Title: Measurement and determinants of innovation efficiency and its impact on asset prices – empirical evidence from listed companies in China
Authors: Kailin Zeng; Fangyan Li; Ebenezer Fiifi Emire Atta Mills
Addresses: School of Economics and Management, Jiangxi University of Science and Technology, Ganzhou, China; Ganzhou Academy of Financial Research (GAFR), Ganzhou, China ' School of Economics and Management, Jiangxi University of Science and Technology, Ganzhou, China ' School of Mathematical Sciences, Wenzhou-Kean University, Wenzhou, China; Ganzhou Academy of Financial Research (GAFR), Ganzhou, China
Abstract: This study adopts a dynamic slack-based DEA framework to estimate the innovation efficiency of the exchange-listed companies that are at the centre of China's innovation network. On average, these companies have low efficiency scores, signalling an over-investment in fixed assets, R&D, and excessive subsidies received from the government, along with a shortage of patent output. A Tobit-based analysis indicates that market share of sales, overvaluation, and profitability are positively linked to innovation efficiency, while excess analyst coverage can impede corporate innovation. Moreover, innovation efficiency is positively associated with stock returns from both cross-sectional regression tests and portfolio strategies.
Keywords: DEA model; dynamic SBM model; innovation efficiency; determinants; Tobit regression; Fama-MacBeth cross-sectional test; stock returns; portfolio strategies; China.
International Journal of Applied Decision Sciences, 2023 Vol.16 No.2, pp.210 - 236
Received: 02 Oct 2021
Accepted: 21 Nov 2021
Published online: 10 Mar 2023 *