A simple Monte Carlo approach to examine sample robustness in growth regressions
Daniel Kaffine and
Graham Davis ()
No 2013-04, Working Papers from Colorado School of Mines, Division of Economics and Business
Growth regressions are often influenced by extreme observations in the sample. We demonstrate the usefulness of a simple Monte Carlo method as a diagnostic for sample robustness. We apply the technique to a data set used by Mehlum et al. (2006), who show that institutional quality is decisive for growth in resource rich countries. Monte Carlo sampling reveals that this result hinges crucially on the inclusion of Malaysia in the sample of countries. Inclusion of Malaysia yields robust, significant estimates of the key interaction term between resource abundance and institutions, whereby strong institutions can turn resource abundance into a blessing. Exclusion of Malaysia yields robust, insignificant estimates of the interaction term, whereby institutions cannot overcome the resource curse. Further explorations find that the remaining results in Mehlum et al. (2006) are similarly sensitive to the sample of countries included. We argue that the Monte Carlo method utilised provides easily interpretable representations of the robustness of estimates to an arbitrary sample of countries and should become standard practice in growth regression diagnostics, similar to robustness testing of alternative specifications and additional covariates.
Keywords: DFBETAS; robust regression; sample robustness; Monte Carlo; growth regressions; institutions; resource curse (search for similar items in EconPapers)
JEL-codes: C21 O43 Q32 Q33 (search for similar items in EconPapers)
Pages: 32 pages
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed
Downloads: (external link)
http://econbus-papers.mines.edu/working-papers/wp201304.pdf First version, 2013 (application/pdf)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:mns:wpaper:wp201304
Access Statistics for this paper
More papers in Working Papers from Colorado School of Mines, Division of Economics and Business Contact information at EDIRC.
Bibliographic data for series maintained by Jared Carbone ().