IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2602.04060.html

The Output Convergence Debate Revisited: Lessons from recent developments in the analysis of panel data models

Author

Abstract

This paper provides a critical examination of the empirical basis of the output convergence debate in the light of recent developments in the analysis of dynamic heterogeneous panels with interactive effects. It shows that popular tools such as Barro's cross-country regressions and two-way fixed effects (TWFE) estimators that assume parallel trends and homogeneous dynamics lead to substantial under-estimation of the speed of convergence and misleading inference. Instead, dynamic common correlated effects (DCCE) estimators due to Chudik and Pesaran (2015a) provide consistent estimates and valid inference that are robust to nonparallel trends and correlated heterogeneity and apply even if there are breaks, trends and/or unit roots in the latent technology factor. It also suggests a way to estimate the effect of slowly moving determinants of growth. The theoretical findings are augmented with empirical evidence using Penn World Tables data, finding little evidence of per capita output convergence across countries, very slow evidence of cross country growth convergence, and reasonably fast within country convergence. Capital accumulation is found to be the most important single determinant of cross-country differences in output while slow moving indicators such as potential for conflict and protection of property rights proved to be statistically significant determinants of the steady state levels of output per capita. We are also able to replicate a positive evidence of democratization on output, but we find that the statistical significance of this effect to fall as we allow for nonparallel trends and dynamic heterogeneity.

Suggested Citation

  • M Hashem Pesaran & Ron Smith, 2026. "The Output Convergence Debate Revisited: Lessons from recent developments in the analysis of panel data models," Papers 2602.04060, arXiv.org.
  • Handle: RePEc:arx:papers:2602.04060
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2602.04060
    File Function: Latest version
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Kapetanios, G. & Pesaran, M. Hashem & Yamagata, T., 2011. "Panels with non-stationary multifactor error structures," Journal of Econometrics, Elsevier, vol. 160(2), pages 326-348, February.
    2. M. Hashem Pesaran, 2006. "Estimation and Inference in Large Heterogeneous Panels with a Multifactor Error Structure," Econometrica, Econometric Society, vol. 74(4), pages 967-1012, July.
    3. Jonathan Temple, 1999. "The New Growth Evidence," Journal of Economic Literature, American Economic Association, vol. 37(1), pages 112-156, March.
    4. Binder, Michael & Pesaran, M Hashem, 1999. "Stochastic Growth Models and Their Econometric Implications," Journal of Economic Growth, Springer, vol. 4(2), pages 139-183, June.
    5. Daron Acemoglu & Simon Johnson & James A. Robinson, 2001. "The Colonial Origins of Comparative Development: An Empirical Investigation," American Economic Review, American Economic Association, vol. 91(5), pages 1369-1401, December.
    6. M. Hashem Pesaran & Qiankun Zhou, 2018. "Estimation of time-invariant effects in static panel data models," Econometric Reviews, Taylor & Francis Journals, vol. 37(10), pages 1137-1171, November.
    7. Pesaran, M. H. & Xie, Y., 2021. "How to Detect Network Dependence in Latent Factor Models? A Bias-Corrected CD Testy," Cambridge Working Papers in Economics 2158, Faculty of Economics, University of Cambridge.
    8. Moon, Hyungsik Roger & Weidner, Martin, 2017. "Dynamic Linear Panel Regression Models With Interactive Fixed Effects," Econometric Theory, Cambridge University Press, vol. 33(1), pages 158-195, February.
    9. Aghion, Philippe & Howitt, Peter, 1992. "A Model of Growth through Creative Destruction," Econometrica, Econometric Society, vol. 60(2), pages 323-351, March.
    10. Kahn, Matthew E. & Mohaddes, Kamiar & Ng, Ryan N.C. & Pesaran, M. Hashem & Raissi, Mehdi & Yang, Jui-Chung, 2021. "Long-term macroeconomic effects of climate change: A cross-country analysis," Energy Economics, Elsevier, vol. 104(C).
    11. Joakim Westerlund & Hande Karabiyik & Paresh Kumar Narayan & Seema Narayan, 2022. "Estimating the Speed of Adjustment of Leverage in the Presence of Interactive Effects [The Determinants of Capital Structure: Capital Market-Oriented versus Bank-Oriented Institutions]," Journal of Financial Econometrics, Oxford University Press, vol. 20(5), pages 942-960.
    12. M. Hashem Pesaran & Liying Yang, 2023. "Heterogeneous Autoregressions in Short T Panel Data Models," CESifo Working Paper Series 10509, CESifo.
    13. Pesaran, M. Hashem & Yang, Cynthia Fan, 2021. "Estimation and inference in spatial models with dominant units," Journal of Econometrics, Elsevier, vol. 221(2), pages 591-615.
    14. Robert J. Barro, 1991. "Economic Growth in a Cross Section of Countries," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 106(2), pages 407-443.
    15. Paul Johnson & Chris Papageorgiou, 2020. "What Remains of Cross-Country Convergence?," Journal of Economic Literature, American Economic Association, vol. 58(1), pages 129-175, March.
    16. Jan Ditzen, 2021. "Estimating long-run effects and the exponent of cross-sectional dependence: An update to xtdcce2," Stata Journal, StataCorp LLC, vol. 21(3), pages 687-707, September.
    17. Pesaran, M. Hashem & Smith, Ron, 1995. "Estimating long-run relationships from dynamic heterogeneous panels," Journal of Econometrics, Elsevier, vol. 68(1), pages 79-113, July.
    18. Gerdie Everaert & Tom De Groote, 2016. "Common Correlated Effects Estimation of Dynamic Panels with Cross-Sectional Dependence," Econometric Reviews, Taylor & Francis Journals, vol. 35(3), pages 428-463, March.
    19. Steven N. Durlauf, 2009. "The Rise and Fall of Cross-Country Growth Regressions," History of Political Economy, Duke University Press, vol. 41(5), pages 315-333, Supplemen.
    20. Kevin Lee & M. Hashem Pesaran & Ron Smith, 1998. "Growth Empirics: A Panel Data Approach—A Comment," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 113(1), pages 319-323.
    21. Maseland, Robbert, 2021. "Contingent determinants," Journal of Development Economics, Elsevier, vol. 151(C).
    22. M. Hashem Pesaran & Liying Yang, 2024. "Heterogeneous autoregressions in short T panel data models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(7), pages 1359-1378, November.
    23. Michael Kremer & Jack Willis & Yang You, 2022. "Converging to Convergence," NBER Macroeconomics Annual, University of Chicago Press, vol. 36(1), pages 337-412.
    24. Juodis, Artūras & Karabiyik, Hande & Westerlund, Joakim, 2021. "On the robustness of the pooled CCE estimator," Journal of Econometrics, Elsevier, vol. 220(2), pages 325-348.
    25. N. Gregory Mankiw & David Romer & David N. Weil, 1992. "A Contribution to the Empirics of Economic Growth," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 107(2), pages 407-437.
    26. Chudik, Alexander & Pesaran, M. Hashem, 2015. "Common correlated effects estimation of heterogeneous dynamic panel data models with weakly exogenous regressors," Journal of Econometrics, Elsevier, vol. 188(2), pages 393-420.
    27. Nickell, Stephen J, 1981. "Biases in Dynamic Models with Fixed Effects," Econometrica, Econometric Society, vol. 49(6), pages 1417-1426, November.
    28. Lee, Kevin & Pesaran, M Hashem & Smith, Ron, 1997. "Growth and Convergence in Multi-country Empirical Stochastic Solow Model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 12(4), pages 357-392, July-Aug..
    29. Marcelle Chauvet & Chengxuan Yu, 2006. "International business cycles: G7 and OECD countries," Economic Review, Federal Reserve Bank of Atlanta, vol. 91(Q 1), pages 43-54.
    30. Ron P. Smith, 2024. "Econometric Aspects of Convergence: A Survey," Open Economies Review, Springer, vol. 35(4), pages 701-721, September.
    31. Ignace De Vos & Gerdie Everaert, 2021. "Bias-Corrected Common Correlated Effects Pooled Estimation in Dynamic Panels," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(1), pages 294-306, January.
    32. Kinnunen, Maarit & Wood, Emma H. & Li, Yanning & Moss, Jonathan, 2022. "Self-recorded conversations in tourism memory research," Annals of Tourism Research, Elsevier, vol. 96(C).
    33. Daron Acemoglu & Suresh Naidu & Pascual Restrepo & James A. Robinson, 2019. "Democracy Does Cause Growth," Journal of Political Economy, University of Chicago Press, vol. 127(1), pages 47-100.
    34. Nazrul Islam, 1995. "Growth Empirics: A Panel Data Approach," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 110(4), pages 1127-1170.
    35. Joakim Westerlund, 2018. "CCE in panels with general unknown factors," Econometrics Journal, Royal Economic Society, vol. 21(3), pages 264-276, October.
    36. Lee, Nayoung & Moon, Hyungsik Roger & Zhou, Qiankun, 2017. "Many IVs estimation of dynamic panel regression models with measurement error," Journal of Econometrics, Elsevier, vol. 200(2), pages 251-259.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ron P. Smith, 2024. "Econometric Aspects of Convergence: A Survey," Open Economies Review, Springer, vol. 35(4), pages 701-721, September.
    2. Dai, Siqi & Hong, Yongmiao & Li, Haiqi & Zheng, Chaowen, 2025. "Shrinkage estimation of spatial panel data models with multiple structural breaks and a multifactor error structure," Journal of Econometrics, Elsevier, vol. 251(C).
    3. Markus Eberhardt & Francis Teal, 2011. "Econometrics For Grumblers: A New Look At The Literature On Cross‐Country Growth Empirics," Journal of Economic Surveys, Wiley Blackwell, vol. 25(1), pages 109-155, February.
    4. Kian Ong & Kent Matthews & Baoshun Wang, 2024. "The Rising Tides That Lift the Boats: Growth through Heterogeneous Convergence in Chinese Provinces," Open Economies Review, Springer, vol. 35(4), pages 751-778, September.
    5. Naima Chrid & Sami Saafi & Mohamed Chakroun, 2021. "Export Upgrading and Economic Growth: a Panel Cointegration and Causality Analysis," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 12(2), pages 811-841, June.
    6. Capolupo, Rosa, 2009. "The New Growth Theories and Their Empirics after Twenty Years," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy, vol. 3, pages 1-72.
    7. Jan Ditzen, 2016. "xtdcce: Estimating Dynamic Common Correlated Effects in Stata," SEEC Discussion Papers 1601, Spatial Economics and Econometrics Centre, Heriot Watt University.
    8. Markus Eberhardt & Francis Teal, 2020. "The Magnitude of the Task Ahead: Macro Implications of Heterogeneous Technology," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 66(2), pages 334-360, June.
    9. Markus Eberhardt & Francis Teal, 2011. "Econometrics For Grumblers: A New Look At The Literature On Cross‐Country Growth Empirics," Journal of Economic Surveys, Wiley Blackwell, vol. 25(1), pages 109-155, 02.

    More about this item

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • E10 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - General
    • F43 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - Economic Growth of Open Economies
    • O40 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - General

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:arx:papers:2602.04060. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.