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The Estimation of Multi-dimensional Fixed Effects Panel Data Models

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  • László Balázsi
  • László Mátyás
  • Tom Wansbeek

Abstract

The paper introduces for the most frequently used three-dimensional fixed effects panel data models the appropriate Within estimators. It analyzes the behaviour of these estimators in the case of no-self-flow data, unbalanced data and dynamic autoregressive models. Then the main results are generalized for higher dimensional panel data sets as well.

Suggested Citation

  • László Balázsi & László Mátyás & Tom Wansbeek, 2014. "The Estimation of Multi-dimensional Fixed Effects Panel Data Models," CEU Working Papers 2014_1, Department of Economics, Central European University, revised 10 Feb 2014.
    • Handle: RePEc:ceu:econwp:2014_1
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    References listed on IDEAS

    as
    1. Mark Harris & Laszlo Matyas & Patrick Sevestre, 2008. "Dynamic Models for Short Panels," Post-Print halshs-00279980, HAL.
    2. Gourieroux,Christian & Monfort,Alain, 1995. "Statistics and Econometric Models," Cambridge Books, Cambridge University Press, number 9780521471626, June.
    3. Wansbeek, Tom, 1991. "Singular value decomposition of design matrices in ANOVA with balanced data," Statistics & Probability Letters, Elsevier, vol. 12(5), pages 441-441, November.
    4. Laszlo Matyas, 1997. "Proper Econometric Specification of the Gravity Model," The World Economy, Wiley Blackwell, vol. 20(3), pages 363-368, May.
    5. I-Hui Cheng & Howard J. Wall, 2005. "Controlling for heterogeneity in gravity models of trade and integration," Review, Federal Reserve Bank of St. Louis, vol. 87(Jan), pages 49-63.
    6. Richard Baldwin & Daria Taglioni, 2006. "Gravity for Dummies and Dummies for Gravity Equations," NBER Working Papers 12516, National Bureau of Economic Research, Inc.
    7. Wansbeek, Tom & Kapteyn, Arie, 1989. "Estimation of the error-components model with incomplete panels," Journal of Econometrics, Elsevier, vol. 41(3), pages 341-361, July.
    8. Baltagi, Badi H. & Egger, Peter & Pfaffermayr, Michael, 2003. "A generalized design for bilateral trade flow models," Economics Letters, Elsevier, vol. 80(3), pages 391-397, September.
    9. László Mátyás & Patrick Sevestre (ed.), 2008. "The Econometrics of Panel Data," Advanced Studies in Theoretical and Applied Econometrics, Springer, number 978-3-540-75892-1, April.
    10. Cecília Hornok, 2011. "Gravity or Dummies? The Limits of Identification in Gravity Estimations," CeFiG Working Papers 15, Center for Firms in the Global Economy, revised 26 Sep 2011.
    11. Wansbeek, Tom, 1991. "Singular value decomposition of design matrices in ANOVA with balanced data," Statistics & Probability Letters, Elsevier, vol. 11(1), pages 33-36, January.
    12. Patrick Sevestre & Laszlo Matyas, 2008. "The Econometrics of Panel Data," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00279977, HAL.
    13. Peter Egger & Michael Pfaffermayr, 2003. "The proper panel econometric specification of the gravity equation: A three-way model with bilateral interaction effects," Empirical Economics, Springer, vol. 28(3), pages 571-580, July.
    14. Davis, Peter, 2002. "Estimating multi-way error components models with unbalanced data structures," Journal of Econometrics, Elsevier, vol. 106(1), pages 67-95, January.
    15. Nickell, Stephen J, 1981. "Biases in Dynamic Models with Fixed Effects," Econometrica, Econometric Society, vol. 49(6), pages 1417-1426, November.
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    More about this item

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • C20 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - General
    • C40 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - General
    • F17 - International Economics - - Trade - - - Trade Forecasting and Simulation
    • F47 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - Forecasting and Simulation: Models and Applications

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