Purpose
This paper aims to find the endogenous relationship between innovation input and corporate performance and deepen the study of innovation performance theory in industry and enterprise at the micro level.
Design/methodology/approach
This paper selects the firms listed on A shares in Shanghai and Shenzhen Stock Exchanges from 2009 to 2015 as samples. The authors cluster these samples according to the factors of production and classify the samples into three types: technology-intensive, capital-intensive and labor-intensive. After obtaining the samples and classifying them, the authors conduct a research on the endogenous relationship between the innovation input and the corporate performance through the simultaneous equations model and 3SLS estimation method. Meanwhile, they also make a study on the influence of executive incentive mechanism on the relationship between the innovation input and the corporate performance.
Findings
In technology-intensive industry, the increase of pre-innovation input will enhance the corporate performance in the current period, however, which will slow down the pace of innovation and lead to lower corporate performance in the future, and then increase innovation input again. In contrast, in capital-intensive industries, innovation input just improves corporate performance in the current period and the promotion of corporate performance will promote the intensity of innovation input in the future. With labor-intensive industries, innovation input also depends on early good returns, but innovation input has no significant impact on the corporate performance both at present and in the future. While in the executive incentive mechanism, salary incentive has a significant positive regulatory effect on the relationship between innovation input and corporate performance.
Originality/value
This paper presents a new research perspective on the relationship between innovation input and firm corporate performance, which is of great value to the listed company in balancing the R&D input with the company’s target performance and the design of executive incentive mechanism.
A Lagrange multiplier test for testing the parametric structure of a constant conditional correlation generalized autoregressive conditional heteroskedasticity (CCC-GARCH) model is proposed. The test is based on decomposing the CCC-GARCH model multiplicatively into two components, one of which represents the null model, whereas the other one describes the misspeci…cation. A simulation study shows that the test has good …nite sample properties. We compare the test with other tests for misspeci…cation of multivariate GARCH models. The test has high power against alternatives where the misspeci…cation is in the GARCH parameters and is superior to other tests. The test is not greatly affected by misspeci…cation in the conditional correlations and is therefore well suited for considering misspeci…cation of GARCH equations.JEL Codes: C32, C52, C58
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