IDEAS home Printed from https://ideas.repec.org/p/iza/izadps/dp9157.html
   My bibliography  Save this paper

Why Do South Korean Firms Produce So Much More Output per Worker than Ghanaian Ones?

Author

Listed:
  • Baptist, Simon

    (Economist Intelligence Unit)

  • Teal, Francis J.

    (University of Oxford)

Abstract

Macro analysis of the sources of income differences has produced very different results as to the importance of education. In this paper we investigate the roles of education and technology in explaining differences in firm level productivity across Ghana and South Korea. The labour productivity differentials across these firms exceed those implied by macro analysis. Median value-added per employee is over thirty times higher in South Korean than in Ghanaian manufacturing firms. We show that if we allow for a non-linear effect of education on output the whole of the average productivity differences across the countries can be explained. We discuss the policy implications that flow from this finding.

Suggested Citation

  • Baptist, Simon & Teal, Francis J., 2015. "Why Do South Korean Firms Produce So Much More Output per Worker than Ghanaian Ones?," IZA Discussion Papers 9157, Institute of Labor Economics (IZA).
    • Handle: RePEc:iza:izadps:dp9157
    as

    Download full text from publisher

    File URL: https://docs.iza.org/dp9157.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Stephen Bond & Måns Söderbom, 2005. "Adjustment Costs and the Identification of Cobb Douglas Production Functions," Economics Papers 2005-W04, Economics Group, Nuffield College, University of Oxford.
    2. Sofronis K. Clerides & Saul Lach & James R. Tybout, 1998. "Is Learning by Exporting Important? Micro-Dynamic Evidence from Colombia, Mexico, and Morocco," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 113(3), pages 903-947.
    3. Falco, Paolo & Kerr, Andrew & Rankin, Neil & Sandefur, Justin & Teal, Francis, 2011. "The returns to formality and informality in urban Africa," Labour Economics, Elsevier, vol. 18(S1), pages 23-31.
    4. Richard Blundell & Stephen Bond, 2000. "GMM Estimation with persistent panel data: an application to production functions," Econometric Reviews, Taylor & Francis Journals, vol. 19(3), pages 321-340.
    5. Arne Bigsten & Paul Collier & Stefan Dercon & Marcel Fafchamps & Bernard Gauthier & Jan Willem Gunning & Abena Oduro & Remco Oostendorp & Catherine Pattillo & Måns Soderbom & Francis Teal & Albert Zeu, 2004. "Do African Manufacturing Firms Learn from Exporting?," Journal of Development Studies, Taylor & Francis Journals, vol. 40(3), pages 115-141.
    6. Nicholas Bloom & Renata Lemos & Raffaella Sadun & Daniela Scur & John Van Reenen, 2014. "The New Empirical Economics of Management," NBER Working Papers 20102, National Bureau of Economic Research, Inc.
    7. Basu, Susanto & Fernald, John G., 1995. "Are apparent productive spillovers a figment of specification error?," Journal of Monetary Economics, Elsevier, vol. 36(1), pages 165-188, August.
    8. Duraisamy, P., 2002. "Changes in returns to education in India, 1983-94: by gender, age-cohort and location," Economics of Education Review, Elsevier, vol. 21(6), pages 609-622, December.
    9. Francesco Caselli & Wilbur John Coleman II, 2006. "The World Technology Frontier," American Economic Review, American Economic Association, vol. 96(3), pages 499-522, June.
    10. Arellano, Manuel & Bover, Olympia, 1995. "Another look at the instrumental variable estimation of error-components models," Journal of Econometrics, Elsevier, vol. 68(1), pages 29-51, July.
    11. Bennell, Paul, 1996. "Rates of return to education: Does the conventional pattern prevail in sub-Saharan Africa?," World Development, Elsevier, vol. 24(1), pages 183-199, January.
    12. Blundell, Richard & Bond, Stephen, 1998. "Initial conditions and moment restrictions in dynamic panel data models," Journal of Econometrics, Elsevier, vol. 87(1), pages 115-143, August.
    13. Nicholas Bloom & Renata Lemos & Raffaella Sadun & Daniela Scur & John Reenen, 2014. "Jeea-Fbbva Lecture 2013: The New Empirical Economics Of Management," Journal of the European Economic Association, European Economic Association, vol. 12(4), pages 835-876, August.
    14. Escribano, Alvaro & Guasch, J. Luis, 2005. "Assessing the impact of the investment climate on productivity using firm-level data : methodology and the cases of Guatemala, Honduras, and Nicaragua," Policy Research Working Paper Series 3621, The World Bank.
    15. Ackerberg, Daniel & Caves, Kevin & Frazer, Garth, 2006. "Structural identification of production functions," MPRA Paper 38349, University Library of Munich, Germany.
    16. Martin Neil Baily & Robert M. Solow, 2001. "International Productivity Comparisons Built from the Firm Level," Journal of Economic Perspectives, American Economic Association, vol. 15(3), pages 151-172, Summer.
    17. Simon Appleton & John Hoddinott & John MacKinnon, 1996. "Education and health in sub-Saharan Africa," Journal of International Development, John Wiley & Sons, Ltd., vol. 8(3), pages 307-339.
    18. Manuel Arellano & Stephen Bond, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 58(2), pages 277-297.
    19. Stephen Bond & Måns Söderbom, 2005. "Adjustment Costs and the Identification of Cobb Douglas Production Functions," Economics Series Working Papers 2005-W04, University of Oxford, Department of Economics.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Francis Teal & Simon Baptist, 2008. "Why do South Korean firms produce so much more output per worker than Ghanaian ones?," Economics Series Working Papers WPS/2008-10, University of Oxford, Department of Economics.
    2. Jinhyung Lee & Jeffrey S. McCullough & Robert J. Town, 2013. "The impact of health information technology on hospital productivity," RAND Journal of Economics, RAND Corporation, vol. 44(3), pages 545-568, September.
    3. Aguirregabiria, Victor, 2009. "Econometric Issues and Methods in the Estimation of Production Functions," MPRA Paper 15973, University Library of Munich, Germany.
    4. Almeida, Rita & Carneiro, Pedro, 2009. "The return to firm investments in human capital," Labour Economics, Elsevier, vol. 16(1), pages 97-106, January.
    5. Dobbelaere, Sabien & Kiyota, Kozo & Mairesse, Jacques, 2015. "Product and labor market imperfections and scale economies: Micro-evidence on France, Japan and the Netherlands," Journal of Comparative Economics, Elsevier, vol. 43(2), pages 290-322.
    6. Göbel, Christian & Zwick, Thomas, 2009. "Age and productivity: evidence from linked employer employee data," ZEW Discussion Papers 09-020, ZEW - Leibniz Centre for European Economic Research.
    7. Amit Gandhi & Salvador Navarro & David Rivers, 2011. "On the Identification of Production Functions: How Heterogeneous is Productivity?," University of Western Ontario, Centre for Human Capital and Productivity (CHCP) Working Papers 20119, University of Western Ontario, Centre for Human Capital and Productivity (CHCP).
    8. Jan De Loecker & Frederic Warzynski, 2012. "Markups and Firm-Level Export Status," American Economic Review, American Economic Association, vol. 102(6), pages 2437-2471, October.
    9. Simon Pröll & Giannis Karagiannis & Klaus Salhofer, 2019. "Advertising and Markups: The Case of the German Brewing Industry," Working Papers 732019, University of Natural Resources and Life Sciences, Vienna, Department of Economics and Social Sciences, Institute for Sustainable Economic Development.
    10. Nemlioglu, Ilayda & Mallick, Sushanta, 2021. "Effective innovation via better management of firms: The role of leverage in times of crisis," Research Policy, Elsevier, vol. 50(7).
    11. Bruno Merlevede & Angelos Theodorakopoulos, 2018. "Productivity Effects of Internationalisation Through the Domestic Supply Chain: Evidence from Europe," Working Papers of VIVES - Research Centre for Regional Economics 627689, KU Leuven, Faculty of Economics and Business (FEB), VIVES - Research Centre for Regional Economics.
    12. repec:zbw:inwedp:732019 is not listed on IDEAS
    13. Petrick, Matin & Kloss, Mathias, 2013. "Identifying Factor Productivity from Micro-data: The case of EU agriculture," Factor Markets Working Papers 144, Centre for European Policy Studies.
    14. Bruno Merlevede & Angelos Theodorakopoulos, 2016. "Productivity effects from inter-industry offshoring and inshoring: Firm-level evidence from Belgium," FIW Working Paper series 165, FIW.
    15. Yuriy Gorodnichenko, 2007. "Using Firm Optimization to Evaluate and Estimate Returns to Scale," NBER Working Papers 13666, National Bureau of Economic Research, Inc.
    16. Markus Eberhardt & Christian Helmers, 2010. "Untested Assumptions and Data Slicing: A Critical Review of Firm-Level Production Function Estimators," Economics Series Working Papers 513, University of Oxford, Department of Economics.
    17. repec:zbw:iamodp:271870 is not listed on IDEAS
    18. Bruno Merlevede & Angelos Theodorakopoulos, 2021. "Productivity effects of internationalisation through the domestic supply chain," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(6), pages 808-832, September.
    19. Lior Gallo, 2011. "Export and Productivity - Evidence from Israel," Bank of Israel Working Papers 2011.08, Bank of Israel.
    20. Meschi, Elena & Taymaz, Erol & Vivarelli, Marco, 2011. "Trade, technology and skills: Evidence from Turkish microdata," Labour Economics, Elsevier, vol. 18(S1), pages 60-70.
    21. Crt Kostevc, 2005. "Performance of Exporters: Scale Effects or Continuous Productivity Improvements," LICOS Discussion Papers 15905, LICOS - Centre for Institutions and Economic Performance, KU Leuven.
    22. Coviello, Decio & Islam, Roumeen, 2006. "Does aid help improve economic institutions ?," Policy Research Working Paper Series 3990, The World Bank.

    More about this item

    Keywords

    African and Asian manufacturing; productivity; efficiency; human capital;
    All these keywords.

    JEL classification:

    • O14 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Industrialization; Manufacturing and Service Industries; Choice of Technology
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:iza:izadps:dp9157. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Holger Hinte (email available below). General contact details of provider: https://edirc.repec.org/data/izaaade.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.