Arindrajit Dube

About

Arindrajit Dube is the Provost Professor of Economics at the University of Massachusetts Amherst. His research focuses on labor economics, health economics, public finance, and political economy. His current areas of research include wage inequality, the importance of labor market competition, minimum wage effects on employment and inequality, the role of fairness concerns at the workplace, the interplay of behavioral biases and labor market power, the impact of unemployment benefits, and the role of firm wage policies in explaining the growth in inequality. Dube has also conducted research on employer health mandates, unions and collective bargaining, outsourcing and sub-contracting, gun laws and violence, and the capitalization of private information in stock prices. He received his B.A. in Economics and M.A. in Development Policy from Stanford University, and his Ph.D. in Economics from the University of Chicago. He has previously held positions as a Visiting Professor at the MIT Department of Economics and Boston University's Questrom School of Business. Dube is a research associate at the NBER, a research fellow at IZA, and a research affiliate of the MIT Stone Center on Inequality and Shaping the Future of Work.

Research topics

• Economics
• Microeconomics
• Labour economics
• Political Science
• Econometrics

Selected publications

• Monopsony in Online Labor Markets

  American Economic Review Insights · 2020 · 206 citations

  1st authorCorresponding

  Despite the seemingly low switching and search costs of on-demand labor markets like Amazon Mechanical Turk, we find substantial monopsony power, as measured by the elasticity of labor supply facing the requester (employer). We isolate plausibly exogenous variation in rewards using a double machine learning estimator applied to a large dataset of scraped MTurk tasks. We also reanalyze data from five MTurk experiments that randomized payments to obtain corresponding experimental estimates. Both a…

  DOI

• The Unexpected Compression: Competition at Work in the Low Wage Labor Market

  National Bureau of Economic Research · 2023-03-01 · 129 citations

  report

  Labor market tightness following the height of the Covid-19 pandemic led to an unexpected compression in the US wage distribution that reflects, in part, an increase in labor market competition. Rapid relative wage growth at the bottom of the distribution reduced the college wage premium and counteracted approximately one-quarter of the four-decade increase in aggregate 90-10 log wage inequality. Wage compression was accompanied by rapid nominal wage growth and rising job-to-job separations - es…

  PublisherDOI

• A Local Projections Approach to Difference-in-Differences

  National Bureau of Economic Research · 2023-04-01 · 92 citations

  reportOpen access1st authorCorresponding

  We propose a local projections (LPs) based difference-in-differences approach that subsumes many of the recent solutions proposed in the literature to address possible biases arising from negative weighting. We combine LPs with a flexible ‘clean control’ condition to define appropriate sets of treated and control units. Our proposed LP-DiD estimator can be implemented with various weighting and normalization schemes for different target estimands, can be extended to include covariates or accommo…

  PublisherDOI

• Monopsony in Movers

  The Journal of Human Resources · 2021 · 77 citations

  We estimate the impact of the firm component of hourly wage variation on separations from matched Oregon employer-employee data. We use both firm fixed effects estimated from a wage equation as well as a matched IV event study around employment transitions between firms. Separations decline with firm wage policies: the implied firm-level labor supply elasticities are around 4, consistent with recent quasiexperimental evidence, but 3 to 4 times larger than existing estimates using individual wage…

  DOI

• A Local Projections Approach to Difference-in-Differences Event Studies

  SSRN Electronic Journal · 2023-01-01 · 63 citations

  articleOpen access1st authorCorresponding
  PublisherDOI

Frequent coauthors

• Attila Lindner

  University College London

  143 shared

• Suresh Naidu

  114 shared

• Ben Zipperer

  112 shared

• Doruk Cengiz

  107 shared

• Ethan Kaplan

  99 shared

• Michael Reich

  29 shared

• Siddharth Suri

  19 shared

• Jeff Jacobs

  Columbia University

  18 shared

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