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A Monte Carlo Study of Growth Regressions

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Author Info
Lee, Angela Y. (Stanford U)
Aaker, Jennifer L. (U of South Carolina)
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 coeffcients. 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.

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Paper provided by Stanford University, Graduate School of Business in its series Research Papers with number 1836r1.

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Date of creation: Nov 2006
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Handle: RePEc:ecl:stabus:1836r1

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  21. Levine, Ross & Loayza, Norman & Beck, Thorsten, 2000. "Financial intermediation and growth: Causality and causes," Journal of Monetary Economics, Elsevier, vol. 46(1), pages 31-77, August. [Downloadable!] (restricted)
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  22. Mankiw, N Gregory & Romer, David & Weil, David N, 1992. "A Contribution to the Empirics of Economic Growth," The Quarterly Journal of Economics, MIT Press, vol. 107(2), pages 407-37, May. [Downloadable!] (restricted)
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  23. Griliches, Zvi & Hausman, Jerry A., 1986. "Errors in variables in panel data," Journal of Econometrics, Elsevier, vol. 31(1), pages 93-118, February. [Downloadable!] (restricted)
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  24. 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. [Downloadable!] (restricted)
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  26. Cragg, John G. & Donald, Stephen G., 1993. "Testing Identifiability and Specification in Instrumental Variable Models," Econometric Theory, Cambridge University Press, vol. 9(02), pages 222-240, April. [Downloadable!]
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