Data and Methods: Micro data are taken from the General Social Surveys (GSS) of the National Data Program for the Social Sciences. GSS provides data on Government economic policy, inflation and unemployment, as well as individual data on labor force participation, family, education, health, and other variables germane to labor force participation decisions. Using a probit (logit) model I estimate the probability that an individual will be unemployed as a function of differences in individual specific, industry specific, and labor force variables using peak employment prior to the 2001 recession as base year for comparison.
Expected Results: Probit estimates yield four sources of unemployment; [1] Size of the labor force, [2] Industrial distribution of the labor force, [3] Sex-specific industry unemployment rates, and [4] Number of new entrants into the labor force. Changes in one of the above sources provides the independent effect on unemployment controlling for other effects. By decomposing the changes in unemployment I anticipate [2] to reflect changes brought about by structural changes in industrial composition of the labor force while [3] reflects the impact of sex-specific unemployment by industry and [4] reflects the impact of new entrants into the labor force in the unemployment rate.
Discussion: During the recessions of 2001 and 2008-2009 the rates of unemployment for men exceeded those of women. Conventional wisdom holds that higher unemployment rates among men can be explained by their employment within industries most susceptible to cyclical downturn while women are employed in more "recession proof" industries. Yet differential rates of unemployment between men and women cannot be explained solely by changes within industry distribution of men and women in the labor force. An empirical investigation of relative unemployment of men and women over the business cycle can provide a greater understanding of the nature of unemployment by controlling for changes in the size of the labor force as well as changes in sex-specific unemployment rate.