Weighted-Average Least Squares Estimation of Generalized Linear Models

Tinbergen Institute Discussion Paper 2017-029/III

36 Pages Posted: 28 Feb 2017

See all articles by Giuseppe De Luca

Giuseppe De Luca

University of Palermo - d/SEAS

J.R. Magnus

Vrije Universiteit Amsterdam, School of Business and Economics

Franco Peracchi

University of Rome Tor Vergata - Department of Economics and Finance; University of Rome Tor Vergata - Centre for International Studies on Economic Growth (CEIS); EIEF

Date Written: February 25, 2017

Abstract

The weighted-average least squares (WALS) approach, introduced by Magnus et al. (2010) in the context of Gaussian linear models, has been shown to enjoy important advantages over other strictly Bayesian and strictly frequentist model averaging estimators when accounting for problems of uncertainty in the choice of the regressors. In this paper we extend the WALS approach to deal with uncertainty about the specification of the linear predictor in the wider class of generalized linear models (GLMs). We study the large-sample properties of the WALS estimator for GLMs under a local misspecification framework that allows the development of asymptotic model averaging theory. We also investigate the finite sample properties of this estimator by a Monte Carlo experiment whose design is based on the real empirical analysis of attrition in the first two waves of the Survey of Health, Ageing and Retirement in Europe (SHARE).

Keywords: WALS, model averaging, generalized linear models, Monte Carlo, attrition

JEL Classification: C51, C25, C13, C11

Suggested Citation

De Luca, Giuseppe and Magnus, Jan R. and Peracchi, Franco, Weighted-Average Least Squares Estimation of Generalized Linear Models (February 25, 2017). Tinbergen Institute Discussion Paper 2017-029/III. Available at SSRN: https://ssrn.com/abstract=2924333 or http://dx.doi.org/10.2139/ssrn.2924333

Giuseppe De Luca (Contact Author)

University of Palermo - d/SEAS

Viale delle Scienze, edificio 13
Palermo, 90124
Italy

Jan R. Magnus

Vrije Universiteit Amsterdam, School of Business and Economics ( email )

De Boelelaan 1105
Amsterdam, 1081HV
Netherlands

Franco Peracchi

University of Rome Tor Vergata - Department of Economics and Finance ( email )

Via di Tor Vergata
Rome, Lazio 00133
Italy

University of Rome Tor Vergata - Centre for International Studies on Economic Growth (CEIS) ( email )

Via Columbia, 2
Rome, I-00133
Italy

EIEF ( email )

via Sallustiana 62
Rome, 00187
Italy

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