| تعداد نشریات | 24 |
| تعداد شمارهها | 917 |
| تعداد مقالات | 8,230 |
| تعداد مشاهده مقاله | 16,274,279 |
| تعداد دریافت فایل اصل مقاله | 13,749,801 |
Analyzing Stock Prices to Identify Unconventional Monetary Policy Shocks Applying The SVARIH Methodology | ||
| Iranian Journal of Economic Studies | ||
| مقاله 3، دوره 13، شماره 1 - شماره پیاپی 25، 2024، صفحه 25-50 اصل مقاله (582.81 K) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22099/ijes.2025.52786.2022 | ||
| نویسندگان | ||
| Mahboobeh Khadem Nematollahy* 1؛ Mojtaba Bahmani2؛ Teymour Mohammadi1 | ||
| 1Faculty of Economics, Allameh Tabataba'i University, Tehran, Iran. | ||
| 2Faculty of Management and Economics, Shahid Bahonar University of Kerman, Kerman. Iran. | ||
| چکیده | ||
| Identifying monetary policy shocks is a crucial determinant influencing stock price index in esteemed global stock exchanges. Given that the implications of this policy might impact individual’s wellbeing, unemployment, and economic growth, it is essential to analyze and quantify these effects. This study aims to analyze the dynamic responses of macroeconomic variables in fuel-exporting countries, including Colombia, Indonesia, Iran, Russia, and Saudi Arabia, to unconventional monetary policy within the SVARIH framework, utilizing stock price fluctuations from the years 2000 to 2023. The variables studied in the study include inflation, unemployment, stock prices, interest rates, and gross domestic product. The results indicate that the slope policies enacted by governments like Colombia, Iran, and Russia can facilitate economic recovery by decreasing unemployment and credit expenses. Furthermore, stock prices are demonstrated to be effective in identifying slope policy shocks. The Iranian government can implement unconventional monetary policies to enhance credit availability, hence boosting production and decreasing unemployment. The findings can be concisely presented as follows:1) This study aims to develop a novel approach for identifying unconventional monetary policy shocks using a heteroskedasticity-based identification method in fuel-exporting countries.2) Stock price fluctuations are employed as a means of identifying the shocks.3)Policymakers can significantly influence the implementation of unconventional monetary policies to reduce stock market volatility through enhanced liquidity provision and increased equity returns. | ||
| کلیدواژهها | ||
| Slope policy؛ heteroskedasticity identification method؛ structural vector autoregressive approach | ||
| مراجع | ||
|
Allais, M. (1974). The Psychological Rate of Interest, Journal of Money, Credit and Banking, 6(3), 285-331. Arshadi, A. (2012). optimal monetary policy under uncertainty conditions (philips curve). Quarterly Journal of Quantitative Economics (JQE), 9(3), 1-23. Beaudry, P., & Portier, F. (2006). Stock prices, news, and economic fluctuations. American Economic Review, 96(4), 1293–1307. Bernanke, B. S. (2020). The new tools of monetary policy, American Economic Review, 110(4), 943–983. Bhattarai, S., Neely, C.J., (2020). An Analysis of the Literature on International Unconventional Monetary Policy, Federal Reserve Bank of St. Louis Working Paper, 1-93. Breitung, J., R. Bruggemann and H. Lütkepohl (2004). Structural vector autoregressive modeling and impulse responses. In H. Lütkepohl and M. Kratzig (Eds.), Applied Time Series Econometrics, pp.159–96. Cambridge: Cambridge University Press. Campbell, J. R., Evans, C. L., Fisher, J. D., Justiniano, A., Calomiris, C. W., & Woodford, M. (2012). Macroeconomic effects of federal reserve forward guidance [with comments and discussion]. Brookings Papers on Economic Activity, 1–80. Chen, W. and A. Netsunajev (2016). On the long-run neutrality of demand shocks. Economics Letters 139, 57–60. Cole, S. J., & Huh, S. (2024). Measuring the effects of unconventional monetary policy tools under adaptive learning. Journal of Economic Dynamics and Control, 164, 104876. Cole, Stephen J. (2021). Learning and the effectiveness of central bank forward guidance. J. Money Credit Bank. 53 (1), 157–200. Davtyan, K. (2023). Unconventional monetary policy and economic inequality. Economic Modelling, 126, 106380, 1-12. Eberly, J., Stock, J. H., & Wright, J. H. (2019). The federal reserve’s current framework for monetary Policy: A review and assessment: Working paper no. w26002, National Bureau of Economic Research, 1-69. Ehrmann, M., & Fratzscher, M. (2005). Exchange rates and fundamentals: new evidence from real-time data. Journal of International Money and Finance, 24(2), 317–341. Friedman, M.(1969). The Optimum Quantity of Money. in Friedman, M.; the Optimum Quantity of Money and Other Essays, Aldine, Chicago, IL, Gertler, M. and Karadi, P. (2011). A model of unconventional monetary policy. J. Monet. Econ. 58 (1), 17–34. Gertler, M., & Karadi, P. (2015). Monetary policy surprises, credit costs, and economic activity. American Economic Journal: Macroeconomics, 7(1), 44–76. Gilchrist, S., López-Salido, D., & Zakrajšek, E. (2015). Monetary policy and real borrowing costs at the zero lower bound. American Economic Journal: Macroeconomics, 7(1), 77–109. Haldane, A.G. (2015). Stuck. BoE staff Speech (London: Bank of England). Open University, Milton Keynes, 1-25. Hanson, S. G., Lucca, D. O., & Wright, J. H. (2018). The excess sensitivity of long-term rates: A tale of two frequencies: Staff report no. 810, Federal Reserve Bank of New York, 1-78. Haynes, D. (2023). A Brief History of Central Banking: How the Quest for Financial Stability Led to Unconventional Monetary Practices, 1-188. Hemmati, Maryam. (2010). Interest rate-based monetary policy tools compared to non-interest rate monetary policy tools, report of Dr. Seyed Ahmadreza Jalali Naeini's speech at the conference "Experience of Monetary Policy in Islamic Countries" , Monetary and Banking Research Institute, Economic News,132, 70-75. Hohberger, S., Ratto, M., & Vogel, L. (2023). The macroeconomic effects of unconventional monetary policy: Comparing euro area and US models with shadow rates. Economic Modelling, 127, 106438. Ioannidis, C., Kontonikas, A., (2008). The impact of monetary policy on stock prices. J. Policy Model. 30 (1), 33–53. Jarociński, M., & Karadi, P. (2020). Deconstructing monetary policy surprises—the role of information shocks. American Economic Journal: Macroeconomics, 12(2),1–43. Keynes, J.M. (1936). The General Theory of Employment, Interest, and Money, International relations and security networks, 1-190. khadem Nematollahy, M. , Mohammadi, T. , Shakeri, A. and Salem, A. A. (2023). Combining Zero and Sign Restrictions in VAR Models: Identifying Monetary Policy Shocks in Iran. Iranian Journal of Economic Studies, 12(1), 155-180. Kilian, L. and H. Lütkepohl (2017). Structural Vector Autoregressive Analysis. Cambridge, UK: Cambridge University Press. Kim, K. (2017). Identification of monetary policy shocks with external instrument SVAR, Finance and economics discussion series no. 113, Board of Governors of the Federal Reserve System, 1-34. Kuttner, K. N. (2018). Outside the box: Unconventional monetary policy in the great recession and beyond, Journal of Economic Perspectives, 32(4), 121–146. Lakdawala, A. (2019). Decomposing the effects of monetary policy using an external instruments SVAR, Journal of Applied Econometrics, 34(6), 934–950. Lanne, M. and H. Lutkepohl (2008): Identifying Monetary Policy Shocks via Changes in Volatility. Journal of Money, Credit and Banking, 40 (6), 1131-1149. Lerner, Abba P. (1959). Consumption-Loan Interest and Money, Journal of Political Economy, University of Chicago Press, vol. 67(5), 512-518. Lewis, D. J. (2018a). Identifying shocks via time-varying volatility. Technical Report 871, Federal Reserve, Bank of New York, New York, NY, USA. Lütkepohl, H. (2005), New Introduction to Multiple Time Series Analysis. Berlin, Germany: Springer-Verlag. Lütkepohl, H. (2013). Identifying structural vector autoregressions via changes in volatility. Advances in Econometrics 32, 169–203. Lütkepohl, H. and G. Milunovich (2016). Testing for identification in SVAR-GARCH models. Journal of Economic Dynamics and Control 73, 241–58. Lütkepohl, H. and T. Wozniak (2020). Bayesian inference for structural vector autoregressions identified by Markov-switching heteroskedasticity. Journal of Economic Dynamics and Control, 113. Lütkepohl, H., Meitz, M., Netšunajev, A., & Saikkonen, P. (2021). Testing identification via heteroskedasticity in structural vector autoregressive models. The Econometrics Journal, 24(1), 1-22. Ma, L. (2024). Using stock prices to help identify unconventional monetary policy shocks for external instrument SVAR. International Review of Economics & Finance, 89, 1234-1247. Mertens, K., & Ravn, M. O. (2013). The dynamic effects of personal and corporate income tax changes in the United States. American Economic Review, 103(4), 1212–1247. Mohammadi, Hossein. and Mehdi Mahmoudi. (2017). Investigating the interaction effects of interest rates with selected macroeconomic variables in Islamic and non-Islamic countries, Economic Modeling Research, 8 (28), 103-138. Neuhierl, A., & Weber, M. (2021). Monetary momentum: Working paper no. 20–05, Chicago Booth Research Paper, 1-59. NONEJAD, MASOUD, ZAMANI KORDSHOULI, BEHZAD, & HOSSEINZADEH YOSEF ABAD, SEYED MOJTABA. (2012). THE IMPACT OF MONETARY POLICY ON STOCK PRICE INDEX IN IRAN. JOURNAL OF FINANCIAL ECONOMICS (FINANCIAL ECONOMICS AND DEVELOPMENT), 6(20), 9-38. Rasouli, M., Abrishami, H., mehrara, M. and Esfahanian, H. (2020). Predicting the Impact of monetary and fiscal policies on the unemployment rate in the Iranian Economy. Journal of Economic Research (Tahghighat- E- Eghtesadi), 55(2), 321-345. Rigobon, R. (2003). Identification through heteroskedasticity, The Review of Economics and Statistics, 85(4), 777–792. Rigobon, R., & Sack, B. (2004). The impact of monetary policy on asset prices, Journal of Monetary Economics, 51(8), 1553–1575. Salmani Bishak, Mohammad Reza, Bargi Oskoui, Mohammad Mehdi and Sewda Lak. (2015). The Impact of Monetary and Fiscal Policy Shocks on the Iranian Stock Market, Quarterly Journal of Economic Modeling Research, 1-39. Saraceno, F. & Tamborini, R. (2020). Quantitative easing in a monetary union. Oxf. Econ. Pap, 72 (1), 124–148. Shajari, Parasto. and Bita Mohebikhah (2010). Predicting banking crises and balance of payments using the KLR signaling method (Case study: Iran), Quarterly Journal of Monetary and Banking Research, 2(4), 115-152. Sims, Eric, Wu, Jing Cynthia, Zhang, Ji, (2023). The four equations new Keynesian model. Rev. Econ. Stat. 105, 1–17. Stroebel, J. C., & Taylor, J. B. (2012). Estimated impact of the Fed's mortgage-backed securities purchase program (No. w15626). National Bureau of Economic Research, 1-32. Tang, H., Zhang, C., & Zhou, H. (2022). Monetary policy surprises and investment of non-listed real sector firms in China, International Review of Economics & Finance, 79, 631–642. Tobin, J. (1967). Notes on Optimal Monetary Growth, Journal of Political Economy, Vol. 76, No. 4, Part 2: Issues in Monetary Research, 833-859. Wozniak, T. and M. Droumaguet (2015). Assessing monetary policy models: Bayesian inference for heteroskedastic structural VARs. Technical report, University of Melbourne, Melbourne, Australia. Zamanzadeh, A. , Ehsani, M. A. and Ganjali, M. (2020). Evaluating the Effects of Fiscal and Monetary Policies on the Unemployment Duration in Industrial Countries. Journal of Economics and Modelling, 11(3), 195-225.
| ||
|
آمار تعداد مشاهده مقاله: 363 تعداد دریافت فایل اصل مقاله: 343 |
||