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Maximum-likelihood based inference in the two-way random effects model with serially correlated time effects

  • Karlsson, Sune

    ()

    (Dept. of Economic Statistics, Stockholm School of Economics)

  • Skoglund, Jimmy

    ()

    (Dept. of Economic Statistics, Stockholm School of Economics)

This paper considers maximum likelihood estimation and inference in the two-way random effects model with serial correlation. We derive a straightforward maximum likelihood estimator when the time-specific component follow an AR(1) or MA(1) process. The estimator is easily generalized to arbitrary stationary and strictly invertible ARMA processes. In addition we consider the model selection problem and derive tests of the null hypothesis of no serial correlation as well as tests for discriminating between the AR(1) and MA(1) specifications. A Monte-Carlo experiment evaluates the finite-sample properties of the estimators, test-statistics and model selection procedures.

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Paper provided by Stockholm School of Economics in its series SSE/EFI Working Paper Series in Economics and Finance with number 383.

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Length: 31 pages
Date of creation: 15 May 2000
Date of revision:
Publication status: Published in Empirical Economics, 2004, pages 79-88.
Handle: RePEc:hhs:hastef:0383
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