Matthew A Masten
  • Matthew A Masten

  • Assistant Professor in the Department of Economics
  • Economics
  • 202 Social Sciences Building
  • Phone: (919) 660-1877
  • Homepage
  • Curriculum Vitae
  • Overview

    Professor Masten's research focuses on econometrics, social interactions, and decision making. He is currently working on models with high dimensional heterogeneity and simultaneity, with applications to social interactions and peer effects.
  • Bio

    Matthew Masten joined the Duke faculty as an assistant professor in July of 2013. Professor Masten received his Ph.D. in 2013 in economics from Northwestern University. He received a B.A. in economics and statistics in addition to a B.S. in mathematics from the University of Florida in 2008.
  • Specialties

    • Econometrics
    • Economics of Networks
    • Mathematical and Quantitative Methods
    • Microeconomics
  • Working Papers

    • Matthew A Masten.
    • (2015).
    • Random coefficients on endogenous variables in simultaneous equations models.
    • cemmap Working Papers
    • .
    • [web]
    • MA Masten and A Torgovitsky.
    • (2013).
    • Instrumental Variables Estimation of a Generalized Correlated Random Coefficients Model.
    • cemmap Working Papers
    • .
    • [web]
    Publication Description

    We study identification and estimation of the average treatment effect in a correlated random coefficients model that allows for first stage heterogeneity and binary instruments. The model also allows for multiple endogenous variables and interactions between endogenous variables and covariates. Our identification approach is based on averaging the coefficients obtained from a collection of ordinary linear regressions that condition on different realizations of a control function. This identification strategy suggests a transparent and computationally straightforward estimator of a trimmed average treatment effect constructed as the average of kernel-weighted linear regressions. We develop this estimator and establish its $\sqrt{n}$--consistency and asymptotic normality. Monte Carlo simulations show excellent finite-sample performance that is comparable in precision to the standard two-stage least squares estimator. We apply our results to analyze the effect of air pollution on house prices, and find substantial heterogeneity in first stage instrument effects as well as heterogeneity in treatment effects that is consistent with household sorting.

  • Areas of Interest

    Models with high dimensional heterogeneity
    Econometrics of networks and social interactions
    Statistical decision theory
  • Education

      • Ph.D.,
      • Northwestern University,
      • 2013
  • Recent Publications

      • M Chicu and MA Masten.
      • (2013).
      • A specification test for discrete choice models.
      • Economics Letters
      • ,
      • 121
      • (2)
      • ,
      • 336-339.
      • [web]
      Publication Description

      In standard discrete choice models, adding options cannot increase the choice probability of an existing alternative. We use this observation to construct a simple nonparametric specification test by exploiting variation in the choice sets individuals face. We use a multiple testing procedure to determine the particular kind of choice sets that produce violations. We apply these tests to the 1896 US House of Representatives election and reject commonly used discrete choice voting models. © 2013 Elsevier B.V.

      • JM Abito, K Borovickova, H Golden, J Goldin, MA Masten, M Morin, A Poirier, V Pons, I Romem, T Williams and C Yoon.
      • (2011).
      • How Should the Graduate Economics Core be Changed?.
      • ,
      • 42
      • (4)
      • ,
      • 414-417.
      • [web]
  • View All Publications
  • Teaching

    • ECON 707D.001
      • Gross Hall 103
      • TuTh 10:05 AM-11:20 AM
    • ECON 707D.01D
      • Gross Hall 230E
      • Th 06:30 PM-07:20 PM
    • ECON 707D.02D
      • Social Sciences 136
      • Th 07:30 PM-08:20 PM
    • ECON 883.09
      • Social Sciences 105
      • WF 10:05 AM-11:20 AM
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