Aghion P., P. Bacchetta, R. Ranciere, and K. Rogoff, 2009, “Exchange Rate Volatility and Productivity Growth: The Role of Financial Development,” Journal of Monetary Economics, 56, pp. 494–513.
Azis, I.J., and N. Puttanapong, 2008, “A Regional Trend Towards a Basket Peg System,” Trade and Global Markets, Vol. 1, No. 2, pp. 144–162.
Bagella M., L. Becchetti, and I. Hasan, 2006, “Real effective exchange rate volatility and growth: A framework to measure advantages of flexibility vs. costs of volatility,” Journal of Banking & Finance, 30, pp. 1149–1169.
Bird, G., R. Rajan, 2002, “Optimal Currency Baskets and the Third Currency Phenomenon: Exchange Rate Policy in South East Asia,” Journal of International Development, 14, 1053– 1073.
Branson, W., L. Katseli, 1981, “Currency Baskets and Real Effective Exchange rates,” NBER Working Paper 666 (Cambridge, MA: National Bureau of Economic Research).
Crockett, A. D., and S. M. Nsouli, 1977, “Exchange Rate Policies for Developing Countries,” Journal of Development Studies, 13:2, 125–143.
Duarte, M., D. Restuccia, and A. Waddle, 2007, “Exchange Rates and Business Cycles across Countries,” Federal Reserve Bank of Richmond, Economic Quarterly, Volume 93 (1), pp. 57–76.
Gunther, S., 2007, “Exchange Rate Volatility and Growth in Small Open Economies at the EMU Periphery,” The ECB Working Paper Series No. 773 (Frankfurt: European Central Bank).
Ito, T., E. Ogawa, and S. Nagataki, 1998, “How Did the Dollar Peg Fail in Asia?” Journal of the Japanese and International Economies, 12, 256–304.
Mohtadi, S., 1988, “The Stabilization of the Effective Exchange Rates of the Less Developed Countries under Alternative Exchange Rate Arrangements,” Journal of Economic Development, Vol. 13, No. 1.
Rey, S., 2006, “Effective Exchange Rate Volatility and MENA Gountries’ Exports to the EU,” Journal of Economic Development, 23, Vol. 31, No. 2.
Rogoff, K., A. Hussain, A. Mody, R. Brooks, and N. Oomes, 2003, “Evolution and Performance of Exchange Rate Regimes,” IMF Working Paper No. 03/243 (Washington: International Monetary Fund).
Slavov, S.T., 2008, “Should Small Open Economies in East Asia Keep All Their Eggs in One Basket: The Role of Balance Sheet Effects,” The Journal of the Korean Economy, Vol. 9, No. 1, pp. 1–43.
Williamson, J., 1996, “The Case for a Common Basket Peg for East Asian Currencies,” Exchange Rate Policies in Emerging Asian Countries: Domestic and International Aspects, Association for the Monetary Union of Europe and the Korea Institute of Finance.
I am grateful to Norbert Funke for his valuable input from the early stage of this project. I would like to thank Christina Daseking, Montfort Mlachila, Roger Nord, Philippe Wingender, the WAEMU team (Alexei Kireyev and Christina Kolerus in particular), and seminar participants in the African Department’s External Sector Network at the IMF for useful comments and suggestions, and Jenny DiBiase for helpful editorial comments. Thanks are also due to seminar participants at the Central Bank of West African States (BCEAO) in Dakar, and at the WAEMU Commission in Ouagadougou for useful comments on preliminary findings of the paper during the 2011 IMF’s multilateral surveillance discussions with WAEMU member countries. The usual caveat applies.
The selection bias may arise from the fact that countries that adopt flexible exchange rate regimes have relatively well-developed financial markets. Now, because financial markets are growth-enhancing and also help smooth-out consumption—through the sale and purchase of financial instruments—countries with flexible exchange rate regimes will tend to display both higher growth rates and lower growth volatility in the data.
The nominal effective exchange rate (NEER) corresponds to the value of a home country’s currency compared to the currencies of its trading partners, weighted by their trade shares. The real effective exchange rate (REER) adjusts the NEER by the price differentials between the home country and its trading partners.
Although the authors focus on the REER, their findings are also relevant for this paper, which focuses on the NEER, given that Duarte, Restuccia, and Waddle (2007) document a very strong co-movement between the NEER and REER, with the correlation ranging from 0.76 for developing countries to 0.92 for developed countries. See Section II.B for detailed WAEMU-related evidence.
The diversification of trade patterns is a positive development in general, as it may allow the domestic country to partially edge against trading partners’ idiosyncratic shocks.
The WAEMU includes eight countries in West Africa: Benin, Burkina Faso, Côte d’Ivoire, Guinea Bissau (which joined the union only in 1998), Mali, Niger, Senegal, and Togo.
The weights were 41.9 percent for the US dollar, 37.4 percent for the euro, 11.3 percent for the pound, and 9.4 percent for the Japanese yen, as of December 2010.
The third currency phenomenon is a situation whereby changes in the exchange rate of the anchor vis-à-vis other currencies translate into changes in the domestic currency’s effective exchange rate.
The CEMAC (Central African Economic and Monetary Community) includes Cameroon, Chad, Equatorial Guinea, Gabon, the Central African Republic, and the Republic of Congo.
The upward trend in the NEER and the REER appears more clearly when one portrays the post-1994 episode separately (see right panel).
P and P* represent the domestic and foreign prices respectively, and E is the nominal effective exchange rate.
The steps of the proof are the following: (i) take the logarithm of the above expression; (ii) split the sample of trading partners into two groups: one group made of countries that share the anchor currency i*, and another group with the remainder countries; and (iii) use the relation
The equation assumes no month-to-month changes in trade shares because trade data is not available at monthly frequency. This is somewhat innocuous for the analysis because a country’s trade shares are unlikely to change substantially in such a short time. The trade shares (Øi, wi*) in a given month are set at the corresponding annual figure. Although trade weights do not change on a monthly basis, their levels do affect the volatility of the effective exchange rate and are accounted for in the set-up (second term in the right hand side).
Time subscripts have been dropped for clarity.
Partner countries on the list cover on average three-quarters of individual WAEMU countries’ trade.
In evaluating Equation (*), I netted out intraregional trade and recomputed partner countries trade shares accordingly. This is because, as explained above, the monetary union is treated as a whole in this paper.
This corresponds technically to setting wi* = 0 (which also implies that Øi = wi) in Equation (*).
The SDR peg, however, yields a slightly lower NEER volatility than the current euro peg during the first two decades of the sample period.
The Figures presented in Table 3 are standard deviations, and the statistical tests are based on differences in the corresponding variances.
In principle, the dynamics of trade patterns would have been different from what was observed, had the WAEMU pegged its currency to a basket. Assuming that one advantage of hard peg is to enhance trade flows with the anchor country (all else being equal), the shifts in trade patterns would probably have been more substantial under a basket peg. Table 3 therefore provides a lower bound to the volatility differential between the euro peg and the SDR peg.
The results are robust to the frequency at which the volatilities are computed, within the above-identified sub-periods.
I restrict the focus to that episode for three main reasons: (i) results in Table 3 suggest that before 2001, the volatilities under the two alternative peg arrangements were not significantly different; (ii) this prevents us from dealing with the structural break caused by the devaluation that occurred earlier in 1994; and (iii) the appreciation of the effective exchange rates has become a source of concern since the devaluation, particularly since the early 2000s.
The results are not very sensitive to the choice of sub periods. It is also worth noticing that, although the ratio of volatilities during Jan 1999—Dec 2000 is close to the corresponding ratio during Jan 2001—Dec 2007, the former is not found to be statistically different from 1, whereas the latter is. This is because a larger sample size provides more confidence for rejecting the null hypothesis of equal volatilities.
Note, however, that the difference is only statistically significant in the latter part of the sample (2000–10).
I also make all the above computations with imports weights separately, and the volatility differential between the two types of peg arrangements appears to be even larger.
It is also made in the standard computation of the NEER and the REER.
Slavov (2008) reports a similar data issue.