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Cointegration Vector Estimation By Dols For A Three-Dimensional Panel

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  • Luis Fernando Melo
  • John Jairo León
  • Dagoberto Saboya

Abstract

This paper extends the asymptotic results of the dynamic ordinary least squares (DOLS) cointegration vector estimator of Mark and Sul (2003) to a three-dimensional panel. We use a balanced panel of N and M lengths observed over T time periods. The cointegration vector is homogenous across individuals but we allow for individual heterogeneity using different short-run dynamics, individual-specific fixed effects and individual-specific time trends. Both individual effects are considered for the first two dimensions. We also model some degree of cross-sectional dependence using time-specific effects.This paper was motivated by the three-dimensional panel cointegration analysis used to estimate the total factor productivity for Colombian regions and sectors during 1975-2000 by Iregui, Melo and Ram´ırez (2007). They used the methodology proposed by Marrocu, Paci and Pala (2000); however, hypothesis testing is not valid under this technique. The methodology we are currently proposing allows us to estimate the long-run relationship and to construct asymptotically valid test statistics in the 3D-panel context.

Suggested Citation

  • Luis Fernando Melo & John Jairo León & Dagoberto Saboya, 2007. "Cointegration Vector Estimation By Dols For A Three-Dimensional Panel," Borradores de Economia 4391, Banco de la Republica.
    • Handle: RePEc:col:000094:004391
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    References listed on IDEAS

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    1. repec:cup:etheor:v:7:y:1991:i:1:p:1-21 is not listed on IDEAS
    2. Ana María Iregui B. & Luis Fernando Melo V. & María Teresa Ramírez G., 2007. "Productividad regional y sectorial en Colombia: un análisis utilizando datos de panel," Revista ESPE - Ensayos sobre Política Económica, Banco de la Republica de Colombia, vol. 25(53), pages 18-65, January.
    3. R. Pala & E. Marrocu & R. Paci, 2000. "Estimation of total factor productivity for regions and sectors in Italy. A panel cointegration approach," Working Paper CRENoS 200016, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    4. Kremers, Jeroen J M & Ericsson, Neil R & Dolado, Juan J, 1992. "The Power of Cointegration Tests," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 54(3), pages 325-348, August.
    5. Peter C. B. Phillips & Mico Loretan, 1991. "Estimating Long-run Economic Equilibria," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 58(3), pages 407-436.
    6. Stock, James H & Watson, Mark W, 1993. "A Simple Estimator of Cointegrating Vectors in Higher Order Integrated Systems," Econometrica, Econometric Society, vol. 61(4), pages 783-820, July.
    7. Banerjee, Anindya, et al, 1986. "Exploring Equilibrium Relationships in Econometrics through Static Models: Some Monte Carlo Evidence," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 48(3), pages 253-277, August.
    8. Saikkonen, Pentti, 1991. "Asymptotically Efficient Estimation of Cointegration Regressions," Econometric Theory, Cambridge University Press, vol. 7(1), pages 1-21, March.
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    More about this item

    Keywords

    Cointegration; Dynamic OLS estimation; panel data in three dimensions.;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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