Truth and robustness in cross-country growth regressions

Arbeitspapier

The work of Levine and Renelt (1992) and Sala-i-Martin (1997a, b) which attempted to test the robustness of various determinants of growth rates of per capita GDP among countries using two variants of Edward Leamerâ??s extreme-bounds analysis is reexamined. In a realistic Monte Carlo experiment in which the universe of potential determinants is drawn from those in Levine and Reneltâ??s study, both versions of the extreme-bounds analysis are evaluated for their ability to recover the true specification. Levine and Reneltâ??s method is shown to have low size and extremely low power: nothing is robust; while Sala-i-Martinâ??s method is shown to have high size and high power: it is undiscriminating. Both methods are compared to a cross-sectional version of the generalto-specific search methodology associated with the LSE approach to econometrics. It is shown to have size near nominal size and high power. Sala-i-Martinâ??s method and the general-to-specific method are then applied to the actual data from the original two studies. The results are consistent with the Monte Carlo results and are suggestive that the factors that most affect differences of growth rates are ones that are beyond the control of policymakers.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: Working Paper ; No. 01-1

Classification and Topics

• Classification: Wirtschaft
• Subject: growth ; cross-country growth regressions ; extreme-bounds analysis ; general-to-specific specification search ; Wirtschaftswachstum ; Regression ; Vergleich ; Welt

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Hoover, Kevin D. ; Perez, Stephen J.
• Event: Veröffentlichung
• (who): University of California, Department of Economics
• (where): Davis, CA
• (when): 2000

Further information

• Handle: http://hdl.handle.net/10419/79439
• Last update: 10.03.2025, 11:43 AM CET