from the Chicago Fed
— this post authored by Mariacristina De Nardi and Sharada Dharmasankar
Women contribute a large fraction of aggregate labor hours, earnings, and labor force participation. Yet, many models used to study the effects of government policy ignore gender differences and use data on men only. These models are used extensively for examining the effects of government policies and programs – including Social Security, taxation, and welfare programs.
Before evaluating how people respond to such policies, it is important to construct a reliable model of how people behave and why.
The exclusion of women from models aimed at understanding reality and the consequences of policy likely undermines the credibility of the lessons that we learn from these models.
A model’s credibility is heavily dependent on how well it reproduces key features of the data, including aggregate earnings, hours, and output. Constructing a model that accurately estimates these aggregates will likely yield more reliable predictions of how people react to changes in the economic environment, such as changes in wages and taxes. Because women now participate extensively in the labor market, the exclusion of women from models aimed at understanding reality and the consequences of policy likely undermines the credibility of the lessons that we learn from these models.
This Chicago Fed Letter summarizes research from several papers related to these issues. Borella, De Nardi, and Yang (BDY)1 study the cohort of households born in 1941 – 45 using the Panel Study of Income Dynamics (PSID). This cohort has by now completed its working period and has retired, and thus constitutes a useful benchmark. BDY first quantify the labor supply of women, including the fraction of total hours, earnings, and participation by women. Second, they show that the aggregate patterns of hours, earnings, and participation over the life cycle depend on gender and marital status.
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Source
http://app.frbcommunications.org/e/er?s=1064 &lid=4692 &elqTrackId=75a5a7cf84f04a788a689d30d7f3c610 &elq=c9122df688664036a7dc9afaac4dc1f2 &elqaid=11865&elqat=1