Modified Profile Likelihood for Panel Data Models

45 Pages Posted: 7 Feb 2012 Last revised: 10 Feb 2012

See all articles by Francesco Bartolucci

Francesco Bartolucci

Università di Perugia - Finanza e Statistica - Dipartimento di Economia

Ruggero Bellio

University of Udine

Alessandra Salvan

University of Padua

Nicola Sartori

University of Padua

Date Written: February 6, 2012

Abstract

We show how modified profile likelihood methods, developed in the statistical literature, may be effectively applied to estimate the structural parameters of econometric models for panel data, with a remarkable reduction of bias with respect to the ordinary likelihood methods. The implementation of these methods is illustrated in detail for certain static and dynamic models which are commonly used in economic applications. We consider, in particular, the truncated linear regression model, the first order autoregressive model, the (static and dynamic) logit model, and the (static and dynamic) probit model. Differently from static models, dynamic models include the lagged response variable among the regressors. For each of these models, we report the results of simulation studies showing the good behaviour of the proposed estimation methods, even with respect to an ideal, although infeasible, procedure. The methods are made available through an R package.

Keywords: autoregressive models, bias reduction, dynamic models, incidental parameter problem, logit model, probit model, truncated regression

JEL Classification: C10, C13, C23

Suggested Citation

Bartolucci, Francesco and Bellio, Ruggero and Salvan, Alessandra and Sartori, Nicola, Modified Profile Likelihood for Panel Data Models (February 6, 2012). Available at SSRN: https://ssrn.com/abstract=2000666 or http://dx.doi.org/10.2139/ssrn.2000666

Francesco Bartolucci (Contact Author)

Università di Perugia - Finanza e Statistica - Dipartimento di Economia ( email )

06123

Ruggero Bellio

University of Udine ( email )

Via Treppo 18
33100 Udine
Italy

Alessandra Salvan

University of Padua ( email )

Via 8 Febbraio, 2
Padova, Vicenza 35122
Italy

Nicola Sartori

University of Padua ( email )

Via 8 Febbraio, 2
Padova, Vicenza 35122
Italy

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
193
Abstract Views
975
rank
195,417
PlumX Metrics