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System GMM estimation with a small sample

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  • Marcelo Soto

Abstract

Properties of GMM estimators for panel data, which have become very popular in the empirical economic growth literature, are not well known when the number of individuals is small. This paper analyses through Monte Carlo simulations the properties of various GMM and other estimators when the number of individuals is the one typically available in country growth studies. It is found that, provided that some persistency is present in the series, the system GMM estimator has a lower bias and higher efficiency than all the other estimators analysed, including the standard first-differences GMM estimator.

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Bibliographic Info

Paper provided by Barcelona Graduate School of Economics in its series Working Papers with number 395.

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Date of creation: Jul 2009
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Handle: RePEc:bge:wpaper:395

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Keywords: Economic Growth; System GMM estimation; Monte Carlo Simulations;

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  1. R Blundell & Steven Bond, . "Initial conditions and moment restrictions in dynamic panel data model," Economics Papers W14&104., Economics Group, Nuffield College, University of Oxford.
  2. Carl-Johan Dalgaard & Henrik Hansen & Finn Tarp, 2004. "On The Empirics of Foreign Aid and Growth," Economic Journal, Royal Economic Society, Royal Economic Society, vol. 114(496), pages F191-F216, 06.
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  4. Windmeijer, Frank, 2005. "A finite sample correction for the variance of linear efficient two-step GMM estimators," Journal of Econometrics, Elsevier, Elsevier, vol. 126(1), pages 25-51, May.
  5. Greenaway, David & Morgan, Wyn & Wright, Peter, 2002. "Trade liberalisation and growth in developing countries," Journal of Development Economics, Elsevier, Elsevier, vol. 67(1), pages 229-244, February.
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  8. Caselli, Francesco & Esquivel, Gerardo & Lefort, Fernando, 1996. " Reopening the Convergence Debate: A New Look at Cross-Country Growth Empirics," Journal of Economic Growth, Springer, Springer, vol. 1(3), pages 363-89, September.
  9. Kiviet, Jan F., 1995. "On bias, inconsistency, and efficiency of various estimators in dynamic panel data models," Journal of Econometrics, Elsevier, Elsevier, vol. 68(1), pages 53-78, July.
  10. M Arellano & O Bover, 1990. "Another Look at the Instrumental Variable Estimation of Error-Components Models," CEP Discussion Papers, Centre for Economic Performance, LSE dp0007, Centre for Economic Performance, LSE.
  11. Aghion, Philippe & Bacchetta, Philippe & Rancière, Romain & Rogoff, Kenneth, 2006. "Exchange Rate Volatility and Productivity Growth: The Role of Financial Development," CEPR Discussion Papers, C.E.P.R. Discussion Papers 5629, C.E.P.R. Discussion Papers.
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Cited by:
  1. Barth, Anne-Kathrin & Heimeshoff, Ulrich, 2012. "Does the growth of mobile markets cause the demise of fixed networks? Evidence from the European Union," DICE Discussion Papers, Heinrich‐Heine‐Universität Düsseldorf, Düsseldorf Institute for Competition Economics (DICE) 42, Heinrich‐Heine‐Universität Düsseldorf, Düsseldorf Institute for Competition Economics (DICE).
  2. Ziesemer, Thomas H.W., 2010. "The impact of the credit crisis on poor developing countries: Growth, worker remittances, accumulation and migration," Economic Modelling, Elsevier, Elsevier, vol. 27(5), pages 1230-1245, September.
  3. Roach, Travis, 2013. "A dynamic state-level analysis of carbon dioxide emissions in the United States," Energy Policy, Elsevier, Elsevier, vol. 59(C), pages 931-937.
  4. Kosta Josifidis & Radmila Dragutinović Mitrović & Olgica Ivančev, 2012. "Heterogeneity of Growth in the West Balkans and Emerging Europe: A Dynamic Panel Data Model Approach," Panoeconomicus, Savez ekonomista Vojvodine, Novi Sad, Serbia, Savez ekonomista Vojvodine, Novi Sad, Serbia, vol. 59(2), pages 157-183, May.
  5. Karsten Staehr, 2010. "The global financial crisis and public finances in the New EU Countries from Central and Eastern Europe," Bank of Estonia Working Papers, Bank of Estonia wp2010-02, Bank of Estonia, revised 04 Feb 2010.
  6. Hartwig, Jochen, 2014. "Testing the Uzawa–Lucas model with OECD data," Research in Economics, Elsevier, Elsevier, vol. 68(2), pages 144-156.

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