Title

Effects of Temporary Agencies on Poverty Change

Presenter Information

Russell Ulrich-Strickland

Document Type

Oral Presentation

Location

Higher Education Center Bldg 29 - Des Moines Center

Start Date

19-5-2015

End Date

19-5-2015

Keywords

Poverty, Temporary Work and Statistical Modeling

Abstract

The temporary help services industry is doing exceptionally well, but is it doing any good? Previous research on the temporary help services industry tends to fall into two basic categories: 1) research by mainstream labor economists emphasizing the beneficial effects of the industry for workers and consumers of temp labor; or 2) analyses by radical labor economists and sociologists that, in contrast, emphasizes the vulnerability of the temp industry workforce to direct economic exploitation, and employers’ use of temp labor to bust permanent workers’ labor unions. Some sociological research has examined the temporary services industry in the context of the welfare reform legislation of the late 1990s, arguing that the dominant narrative of the success of Personal Responsibility and Work Opportunity Act needs to be reconsidered in light of evidence that large numbers of former Temporary Assistance for Needy Families recipients have transitioned from welfare-to-temp work. Our research extends this line of inquiry with an investigation of the relationship between the temp services industry and local level poverty rates and welfare spending. To some extent, our analysis ais inspired by research by Goetz and Swaminathan on the local-level effects of Walmart stores and store openings on poverty rates. In a similar vein, we ask whether changes in the local density and size of the temporary help services industry predict subsequent changes in local poverty rates and local government welfare spending. We analyze these relationships in all counties in the contiguous United States between 2002 and 2007, and include controls for potentially confounding variables, and corrections for endogeneity and spatial dependence. Methods: Using a two-stage regression model, we use a similar method to Goetz and Swaminathan to show the year-to-year change of temporary help service agencies which helps to reduce potential endogeneity bias in the poverty-change equation.

Poster Number

3

Faculty Mentor(s)

Michael Mulcahy

Department/Program

Sociology

Additional Mentoring Department

Sociology

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May 19th, 2:00 PM May 19th, 5:30 PM

Effects of Temporary Agencies on Poverty Change

Higher Education Center Bldg 29 - Des Moines Center

The temporary help services industry is doing exceptionally well, but is it doing any good? Previous research on the temporary help services industry tends to fall into two basic categories: 1) research by mainstream labor economists emphasizing the beneficial effects of the industry for workers and consumers of temp labor; or 2) analyses by radical labor economists and sociologists that, in contrast, emphasizes the vulnerability of the temp industry workforce to direct economic exploitation, and employers’ use of temp labor to bust permanent workers’ labor unions. Some sociological research has examined the temporary services industry in the context of the welfare reform legislation of the late 1990s, arguing that the dominant narrative of the success of Personal Responsibility and Work Opportunity Act needs to be reconsidered in light of evidence that large numbers of former Temporary Assistance for Needy Families recipients have transitioned from welfare-to-temp work. Our research extends this line of inquiry with an investigation of the relationship between the temp services industry and local level poverty rates and welfare spending. To some extent, our analysis ais inspired by research by Goetz and Swaminathan on the local-level effects of Walmart stores and store openings on poverty rates. In a similar vein, we ask whether changes in the local density and size of the temporary help services industry predict subsequent changes in local poverty rates and local government welfare spending. We analyze these relationships in all counties in the contiguous United States between 2002 and 2007, and include controls for potentially confounding variables, and corrections for endogeneity and spatial dependence. Methods: Using a two-stage regression model, we use a similar method to Goetz and Swaminathan to show the year-to-year change of temporary help service agencies which helps to reduce potential endogeneity bias in the poverty-change equation.