Research on the Impact of the Specialized, Refined, Unique, and Innovative “Little Giant” Policy on the Small and Medium Enterprises’ Innovation
DOI:
https://doi.org/10.54097/8463cd79Keywords:
Small and Medium Enterprises’ Innovation, Staggered Difference-in-difference, The Specialized, Refined, Unique, and Innovative “Little Giant” PolicyAbstract
Using data from Chinese A-share listed companies and companies listed on the New Third Board from 2018 to 2022, this study evaluates the causal effect of the "Little Giant" policy on innovation in small and medium-sized enterprises through a staggered difference-in-difference model. Research has found that the "little giant" policy of specialization, refinement, and innovation has significantly promoted innovation in small and medium-sized enterprises. The robustness test found that the policy significantly promoted the level of innovation input and innovation output, with the innovation output level specifically manifested as a significant increase in the number of invention patents. Mechanism analysis confirms that the "Little Giant" policy of specialization, refinement, and innovation has significantly promoted enterprise innovation through three mechanisms: alleviating financing constraints, providing government subsidies, and promoting market competition. Heterogeneity analysis found that enterprises in key areas of policy implementation and those related to "bottleneck" technology are significantly more affected by the causal effect of the policy on promoting innovation.
Downloads
References
Wu Chaopeng, Yan Zehao. Government Fund Guidance and Enterprise Core Technology Breakthrough: Mechanisms and Effects [J]. Economic Research, 2023,58 (06): 137-154.
CRISCUOLO C, MARTIN R, Overman H G, etc Some Causal Effects of an Industrial Policy [J/OL] American Economic Review, 2019, 109 (1): 48-85.
Li Wenjing, Zheng Manni Substantive innovation or strategic innovation-- The impact of macro industrial policies on micro enterprise innovation [J] Economic Research, 2016, 51 (4): 60-73.
Li Linlin, Wang Chong Tax Burden, Innovation Capability, and Enterprise Upgrading: Empirical Evidence from Companies Listed on the New Third Board Economic Research, 2017, 52 (11): 119-134.
Liu Shiyuan, Lin Zhifan, Leng Zhipeng Has tax incentives improved the innovation level of enterprises--Testing based on the theory of enterprise lifecycle [J] Economic Research, 2020, 55 (6): 105-121.
Zheng Shilin, Zhang Guoguo An Analysis of the Path to Enhancing Enterprise Innovation through Manufacturing Development Strategy: Evidence from Ten Key Areas [J] Economic Research, 2022, 57 (9): 155-173.
HOWELL S T. Financing Innovation: Evidence from R&D Grants [J/OL] American Economic Review, 2017, 107 (4): 1136-1164.
DAI X, WANG F. Does the high and new technology enterprise program promote innovative performance? Evidence from Chinese firms [J/OL] China Economic Review, 2019, 57:101330.
LIU C, LI L. Place based technological industrial policy and innovation: Government responses to the information revolution in China [J/OL] China Economic Review, 2021, 66: 101600.
MAO J, TANG S, XIAO Z, etc Industrial policy intensity, technological change, and productivity growth: Evidence from China [J/OL] Research Policy, 2021, 50 (7): 104287.
BLOOM N, VAN REENEN J, WILLIAMS H. A Toolkit of Policies to Promote Innovation [J/OL] Journal of Economic Perspectives, 2019, 33 (3): 163-184.
GAO Y, HU Y, LIU X, etc Can public R&D subsidiary facilitate firm 'exploratory innovation? The heterogeneous effects between central and local subsidiary programs [J/OL] Research Policy, 2021, 50 (4): 104221.
AGHION P, CAI J, DEWATRIPONT M, etc Industrial Policy and Competition [J/OL] American Economic Journal: Macroeconomics, 2015, 7 (4): 1-32.
Goodman BACON A. Difference in differences with variation in treatment timing [J/OL] Journal of Economics, 2021, 225 (2): 254-277.
Liu Chong, Sha Xuekang, Zhang Yan Interlaced Double Difference: Dealing with Effect Heterogeneity and Selection of Estimation Methods [J/OL] Research on Quantitative Economics, Technology and Economics, 2022, 39 (9): 177-204.
BAKER A C, LARCKER D F, WANG C C. Y. How much should we trust staged differences in differences estimates? [J/OL] Journal of Financial Economics, 2022, 144 (2): 370-395.
SUN L, ABRAHAM S. Estimating dynamic treatment effects in event studies with heterogeneous treatment effects [J/OL] Journal of Economics, 2021, 225 (2): 175-199.
CALLAWAY B, SANT'ANNA P H C. Differences in Differences with multiple time periods [J/OL] Journal of Economics, 2021, 225 (2): 200-230.
COHN J B, LIU Z, WARDLAW M I. Count (and count like) data in finance [J/OL] Journal of Financial Economics, 2022, 146 (2): 529-551.
Bai Junhong, Zhang Yixuan, Bian Yuanchao Does innovation driven policies enhance urban entrepreneurial activity: empirical evidence from national innovative city pilot policies [J/OL] China Industrial Economy, 2022 (6): 61-78.
Gu Xiaming, Chen Yongmin, Pan Shiyuan Economic Policy Uncertainty and Innovation: An Empirical Analysis Based on Listed Companies in China [J] Economic Research, 2018, 53 (2): 109-123.
Chen Aizhen, Zhang Pengfei Merger and acquisition models and corporate innovation [J/OL] China Industrial Economy, 2019 (12): 115-133.
Downloads
Published
Issue
Section
License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.