Impacts of the SADC Free Trade Agreement on South African Agricultural Trade

Abstract

Trade is an essential component of modern society, with nations signing bilateral trade agreements to engage in various forms of economic integration. Developing countries in southern Africa are also involved in economic integration to underpin development. The Southern African Development Community (SADC) became a free trade area in 2008 for the economic integration of its members. This study evaluates the impact of the SADC Free Trade Agreement (SADC FTA) on South African agricultural trade using the Poisson Pseudo-Maximum Likelihood (PPML) specification of gravity model to determine the significance of variables within the model. Bilateral trade data were obtained from the United Nations Commodity Trade Statistics (UN Comtrade) database and the Department of Agriculture, Forestry and Fisheries (DAFF), while data on gross domestic product and population were sourced from the World Bank Development Indicators (WDI) database. The results show that there has been a net trade-creating effect and increasing intra-SADC bloc trade in beef. Intra-regional trade in maize has also been stimulated by the implementation of the agreement.

Finding impact of Pakistan-China Free Trade Agreement (PCFTA) on agricultural exports of Pakistan- Gravity Model Approach

“…In our case, because China and Pakistan are neighboring countries, distance proved to be very important determinant of trade of agricultural products. Our results for this variable are consistent with the previous studies regarding trade of agricultural products [9,32].…”

“…Table 1 show p-values of RESET test which is 0.2535 for PPML and 0.000 for OLS, it proves that PPML model is correctly specified and OLS estimation is not adequate for our model. Earlier studies by some researchers [9,27,32] had similar results for PPML and OLS model when they performed RESET on their models. …”

“…To deal with heterosketdasticity, that is also a big problem in trade data, we used Poisson Pseudo-Maximum Likelihood (PPML) method as suggested by Silva and Tenreyro [27]. The same method was also used by other researchers [9,32] …”

“…To deal with zero trade observations we have used the technique as used in studies [31,32], they added a value equal to one in the case where observed bilateral trade is zero. So that the dependant variable Xit= Xit + 1 for every case where Xit=0.…”

Pulling back the curtain on 'behind the border' trade costs: The case of EU-US agri-food trade

“…The model assumes that the observed volume of trade between countries i and j, X ij follows a Poisson distribution with a conditional mean (µ ij ) which is an exponential function of the explanatory variables z: μ ij = exp(β'z ij ) 5 . Time series trade data were obtained from UN ComTrade database (http://comtrade.un.org/), which has been widely used in the literature (Burger et al, 2009;Fadeyi et al, 2014;Serrano et al, 2015). Thus, annual HS6 bilateral import trade values for the years 2001 to 2011, and 78 countries was collected and reconciled with the GTAP nomenclature of 18 agri-food sectors ( Data on ad-valorem applied tariffs were taken from versions six (Dimaranan, 2006), seven (Narayanan & Walmsley, 2008), eight (Narayanan et al, 2012) and nine of the GTAP database corresponding to the years 2001, 2004, 2007 and 2011, respectively.…”