Study on the nonlinear relationship between China's economic growth and leverage-Based on the panel data threshold regression analysis of manufacturing industry
DONG Xiangyu, ZHAO Shouguo
School of Economics and Management, Northwestern University, Xi'an 710127, China
Abstract:Based on the effective market theory (EMH), the traditional theory mainly studies the leverage ratio from the corporate financial perspective and neglects the decision mechanism of the production link. A new understanding of the decision mechanism of leverage ratio from the perspective of total factor productivity in determining production efficiency. Using the panel data of 29 manufacturing industries for 1995-2016 years, the dynamic panel threshold model is constructed with the lever rate as the threshold variable. The main conclusions are as follows:1) Economic growth-the threshold value of the leverage ratio is located at 114 of the nominal leverage ratio. On the left side of the threshold, leverage increases to promote economic growth. On the right side of the threshold, leverage growth is a drag on economic growth. Leverage has a "U" relationship with the overall performance of economic growth. 2) Economic growth-the lever rate threshold of leverage ratio is located at the bubble rate of 65, when the leverage ratio of the nominal leverage ratio is less than 65, leverage increase has a significant promoting effect on the economy. When the leverage ratio is more than 65, the leverage ratio has no obvious effect one economic growth, indicating that the economy may have entered the stagflation stage. 3) The double threshold effect of economic growth real leverage rate on bubble leverage is 43 and 49 respectively, and the real leverage rate has different effects on economic growth according to the different investment climate.
董翔宇, 赵守国. 中国经济增长与杠杆率的非线性关系研究——基于制造业面板数据门限回归分析[J]. 系统工程理论与实践, 2020, 40(2): 343-354.
DONG Xiangyu, ZHAO Shouguo. Study on the nonlinear relationship between China's economic growth and leverage-Based on the panel data threshold regression analysis of manufacturing industry. Systems Engineering - Theory & Practice, 2020, 40(2): 343-354.
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