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A Monte Carlo evaluation of the efficiency of the PCSE estimator

Author

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  • Xiujian Chen
  • Shu Lin
  • W. Robert Reed

Abstract

Panel data characterized by groupwise heteroscedasticity, cross-sectional correlation, and AR(1) serial correlation pose problems for econometric analyses. It is well known that the asymptotically efficient, Feasible Generalized Least Squares (FGLS) estimator (Parks) sometimes performs poorly in finite samples. In a widely cited paper, Beck and Katz (1995) claim that their estimator panel-corrected SE (PCSE) is able to produce more accurate coefficient SE without any loss in efficiency in 'practical research situations'. This study disputes that claim. We find that the PCSE estimator is usually less efficient than Parks - and substantially so - except when the number of time periods is close to the number of cross sections.

Suggested Citation

  • Xiujian Chen & Shu Lin & W. Robert Reed, 2010. "A Monte Carlo evaluation of the efficiency of the PCSE estimator," Applied Economics Letters, Taylor & Francis Journals, vol. 17(1), pages 7-10, January.
    • Handle: RePEc:taf:apeclt:v:17:y:2010:i:1:p:7-10
    DOI: 10.1080/13504850701719702
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    Cited by:

    1. Moundigbaye, Mantobaye & Messemer, Clarisse & Parks, Richard W. & Reed, W. Robert, 2020. "Bootstrap methods for inference in the Parks model," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 14, pages 1-18.
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    9. José M. Alonso & Judith Clifton & Daniel Díaz-Fuentes, 2015. "Did New Public Management Matter? An empirical analysis of the outsourcing and decentralization effects on public sector size," Public Management Review, Taylor & Francis Journals, vol. 17(5), pages 643-660, May.
    10. Şanlı, Devran & Gülbay Yiğiteli, Nadide, 2020. "Türkiye’de enflasyonun belirleyicilerine dair bölgesel bir analiz 2005-2018 [Regional analysis of the causes inflation in Turkey 2005-2018]," MPRA Paper 122699, University Library of Munich, Germany.
    11. Samet Günay, 2017. "Risk Configuration of S&P 500 Industries: Sigma-risk and Alpha-risk Approximation," Margin: The Journal of Applied Economic Research, National Council of Applied Economic Research, vol. 11(2), pages 196-221, May.
    12. Hyejin Ko, 2020. "Measuring fiscal sustainability in the welfare state: fiscal space as fiscal sustainability," International Economics and Economic Policy, Springer, vol. 17(2), pages 531-554, May.
    13. Mehmet Ugur, 2013. "Governance, regulation and innovation: new perspectives and evidence," Chapters, in: Mehmet Ugur (ed.), Governance, Regulation and Innovation, chapter 1, pages 1-22, Edward Elgar Publishing.
    14. Jiang, Jinglu & Goodarzi, Soheil & Kahai, Surinder & Cameron, Ann-Frances, 2025. "Navigating the technology-tide: Mitigating the impact of technology-related political risks on firm innovativeness through strategic diversification and board technology competency," Journal of Business Research, Elsevier, vol. 194(C).
    15. Roberto Fernández Llera & María A. García Valiñas, 2013. "The Role of Regional Public Enterprises in Spain: Room for a Shadow Government?," Hacienda Pública Española / Review of Public Economics, IEF, vol. 205(2), pages 9-31, June.
    16. Le Clech, Néstor A., 2024. "Policy market orientation, property rights, and corruption effects on the rent of non-renewable resources in Latin America and the Caribbean," Resources Policy, Elsevier, vol. 91(C).
    17. Néstor A. Clech, 2025. "Macroeconomic and institutional determinants of human capital wealth: gender disparities and implications," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 42(1), pages 121-153, April.
    18. Zohaib Zahid & Jijian Zhang & Chongyan Gao & Judit Oláh, 2025. "ICT-Driven Strategies for Enhancing Energy Efficiency in G20 Economies: Moderating the Role of Governance in Achieving Environmental Sustainability," Energies, MDPI, vol. 18(3), pages 1-22, February.

    More about this item

    JEL classification:

    • 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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