Structural and reduced form methods in labor economics: Course Outline

Outline

  • Principles of empirical research
    • Identification
      • “Non-parametric identification”, Matzkin (2007)
      • “Identification of models of the labor market” Taber and French (2010)
      • “Partial Identification in Econometrics” Tamer (2010)
    • Advantages of reduced form methods and advantages of structural models
    • Feasibility of each approach individually and jointly
    • “Structural Equations, Treatment Effects and Econometric Policy Evaluation” Heckman and Vytlacil (2003)
  • Reduced form methods
    • Shift-share exclusion restrictions
      • “Bartik Instruments: What, When, Why and How” Goldsmith-Pinkham, Sorkin and Swift (2020)
      • “Quasi-experimental shift-share research designs” Borusyak, Hull and Jaravel (2020)
    • Variation in treatment timings and heterogenous effects
      • “What’s trending in difference-in-differences?” Roth and Santa’Anna (2022)
      • “Two-way fixed effects estimators with heterogeneous treatment effects” de Chaisemartin and d`Haultfoeuille (2020)
      • “The Unintended Benefits of Women’s Empowerment on Household Sanitation” Alam and Agarwal (2023)
    • Empirical Bayes
      • “Empirical Bayes deconvolution estimates.” Efron (2016)
      • “Systemic discrimination among large US employers”, Kline, Rose and Walters (2022)
      • “Robust empirical bayes confidence intervals” Armstrong, Kolesár and Plagborg-Møller (2022)
    • Discontinuity based designs
      • “Inference on causal effects in a generalized regression kink design” Card et al. (2015)
      • “Inference in Regression Discontinuity Designs with a Discrete Running Variable”, Kolesar and Rothe (2018)
  • Structural models
    • Conditional choice probabilities, discrete choice and dynamic models
      • “Discrete Choice Methods with Simulation” Train (2009)
      • “Conditional Choice Probabilities and the Estimation of Dynamic Models”, Hotz and Miller (1993)
      • “College Attrition and the Dynamics of Information Revelation”, Arcidiacono, Aucejo, Maurel, et al. (2018)
      • “The Structural Estimation of Behavioral Models: Discrete Choice Dynamic Programming Methods and Applications,” Keane and Wolpin (2011)
    • Stated preference
      • “Preference for the workplace, investment in human capital and gender”, Wiswall Zafar (2018)
      • “Understanding Migration Aversion Using Elicited Choice Probabilities”, Kosar, Ransom, van der Klaauw (2022)
      • “Optimal Place-based redistribution” Alam, Davis and Gregory (2023)
    • Models on wage inequality
      • “High wage workers and high wage firms” Abowd, Kramarz and Margolis (1999)
      • “A Distributional Framework for Matched Employer-employee data”, Bonhomme, Lamadon, Manresa (2019)
      • “Racial Gaps in Wage Growth: Discrimination and Search Frictions” Alam (2020)
      • “Discretizing Unobserved heterogeneity” Bonhomme, Lamadon, Manresa (2019)
      • “Monopsony in Movers: The Elasticity of Labor Supply to Firm Wage Policies”, Bassier, Dube, Naidu (2021)
  • Using both reduced form and structural models
    • “Worker-side discrimination–Beliefs and Preferences - Evidence from an Information Experiment on Jobseekers”, Alam, Mookerjee, Roy (2022)
    • “Estimating Equilibrium Effects of Job Search Assistance,” Gautier, Muller, van der Klaauw, Rosholm and Svarer (2018)
    • “The Demand for Food of Poor Urban Mexican Households: Understanding Policy Impacts Using Structural Models” Angelucci and Attanasio (2013)
    • “Evaluating Search and Matching Models Using Experimental Data” Lise, Seitz and Smith (2015)
    • “Evaluating a Structural Model of Labor Supply and Welfare Participation: Evidence from State Welfare Reform Experiments,” Choi (2018)
    • “Estimating labour supply responses and welfare participation: Using a natural experiment to validate a structural labour supply model” Hansen and Liu (2015)
    • “The Role of Labor and Marriage Markets, Preference Heterogeneity and the Welfare System on the Life Cycle Decisions of Black, Hispanic and White Women,” Keane and Wolpin (2010)
    • “Approximating the Equilibrium Effects of Informed School Choice,” Allende, Gallego and Nielson (2019)
  • Coding in Julia (if time permits)
    • Why Julia?
    • Efficient code, version control and large project workflow
    • Automatic testing and reproducibility
    • Introduction to numerical optimization #### Other readings
  • Control function approach
    • Control Function Methods in Applied Econometrics, Wooldridge (2015)
    • “Identification of Treatment Effects Using Control Functions in Models with Continuous, Endogenous Treatment and Heterogeneous Effects”, Heckman et. al (2008)
    • “Using Matching, Instrumental Variables, and Control Functions to Estimate Economic Choice Models” Heckman and Navarro (2004)
    • “Control functions” Navarro (2010)