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【Abstract】Based on the inter-provincial panel data from 2000 to 2014， the paper analyzes the influence of oil price and environmental regulation on the technological innovation of enterprises. The results show that the induced effect of oil price factor is confirmed in our country， and the influence of environmental regulation on the promotion of technological innovation has been improved. Finally， according to the results of empirical tests， give the appropriate regional feasibility advice and constructive suggestions.
【Key words】environmental regulation； induced innovation effect； “Porter hypothesis”
1. Introduction Literature review
In the context of the slowdown in global GDP growth and the new economic background， China has implemented government， such as price and environment， and domestic enterprises are still in the macroeconomic environment in which oil prices are rising and environmental regulation is strengthened. In order to deeply study the influence of economic environment on technological innovation， This paper introduces the theory of induced technological innovation and the theory of“the Porter hypothesis” about the elements and the environment.
In recent years， domestic and foreign scholars based on different regions， different industries set off the theory of induced technology innovation and“wave hypothesis” research wave. Hayley and Ruttan （1970）， starting from the domestic and Japanese factors of production factors， reveal that under the different constraints of resources， the agricultural market factor prices rise to induce the relevant enterprises to carry out technological innovation and development， confirming the induced innovation theory. Shen Neng （2012） built the enterprise governance environment technology innovation and using the panel threshold model to prove that they are not a simple linear relationship but there is a“U” type relationship.
In summary， although the induced innovation theory and the“Porter hypothesis” are confirmed in different economies at home and abroad， but the cross-effects of the two literature is still relatively small， to fill this gap， this paper based on changes in oil prices and Environmental regulation on the role of technological innovation in enterprises to conduct empirical analysis and research.
2. The empirical results and analysis
In order to further study the relationship between environmental regulation and enterprise technological innovation from the perspective of institutional environment， with reference to the super-logarithmic model test of Nghiep application， the square of environmental regulation is added to the model test. In addition， for the weakening of the heteroscedry interference， in addition to the value of the variable other variables are taken logarithm. In order to avoid the stability of the model， the clustering Standard error adjustment of the panel data method for empirical testing. At the same time， in order to compare with the clustering robust standard error method， we also give a comprehensive treatment method to correct the heteroskedasticity and autocorrelation and the regression results of the correlation problem of the group. The generalized least squares method， in addition， the model Hausman test p value of 0.004， accept the fixed effect model. In addition， this paper refers to the system GMM test model proposed by Blundell and Bond to reduce the errors caused by the missing variables. The regression results of the system GMM show that the regression characteristics of the core explanatory variables are not changed and the model is robust.
Table 1 shows the results of the overall regression. Models （1） - （3） are regression methods that use clustering criteria to incrementally add variables. The model （4） uses the generalized least squares method， and the model （5） is the fixed effect model. Since the fixed effect model is more efficient， we mainly describe the model （5）. In the model （5）， the regression parameter of the variable lnEP is 0.198， and through the significance test， the oil price increase leads to the verification of the technological innovation activities.
In the model （3） to the model （5）， the first-order regression parameter of the environmental regulation and the quadratic regression parameter are opposite. Comparing the model （2） and the model （3）， the effect of oil price changes on the R
【Key words】environmental regulation； induced innovation effect； “Porter hypothesis”
1. Introduction Literature review
In the context of the slowdown in global GDP growth and the new economic background， China has implemented government， such as price and environment， and domestic enterprises are still in the macroeconomic environment in which oil prices are rising and environmental regulation is strengthened. In order to deeply study the influence of economic environment on technological innovation， This paper introduces the theory of induced technological innovation and the theory of“the Porter hypothesis” about the elements and the environment.
In recent years， domestic and foreign scholars based on different regions， different industries set off the theory of induced technology innovation and“wave hypothesis” research wave. Hayley and Ruttan （1970）， starting from the domestic and Japanese factors of production factors， reveal that under the different constraints of resources， the agricultural market factor prices rise to induce the relevant enterprises to carry out technological innovation and development， confirming the induced innovation theory. Shen Neng （2012） built the enterprise governance environment technology innovation and using the panel threshold model to prove that they are not a simple linear relationship but there is a“U” type relationship.
In summary， although the induced innovation theory and the“Porter hypothesis” are confirmed in different economies at home and abroad， but the cross-effects of the two literature is still relatively small， to fill this gap， this paper based on changes in oil prices and Environmental regulation on the role of technological innovation in enterprises to conduct empirical analysis and research.
2. The empirical results and analysis
In order to further study the relationship between environmental regulation and enterprise technological innovation from the perspective of institutional environment， with reference to the super-logarithmic model test of Nghiep application， the square of environmental regulation is added to the model test. In addition， for the weakening of the heteroscedry interference， in addition to the value of the variable other variables are taken logarithm. In order to avoid the stability of the model， the clustering Standard error adjustment of the panel data method for empirical testing. At the same time， in order to compare with the clustering robust standard error method， we also give a comprehensive treatment method to correct the heteroskedasticity and autocorrelation and the regression results of the correlation problem of the group. The generalized least squares method， in addition， the model Hausman test p value of 0.004， accept the fixed effect model. In addition， this paper refers to the system GMM test model proposed by Blundell and Bond to reduce the errors caused by the missing variables. The regression results of the system GMM show that the regression characteristics of the core explanatory variables are not changed and the model is robust.
Table 1 shows the results of the overall regression. Models （1） - （3） are regression methods that use clustering criteria to incrementally add variables. The model （4） uses the generalized least squares method， and the model （5） is the fixed effect model. Since the fixed effect model is more efficient， we mainly describe the model （5）. In the model （5）， the regression parameter of the variable lnEP is 0.198， and through the significance test， the oil price increase leads to the verification of the technological innovation activities.
In the model （3） to the model （5）， the first-order regression parameter of the environmental regulation and the quadratic regression parameter are opposite. Comparing the model （2） and the model （3）， the effect of oil price changes on the R