IDEAS home Printed from https://ideas.repec.org/a/eee/ecanpo/v84y2024icp1287-1308.html

Automated workforce, financial precarities and family consumption: The importance of demand-side policies under the background of automation applications

Author

Listed:
  • Li, Chao
  • Lao, Wenyu
  • Li, Xiang
  • Zhang, Yuhan

Abstract

The continuous innovation of automation technology is expanding its application in the workplace, with wide-ranging implications for the economy and society. However, it is not yet clear how workplace automation changes people’s consumption behavior. This paper conducts an empirical analysis in this regard based on the Chinese General Social Survey. The main results are shown as follows: (1) One standard deviation increase in automation contributes to an average reduction of 7.073 % in family consumption. This finding is validated by conducting several robustness and endogeneity checks using various measures of automation and consumption, instrumental variable approach, placebo analysis, etc. (2) The mechanism is that automation decreases family income and work-related social capital, resulting in a decline in families’ socioeconomic status and increased financial precarities. In addition, financial uncertainties brought about by automation decrease people’s subjective well-being, expectations for future life and risk appetite, thus prompting them to lower consumption as a precautionary measure to prepare for potential risks caused by the technological change. (3) Automation has greater negative effects on hedonic and developmental consumption, which are about three times the impact on non-hedonic and basic living expenses respectively, thus leading to a downgrade in families’ consumption structure. In addition, its effect is more pronounced for families with lower economic status, having no houses and living in urban areas. This study also highlights the importance of demand-side policies in the application of automation technology by finding that better labor protection is needed to mitigate automation’s adverse consequences for family consumption. In the context of automation’s increasingly profound impact on the society, this research has important policy implications.

Suggested Citation

  • Li, Chao & Lao, Wenyu & Li, Xiang & Zhang, Yuhan, 2024. "Automated workforce, financial precarities and family consumption: The importance of demand-side policies under the background of automation applications," Economic Analysis and Policy, Elsevier, vol. 84(C), pages 1287-1308.
    • Handle: RePEc:eee:ecanpo:v:84:y:2024:i:c:p:1287-1308
    DOI: 10.1016/j.eap.2024.10.029
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0313592624002844
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.eap.2024.10.029?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

    for a different version of it.

    References listed on IDEAS

    as
    1. Benjamin Moll & Lukasz Rachel & Pascual Restrepo, 2022. "Uneven Growth: Automation's Impact on Income and Wealth Inequality," Econometrica, Econometric Society, vol. 90(6), pages 2645-2683, November.
    2. 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.
    3. Bostic, Raphael & Gabriel, Stuart & Painter, Gary, 2009. "Housing wealth, financial wealth, and consumption: New evidence from micro data," Regional Science and Urban Economics, Elsevier, vol. 39(1), pages 79-89, January.
    4. Miha Dominko & Miroslav Verbič, 2022. "The effect of subjective well‐being on consumption behavior," Journal of Consumer Affairs, Wiley Blackwell, vol. 56(2), pages 876-898, June.
    5. Phitawat Poonpolkul, 2023. "Age-Dependent Risk Aversion: Re-evaluating Fiscal Policy Impacts of Population Aging," PIER Discussion Papers 198, Puey Ungphakorn Institute for Economic Research.
    6. Nguyen, Hien Phuc & Khieu, Hoang, 2021. "Progressive wealth tax: An inquiry into Biden’s tax policy," Economic Analysis and Policy, Elsevier, vol. 72(C), pages 735-742.
    7. Carroll, Christopher D., 2009. "Precautionary saving and the marginal propensity to consume out of permanent income," Journal of Monetary Economics, Elsevier, vol. 56(6), pages 780-790, September.
    8. Hubbard, R Glenn & Skinner, Jonathan & Zeldes, Stephen P, 1995. "Precautionary Saving and Social Insurance," Journal of Political Economy, University of Chicago Press, vol. 103(2), pages 360-399, April.
    9. Tiago Neves Sequeira & Susana Garrido & Marcelo Santos, 2021. "Robots are not always bad for employment and wages," International Economics, CEPII research center, issue 167, pages 108-119.
    10. Wang, Junhui & Ai, Shuang & Huang, Mian, 2021. "Migration history, hukou status, and urban household consumption," Economic Modelling, Elsevier, vol. 97(C), pages 437-448.
    11. Christopher D. Carroll & Karen E. Dynan & Spencer D. Krane, 2003. "Unemployment Risk and Precautionary Wealth: Evidence from Households' Balance Sheets," The Review of Economics and Statistics, MIT Press, vol. 85(3), pages 586-604, August.
    12. 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.
    13. Ajay Agrawal & Joshua Gans & Avi Goldfarb, 2019. "Economic Policy for Artificial Intelligence," Innovation Policy and the Economy, University of Chicago Press, vol. 19(1), pages 139-159.
    14. Naomitsu Yashiro & Tomi Kyyrä & Hyunjeong Hwang & Juha Tuomala, 2022. "Technology, labour market institutions and early retirement," Economic Policy, CEPR, CESifo, Sciences Po;CES;MSH, vol. 37(112), pages 811-849.
    15. Carmen Aina & Daniela Sonedda, 2022. "Sooner or later? The impact of child education on household consumption," Empirical Economics, Springer, vol. 63(4), pages 2071-2099, October.
    16. Guimarães, Luís & Mazeda Gil, Pedro, 2022. "Explaining the Labor Share: Automation Vs Labor Market Institutions," Labour Economics, Elsevier, vol. 75(C).
    17. David H. Autor, 2015. "Why Are There Still So Many Jobs? The History and Future of Workplace Automation," Journal of Economic Perspectives, American Economic Association, vol. 29(3), pages 3-30, Summer.
    18. David Autor, 2024. "Applying AI to Rebuild Middle Class Jobs," NBER Working Papers 32140, National Bureau of Economic Research, Inc.
    19. Mark Aguiar & Mark Bils, 2015. "Has Consumption Inequality Mirrored Income Inequality?," American Economic Review, American Economic Association, vol. 105(9), pages 2725-2756, September.
    20. Poonpolkul, Phitawat, 2023. "Age-dependent risk aversion: Re-evaluating fiscal policy impacts of population aging," The Journal of the Economics of Ageing, Elsevier, vol. 26(C).
    21. Duarte, Fabian, 2012. "Price elasticity of expenditure across health care services," Journal of Health Economics, Elsevier, vol. 31(6), pages 824-841.
    22. Lene Kromann & Anders Sørensen, 2019. "Automation, performance and international competition: a firm-level comparison of process innovation," Economic Policy, CEPR, CESifo, Sciences Po;CES;MSH, vol. 34(100), pages 691-722.
    23. Andreas Irmen, 2021. "Automation, growth, and factor shares in the era of population aging," Journal of Economic Growth, Springer, vol. 26(4), pages 415-453, December.
    24. Zhang, Xinchun & Sun, Murong & Liu, Jianxu & Xu, Aijia, 2024. "The nexus between industrial robot and employment in China: The effects of technology substitution and technology creation," Technological Forecasting and Social Change, Elsevier, vol. 202(C).
    25. Ku, Inhoe & Ham, Sunyu & Moon, Heyjin, 2023. "Means-tested COVID-19 stimulus payment and consumer spending: Evidence from card transaction data in South Korea," Economic Analysis and Policy, Elsevier, vol. 78(C), pages 1359-1371.
    26. Jim Been & Eduard Suari‐Andreu & Marike Knoef & Rob Alessie, 2024. "Consumption and time use responses to unemployment: Implications for the lifecycle model," Economica, London School of Economics and Political Science, vol. 91(361), pages 1-32, January.
    27. Zhenqiang Li & Qiuyang Zhou & Ke Wang, 2024. "The impact of the digital economy on industrial structure upgrading in resource-based cities: Evidence from China," PLOS ONE, Public Library of Science, vol. 19(2), pages 1-13, February.
    28. Harrigan, James & Reshef, Ariell & Toubal, Farid, 2021. "The March of the Techies: Job Polarization Within and Between Firms," Research Policy, Elsevier, vol. 50(7).
    29. James Harrigan & Ariell Reshef & Farid Toubal, 2021. "The March of the Techies: Job Polarization Within and Between Firms," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-02973332, HAL.
    30. Harrigan, James & Reshef, Ariell & Toubal, Farid, 2021. "The March of the Techies: Job Polarization Within and Between Firms," Research Policy, Elsevier, vol. 50(7).
    31. David H. Autor & David Dorn, 2013. "The Growth of Low-Skill Service Jobs and the Polarization of the US Labor Market," American Economic Review, American Economic Association, vol. 103(5), pages 1553-1597, August.
    32. Raj Chetty & Adam Szeidl, 2016. "Consumption Commitments and Habit Formation," Econometrica, Econometric Society, vol. 84, pages 855-890, March.
    33. Daniel J. Walters & Gülden Ülkümen & David Tannenbaum & Carsten Erner & Craig R. Fox, 2023. "Investor Behavior Under Epistemic vs. Aleatory Uncertainty," Management Science, INFORMS, vol. 69(5), pages 2761-2777, May.
    34. Stojanovikj, Martin, 2022. "Government size, inflation targeting and business cycle volatility," Economic Analysis and Policy, Elsevier, vol. 74(C), pages 1-12.
    35. Alberto Alesina & Ekaterina Zhuravskaya, 2011. "Segregation and the Quality of Government in a Cross Section of Countries," American Economic Review, American Economic Association, vol. 101(5), pages 1872-1911, August.
    36. Ajay Agrawal & Joshua Gans & Avi Goldfarb, 2019. "The Economics of Artificial Intelligence: An Agenda," NBER Books, National Bureau of Economic Research, Inc, number agra-1, January.
    37. Colen, L. & Melo, P.C. & Abdul-Salam, Y. & Roberts, D. & Mary, S. & Gomez Y Paloma, S., 2018. "Income elasticities for food, calories and nutrients across Africa: A meta-analysis," Food Policy, Elsevier, vol. 77(C), pages 116-132.
    38. Olivier Coibion & Dimitris Georgarakos & Yuriy Gorodnichenko & Geoff Kenny & Michael Weber, 2024. "The Effect of Macroeconomic Uncertainty on Household Spending," American Economic Review, American Economic Association, vol. 114(3), pages 645-677, March.
    39. Mao, Rui & Xu, Jianwei, 2014. "Population aging, consumption budget allocation and sectoral growth," China Economic Review, Elsevier, vol. 30(C), pages 44-65.
    40. Christopher Carroll & Jiri Slacalek & Kiichi Tokuoka & Matthew N. White, 2017. "The distribution of wealth and the marginal propensity to consume," Quantitative Economics, Econometric Society, vol. 8(3), pages 977-1020, November.
    41. Hetschko, Clemens & Preuss, Malte, 2020. "Income in jeopardy: How losing employment affects the willingness to take risks," Journal of Economic Psychology, Elsevier, vol. 79(C).
    42. Brown, Sarah & Gray, Daniel & Harris, Mark N. & Spencer, Christopher, 2021. "Household portfolio allocation, uncertainty, and risk," Journal of Empirical Finance, Elsevier, vol. 63(C), pages 96-117.
    43. Chen, Yuanyuan & Yuan, Meng & Zhang, Min, 2023. "Income inequality and educational expenditures on children: Evidence from the China Family Panel Studies," China Economic Review, Elsevier, vol. 78(C).
    44. Meng, Xin, 2003. "Unemployment, consumption smoothing, and precautionary saving in urban China," Journal of Comparative Economics, Elsevier, vol. 31(3), pages 465-485, September.
    45. Anna Kollerup & Jakob Kjellberg & Rikke Ibsen, 2022. "Ageing and health care expenditures: the importance of age per se, steepening of the individual-level expenditure curve, and the role of morbidity," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 23(7), pages 1121-1149, September.
    46. Esa Karonen & Mikko Niemelä, 2022. "Necessity-Rich, Leisure-Poor: The Long-Term Relationship Between Income Cohorts and Consumption Through Age-Period-Cohort Analysis," Journal of Family and Economic Issues, Springer, vol. 43(3), pages 599-620, September.
    47. Daron Acemoglu, 2025. "The simple macroeconomics of AI," Economic Policy, CEPR, CESifo, Sciences Po;CES;MSH, vol. 40(121), pages 13-58.
    48. Barili, Emilia & Grembi, Veronica & Rosso, Anna C., 2023. "Mental health between present issues and future expectations," Health Policy, Elsevier, vol. 128(C), pages 42-48.
    49. Wang, Phyllis Xue & Kim, Sara & Kim, Minki, 2023. "Robot anthropomorphism and job insecurity: The role of social comparison," Journal of Business Research, Elsevier, vol. 164(C).
    50. Qingxin Xie & Fujin Yi & Xu Tian, 2022. "Disparate changes of living standard in China: perspective from Engel's coefficient," China Agricultural Economic Review, Emerald Group Publishing Limited, vol. 15(3), pages 481-505, August.
    51. Milton Friedman, 1957. "The Permanent Income Hypothesis," NBER Chapters, in: A Theory of the Consumption Function, pages 20-37, National Bureau of Economic Research, Inc.
    52. 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.
    53. Xie, Qian & Ke, Haie & Peng, Juan, 2024. "Impacts of Financial Literacy on Elderly Households’ Consumption," Finance Research Letters, Elsevier, vol. 62(PA).
    54. Nazareno, Luísa & Schiff, Daniel S., 2021. "The impact of automation and artificial intelligence on worker well-being," Technology in Society, Elsevier, vol. 67(C).
    55. Zhao, Weimin, 2019. "Does health insurance promote people's consumption? New evidence from China," China Economic Review, Elsevier, vol. 53(C), pages 65-86.
    56. Liu, Jun & Chang, Huihong & Forrest, Jeffrey Yi-Lin & Yang, Baohua, 2020. "Influence of artificial intelligence on technological innovation: Evidence from the panel data of china's manufacturing sectors," Technological Forecasting and Social Change, Elsevier, vol. 158(C).
    57. Syed Abdul Rehman Khan & Arsalan Zahid Piprani & Zhang Yu, 2022. "Digital technology and circular economy practices: future of supply chains," Operations Management Research, Springer, vol. 15(3), pages 676-688, December.
    58. Agrawal, Ajay & Gans, Joshua & Goldfarb, Avi (ed.), 2019. "The Economics of Artificial Intelligence," National Bureau of Economic Research Books, University of Chicago Press, number 9780226613338, August.
    59. Francisco Gomes & Thomas Jansson & Yigitcan Karabulut, 2024. "Do Robots Increase Wealth Dispersion?," The Review of Financial Studies, Society for Financial Studies, vol. 37(1), pages 119-160.
    60. Yingying Lu & Yixiao Zhou, 2019. "A Short Review on the Economics of Artificial Intelligence," CAMA Working Papers 2019-54, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    61. Brougham, David & Haar, Jarrod, 2020. "Technological disruption and employment: The influence on job insecurity and turnover intentions: A multi-country study," Technological Forecasting and Social Change, Elsevier, vol. 161(C).
    62. Foellmi, Reto & Jaeggi, Adrian & Rosenblatt-Wisch, Rina, 2019. "Loss aversion at the aggregate level across countries and its relation to economic fundamentals," Journal of Macroeconomics, Elsevier, vol. 61(C), pages 1-1.
    63. Chen, Kaiming & Chen, Xiaoqian & Wang, Zhan-ao & Zvarych, Roman, 2024. "Does artificial intelligence promote common prosperity within enterprises? —Evidence from Chinese-listed companies in the service industry," Technological Forecasting and Social Change, Elsevier, vol. 200(C).
    64. Choi, Jung Hyun & Zhu, Linna, 2022. "Has the effect of housing wealth on household consumption been overestimated? New evidence on magnitude and allocation," Regional Science and Urban Economics, Elsevier, vol. 95(C).
    65. Christian Dreger & Tongsan Wang & Yanqun Zhang, 2015. "Understanding Chinese Consumption: The Impact of Hukou," Development and Change, International Institute of Social Studies, vol. 46(6), pages 1331-1344, November.
    66. Luo, Sumei & Sun, Yongkun & Zhou, Rui, 2022. "Can fintech innovation promote household consumption? Evidence from China family panel studies," International Review of Financial Analysis, Elsevier, vol. 82(C).
    67. Islam, Asadul & Maitra, Pushkar, 2012. "Health shocks and consumption smoothing in rural households: Does microcredit have a role to play?," Journal of Development Economics, Elsevier, vol. 97(2), pages 232-243.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Liu, Wenling & Ma, Ziqing & Xiao, Shuwen & Xiao, Yuedong, 2025. "Habit formation under stress: How COVID-19 reshaped Chinese consumer behavior — short-term disruptions and long-term behavioral entrenchment," Structural Change and Economic Dynamics, Elsevier, vol. 75(C), pages 926-936.
    2. Del Río, Fernando & Rebelo, Francisco, 2025. "OECD labour share trends: Factor efficiency vs. market distortions in a neoclassical framework," Economic Analysis and Policy, Elsevier, vol. 87(C), pages 2554-2591.

    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. Caselli, Mauro & Fracasso, Andrea & Scicchitano, Sergio & Traverso, Silvio & Tundis, Enrico, 2025. "What workers and robots do: An activity-based analysis of the impact of robotization on changes in local employment," Research Policy, Elsevier, vol. 54(1).
    2. Thomas Gries & Wim Naudé, 2022. "Modelling artificial intelligence in economics," Journal for Labour Market Research, Springer;Institute for Employment Research/ Institut für Arbeitsmarkt- und Berufsforschung (IAB), vol. 56(1), pages 1-13, December.
    3. Zhang, Xinchun & Sun, Murong & Liu, Jianxu & Xu, Aijia, 2024. "The nexus between industrial robot and employment in China: The effects of technology substitution and technology creation," Technological Forecasting and Social Change, Elsevier, vol. 202(C).
    4. Czarnitzki, Dirk & Fernández, Gastón P. & Rammer, Christian, 2023. "Artificial intelligence and firm-level productivity," Journal of Economic Behavior & Organization, Elsevier, vol. 211(C), pages 188-205.
    5. Li, Chao & Zhang, Yuhan & Li, Xiang & Hao, Yanwei, 2024. "Artificial intelligence, household financial fragility and energy resources consumption: Impacts of digital disruption from a demand-based perspective," Resources Policy, Elsevier, vol. 88(C).
    6. Fossen, Frank M. & Sorgner, Alina, 2022. "New digital technologies and heterogeneous wage and employment dynamics in the United States: Evidence from individual-level data," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    7. Chao Li & Zhanjun Xing & Xiang Li & Liping Chen, 2026. "How Does Automation in the Workplace Impact Workers’ Happiness? Disentangling the Competing Mechanisms Through Income Shock and Reduced Working Time," Journal of Happiness Studies, Springer, vol. 27(2), pages 1-41, February.
    8. Anderton, Robert & Jarvis, Valerie & Labhard, Vincent & Morgan, Julian & Petroulakis, Filippos & Vivian, Lara, 2020. "Virtually everywhere? Digitalisation and the euro area and EU economies," Occasional Paper Series 244, European Central Bank.
    9. Belloc, Filippo & Burdin, Gabriel & Cattani, Luca & Ellis, William & Landini, Fabio, 2022. "Coevolution of job automation risk and workplace governance," Research Policy, Elsevier, vol. 51(3).
    10. Arntz, Melanie & Gregory, Terry & Zierahn-Weilage, Ulrich, 2019. "Digitalization and the Future of Work: Macroeconomic Consequences," IZA Discussion Papers 12428, IZA Network @ LISER.
    11. Sun, Hongye & Gao, Gongjing, 2025. "The impact of intelligent automation on subjective well-being and job satisfaction: A comparison between standard and nonstandard employment," China Economic Review, Elsevier, vol. 94(PB).
    12. Yingying Lu & Yixiao Zhou, 2021. "A review on the economics of artificial intelligence," Journal of Economic Surveys, Wiley Blackwell, vol. 35(4), pages 1045-1072, September.
    13. Wang, Linhui & Cao, Zhanglu & Dong, Zhiqing, 2023. "Are artificial intelligence dividends evenly distributed between profits and wages? Evidence from the private enterprise survey data in China," Structural Change and Economic Dynamics, Elsevier, vol. 66(C), pages 342-356.
    14. Chen, Xiaoxiao & Yang, Jiayi & Wu, Bo, 2025. "How is artificial intelligence shaping the labor demand of firms? ——evidence from text-mining analysis of listed companies," Telecommunications Policy, Elsevier, vol. 49(10).
    15. Zhou, Huilin & Wang, Linhui & Cao, Yutong & Li, Jincheng, 2025. "The impact of artificial intelligence on labor market: A study based on bibliometric analysis," Journal of Asian Economics, Elsevier, vol. 98(C).
    16. Alessandro Sterlacchini, 2022. "AI Patenting and Employment: Evidence from the World's Top R&D Investors," Working Papers 462, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.
    17. Ahmet Koseoglu & Ali Gokhan Yucel, 2025. "On the Impact of Artificial Intelligence on Employment: Empirical Evidence from Selected Countries," RAIS Conference Proceedings 2022-2026 0552, Research Association for Interdisciplinary Studies.
    18. Stähler, Nikolai, 2021. "The Impact of Aging and Automation on the Macroeconomy and Inequality," Journal of Macroeconomics, Elsevier, vol. 67(C).
    19. Gao, Jie & Li, Zhizhuo & Nguyen, Thithuha & Zhang, Wentao, 2025. "Digital transformation and enterprise employment," International Review of Economics & Finance, Elsevier, vol. 99(C).
    20. Lionel Fontagné & Ariell Reshef & Gianluca Santoni & Giulio Vannelli, 2024. "Automation, global value chains and functional specialization," Review of International Economics, Wiley Blackwell, vol. 32(2), pages 662-691, May.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    JEL classification:

    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • O30 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - General
    • J23 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Demand

    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:eee:ecanpo:v:84:y:2024:i:c:p:1287-1308. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/economic-analysis-and-policy .

    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.