Abstract
The existing research on testing Porter’s hypothesis has not considered the selective bias in the sample when establishing a model. However, the selective bias is likely to cause instability of estimation results and reduce the reference value of conclusions. This article, based on individual enterprises in the China Industrial Enterprise Database, aims to verify the selective bias existing in previous research. Then, using the generalized propensity score matching method, a frontier method in the field of causal inference, we re-examined the causal relationship between environmental regulation and two types of technological innovation, weakened endogenous and reverse causal effects, and obtained a more complete and accurate dynamic impact of environmental regulation on the level of technological innovation for enterprises. The main conclusions of this paper are as follows: (1) The influence of environmental regulation on the level of process innovation has two dimensions: time and intensity, and the causal relationship between these dimensions changes from an N shape to an inversed-U shape over time. (2) The influence of environmental regulation on product innovation levels only includes the intensity dimension, and the two produce a U shape. (3) Process innovation and product innovation, to a certain extent, are reflected in the intriguing situation that they cannot gain and lose at the same time. (4) Light industries have a lower tolerance of environmental regulation than heavy industries, and they are more likely to be stimulated by environmental regulation. The conclusions of this paper can provide valuable advice to governments in relation to the formulation of environmental policies and laws.
Highlights
General Secretary Xi Jinping pointed out at the 19th National Congress of the Communist Party of China that the Chinese economy has shifted from a high-speed development stage to a high-quality development stage, with the ultimate goal of achieving sustainable economic development
This paper expects to solve the selective bias in the previous research by using the generalized propensity score matching (GPS) method, weakening the endogenous and reverse causal effects, and obtaining a more accurate and stable nonlinear causal relationship between the environmental regulation and technological innovation level, which can provide a feasible path for a country’s sustainable development
The relationship between the two is U-shaped with a threshold of 0.3, which is the same as the first inflection point value of environmental regulation affecting process innovation. This shows that if we want to achieve the same growth of product innovation and process innovation, it is necessary to set the environmental regulation intensity to be more than 0.35 when the first phase is delayed, but this growth cannot be achieved when the lag is more than 1 period
Summary
General Secretary Xi Jinping pointed out at the 19th National Congress of the Communist Party of China that the Chinese economy has shifted from a high-speed development stage to a high-quality development stage, with the ultimate goal of achieving sustainable economic development. This paper expects to solve the selective bias in the previous research by using the generalized propensity score matching (GPS) method, weakening the endogenous and reverse causal effects, and obtaining a more accurate and stable nonlinear causal relationship between the environmental regulation and technological innovation level, which can provide a feasible path for a country’s sustainable development. This paper selects the GPS method to describe the nonlinear relationship between environmental regulation and technological innovation This method overcomes the selective bias of the sample, and applies to the continuous treatment variable.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
