No Need to Run Millions of Regressions
We argue that in modelling cross-country growth models one should first identify so-called outlying observations. For the data set of Sala-i-Martin, we use the least median of squares (LMS) estimator to identify outliers. As LMS is not suited for inference, we then use reweighted least squares (RLS) for our cross-country growth models. We identify 27 variables that are significantly related to economic growth. Subsequently, applying Sala-i-Martin's approach for the data set without outliers hardly reveals any additional information. Variables that are insignificant according to the RLS method are generally not significantly related to economic growth under the Sala-i-Martin approach.
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- de Haan, Jakob & Sturm, Jan-Egbert, 2000.
"On the relationship between economic freedom and economic growth,"
European Journal of Political Economy,
Elsevier, vol. 16(2), pages 215-241, June.
- Haan, Jakob de & Sturm, Jan-Egbert, 1999. "On the relationship between economic freedom and economic growth," CCSO Working Papers 199903, University of Groningen, CCSO Centre for Economic Research.
- Leamer, Edward E, 1983. "Let's Take the Con Out of Econometrics," American Economic Review, American Economic Association, vol. 73(1), pages 31-43, March.
- Sala-i-Martin, Xavier, 1997. "I Just Ran Two Million Regressions," American Economic Review, American Economic Association, vol. 87(2), pages 178-183, May.
- Levine, Ross & Renelt, David, 1992. "A Sensitivity Analysis of Cross-Country Growth Regressions," American Economic Review, American Economic Association, vol. 82(4), pages 942-963, September.Full references (including those not matched with items on IDEAS)
- Levine, Ross & Renelt, David, 1991. "A sensitivity analysis of cross-country growth regressions," Policy Research Working Paper Series 609, The World Bank.
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