imprint:
Cambridge, Mass: National Bureau of Economic Research, August 2009
Published in:NBER working paper series ; no. w15210
Extent:
1 Online-Ressource
Language:
English
DOI:
10.3386/w15210
Identifier:
Reproduction note:
Hardcopy version available to institutional subscribers
Origination:
Footnote:
Mode of access: World Wide Web
System requirements: Adobe [Acrobat] Reader required for PDF files
Description:
We propose a simple nonparametric mixtures estimator for recovering the joint distribution of parameter heterogeneity in economic models, such as the random coefficients logit. The estimator is based on linear regression subject to linear inequality constraints, and is robust, easy to program and computationally attractive compared to alternative estimators for random coefficient models. We prove consistency and provide the rate of convergence under deterministic and stochastic choices for the sieve approximating space. We present a Monte Carlo study and an empirical application to dynamic programming discrete choice with a serially-correlated unobserved state variable