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Panel Estimation for Worriers

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  • Markus Eberhardt
  • Anindya Banerjee and J. James Reade

Abstract

The recent blossoming of panel econometrics in general and panel time-series methods in particular has enabled many more research questions to be investigated than before. However, this development has not assuaged serious concerns over the lack of diagnostic testing procedures in panel econometrics, in particular vis-a-vis the prominence of such practices in the time-series domain: the recent introduction of residual cross-section independence tests aside, within mainstream panel empirics the combination of 'model', 'spefication' and 'testing' typically refers to the distinction between fixed and random effects, as opposed to a rigorous investigation of residual properties. In this paper we investigate these issues in the context of non-stationary panels with multifactor error structure, employing Monte Carlo simulations to investigate the distributions and rejection frequencies for standard time-series diagnostic procedures, including tests for residual autocorrelation, ARCH, normality, heteroskedasticity and functional form.

Suggested Citation

  • Markus Eberhardt & Anindya Banerjee and J. James Reade, 2010. "Panel Estimation for Worriers," Economics Series Working Papers 514, University of Oxford, Department of Economics.
    • Handle: RePEc:oxf:wpaper:514
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    References listed on IDEAS

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    1. Markus Eberhardt & Christian Helmers & Hubert Strauss, 2013. "Do Spillovers Matter When Estimating Private Returns to R&D?," The Review of Economics and Statistics, MIT Press, vol. 95(2), pages 436-448, May.
    2. Chihwa Kao & Min‐Hsien Chiang & Bangtian Chen, 1999. "International R&D Spillovers: An Application of Estimation and Inference in Panel Cointegration," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 61(S1), pages 691-709, November.
    3. Costantini, Mauro & Destefanis, Sergio, 2009. "Cointegration analysis for cross-sectionally dependent panels: The case of regional production functions," Economic Modelling, Elsevier, vol. 26(2), pages 320-327, March.
    4. Cavalcanti, Tiago V. de V. & Mohaddes, Kamiar & Raissi, Mehdi, 2011. "Growth, development and natural resources: New evidence using a heterogeneous panel analysis," The Quarterly Review of Economics and Finance, Elsevier, vol. 51(4), pages 305-318.
    5. repec:bla:obuest:v:61:y:1999:i:0:p:691-709 is not listed on IDEAS
    6. Philippe Aghion & Steven Durlauf (ed.), 2005. "Handbook of Economic Growth," Handbook of Economic Growth, Elsevier, edition 1, volume 1, number 1.
    7. Franz C. Palm & Gérard A. Pfann, 1995. "Unraveling Trend and Stationary Components of Total Factor Productivity," Annals of Economics and Statistics, GENES, issue 39, pages 67-92.
    8. Eberhardt, Markus & Bond, Stephen, 2009. "Cross-section dependence in nonstationary panel models: a novel estimator," MPRA Paper 17692, University Library of Munich, Germany.
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    Cited by:

    1. Julio, Juan Manuel & Lozano, Ignacio, 2016. "Descentralización fiscal y crecimiento económico en Colombia: evidencia de datos de panel a nivel regional," Revista CEPAL, Naciones Unidas Comisión Económica para América Latina y el Caribe (CEPAL), August.
    2. Anindya Banerjee & Josep Lluis Carrion-i-Silvestre, 2011. "Testing for Panel Cointegration Using Common Correlated Effects," Discussion Papers 11-16, Department of Economics, University of Birmingham.
    3. Giray Gozgor, 2013. "Testing Unemployment Persistence in Central and Eastern European Countries," International Journal of Economics and Financial Issues, Econjournals, vol. 3(3), pages 694-700.
    4. Bakas, Dimitrios & Papapetrou, Evangelia, 2014. "Unemployment in Greece: Evidence from Greek regions using panel unit root tests," The Quarterly Review of Economics and Finance, Elsevier, vol. 54(4), pages 551-562.
    5. Anindya Banerjee & Josep Lluís Carrion-i-Silvestre, 2017. "Testing for Panel Cointegration Using Common Correlated Effects Estimators," Journal of Time Series Analysis, Wiley Blackwell, vol. 38(4), pages 610-636, July.
    6. Evangelia Papapetrou & Dimitrios Bakas, 2012. "Unemployment in Greece: evidence from Greek regions," Working Papers 146, Bank of Greece.
    7. Georg von Graevenitz & Christian Helmers & Valentine Millot & Oliver Turnbull, 2016. "Does Online Search Predict Sales? Evidence from Big Data for Car Markets in Germany and the UK," Working Papers 71, Queen Mary, University of London, School of Business and Management, Centre for Globalisation Research.
    8. Roth, Felix & Gros, Daniel & Nowak-Lehmann D., Felicitas, 2012. "Has the financial crisis eroded citizens' trust in the European Central Bank? Panel data evidence for the Euro area, 1999-2011," University of Göttingen Working Papers in Economics 124, University of Goettingen, Department of Economics.
    9. Julio, Juan Manuel & Lozano, Ignacio, 2016. "Fiscal decentralization and economic growth in Colombia: evidence from regional-level panel data," Revista CEPAL, Naciones Unidas Comisión Económica para América Latina y el Caribe (CEPAL), August.
    10. Dierk Herzer & Holger Strulik & Sebastian Vollmer, 2012. "The long-run determinants of fertility: one century of demographic change 1900–1999," Journal of Economic Growth, Springer, vol. 17(4), pages 357-385, December.
    11. Heike Belitz & Florian Mölders, 2016. "International knowledge spillovers through high-tech imports and R&D of foreign-owned firms," The Journal of International Trade & Economic Development, Taylor & Francis Journals, vol. 25(4), pages 590-613, June.
    12. Ernesto R. Gantman & Marcelo P. Dabós, 2018. "Does trade openness influence the real effective exchange rate? New evidence from panel time-series," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 9(1), pages 91-113, March.
    13. Markus Eberhardt & Francis Teal, 2013. "No Mangoes in the Tundra: Spatial Heterogeneity in Agricultural Productivity Analysis," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 75(6), pages 914-939, December.
    14. repec:got:cegedp:124 is not listed on IDEAS

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    More about this item

    Keywords

    Panel time-series; residual diagnostics; common factor model;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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