Truth and Robustness in Cross-country Growth Regressions
AbstractWe re-examine studies of cross-country growth regressions by Levine and Renelt ("American Economic Review", Vol. 82, 1992, pp. 942-963) and Sala-i-Martin ("American Economic Review", Vol. 87, 1997a, pp. 178-183; Economics Department, Columbia, University, 1997b). In a realistic Monte Carlo experiment, their variants of Edward Leamer's extreme-bounds analysis are compared with a cross-sectional version of the general-to-specific search methodology associated with the LSE approach to econometrics. Levine and Renelt's method has low size and low power, while Sala-i-Martin's method has high size and high power. The general-to-specific methodology is shown to have a near nominal size and high power. Sala-i-Martin's method and the general-to-specific method are then applied to the actual data from Sala-i-Martin's original study. Copyright 2004 Blackwell Publishing Ltd.
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Bibliographic InfoArticle provided by Department of Economics, University of Oxford in its journal Oxford Bulletin of Economics & Statistics.
Volume (Year): 66 (2004)
Issue (Month): 5 (December)
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Other versions of this item:
- Kevin D. Hoover & Stephen J. Perez, . "Truth and Robustness in Cross-country Growth Regressions," Department of Economics 01-01, California Davis - Department of Economics.
- Hoover, Kevin, 2000. "Truth and Robustness in Cross-Country Growth Regression," Working Papers 01-1, University of California at Davis, Department of Economics.
- Kevin Hoover & Harris Dellas, 2003. "Truth and Robustness in Cross-country Growth Regressions," Working Papers 11, University of California, Davis, Department of Economics.
- C40 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - General
- C80 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - General
- O40 - Economic Development, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - General
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