Nothing Special   »   [go: up one dir, main page]
IDEAS home Printed from https://ideas.repec.org/p/wiw/wus005/8284.html
   My bibliography  Save this paper

Population growth and automation density: theory and cross-country evidence

Author

Listed:
  • Abeliansky, Ana Lucia
  • Prettner, Klaus
Abstract
We analyze the effects of declining population growth on automation. Theoretical considerations imply that countries with lower population growth introduce automation technologies faster. We test the theoretical implication on panel data for 60 countries over the time span 1993-2013. Regression estimates support the theoretical implication, suggesting that a 1% increase in population growth is associated with an approximately 2% reduction in the growth rate of robot density. Our results are robust to the inclusion of standard control variables, different estimation methods, dynamic specifications, and changes with respect to the measurement of the stock of robots.

Suggested Citation

  • Abeliansky, Ana Lucia & Prettner, Klaus, 2021. "Population growth and automation density: theory and cross-country evidence," Department of Economics Working Paper Series 315, WU Vienna University of Economics and Business.
    • Handle: RePEc:wiw:wus005:8284
    as

    Download full text from publisher

    File URL: https://epub.wu.ac.at/8284/
    File Function: original version
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Dario Cords & Klaus Prettner, 2022. "Technological unemployment revisited: automation in a search and matching framework [The future of work: meeting the global challenges of demographic change and automation]," Oxford Economic Papers, Oxford University Press, vol. 74(1), pages 115-135.
    2. David E. Bloom & David Canning & Günther Fink, 2010. "Implications of population ageing for economic growth," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 26(4), pages 583-612, Winter.
    3. Guimarães, Luís & Mazeda Gil, Pedro, 2022. "Explaining the Labor Share: Automation Vs Labor Market Institutions," Labour Economics, Elsevier, vol. 75(C).
    4. Holger Strulik & Klaus Prettner & Alexia Prskawetz, 2013. "The past and future of knowledge-based growth," Journal of Economic Growth, Springer, vol. 18(4), pages 411-437, December.
    5. Gehringer, Agnieszka & Prettner, Klaus, 2019. "Longevity And Technological Change," Macroeconomic Dynamics, Cambridge University Press, vol. 23(4), pages 1471-1503, June.
    6. Georg Graetz & Guy Michaels, 2018. "Robots at Work," The Review of Economics and Statistics, MIT Press, vol. 100(5), pages 753-768, December.
    7. David E. Bloom & Dara Lee Luca, 2016. "The Global Demography of Aging: Facts, Explanations, Future," PGDA Working Papers 13016, Program on the Global Demography of Aging.
    8. Südekum, Jens & Dauth, Wolfgang & Findeisen, Sebastian & Woessner, Nicole, 2017. "German Robots – The Impact of Industrial Robots on Workers," CEPR Discussion Papers 12306, C.E.P.R. Discussion Papers.
    9. Robert M. Solow, 1956. "A Contribution to the Theory of Economic Growth," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 70(1), pages 65-94.
    10. Brent Neiman, 2014. "The Global Decline of the Labor Share," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 129(1), pages 61-103.
    11. Quamrul H. Ashraf & David N. Weil & Joshua Wilde, 2013. "The Effect of Fertility Reduction on Economic Growth," Population and Development Review, The Population Council, Inc., vol. 39(1), pages 97-130, March.
    12. Grossmann, Volker & Steger, Thomas & Trimborn, Timo, 2013. "Dynamically optimal R&D subsidization," Journal of Economic Dynamics and Control, Elsevier, vol. 37(3), pages 516-534.
    13. Prettner, Klaus & Strulik, Holger, 2020. "Innovation, automation, and inequality: Policy challenges in the race against the machine," Journal of Monetary Economics, Elsevier, vol. 116(C), pages 249-265.
    14. Bruno, Giovanni S.F., 2005. "Approximating the bias of the LSDV estimator for dynamic unbalanced panel data models," Economics Letters, Elsevier, vol. 87(3), pages 361-366, June.
    15. d’Albis, Hippolyte & Boubtane, Ekrame & Coulibaly, Dramane, 2021. "Demographic changes and the labor income share," European Economic Review, Elsevier, vol. 131(C).
    16. Terry Gregory & A.M. Salomons & Ulrich Zierahn, 2016. "Racing With or Against the Machine? Evidence from Europe," Working Papers 16-05, Utrecht School of Economics.
    17. Quamrul H. Ashraf & David N. Weil & Joshua Wilde, 2011. "The Effect of Interventions to Reduce Fertility on Economic Growth," NBER Working Papers 17377, National Bureau of Economic Research, Inc.
    18. 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.
    19. Joe Whittaker & Chris Whitehead & Mark Somers, 2005. "The neglog transformation and quantile regression for the analysis of a large credit scoring database," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 54(5), pages 863-878, November.
    20. Lankisch, Clemens & Prettner, Klaus & Prskawetz, Alexia, 2019. "How can robots affect wage inequality?," Economic Modelling, Elsevier, vol. 81(C), pages 161-169.
    21. Giovanni S. F. Bruno, 2005. "Estimation and inference in dynamic unbalanced panel-data models with a small number of individuals," Stata Journal, StataCorp LP, vol. 5(4), pages 473-500, December.
    22. Frey, Carl Benedikt & Osborne, Michael A., 2017. "The future of employment: How susceptible are jobs to computerisation?," Technological Forecasting and Social Change, Elsevier, vol. 114(C), pages 254-280.
    23. Matthias Busse & Christian Spielmann, 2006. "Gender Inequality and Trade," Review of International Economics, Wiley Blackwell, vol. 14(3), pages 362-379, August.
    24. Prettner, Klaus, 2019. "A Note On The Implications Of Automation For Economic Growth And The Labor Share," Macroeconomic Dynamics, Cambridge University Press, vol. 23(3), pages 1294-1301, April.
    25. David Bloom & David Canning & Günther Fink & Jocelyn Finlay, 2009. "Fertility, female labor force participation, and the demographic dividend," Journal of Economic Growth, Springer, vol. 14(2), pages 79-101, June.
    26. Michael Elsby & Bart Hobijn & Ayseful Sahin, 2013. "The Decline of the U.S. Labor Share," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 44(2 (Fall)), pages 1-63.
    27. World Bank, 2016. "World Development Indicators 2016," World Bank Publications - Books, The World Bank Group, number 23969.
    28. Bloom, David E. & Canning, David & Mansfield, Richard K. & Moore, Michael, 2007. "Demographic change, social security systems, and savings," Journal of Monetary Economics, Elsevier, vol. 54(1), pages 92-114, January.
    29. Arntz, Melanie & Gregory, Terry & Zierahn, Ulrich, 2017. "Revisiting the risk of automation," Economics Letters, Elsevier, vol. 159(C), pages 157-160.
    30. Gruber, Jonathan & Wise, David, 1998. "Social Security and Retirement: An International Comparison," American Economic Review, American Economic Association, vol. 88(2), pages 158-163, May.
    31. Daron Acemoglu & Pascual Restrepo, 2020. "Robots and Jobs: Evidence from US Labor Markets," Journal of Political Economy, University of Chicago Press, vol. 128(6), pages 2188-2244.
    32. Barro, Robert J. & Lee, Jong Wha, 2013. "A new data set of educational attainment in the world, 1950–2010," Journal of Development Economics, Elsevier, vol. 104(C), pages 184-198.
    33. Gasteiger, Emanuel & Prettner, Klaus, 2022. "Automation, Stagnation, And The Implications Of A Robot Tax," Macroeconomic Dynamics, Cambridge University Press, vol. 26(1), pages 218-249, January.
    34. Daron Acemoglu & Pascual Restrepo, 2018. "The Race between Man and Machine: Implications of Technology for Growth, Factor Shares, and Employment," American Economic Review, American Economic Association, vol. 108(6), pages 1488-1542, June.
    35. Mankiw, N. Gregory & Weil, David N., 1989. "The baby boom, the baby bust, and the housing market," Regional Science and Urban Economics, Elsevier, vol. 19(2), pages 235-258, May.
    36. Antony, Jürgen & Klarl, Torben, 2020. "The implications of automation for economic growth when investment decisions are irreversible," Economics Letters, Elsevier, vol. 186(C).
    37. Nickell, Stephen J, 1981. "Biases in Dynamic Models with Fixed Effects," Econometrica, Econometric Society, vol. 49(6), pages 1417-1426, November.
    38. Borghans, L. & ter Weel, B.J., 2002. "Do older workers have more trouble using a computer than younger workers?," ROA Research Memorandum 1E, Maastricht University, Research Centre for Education and the Labour Market (ROA).
    39. Ronald Lee & Andrew Mason, 2010. "Fertility, Human Capital, and Economic Growth over the Demographic Transition [Fécondité, capital humain et croissance économique au cours de la transition démographique]," European Journal of Population, Springer;European Association for Population Studies, vol. 26(2), pages 159-182, May.
    40. Dauth, Wolfgang & Findeisen, Sebastian & Südekum, Jens & Wößner, Nicole, 2017. "German robots - the impact of industrial robots on workers," IAB-Discussion Paper 201730, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    41. 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.
    42. Judson, Ruth A. & Owen, Ann L., 1999. "Estimating dynamic panel data models: a guide for macroeconomists," Economics Letters, Elsevier, vol. 65(1), pages 9-15, October.
    43. Canton, Erik J. F. & de Groot, Henri L. F. & Nahuis, Richard, 2002. "Vested interests, population ageing and technology adoption," European Journal of Political Economy, Elsevier, vol. 18(4), pages 631-652, November.
    44. Bloom, D.E. & Luca, D.L., 2016. "The Global Demography of Aging," Handbook of the Economics of Population Aging, in: Piggott, John & Woodland, Alan (ed.), Handbook of the Economics of Population Aging, edition 1, volume 1, chapter 0, pages 3-56, Elsevier.
    45. Abeliansky, Ana Lucia & Martínez-Zarzoso, Inmaculada & Prettner, Klaus, 2020. "3D printing, international trade, and FDI," Economic Modelling, Elsevier, vol. 85(C), pages 288-306.
    46. Anderson, T. W. & Hsiao, Cheng, 1982. "Formulation and estimation of dynamic models using panel data," Journal of Econometrics, Elsevier, vol. 18(1), pages 47-82, January.
    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. Abeliansky, Ana Lucia & Prettner, Klaus, 2017. "Automation and demographic change," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168215, Verein für Socialpolitik / German Economic Association.
    2. Abeliansky, Ana Lucia & Prettner, Klaus, 2023. "Automation and population growth: Theory and cross-country evidence," Journal of Economic Behavior & Organization, Elsevier, vol. 208(C), pages 345-358.
    3. Gehringer, Agnieszka & Prettner, Klaus, 2019. "Longevity And Technological Change," Macroeconomic Dynamics, Cambridge University Press, vol. 23(4), pages 1471-1503, June.
    4. Gasteiger, Emanuel & Prettner, Klaus, 2022. "Automation, Stagnation, And The Implications Of A Robot Tax," Macroeconomic Dynamics, Cambridge University Press, vol. 26(1), pages 218-249, January.
    5. Dario Cords & Klaus Prettner, 2022. "Technological unemployment revisited: automation in a search and matching framework [The future of work: meeting the global challenges of demographic change and automation]," Oxford Economic Papers, Oxford University Press, vol. 74(1), pages 115-135.
    6. Stähler, Nikolai, 2021. "The Impact of Aging and Automation on the Macroeconomy and Inequality," Journal of Macroeconomics, Elsevier, vol. 67(C).
    7. Arthur Jacobs & Freddy Heylen, 2021. "Demographic change, secular stagnation and inequality: automation as a blessing?," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 21/1030, Ghent University, Faculty of Economics and Business Administration.
    8. Basso, Henrique S. & Jimeno, Juan F., 2021. "From secular stagnation to robocalypse? Implications of demographic and technological changes," Journal of Monetary Economics, Elsevier, vol. 117(C), pages 833-847.
    9. Prettner, Klaus & Strulik, Holger, 2020. "Innovation, automation, and inequality: Policy challenges in the race against the machine," Journal of Monetary Economics, Elsevier, vol. 116(C), pages 249-265.
    10. Lankisch, Clemens & Prettner, Klaus & Prskawetz, Alexia, 2019. "How can robots affect wage inequality?," Economic Modelling, Elsevier, vol. 81(C), pages 161-169.
    11. Damioli, G. & Van Roy, V. & Vertesy, D. & Vivarelli, M., 2021. "May AI revolution be labour-friendly? Some micro evidence from the supply side," GLO Discussion Paper Series 823, Global Labor Organization (GLO).
    12. Michael Kuhn & Klaus Prettner, 2023. "Rising Longevity, Increasing the Retirement Age, and the Consequences for Knowledge‐based Long‐run Growth," Economica, London School of Economics and Political Science, vol. 90(357), pages 39-64, January.
    13. Naude, Wim, 2019. "The race against the robots and the fallacy of the giant cheesecake: Immediate and imagined impacts of artificial intelligence," MERIT Working Papers 2019-005, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    14. Prettner, Klaus, 2023. "Stagnant wages in the face of rising labor productivity: The potential role of industrial robots," Finance Research Letters, Elsevier, vol. 58(PD).
    15. Abeliansky, Ana & Algur, Eda & Bloom, David E. & Prettner, Klaus, 2020. "The Future of Work: Challenges for Job Creation Due to Global Demographic Change and Automation," IZA Discussion Papers 12962, Institute of Labor Economics (IZA).
    16. Geiger, Niels & Prettner, Klaus & Schwarzer, Johannes A., 2018. "Automatisierung, Wachstum und Ungleichheit," Hohenheim Discussion Papers in Business, Economics and Social Sciences 13-2018, University of Hohenheim, Faculty of Business, Economics and Social Sciences.
    17. Damioli, Giacomo & Van Roy, Vincent & Vertesy, Daniel & Vivarelli, Marco, 2021. "Will the AI revolution be labour-friendly? Some micro evidence from the supply side," MERIT Working Papers 2021-016, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    18. Giacomo Damioli & Vincent Van Roy & Daniel Vertesy & Marco Vivarelli, 2021. "Detecting the labour-friendly nature of AI product innovation," DISCE - Quaderni del Dipartimento di Politica Economica dipe0017, Università Cattolica del Sacro Cuore, Dipartimenti e Istituti di Scienze Economiche (DISCE).
    19. Bloom, David E. & Canning, David & Kotschy, Rainer & Prettner, Klaus & Schünemann, Johannes, 2024. "Health and economic growth: Reconciling the micro and macro evidence," World Development, Elsevier, vol. 178(C).
    20. Xiaomeng Zhang & Theodore Palivos & Xiangbo Liu, 2022. "Aging and automation in economies with search frictions," Journal of Population Economics, Springer;European Society for Population Economics, vol. 35(2), pages 621-642, April.

    More about this item

    Keywords

    Automation; Industrial Robots; Demographic Change; Declining Fertility;
    All these keywords.

    JEL classification:

    • J11 - Labor and Demographic Economics - - Demographic Economics - - - Demographic Trends, Macroeconomic Effects, and Forecasts
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • O40 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - General

    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:wiw:wus005:8284. 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: WU Library (email available below). General contact details of provider: https://research.wu.ac.at/ .

    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.