IDEAS home Printed from https://ideas.repec.org/a/pal/palcom/v11y2024i1d10.1057_s41599-024-03100-7.html
   My bibliography  Save this article

Robots, firm relocation, and air pollution: unveiling the unintended spatial spillover effects of emerging technology

Author

Listed:
  • Yanying Wang

    (Peking University
    University of Cambridge)

  • Qingyang Wu

    (University of California)

Abstract

Amidst the global upsurge in industrial robot deployment, there remains a notable gap in our understanding of their environmental impact. This paper explores how the introduction of industrial robots has changed air quality at both the local and neighborhood levels in China. Using the Spatial Durbin Model, we investigate the regional spillovers of PM 2.5 concentration and the diffusion of this innovative technology. Our findings reveal that the rise of robots significantly reduces air pollution in the local area, while exacerbating it in neighboring regions. This contrast is mainly because pollution-intensive industries are more inclined to relocate to neighboring regions than their cleaner counterparts, after the local use of robots increases. Throughout the process, internal costs rather than external costs dominate firms’ relocation decisions. This study provides novel insights into the complex environmental externalities associated with the spread of industrial robots and highlights the critical issue of growing environmental inequality in the era of emerging technologies.

Suggested Citation

  • Yanying Wang & Qingyang Wu, 2024. "Robots, firm relocation, and air pollution: unveiling the unintended spatial spillover effects of emerging technology," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-17, December.
  • Handle: RePEc:pal:palcom:v:11:y:2024:i:1:d:10.1057_s41599-024-03100-7
    DOI: 10.1057/s41599-024-03100-7
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1057/s41599-024-03100-7
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1057/s41599-024-03100-7?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Wu, Qingyang & Wang, Yanying, 2022. "How does carbon emission price stimulate enterprises' total factor productivity? Insights from China's emission trading scheme pilots," Energy Economics, Elsevier, vol. 109(C).
    2. repec:dgr:rugsom:02d31 is not listed on IDEAS
    3. Liu, Haiying & Owens, Katharine A. & Yang, Ke & Zhang, Chunhong, 2020. "Pollution abatement costs and technical changes under different environmental regulations," China Economic Review, Elsevier, vol. 62(C).
    4. Giuntella, Osea & Wang, Tianyi, 2019. "Is an Army of Robots Marching on Chinese Jobs?," IZA Discussion Papers 12281, Institute of Labor Economics (IZA).
    5. Sheikh Moniruzzaman Moni & Roksana Mahmud & Karen High & Michael Carbajales‐Dale, 2020. "Life cycle assessment of emerging technologies: A review," Journal of Industrial Ecology, Yale University, vol. 24(1), pages 52-63, February.
    6. Arik Levinson & M. Scott Taylor, 2008. "Unmasking The Pollution Haven Effect," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 49(1), pages 223-254, February.
    7. Philippe Aghion & Céline Antonin & Simon Bunel, 2019. "Artificial Intelligence, Growth and Employment: The Role of Policy," Economie et Statistique / Economics and Statistics, Institut National de la Statistique et des Etudes Economiques (INSEE), issue 510-511-5, pages 149-164.
    8. Ben Kheder, Sonia & Zugravu, Natalia, 2012. "Environmental regulation and French firms location abroad: An economic geography model in an international comparative study," Ecological Economics, Elsevier, vol. 77(C), pages 48-61.
    9. Grossman, G.M & Krueger, A.B., 1991. "Environmental Impacts of a North American Free Trade Agreement," Papers 158, Princeton, Woodrow Wilson School - Public and International Affairs.
    10. Daron Acemoglu & Pascual Restrepo, 2019. "Automation and New Tasks: How Technology Displaces and Reinstates Labor," Journal of Economic Perspectives, American Economic Association, vol. 33(2), pages 3-30, Spring.
    11. Fujita , Masahisa & Krugman, Paul, 2004. "The new economic geography: Past, present and the future," INVESTIGACIONES REGIONALES - Journal of REGIONAL RESEARCH, Asociación Española de Ciencia Regional, issue 4, pages 177-206.
    12. Cui, Jingbo & Wang, Chunhua & Zhang, Junjie & Zheng, Yang, 2021. "The effectiveness of China’s regional carbon market pilots in reducing firm emissions," LSE Research Online Documents on Economics 113492, London School of Economics and Political Science, LSE Library.
    13. Jess Benhabib & Jesse Perla & Christopher Tonetti, 2021. "Reconciling Models of Diffusion and Innovation: A Theory of the Productivity Distribution and Technology Frontier," Econometrica, Econometric Society, vol. 89(5), pages 2261-2301, September.
    14. Wolfgang Dauth & Sebastian Findeisen & Jens Suedekum & Nicole Woessner, 2021. "The Adjustment of Labor Markets to Robots [“Skills, Tasks and Technologies: Implications for Employment and Earnings]," Journal of the European Economic Association, European Economic Association, vol. 19(6), pages 3104-3153.
    15. Andrew Weiss, 1995. "Human Capital vs. Signalling Explanations of Wages," Journal of Economic Perspectives, American Economic Association, vol. 9(4), pages 133-154, Fall.
    16. Wang, En-Ze & Lee, Chien-Chiang & Li, Yaya, 2022. "Assessing the impact of industrial robots on manufacturing energy intensity in 38 countries," Energy Economics, Elsevier, vol. 105(C).
    17. Huzhou Zhu & Bin Sang & Chunyuan Zhang & Lin Guo, 2023. "Have Industrial Robots Improved Pollution Reduction? A Theoretical Approach and Empirical Analysis," China & World Economy, Institute of World Economics and Politics, Chinese Academy of Social Sciences, vol. 31(4), pages 153-172, July.
    18. Mark Doms & Eric J. Bartelsman, 2000. "Understanding Productivity: Lessons from Longitudinal Microdata," Journal of Economic Literature, American Economic Association, vol. 38(3), pages 569-594, September.
    19. Pennings, Enrico & Sleuwaegen, Leo, 2000. "International relocation: firm and industry determinants," Economics Letters, Elsevier, vol. 67(2), pages 179-186, May.
    20. Daron Acemoglu & Pascual Restrepo, 2017. "Secular Stagnation? The Effect of Aging on Economic Growth in the Age of Automation," American Economic Review, American Economic Association, vol. 107(5), pages 174-179, May.
    21. Massimo Anelli & Italo Colantone & Piero Stanig, 2019. "We Were The Robots: Automation and Voting Behavior in Western Europe," RF Berlin - CReAM Discussion Paper Series 1917, Rockwool Foundation Berlin (RF Berlin) - Centre for Research and Analysis of Migration (CReAM).
    22. David Autor & Caroline Chin & Anna Salomons & Bryan Seegmiller, 2024. "New Frontiers: The Origins and Content of New Work, 1940–2018," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 139(3), pages 1399-1465.
    23. Richard Florida & Charlotta Mellander & Kevin Stolarick, 2008. "Inside the black box of regional development: human capital, the creative class and tolerance," Journal of Economic Geography, Oxford University Press, vol. 8(5), pages 615-649, September.
    24. Saha Atanu & H. Alan Love & Robert Schwart, 1994. "Adoption of Emerging Technologies Under Output Uncertainty," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 76(4), pages 836-846.
    25. Philippe Aghion & Benjamin F. Jones & Charles I. Jones, 2018. "Artificial Intelligence and Economic Growth," NBER Chapters, in: The Economics of Artificial Intelligence: An Agenda, pages 237-282, National Bureau of Economic Research, Inc.
    26. Corinne Autant‐Bernard & James P. LeSage, 2011. "Quantifying Knowledge Spillovers Using Spatial Econometric Models," Journal of Regional Science, Wiley Blackwell, vol. 51(3), pages 471-496, August.
    27. repec:clg:wpaper:2008-02 is not listed on IDEAS
    28. Yin Feng & Jinhua Cheng & Jun Shen & Han Sun, 2019. "Spatial Effects of Air Pollution on Public Health in China," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 73(1), pages 229-250, May.
    29. Lin, Faqin, 2017. "Trade openness and air pollution: City-level empirical evidence from China," China Economic Review, Elsevier, vol. 45(C), pages 78-88.
    30. Masahisa Fujita & Paul Krugman, 2004. "The new economic geography: Past, present and the future," Advances in Spatial Science, in: Raymond J. G. M. Florax & David A. Plane (ed.), Fifty Years of Regional Science, pages 139-164, Springer.
    31. Ding, Tao & Li, Jiangyuan & Shi, Xing & Li, Xuhui & Chen, Ya, 2023. "Is artificial intelligence associated with carbon emissions reduction? Case of China," Resources Policy, Elsevier, vol. 85(PB).
    32. 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.
    33. Sahar Milani, 2017. "The Impact of Environmental Policy Stringency on Industrial R&D Conditional on Pollution Intensity and Relocation Costs," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 68(3), pages 595-620, November.
    34. Werner Antweiler & Brian R. Copeland & M. Scott Taylor, 2001. "Is Free Trade Good for the Environment?," American Economic Review, American Economic Association, vol. 91(4), pages 877-908, September.
    35. Joseph Junior Aduba & Behrooz Asgari, 2020. "Correction to: Productivity and technological progress of the Japanese manufacturing industries, 2000–2014: estimation with data envelopment analysis and log-linear learning model," Asia-Pacific Journal of Regional Science, Springer, vol. 4(2), pages 389-389, June.
    36. Pargal, Sheoli & Wheeler, David, 1996. "Informal Regulation of Industrial Pollution in Developing Countries: Evidence from Indonesia," Journal of Political Economy, University of Chicago Press, vol. 104(6), pages 1314-1327, December.
    37. Hong Cheng & Ruixue Jia & Dandan Li & Hongbin Li, 2019. "The Rise of Robots in China," Journal of Economic Perspectives, American Economic Association, vol. 33(2), pages 71-88, Spring.
    38. Bommer, Rolf, 1999. "Environmental Policy and Industrial Competitiveness: The Pollution-Haven Hypothesis Reconsidered," Review of International Economics, Wiley Blackwell, vol. 7(2), pages 342-355, May.
    39. Zheng, Shiming & Yao, Rongrong & Zou, Ke, 2022. "Provincial environmental inequality in China: Measurement, influence, and policy instrument choice," Ecological Economics, Elsevier, vol. 200(C).
    40. Joseph Junior Aduba & Behrooz Asgari, 2020. "Productivity and technological progress of the Japanese manufacturing industries, 2000–2014: estimation with data envelopment analysis and log-linear learning model," Asia-Pacific Journal of Regional Science, Springer, vol. 4(2), pages 343-387, June.
    41. Buera,Francisco J. & Fattal Jaef,Roberto N., 2018. "The dynamics of development : innovation and reallocation," Policy Research Working Paper Series 8505, The World Bank.
    42. Tabuchi, Takatoshi, 1998. "Urban Agglomeration and Dispersion: A Synthesis of Alonso and Krugman," Journal of Urban Economics, Elsevier, vol. 44(3), pages 333-351, November.
    43. Chun, Hyunbae & Kim, Jung-Wook & Lee, Jason, 2015. "How does information technology improve aggregate productivity? A new channel of productivity dispersion and reallocation," Research Policy, Elsevier, vol. 44(5), pages 999-1016.
    44. Chen, Yang & Shao, Shuai & Fan, Meiting & Tian, Zhihua & Yang, Lili, 2022. "One man's loss is another's gain: Does clean energy development reduce CO2 emissions in China? Evidence based on the spatial Durbin model," Energy Economics, Elsevier, vol. 107(C).
    45. repec:hal:spmain:info:hdl:2441/7n49nkmngd8448a5ts5gt5ade0 is not listed on IDEAS
    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. Wang, Ting & Zhang, Yi & Liu, Chun, 2024. "Robot adoption and employment adjustment: Firm-level evidence from China," China Economic Review, Elsevier, vol. 84(C).
    2. Cheng, Can & Luo, Jiayu & Zhu, Chun & Zhang, Shangfeng, 2024. "Artificial intelligence and the skill premium: A numerical analysis of theoretical models," Technological Forecasting and Social Change, Elsevier, vol. 200(C).
    3. Jurkat, Anne & Klump, Rainer & Schneider, Florian, 2023. "Robots and Wages: A Meta-Analysis," EconStor Preprints 274156, ZBW - Leibniz Information Centre for Economics.
    4. Lin, Boqiang & Xu, Chongchong, 2024. "Enhancing energy-environmental performance through industrial intelligence: Insights from Chinese prefectural-level cities," Applied Energy, Elsevier, vol. 365(C).
    5. Zhang, Yi & Wang, Ting & Liu, Chun, 2024. "Beyond the modern productivity paradox: The effect of robotics technology on firm-level total factor productivity in China," Journal of Asian Economics, Elsevier, vol. 90(C).
    6. Zhou, Wei & Zhuang, Yan & Chen, Yan, 2024. "How does artificial intelligence affect pollutant emissions by improving energy efficiency and developing green technology," Energy Economics, Elsevier, vol. 131(C).
    7. Lin, Boqiang & Xu, Chongchong, 2024. "The effects of industrial robots on firm energy intensity: From the perspective of technological innovation and electrification," Technological Forecasting and Social Change, Elsevier, vol. 203(C).
    8. Samuel Muehlemann, 2024. "AI Adoption and Workplace Training," Economics of Education Working Paper Series 0232, University of Zurich, Department of Business Administration (IBW).
    9. Li, Daiyue & Jin, Yanhong & Cheng, Mingwang, 2024. "Unleashing the power of industrial robotics on firm productivity: Evidence from China," Journal of Economic Behavior & Organization, Elsevier, vol. 224(C), pages 500-520.
    10. Ana L. ABELIANSKY & Eda ALGUR & David E. BLOOM & Klaus PRETTNER, 2020. "The future of work: Meeting the global challenges of demographic change and automation," International Labour Review, International Labour Organization, vol. 159(3), pages 285-306, September.
    11. Bernardo S Buarque & Ronald B Davies & Ryan M Hynes & Dieter F Kogler, 2020. "OK Computer: the creation and integration of AI in Europe," Cambridge Journal of Regions, Economy and Society, Cambridge Political Economy Society, vol. 13(1), pages 175-192.
    12. Gihleb, Rania & Giuntella, Osea & Stella, Luca & Wang, Tianyi, 2022. "Industrial robots, Workers’ safety, and health," Labour Economics, Elsevier, vol. 78(C).
    13. Michael Schymura & Andreas Löschel, 2012. "Trade and the Environment: An Application of the WIOD Database," EcoMod2012 3948, EcoMod.
    14. Roberta Capello & Simona Ciappei & Camilla Lenzi, 2024. "Unveiling the automation—wage inequality nexus within and across regions," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 73(4), pages 1729-1756, December.
    15. Klump, Rainer & Jurkat, Anne & Schneider, Florian, 2021. "Tracking the rise of robots: A survey of the IFR database and its applications," MPRA Paper 107909, University Library of Munich, Germany.
    16. Ekaterina Prytkova & Fabien Petit & Deyu Li & Sugat Chaturvedi & Tommaso Ciarli, 2024. "The Employment Impact of Emerging Digital Technologies," CEPEO Working Paper Series 24-01, UCL Centre for Education Policy and Equalising Opportunities, revised Feb 2024.
    17. Mühlemann, Samuel, 2024. "AI Adoption and Workplace Training," IZA Discussion Papers 17367, Institute of Labor Economics (IZA).
    18. Cui, Huijie & Liang, Shangkun & Xu, Canyu & Junli, Yu, 2024. "Robots and analyst forecast precision: Evidence from Chinese manufacturing," International Review of Financial Analysis, Elsevier, vol. 94(C).
    19. Luca Grilli & Sergio Mariotti & Riccardo Marzano, 2024. "Artificial intelligence and shapeshifting capitalism," Journal of Evolutionary Economics, Springer, vol. 34(2), pages 303-318, April.
    20. Zhang, Weike & Zeng, Ming, 2024. "Is artificial intelligence a curse or a blessing for enterprise energy intensity? Evidence from China," Energy Economics, Elsevier, vol. 134(C).

    More about this item

    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:pal:palcom:v:11:y:2024:i:1:d:10.1057_s41599-024-03100-7. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: https://www.nature.com/ .

    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.