On A New Measure of Human Capital and Its Impact on Gross Domestic Product

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dc.contributor.author Bandyopadhyay, Debasis en
dc.contributor.author Lahiri, P en
dc.contributor.author Yu, Feng en
dc.date.accessioned 2006-11-30T20:53:28Z en
dc.date.available 2006-11-30T20:53:28Z en
dc.date.issued 1999 en
dc.identifier.citation Department of Economics Working Paper Series 196 en
dc.identifier.uri http://hdl.handle.net/2292/164 en
dc.description.abstract The general goal of this paper is first to develop an operationally simple measure of human v capital using the relative frequency histogram of the highest educational attainment and then to analyze the cross-country variations of the proposed measure. Visual inspection and the matrix of rank correlation coefficients show that relative frequency distributions of the highest educational attainment are similar for countries with similar Gross Domestic Products (GDP) level, but they are very different for countries whose GDP levels are quite different. Guided by intuition, we define a simple descriptive statistic, EER measured by the relative proportion of labor force with education beyond the secondary level to those with no formal education. This simple statistic turns out to extract the most essential information contained in the relative frequency histogram of the highest educational attainment to forecast future economic growth of a country. Consequently, we propose this statistic EER as a new measure of human capital. Non-parametric tests show that both the means and variances of the distribution of log (EER) for the high GDP countries are significantly higher than the corresponding means and variances for the low GDP countries. A chi-square test reveals that for the two groups of low and high GDP countries, the distributions of EER can be characterized by a unified class of gamma distributions with the same shape parameter but with very different scale parameters. Based on the data created by Barro and Lee (1993), we note that our new measure of human capital (i.e., EER) alone can explain cross-country variations in per capita GDP much better than the other growth models such as Solow (1956) and Mankiw, Romer, and Weil(1992). Those models include population growth rate and investment rate as covariates and the latter model use an additional covariate SCHOOL measured by the average secondary school enrollment rate or in addition to those two covariates. We explain the better performance of our model by noting that the statistic EER is significantly negatively correlated with population growth rate and positively correlated with investment rate and SCHOOL. en
dc.format.extent application/pdf en
dc.format.mimetype text en
dc.language.iso en en
dc.publisher ResearchSpace@Auckland en
dc.relation.ispartofseries Department of Economics Working Paper Series (1997-2006) en
dc.rights Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated. Previously published items are made available in accordance with the copyright policy of the publisher. en
dc.rights.uri https://researchspace.auckland.ac.nz/docs/uoa-docs/rights.htm en
dc.subject.other Chi-square test en
dc.subject.other Economics en
dc.title On A New Measure of Human Capital and Its Impact on Gross Domestic Product en
dc.type Working Paper en
dc.rights.holder Copyright: the author en
dc.rights.accessrights http://purl.org/eprint/accessRights/OpenAccess en
pubs.org-id Economics en

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