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The Euro and the CFA Franc: Evidence of Sectoral Trade Effects

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Abstract

This paper estimates a gravity model of trade to evaluate the trade effects of the Euro on sectoral trade within the Eurozone (EZ), the CFA Franc Zone (CFA) and between the EZ and the CFA, when CFA countries acquired fixed rates against the non-francophone EZ members. The formation of the EZ provides a quasi-natural experiment to estimate the effects on trade of fixed exchange rates, since the change in exchange rate regime for CFA countries with all EZ countries but France was not trade related. This is tested using sectoral trade data for 175 countries over the period 1995–2016 and validated using a longer time period starting in the seventies. The main departure from Frankel (2008), is the estimation of a structural gravity model using sectoral trade and bilateral-sectoral fixed effects as well as controls for multilateral resistance, namely time varying country-sector fixed-effects for exporters and importers, in a PPML framework. The main results indicate that the introduction of the Euro does show positive and significant effects for export flows from the CFA to other EZ countries different from France, whereas exports in the opposite direction are negatively affected. Moreover, the results differ by sector and we find that agricultural and homogeneous goods exports from CFA countries to Euro adopters increased by around forty and hundred twenty percent, respectively after the euro adoption.

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Notes

  1. CFA is the acronym for Communauté Financière Africaine (African Financial Community) - See more at: http://africanbusinessmagazine.com/uncategorised/a-brief-history-of-the-cfa-franc/#sthash.OcjOKe7i.dpuf.

  2. Convertibility is still today guaranteed by France and, ultimately, by the European Central Bank. CFA countries must deposit half of their foreign-exchange reserves with the French treasury and French delegates are part of the CFA central banks’ boards (The Economist 2018).

  3. Rose (2017) explains the high variation in the estimates of the EMU effect by examining systematic biases in MRT.

  4. Defined according to Rauch (1999) classification.

  5. In 2012 consisting of Benin, Burkina Faso, Ivory Coast, Guinea-Bissau, Mali, Niger, Senegal and Togo. See Appendix Table 4.

  6. In 2012 consisting of Cameroon, Central African Republic, Chad, Republic of Congo, Equatorial Guinea and Gabon.

  7. Since the last devaluation of the CFA Franc in 1994, the fixed exchange rates are FF 1 = CFA 100 and Euro 1 = CFA 655.957.

  8. However, the central banks of the two CFA monetary unions decided in 1993 that notes presented outside the unions could not be exchanged (Carrere 2004).

  9. The CFA Franc lost 50% of its value. One French Franc was worth 50 CFA Francs before the devaluation and 100 after. It was an important shock for the CFA economies, which led to a high increase in the price of imported goods and deteriorated the living standards of the population in the short run.

  10. Given the one to one convertibility between both CFA francs and the fact that France is the anchor currency with significant influence on the central bank policy for both currencies, one might also consider the two monetary unions of the CFA as one large currency union. In the core of this study, we do not distinguish between both currency unions and treat the CFA Franc as a single currency union. We add as robustness check an estimation of separated effects for both areas.

  11. See survey papers on the relationship between exchange rate volatility and trade from McKenzie (1999), Ozturk (2006), Bahmani-Oskooee and Hegerty (2007) and Auboin and Ruta (2011).

  12. An excellent overview of the literature can be found in Baldwin (2006).

  13. Baldwin et al. (2005) and Flam and Nordström (2006) estimate sectoral effects for the adoption of the Euro.

  14. See Mayer and Zignago (2011) for a more detailed description.

  15. Given the inclusion of time-variant MRT, the GDP coefficients are not identified in the estimations. Hence, the GDP variables included in the traditional gravity model of trade are dropped.

  16. EZ excludes France.

  17. Dummy variables identifying trade flows between the Eurozone and the CFA take the value zero if the exporting or importing country is France as these flows are identified by additional variables. We have separated the Euro effect from the common currency effect in the model specification by including a Euro dummy and excluding the Eurozone from the common currency dummy. Moreover, the intraCFA and the FranceCFA dummies only take the value of 1 after 1999 to compare trade within these groups before and after adoption of the Euro.

  18. The currency union dummy variable takes the value zero when both countries are members of the CFA as the dummy variable for mutual CFA Zone membership already captures this.

  19. The PPML algorithm dramatically improves computational speed when including a full set of fixed effects in comparison with other available methods.

  20. The percentage change in trade is calculated as 195 = (exp(1.082)-1)*100 using the coefficient of the intraCFA dummy in column (2) of Table 2.

  21. Estimates of the Euro effect in columns (3) and (4) are slightly higher to Glick and Rose (2016) in Table 5, columns (3) and (5).

  22. The volume effect can be calculated in percentage terms using the estimate of the EURO variable in column (4) of Table 2 as [EXP(0.346)-1] = 0.413.

  23. For completeness column (4) reports the original estimates in Frankel (2008): Table 7A in page 31, with a comparable model specification to column (1) using our dataset and including distance. However, Frankel (2008) dataset is for the period 1948–2006 and his dependent variable is a country- pair’s total bilateral trade, rather than unidirectional exports. Moreover, Frankel does not include distance, importer or exporter fixed effects in his gravity equation.

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Acknowledgements

Financial support received from the Spanish Ministry of Economy and Competitiveness, Project ECO2017-83255-C3-3-P (AEI, FEDER, EU) and from project UJI-B2017-33 is gratefully acknowledged. I also would like to thank the editor and the anonymous referee for their helpful comments and suggestions.

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  1. Georg-August Universität Göttingen, Göttingen, Germany

    Inmaculada Martínez-Zarzoso

  2. Universitat Jaume I, Castellón, Spain

    Inmaculada Martínez-Zarzoso

  3. Department of Economics, University of Goettingen, 37073, Goettingen, Germany

    Inmaculada Martínez-Zarzoso

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Appendix

Appendix

Table 4 List of countries
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Table 5 List of sectors and codes
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Table 6 Variable, description and sources
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Table 7 Replication of Table 7A in Frankel (2008) with sectoral data
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Table 8 Estimation results for the extended period with PPML
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Table 9 Estimation results for extended period including separated effects for WAEMU and CEMAC
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Martínez-Zarzoso, I. The Euro and the CFA Franc: Evidence of Sectoral Trade Effects. Open Econ Rev 30, 483–504 (2019). https://doi.org/10.1007/s11079-018-09520-8

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