Specification and Estimation of Random Effects Models with Serial Correlation of General Form

Posted: 30 Mar 2013

See all articles by Jimmy Skoglund

Jimmy Skoglund

SAS Institute Inc.

Sune Karlsson

University of Orebro - Department of Economics

Date Written: March 28, 2001

Abstract

This paper is concerned with maximum likelihood based inference in random effects models with serial correlation. Allowing for individual effects we introduce serial correlation of general form in the time effects as well as the idiosyncratic errors. A straightforward maximum likelihood estimator is derived and a coherent model selection strategy is suggested for determining the orders of serial correlation as well as the importance of time and individual effects. The methods are applied to the estimation of a production function for the Japanese chemical industry using a sample of 72 firms observed during 1968-1987. Empirically, our focus is on measuring the returns to scale and technical change for the industry.

Keywords: random effects, panel data, model specification, hypothesis testing

Suggested Citation

Skoglund, Jimmy and Karlsson, Sune, Specification and Estimation of Random Effects Models with Serial Correlation of General Form (March 28, 2001). Available at SSRN: https://ssrn.com/abstract=2241034

Jimmy Skoglund (Contact Author)

SAS Institute Inc. ( email )

100 SAS Campus Drive
Cary, NC 27513-2414
United States

Sune Karlsson

University of Orebro - Department of Economics ( email )

SE-70182 Orebro
Sweden
+46 19 301 257 (Phone)

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