Human capital in growth regressions: how much difference does data quality make? An update and further results

Angel de La Fuente () and Rafael Dom?ech
Authors registered in the RePEc Author Service: Rafael Domenech

UFAE and IAE Working Papers from Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC)

Abstract: We construct estimates of educational attainment for a sample of OECD countries using previously unexploited sources. We follow a heuristic approach to obtain plausible time profiles for attainment levels by removing sharp breaks in the data that seem to reflect changes in classification criteria. We then construct indicators of the information content of our series and a number of previously available data sets and examine their performance in several growth specifications. We find a clear positive correlation between data quality and the size and significance of human capital coefficients in growth regressions. Using an extension of the classical errors in variables model, we construct a set of meta-estimates of the coefficient of years of schooling in an aggregate Cobb-Douglas production function. Our results suggest that, after correcting for measurement error bias, the value of this parameter is well above 0.50.

Keywords: human capital; growth; measurement error (search for similar items in EconPapers)
JEL-codes: C19 I20 O30 O40 (search for similar items in EconPapers)
Pages: 46+appendix
Date: 2002-08-25
New Economics Papers: this item is included in nep-dev, nep-dge and nep-lab
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (54)

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Related works:
Working Paper: Human Capital in Growth Regressions: How Much Difference Does Data Quality Make? An Update and Further Results (2002)
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