Exchange Rate Volatility Effect on Economic Growth under Different Exchange Rate Regimes: New Evidence from Emerging Countries Using Panel CS-ARDL Model
Abstract
1. Introduction
2. Literature Review
3. Methodology and Data
4. Empirical Analysis
4.1. GARCH Model Specification
4.1.1. Normality and Stationarity Analysis
4.1.2. ARMA Analysis Process
4.1.3. ARCH Effect Analysis
4.2. CS-ARDL Panel Model Specification
- -
- The order of integration of the variables.
- -
- The homogeneity of the panel.
- -
- Cross-sectional dependency.
- -
- The existence of a long-term link between the variables, notably the presence of cointegration.
4.2.1. Cross-Sectional Dependency Test
4.2.2. Homogeneity Test
4.2.3. Unit Root Test
4.2.4. Cointegration Test
5. Results and Discussion
6. Conclusions
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
1 | These authors argue that only the monetary or real aspect matters, while the source of shocks (internal or external) is not a determining factor in the choice of exchange rate regime. |
2 | The authors point out that given the infrequent adoption of fixed exchange rate regimes in advanced economies, confirmation or denial of their relevance for shock absorption remains ambiguous. |
3 |
References
- Aghion, Philippe, Philippe Bacchetta, Romain Rancière, and Kenneth Rogoff. 2009. Exchange rate volatility and productivity growth: The role of financial development. Journal of Monetary Economics 56: 494–513. [Google Scholar] [CrossRef]
- Aizenman, Joshua. 1992. Exchange Rate Flexibility, Volatility, and Domestic and Foreign Direct Investment. Staff Papers (International Monetary Fund) 39: 890–922. [Google Scholar] [CrossRef]
- Akgül, Isil, and Selin Özdemir. 2012. Inflation Threshold and The Effects on Economic Growth. İktisat İşletme ve Finans Dergisi 27: 85–106. [Google Scholar]
- Ameziane, Karim, and Bouchra Benyacoub. 2022. Islamic Stock Market Performance in the Era of the COVID19 Crisis: An Empirical Study Using the GARCH Model. International Journal of Accounting, Finance, Auditing, Management and Economics 3: 139–54. [Google Scholar] [CrossRef]
- Arize, Augustine C., Thomas Osang, and Daniel J. Slottje. 2000. Exchange-Rate Volatility and Foreign Trade: Evidence from Thirteen LDC’s. Journal of Business and Economic Statistics 18: 10–17. [Google Scholar] [CrossRef]
- Asteriou, Dimitrios, and Simon Price. 2005. Uncertainty, Investment and Economic Growth: Evidence from a Dynamic Panel. Review of Development Economics 9: 277–88. [Google Scholar] [CrossRef]
- Bailliu, Jeannine, Robert Lafrance, and Jean-François Perrault. 2002. Does Exchange Rate Policy Matter for Growth? International Finance 6: 381–414. [Google Scholar] [CrossRef]
- Balassa, Bela. 1964. The purchasing-power parity doctrine: A reappraisal. Journal of Political Economy 72: 584–96. [Google Scholar] [CrossRef]
- Barguellil, Achouak, Ousama Ben-Salha, and Mourad Zmami. 2018. Exchange rate volatility and economic growth. Journal of Economic Integration 33: 1302–36. [Google Scholar] [CrossRef]
- Baxter, Marianne. 1991. Business cycles, stylized facts, and the exchange rate regime: Evidence from the United States. Journal of International Money and Finance 10: 71–88. [Google Scholar] [CrossRef]
- Baxter, Marianne, and Alan C. Stockman. 1989. Business cycles and the exchange-rate regime: Some international evidence. Journal of Monetary Economics 23: 377–400. [Google Scholar] [CrossRef]
- Bekaert, Geert, Campbell R. Harvey, and Christian Lundblad. 2005. Does financial liberalization spur growth? Journal of Financial Economics 77: 3–55. [Google Scholar] [CrossRef]
- Bollerslev, Tim. 1986. Generalized autoregressive conditional heteroskedasticity. Journal Econometrics 31: 307–27. [Google Scholar] [CrossRef]
- Chudik, Alexander, and Hashem M. Pesaran. 2015. Common correlated effects estimation of heterogeneous dynamic panel data models with weakly exogenous regressors. Journal of Econometrics 188: 393–420. [Google Scholar] [CrossRef]
- Cihak, Martin, Sharika T. Sharifuddin, Kalin I. Tintchev, Samir Jahjah, and Sònia Muñoz. 2012. Financial Stability Reports: What Are They Good for? IMF Working Papers 2012/001. Washington, DC: International Monetary Fund. [Google Scholar]
- Cline, William R. 1985. Debt, Macro Policy and State Intervention: The Next Phase for Latin America. Journal of Interamerican Studies and World Affairs 27: 155–72. [Google Scholar] [CrossRef]
- Cuaresma, Jesús C., and Cezary Wójcik. 2006. Measuring monetary independence: Evidence from a group of new EU member countries. Journal of Comparative Economics 34: 24–43. [Google Scholar] [CrossRef]
- Cushman, David O., and Glauco De Vita. 2017. Exchange rate regimes and FDI in developing countries: A propensity score matching approach. Journal of International Money and Finance 77: 143–63. [Google Scholar] [CrossRef]
- Daly, Sfia M. 2007. The Choice of Exchange Rate Regime for Emergency Market. MPRA Paper No. 4075. Munich: University Library of Munich. [Google Scholar]
- Darvas, Zsolt. 2021. Timely Measurement of Real Effective Exchange Rates, Bruegel Working Paper December 2021. Working Paper.
- De Santis, Giorgio, and Bruno Gerard. 1998. How big is the premium for currency risk? Journal of Financial Economics 49: 375–412. [Google Scholar] [CrossRef]
- Dell’Ariccia, Giovanni. 1999. Exchange Rate Fluctuations and Trade Flows: Evidence from the European Union, IMF Staff Papers 46, no. 3. 315–34.
- Dickey, David, and Wayne A. Fuller. 1979. Distribution of the estimators for autoregressive time series with a unit root. Journal of the American Statistical Association 74: 427–31. [Google Scholar]
- Dumas, Bernard, and Bruno Solnik. 1995. The world price of foreign exchange risk. The Journal of Finance 50: 445–79. [Google Scholar] [CrossRef]
- Dumitrescu, Elena-Ivona, and Christophe Hurlin. 2012. Testing for Granger non-causality in heterogeneous panels. Economic Modelling 29: 1450–60. [Google Scholar] [CrossRef]
- Duval, Romain A., and David Furceri. 2019. Chapter 3 Reigniting Growth in Low-Income and Emerging Market Economies: What Role can Structural Reforms Play? In World Economic Outlook, October 2019. Washington, DC: International Monetary Fund. [Google Scholar]
- Edwards, Sebastian. 1984. The role of international reserves and foreign debt in the external adjustment process. In Adjustment, Conditionality, and International Financing. Washington, DC: International Monetary Fund. [Google Scholar]
- Edwards, Sebastian, and Daniel Lederman. 1998. The Political Economy of Unilateral Trade Liberalization: The Case of Chile. NBER Working Papers 6510. Cambridge: National Bureau of Economic Research, Inc. [Google Scholar]
- Eichengreen, Barry, and Ricardo Hausmann. 1999. Exchange Rates and Financial Fragility. NBER Working Papers 7418. Cambridge: National Bureau of Economic Research, Inc. [Google Scholar]
- Elbadawi, Ibrahim, and Bassem Kamar. 2006. The Great Debate on Exchange Rate Regimes: Why Should the Mena Region Care? Available online: https://ssrn.com/abstract=1465594 (accessed on 5 October 2022).
- Engle, Robert F. 1982. Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica 50: 987–1007. [Google Scholar] [CrossRef]
- Farhi, Emmanuel, and Ivan Werning. 2012. Dealing with the Trilemma: Optimal Capital Controls with Fixed Exchange Rates. No. w18199. Cambridge: National Bureau of Economic Research. [Google Scholar]
- Ferrari-Filho, Fernando, and Luiz F. De Paula. 2008. Exchange rate regime proposal for emerging countries: A Keynesian perspective. Journal of Post Keynesian Economics 31: 227–48. [Google Scholar] [CrossRef]
- Flood, Robert P., and Nancy P. Marion. 1982. The Transmission of Disturbances under Alternative Exchange-Rate Regimes with Optimal Indexing. Quarterly Journal 0/Economics 97: 43–66. [Google Scholar] [CrossRef]
- Frankel, Jeffrey. 1999. No Single Currency Regime Is Right for All Countries or at All Times. Working Paper. Available online: http://www.nber.org/papers/w7338 (accessed on 5 October 2022).
- Frankel, Jeffrey. 2003. A Proposed Monetary Regime for Small Commodity Exporters: Peg the Export Price (‘PEP’). International Finance 6: 61–88. [Google Scholar] [CrossRef]
- Frankel, Jeffrey, Sergio L. Schmukler, and Luis Serven. 2002. Global Transmission of Interest Rates: Monetary Independence and Currency Regime. Journal of international Money and Finance 23: 701–33. [Google Scholar] [CrossRef]
- Friedman, Milton. 1953. The Case for Flexible Exchange Rates. In Essays in Positive Economics. Edited by M. Friedman. Chicago: University of Chicago Press. [Google Scholar]
- Fritz-Krockow, Bernhard, and Emilia M. Jurzyk. 2004. Will You Buy My Peg?: The Credibility of a Fixed Exchange Rate Regime as a Determinant of Bilateral Trade (September 2004). IMF Working Paper No. 04/165. Available online: https://ssrn.com/abstract=878990 (accessed on 5 October 2022).
- Gertler, Mark, Simon Gilchrist, and Fabio M. Natalucci. 2007. External Constraints on Monetary Policy and the Financial Accelerator. Journal of Money, Credit and Banking 39: 295–330. [Google Scholar] [CrossRef]
- Ghosh, Atish R., and Jonathan D. Ostry. 2009. Choosing an exchange rate regime. Finance & Development 46: 4. [Google Scholar]
- Ghosh, Atish R., Anne-Marie Gulde, and Holger C. Wolf. 2003. Exchange Rate Regimes: Choices and Consequences, 1st ed. MIT Press Books. Cambridge and London: The MIT Press, vol. 1, number 0262072408. [Google Scholar]
- Giovanni, Julian di, and Jay C. Shambaugh. 2008. The Impact of Foreign Interest Rates on the Economy: The Role of the Exchange Rate Regime. Journal of International Economics 74: 341–61. [Google Scholar] [CrossRef]
- Gouriéroux, Christian. 1997. ARCH Models and Financial Applications. Berlin: Springer. [Google Scholar]
- Guzman, Martin, Jose A. Ocampo, and Joseph E. Stiglitz. 2018. Real exchange rate policies for economic development. World Development 110: 51–62. [Google Scholar] [CrossRef]
- Ilzetzki, Ethan, Carmen M. Reinhart, and Kenneth S. Rogoff. 2017. Exchange Arrangements Entering the 21st Century: Which Anchor Will Hold? NBER Working Papers 23134. Cambridge: National Bureau of Economic Research, Inc. [Google Scholar]
- Ito, Takatoshi, Yuri N. Sasaki, and Kiyotaka Sato. 2005. Pass-Through of Exchange Rate Changes and Macroeconomic Shocks to Domestic Inflation in East Asian Countries. Japan Discussion Paper Series; Tokyo: Research Institute of Economy, Trade and Industry (RIETI). [Google Scholar]
- Johnson, Simon, Jonathan D. Ostry, and Arvind Subramanian. 2010. The Prospects for Sustained Growth in Africa: Benchmarking the Constraints. IMF Staff Papers 57, no. 1. Cambridge: National Bureau of Economic Research, Inc., pp. 119–71. [Google Scholar]
- Kapetanios, George, Hashem M. Pesaran, and Takashi Yamagata. 2011. Panels with non-stationary multifactor error structures. Journal of Econometrics 160: 326–48. [Google Scholar] [CrossRef]
- Keho, Yaya, and Miao Grace Wang. 2017. The impact of trade openness on economic growth: The case of Cote d’Ivoire. Cogent Economics and Finance 5: 1332820. [Google Scholar] [CrossRef]
- Kenen, Peter B., and Dani Rodrik. 1986. Measuring and analyzing the effects of short-term volatility in real exchange rates. The Review of Economics and Statistics 68: 311–15. [Google Scholar] [CrossRef]
- Khan, Mohsin S., Peter J. Montiel, and Bijan B. Aghevli. 1991. Exchange Rate Policy in Developing Countries: Some Analytical Issues. Washington: World Bank Publications, vol. 78. [Google Scholar]
- Kim, Hae-Young. 2013. Statistical notes for clinical researchers: Assessing normal distribution (2) using skewness and kurtosis. Restorative Dentistry & Endodontics 38: 52–54. [Google Scholar]
- Levine, Ross. 1997. Financial Development and Economic Growth: Views and Agenda. Journal of Economic Literature 35: 688–726. [Google Scholar]
- Levy-Yeyati, Eduardo, and Federico Sturzenegger. 2005. Classifying exchange rate regimes: Deeds vs. words. European Economic Review 49: 1603–35. [Google Scholar] [CrossRef]
- Mahapatra, Smita, and Saumitra N. Bhaduri. 2019. Dynamics of the impact of currency fluctuations on stock markets in India: Assessing the pricing of exchange rate risks. Borsa Istanbul Review 19: 15–23. [Google Scholar] [CrossRef]
- McKinnon, Ronald I. 1973. Money and Capital in Economic Development. Washington, DC: Brookings Institution. [Google Scholar]
- McKinnon, Ronald, and Gunther Schnabl. 2003. China: A Stabilizing or Deflationary Influence in East Asia? The Problem of Conflicted Virtue (May 26). Stanford Economics Working Paper No. 03007. Available online: https://ssrn.com/abstract=753385 or http://dx.doi.org/10.2139/ssrn.753385 (accessed on 5 October 2022).
- Miles, William. 2006. To Float Or Not To Float? Currency Regimes And Growth. Journal of Economic Development 31: 91–105. [Google Scholar]
- Mubarik, Yasir A., and Riaz Riazuddin. 2005. Inflation and Growth: An Estimate of the Threshold Level of Inflation in Pakistan. Karachi: State Bank of Pakistan. [Google Scholar]
- Mundell, Robert A. 1961. A Theory of Optimum Currency Areas. The American Economic Review 51: 657–65. [Google Scholar]
- Munir, Qaiser, Kasim Mansur, and Fumitaka Furuoka. 2009. Inflation and economic growth in Malaysia: A threshold regression approach. ASEAN Economic Bulletin, 180–93. [Google Scholar] [CrossRef]
- Obstfeld, Maurice, Jonathan D. Ostry, and Mahvash S. Qureshi. 2018. Global Financial Cycles and the Exchange Rate Regime: A Perspective from Emerging Markets. AEA Papers and Proceedings. Nashville: American Economic Association, vol. 108, pp. 499–504. [Google Scholar]
- Olimov, Ulugbek, and Nishanbay Sirajiddinov. 2008. The Effects of the Real Exchange Rate Volatility and Misalignments on Foreign Trade Flows in Uzbekistan. MPRA Paper 9749. Munich: University Library of Munich. [Google Scholar]
- Perée, Eric, and Alfred Steinherr. 1989. Exchange rate uncertainty and foreign trade. European Economic Review 33: 1241–64. [Google Scholar] [CrossRef]
- Perekunah, Bright. E. 2020. Exchange Rate Regimes and Foreign Direct Investment Flow in West African Monetary Zone (WAMZ). International Economic Journal 34: 85–99. [Google Scholar]
- Pesaran, Hashem M. 2003. A Simple Panel Unit Root Test in the Presence of Cross Section Dependence. Cambridge Working Papers in Economics 0346. Cambridge: Faculty of Economics, University of Cambridge. [Google Scholar]
- Pesaran, Hashem M. 2006. Estimation and Inference in Large Heterogeneous Panels with a Multifactor Error Structure. Econometrica 74: 967–1012. [Google Scholar] [CrossRef]
- Pesaran, Hashem M. 2007. A Simple Panel Unit Root Test in the Presence of Cross-Section Dependence. Journal of Applied Econometrics 22: 265–312. [Google Scholar] [CrossRef]
- Pesaran, Hashem M. 2015. Testing Weak Cross-Sectional Dependence in Large Panels. Econometric Reviews 34: 1089–117. [Google Scholar] [CrossRef]
- Pesaran, Hashem M., and Yongcheol Shin. 1996. Cointegration and speed of convergence to equilibrium. Journal of Econometrics 71: 117–43. [Google Scholar] [CrossRef]
- Pesaran, Hashem M., and Ron Smith. 1995. Estimating long-run relationships from dynamic heterogeneous panels. Journal of Econometrics 68: 79–113. [Google Scholar] [CrossRef]
- Pesaran, Hashem M., and Takashi Yamagata. 2008. Testing slope homogeneity in large panels. Journal of Econometrics 142: 50–93. [Google Scholar] [CrossRef]
- Pesaran, Hashem M., Yongcheol Shin, and Ron Smith. 1999. Pooled Mean Group Estimation of Dynamic Heterogeneous Panels. Journal of the American Statistical Association 94: 621–34. [Google Scholar] [CrossRef]
- Ramey, Garey, and Valerie A. Ramey. 1995. Cross-Country Evidence on the Link Between Volatility and Growth. The American Economic Review 85: 1138–51. [Google Scholar]
- Reinhart, Carmen M., and Kenneth Rogoff. 2004. The Modern History of Exchange Rate Arrangements: A Reinterpretation. Quarterly Journal of Economics 119: 1–47. [Google Scholar] [CrossRef]
- Rodney, Ramcharan. 2007. Does the exchange rate regime matter for real shocks ? Evidence from windstorms and earthquakes. Journal of International Economics 73: 31–47. [Google Scholar]
- Rogoff, Kenneth S., Aasim M. Husain, Ashoka Mody, Robin Brooks, and Nienke Oomes. 2003. Evolution and Performance of Exchange Rate Regimes. Working Paper N 243. Washington, DC: International Monetary Fund. [Google Scholar]
- Rose, Andrew K. 2000. One money, one market: The effect of common currencies on trade. Economic Policy 15: 8–45. [Google Scholar] [CrossRef]
- Samuelson, Paul A. 1964. Theoretical notes on trade problems. The Review of Economics and Statistics, 145–54. [Google Scholar] [CrossRef]
- Shaw, Edward S. 1973. Financial Deepening in Economic Development. New York: Oxford University Press. [Google Scholar]
- Swamy, Paravastu A. V. B. 1970. Efficient Inference in a Random Coefficient Regression Model. Econometrica 38: 311–23. [Google Scholar] [CrossRef]
- Syarifuddin, Ferry, Noer A. Achsani, Dedi B. Hakim, and Toni Bakhtiar. 2014. Monetary policy response on exchange rate volatility in Indonesia. Journal of Contemporary Economic and Business 1: 35–54. [Google Scholar]
- Westerlund, Joakim. 2007. Testing for Error Correction in Panel Data (0000). Oxford Bulletin of Economics and Statistics 69: 709–48. Available online: https://ssrn.com/abstract=1031259 (accessed on 5 October 2022). [CrossRef]
Variable | Measurements | Source | Observations |
---|---|---|---|
GDP | Real GDP per capita | World Bank database | Annual observations from 1990 to 2020 |
Exchange rate volatility | Real effective exchange rate (REER) volatility via GARCH Model | Bruegel database developed by Darvas (2021) | Monthly observations from 1990 to 2020 |
Degree of trade openness | (Exportations + importations)/GDP | World Bank database | Annual observations from 1990 to 2020 |
Inflation | Consumer price index (CPI) | World Bank database | Annual observations from 1990 to 2020 |
Foreign direct investment (FDI) | FDI/GDP | World Bank database | Annual observations from 1990 to 2020 |
Foreign debt | Total external debt/GNI | World Bank database | Annual observations from 1990 to 2020 |
Financial system development | M3/GDP | World Bank database | Annual observations from 1990 to 2020 |
Exchange Rate Regime | IRR Code |
---|---|
Fixed exchange rate regime (regime 1) | 1,2,3,4 |
Intermediate exchange rate regime (regime 2) | 5,6,7,8,9,10,11 |
Floating exchange rate regime (regime 3) | 12,13,14,15 |
Mean | Median | Std Dev | Skewness | Kurtosis | Jarque–Bera | ||
---|---|---|---|---|---|---|---|
REER return | Morocco | 0.000312 | −0.000237 | 0.008407 | 0.447027 | 12.54703 | 1425.15 *** |
Egypt | 0.003264 | 0.004749 | 0.021498 | −0.467962 | 7.125809 | 277.4230 *** | |
Turkey | −0.000486 | 0.003296 | 0.036726 | −1.537170 | 11.20015 | 1188.758 *** | |
Brazil | −0.001072 | 0.000124 | 0.041902 | −0.886052 | 7.807281 | 406.8797 *** | |
China | 0.001162 | 0.001925 | 0.015185 | −2.176065 | 16.64212 | 3178.250 *** | |
South Africa | −0.000930 | 0.000582 | 0.030645 | −0.540152 | 6.156610 | 172.5343 *** | |
Thailand | 0.00326 | 0.001560 | 0.020634 | −1.293796 | 26.15978 | 8417.601 *** | |
Tunisia | −0.000909 | −0.000544 | 0.009571 | −0.411172 | 8.354141 | 454.8176 *** | |
Nigeria | 0.004832 | 0.007129 | 0.039589 | −4.194360 | 44.00281 | 27149.81 *** | |
Indonesia | −0.000210 | 0.000742 | 0.053708 | −3.735562 | 50.14433 | 35315.28 *** | |
Mexico | 0.003837 | 0.122708 | −3.247965 | 29.85828 | 11835.25 *** | ||
Jordan | 0.000946 | 0.000367 | 0.014151 | 0.517037 | 4.209452 | 39.24729 *** | |
Peru | −0.000414 | 0.001146 | 0.035408 | −5.040494 | 56.22029 | 45477.93 *** | |
Bolivia | 0.000752 | 0.000383 | 0.011745 | 0.256123 | 3.515384 | 8.184254 *** |
Trend and Intercept | Intercept | None | |||||
---|---|---|---|---|---|---|---|
T-Stat | Prob. | T-Stat | Prob. | T-Stat | Prob. | ||
REER Return | Morocco | −21.78205 | 0.0000 | −21.74081 | 0.0000 | −21.73509 | 0.0000 |
Egypt | −13.39497 | 0.0000 | −13.40213 | 0.0000 | −9.360131 | 0.0000 | |
Turkey | −13.00595 | 0.0000 | −12.95937 | 0.0000 | −12.97487 | 0.0000 | |
Brazil | −13.74271 | 0.0000 | −13.75004 | 0.0000 | −13.76528 | 0.0000 | |
China | −16.80247 | 0.0000 | −16.84384 | 0.0000 | −16.71348 | 0.0000 | |
South Africa | −15.62128 | 0.0000 | −15.64262 | 0.0000 | −15.65239 | 0.0000 | |
Thailand | −14.07934 | 0.0000 | −14.07730 | 0.0000 | −14.09324 | 0.0000 | |
Tunisia | −14.56372 | 0.0000 | −14.54470 | 0.0000 | −14.46113 | 0.0000 | |
Nigeria | −13.55185 | 0.0000 | −13.46698 | 0.0000 | −13.23501 | 0.0000 | |
Indonesia | −16.48059 | 0.0000 | −16.49835 | 0.0000 | −16.52051 | 0.0000 | |
Mexico | −15.1429 | 0.0000 | −15.14028 | 0.0000 | −15.16076 | 0.0000 | |
Jordan | −14.34529 | 0.0000 | −14.36668 | 0.0000 | −14.33124 | 0.0000 | |
Peru | −13.37768 | 0.0000 | −13.37742 | 0.0000 | −13.39030 | 0.0000 | |
Bolivia | −12.33671 | 0.0000 | −12.25317 | 0.0000 | −12.22659 | 0.0000 |
Heteroskedasticity Test: ARCH | |||||
---|---|---|---|---|---|
F-Statistic | Prob. F | Obs Rsquared | Prob. Chi Square | ||
REER return | Morocco | 17.29655 | 0.0000 | 16.61164 | 0.0000 |
Egypt | 6.922622 | 0.0089 | 6.831971 | 0.0090 | |
Turkey | 13.03979 | 0.0003 | 12.66298 | 0.0004 | |
Brazil | 58.22206 | 0.0000 | 50.56009 | 0.0000 | |
China | 6.557652 | 0.0108 | 6.478070 | 0.0109 | |
South Africa | 3.915363 | 0.0486 | 3.895253 | 0.0484 | |
Thailand | 46.35219 | 0.0000 | 41.40260 | 0.0000 | |
Tunisia | 29.32515 | 0.0000 | 27.31344 | 0.0000 | |
Nigeria | 5.442191 | 0.0202 | 5.392162 | 0.0202 | |
Indonesia | 99.44115 | 0.0000 | 78.75625 | 0.0000 | |
Mexico | 26.86426 | 0.0000 | 26.17691 | 0.0000 | |
Jordan | 4.000524 | 0.0462 | 3.979068 | 0.0461 | |
Peru | 19.92205 | 0.0000 | 19.00401 | 0.0000 | |
Bolivia | 4.683871 | 0.0311 | 4.650231 | 0.0310 |
Validation Tests of the GARCH (1.1) Model | ||||
---|---|---|---|---|
Q (20) | Q2 (20) | ARCH 1-10 | ||
REER Return | Morocco | 18.3329 (0.4339347) | 11.3275 (0.8799475) | 0.90473 (0.5295) |
Egypt | 15.4577 (0.6303388) | 14.2312 (0.7139015) | 1.2186 (0.2775) | |
Turkey | 19.5698 (0.3575539) | 5.49497 (0.9978522) | 0.28138 (0.9848) | |
Brazil | 23.3262 (0.1783642) | 13.6104 (0.7541156) | 0.43752 (0.9270) | |
China | 10.0384 (0.2623423) | 16.8055 (0.5365104) | 1.2018 (0.2884) | |
South Africa | 19.6164 (0.4179836) | 19.7298 (0.3482343) | 1.1029 (0.3589) | |
Thailand | 16.9175 (0.5287857) | 17.6937 (0.4759965) | 1.0546 (0.3987) | |
Tunisia | 21.1785 (0.3270212) | 23.5922 (0.1688471) | 1.3031 (0.2271) | |
Nigeria | 18.9419 (0.3954077) | 20.2343 (0.3197841) | 0.30567 (0.9792) | |
Indonesia | 23.7845 (0.1622139) | 12.1431 (0.8397614) | 0.59759 (0.8151) | |
Mexico | 19.2688 (0.3754485) | 8.37274 (0.9725557) | 0.32059 (0.9755) | |
Jordan | 19.5176 (0.3606243) | 10.8110 (0.9022039) | 0.61233 (0.8027) | |
Peru | 19.5529 (0.1622139) | 9.01299 (0.9594410) | 0.75130 (0.6758) | |
Bolivia | 21.1850 (0.2701801) | 12.9625 (0.7937978) | 0.64689 (0.7732) |
CD-Test for Cross-Sectional Dependence | |||
---|---|---|---|
Variables | CD-Test | p-Value | Average Joint T |
Log GDP | 48.763 | 0.000 | 31.00 |
Log REER volatility | 3.291 | 0.001 | 31.00 |
Log degree of openness | 17.985 | 0.000 | 31.00 |
Log CPI | 48.77 | 0.000 | 31.00 |
Log M3/GDP | 22.18 | 0.000 | 31.00 |
Log foreign debt | 17.28 | 0.000 | 31.00 |
Log FDI/GDP | 11.207 | 0.000 | 31.00 |
Swamy’s Test | Pesaran and Yamagata’s Test | ||
---|---|---|---|
Chi-2 (91) | 33,126.27 (0.000) | Delta | 14.745 (0.000) |
Delta adj. | 17.118 (0.000) |
CIPS Test | CADF Test | |||
---|---|---|---|---|
Variables | Level | First Difference | Level | First Difference |
Log GDP | −1.898 (−2.44) | −3.559 *** (−2.45) | −1.898 (0.306) | −3.559 (0.000) |
Log REER volatility | −3.643 *** (−2.44) | − | −3.643 (0.000) | − |
Log degree of openness | −1.436 (−2.44) | −4.506 *** (−2.45) | −1.436 (0.908) | −4.506 (0.000) |
Log CPI | −1.872 (−2.44) | −4.307 *** (−2.45) | −1.872 (0.342) | −4.307 (0.000) |
Log M3/GDP | −2.235 ** (−2.25) | − | −2.235 (0.032) | − |
Log foreign debt | −2.905 *** (−2.44) | − | −2.905 *** (0.000) | − |
Log FDI/GDP | −3.110 *** (−2.44) | − | −3.110 *** (0.000) | − |
Statistics | Value | Z-Value | Robust p-Value |
---|---|---|---|
Gt | −0.199 | 8.169 | 0.820 |
Ga | −0.646 | 5.926 | 0.030 |
Pt | −0.203 | 6.493 | 0.020 |
Pa | −0.055 | 4.253 | 0.040 |
Common Correlated Effects Estimator–(CS-ARDL Panel) | |||
---|---|---|---|
Variables | Coefficients | Std. Err | p-Value |
Short-run estimation | |||
L.Log GDP | 0.5158881 | 0.0809883 | 0.000 *** |
Log REER volatility | −0.0134248 | 0.0073008 | 0.066 * |
Log degree of openness | −0.0088341 | 0.0197377 | 0.654 |
Log CPI | −0.1736491 | 0.081663 | 0.033 ** |
Log FDI/GDP | 0.0090205 | 0.0033645 | 0.007 *** |
Log foreign debt | −0.0170404 | 0.008012 | 0.033 ** |
L.Log M3/GDP | 0.092221 | 0.0252932 | 0.000 *** |
Long-run estimation | |||
Log REER volatility | −0.0751851 | 0.0383397 | 0.050 ** |
Log degree of openness | 0.020038 | 0.0652003 | 0.759 |
Log CPI | −0.3716829 | 0.1441866 | 0.010 *** |
Log FDI/GDP | 0.0307217 | 0.0121971 | 0.012 ** |
Log foreign debt | −0.0308979 | 0.0228938 | 0.177 |
Log M3/GDP | 0.2546056 | 0.1137025 | 0.025 ** |
Dumitrescu and Hurlin (2012) Granger Non-Causality Test | |||
---|---|---|---|
W-Bar | Z-Bar | Z-Bar Tilde | |
Log REER Volatiliy | |||
Log CPI | 3.6245 | 6.9438 *** (0.0000) | 5.8628 *** (0.0000) |
Log FDI/GDP | 1.8573 | 2.2682 ** (0.0233) | 1.7910 * (0.0733) |
Log foreign debt | 2.5267 | 4.0392 *** (0.0001) | 3.3333 *** (0.0009) |
Log M3/GDP | 2.1524 | 3.0490 *** (0.0023) | 2.4710 ** (0.0135) |
Common Correlated Effects Estimator–(CS-ARDL) | |||||||||
---|---|---|---|---|---|---|---|---|---|
Variables | Fixed ERR | Intermediate ERR | Floating ERR | ||||||
Coeff | Std. Err | p-Value | Coeff | Std. Err | p-Value | Coeff | Std. Err | p-Value | |
Short-run estimation | |||||||||
L.Log GDP | 0.6182333 | 0.1716174 | 0.000 *** | 0.8587536 | 0.0512364 | 0.000 *** | 0.4402354 | 0.137329 | 0.001 *** |
Log REER volatility | −0.0579011 | 0.0021231 | 0.000 *** | −0.0039421 | 0.0040626 | 0.332 | −0.0171749 | 0.0094374 | 0.069 * |
Log degree openness | 0.3722057 | 0.0341857 | 0.000 *** | −0.1523318 | 0.0109061 | 0.000 *** | 0.1006791 | 0.0413309 | 0.015 ** |
Log CPI | 0.3420491 | 0.0602633 | 0.000 *** | −0.5102768 | 0.1253434 | 0.000 *** | −0.0841091 | 0.0312508 | 0.007 *** |
Log FDI/GDP | 0.0055867 | 0.0083584 | 0.504 | 0.0365185 | 0.0041678 | 0.000 *** | 0.0063403 | 0.0045638 | 0.165 |
Log foreign debt | 0.0213044 | 0.0117241 | 0.069 * | 0.0482735 | 0.00937 | 0.000 *** | 0.0037782 | 0.0189084 | 0.842 |
L.Log M3/GDP | 0.3395888 | 0.0064759 | 0.000 *** | 0.2555339 | 0.0722258 | 0.000 *** | −0.0298541 | 0.0497969 | 0.549 |
Long-run estimation | |||||||||
Log REER volatility | −0.1869441 | 0.0784766 | 0.017 *** | −0.0441529 | 0.0447785 | 0.324 | −0.0231588 | 0.0113464 | 0.041 ** |
Log degree of openness | 1.272323 | 0.6614994 | 0.054 * | −1.209643 | 0.3615779 | 0.001 *** | 0.1931079 | 0.0726293 | 0.008 *** |
Log CPI | 1.211809 | 0.7026037 | 0.085 * | −4.530748 | 2.530914 | 0.073 * | −0.2583357 | 0.1786905 | 0.148 |
Log FDI/GDP | 0.006005 | 0.0191947 | 0.754 | 0.310045 | 0.1419746 | 0.029 ** | 0.0150599 | 0.0074 | 0.042 ** |
Log foreign debt | 0.0526364 | 0.0070482 | 0.000 *** | 0.4212627 | 0.2191484 | 0.055 * | −0.0305881 | 0.0521901 | 0.558 |
Log M3/GDP | 1.124356 | 0.5224001 | 0.031 ** | 2.296852 | 1.344517 | 0.088 * | −0.0753632 | 0.1188511 | 0.526 |
Dumitrescu and Hurlin (2012) Granger Non-Causality Test | |||||||||
---|---|---|---|---|---|---|---|---|---|
Fixed ERR | Intermediate ERR | Floating ERR | |||||||
Log REER Volatiliy | |||||||||
W-Bar | Z-Bar | Z-Bar Tilde | W-Bar | Z-Bar | Z-Bar Tilde | W-Bar | Z-Bar | Z-Bar Tilde | |
Log degree of openness | 1.5106 | 1.0212 (0.3072) | 0.7500 (0.4533) | 1.3476 | 0.8863 (0.3754) | 0.5943 (0.5523) | 1.1000 | 0.2122 (0.8319) | 0.0370 (0.9705) |
Log CPI | 4.2536 | 6.5072 (0.0000) | 5.5276 (0.0000) | 3.4688 | 6.2941 (0.0000) | 5.3037 (0.0000) | 5.1013 | 8.7003 (0.0000) | 7.4290 (0.0000) |
Log FDI/GDP | - | - | - | 1.6630 | 1.6902 (0.0910) | 1.2943 (0.1956) | 2.5985 | 3.3908 (0.0007) | 2.8052 (0.0050) |
Log foreign debt | 3.9612 | 5.9223 (0.0000) | 5.0182 (0.0000) | 2.6410 | 4.1838 (0.0000) | 3.4659 (0.0005) | - | - | - |
Log M3/GDP | 0.6316 | −0.7368 (0.4613) | −0.7810 (0.4348) | 1.8304 | 2.1172 (0.0342) | 1.6662 (0.0957) | - | - | - |
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Ameziane, K.; Benyacoub, B. Exchange Rate Volatility Effect on Economic Growth under Different Exchange Rate Regimes: New Evidence from Emerging Countries Using Panel CS-ARDL Model. J. Risk Financial Manag. 2022, 15, 499. https://doi.org/10.3390/jrfm15110499
Ameziane K, Benyacoub B. Exchange Rate Volatility Effect on Economic Growth under Different Exchange Rate Regimes: New Evidence from Emerging Countries Using Panel CS-ARDL Model. Journal of Risk and Financial Management. 2022; 15(11):499. https://doi.org/10.3390/jrfm15110499
Chicago/Turabian StyleAmeziane, Karim, and Bouchra Benyacoub. 2022. "Exchange Rate Volatility Effect on Economic Growth under Different Exchange Rate Regimes: New Evidence from Emerging Countries Using Panel CS-ARDL Model" Journal of Risk and Financial Management 15, no. 11: 499. https://doi.org/10.3390/jrfm15110499
APA StyleAmeziane, K., & Benyacoub, B. (2022). Exchange Rate Volatility Effect on Economic Growth under Different Exchange Rate Regimes: New Evidence from Emerging Countries Using Panel CS-ARDL Model. Journal of Risk and Financial Management, 15(11), 499. https://doi.org/10.3390/jrfm15110499