Back Matter
  • 1 https://isni.org/isni/0000000404811396, International Monetary Fund
  • | 2 https://isni.org/isni/0000000404811396, International Monetary Fund
  • | 3 https://isni.org/isni/0000000404811396, International Monetary Fund
  • | 4 https://isni.org/isni/0000000404811396, International Monetary Fund
  • | 5 https://isni.org/isni/0000000404811396, International Monetary Fund

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Appendix I. Selected African Country Indicators, 20161

(Billions of US dollars, unless indicated otherwise)
article image
Sources: World Integrated Trade Solutions; and IMF, World Economic Outlook database, April 2018.Note: a-2015; b-2014; c-2013; d-2012; e-2007; f-2006. Bns = billions; PPP = purchasing power parity

No data are available for the Republic of Saharawi, a full member of the African Union, which also signed the AfCFTA agreement.

Appendix II. List of Signatory Countries to the AfCFTA

article image
Sources: African Union webpage, https://au.int/.../list-african-countries-signed-establisment-african-continental-free-trade-agreement; and Tralac webpage, https://www.tralac.org/resources/infographics/13795-status-of-afcfta-ratification.html.1 Date on which the AfCFTA instrument of ratification was deposited with the African Union Commission chairperson.

Appendix III. Firm-Level Evidence of Labor Reallocation in Africa

Although firm-level characteristics are important factors to explain the decision to export, other factors, such as the level of tariffs, also play a role. Table A1 shows the result of the authors’ probit regression (unpublished) on the decision to export. It uses detailed firm-level data for a sample of African firms. The regression shows that firm age, firm size (using various size indicators), and firm origin (foreign versus domestic) are key factors that explain the decision to export. Using changes in tariffs across countries and years, the regression also shows evidence that the decision to export is positively affected by large reductions in import tariffs faced by firms.1

Table A1.

African Firms: Decision to Export, Firm Characteristics, and Tariff Reduction

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Note: Robust standard errors are in parentheses. *** p<0.01, ** p<0.05, * p<0.1.Source: Authors’ calculations.Note: Probit regression on the probability of exportation by firms using firm-level data from the World Bank Enterprise Survey Database. The sample is divided into two periods (2005–08 and 2013–16). The variable “Reduct X percentile” is equal to 1 if the country where the firm is located experiences a great reduction in tariffs faced by exporter firms in the late period compared with the early period (the country is ranked in the X highest percentile of tariff reduction). The interaction terms suggest that firms are more likely to export in countries where tariffs have been reduced the most, controlling for other factors.

There is also evidence that exporting firms pay higher wages than other firms. Detailed firm-level and employee-level data show that African firms that export pay salaries that are almost 18 percent higher than firms that do not export (Duda-Nyczak and Viegelahn 2018). This is called the “exporter wage premium,” and it has also been found in other studies on Africa (Van Biesebroeck 2005) and on other regions in the world.2 Conversely, there is little evidence that importing firms pay a positive wage premium.

Firm-level evidence suggests that export activities may be less conducive to employment growth than other activities. Table A2 shows that firms that export reduce employment growth by 1.2 percent, compared with similar firms that do not export. Exporting firms also tend to show higher labor productivity. This evidence is consistent with Bernard and others (2007) who show that exporting firms tend to be larger, be more productive, employ more skilled workers, and pay higher wages. This suggests that exporting firms may not be able to absorb all unskilled trade-displaced labor and thus may not contribute to unskilled-labor employment growth (Haltiwanger 2004).

Table A2.

African Firms: Employment Growth and Exporting Firms

article image
Note: Robust standard errors are in parentheses. *** p<0.01, ** p<0.05, * p<0.1.Source: Authors’ calculations.Note: Regression on employment growth and other relevant variables. Firm-level data are used from the World Bank Enterprise Survey Database. “Employment growth” in the firm (percent) is compared with the previous year. “Labor productivity growth” (in percent) is compared with the previous year. “Exporter” is an indicator variable equal to 1 if the firm exports to other countries in the current period.
1

By late January 2020, 54 (of 55) member countries of the African Union (AU) had signed the AfCFTA agreement. See Appendix II for the full list of signatory countries.

2

Africa conducts most of its trade with countries outside the continent. Since 2000, Africa’s direction of trade has shifted from the United States and Europe to China and Asia more generally.

3

Unilateral trade liberalization has also contributed to a significant reduction in tariffs imposed on non-African countries, which fell from 21.7 percent in 1997 to 11.8 percent in 2016.

4

The Presidential Infrastructure Champion Initiative was launched in 2011 and the Program for Infrastructure Development in Africa was adopted in 2012.

5

The AfCFTA is an overall framework agreement of which various protocols, annexes, and appendices form an integral part. Most of the details still need to be negotiated. Thus far, agreement has been reached on the objectives, principles, and institutions and on a work plan for completing the negotiations.

6

The protocol on trade in goods also includes annexes on tariff concessions, rules of origin, customs cooperation, trade facilitation, technical barriers to trade, sanitary and phytosanitary measures, and transit and trade remedies.

7

This followed the receipt of the 22nd ratification instrument by the chairman of the African Union Commission (AUC). As of late January 2020, 29 countries had ratified the agreement and deposited the instrument with the AUC.

8

Some of the manufacturing sectors that expand the most in the small economies are electricity generation, machinery, chemicals, and textiles.

9

In a seminal article, Stolper and Samuelson (1941) used the well-known Heckscher-Ohlin model to explain how trade policy affects the relative return of factors of production and thereby income distribution.

10

See Goldberg and Pavcnik (2007) and Helpman (2016) for other reviews of the literature on globalization and inequality.

11

By design, partial equilibrium studies focus on specific sectors and do not draw conclusions on the effects of increased trade openness on economy-wide employment.

13

Abrego and others (2019) use an elasticity of 1 when estimating the impact on revenue from income and consumption taxes. This may be on the conservative side. Jalles (2017), for example, estimates an average elasticity of 1.22, which would result in more positive AfCFTA effects on tax revenue.

14

IMF (2019) estimates revenue effects using non-CGE methods, considers a common average tariff rate, and uses very fine product–country level data. Estimates consider only the effect of tariff removal and use most-favored-nation -based tariffs in their calculations, which results in higher revenue losses compared with CGE-based models.

15

At 3.4 km per 1,000 inhabitants, road density in sub-Saharan Africa is less than half of the global average, and paved road density, at 0.7 km per 1,000 inhabitants, is one-fifth of the global average (Gwilliam 2011).

1

Using a related database, Vijil, Wagner, and Woldemichael (2019) also find that uncertainty about the time required to clear imported inputs affects survival rates for new exporters, reducing the number of firms that continue to serve the foreign market beyond their first year.

2

Since exporting firms tend to be much larger than non-exporting firms, the wage premium for exporters may result from a scale effect.

The African Continental Free Trade Area: Potential Economic Impact and Challenges
Author: Mr. Lisandro Abrego, Mr. Mario de Zamaroczy, Tunc Gursoy, Garth P. Nicholls, Hector Perez-Saiz, and Jose-Nicolas Rosas