{"title":"大衰退期间印第安纳州县失业率变化的分位数回归方法","authors":"Arundhati Srinivasan, Kathryn G. Arano","doi":"10.52324/001c.11094","DOIUrl":null,"url":null,"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.","PeriodicalId":44865,"journal":{"name":"Review of Regional Studies","volume":null,"pages":null},"PeriodicalIF":0.6000,"publicationDate":"2019-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Quantile Regression Approach to Examine Changes in County Unemployment Rates in Indiana during the Great Recession\",\"authors\":\"Arundhati Srinivasan, Kathryn G. Arano\",\"doi\":\"10.52324/001c.11094\",\"DOIUrl\":null,\"url\":null,\"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.\",\"PeriodicalId\":44865,\"journal\":{\"name\":\"Review of Regional Studies\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.6000,\"publicationDate\":\"2019-11-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Review of Regional Studies\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.52324/001c.11094\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"ECONOMICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Review of Regional Studies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.52324/001c.11094","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ECONOMICS","Score":null,"Total":0}
A Quantile Regression Approach to Examine Changes in County Unemployment Rates in Indiana during the Great Recession
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.