The Journal of Human Resources· 2015Q1· Review
Control Function Methods in Applied Econometrics
- 1,578citations
- Q1SCImago
- 2015year
Short summary
Control function (CF) methods offer a computationally simpler and less assumption-heavy alternative to plug-in approaches for addressing endogenous explanatory variables in econometric models.
AI-generated from the title and abstract; the full text is not read.
Key points
- Control function (CF) methods address endogenous explanatory variables in econometric models.
- CF methods are often more computationally simple and require fewer assumptions than plug-in approaches.
- Recent work on average partial effects and nonparametric identification supports flexible parametric CF strategies.
- Approximate solutions exist for discrete endogenous variables in nonlinear models, though this area is more controversial.
AI-generated from the title and abstract; the full text is not read.
Abstract
This paper provides an overview of control function (CF) methods for solving the problem of endogenous explanatory variables (EEVs) in linear and nonlinear models. CF methods often can be justified in situations where “plug-in” approaches are known to produce inconsistent estimators of parameters and partial effects. Usually, CF approaches require fewer assumptions than maximum likelihood, and CF methods are computationally simpler. The recent focus on estimating average partial effects, along with theoretical results on nonparametric identification, suggests some simple, flexible parametric CF strategies. The CF approach for handling discrete EEVs in nonlinear models is more controversial but approximate solutions are available.
The authors' abstract, as published at the source. The Journal of Human Resources, 2015 · DOI ↗
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Field: General Economics, Econometrics and Finance
General Economics, Econometrics and FinanceEconomics, Econometrics and Finance