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author:

Chen, Yu (Chen, Yu.) [1] | Wang, Yuandi (Wang, Yuandi.) [2] | Hu, Die (Hu, Die.) [3] | Zhou, Zhao (Zhou, Zhao.) [4]

Indexed by:

EI

Abstract:

Government subsidies for corporate research and development (R&D) are thought to be necessary, in theory and in practice. However, both policymakers and scholars question the efficiency of such subsidies, because numerous innovative enterprises receive funding but fail. Some researchers suggest that the main cause of perceived inefficiency is the information asymmetry between the government and enterprises. In this study, we focus on signal theory, proposing that foreign investors as a signal can help the government to reduce the information asymmetry when selecting enterprises to sponsor. China's Shanghai-Hong Kong Stock Connect provides an appropriate setting for our quasi-natural experiment. Our empirical results reveal that the enterprises targeted by the Shanghai-Hong Kong Stock Connect can receive more R&D subsidies from the government. And the positive net impacts are more apparent in smaller-sized enterprises, and enterprises in high-tech industries and those with a high proportion of intangible assets. The study further shows that enterprises sponsored by the government are more likely to use the subsidy efficiently and improve their performance. © 2020 Elsevier Inc.

Keyword:

Signal theory Technological forecasting

Community:

  • [ 1 ] [Chen, Yu]Business school, Sichuan University, Chengdu; 610064, China
  • [ 2 ] [Wang, Yuandi]Business school, Sichuan University, Chengdu; 610064, China
  • [ 3 ] [Hu, Die]School of Economics and Management, Fuzhou University, Fuzhou; 350108, China
  • [ 4 ] [Zhou, Zhao]College of Business, Shanghai University of Finance and Economics, Shanghai; 200433, China

Reprint 's Address:

  • [hu, die]school of economics and management, fuzhou university, fuzhou; 350108, china

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Source :

Technological Forecasting and Social Change

ISSN: 0040-1625

Year: 2020

Volume: 158

8 . 5 9 3

JCR@2020

1 2 . 9 0 0

JCR@2023

ESI HC Threshold:91

JCR Journal Grade:1

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 36

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 1

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