BenHyman.jpg

Welcome! I am an applied microeconomist at the Federal Reserve Bank of New York with interests in public finance, labor economics, urban economics, and international trade. I received my Ph.D. in Applied Economics from the Wharton School, University of Pennsylvania, and hold a Masters in Urban and Regional Planning from the Massachusetts Institute of Technology, as well as a B.A. (Honors) from the University of Southern California. Prior to joining the Fed, I was the George Tolley visiting fellow at the Becker-Friedman Institute at the University of Chicago.

Contact: ben.hyman@ny.frb.org

CV: link

Google Scholar: link


RESEARCH

"Can Displaced Labor be Retrained? Evidence from Quasi-Random Assignment to Trade Adjustment Assistance"
Latest Draft (November, 2018)SSRN Draft (January, 2018)

Abstract. The extent to which workers adjust to labor market disruptions in light of increasing pressure from trade and automation commands widespread concern. Yet little is known about efforts that deliberately target the adjustment process. This project studies 20 years of worker-level earnings and re-employment responses to Trade Adjustment Assistance (TAA)—a large social insurance program that couples retraining incentives with extended unemployment insurance (UI) for displaced workers. I estimate causal effects from the quasi-random assignment of TAA cases to investigators of varying approval leniencies. Using employer-employee matched Census data on 300,000 workers, I find TAA-approved workers have $50,000 greater cumulative earnings ten years out—driven by both higher incomes and greater labor force participation. Yet annual returns fully depreciate over the same period. In the most disrupted regions, workers are more likely to switch industries and move to labor markets with better opportunities in response to TAA. Combined with evidence that sustained returns are delivered by training rather than UI transfers, the results imply a potentially important role for human capital in overcoming adjustment frictions.

"When do Firms Go Green? Comparing Command and Control Regulations with Price Incentives in India" with Ann Harrison, Shanthi Nataraj, and Leslie Martin 
Latest Draft (October, 2019)NBER Version (November, 2015)

Abstract. There are two commonly accepted views about command-and-control (CAC) environmental regulation. First, CAC delivers environmental outcomes at very high cost. Second, in a developing country with weak regulatory institutions, CACs may not even yield environmental benefits: regulators can force firms to install pollution abatement equipment, but cannot ensure that they use it. We examine India’s experience and find evidence that CAC policies achieved substantial environmental benefits at a relatively low cost. Constructing an establishment-level panel from 1998 to 2009, we find that the CAC regulations imposed by India’s Supreme Court on 17 cities improved air quality with little effect on establishment productivity. We document a strong effect of deterred entry of high-polluting industries into regulated cities; however little effect on the overall level of manufacturing output, employment, or productivity in those cities. We also find sustained reductions in within-establishment coal use, with no evidence of leakage into other fuels. To benchmark our results, we use variation in coal prices to compare the CAC policies to price incentives. We show that CAC regulations were primarily effective at reducing coal consumption of large urban polluters, while a coal tax is likely to have a broader impact across all establishment types. Our estimated coal price elasticity suggests that a 15-30% excise tax would be needed to generate reductions in coal consumption equivalent to those produced by these CAC policies.

"Imported Inputs and Productivity Spillovers from Foreign Direct Investment"
New Draft Coming Soon | Latest Draft (August, 2016)  | SSRN Draft (August, 2016)

Abstract. This paper considers how input market liberalization affects host country productivity spillovers from multinational corporation (MNC) investments. The standard “Backward Linkage” measure used to estimate technology and learning spillovers to local upstream suppliers– —pioneered by Javorcik (2004) and replicated across several influential papers—–implicitly assumes domestic and foreign firms share the same input structure. I show that this assumption constitutes an omitted variable bias of imported inputs in TFP spillover estimation. Using a novel Colombian firm panel that isolates imported from domestic inputs, mean backward linkage productivity spillovers reduce in half when the share of locally sourced inputs is adjusted to reflect MNCs’ observably higher propensity to import inputs. However in some industries, productivity spillovers increase in response to the adjustment. I demonstrate that the sign and magnitude of this bias are proportional to the elasticity of substitution between imported and domestic inputs. The results highlight how input market liberalization (usually associated with increased FDI inflows) can have important feedback effects on local productivity spillovers from MNCs.


Works in Progress

"Wage Insurance for Displaced Workers" with Brian Kovak and Adam Leive

  • Supported by National Science Foundation award #SES-1851679 (Co-PI, $292,000)

"Firm Responsiveness to Location Subsidies: Regression Discontinuity Estimates from a Tax Credit Formula" with Matt Freedman and David Neumark

"Big Pushes, Little Hollywoods: Local Economic Development Effects of Film Tax Credit Lotteries"


OTHER

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