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Human capital in growth regressions: how much difference does data quality make? An update and further results Author info | Abstract | Publisher info | Download info | Related research | Statistics Angel de la Fuente ()
Rafael Dom?ech
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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.
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Paper provided by Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC) in its series UFAE and IAE Working Papers with number
537.02.
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Length: 46+appendix
Date of creation: 25 Aug 2002Date of revision:
Handle: RePEc:aub:autbar:537.02Contact details of provider: Postal: 08193, Bellaterra, Barcelona Phone: 34 93 592 1203 Web page: http://pareto.uab.cat More information through EDIRC
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Keywords: human capital growth measurement error Other versions of this item:
Find related papers by JEL classification: O40 - Economic Development, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - General I20 - Health, Education, and Welfare - - Education - - - General O30 - Economic Development, Technological Change, and Growth - - Technological Change - - - General C19 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Other
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