IDEAS home Printed from https://ideas.repec.org/p/brt/depwps/014.html
   My bibliography  Save this paper

Decomposition of wage inequalities: an input-output approach

Author

Listed:
  • Martin Lábaj
  • Paula Puskarova

Abstract

Income and wealth inequalities, both between and within the advanced and developing countries,haveattracted much attention in current economic debates. Wage inequalities appear to play akeyrole in the generation of final inequalities in terms of households’ income, consumptionand wealth. In this paper, we propose a decomposition approach based on the input-output analysis that allows us to disentangle the effects on the final inequalities’levels into the contributions of various determinants. So far, the analysis of income and wealth inequalities measured by standard inequality indices, e.g. Gini coefficient, Theil index, has received limited space in the input-output analysis. This does not imply thatissuesof income and wealth inequalities havebeen ignored in this stream of research. The focus of the input-output research has however been directed into distinct aspectsof inequalities. In one way, researchers have put a lot of effort in the understanding how the income and wealthinequalities influence the structure of final demand of households,and eventuallygenerate ambivalent effects on production, value added and employment. Other stream of research in input-output analysis has paid a lot of attention to inequalities that arise from the distribution of income that goes to labour andcapital. We propose to calculate cross-industry and cross-country wage inequalities directly from the input-output tablesandanalyse the final inequality variations through the lens of changes in the inputs. Detailed industry-level data on employees’ wages linked to their hours worked and education attainments, which are covered bythe World input-output database, allow us to illustrate the application of proposed methodology on major advanced and developing countries in the world. The analysis contributes to solving the puzzle around the impactsof human capital and technological progress on income inequality but may shed also more light on the rising global inequalities unfolded by international trade and fragmentation of global value chains.

Suggested Citation

  • Martin Lábaj & Paula Puskarova, 2018. "Decomposition of wage inequalities: an input-output approach," Department of Economic Policy Working Paper Series 014, Department of Economic Policy, Faculty of National Economy, University of Economics in Bratislava.
  • Handle: RePEc:brt:depwps:014
    as

    Download full text from publisher

    File URL: https://nhf.euba.sk/www_write/files/katedry/khp/working-papers/dep_wp014.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Robert Koopman & Zhi Wang & Shang-Jin Wei, 2014. "Tracing Value-Added and Double Counting in Gross Exports," American Economic Review, American Economic Association, vol. 104(2), pages 459-494, February.
    2. Guy Michaels & Ashwini Natraj & John Van Reenen, 2010. "Has ICT Polarized Skill Demand? Evidence from Eleven Countries over 25 Years," CEP Discussion Papers dp0987, Centre for Economic Performance, LSE.
    3. Anthony B. Atkinson & Thomas Piketty & Emmanuel Saez, 2011. "Top Incomes in the Long Run of History," Journal of Economic Literature, American Economic Association, vol. 49(1), pages 3-71, March.
    4. Paolo Figini & Holger Go¨rg, 2011. "Does Foreign Direct Investment Affect Wage Inequality? An Empirical Investigation," The World Economy, Wiley Blackwell, vol. 34(9), pages 1455-1475, September.
    5. Bronwyn H. Hall & Nathan Rosenberg (ed.), 2010. "Handbook of the Economics of Innovation," Handbook of the Economics of Innovation, Elsevier, edition 1, volume 1, number 1.
    6. Roland Bénabou, 1996. "Inequality and Growth," NBER Chapters, in: NBER Macroeconomics Annual 1996, Volume 11, pages 11-92, National Bureau of Economic Research, Inc.
    7. Maarten Goos & Alan Manning & Anna Salomons, 2014. "Explaining Job Polarization: Routine-Biased Technological Change and Offshoring," American Economic Review, American Economic Association, vol. 104(8), pages 2509-2526, August.
    8. Kaveri Deb & William R. Hauk, 2017. "RCA indices, multinational production and the Ricardian trade model," International Economics and Economic Policy, Springer, vol. 14(1), pages 1-25, January.
    9. Javier Lopez Gonzalez & Przemyslaw Kowalski & Pascal Achard, 2015. "Trade, global value chains and wage-income inequality," OECD Trade Policy Papers 182, OECD Publishing.
    10. Jones, Charles I, 1995. "R&D-Based Models of Economic Growth," Journal of Political Economy, University of Chicago Press, vol. 103(4), pages 759-784, August.
    11. Vassilis Tselios, 2008. "Income and educational inequalities in the regions of the European Union: Geographical spillovers under welfare state restrictions," Papers in Regional Science, Wiley Blackwell, vol. 87(3), pages 403-430, August.
    12. Fagerberg, Jan & Srholec, Martin & Verspagen, Bart, 2010. "Innovation and Economic Development," Handbook of the Economics of Innovation, in: Bronwyn H. Hall & Nathan Rosenberg (ed.), Handbook of the Economics of Innovation, edition 1, volume 2, chapter 0, pages 833-872, Elsevier.
    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. Aleksandra Parteka & Joanna Wolszczak-Derlacz, 2019. "Global Value Chains and Wages: Multi-Country Evidence from Linked Worker-Industry Data," Open Economies Review, Springer, vol. 30(3), pages 505-539, July.
    2. Jan Fagerberg & Bengt-Åke Lundvall & Martin Srholec, 2018. "Global Value Chains, National Innovation Systems and Economic Development," The European Journal of Development Research, Palgrave Macmillan;European Association of Development Research and Training Institutes (EADI), vol. 30(3), pages 533-556, July.
    3. T. Gries & R. Grundmann & I. Palnau & M. Redlin, 2017. "Innovations, growth and participation in advanced economies - a review of major concepts and findings," International Economics and Economic Policy, Springer, vol. 14(2), pages 293-351, April.
    4. Taiji Furusawa & Hideo Konishi & Duong Lam Anh Tran, 2020. "International Trade and Income Inequality," Scandinavian Journal of Economics, Wiley Blackwell, vol. 122(3), pages 993-1026, July.
    5. Holger M. Mueller & Paige P. Ouimet & Elena Simintzi, 2015. "Wage Inequality and Firm Growth," LIS Working papers 632, LIS Cross-National Data Center in Luxembourg.
    6. Muendler, Marc-Andreas, 2017. "Trade, technology, and prosperity: An account of evidence from a labor-market perspective," WTO Staff Working Papers ERSD-2017-15, World Trade Organization (WTO), Economic Research and Statistics Division.
    7. Sara Amoroso & Pietro Moncada-Paternò-Castello, 2018. "Inward Greenfield FDI and Patterns of Job Polarization," Sustainability, MDPI, vol. 10(4), pages 1-20, April.
    8. Carpa, Nur & Martínez-Zarzoso, Inmaculada, 2022. "The impact of global value chain participation on income inequality," International Economics, Elsevier, vol. 169(C), pages 269-290.
    9. Andrés César & Guillermo Falcone & Pablo Garriga, 2022. "Robots, Exports and Top Income Inequality: Evidence for the U.S," CEDLAS, Working Papers 0307, CEDLAS, Universidad Nacional de La Plata.
    10. David Autor, 2014. "Polanyi's Paradox and the Shape of Employment Growth," NBER Working Papers 20485, National Bureau of Economic Research, Inc.
    11. Sabrina Aufiero & Giordano De Marzo & Angelica Sbardella & Andrea Zaccaria, 2023. "Mapping job complexity and skills into wages," Papers 2304.05251, arXiv.org.
    12. Cavenaile, Laurent, 2021. "Offshoring, computerization, labor market polarization and top income inequality," Journal of Macroeconomics, Elsevier, vol. 69(C).
    13. Gries, T. & Grundmann, R. & Palnau, I. & Redlin, M., 2015. "Does technological change drive inclusive industrialization? : A review of major concepts and findings," MERIT Working Papers 2015-044, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    14. Jan Fagerberg & Martin Srholec, 2017. "Global Dynamics, Capabilities and the Crisis," Economic Complexity and Evolution, in: Andreas Pyka & Uwe Cantner (ed.), Foundations of Economic Change, pages 83-106, Springer.
    15. Wang, Shanchao & Alston, Julian M. & Pardey, Philip G., 2023. "R&D Lags in Economic Models," Staff Papers 330085, University of Minnesota, Department of Applied Economics.
    16. Aleksandra Parteka & Joanna Wolszczak-Derlacz, 2020. "Wage response to global production links: evidence for workers from 28 European countries (2005–2014)," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 156(4), pages 769-801, November.
    17. Herz, Holger & Schunk, Daniel & Zehnder, Christian, 2014. "How do judgmental overconfidence and overoptimism shape innovative activity?," Games and Economic Behavior, Elsevier, vol. 83(C), pages 1-23.
    18. Matthias Firgo & Peter Mayerhofer, 2015. "Wissens-Spillovers und regionale Entwicklung - welche strukturpolitische Ausrichtung optimiert des Wachstum?," Working Paper Reihe der AK Wien - Materialien zu Wirtschaft und Gesellschaft 144, Kammer für Arbeiter und Angestellte für Wien, Abteilung Wirtschaftswissenschaft und Statistik.
    19. Laetitia Comminges & Arnak Dalalyan, 2012. "Minimax Testing of a Composite null Hypothesis Defined via a Quadratic Functional in the Model of regression," Working Papers 2012-19, Center for Research in Economics and Statistics.
    20. Vahagn Jerbashian, 2019. "Automation and Job Polarization: On the Decline of Middling Occupations in Europe," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 81(5), pages 1095-1116, October.

    More about this item

    Keywords

    wage inequality; input-output analysis; world input-output database; global value chains;
    All these keywords.

    JEL classification:

    • C67 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Input-Output Models
    • D57 - Microeconomics - - General Equilibrium and Disequilibrium - - - Input-Output Tables and Analysis
    • D63 - Microeconomics - - Welfare Economics - - - Equity, Justice, Inequality, and Other Normative Criteria and Measurement
    • I24 - Health, Education, and Welfare - - Education - - - Education and Inequality

    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:brt:depwps:014. 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: Martin Labaj (email available below). General contact details of provider: https://edirc.repec.org/data/khnfesk.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.