We study a linear index binary response model with random coefficients B allowed to be correlated with regressors X. We identify the mean of the distribution of B and show how the mean can be interpreted as a vector of expected relative effects. We use instruments and a control vector V to make X independent of B given V. This leads to a localize-then-average approach to both identification and estimation. We develop a -consistent and asymptotically normal estimator of a trimmed mean of the distribution of B, explore its small sample performance through simulations, and present an application.
Authors
Associate Professor Boston College
Robert Sherman
Journal article details
- DOI
- 10.1016/j.jeconom.2015.03.044
- Publisher
- Elsevier
- Issue
- Volume 188, Issue 1, September 2015
Suggested citation
Hoderlein, S and Sherman, R. (2015). 'Identification and estimation in a correlated random coefficients binary response model' 188(1/2015)
More from IFS
Understand this issue
Council funding is a numbers game in which everybody is losing
13 May 2024
Empty defence spending promises are a shot in the dark
29 April 2024
Public investment: what you need to know
25 April 2024
Policy analysis
The past and future of UK health spending
14 May 2024
NHS spending has risen less quickly than was planned at the last election, despite the pandemic and record waiting lists
14 May 2024
Recent trends in and the outlook for health-related benefits
19 April 2024
Academic research
The employment and distributional impacts of nationwide minimum wage changes
10 April 2024
Willingness to pay for improved public education and public healthcare systems: the role of income mobility prospects
14 March 2024
Unfunded mandates and taxation
14 March 2024