IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v13y2021i23p13495-d696163.html
   My bibliography  Save this article

Could Government Data Openness Enhance Urban Innovation Capability? An Evaluation Based on Multistage DID Method

Author

Listed:
  • Yi Luo

    (School of Management and Economics, University of Electronic Science and Technology of China, Chengdu 611731, China)

  • Zhiwei Tang

    (School of Public Affairs and Administration, University of Electronic Science and Technology of China, Chengdu 611731, China)

  • Peiqi Fan

    (School of Public Affairs and Administration, University of Electronic Science and Technology of China, Chengdu 611731, China)

Abstract

The wave of government data opening has gradually swept the world since it rose from the United States in 2009. The purpose is not to open government data, but to release data value and drive economic and social development through data accessibility. At present, the impact of academic circles on government open data mostly stays in theoretical discussion, especially due to the lack of empirical tests. Using the multistage difference-in-difference (DID) model, this paper analyzes the panel data from 2009 to 2016 by taking two batches of Chinese cities with open data released in 2014 and 2105 as samples to test the impact of government data opening on urban innovation ability. The results show that the opening of government data significantly improves urban innovation abilities. After considering the heterogeneity and fixed effects of urban characteristics, the opening of government data still significantly improves urban innovation ability and shows a greater innovation driving role in cities with high levels of economic development, human capital, and infrastructure. Based on this, this paper believes that we should continue to promote the opening of government data, release the value of data, and pay attention to the Matthew effect between cities that may appear in the era of big data.

Suggested Citation

  • Yi Luo & Zhiwei Tang & Peiqi Fan, 2021. "Could Government Data Openness Enhance Urban Innovation Capability? An Evaluation Based on Multistage DID Method," Sustainability, MDPI, vol. 13(23), pages 1-16, December.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:23:p:13495-:d:696163
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/13/23/13495/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/13/23/13495/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jacobson, Louis S & LaLonde, Robert J & Sullivan, Daniel G, 1993. "Earnings Losses of Displaced Workers," American Economic Review, American Economic Association, vol. 83(4), pages 685-709, September.
    2. Ward, Michael R. & Zheng, Shilin, 2012. "Mobile and fixed substitution for telephone service in China," Telecommunications Policy, Elsevier, vol. 36(4), pages 301-310.
    3. Teresa M. Harrison & Theresa A. Pardo & Meghan Cook, 2012. "Creating Open Government Ecosystems: A Research and Development Agenda," Future Internet, MDPI, vol. 4(4), pages 1-29, October.
    4. Thorsten Beck & Ross Levine & Alexey Levkov, 2010. "Big Bad Banks? The Winners and Losers from Bank Deregulation in the United States," Journal of Finance, American Finance Association, vol. 65(5), pages 1637-1667, October.
    5. Lucarelli Stefano & Carlo Vercellone, 2014. "The Thesis of Cognitive Capitalism. New Research Perspectives. An Introduction," Post-Print halshs-00973501, HAL.
    6. Pakes, Ariel & Schankerman, Mark A., 1978. "The Rate of Obsolescence of Knowledge, Research Gestation Labs, and the Private Rate of Return to Research Resources," Working Papers 78-13, C.V. Starr Center for Applied Economics, New York University.
    7. repec:pri:indrel:dsp01d791sg182 is not listed on IDEAS
    8. Li, Pei & Lu, Yi & Wang, Jin, 2016. "Does flattening government improve economic performance? Evidence from China," Journal of Development Economics, Elsevier, vol. 123(C), pages 18-37.
    9. Linda Veiga & Maria Pinho, 2007. "The political economy of intergovernmental grants: Evidence from a maturing democracy," Public Choice, Springer, vol. 133(3), pages 457-477, December.
    10. James J. Heckman & Hidehiko Ichimura & Petra Todd, 1998. "Matching As An Econometric Evaluation Estimator," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 65(2), pages 261-294.
    11. Orley Ashenfelter, 1976. "Estimating the Effect of Training Programs on Earnings with Longitudinal Data," Working Papers 473, Princeton University, Department of Economics, Industrial Relations Section..
    12. Bernd W. Wirtz & Robert Piehler & Marc-Julian Thomas & Peter Daiser, 2016. "Resistance of Public Personnel to Open Government: A cognitive theory view of implementation barriers towards open government data," Public Management Review, Taylor & Francis Journals, vol. 18(9), pages 1335-1364, October.
    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. Li, Changsheng & Qi, Yaping & Liu, Shaohui & Wang, Xu, 2022. "Do carbon ETS pilots improve cities' green total factor productivity? Evidence from a quasi-natural experiment in China," Energy Economics, Elsevier, vol. 108(C).
    2. Sun, Chuanwang & Zhan, Yanhong & Du, Gang, 2020. "Can value-added tax incentives of new energy industry increase firm's profitability? Evidence from financial data of China's listed companies," Energy Economics, Elsevier, vol. 86(C).
    3. Guo, Qingbin & Zhong, Jinrong, 2022. "The effect of urban innovation performance of smart city construction policies: Evaluate by using a multiple period difference-in-differences model," Technological Forecasting and Social Change, Elsevier, vol. 184(C).
    4. Li, Bo & Han, Yukai & Wang, Chensheng & Sun, Wei, 2022. "Did civilized city policy improve energy efficiency of resource-based cities? Prefecture-level evidence from China," Energy Policy, Elsevier, vol. 167(C).
    5. Yi Li & Lili Ding & Yongliang Yang, 2020. "Can the Introduction of an Environmental Target Assessment Policy Improve the TFP of Textile Enterprises? A Quasi-Natural Experiment Based on the Huai River Basin in China," Sustainability, MDPI, vol. 12(4), pages 1-19, February.
    6. Kong, Dongmin & Liu, Chenhao & Ye, Wenxu, 2023. "Randomized inspection and firm's government subsidies: A natural experiment in China," China Economic Review, Elsevier, vol. 82(C).
    7. Hongsheng Fang & Xufei Zhang & Lin Guo, 2023. "Productivity effects of corporate income tax: Evidence from China," The World Economy, Wiley Blackwell, vol. 46(6), pages 1815-1842, June.
    8. Xiao Wang & Jinming Shi & Jia Li & Yu Chen & Jianxu Liu & Songsak Sriboonchitta, 2023. "Analysis on Trade Competition and Complementarity of High-Quality Agricultural Products in Countries along the Belt and Road Initiative," Sustainability, MDPI, vol. 15(8), pages 1-34, April.
    9. Xiaoshu Xu & Airong Yue & Xuechen Meng, 2023. "Increase in Industrial Sulfur Dioxide Pollution Fee and Polluting Firms’ Green Total Factor Productivity: Evidence from China," Sustainability, MDPI, vol. 15(14), pages 1-12, July.
    10. Keqiang Wang & Chunxin Lin, 2024. "Can Low-Carbon Transition Impact the High-Quality Development of the Manufacturing Industry?—Experience Evidence from a Low-Carbon Pilot Policy," Sustainability, MDPI, vol. 16(23), pages 1-28, December.
    11. Cailou Jiang & Rong Liu & Jie Han, 2023. "Does accountability audit of natural resource promote corporate environmental performance? An external supervision perspective," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(9), pages 9417-9438, September.
    12. Zifang Ding & Xiang Gao & Xuesong Qian & Huanhuan Wang, 2022. "Governmental inspection and local legislation on environmental protection: Evidence from China," Journal of Economic Surveys, Wiley Blackwell, vol. 36(3), pages 728-763, July.
    13. Mengjia Zhen & Junlan Yu & Siyi Chen & Ning Wang & Zhigang Chen, 2023. "Evaluating the Impact of County-to-District Transformation on Urban Residential Land Supply: A Multi-Period Difference-in-Differences Model Analysis," Land, MDPI, vol. 12(6), pages 1-20, May.
    14. Laiqun Jin & Xiuyan Liu & Sam Hak Kan Tang, 2021. "High-Technology Zones, Misallocation of Resources among Cities and Aggregate Productivity: Evidence from China," Economics Discussion / Working Papers 21-11, The University of Western Australia, Department of Economics.
    15. Francesco Serti & Chiara Tomasi, 2008. "Self-Selection and Post-Entry Effects of Exports: Evidence from Italian Manufacturing Firms," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 144(4), pages 660-694, December.
    16. Xuefeng Shao & Shi Chen, 2024. "Research on Tax Compliance Incentive Effects of Platform Companies from the Perspective of Incomplete Contract – An Empirical Study Based on China," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 26(65), pages 330-330, February.
    17. von Greiff, Jenny, 2009. "Displacement and self-employment entry," Labour Economics, Elsevier, vol. 16(5), pages 556-565, October.
    18. Jingyi Tian & Jun Nagayasu, 2023. "Financial Systemic Risk behind Artificial Intelligence:Evidence from China," TUPD Discussion Papers 44, Graduate School of Economics and Management, Tohoku University.
    19. Guorong Chen & Changyan Liu, 2023. "Can Low–Carbon City Development Stimulate Population Growth? Insights from China’s Low–Carbon Pilot Program," Sustainability, MDPI, vol. 15(20), pages 1-22, October.
    20. Wang, Yunmin & Cao, Guohua & Yan, Youliang & Wang, Jingjing, 2022. "Does high-speed rail stimulate cross-city technological innovation collaboration? Evidence from China," Transport Policy, Elsevier, vol. 116(C), pages 119-131.

    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:gam:jsusta:v:13:y:2021:i:23:p:13495-:d:696163. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.