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Can Dynamic Panel Data Explain the Finance-Growth Link? An Empirical Likelihood Approach

  • Umut Oguzoglu

    ()

    (Department of Economics, University of Guelph)

  • Thanasis Stengos

    ()

    (Department of Economics, University of Guelph)

The short run effect of the financial intermediary development on economic growth is analyzed using an unbalanced panel of 77 countries covering 35 years. Empirical Likelihood (EL) estimation is used and compared to more conventional GMM methods that weight moment conditions equally over the sample. However, if a part of the data is associated with only weak instruments, GMM estimators are subject to considerable small sample bias. EL appropriately re-weights the moment restrictions to deal with that problem. Using EL, we obtain more robust estimates of the effect of financial intermediation on economic growth than GMM.

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Paper provided by University of Guelph, Department of Economics and Finance in its series Working Papers with number 0502.

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Length: 29 pages
Date of creation: 2005
Date of revision:
Handle: RePEc:gue:guelph:2005-2
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Web page: https://www.uoguelph.ca/economics/

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  1. Kalaitzidakis, P. & Mamuneas, T.P. & Savvides, A. & Stengos, T., 2000. "Measures of Human Capital and Nonlinearities in Economic Growth," Working Papers 2000-5, University of Guelph, Department of Economics and Finance.
  2. Whitney Newey & Richard Smith, 2003. "Higher order properties of GMM and generalised empirical likelihood estimators," CeMMAP working papers CWP04/03, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
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  7. Levine, Ross & Renelt, David, 1992. "A Sensitivity Analysis of Cross-Country Growth Regressions," American Economic Review, American Economic Association, vol. 82(4), pages 942-63, September.
  8. M Arellano & O Bover, 1990. "Another Look at the Instrumental Variable Estimation of Error-Components Models," CEP Discussion Papers dp0007, Centre for Economic Performance, LSE.
  9. 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.
  10. Stephen Bond & Frank Windmeijer, 2002. "Finite Sample Inference for GMM Estimators in Linear Panel Data Models," 10th International Conference on Panel Data, Berlin, July 5-6, 2002 C6-3, International Conferences on Panel Data.
  11. McCaig, Brian & Stengos, Thanasis, 2005. "Financial intermediation and growth: Some robustness results," Economics Letters, Elsevier, vol. 88(3), pages 306-312, September.
  12. Mittelhammer, Ron C & Judge, George G. & Schoenberg, Ron, 2003. "Empirical Evidence Concerning the Finite Sample Performance of EL-Type Structural Equation Estimation and Inference Methods," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series qt2xm0n02g, Department of Agricultural & Resource Economics, UC Berkeley.
  13. Levine, Ross, 1999. "Law, Finance, and Economic Growth," Journal of Financial Intermediation, Elsevier, vol. 8(1-2), pages 8-35, January.
  14. Arellano, Manuel & Bond, Stephen, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," Review of Economic Studies, Wiley Blackwell, vol. 58(2), pages 277-97, April.
  15. Kiviet, Jan F., 1995. "On bias, inconsistency, and efficiency of various estimators in dynamic panel data models," Journal of Econometrics, Elsevier, vol. 68(1), pages 53-78, July.
  16. Judson, Ruth A. & Owen, Ann L., 1999. "Estimating dynamic panel data models: a guide for macroeconomists," Economics Letters, Elsevier, vol. 65(1), pages 9-15, October.
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