Growth regressions and data revisions in Penn World Tables

Growth regressions and data revisions in Penn World Tables Purpose – Penn World Tables (PWT) data on output measured at international prices are the data most frequently used in cross‐country growth regressions. These data are subject to revision, and the amendments can be substantial for a minority of countries, although negligible for most. The purpose of this paper is to investigate the effect of data revisions on research results using the data. Design/methodology/approach – Using Hanushek and Kimko's analysis of the relationship between growth and schooling quality and Sala‐i‐Martin's tests of model selection, the authors investigate how much the results of cross‐country growth regressions vary if the most recent vintage (6.2) of PWT data is used, rather than the previous vintage (6.1). Findings – The variation is substantial enough to imply significant differences in research results using different vintages of the PWT data. Practical implications – The results reinforce the case for examining the sensitivity of growth regressions to outliers, which may be subject to subsequent data revision that might substantially affect the conclusions. Originality/value – Previous research has identified significant revisions between successive vintages of PWT growth data, but has implied that this is not likely to affect the results of cross‐country growth regressions based on long‐run averages rather than on annual data. The findings suggest that this is not necessarily the case. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Economic Studies Emerald Publishing

Growth regressions and data revisions in Penn World Tables

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Publisher
Emerald Publishing
Copyright
Copyright © 2011 Emerald Group Publishing Limited. All rights reserved.
ISSN
0144-3585
DOI
10.1108/01443581111152418
Publisher site
See Article on Publisher Site

Abstract

Purpose – Penn World Tables (PWT) data on output measured at international prices are the data most frequently used in cross‐country growth regressions. These data are subject to revision, and the amendments can be substantial for a minority of countries, although negligible for most. The purpose of this paper is to investigate the effect of data revisions on research results using the data. Design/methodology/approach – Using Hanushek and Kimko's analysis of the relationship between growth and schooling quality and Sala‐i‐Martin's tests of model selection, the authors investigate how much the results of cross‐country growth regressions vary if the most recent vintage (6.2) of PWT data is used, rather than the previous vintage (6.1). Findings – The variation is substantial enough to imply significant differences in research results using different vintages of the PWT data. Practical implications – The results reinforce the case for examining the sensitivity of growth regressions to outliers, which may be subject to subsequent data revision that might substantially affect the conclusions. Originality/value – Previous research has identified significant revisions between successive vintages of PWT growth data, but has implied that this is not likely to affect the results of cross‐country growth regressions based on long‐run averages rather than on annual data. The findings suggest that this is not necessarily the case.

Journal

Journal of Economic StudiesEmerald Publishing

Published: Aug 2, 2011

Keywords: Growth; Education; Data revisions; Model selection; Economic growth

References

  • Schooling, labor‐force quality, and the growth of nations
    Hanushek, E.; Kimko, D.
  • Growth accelerations
    Hausmann, R.; Pritchett, L.; Rodrik, D.

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