Threshold Cointegration Approach for Assessing the Impact of US Economic Policy Uncertainty on Monetary Policy Decision of African Countries
DOI:
https://doi.org/10.47743/saeb-2021-0024Keywords:
Monetary policy rate, economic policy uncertainty, threshold cointegration, asymmetric adjustment, Granger causality.Abstract
This study uses threshold cointegration technique to ascertain the relationship between United States (US) economic policy uncertainty (EPU) and monetary policy rate (MPR) of each of the four African countries, namely Egypt, Ghana, Namibia and South Africa using monthly data from March 1998 to April 2020. The impact of US EPU on MPR of each country is assessed by examining the linear cointegration, asymmetric cointegration and causal relationships in the frequency domain between the US EPU and MPR of each African country. The findings provide evidence of long-run threshold cointegration and the adjustment mechanisms towards long-run equilibrium are asymmetric in the short run for the MPR models for Ghana, Namibia and South Africa in the M-TAR specification except for Egypt’s MPR model which does not provide evidence of asymmetric adjustment towards the equilibrium position. The bivariate analysis performed in the spectral frequency domain suggests unidirectional causality between US EPU and MPR of each country and that, the US EPU influences the MPR of each country in the long run. The findings provide important guidelines to monetary policy reviewers to take policy stance that would stimulate economic growth amid US policy uncertainties.
References
Adam, A. M. (2020). Susceptibility of stock market returns to international economic policy evidence from effective transfer entropy of Africa with the implication for open innovation. Journal of Open Innovation, 6(3), 71. http://dx.doi.org/10.3390/joitmc6030071
Asafo-Adjei, E., Agyapong, D., Agyei, S. A., Frimpong, S., Djimatey, R., & Adam, A. M. (2020). Economic Policy Uncertainty and Stock Returns of Africa: A Wavelet Coherence Analysis. Discrete Dynamics in Nature and Society, 2020, 1-8. http://dx.doi.org/10.1155/2020/8846507
Baker, S. R., Bloom, N., & Davis, S. J. (2016). Measuring Economic Policy Uncertainty. The Quarterly Journal of Economics, 131, 1593-1636. http://dx.doi.org/10.1093/qje/qjw024
Balcilar, M., Bekiros, S., & Gupta, R. (2017). The Role of News-Based Uncertainty Indices in Predicting Oil Markets: A Hybrid Nonparametric Quantile Causality Method. Empirical Economics, 53(3), 879-889. http://dx.doi.org/10.1007/s00181-016-1150-0
Bauer, M. D., & Neely, C. J. (2014). International channels of the Fed's unconventional monetary policy. Journal of International Money and Finance, 44, 24-46. http://dx.doi.org/10.1016/j.jimonfin.2013.12.007
Belke, A. B., Gros, D., & Thomas, O. (2017). The effectiveness of the Fed's quantitative easing policy: New evidence based an international interest rate differential. Journal of International Money and Finance, 73, 335-349. http://dx.doi.org/10.1016/j.jimonfin.2017.02.011
Bhattarai, S., Chatterjee, A., & Park, W. Y. (2019). Global spillover indices of US uncertainty. Journal of Monetary Economics, 114, 71-89. http://dx.doi.org/10.1016/j.jmoneco.2019.05.008
Bowman, D., Juan, M., & Sapriza, L. H. (2014). U.S. Unconventional Monetary Policy and Transmission to Emerging Market Economies. Board of Governors of the Federal Reserve System, International Finance Discussion Papers 1109.
Brauning, F., & Ivashina, V. (2020). U.S. monetary policy and emerging market credit cycles. Journal of Monetary Economics, 112(C), 57-76. http://dx.doi.org/10.1016/j.jmoneco.2019.02.005
Breitung, J., & Candelon, B. (2006). Testing for short-and long-run causality: A frequency-domain approach. Journal of Econometrics, 132(2), 363-378. http://dx.doi.org/10.1016/j.jeconom.2005.02.004
Brock, W. A. (1991). Nonlinear dynamics, chaos, and instability:statistical theory and economic evidence: MIT Press.
Brock, W. A. (2018). Nonlinearity and complex dynamics in economics and finance: The economy as an evolving complex system: CRC Press. http://dx.doi.org/10.1201/9780429492846-5
Bruno, V., & Shin, H. S. (2015). Capital Flows and the Risk-taking Channel of Monetary Policy. Journal of Monetary Economics, 71, 119-132. http://dx.doi.org/10.1016/j.jmoneco.2014.11.011
Caggiano, G., Castelnuovo, E., & Figueres, J. M. (2017). Economic policy uncertainty spillovers in booms and busts. SSRN. http://dx.doi.org/10.2139/ssrn.2972967
Castelnuovo, E., Lim, G., & Pellegrino, G. (2017). A Short Review of the Recent Literature on Uncertainty. The Australian Economic Review, 50(1), 68-78. http://dx.doi.org/10.1111/1467-8462.12210
Chan, K. S. (1993). Consistency and limiting distribution of the least squares estimator of a threshold autoregressive model. Annals of Statistics, 21(1), 520-533. http://dx.doi.org/10.1214/aos/1176349040
Choi, S. (2018). The Impact of US Financial Uncertainty Shocks on Emerging Market Economies: An International Credit Channel. Open Economies Review, 29(1), 89-118. http://dx.doi.org/10.1007/s11079-017-9471-y
Chulia, H., Gupta, R., Uribe, J. M., & Wohar, M. E. (2017). Impact of US uncertainties on emerging and mature markets: Evidence from a quantile-vector autoregressive approach. Journal of International Financial Markets, Institutions and Money, 48, 178-191. http://dx.doi.org/10.1016/j.intfin.2016.12.003
Colombo, V. (2013). Economic policy uncertainty in the US: Does it matter for the Euro area? Economics Letters, 121(1), 39-42. http://dx.doi.org/10.1016/j.econlet.2013.06.024
Dakhlaoui, I., & Aloui, C. (2016). The Interactive Relationship between the US Economic Policy Uncertainty and BRIC Stock Markets. Inter Economics, 146, 141-157. http://dx.doi.org/10.1016/j.inteco.2015.12.002
Enders, W., & Granger, C. W. J. (1998). Unit-root Tests and Asymmetric Adjustment with an Example Using the Term Structure of Interest Rates. Journal of Business & Economic Statistics, 16, 304-311. http://dx.doi.org/10.2307/1392506
Enders, W., & Siklos, P. (2001). Cointegration and threshold adjustment. Journal of Business & Economic Statistics, 19, 166-176. http://dx.doi.org/10.1198/073500101316970395
Engle, R. F., & Granger, C. W. J. (1987). Co-integration and error correction: Representation, estimation, and testing. Econometrica, 55(2), 251-276. http://dx.doi.org/10.2307/1913236
Gabauer, D., & Gupta, R. (2020). Spillovers across macroeconomic, financial and real estate uncertainties: A time-varying approach. Structural Change and Economic Dynamics, 52, 167-173. http://dx.doi.org/10.1016/j.strueco.2019.09.009
Geweke, J. (1982). Measurement of linear dependence and feedback between multiple time series. Journal of the American Statistical Association, 77(378), 304-313. http://dx.doi.org/10.1080/01621459.1982.10477803
Gilchrist, S., Sim, J. W., & Zakrajšek, E. (2014). Uncertainty, Financial Frictions, and Investment Dynamics. National Bureau of Economic Research, Working Paper, 20038. http://dx.doi.org/10.3386/w20038
Gupta, R., Lau, C. K. M., Nel, J. A., & Sheng, X. (2020). Monetary policy uncertainty spillovers in time and frequency domains. Journal of Economic Structures, 9(41), 41. http://dx.doi.org/10.1186/s40008-020-00219-z
Gupta, R., Ma, J., Risse, M., & Wohar, M. E. (2018). Common Business Cycles and Volatilities in US States and MSAs: The Role of Economic Uncertainty. Journal of Macroeconomics, 57, 317-337. http://dx.doi.org/10.1016/j.jmacro.2018.06.009
Hansen, B. (1997). Inference in TAR Models. Studies in Nonlinear Dynamics and Econometrics, 2(1), 1-16. http://dx.doi.org/10.2202/1558-3708.1024
Hosoya, Y. (1991). The decomposition and measurement of the interdependency between second-order stationary processes. Probability Theory and Related Fields, 88(4), 429-444. http://dx.doi.org/10.1007/BF01192551
IMF. (2013). 2013 Spillover Report - Analytical Underpinnings and Other Background 2013(60).
Jones, P. M., & Olson, E. (2015). The International Effects of US Uncertainty. International Journal of Finance & Economics, 20, 242-252. http://dx.doi.org/10.1002/ijfe.1513
Kabundi, A., Loate, T., & Viegi, N. (2020). Spillovers of the Conventional and Unconventional Monetary Policy from the US to South Africa. Economic Research Southern Africa, ERSA Working Paper, 818.
Kalu, E., Okoyeuzu, C., Ukemenam, A., & Ujunwa, A. (2020). Spillover effects of the US monetary policy normalization on African stock markets. Journal of Economic Development, 22(1), 3-19. http://dx.doi.org/10.1108/JED-09-2019-0038
Kang, W., Ratti, R. A., & Vespignani, J. (2019). Impact of Global Uncertainty on the Global Economy and Large Developed and Developing Economies. Applied Economics, 52(22), 2392-2407. http://dx.doi.org/10.1080/00036846.2019.1690629
Li, R., Li, S., Yuan, D., & Yu, K. (2020). Does economic policy uncertainty in the U.S. influence stock markets in China and India? Time-frequency evidence. Applied Economics, 52, 4300-4316. http://dx.doi.org/10.1080/00036846.2020.1734182
Mensi, W., Hammoudeh, S., Reboredo, J. C., & Nguyen, D. K. (2014). Do Global Factors Impact BRICS Stock Markets? A Quantile Regression Approach. Emerging Markets Review, 19, 1-17. http://dx.doi.org/10.1016/j.ememar.2014.04.002
Olanipekun, I. O., Gungor, H., & Olasehinde-Williams, G. (2019). Unraveling the Causal Relationship between Economic Policy Uncertainty and Exchange Market Pressure in BRIC Countries: Evidence from Bootstrap Panel Granger Causality. SAGE Open, 9(2). http://dx.doi.org/10.1177/2158244019853903
Perron, P. (1990). Testing for a unit root in a time series with a changing mean. Journal of Business & Economic Statistics, 8(2), 153-162. http://dx.doi.org/10.2307/1391977
PolicyUncertainty. (2020). Retrieved from http://www.policyuncertainty.com/
Sum, V. (2012). The Reaction of Stock Markets in the BRIC Countries to Economic Policy Uncertainty in the United States. SSRN. http://dx.doi.org/10.2139/ssrn.2094697
Sum, V. (2013). The ASEAN stock market performance and economic policy uncertainty in the United States. Economic Papers, 32(4), 512-521. http://dx.doi.org/10.1111/1759-3441.12049
Zhang, D., Lei, L., Ji, Q., & Kutan, A. M. (2019). Economic Policy Uncertainty in the US and China and Their Impact on the Global Markets. Economic Modelling, 79, 47-56. http://dx.doi.org/10.1016/j.econmod.2018.09.028
Zivot, E., & Andrews, D. W. K. (2002). Further evidence on the great crash, the oil-price shock, and the unit-root hypothesis. Journal of Business & Economic Statistics, 20(1), 25-44. http://dx.doi.org/10.1198/073500102753410372
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