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Erschienen in: Empirical Economics 6/2020

29.06.2019

The trade creation effects of Africa’s reciprocal vis-à-vis non-reciprocal trade agreements

verfasst von: Samuel Admassu

Erschienen in: Empirical Economics | Ausgabe 6/2020

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Abstract

The advancement of growth through the promotion of exports by granting developing countries preferential terms to rich markets is considered central in global trade policy negotiations. This paper investigates the impact of reciprocal versus non-reciprocal trade agreements on Africa’s trade. The study uses a gravity model with a 5-year-interval comprehensive dataset of 148 countries for the period 1970–2010. The results reveal that African reciprocal trade agreements perform better than non-reciprocal agreements in promoting exports and imports.

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Fußnoten
1
In fact, the promotion of economic development via preferential terms was an agenda in the Doha’s round of trade negotiations.
 
2
The relatively weak performance of non-reciprocal trade agreements is not surprising given the trade realities of Africa. The share of Africa export value in terms of the total world export is a mere 2.4% (IMF DOT dataset). The estimated annual trade loss is equivalent to $70 billion—roughly 21% of GDP and five times the $13 billion received in foreign aid (World Bank 2012).
 
3
Given that export is absolutely essential for countries to foster economic growth (Chow 1987; de Piñeres and Ferrantino 1997; Giles and Williams 2000; Moschos 1989), a fruitful future research avenue would be an in-depth study of the impact of trade reciprocity on exports at commodity-level disaggregation.
 
4
These agreements include regional General Agreement on Tariff and Trade (GATT) agreements. For example, in the case of Africa, reciprocal regional trade agreements (RTAs) include the EAC, COMESA, ECCAS, CENSAD, SADC, ECOWAS, EU-EPA, PAFTA and PTN.
 
5
These include non-reciprocal trade agreements such as the GSP, ACP, EU’s recent Everything But Arms (EBA) initiative, US African Growth and Opportunity Act (AGOA), Cotonou and CBI.
 
6
For the small and undiversified economies of sub-Saharan Africa, excessively strict rules of origin can impede the usefulness of preferential agreements (Mold 2005).
 
7
The proliferation of non-reciprocal agreements undermines the effort to advance free trade while reciprocal agreements are trade creating because they do not interfere with the current international trade regime (Bhagwati 2008; Özden and Reinhardt 2005).
 
8
For non-reciprocal trade agreements, the data are arranged in such a way that the exporter countries are recipients while the importer countries grant preferences.
 
9
The random effect is considered less plausible because it assumes a zero correlation between the unobservable and the preferential trade agreement (PTA). Moreover, past empirical studies reveal overwhelming evidence for the rejection of a random-effects gravity model relative to a fixed effects gravity model, using either bilateral-pair or country-specific fixed effect (Baier and Bergstrand 2007; Egger 2000). I also run a Hausman test and find that the p-value equals 0.01 implying the rejection of the random-effects model in favour of the fixed effects gravity model (Baltagi 2008).
 
10
Theoretically, simultaneity and measurement errors are also the sources of endogeneity, but prominent studies argue these issues are less serious, compared with endogeneity due to omitted variables (Baier and Bergstrand 2007).
 
11
There are some variables (bilateral and multilateral resistance terms) that can potentially affect trade, but these are not observable for the researcher. Because these variables are likely to be correlated with PTAs, they are best controlled by using bilateral fixed effects.
 
12
The omitted variable bias arises from disregarding multilateral trade resistance terms as trade choices are established on relative rather than absolute prices (Anderson and Van Wincoop 2003).
 
13
The entire effects of trade agreements on export flow cannot be captured in concurrent years only. Trade agreements alter the terms of trade, which tends to have lagged impact on trade volumes. As a result, trade agreements might also have effects a few years after they are phased in.
 
14
However, the trade agreements, either reciprocal or non-reciprocal, are very different. For example, the FTA between the USA and Morocco differs greatly from the PAFTA. As a result, the usual 0 and 1 dummies may not account for such issues. A better way to address this is to use a measure that assigns different values—other than 0 and 1—to the different types of trade agreement, which of course is beyond the scope of this study.
 
15
Although the RTAs are mainly within Africa, there are a handful of African countries that are also members of a number of cross-regional free trade agreements (FTAs) such as the EFTA, EU, Pan-Arab Free Trade Area (PAFTA) and Protocol on Trade Negotiations (PTN).
 
16
The log-linear specification excludes zero trade flows as the log of zero is undefined.
 
17
The trade agreement variable dummies are constructed using the ‘Date of Entry into Force’ of the agreement, but they fail to take into account the phase-in effect of the agreements. Two lags of trade agreements are also introduced because most PTAs are typically ‘phased in’ over 10 years.
 
18
The finding also reveals that African reciprocal trade agreements perform worse than those in other regions. This is plausible given that the inter-regional trade in Africa stagnated at around 10% among African countries over decades. As a result, the growth-fostering potential of reciprocal trade agreements in Africa is almost untapped, which could otherwise spur growth. For example, according to a World Bank study, African food imports elsewhere have a trade value of up to $52 billion a year. This suggests that broad and deep reciprocal trade agreements in Africa have the potential to enable the region to replace its food imports from outside of Africa.
 
19
Zero trade flows may be the result of rounding errors, especially for small or distant countries. Zeros can also be missing observations that are wrongly recorded as zero. These errors depend on the value of the covariates leading to inconsistency of the estimators.
 
20
The results shown in Table 3 do not account for zeros and heteroskedastic residuals.
 
21
The R2 of the first-differenced equation is very small. However, this might not be surprising as it is a regression on residuals. Moreover, a very low R2 is observed in prominent studies for such models, such as in Baier and Bergstrand (2007).
 
22
However, it contradicts those of Goldstein et al. (2007) and Özden and Reinhardt (2005), who reveal a negative effect of non-reciprocal trade agreements on export.
 
23
The GATT/WTO coefficient is not significant in a number of specifications, but this finding is in line with the findings of Rose (2004) and Esteve-Pérez et al. (2018). Studies such as those of Subramanian and Wei (2007), Felbermayr and Kohler (2010) and Bista (2015) indicate a positive effect, but only for some groups of countries, sectors or periods. Nevertheless, there are also studies such as those of Liu (2009) and Gil-Pareja et al. (2016) that indicate that the GATT/WTO has a strong effect.
 
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Metadaten
Titel
The trade creation effects of Africa’s reciprocal vis-à-vis non-reciprocal trade agreements
verfasst von
Samuel Admassu
Publikationsdatum
29.06.2019
Verlag
Springer Berlin Heidelberg
Erschienen in
Empirical Economics / Ausgabe 6/2020
Print ISSN: 0377-7332
Elektronische ISSN: 1435-8921
DOI
https://doi.org/10.1007/s00181-019-01723-3

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