A Quantile Regression Approach to Examine Changes in County Unemployment Rates in Indiana during the Great Recession

Abstract

We take a closer look at changes in county unemployment rates in Indiana during the Great Recession and evaluate how local population and the mix of sectoral employment influence these patterns. Using a quantile regression approach, we specifically observe the impacts on counties on both tails of the changes in unemployment distribution. We find the impact of sectoral composition of a county’s workforce depends on its geographical classification. Overall, greater reliance on pro-cyclical industries, most notably manufacturing, magnifies the increases in unemployment during the recession. This effect is further amplified for MSA counties. In contrast, counter-cyclical industries, education in particular, insulates the counties in the top 10th percentile of the distribution of changes in unemployment rates, and a stronger insulation effect is observed for MSA counties. At the bottom 10th percentile, education marginally amplifies changes in unemployment rates for MSA counties, whereas it insulates non-MSA counties from the same distribution.