The Contagion Mechanism between Industrial Risk and the Macro Economy in China
ZHOU Kaiguo, XING Ziyu, PENG Shiyuan
Lingnan College, Sun Yat-Sen University; School of Economics and Trade,Xin hua College of Sun Yat-sen University; Guangdong Branch, Bank of Communication
Summary:
The role of finance is central to the modern economy, as the interaction between finance and the real economy is prominent. The healthy development of China's economy requires allowing finance to serve the real economy. The prevention of “risk resonance” between China's financial market and its real economy will ensure that the co-development of finance and the real economy is benign. This study on the interaction between financial risk and the real economy will demonstrate how to prevent “risk resonance” and improve the financial services to the real economy. This paper uses a method proposed by Diebold and Yilmaz (2009) to calculate the industry yield spillover index of the stock market. which is called “Industry Risk of the Stock Market.” It analyzes the linkage relationship and risk spillover effect between various industries in the stock market. The dividend yield and interest rate are applied as intermediary channels. This allows us to use the GARCH-in-mean model to analyze the transmission mechanism of the first and second moments between the industry risk of the stock market and macroeconomic variables. The model measures the interaction between the stock market and the macro economy from a new perspective. It also describes the two-way transmission of industry risk between the stock market and macroeconomic fluctuations, filling a gap in the literature by demonstrating how stock market fluctuations affect macroeconomic performance. This paper studies the risk spillover effect among various industries in the stock market. A total of 3,284 stock samples are selected from China's Shanghai and Shenzhen A-share markets. A total of 18 industries are selected, following the industry classification standards of the China Securities Regulatory Commission in 2012. The sample period is from May 10, 1996 to December 31, 2019. Economic indicators such as consumer price index, broad money supply, export value, fixed asset investment completion, unemployment rate, and RMB exchange rate against the US dollar are used as representatives of the macroeconomic performance. All data are obtained from the WIND database. The main findings are as follows. First, the results of examining the spillover effect of the return of the stock market industry in China show that compared with the consolidation cycle, the stock market has a relatively large industry-wide yield spillover index during the rising cycle and falling cycle. The manufacturing industry, as the foundation of national economy, is at the forefront of all industries in terms of its total outgoing spillover effect, while the financial industry as a whole is the recipient of incoming spillover. Second, there is a significant two-way impact between the industrial risk of the stock market and the macro economy, whether at the mean level or the volatility level. Macroeconomic fluctuations will lead to stronger correlations between various sectors in the stock market, and the yields of various industries can rise and fall at the same time. The fluctuation of the industrial risk of the stock market generally inhibits the growth of the macro economy. In terms of the impact of industrial risks on macroeconomic variables, both dividend rate and interest rate are intermediary channels. Conversely, regarding the impact of macroeconomic variables on industrial risks, only interest rate is an intermediary channel. In addition, during the period of external shocks, represented by the international financial crisis in 2008, the industrial risks and macroeconomic variables do not show a significant spillover relationship. This study's findings offer some policy recommendations. Firstly, regulators can use quantitative indicators such as the industrial spillover index to measure the industrial risk of the stock market. Secondly, the effective prevention of two-way contagion between financial risks and fluctuations of the real economy and of “risk resonance” between the financial market and real economy requires stronger macro-prudential supervision. Accurately identifying the source of risks is helpful to regulators who will be able to implement better risk supervision measures after accurately identifying the source of the risks. By analyzing the characteristics of the industrial risk of stock market, we can accurately identify its source and accurately implement measures to prevent and control financial risks at the relevant industry level. Third, regulators should consider the intermediary objectives of financial risk supervision to improve the financial market and real economy's ability to supervise and prevent risk resonance. The regulators should not ignore the other aspect when unilaterally implementing policies from the perspective of the financial market or real economy.
Acemoglu, D., V. M. Carvalho, A. Ozdaglar, and A. Tahbaz-Salehi. 2012. “The Network Origins of Aggregate Fluctuations”, Econometrica, 80(5):1977～2016.
[14]
Bansal, R., D. Kiku, I. Shaliastovich, and A. Yaron. 2014. “Volatility, the Macroeconomy and Asset Prices”, Journal of Finance, 69(6):2471～2511.
[15]
Barrot, J. N. and J. Sauvagnat. 2016. “Input Specificity and the Propagation of Idiosyncratic Shocks in Production Networks”, The Quarterly Journal of Economics, 131(3):1543～1592.
[16]
Beirne, J., G. M. Caporale, M. Schulzeghatts, and N. Spagnolo. 2013. “Volatility Spillovers and Contagion from Mature to Emerging Stock Markets”, Review of International Economics, 21(5):1060～1075.
[17]
Bollerslev, T. 1990. “Modelling the Coherence in Short-Run Nominal Exchange Rates: A Multivariate Generalized Arch Model”, Review of Economics and Statistics, 72(3):498～505.
[18]
Chen, A. Y. 2017. “External Habit in a Production Economy: A Model of Asset Prices and Consumption Volatility Risk”, Review of Financial Studies, 30(8):2890～2932.
[19]
Chen, P., L. Karabarbounis, and B. Neiman. 2017. “The Global Rise of Corporate Saving”, Journal of Monetary Economics, 89:1～19.
[20]
Chiu, C. W., D. F. Harris, E. Stoja, and M. Chin. 2018. “Financial Market Volatility, Macroeconomic Fundamentals and Investor Sentiment”, Journal of Banking and Finance, 92(7):130～145.
[21]
Chiu, C. W., J. I. Peña and C. W. Wang. 2015. “Industry Characteristics and Financial Risk Contagion”, Journal of Banking and Finance, 50(1):411～427.
[22]
Cohen, L. and A. Frazzini. 2008. “Economic Links and Predictable Returns”, The Journal of Finance, 63(4):1977～2011.
[23]
Diebold, F. X. and K. Yilmaz. 2009. “Measuring Financial Asset Return and Volatility Spillovers, with Application to Global Equity Markets”, Economic Journal,119(534):158～171.
[24]
Diebold, F. X. and K. Yilmaz. 2012. “Better to Give Than to Receive: Predictive Directional Measurement of Volatility Spillovers”, International Journal of Forecasting, 28(1):57～66.
[25]
Engle, R. 2002. “Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models ”, Journal of Business and Economic Statistics, 20(3):339～350.
[26]
Engle R. F., E. Ghysels, and B. Sohn. 2013. “Stock Market Volatility and Macroeconomic Fundamentals”, The Review of Economics and Statistics, 95(3):776～797.
[27]
Engle, R. F., D. M. Lilien and R. P. Robins. 1987. “Estimating Time Varying Risk Premia in the Term Structure: The Arch-M Model”, Econometrica, 55(2):391～407.
[28]
Fama, E. F. and K. R. French. 1988. “Dividend Yields and Expected Stock Returns”, Journal of Financial Economics, 22(1):3～25.
[29]
Giglio, S., B. Kelly and S. Pruitt. 2016. “Systemic Risk and the Macroeconomy: An Empirical Evaluation”, Journal of Financial Economics, 119(3):457～471.
[30]
Gonzalez M., J. Nave, and G. Rubio. 2018. “Macroeconomic Determinants of Stock Market Betas”, Journal of Empirical Finance, 45:26～44.
[31]
Jensen, M. C. 1986. “ Agency Costs of Free CashFlow, Corporate Finance, and Takeovers”, American Economic Review,76(2),:323～329.
[32]
Lobo, B. J. 2000. “Asymmetric Effects of Interest Rate Changes on Stock Prices”, The Financial Review, 35(3):125～144.
[33]
Turnovsky, S. 1990. “The Effects of Taxes and Dividend Policy on Capital Accumulation and Macroeconomic Behavior”, Journal of Economic Dynamics and Control, 14:491～521.
