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Testing for Multicointegration in Panel Data with Common Factors

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  • Vanessa Berenguer‐Rico
  • Josep Lluís Carrion‐i‐Silvestre

Abstract

This paper addresses the concept of multicointegration in a panel data framework and builds upon the panel data cointegration procedures developed in Pedroni [Econometric Theory (2004), Vol. 20, pp. 597–625]. When individuals are either cross‐section independent, or cross‐section dependence can be removed by cross‐section demeaning, our approach can be applied to the wider framework of mixed I(2) and I(1) stochastic processes. The paper also deals with the issue of cross‐section dependence using approximate common‐factor models. Finite sample performance is investigated through Monte Carlo simulations. Finally, we illustrate the use of the procedure investigating an inventories, sales and production relationship for a panel of US industries.

Suggested Citation

  • Vanessa Berenguer‐Rico & Josep Lluís Carrion‐i‐Silvestre, 2006. "Testing for Multicointegration in Panel Data with Common Factors," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 68(s1), pages 721-739, December.
  • Handle: RePEc:bla:obuest:v:68:y:2006:i:s1:p:721-739
    DOI: 10.1111/j.1468-0084.2006.00453.x
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    Cited by:

    1. Karikallio, Hanna, 2015. "Cross-commodity Price Transmission and Integration of the EU Livestock Market of Pork and Beef: Panel Time-series Approach," 2015 Conference, August 9-14, 2015, Milan, Italy 211832, International Association of Agricultural Economists.
    2. Jaroslava Hlouskova & Martin Wagner, 2009. "Finite Sample Correction Factors for Panel Cointegration Tests," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(6), pages 851-881, December.
    3. António Afonso & Christophe Rault, 2010. "What do we really know about fiscal sustainability in the EU? A panel data diagnostic," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 145(4), pages 731-755, January.
    4. María-Dolores, Ramon, 2009. "How different is the exchange rate pass-through in new member states of the EU? Some potential explanatory factors," UMUFAE Economics Working Papers 4698, DIGITUM. Universidad de Murcia.
    5. Martin Wagner & Jaroslava Hlouskova, 2010. "The Performance of Panel Cointegration Methods: Results from a Large Scale Simulation Study," Econometric Reviews, Taylor & Francis Journals, vol. 29(2), pages 182-223, April.
    6. Cassim, Lucius, 2020. "A Residual-based Test For Multicointegration In Models With Structural Breaks And Threshold Adjustment To Steady State," MPRA Paper 101453, University Library of Munich, Germany.
    7. Piotr Krajewski & Michał Mackiewicz & Agata Szymańska, 2016. "Fiscal Sustainability in Central and Eastern European Countries - A Post-Crisis Assessment," Prague Economic Papers, Prague University of Economics and Business, vol. 2016(2), pages 175-188.
    8. Vanessa Berenguer‐Rico & Josep Lluís Carrion‐i‐Silvestre, 2006. "Testing for Multicointegration in Panel Data with Common Factors," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 68(s1), pages 721-739, December.
    9. Afonso, António & Rault, Christophe, 2015. "Multi-step analysis of public finances sustainability," Economic Modelling, Elsevier, vol. 48(C), pages 199-209.
    10. Christian Gengenbach & Franz C. Palm & Jean‐Pierre Urbain, 2006. "Cointegration Testing in Panels with Common Factors," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 68(s1), pages 683-719, December.
    11. Olgica Glavaški & Emilija Beker Pucar, 2021. "Heterogeneity of fiscal adjustments in EU economies in the pre- and post-crisis periods: common correlated effects approach," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 11(1), pages 191-226, March.

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    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General

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