IDEAS home Printed from https://ideas.repec.org/a/oup/restud/v90y2023i4p1701-1723..html
   My bibliography  Save this article

Data-intensive Innovation and the State: Evidence from AI Firms in China

Author

Listed:
  • Martin Beraja
  • David Y Yang
  • Noam Yuchtman

Abstract

Developing artificial intelligence (AI) technology requires data. In many domains, government data far exceed in magnitude and scope data collected by the private sector, and AI firms often gain access to such data when providing services to the state. We argue that such access can stimulate commercial AI innovation in part because data and trained algorithms are shareable across government and commercial uses. We gather comprehensive information on firms and public security procurement contracts in China’s facial recognition AI industry. We quantify the data accessible through contracts by measuring public security agencies’ capacity to collect surveillance video. Using a triple-differences strategy, we find that data-rich contracts, compared to data-scarce ones, lead recipient firms to develop significantly and substantially more commercial AI software. Our analysis suggests a contribution of government data to the rise of China’s facial recognition AI firms, and that states’ data collection and provision policies could shape AI innovation.

Suggested Citation

  • Martin Beraja & David Y Yang & Noam Yuchtman, 2023. "Data-intensive Innovation and the State: Evidence from AI Firms in China," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 90(4), pages 1701-1723.
  • Handle: RePEc:oup:restud:v:90:y:2023:i:4:p:1701-1723.
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1093/restud/rdac056
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

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

    Other versions of this item:

    References listed on IDEAS

    as
    1. Anderson, Michael L., 2008. "Multiple Inference and Gender Differences in the Effects of Early Intervention: A Reevaluation of the Abecedarian, Perry Preschool, and Early Training Projects," Journal of the American Statistical Association, American Statistical Association, vol. 103(484), pages 1481-1495.
    2. Daron Acemoglu & Philippe Aghion & Leonardo Bursztyn & David Hemous, 2012. "The Environment and Directed Technical Change," American Economic Review, American Economic Association, vol. 102(1), pages 131-166, February.
    3. Petra Moser, 2005. "How Do Patent Laws Influence Innovation? Evidence from Nineteenth-Century World's Fairs," American Economic Review, American Economic Association, vol. 95(4), pages 1214-1236, September.
    4. Nicholas Bloom & Charles I. Jones & John Van Reenen & Michael Webb, 2020. "Are Ideas Getting Harder to Find?," American Economic Review, American Economic Association, vol. 110(4), pages 1104-1144, April.
    5. Raffaello Bronzini & Eleonora Iachini, 2014. "Are Incentives for R&D Effective? Evidence from a Regression Discontinuity Approach," American Economic Journal: Economic Policy, American Economic Association, vol. 6(4), pages 100-134, November.
    6. Achyuta Adhvaryu & Anant Nyshadham & Jorge A. Tamayo, 2019. "Managerial Quality and Productivity Dynamics," NBER Working Papers 25852, National Bureau of Economic Research, Inc.
    7. Nicholas Bloom & John Van Reenen & Heidi Williams, 2019. "A toolkit of policies to promote innovation," Voprosy Ekonomiki, NP Voprosy Ekonomiki, issue 10.
    8. Lane, Nathaniel, 2016. "Manufacturing Revolutions: Industrial Policy and Industrialization in South Korea," SocArXiv 6tqax, Center for Open Science.
    9. Heidi L. Williams, 2013. "Intellectual Property Rights and Innovation: Evidence from the Human Genome," Journal of Political Economy, University of Chicago Press, vol. 121(1), pages 1-27.
    10. Philippe Aghion & Antoine Dechezleprêtre & David Hémous & Ralf Martin & John Van Reenen, 2016. "Carbon Taxes, Path Dependency, and Directed Technical Change: Evidence from the Auto Industry," Journal of Political Economy, University of Chicago Press, vol. 124(1), pages 1-51.
    11. Raymond Fisman & Yongxiang Wang, 2015. "The Mortality Cost of Political Connections," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 82(4), pages 1346-1382.
    12. Viktor Slavtchev & Simon Wiederhold, 2016. "Does the Technological Content of Government Demand Matter for Private R&D? Evidence from US States," American Economic Journal: Macroeconomics, American Economic Association, vol. 8(2), pages 45-84, April.
    13. Pierre Azoulay & Joshua S Graff Zivin & Danielle Li & Bhaven N Sampat, 2019. "Public R&D Investments and Private-sector Patenting: Evidence from NIH Funding Rules," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 86(1), pages 117-152.
    14. Enrico Moretti & Claudia Steinwender & John Van Reenen, 2019. "The intellectual spoils of war? Defense R&D, productivity and international spillovers," CEP Discussion Papers dp1662, Centre for Economic Performance, LSE.
    15. Daron Acemoglu & David Cutler & Amy Finkelstein & Joshua Linn, 2006. "Did Medicare Induce Pharmaceutical Innovation?," American Economic Review, American Economic Association, vol. 96(2), pages 103-107, May.
    16. Maryam Farboodi & Roxana Mihet & Thomas Philippon & Laura Veldkamp, 2019. "Big Data and Firm Dynamics," AEA Papers and Proceedings, American Economic Association, vol. 109, pages 38-42, May.
    17. Lawrence J. Lau & Yingyi Qian & Gerard Roland, 2000. "Reform without Losers: An Interpretation of China's Dual-Track Approach to Transition," Journal of Political Economy, University of Chicago Press, vol. 108(1), pages 120-143, February.
    18. Mark J Roberts & Daniel Yi Xu & Xiaoyan Fan & Shengxing Zhang, 2018. "The Role of Firm Factors in Demand, Cost, and Export Market Selection for Chinese Footwear Producers," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 85(4), pages 2429-2461.
    19. Daron Acemoglu & Philippe Aghion & Fabrizio Zilibotti, 2006. "Distance to Frontier, Selection, and Economic Growth," Journal of the European Economic Association, MIT Press, vol. 4(1), pages 37-74, March.
    20. Barro, Robert J, 1990. "Government Spending in a Simple Model of Endogenous Growth," Journal of Political Economy, University of Chicago Press, vol. 98(5), pages 103-126, October.
    21. Amit K. Khandelwal & Peter K. Schott & Shang-Jin Wei, 2013. "Trade Liberalization and Embedded Institutional Reform: Evidence from Chinese Exporters," American Economic Review, American Economic Association, vol. 103(6), pages 2169-2195, October.
    22. Hémous, David, 2016. "The dynamic impact of unilateral environmental policies," Journal of International Economics, Elsevier, vol. 103(C), pages 80-95.
    23. Arnaud Costinot & Dave Donaldson & Margaret Kyle & Heidi Williams, 2019. "The More We Die, The More We Sell? A Simple Test of the Home-Market Effect," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 134(2), pages 843-894.
    24. Chong-en Bai & Chang-Tai Hsieh & Zheng Song, 2020. "Special Deals with Chinese Characteristics," NBER Macroeconomics Annual, University of Chicago Press, vol. 34(1), pages 341-379.
    25. Tsai, Lily L., 2007. "Solidary Groups, Informal Accountability, and Local Public Goods Provision in Rural China," American Political Science Review, Cambridge University Press, vol. 101(2), pages 355-372, May.
    26. Daniel P. Gross & Bhaven N. Sampat, 2023. "America, Jump-Started: World War II R&D and the Takeoff of the US Innovation System," American Economic Review, American Economic Association, vol. 113(12), pages 3323-3356, December.
    27. Guy Aridor & Yeon-Koo Che & Tobias Salz, 2020. "The Effect of Privacy Regulation on the Data Industry: Empirical Evidence from GDPR," NBER Working Papers 26900, National Bureau of Economic Research, Inc.
    28. Murphy, Kevin M & Shleifer, Andrei & Vishny, Robert W, 1989. "Industrialization and the Big Push," Journal of Political Economy, University of Chicago Press, vol. 97(5), pages 1003-1026, October.
    29. Alvin E. Roth, 2007. "Repugnance as a Constraint on Markets," Journal of Economic Perspectives, American Economic Association, vol. 21(3), pages 37-58, Summer.
    30. 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.
    31. Li, Hongbin & Zhou, Li-An, 2005. "Political turnover and economic performance: the incentive role of personnel control in China," Journal of Public Economics, Elsevier, vol. 89(9-10), pages 1743-1762, September.
    32. Guojun He & Shaoda Wang & Bing Zhang, 2020. "Watering Down Environmental Regulation in China," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 135(4), pages 2135-2185.
    33. Ruixue Jia & Masayuki Kudamatsu & David Seim, 2015. "Political Selection In China: The Complementary Roles Of Connections And Performance," Journal of the European Economic Association, European Economic Association, vol. 13(4), pages 631-668, August.
    34. Richard G. Newell & Adam B. Jaffe & Robert N. Stavins, 1999. "The Induced Innovation Hypothesis and Energy-Saving Technological Change," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 114(3), pages 941-975.
    35. Avi Goldfarb & Daniel Trefler, 2018. "Artificial Intelligence and International Trade," NBER Chapters, in: The Economics of Artificial Intelligence: An Agenda, pages 463-492, National Bureau of Economic Research, Inc.
    36. Daron Acemoglu, 1998. "Why Do New Technologies Complement Skills? Directed Technical Change and Wage Inequality," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 113(4), pages 1055-1089.
    37. Charles I. Jones & Christopher Tonetti, 2020. "Nonrivalry and the Economics of Data," American Economic Review, American Economic Association, vol. 110(9), pages 2819-2858, September.
    38. Pierre Azoulay & Erica Fuchs & Anna P. Goldstein & Michael Kearney, 2018. "Funding Breakthrough Research: Promises and Challenges of the "ARPA Model"," NBER Chapters, in: Innovation Policy and the Economy, Volume 19, pages 69-96, National Bureau of Economic Research, Inc.
    39. Zheng Song & Kjetil Storesletten & Fabrizio Zilibotti, 2011. "Growing Like China," American Economic Review, American Economic Association, vol. 101(1), pages 196-233, February.
    40. Sabrina T. Howell, 2017. "Financing Innovation: Evidence from R&D Grants," American Economic Review, American Economic Association, vol. 107(4), pages 1136-1164, April.
    41. W. Walker Hanlon, 2015. "Necessity Is the Mother of Invention: Input Supplies and Directed Technical Change," Econometrica, Econometric Society, vol. 83, pages 67-100, January.
    42. Dominick Bartelme & Arnaud Costinot & Dave Donaldson & Andres Rodriguez-Clare, "undated". "The Textbook Case for Industrial Policy: Theory Meets Data," Working Papers 675, Research Seminar in International Economics, University of Michigan.
    43. Ethan Lewis, 2013. "Immigration and Production Technology," Annual Review of Economics, Annual Reviews, vol. 5(1), pages 165-191, May.
    44. Michela Giorcelli, 2019. "The Long-Term Effects of Management and Technology Transfers," American Economic Review, American Economic Association, vol. 109(1), pages 121-152, January.
    45. Ernest Liu, 2019. "Industrial Policies in Production Networks," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 134(4), pages 1883-1948.
    46. 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.
    47. David Popp, 2002. "Induced Innovation and Energy Prices," American Economic Review, American Economic Association, vol. 92(1), pages 160-180, March.
    48. Timothy Besley & Torsten Persson, 2019. "JEEA-FBBVA LECTURE 2017: The Dynamics of Environmental Politics and Values," Journal of the European Economic Association, European Economic Association, vol. 17(4), pages 993-1024.
    49. North,Douglass C. & Wallis,John Joseph & Weingast,Barry R., 2013. "Violence and Social Orders," Cambridge Books, Cambridge University Press, number 9781107646995.
    50. Jeffrey Clemens & Parker Rogers, 2020. "Demand Shocks, Procurement Policies, and the Nature of Medical Innovation: Evidence from Wartime Prosthetic Device Patents," NBER Working Papers 26679, National Bureau of Economic Research, Inc.
    51. Kalouptsidi, Myrto, 2017. "Detection and Impact of Industrial Subsidies: The Case of Chinese Shipbuilding," CEPR Discussion Papers 12080, C.E.P.R. Discussion Papers.
    52. Pierre Azoulay & Erica Fuchs & Anna Goldstein & Michael Kearney, 2018. "Funding Breakthrough Research: Promises and Challenges of the “ARPA Model”," NBER Working Papers 24674, National Bureau of Economic Research, Inc.
    53. Panzar, John C & Willig, Robert D, 1981. "Economies of Scope," American Economic Review, American Economic Association, vol. 71(2), pages 268-272, May.
    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. Tamay Besiroglu & Nicholas Emery-Xu & Neil Thompson, 2022. "Economic impacts of AI-augmented R&D," Papers 2212.08198, arXiv.org, revised Jan 2023.
    2. Igna, Ioana & Venturini, Francesco, 2023. "The determinants of AI innovation across European firms," Research Policy, Elsevier, vol. 52(2).
    3. Hao, Xuejing & Hu, Feng & Li, Zhu, 2024. "Entrepreneur-investor gender match effects in startup funding: Evidence from an entrepreneurial-themed reality TV show in China," International Review of Economics & Finance, Elsevier, vol. 93(PA), pages 811-832.
    4. Mary Merva & Adrian Stoian & Simona Costagli, 2021. "Effective information, political structure and economic growth," Economics of Transition and Institutional Change, John Wiley & Sons, vol. 29(4), pages 597-620, October.
    5. Ding, Jeffrey, 2022. "Techno-industrial Policy for New Infrastructure: China’s Approach to Promoting Artificial Intelligence as a General Purpose Technology," Institute on Global Conflict and Cooperation, Working Paper Series qt1sb844ws, Institute on Global Conflict and Cooperation, University of California.
    6. Christian Peukert & Florian Abeillon & Jérémie Haese & Franziska Kaiser & Alexander Staub, 2024. "Strategic Behavior and AI Training Data," CESifo Working Paper Series 11099, CESifo.
    7. Christian Peukert & Florian Abeillon & J'er'emie Haese & Franziska Kaiser & Alexander Staub, 2024. "Strategic Behavior and AI Training Data," Papers 2404.18445, arXiv.org.
    8. Freeman, Richard B. & Yang, Buyuan & Zhang, Baitao, 2023. "Data deepening and nonbalanced economic growth," Journal of Macroeconomics, Elsevier, vol. 75(C).
    9. Chakraborty, Pavel & Chakrabarti, Anindya S. & Chatterjee, Chirantan, 2023. "Cross-border environmental regulation and firm labor demand," Journal of Environmental Economics and Management, Elsevier, vol. 117(C).
    10. David Karpa & Torben Klarl & Michael Rochlitz, 2021. "Artificial Intelligence, Surveillance, and Big Data," Bremen Papers on Economics & Innovation 2108, University of Bremen, Faculty of Business Studies and Economics.
    11. Naudé, Wim & Dimitri, Nicola, 2021. "Public Procurement and Innovation for Human-Centered Artificial Intelligence," IZA Discussion Papers 14021, Institute of Labor Economics (IZA).
    12. Catherine E. Tucker, 2023. "The Economics of Privacy: An Agenda," NBER Chapters, in: The Economics of Privacy, National Bureau of Economic Research, Inc.
    13. Yan Wang & Ping Han, 2023. "Digital Transformation, Service-Oriented Manufacturing, and Total Factor Productivity: Evidence from A-Share Listed Companies in China," Sustainability, MDPI, vol. 15(13), pages 1-24, June.
    14. repec:ocp:ppaper:pb10-24 is not listed on IDEAS
    15. Ma, Rui & Guo, Fei & Li, Dongdong, 2024. "Can public data availability affect stock price crash risk? Evidence from China," International Review of Financial Analysis, Elsevier, vol. 94(C).
    16. Matheus Eduardo Leusin, 2022. "The Development of Al in Multinational Enterprises - Effects upon Technological Trajectories and Innovation Performance," Bremen Papers on Economics & Innovation 2201, University of Bremen, Faculty of Business Studies and Economics.
    17. Tiago C. Peixoto & Otaviano Canuto, & Luke Jordan, 2024. "AI and the Future of Government: Unexpected Effects and Critical Challenges," Policy briefs on Economic Trends and Policies 2408, Policy Center for the New South.
    18. Li, Yuetong & Wang, Xinyi & Zheng, Xiaojia, 2024. "Data assets and corporate sustainable development: evidence from ESG in China," Pacific-Basin Finance Journal, Elsevier, vol. 85(C).
    19. Lee, Yong Suk & Kim, Taekyun & Choi, Sukwoong & Kim, Wonjoon, 2022. "When does AI pay off? AI-adoption intensity, complementary investments, and R&D strategy," Technovation, Elsevier, vol. 118(C).

    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. Pallante, Gianluca & Russo, Emanuele & Roventini, Andrea, 2023. "Does public R&D funding crowd-in private R&D investment? Evidence from military R&D expenditures for US states," Research Policy, Elsevier, vol. 52(8).
    2. Cameron Hepburn & Jacquelyn Pless & David Popp, 2018. "Policy Brief—Encouraging Innovation that Protects Environmental Systems: Five Policy Proposals," Review of Environmental Economics and Policy, Association of Environmental and Resource Economists, vol. 12(1), pages 154-169.
    3. Julián D. Gómez, 2018. "¿Qué determina la adopción de tecnologías para la generación de energías renovables entre países?," Documentos CEDE 17132, Universidad de los Andes, Facultad de Economía, CEDE.
    4. Boyce, John R., 2019. "The paradox of value, directed technical change, and the relative abundance of the chemical elements," Resource and Energy Economics, Elsevier, vol. 58(C).
    5. Danzer, Alexander M. & Danzer, Natalia & Feuerbaum, Carsten, 2023. "Military Spending and Innovation: Learning from 19th Century World Fair Exhibition Data," IZA Discussion Papers 16034, Institute of Labor Economics (IZA).
    6. Chiappinelli, Olga & Giuffrida, Leonardo M. & Spagnolo, Giancarlo, 2023. "Public procurement as an innovation policy: Where do we stand?," ZEW Discussion Papers 23-002, ZEW - Leibniz Centre for European Economic Research.
    7. Howell, Sabrina T. & Rathje, Jason & Van Reenen, John & Wong, Jun, 2021. "Opening up Military Innovation: Causal Effects of 'Bottom-up' Reforms to U.S. Defense Research," IZA Discussion Papers 14297, Institute of Labor Economics (IZA).
    8. Howell, Sabrina T. & Rathje, Jason & Van Reenen, John & Wong, Jun, 2021. "Opening up military innovation: causal effects of reforms to US defense research," LSE Research Online Documents on Economics 114430, London School of Economics and Political Science, LSE Library.
    9. Philippe Aghion & Antoine Dechezleprêtre & David Hémous & Ralf Martin & John Van Reenen, 2016. "Carbon Taxes, Path Dependency, and Directed Technical Change: Evidence from the Auto Industry," Journal of Political Economy, University of Chicago Press, vol. 124(1), pages 1-51.
    10. Gregory Casey, 2024. "Energy Efficiency and Directed Technical Change: Implications for Climate Change Mitigation," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 91(1), pages 192-228.
    11. Li, Zhen & Wu, Baijun & Wang, Danyang & Tang, Maogang, 2022. "Government mandatory energy-biased technological progress and enterprises' environmental performance: Evidence from a quasi-natural experiment of cleaner production standards in China," Energy Policy, Elsevier, vol. 162(C).
    12. Yang, Jun & Yang, Dingjian & Cheng, Jixin, 2024. "The non-rivalry of data, directed technical change and the environment: A theoretical study incorporating data as a production factor," Economic Analysis and Policy, Elsevier, vol. 82(C), pages 417-448.
    13. van den Bijgaart, Inge, 2017. "The unilateral implementation of a sustainable growth path with directed technical change," European Economic Review, Elsevier, vol. 91(C), pages 305-327.
    14. Hémous, David & Dechezleprêtre, Antoine & Olsen, Morten & Zanella, carlo, 2019. "Automating Labor: Evidence from Firm-level Patent Data," CEPR Discussion Papers 14249, C.E.P.R. Discussion Papers.
    15. David Andersson & Mounir Karadja & Erik Prawitz, 2022. "Mass Migration and Technological Change," Journal of the European Economic Association, European Economic Association, vol. 20(5), pages 1859-1896.
    16. Bo, Shiyu & Liu, Cong & Zhou, Yan, 2023. "Military investment and the rise of industrial clusters: Evidence from China’s self-strengthening movement," Journal of Development Economics, Elsevier, vol. 161(C).
    17. Naqvi, Asjad & Stockhammer, Engelbert, 2018. "Directed Technological Change in a Post-Keynesian Ecological Macromodel," Ecological Economics, Elsevier, vol. 154(C), pages 168-188.
    18. Naudé, Wim & Dimitri, Nicola, 2021. "Public Procurement and Innovation for Human-Centered Artificial Intelligence," IZA Discussion Papers 14021, Institute of Labor Economics (IZA).
    19. Jeffrey P. Clemens & Parker Rogers, 2020. "Demand Shocks, Procurement Policies, and the Nature of Medical Innovation: Evidence from Wartime Prosthetic Device Patents," CESifo Working Paper Series 8781, CESifo.
    20. Andreas Schaefer, 2017. "Enforcement of Intellectual Property, Pollution Abatement, and Directed Technical Change," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 66(3), pages 457-480, March.

    More about this item

    Keywords

    Data; Innovation; Artificial intelligence; China; Innovation policy; Privacy; Surveillance;
    All these keywords.

    JEL classification:

    • O30 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - General
    • P00 - Political Economy and Comparative Economic Systems - - General - - - General
    • E00 - Macroeconomics and Monetary Economics - - General - - - General
    • L50 - Industrial Organization - - Regulation and Industrial Policy - - - General
    • L63 - Industrial Organization - - Industry Studies: Manufacturing - - - Microelectronics; Computers; Communications Equipment
    • O23 - Economic Development, Innovation, Technological Change, and Growth - - Development Planning and Policy - - - Fiscal and Monetary Policy in Development
    • O40 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - General

    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:oup:restud:v:90:y:2023:i:4:p:1701-1723.. 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: Oxford University Press (email available below). General contact details of provider: https://academic.oup.com/restud .

    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.