Structural and reduced form methods in labor economics: Course Outline

• Principles of empirical research
  • Identification
    • “Non-parametric identification”, Matzkin (2007)
    • “Identification of models of the labor market” Taber and French (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)
    • “Inheritance rights and 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
    • “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)
    • “Discrete Choice Methods with Simulation” Train (2009)
    • “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)
    • “Optimal Place-based redistribution” Alam, Davis and Gregory (2023)
    • “Understanding Migration Aversion Using Elicited Choice Probabilities”, Kosar, Ransom, van der Klaauw (2022)
  • 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