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Measuring the Impact of Living Wage Laws: A Critical Appraisal of David Neumark's How Living Wage Laws Affect Low-Wage Workers and Low-Income Families
Author(s) -
Mark Brenner,
Jeannette WicksLim,
Robert Pollin
Publication year - 2003
Publication title -
ssrn electronic journal
Language(s) - English
Resource type - Journals
ISSN - 1556-5068
DOI - 10.2139/ssrn.341762
Subject(s) - affect (linguistics) , wage , living wage , law , economics , labour economics , demographic economics , sociology , political science , communication
Drawing on data from the Current Population Survey (CPS), David Neumark (2002) finds that living wage laws have brought substantial wage increases for a high proportion of workers in cities that have passed these laws. He also finds that living wage laws significantly reduce employment opportunities for low-wage workers. We argue, first, that by truncating his sample to concentrate his analysis on low-wage workers, Neumark's analysis is vulnerable to sample selection bias, and that his results are not robust to alternative specifications that utilize quantile regression to avoid such selection bias. In addition, we argue that Neumark has erroneously utilized the CPS data set to derive these results. We show that, with respect to both wage and employment effects, Neumark's results are not robust to more accurate alternative classifications as to which workers are covered by living wage laws. We also show that the wage effects that Neumark observes for all U.S. cities with living wage laws can be more accurately explained as resulting from effects on sub-minimum wage workers in Los Angeles alone of a falling unemployment rate and rising minimum wage in that city. ACKNOWLEDGEMENTS: We wish to thank David Neumark for providing us with the original data base and program files for his 2002 study. We are grateful to Jared Bernstein of the Economic Policy Institute, David Fairris of UC-Riverside, Peter Hall of UC-Berkeley, and Larry Katz of Harvard University for their detailed, perceptive comments on a previous draft. We especially acknowledge our University of Massachusetts colleague Michael Ash for his commitment and ongoing insights, which have been a major assistance throughout this project.

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