Bradley Setzler

Bradley Setzler

Associate Professor of Economics

Penn State & NBER

Appointments:

  • The Strumpf Early Career Associate Professor of Economics (with tenure), Penn State.
  • Research Associate in Labor Studies, NBER.

Links: Research | CV | bradley.setzler@gmail.com

Fields:

  • Primary: Labor Economics, Applied Micro
  • Secondary: Industrial Organization, Trade and Spatial Economics

Topics of Interest:

  • Labor market power and
    • mergers, collusion, and conduct in labor markets (see 7, 8);
    • its interactions with product market power (see 5, 7);
    • the role of firms in wage inequality (see 3, 4).
  • Local labor market adjustment to
    • trade exposure (see 6, 9, 10, 11);
    • automation and technology exposure (see 11);
    • foreign firm entry (see 2);
    • worker-specific productivity shocks (see 1).

Note: the numbers are links to my relevant papers, ordered chronologically.


Publications

Places vs People: The Ins and Outs of Labor Market Adjustment to Globalization

Handbook of Labor Economics, 2025.

Imperfect Competition and Rents in Labor and Product Markets: The Case of the Construction Industry

American Economic Review, 2025.

How Much Should we Trust Estimates of Firm Effects and Worker Sorting?

Journal of Labor Economics, 2023. (Lead article.)

Disability Benefits, Consumption Insurance, and Household Labor Supply

American Economic Review, 2019.

Working Papers

Labor and Product Market Power, Endogenous Quality, and the Consolidation of the US Hospital Industry

Newly available to present in 2025. Presentations: ASSA, Brandeis, Cornell, Leuven, Michigan, MIT, NBER Labor Studies, NBER Megafirms, Ohio State, Princeton, Stanford, UEA. NBER Working Paper now available.

Conduct in US Labor Markets

Newly available to present in 2026. Scheduled: ASSA. Submitted for disclosure review.

In Progress

The Children of the China Shock

The Local Impacts of Structural Change

Resources


Advice

Software Packages

  • textab: construct and compile highly-customized LaTeX tables in R
  • DiD for Big Data: fast and big-data-friendly diff-in-diffs in R

Event Organization

Disclaimer: Materials provided are for Educational Use Only. All articles are the sole copyright of their respective publishers.