Publications
Publications
- 2018
Semi-Parametric Estimation of Dynamic Discrete Choice Models
By: David Hao Zhang
Abstract
I develop a new method for estimating counterfactuals in dynamic discrete choice models, a widely used set of models in economics, without requiring a distributional assumption on utility shocks. Applying my method to the canonical Rust (1987) setting, I find that the typical logit assumption on utility shocks can lead the researcher to conclude that the agent's counterfactual choice probabilities are much more sensitive to policy changes than what a semi-parametric model would suggest. Therefore, my method may be useful to applied researchers in generating policy counterfactuals that are robust to such distributional assumptions.
Keywords
Citation
Zhang, David Hao. "Semi-Parametric Estimation of Dynamic Discrete Choice Models." Working Paper, April 2018.