ECONOMIA INTERNAZIONALE / INTERNATIONAL ECONOMICS 2016 Volume 69, Issue 3 – August, 248-265 Authors: Teboho Jeremiah MOSIKARI Economics Department, North West University, South Africa Joel Hinaunye EITA Department of Economics and Econometrics, University of Johannesburg, South Africa DETERMINANTS OF SOUTH AFRICA’S EXPORTS OF AGRICULTURE, FORESTRY AND FISHING PRODUCTS TO SADC: A GRAVITY MODEL APPROACH ABSTRACT The objective of the study is to examine agricultural, forestry and fishing exports determinants between South Africa and SADC countries using a gravity model approach. This paper uses annual data covering the year 2005 to 2014. The result of the study indicates that exporter’s GDP, importer’s population, South African inflation, exchange rate have a negative association with South African exports of agriculture, forestry and fishing. On the other hand, the results indicate that importer’s GDP and exporter’s population have a positive impact on South African export of agriculture, forestry and fisheries products. The results imply that increase in GDP suggests self-sufficiency and less need to export. Price and exchange rate stability are important for export of these products. The results also indicate that increase in GDP of SADC countries are important for exports of these products. Keywords: Gravity Model, Agricultural Exports, South Africa, SADC JEL Classification: A10, C01, C51, F30, F36 RIASSUNTO Le determinanti delle esportazioni di prodotti agricoli, della silvicoltura e della pesca dal Sud Africa verso i paesi della Comunità di Sviluppo dell’Africa Meridionale Obbiettivo di questo studio è quello di esaminare le determinanti delle esportazioni di prodotti agricoli, della silvicoltura e della pesca dalla Repubblica del Sud Africa verso i paesi della Comunità di Sviluppo dell’Africa Meridionale (SADC) attraverso un modello gravitazionale. Questo articolo usa dati annuali che coprono il periodo 2005-2014. Il risultato dello studio indica che il PIL del paese esportatore, la popolazione del paese importatore, l’inflazione del Sud Africa
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ECONOMIA INTERNAZIONALE / INTERNATIONAL ECONOMICS 2016 Volume 69, Issue 3 – August, 248-265
Authors:
Teboho Jeremiah MOSIKARI
Economics Department, North West University, South Africa
Joel Hinaunye EITA
Department of Economics and Econometrics, University of Johannesburg, South Africa
DETERMINANTS OF SOUTH AFRICA’S EXPORTS OF AGRICULTURE, FORESTRY AND FISHING PRODUCTS TO
SADC: A GRAVITY MODEL APPROACH
ABSTRACT
The objective of the study is to examine agricultural, forestry and fishing exports determinants
between South Africa and SADC countries using a gravity model approach. This paper uses
annual data covering the year 2005 to 2014. The result of the study indicates that exporter’s
GDP, importer’s population, South African inflation, exchange rate have a negative association
with South African exports of agriculture, forestry and fishing. On the other hand, the results
indicate that importer’s GDP and exporter’s population have a positive impact on South African
export of agriculture, forestry and fisheries products. The results imply that increase in GDP
suggests self-sufficiency and less need to export. Price and exchange rate stability are important
for export of these products. The results also indicate that increase in GDP of SADC countries
are important for exports of these products.
Keywords: Gravity Model, Agricultural Exports, South Africa, SADC
JEL Classification: A10, C01, C51, F30, F36
RIASSUNTO
Le determinanti delle esportazioni di prodotti agricoli, della silvicoltura e della pesca dal Sud
Africa verso i paesi della Comunità di Sviluppo dell’Africa Meridionale
Obbiettivo di questo studio è quello di esaminare le determinanti delle esportazioni di prodotti
agricoli, della silvicoltura e della pesca dalla Repubblica del Sud Africa verso i paesi della
Comunità di Sviluppo dell’Africa Meridionale (SADC) attraverso un modello gravitazionale.
Questo articolo usa dati annuali che coprono il periodo 2005-2014. Il risultato dello studio indica
che il PIL del paese esportatore, la popolazione del paese importatore, l’inflazione del Sud Africa
e il tasso di cambio sono in relazione negativa con l’export sudafricano di prodotti agricoli, della
silvicoltura e della pesca. Dall’altra parte, il risultato indica che il PIL del paese importatore e la
popolazione del paese esportatore hanno un’influenza positiva sull’export sudafricano di tali
prodotti. I risultati implicano che un aumento del PIL determina una minore necessità di
esportare. La stabilità dei prezzi e del tasso di cambio così come l’aumento del PIL sono
importanti per l’export di questi prodotti.
1. INTRODUCTION
South Africa is one of the upper middle class country according to World Bank classification. The
economy is second largest in the continent after Nigeria. The South Africa economy is praised
for its great governance and economic policies. The economy of South Africa contributes almost
24% to Africa’s gross domestic product (GDP). South Africa is a member of several trade blocs as
a way to improve its economic growth. Although South Africa is being perceived to be at better
living standards compared to its counter parts in Africa, the economy is not without socio-
economic problems.
Unemployment in South Africa is one of the major concern for economic policy makers to fight
it. Unemployment in 1994 was 22% and stood at 25% in 2014 (StatsSA, 2014). These statistics
clearly show a serious concern since unemployment is the root of poverty and inequality.
Through the good practice of economic policies South Africa can benefit from agriculture,
forestry and fishing (DAFF) to generate 1 million jobs by 2030 through agriculture projects.
Agriculture alone contributes about 0.2% to GDP growth, whereas 0.4% and 0.1% is contributed
by forestry and fishing respectively (DAFF, 2013).
DAFF (2013) annual report indicates that leading exports commodities to SADC1 include soya-
bean oil, sugar, food preparation, sunflower oil, wheat, maize and apples. The report also shows
that South African exports to its SADC trading partners have escalated from R5.3 billion to
almost R15 billion between the year 2007 and 2012. During the year 2011 and 2012 South Africa
export to SADC increased of 16% compared to 6% to COMESA2. Total export value of
1 South African Development Community (SADC) is a trade region formed by most southern African economies. The region is formed by countries such as Angola, Botswana, DRC Congo, Lesotho, Madagascar, Mauritius, Malawi, Mozambique, Namibia, Seychelles, South Africa, Tanzania, Zambia and Zimbabwe. 2 Common Market for Eastern and Southern African (COMESA) consist of twenty member states which are Djibouti,
Ethiopia, Egypt, Libya, Sudan, Comoros, Madagascar, Mauritius, Seychelles, Burundi, Kenya, Malawi, Rwanda, Uganda, Swaziland, Zambia, Zimbabwe, DR Congo and South Sudan.
Determinants of South Africa’s exports of agriculture, forestry and fishing products to SADC: a gravity model approach 250
ECONOMIA INTERNAZIONALE / INTERNATIONAL ECONOMICS 2016 Volume 69, Issue 3 – August, 248-265
agricultural products increased by less than 1%, from R10,7 billion to R10,8 billion between the
first quarter of 2011 and the first quarter of 2012 and forestry products increased by 3%, from
R2,4 billion to R2,5 billion. Whereas fishery decreased considerably by 30%, from R625 million
to R440 million between the first quarter of 2011 and the first quarter of 2012.
The study is structured as follows: Section 2 reviews previous studies; Section 3 presents model
specification; Section 4 presents data description and their source. Section 5 describes
estimation methods of the study. Section 6 presents the empirical results and Section 7
concludes the study.
2. PREVIOUS STUDIES
Considering some socio-economic problems in many developing economies, regional
integration can play a significant role in expanding their economic wealth through international
trade. The work of previous studies such as Nikbakht and Nikbakht (2011), Lubinga and Kiiza
(2013) and Tay (2014) have studied bilateral trade benefits among the countries through their
regional trade agreements. The study by Nikbakht and Nikbakht (2011) investigated the bilateral
trade benefits between 8 Muslim developing countries which are Iran, Turkey, Pakistan,
Bangladesh, Malaysia, Egypt and Nigeria. The study was motivated by the fact that these
countries have a dispersed location, between Africa and Asia. Their study found that GDP has a
significant positive impact for both importing and exporting country. The results also show that
distance has a negative impact between trading partners and is significant. Lubinga and Kiiza
(2013) analysed the effects of real exchange rate volatility on the level and volatility of Uganda’s
bilateral trade flows with several major trade partners such as Switzerland, Belgium,
Netherlands, Kenya, South Africa, United Kingdom and France. The results show that real
exchange rate volatility depresses Uganda’s bilateral trade flows. The results also indicate that
GDP of Uganda and trading partners has a positive impact on exports.
Tay (2014) used gravity model to examine trade in education using a nexus of international trade
theories. The study revealed that conventional determinants of bilateral trade such as GDP,
population and common language have a positive and highly significant impact on trade in
education. Greene (2013) employed gravity model to examine government policies and other
measures of market access for Unites States (U.S) exports of advanced technology goods to
India. The study found that per capita income coefficient for the exporting (United States) and
Tanzania, Zambia and Zimbabwe, except Madagascar due to data unavailability. Total
population (POPit) of each SADC countries is collected from World Bank database of World
Development Indicators (WDI). The variable distance (DISTij) data between South Africa and
respective SADC countries is extracted from http://www.timeandate.com website and is
computed as distance in kilometers between capital cities. South African real exchange rate
(SA_RERit) and South African consumer prices (lnSA_PRit ) data is collected from African
Development Indicators (ADI).
5. ESTIMATION METHODS The study uses panel data econometric technique to estimate equation (2) and (3). The study can
adopt various panel estimation techniques. Panel data involves the use of pooled, fixed and
random effect model. The pooled method is restricted and assumes a single constant and the
same parameters over time and across countries. This presumption might be inappropriate
since each country has different individual effect. Therefore, the test of poolability can be
applied to test for homogeneity in the dataset3. The second method is fixed effect model: this
technique is appropriate in a study where there is a correlation between individual effects and
exogenous variables. Also according to Binh et al. (2011) the random effect model is effective
when there is no correlation explanatory variables, of which it can consider time invariant
variables unlike the fixed effect model. Since this study examines exports determinants of
agricultural, forestry and fishing and 13 SADC countries, the fixed effect model is more
appropriate than random effect model. These countries were selected on the base of data
availability and their affiliation to SADC trade block, therefore fixed effect model is presumed.
3 The study applied the F-test on pooled model to test for null hypothesis of homogeneity for all countries. The results indicate that p-value for F-test is 0.0000. Therefore, the study rejects the null of homogeneity for all countries. See the results under appendix.