Introduction

Regional trade is important in stimulating economies of regional block countries through free trade agreements.[1] The history of cooperation in East Africa can be traced to 1917 when the British colonies of Kenya and Uganda were first joined into a Customs Union (CU) and later the defunct East African Community (EAC) in 1967 which collapsed in 1997[2] and re-established in 1999.[3]

Theoretical Background

The theory of comparative advantage attributed to David Ricardo can explain determinants of bilateral trade flows. It is the ability of a party to produce a good at a lower marginal and opportunity cost over another.[4] The theory has, however, been criticized for restraining competition with non-regional trading bloc firms and increasing welfare among state parties implementing such strategic trade policies.[5] Nonetheless, it still remains invaluable.

Review of literature

Bilateral trade flows are common dependent variables used in trade flow gravity models.[6] Factors indicating demand and supply and those representing impediments imposed to trade flows have been used as explanatory variables.[7] The common proxies for demand and supply factors are measurements of countries’ economic and market sizes (population, GDP and GDP per capita).[8] Impedance factors include transportation costs proxied by great circle distance between a pair of countries economic centers.[9] Others are common language, boarder adjacency, land-lockedness of a country and regional integration agreements. [10]

Methodology

This study adopted longitudinal research design.[11] It included state parties; Burundi, Kenya, Rwanda, Tanzania and Uganda. Macro-economic panel time-series (monthly) data from 1980 to 2013 were generated from IMF Financial Statistics databases (Bilateral trade ($), GDP, GDP per capita, population) and circle distances between state capitals. Dummy variables in the model represented membership to trade agreements, adjacency and land lockedness of a country.

Data analysis

A log-linearized augmented Gravity Model was used to analyze data. The model was estimated on the basis of single country variables. This specification distinguishes structural factors in the exporting country to those in the importing country. This made it possible to test and compare the relative importance of the study variables in the countries of origin and destination countries.

Results

Regression results show according to a priori expectations that the following variables were positively related to Uganda’s bilateral trade flows and were statistically significant (p < 0.05): Uganda’s GDP (β =1.42), Uganda’s GDP per capita (β = 0.45), Uganda’s population (β = 3.80), absolute difference between Uganda’s GDP per capita and partners (β = 0.23) and circle distance (β = – 0.13). Partner’s population, GDP per capita and Uganda’s GDP were not found to be statistically significant while Uganda’s GDP was negative and so was GDP per capita of partners.

Discussions

Gross domestic product (GDP) indicates economic size. The bigger the GDP the higher the aggregate demand potential.[12] The findings, however, contrasts with findings that GDPs of trading bilateral partners were statistically insignificant.[13] GDP per capita indicates purchasing power of the people in a country. This study found that Uganda’s GDP per capita was positive and significant which contradicts other studies.[14] This study however found a negative relationship between Uganda’s partners GDP per capita with Uganda’s bilateral trade flows. Population size is associated with production capacity and market consumption potential. Uganda’s population was found to positively relate to bilateral trade flows consistent with Lwin.[15]

Absolute differences in per capita GDP of Uganda and partners was found to positively relate to bilateral trade flows which contradicts other studies.[16] Economic integration showed positive and significant relationship with bilateral trade flows. Membership to the regional trade agreement introduced widening of the common market reducing cost of trade by abolishing tariffs among partners consistent with other studies in Malawi, Fiji and Namibia.[17] This study however contradicts findings that failed to account for possible influence of regional integration agreement on Fiji.[18] Land lockedness status of a state, regional integration (EAC) and distance were statistically significant consistent with studies in Fiji.[19] In examining the factors influencing trade between Fiji and her Asian partners, results suggested that Fiji’s exports are significantly influenced by Fiji’s trade infrastructure.[20]Such resistance is posed by factors like land lockedness, adjacency and language and various other obstacles to trade with trading partners.[21] In analysis of trade creation and trade diversion effects of Southern Asian Association for Regional Cooperation a study found that trade was positively determined by regional cooperation agreements.[22]

Distance between trading partners proxied by transportation costs is as expected, negatively related to trade flows and significant in this study consistent with other study findings.[23] Contrary to the above findings it was found that transport cost reductions do not have a significant effect on exports from African countries[24] and did not play an important role in determining Ethiopian volume of exports.[25]

Conclusion

Economies of EAC countries are expected to grow (GDP and GDP per capita) increasing Uganda’s bilateral trade flows with EAC partners. Regional integration has promoted Uganda’s bilateral trade. Integration efforts have boosted bilateral trade while longer destination markets impedes trade due to increased transportation costs.

Recommendations

Policies that support economic growth, deepen regional integration efforts, improves communication infrastructure (roads, rail and air transport) and focus on efficient production and scale economies should be pursued to promote Uganda’s bilateral trade.

[1] Lwin, N., N (2009). Analysis of international trade of Cambodia, Laos and Myanmar countries. Institute of Development Economics Discussion Paper no. 215, August 2009.
[2] Kenya Economic Update, June (2012).
[3] Protocol establishing the East African Community (1999).
[4] Samuelsson, (1969)
[5] Krugman, Paul R. (1987). “Is Free Trade Passed?”Journal of Economic Perspectives1(2).pp. 131–144.
[6] Simwaka, K. (2006). Dynamics of Malawi’s trade flows: A Gravity Model approach. Munich Personnel re PECArchives, MPRA Paper No. 1122.
[7] Kepatsoglou, K., Karlaftis, M., G. & Tsamboulas, D. (2010). The Gravity Model specification for modeling International Trade Flows and international trade agreements effects: A 10-year review of empirical studies. Open Economics Journal 2010 (3), 1 – 13.
[8] Bergstrand, J. H. (1985). The Gravity Equation in International Trade: Some Microeconomic Foundations and Empirical Evidence. The Review of Economics and Statistics. No. 67. Pp. 474 -481.
[9] Martinez-Zarizosa, I., & Suarez-Bougueat, C. (2005). Trade costs and trade: Empirical evidence for Latin American Imports from the European Union. Journal of International Trade Economics and Development 2005; 14 (3), 353 – 371.
[10] Kepatsoglou, Karlaftis, & Tsamboulas, (2010).
[11] Amin, M., E. (2005).Social science research: Conception, methodology and analysis. Kampala: Makerere University.
[12] Eita (2008). Eita, J. H. (2008). Determinants of Namibian exports: A Gravity Model Approach, University of Namibia, Namibia.
[13] Gani, A. (2008). Factors influencing trade between Fiji and its Asian partners. Pacific Economic Bulletin. Vol. 23, no. 2. The Australian National University.
[14] Rahman, M. M. (2009). Australia’s Global Trade Potential: Evidence from the Gravity Model Analysis in Oxford. Business and Economics Conference, 24-26 June, 2009, Oxford University, Oxford, UK.
[15] Lwin, N., N (2009). Analysis of international trade of Cambodia, Laos and Myanmar countries. Institute of Development Economics Discussion Paper no. 215, August 2009.
[16] Rahman, M. M. (2009). Australia’s Global Trade Potential: Evidence from the Gravity Model Analysis in Oxford. Business and Economics Conference, 24-26 June, 2009, Oxford University, Oxford, UK.
[17] Simwaka, K. (2006). Dynamics of Malawi’s trade flows: A Gravity Model approach. Munich Personnel re PECArchives, MPRA Paper No. 1122; Roy, M. and Rayhan, I. (2011). Trade Flows of Bangladesh: A Gravity Model Approach, Economics Bulletin, Vol. 31 no.1 pp. 950 -959.
[18] Eita, J. H. (2008). Determinants of Namibian exports: A Gravity Model Approach, University of Namibia, Namibia.
[19]Gani, A. (2008). Factors influencing trade between Fiji and its Asian partners. Pacific Economic Bulletin. Vol. 23, no. 2. The Australian National University.
[20] Gani, A. (2008). Factors influencing trade between Fiji and its Asian partners. Pacific Economic Bulletin. Vol. 23, no. 2. The Australian National University.
[21] Lwin, N., N (2009). Analysis of international trade of Cambodia, Laos and Myanmar countries. Institute of Development Economics Discussion Paper no. 215, August 2009.
[22] Hassan, M. K. (2001). “Is SAARC a viable economic block?” Evidence from Gravity Model, Journal of Asian Economics, Vol. 12, pp. 263 – 290.
[23] Lwin, N., N (2009). Analysis of international trade of Cambodia, Laos and Myanmar countries. Institute of Development Economics Discussion Paper no. 215, August 2009; Hassan, M. K. (2001). “Is SAARC a viable economic block?” Evidence from Gravity Model, Journal of Asian Economics, Vol. 12, pp. 263 – 290; Rahman, M. M. (2009). Australia’s Global Trade Potential: Evidence from the Gravity Model Analysis in Oxford. Business and Economics Conference, 24-26 June, 2009, Oxford University, Oxford, UK.
[24] Márquez-Ramos, L. (2007). Understanding the determinants of international trade in African countries: An Empirical analysis for Ghana and South Africa. Instituto de Economía Internacional, Universitat Jaume I.
[25]Taye (2009)