Leonard Goff

I am an assistant professor of economics at the University of Georgia. My primary research fields are applied econometrics and labor economics, and I also have interests in environmental and public economics.

I recently obtained my PhD in economics from Columbia University, and previously studied physics and philosophy at the University of British Columbia and the University of Maryland.

You can reach me at leonard.goff@uga.edu.

Research

Working Papers

  • Treatment Effects in Bunching Designs: The Impact of the Federal Overtime Rule on Hours
    • (Job Market Paper)
    • [Supplemental Material]
    • Abstract: The Fair Labor Standards Act (FLSA) mandates overtime premium pay for most U.S. workers, but a lack of variability in the rule has made it difficult to assess its impacts on the labor market. This paper uses bunching at 40 hours to estimate the effect of the FLSA overtime rule on hours of work, leveraging an extension of the ``bunching design'' identification strategy and an administrative dataset of weekly paychecks. I develop a framework in which bunching at a choice-set kink reveals causal effects in a manner that is robust across underlying structural models, generalizing the canonical bunching-design approach. Under a non-parametric shape constraint on the distribution of hours and flexible assumptions on choice, I show that a local average treatment effect among bunchers is partially identified. The bounds are informative in the overtime context and suggest that directly affected hourly workers in the U.S. work an average of at least half an hour less per week, as a result of the FLSA mandate. This delivers an estimate of the wage elasticity of hours demand of -0.04.
    • Identifying the buncher LATE

  • A Vector Monotonicity Assumption for Multiple Instruments
    • [Supplemental Material]
    • Abstract: When a researcher wishes to use multiple instrumental variables for a single binary treatment, the familiar LATE monotonicity assumption can become restrictive: it requires that all units share a common direction of response even when different instruments are shifted in opposing directions. What I call vector monotonicity, by contrast, simply restricts treatment status to be monotonic in each instrument separately. This is a natural assumption in many contexts, capturing the intuitive notion of "no defiers" for each instrument. I show that in a setting with a binary treatment and multiple discrete instruments, a class of causal parameters is point identified under vector monotonicity, including the average treatment effect among units that are responsive to any particular subset of the instruments. I propose a simple "2SLS-like" estimator for the family of identified treatment effect parameters. An empirical application revisits the labor market returns to college education.

Work in Progress

  • The Career Impact of First Jobs: Evidence and Labor Market Design Lessons from Randomized Choice Sets
  • Do Firms Fully Exploit Their Labor Market Power in Setting Wages? Evidence from Canada

Publications

Outside of economics:

Curriculum Vitae

Teaching Materials

Statistics for Econometrics (Fall 2021; UGA ECON8070)

  • Course materials available through eLearningCommons. Email me if you need access!

    Senior Honors Thesis Workshop (Fall 2019; Columbia ECON GU4999)

    (Professor: Michael Best)

    Microeconometrics (Fall 2018; Columbia ECON GR6414)

    • Code

    Visit my Github

    Some software projects:

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