E3S Web Conf.
Volume 235, 20212020 International Conference on New Energy Technology and Industrial Development (NETID 2020)
|Number of page(s)||5|
|Section||Research on New Energy Technology and Energy Consumption Development|
|Published online||03 February 2021|
Managerial Ability and R&D Investment: An Empirical Analysis Based on DEA-Tobit Model
Business School of Henan University, Kai Feng, China
a e-mail: email@example.com
DEA is a statistical procedure used to evaluate the relative efficiency of separable entities, termed “decision-making units” (DMUs), where each DMU converts certain inputs into outputs. The DEA efficiency methodology can provides an ordinal ranking of relative efficiency compared to the Pareto-efficient frontier, and the widely used efficiency measure require that weights be explicitly set, which is more advantageous than the conventional measures of efficiency. The Tobit model is a dependent variable limited model. Since the efficiency value measured by the DEA model is a truncated discrete distribution value between 0 and 1, the Tobit model can effectively avoid the problems of bias and inconsistency in parameter estimation. Based on this, this paper takes Chinese A-share listed companies from 2008 to 2018 as samples, adopts DEA-Tobit model to measure managerial ability, and studies the impact of managerial ability on firm innovation investment. It is found that managerial ability is negatively correlated with R&D investment. Further research shows that the negative relationship between managerial ability and firm innovation investment is more significant in non-state-owned companies. Transparency of accounting information can alleviate the restraining effect of managers ability on innovation input. This study not only enriches the research literature in the field of managerial ability and firm innovation input, but also has important enlightenment significance on how to improve managerial innovation willingness in reality and further promote firm innovation behavior.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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