UCL Discovery
UCL home » Library Services » Electronic resources » UCL Discovery

Estimating derivatives in nonseparable models with limited dependent variables

Altonji, J.; Ichimura, H.; Otsu, T.; (2008) Estimating derivatives in nonseparable models with limited dependent variables. (cemmap Working Papers CWP20/). Institute for Fiscal Studies: London, UK. Green open access

[img]
Preview
PDF
14711.pdf

Download (689kB)

Abstract

We present a simple way to estimate the effects of changes in a vector of observable variables X on a limited dependent variable Y when Y is a general nonseparable function of X and unobservables. We treat models in which Y is censored from above or below or potentially from both. The basic idea is to first estimate the derivative of the conditional mean of Y given X at x with respect to x on the uncensored sample without correcting for the effect of changes in x induced on the censored population. We then correct the derivative for the effects of the selection bias. We propose nonparametric and semiparametric estimators for the derivative. As extensions, we discuss the cases of discrete regressors, measurement error in dependent variables, and endogenous regressors in a cross section and panel data context.

Type: Working / discussion paper
Title: Estimating derivatives in nonseparable models with limited dependent variables
Open access status: An open access version is available from UCL Discovery
Publisher version: http://www.cemmap.ac.uk/publications.php
Language: English
Additional information: This is a revised version of a 1996 working paper
UCL classification: UCL > Provost and Vice Provost Offices > UCL SLASH > Faculty of SandHS > Dept of Economics
URI: https://discovery.ucl.ac.uk/id/eprint/14711
Downloads since deposit
449Downloads
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item