Abstract：This paper uses the mixture innovation time-varying parameter vector autoregressive models with stochastic volatility model (MI-TVP-SV-VAR) to construct the China financial status index (MFCI) to measure China's financial situation. Based on the multifractal asymmetric detrended cross-correlation analysis (MF-ADCCA) algorithm, the MFCI is used to predict the development of the real economy. In the empirical study, the research sample selects the monthly data of China from 2000 to 2017. The empirical results show that the weights of various financial status variables have flexible time-varying, and the stock price, bond price and real estate price have greater weight in MFCI. During the sample period, MFCI is able to maintain a consistency trend with the development of the real economy (EC) and is ahead of changes in the real economy. The asymmetric correlation test based on MF-ADCCA algorithm shows that MFCI has a persistent cross-correlation with EC. The decline of MFCI will lead to the decline of EC, and the rise of MFCI will lead to the rise of EC. The cross-effect of MFCI on EC changes the asymmetric influence of the individual sequence itself, indicating that the impact of China's financial situation on the development of the real economy exists, and MFCI has a predictive effect on the development of the real economy. The intertemporal correlation test shows that the predictive effect of MFCI on the real economy is more effective within 6 months.
刘超, 马玉洁, 谢启伟. 中国金融状况与实体经济发展研究——来自中国2000-2017年月度数据[J]. 系统工程理论与实践, 2019, 39(11): 2723-2738.
LIU Chao, MA Yujie, XIE Qiwei. Research on China's financial situation and real economy development—Monthly data from China 2000-2017. Systems Engineering - Theory & Practice, 2019, 39(11): 2723-2738.
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2019, Vol. 39 
