The analysis of relationship between financial markets' illiquidity shocks and macroeconomic dynamics: Time-varying parameter vector autoregression (TVP-VAR) approach in Iran

Document Type : Original Article

Authors

1 Ph.D. Candidate in Economics, Isfahan (Khorasgan) Branch, Islamic Azad University, Isfahan, Iran.

2 Associate Prof., Department of Economics, Isfahan (Khorasgan) Branch, Islamic Azad University, Isfahan, Iran

3 Associate Prof., Department of Economics, Isfahan (Khorasgan) Branch, Islamic Azad University, Isfahan, Iran.

Abstract

liquidity of financial markets have been different over time. Unpredictability of liquidity in these markets is a crucial source of risk for investors. The illiquidity of the financial market through financial channels can affect the real economy. The present study analyzed the relationship between financial market,s illiquidity shocks and macroeconomic dynamics by using Time-varying parameter vector autoregression (TVP-VAR) model and using quarterly time series data between 3:1387 and 4:1399. In order to achieve this goal, the Amihud index (2002) has been used to calculate the illiquidity variable. The results of the study indicate that the reaction of production growth to the illiquidity shock is negative and decreasing. Also, illiquidity shocks have an increasing effect on inflation, and the effect of liquidity growth on these shocks has been accompanied by a relative increase. Finally, the impact of the stock market illiquidity shock on the unemployment rate was increasing at the beginning of the period, and this effect decreased at the end of the period.

Keywords


1. Aleheidar, S., Aghababaei, M., & Eghbalnia, M. (2020). The Effect of oil price dynamics on industry momentum in Tehran stock Exchange. Journal of Financial Management Perspective, 10(30), 121-142. (In Persian) 
2. Acharya, V.V., Pedersen, L.H. (2005). Asset pricing with liquidity risk. Journal of Finance Econ 77 (2), 375–410.
3. Amihud, Y. (2002). Illiquidity and stock returns: cross-section and time-series effects. Journal of Finance Markets, 5 (1), 31–56.
4. Anginer, D. (2010). Liquidity clienteles: transaction costs and investment decisions of individual investors. World Bank Research- DEC Group, World Bank Policy Research Working Paper No 5318:1-40.
5. Brunnermeier, M. K.., & Pedersen, L. H. (2009). Market liquidity and funding liquidity. Rev Finance, Stud 22 (6), 2201–2238. 
6. Beiranvand, S., Rezaei, M., & Keshavarz, H. (2020). The effect of monetary and financial instability on energy-intensive industries stocks. Journal of Financial Management Perspective, 10(32), 81-107. (In Persian)
7. Camba, A. C., & Camba, A. L. (2019). The dynamic relationship of domestic credit and stock market liquidity on the economic growth of the Philippines. Journal of Asian Finance, Economics and Business 7 )1(, 37-46.
8. Ebrahimi, S., & Efarnaghi, E. (2016). Monetary and fiscal effects on stock market liquidity. Journal of Economic Research and Policies, )24(77, 7 - 36. (In Persian)
9. Ellington, M. (2018). Financial market illiquidity shocks and macroeconomic dynamics: Evidence from the UK. Journal of Banking and Finance, 89, 225–236.
10. Ellington, M., Florackis, C., & Milas, C. (2017). Liquidity shocks and real GDP growth: evidence from a Bayesian time–varying parameter VAR. Journal of Money Finance, 72, 93–117.
11. Fabozzi, F., Modigliani, F. (1995). Capital market Institutions and Instruments. Upper Saddle River, NJ: Prentice Hall, ECONIS - Online Catalogue of the ZBW.
12. Florackis, C., Giorgioni, G., Kostakis, A., & Milas, C. (2014). On stock market illiquidity and real-time GDP growth. Journal of Money Finance, 44, 210–229.
13. Jafari Seresht, D., Setarehie, M., & Hosseini Nikravesh, Z. (2017). A study on the relationship between the attitudes of investors and the tse liquidity and economic growth in iran. Journal of Securities Exchange,  10 )39(, 49 - 69. (In Persian)
14. Khanmohammadi, M., Asadi, A., & mohseni dehkalani, N. (2018). Dynamics of the shock of markets in parallel with the Stock Market on Stock Return (An approach of the models of time parameter change). Journal of Financial Management Perspective, 8(23), 61-85. (In Persian)
15. Kiyotaki, N., & Moore, J. (2019). Liquidity, business cycles and monetary policy, Journal of Political Economy, (127), 2926–2966.
16. Levine, R. (1991). Stock markets, growth, and tax policy. Journal of Finance, 46 (4), 1445–1465.
17. Levine, R., & Zervos, S. (1998). Stock markets, banks, and economic growth. Journal of Economics, 88 (3), 537–558.
18. Longstaff, F. A. (2004). The flight-to-liquidity premium in US treasury bonds prices. Journal of Financial of Bus, 77 (3), 511–526.
19. Nakajima, J., Kasuya, M., & Watanabe, T. (2011). Bayesian analysis of time-varying parameter vector autoregressive model for the Japanese economy and monetary policy. Journal of Economics, 25, 225–245.
20. Primiceri, G. E. (2005). Time varying structural vector autoregressions and monetary. Journal of Economic, 72 (3), 821-852.
21. Randi, N., Johannes, S., & degaard, B. (2010). Stock market liquidity and the business cycle, Journal of Finance, (66), 139-176.  
22. Rosengren, E.S. (2010). The impact of liquidity, securitization, and banks on the real economy. Journal of Money Credit Bank, 42 (1), 221–228.
23. Switzer, L., & Picard, A. (2016). Stock market liquidity and economic cycles: A non-linear approach, Economic Modelling, Elsevier, 57(C), 106-119.
24. Wu, L., & Fu, G. (2014). RMB exchange rate, short-turn capital flows and stock price. Journal of Economic, (49), 72–86.
25. Yen, C. Y., & Yu, C. H. (2020). Understanding the macroeconomic impact of illiquidity shocks in the United States. Economic Inquiry, Western Economic Association International, 58(3), 1245-1278.