A STUDY OF ~ERCOHORT C~GE IN WO~ ‘S WOW

PATTERNS AND W~GS

M. ke Hill and June E. O‘ Neill

Center for the Study of Business and Goverment

Baruch College

F~AL MPORT

Dec~ber 1990

This Project was fmded by the U.S. Depart~nt of Labor, Bureau of Labor

Statistics under Grant Number E-9-J-8-0092. Opfiions statd in this docummt

do not necessarily represent the official position or policy of the U.S.

Department of Labor. We gratefully acknowledge the excellent data preparation

and programg assistance provided by Hengzhong Liu, Partha Deb, Chm-Yong

Y~g, md T. Jithendranath~. Additional fwding for this res-rch haa been

provided by The Rockefeller Foundation.
This Pro ject was funded by the U.S. Department of Labor, Bureau of Labor

Statistics under Grant Number E-9-J-S-0092. Opinions stated in this document

do not necessarily represent the of fictil position or policy of the U.S.

Department of Labor. We gratefully acknowledge the excellent data preparation

and programing assistance provided by Hengzhong Liu, Partha Deb, Chun-Yong

Yang, and T. Jithendranathan. Additioml finding for this research has been

provided by The Rockefeller Foundation.

A STUDY OF INTERCOHORT CHANGE IN WO~N ‘S WOW

PATTERNS AND RAHNINGS

M. Anne Hill and June E. O ‘Neill

Center for the Study of Business and @vernment

Baruch College

FINti HSPORT

December 1990
TABLE OF CONTENTS

E=cUTI~ S~Y

I. INTRODUCTION

II- CHANGES IN LIFE-CYCLE LASOR FORCE PATTERNS,

SCHOOLING , AND FERTILITY

A. Background

B. Description of the Data

c. Descriptive Analysis

Work Participation

;: Cuulative Years of Work Experience

3. Year= of Schooling

4. Changes in Marital Status and Fertility

D. Sumary

III. DETERMINANTS OF THE DURATION OF WORX AND NON-WORR SPELLS

A. Multiple Spell Hazard Rate Model

1- M:thod610.gy

2. Description of the Data

Model

3. Empirical Analysis

IV. DETE~INANTS OF THE PROPORTION OF

T~ LIFETI~

for the Multiple Spel 1

YEARs WO=D OVSR

A. Empirical Results

B. Accounting for the Increase in Lifetime Participation

c. Sumary

v. IS THE FEMALE EXPERIENCE-WAGE PROFILE GROWING STEEPER?

A. Cohort/Age/Race Specifti Regressions

s. Regressions Using Pooled Data

~FERENCES

APPENDIX A

APPENDIX B

1

8

8

9

13

13

19

26

26

35

36

36

3s

40

44

56

56

63

6S

70

70

73

78
After remaining virtually constant during the post-World War II yriod,

the ratio of women, s earnings to men, s incre=ed sharply during the 1980, e,

rising from 59.7 percent in 1979 to 68.5 percent in 1989. The failure of the

overall wage gap to narrow during the 1950-1980 period has been somettig of a

puzzle. The lsbor force patiicipation of mmen had escalated over the entire

post World War II period, the women, s mov~ent had blossomed, and barriers to

women, s entry into many professions and occ”pakions appeared tO have eroded.

Yet, overall women, e relative earnings did not rise through the lg60S -d

1970s. -

Explanations for the app=ent paradox have pointed out that during the

post War period of rapid increases in the proportion of mmen who work, the

experience level =d other work related attributes of the average employed

women did not increase, as less experienced women joined the ranks of the

employed. The failure of the wage gap to narrow before 1980, therefore, can

be partly explained by the failure of women, s lifettie work experience to rise

as new l~or force entrants lowered the work experience of the average working

woman.

Quite the opposite phenomenon may underlie the increase in women, s

relative earnings in the 1980s. Indeed, one explanation for this recent

development is that there has been an intercohort increase in the continuity

of women, s labor force participation resulting in a greater accumulation of

work experience. The fact that the recent gains in women, s relative wages

have been larger mong younger women suggests that intercohort trends in human

capital acquisition are important and that more recent cohorts of women have

gained relative to men in terms of market~le skills.

Yet because women are heterogeneous with respect to lif ethe experience,

changes in accumulated work experience cannot be measured using stand-d

cross-sectional data. Longitudinal or retrospective data on life-cycle

experience are crucial for studying issues related to women, s labor supply,

human capital formation, and earnings. This research utilizes data from the

three continuing panels of the National Longitudinal Surveys (NLS ) -- the

mature women, the young women, and the youth cohort -- to measure accumulated

years of work experience ad to exmine changes in life-cycle work patterns

acros5 successive cohorts of women born between, 1923 =d 1964.

This study has investigated how these successive cohorts of women have

changed with respect to their accumulation of work-related skills, in terns of

level of schooling, career orient at ion, and attatient to the l~or force. We

consider how the nature of entry into and exit from the ldor force chwged

across cohorts and how the reeponse of women, s labor force participation

decisions to life-cycle events (e.g. , marriage, the bfith of a child, divorce)

may have changed. Inter cohort changes in women, s returns to work e~erience,

schooling, and other hman capital investments are also considered. This

research has yielded important insights into the nature and determinants of

the work patterns and earnings of Werican women.

Our comparison of human capital and demographic characteristics across

these seven cohorts of women has illuminated the dr-atic changes in l~or

market experience and its correlates. Labor force participation, whether
measured at a point fi the or over the lifettie has increased markedly for

white women, with black women +periencing slight increases or declinee. For

working and nonworking women chined, the cuulative ye=s during which an

individual has worked at least six mnths has risen, although the average

level of e~erience of employed women has groin more slowly or has actually

declined. While 5ome of this slomr grotih cm be attrfiuted to the lower

levels of aperience held by new. entrants and the rapid increase in the rider

of new entrants (as signal led by the rise in sufiey week participation rates) ,

rising leve15. of schooling have. also diminished the ..nher of post-schooling

ye-s within which women (at a fixed age) could have worked.

Along with rising levels of investment in education, these cohorts of

women have experienced drmst ic demographic changes. A larger proportion of

each cohort remains umarried and mre women conttiue to be ctildless.

Moreover, the nutier of children ever born mong these women has declfied

sharply, with mmen in..the earlier cohorts bearing three to four children and

more recent cohorts giving birth to two to three children.

We have exmined the deteminante of work ~erience using two mOdel B.

For the ~SY and the ~S young women, we were able to estimate the multiple

spell hazard rate model of work status transition. Moreover, we have

ex-ined, for all cohorts, ordinary least s~=es regressions of the

propotiion of possible years worked as of a given age.

Both the duration model and the lifethe participation model yield

strikingly similar results - During the period 1967 to 1987, the length of

work spells and the proportion of the lifet tie worked have increased. These

chmgee are strongly related to rising levels of schooling, delayed

childbearing and reductions in fertility, and transformations in marri~e

patterns. Results from the duration models imply that labor 5upply responses

are becoming increasingly sensitive_ to schooling and prior work e~erience

(especially =ong black women) . And for white women, much of the intercohort

change in lifetime participation ap~ars to result from drmatic fertility

declines - Yet the esttiates from pooled models for lifettie participation

indicate that, holding constant the effects of the independent variables,

there remains a strong, etatietically significant effect of the passage of

time. Even with identical ch=acteristics, women from more recent cohotis

spending a higher proportion of their time at work in the market.

Finally, we have estimated wage models for these cohorts of women to

are

investigate whether or not experience-wage profiles have grow steeper over

ttie. Our .result5 provide evidence that work-related investments have

increased from cohort to cohort mong white women, although not necessarily

for all cohorts of black women. And while we cannot detemine from our

analysis the extent to which women or their employers =e responsible for the

increased levels of investment, the fomer pattern of flat age-earnings

profiles for women -- the dead-end job syndrome -- finally appears to have

been uvercome, which bodes well for future narrowing of the gender wage gap.
women did not increase, as less experienced women joined the ranks of the

employed (Goldin, 1989; O, Neill, 1985; Smith ~d Ward, 1989) . It has been

demonstrated in a n~er of studies that a prhary factor underlying the

gender gap in wages is the gender differential in the mount and continuity of

lifetime work experience (e.g., Mincer and Polachek, 1974, 1978; Corcoran and

A ST~Y OF INTERmHORT CSANGE IN

WOmN ,S WORW PATTE~S ANO EARNINGS

M. hne Hill and June E. O, Neill

Center for the Study of Business and Goverment

Baruch College

I. I~ODU~IOR

After rwining virtually constant during the post-world War II period,

the ratio of wmen, 5 earnings to men, s increased sha~ly during the 1980,s,

rising from 59.7 percent in 1979 to 6B. 5 percent in 1989 (based on the annual

earnings of full-time ye--round workers aged 16 ye-s and over) . As Fi~re 1

indicates, relative wage gatis were experienced both by black women and white

women in the 19S0s. However, the wage gap between black women and men began

to narrow several decade= ago and it has been smaller tha the gap between

white women and men since the 1960s.

The failure of the overall wage gap to narrow during the 1950-1980

period has been something of a puzzle. The labor force participation of women

had escalated over the entire post World War II period, the women, 5 movement

had blossomed, and barriers to women, s entry into many professions and

occupations appeared to have eroded.. Yet, overall women, e relative earnings

did not rise through the 1960s and 1970s.

Explanations for the apparent paradox have pointed out that during the

poet War period of rapid increases in the proportion of women who work, the

experience level and other work related attrtiutes of the average employed
s.—
Duncan, 1979) . The failure of the wage gap to narrow before 1980, therefore,

can be partly explained by the failure of women, 5 lifethe work experience to

rise as new I*or force entrants lowered the work =perience of the av-age

working woman.

@ite -the.opposite phenomenon my underlie the increase in women”s

relative earnings in the 1980s. Indeed, one explanation for this recent

development is that there ha9 been an intercohort increase in the continuity

of women, s ldor force participation resulttig in a greater accumulation of

work experience. The fact that the recent gains in women, s relative wages

have been larger mong younger women suggests that intercohort trends in human

capital ac~isition are important and that more recent cohorts of women have

gained relative to men in terms of marketable skills.

Figure 2 illustrates lifetime patterns of labor force participation for

successive cohorts of women born between 19.26-30 and 1961-65. These cohorts

roughly correspond to the panels of women included in the National

Longitudinal Surveys which -e the focus of this study. For each cohofi the

figure shows the change in lsbor force participation rates at different ages

in the life cycle. Two observations stand out. One is that there has been a

large rise in participation from one cohort to the next at all stages of the

life cycle. Second, the shape of the cohort profiles have changed. Wong

earlier birth cohorts, participation rates decline between ages 20 to 24 md

25-29, ref letting lower levels of lsbor force activity during ages when young

children are present. However, the cohort profiles then rise, part icularly

between ages 30 to 34 and 45 to 49- Thus , the labor force participation rate

of the cohort born 1941-1945 was 45 percent at ages 25 to 29 but rose to 74

percent when they reached ages 45 to 49.

3
Figure 2

Cohort Participation Rates

PatiiciDation Rate

80

75

70

65

60

55

50

45

40

35

30

20–24 25–29 30-34 35–39 40-44 45–49 50–54 55–59 60–64

Age

— 1926-30 + ~g31-35 + 1936-40 + lg41–45

+ 1946-50 + Igsl-ss & lg56_60 + 1961-65

1,

,,
men the profile line rises steeply, as it does for the cohort born

1941-45 it is evident that a large proportion of those in the I*or force at

ages 45 to 49 could not have worked continuously over much of theti adult

years. By contrast, the cohotis born 1951-55 and thereafter, have much

flatter cohort profiles--- Their -l*or force participation is initially high at “–

ages 20 to 24 and continues to rise without emeriencing the characteristic

dip or the steep rebound of the earlier cohorts. The flatter profiles of

these recent cohorts, cofiined with theti high levels of participation hint

that a l-ger proportion of women currently in their thirties have accumulated

more years of work experience than was the case mong earlier cohort#. since

the younger cohorts have yet to be obse~ed over the life-cycle, the extent to

which theti participation will eventually decline or will co-ntinue to rise

throughout the life-cycle remains to be seen.

The fact that the recent gains in women, s relative wages have been

largest =ong younger women, and decline systematically with age, suggests

that intercohort trends in human capital ac~isition are important and that

more recent cohorts of women have gained relative to men in terns of

1. markettile skills.

It is important to recognize that changes in accumulated work experience

cannot be constructed from tbe standard crose-sectional data. Because women

are heterogeneous with respect to lifet be work experience, longitudinal or

retrospective data on life-cycle experience are crucial for studying issues

1

Femle-male hourly earnings ratios mong white full-the workers have

changes as follows, by age, from 1977 to 1988: ages 25-34, from 69.4 to SO. 3

percent; ages 35-44, from 56.2 to 66-9 percent; ages 45-54, from 54 to 62. S

percent; ages 55-64, 57. S to 60.8 percent. (U. S. Bureau of the Census, Current

Population Survey, March Supplements Public Use Tapes ).

5
related to women, e labor supply, human capital fomat ion, and earnings. This

research utilizes data from the three continuing panels of the National

Longitudinal Surveys (NLS ) -- the mature women, the young women, and the youth

cohort -- to meaeure accumulated years of work exwrience and to -mine

changee in life-cycle work patterns across successive cohorts of women born

between 1923 and 1964.

In this report, we provide detailed descriptive analysis of how marital

and fertility patterns, schooling attaiwent, labor force pa*icipation, and

work attactient have changed from cohort to cohort. We esttiate the factors

associated with entq into and exit from the labor force for a given cohort

and consider how the responses to theee factors compare across cohorts. We

also analyze the determinants of lifettie ltior force participation and the

wages.

We addres5 the following broad

1. How have successive cohorts of

accumulation of work-related skills?

~estions:

women changed with respect to their

In particul=, hm have life-cycle

patterng of labor force participation changed? -d what have been the

intercohort changes in schooling levels and in career orientation?

2. What are the factors associated with entry and exit from the labor force

for a given cohort and how do the responses to these factore compare acrosa

cohort=? Factors potentially influencing the duration of ltior force spells

include school ing, birth=, changes in marital etatus, and changes in

market conditions.

3. How have returns to work experience, echooling and other human

investments changed between successive cohorts of women?

The following section descrties the data in greater detail and

6

labor

capital

by
comparing change= across cohorts in labor force participation, schooling,

marriage and fertility, provides a background for our empirical analysis of

the dete~inants of these ch=ges. The third and fourth sections focus on the

estimation of economic models of lifetime work decisions, with 5ection thee

describing the xesults -for. a dynmic work spell model, and section four

repo*ing the results of regressions for the proportion of possible years

worked. The fifth section provides estimates of wage models to asc=tain the

extent to which the underlying intercohort chmges in accwulation of huan

capital have influenced wages.

7
A. Background

In this section we sumarize our findings on

women ●s patterns of labor force patiicipation at a

intercoho* changes in

mment in ttie and over the

life cycle. .The ba5ic- economic fimework for ssalyzing wmen, s labor supply

derives from the fmily, a allocation of its mtiers time mong market work,

home work, and leisure. 2 The extent of market work de~nds on the expected

remuneration from market work relative to the “mhadow wage” fra home

production. The theory, therefore, predicts that economic gro~h would

increase women, s participation in the market provided that the substitution

effect of rising relative market wages dominaten the income effect of rising

fmily income on leisure (and the demand for home produced goods) . Evidence

on the dominance of the eubetitution effect has been found in a nuder of

croee-eectional studies, and sme the series studies , using U.S. data as well

as data from other countries (e.g. , Mincer, 1962; Cain, 1966; Hill, 1983;

O, Neill, 1981, and the articlee in Layard and Mincer, 1985) .3

It is unlikely that BO fundamental a change as the shift of women’ # work

activity from the home to the market would be a simple story of response to

rising wage levels; and it is not. Changes in the l~or force participation

of women are closely intertwined with cbangee in fertility and marital

stability, and it has proven difficult to separate cause and ef feet. Some

decline in fertility may have been exogenoue (for exmple, due to developments

in contraceptives) , but to a large extent fertility must surely be a decision

2

The pioneering work in thi5 area is that of Mincer (1962) .

3See also Kil lingsworth (19S3 ) for a comprehensive survey of mpirical

results for female labor supply. .

8
joint ly detemined with l~or force pafiicipat ion. The draatic increase in

the divorce rate in the United States also may have some exogenous cmponent

associated with 1iberalization in divorce laws. However, maritil inst *ility

is also likely to bcrease as a result of women, s rising l~or force

participation (which reduces the gain to marriage) ; and lsbor force

participation may in turn increase in response to ristig mrital instability

(and concomitant uncertainty regarding income) .

We therefore exmine intercohort changes in tipofi-t v=i~les that are

associated with labor .force participation -- schooling, marital status, and

fertility. Our analysis is based on three uni~e panel surveys. The

following section descrfies these data.

B. Description of the Data

The data for this analysis have been drawn from two panels of the

Nat ional Longitudinal Suneys of LabOr Market Experience (NLS ) -- the mature

women and the young women -- and from the panel of y“oung women in the National

Longitudinal Survey of Youth (NLSY ).

The NLS panel of mature women were born in the ye=s 1923 to 1937 and

were first surveyed in 1967, when they were ages 30 to 44. Personal and

telephone interviews were conducted at .re.Wlar Lntervds over the years (most

recently in 19SS) . The NLS young women, born 1944-53 were intemiewed

initially in 196S when they were 14 to 24 years of age. Of the initial saple

of 5, 0s3 mature ””wom”en,an estimated 3,346 remined in the smple in 1986.

Wong young women, 3,720 of the original 5,159 remained by 1985. The smple

of NLSY women nutiers 6,282. This panel was born in 1959 to 1965 and was

first interviewed in 1979 at ages 14 to 21.

The NLS panels provide a superior source of data fOr this analysis since

9
the longitudinal nature of the survey emits direct obsemations on work

ex~rience, earning5, and other related vari~les. Unfortunately, the sumeys

of mature women and young women began skipping yeare in the 19706, so that a

full se~ence of annual obsenations on all vari~les is not avail~le.

However, through the use of retrospective West ions, it has been Wssible to

complete much information for the missing years on work ex~rience, fehility,

and other important variables. tir methodology for accomplishing this will be

described in detail below.

For thi5 analysis, we divide the s~ples into five-year age cohorts and

view these cohorts over the. ~tiining these groups yields seven cohotis

observed at five-year intervals, as outlined in Tale 1. As ~dicated in thi5

table, the NLS Mature Women are observed in 1967,

1968, 1973, 197S, and 19S3 for the Young Women) .

pivotal years were taken using detailed in-person

1972, 1977, and 19S2 (and

The sumeys during these

interviews, and they

con5e~ently yield greater detail regarding demographic characteristics.

Moreover, west ions for these years often gleaned retrospect ive information

that can be cotiined with the panel data to create a complete the serie= for

important variables.

While these surveys include detailed retrospect ive

estimttig characteristics such as schooling, fertility,

(inter alia ), surveys for the mature women, young women,

components for

and marital status

and ~SY differ

markedly in the Wality of information available regarding years of work

experience.

In the initial survey ~estionnaire for the mature wmen (in 1967),

respondent were asked

schooling during which

to report the ntier of years since cmpleting

they had worked at least six months. For subse~ent

10
Table 1

NLS and NLSY Cohorts by Age, Survey Year and Cohort Nmber

Data Source

As of Age Mature Women Young Women NLSY

15 to 19 1968 (5)

1979 (7)

20 to 24 1968 (4)

1973 (5)

1982 (6)

25 to 29 19.73 (4)

1978 (5)

1987 (6)*

30 to 34 1967 (3)

1978 (4)

1983 (5)

35 to 39 1967 (2)

1972 (3)

1983 (4)

40 to 44 1967 (1)

1972 (2)

1977 (3)

45 to 49 1972 (1)

1977 (2)

1982 (3)

50 to 54 1977 (1)

1982 (2)

*NLSY cohorts 6 and 7 overlap.

11
years, we define a “work year. as one in which the respondent worked 26 weeks

or more (or at least half of the pos8ible weeks if the ,,weeks worked,, west ion

pertains to more than 52 weeks) . The sum of retrospective years and observed

years worked yields the cumulative years of experience. This measure, defined

as years since school completion, can be constructed for both the mature women

and the NLS young women. However, both surveys skipped two years during the

1970s for which the NLS failed to obtain weeks worked. The NLS young womenss

survey in 1978 included a retrospective pest ion asking how many of the past

five years had the respondent worked at least six months. For the young

women, then, we c- infer for most respondents whether or not the two missing

years were work years by comparing the response to this retrospective question

to the prospective information combined with all emplo~ent inf ormat ion

available (especially tenure and emplo~ent history details) . Unfortunately,

the detailed 1977 survey of the NLS mature women failed to include a similar

retrospective ‘,past five years,, vest ion. The available information on items

such as tenure and job history rosters provided complete coverage for only a

port ion of the sample. Consequent ly, for the mature women, we estimate the

nutier of years worked during the five-year interval 1973 to 1977 by

evaluating the proportion of the three known yeara worked (i.e. , 0, 1/3, 2/3,

or 1 ) and assigning that proportion to the remaining two years.. The computer

progrms used to generate these data are available from the authors.

The women from the NLSY are observed annually in the panel - A

retrospective question fills in years worked si.nc.eage 18 for tae older

metiers of the smple. Since the NLSY were not asked years worked since

school completion, we calculate for them the nutier of years since age 18

during which they worked at least 2.6 weeks. Unfortunately, we” can construct a

12
comparable measure for only one other age cohort, =S young women who were 15

to 19 in 1968 (for whom 1967 data are reported) . Because the year left school

is not fixed and many women retun to 6chool at a later the (which is

increasingly 80) , the measure of years worked since age 1S is likely to be

more accurately and consistently reported acroas individuals and cohorts than

the more sub ject ive measure of years worked since leaving school.

c.

1.

we

Descriptive Malysis

Wor ~

Participation in labor market activity can be described in several waye.

begin by examining labor force participation ratea during the ❑urvey week,

which are the rates traditionally used by the Bureau of L*or Statistics to

measure labor market act ivity. The labor force participation rate shows the

percentage of women in the population who are either employed or unemployed

(as oppo5ed to those who are out of the labor force and are not seeking work) .

Table 2 illustrates these survey week part icipat ion rates by five-year

age group, race and survey year. When we compare participation rates of a

given age group in different years -- e.g. the group ages 30-34 in 196?, 1978,

and 19S3 -- we are making an intercohort comparison since we are comparing the

rate of cohorts born at different times and reaching the designated age in the

years specified. 4 Wong white women, participation ratea have grown steadily

over time at each age level. For exmple, mong white women 30 to 34, 44

percent were part icipants in 1967. Thi B rate increased to 61.4 ~rcent in

1978 and further to 71.2 percent in 19S3.

4

8y reading down the diagonal one can examine the change in labor force

participation rates for a cohort as it ages. For exmple, the cohort ages 30-

34 in 1967 was 35-39 in 1972, 40-44 in 1977, and so on.

13
Table 2

Sumey Week Participation Rates, Weightad

Sumey Year

Age

1967 1972 1977 1982 1987

1968 1973 1978 1983

1979

Black

15-19 32.6 44.7

20-24 61.9 60.1 65.4

25-29 63.2 64.0 66.1

30-34 62.3 67.2 75.2

35-39 69.2 61.8 76.7

40-44

45-49

50-54

NonBlack

15-19

20-24

25-29

30-34

35-39

40-44

45-49

50-54

67.8 61.9

66.0

37.7

58.7 65.8

56:1

44.0

47.6 53.7

51.0 56.1

57.1

69.5

64.9 67.8

63.9 63.8

55.2

73.2

67.6

61.4 71.2

73.2

62.2

61.2 67.3

58.4 59.4

67.2

Source: N= Sumeys of Mature Women, Young Women, and Youth.
The picture for black women differe. In the earliest period, black

women, s participation rates were in exce5s of 60 percent at agee 20 and OVer

and were, for the most part, considerably above the rates of white women.

However, during this twenty-year period, black women, s pa*icipation rates

actually. declined in the early 1970s and then increased, but more slowly than

white women,s. Since the 19706, white women, a participation has been well

above black women, e at younger ages (15 to 24) when the higher fertility of

black women is a factor. At ages above 25, participation rates no longer

differ between black and white women to any s Ignif icant degree.

This measure of participation correspond=. to activity reported within

one week. If there is considerable labor force turnover, the survey wek

participation rate can underestimate the proportion of women who work at some

point during a year, but will overestimate the proportion working a full year.

Our interest here, however, is participation over the life cycle. We first

estimate lifetime participation in terms of the proprtion of years worked

since leaving school, defined as the nutier of years during which the

respondent works 26 or more weeks divided by the total nutier of years mince

being enrolled full-the in school. Tables 3 and 4 present such lifetime

measures first for all women, and then for the group of women who were

employed in the survey week.

Mong all white women, the proportion of years worked haa increaaed

syetemat ically, with rises corresponding to those in the survey week rates.

In fact, the survey week part icipat ion rates are ~ite similar to the lifettie

.15
Tale 3

Propotiion of Years Worked Since Leaving School, or Since Age 18,

All Women, Weighted

Since Leaving School Since Age 18

1967 1972 1977 1982

1968 1973 1978 1983 1978 1987

Age 

Black

25-29

30-34 0.556

35-39 0.560

40-44 0.599

45-49

50-54

NonBlack

25-29

30-34 0.463

35-39 0.453

40-44 0.454

45-49

50-54

0.463 0.564

0.557

0.550

0.587 0.579

0.658 0.618

0.618

0.523 0.663

0.559

0.466

0.462 0.494

0..461 0.488

0.476

0.486 0.516

0.574

0.577

0.603

0.621

0.621

0.568

0.519

0.506

0.583 0.673

Source: NLS surveys of Mature women, Young Women, and youth.
Table 4

Proportion of Years Worked Since Leaving School, or Since Age 18,

Employed Women, Weighted

Since Leaving School Since Age 18

1967 1972 1977 1982 1978

1968

1987

1973 1978 1983

Age

Black

25-29

30-34

35-39

40-44

45-49

50-54

NonBlack

25-29

30-34

35-39

40-44

45-49

50-54

0.626

0.672

0.643 0.670

0.730 0.685

0.723

0.699

0.645

0.610 0.612

0.594 0.600

.0.576

0.741

0.718

0.698

0.706

0.748

0.822

0.730

0.638

0.622

0.612

0.640 0.634

0.732

0.704

0.738.

0.711

0.703 0.753

0.755

0.693

0.651

0.635

Source: NLS Suweys of Mature Women, Young Women, and Youth.
meaaurea, although they diverge somewhat in recent yeas=.

5 For exmple, the

survey week participation rate for white wmen 35 to 39 was 47.6 pccent in

1967 and the lifetime rate for the s-e group was then 45.3 percent. The

lifetime rate has increased more slowly than the survey week rate, ri5ing to

56.8 percent for women 35 to. 39 years old in 19a3, while the corresponding

part icipation rate was 73.2 percent. Wong black women, lifetime

participation rates have changed in ways stiilar to the survey week rate:

falling alight lY mong the older groups and increasing slightly mong the

younger groups.

Table 4 presents these lifetime participation rates for the skgroup of

women who were employed during the survey week. If women were perfectly

homogeneous so that employed women had the same prior work experience as thoee

out of the labor force the rate for the employed would be the sme as the rate

for all women. However, this is not the case. Across all race and age

group5, the rates for employed women exceed those for all women, implying that

women who are current ly working are much more 1ikely to have been working (26

weeks or more) in prior years. For example, current ly employed white women

ages 30 to 34 in 1983 had worked 75.5 percent of all wseible years since

completing school, while the average for all women wa8 62.1 percent. These

rates have increased mong all white women, though the ef feet is largest at

younger ages, and among younger black women. This tiplies that the average

working woman in the late 1970s and early 1980s possessed higher levels of

5

The lifetime part icipat ion rate for all women (employed and nonemployed ) would be e~ivalent to the average. of the survey week part icipat ion

rates in each year over the cohort, e year5 since leaving school if the

lifetime rate were defined as the proportion of years worked one week or more.

our estimate is more restrictive since it counts a year of work if 26 or more

weeks were worked during the year.

18
prior work

noteworthy

priOE work

n=rowing.

experience thm her counterpart in the last 1960s. It ia also

that at ages 40 and over black working women have considerdly

experience than white women although that difference has been

more

We consider also the dist~ution of the proportion of years worked,

displayed in T*les 5 and 6 for black and white women, respectively.

Considering black women at ages 40 and older, ricing proportions have wortid

more than half of all possible years since completing schooling, although the

proportion of women working all possible years has fallen -ong these groups.

For ex-pie, in 1967, 13.3 percent of all black women 40 to 44 had worked each

year since completing school. This share fell to 6.4 percent by 1977. tiong

the younger groups of black women, there appears to be greater heterogeneity,

and this divers ity is increasing somewhat - For exaple, while the proportion

of black women 30 to 34 who worked some (but not all) years remained stale,

the proportion working all years u from 9.3 percent in 1967 to 11.4 percent

in 1983. Also, the proportion working no years rose from 6 iO percent to 8.1

percent during the s-e period.

Table 6 indicates that the patterns in these proportions for white women

are reasonably consistent, with a rising proportion of women at all ages

working more than half of all possible years, and generally, falling

proportions of women who have never worked. It is interesting to note

especially among ‘younger black women, there are higher proportions who

never worked than among white women.

2. -ulative Years of Work E ~rience

that ,

have

We turn to consider the effect that the dr-tic increases in labor

19
r,

Table 5

Percent Distribution of Black Women by Proportion of Years Worked

Since Maving School Since Age 18

1967 1972 1977 1982

1968 1973 1978 1983

Age

1978 1987

25-29

.01:.49

.50-.99

1

30-34

0

.01-.49

.50-.99

1

35-39

.01:.49

.50-.99

1

3:::

52.6

9.3

3:::

48.3

9.9

40-44

0

.01-.49 3::+

.50-.99 48.8

1

45-49

0

.01-.49

.50-.99

1

50-54

0

.01-.49

.50-.99

1

13.3

24.7

26.0

38.2

11.1

3.2

35.4

55.7

5.8

2.3

35.3

55.6

6.8

1.5

.32.5

58.4

7.7

14.0

26.5

37.4

22.1

13.0

26.0

48.6

12.4

1.9

35.4

56.2

6.4

1.2

32.5

59.1

7.2

0.7

31.3

60.0

8.0

14.4 13.4

33.1 30.9

47.0 45.9

5.6 9.8

2::+

51.8

11.4

6.8

31.4

54.5

7.4

1.9

32.0

61.2

4.9

2;:;

61.5

8.2

Source: NW Surveys of Mature Women, Young Women, and Youth.
Table 6

Percent Distribution of Nonblack Women by Proportion of Years Worked

Since Leaving School Since Age 18

1967 1972 1977 198’2

.

1968 1973

Age

1978 1983 1978 1987

25-29

0

.01-.49

.50-.99

1

30-34

0

.01-.49

.50-.99

1

35-39

0

.01-.49

.50-.99

1

40-44

.01:.49

.50-.99

1

45-49

0

.01-.49

.50-.99

1

50-54

.01:.49

.50-.99

1

5.2

52.7

31.8

-.10.3

5:::

30.6

9.6

52::

33.8

6.6

17.5

.25.4

.40.0

17.1

3.0

53.0

37.2

6.8

3.0

55”.3

35.9

5.8

5+::

37.5

3.8

6.0

22.0

41.3

30.6

6.9

33.6

46.5

13.0

1.4

51.1

40.7

6.8

1.5

53.0

41.0

4.6

5:::

40.7

3.6

4.5

2;:; 21.1

54.7 51.2

““1O-8 23.2

2;::

56.6

12.3

4.5

35.8

51.2

8.5

~:’* :

46.7

47.1 ‘

5.8

4:::

47.2

3.7

Source: NLS Surveys of Mature Women, Young Women, and youth.
force part icipat ion have had on cumulative years of work exprience. Table 7

displays for all women the average emulative year5 since leaving school

during which the respondents worked 26 weeke or more by cohort and race.

mong all black women the average level of experience has either fallen or

r-ained steady through this period. For exmple, women 35 to 39 possesmed,

on average, 11..2 years of experience in 1967 and only 9.7 in 1983. A1l white

women, however, have gained experience, with increases of roughly one year on

average =ong all gr0up5. And while older black wmen exhibit high= levels

of experience on average, years of work experience mong younger white mmen

has begun to exceed that of their black counterparts.

T*le 8 restricts the s-pie to women who were employed in the su~ey

week and considers bow levels of cumulative experience wong employed women

haB changed. Levels of work experience mong employed women clearly exceed

the popu lat ion average, and experience gains have been modest mong employed

white women, with declines experienced by some groups. The patterns mong

current ly employed black women reflect the changes in the overall population.

In 1982 (or 1983) , employed black women in most age groups possess fewer years

of experience than did similar women in earlier ye-5.

Table 9 displays the cumulative years of experience since age 18, which

we calculate for the NLSY and for

We also present data for men from

average yearO of experience since

the youngest group of the NLS young waen.

the NLSY. ~0n9 black women 25 to 29, the

age 18 increased for the entire population

by one-tenth of one year between 1978 and 1983, from 4.4 to 4.5, but actually

fell for the average employed black woman. For white women, average

experience increased both for the average employed woman and the average woman

overall, although by a smaller -ount for employed women.

22
Table 7

~ulative Years of Eqerience Since School Completion,

All Womenr Weighted

Survey Year

1967 1972 1977* 1982*

1968 1973

Aqe

197s 1983

1979

Black

25-29 3.6 4.0

30-34 8.6 6.4 7.3

35-39 11.2 11.1 9.7

40-44 15.0 14.5 14.4

45-49 18.2 18.2 18.1

50-54 21.5 21.5

NonBlack

25-29 3.7 4.4

30-34 6.6 6.4 7.7

35-39 8.8 9.0 9.5

40-44 11.2 11.3 12.0

45-49 13.7 14.4 15.1

50-54 16-5 17.4

*Mature womenrs years of e~erience calculated usinq ratio

metiod.

Source: NE Surveys of Mature Women, Younq Women and Youth.
Tale 8

~ulative Years of E~erience Since S&OOl Completion,

Employed Women, Weighted

Survey Year

1967 1972 1977* ig82*

1968 1973 1978 1983

Age 1979

Black

25-29

30-34

35-39

40-44

45-49

50-54

NonBlack

25-29

30-34

35-39

40-44

45-49

50-54

4.9

10.2

12.6 13.2

18.1 16.6

21.7

4.7

9.2

11.9 11.9.

14.6 14.6

17.0

5.1

8.1

17.1

20.6

25.8

5.2

8.2

15.4

18.2

21.0

9.3

11.7

21.9

24.4

9.3

.11.5

18.9

21.9

*Mature women?s years of eqerience calculated using ratio

method.

Source: NM Surveys of Mature Women, Young Women, and Youti.
Table 9

Cumulative Years of E~erience Since Age 18, by Employment Status

(Weighted)

Women Men

Age

Black

25-29

All

Employed

Out of the

30-34

All

Employed

Out of the

NonBlack

25-29

All

Employed

Out of the

30-34

All

Employed

Out of the

1978 1983 1987 1987

4.4 4.5 5.8

5.7 5.5 6.2

Labor Force 2.2 2.6 4.0

7.7

9.9

Labor Force 3.5

5.2

Labor Force ::;

8.5

10.3

Labor Force 5.7

5.9

6.5

4.5

6.9.

7.2

5.4

Source: NM Surveys of Mature Women, Young Women, and Youth.
This comparison of years of e~erience between all women and currently

employed women clearly indicates that while l~or force participation has been

rising rapidly and the cumulative years of work experience have increased for

the population of ~ women, experience for the average ~lovd woman has

undergone slower -grotih, and in some cases has even declined.

Yet some of these apparent declines in work =perience since

(and as of a given age) my reflect the rising lwels of education

schooling

attained by

these groups of women, and conse~ently, fewer years within which to work at

any fixed age. We turn now to consider changes in schooling attaiment.

3. Yeas of Schooltiq

As Table 10 indicates, level of women, s schooling has increased

considerably during this period- Rising levels of educational attaiment have

been achieved by black and white women in all. age groups, with gains as large

as two years for some groups. Perhaps more notable thm the overall grotih is

the educational gains that black women have made relative to white women of

similar ages. The schooling difference has narrowed from 1.0 to 1.5 years in

1967-68 to 0.2 to 0.9 years among the most recent groups of women under 35.

Table 11 reports schooling attainment levels for currently employed

women. Working women are, on average, better educated than in the population

at large, with one-thtid to one-half years more schooling attained than the

average for all women.

4. Chanaes in Marital stat”= and Fe*ility

Rising investments in human capital ad l~or force attactient can

expected to affect (and be influenced by) marital status -d fertility.

Table 12 exhibits the proportion of the cohort that hs never mrried by

26

be

given
Table 10

Years of Schooling Completed by All Women, Weighted

Suwey Year

1967 1972 1977 1982 1987

1968 1973 1978 1983

Age 1979

Black

15-19

20-24

25-29

30-34

35-39

40-44

45-49

50-54

NonBlack

15-19

20-24

25-29

30-34

35-39

40-44

45-49

50-54

9.95

11.37

10.27

10.29

9.77

10.48

12.46

11.79

11.60

11.17

11.65

11.57

10.54

10.44

10.13

12.63

12.76

12.08

11.88

11.37

9.56

12.15

11.67

11.12

10.91

10.52

9.70

13.11

12.99

12.20

12.05

11.53

12.35

12..38

11.69

11.07

10.72

12.53

13.27

13.21

12.32

12.16

12.72

13.10

Source: NW Su=eys of Mature Women, Young Women, and Youth.
Table 11

Years of Schooling Completed by Employed Women, Weighted

Sumey Year

1967 1972 1977 1982 1987

1968 1973 1978 -.83

Age 1979

Black

15-19

20-24

25-29

30-34

35-39

40-44

45-49

50-54

NonBlack

15-19

20-24

25-29

30-34

35-39

40-44

45-49

50-54

10.42 10.70

1X. 89. 11.92 12.81

12.11 12.72 13.21

10.18 12.41 12.99

10.89 11.08 12.38

10.38 11.12 11.62

10.57 11.60 11.51

11.27 11.38

.m..34 10.25

12.88

12.64 12.71

13.31 13.54

11.83 13.30 =.54

11.57 12.22 13.53

11.28 11.99 12.50

11.60 12.42 U.68

11.96 12.46

13..42

Source: NM SuNeys of Mature Women, Young Womenr and Youth.
Table 12

Propotiion of Cohoti Never Married, Weighted

Survey Year

1967” 1972 1977 1982 1987

1968 1973 1978

Age

1983

1979

Black

15-19 0.92 .0.98

20-24 0.51 0.5’7 0.77

25-29 0.25 0.39 0.53

30-34 0.12 0.21 0.29

35-39 0.04 0.09 0.18

40-44 0.07 0.03 0.08

45-49 0.05 0.02 0.09

50-54 0.05 0.02

NonBlack

15-19 0.94 0.95

20-24 0.45 0.44 0.59

25-29 0.12 0.18 ‘0.28

30-34 0.05 0.08 0.11

35-39 0.05 0.04 0.07

40-44 0.04 0.04 0.03

45-49 0.03 0.04 0.03

50-54 0.03 0.03

Source: N= Surveys of Mature Women, Young Women, and Youth.
ages. At all ages younger than 40, white mmen have experienced declining

marriage rates. In 1967, only 5 percent of white women had never m~ried by

age 30 to 34. This proportion has more than doubled (to 11 percent) in 1983.

While 12 percent of women 25 to 29 had never married in 1973, 2a percent

remained never married as of. this age in 19a7. And mong black women, the

proportion who never married rose even more sharply during this period, e. g.,

from 25 percent to 53 percent mong black women 25 to 29 and from 12 percent

to 29 percent mong women 30 to 34.

hong black and white women under 40, the proportion of women who

remained childless also rose during this period, as illustrated in Tale 13.

While only 7.5 percent of black women 35 to 39 had no children in 1967, 14.7

percent had no children by these ages in 1983. Comparable declines in

childbearing were experienced by white women. And while working women are

more 1 ikely than average to be childless, these proportions have also risen,

as illustrated in Table 14. An increase in the propotiion of women who have

no children at a given age can signal either delayed childbearing or reduced

total fertility, or both. Tables 15 and 16 illustrate the nutiers of chiltien

ever born to al 1 women and employed women, respectively. These data indicate

striking reductions in total fertility for women younger than 40. Average

declines in children born are highest mong black women. For ex~le, by ages

35 to 39, women in 1967 had borne 4.6 children yet only 2.6 in 1983. Black

women 30 to 34 had already given birth to almost 4 children in 1967, and only

to about 2 in 1983. Throughout thie period, working women have borne fewer

children than average (data for them are depicted in Table 16) . However,

difference between the nuder of children ever borne by working women and all

women has narrowed recent ly, as women with children have increased their work

30
Table 13

Percentage of Women witi No Children By Age and Race, All Women,

Weighted

Sumey Year

1967

1968

1972

1973

1977

1978

1982

1983

1987

Age 1979

Black

20-24 0.433 0.504

25-29 0.210 0.204 0.303

30-34 0.058 0.160 0.134

35-39 0.075” 0.053 0.147

40-44 0.182 0.064 0.053

45-49

50-54

NonBlack

20-24

25-29

30-34

35=39

40-44

45-49

50-54

0.175 0.064

0.179

0.701

0.327 0.429

0.116 0.201

0.102 0.093.

0.117 0.094 0.092

0.114 0.093

0.114

0.059

0.064

0.737

0.483

0.267

0.156

0..086

0.090

Source: NLS Suweys of Mature Women, Young Womenr and Youti.
Tale 14

Percentage of Employed Women wifi NO Children, Weighted

Sumey Year

1967 1972 1977 1982 1987

1968 ‘1973

Age

1978 1983

1979

Black

20-24 0.446 0.646

25-29 0.277 0.280 0.384

30-34 0.078 0.189 0.163

35-39 0.087 0.075 0.144

40-44 0.222. 0.083 0.058

45-49 0.179 0.086 ‘0.077

50-54 0.225 0.083

NonBlack

20-24 0.824 0.847

25-29 0.539 0.610 0.614

30-34 0.241 0.320 0.379

35-39 0.179 0.139 0.209

40-44 0.178 0.129 0.125

45-49 0.142 0.109 0.094

50-54 0.134 0.102

Source: N= Sumeys of Mature Women, Young Womenr and You#.
Tale 15

N~er of Children Ever Born, By Age and Race, All ~omen,

Weighted

Survey Year

1967 1972 1977 1982 1987

1968 1973 1978 1983

Age 1979

Black

20-24

25-29

30-34

35-39

40-44

45-49

50-54

NonBlack

20-24

25-29

30-34

35-39

40-44

45-49

50-54

0.998

2.318

3.990

4.637 4.302

3.279 4.798

3.313

0.423

1.269

2.753

2.928 2.990

2.933 3.036

2.962

1.672

2.490

4.276

4.736

3.243

1.017

1.791

3.050

3.043

2.967

0.766

2.076

2.602

4.439

4.927

0.370

1.543

2.003

3.087

3.069

1.369

0.928

Source: N= Sumeys of Mature Women, Young Women, and Youth.

.
Tale 16

Ntier of Children Ever Born, By Age and Race.

~ployed Women, Weighted

Suwey Year

1967 1’972 1977 “1982 “’-”-1987

1968 1973 1978 1983

Age 1979

Black

20-24

25-29

30-34

35-39

40-44

45-49

50-54

NonBlack

20-24

25-29

30-34

35-39

40-44

45-49

50-54

0.863

1.690

3.342

4.205 3.832

2.604 4.239

2.860

0.240

0.791

2.188

2.449 2.558

2.421 2.718

2.646

1.292

2.227

3.792

4.024

2.680

0.625

1.379

2.769

2.899

2..673

0.500

1...085

1.725

2.464

3.863

4.343

0.208

0.625

1.171

1.760

2.879

2.950

Source: NM Suweys of Mature Women, Young Women, and Youti.

.
participation.

D. S~

Our comparison of human capital and daographic characteri@tic5 acros6

these seven cohorts of women has illuminated the drmatic changes in labor

market experience and-its correlates. - L*or -force participation, whether

measured at a point in ttie or over the lifetime has increased markedly for

white women, with black women experiencing slight increases or declines. For

working and nonworking women cotiined, the cumulative years during which an

individual has worked at least sti months ha6 rieen, although the average

level of experience of employed women has grown more S1OW1Y or has actually

declined. mile some of this slower grotih can be attributed to the lower

levels of experience held by new entranta and the rapid increase in the nu@er

of new entrants (as signal led by the rise in survey week participation ratea ),

rising levels of schooling have also diminished the nutier of post-schooling

yeare within which women (at a fixed age) could have worked.

Along with rising levels of investment in education, these cohorts of

women have experienced draatic demographic changes. A larger proportion of

each cohort remains unmarried and more women continue to be childless.

Moreover, the nuder of children ever born mong these women has declined

sharply, with women in the earlier cohorts bearing three to four children and

more recent cohorts giving birth to two to three children.

35
III. DE~NANTS OF = DDWATION OF WOX AND NON-WO= SPEUS

We have obeerved drmatic changes in fertility, marital status, and

schooling, along with e~ally striking inter cohort dcreases. in work

attactient, whether measured by contemporaneous part icipat ion or lif et be

experience. ..-We emplay two methodologies to help eort out the influences of

demographic changes on women, s life-cycle labor supply behavior. In thi5

section we estimate, for NLS Young Women and the NLSY, a multiple spell hazard

rate model of exits from work and non-work spells. Unfortunately, the

re~irements of the multiple spel 1 model outstripped the data available from

the Mature Women, s smple. However, in our second approach we esttiate for

all cohorts the determinants of the proportion of the lifetime worked as of a

given age. These results are described in Section IV which follows.

A. Multiple S~ll Haz=d Rate Model

This research builds on recent work using longitudinal data to analyze

labor supply behavior and the impl icat ions of labor force patterns for the

6

wage gap. Notable mong them is Donohue (1987) who uses NLS data to esttiate

the duration of the first post-schooling job for smples of young men and

women from two four-year periods, 1968-1971 and 1979 -19S2, reflecting

different cohorts. His results indicate that for the more recent cohoti the

early labor force behavior of young women appears virtually identical to that

of young men.

Donohue reports that in the early period, young women appear to leave

their first jobs at considerably higher rates than do young men. However, in

6See also work on dynaic ltior supply, e.g. , Hechan and MaCurdy (1980)

and Flinn and Hectian (19S2, 19S3 ).

36
the later ~riod, the early l~or force behavior for young women appears

vifiually identical to that of young men. Especially, the distribution by job

tenure and occupation, and the behavioral estimate= of his haz-d rate model

differ little by gender. The closing of the “first-job tenure gap” appars

associated with narrowing the wage gap. - For his Smple, Donohue repofis that

the female-male wage ratio for white high school graduates of 77 ~rcent for

1968-1971 rises to 89 percent by 1979-82. Donohue hypothesizes that the

increasing similarity in behavior derives both from greater l~or force

attactient of young women as well as from increases in the age at marriage and

first birth.

Other recent etudies that should be noted are Felmlee (1984) who uses

the NLS panel of Young Women (1968-1973) and continuous-the modelling to

analyze the process by which young women leave emploment to become unemployed

or to exit the labor force. She separates labor force transitions out of

~PlOwent due tO Pregnancy and transitiOne made fOr other reasons and mong

tbe latter category, further separates voluntary from involuntary exitw.

Meitzen (1986) uses data from the Emplowent Opportunities Pilot Progrma

(EOPP ) Employers, Survey to estimate a continuous-time model of male and

femle witting behavior. The EOPP data, which were collected March-May 1980

include recently hired women with 2.5 or fewer years of tenure in the fire.

Meitzen reports that the possibility of Witting a job declines with tenure

for men and increases with tenure for women. However, his model includes only

one duration parameter, forcing a monotonic relationship between tentie and

the likelihood of Witting. Blank (1988) uses PSID data to estimate a

competing risks model for transitions into and out of both full-time and parttime work. She finds age, nutier of children, race, and education to be

37
~o*ant determinants of l&or force movements. This research illustrate~

the tiportance of treating female l~or force decisions within the context of

a dynmic model. A sfigle cross-section of data can yield little insight into

the heterogeneity ~ong women in their life-cycle patternn of work.

1. wthodolo~

tir theoretical model follows work by others on dynmic lsbor supply,

especially that of Hecban and MaCurdy (1980) and Flinn and HecMan (1982,

1983) .7 These models generalize one-period models of l~or force

part icipat ion in a straight fomard manner - Suppose that we define Wr (t) as

the marginal rate of substitution between goods and leisure if the woman is

not working and W (t ) as her market “age rate. Let I (t) be an index function

defined by: a

I (t) =W (t) -W, (t).

If I (t) z O_then. the womn chooses to work in the market and we set a work

dumy d (t) = 1. If I (t) < 0, she chooses not to work and d (t) = O. The

object of our model is to explain variation in the nuder of consecutive years

a woman is working. Similarly we would 1ike to explain the variation in

consecutive years not working.

Given the dynmic nature of female l~or supply and the availability of

event history information we use continuous time methods to model the

determinants of exit rates from work and entry rates into work. EstMtion of

7

See Killingsworth (1983) , Killingsworth and Hechan (1986) , and MaCurdy

(1985) for reviews of dynmic models and empirical results and Bee Hechn and

Singer (1986) for a brief outlke of a stiilar dyn-ic labor supply model.

8

This index is analogous to the one-period decision rule comon to the

labor force participation models of HeChan (1974, 1977) , and Cogan (1977) ,

=ong others.

38
transition rate (or hazard rate) models has become widespread in economics

with applications to a variety of econmic events including unemplopent

(Lancaster, 1979; Fli- and Hec*n, 1983), marriage and divorce (kdernon ~

& 1987; ~nken et al. 1981, fertility (Nman and McCulloch 1984; Hechan,

Hotz, and Walker, 1985) and welfare receipt (O,Neill et al., 1987).

~r model focuses on the exit (entrance) probability at year t,

conditional on having been h (out of) the labor force for t years. The NLS

data include both completed epella, for which the ttie in the ltior force is

measured, and censored epells, for which the end of the lsbor force SP1l is

not yet obeerved. MaxMum likelihood esttiation makee full use of the

information both for completed and censored work md non+ork spells. We use

information on all labor force spells for all women, which tiplies multiple

spells for sae women.

If we define the instantaneous unconditional prob~ility of exiting the

labor force at time t to be f“ (t ), where FM(t) is the corresponding emulative

density and l-FW (t ) the unconditional survivor prob~ility, then tbe

conditional probability of exiting the l~or force at the t given

pa*icipation up to that ttie -- called the hazard rate -- is given by:

h“ (t”) = fw (tW) / ( l-FM (t”) ) .

The transition rate from non-work to work hm can be defined in an analogoue

manner.

The expected duration of a wrk spell, e.g. , is then:

m

t

J exp (- j hw (u.) du ) dt

o 0

In order to study the determinants of the hazard rates acrose individual

39
women w have be~n with a general functional fom of the multiple spell

model. (See Yi, ~. (1987), Flinn ad Hechan (1982, 1983), Hechn and

Singer (1986) , and also Alison (1984) .) The general fom of the conditional

hazard for the transit ion out of work state j (= w, nw) for individual i can

be written as:

2

Ljk

hij (tij I Z, O)=exp{ yjo + Zi P j + E y jk (tfj - 1)/ kjk + Cij 0}

k=l

where the Z are explanatory variables that include both fixed and the-varying

variables and 6 measures individual unobserved heterogeneity. Our model has

specified the term capturing the ef feet of duration to be ~adratic, with Xj,

= 1 and Xj2 = 2. We initially specified a non-par-etric distribution to

allow for the effects of unobserved heterogeneity, however, the estimated

reeults differed little from those with no heterogeneity corrections,

therefore we present results for models with no heterogeneity controls.

2. ~Dec”i~ 11 Model

We analyze the extent to which the l~or force behavior of recent

cohorts (and its determinants) has actually changed by comparing the early

labor force experience of women who were between the ages of 15 and 19 in 1968

with those who were between the ages of 15 and 19 in 1979. We also consider

the cohofis ages 20 to .24 in 1968 and 20 to 24 in 1973. Eight-year s-pies

from the National Longitudinal Sumeys of Young Women and Youth fom the data

base for this analysis. For compar~ility, the 15 to 19 year old NLS Young

Women are followed from 1968 through 1975, while tbe NLS Youth include

obsemations from the period 1979 through 1986. The 20 to 24 year old groups

40
from the ~S Young Women are followed from 1968 through 1975 and from 1973 ‘

through 19S0.

Our objective is to explain variation in the nutier of consecutive ye~s

a wman is wrking (that is, the duration of a work spell) as -11 as

consecutive years not. working. .-Given the dynmic. nature of female ltior

supply and the avail tiility of event history information w use continuous

the methode to model the determinants of exits from work spelle as well as

from non-work spells.

The NLS data include both cmpleted epells, the duration of which iw

h-n, and gensored spells, for which the end of the labor force spell is not

yet ob5emed. Maximum likelihood estimation makes full use of the information

both for completed and censored work and non-work spells. We use information

on all spells for all women, which implies multiple spells for some women.

9

The analysia includes those persons who eventually leave the swple if we

observe at least three years data for them; their work and non-work spells are

treated as being right-censored.

Spell lengths are measured in years; if an individual reports herself to

be employed for. at least six months of a given year, that year i5 counted aa a

work 8pell year. Otherwise tbe year is defined as a non-work spell year.

10

9

See Yi, ~. (19S7 ), Flinn and Hectian (1982, 19S3 ), and Hectian and

Singer (1986) for description of the multiple--pen hazard rate model md

estimation.

10

The NLS Young Waen, s Smple began skipping yeara in the late 1970s so

a full seaence of annual observations is not available. However, through the

use of retrospective Vest ions, it is Pgsible to fill in important

infomt ion for the missing years. Given the nature of the retrospective

qeetiona, we define a work year aa one in which the respondent worked at

least six months to link the retrospective and prospective data.

Unfortunately this definition cotiines together the etates “unemplo~ent-

“out of the labor force” a5 ‘non-work. ”

41

and
The explanatory variables, described in Table 17, include both those

which are fixed for a given spell and those which vary with the a5 the SP1l

progresses. Fixed vari&les consist of years of experience, 11age, and ye~s

of schooling, each measured at the beginning of the spell. Time-varying

variables. include a dmy variable e~al to one. if the wman is enrolled in

school during the spell year, two the-varying residential dumies which

capture Southern and SMSA residence, and vectors of dichotomous marital status

and fertility varisbles, included to capture changes in household composition.

These variables are married to not mrried, not married to married, and

married to married. Women who remain umarried in a spell year define the

reference categoq for marital status. The fertility variables include first

birth; subse~ent birth; no births, but children younger than six present;

and, for the women 20 to 24, the nutier of children older than sfi. 12Women

who have no children are the reference fertflity group. The model includes

13

also spell duration and its s~are.

11Experience is measured as years since echooltig w- capleted for the

20 to 24 year olds and as years since age 18 for the 15 to 19 year olds.

12

For the 15 to 19 year olds, there was so little variation in the ntier

of chiltien older than 6 that the multiple spell models were not esth~le

when they included that varitile.

13Missing Su=ey years ruled out including the unemplo~ent rate in the

local l&or market as an additional explanatory vari~le.

42
Table 17

V~IABLE DEFINITIONS FOR WORK AND NON-WORK SPELL MODEL

DeDendent Variables

Work spells: Consecutive years in which respondent worked at

least six months

Non-work consecutive years in which respondent did not

spells: work at least six months

Em lanatory Variables

Fixed at beginning of spell:

EXPERIENCE equals cumulative years of work

experience

AGE -

GRADE highest level of schooling completed

Time-varying:

ENROLLED equals one if enrolled in school during

spell year

SO~H equals one if residing in Southern state

CITY CENTER equals one if in SMSA central city

MAR TO NOT W equals one if marital dissolution

occurs during spell year

NOT MAR TO M equals one if respondent marries

during spell year

W TO.NAR equale on if respondent remains married

during spell year

BIRTH:NO KIDS equals one if respondent has a first

birth during a spell year

BIRTH:KIDS equals one if respondent has a second

or higher order birth during a spell year

NO BIRTH:KIDS LT6 equals one if respondent has

children under age six, but no births during

a spell year

ALL KIDS GT6 equals the number of children older

than six if all children are over 6 in a

spell year

SCHOOL CHILD equals one if youngest child reaches

age 6 in a spell year
Given that labor force behavior may differ by race, models are esttiated

separately for non-black and black women.

14 Tale 18 describes the’dependent

variables by including the nutier and mean duration of censored and completed

mrk and non-work spelk. Comparing the 15 to, 19 year olds, the most striking

difference in spell characteristic is that the mean duration of censored work

epells increases by about one year, rising from 3.9 to 4.9 years (of a

potential eight) for non-black women and from 3.3 to 4.1 ye~s for black

women. For 15 to 19 year olds, the length of completed work spells is also

higher by one-half year for the more recent group. Cen50red non-work splls

have lengthened for the more recent group of women, with mean duration rising

about 6 months, except for Non-black 20 to 24 year olds, for “hem they have

shortened - The 20 to 24 year olds experience longer censored work spells than

does the younger age group, and these spell lengths dso increased mong the

more recent cohort.

Tables 19 and 20 provide somewhat more detail regarding the distrtiution

of spells by their duration, first for censored, then for completed spells.

Turning to Table 19, the proportion of all censored work spelSs that last the

entire eight-year period has increased for all age and race groups. For 15 to

19 year old non-black women, this proportion more than doubles from 9.8

percent to 24.0 percent. Tbe proportion of censored non-work

of eight-years duration also increases modestly over time for

spells that are

each age ad

74

To adjust for the oversampling of Hispanics in the NLS-Y, we dr~ a

random smple of all Hispanic women such that o- saple proportion

corresponds with the age and sex specific population proportion as reported in

the 1980 Census.

44
Table 18

Kean ~ration and Ntier of Censored and Completed Spells, by Age Cohort,

Race, and Time Period

Work Spells

Age and Race

Non-Work Spells

Censored Completed Censored Completed

1968-75 1979-86

15-19 to 23-27

Non-Black 3.89 4.94

591 1582

Black 3.27 4.08

230 563

1968-75 1973-80

20-24 to 28-32

Non-Black 4.85 5.35

676 569

Black 4.41 5.04

244 254

1968-75 1979-86

1.81 2.29

636 1273

1.42 1.92

251 480

1968-75 1973-80

2.16 2.25

S46 634

1.90 1.87

301 245

1968-75 1979-86 1968-75 1979-86

3.58 4.18

357 696

4.44 5.15

165 356

1968-75 1973-80

4.72 4.37

493 329

4.54 4,95

147 121

1.99 2.14

886 1866

2.23 2.60

389 823

1968-75 1973-80

2.02 1.86

900 611

2.10 1.99

362 288

Source: NU Suweys of Nature Women, Youg Wonen, and youth.
MK SP2LLS

15-19To23-27 20.24TO2S2-32

Um-niuk Bl#k Nm-Blmk Slffik

196s-n 1979-s6 WW-73 19m-& 1*-73 1973-W 196s-73 19n-m

W-W WELLS

15-19 TO 23-27 20-24 TO =32

Um-Bl~k Black Mm-Slwk BIUk

lW-75 1979-s6 lW-73 1979-U 196s-73 1973-M 196s-73 1973-W

1 Ycor 110 177 72 10” 126 m 52 33

Q.lu 0.112 0.313 0.1s3 O.lu 0.132 0.213

2 Yurs

0.130

39 Iw 13 87 a 49 11 23

O.M 0.116 0.037 0.155 Owl O.ow 0.W5 O.m

3 Ymrs 114 173 34 * M 56 44 27

0.193 0.109 0.235 0.151 0.127 O.~

b Yars

o. tm O.lM

106 170 a 39 70 37 24 23

0.179 0.107 O.lw O.lfi ‘O.1O4 0.063 O.ow O.m

3 YNm 76 167 26 ‘s8 52 -.60 18 21

O.la 0.16 0.113 0.103 0.121 0. lm

6 Years

0.074 0. lM

55 153 18 40 40 2s 26 22

0.093 ‘0.097 0.07s 0.071 0.039 0.049

7 Ywrs

0.115 0.M7

33 1s 13 51 46 26 20 11

0.O56 0.117 0.037 0.091 O.m 0.046 O.ow 0.043

a Y**rs 5s 360 9 60 19s m 47 &

O.wo 0.2W 0.039 0.142 0.293 0.418 0.193 0.331

Total

B-r d 591 15s3 230 5a 676 569 244 234

*11*

lW l=

0.303 0.267

M 30

O.lM 0.119

34 67

0.093 0.096

27 52

0.076 O.0~

‘% 49.

0.106 O.om

lb 41

0.039 0.039

13 29

O.w 0.042

74 179

0.207 0.237

357 6%

43

0.261

12

0.073

9

0.055

9.

0.035

14

O.ms

7

O.w

7

0.M2

67

0.406

163

39

0.166

32

0.090

37

O.lw

18

0;051

17”

O.w

12

0.034

9

O.m

162

0.435

93

0.193

57

0.t16

35

0.071

42

O.m

49

O.ow

40

O.ml

3s

0.077

137

0.27s

493

33 43

0.161 0.293

58 f4

0.17b O.~

36. 10

O.lw O.w

35. s

O.lM ‘“0.034

32 3

0.097 0.020

17 ‘ 11

0.032 0.073

23 11

0.07b 0.073

73 47

0.222 0.320

22

0.1s2

8

0.066

12

O.ow

14

0.116

13

0.107

3

0.023

6

0.030

43

0.353

121

smrm: NLS W- of Mtura W, V- W, d Ymth. ‘“”

_..
Ttile 20

Wtir d P~rtim of qletd Wrk d Mm-Wrk Xlls, W SP1l l~th

~K SPELLS M~-WK WELLS

15-19 TO 23-27 20-24 TO 2S-32 15-19 TO 23-27 20-24 TO 2S-32

Nm-Black Blak Mm-BIMk Blink Nm-Black Black Nm-Blwk Black

196s-73 1979-s6 lW-E 1979-66 lW.E 1973-60 1965-75 1973.s0 196s-73 19n-M lw-n 1979-66 1%-73 1973-M 196s-73 1973-W

411

0.565

146

0.201

72

0.099

34

0.074

24

0.033

17

0.023

4

0.003

n8

550

0.431

3M

0.240

167

0.131

131

0.103

63

0.M9

42

0.033

33

0.0=

12n

lW

0.701

50

0.185

17

0.063

8

0.030

5

0.018

1

0.004

0

O.wo

271

240

0.500

13s

O.m

49

0.102

25

0.032

f4

0.029

9

0.019

5

0.010

4s0

3W

0.4s2

193

0.233

103

0.127

62

0.073

50

O.ow

2s

0.034

9

0.011

W8

323

0.5W

90

0.142

87

0.137

63

0.099

n

0.046

30

0.W7

12

0.019

634

172

0.571

50

0.166

45

0.150

16

0.033

8

0.027

8

0.027

2

0.007

301

156

0.637

29

0.11s

24

O.ow

22

0.090

5

O.mo

4

0.016

5

0.020

245

447

0.435

221

0.21s

151

0.147

93

0.092

e

0.0s0

26

0.023

6

0.006

523

0.471

451

0.241

235

0.123

129

O.w

52

0.044

65

0.035

2s

0.015

166 337 U7

0.419 0.4W 0.%1

73 150 171

0.169 0.102 O.lm

55 116 93

0.124 0.141 0.106

43 .66 73

O.WY 0.0s0 0.W3

m 67 42

0.135 0.0s1 0.047

15 32 17

0.034 0.W3 0.019

10 35 13

0.023 0.U3 0.014

39s

0.653

69

0.113

52

0.W5

49

O.m

17

0.020

12

0.020

13

0.021

611

194

0.536

69

0.191

30

0.W3

24

0.W6

29

O.m

13

0.036

3

O.m

w

172

0.618

33

0.115

34

0.118

12

0.042

12

0.042

13

0.045

6.

0.021

m
race group except the non-black 20 to 24 years old5 (for whom the mean

duration of such spells also declined) .

Tale 20 describee these distributions for completed

spells. The majority of completed spelle laat only one or

work and non-work

two years. The

proportion of completed work spells, that end within one year declines for the

more recent cohort of 15 to 19 ..year olds, but rise5 ❑lightly for the more

recent group of 20 to 24 year olds.

Tables 21 and 22 present the e5t hates of the multiple 5pell hazard rate

models for women ages 15 to 19 at the beginning of the smple period, for nonblack and for black women, respectively. 15 The result= reported here do not

include correct ions for unobserved heterogeneity. However, given the

heterogeneity mong women in peasured ch=acterist ice for which we do control,

we would anticipate no drmatic change in our estimates. 16

Cons idering first the estimated risk of leaving a work spell, the effeet

of prior experience becomes negative end highly significant for the more

recent cohort, having an insignificant (but positive) effect for the earlier

cohort. Yeare of schooling

changes little for the more

the likelihood of leaving a

associated with longer work

increases the length of the work spell; its ef feet

recent group. Being enrolled in school increases

work spell. Southern residence is significantly

duration among the more recent cohort of women.

15

We use a @adratLc duration specification. Likelihood ratio tests

indicated that we could reject both Weibull ~nd GWpe&z spec~ications in

favor of the ~adrat ic model.

16Early reSUlts based on a non-par~etric mixture distribution with tm

support point5 indicated little change in any of the estimated parmeters.

48
Table 21

Work and’Non-Work Spell Hazard Rate Model,

Non-Black Woman 15 to 19

1968-75 1979-86

(N=948) (N=2278)

INTERCEPT

EXPERIENCE/10 O

AGE/100

GRADE/ 100

ENROLLED

SOUTH

CITY CENTER

~ TO NOT NAR

NOT & TO NAR

NARTONAR

BIRTH:NO KIDS

BIRTH:KIDS

NO BIRTH:KIDS LT6

D~TION

DURATION2

INTERCEPT

EXPERIENCE/10 O

AGE/ 100

G~DEj100

ENROLLED

SOUTH

CITY CENT%

NAR TO NOT -

NOT ~ TO M

NARTONAR

BIRTH:NO KIDS

BIRTE:KIDS

NO BIRTH:KIDS LT6

DURATION

DURATSON2

NEGATIVE LOG LIKELIHOOD

Estimate Standard Estimate Standard

-- —.-—-. -– —----— Error Urror

work to Non-Work Transition

-8.3268 1.4674 -4.2873

8.4791 5.8769 -16.5922

-0.0516 2.6851 3.9815

-15.3758 1.7290 -14.6974

0.3720 0.1062 0.3517

0.0175 0.0921 -0.1145

-0.0740 0.0985 -0.1153

-0.9052 0.5032 0.2950

0.2513 0.1538 0.1598

0.1568 0.1389 0.1959

0.3624 0.2458 0.7427

0.2834 0.4571 0.2513

0.0555 0.1680 0.5071-

0.7682 0.1543 0.5119

-0.3554 0.0538 -0.2019

Non-Work to Work Transition

-11.2336 1.3500

6.1230 4.2746

9.5546 3.0993

9.7537 2.5012

-0.3902 0.0900

-0.0506 0.0712

-0.0312 0.0757

-1.9333 0.6141

-0.5086 0.1366

-1.0006 0.1214

-0.5537 0.1828

-0.6542 0.3056

-0.5827 0.1375

1.5103 0.1297

-0.4699 0.0474

-134.8135

-5.2180

9.1165

-2.9470

14.2659

0.3409

-0.0253

-0.1067

-0.2234

-0.3170

-0.2807

-0.5056

-0.1536

-0.5185

0.9241

-0.2717

0.5609

4.9633

2.3382

2.0032

0.0751

0.0623

0.0904

0.2104

0.1232

0.0930

0.1514

0.2172

0.0966

0.0718

0.0206

0.5313

3.5678

2.3064

1.8995

0.0679

0.0495

0.0720

0.2170

0.1298

0.0788

0.1314

0.1334

0.0782

0.0605

0.0184

510.4882
Table 22

Work and Non-Work Spell Hazard Rate Model,

Black Women 15 to 19

1968-75 1973-80

(N=395] (N=929)

INTERCEPT

EXPERIENCE/10 O

AGE/100

GRADE/100

ENROLLED

somH

CITY CENTER

NAR TO NOT ~

NOT - TO ~

MTO~

BIRTH:NO KIDS

BIRTH:KIDS

NO BIRTH:KIDS LT6

D~TION

D~TION2

Estimate Standard Estimate Standard

Error Error

Work to Non-WoEK Transition

INTERCEPT

EXPERIENCE/1 00

AGE/100

GRADEj100

ENROLLED

SO~H

CITY CENTER

~ TO NOT ~

NOT M TO MAR

=TOM

BIRTH:NO KIDS

BIRTH:KIDS

NO BIRTH:KIDS LT6

D~TION

D~TION2

-40.2922

-1.9012

-1.8386

-9.9666

0.2314

-0.0822

-0.0360

-0.1759

0.2840

.-0.2460

0.4410

0.0807

-0.1908

2.2082

-1.2719

4.1753

9.4739

3:9983

2.3804

0.1861

0.1362

0.1361

0.5318

0.2712

0.2143

0.3127

0.3641

0.1682

0.3531

0.1419

-7.5730

-12.4535

3.5270

-22.5093

0.2288

-0.2486

0.1086

-0.4685

-0.0451

-0.5832

0.2411

0.2203

0.2968

0.8635

-0.3625

Non-Work to Work Transition

-10.1327

2.9780

16.2712

9.8664

0.2737

0.0879

~ 0.0045

-1.0006

-0.0861

-0.2089

-0.0690

-0.8459

0.0062

“1.1128

-0.3365

1.6148

7.4784

4.1344

3.2069

0.1457

0.1122

0.1063

0.5567

0.2272

0.1571

0.2111

0.3065

0.1416

0.1867

0.0613

-4.2102

10.0282

-1.2155

28.1962

0.4745

0.1712

-0.1036

0.3123

0.1825

“-0.0009

-0.2239

-0.0520

-0.5802

0.7181

-0.1647

1.1368

7.4253

3.0831

2.6122

0.1180

0.0934

0.0982

0.4940

0.2486

0.2099

0.2591

0.3005

0.1177

0.1322

0.0407

0.6631

5.7408

3.5189

3.1888

0.0944

0.0740

0.0808

0.3423

0.2123

0.1404

0,1695

0.1754

0.0909

0.0846

0.0228

NEGATIVE LOG LIKELIHOOD -72.5013 242.7594
wong the earlier cohort, only a mr+tal dissolution for white women has

a statistically significant effeet, reducing the probability of =iting a wrk

spell. hong the NLSY, only remaining married matters (statistically), with

OPPOSite ef feCts by race. The relative effect of remaining married is to

raise the likelihood OS exiting a work spell- for white women and increases the

duration of a work spell for black women. Relative to a childless woman, one

who gives birth to her first child during a work spell year is more likely to

end the work ❑pel 1. Thie effect changes little for white women, but weakens

for black women. Bearing a second or higher order child while working has no

statistically significant effect on leaving work, yet the presence children

under age six increases the probability of ending a work spell. Finally,

after roughly one month in a work spell, the effect of duration becomes

negative. This supports our intuition that cumulative experience within a

epell raises otherwise umeaaured returns to continued work participation and

reduces the probability of leaving work. The most notable difference between

the two time periods is that, for black women, there is a drmatic increase in

the ef feet of schooling on the duration of their work spells.

Turning to the estimates for non-work spells, residing in the South

exerts a statistically significant effect to reduce the length of a non-work

spell only for the more recent group of black women, while SKSA is not

significant. Being older at the beginning of a non-work SP1l significantly

reduces non-work spells only for the earlier cohort. The risk of leaving a

spell of non-work increases with experience and schooling. The stren@h and

significance of these effects increases markedly as we compare acroes the two

time periods, and this is especially true for black women.

The consequence of school enrollment appeara to change over time for

51
whit e women. -ong the earlier coho* of white women, school enrollment

lengthens a non-work spell, while the opposite holds for the more recent group

and for both groups of black women.

The tipact of marital status on the non-work spells of white women

appears diminished over ttie. Relative to remaining single, separating,

getting married and Btaying married inhibit labor market entry for white

women. But only mong the earlier cohort of black women does marital status

bear any significant ef feet on non-work spells; the effect of a mutial

dissolution weakly reduce= the likelihood of ending a spell of non-work. For

each group childbearing reduces the likelihood of leaving a non-wrk spell.

hong white women, these effects dec~ine somewhat in magnitude for the more

recent cohort. For black women, a first or higher order birth during a nonwork spell year has an insignificant effect on the. likelihood of leaving the

spell. The presence of children under 6 matters only for the mSY cohort.

Tales 23 and 24 present the results for the 20 to 24 year olds, with

both groups from the NLS Young Women. These data include eight-years of

observations, with women being 28 to 32 in the last smple year. Comparing

the two time periods (which are five years apart ), the results for white women

remain Tite similar. The effect of a change in marital sta.tu.sbecomes

insignificant for the more recent group; this change holds true for the black

women as well .“ Also, southern residence reduces the duration of a non-work

spell mong the more recent group.

hong black women, the ef feet of experience to increase work spell

length doubles. for the more recent group and, the ef feet of a first birth

becomes insignificant. The effect of experience to reduce the length of non52
Table 23

Work and Non-Work Spell Hazard Rate Model,

Non-Black Women 20 to 24

1968-75 ,1973-80

(N=1169) (N=898)

INTERCEPT

EXPERI~CE/ 100

AGE/100

GRADE/100

ENROLLED

SOUTH

CITY CENTER

~ TO NOT M

NOT NAR TO ~

NARTO~

BIRTH:NO KIDS

BIRTH:KIDS

NO BIRTH:KIDS LT6

ALL KIDS GT6

DURATION

DURATION2

INTERCEPT

EXPERI~CE/100

AGE/ 100

GRADE/100

ENROLLED

SOUTH

CITY CENTER

NAN TO NOT NAR

NOT = TO ~

NARTO~

BIRTH:NO KIDS

BIRTH:KIDS

NO BIRTH:KIDS LT6

ALL KIDS GT6

D~TION

DURATION2

Estimate Standard Estimate Standard

Error Error

Work to Non-work Transition

-5.0761 0.8059 -4.6136

1.4867 2.2240 -3.6704

1.3657 2.1236 4.7135

-9.1898 2.0267 -6.6097

0.3206 0.1553 0.3883

-0.1109 0.0783 -0.1037

0.0016 0.0772 0.0560

-0.5848 0.3500 -0.0196

0.4510 0.1370 0.0835

0.1938 0.0986 0.2707

0.5058 0.1925. 0.6653

0.1874 0.2169 0.1449

0.0861 0.1011 0.1767

-0.5954 0.2937 -0.5478

0.6067 0.1016 0.3916

-0.2384 0.0302 -0.1659

Non-Work to Work Transition

-9.3619 0.7644 -5.4088

4.4442 1.7529 2.4494

9.3705 “1.8850 1.4885

10.1085 1.7183 7.3322

0.0168 0.1363 -0.0417

0.0651 0.0686 0.2705

-0.0441 0.0713 -0.0315

-0.3720 0.3137 -0.4660

-0.5492 0.1747 -0.3492

-0.9068 0.1066 -0.9010

-0.5725 0.1464 -0.9995

-0.3349 0.1508 -0.2108

-0.5124 0.0964 -0.8198

-0.7700 0.3295 -0.6486

1.0734 0.,0974 0.8917

-0.3443 0.0292 -0.2835

0.7383

3.7134

2.1328

2.6660

0.1807

0.0941

0.0946

0.2564

0.1840

0.1236

0.1.9.50

0.2763

0.1180

0.2777

0.1123

0.0321

0.8066

3.0362

2.0226

1.9973

0.2008

0.0826

0.0969

0.2598

0.2106

0.1224

0.2065

0.1705

0.1057

0.2371

0.1138

0.0338

NEGATIVE LOG LIKEL~OOD 294.8949 266.2973
Table 24

Work and Non-Work Spell Hazard Rate Model,

Black Women 20 to 24

1968-75 1973-ao

(N=391) (N=375)

INTERCEPT

EXPERIENCE/:

AGE/100

GRADE/100

ENROLLED

SO~H

CITY CENTER

~ TO NOT

00

AR

NOT MAR TO MAR

-Tom

BIRTH:NO KIDS

BIRTH:KIDS

NO BIRTH:KIDS LT6

ALL KIDS GT6

D~TION

D~TION2

INTERCEPT

EXPERIENCE/100

AGE/100

GRADE/100

ENROLLED

SOWH

CITY CENTBR

MAR-TO NOT =

NOT NAR TO MAR

MAR ToNAR

BIRTH:NO KIDS

BIRTH:KIDS

NO BIRTH:KIDS LT6

ALL KIDS GT6

D=TION

D~TION2

... ... . .

Estimate Standard Estimate Standard

Error Error

Work to Non-Work Transition

-7.9106

-6.6746

6.9445

-12.2650

0.3792

-o.202a

-o.la9a

-1. 145a

-0.5909

-0.1743

0.6581

0.3560

-0.1120

-0.3061

o.aoo9

-o.323a

Non-Work to Work

-a.33a3

13..743a

9.1704

17.7011

o.ola2

0.4146

-o.la43

-o.aa21

0.1095

-0.3702

-o.laa6

-0.1872

-0.4291

-0.6170

0.9538

-o.275a

1.6290 -5.9315

3.5059 -12.3340

3.1014 4.1276

2.69a5 -10.6435

o.2a59 -0.2963

0.1429 0.0364

o.126a 0.0927

0.5352 o.063a

0.3291 0.3032

o.146a -o.33a4

0.2910 0.1473

0.2563 0.2252

0.1707 0.0114

0.2941 -0.3501

o.la63 o.3a5a

o.05ao -0.2102.

Transition

1.3457 -4.7726

2.5975 5.0175

3.03ao 0.7193

2.706a 16.la15

0.2335 “0.2a49

o.129a o.31a2

0.1176 -o.121a

0.4167 -0.3746

.0.2352 -0.1311

o.13al -o.26al

0.2710 -o.023a

0.2061 -0.6477

0.1566 -0.2914

0,.3347 -0.7222

o.154a 0.5663

0.0470 -o.la31

1.3226

6.a219

2.6a50

2.a484

0.3493

0.1415

0.1475

o.33a3

0.2574

0.1962

o.4,15a

0.3041

0.1614

o.3oa6

o.la53

0.0547

1.12aa

4.9211

2.9236

3.a195

0.2932

0.1317

0.1356

0.3294

o.2aa6

0.1547

0.3377

o.2a05

0.1436

o.2a40

0.1652

0.0476

NEGATI~ LOG LIKELIHOOD -10.9549 85.5035
work spells declines in magnitude and becomee insignificant. The effect of a

second or higher order birth significantly deters ltior

more recent group of black women.

What do these results inform us *out intercohort differences in ltior

force transitions? Considering the dependent v=i~le alone, the length of

censored work spells has risen nealy one year (of a potential eight) for both

white and black women. The human capital variables, in particular the level

of labor market experience and schooling both increase the duration of work

spells and haaten exits from a non-work swll. Theme effects appear etronger

for the more recent group of 15 to 19 year old women, especially, black wmen.

Yet the intercohort differences in responees to demographic variablea appear

mixed. Relative to being single, all marital states generally deter exits

from non-work spells; and these effects are waker mong the more recent

cohorts of women. Yet, the labor supply ef fecte of childbearing appear not

have changed dramatically over t tie. 17

to

170ne topic that remains for the future is the Ptential endogeneity of

some explanatory variables (measure5 of fertility in particular) . A recent

paper by Oleen and Farkas (1989) outlinee one methodological approach to

treat ing endogenous variables within a hazard rate model.

55
IV. DE~MIWAWTS OF = PROPORTION OF ~ W=D 0= = LI~T~

In this section we sumarize the results of an analysis of the

proportion of years worked since leaving school, or since age 18 for the

youngest cohorts. The perspective here differs from that of the duration

model described -in the -preceding chapter in that we seek-to exmine the

relationship between lifetime work experience and lifettie fertility history,

marriage patterns, education and other factors. This approach does not

inco~orate time-dependent variables; and rather than using annual data,

employs data which sumarize past behavior. mnse~ently, the data

re~irements are less

this analysis for all

A. ~irical Results

We estimate for

stringent than

of the cohorts

for the duration model and we c= perfom

including the mature women.

all cohorts regression models of the determinants of the

proportion of the lifetime worked

Pta =Ot’xt’+u t’,

for a given age group, a:

where t indicates the survey year- Parmeters are allowed to va~ over ttie

within m age group and acroBs age groups. We focu5 on a few key variables

which are known to be strongly associated with women, s l&or force

participation. They are as follows:

~ completed (measured as of the ye= the cohort reached

the stated ages ). Since schooling is positively correlated with the expected

wage it is likely to be positively associated with cumulative

participation (Mincer, 1962 ). The strength of the effect may

and between cohorts due to changes in the return to education

the extent to which wages rise with schooling)

56

work

Vaq over the

(and, hence, in

and to offsetting income
~tal status im meaeured by a dichotomous varisble which ewals one if

the mma had never married as of the stated ye=. In the past a career in

the l~or market often precluded marriage; conse~ently women who sought

careers were less likely to marry (Goldin, 1990) . It has become much more

commonplace .for.married -women to work and we expect that the relation between

lifettie participation and marital statue would weaken from one cohort to the

next. Contributing to this effect is the increase ever the in the proportion

of never-married women who have borne chiltien, a develo~ent which has

narrowed the difference in home responsibilities by marital status. In fact

the availability of welfare to non-married women with children creates

pafiicular work disincentives for this group.

Differences in ferti litv are captured by a series of dichotomous

measures of ntiers of children ever born -- none, one, two, or three -- each

of which is relative to the omitted group of four or more children.

Control variables for w and ~sou e in the stated year are

also included. Southern rotates have lower wage rates and this relative wage

difference (and substitution ef feet) would likely reduce labor force

part icipat ion in the South. However, husbands incomes aze also lower in the

South, and this would be a factor pulling in the opposite direction -- that

is, increasing married women, s participation. Moreover, welfare pa~ents ~e

substantially lower in the South thereby encouraging relatively higher work

participation mong non-married mmen in the South cmpared to the North,

particularly those with low potential earnings.

Complete regression results for the determinants of the proprtion of

years since leaving school (or since age

six months are presented in Appendix A.

57

1S ) in which a woman worked at least

Table 25 swarizes the effects of
Table 25

EffWtS of Schw( im nd Maritnl StntW m the Prvrt im

of Yenrs Mrk& Sime LenVim Schm(, w Age EM Year

1967 ““”

196s

SchmLiw

Never Marrid

1972

1973

0.0006

0.0153

0.0087

0.0112

0.0472

0.13s3

0.14W

0.2W

1977 wa2

1978 1983

O.om

0.0212 0.0111

0.0217

0.0162

O.owb 0.0204

0.0182 0.0124

0.0049

0.04W -0.oln

0.0s37

o.lm5

O.lsm 0.1346

0.2213 0.1745

-0.0007

O.owl

0.0044

0.0438

0.0463

0.W26
--. --1 :-- ..a ---, &., .* .*..” -- -k- ---—--, -” -s ------ ..--,. -a -U,,u”z-,,g m,,= .,-.A.-L - .-*”- “., -.1- &&w&. *AWL, w. X=-A - w“. a=-, ..&“kAAAa ’’’-’-- A.,g the

coefficients dram from the full @et of regressions. The tale enables a

co~=iaon of effects for different cohorts reaching a given age r~nge in

different years and the results =e sh- separately by race. For ex-pie, it

shows the. effect of schooling on lifet~e participation for. cohorts reaching

ages 35 to 39 in 1967, 1972, and 1983. For white women in the 35-39 age group

in 1967 a one-year increase in schooling was associated with a nonsignificant

increase of 0.0061 in the proportion of years worked; but in 1983 the effect

was 0.0217 and it was statistically significant.

In general, an increase in echooling is associated with an increase in

the proportion of yeara spent working. The strength of this effect increases

over time, particularly in the late 1970s and early 19805 and it is somewhat

stronger for blacks - The increase over time occurs within a given age group

(across cohorts ) and within a given cohort as it ages. The within-cohort

effect c- be seen by reading don the diagonal -- for exmple, the cohort

age6 35 to 39 in 1967 was 40 to 44 in 1972, 45 to 49 in 1977 and 50 to 54 in

1982. The change over time seems then to be more strongly related to temporal

rather than cohort effects. The increase in the return to echooling in the

1980s provides a possible explanation of the pattern.

The effect of martial status on the proportion of years worked differs

by cohort and by race. In general, the relation between remining single and

lifettie work participation i6 positive initially but becaes considertily

weaker from cohort to cohort. hong white w-en in the oldest cohort ex-ined

-- those ages 40 to 44 in 1967 -- the promrtion of yeare worked is about onefifth higher among never married women capared to married women. This

pronounced effect is sharply reduced, however, and becomes insignificant mong

59
the youngest cohoti of white women.

hong black women marital status beara no statistically significant

relationship to lif ettie work experience, although the ef feet of n-er

marrying is generally weakly positive mong the oldest cohort ad weakly

negative. mre recently. However, for 25 to 29. year-old black women, having

never married reduces participation and is statistically signific=t h 1978

and 1987 (Appendix A) . The increased tendency for single women to become

mothers has been particularly strong mong black woman and this factor likely

helps explain the observed pattern.

The set of regression results repofied in Appendix A shows that bearing

chiltien dtiinishes lifetime participation and the greater the nutier of

children born the lower the proportion of years worked. The negative effect

of fertility on lifetime part icipat ion is stronger -ong white women than

mong black women. hong both races, once women reach their late fort ies and

fifties when children are likely to be of school age (or older) the effect

dtiinishes somewhat, suggesttig that there is an intensif icat ion of labor

force part icipat ion after fertility is completed.

Tables 26 and 27 sumarize by cohort for white and black women

respectively, the esttiated effects of fertility on the proportion of year5

worked. These effects are calculated from the TAbles in Append& A by taking

the difference between the effects of, for exaple, bearing one child relative

to having borne no chil&en. Overall, the most consistent pattern for white

women is that the negative effect of increasing parity from three to four or

more children strengthens considerably during this period. Relative to white

women, childbearing generally has weaker effect5 on the lifetime work

part icipation of black women, especially when considering the ef feet of the

60
Table 26 ,.

,,

Estimtd Effmts of”Relatiw N-rs of tiildrm .m Pr@rtim of YenFs Wrk .:

(Ntilack w).

sime Le4vim Schwl Sitie A@ 18. “.’”. ‘ .;

.. . .

1%7 1972 1977 lW 197s lp7 ““““

lW 1973 197a 19s3

Age 19n lW

25-~

Otol

lt02

2t03

3 to h+

3&34

Otol

lt02

2t03

3 to 4+

35-39

Otol

lt02

2t03

3 to 4+

40-44

Otol

lt02

, 2t03

3 to 4+

45-49

Otol.

ltoz

2t03

3 to 4+

50-54

Otol

lt02

2t03

3 to 4+

-0.1145

-0.1602

-0.wza

-0.w

-0.1210

-0.1587

-0.0314

-0.0624

-0.1427

-o.073a

-0.M90

-0.0434

-0.ml -0.14%

-0.1625 -0.lm

-0.0948 -o.03&

-0.0024 -0.lw

-0.15M

-0.lw

-0.0900

-0.wll

-0.0796

-o.14n

-0.1185

-0.0727

-0.1717 -0.0727

-0.wa -0.1422

-0.0573 -0.0972

-0.0622 -0.0777

-0.0933 -0.1703

-0.07a7 -0.0793

-0.0564 -o.052a

-0.0522 -0.0543

-0.W9

-0.w

-0.0453

-0.0320

.0.1123 -0.lti . ‘. : ‘..

-0.lw -0.1579

-0.lwl .O.14W

-0.1173 -0.1Z03

-0.W7 ,“

-0.1512

-0.1266

-0.1115

-0.1174

-0.0963

-0.072Z

-0.1167

-0.0423

-0.1145

-0.0921

-0.0942

-0.1331

-0.W7. ‘

-0.M30 ,

-0.0336

:.. .

*Oiffermes ht~ rqr=sim coefficimts, frm Tables 25-30.

:,

!

,..,>.;... .,,..::

.,.:..:.... .

..::.:.

!,’.’.

. .. . ..

., .’..

,. .,., ,: ..’

..: .:

.... .’.,

!:

,,

I

,,,

,,

,,
TabLe 27

Estimtd Effects of Relative Ntirs of Childrm m Pr~rtim of Years Wrk

(Biack””-)

$ime Leavim Sohml Slme Age 18

1%7 1972 1977 19U 1978 1987

1968 1973 1978 1983

Am 1979 1984

25-29

Otol

ltoz

2t03

3 tok+

30-34

Otol

ltoz

2t03

3 t04+

35-39

Otol

ltoz

2t03

3 toh+

40-44

Otol

lt02

2t03

3 to4+

45-49

Otol

lt02

2t03

3 t04+

50-54

Otol

lt02

2t03

3 t04+

0.0480

-o.ln7

-0.!042

-0.W02

-0.0451

-0.0369

-0.1389

-0.0467

-0.0567

-0.W7

-0.w

-0.0162

0.0202

-0.0424

-0.1244

-0.0511

-0.1034

-0.0094

-o.140d

-0.0595

-0.0145

-0.0502

-0.0381

-0.1476

-0.0281

-0.0677

-0.W29

-0.m

-0.0581

-0.0423

-0.0873

-0.OIB

-0.1278

-0.1477

-Owl

-0.ml

-0.0831

-0.0200

-0.0270

-0.18%

-0.W02

-0.0417

-0.owo

-0.1021

-0.04M

-0.02U

-0.1055

-0.0321

-0.0638 -0.0770

-0.1113 -0.0879

-0.0707 -0.1142

-0.14W -0.05’05

-0.0331

-0.0660

-0.1340

-0.0444

-0.0803

0.0157

-0.0948

-0.0953

-0.1167

0.0583

-0.0201

-0.1854

-0.0749

-0.0341

-0.0442

-0.lw

*Differmes btwm rqr-sim cwfficlmt~, frm Tablm 25-30.
first (and sometties the second) child. Yet the negative mf feet on

participant ion of the ffist child borne by black women hae increased over ttie.

Finally, we note that the effect of southern residence on lifetbe

pa fiicipation differs considerably between black and white women. hong white

women the effect is typically negligible and not statistically significant.

hong black women, however, those who live in the South typically have worked

a larger proportion of yems -d the effect is statistically. significant.

Since relative wage= in the South versus the North are lower wong blacks than

mong whites the relatively higher ltior force participation of black women in

the South must be attributable to offsetting ticome effects. AB noted, lower

husbands incomes and lower welf=e benefits in the South would produce less of

a disincentive than in the North. The greater extent of marital dissolution

and reliance on welfare mong black women is consistent with their greater

exposure to the effects of differences in potential welfare benefit5.

B. Accounting for the Increase in Lifetti P&icipation

A natural ~estion tO ask is the extent to which changes in the ntier

of children borne, in schooling, in marital statue and in the other factors

exained can explain the upward trend in lifetbe work e~erience. We first

address this ~estion in Table 2S which Smarizes these results by

decomposing the intercohort changes in predicted lifetime participation into

components measuring the effect of changee due to differences in the mean

values of the independent variables and changes due to variations in the

estimated structure of the participation model (suppressing the age group

superscript ):

Pt=Bt Xt+ Ut *for the earlieat year,

63
PW1 = Bt+l Xt+l + Ut+l , for the latest year, then at the

smple means:

Pt+,- Pt = Bt (Xt+l-Xi) + .(Bt+l-.Bt) xt + (Bt+l- Bt) (x~+l- xt)

The first tem represents the chages due to changes in the 5mple mean5, the

second tem corresponds to variations in the parmeters and the final tem

represents the interaction. The results are presented first regarding all

variables and second focus sing on the changes in fertility (and fertility

coefficients) alone.

The increases in participation have been most &aatic mong white women

younger than 40 and mong these groups, much of the overall change appears due

to changes in the average levels of the independent vari~les, with much of

effect of changes in the means resulting from starkly lower fertility rates.

Wong younger black women, changes in the esttiated coefficients and tiplied

structure of the participation model actually suggest ~solute reduction5 in

participant ion, although lower fertility (and concomitant increases in

participation) offset 5omewhat these reductions.

To focus on cohort differences in lifethe participation, we pool over

time women within the sme five-year age group and reesttiate the regression

models. Tables 29 and 30 display these results. These models constrain the

effects of the independent variables to be e~al within a five-ye= age group

across the periods. For each age group, the earliest cohofi is taken as the

reference group. hong white women, with one exception, each of the cohoti

effect5 is positive, with cohort dumies tiplying a five to 15 percent higher

64
Decomposition of Changes in Lifetime Participation

Overall Due to Due to

Age Group Change Means” Coefficientsb Interactione

25 to 29: 1973-78

Nonblack To al 2

Fertility

Black Total

Fertility

30 to 34: 1967-83

Nonblack Total

Fertility

Black Total

Fertility

35 to 39: 1967-83

Nonblack Total

Fertility

Black Total

Fertility

40 to 44: 1967-77

No&lack Total

Fertility

Black Total

Fertility

45 to 49: 1972-82

Nonblack Total

Fertility

Black Total

Fertility

50 to 54: 1977-82

Nonblack Total

Fertility

Black Total

Fertility

0.1143

0.1134

0.1559

0.0472

0.1165

0.0375

0.0462

-0.0406

0.0586

0.0013

0.0272

-0.0008

0.0347

0.0352

0.0425

0.0226

0.1392

0.1116

0.0908

0.0876

0.0600

0.0468

0.0547

0.0446

0.0013

-0.0063

-0.0334

-0.0125

0.0050

-0.0084

-0.0133

-0.0269

0.0062

-0.0047

-0.0195

-0.0266

0.0596

0.0711

0.0481

0.0837

0.0189

0.0338

-0.0810

-0.0268

0.0218

0.0603

-0.0962

-0.0095

0.0408

0.0566

-0.0074

0.0109

0.0482

0.0706

0.0143

0.0261

0.0250

0.0334

0.0323

0.0375

0.0200

0.0080

0.0228

0.0071

-0.0022

0.0105

0.0374

-0.0136

0.0347

0.0094

0.0790

0.0024

0.0041

-0.0041

0.0002

-0.0390

0.0054

-0.0036

0.0003

0.0021

-0.0040

-0.0015

-0.0136

-0.0117

a

Bt (Xt+l - Xt)

: (Bt+, - @t )Xt

(P 1 - @t) (Xt+ - Xt)

d Fe~tility re~u~ts a~~~e ~eana and ocefficients remain constant for

all variables except numbers of children.
Tnble 29

Detemlmnts of Prwrtim of Y@OfS Wrkd Sime Leavlw Stiml

MDK SLACK ~EM

VARIAOLE

Aes25t029 A-30 t034 ; yM::Ep 39

PflRMETER

Aes40t044

P]RMETER I

A es 45 to 49 A s50t054

PRRMETER PflRMETER PfiAHETER

ESTIMTE I-STAT ESTIMTE T-STAT ESTINATE T-STAT ESTIMTE T-STAT ESTIMTE T-STAT EsTIWTE T.STAT

IMTERcEPT

A03

0.01s3 0.1430 -0.0M2 -0.0350

SCH~lNe

0.0030 0.6770 0.0039 1.OWO

mTH -0.011, -0.8s70 -0.0077 -;3%

00156 5 36~ 00158

HEVER MRRIEO

NO CHILDREU

0:0285 1:4390 0:0333 1:5920

05E CHILD ::;% ‘J:M8 l:j?n !%%T

TW CHILDREN O.w 3.0150 0.1985 11.1190

TNREE CHILDREN

COHmTl

0.0223 0.6160 0.0845 4.-

. . . .

COHOAT2 . . .

mHoRT3 . . ;

COHORT4 -0.;W -0.6770

mHMT5 O.hn 7.;280 O.olm 1.2300

Adjwt4. R-SWre 0.2640 0.3119

Sq[e Size 2446 2877

Oeptimt Mean 0.5914 0.5526

0.2190 1.4980 0.2038 1.2 0

-0.0021 -o.53m 0.0000 0.01Y 0

0.0144 6.32oo 0.0105 4.4T2o

0.0069 0.5910 0.0101 0.81s0

0.1221 4.1940 0.1629 4.7320

0.404S 17.95W 0.3640 16.0350

0.2897 14.3040 0.2273 10.W3D

0.1648 10.7330 0.1325 S.871O

0.8S15 5.1670 0.~605 3.~

: 0.0176 1.3130

0.;170 1.2330 0.0462 3.31S0

0.0M7 2.7330 - -

. . . .

0.2704

2408 :.~~

0.4981

1

0.148 0.71w3 0.3918 1.4250

0.000 0.2540 -0.00U -0.&O

0.0131 5.3S10 0.0156 5.1410

0.0165 1.2810 0.0192 1.18

0.1750 4.71M 0.2037 4.11E

0.3232 13.4940 0.2M 9.W40

0.2141 10.0430 0.15% 6.0570

0.1295 8.2640 0.M78 4.4500

0.$58 4.1250 0.W3D 2.j270

● *

0.0253 1.83a 0.02s2 1.5570

0.0334 3.6250 - -

. . . .

.- . .

0.1903 0.1535

19T2 127s

0.4832 0.4900

BLACK WEN

Aes25t029 Aw30t034 Aw35t039 # ~m:;Ep44 A=45t049

P~RMETER P~RAMETER PflMHETER I PfRWETER

A s50t054

VARIASLE P~MWTER

ESTIM!E T-STAT ESTIMTE T-STAT ESTIMATE T-STAT EST[MTE T-STAT ESTIMTE T-STAT ESTIMTE T.STAT

INTERCEPT

AGE ‘“.ml - .3!% ‘1.!F7 ‘!*YA I.l$W l:%!! -8:ttti -;:S1$!

SCHMLINO ~.~~i$ !.~~o 0.0292 8.05W 0:0229 5.75W 0.0105 2.8550

SWTH

MEVERMRRIEO

0:036S 1:3440 0:0570 2:8970 0.W85 4.3100 0.12M 5.2620

10 CNILOREN

-0.0594 -2.2550 -0.0412 -1.61W3 -0.0449 -1.2180 O.OZTZ 0.5S60

05E CHILO

0.3135 ~2~j ~.;~9 S.3:;~ ~.;~3~ 6:~;0 ~.;~jj $.%

TW CHILOREN 8:;2!$ 3:?550 0:205; %3210 0:1~3 ~.8398 0:1552 4:7850

~~~r$NILOREN 0.0459 1.1540 O.w 2.367a 0.1844 3.33W O.p% 2.:m

. . -. .

0.6962 1.s650 o.awz 1.MO

-0.0W8 -1.2610 -0.0117 -1.24h

0.0767 4.4500 O.OIM 4.51M

0.12% 3.5430 0.1125 3.90W

0.0456 0.9W0 0.W17 ~.~~

0.2529 6.6270 0.2481

::!::! 2:8;:8 t:lztl i:;w

o.p36 2.@o 0.$843 l:ym

-, . ..-

mHmT4

COMORT5 O.’m

:- -0.6188 -0.fioo

-0.;115 -0.;2W -0.0106 -0.3830

; -0.D6W -2.kO -0.0437 -1.6340 - -

2.6550 -0.0S57 -3.3588 - - - -

0.2115 0.1678 0.1351

1010

0.51E

760

0.5447 0.5773

0.~040 0.;610 0.02S0 0.8740

0.01% 0.6920 - -

.-. .

. . . .

0.1636 o,l~g

o.5@ 0.5855
time. Even with identical characteristics, women from more recent cohorts are

spending a higher proportion of their ttie at work h the wrket.

69

v. IS - ~ =SSIEN~-WAGE P~F= GR~NG STSS~?

This report has exmined intercohort ch=ges in emulated years of mrk

experience mong wmen. We have fouti that the Wantity of work experience

ha5 increased from cohort to cohort. Here we in~ire whether the ~ality of

-men, s work experience. has increased.. We do this by est hating the relation

between wages and years of work ex~rience. If waen were investing more in

wrk 5kills either on-the-job or in school (e.g. by taking more courses in

subjects with a etronger market pay-off) then we would ex~ct to see an

increase in the effect of experience on wages from one cohort of women to the

next.

To investigate the intercohort change in the relation between years of

work experience and earnings we have estimated a 5erLes of log wage e~titions,

by cohort, for both white and black women. The full set of e~ations is

displayed in Appendix B, Table5 B-1 through B-6 where each t~le presents the

results for specific cohort/race groups at the point of reaching a given age.

We first 5umarize the results of these cohort specific regressions and then

descrfie the results of regression using data pooling the different cohofis.

A. Coho* lAqelRace Sw Cific Re q ressignm

In the regressions shown in Appendix B experience is defined as years

worked six months or more since completing school. An alternative

specification also includes the nutier of wars in the past five during which

tbe respondent was ~ working. This variable is included for all cohorts and

survey years except for 1967, for which it could not be measured. Additional

explanatory variables include age, years of schooling, southern residence,

SMSA residence, and three dumy variables measuring

one child, and two children, each measuring ef feets

70

fertility: no children,

relative to three or more
children ever born. In brief our results -e a= follows.

tiong white women, years of work experience generally

significant -d positive effects. In instances where years

have statistically

of experience is

not 5ignificat the model specification typically includee ye-s not working

during the past five, a-variable tbst is becomes. highly collinear with total

ex~rience at younger ages. The effect of work e~erience is less consistent

mong black women.

The esttiated effect of schooling is generally statistically significmt

and posit ive for all women. Southern residence dmpens wages, particularly

mong

white

black women. However, this effect is small and often insignif ic~t for

women. SMSA residents receive significantly higher earnings.

Not surprisingly, the effects of children on wages are ~ite variable

and are often not statistically significant. The main effect of children

aPPears tO OPerate through effects on years of work experience. As shon in

Section IV, the nutier of children ever born is an tiport-t correlate of

lifetime work experience. Once work experience is held constant, the expected

effect of children on wages is ~ivalent. Women with children may seek

situations with flexfile hours and other menities compatible with their child

care responsibilities ad to the extent there are employer costs associated

with providing these menities, wages would be commensurately lower. However ,

women who work despite the presence of children may well be positively

selected, or they may work harder because they contribute to their f-ily, s

support and these factors would lead to a positive relationship between

chiltien and wages.

The coefficient on ye=s of experience can be compared across cohort5

and within an age group as done in Tale 31 utilizing the results of

71
Table 31

Estimated Wage Effects of Years of E~erience

E~erience Since kaving School Since Age 18

1967 1972 1977 1982 1978 1987

Age 1968 1973 1978 1983

Black

25-29

30-34

35-39

40-44

45-49

50-54

NonBlack

25-29

30-34

35-39

40-44

45-49

50-54

0.0082

1.026

0.0005

0.074

0.0025 -0.0033

0.533 -0.451

0.0151 0.0007

3.188 0.151

0.0048

0.975

0.0161

2.386

0.0230

4.502

0.0172 0.0184

4.782 4.244

0.0119 0.0189

3.900 5.436

0.0151 0.0200

5.477 5.466

0.0165

1.918

0.0138 0.0351

2.049 5.058

0.0352

5.844

-0.0142

-2.159

0.0016 -0.0032

0.346 -0.478

0.0083 -0.0014

1.463 -0.324

0.0326

5.088

0.0230 0.0337

4.867 6.025

0.0388

9.101

0.0228

5.108

0.0244

5.530

0.0140 0.0205

4.173 6.022

0.0202 0.0522

2.019 6.041

0.0348 0.0413

5.365 6.788

Sumaq of regression coefficients and t-statistics from Appendix B Tables.
regression models that do not include years out of the l~or force in the past

five. We ffid that mong white women, the returns to e~erience increase

systmat ically in size and statistical significance over this period. Foz

-aple, the estimated ef feet for women ages 35 to 39 increases from 0.017 in

1967 to 0.039. in -1983. - tid while these effects are ~ite -vari~le for black

women, -ong black women ages 30 to 34 and 35 to 39 in 1983, the esttiated

returns to experience are positive, statistically significant, and compar~le

in magnitude to those for white women in the eme year.

B. ~

The comparison of coefficients shown in Table 31 5uggests that more

recent cohorts have been gaining more in terns of higher pay from an

additional year of work experience than was t~e for earlier generations.

However, it is possible that the ef feet observed is attributable to some other

unspecified cohort effect. To estimate the titercohort change in the returns

to experience more precisely we have estimated a model pooled across cohorts

(and hence across survey groups) for specific age groups. These models focus

on the first specification used in the Appendix B tables that hcludes only

the emulative level of experience and does not ficlude years out of the l~or

force. AU wages =e expressed in constant dollars, deflated by the U.S.

Bureau of Ltior Statistics experimental COnSumer Price Index (cPI-U-Xl ). For

this pooled model, the cohorts are cotiined into five-year age groups. D-y

variables for the cohort and for the cohort interacted with experience are

included as explanato~ variables. Each cohort is considered relative to the

earliest one relevant for that age group.

The

women the

results of these pooled models are show in Table

cohort dumy itself is negative in each case, and

73

32. hong white

usually become8
The Effects of Ex~rieme ad Other Factors m Log Uagts

NoR BLACK ~EN

Adjmt&. R-Square

SaW[e Size

Oeptient Mean

A es 25 to 29 A es 30 to 34

PARkETER PAR~ETER

A es 35 to 39 A ES 40 to 44 Am45t049 PAR~METER PARflMETER P&ETER

A=50t054

ESTI~TE T-STAT ESTIMTE T-STAT ESTIWTE T-STAT EST1~TE T-STAT

P~ETER

ESTIMTE T-STAT ESTIMTE T-STAT

0.50W 2.4010 0.5S44 2.4!70

0.0175 2.ltio g:~f~ :.j;]:

1.294o 4.1430

-0.0130 -1.5760

1.1257 3.6250 1.7004 4.1150 1.5028 2.4W0

0.0153 2.6590

0.0591 10.s930 0.07ss 17:6410

0.0146 3.7290

0.0740 15.36W

-0.0W6 -4.2140 -0.0555 -2.6120

:~:~ ;/:# :~:~ ;~jfl -~:~fl ;~:~

-0.1180 -4.8E0

0.1022 4.5500 0.1W4 7.6520 0.1547 6.1660 0:1133 4:4s90 0:1248 4:6910

0:WT9 o:21a

0.1156 2.6710 0,0779 2.2630

I:!% :::%

0.0427 1.1690 0.0508 1.3560 0.0134 0.3130 !::~$ f::g! 0.0785 2.1990

0.0315 0.98W -::yti -!:~H8

0.0326 0.8070

o.g4n l,poo -::#1: -1:~% 8:p7 !:#!

. . ●

-0.;253 -1.7410

-0.~36 -1.3370 -0.1374 -1.6390

i

-o.om7 -0.wo

; -Ok - 31?0

-0.2003 -3.0240 -0.1154 -1.5W - -

-0.1ss0 -3.2940 -0.0182 .;.: - .5290 - :, - ; ; ; ; ;

-0.3223 -4.S070 - -

. .

. . :

0.0056 1.;290

0.:039 0.97s0 O.ml 1.0470 0.0040 0.W20

:: 0.:045 0.:950

0.0073 1.7m

0.0232 4.5650 - -

0,0040 0.%10 - -

0.0159 2.1520 0.0128 1.s420 - -

. . . .

. . . .

o.j~ 0.3W1 O.mj$

1376

0.2916 0.2gf 0.2794

1.9% 1.W63 1.%18 1.9Z; 1.9465

578

1.9601

BLACK ~EN

VARIASLE

INTERCEPT

AGE

EXPERIENCE

SCHWLIHG

WTH

SXSA

NO CHTLOREM

WE CHILO

TW CH1LOREN

COHWT1

COHORT2

COHORT3

canoRT4

WHmT5

COHORT 1*EXPERIENCE

CGMORT2*EXPERIENCE

COHORT3*EXPERIENCE

COKORT4*EXPERIENCE

COWRT5*EXPERIENCE

Adjmtd R-mare

sawle Size

Oeptimt nean

A es 25 to 29 A es 30 to 34

PAR~ETER PARhETER

ESTIWTE T-STAT ESTI~TE T-STAT

0.S976 2.8360 1.1683 3.3070

0.0057 0.5000

0.0095 1.2740

-0.00s7 -0.79s0

0.0590 8.S360

-0.oom -0.1350

-0.2540 .8.0400

0.07W 11.7330

0.0870 2.43W

-0.2345, -7.4690

0.0695 1.5350

o.lm3’ 5.1730

-0.01311 -0.2940

0.028s 0.6670 -0.0348 -0.S490

0.0730 1.6900 0.0137: O.wo

. . . .

. .

:-

:

-0.:110 -0.1780

-0.0508 -0.;690

-0.2103 -2.25010

. .

. .

:- 0.;181 2.;460

O.owl O.ho 0.0333 3.7380

0.3::; 0.4241

1.7925 l.&Y

A eS35 to 39 A es 40 to 44

PAR~METER

$ &::Eo 49

PARiMETER I

A es 50 to 54

PAR~ETER ESTIMATE T-STAT ESTIXATE T-STAT ESTIMTE T-STAT ESTIMTE T-STAT

0.9403 1.Ww

-0.0131 -0.9M0

0.0056 1.1690

0.1016 14.W30

-0.2651 -6.2120

0.1769 3.9290

.0.0117 -0.1s20

0.03% 0.6730

-0.W5 -1.W

. .

● ☛

0.2601 2.3550

-0.2342 -2.2530

. .

●

-0.:080 -1.014

0.0282 3.5320

0.5W3

437

1.7045

0.1517 0.24W -0;1315 -0.lMO

0.0068 0.4810 0.0172 1.1490

2.8659 3.0130

0.0119 2.7260

-0.0428 -2.SS O

0.0038 O.WW r

O.OM 13.1010

0.0089 2.000

-0.2S97 -5.26W

0.W52 13.0610

-0.2915 -6.0450

0.0804 10.0s70

0,1930 4.1970 0.1707 3.4600

-0.=7 -3.M20

0.0759 1.1920 -0.0W8 -0.1370

0.1853 2.w5o

-0.0329 -0.53~ -0.0S27 -1.29~

0.0326 0.4060

0.0010 1.0370

0.1517 Z.plo 0.0012 0.9210

●

0.:509 o.~40

0.;029 2.60u 0.2633 1.W50 0.19W 1.2270

0.4240 3.1140 0.0474 0.%50 - -

. .

:

:t: :;;

-0.0111 -1.;90

-0.0134 -1.890

-0.:002 -o.h20 -0.0079 -1.2W0

-0.0E7 -0.7700

.- . . . .

0.4874

397

0.4995 0.4444

1.6764

, 7gJ

1.7if:

Note: ;;e years in tilch each cohort reach~ a es 25 to 29 is as fo[lws:

- 1952,.C2- 1957,C3 - 1960,S4 - 19%, C5 - 1978.

A stariti,catesthectiortuhlch is the refereme gr~ in the swcif ic rwressim.
more negative mong higher order (i.e., more recent) coho*s. This hplies

that, all else e~al, more recent cohorts of ~men ❑tati at low= wage levels,

although not all of these cohort effects =e statistically significmt.

Moreover, the effect of cohort interacted with experience is ~sitive, and

grows larger, indicating that -women in more recent- cohotis earn higher returns

to investments in human capital than their earlier counterparts. For exmple,

for white women 25 to 29, the effect of experience on earnings increases fra

0.0153

cohoti

likely

the.

accord

imply

black

for cohort 4 in 1978 by 0.0159 to 0.0302 for cohoh 5 in 19S3. The

differentials in the esthated return to experience are larger and more

to be statistically significant when the cohorts are farther apart in

Results based on experience defined 5ince age 18, displayed in Table 33

with this findings.

@ong black men younger than 40, these effects (when significant)

3imilar gaina in returns to experience as mong white women. Yet, for

tomen 40 to 44, ❑tart ing wages (all else e-al) are Bigher for more

recent cohorts, with returns to ex~rience est hated at - levels.

Although this pattern hold5 for black women 35 to 39 in 1972 compared with

those in 1967, by 1983, the return to experience differential become5

posit ive.

These results provide evidence that work related investments have

increased from cohort to cohort mong white women, although not necessarily

for all cohorts of black women. The negative cohort effect mong l~or force

entrants may be explained by hman capital theog which suggests that On-thejob training would be funded in part through lower wages paid to the trainee

(Becker, 1962 ) . Since training is more lfiely to

their c=eers, an increase in on-the-job training

75

occur when workers begin

from one generation to the
Table 33

Dete&inants of Log Wages Years of E~erience Since Age 18

NON BLACK WO~N

VARIABLE

INTERCEPT

AGE

EXPERIENCE

SCHOOLING

SO~H

SHSA

NO CHILDREN

ONE CHILD

TWO CHILDREN

COHORT5

COHORT6

COHORT5*EXPERI ENCE

COHORT6*EXPERIENCE

Adjusted R-S~are

Sample Size

Dependent Mean

Ages 25 to 29

PARAMETER

ESTI~TE T-STAT

0.4701 2.2860

0.0075 0.9860

0.0339 4.8570

0.0617 13.4790

-0.0343 -1.7650

0.1350 6.2620

0.1413 2.8950

0.0969 1.9820

0.0667 1.3600

* *

-0.0662 -1.2150

* *

0.0101 1.2520

0.2239

1953

1.9165

BLACK WOMEN

VARIABLE

INTERCEPT

AGE

EXPERIENCE

SCHOOLING

Som

SNSA

NO CHILDREN

ONE CHILD

TWO CHILDREN

COHORT5

COHORT6

COHORT5*EXPERIENCE

COHORT6*EXPERI ENCE

Ages 25 to 29

P~TER

ESTINATE T-STAT

0.8008

0.0057

0.0200

0.0648

-0.1343

0.0968

-0.0523

-0.0575

-0.0785

*

-0.2601

*

0.0344

Adjusted R-S~are 0.2542

Sample Size 720

Dependent Mean 1.7941

2.4930

0.4820

1.9510

9.2740

-4.4520

2.5840

-1.0220

-1.1770

-1.5660

*

-3.5820

*

2.8690

*Designates the cohort that is the reference group for the regression.
next would be expected to generate a greater reduction in wages for new

entrants mong more recent cohorts. The s~se~ent steeper rise in earnings

with experience reflects the return to the greater level of invest fient in work

skills.

Of course,. we cannot detiemine from this analysis the extent to which

women or their employers are responsible for the increase in investment

levels. For ex~ple, women may have initiated the change by applying for

entry into management traintig progrms or through choice of occupations where

training is more commonplace. Mployers, however, may have become more

willing to invest in the traintig of women either because they have become

less prejudiced, or because they are responding to the reduction in turnover

and increased labor force attachent exhibited by the average woman, a factor

that would have reduced the risk of training women. Stice there is 50 much

feedback between the labor force choices of women and the behavior of

employers it is probtile that botb sides contrfiuted to the increase in

earnings effects of experience that we have estimated for more recent cohorts

of women. The old pattern of flat age-earnings profiles for women -- the

dead-end job syndrome -- finally appears to have been overcome, which bodes

well for future narrowing of the gender gap in earnings.

77
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ation a

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80
APPENDIX A
Table A-1

Determinants of Pr~rtim of Years hrkd, Ages 25-29

HW BLACK WEN

Since LeaVim Schml Sime Age 18

VARIABLE

INTERCEPT

AGE

scMmt InG

WTH

NEVER NARRIED

NO CHILOREN

WE CNILD

TW CNILDREN

THREE CHILOREW

Adjustti R-Sqmre

Swle Size

De@ent Nean

1973 1978 1978

PARANETER PARAMETER PARMETER

EST[~TE T-STAT ESTIMATE T-STAT ESTIWTE T-STAT

1987

PARANETER

ESTIWTE T-STAT

0.4020

-0.0030

0.0006

-0.0020

0.0472

0.3547

0.25%

0.0971

0.0024

2.0020

-O.42OO

0.1380

-0.0970

1.3826

8.0060

6.1310

::%

-0.29& -1.81w

0.0072 1.3160

0.0295 8.49M

-0.0230 -1.429o

0.0049 0.2180

0.5290 9.0330

0.3793 6.5310

0.1948 3.35W

0.1384 2.255o

-0.0150

0.0080

0.0014

-0.0482

-0.0347

0.5076

0.3953

40.091

1.446

0.405

-2.957

-1.529

8.567

6.719

0.2264

0.1173

3.853

1.879

-0.4553 -3.515

O.olw 4.297

0.0126 3.917

-0.0104 -0.769

-0.066s -4.228

o,5m3 13.737

0.4263 10.56s

0.2W 6.656

0.1203 2.%

0.1537 0.3673

1204

0.2227

1241

0.5245

1193

0.6563 0.5736

0.2W

1812

0.6356

BLACK ~EN

Since Leavi~ schwl Sime Age 18

19n 1978 1978 1987

PARMETER PARAMETER PARMEIER

VARIABLE

PARAMETER

EST1mTE T-STAT ESTrWTE T-STAT ESTINATE T-STAT ESTINATE T-STAT

IWTERCEPT -0.lw’ -0.3740 -1.3637 -4.4M0 -1.0417

AGE

.3.6W

0.0069 0.5270

-0.5480 -2.270

0.0483 4.5400 0.038s 3.945 0.0085 0.966

SCHWLI WG 0.0244 3.1310 0.0310 5.6040

WTH

O.OIM 3.618 0.048s 7.692

-0.00M -0.1770 0.0534 1.8no

NEVER NARRIEO

0.0217 0.812

-0.03W’ -0.8300 -0.0617 -1.WO

0.0639 2.790

-0.0392 -1.370 -0.W25

WO CWILOREN

-3.%1

0.1977 3.1140 0.4278 7.0450

DNE CHILO

0.3M7 6.971

0.2179 3.7450

0.3293 5.814

0.3000 5.5430 0.3229 6.482

TW CWILOREN

0.2526 4.549

0.1755 3.2110 0.1523 2.82oo 0.2116 4.264

THREE CHILOREW 0.0311 0.9210 0.0661 1.13m

0.1647 2.921

0.1409 2.627 0.0505 0.822

Adjustd R-~re 0.W73 0.2622

Swle Size 395

0.1965 0.2458

D%mt Hean

492

0.4425

458

0.5561

653

0.4776 0.5042
T*le A-2

DetemiMt8 of Prmrtim of Year6 Vork4 Sime Leavim S~Wl, Ag- 30 to 34

w BLA2S Wn

vAAIABLE

1%7 1978 19s3

PAAANETER PAMIER PAMIER

ESTl~TE T-STAT ESTINATE T-STAT ESTINATE T-STAT

IHTERCEPT

AGE

SCH~IHG

WTH

HEVER MRIEO

so cHILDREN

WE CHILD

TW CHILOREN

THREE CHILOREH

-0.0538

0.0055

0.0148

0.0173

0.1171

0.454s

0.3403

0.1001

0.0s63

-0.2330

0.7s40

3.5m

0.8140

2.=0

11.6270

8.7630

6.7G7D

3.2720

0.2%1

-0.0M9

0.0212

.O.w

0.049

0.4507

0.3001

0.1519

0.0611

1.45m

-1.lW

5.93n

-0.0200

ll:M

8.*

4.8620

1.mo

Adjutd R-Xre 0.3W

Smle Six@ 747

o-t km 0.4627

O.w

1142

0.5549

-o.m7

0.0137

0.0111

-0.0318

-0.0178

0.4720

O.m

0.2381

0.1115

0.2656

w

0.6181

-1.3s50

2.34m

3.2910

-1.W

-o.@

11.6440

9.s3n

6.33W

2.7260

1%7 1978 1903

PAWETER PA~ETER PARA2GE1ER

VARIASLE ESTlMTE T-STAT ESTIMTE T-STAT EsTIWTE T-STAT

INTERCEPT

A=

SC~lNG

MTk

NEVER MRRIEG

NO CNILOSEH

WE CHILD

TW CHIWREN

0.2761 2.93~

0.3241 4.~8G

0.1944 Z.qm

0.0902 1.5900

Adjwtti R-Wre 0.1101

s~le Size 262

O-t Mean 0.5161

0.1345

-0.010s

0.04%

0.0650

-0.0504

0.313

0.2093

0.2001

0.03%

o.3m

-0.qm

8.3320

2.0410

-1.lqlo

S.m

4.om

4.4290

1.3690

-1.1932

0.03T9

0.0317

0.0351

-o.G4q3

o.2m

0.2452

0.17G5

0.0444

-3.3640

3.5150

5.W

1.2030

.1.4510

4.6430

5.24~

4.G530

o.qlM

0.3418

357

0.5447

0.2276

o.5n

Table A-4

Detemimnts of Pr~rtim of Vears Wrkd Sime Leavim SchmL, AW 40 to 44

VARIASLE

INTERSEPT

AGE

SCM~LIMG

Smn

MEWR HARRIEO

MO CHILDREN

ONE CHILD

TW CHILOREH

THREE CH1LOREN

Adjustd R-S~re

s~le Size

De-t Mean

1%7

PARNETER

ESTIWTE T-STAT

1972

PA~ETER

ESTIMTE T-STAT

1977

PARWETER

ESTINATE T-STAT

0.5212

-0.0064

0.0083

-0.0073

O.lw

0.3289

0.1s62

0.lf24

0.0434,

0.1711

a59

0.4442

1.a540

-0.9730

2.269Q

-0.3620

2.9710

a.9310

5.0220

4.4690

1.6310

o.15a3

0.01021

0.0QS7

0.0079

0.1499

0.3871

0.2154

0.1194

0.0622

0.5310

0.3060

2.0220

0.3570

2.5020

9.1540

5.7070

4.54ao

2.35ao

-0.1265

0.00M

0.0162,

0.0299

0.1385

o.3am

0.3172

0.1730

0.0777

-o.41m

0.9420

3.633Q

1.3aw

2.4150

9.m30

7.9zaQ

6.7360

Z.mo

Q.21OO

701

0.4609

0.2762

634

0.4927

VARIAELE

1967

PARANETER

ESTl~TE T-STAT

INTERCEPT

k=

SC~LIMG

SWTH

NEVER MARRIEO

NO CHILOREN

ONE CHILO

TW CHILOREN

THREE CHILOREN

1.1734

-0.olu

0.0044

0.1201

0.0926

O.zzm

0.1693

0.0026

0.0162

2.1330

-1.4310

0.7630

3.1180

1.2100

4.1650

3.2040

1.4730

0.2550

AdJmt4 R-SWre 0.0921

$~le Size 3Q9

O@nt Mean 0.6017

1972

PARNETER

ESTIMATE T-STAT

0.3903 0.6650

-0.0034 -0.2490

O.OIW 2.55W

0.W16 2.2~

-0.OW -0.0620

0.2693 3.4?40

0.2412 3.2400

0.1~5 3.160’0

O.W, 1.2a50

o.lzal

253

0.5482

1977

PARMETER

ESTIWTE T-STAT

0.6033

-0.00s9

0.0133

o.a571

-0.0100

0.31%

0.2365

0.2165

0.1893

1.0260

-0.U70

1.W

3.a240

-0.2510

3.2130

3.0270

3.7s70

3.2610

0.2042

196

o.5m
Table A-5

Dctemiwts of PWrtim of Years Mrkd Sime LeaVim Schml, Agm 45 to 49

VARIMLE

1MTERCEPT

AGE

SC~LING

WTH

NEVER WRIEO

NO CHILDREN

WE CHILD

TW CHILDREU

THREECHILOREN

Adjwtd R-Xre

Sqle size

D-t Mean

1972

PARAMETER

ESTINATE T-STAT

0.4354 1.3500

-0.0043 -0.6410

0.0112 2.9130

o.m29 O.lw

0.2M 3.2230

0.2~6 7.5570

0.1872 5.U20

O.lM 4.2440

0.0522 1.9300

0.1562

773

o.45n

1977

PAMETER

ESTI~TE T-STAT

0.2355 0.6950

Q.0007 O.m

O.OM 2.2430

0.0118 0.5300

o.15n 2.3470

0.35b9 8.3~

O.lsaa 4.8720

0.1071 3.9030

o.m43 2.0110

0.1%6

650

0.4s66

1982

PAWIER

ESTINATE T-STAT

-0.2705

0.Oou

0.0204

0.0340

0.1346

0.3431

0.300s

O.lm

0.M2

0.2465

537

0.5164

-0.7230

1.055’0

4.27S0

1.4230

1.9770

7.4s40

6.W

b.32m

3.2420

BLACK WEN

VARIASLE

INTERCEPT

AGE

WHWLING

SWTti

NEVER MRRIEO

NO cHILOREN

ONE CHILO

TW CNILOREN

TNREE CNILOREN

1972

PAMETER

ESTl~TE T-STAT

1.0005 1.6150

-0.0153 -1.1820

0.0131 2.lW

0.1457 3.SSW

0.1247 1.5160

0.2074 3.W20

0.1493 2.8760

0.1070 1.8550

0.01% 0.3140

Adjwtd R-S~re 0.1251

5wle Size 2n

O-t, Mean o.58m

1977

PAMETER

ESTI~TE T-STAT

0.4W O.w

-0.W -0.2650

0.01S6 2.9~

0.0711 1.8130

Owl 0.3440

o.3m 4.3350

0.23M’ 3.3W

O.lwl 3.5s20

0.1021 1.n30

0.1796

232

0.5674

0.s464 1.1490

-0.0146 -0.93s0

0.0203 2.5210

o.193a 4.13w

-0.002b -0.M50

0.26S9 2.9a50

0.1472 1.6370

0.2055 3.1790

0.1G34 z.asm

0.2119

159

0.5W
Tabte A-6

Detemlmnts of Prwrtim of Years tirkd Sime Leavim Stiml, Ages 50 to54

VARIABLE

1977

PARAMETER

ESTIWTE T-STAT

lW

PARMETER

EST1~lE T-STAT

INTEREPT

AGE

SCHmLING

WtH

NEWR WRRIED

MD CHILDREN

WE CHILD

TW CNILOREN

TNREE CNILDREN

Adjmtd R-Square

sa~~e Size

DeF&nt Mean

0.5587

-0.0074

0.0182

0!D2M

0.2213

0.2502

1.5370

-1.0760

4.64?0

0.9760

3.3370

6.7170

0.1633 4.9910

Own 3.7230

0.0320 1.9110

0.15M,

0.4%

0.1385

552

0.5057

SLACK WEN

VARIABLE

1977

PARMETER

EsTINATE T-STAT

INTESCEPT

AGE

SCNmLIMG

WTN

HEVER WRRIED

NO CHILOREN

ONE CHILO

TN CNILOREN

THREE CNILOREN

Adjustd R-mCe

Swle Size

Oe-t Hean

1.2024

-0.0104

0.0167

0.1292

0.0U5

0.2130

0.1664

0.1376

0.0321

o.13n

244

0.5859

1.7160

-1.3890

2.~30

3.23W

0.8750

3.8500

3.0890

2.2760

0.5140 O.lw 2.2300

0.2208

200

0.5850

Table s-1

Detemimnts of Log Uages, Ages Z5-29

Years Simc Age 18

MN BLACK WIEM

VMIANLE

1978 (a) 19s7 (a) 1978 (b) 1987 (b)

PARMETER PARAMETER PARAMETER PAR~ETER

ESTIMATE T-STAT ESTIMATE T-STAT EsTINATE T-sTAT ESTIWTE T-sTAT

IMTERCEPT

Au

EXPERIENCE

SC~LING

MTN

SUSA

NO CHILDREN

WE CHILD

TW CHILDREM

YmS ~ lM PAST FIVE

0.M7

O.oqlo

0.0348

0.0494

-0.0390

0.1324

0.0221

-0.0058

-0.03s9

2.414

1.Om

5.3b5

8.363

-1.428

4.5a7

0.330

-0.0s6

0.2407

0.0073

0.0413

0.0710

-0.0353

0.132s

0.2069

o.q569

-0.561 0.1263

0.s83 0.6648

0.732 0.01s6

6.7B 0.0176

10.W4 0.0470

-q.346 -o.04n

4.4W 0.1331

3.117 0.0137

2.3~ -0.0084

1.892 -0.0327

-0.0413

2.339

1.656

1.a98

7.9o2

-1.573

4.63o

0.2M

-0.124’

-0.474

-2.603

0.1197

0.0224

o.o13a

0.0691

-0.0393

o.q342

o.qm

o.q34q

o.lq47

-0.0555

0.437

2.000

f.327

10.M2

-1.503

4.4s8

2 .b59

2.029

q.750

-3.245

Adjustd R-~re 0.2154 0.2305

s~le Size b94 125b

O*timt Hean q.9667 f .9097

0.2219

b94

q.9667

0.2U3

125b

1.9097

sLAcK WEN

,,,

VARIABLE

1976 (a) q987 (a) q9TS (b) 1987 (b)

PAR~ETER PA~ETER PAWETER

EsTINATE T-STAT

PARMETER

ESTIWTE T-STAT EsTINATE T-STAT ESTIWTE T-aTAT

INTERCEPT

AGE

EXPERIENCE

scnmLIMG

WTH

WSA

NO CHILOREN

ONE CHILO

TW CHILDREN

YEANS ~ IM PAST

Adjustd R-~re

Swle Size

o-t mean

1.2542

-0.0033

0.0202

0.04a7

-0.2112

0.oa30

0.077s

o.03q3

0.0289

FIVE

O.2S43

276

1.m

2.7q9

-0.195

2.019

-;:~8

q.6T3

q.om

0.401

0.424

0.252S

0.0125

0.0522

0.0781

-o. qoq9

0.0820

-o. qN7

-0.llm

0.591

0.794

6.041

7.112

-2.503

1.5q3

-1.843

-1.7qo

1.2543

-0.0024

o.oq73

o.04a7

-o.2q20

0.W7

o.073a

O.om

2.715

-o.13a

1.lb7

5.736

-4.a17

1.6s4

q.044

0.455

-o.q527 -2.q71

0.2466

445

1.m7

0.0281 0.411

-0.OW -0.2b9

0.2819

276

1.8626

0.1656

0.0245

0.0250

0.0778

-o.q137

0.0260

-0.1454

-0.12s4

-0.1576

-0.0493

0.2513

445

1.m7

0.3s6

1.454

1.511

7.wa

-2.7F1

1.592

-2.038

-1.sbq

-2.245

-1.930
Table 8-2

DetGmimts of LW Wges, Ages 23-~

Years Sfme Leavim Schml

VARIABLE

IHTERCEPT

m

EXPERIENm

SCti~tNG

WTH

2PC2A

NO CNILDREN

ONS CNILD

W CHIWREN

YEARS WT IN PASY FIVE

T-STAT ESTIWTE

1.654 0.4279

1.651 0.0158

2.3M 0.M26

5.b78 D.0615

.4.525 -0.&27

1.691 O.lm

2.917 0.0472

1.922 0.0189

0.14s -0.0362

0.2114

71b

1.mo

NW SLACK wEM

19n (8) 197s (a) 19T3 (b)

PAWETER PARMETER PAR~ETER

VARIASLE EST INATE

INTERCEPT 0.5502

AGE 0.0202

EXPERIENCE 0.0161

SCHmLIUG 0.0515

WTH -0.1537

WSA 0.0626

NO CNIUREN 0.1784

WE CHILD 0.11s1

TW CNILDREN O.m

YEARS M IN PAST FtVS

Mjwtd R-Wre 0.1s91

s~le Size 5b5

o-t Mean Y.9654

sUCX ~EN

T-STAT

1.5M

1.b59

S.m

9.0s1

-1.5M

4.495

0.713

0.281

-0.52s

ESTIXAYE

Owl

0.0215

-0.W55

0.0457

-0.lw

0.M57

o.m50

0.0556

-0.w

-0.0974

0.2570

545

1.%54

197s (b)

PARMETER

T-STAT ESTIMTE

2.735

1.s37,

-0.T7b

-::E

1.854

0.900:

0.9M

.0.047

-7.070

0.5111

0.0212

0.0177

0.05n

-0.0447

0.13W

0.0294

0 .0W5

-0.0313

-0.0411

0.2198

714

1.9700

T-STAT

t.s63

1.946

2.174

7.453

-1.646

4.550

0.445

0.127

-0.b55

-2.930

19n (a) 19T8 (a) 1973 (b) 197s (b)

PARANETER PAWETER PAWETER PAWETER

EsTIMYE T-STAT ESTIMTE T-STAT EST[MTE T-STAT ESTIXATE T-STAT

0.6s1s

0.0129

0.00s2

0.D6W

-0.3035

0.1153

0.0200

0.0436

0.1079

1.3W

0.765

1.026

6.297

-5.944

1.952

0.305

0.634

1.752

1.1502

-0.0013

0.0165

0.05U

-0.2144

0.0713

0.1107

0.fi60

0.06s9

0.2798

1.8E

2.67S

-0.079

1.918

-;:F7

1.4ss

1.650

0.913

0.W7

1.0120

0.0110

-0.0083

0.0577

-0.3102

0.1231

-0.0100

0.0171

0.0775

-o.on7

0.4421

1.Jfi

2.131

0.679

-0.971

5.285

-6.3o7

2.163

-0.157

0.257

1.2%

-3.974

1.2028

-0.0006

0.0115

0.0517

-0.2150

0.072s

0.1010

0.0500

0.M7

-0.0150

0.27s8

1.8E

2.765

-0.037

;:29

-5.118’

1.500

1.47s

0.009

0.944

-0.7s0
Table B-3

Determimnts of Log Wages, Ag= 30-34

MM BLACK MEW

1967 (a) 1970 (a) 1983 (a) 1~ (b) 1985 (b)

PARAMETER PARAMETER PARAWETER PARAMETER

ESTIWTE T-STAT EsTIWTE

PA~ETER

VARIABLE T-STAT ESTIWTE T-STAT ESTINATE T-STAT ESTIWTE T-STAT

1.272

-0.059

6.025

11.100

-0.026

0.3289

0.0229

0.0070

0.0652

-0,0944

0.1401

0.0474

o.m7

0.0363

-0.0691

0.W7

1.975

1.242

8.W

-2.M5

6.192

0.859

0.5128 1.344

0.00% 0.778

O.ola 2.273

0.0703 9.442

-0.M74 -0.211

0.1879 5.211

0.0484 0.761

0.0395 0.6M

0.0161 0.265

-0.w -3.479

INTERCEPT

AGE

EXPERIENCE

sC~LING

WTH

1.50s8

-0.0271

0.0230

0.0745

-0.1296

0.1808

0.0396

0.0210

3.006

-1.801

4.502

8.709

-2.955

3.841

O.ao

0.?87

0.7s5

0.0902

0.01s4

0.0230

0,0767

-0.0826

0.1391

0.0954

0.1253

0.0478

0.243

1.559

4.M7

10.247

-2.47S

4.077

f.720

2.251

0.%9

o.4a9a

-0.0007

0.0337

0.07s8

-0.0009

0.1906

0.0920

0.0759

0.0342

5.234

1.463

1.139

0.562

wSA

NO CHILDREW

oWE CNILD

TW CHILDREN

YEARS ~T [W PAST FIVE

1.002

0.730

-4.%7

0.0446

0.2967

2.0::

0.3142

2.OL?

0.3103

2.2:

AdJust4 R-Svre

Samle Size

Oewtient Mean

o.3a33

239

1.0370

0.2049

2.0::

8LACK WEM

1%7 (a) 197a (~) 1903 (n) 1978 (b) 19s3 (b)

PARMETER PARMETER PARMETER

VARIAaLE

PARANETER PAMMETER

ESTIWTE T-aTAT ESTIMATE T-STAT ESTIMATE T-STAT ESTIWATE T-STAT ESTIWTE T-STAT

2.2b7,

-1.223’

5.058

8.345

-3.W7

3.W

0.9393

0.0144

-0.0011

0.0514

-o.31a2

o.la71

-0.0343

1.bT3

o.ala

-0.141

4.762

-6.o45

3.221

-0.526

-0.120

1.122a

-0.0095

0.0213

O.ow

-0.134s

0.2356

0.0076

-0.0811

0.0160

-::E

2.5b5

7.343

-3.005

4.162

O.lM

-1,393

-kK

INTERCEPT

AGE

EXPERIENCE

SC~LIMG

WTH

1.2114

-0.0127

0.0005

0.0791

-0.32%

o.lova

-0.2133

o.ola5

1.5a3

-0.530

0.074

5.a52

-4.343

1.3b9

-1.m

0.196

0.950

0.W7

o.om7

o.o13a

0.W17

-0.3096

o.la34

-0.0022

0.0084

0.0032

1.406

0.485

2.049

5.872

1.2342

-OIO21O

0J0351

O;9736

-0.1410

0.2237

-5.7b3

3.m

-0.034

0.110

0.052

WSA

ND CHILDREN

ONE CHILD

TW CHILOREN

YEARS WT IM PAaT

0.0255

-0.0626

0.0214

o.34a

-1.064

0.373

.O.OM

0.0057

-0.0740

0.0913

FIVE -0.0780

Adjmtd R-Xre 0.4615

s~le Size 113

Owtimt Hean 1.5169

0.3724

204

1.0918

0.3739

249

1.9200

0.3991

204

1.8918

0,3935

249

1.9200
Tab[e B-4

Detemimnts of Lw UaW, AEe 35-39

1%7 (a) 1972 (a)

PARAXETER PARWETER

VARIABLE ESTIWIE T-STAT ESTIMTE T-STAT

19S3 (a)

PAMETER

ESTl~TE T-STAT

1972 (b) 19S3 (b)

PARMETER PAMETER

EsTlmTE T-STAT ESTINATE T-STAT

IHTERCEPT

AGE

EXPERIENCE

SCH~lNG

~TH

%SA

fflCHILOREM

ME CHILD

TW CH1LDREM

Y~RS WT IN THE PAST FIVE

1,1103

-0.00G3

O.oln

0.06s3

-0.w

0.0965

-0.0232

-0.0499

-0.02U

2.1%

-0.625

4.W

9.210

-1.5n

2.269

-0.3s6

-0.69S

-0.639

0.%50

-0.0M2

0.01%

0.0672

-o.07m

0.1421

0.05%

0.W9S

-0.0337

1.739

-0.204

4.244

7.563

-;.g

0:877

0.969

-0.w

1.0G67

-0.01s4

O.om

o.0P3

-0.1617

O.lm

0.0637

0.0247

0.0272

2.246

-1 .3s7

9.101

10.15s,

<4.241

4.M2

::%

0.591

Ad]wtti R-~rO 0.30s2

s~ie Size 263

D-t nem 1.US1

0.2763

1.nT7

o.3@

565

2.02m

0.0634 0.929

O.om 0.9s3

-0.0329 -0.672

-0.0114 -0.656

1.2735

-0.0150

0.0240

0.0713

-0.155b

0.1929

2.b56

-1.149

4.554

8.979

-4.135

5.046

0.0734

0.03s2

0.U31

-0.0715

::%

0.%5

-4.W

0.2749 0.3249

5b5

1.mm7 2.0270

SLACK ~EN

1%7 (a) 1972 (a) 19s3 (a)

PMMETER PARMETER PA~ETER

VARIABLE ESTIKATE l-STAT ESTIMTE T-STAT ESTIMTE

1972 (b) 19G3 (b)

PARAN3TER PARMETER

T-STAT ESTINATE T-STAT ESTIMTE T-STAT

INTERCEPT

AGE

EXPERIENCE

SCWWL ING

=TH

SHSA

MO CNILDREN

WE CNILO

TW CHILOREM

YEASS WT IN PAST FIK

0,9418

-0.0119

0.0025

0.0979

-0.3772

0.1623

0.1%9

-0.0675

o.m3

1.lM

-0.564

0.533

S.S37

-5.419

2.145

1.739

-0.571

1.069

0.7013

-0.W9

-o.om3

0.1215

-o.2m

0.1s17

-0.1062

0.W2

-0.wm

.::E

-0.451

-;:

-o:m7

0.613

-0.418

1.7197

-0.0331

0.0352

0.M19

-0.1935

O.lla

-0.0635

0.0239

-0.1761

2.431 ~

-1.7s2

5.W

7.377

-3.247

1.7M,

-0.m

0.318

-2.6s9

1.1126

-0.0052

-0.0W2

O.lw

-0.3241

0.1337

-0.1439

0.1144

-o.02n

.o.m7

0.940

-0.164

-1.236

b.394

-3.319

1.403

.0.979

0.s72

-0.243

.2.5W

1.7759

-0.0289

0,0267

0.0757

-0.2132

0.1349

-0.0777

0.0191

-0.15T2T

-0.E09

2.52S

-1.554

3.561

6.592

-3.551

2.on

.0.904

o.a7

-2.402

-1.914

Adjwtd R-~rc 0.5527 0.4s49 0.4228

s~le Size 13s 113 1s3

oat Mean 1.4559 1.7498 1.W15

0.5115

113

1.749s

0.4314

1s5

1.M15
Tab[e 8-5

Determinants of Lw Wages, Aws 40-44

VARIABLE

1%7 (a) 1972 (a)

PARAWETER PAR~ETER

EST~WTE T-STAT ESTIMATE

INTERCEPT

AGE

EXPERIENCE

SCHmLIWG

~TH

SMSA

kO CHILDREM

WE CHILD

1~ CNILDREN

YEARS ml IN PAST

Adjustd R-S~are

5qLe Size

Oe-t Mean

-0.0517 -0.876

0.0307 2.285

0.0119 3.900

O.M, 8.727

-0.0814 -1.s58

0.1147, 2.577

0.1279 2.116

-0.0035 -0.058

0.1240 2.552

FIVE

0.3231

329

1.8152

2.1714

-0.0303

0.0189

0.0610

-0.0708

0.1119

0.0017

0.1W8

0.0279

0.2575

53b

1.9589

1977 (a)

PARAHETER

T-STAT ESTINATE

3.647 z.0327

-2.198 -0.0355

5.436 0.0228

7.37b 0.0005

-1.654’ .0.0911

2.644 0.1125

0.024 0.0049

1.365 0.0s37

0.616 -0.0080

0.3134

235

1.97s0

0.2807

336

1.9389

T-STAT

3.W1

-2.222

3.497

b.M9

-1.782

2.707

0.429

1.5W

0.567

-3.393

7977 (b)

PAWETER

EST~WTE

1.93s6

-0.02s7

0.0144

0.0747

-0.0743

0.1498

o.04az

0,0891

0.Ooa

-0.om

T-STAT

z.72a

-1.M9

2.895

7.137

-1.4n”

z.a77

0.655

1.015

0.035

-3.470

0.3453

1.9%

BLACK ~EN

VARIASLE

1967 (a) 1972 (a) 1977 (a) 1972 (b)

PAR*ETER

1977 (b)

PARAMETER PARAMETER PARMETER

ESTIWTE T-STAT

P~ETER

ESTIWTE T-STAT ESTIMATE T-STAT ESTIMTE T-STAT ESTIMTE T-STAT

tNTEkCEPT

AGE

EXPERIENCE

SC~LING

SWTH

SMSA

MO CHILOREN

NE CNILD

TW CNlLDREN

YEARS WI IM

0.7106

-0.Ol?b

0.0151

0.W70

-0.2783

0.1303

0.M78

-0.0250

0.700

-0.490

3.1s8

9.50s

-3.629

1.653

0.731

-0.na

0.2012

0.0140

0.W07

o.0s74

-0.3346

0.2537

0.2011

-0.1811

0.205

0.614

0.151

7.985

-4.547

3.439

1.E2

-1.370

PAST I:Ivz

2.96s 0.0825 0.970

Adjmtd R-Xre 0.5141

se~le Size 152

De~tient Mean 1.4533

0.5104

136

1.7127

-1.8349

0.D704

-0.0f42

0.0702

-0.05W

0.3330

-0.1349

0.071?

O.MI1

-1.451

2.338

-2.159

4.644

-0.624

3.677

-0.912

0.518

0.593

0.2041

0.0138

0.000a

0.0875

-0.3350

0.2539

0.2014

-o.lalo

0.W6

0.44W

1.88::

0.0015

O.ZM

0.597

0.157

7.no

-4.51b

3.425

1.746

-1.372

0.%

0.053

.1.9695

0.0722

-0.0136

0.0728

-0.0479

0.3427

-0.1s47

0.0646

0.03!1

O.ozu

-1.53a

2.3W

-2.061

4.6~’

-0.491

3.735’

-0.ws

0.468 ;

0.491

o.n8

0.5065

13b

1.7127

0.4453

1.d
lsb(eB-6

Detemimnts of La Ua$-, Ages 45-49

1972 (a) 1977 (a) 19U (a)

PAMTER PAMETER PAWTER

ESTINATE T-STAT ESTIUTE T-STAT ESIIMTE T-STAT

1~ (b)

PARAMETER

ESTl~TE T-STAT

1977 (b)

PAWETER

ESTINATE T-STAT

lW (b)

PAWETER

ESTIMTE

3.0.’?:

-0.osm

0.0177

O.mo

-0.0314

0.19T4

-0.1226

-o.m%

o.m5f

-0.0055

VARIABLE T

lNIERCEPT

AGE

EXPERIENCE

SC~ING

SWTH

w%

NO CHILOREN

mE CHILO

7W CNILOREN

YEARS @T IN PAST FIVE

0.9644

-0.0041

0.0151

0.0731

-0.M14

o.m%

0.0702

0.0212

0.0325

1.534

-0.3W

5.477

9.533

-1.918

1.431

l.om

0.360

0.694

1.7s03

-0.0217

0.0200

0.0634

-0.0705

0.133s

2.4M

-1.426

S.&

-::%

2.856

2.~26

-0.0549

0.0244

0.0d76

-0.0331

0.lUO

-0.1614

-0.ww

O.w

3.239

-2.mb

5.530

7.521

-0.59T

3.173

-t.73b

-0.929

0.672

1.2359

-0.oul

O.olm

0.0702

-0.GOS4

0.0631

O.w

0.0125

0.0407

-0.053s

1.9s2

-0.b70

3.693

8.097

-2.114

1.5W

1.393

0.216

O.ml

-3.523

1.7942

-0.020s

O.olm

0,0618

2.bS2

-T.36s

4.m

6.743

.1.497

2.911

1.7M’

0.673

0.U3

-1.247

3

-2

:

-o

3

-

-0

0

-o.oml

0.1364

0.1318

0.0532

0.0426

-0.m

0.12b5

0.0485

0.0425

1.67f

0.614

0.031

-3

Adjwtd R-~re 0.3264

S~le Size

O-t Hean T.9&7

0.3152

z.o~:

O.zmo

261

1.W38

0.3473

1.9;;

0.31M

250

2.0259

0.3001

261

1.993s

8LACK WEN

1972 (a) 1977 (a) 1W2 (a) 1972 (b) 1977 (b) 19S2 (b)

PMETER PAWETER PMETER PWETER PA~ETER PAWTER

VARIABLE ESTINATE T-STAT ESTIMTE T-STAT ESTIUTE T-STAT ESTIWTE T-STAT ESTINATE T-STAT EST[UTE T

INTERSEPT o.7m3 ~ 5s4

AGE -0.0021 d.oT3

o.ooa3

).1167

;.u016

1045

~~m29

0.1302

-0.00;

-0.010>

0.0W3

0.744

::%

-5.002

-::E

.0.082

-0.5373

-::W

O.moa

-0.2153

0.2007

0.0652

-0.0397

-0.1622

-0.339

1.016

.0.!%

k.

0.4251

0.0007

O.oom

O.lobo

-0.3120

0.1716

-0.0557

-0.0s23

0.321

0.024

l.m

8.579

-3.544

1.s46

-0.473

-0.877

0.07s4

0.0163

0.0005

0.1022

-0.3850

0.1372

0.0012

0.0094

0.0217

-0.0170

0.071

0.722

O.lw

8.b53”

-5.002

1.069

0.011

0.069

0.2M

-o.4m

-0.0619

o.04m

-0.0114

0.0772

-0.2327

0.2265

0.0340

-o.m87

.O.19W

-0.30M

-0

1

-1

4

-2

2

0

-0

-1

-2

EXPERIENCE 0.004s 0.973

SCH~ING 0.W64 8.627

SWTH -0.3126 -3.530

SMBA 0.1652 1.769

NO CHILDREN -0.= -0.407

-i:ob,

1.927

0.413

.0..-,

-1.35.

HE CNILO -o.om9 -0.M9

Tm CNILOREN 0.0719 O.aba

YEARS WT IN PAST FIW

O.OWb 0.115 0.0738

0.W4

O.w

1.5M

Adjmtsd R-*PG 0.453s O.mol 0.W2 0.45W

s@le size 137 109

0.5970 0.4406

a5 137

D-t neon

53

1.69= 1.S27b 1.9101 1.b93S 1.4% 1.9101
TabLe B-7

Determinants of Log Hag=, Ages 50-54

NON BLACK ~EH

1977 (a)

PARAMETER

VARIABLE ESTINATE

INTERCEPT 1.8%9

AGE -0.0240

EXPERIENCE 0.0140

scNmLIMG O.wo

SWTN -0.0413

*SA 0.0%1

NO CNILDSEN 0.01%

OWE CHILO 0.0173

TW CNILDREN 0.0103

YEAAS WT IN PAST FIW

AdJmt4 R-S~are 0.3408

S8~[e Size 257

oe~timt Mean 2.0273

T-STAT

2.179

-1.445

4.173

9.159”

-0.762

1.891

0.269

0.234

O.la

1982 (a)

PARANETER

ESTINATE T-STAT

1977 (b)

PARMETER

ESTIMTE T-STAT

1982 (b)

PAMETER

EsT[wTE l-STAT

2.07S5

-0,0313

0.0205

0.0742

O.obol

0.2062

O.oal

O.OIM

-0.0207

0.2795

246

1.9852

2.257

-1.815

6.022

6.250

1.07a

3.910

0.791

0.178

1.9873

-0.0247

0.0124

0.0809

-0.0410

0.W60

0.0315

0.0240

-0.346 0.0128

-0.0372

2.2n

-1.4m

3.4M

9.002

-0.7571

1.s92

0.431

0.320

0.210

-1.269

2.287s

-0.0322

0.0158

0.0710

0.04=

0.2175

0.1033

0.0306

-0.0141

-0. 07b7

2.510

-1.893

4.2W

6.o31

0.876

4.16s

1.203

0.327

-0.23s’

-2.75s

0.3424

257

2.0275

0.2W1

1.9:$

VARIABLE

1977 (a) 1982 (a) 1977 (b) 1982 (b)

PARAHETER PARANETER PARANETER PAR~TER

ESTINATE T-STAT ESTI~TE T-STAT ESTIWTE T-STAT ESTl~TE T-STAT

IMTERCEPT 2.7a74 1.916

AGE -0.0416 -1.522

ExPERIENCE 0.0083 f.463

SCNWLI WG o.oa42 7.M

SWTH -0.2028 -2.la7

SMSA 0.1%9 1.92a

HO CHILOREN -0.0227 -0.1%

ONE CHILO -o.04a7 -0.46s

Tw CNILOREN o.04ti o.41a

YEARS WT IW PAST FIVE

Adlust*, R-aware 0.4504

sn~le Size

O@nt Mean 1.A?

2.a134

-0.0335

-0.0014

0.0732

-0.3381

0.1172

0.1333

0.3489

0.0943

0.5015

101

1.7532

2.254

-1.424

-0.324’

6.231

.4.lob

1.477

1.129

2.63

1.106

2.7757

-0.0414

0.0084

0.0843

-0.2031

0.1844

-0.0222

-0.0406

0.0471

0.002s

l.ml

-1.500

1.443

7.562

-2.176

1.906

-0.189

-0.4b5

0.419

O.obo

2.6M

-0.02ss

-0.0057

0.0715

-0.3271

0.1453

o.12al

O.m

0.1025

-0.11%

2.25b

-1.276

-1.322’

6.345

-4.143

1.a9a

1.132

2.935

1.253

-3.035

0.4449

1oa

1.7849

0.3423

101

1.7332