Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/79508 
Year of Publication: 
2012
Series/Report no.: 
cemmap working paper No. CWP42/12
Publisher: 
Centre for Microdata Methods and Practice (cemmap), London
Abstract: 
We study identification and estimation in a binary response model with random coefficients B allowed to be correlated with regressors X. Our objective is to identify the mean of the distribution of B and estimate a trimmed mean of this distribution. Like Imbens and Newey (2009), we use instruments Z and a control vector V to make X independent of B given V . A consequent conditional median restriction identifies the mean of B given V . Averaging over V identifies the mean of B. This leads to an analogous localize-then-average approach to estimation. We estimate conditional means with localized smooth maximum score estimators and average to obtain a Ín-consistent and asymptotically normal estimator of a trimmed mean of the distribution of B. The method can be adapted to models with nonrandom coefficients to produce Ín-consistent and asymptotically normal estimators under the conditional median restrictions. We explore small sample performance through simulations, and present an application.
Subjects: 
Heterogeneity
Correlated Random Coefficients
Endogeneity
Binary Response Model
Instrumental Variables
Control Variables
Conditional Median Restrictions
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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