A Two-Step First Difference Estimator for a Panel Data Tobit Model under Conditional Mean Independence Assumptions

A.S. Kalwij

Research output: Working paperDiscussion paperOther research output

295 Downloads (Pure)

Abstract

This study develops a two-step estimator for a panel data Tobit model based on taking first-differences of the equation of interest, under conditional mean independence assumptions.The necessary correction terms are non-standard and a substantial part is therefore devoted to the formal derivation of these correction terms.The main advantage of this estimator is that it yields estimates that are far less sensitivity to misspecification of the conditional mean independence assumption than an estimation procedure set up in levels.Monte Carlo simulations are provided in support of this.
Original languageEnglish
Place of PublicationTilburg
PublisherEconometrics
Number of pages19
Volume2004-67
Publication statusPublished - 2004

Publication series

NameCentER Discussion Paper
Volume2004-67

Keywords

  • panel data
  • estimating
  • monte carlo technique

Fingerprint Dive into the research topics of 'A Two-Step First Difference Estimator for a Panel Data Tobit Model under Conditional Mean Independence Assumptions'. Together they form a unique fingerprint.

  • Cite this

    Kalwij, A. S. (2004). A Two-Step First Difference Estimator for a Panel Data Tobit Model under Conditional Mean Independence Assumptions. (CentER Discussion Paper; Vol. 2004-67). Econometrics.