Abstract
This paper explores and quantifies several aspects of the performance of Africa's currency unions. It benchmarks Africa's experience with that of the world using an augmented version of the gravity model and applying a comprehensive set of robustness checks. The empirical findings suggest that membership in a currency union should benefit Africa as much as it does the rest of the world. In addition, for both samples, we find evidence that (1) there is a significant currency union trade-generating effect; (2) currency unions are associated with trade creation and increased price comovements among member countries; and (3) the duration of currency union membership matters for trade: longer duration brings about greater benefits, and vice versa, however with some diminishing returns.
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Notes
Initially, these models were criticized for lacking a proper theoretical justification. Anderson (1979) and Bergstrand (1985) were the first formal attempts to address this criticism and derived the gravity equation theoretically. Deardorff (1998) provides a comprehensive overview of the gravity model and shows that a variety of theoretical models can be tied to it. Similarly, Feenstra, Markusen, and Rose (2001) argue that gravity models are consistent with several theoretical models of trade.
See Baldwin (2005) for a comprehensive review of the literature and relevant issues on currency unions and trade.
Figure A1 lists African regional economic integration arrangements. See Masson and Pattillo (2004) for a detailed discussion of currency unions in Africa.
However, he acknowledges that the effect may be smaller for modern industrial countries; most currency unions in Rose (2000) comprise small or poor countries or both.
Rose (2004) performs a “meta-analysis” of the currency union effect by combining estimates from 34 other studies and estimates a range of 30 to 90 percent for the currency union effect.
See Collier (1995), Rodrik (1998), Yeats (1998), Collier and Gunning (1999), Limão and Venables (2001), and Subramanian and Tamirisa (2003) for a detailed discussion on this issue.
However, the currency union variable used by Masson and Pattillo (2004) uses the FTA definition from Glick and Rose (2002), which does not distinguish between FTA and currency union effects. We overcome this limitation by constructing separate variables for FTA and currency unions, and identify their impacts separately.
The definition of “currency union,” following Glick and Rose (2002), implies that money is interchangeable between the two countries at a 1:1 par for an extended period of time, so that there is no need to convert prices when trading between a pair of countries. Under this definition, hard fixes are not identified as currency unions. Further, the definition of currency union is transitive: if country pairs X, Y and X, Z are in a currency union, then Y and Z are in a currency union.
Because the sample period of our data set begins in 1948, we ignore years spent in a currency union before 1948.
For details on the “classic gravity model mistakes,” see Baldwin (2005) and Frankel (2005).
Anderson and van Wincoop (2003) use the national price indices (P i and P j ) to account for “multilateral resistance” between countries i and j, which can be estimated using an iterative process. However, because the estimation process is complex, they propose an alternative method that is preferable for empirical work: namely, estimating implicit prices by fixed effects, that is, by including country-specific dummy variables.
However, the instrument applied by Alesina and Tenreyro (2002) is not designed for multilateral currency unions.
The CFA franc zone and the Common Monetary Area were formed, in large part, due to the political self-interest of the major powers (France in the former case, and South Africa in the latter).
The issue of nonlinearities is also discussed in Baldwin (2005). See Frankel (2005) for a justification of using the “pooled” export-import specification. The treatment of zero-trade observations in the estimation is discussed in detail in Santos Silva and Tenreyro (2006).
Greene (1981) shows that the size of the “truncation bias” when the variables are distributed normally is inversely proportional to the “proportion of nonlimit observations in the sample,” but this bias decreases when the fit of the model improves or the regressors have a skewed distribution.
Jensen's inequality implies that even if the expected value of the error term obtained from Equation (1) is 0, E[log X ij ∣Z ij ] is not essentially equivalent to exp(E[X ij ∣Z ij ]). The possible bias in the presence of heteroskedasticity can be mitigated with the use of heteroscedasticity-robust standard errors in the estimations.
Political units include overseas territories, parts of kingdoms, possessions, self-governing territories in free association with another country, unincorporated territories, and crown dependencies.
Henceforth, unless stated otherwise, our panel and PML estimates include country-pair fixed effects along the lines of Glick and Rose (2002), as well as time effects. In addition, country fixed effects were also used to account for the Anderson and van Wincoop (2003) “multilateral resistance” factor in pooled OLS estimations and are available from the authors on request. In the interest of clarity, we do not show results of all the pooled OLS country fixed effects estimates in Tables 1, 2 and 3, but some are summarized in Table 4.
Masson and Pattillo (2004) also estimate the gravity equation for Africa. However, their results may not be directly comparable to ours because they do not take into account free trade areas operating in Africa.
Although we estimate both fixed effects “within” and random effects, we rely on the robust fixed effects within estimator as suggested by the Hausman test.
To explore this issue in detail, we “decompose” the trade-generating coefficient for the world sample into the coefficients of two homogeneous groups—the industrialized and nonindustrialized countries—using fixed effects within estimator and PML. The results suggest that the PML technique is more sensitive to sample homogeneity than the other estimator. Thus, for example, the estimated coefficient for the currency union variable obtained from PML (fixed effects) is 0.14 (0.37) and 1.07 (0.51) for the industrialized and nonindustrialized groups, respectively. The world weighted average of 0.15 under PML appears to be influenced by the industrialized group average, and hence is smaller in magnitude. It is worth pointing out here that some other studies that estimate the gravity model using PML also obtain smaller estimated coefficients vis-à-vis other techniques, such as Tobit (see, for example, Amurgo-Pacheco and Pierola, 2008).
However, when we decompose the world sample into homogeneous groups we find that for the nonindustrialized group the trade creation effect is significantly positive (0.22), but a trade diversion effect exists for the industrialized group. As discussed in footnote 21, it appears that the PML result for the world in this case is also influenced by the industrial group observations.
To compare our results with those obtained by Alesina and Tenreyro (2002) we set the constant equal to 100. The dependent variable therefore becomes log(100+X ij ).
See Amemiya (1984) for a detailed discussion on this issue.
See Tables A2, A3 and A4 for the number of identified currency union dissolutions for the world and Africa samples.
The horizontal lines in Figures 1 and 2 correspond to the estimate of the coefficient of the currency union dummy (namely, the γ coefficient in equation (1) extended to include the vector of lagged variables described in the text) for the world and Africa, respectively. The 95 percent confidence intervals are also included.
The equations are estimated using the average values of the period 1948–2003 and pooled OLS. Because we cannot use panel estimation here, we account for country fixed effects as in Anderson and Van Wincoop (2003).
As discussed in Alesina and Tenreyro (2002), increased interindustry trade may stimulate sectoral specialization and lead to less output comovement, but intra-industry trade is likely to increase their comovement.
For trade stability, we estimate the model with various measures of stability, including the maximum absolute value, mean absolute value, and standard deviation of the residual from a conventional gravity equation of exports in levels. Results are available on request.
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Additional information
*Charalambos Tsangarides is an economist in the IMF's Research Department; Pierre Ewenczyk is a senior economist with the IMF's Offices in Europe; Michal Hulej is an economist at the National Bank of Poland; and Mahvash Saeed Qureshi is an economist in the IMF's African Department. The authors thank the editor, the anonymous referees, Xavier Debrun, Anne-Marie Gulde, Catherine Pattillo, Andrew Rose, Sylvana Tenreyro, and João Santos Silva for helpful comments and suggestions.
Appendix I
Appendix I
See Tables A1, A2, A3 and A4 and Figure A1.
Main African Regional and Subregional Economic Integration Arrangements (as of August 2005)