Inequality in the Evolving Labor Market
Paper Session
Saturday, Jan. 7, 2017 3:15 PM – 5:15 PM
Hyatt Regency Chicago, Crystal C
- Chair: Kevin Lang, Boston University
Survival of the Fittest: The Impact of the Minimum Wage on Restaurant Exit
Abstract
Recent years have witnessed sharp increases in the minimum wage across a number of cities in the United States - some larger than increases that have historically been studied. While higher minimum wages have the potential to causes small businesses to exit the market, prior research has shown minimal overall employment effects. <br /><br /><br /><br /><br /><br />
To shed new light on the impact of minimum wage increases, we combine entry and exit data with ratings and demand data from Yelp.com. We find that looking at the average impact of minimum wage on business outcomes masks important heterogeneity. Increases in the minimum wage have little effect overall, but have large effects on the worst quality restaurants (as measured by their Yelp ratings), which are driven to exit by these increases. We provide evidence that this is because low quality restaurants are already closer to the margin of exiting (at any wage level). <br /><br /><br />
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We then look at the changes in demand and quality after minimum wage increases. Controlling for restaurant fixed effects, we find that average Yelp ratings increase after the passage of a higher minimum wage. Further, we see no evidence of declines in restaurant going (as measured by reservation and delivery data), suggesting that diners are shifting from worse to better restaurants after the increase in minimum wage. We discuss implications for consumer welfare and employment.
Price Floors and Preferences: Evidence From a Minimum Wage Experiment
Abstract
Firms posting job openings in an online labor market were randomly assigned minimum hourly wages. When facing a minimum wage, firms hired fewer workers but paid those they did hire a higher wage. However, the reduction in hiring was not large, even at the highest minimum wage imposed. In contrast, minimum wages substantially reduced hours-worked, across cells. Firms facing a higher minimum wage also hired more productive workers, which can explain, in part, the reduction in hours-worked: with more productive workers, projects were simply completed in less time. This labor-labor substitution margin of adjustment would presumably be less effective in equilibrium, if all firms sought out more productive workers. However, using the platform’s imposition of a market- wide minimum wage after the experiment, I find that many of the experimental results also hold in equilibrium, including the labor-labor substitution towards more productive workers.LINK to paper: <a href="http://john-joseph-horton.com/papers/minimum_wage.pdf">http://john-joseph-horton.com/papers/minimum_wage.pdf</a>
An Experiment in Hiring Discrimination via Online Social Networks
Abstract
We investigate whether personal information posted by job candidates on social media sites is sought and used by prospective employers. We create profiles for job candidates on popular social networks, manipulating information protected under U.S. laws, and submit job applications on their behalf to over 4,000 employers. We find evidence of employers searching online for the candidates. After comparing interview invitations for a Muslim versus a Christian candidate, and a gay versus a straight candidate, we find no difference in callback rates for the gay candidate compared to the straight candidate, but a 13% lower callback rate for the Muslim candidate compared to the Christian candidate. While the difference is not significant at the national level, it exhibits significant and robust heterogeneity in bias at the local level, compatible with existing theories of discrimination. In particular, employers in Republican areas exhibit significant bias both against the Muslim candidate, and in favor of the Christian candidate. This bias is significantly larger than the bias in Democratic areas. The results are robust to using state- and county-level data, to controlling for firm, job, and geographical characteristics, and to several model specifications. The results suggest that 1) the online disclosure of certain personal traits can influence the hiring decisions of U.S. firms and 2) the likelihood of hiring discrimination via online searches varies across employers. The findings also highlight the surprisingly lasting behavioral influence of traditional, offline networks in processes and scenarios where online interactions are becoming increasingly common.Discussant(s)
Hilary Hoynes
, University of California-Berkeley
Laura Gee
, Tufts University
Dominic Coey
, Facebook
Kevin Lang
, Boston University
JEL Classifications
- J0 - General