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DYNAMIC FEMALE LABOR SUPPLY

ZVI ECKSTEIN and OSNAT LIFSHITZ

The Walras-Bowley Lecture, Econometric Society Meeting, June 19, 2008 Pittsburgh, USA

Paper

Econometrica, Vol. 79, No. 6, November 2011.

Presentation

The rise in US GDP per capita (section 1)

Ø GDP analysis	do file	(including Figure 1.1 in the paper)
Ø Details of the calculations

Main Facts and the Literature (section 2)

We present a complete set of the figures created during this project, including figures that do not appear in the paper, together with the code used to construct them. Note that the Excel files include hidden worksheets containing the data.

Ø participation, employment and hours trends	do file	(including Figure 1.2 in the paper)
Ø education trends and effects	do file	(including Figures 2.1, 2.2 in the paper)
Ø wage trends	do file	(including Figure 2.3 in the paper)
Ø fertility and marital status trends	do file	(including Figures 2.4, 2.5 in the paper)
Ø cohort effect - employment (grouped cohorts)	do file	(including Figure 2.6 in the paper)
Ø cohort effect - participation	do file
Ø cohort effect - employment	do file
Ø cohort effect - hours	do file
Ø cohort effect - education	do file
Ø households participation, employment, hours and wage trends	do file
Ø assertive mating	do file
Ø cohort effect - households participation	do file
Ø cohort effect - households employment	do file
Ø cohort effect - households hours	do file
Ø cohort effect - households wages	do file
Ø husband’s wage effect	do file

Data and Estimation (section 4)

Ø code for constructing moments and education distribution	For details see Appendix D in the paper.
Ø code for constructing husbands’ moments	For details see Appendix C in the paper.
Ø code for constructing aggregated moments

Estimation Results for the 1955 Cohort (section 5)

Ø estimated parameters	(including Tables 5.1, B.5 in the paper)
Ø model fit - 1955 cohort	(including Table 5.2 and Figures 5.1, 5.2, 5.3 in the paper)

Accounting for the Increase in Female Employment (section 6)

Ø the increase in female employment – Dynamic Model	(including Tables 6.1a, 6.2, 7.1 in the paper)
Ø the increase in female employment – Static Model	(including Table 6.1b)
Ø the increase in female employment – Heckman Model	(including Table 6.1c)
Ø robustness tests for the order of the simulations – Dynamic model: o Schooling, wages, martial status and fertility: no change in initial condition o Wages + initials, schooling, fertility, martial status o Wages + initials, fertility, schooling, martial status o Wages + initials, fertility, martial status, schooling o Schooling + initials, wages, martial status, fertility	For details see pages 26-27 in the paper.

Changes by Cohort and Aggregate Fit (section 7)

Ø changing α1 and α41 for all cohorts	(including Figures 7.1a,b in the paper)
Ø aggregate fit	(including Table 7.2 and Figure 7.2 in the paper)

CPS Data, variables and sample restriction

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.census.gov/cps/ads/adsmain.htm. 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/national/nipaweb/index.asp). 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).

Ø list of extracted variables

Ø code for constructing the file used in the paper

Ø code for completing missing children data

Ø code for matching couples