IDEAS home Printed from https://ideas.repec.org/a/kap/jecgro/v14y2009i2p103-147.html
   My bibliography  Save this article

A Monte Carlo study of growth regressions

Author

Listed:
  • William Hauk
  • Romain Wacziarg

Abstract

Using Monte Carlo simulations, this paper evaluates the bias properties of common estimators used in growth regressions derived from the Solow model. We explicitly allow for measurement error in the right-hand side variables, as well as country-specific effects that are correlated with the regressors. Our results suggest that using an OLS estimator applied to a single cross-section of variables averaged over time (the between estimator) performs best in terms of the extent of bias on each of the estimated coefficients. The fixed-effects estimator and the Arellano-Bond estimator greatly overstate the speed of convergence under a wide variety of assumptions concerning the type and extent of measurement error, while between understates it somewhat. Finally, fixed effects and Arellano-Bond bias towards zero the slope estimates on the human and physical capital accumulation variables.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • William Hauk & Romain Wacziarg, 2009. "A Monte Carlo study of growth regressions," Journal of Economic Growth, Springer, vol. 14(2), pages 103-147, June.
    • Handle: RePEc:kap:jecgro:v:14:y:2009:i:2:p:103-147
    DOI: 10.1007/s10887-009-9040-3
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s10887-009-9040-3
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s10887-009-9040-3?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Francesco Caselli & James Feyrer, 2007. "The Marginal Product of Capital," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 122(2), pages 535-568.
    2. Caselli, Francesco, 2005. "Accounting for Cross-Country Income Differences," Handbook of Economic Growth, in: Philippe Aghion & Steven Durlauf (ed.), Handbook of Economic Growth, edition 1, volume 1, chapter 9, pages 679-741, Elsevier.
    3. Robert E. Hall & Charles I. Jones, 1999. "Why do Some Countries Produce So Much More Output Per Worker than Others?," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 114(1), pages 83-116.
    4. Stephen Bond & Anke Hoeffler & Jonathan Temple, 2001. "GMM Estimation of Empirical Growth Models," Economics Papers 2001-W21, Economics Group, Nuffield College, University of Oxford.
    5. Durlauf, Steven N. & Johnson, Paul A. & Temple, Jonathan R.W., 2005. "Growth Econometrics," Handbook of Economic Growth, in: Philippe Aghion & Steven Durlauf (ed.),Handbook of Economic Growth, edition 1, volume 1, chapter 8, pages 555-677, Elsevier.
    6. William Hauk & Romain Wacziarg, 2009. "A Monte Carlo study of growth regressions," Journal of Economic Growth, Springer, vol. 14(2), pages 103-147, June.
    7. Baumol, William J & Wolff, Edward N, 1988. "Productivity Growth, Convergence, and Welfare: Reply," American Economic Review, American Economic Association, vol. 78(5), pages 1155-1159, December.
    8. 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.
    9. Arellano, Manuel & Bover, Olympia, 1995. "Another look at the instrumental variable estimation of error-components models," Journal of Econometrics, Elsevier, vol. 68(1), pages 29-51, July.
    10. Arellano, Manuel, 2016. "Modelling optimal instrumental variables for dynamic panel data models," Research in Economics, Elsevier, vol. 70(2), pages 238-261.
    11. 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.
    12. Ross Levine & Norman Loayza & Thorsten Beck, 2002. "Financial Intermediation and Growth: Causality and Causes," Central Banking, Analysis, and Economic Policies Book Series, in: Leonardo Hernández & Klaus Schmidt-Hebbel & Norman Loayza (Series Editor) & Klaus Schmidt-Hebbel (Se (ed.),Banking, Financial Integration, and International Crises, edition 1, volume 3, chapter 2, pages 031-084, Central Bank of Chile.
    13. Wansbeek, Tom, 2001. "GMM estimation in panel data models with measurement error," Journal of Econometrics, Elsevier, vol. 104(2), pages 259-268, September.
    14. Robert M. Solow, 1956. "A Contribution to the Theory of Economic Growth," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 70(1), pages 65-94.
    15. Ben S. Bernanke & Refet S. Gürkaynak, 2002. "Is Growth Exogenous? Taking Mankiw, Romer, and Weil Seriously," NBER Chapters, in: NBER Macroeconomics Annual 2001, Volume 16, pages 11-72, National Bureau of Economic Research, Inc.
    16. Blundell, Richard & Bond, Stephen, 1998. "Initial conditions and moment restrictions in dynamic panel data models," Journal of Econometrics, Elsevier, vol. 87(1), pages 115-143, August.
    17. David H. Romer & Jeffrey A. Frankel, 1999. "Does Trade Cause Growth?," American Economic Review, American Economic Association, vol. 89(3), pages 379-399, June.
    18. 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.
    19. Caselli, Francesco & Esquivel, Gerardo & Lefort, Fernando, 1996. "Reopening the Convergence Debate: A New Look at Cross-Country Growth Empirics," Journal of Economic Growth, Springer, vol. 1(3), pages 363-389, September.
    20. Barro, Robert J & Lee, Jong-Wha, 2001. "International Data on Educational Attainment: Updates and Implications," Oxford Economic Papers, Oxford University Press, vol. 53(3), pages 541-563, July.
    21. Easterly, William & Loayza, Norman & Montiel, Peter, 1997. "Has Latin America's post-reform growth been disappointing?," Journal of International Economics, Elsevier, vol. 43(3-4), pages 287-311, November.
    22. Griliches, Zvi & Hausman, Jerry A., 1986. "Errors in variables in panel data," Journal of Econometrics, Elsevier, vol. 31(1), pages 93-118, February.
    23. Cragg, John G. & Donald, Stephen G., 1993. "Testing Identifiability and Specification in Instrumental Variable Models," Econometric Theory, Cambridge University Press, vol. 9(2), pages 222-240, April.
    24. Klepper, Steven & Leamer, Edward E, 1984. "Consistent Sets of Estimates for Regressions with Errors in All Variables," Econometrica, Econometric Society, vol. 52(1), pages 163-183, January.
    25. repec:cup:etheor:v:9:y:1993:i:2:p:222-40 is not listed on IDEAS
    26. James H. Stock & Motohiro Yogo, 2002. "Testing for Weak Instruments in Linear IV Regression," NBER Technical Working Papers 0284, National Bureau of Economic Research, Inc.
    27. Benhabib, Jess & Spiegel, Mark M., 1994. "The role of human capital in economic development evidence from aggregate cross-country data," Journal of Monetary Economics, Elsevier, vol. 34(2), pages 143-173, October.
    28. Douglas Staiger & James H. Stock, 1997. "Instrumental Variables Regression with Weak Instruments," Econometrica, Econometric Society, vol. 65(3), pages 557-586, May.
    29. Stock, James H & Wright, Jonathan H & Yogo, Motohiro, 2002. "A Survey of Weak Instruments and Weak Identification in Generalized Method of Moments," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(4), pages 518-529, October.
    30. Peter J. Klenow & Andrés Rodríguez-Clare, 1997. "The Neoclassical Revival in Growth Economics: Has It Gone Too Far?," NBER Chapters, in: NBER Macroeconomics Annual 1997, Volume 12, pages 73-114, National Bureau of Economic Research, Inc.
    31. Baumol, William J, 1986. "Productivity Growth, Convergence, and Welfare: What the Long-run Data Show," American Economic Review, American Economic Association, vol. 76(5), pages 1072-1085, December.
    32. Stephen Bond & Anke Hoeffler, 2001. "GMM Estimation of Empirical Growth Models," Economics Series Working Papers 2001-W21, University of Oxford, Department of Economics.
    33. Romain Wacziarg, 2002. "Review of Easterly's The Elusive Quest for Growth," Journal of Economic Literature, American Economic Association, vol. 40(3), pages 907-918, September.
    34. Delano S Villanueva & Roberto S Mariano & Diwa C Guinigundo & Abbas Mirakhor, 2023. "Testing the Neoclassical Theory of Economic Growth: A Panel Data Approach," World Scientific Book Chapters, in: Economic Adjustment and Growth Theory and Practice, chapter 2, pages 10-43, World Scientific Publishing Co. Pte. Ltd..
    35. Philippe Aghion & Steven Durlauf (ed.), 2005. "Handbook of Economic Growth," Handbook of Economic Growth, Elsevier, edition 1, volume 1, number 1.
    36. Manuel Arellano & Stephen Bond, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 58(2), pages 277-297.
    37. Windmeijer, Frank, 2005. "A finite sample correction for the variance of linear efficient two-step GMM estimators," Journal of Econometrics, Elsevier, vol. 126(1), pages 25-51, May.
    38. 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.
    39. Jonathan R. W. Temple, 1998. "Robustness tests of the augmented Solow model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 13(4), pages 361-375.
    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. Lee, Angela Y. & Aaker, Jennifer L., 2006. "A Monte Carlo Study of Growth Regressions," Research Papers 1836r1, Stanford University, Graduate School of Business.
    2. Ulaşan, Bülent, 2012. "Cross-country growth empirics and model uncertainty: An overview," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 6, pages 1-69.
    3. 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 (IfW Kiel), vol. 3, pages 1-72.
    4. Hauk, William R., 2017. "Endogeneity bias and growth regressions," Journal of Macroeconomics, Elsevier, vol. 51(C), pages 143-161.
    5. Jean-Louis ARCAND & Béatrice D'HOMBRES, 2002. "Explaining the Negative Coefficient Associated with Human Capital in Augmented Solow Growth Regressions," Working Papers 200227, CERDI.
    6. Bloom, David E. & Canning, David & Kotschy, Rainer & Prettner, Klaus & Schünemann, Johannes, 2024. "Health and economic growth: Reconciling the micro and macro evidence," World Development, Elsevier, vol. 178(C).
    7. Aisen, Ari & Veiga, Francisco José, 2013. "How does political instability affect economic growth?," European Journal of Political Economy, Elsevier, vol. 29(C), pages 151-167.
    8. 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.
    9. Vieira, Flávio & MacDonald, Ronald & Damasceno, Aderbal, 2012. "The role of institutions in cross-section income and panel data growth models: A deeper investigation on the weakness and proliferation of instruments," Journal of Comparative Economics, Elsevier, vol. 40(1), pages 127-140.
    10. Vu, Khuong M & Asongu, Simplice, 2020. "Backwardness advantage and economic growth in the information age: A cross-country empirical study," Technological Forecasting and Social Change, Elsevier, vol. 159(C).
    11. John Knight & Sai Ding, 2008. "Can the Augmented Solow Model Explain China's Economic Growth? A Cross-Country Panel Data Analysis," Economics Series Working Papers 380, University of Oxford, Department of Economics.
    12. Jones, C.I., 2016. "The Facts of Economic Growth," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 3-69, Elsevier.
    13. Ulaşan, Bülent, 2011. "Cross-country growth empirics and model uncertainty: An overview," Economics Discussion Papers 2011-37, Kiel Institute for the World Economy (IfW Kiel).
    14. Chris Papageorgiou & Petia Stoytcheva, 2005. "What Do We Know About the Impact of AIDS on Cross-Country Income So Far?," Departmental Working Papers 2005-01, Department of Economics, Louisiana State University.
    15. Ding, Sai & Knight, John, 2009. "Can the augmented Solow model explain China's remarkable economic growth? A cross-country panel data analysis," Journal of Comparative Economics, Elsevier, vol. 37(3), pages 432-452, September.
    16. Fedderke, Johannes & Klitgaard, Robert, 2013. "How Much Do Rights Matter?," World Development, Elsevier, vol. 51(C), pages 187-206.
    17. Papaioannou, Elias, 2007. "Finance and growth: a macroeconomic assessment of the evidence from a European angle," Working Paper Series 787, European Central Bank.
    18. Bayraktar-Sağlam, Bahar & Yetkiner, Hakan, 2014. "A Romerian contribution to the empirics of economic growth," Journal of Policy Modeling, Elsevier, vol. 36(2), pages 257-272.
    19. Rui HAO & Zheng WEI, 2009. "Sources Of Income Differences Across Chinese Provinces During The Reform Period: A Development Accounting Exercise," The Developing Economies, Institute of Developing Economies, vol. 47(1), pages 1-29, March.
    20. Alali, Walid Y., 2010. "Impact of Institutions and Policy on Economic Growth: Empirical Evidence," EconStor Preprints 269878, ZBW - Leibniz Information Centre for Economics.

    More about this item

    Keywords

    Growth regressions; Measurement error; System-GMM; O47; O57; C15; C23;
    All these keywords.

    JEL classification:

    • O4 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity
    • O5 - Economic Development, Innovation, Technological Change, and Growth - - Economywide Country Studies

    Lists

    This item is featured on the following reading lists, Wikipedia, or ReplicationWiki pages:
    1. A Monte Carlo study of growth regressions (JEG 2009) in ReplicationWiki

    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:kap:jecgro:v:14:y:2009:i:2:p:103-147. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.