DOI: 10.5061/dryad.p8cz8w9p2
title: An impact assessment of the SADC FTA on bilateral trade relations between South Africa and Zimbabwe

description: The Journal paper uses the Gravity Model of International Trade to
 investigate the impact of the Southern African Development Comuunity
 (SADC) Free Trade Area (FTA) on trade between South Africa and Zimbabwe.
 The study found out that South Africa gained more in trade by 88.4% if the
 country used the SADC FTA than the 1964 Bilateral Trade Agreement which
 was between South Africa and Zimbabwe. In addition, there was trade
 diversion of 176% for Zimbabwe when trading in SADC FTA. Furthermore the
 paper showed that South Africa will in future trade more with countries
 such as the Seychelles and Angola whilst Zimbabwe will gain more in trade
 if it trades with  South Africa. The paper recommends that there
 is need for Zimbabwe and South Africa to expand trade with SADC Countries
 in order to promote intra-regional trade.
description: Data was collected from various websites such as the World Bank
 World Development Indicators , CEPII and own computations of dummy
 variables. The data was colllected and arranged in excel documents and
 stata files.
description:   TF<sub>ij </sub>- This is the
 dependent variable which shows annual trade of exports plus imports of
 SADC member states. Other studies which have used the gravity model as
 their methodology such as Sunge & Mapfumo (2014) and Simwaka
 (2011) have used the log of exports as the dependent variable arguing that
 imports in Africa are understated in order to minimize their import bills.
 However this may not be holistic view in all countries and will not
 reflect the true picture of trading activities in Africa.
 Y<sub>j</sub>  and Y<sub>i</sub> - These
 are explanatory quantitative variables which show the economic sizes of
 the exporting and importing countries. Ogunkola (1998) explains that the
 higher the GDP for exporting and importing countries, the higher is the
 respective countries’ potential for foreign product demand
 Dist<sub>ij</sub>- This is a quantitative explanatory
 variable which is a proxy to transportation costs in bilateral trade.
 Simwaka (2001) uses the quality of infrastructure as a proxy for transport
 costs as the author highlights that distance may be biased if the poor and
 not well connected. However distance is a traditional variable which is
 calculated in kilometers from the capital city of one SADC member state to
 the other capital city of a SADC member state contig-
 This is a dummy explanatory variable which represents the common borders
 between SADC member states. The variable will show one if there is a
 common border between an importing country and the exporting country and
 zero if there is no common border between the two. Countries with common
 borders will trade more than countries without common borders.
 lang- This is a qualitative variable which takes the value of one
 if the importing country has a common language with the exporting country
 and zero otherwise. TC- The variables show trade
 creation in the SADC region. The dummy variables takes the value of one if
 both the importing and exporting countries are in the SADC Free Trade Area
 and zero otherwise TD- The variable shows trade
 diversion in SADC trade. The dummy variable represents one if one of the
 member states is in the SADC FTA and zero otherwise.
 llc- This is a dummy variable which represents one if the
 exporting country is landlocked and zero otherwise
 exc<sub>ij </sub>- Bergstand (1985) explains that the
 exchange rate variable is important to show trade variation between member
 states. The quantitative variable will determine annual exchange rate by
 the importing country’s currency unit per one unit of the exporting
 country’s currency. Following Binh et al (2013) the variable is calculated
 as the annual average of the importing country’s currency unit per US
 dollar divided by the annual average of the exporting country’s national
 currency unit per US dollar per year.
 PI<sub>i</sub> & PE<sub>j</sub>-
 These two quantitative variables estimate the market size of member
 states. A member state with a larger market size than the other is more
 likely to trade more in the region. This is a panel
 data set  consisting of 16 SADC countries. and data was obtained from
 World Bank's World Development Indicators, CEPII and own computations
 in terms of dummy variables .