Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/56186 
Year of Publication: 
2001
Series/Report no.: 
SSE/EFI Working Paper Series in Economics and Finance No. 433
Publisher: 
Stockholm School of Economics, The Economic Research Institute (EFI), Stockholm
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.
Subjects: 
Panel data
serial correlation
random effects
JEL: 
C12
C13
C23
Document Type: 
Working Paper

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