Opening the Black Box: The Impacts of Environmental Regulations on Technological Innovation.

Environmental regulations (ERs) that can stimulate technological innovation (TI) are the key to enabling a win-win strategy that benefits both economic development and environmental protection. This study seeks to analyze the impacts of ERs on TI. Previous literature highlighted that the black box of TI can be decomposed into technology investment and technology transformation, but empirical studies on such a decomposition have largely been ignored. Moreover, a detailed discussion of the links between ERs and the decomposed components of TI has not been conducted in developing countries such as China. Our study attempts to address these research gaps by (i) decomposing TI using a novel data envelopment analysis (DEA) procedure and further analyzing the impacts of ERs on the decomposed components of TI and (ii) applying this novel methodology to Chinese context. Accordingly, this study is conducted in two stages. First, a novel application of the slack-based measure Network DEA model is developed to uncover the black box of TI using Chinese data in order to estimate the overall efficiency of technological innovation (TIE) and to decompose it into the efficiency of technology investment (TVE) and the efficiency of technology transformation (TTE). Second, a random effect Tobit model is applied to (i) investigate both the linear and nonlinear impacts of ERs on TIE in all sectors and (ii) examine whether the impacts of ERs on TVE and TTE in different subprocesses are heterogeneous or not. Our results have showed the benefits of decomposing TI: while technology transformation in China closely follows the trend of TI, the trend of technology investment is somewhat different. The estimation results further indicate that the impacts of ERs on TIE are nonlinear. Besides, ERs have heterogeneous impacts on the decomposed components of TI. The impacts of ERs on TVE are nonlinear, whereas the impacts of ERs on TTE are statistically insignificant.