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Measuring the Stock of Human Capital for Comparative Analysis: An Application of the Lifetime Income Approach to Selected Countries

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  • Gang Liu

    (OECD)

Abstract

This paper summarizes the outcomes of the first phase of the OECD human capital project. In so doing, it shows the feasibility of applying the lifetime income approach to measuring human capital for comparative analysis, both across countries and over time. It also highlights the feasibility of applying the methodology to the categorical data (i.e. by 5-year or 10-year age group) that are typically available within the OECD statistics system, rather than to data by single year of age required by the original Jorgenson- Fraumeni methodology. The results in this paper indicate that the estimated value of human capital is substantially larger than that of traditional physical capital. Ratios of human capital to GDP are in a range from around eight to over ten across countries, broadly in line with those reported in a number of national studies. The distributions of human capital by age, gender, and education show that men dominate women in terms of their human capital holdings. In addition, people with higher education are better off than those with lower education, and the same is true for younger people compared to their older counterparts, although the detailed patterns vary across countries. Decomposition analysis of changes in the volume of human capital demonstrates that changes in population structure between men and women had little effect on the change of human capital per capita. While in all countries higher educational attainment contributed positively to the change of human capital per capita, this is not always sufficient to offset the negative effect of population ageing; as a result, the volume of human capital per capita appeared to have declined in some countries over the observed period. Finally, sensitivity analysis confirms that estimates of the value of human capital depend on the choice of the two key parameters, i.e. annual real income growth rate and discount rate, while within-country distribution of human capital and trends of the volume of human capital are less sensitive to these assumptions. Ce document de travail fait la synthèse des résultats de la première phase du projet de l’OCDE consacré au capital humain. Il démontre notamment qu’il est possible d’appliquer l’approche en terme de revenus actualisés le long du cycle de vie à la mesure du capital humain à des fins d’analyse comparative, à la fois entre les pays et dans le temps. Le document souligne également que cette méthodologie peut aussi être appliquée à des données catégoriels (c’est-à-dire par classe d’âge de 5 ou 10 ans), généralement disponibles dans le système statistique de l’OCDE, plutôt qu’aux données continues par âge, requises par la méthode Jorgenson-Fraumeni. Les résultats présentés dans ce rapport montrent que la valeur estimée du capital humain est bien plus importante que celle du capital physique traditionnel. Le rapport capital humain/sur PIB s’inscrit dans une fourchette comprise entre huit et dix dans les différents pays, ce qui est globalement conforme aux chiffres rapportés par un certain nombre d’études nationales. La répartition du capital humain en fonction de l’âge, du sexe et du niveau d’instruction montre que les hommes surpassent les femmes en termes de stock de capital humain. Par ailleurs, les individus les plus instruits tirent davantage leur épingle du jeu que les personnes moins qualifiées et les jeunes ont un capital humain supérieur à celui des personnes plus âgées, bien que dans le détail les schémas varient d’un pays à l’autre. L’évolution des volumes de capital humain montre que l’évolution démographique entre hommes et femmes n’a eu finalement qu’un impact limité sur la variation du capital humain par habitant. Si, dans tous les pays, l’amélioration du niveau d’instruction a contribué à l’augmentation du capital humain par habitant, cela n’a pas toujours été suffisant pour compenser les conséquences du vieillissement de la population, entraînant une baisse des volumes de capital humain par habitant dans certains pays. Enfin, l’analyse de sensibilité confirme que les estimations des valeurs du capital humain dépendent du choix de deux paramètres, à savoir le taux de croissance annuel du revenu réel et le taux d’actualisation. Mais la répartition du capital humain et l’évolution des volumes de capital humain dans chaque pays sont moins sensibles à ces paramètres.

Suggested Citation

  • Gang Liu, 2011. "Measuring the Stock of Human Capital for Comparative Analysis: An Application of the Lifetime Income Approach to Selected Countries," OECD Statistics Working Papers 2011/6, OECD Publishing.
  • Handle: RePEc:oec:stdaaa:2011/6-en
    DOI: 10.1787/5kg3h0jnn9r5-en
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    Cited by:

    1. Valerio Mendoza, Octasiano Miguel & Borsi, Mihály Tamás & Comim, Flavio, 2022. "Human capital dynamics in China: Evidence from a club convergence approach," Journal of Asian Economics, Elsevier, vol. 79(C).
    2. Katharine G. Abraham, 2014. "Expanded Measurement of Economic Activity: Progress and Prospects," NBER Chapters, in: Measuring Economic Sustainability and Progress, pages 25-42, National Bureau of Economic Research, Inc.
    3. Barbara M. Fraumeni, 2013. "Comments on "Productivity or Employment: Is It a Choice?"," International Productivity Monitor, Centre for the Study of Living Standards, vol. 25, pages 61-64, Spring.
    4. Barbara M. Fraumeni, 2014. "Frontiers and Opportunities in Productivity Research," International Productivity Monitor, Centre for the Study of Living Standards, vol. 27, pages 20-21, Fall.
    5. Lee, Jiho, 2013. "Consumption, financial wealth and labor income in Korea," Japan and the World Economy, Elsevier, vol. 25, pages 59-67.
    6. Trofimov, Ivan D. & Baawi, Nurulhana A., 2020. "Human Capital: State of the Field and Ways to Extend the Concept," MPRA Paper 107039, University Library of Munich, Germany.
    7. Yamaguchi, Rintaro, 2020. "Available capital, utilized capital, and shadow prices in inclusive wealth accounting," Ecological Economics, Elsevier, vol. 169(C).
    8. Gahramanov, Emin & Hasanov, Rashad & Tang, Xueli, 2020. "Parental involvement and Children's human capital: A tax-subsidy experiment," Economic Modelling, Elsevier, vol. 85(C), pages 16-29.
    9. Laverde, Henry, 2015. "Analysis of human capital by means of a prospective method: A study for Latin America," MPRA Paper 81633, University Library of Munich, Germany, revised Jul 2017.
    10. Leif Danziger & Eliakim Katz, 2019. "Compensation in Personal Injury Cases: Mean or Median Income?," CESifo Working Paper Series 7748, CESifo.
    11. Fraumeni, Barbara M. & He, Junzi & Li, Haizheng & Liu, Qinyi, 2019. "Regional distribution and dynamics of human capital in China 1985–2014," Journal of Comparative Economics, Elsevier, vol. 47(4), pages 853-866.
    12. Mr. Thomas F Alexander & Ms. Claudia H Dziobek & Tadeusz Galeza, 2018. "Sustainable Development Goals (SDGs) and GDP: What National Accounts Bring to the Table," IMF Working Papers 2018/041, International Monetary Fund.
    13. Mauro, Luciano & Pigliaru, Francesco, 2023. "Italy’s National Recovery and Resilient Plan: Will it Narrow the North-South Productivity Gap?," FEEM Working Papers 338592, Fondazione Eni Enrico Mattei (FEEM).
    14. Leif Danziger & Eliakim Katz, 2017. "Compensation for Loss of Work Income in Personal Injury Cases," CESifo Working Paper Series 6570, CESifo.
    15. Tamilina, Larysa, 2012. "Explaining human capital composition and formation mechanisms: a new conceptual framework of analysis," MPRA Paper 49820, University Library of Munich, Germany, revised 01 Sep 2013.
    16. Leif Danziger & Eliakim Katz, 2019. "Compensation in personal injury cases: mean or median income?," European Journal of Law and Economics, Springer, vol. 48(2), pages 291-303, October.
    17. S. B. Reshetnikov & M. R. Skirdov, 2017. "Analysis of methodological approaches to determination and assessment of the human capital," Russian Journal of Industrial Economics, MISIS, vol. 10(1).
    18. Myasoyedov, Sergei & Martirosyan, Emil & Sergeeva, Anastasia, 2015. "Modern Forms of Globalization of Human Capital - The New Trends in the Global Mobility of Staff," Published Papers 2312, Russian Presidential Academy of National Economy and Public Administration.
    19. Wulong Gu & Ambrose Wong, 2015. "Productivity and economic output of the education sector," Journal of Productivity Analysis, Springer, vol. 43(2), pages 165-182, April.
    20. Li, Haizheng & Liu, Qinyi & Li, Bo & Fraumeni, Barbara & Zhang, Xiaobei, 2014. "Human capital estimates in China: New panel data 1985–2010," China Economic Review, Elsevier, vol. 30(C), pages 397-418.
    21. Danziger, Leif & Katz, Eliakim, 2019. "Compensation in Personal Injury Cases: Mean or Median Income?," IZA Discussion Papers 12466, Institute of Labor Economics (IZA).
    22. Lees, Kirdan, 2013. "Golden years? The impacts of New Zealand’s ageing on wages, interest rates, wealth and macroeconomy," NZIER Working Paper 2013/1, New Zealand Institute of Economic Research.
    23. Barbara M. Fraumeni, 2012. "Human Capital Productivity: A New Concept for Productivity Analysis," International Productivity Monitor, Centre for the Study of Living Standards, vol. 24, pages 20-26, Fall.

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