关键词: 技术冲击, 消费冲击, DSGE模型, 黄河流域

Abstract: Carbon emission is an important link affecting the ecological protection and high-quality development of the Yellow River basin. In order to effectively protect the ecological environment of the Yellow River basin, achieve the goal of “carbon neutrality and carbon peak”, and actively promote the high-quality development of the Yellow River basin, it is urgent to further analyze the carbon emission behaviors in the provinces and regions in the Yellow River basin. This paper takes the emission reduction behaviors of enterprises and residents in the Yellow River basin as the main research object, and analyzes the main problems affecting the carbon emission behaviors of enterprises and residents under the impact of technology and residents. This is of guiding significance to the emission reduction in the Yellow River basin, and will further promote the high-quality development and strategic layout of carbon peak and carbon neutrality.
On the basis of RBC structure, this paper constructs a two-sector closed economic model including enterprises and residents, and the model follows the principle of utility maximization and profit maximization. Some parameters in the model are obtained by Bayesian estimation based on relevant data of the Yellow River basin. By using the robustness of Bayesian estimation results, the final multi-variable diagnosis results show that the numerical estimation results are robust. Other parameters are calibrated based on existing research andrelevant statistical data. In this paper, the DSGE model is used to simulate the impact of technological innovation by applying the unit positive technological impact. It mainly analyzes the response of enterprises' emission reduction behaviors, carbon emissions and macroeconomic conditions to productivity. All the results are given the percentage of stable state in 20 quarters. According to the numerical simulation results of the DSGE model, the simulation data of 9 provinces in the Yellow River basin are studied when different indicators are faced with technology shock and consumption shock. The impact intensity, stable state and response trend of 20 quarters are analyzed. The factors that affect the carbon emission reduction behaviors of enterprises and residents include internal factors and external environmental factors.
The research results show that: Firstly, technology shock has a positive impact on the enterprise emission reduction behaviors, carbon emissions and macroeconomic indicators. The expansion effect of economy under consumption shock is obvious, but different provinces have different sensitivity to consumption shock. Secondly, the fluctuation and cycle characteristics of the provinces in the Yellow River basin are different when facing the impact. On the one hand, different provinces and regions have different rates of return to steady state when facing shocks. Under the positive impact of the unit, Shandong, Shanxi and Henan provinces respond and basically stabilize in the 8th quarter. Sichuan and Shanxi provinces do not directly tend to steady state, but continue to fluctuate positively and negatively, with a fluctuation cycle of about 12 quarters. The rest of the provinces are in a state of shock and tend to be stable gradually. The fluctuation cycle of Gansu and Ningxia provinces is about 8 quarters, and that of Inner Mongolia Autonomous Region and Qinghai Province is about 4 quarters. On the other hand, the fluctuation amplitude of the response is also different. Taking carbon emissions as an example, in the face of technology shocks and consumption shocks, Inner Mongolia Autonomous Region, Gansu, Qinghai and Ningxia provinces experience the most drastic fluctuations. In the face of technology shock, the fluctuation range in the above provinces is far greater than that in other provinces, and the fluctuation range of consumption shock is relatively small. Third, the technological impact is more sustainable for Inner Mongolia Autonomous Region and Qinghai Province. The impact of increased technology on these two provinces is greater than that in other provinces, and the impact of consumption on the sustainability of Shanxi Province is better. Improving the technological influence in Shanxi Province is better than that in Inner Mongolia Autonomous Region and Qinghai Province. Fourth, the sustainability of technological shocks in the provinces in the Yellow River basin is lower than that of consumption shocks.

Key words: technology shock, consumer shock, DSGE model, Yellow River basin