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Maximum-Likelihood Based Inference in the Two-Way Random Effects Model with Serially Correlated Time Effects

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  • Sune Karlsson

    (Stockholm School of Economics)

  • Jimmy Skoglund

    (Stockholm School of Economics)

Abstract

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. Furthermore we 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 and test-statistics

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Bibliographic Info

Paper provided by Econometric Society in its series Econometric Society World Congress 2000 Contributed Papers with number 1178.

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Date of creation: 01 Aug 2000
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Handle: RePEc:ecm:wc2000:1178

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Cited by:
  1. Robert F. Phillips, 2012. "On computing generalized least squares and maximum-likelihood estimates of error-components models with incomplete panels and correlated disturbances," Economics Bulletin, AccessEcon, vol. 32(4), pages 3017-3024.
  2. Paolo, Foschi, 2005. "Estimating regressions and seemingly unrelated regressions with error component disturbances," MPRA Paper 1424, University Library of Munich, Germany, revised 07 Sep 2006.
  3. Jimmy Skoglund & Sune Karlsson, 2002. "Asymptotics for random effects models with serial correlation," 10th International Conference on Panel Data, Berlin, July 5-6, 2002 A6-1, International Conferences on Panel Data.
  4. Marcel die Dama & Boniface ngah Epo & Galex syrie Soh, 2013. "Developing a two way error component estimation model with disturbances following a special autoregressive (4) for quarterly data," Economics Bulletin, AccessEcon, vol. 33(1), pages 625-634.
  5. Pardo Martínez, Clara Inés, 2013. "An analysis of eco-efficiency in energy use and CO2 emissions in the Swedish service industries," Socio-Economic Planning Sciences, Elsevier, vol. 47(2), pages 120-130.
  6. Giorgio Calzolari & Laura Magazzini, 2009. "Autocorrelation and masked heterogeneity in panel data models estimated by maximum likelihood," Working Papers 53/2009, University of Verona, Department of Economics.
  7. Baltagi, Badi H., 2006. "Forecasting with panel data," Discussion Paper Series 1: Economic Studies 2006,25, Deutsche Bundesbank, Research Centre.
  8. Pardo Martínez, Clara Inés & Silveira, Semida, 2012. "Analysis of energy use and CO2 emission in service industries: Evidence from Sweden," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(7), pages 5285-5294.

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