Higher education not only enhances people's well-being, but also plays an important role in the in-depth implementation of the innovation-driven development strategy. In this paper, we use Chinese urban data for 1995–2020, utilizing the higher education expansion policy implemented in China in 1999 as an external shock. Using Double/Debiased Machine Learning (DML), we examine the impact of the aforementioned policy on urban innovation and its mechanisms. The results show that: (1) The higher education expansion policy significantly promotes urban innovation; (2) the policy promotes human capital expansion and strengthens government financial support, thereby significantly fostering urban innovation; (3) the impact of the policy varies across cities with different geographic locations, population densities and levels of marketization. Therefore, the findings of this paper provide empirical evidence that higher education expansion policy stimulates urban innovation. It also offers useful insights for China's transition from "Made in China" to "Created in China" during its high-quality development phase.
Citation: Qinghua Zhang, Yuhang Chen, Yilin Zhong, Junhao Zhong. The positive effects of the higher education expansion policy on urban innovation in China[J]. AIMS Mathematics, 2024, 9(2): 2985-3010. doi: 10.3934/math.2024147
Higher education not only enhances people's well-being, but also plays an important role in the in-depth implementation of the innovation-driven development strategy. In this paper, we use Chinese urban data for 1995–2020, utilizing the higher education expansion policy implemented in China in 1999 as an external shock. Using Double/Debiased Machine Learning (DML), we examine the impact of the aforementioned policy on urban innovation and its mechanisms. The results show that: (1) The higher education expansion policy significantly promotes urban innovation; (2) the policy promotes human capital expansion and strengthens government financial support, thereby significantly fostering urban innovation; (3) the impact of the policy varies across cities with different geographic locations, population densities and levels of marketization. Therefore, the findings of this paper provide empirical evidence that higher education expansion policy stimulates urban innovation. It also offers useful insights for China's transition from "Made in China" to "Created in China" during its high-quality development phase.
[1] | L. Morales, D. Rajmil, Investing in virtue and frowning at vice? Lessons from the global economic and financial crisis, Quant. Financ. Econ., 7 (2023), 1–18. https://doi.org/10.3934/QFE.2023001 doi: 10.3934/QFE.2023001 |
[2] | Y. Wen, Y. Xu, Statistical monitoring of economic growth momentum transformation: empirical study of Chinese provinces, AIMS Math., 8 (2023), 24825–224847. https://doi.org/10.3934/math.20231266 doi: 10.3934/math.20231266 |
[3] | P. Jin, S. K. Mangla, M. Song, The power of innovation diffusion: How patent transfer affects urban innovation quality, J. Bus. Res., 145 (2022), 414–425. https://doi.org/10.1016/j.jbusres.2022.03.025 doi: 10.1016/j.jbusres.2022.03.025 |
[4] | X. Li, J. Tang, J. Huang, Place-based policy upgrading, business environment, and urban innovation: Evidence from high-tech zones in China, Int. Rev. Financ. Anal., 86 (2023), 102545. https://doi.org/10.1016/j.irfa.2023.102545 doi: 10.1016/j.irfa.2023.102545 |
[5] | T. Yang, M. Han, Y. Zhong, J. Zhong, Q. Zhang, Relationship between financial development and intelligent transformation of manufacturing: evidence from 69 countries, Econ. Change Restruct., 56 (2023), 1–38. https://doi.org/10.1007/s10644-023-09544-2 doi: 10.1007/s10644-023-09544-2 |
[6] | J. M. Le Page, Structural rate of unemployment, hysteresis, human capital, and macroeconomic data, Natl. Account. Rev., 4 (2022), 135–146. https://doi.org/10.3934/NAR.2022008 doi: 10.3934/NAR.2022008 |
[7] | Li Z, Huang Z, Su Y. New media environment, environmental regulation and corporate green technology innovation: evidence from China, Energy Econo., 119 (2023), 106545. https://doi.org/10.1016/j.eneco.2023.106545 doi: 10.1016/j.eneco.2023.106545 |
[8] | R. Wang, W. Cai, H. Ren, X. Ma, Heterogeneous effects of the talent competition on urban innovation in China: evidence from prefecture-level cities, Land, 12 (2023), 719. https://doi.org/10.3390/land12030719 doi: 10.3390/land12030719 |
[9] | Z. Li, H. Chen, B. Mo, Can digital finance promote urban innovation? Evidence from China, Borsa Istanb. Rev., 23 (2023), 285–296. https://doi.org/10.1016/j.bir.2022.10.006 doi: 10.1016/j.bir.2022.10.006 |
[10] | J. Wang, S. Cai, The construction of high-speed railway and urban innovation capacity: based on the perspective of knowledge Spillover, China Econ. Rev., 63 (2020), 101539. https://doi.org/10.1016/j.chieco.2020.101539 doi: 10.1016/j.chieco.2020.101539 |
[11] | C. Tang, M. Guan, J. Dou, Understanding the impact of High Speed Railway on urban innovation performance from the perspective of agglomeration externalities and network externalities, Technol. Soc., 67 (2021), 101760. https://doi.org/10.1016/j.techsoc.2021.101760 doi: 10.1016/j.techsoc.2021.101760 |
[12] | W. Feng, H. Yuan, The impact of medical infrastructure on regional innovation: An empirical analysis of China's prefecture-level cities, Technol. Forecast. Soc. Change, 186 (2023), 122125. https://doi.org/10.1016/j.techfore.2022.122125 doi: 10.1016/j.techfore.2022.122125 |
[13] | M. Nagenborg, Urban robotics and responsible urban innovation, Ethics Inf. Technol., 22 (2020), 345–355. https://doi.org/10.1007/s10676-018-9446-8 doi: 10.1007/s10676-018-9446-8 |
[14] | E. Ezzahid, B. Ferrahi, O. El Hamdani, Determinants of urban concentration in African countries, Natl. Account. Rev., 4 (2022), 191–203. https://doi.org/10.3934/NAR.2022011 doi: 10.3934/NAR.2022011 |
[15] | Y. Liu, Y. Fan, Y. Wang, J. Huang, H. Xun, City innovation ability and internet infrastructure development: Evidence from the "Broadband China" policy, Bull. Econ. Res., 2023. https://doi.org/10.1111/boer.12421 doi: 10.1111/boer.12421 |
[16] | J. Wang, K. Deng, Impact and mechanism analysis of smart city policy on urban innovation: Evidence from China, Econ. Anal. Policy, 73 (2022), 574–587. https://doi.org/10.1016/j.eap.2021.12.006 doi: 10.1016/j.eap.2021.12.006 |
[17] | C. Li, G. Long, S. Li, Research on measurement and disequilibrium of manufacturing digital transformation: Based on the text mining data of A-share listed companies, Data Sci. Financ. Econ., 3 (2023), 30–54. https://doi.org/10.3934/DSFE.2023003 doi: 10.3934/DSFE.2023003 |
[18] | L. Li, M. Li, S. Ma, Y. Zhang, C. Pan, Does the construction of innovative cities promote urban green innovation, J. Environ. Manage., 318 (2022), 115605. https://doi.org/10.1016/j.jenvman.2022.115605 doi: 10.1016/j.jenvman.2022.115605 |
[19] | G. Aisaiti, J. Xie, T. Zhang, National Innovation Demonstration Zone policy and city innovation capability—a quasi-natural experimental analysis, Ind. Manage. Data Syst., 122 (2022), 1246–1267. https://doi.org/10.1108/IMDS-12-2021-0772 doi: 10.1108/IMDS-12-2021-0772 |
[20] | Z. Huang, H. Dong, S. Jia, Equilibrium pricing for carbon emission in response to the target of carbon emission peaking, Energy Econ., 112 (2022), 106160. https://doi.org/10.1016/j.eneco.2022.106160 doi: 10.1016/j.eneco.2022.106160 |
[21] | T. Li, X. Li, G. Liao, Business cycles and energy intensity. evidence from emerging economies, Borsa Istanb. Rev., 22 (2022), 560–570. https://doi.org/10.1016/j.bir.2021.07.005 doi: 10.1016/j.bir.2021.07.005 |
[22] | C. Zou, Y. Huang, S. Wu, S. Hu, Does "low-carbon city" accelerate urban innovation? Evidence from China, Sustain. Cities Soc., 83 (2022), 103954. https://doi.org/10.1016/j.scs.2022.103954 doi: 10.1016/j.scs.2022.103954 |
[23] | Y. Che, L. Zhang, Human capital, technology adoption and firm performance: Impacts of China's higher education expansion in the late 1990s, Econ. J., 128 (2018), 2282–2320. https://doi.org/10.1111/ecoj.12524 doi: 10.1111/ecoj.12524 |
[24] | C. Wang, X. Liu, Z. Yan, Y. Zhao, Higher education expansion and crime: New evidence from China, China Econ. Rev., 74 (2022), 101812. https://doi.org/10.1016/j.chieco.2022.101812 doi: 10.1016/j.chieco.2022.101812 |
[25] | H. Li, Y. Ma, L. Meng, X. Qiao, Skill complementarities and returns to higher education: evidence from college enrollment expansion in China, China Econ. Rev., 46 (2017), 10–26. https://doi.org/10.1016/j.chieco.2017.08.004 doi: 10.1016/j.chieco.2017.08.004 |
[26] | F. Dai, F. Cai, Y. Zhu, Returns to higher education in China—evidence from the 1999 higher education expansion using a fuzzy regression discontinuity, Appl. Econ. Lett., 29 (2022), 489–494. https://doi.org/10.1080/13504851.2020.1871465 doi: 10.1080/13504851.2020.1871465 |
[27] | Y. Wang, Who benefits more from the college expansion policy? Evidence from China, Res. Soc. Strat. Mobil., 71 (2021), 100566. https://doi.org/10.1016/j.rssm.2020.100566 doi: 10.1016/j.rssm.2020.100566 |
[28] | Y. Dong, N. Yu, T. Hong, J. Yue, City administrative level and tertiary educational opportunities: evidence from China's higher education expansion policy, SAGE Open, 12 (2022), 21582440221089931. https://doi.org/10.1177/21582440221089931 doi: 10.1177/21582440221089931 |
[29] | Y. Feng, X. Tan, R. Wang, The value of higher education to entrepreneurial performance: Evidence from higher education expansion in China, China Econ. Rev., 73 (2022), 101789. https://doi.org/10.1016/j.chieco.2022.101789 doi: 10.1016/j.chieco.2022.101789 |
[30] | C. Bollinger, X. Ding, S. Lugauer, The expansion of higher education and household saving in China, China Econ. Rev., 71 (2022), 101736. https://doi.org/10.1016/j.chieco.2021.101736 doi: 10.1016/j.chieco.2021.101736 |
[31] | D. Kong, B. Zhang, J. Zhang, Higher education and corporate innovation, J. Corp. Financ., 72 (2022), 102165. https://doi.org/10.1016/j.jcorpfin.2022.102165 doi: 10.1016/j.jcorpfin.2022.102165 |
[32] | W. Yue, Human capital and firm innovation: evidence from China's higher education expansion in the late 1990s, Emerg. Mark. Financ. Tr., 2023, 1–19. https://doi.org/10.1080/1540496X.2023.2242568 doi: 10.1080/1540496X.2023.2242568 |
[33] | M. F. Leung, A. Jawaid, S. W. Ip, C. H. Kwok, S. Yan, A portfolio recommendation system based on machine learning and big data analytics, Data Sci. Financ. Econ., 3 (2023), 152–165. https://doi.org/10.3934/DSFE.2023009 doi: 10.3934/DSFE.2023009 |
[34] | Z. Li, B. Mo, H. Nie, Time and frequency dynamic connectedness between cryptocurrencies and financial assets in China, Inte. Rev. Econ. Financ., 86 (2023), 46–57. https://doi.org/10.1016/j.iref.2023.01.015 doi: 10.1016/j.iref.2023.01.015 |
[35] | S. Orazi, L. B. Martinez, H. P. Vigier, Determinants and evolution of financial inclusion in Latin America: a demand side analysis, Quant. Financ. Econ., 7 (2023), 187–206. https://doi.org/10.3934/QFE.2023010 doi: 10.3934/QFE.2023010 |
[36] | C. Bandera, E. Thomas, The role of innovation ecosystems and social capital in startup survival, IEEE Trans. Eng. Manage., 66 (2018), 542–551. https://doi.org/10.1109/TEM.2018.2859162 doi: 10.1109/TEM.2018.2859162 |
[37] | X. Zhao, Y. Xu, L. Vasa, U. Shahzad, Entrepreneurial ecosystem and urban innovation: contextual findings in the lens of sustainable development from China, Technol. Forecast. Soc. Change, 191 (2023), 122526. https://doi.org/10.1016/j.techfore.2023.122526 doi: 10.1016/j.techfore.2023.122526 |
[38] | Y. Zhong, F. Xu, L. Zhang, Influence of artificial intelligence applications on total factor productivity of enterprises—evidence from textual analysis of annual reports of Chinese-listed companies, Appl. Econ., 2023, 1–19. https://doi.org/10.1080/00036846.2023.2244246 doi: 10.1080/00036846.2023.2244246 |
[39] | Y. Chen, Y. Wang, D. Hu, Z. Zhou, Government R & D subsidies, information asymmetry, and the role of foreign investors: evidence from a quasi-natural experiment on the shanghai-Hong Kong stock connect, Technol. Forecast. Soc. Change, 158 (2020), 120162. https://doi.org/10.1016/j.techfore.2020.120162 doi: 10.1016/j.techfore.2020.120162 |
[40] | T. Kong, R. Sun, G. Sun, Y. Song, Effects of digital finance on green innovation considering information asymmetry: an empirical study based on Chinese listed firms, Emerg. Mark. Financ. Trade, 58 (2022), 4399–4411. https://doi.org/10.1080/1540496X.2022.2083953 doi: 10.1080/1540496X.2022.2083953 |
[41] | K. Albitar, K. Hussainey, Sustainability, environmental responsibility and innovation, Green Financ., 5 (2023), 85–88. https://doi.org/10.3934/GF.2023004 doi: 10.3934/GF.2023004 |
[42] | X. Jiang, W. Fu, G. Li, Can the improvement of living environment stimulate urban innovation?—analysis of high-quality innovative talents and foreign direct investment spillover effect mechanism, J. Clean. Prod., 255 (2020), 120212. https://doi.org/10.1016/j.jclepro.2020.120212 doi: 10.1016/j.jclepro.2020.120212 |
[43] | X. Lao, H. Gu, H. Yu, F. Xiao, Exploring the spatially-varying effects of human capital on urban innovation in China, Appl. Spat. Anal. Policy, 14 (2021), 827–848. https://doi.org/10.1007/s12061-021-09380-9 doi: 10.1007/s12061-021-09380-9 |
[44] | J. Zhong, Y. Zhong, M. Han, T. Yang, Q. Zhang, The impact of AI on carbon emissions: evidence from 66 countries, Appl. Econ., 2023, 1–15. https://doi.org/10.1080/00036846.2023.2203461 doi: 10.1080/00036846.2023.2203461 |
[45] | M. Huang, C. Xing, X. Cui, Does college location affect the location choice of new college graduates in China, China World Econ., 30 (2022), 135–160. https://doi.org/10.1111/cwe.12421 doi: 10.1111/cwe.12421 |
[46] | D. Acemoglu, P. Restrepo, Robots and jobs: evidence from US labor markets, J. Polit. Econ., 128 (2020), 2188–2244. |
[47] | S. Yang, Z. Li, J. Li, Fiscal decentralization, preference for government innovation and city innovation: evidence from China, Chin. Manag. Stud., 14 (2020), 391–409. https://doi.org/10.1108/CMS-12-2018-0778 doi: 10.1108/CMS-12-2018-0778 |
[48] | J. Guinot, Z. Barghouti, I. Beltrán-Martín, R. Chiva, Corporate social responsibility toward employees and green innovation: exploring the link in the tourism sector, Green Financ., 5 (2023), 298–320. https://doi.org/10.3934/GF.2023012 doi: 10.3934/GF.2023012 |
[49] | Y. Gao, S. Jin, Corporate nature, financial technology, and corporate innovation in China, Sustainability, 14 (2022), 7162. https://doi.org/10.3390/su14127162 doi: 10.3390/su14127162 |
[50] | V. Chernozhukov, D. Chetverikov, M. Demirer, E. Duflo, C. Hansen, W. Newey, et al., Double/debiased machine learning for treatment and structural parameters, Econ. J., 21 (2018), C1–C68. https://doi.org/10.1111/ectj.12097 doi: 10.1111/ectj.12097 |
[51] | Z. Liao, M. Hu, L. Gao, B. Cheng, C. Tao, R. Akhtar, Is air pollution detrimental to regional innovation? An empirical heterogeneity test based on Chinese cities, Front. Public Health, 10 (2022), 981306. https://doi.org/10.3389/fpubh.2022.981306 doi: 10.3389/fpubh.2022.981306 |
[52] | J. Cheng, J. Zhao, D. Zhu, X. Jiang, H. Zhang, Y. Zhang, Land marketization and urban innovation capability: Evidence from China, Habitat Int., 122 (2022), 102540. https://doi.org/10.1016/j.habitatint.2022.102540 doi: 10.1016/j.habitatint.2022.102540 |
[53] | L. He, E. Yuan, K. Yang, D. Tao, Does technology innovation reduce haze pollution? An empirical study based on urban innovation index in China, Environ. Sci. Pollut. Res., 29 (2022), 24063–24076. https://doi.org/10.1007/s11356-021-17448-9 doi: 10.1007/s11356-021-17448-9 |
[54] | Y. Tian, W. Song, M. Liu, Assessment of how environmental policy affects urban innovation: evidence from China's low-carbon pilot cities program, Econ. Anal. Policy, 71 (2021), 41–56. https://doi.org/10.1016/j.eap.2021.04.002 doi: 10.1016/j.eap.2021.04.002 |
[55] | Z. Li, J. Zhong, Impact of economic policy uncertainty shocks on China's financial conditions, Financ. Res. Lett., 35 (2020), 101303. https://doi.org/10.1016/j.frl.2019.101303 doi: 10.1016/j.frl.2019.101303 |
[56] | L. Grassini, Statistical features and economic impact of Covid-19, Natl. Account. Rev., 5 (2023), 38–40. https://doi.org/10.3934/NAR.2023003 doi: 10.3934/NAR.2023003 |
[57] | R. Nymoen, Economic Covid-19 effects analysed by macro econometric models—the case of Norway, Natl. Account. Rev., 5 (2023), 1–22. https://doi.org/10.3934/NAR.2023001 doi: 10.3934/NAR.2023001 |
[58] | Y. Liu, Y. Xie, K. Zhong, Impact of digital economy on urban sustainable development: Evidence from Chinese cities, Sustain. Dev., 2023. https://doi.org/10.1002/sd.2656 doi: 10.1002/sd.2656 |
[59] | N. Nunn, N. Qian, US food aid and civil conflict, Amer. Econo. Rev., 104 (2014), 1630–1666. https://doi.org/10.1257/aer.104.6.1630 doi: 10.1257/aer.104.6.1630 |
[60] | L. Liu, Y. Meng, D. Wu, Q. Ran, J. Cao, Z. Liu, Impact of haze pollution and human capital on economic resilience: evidence from prefecture-level cities in China, Environ. Dev. Sustain., 25 (2023), 13429–13449. https://doi.org/10.1007/s10668-022-02625-8 doi: 10.1007/s10668-022-02625-8 |
[61] | X. Sun, H. Li, V. Ghosal, Firm-level human capital and innovation: evidence from China, China Econo. Rev., 59 (2020), 101388. https://doi.org/10.1016/j.chieco.2019.101388 doi: 10.1016/j.chieco.2019.101388 |
[62] | X. Shi, Y. Chen, M. Xia, Y. Zhang, Effects of the talent war on urban innovation in China: a difference-in-differences analysis, Land, 11 (2022), 1485. https://doi.org/10.3390/land11091485 doi: 10.3390/land11091485 |
[63] | L. Wei, B. Lin, Z. Zheng, W. Wu, Y. Zhou, Does fiscal expenditure promote green technological innovation in China? Evidence from Chinese cities, Environ. Impact Asses. Rev., 98 (2023), 106945. https://doi.org/10.1016/j.eiar.2022.106945 doi: 10.1016/j.eiar.2022.106945 |
[64] | Q. Tan, C. Li, Z. Qin, S. Yu, Y. Pan, M. H. Andrianarimanana, Impact of fiscal education expenditure on innovation of local listed enterprises: evidence from China, Financ. Res. Lett., 57 (2023), 104192. https://doi.org/10.1016/j.frl.2023.104192 doi: 10.1016/j.frl.2023.104192 |
[65] | Z. Tu, T. Hu, R. Shen, Evaluating public participation impact on environmental protection and ecological efficiency in China: evidence from PITI disclosure, China Econ. Rev., 55 (2019), 111–123. https://doi.org/10.1016/j.chieco.2019.03.010 doi: 10.1016/j.chieco.2019.03.010 |
[66] | Z. Li, G. Liao, K. Albitar, Does corporate environmental responsibility engagement affect firm value? The mediating role of corporate innovation, Bus. Strategy Environ., 29 (2020), 1045–1055. https://doi.org/10.1016/j.chieco.2019.03.010 doi: 10.1016/j.chieco.2019.03.010 |
[67] | S. Cai, H. Wang, X. Zhou, Do city size and population density influence regional innovation output evidence from China, Wirel. Commun. Mob. Com., 2021 (2021), 3582053. https://doi.org/10.1155/2021/3582053 doi: 10.1155/2021/3582053 |