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This paper considers a new estimating method for the bent line quantile regression model. By a simple linearization technique, the proposed method can simultaneously obtain the estimates of the regression coefficients and the change-point location. Moreover, it can be readily implemented by current software. Simulation studies demonstrate that the proposed method has good finite sample performance. Two empirical applications are also presented to illustrate the method.

In the past two decades, China has implemented various industrial policies involving all aspects of national economic development. At the same time, the number of patent applications in China has rapidly grown to become the largest in the world. Is industrial policy the one force of China’s patent explosion? We investigate the influence of industrial policy on firm innovation outputs using data from the text of Five-Year Plan and Chinese listed firms during 2008 to 2020. Based on the negative binomial regression model, we find that industrial policy has a positive effect on the number of patent applications. Further tests show the varying relationship between industrial policy and firm innovation with industry heterogeneity. We also find that industrial policy increases the number of patent applications by easing financing constraints and strengthening competition. Conclusion of this study provides corresponding theory and decision basis for the implementation of industrial policy in emerging markets.

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