 

Table VI-1 displays the states in nine geographic clusters. At least one state was selected

from eight clusters. Because the project was particularly interested in the determinants of low

recipiency, more states were selected from the low WBTU clusters than from the high WBTU

clusters. States selected for site visits are identified with S’s. There are five states with low

recipiency, three with high recipiency and one with a large volume of employer-filed claims.

Most states agreed to visits when approached by representatives of the U.S. Department

of Labor’s regional offices. However, Florida elected not to participate as did Arizona. The

project had hoped to visit Arizona during September 2000, but this coincided with the

implementation of telephone claims in the Phoenix area. The timetable for the overall project was

too tight to wait until November 2000 for a visit to Arizona. 

To replace Florida and Arizona, the project respectively selected Louisiana and Oklahoma

as alternatives. Note that both with the original selections and with the alternative selections, eight

of the nine geographic clusters were visited. 

Finally, note that just one of the five states with a high volume of employer-filed claims

was selected. Altogether, four of the nine states visited were located in the South. Geographic

diversity in the low recipiency states was provided by selecting New Hampshire and Indiana. 

The strategy employed in visiting the individual states was to use one (Virginia) as a pilot

and build upon those experiences in visiting the other states. For six of nine states, two members

visited the state for a two-day stay.67 Typically, the visit included meetings at the headquarters

office and visits to one or two local offices in states where in-person filing was still practiced. We

observed the telephone procedures used for initial claims, continued claims and nonmonetary

determinations in states that now rely on telephones. Visits to one-stop centers and discussions of

profiling procedures were also included in the visits. As will soon be apparent, we also gathered
108

information on administrative procedures from Rhode Island. This was important for addressing

certain interstate issues and for formulating the approach to be followed during the full site visits

to the states. The nine full site visits were spread over the period from March to September 2000. 

Attempting to digest the most significant aspects of administrative operations in a state

within two days could be described as presumptuous. We were treated graciously by our hosts in

each of the states visited and received excellent cooperation, both at the time of the visits and in

follow-up telephone conversations intended to clarify questions and issues not posed or resolved

at the time of the visits. However, we are sensitive to the possibility of missing important features

of agency operations during these short visits. Readers of this chapter can probably judge this

question for themselves. If there are errors, it is not for lack of help from the states but rather a

matter of tight timetables for the visits and our limitations as observers of state UI programs.

 

Administrative Diversity

Visiting the nine states yielded two overriding impressions. 1) The states employ a wide

variety of organizational arrangements to gather information and make decisions about initial

eligibility and continuing eligibility. 2) The UI agencies are currently in the midst of several major

changes in their ways of doing business. As a result, many of the procedures observed during the

site visits will have changed if the same states were visited in, say, 2002 or 2003. 

To emphasize the diversity of organizational arrangements, it will be useful to note the

different ways the nine states accomplish three tasks of UI benefits administration: initial claims,

continued claims and nonmonetary determinations. Initial claims are received in two main ways.

Five of the nine states in the year 2000 relied mainly upon telephones to take initial claims while

four relied mainly on in-person applications. Within both of these broad approaches, however,

clear variants can be identified. Of the five that mainly rely on telephones (Massachusetts,

Wisconsin, California, New Hampshire and Oklahoma), Wisconsin stands out in its reliance on

interactive voice response (IVR) procedures. Following a scripted set of questions, claimants

complete a substantial portion of the initial claim using the IVR before moving to a conversation

with a live agency representative. While very few new initial claims are completed within the IVR,

a more substantial share of additional claims are completed within the IVR. In contrast,
109

Massachusetts, California, New Hampshire and Oklahoma use the IVR to sort calls into major

applicant categories and to record modest amounts of claimant-supplied information. Once the

call is identified as an initial claim, their systems move quickly to a live conversation with a claims

specialist in the phone center. Oklahoma takes initial claims by phone in the Oklahoma City and

Tulsa metropolitan areas. However, after completing the claim by phone, the claimant is required

to visit a local office or one-stop center to sign the application form. Signing completes the

application. 

Different approaches to taking in-person claims were also encountered. Local offices may

be co-located with Employment Service or one-stop centers. In filing for benefits, the claimant

may also be informed about job services, the availability of on-line job listings and availability of

computers for preparing resumes. This information may be conveyed by a claims specialist or

through a film presentation. Typically the information needed for the claim is directly entered onto

computer screens by the claims specialist. 

Perhaps the most interesting in-person intake procedure was found in Indiana where the

claimant is directed to a computer terminal in the local office to enter scripted information needed

for the application. Usually the script cannot be fully completed by the claimant, and a one-on-one

session with a claims specialist then follows. The self-entered information is reviewed and further

information is gathered on prior work history and the job separation. If the full script is completed

by the claimant at the terminal, i.e., there are no separation issues and no base period wages

outside Indiana covered employment, the applicant does not need to have a direct conversation

with a claims specialist. The claimant can leave the local office (co-located with the Employment

Service and in many instances a one-stop center) and expect to receive a payment following the

waiting period. 

Continued claims are filed by mail or by telephone in these states. Under both methods,

the claimant answers five or six questions, and typically the responses do not disqualify the person

from receipt in the following week. However, a variety of approaches are followed in matters

such as reliance on eligibility reviews. Of the states visited, New Hampshire and North Carolina

make extensive use of eligibility reviews. Claimants have to report for eligibility reviews at fixed

intervals, e.g., every 4 or 8 weeks, and describe efforts to secure a job. In contrast, California,
110

Massachusetts and Wisconsin conduct eligibility reviews only infrequently.

Several approaches are followed in completing nonmonetary determinations on separation

issues. Louisiana and Virginia still do them in each local office. California, Massachusetts, and

Wisconsin use centralized determination units located in the phone centers (Massachusetts and

Wisconsin) or as freestanding centers (California). Indiana and Oklahoma follow a mixed

approach. In Indiana, there are centralized nonmonetary determination units in three metropolitan

areas (Indianapolis, Fort Wayne and South Bend), but separation determinations are done in local

offices elsewhere. In Oklahoma, determinations are done in local offices except in Oklahoma City

and Tulsa where there are nonmonetary determination units within the phone centers.

Changes in procedures are occurring in several states with a trend towards increased use

of telephones for initial claims and continued claims. Of the nine states, Oklahoma was fully

reliant on the two phone centers in its two largest metropolitan areas as of 2000. Current plans

are to continue with in-person procedures in all other areas of the state. New Hampshire moved

to telephones for all continued claims in January 2000, and by the end of 2000, it was using

telephones for all initial claims. As noted, Arizona was not visited because it was implementing

telephone claims filing in the Phoenix area during September-October 2000.Virginia’s movement

to telephone continued claims was completed in 1999 while Indiana’s use of claimant-entered data

for initial claims at the local office is a recent phenomenon.

Plans for major changes are also present in several of these states. California anticipates

replacing mail-in continued claims with telephone procedures within the next two or three years.

Virginia anticipates a changeover in initial claims procedures to telephones in either 2001 or 2002.

Additionally, several states are starting to actively explore ways to use the internet to take initial

claims and/or continued claims. 

Data on methods of claims filing are available from the Benefit Accuracy Measurement

(BAM) samples of claims drawn in each state to assess the accuracy of benefit payments.

Information on methods of claims filing in these data is instructive. For both initial claims and

continued claims, states increasingly use telephones. National totals based on the BAM samples

show that 6 percent of initial claims were filed by telephone in 1996 but 29 percent in 1999. The

corresponding telephone percentages for continued claims were 35 percent in 1996 and 61
68 See, for example, Tables 4 and 5 in Vroman (1991). 

111

percent in 1999. Paralleling the changes in the method of filing intrastate claims are developments

in interstate claims filing. Increasingly, interstate claims are being received directly by phone in the

liable states. These kinds of changes can be expected to continue into the foreseeable future.

 

Information to Claimants About UI Benefits

A common presumption is that unemployed workers know about UI and can be expected

to file for benefits in most situations. However, from the data displayed in Chapter III it is clear

that rates of applications among the unemployed vary widely across states. The range of

application rates (average ICNU ratios for 1977-1998 as displayed in Table III-1) was from a high

of 0.982 in Rhode Island to a low of 0.236 in Florida. 

Part of the explanation for low application rates in some situations is lack of knowledge

about the UI program, either its existence or, more likely, the exact requirements for eligibility.

How can there be a lack of knowledge about a program that has existed since the 1930s? Data

from special supplements to the household labor force survey show that most of the unemployed

who do not apply know about UI but are deterred because they think they are not eligible.68

On the other hand, because unemployment is disproportionately concentrated among

young workers, they may not know important details concerning UI eligibility. Some support for

this conjecture may be found in survey data from Wisconsin. During each of the first ten weeks

of every quarter, Wisconsin selects a sample of 50 telephone initial claims (500 per quarter) and

asks questions about satisfaction with services and procedures associated with telephone claims

filing. For calendar year 1999, 60 percent of respondents indicated they had never filed for

benefits in-person at a local UI office. Wisconsin moved fully to telephone initial claims in 1996,

and yet only three years later, 60 percent of claimants’ lifetime experiences in filing had been only

by telephone. While 1999 was a year of strong labor markets in Wisconsin (as in nearly all states),

and many who had experienced unemployment in earlier years would have previously filed inperson, these survey responses are instructive. Many clients of UI do not have extensive past

histories in filing for benefits. Informational deficiencies are undoubtedly greatest for those who
69 Rhode Island is included in Table VI-2 and later tables to provide a representation of

four high-recipiency states. While the project did not conduct a full site visit as with the other nine

states, the principal investigator spent half of one day in Providence at the agency headquarters.

Questions similar to those in the other nine states were posed to agency staff. Some of Rhode

Island’s responses were obtained in later telephone conversations. 

112

are young and for persons where unemployment is not a repeated experience.

Information about UI and potential eligibility can be obtained through three channels: 1)

UI agency outreach, 2) at the work site or 3) through inquiries directed to the agency. While

other methods also exist, e.g., from conversations with family, friends and co-workers and from

outreach by unions and claimant advocacy groups, the preceding three were examined during the

site visits. 

Table VI-2 summarizes the findings in ten states.69 The columns in the table array the ten

states in descending order according to their average WBTU ratios for the 1977-1998 period.

Much of the attention of the site visit analysis focused on contrasts between the four high

recipiency states (Rhode Island, Massachusetts, Wisconsin and California) and the five low

recipiency states (Louisiana, New Hampshire, Indiana, Oklahoma and Virginia). Throughout this

chapter, statements about high recipiency states and low recipiency states will refer to these sets

of four and five states respectively. North Carolina is intermediate in terms of average recipiency

(WBTU average of 0.261 compared to the national average of 0.301 for the 1977-1998 period).

However, it was important to include North Carolina because it relies heavily on employer-filed

claims, and it is unusually active in relying on eligibility reviews to determine continuing eligibility

for claimants.

The information in Table VI-2 is displayed in three panels. Panel A summarizes

information on agency outreach efforts. Panel B summarizes posting requirements and other

information provided by the employer at the work site. Panel C summarizes information the

claimant can gather by directly making inquiries of the UI agency. 

For six of the ten states, Panel A indicates that some form of annual report is issued that

summarizes agency activities for the year, but with details that vary widely. Note that reports
Table VI-2. Information About Unemployment Insurance Benefits Available to Unemployed Workers 

Rhode Massachu- Wisconsin California North Louisiana New Indiana Oklahoma Virginia

Island setts Carolina Hampshire

Panel A. Agency Outreach

1. Annual Report? Yes No-a Yes No Yes No Yes Yes Yes No

Issued by Dept. of Labor Dept. of Emp. Advisory ESC to Employment Dept. of Emp. Sec.

and Training and Training Council Governor Security Workforce Dev. Commission

2. Advertising?

Print media Newspaper, No No Some No No-b Yes No-c Yes - Info. about No-d

Jan., July tel. claims

Radio Some public No Some, On occasion Some public Some No, but in No No No-d

service spots Thanksgiving service spots future

Christmas

Television No No No No Some Some No No No No

Panel B. Information at the Place of Work

3. Workplace posting requirement? Yes Yes Yes Yes - 2 posters Yes Yes Yes Yes Yes Yes

4. State law on posting? Yes Yes, revised in1998 Yes Yes Yes Yes Admin. rule Yes Admin. rule Yes

5. Location of notice Prominent place Conspicuous place Prominent Place readily Where all Places readily Conspicuous Not specified Places readily Prominent

at worksite at worksite place accessible can see it accessibe place accessible place

6. Notice include information on No Yes No Yes Yes No Yes, and 800 No No No

 how to file for UI benefits? num. shown

7. Monitoring of postings? No No No, only if No No No No No No No

complaint

8. Sanctions for failure to post? Fines, but Progressive: No No No

never levied Warning, Fines

9. Employer required to inform No Yes-e No Yes No No-f No Yes, but not Yes, if No

 worker about UI in sep. notice enforced requested

 or at exit interview?

10. Penalties for failure to inform Retroactive

entitlement

Panel C. Information from Direct Inquiries of the Agency

11. Claimant handbook? Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes

12. Telephone inquiries? Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes

 Yes-No and numbers 5 Numbers 4 Numbers 2 local and 800 no. 6 Call Cent (800 No)

13. Internet site Yes Yes Yes Yes Yes Yes Yes No Yes Yes

 Yes-No and address www.dlt.state.ri.us www.detma.org dwd.workweb.ui www.edd.ca.gov www.esc.state.nc.us www.laworks.net www.nhes.state.nh.us (but soon) HTTP//info.oesc. www.vec.state.va.us

state.ok.us

a - Quarterly actuarial report.

b - Some advertising for mass layoffs

c - Advertising on amount of benefits paid locally

d - Advertising for TRA and for Job Service

e - To Massachusetts Workers: How to File for Unemployment Insurance Benefits

f - Employer provides form LDOL-ES 77 when separation is thought to be disqualifying
70 Reports on the position of the state’s trust fund are not considered here, rather

summaries of UI activities that include information on workload items such as numbers of

applicants, recipients average benefits, determinations and denials. 

114

are not issued by two states with high recipiency (Massachusetts and California) and two with low

recipiency (Louisiana and Virginia).70 Table VI-2 identifies three forms of advertising available to

the agencies to publicize UI, e.g., print media, radio and television. These are used only sparingly.

When a state indicated it did advertise in the media, it frequently targeted specific client groups

(those affected by mass layoffs or eligible for trade readjustment assistance or disaster

unemployment assistance) as opposed to the general claimant population. Some states did

advertise in peak periods of seasonal claims (Rhode Island and Wisconsin). Of the three media

identified in the table, television was the least utilized. 

Overall, it appears that agency outreach through annual reports and advertising is a

modest endeavor in nearly all the states visited. For the majority of claimants, information about

the UI program in their state would have to come from sources other than agency advertising.

The site visits did not identify large differences between high recipiency states and low recipiency

states in the commitment of agency resources to advertise UI benefit availability.

Panel B summarizes several aspects of information dissemination at the workplace. A

worker might learn about UI availability at the worksite either through posters displayed in

common areas or through information supplied by the employer at the time of termination from

employment. Lines 3-8 and 9-10 respectively address these two possibilities. 

All ten states have a workplace posting requirement, and in eight (all but New Hampshire

and Oklahoma) the requirement is statutory. Nine of the ten (all but Indiana) specify that the

poster be displayed in a prominent place. The states generally supply new employers with the

posters and the instructions for posting. The posters provide general information on applying for

benefits including the location of offices and relevant telephone numbers to call for information

and (where relevant) for filing by telephone. Massachusetts, California, North Carolina and New

Hampshire provide some additional specifics about applying for benefits.

Monitoring and enforcement of posting requirements is generally lax. Wisconsin may be

typical in that it contacts employers only if there is a complaint about the absence of the poster.
115

Rhode Island and Massachusetts have statutory authority to levy fines, but no recent instance of a

fine was cited by the staff of either state.

Four states require employers to inform workers about UI at the time of the job

separation. This is potentially much more relevant than a requirement to post information about

UI since the separation is a real event which will activate worker concerns about future income. A

notice is to be included in the employees final pay slip in Massachusetts. Failure to do so can

result in backdating a claim when the person is eligible. Indiana and Oklahoma also require

employers to inform workers upon termination. The requirement applies in Oklahoma only if there

is a request from the worker. In both states, however, there is no active enforcement of this

requirement. Massachusetts was the only state where there seemed to be real consequences for

failure to inform workers at the time of termination about potential UI eligibility.

Thus posting requirements were present in all states, but only four had a requirement to

inform the worker about UI at the time of termination. Monitoring of these requirements was

generally lax. Only in Massachusetts did failure to inform workers about UI seem to have

consequences for receipt of benefits.

Panel C shows that all states have a claimant handbook. This provides important details

about eligibility including the definition of the base period and the benefit formula. All states have

procedures to answer questions by telephone, and all but Indiana have an internet web site

designed to provide information to claimants. Thus, three media for acquiring information about

UI are widely available. Nothing in Panel C suggests major contrasts between states with high

recipiency and those with low recipiency. 

Claims Filing, Specialized Claims and Claimants in Special Circumstances

Table VI-3 summarizes information on methods of filing claims, specialized claims and

claimants in special circumstances. The historical BAM data in line 1 of Panel A show that

telephones were the predominant method for filing initial claims in four states in 1998 and 1999.

However during the year 2000, Oklahoma operated with telephone claims in the Oklahoma City

and Tulsa metro areas which historically have accounted for 60-65 percent of statewide totals. 

New Hampshire started to use telephone initial claims in the second half of 2000 and expected
Table VI-3. Main Methods of Claims Filing, Specialized Claims and Claimants in Special Circumstances

Rhode Massachu- Wisconsin California North Louisiana New Indiana Oklahoma Virginia

Island setts Carolina Hampshire

Panel A. Main Methods of Filing Claims

1. Initial Claims - Main Method - Pct.-a T 55% - 1998 T 79% - 1998 T 91% - 1998 T 99% - 1998 IP 69% - 1999 IP 100% - 1998 IP 100% 1998 IP 99% - 1998 IP 96% - 1998 IP 98% - 1998

T 85% - 1999 T 91% - 1999 T 90% - 1999 T 99% - 1999 Er 30% - 1999 IP 99% - 1999 IP 80% - 1999 IP 99% - 1999 IP 99% - 1999 IP 95% - 1999

T - 2000 T - 2000 T - 2000 T - 2000 IP-Er - 2000 IP - 2000 T - 2000 IP - 2000 T - 2000 IP - 2000

(interact. w computer)

Telephone: live or IVR? Live Live Both Live Not applic. Live Not applic. Live To be determined-b

No. of call centers 5 4 2 6 1 Not applic. 1 Not applic. 2 Not applic.

Local offices for walk-ins? Yes-c Yes-26 No No Yes - 90 Yes No Yes Yes-d Yes

2. Continued Claims - Main method - Pct.-a T 88% - 1998 M 99% - 1998 T 100% - 1998 M 100% - 1998 T 69% - 1999 T 94% - 1998 M 98% - 1998 M 81% - 1998 T 94% - 1998 T 48% - 1998

T 89% - 1999 M 98% - 1999 T 100% - 1999 M 100% - 1999 Er 31% - 1999 T 94% - 1999 M 99% - 1999 M 82% - 1999 T 96% - 1999 T 70% - 1999

T - 2000 M - 2000 T - 2000 M - 2000 T-Er - 2000 T - 2000 T - 2000 M - 2000 T - 2000 T - 2000

Telephone: Live or IVR? IVR Not applic. IVR Not applic. IVR IVR IVR Not applic. IVR IVR

Panel B. Specialized Types of Claims

3. Interstate liable: telephone initial claims - Pct. Majority Method in 95% 100% 34% and Method in Moving to all by phone Method in Majority Method in 

agent state growing agent state agent state by phone agent state

Live or IVR? Live Both Live Live Live Live

4. Importance of agent versus liable?

Net effect on WBTU? Small Small Small Small Small Intermed. Large Small Intermed. Small

Agent>Lia. Lia. > Agent Lia. > Agent Lia. > Agent Lia. > Agent Agent>Lia. Agent>Lia. Agent>Lia. Agent>Lia Agent>Lia.

Lowers WBTU Raises WBTU Lowers WBTU Lowers WBTU Lowers WBTU

(Agent - Lia)/(Intra. + Agent) - 1998 .010 -.024 -.006 -.008 -.011 0.041 0.116 .024 .038 .017

Continued claims - ETA-5159 data

5. Importance of commuter claims? Low

Net effect on weeks claimed? More out-commuters More in-commuters, Small-d Small-d Small-d Small-d More out-commuters Small-d Small-d Small-d

Lowers WBTU Raises WBTU Lowers WBTU

measurably

6. Importance of combined wage claims?

CWC share of weeks compensated

(U.S. = 0.032 in 1998) 0.060 0.006 0.028 0.018 0.038 0.030 0.201 0.019 0.051 0.033

ETA-586 and ETA-5159 data

Panel C. Applicants in Special Circumstances

7 - Non English speakers

Claims forms/ info. brochures Yes - 5 Yes - 5 Yes - 2 Yes - 3 Yes No No No No No

 in non-English languages? (Spanish, Portuguese, (Spanish, Portuguese, (Spanish, Hmong), (Spanish, Chinese, Spanish

Vietnamese, Hmong, Chinese, Vietnamese, Vietnamese)

Lao) Haitian)

Staff with foreign languages? Yes Yes Yes Yes Yes Yes No Yes Yes, No

 Languages? (Spanish, Portuguese - (Spanish, Portuguese (Spanish, Hmong) 43 in total in EDD Spanish (Spanish, (NHES to use (Spanish, Port., (Spanish, Native

direct phone intake, Chinese) rest - ATT lang. line and other agencies Spanish - IVR French, 3 others) ATT lang. line) Vietnamese, Albanian) American)

Asian - callbacks) ATT lang. line

8 - Hearing impaired Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes-e

Claims Procedures TDD- tel. TDD TTY-TDD, TTY-TDD ESC-paid Some DOL local TDD TDD TDD Mail

device for deaf paper forms consult. signers office staff sign

a - T = telephone, IP = in-person, Er = employer, M = mail. Percentages from BAM data.

b - Conversion to telephone in 2001-2002. Have not determined type of phone system.

c - Share of walk-ins expected to continue to decrease 

d - Net effect uncertain

e - TDD for information only
71 A tabulation from North Carolina for 1999 indicated that average duration for employer

filed claims was about four weeks whereas it was about 16 weeks for claims filed in-person.

117

telephone claims to operate statewide by the end of the year. Wisconsin places greatest reliance

on the IVR for gathering claims information by telephone. Even in Wisconsin, however, roughly

five initial claims in six are completed through a conversation between the claimant and the claims

specialist. 

Of the states with telephone claims, Massachusetts and Oklahoma plan to maintain a walkin filing option. The areas not served by the two phone centers will continue to operate with inperson filing in Oklahoma. Even in the state’s two large metro areas, it is still necessary for

claimants to visit a local office to complete the process by signing the application. Massachusetts

is required by state law to maintain local offices. In some geographic areas the offices have

measurable numbers of walk-ins. The walk-in volume in Massachusetts is declining, and the long

run share of walk-in initial claims is likely to stabilize at less than 10 percent.

Six states used telephones for continued claims in 1998 and 1999 and except for Virginia

the percentages were stable between the two years. This increased to seven states in 2000 with

the changeover in New Hampshire. These claims are done by IVR in all states. Note that

employer filing, for both initial claims and continued claims, is a stable feature of North Carolina’s

procedures. The actual percentages are closer to 50 percent than the 30 percent shown in Table

VI-3. Because the BAM data, the source for the percentages, select disproportionately from

claims with long duration, the percentages understate employer filing which typically involves

short durations in benefit status.71

Panel B of Table VI-3 focuses on three specialized types of claims: interstate, commuter

claims and combined wage claims. As noted in Chapter IV, state practices for filing interstate

claims are evolving. Increasingly, liable states take interstate claims by phone. The states provided

ballpark estimates of the prevalence of this practice. Line 3 summarizes these state estimates. In

some instances the estimates were more qualitative than quantitative. 

Line 4 uses ETA-5159 data from 1998 to show the net effect of agent versus liable

interstate claims for these states. As a rule, states with high recipiency had more liable than agent

claims while those with low recipiency had more agent than liable claims. The difference between
72 The contrast between high recipiency states and low recipiency states shown in line 4

for 1998 was also present in 1997 and 1996.

73 These data were discussed in Chapter IV and displayed in Table IV-3.

118

agent and liable weeks claimed was by far the largest in New Hampshire where it equaled 0.116 of

all continued claims in 1998, but it also exceeded .030 in Louisiana and Oklahoma as well. A

correlate of low recipiency states seems to be that claimant residents of such states are more likely

to be paid by other states than are claimant residents in high recipiency states. From line 4 in

Table VI-3 the direction of the effect is clear even if its size is generally small.72

Conversations with the states about commuter claims did not produce major surprises. In

most states commuter claims were viewed as small and quantitatively unimportant in agency

operations. However, the agencies did not regularly track commuter claims in their reporting

systems. The information shown for Rhode Island, Massachusetts and New Hampshire in line 5

was derived from special tabulations undertaken by the agencies in Rhode Island and

Massachusetts.73 It appears New Hampshire is the only state among these ten where commuter

claims are important enough to affect overall measures of recipiency.

Combined wage claims (CWC) are also generally small among these states except for New

Hampshire. In contrast to commuter claims, however, there are quantitative data on CWCs. Line

6 shows CWCs represented 0.201 of total weeks compensated in New Hampshire in 1998 (0.149

of weeks compensated for the three years 1996-1998). Rhode Island and Oklahoma were two

other states where CWCs represented more than 0.050 of total weeks compensated. 

Discussions with the states did not reveal important problems in processing these claims.

New England is one area where CWCs are prevalent, particularly for states that border

Massachusetts. Note in line 6 that CWCs are relatively more frequent in New Hampshire and

Rhode Island than in Massachusetts. This pattern is to be expected given commuting patterns,

higher wages paid in Massachusetts and the higher UI benefit levels in Massachusetts and Rhode

Island vis-a-vis New Hampshire. As noted in Chapter IV, New Hampshire is unusual in the

importance of all three types of border claims: interstate agent claims, commuter claims

(predominantly against Massachusetts) and combined wage claims.
119

Panel C of Table VI-3 summarizes state treatment of applicants in special circumstances.

Two special circumstances are examined: claimants who are not native English speakers and

applicants who are hearing-impaired. Of the two groups, the hearing-impaired represent a much

smaller part of the claimant population. No state had ready data on numbers served, but all states

had some arrangement for taking their claims. Seven of ten use telephone devices for the deaf or

telephone typing, referred to in short hand as TDD and TTY. North Carolina and Louisiana used

signers (respectively consultants and agency staff) to take these claims while Virginia uses mail

claims from these persons. No state indicated that serving the hearing impaired presented unusual

administrative difficulties.

One of the most striking contrasts among the states concerned agency procedures for nonEnglish speakers. Of the states visited, high recipiency states have much more client-friendly

procedures than low recipiency states. The former states have claims forms and/or information

brochures in several non-English languages. The counts in line 7 are worth noting: Rhode Island -

5, Massachusetts - 5, Wisconsin - 2, and California - 3. The five states with low recipiency

presented a uniform English-only approach to claims filing. In these states the claimant handbook

is available only in English. 

The four high recipiency states all take claims by telephone and all have procedures to

accommodate non-English speakers. The telephone systems are manned by staff fluent in the

particular state’s most common non-English languages. Claimants are routed to these staff in

filing initial claims. What can be termed fully supported languages in these states are the

following: Rhode Island - Spanish and Portuguese; Massachusetts - Spanish, Portuguese and

Chinese; Wisconsin - Spanish and Hmong; and California - Spanish, Chinese and Vietnamese.

Claimants dial-in to designated numbers and speak with claim specialists in these tongues.

Other (usually less common) languages are also accommodated in these states. Typically,

a time for a call-back is established and the information inquiry or claim is serviced at that time.

California goes furthest in this area with access to 43 different languages for claims operations. 

Among these states, California appears unique in its pervasive use of procedures to

accommodate non-English speakers. Not only are initial claims taken in foreign languages but so

are their nonmonetary determination fact finding interviews with claimants. At the claimant’s
120

request, the written determination can be made available in his or her native tongue. Given the

size and diversity of the state, it may not be surprising that California has developed claims

procedures in so many languages.

In low recipiency states the claimant may encounter staff who speak his or her language,

but it appears to be less the result of statewide UI agency policy than of decisions made by certain

local office managers. Four of the five low recipiency states have staff fluent in some non-English

languages. Line 7 in Table VI-3 shows the languages identified during the site visits. They reflect

variation in the ethnic makeup of these states’ populations. New Hampshire has arranged for

support from the ATT language line. Among the five low recipiency states, Virginia appears to be

unique in not offering some form of accommodation to non-English speakers.

States with foreign language options for filing telephone initial claims can track the 

importance of these claims within their overall caseload. The project team was provided

information in Massachusetts and California for selected recent periods. Spanish is uniquely

important among the various foreign languages. In Massachusetts, claims in Spanish represented

about 5 percent of the total while the California percentage was above 10 percent. These

percentages suggest that language accommodation is important to a measurable part of the

claimant population.

Important as it may be, the project did not attempt to estimate the quantitative importance

of language accommodation to observed interstate differences in UI recipiency. The site visits

were useful in establishing that major differences in language accommodation do exist. Several

states with low UI recipiency have large Spanish speaking populations. The possible link between

lack of language accommodation and low recipiency would seem to merit some type of direct

investigation. 

Factors in Initial Eligibility

Information related to initial eligibility determinations summarized in Table VI-4. This

information was gathered both from the site visits to the states and from standard reports

submitted by the states. Panels A and B respectively focus on monetary determinations and
Table VI-4. Monetary and Nonmonetary Provisions Affecting Entry Eligibility 

Rhode Massachu- Wisconsin California North Louisiana New Indiana Oklahoma Virginia

Island setts Carolina Hampshire

Panel A. Aspects of Monetary Eligibility

1. Weeks for monetary eligibility 4.3 2.9 3.1 1.9 5.6 2.6 5.5 5.3 7.3 6.2

 1990s (U.S. = 3.4)-a

2. Added eligibility No No No No No No Yes-b Yes-b Yes-b Yes-b

 requirement?

3. Alternative earnings No No No Yes-c No No No No Yes-c No

 requirement?

4. Alternative Base Period (ABP)? Yes Yes No-d No Yes No No-d No No No

5. Short-time Compensation (STC)? Yes Yes No Yes No Yes-e No No No No

6. Proportion monetarily eligible 0.92 0.94 0.93 0.80 0.86 0.80 0.87 0.82 0.75 0.81

 ETA-218 data 1977-1998

 (U.S. = 0.86)

Panel B. Aspects of Separation Determinations

7. Adjudicate base period separations? No No No No No Yes No Yes No Some, back to

liable employer

 Voluntary quits

8. Statute allow quits for urgent, com- No, but covered Yes No, but similar No, but recognized No No No No No No, but covered

 pelling or necessitous reasons? by case law concept used in admin. dets. by case law

9. Statute allow good personal Yes No No Yes No No No No No Yes

 reasons for quitting?

10. Allowable personal reasons for quitting

Own illness Yes Yes Yes Yes Yes No Yes No Yes Yes

Care of family member Yes Yes Yes Yes No-f No No No Yes-g No

Domestic violence Yes - admin. Yes Yes Yes Yes No Yes No No Yes - admin.

discretion discretion

Follow spouse Yes No No Yes Yes No No No Yes No

To take better job Yes Yes Yes Yes No No Yes Yes Yes-h Yes

11. Volun. quit determination rate, 1977-98 0.077 0.068 0.080 0.090 0.041 0.167-i 0.099 0.158-i 0.126 0.062-i

 ETA-207 (U.S. = 0.104)

Misconduct

12. Agency test for misconduct 2 part test: 1) deliberate 2 part test: 1) deliberate Willful or wanton dis- Willful or wanton dis- Regular misc. or Mismanagement of 2 part test: 1) single Discharge for No definition Deliberate violation of

willful disregard of Er willful disregard of Er regard of Er interest, regard of Er interest, substantial fault position..., action incident that rises .. or just cause, but not of misconduct Er rule or acts of willful

interest or 2) knowing interest or 2) knowing two part test from from Wisconsin or inaction... neglect, 2) repeated occurrence limited to 8 just disregard, Branch

violation of rule or policy violation of rule or policy Boynton Cab case Boynton Cab case dishonesty... cause reasons Case

13. Specific statutory disqualifications No No No Use of Use of Refusal of drug Refuse alcohol, drug 8 - Just cause Refuse drug-alcohol, Misrepresentation of 

intoxicants intoxicants test Felony dishonesty reasons Misrep. criminal rec. past criminal record

or drugs

14. Misconduct determination rate, 1977-98 0.050 0.067 0.062 0.093 0.051 0.179-i 0.093 0.093-i 0.151 0.089-i

 ETA-207 (U.S. = 0.102)

a - Base period earnings requirement as a ratio to the average weekly wage, average 1990-1999. e - Statutory authorization but no STC benefits paid in past ten years.

b - New Hampshire - $1400 in each of two quarters and fixed 12 month base period, Indiana - $1650 in the last two quarters of f - Care of dependent parent

 base period, Oklahoma - person must sign initial claim in a local office of ESC, Virginia - $2500 in highest two quarters of base period. g - Care of minor child

c - California - $1300 in one quarter, Oklahoma - $8700 in base period. h - Leave to take full time work

d - Wisconsin - ABP starting 7-1-00, New Hampshire - ABP starting 7-1-01. i - Includes adjudications of all or some base period separations
122

nonmonetary separation determinations. Both types of determinations influence the rate at which

applicants move into benefit status.

While monetary eligibility criteria vary widely from state to state, the most typical

situation is that an applicant must satisfy both a base period and a high quarter earnings

requirement. Both dollar thresholds vary by state. Some states have additional requirements on

monetary eligibility beyond the base period and high quarter requirements, e.g., Indiana requires a

threshold of earnings in the final two quarters of the base period. Conversely, some states allow

claimants to use alternative monetary amounts if the standard base period requirements are not

satisfied. These alternative requirements may take the form of alternative dollar thresholds (using

the standard base period, usually the earliest four of the five most recent fully completed quarters)

or recognizing more recent earnings than used in the standard base period. 

Lines 1-4 in the table cover these requirements for the ten states. To standardize the base

period monetary requirement across states, each state’s requirement was measured relative to the

average weekly wage in the state. These “weeks for monetary eligibility” ratios were averaged for

the ten years 1990 to 1999. The national average for these ten years (averaged across 51

programs or 510 observations) was 3.4 weeks. Note that three of the four high recipiency states

had averages below 3.4 weeks while four of five low recipiency states had averages above 3.4.

For these latter four, the average was at least 50 percent higher than the national average. 

Four of the five low recipiency states also have an additional eligibility requirement as

shown in line 2. Details of these added requirements are provided in footnote b, but all have the

effect of rewarding steady earnings streams, recent earnings or, in Oklahoma, requiring a visit to

the local ESC office after filing a telephone initial claim. No added requirements are present in any

of the four high recipiency states.

Among the ten states, two (California and Oklahoma) have a second or alternative

requirement to satisfy monetary eligibility. Details are given in footnote c. These alternative

requirements use the same base period as the regular monetary requirements. Additionally, three

states offered an alternative base period (ABP) in 1999 and five will have an ABP in 2001. At that

later date three of four high recipiency states will have an ABP compared to just one of the five
74It should also be noted that the Governor of California vetoed an ABP legislative

proposal in the fall of 2000.

75See Table V-8 and the associated text in Berkeley Planning Associates and Mathematica

Policy Research (1997).

76 This is based on STC data as reported in ETA-5159 reports.

77 National time series data on the monetary eligibility proportion are displayed in Chart

VII-1 of Chapter VII.

123

with low recipiency.74 The alternative earnings requirements and the ABP are both claimantfriendly and would be expected to increase recipiency.

Line 5 shows the presence of short time compensation (STC, also termed worksharing) in

the states. These states allow people to work part week schedules and collect UI benefits for the

remaining days of the work week. As noted in Chapter IV, 18 states have STC programs, and

they have been quite small throughout their histories. Employers initiate plans that allow for STC

payments in states with these programs, but they are generally popular with workers placed on

short schedules.75

Four of the ten states in Table VI-4 have STC, and three are high recipiency states.

Louisiana, the fourth state, has STC but the program is moribund. No Louisiana employer has

utilized STC to compensate workers on short schedules during the past ten years.76 For the states

of interest in this chapter, STC is a phenomenon of the high recipiency states that were visited.

Alternative earnings requirements, the ABP and STC can be described as three claimantfriendly initiatives. They are much more prevalent in high recipiency states than in low recipiency

states. Summing the “Yes” entries in lines 3, 4 and 5 of Table VI-4, the totals are six of twelve in

the four high recipiency states and two of 15 in the five low recipiency states. States with high

recipiency appear more likely to implement these measures than low recipiency states.

A summary measure of monetary eligibility is provided by the ETA-218 data, i.e., the

proportion monetarily eligible out of all monetary determinations. Line 6 displays averages for the

22 years 1977 to 1998. The national average for these years was 0.86.77 Note that three of the

high recipiency states (all but California) had above-average monetary eligibility proportions while

four of the five low recipiency states (all but New Hampshire) had averages below the national
78 The regression analysis of Chapter VII directly examines interstate differences in

monetary eligibility.

124

average. 

From the information summarized in Panel A, monetary requirements and the outcomes of 

monetary determinations are linked. Higher monetary requirements are associated with lower

proportions of claimants who are monetarily eligible. Lower monetary eligibility proportions are

associated with the imposition of additional requirements (line 2) and the absence of alternative

monetary requirements, ABP and STC (lines 3, 4 and 5).78

Panel B presents selected information on nonmonetary separation determinations. If the

claimant and the employer agree that a separation was employer-initiated and it was due to lack of

work, it is commonly termed a clean separation. Clean separations do not need a separation

determination. If either of the parties allege the separation involved a quit or misconduct, the

agency must undertake a separation determination (an adjudication) in judging the claimant’s

eligibility. Nationwide, roughly one quit issue and one misconduct issue is adjudicated for every

ten (new and additional) initial claims. 

Organizational arrangements and administrative procedures for conducting adjudications

vary widely across the states. Adjudication may be undertaken in local offices or in centralized

offices that serve broad geographic areas, perhaps the entire state. Of the states visited, Louisiana

and Virginia conduct all adjudications in local offices. North Carolina conducts all separation

adjudications in one central office located in Raleigh. Massachusetts conducts adjudications from

its phone centers. California has eight adjudication centers that serve broad areas within the state.

Indiana and Oklahoma have mixed arrangements with centralized offices serving the largest urban

areas while local office conduct adjudications in the remainder of the state.

Adjudication is always required if there is a quit or discharge issue associated with the

most recent separation. However, line 7 of Table VI-4 identifies three states where adjudications

also extend back in time into some or all of the base period. Indiana and Louisiana adjudicate all

base period separations. Virginia adjudicates all separations back to the separation from the

chargeable employer. Adjudication of earlier separations can result in reduced claimant eligibility.

In Virginia the claimant may be precluded from eligibility while in Indiana and Louisiana the size
125

of the potential entitlement may be reduced. 

In the regression analysis of Chapter V, the misconduct adjudication (or determination)

rate was found to be a significant determinant that reduced the application rate, the repeat

application rate and the first payment rate. Part of the reason for higher rates of misconduct

determinations in some states is the effect of adjudicating these earlier separations. 

Compensation following voluntary quits is thought to vary widely across the states, and

may be an important factor contributing to interstate differences in IUTU and WBTU ratios.

Interestingly, of all the states visited, none could provide an estimate of the share of total weeks

compensated related to quits that were adjudicated and allowed. Allowances associated with quit

determinations are reported in the ETA-207 reports, but the associated weeks compensated are

not tracked. This is a basic measurement issue for the present project that could and should be

investigated. The required information is present in the data systems of the state programs. A

special tabulation could be undertaken in some states. Perhaps a good starting point would be to

secure the needed information from a few high-recipiency and a few low-recipiency states, both

for total weeks paid following allowable quits and the specific issue that was adjudicated in these

allowable quits.

Quits arise either from factors related to the job or to personal factors. In some states, a

voluntary quit may be compensated only if it is related to the conditions of employment (job

related). In other states, statutory language or administrative rules may recognize personal

reasons for quitting which are “urgent, compelling and necessitous.” Benefits may be paid in the

latter situations if the person first tries to preserve the employment relationship (requests and is

granted a leave of absence), but then the job is no longer available when the person tries at a later

time to resume employment with the former employer. 

Following conversations in a few states regarding personal and job-related reasons for

quitting, it became apparent that contradictory statutory language on these two broad reasons for

quitting could exist. Also, administrative practices and/or determinations from court cases could

allow compensation even though the statute restricted eligibility to quits for job-related reasons.

The Massachusetts statute, for example, restricts quits to job-related reasons but also recognizes

urgent, compelling and necessitous reasons. Lines 8 and 9 of Table VI-4 summarize statutory
126

language on quits for urgent, compelling and necessitous reasons and quits for good personal

reasons in the ten states. 

Since the administrative decisions were not always clear at the level of quits in general, we

decided to pursue the matter by asking about compensability in five specific quit situations. These

were: quits due to own illness, to care for a family member, due to domestic violence, to follow a

spouse whose job is moved out of the local labor market and to take a better job. Line 10

summarizes the results. In each instance, the question of compensability was pursued in the

context of a worker who tries to preserve the employment relationship (for own illness and care

of a family member) or is able and available for work. 

Potential compensability in these five situations does vary systematically between high

recipiency and low recipiency states. For the four high recipiency states, the person could be

compensated in 18 of 20 situations (four states and five situations per state). The corresponding

situation in the five low recipiency states was compensation in 11 of 25 situations. While these

summaries are qualitative, they suggest systematic differences in the potential compensability of

quits. Their actual quantitative importance is not known.

Line 11 of Table VI-4 summarizes average determination rates for voluntary quits in the

ten states for the 22 years 1977-1998. The national average proportion (determinations per new

spell of unemployment) for these years was 0.104 and all four high recipiency states had belowaverage determination rates. For the five with low recipiency, three (Louisiana, Indiana and

Oklahoma) had determination rates substantially above the national average and only Virginia had

a determination rate much below the national average.

Compared to voluntary quits, state-level procedures for misconduct determinations seem

more difficult to summarize (at least to the principal investigator). The burden of proof for

misconduct initially lies with the employer who must demonstrate that the reason for the

separation was employee misconduct. Usually, misconduct has a statutory definition or a

definition based on a court case. Misconduct typically involves willful, deliberate and/or repeated

actions by the worker that the worker knew was not appropriate or was against the employer’s

economic interests and was not accompanied by some mitigating circumstance. The act or acts

must be recognized by the employee as inappropriate. Incompetence in doing the work does not
79 These were the six site visit states outside of North Carolina, New Hampshire and

Oklahoma plus Arizona, Rhode Island, South Carolina and Texas.

127

constitute misconduct.

Exact definitions of misconduct vary by state. Lines 12 and 13 of Table VI-4 briefly

summarize two aspects of agency guidelines in misconduct cases. Respectively these give the

general guidelines under which adjudicators operate and specific acts that the statute identifies as

misconduct. The latter may be related to refusal to take a drug test or a test for intoxication or

misrepresentation of a past criminal record. Note in line 12 that Indiana equates misconduct with

discharge for just cause and identifies 8 specific acts that constitute just cause. Oklahoma does not

define misconduct per se but operates with administrative guidelines for several specific situations.

Given the quantitative importance of the misconduct determination rate as a determinant

of the application rate, the repeat application rate and the first-payment-to-new-initial-claims ratio

(Chapter V), the approaches to misconduct in the site visit states were studied in qualitative data.

One investigation reviewed the statutory and administrative procedures in these states as

summarized in the CCH legal summaries for each state. The misconduct section (paragraph 1970)

in the CCH volumes is arranged alphabetically by topic area. A spreadsheet was developed that

noted each misconduct topic area in the rows and individual states in the columns. The exercise

revealed that the misconduct topic areas (issues) were not the same across the states, or at least

did not follow a common topical organization. North Carolina, New Hampshire and Oklahoma

had an organization of topic areas so different from the other states that they could not be fitted

into the overall framework of topic areas present in the other states. The spreadsheet for ten

states79 eventually grew to about 125 lines. It was clear that the number of lines would continue to

grow if the investigation was widened to include more states.

The short conclusion of the project’s investigation of misconduct was that it was a large

area with many different types of worker actions constituting misconduct. Perhaps an

investigation that focused on a few problematical areas would provide insights into differences in

state procedures, presumptions and standards of evidence for specific acts. Some possible subject

areas might be repeated tardiness, absences from work, disobedience and use of profane language.

This seems appropriate material for a completely separate research project.
128

The final aspect of misconduct addressed in Table VI-4 is variation among states in

determination rates. Line 14 shows that misconduct determination rates were substantially less

than the national average (0.102) for three of the four high recipiency states (all but California).

For the five low recipiency states, two (Louisiana and Oklahoma) had determination rates

substantially above the national average while in the other three states, determination rates were

close to the national average.

Of the information presented in Table VI-4 several consistent differences between low

recipiency and high recipiency states were found. In general, monetary requirements were easier

to satisfy in high recipiency states. More allowable reasons for quits were present in the high

recipiency states. Determination rates both for quits and misconduct were generally higher in the

low recipiency states. The administration of monetary determinations and nonmonetary separation

determinations appear to contribute to interstate differences in UI recipiency.

Continuing Eligibility, Appeals and Claimant Satisfaction Surveys

Panel A in Table VI-5 summarizes information on nonseparation nonmonetary

determinations. Five areas where UI programs make determinations related to continuing

eligibility for benefits are highlighted: able and available for work, disqualifying and deductible

income, refusal of suitable work, reviews of continuing eligibility for benefits and profiling. 

Of the ten states visited, three allow unemployed workers to search for part-time work

(less than 35 hours per week) under certain circumstances and receive UI benefits (line 1). Two of

the three are high recipiency states (Massachusetts and California) and one is a low recipiency

state (Oklahoma). Louisiana also will allow search for part-time work if the person has always

worked part-time in the past. No obvious contrast between the two groups of states was found in

allowing claimants to search for part-time work and receive UI benefits.

Clear contrasts were found in the area of disqualifying and deductible income. State

practices in this area are quite varied. Most states deduct pensions received from base period

employers and most deduct severance pay (at least for some situations). Line 2 of Panel A

identifies three situations where state practices were found to vary: not deducting the employee-
Table VI-5. Determinations of Continuing Eligibility, Appeals and Claimant Satisfaction Surveys.

Rhode Massachu- Wisconsin California North Louisiana New Indiana Oklahoma Virginia

Island setts Carolina Hampshire

Panel A. Nonseparation Nonmonetary Determinations

1. Test of availability for work For full-time work For part-time work For full-time work For part-time work For full-time work For full-time work-a For full-time work For full-time work For part-time work-b For full-time work 

2. Disqualifying and deductable income,

benefits that do not reduce UI-c

Pensions - Exempt employee Yes Yes Yes Yes No No Yes No No No

 share of pension contribution?

Exclude pensions not affected No Yes Yes Yes No No Yes No Yes No-d

 by BP earnings?

Full UI benefit when severance Yes Yes No Yes No No No No Yes No

 is paid?

3. Refusal of Suitable work

Definition of Suitable Several factors-e Ee reasonably fitted 4 elements-f 4 elements-f 4 elements-f 60% of preceding 7 part definition 80% of previous 4 elements-f Not in statute, case

by training and exp. wage wages by case determination

Penalty Duration Week + 7 Wks Duration 1-9 Weeks Duration Duration Duration Duration Duration Duration

4. Relaince on eligibility reviews (ERPs)

Frequency of reviews Pilot, 2 of 7 one stops Infrequent Infrequent Mostly Every 4 weeks In 8th week 4th or 8th week 6th week if profiled, When half of entitle- Infrequent

discontinued 10th week if not profiled ment has been paid

ERP per Claimant Contact, 1998 0.011-g 0.000 0.000 0.000 0.056 0.074 0.072 0.002 0.040 0.004

 (ETA -5159 data, U.S. = 0.020)

Denials per Rep. Req. Det., 1998 0.871 0.501 0.393 0.522 0.838 0.930 0.917 0.922 0.991 0.931

 (ETA-207 data, U.S. = 0.623)

Penalty for failure to appear 1 week denial 1 week denial 1 week denial for 1 week denial 1 week denial for Indefininite Indefinite denial Indefinite denial Indefinite denial 1 week denial for

first failure first failure denial first failure

5. Profiling

Method of selecting potential Characteristics Declining industries Model Model Model National model Model Model Model Model

 exhaustees (done by ES)

Profiling frequency, determinations 

 per new spell of unemp., 1998

 (ETA-207 data U.S. = 0.0043 ) 0.0001 0.0049 0.0026 0.0176 0.0001 0.0092 0.0033 0.0019 0.0181 0.0009

Panel B. Appeals

6. Frequency (ETA-5130 data, 1998)

Lower authority - Claimant, 0.246 0.160 0.094 0.159 0.161 0.152 0.093 0.159 0.150 0.132

All issues (U.S. = 0.160)

Lower authority - Employer, 0.046 0.073 0.056 0.029 0.141 0.145 0.042 0.155 0.128 0.122

All issues (U.S. = 0.074)

7. Time limits for filing appeals 15 days - lower 10 days - lower 14 days - lower 20 days 10 days 15 days 14 days 20 days - lower 10 days 30 days

(Comparison of UI Laws, Table 502) 10 days upper 30 days - upper 21 days - upper 15 days - upper

8. Who pays lawyers' fees Sometimes agency Claimant Claimant Claimant Claimant Claimant NH Emp Comm-h Claimant Claimant Claimant

for claimant

Panel C. Surveys of Claimants?

9. Claimant satisfaction surveys? No Yes, when telephone Yes Yes-i Yes, ES Yes-j Yes - but only in refer- Yes-on occasion Yes - mid 1990s, Yes - mid 1990s

claims initiated Division ence to profiling one is planned

10. Regular survey of claimants? No No Yes No, but No No No No No No

future plans

a - Full-time unless always worked part-time in the past f - Four components: 1 - wages, 2 - commuting distance, 3 - shift offered, 4 - occupation

b - Availability in line with prior work experience g - Data for 1997

c - Most states (all but three) reduce UI benefits when pensions are received from base period employer. h - Two NHES claims representatives advise and represent claimants 

d - Virginia also reduces UI benefits when pensions are received from non-base-period employers i - Surveys in 1998 and 1999 linked to BAM, surveys linked to telephone claims

e - Distance from home, working conditions, wages and working conditions not substantially less favorable than prevailing j - One survey of satisfaction with telephone claims
80 In 1999 average benefit duration was 14.5 weeks nationwide, but it was 9.6 weeks in

New Hampshire and 10.0 weeks in North Carolina.

130

financed share of a pension payment, not deducting pensions from other-than base period

employers and payment of full benefits when severance pay is received. Each “Yes” entry

indicates the payment of UI is not reduced in the indicated situations. For the four high recipiency

states, ten of the twelve cells have “Yes” entries. In contrast, only four of fifteen cells have “Yes”

entries for the five low recipiency states. Deductions from UI benefits in these three situations are

much more likely in the low recipiency states than in high recipiency states.

Over the past three decades, disqualifications for refusing suitable work have been

declining for nearly all UI programs. A variety of definitions of “suitable” are used by the states.

In line 3 note that the most common situation involves consideration of four factors: the level of

wages, commuting distance, the shift offered and occupation of the offer. If the wage of the job

offered is below the wage of the past job, the refusal of such a job is not disqualifying in most

states. In Louisiana and Indiana respectively, however, an offer is deemed suitable when the level

of pay is 60 percent and 80 percent of the previous wage. In Virginia, case by case determinations

of suitability are made. 

Usually a refusal of suitable work is disqualifying for the duration of the current

unemployment spell. Of the ten states, only Massachusetts and California have penalties of shorter

duration. 

Visits to individual states encountered a wide range of reliance on eligibility reviews for

determining continuing eligibility. Massachusetts, Wisconsin and California indicated that they

have largely or completely stopped relying on eligibility reviews. At the opposite extreme, North

Carolina and New Hampshire both indicated that eligibility reviews were so important to the

integrity of the claims process that they provide supplemental administrative funding for eligibility

reviews. Reviews take place at set intervals, e.g., every 4 or 8 weeks, while a claimant is receiving

benefits. These two states are characterized by short durations in benefit status.80

Line 4 of Table VI-5 summarizes the guidelines as to when reviews are to take place and

provides some quantitative data on their frequency. Across the U.S. in 1998, eligibility reviews

occurred with a frequency of about one week for every fifty weeks claimed (a rate of 0.020
81 There is an explicit ETA report on profiling, the ETA 9048 report. 

131

nationwide). Note the higher rates in North Carolina, Louisiana, New Hampshire and Oklahoma.

In contrast, rates were zero or very close to zero in Rhode Island, Massachusetts, Wisconsin,

California, Indiana and Virginia. 

Two other patterns of note are the contrasts in denial rates (denials per determination) and

denial penalties. For all five low recipiency rate states the denial rates related to reporting

requirement determinations exceeded 0.90 in 1998. In contrast, three of four high recipiency

states had denial rates in the 0.39-0.52 range. Note also the contrasts in the denial penalties for

failure to appear. In states with low recipiency it is much more likely to be an indefinite denial

rather than a one week denial. On average, eligibility reviews and reporting requirements have

more “teeth” in the five low recipiency states than in the four high recipiency states included in

Table VI-5.

Line 5 in the Table VI-5 focuses on “profiling” in the states. All states are required to

follow a procedure to identify the claimants most likely to exhaust their benefit entitlements.

Profiling is applied to all except for a few exempt categories, e.g., claimants on temporary layoff.

Claimants identified as likely exhaustees are scheduled for group meetings, and, depending upon

local availability, may receive specific reemployment services. The group sessions and services

may help to shorten benefit duration. Most states use a statistical model to identify likely

exhaustees. Rhode Island and Massachusetts are the two exceptional states among these ten.

Those identified as likely exhaustees do not always follow recommended procedures and

may be subject to sanctions. However, the frequency of profiling determinations among these

states appears generally low in 1998. The national average was 0.0043 determinations per new

spell of unemployment. Among the ten states in Table VI-5, the determination rate exceeded 0.01

in just two, California and Oklahoma. Louisiana was a third state where the determination rate

was close to 0.01. The other seven states had determination rates below 0.005. These low

determination rates stand in apparent contrast to supportive comments made in some states about

the importance and usefulness of profiling. The low rates merit some added explanation. 

The frequency of profiling is high in all states, and this is shown in other reported data.81
132

However, the aspect of profiling that typically appears in nonmonetary determination reports is

explicit refusals by claimants to report to profiling sessions. If someone simply does not appear at

a profiling session, this no-show may prompt follow-up by the state. At that point the no-show

may be classified as a reporting issue in state reports on nonmonetary determinations. Thus

determinations and sanctions associated with failure to participate in profiling activities may be

classified as “reporting” issues not as “profiling” issues. This probably explains the low reported

rates of nonmonetary determinations related to profiling shown in line 5. 

Varying opinions regarding the usefulness of profiling were offered by the states. Some

supported profiling as useful both to administrators and to claimants. However, concerns were

expressed that effective services could not be provided to many identified as likely exhaustees.

The site visits also found that no-show rates at profiling sessions varied widely across states. 

Panel B of Table VI-5 addresses appeals. The project held lengthy conversations about

appeals in some states (Virginia, Wisconsin, Indiana and Louisiana) while in others appeals

received only cursory attention (Massachusetts, North Carolina, New Hampshire and Oklahoma).

This uneven treatment of appeals reflects a judgement made early in the project that state-level

measures of UI benefit recipiency are not linked to appeals volume and/or procedures in an

important way. Appeals of individual cases may provide redress for one party when it disagrees

with an agency decision, but in the aggregate they largely net out as a determinant of weeks

compensated. This judgement was corroborated during interviews in more than one state. 

One pattern in appeals is apparent in line 6 of the table. Rates of appeals by employers are

generally high in states with low recipiency. Nationally, the rate of employer appeals (all issues)

per nonmonetary determination was 0.074 in 1998. For four of the five low recipiency states, the

rates of appeals ranged from 0.122 to 0.155. In contrast, for three of the four high recipiency

states, rates of appeals were substantially below the national average. No similar patterns are

apparent in the rates of appeals by claimants. The simple averages of the employer rates of

appeals were 0.051 in the four high recipiency states and 0.118 in the five low recipiency states.

Employers appeal when agency decisions rule in favor of claimants regarding a

disagreement over eligibility. It seems that a greater willingness of employers to dispute agency

determinations is associated with low recipiency. 
82 An analysis of appeals in Wisconsin was conducted under the auspices of the Advisory

Council on Unemployment Compensation. See Ashenfelter and Levine (1996).

133

Conversations with UI agency staff regarding employer appeals encountered one common

suggestion. In Massachusetts, Wisconsin and California there were comments that the burden of

proof on employers is sufficiently high that it deters employers from pursuing appeals. Low rates

of appeals do not necessarily reflect employer satisfaction with decisions in areas such as

misconduct but rather the difficulty of prevailing on misconduct issues. In at least one state,

Wisconsin, there is active legislative interest in changing the approach to appeals, and during the

year 2000 a working group had started to examine the issue. 

When claimants’ prevail in an appeal and have representation, they typically pay the

lawyer with money from their own resources. Alternative arrangements were encountered in two

states. In Rhode Island the UI agency will pay claimant legal fees in some instances, and in New

Hampshire the agency will provide representation of claimants in some cases. 

In certain areas, information about appeals could be improved. Two areas come

immediately to mind. First, we heard several comments that employers were much more likely to

be represented at appeals hearings than workers. However, no data on rates of representation

were available from any of the states. A study of appeals in Wisconsin in 1994 found that

employers appealed in about 8 percent of cases and that employers were more likely to have

representation than claimants at appeals.82 Having more recent information on representation at

hearings from several states would be useful. Second, the current reporting system (monthly

ETA-5130 reports) does not show appeals by issue and by moving party. Thus one cannot

determine from these data the number of employer appeals that follow an award on a misconduct

case. Data are reported by moving party and by issue but are not cross-classified. Three states

provided tabulations on the moving party and issue for lower appeals on separation issues:

Massachusetts, New Hampshire and Rhode Island. In these states, employers were more likely to

appeal awards in misconduct cases in New Hampshire than in Massachusetts and Rhode Island. 

To improve understanding of the causes for differences among states in UI benefit

recipiency, pursuing research into appeals may not be a high priority area. This reflects a

judgement about the netting out in weeks compensated that occurs when both employers and
134

claimants file appeals and both win a measurable proportion of cases. 

Paying benefits to unemployed workers is a principal purpose of UI. In each site visit, we

asked questions about claimant satisfaction surveys. Lines 9 and 10 summarize aspects of state

responses. Nearly all states (nine of ten) reported past use of claimant satisfaction surveys.

However, Wisconsin was unique among these ten states in having an ongoing survey of claimants.

It surveys 500 claimants each quarter asking questions about filing by phone and comparing

current procedures with earlier in-person filing. The other states have conducted ad-hoc surveys

at some point (or points) in the past. Often surveys were mounted following the changeover to

telephone claims filing. 

It appears these states could make greater use of surveys to improve services to clients.

Surveys could lead to improvements in existing services and could identify areas where new

services are needed. 

Summary

Site visits to states revealed a number of contrasts among the states. In several areas the

contrasts between high recipiency states and low recipiency states were in the expected direction,

i.e., procedures and requirements were less claimant friendly in low recipiency states.

Seven specific examples identified in this chapter that illustrate contrasts among the states

were the following. 1) High recipiency states have made much more accommodation to nonEnglish speakers in filing for UI benefits. 2) Requirements for monetary eligibility are generally

easier to satisfy in high recipiency states. This encompasses lower monetary thresholds (measured

relative to the average weekly wage), the absence of added monetary requirements, having

alternative earnings requirements and offering an ABP and STC. The differences in monetary

requirements can be summarized with average monetary eligibility proportions. In line 6 of Table

VI-4 these proportions averaged 0.90 in the four high recipiency states but only 0.81 in the five

low recipiency states. 3) Rates of adjudication on separation issues, both quits and misconduct,

are generally lower in states with high recipiency. 4) Quits are more likely to be compensated in

high recipiency states. 5) Disqualifying and deductible income denials are less likely in high

recipiency states. 6) Eligibility reviews generally occur less frequently in high recipiency states
135

while penalties for failure to meet reporting requirements have more teeth in low recipiency states.

7) Rates of employer appeals of nonmonetary determinations are much lower in high recipiency

states, less than half the rate of appeals in low recipiency states.

Perhaps the most important finding of the site visits is that many contrasts were

encountered and that several are plausibly linked to interstate differences in UI recipiency. The

previous paragraph highlights the most important of these contrasts. 

This chapter did not try to assess the quantitative importance of the differences that were

encountered. However, some variables highly significant in the regression analysis of Chapter V

reflect contrasts in administrative outcomes studied in this chapter. Recall that monetary eligibility

rates and misconduct determination rates were both highly significant determinants of the FPNIC

ratio and that the misconduct determination rate was also significantly linked to the application

rate, i.e., higher determination rates reduce the ICNU ratio. 

Direct regression analysis of monetary eligibility and separation determination rates (both

voluntary quits and misconduct) is undertaken in the next chapter. One purpose of that analysis is

to examine the similarity across states in monetary and nonmonetary administrative outcomes.

This chapter noted several areas where information about administrative procedures could

be improved. These will not be reviewed here but rather reserved for a section of the final chapter

which discusses useful areas for new data collection and added research. 

 
136

Chapter VII. Regression Analysis of Three UI Administrative Variables

Chapter VI examined several aspects of UI program administration utilizing data gathered

from site visits as well as information from state reporting on administrative activities. Attention

was focused on a sample of states selected from the high and low ends of the overall recipiency

distribution. Site visits were conducted in five states with low WBTU ratios and three with high

WBTU ratios.

This chapter is also concerned with UI administrative activities. Three administrative

variables are the center of attention: 1) monetary eligibility proportions, 2) determination rates for

voluntary quits and 3) determination rates for misconduct. All three variables entered the

regression analysis of Chapter V as explanatory variables included in regressions to explain the

accounting identity ratios from expression (3) of Chapter III. Here, the three are dependent

variables, and the reasons for their interstate variation are examined. 

The scope of this chapter is deliberately limited. Several other UI program variables

introduced in earlier chapters could also be examined, e.g., nonseparation determination rates and

denial rates for both separation and nonseparation issues. However, the three selected reflect

major administrative decisions central to the initial receipt of UI benefits. The monetary eligibility

rate and the misconduct determination rate were important determinants of the first payment ratio

(FPNIC), and the misconduct determination rate was also a significant determinant of both the

application rate (ICNU) and the repeat application rate (NICIC). Because these variables have an

important effect on recipiency, it is logical to investigate factors that cause them to vary across

states. 

The approach of this chapter is similar to that of Chapter V in that all states are included in

a multiple regression analysis. The explanatory variables of interest reflect the operation of macrolabor market forces and aspects of UI statutes and administration. 

One objective here is to determine how much of the variation in the three administrative

variables could be explained. A second objective, closely linked to the larger concerns of the

project, was to test for interstate differences in administrative stringency. Chapter VI found
137

several important differences between high recipiency and low recipiency states in administrative

procedures and outcomes. In a later section, this chapter examines the unexplained elements of

the three administrative variables to compare patterns. If a state makes it relatively difficult to

collect UI benefits, a specific pattern of unexplained residuals would be expected, e.g.,

overprediction of monetary eligibility rates but underprediction of both misconduct and voluntary

quit determination rates.

The chapter reaches three principal conclusions. 1) The regressions do explain a significant

share of the variation in all three UI administrative variables. The R2s fall into the range from 0.20

to 0.40, and several highly significant explanatory variables were identified. 2) Some systematic

patterns in average residuals by state were found to lend support to the idea of administrative

stringency (or its opposite) being especially noticeable in some states. One noteworthy pattern

was found: states with unexpectedly high rates of misconduct determinations tended to have

unexpectedly high rates of voluntary quit determinations. 3) Two measures of administrative

stringency demonstrate a measurable association with benefit recipiency. Positive average

residuals (underpredictions) from voluntary quit and misconduct determination rate regressions

were found in several states with low UI benefit recipiency, i.e., low WBTU ratios. 

The sequencing of the analysis in the chapter follows the sequencing of administrative

determinations made in an application for UI benefits. Monetary determinations are examined first

and then separation nonmonetary determinations are studied, both voluntary quits and

misconduct. Then in the last section, the results from the regressions are tied back to measures of

overall UI benefit recipiency.

Monetary Eligibility Rates

Monetary eligibility data by state are available for more than forty years. The proportion

monetarily eligible in national data is displayed in Chart VII-1 for the 33 years 1967 to 1999. The

most striking feature of this chart is the decrease in monetary eligibility during 1975-1977. These

were years of the Supplemental Unemployment Assistance (SUA) program, a program that paid

benefits to persons not eligible under the regular UI program. To be eligible for SUA benefits, the

claimant had first to file for regular UI and be deemed ineligible. Monetary determinations
68 78 88 98

0.76

0.78

0.8

0.82

0.84

0.86

0.88

0.9

Proportion Eligible

Monetary Eligibility Proportion

Chart VII-1. Monetary Eligibility, 1967 to 1999
139

for these three years thus reflect a large volume of denials among claimants who normally would

not have applied for regular UI benefits. 

The regression analysis of monetary eligibility utilized two macro-labor market variables.

The state level unemployment rate (TUR) as measured in the CPS entered as a cyclical indicator.

It is known that monetary eligibility declines at some point after the onset of a recession because

unemployed workers experience reduced base period earnings. Thus the TUR in the regressions

was lagged one year. Unionization was included as a second labor market variable.

Several UI variables entered the regression specifications. Most of these were introduced

previously in Chapter VI in the discussion related to Table VI-4. 1) The effect of the base period

earnings requirement, measured as a ratio to the state’s average weekly wage, was tested. A

higher requirement would be expected to reduce monetary eligibility. 2). Dummy variables were

included to test for three special features of monetary eligibility in the states. The first was the

presence of added earnings requirements, such as the minimum earnings threshold for the final

two quarters of the base period required in Indiana. 3) The second was the presence of an

alternative monetary eligibility requirement if a claimant was found ineligible under the standard

monetary eligibility requirement. In Table VI-4 it was noted that among the site visit states,

California and Oklahoma both had alternative earnings requirements. 4) A dummy variable for the

presence of an alternative base period (ABP) was tested. Having an alternative earnings

requirement or an ABP would be expected to increase the monetary eligibility proportion.

Three time-specific dummies were tested. The first was a dummy for the 1975-1977

period to capture effects of the SUA program on monetary eligibility. Dummies for years from

1981 and years from 1990 were also included to test for changes in monetary eligibility during the

past two decades. Finally, dummies for census bureau divisions were also included.

Table VII-1 displays six regressions, three for the 1967-1999 period and three for the

1971-1999 period. The shorter estimation period starting in 1971 was selected due to a data

availability constraint for nonmonetary determinations. Regressions (4)-(6) have the same

estimation period as the nonmonetary determination rate regressions to be examined later. The

results for the two time periods in Table VII-1 were very similar. 

The TUR and the unionization rate entered all regressions with highly significant
Table VII-1. Factors Related to Monetary Eligibility Rates 

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

Constant 0.845 0.835 0.860 0.854 0.842 0.858

(109.7) (104.7) (77.9) (100.8) (95.6) (70.0)

TUR Lagged -1.137 -1.026 -0.976 -1.118 -0.998 -0.968

(13.4) (11.7) (10.4) (12.0) (10.4) (9.3)

Unionization 0.336 0.351 0.310 0.323 0.340 0.316

(14.3) (14.9) (9.0) (12.1) (12.7) (8.1)

Weeks for Minimum -0.0070 -0.0065 -0.0069 -0.0079 -0.0075 -0.0078

 Benefits-a (6.6) (6.2) (6.6) (6.9) (6.5) (6.7)

Added Earnings -0.0055 -0.0059 -0.0057 -0.0070 -0.0076 -0.0062

 Requirement Dummy-a (1.1) (1.2) (1.1) (1.3) (1.4) (1.1)

Alternative Earnings 0.0172 0.0147 0.0133 0.0168 0.0139 0.0126

 Requirement Dummy-a (3.7) (3.1) (2.6) (3.4) (2.8) (2.3)

Alternative Base Period 0.0293 0.0201 0.0120 0.0308 0.0215 0.0172

 (ABP) Dummy-a (3.2) (2.2) (1.3) (3.3) (2.3) (1.8)

Dummy Variable, 1975- -0.020 -0.021 -0.023 -0.023 -0.025 -0.025

 1977 = 1 (3.1) (3.4) (3.7) (3.5) (3.7) (3.8)

Dummy Variable, 1981 0.058 0.047 0.044 0.054 0.044 0.042

 and Later Years = 1 (13.0) (9.3) (8.2) (11.2) (8.2) (7.6)

Dummy Variable, 1990 0.022 0.022 0.022 0.022

 and Later Years = 1 (4.6) (4.7) (4.5) (4.5)

Div 2 - Mid-Atlantic -0.002 0.001

(0.3) (0.1)

Div 3 - East North Central -0.002 0.003

(0.2) (0.4)

Div 4 - West North Central -0.029 -0.024

(4.4) (3.3)

Div 5 - South Atlantic -0.017 -0.011

(2.6) (1.5)

Div 6 - East South Central -0.026 -0.018

(3.4) (2.2)

Div 7 - West South Central -0.037 -0.027

(4.5) (3.1)

Div 8 - Mountain -0.005 0.005

(0.8) (0.7)

Div 9 - Pacific -0.033 -0.030

(4.3) (3.6)

Adjusted R2 0.239 0.248 0.273 0.236 0.246 0.269

Standard Error 0.067 0.066 0.065 0.068 0.067 0.066

Mean Dep. Variable 0.852 0.852 0.852 0.851 0.851 0.851

Time Period 1967-99 1967-99 1967-99 1971-99 1971-99 1971-99

Sample Size 1683 1683 1683 1479 1479 1479

Source: Monetary determinations as reported in ETA-218 data. a - Variables in Table VI-4 of Chapter VI.
83 Specifications were tested that included the TUR for the current year as well as the

TUR lagged. In all regressions the current year TUR entered with a negative coefficient which

was much smaller and less significant than for the TUR lagged. 

84 The average unionization rate in the top 13 states during 1971-1999 was 0.267

compared to an average of 0.099 in the lowest 13. Multiplying this differential of 0.168 times the

coefficient of 0.313 in equation (6) yields an estimated effect of 0.053. 

141

coefficients. Higher unemployment rates significantly reduced monetary eligibility83 while higher

unionization had consistently positive effects. The size of the coefficients for unionization is

somewhat surprising. While union members are generally high wage workers compared to many

others among the unemployed, the implied differential in monetary eligibility rates between high

and low unionization states exceeds 0.05.84 This seems to be a large effect. 

Of the UI monetary requirements variables, the greatest significance was added by the

base period weeks-for-minimum-benefits variable. Its negative coefficients and its t ratios are

remarkably stable across the six regressions, with the t ratios ranging from 6.2 to 6.9. The other

three monetary variables enter with expected signs but they exhibit more modest significance

levels. All six coefficients for added earnings requirements are negative while all six are positive

for both alternative earnings requirements and for the alternative base period (ABP). Ten of

twelve t ratios for the latter two variables exceed 2.0 and five exceed 3.0.

The time dummies all make significant contributions. The 1975-1977 dummy enters with a

negative coefficient as expected. The 1981 and 1990 time dummies both enter positively

suggesting that monetary eligibility has been increasing in recent years. Of the two, the 1981

dummy makes the more significant contribution in all four equations where both are included.

The dummy variables for the census bureau divisions are often significant in equations (3)

and (6). Since New England is the omitted division, the coefficients show the deviations in

monetary eligibility proportions in the other divisions from the average proportion in New

England. Five divisional dummies are significant in equation (3) and four are significant in

equation (6). Compared to the states in New England, monetary eligibility is systematically lower

in four divisions: the West North Central, East South Central, West South Central and Pacific.

Formal F tests showed the divisional dummies as a group made a significant contribution to
85 The calculated F ratios were 7.97 and 6.69 for equations (3) and (6) respectively. The F

required for significance at the .01 level was 2.53.

142

explained variation in both equations.85 

Overall, the regressions yielded several significant findings and the variables entered with

expected signs. Note that the regressions explained from 23 to 27 percent of the variation in the

monetary eligibility proportion even with the inclusion of dummy variables for census divisions.

These R2s are somewhat lower than the R2s for most regressions fitted in Chapter V.

Separation Determinations

As recorded in ETA-207 reports, voluntary quits and misconduct account for nearly all

separation nonmonetary determinations. Given the contrasting findings of Chapter V regarding

their differential significance in explaining recipiency (misconduct had consistently higher

significance), they were examined separately. Data on determination rates for both

(determinations as a proportion of new UI spells) are first available in 1971. This availability

dictated the starting year for the analysis of both types of determinations.

Over the past three decades the penalties for nonmonetary determinations on separation

issues have become more severe. Nearly all states now impose a durational penalty for a voluntary

quit denial. About three-quarters of the states also impose durational penalty for misconduct

denials. The claimant is disqualified for the entire current spell of unemployment in these

situations. 

Chart VII-2 summarizes the evolution of durational penalties since 1965. Across 51 UI

programs (the 50 states plus the District of Columbia), the voluntary quit penalty in 1999 was for

the duration of the unemployment spell in 47 programs. Note the increases from 1965 when only

21 states imposed a durational penalties for voluntary quits. Over the same period this penalty for

misconduct denials increased in prevalence from 12 states to 38 states. Note that most of the

increase took place between 1976 and 1985.

The time series patterns for the two durational penalties are similar. Essentially there was a

period of stability until 1975 and stability again prevailed from the late 1980s. However, between

1975 and 1986-1987 there was a sharp increase in their prevalence. This interval
65 77 87 98

10

20

30

40

50

Number of States

Misconduct Voluntary Quit

Chart VII-2. States with Durational Penalties

1965 to 1999
144

coincides with two periods when UI financing problems were experienced by the majority of the

states. There undoubtedly was a link between the financing problems and the adoption of

durational penalties by many individual states.

Table VII-2 displays eight regressions that explain variation in the two nonmonetary

determination rates. The sequencing of both sets of regressions is identical. The 1990 dummy is

added in equations (2) and (6) and census division dummies enter the last two of each set of four

equations. The specifications all have two macro-labor market variables, the unemployment rate 

(TUR) and the unionization rate. 

The effects of three UI statutory provisions are tested in Table VII-2. 1) Durational

penalties for the two types of determinations enter as dummy variables (= 1 when the denial is for

the duration of the spell). 2) States that compensate quits only for job-related reasons are

identified with 0-1 dummies. This number increased from 24 states in 1965 to 37 since 1987. If

quits for a broader range of reasons are allowed, it would be expected to increase the rate of quit

determinations. Thus a negative coefficient is expected. 3) The states with two levels of

misconduct (regular and aggravated or gross misconduct) are identified with 0-1 dummy

variables. Having two levels makes it more likely that issues of regular misconduct will be raised,

thus increasing the misconduct determination rate.

As in Table VII-1, the regressions in Table VII-2 include time dummies. The 1981 dummy

and the 1990 dummy equal zero before these years, and then one from these years forward.

Dummies for the census bureau divisions are also included. 

The macro-labor market variables enter these regressions in a consistent manner and at

high levels of statistical significance. The unemployment rate has much larger coefficients in

explaining the voluntary quit determination rate than the misconduct determination rate. Both

variables have uniformly significant coefficients, and 12 of 16 have t ratios above 5.0. Higher rates

of unionization consistently lower separation determination rates.

Durational penalties are uniformly significant in all equations. For both types of separation

issues, the determination rate is lower when denials are for the duration of unemployment.

However, the coefficients in the voluntary quit regressions are roughly six to eight times larger

than in the misconduct regressions. The t ratios in the voluntary quit
Table VII-2. Determination Rates for Voluntary Quits and Misconduct.

Vol Quit Vol Quit Vol Quit Vol Quit Miscond. Miscond. Miscond. Miscond.

(1) (2) (3) (4) (5) (6) (7) (8)

Constant 0.282 0.282 0.238 0.235 0.169 0.166 0.121 0.114

(31.6) (30.7) (20.7) (19.7) (31.8) (30.1) (17.7) (16.0)

TUR -1.017 -1.015 -0.795 -0.766 -0.411 -0.371 -0.531 -0.469

(10.4) (10.0) (7.9) (7.3) (6.5) (5.6) (8.4) (7.2)

Unionization -0.158 -0.158 -0.145 -0.138 -0.246 -0.241 -0.121 -0.104

(5.4) (5.4) (3.6) (3.4) (13.1) (12.8) (4.8) (4.0)

Durational -0.090 -0.090 -0.080 -0.080 -0.012 -0.012 -0.013 -0.013

 Penalty (17.5) (17.5) (15.9) (15.9) (4.2) (4.3) (4.9) (5.0)

Quits Allowed Only for 0.003 0.003 0.002 0.001

 Job-Related Reasons (0.8) (0.8) (0.3) (0.3)

Gross Misconduct 0.004 0.004 0.003 0.003

 Disqualifications (1.6) (1.5) (1.3) (1.0)

Dummy Variable, 1981 -0.017 -0.017 -0.020 -0.022 0.005 0.001 0.014 0.010

 Later Years = 1 (3.4) (3.1) (3.9) (4.0) (1.5) (0.4) (4.4) (2.9)

Dummy Variable, 1990 0.000 0.005 0.008 0.011

 Later Years = 1 (0.1) (1.0) (2.3) (3.5)

Div 2 - Mid-Atlantic 0.005 0.004 0.006 0.004

(0.5) (0.4) (1.0) (0.7)

Div 3 - East North Central 0.023 0.022 0.024 0.022

(2.8) (2.7) (4.5) (4.2)

Div 4 - West North Central 0.062 0.062 0.032 0.034

(8.4) (8.4) (7.0) (7.3)

Div 5 - South Atlantic -0.012 -0.012 0.033 0.033

(1.6) (1.6) (7.3) (7.4)

Div 6 - East South Central -0.007 -0.007 0.001 -0.001

(0.8) (0.8) (0.1) (0.1)

Div 7 - West South Central 0.052 0.053 0.088 0.089

(5.8) (5.8) (15.7) (15.9)

Div 8 - Mountain 0.054 0.054 0.041 0.042

(7.4) (7.4) (9.4) (9.5)

Div 9 - Pacific 0.021 0.020 0.024 0.021

(2.3) (2.2) (4.6) (4.1)

Adjusted R2 0.290 0.290 0.382 0.383 0.202 0.204 0.350 0.355

Standard Error 0.075 0.075 0.070 0.070 0.048 0.048 0.043 0.043

Mean Dep. Variable 0.113 0.113 0.113 0.113 0.098 0.098 0.098 0.098

Time Period 1971-99 1971-99 1971-99 1971-99 1971-99 1971-99 1971-99 1971-99

Sample Size 1479 1479 1479 1479 1479 1479 1479 1479

Source: Determinations reported in ETA-207 data. Determination rate measured as determinations per new spell of unemployment.
86 F tests for addition of the census division dummies had the following results. The

calculated F were 28.57 between equations (2) and (4) and 43.95 between equations (6) and (8). 

146

regressions are some three to four times larger than in the misconduct regressions. Durational

denials have a larger effect in reducing determinations when the issue is a voluntary quit. This

finding suggests a negative effect on UI application rates among job leavers. 

The effects of quits for only job-related reasons is uniformly insignificant. The presence of

gross misconduct penalties has marginal significance. The largest of the eight t ratios for these

two variables is only 1.6. 

There are also different time patterns of change in the determination rates for the two

separation issues. For voluntary quits, there is a decline in the determination rate after 1981 but

no additional change in 1990. For misconduct, there seems to be a secular increase in the

determination rate. The coefficients for the 1981 dummy and the 1990 dummy are both positive

and significant in equation (8). 

Addition of divisional dummies improves the fits for both types of determinations. For

voluntary quits, the adjusted R2 increases from 0.290 in equation (2) to 0.383 in equation (4), or

by about one third. Compared to New England, determination rates on voluntary quits are

especially high in three divisions: West North Central, West South Central and Mountain. These

three sets of divisional dummy coefficients are about half the size of the overall mean of 0.113.

An even larger increase in explained variation is realized when divisional dummies are

added in the misconduct equations. The adjusted R2s increase by about 75 percent (from 0.204 in

(6) to 0.355 in (8)). Note the particularly large dummy for the West South Central division. There

are also large and highly significant dummies for three other divisions: West North Central, South

Atlantic and Mountain.86 Compared to their effects in the monetary eligibility equations of Table

VII-1, the regional dummies in Table VII-2 have larger effects on explained variation in both the

voluntary quit and the misconduct equations. 

The regressions summarized in Tables VII-1 and VII-2 revealed several important factors

linked to interstate differences in monetary eligibility rates, voluntary quit determination rates and

misconduct determination rates. State-level unemployment rates and unionization both had strong

and statistically significant effects on these administrative measures. High unemployment reduces
147

monetary eligibility rates and it also lowers separation determination rates, particularly for

voluntary quits. High unionization increases monetary eligibility while it reduces both types of

separation determination rates. The exact mechanism linking high unionization to lower

determination rates was not identified. Union influence may well operate to lower the presumptive

bar a claimant must meet in cases of voluntary quits and to raise the presumptive bar that

employers must meet to establish misconduct. 

Several UI statutory provisions were also found to be important. Monetary eligibility

proportions are higher when base period earnings requirements are lower and when there are

alternative earnings requirements and an ABP in a state. Voluntary quit and misconduct

determination rates are lower when durational penalties are present. Their effect on voluntary quit

determinations was especially large.

The regressions also found evidence of time-dependent effects. The post-1981 and post1990 dummy variables were both significant in the monetary eligibility regressions, both showing

increases in the monetary eligibility proportions. In contrast, voluntary quit determination rates

decreased after 1981. There was also evidence of increases in misconduct determination rates

after 1981 and after 1990.

Finally, strong regional contrasts in administrative determination rates were found.

Dummy variables for the census divisions made significant contributions to explained variation.

However, the regional contrasts were much more muted for monetary determinations (Table VII1) than for separation determinations (Table VII-2). Addition of regional dummies raised the

adjusted R2s in Table VII-1 by about 10 percent. The increments to the adjusted R2s in Table VII2 were roughly 30 percent for the voluntary quit determination rates and 75 percent for the

misconduct determination rates. Of the three types of administrative determinations examined

here, regional contrasts in misconduct determination rates are by far the largest.

The findings in Tables VII-1 and VII-2 show that several factors can be identified that

cause interstate differences in monetary eligibility proportions and separation determination rates.

Statutory factors play an important role in this interstate variation. Additional analysis of these

and other UI administrative outcomes would seem to be warranted. Given the important effects of

misconduct determinations rates on UI recipiency (Recall Tables V-1, V-2 and V-3), developing a
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better understanding of the factors leading to these contrasts would seem to be a high priority

area for future research. 

Evidence of Stringency in UI Program Administration

The regressions in Tables VII-1 and VII-2 can be utilized to explore the issue of

stringency in UI program administration. Agency decisions regarding monetary eligibility and

separation issues could operate to the disadvantage of claimants and contribute to low rates of UI

benefit recipiency. States where, on balance, administrative decisions operate to exclude a

proportionately larger share of UI claimants from benefits could be described as having stringent

program administration.

To address this question, the analysis focuses on the pattern of residuals from the

regressions shown in Tables VII-1 and VII-2. If a state operated with a stringent administration,

evidence could be provided by the residuals. Stringent administration of monetary eligibility

would be evidenced by overpredictions of monetary eligibility proportions, i.e., lower proportions

than projected by the regression equation. For separation determinations, underpredictions of both

voluntary quit and misconduct determination rates would be expected, i.e., higher determination

rates than projected by the regression equations. The reader should note that some interstate

variation is included in the predictions from the regressions. Essentially, this analysis focuses on

the unexplained reasons for interstate variation. 

 Equation (5) from Table VII-1 and equations (2) and (6) from Table VII-2 were used in

the exercise. Note that all equations were fitted over the 29 year period 1971 to 1999. Note also

that the residuals are from regressions where divisional dummy variables were not included in the

specifications. Thus the residuals can be interpreted as the deviation of each state from the

national average, not from the census division average. The residuals to be examined are the

averages for the full 29 years 1971 to 1999.

These average residuals are displayed in Table VII-3. Note that the states have been

sorted by census division with states in the South Atlantic division further divided into the

northern four and the southern five. Columns (2)-(4) show individual state average residuals

while columns (5)-(7) show simple averages for the ten geographic groupings.
Table VII-3. Comparison of Average Errors for Monetary Eligibility and Separation Determinations by State and Division

Proportion Vol. Quit Misconduct Proportion Vol. Quit Misconduct

Census Mon. Qual. Det Rate Det Rate Mon. Qual. Det Rate Det Rate

State Division Average Average Average Avg. Error Avg. Error Avg. Error

Error Error Error by Division by Division by Division

1971-99 1971-99 1971-99

(1) (2) (3) (4) (5) (6) (7)

CONNECTICUT N Eng -0.057 -0.032 0.016

MAINE N Eng -0.082 -0.028 -0.038

MASSACHUSETTS N Eng 0.083 -0.035 -0.023

NEW HAMPSHIRE N Eng 0.044 -0.023 -0.027

RHODE ISLAND N Eng 0.053 0.003 -0.033

VERMONT N Eng 0.019 -0.024 -0.059 0.010 -0.023 -0.028

NEW JERSEY M Atl -0.008 -0.013 -0.009

NEW YORK M Atl 0.046 0.006 0.004

PENNSYLVANIA M Atl -0.011 -0.031 -0.029 0.009 -0.012 -0.011

ILLINOIS EN Cent -0.034 -0.024 0.025

INDIANA EN Cent -0.027 0.074 0.011

MICHIGAN EN Cent 0.038 0.012 0.005

OHIO EN Cent 0.032 -0.024 0.003

WISCONSIN EN Cent 0.051 -0.028 -0.025 0.012 0.002 0.004

IOWA WN Cent -0.003 0.063 -0.014

KANSAS WN Cent -0.023 -0.043 0.012

MINNESOTA WN Cent 0.054 0.010 0.010

MISSOURI WN Cent -0.068 0.011 0.027

NEBRASKA WN Cent 0.074 0.245 0.059

NORTH DAKOTA WN Cent -0.045 -0.043 -0.048

SOUTH DAKOTA WN Cent -0.077 -0.005 -0.016 -0.013 0.034 0.004

DELAWARE S Atl-a 0.049 -0.046 -0.022

DIST OF COL S Atl-a -0.107 0.003 0.087

MARYLAND S Atl-a -0.052 -0.054 0.018

WEST VIRGINIA S Atl-a 0.064 -0.006 -0.015 -0.011 -0.026 0.017

FLORIDA S Atl-b -0.018 0.015 0.044

GEORGIA S Atl-b 0.056 -0.026 0.031

NORTH CAROLINA S Atl-b 0.046 -0.096 -0.076

SOUTH CAROLINA S Atl-b -0.024 -0.064 -0.046

VIRGINIA S Atl-b -0.008 -0.050 -0.030 0.010 -0.044 -0.015

ALABAMA ES Cent -0.027 -0.013 -0.039

KENTUCKY ES Cent 0.005 -0.031 -0.036

MISSISSIPPI ES Cent -0.013 -0.005 -0.018

TENNESSEE ES Cent 0.011 -0.056 -0.043 -0.006 -0.026 -0.034

ARKANSAS WS Cent 0.040 -0.002 -0.038

LOUISIANA WS Cent -0.020 0.077 0.063

OKLAHOMA WS Cent -0.080 0.026 0.042

TEXAS WS Cent -0.001 0.017 0.133 -0.015 0.029 0.050

ARIZONA Mountain 0.006 0.027 0.033

COLORADO Mountain 0.050 0.166 0.021

IDAHO Mountain 0.019 -0.010 -0.034

MONTANA Mountain -0.031 0.014 -0.030

NEVADA Mountain 0.047 0.036 0.078

NEW MEXICO Mountain 0.027 0.028 0.009

UTAH Mountain 0.056 0.017 0.017

WYOMING Mountain -0.044 -0.040 -0.015 0.016 0.030 0.010

ALASKA Pacific -0.034 -0.049 -0.028

CALIFORNIA Pacific -0.055 0.021 0.019

HAWAII Pacific 0.035 0.027 0.027

OREGON Pacific -0.037 0.008 0.012

WASHINGTON Pacific -0.015 -0.001 -0.014 -0.021 0.001 0.003

Source: Average errors based on equation (5) in Table VII-1 and equations (2) and (6) in Table VII-2. 

 a - Four northern states of the South Atlantic division. b - Five southern states of the South Atlantic division.
87 For voluntary quit and misconduct determinations positive residuals indicate that more

determinations occurred than predicted by the regression. For monetary eligibility a positive

residual would mean eligibility was greater than predicted by the regressions. If this sign is

reversed a positive number would then mean there was a lower eligibility proportion than

predicted by the regression.

88 The states with three positive signs were Indiana, Missouri, the District of Columbia,

Florida, Louisiana, Oklahoma, Texas, California and Oregon. The states with three negative signs

were Massachusetts, New Hampshire Vermont, Wisconsin, Delaware, West Virginia, North

Carolina, Kentucky, Tennessee, Arkansas and Idaho. Readers are reminded to change the sign for

the column (2) residuals in performing this test.

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One aspect of the divisional averages is to show the importance a single state can have on

a divisional average. Note, for example, the states in the West North Central division in columns

(3) and (6). Nebraska has a very high volume of unexplained voluntary quit determinations. Its

average residual in column (3) is 0.245. When this average residual is removed from the divisional

average in column (6), the average decreases from 0.034 to -0.001. This illustrates how a single

state can have a large impact on the divisional averages in columns (5)-(7).

One analysis of the average residuals noted their correlations. A second analysis examined

the consistency of their algebraic signs. To examine the consistency of algebraic signs it was

necessary to reverse the signs for the monetary eligibility residuals. Thus positive averages would

indicate greater restrictiveness than suggested by the predicted value from the underlying

regression.87 The null hypothesis for the tests of algebraic signs was that the distribution of pluses

and minuses was random within each state. If this were the case, the distribution of outcomes

should be the same as from three flips of a coin, i.e., outcome proportions of 1/8, 3/8, 3/8 and 1/8.

The two extreme combinations (three pluses and three minuses) should each occur in one state in

eight or in six programs across the 51 included in Table VII-3. 

This test of signs found nine states where all three average residuals were positive and

eleven where all three were negative.88 These counts exceed what would be expected if the

average residuals were randomly distributed within each state. Of the nine states where all three

average residuals were positive (suggesting stringent UI administration), five were among the 13

states with the lowest long average WBTU ratios: Indiana, Florida, Louisiana, Oklahoma and

Texas. Two were from among the 13 with the highest long run WBTU ratios: the District of
89 Recall that California which also had three positive residuals had the 15th highest long

run WBTU average.

90 The three pairwise correlations were: 0.192 between columns (2) and (3), negative

0.112 between columns (2) and (4) and positive 0.514 between columns (3) and (4). Significance

at the 0.05 and 0.01 levels requires correlations that exceed 0.277 and 0.358 respectively. 

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Columbia and Oregon.89 From the eleven where all three average residuals in Table VII-3 were

negative (suggesting non-stringent or more passive UI administration) three were from the group

of 13 states with the highest WBTU ratios (Massachusetts, Vermont and Wisconsin) while just

one state (New Hampshire) was from the 13 with the lowest long run WBTU ratios. These

patterns are suggestive of a link between the Table VII-3 residuals as indicators of administrative

stringency and low overall UI benefit recipiency. 

The correlation analysis examined pairwise correlations among columns (2)-(4) and (5)-

(7) of Table VII-3 (with the signs reversed for (2) and (5)). When columns (2)-(4) were

compared, two of three pairwise correlations were positive, to be expected if administrative

stringency affects many aspects of UI administration within a state. However the pairwise

correlation between the monetary eligibility errors and voluntary quit determination errors, e.g.,

columns (2) and (3), was not significant. Similarly, the correlation between the monetary eligibility

errors and the misconduct determination errors, e.g., columns (2) and (4), also was not

significant. However, the correlation between the average errors for voluntary quit and

misconduct determination rates, i.e., columns (3) and (4), was positive and statistically significant.

The average errors for these two determination rates were strongly positively linked.90

The preceding discussion referred to correlation tests conducted with the 51 programs

included in columns (2)-(4). Identical results were obtained when the average residuals for the ten

divisions in columns (5)-(7) were tested for significant correlations. The only pairwise correlation

that was significant was between the voluntary quit average residuals and the misconduct average

residuals.

A final analysis of the Table VII-3 residuals was to make direct comparisons between the

residuals and long run benefit recipiency. Some interesting and (perhaps) expected patterns were

found. The average residuals in columns (2), (3) and (4) were sorted, and the top 13 and bottom
91 The thirteen states with the lowest WBTU ratios during 1971-1999 were the same 13

as shown earlier in Table III-1. The seven with the largest voluntary quit residuals and lowest

WBTU ratios were Colorado, Louisiana, Indiana, New Mexico, Arizona, Oklahoma, and Texas.

92 The t ratio required for significance at the 0.10 level is 1.68.

93 These were Texas, Louisiana, Florida, Oklahoma, Arizona, Georgia, and Colorado.

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13 states were then compared with the WBTU ratios (like those in Table III-1 but calculated for

the period 1971-1999). For the monetary eligibility residuals of Table VII-3, no clear pattern

distinguished states with large positive average residuals from those with large negative average

residuals. Of the 13 with the largest negative residuals in column (2), four were among the 13

with the highest WBTU ratios and two were among the 13 with the lowest WBTU ratios. Of the

13 with the largest positive residuals in column (2), four were from the 13 with the highest

WBTU ratios and two were from the 13 with the lowest WBTU ratios. Average monetary

eligibility residuals, in effect, had no systematic relationship with overall UI benefit recipiency.

Comparing the voluntary quit residuals of column (3) with average WBTU ratios yielded

different results. Of the 13 states with the largest positive voluntary quit residuals in Table VII-3

(indicating administrative stringency), seven were from the group with the lowest WBTU ratios.91

Conversely three with the most negative average residuals in column (3) of Table VII-3 were

from the 13 with the highest WBTU ratios (Connecticut, Massachusetts and Alaska).

While the preceding comparison is suggestive, a formal statistical test did not yield strong

findings. The correlation between the WBTU ratio (1971-1999 average) and the average

voluntary quit residuals in column (3) was negative (more stringent administration associated with

low recipiency). However, the t ratio was only -1.62, just short of significance at the 0.10 level

using a two sided test.92 

Similar results were obtained when the column (4) average residuals for misconduct were

compared with the WBTU ratio. From the 13 states with the largest positive residuals for

misconduct determinations, seven had the lowest WBTU (1971-1999 average).93 Again three of

the 13 states with the largest negative average residuals were from the top 13 states in Table III-1

(Rhode Island, Maine and Vermont). The statistical test of the association between these

misconduct determination errors and the WBTU ratio also showed a negative association, but just
94 Note that all five states are from the group of nine “southwestern” states identified in

Map 3 of Chapter III. They are characterized by low inflow rates but high relative duration in UI

benefit status.

153

short of statistical significance at the 0.10 level, i.e., t ratio of -1.61. 

Five states with low WBTU ratios had large positive average residuals (among the top 13)

for both voluntary quit and misconduct determination rates. These states were Arizona, Colorado,

Louisiana, Oklahoma and Texas. Low recipiency was associated with higher than predicted

determination rates for both types of separations in these five states.94

Summary

This chapter examined three measures of administrative activities, the monetary eligibility

proportion, the voluntary quit determination rate and the misconduct determination rate. Multiple

regressions identified several factors that had significant effects on these three variables that

reflect UI administrative decisions. 

State unemployment rates and unionization rates had highly significant effects on all three

administrative variables. Of the 28 regression coefficients for these two variables displayed in

Tables VII-1 and VII-2, 13 had t ratios of 10.0 or larger and 24 had t ratios of 5.0 or larger. High

unemployment reduced all three administrative variables though undoubtedly for different reasons,

a lagged effect on monetary eligibility and a mix effect on separation determinations. High

unionization is associated with high monetary eligibility rates but low rates of both voluntary quit

and misconduct determinations.

Monetary eligibility was also affected by several UI program variables. Higher monetary

requirements reduced eligibility. The presence of added earnings requirements, alternative

earnings requirements and the alternative base period all entered with anticipated effects but with

mixed levels of significance. Eligibility was lower during 1975-77, the years of the SUA program.

The positive coefficients for the 1981 and 1990 time dummies suggest a secular increase in

monetary eligibility rates during the most two recent two decades. 

Imposition of durational penalties reduced determination rates for both quits and

misconduct. The effect on voluntary quits was particularly large. The time dummies suggest the
154

prevalence of voluntary quit determinations decreased after 1981 while misconduct

determinations were higher after 1981 and again after 1990.

One interesting contrast between the monetary and separation determinations should be

pointed out. For all three administrative variables, specifications were fitted which included

dummy variables for census divisions. These dummies cause only modest increases in explained

variation for monetary eligibility, roughly 10 percent in Table VII-1. However, for voluntary quit

and especially for misconduct determinations, their contributions are much larger. The adjusted

R

2

s increase by more than 30 percent for voluntary quits in Table VII-2 (compare (3) and (4) with

(1) and (2)) and by more than 70 percent for misconduct (compare (7) and (8) with (5) and (6)).

The especially large positive coefficients and associated t ratios for some census division dummies

pinpoint divisions where these determination rates are especially high. The pattern of these

dummies in Tables VII-1 and VII-2 suggest large differences in administration of nonmonetary

determinations across areas. High determination rates for both voluntary quits and misconduct

were found in the West North Central, West South Central and Mountain divisions.

Using average residuals from the regressions, the chapter conducted a first analysis of

administrative stringency. Stringency was approximated with the average state-level residuals

from the regressions. There was a link between the residuals for voluntary quit determinations

and the misconduct determinations and UI recipiency. States where these two residuals were large

and positive, i.e., with more determinations than projected by the regression equations, were

found to be disproportionately concentrated among the 13 states with the lowest average UI

recipiency as reflected in WBTU ratios. Formal statistical tests of this association using the

WBTU ratio as the measure of recipiency were supportive of this interpretation but not

particularly robust. 
95 The five are Indiana, Mississippi, New Hampshire, South Dakota and Virginia.

155

Chapter VIII. Summary and Conclusions

This project examined a major question about the unemployment insurance (UI) program

in the United States. Why does the receipt of UI benefits vary so widely from one state to the

next? In addressing this question, greatest interest centered on those states where recipiency is 

especially low.

Chapter II documented the variation in recipiency rates examining two state level

measures, IUTU ratios and WBTU ratios. Focusing primarily on WBTU ratios (weekly UI

beneficiaries as a ratio to weekly unemployment ), the chapter summarized state-level data for the

years since 1967. Long run averages of WBTU ratios were found to exceed 0.40 in some states

while in other states WBTU ratios averaged less than 0.20. State-specific patterns of high

recipiency and low recipiency were shown to persist over several years.

As a matter of logic, low recipiency results from the effects of a low inflow rate into

benefit status by unemployed workers and/or short duration in benefit status. In Chapter III, an

accounting framework was developed that is useful for examining interstate differences in

recipiency. The framework explicitly identifies three factors related to inflows into benefit status

(the application rate, the repeat application rate and the first payment rate) which along with

relative duration (UI benefit duration relative to overall unemployment duration) combine to

determine the level of benefit recipiency. 

Applying this framework to state-level data, three distinct patterns of low recipiency were

identified. 1) In five widely dispersed states, a low inflow rate and short benefit duration both

contribute to low recipiency.95 2) In nine states, inflows into benefit status are low while relative

duration exceeds the national average. Because inflow rates are so very low, however, low

recipiency is the result. Eight of these nine states are geographically contiguous, located broadly
96 The eight contiguous states are Louisiana, Texas, Oklahoma New Mexico, Arizona.

Colorado, Utah and Wyoming. The ninth is Florida. 

97The five are North Carolina, South Carolina, Georgia, Alabama and Tennessee.

156

in the southwest and Rocky Mountains.96 A common characteristic of UI program administration

in these states is an above-average rate of agency determinations on separation issues, i.e.,

voluntary quits and misconduct. 3) In five states, there is an average rate of inflow into benefits

but short relative benefit duration. These five are also contiguous, located in the southeast.97 A

characteristic of the UI program in these states is that many claims are filed by employers on

behalf of job-attached workers. The ability to identify these contrasts among three groups of

states with low recipiency illustrates the usefulness of accounting framework developed within the

project. Map 3 of Chapter III displays the three groups of states. 

The project followed two approaches in studying the explanation for low recipiency. 1)

Inferences were drawn from multiple regressions and other analyses using data from all states.

Chapters IV, V and VII reported findings from the regressions and related analyses. 2) Site visits

were conducted in nine states. The site visits focused on detailed aspects of UI statutes and

administration and the findings were summarized in Chapter VI. 

The regression analysis of UI recipiency in Chapter V utilized the accounting framework

from Chapter III and applied it to pooled data from the states spanning several years. The

regressions included both macro-labor market variables and variables reflecting key aspects of UI

statutes and program administration as well as methods of filing for benefits. All three groups of

variables made important contributions to explained variation. The regressions focused on three

ratios related to the inflow into UI benefit status and a fourth ratio reflecting relative duration in

benefit status.

The application rate, the inflow variable with the widest range of state to state variation,

was found to depend on several identifiable factors. 1) Two labor market variables, the job loser

share of new unemployment spells and the unionization rate, made important contributions to

explained variation. 2) Applications were strongly and inversely linked to the misconduct

determination rate (determinations as a share of new applications). 3) Applications were
157

significantly higher in states where partial benefits were more prevalent and where minimum

monetary eligibility requirements were easier to satisfy. 4) Methods of filing initial claims other

than in-person filing were found to increase application rates with the biggest effect caused by

employer-filed claims. Of the various influences on the application rate, the most important single

factor was the misconduct determination rate. This finding strongly suggests that applications are

deterred in states where misconduct determinations occur with high frequency. 

Repeat applications for unemployment benefits were also found to depend negatively on

the misconduct determination rate. Other important determinants of repeat applications included

the prevalence of partial benefits and the rate at which voluntary quit determinations resulted in

denials. The misconduct determination rate had the largest quantitative on repeat applications of

all the individual explanatory variables.

The first payment rate, first payments as a proportion of new initial claims, was

significantly dependent on several factors. 1) An indicator of net (liable less agent) interstate

claims activity exerted a strong positive effect on the first payment rate. 2) The misconduct

determination rate had a large negative effect. 3) As would be expected, the monetary eligibility

proportion had a large and significantly positive effect. 4) The misconduct denial rate had a large

negative effect on the first payment rate. 5) Interestingly, the share of initial claims filed by

employers had a negative effect on first payments. This probably reflects a low first payment rate

on new claims other than employer-filed claims. 

While several important determinants of the repeat application rate and the first payment

rate were identified, their range of variation across states was much smaller than the range for the

application rate. In states with low recipiency the biggest single factor is that claimants simply do

not file for benefits. 

In the explanation of inflows into UI benefit status, the largest effect was found for the

misconduct determination rate. High misconduct determination rates were associated with low

application rates, low repeat application rates and low first payment ratios. In short, all three

facets of claimant inflows into benefits were reduced by high misconduct determination rates.

While several other factors were important determinants of one or, sometimes, two of the inflow

variables, the misconduct determination rate was uniquely important in exerting large, significant
158

and negative effects on all three inflow variables.

Relative unemployment duration, i.e., duration of UI benefits relative to overall

unemployment duration in the state, was strongly linked to several factors. 1) Relative duration

was high in states with a high job loser share of new unemployment spells. 2) High potential UI

benefit duration increased relative duration. 3) The method of filing continued claims was

important. High shares of claims filed by mail and telephone both increased relative duration while

a high share of employer-filed claims shortened duration. The latter effect was especially large. 4)

High levels of the nonseparation determination rate, the nonseparation denial rate and the rate of

eligibility reviews all operate to reduce relative duration in benefit status. 

The strong effects of the nonseparation determination rate and the eligibility review rate

on relative duration show that active administration of continuing claims significantly shortens the

average duration of benefits. Some states, e.g., New Hampshire and North Carolina, even add

state-level resources to ensure that the administrative activities related to continuing eligibility are

adequately funded.

It should be reemphasized that the preceding findings were based on multiple regressions

that also included large and significant effects of capacity utilization, the job loser share of new

spells of unemployment and the unionization rate. Even controlling for these key factors in the

macro-labor market of the states, UI program (statutory and administrative) variables had

important effects on all aspects of UI recipiency covered by the regression analysis. 

While the findings of the site visits were more qualitative than quantitative, several

patterns were identified that differentiated four high recipiency states from five low recipiency

states. Seven specific examples were the following. 1) States with high recipiency states have

made much more accommodation to non-English speakers in filing for UI benefits. 2)

Requirements for monetary eligibility are generally easier to satisfy in high recipiency states. This

encompasses lower monetary thresholds (measured relative to the average weekly wage), the

absence of added monetary requirements, having alternative earnings requirements and offering an

ABP and STC. The net effect of differences in monetary eligibility requirements can be

summarized with average monetary eligibility proportions. These proportions averaged 0.90 in the

four high recipiency states but only 0.81 in the five low recipiency states while the national
159

average was 0.86. 3) Rates of adjudication on separation issues, both quits and misconduct, are

generally lower in states with high recipiency. 4) Quits are more likely to be compensated in high

recipiency states. 5) Disqualifying and deductible income denials are less likely in high recipiency

states. 6) Eligibility reviews generally occur less frequently in high recipiency states while

penalties for failure to meet reporting requirements have more “teeth” in low recipiency states. 7)

Rates of employer appeals of nonmonetary determinations are much lower in high recipiency

states, less than half the rate of appeals in low recipiency states. While the separate contributions

of these individual factors are difficult to estimate, all operate to reduce recipiency in the states

with low recipiency.

Because the methodologies used in the two research approaches were so different, exact

comparisons of their findings are somewhat difficult to make. However, the two approaches did

yield one broad common finding. From the regressions and from the site visits, factors related to

UI statutes and program administration were identified that result in low recipiency. Additional

quantitative and qualitative analysis seems warranted in order to develop a more complete

understanding of low benefit recipiency.

Chapter VII addressed the issue of UI administrative stringency by examining three

administrative decisions important in determining the inflow of claimants into benefit status: the

monetary eligibility proportion, the voluntary quit determination rate and the misconduct

determination rate. These variables were examined with a series of multiple regressions. The

patterns of average residuals from the regressions were then compared. Probably the most

important finding of Chapter VII was that low benefit recipiency, as signaled by the WBTU ratio,

was negatively associated both with the voluntary quit determination rate residuals and with the

misconduct determination rate residuals. Large positive average determination rate residuals, i.e.,

unexpectedly high determination rates, were present in several states with low WBTU ratios.

Considering the findings across all chapters, three broad conclusions can be offered. 1)

Variation from state to state in UI benefit recipiency can be productively studied, and the present

analysis indicated that low recipiency is systematically linked to variables reflecting UI statutes

and administrative operations. 2) Varying rates of inflow into benefit status generally have larger

effects on benefit recipiency than duration in benefit status. The application rate and the first
160

payment rate, two of the three inflow variables studied in Chapter V, are most closely linked to

overall recipiency as measured by the WBTU ratio. 3) The misconduct determination rate has an

especially large effect on all three ratios linked to inflows into UI benefit status. Developing a

more detailed understanding of the reasons for variation in misconduct determinations should be a

priority area for future research.

Employer filing of UI claims is a major phenomenon in the UI programs of five states, all

located in the southeast. When this type of filing is examined, however, it has large effects on UI

recipiency in these five states. A short summary of key features of the UI programs in these states

would be: 1) high application rates, 2) low first payment rates, 3) low benefit duration and 4) low

determination rates on separation issues, both voluntary quits and misconduct. These

consequences flow largely from a situation where a high proportion of claimants are still job

attached. In states with a significant volume of employer filing, the UI program experiences an

especially fast flow-through of claimants when compared to other states. 

The distinctive features of the UI programs in these five southeastern states are

highlighted in the regressions by their distinct “marker” variable, i.e., the high share of employerfiled claims. There is no comparable marker variable that specifically distinguishes the nine, mainly

southwestern, states characterized by very low inflows but above-average benefit duration. As

noted, these states also have distinct characteristics: 1) low application rates, 2) long benefit

duration, and 3) high determination rates on separation issues, both voluntary quits and

misconduct. The closest to a marker variable for these states is the misconduct determination rate.

They account for seven of the thirteen states with the highest average misconduct determination

rates, and only one state from these nine (New Mexico) has an average lower than the national

average. This could suggest that UI agencies in these states set a low threshold for the burden of

proof that employers must satisfy in order to establish claimant misconduct. 

In conducting the research for this project, several questions were encountered that

seemed fruitful areas for further research. Some were questions that could be addressed through

requests for information already resident in UI administrative records but not routinely

summarized in reports submitted by the states. 

A short listing would include the following. 1) How many people combine work with the
161

receipt of UI benefits in the same week? Data on partial weeks compensated, about 9 percent of

all weeks compensated, understate the prevalence of this phenomenon because some claimants

receive full weekly benefits and also have earnings in the same week. 2) What share of weeks

compensated is paid to persons who quit their last jobs? All that is known at present is the number

of allowances of claims where there was a voluntary quit separation issue. Subsequent first

payments and weeks compensated are not tracked. 3) What is the net effect of commuter

claimants on recipiency by state when all commuters are classified according to their state of

residence? All three questions could be addressed with tabulations of UI administrative data and

ICON data. A starting point would be to make selective inquiries in a few high recipiency states

and a few low recipiency states.

Other important questions would have to be pursued with differing approaches. 5) Of the

issues affecting recipiency addressed in the present project, one in particular deserves more

analysis. That is the reason(s) for increased unemployment duration in the 1980s and 1990s

compared to earlier decades. As documented in Chapter IV and in Chart IV-2, the increase is

apparent in both UI data and in data from the CPS. Because average duration has increased more

in CPS data than in UI data, this has contributed to the decrease in IUTU and WBTU ratios. The

question has ramifications beyond just the regular UI program, the principal arena for the present

project. UI benefit duration is affected by agency activities examined in Chapter V (nonseparation

determinations and eligibility reviews). It is also a concern of OWS as it encourages states to

institute effective profiling procedures. However, if evolutionary changes in the labor market are

causing the increase in average unemployment duration, it then becomes all the more important to

understand why, if initiatives to shorten UI benefit duration are to be effective. There is a need for

added research on the determinants of unemployment duration.

Some other questions not directly addressed by this project also merit research. 5) Why do

voluntary quit and misconduct determination rates vary so widely across states? 6) How much is

recipiency increased by having language accommodation to non English speakers? 7) What role

do third party representatives play in influencing UI benefit recipiency? 8) Do high rates of

employer appeals affect UI benefit recipiency?

All these questions seem worthy of further investigation. 
162

References

Advisory Council on Unemployment Compensation. (1996). Collected Findings and

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List of Abbreviations

ABP - alternative base period, time period more recent than the regular base period used for

monetary eligibility determinations

AD - average unemployment duration, CPS data, derived by the project

ADPUB - average unemployment duration, published CPS data

ADUI - average duration in UI benefit status

ADUIAD - ratio of ADUI to AD

CCH - Commerce Clearing House, Inc., UI statutes summarized in CCH UI Reports

CPS - Current Population Survey, monthly labor force survey of households

CWC - combined wage claims, claims involving covered wages from two or more states

ETA - Employment and Training Administration of the U.S. Department of Labor

FPNIC - ratio of first payments to new initial claims

ICNU - ratio of initial claims to new spells of unemployment

IU - insured unemployment or active UI claimants

IUTU - ratio of insured unemployment to total unemployment

IVR - Interactive Voice Response, automated telephone system for collecting claims information 

 

NICIC - ratio of new initial claims to initial claims

STC - short time compensation or worksharing, specialized claims in for situations where the

claimant works but less than a full-week schedule

SUA - Supplemental Unemployment Assistance, special UI benefit program for those not eligible

for regular UI, operative from 1975 to early 1978

TU - total unemployment from the monthly labor force survey of households

WB - average weekly number of UI beneficiaries

WBIU - ratio of weekly UI beneficiaries to insured unemployment

WBTU - ratio of weekly UI beneficiaries to total unemployment