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Determining the Poolability of Individual Series in Panel Datasets

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  • George Kapetanios

    (Queen Mary, University of London)

Abstract

Panel datasets have been increasingly used in economics to analyse complex economic phenomena. One of the attractions of panel datasets is the ability to use an extended dataset to obtain information about parameters of interest which are assumed to have common values across panel units. However, the assumption of poolability has not been studied extensively beyond tests that determine whether a given dataset is poolable. We propose a method that enables the distinction of a set of series into a set of poolable series for which the hypothesis of a common parameter subvector cannot be reject and a set of series for which the poolability hypothesis fails. We discuss its theoretical properties and investigate its small sample performance for a particular simple model in a Monte Carlo study.

Suggested Citation

  • George Kapetanios, 2003. "Determining the Poolability of Individual Series in Panel Datasets," Working Papers 499, Queen Mary University of London, School of Economics and Finance.
    • Handle: RePEc:qmw:qmwecw:499
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    References listed on IDEAS

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    1. Ziemer, Rod F. & Wetzstein, Michael E., 1983. "A Stein-rule method for pooling data," Economics Letters, Elsevier, vol. 11(1-2), pages 137-143.
    2. Camba-Méndez, Gonzalo & Kapetanios, George, 2001. "Testing the rank of the Hankel matrix: a statistical approach," Working Paper Series 45, European Central Bank.
    3. Baltagi, Badi H. & Hidalgo, Javier & Li, Qi, 1996. "A nonparametric test for poolability using panel data," Journal of Econometrics, Elsevier, vol. 75(2), pages 345-367, December.
    4. Camba-Mendez, Gonzalo, et al, 2003. "Tests of Rank in Reduced Rank Regression Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 21(1), pages 145-155, January.
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    Citations

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    Cited by:

    1. Hasse, Jean-Baptiste & Lajaunie, Quentin, 2022. "Does the yield curve signal recessions? New evidence from an international panel data analysis," The Quarterly Review of Economics and Finance, Elsevier, vol. 84(C), pages 9-22.
    2. Candelon, Bertrand & Dumitrescu, Elena-Ivona & Hurlin, Christophe, 2014. "Currency crisis early warning systems: Why they should be dynamic," International Journal of Forecasting, Elsevier, vol. 30(4), pages 1016-1029.
    3. Bertrand Candelon & Elena-Ivona Dumitrescu & Christophe Hurlin, 2012. "How to Evaluate an Early-Warning System: Toward a Unified Statistical Framework for Assessing Financial Crises Forecasting Methods," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 60(1), pages 75-113, April.
    4. Trapani, Lorenzo, 2021. "Inferential theory for heterogeneity and cointegration in large panels," Journal of Econometrics, Elsevier, vol. 220(2), pages 474-503.
    5. Johan Blomquist & Joakim Westerlund, 2016. "Panel bootstrap tests of slope homogeneity," Empirical Economics, Springer, vol. 50(4), pages 1359-1381, June.
    6. Kapetanios, George, 2006. "Cluster analysis of panel data sets using non-standard optimisation of information criteria," Journal of Economic Dynamics and Control, Elsevier, vol. 30(8), pages 1389-1408, August.
    7. Castagnetti, Carolina & Rossi, Eduardo & Trapani, Lorenzo, 2015. "Inference on factor structures in heterogeneous panels," Journal of Econometrics, Elsevier, vol. 184(1), pages 145-157.
    8. Chen, Zhongfei & Matousek, Roman & Stewart, Chris & Webb, Rob, 2019. "Do rating agencies exhibit herding behaviour? Evidence from sovereign ratings," International Review of Financial Analysis, Elsevier, vol. 64(C), pages 57-70.
    9. Chortareas, Georgios & Kapetanios, George, 2009. "Getting PPP right: Identifying mean-reverting real exchange rates in panels," Journal of Banking & Finance, Elsevier, vol. 33(2), pages 390-404, February.
    10. Zigraiova, Diana & Jakubik, Petr, 2015. "Systemic event prediction by an aggregate early warning system: An application to the Czech Republic," Economic Systems, Elsevier, vol. 39(4), pages 553-576.
    11. Perevyshin, Yu. & Skrobotov, A., 2017. "The Price Convergence of Individual Goods in the Russian Regions," Journal of the New Economic Association, New Economic Association, vol. 35(3), pages 71-102.
    12. Chortareas, Georgios & Kapetanios, George, 2009. "Getting PPP right: Identifying mean-reverting real exchange rates in panels," Journal of Banking & Finance, Elsevier, vol. 33(2), pages 390-404, February.
    13. Kapetanios, George, 2006. "Cluster analysis of panel data sets using non-standard optimisation of information criteria," Journal of Economic Dynamics and Control, Elsevier, vol. 30(8), pages 1389-1408, August.
    14. van den Berg, Jeroen & Candelon, Bertrand & Urbain, Jean-Pierre, 2008. "A cautious note on the use of panel models to predict financial crises," Economics Letters, Elsevier, vol. 101(1), pages 80-83, October.
    15. Pesaran, M. Hashem, 2012. "On the interpretation of panel unit root tests," Economics Letters, Elsevier, vol. 116(3), pages 545-546.

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    More about this item

    Keywords

    Panel datasets; Poolability; Sequential testing;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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