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ZVI ECKSTEIN |
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RESEARCH AND PUBLICATIONS HOUSEHOLD INTERACTION and the LABOR
SUPPLY of MARRIED WOMEN ZVI ECKSTEIN and OSNAT LIFSHITZ
Data and Estimation (section 3) - PSID Data The data is based on the PSID survey
(Panel Study of Income Dynamics) during the years 1983-1993. The yearly
source files were downloaded from http://psidonline.isr.umich.edu.
From each file we kept and/or calculate the model variables, using the
following do file (create85.do). We choose to use quarterly data which is
available only from 1983 (the data is available on a monthly frequency, and
we created the quarterly data using the do file: mon_to_q.do).
We restrict the model for the first ten years since marriage. In order to
give similar initial conditions to all individuals, we restrict the data, as
in the model, to start at the date of marriage and we consider all married
couples during the years 1983-1984. The file (PSID.dta)
contains details on 863 couples and follows them until 1993 or until they are
separated. 36.3% of the couples are divorced or separate during the sample
period; 14.5% leave the sample from other reaons, such that after 10 years
49.2% of the couples remain in the sample (Descriptive statistics and reduced form estimation of
the model's equation, including tables 1 and 2 in the
paper). The data contains individual and
household demographic information and labor supply, such as, wage, working
hours, unemployment and non-participating in the labor force. The
participation rate of women in the sample is 72% in 1984, and climbs up to
79% after 10 years of marriage. Note that the participation rate of married
women, aged 25-55, in the year 1984 was 66% according to CPS data. The unemployment
rate falls from 6% to 3.1% during those years. The participation rate of men
in the sample is 93% and constant in time. Note that using the CPS data this
rate among men aged 25-55 in the year 1984 was 93.9%. The unemployment rate
decreased from 9% in 1984 to 3.6% in 1993. In addition, the income data and
working hours in the sample is comparable to that in the CPS. Estimation Results (section 4)
Counterfactuals (section
5)
CPS Data, variables and sample
restriction for Table 1 Data was taken
from the Annual Demographic Surveys (March CPS supplement) conducted by the
Bureau of Labor Statistics and the Bureau of the Census. This survey is the
primary source for detailed information on income and work experience in the
United States. A detailed description of the survey can be found at www.bls.gov/cps. Our data, for the years 1962-2007,
was extracted using the Unicon CPS utilities. The sample
is restricted to civilian adults, ignoring armed forces and children. We
divided the sample into five education groups: high school dropouts (HSD),
high school graduates (HSG), individuals with some college (SC), college
graduates (CG) and post-college degree holders (PC). In order to construct
the education variable, until 1991 we used the years of schooling completed
and added 0.5 years if the individual did not complete the highest grade
attended and from 1992 we used years of schooling as is. Weekly wages
are constructed by taking the previous year’s wage and salary income and
dividing it by the number of weeks worked in the previous year. Hourly wages
are defined as the weekly wage divided by the number of hours worked in the
previous week in all jobs, while annual (annualized) wages are defined as the
weekly wage multiplied by 52. Wages are multiplied by 1.75 for top-coded
observations until 1995. Nominal wages are deflated using the Personal
Consumption Expenditure (PCE) index from NIPA table 2.3.4 (http://www.bea.gov/iTable/iTable.cfm?ReqID=9&step=1).
Since wages refer to the previous year, we use PCE for year X-1 for
observations in year X and therefore all wages are expressed in constant 2006
dollars. Information
on number of children under six for the period 1968 - 1975, which is missing
from the survey data, is completed where possible using the distribution of
this variable in 1967 and 1976 for each gender, marital status and cohort
separately. The completed information can be used to construct an aggregate
trend, but not to identify the number of children for a specific individual. In order
to construct couples, we kept only heads of households and spouses (i.e. no
secondary families were used) and dropped households with more than one male
or more than one female. We then merged women and men based on year and
household id and dropped problematic couples (with two heads or two spouses,
with more than one family or with inconsistent marital status or number of
children). |
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