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South-South Trade: A Quantitative Assessment

Raihan, Selim (2014): South-South Trade: A Quantitative Assessment.

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Abstract

The share of North-North trade in global trade declined from 55.5 percent in 1990 to around 32 percent in 2010. Such fall in North-North trade had been accompanied by rising trade involving the South countries. The South-North trade share increased from 13.9 percent to 16.5 percent during the same time. However, the most spectacular phenomenon was the rise in South-South trade, which increased from only 6.4 percent to 19.4 percent during this period.

Such rise in South-South trade has not been uniform across different South countries. During 1990 and 2010, though all categories of South countries (all South, LDCs, SVEs, advanced South and South excluding advanced South) experienced rises in their shares in global trade, trade involving the advanced South countries was the major contributor to the changing landscape in global trade, which resulted in remarkable rise in the South-South trade.

When it comes to country-wise shares in South-South export, there are some gainers and losers. Out of the 135 South countries, 50 countries experienced rise in their shares in South-South export while 85 countries experienced fall in shares.

The structures of the export of the South countries are not uniform. Many of the South countries’ export are agriculture based, many of them are extraction based and the rest are manufacturing oriented. The destinations of the export from South countries are primarily the developed countries.

A comparison among the sizes of coefficients of different variables under the basic gravity models suggests that as far as intra-South trade is concerned, among the continuous variables, the largest positive effect stems from the per capita GDP of the home country, and largest negative effect comes from the distance. Among the dummy variables, the common border dummy has the largest positive effect, whereas the island dummy of the partner country has the largest negative effect. However, these variables have differential effects when it comes to trade between different groups of South countries.

Gravity modeling results suggest that when considering South countries as the home, there are marked differences among different groups of countries as far as the impact of per capita GDP of home country (in this case the South countries) on exports from these groups of countries to the South countries are concerned. Per capita GDP of the South countries has the largest positive effect on the export from the North countries; and among different South countries such positive effect is the largest for the export from the Emerging South countries. For SVEs the effect is positive but is the smallest among all country groups. Now, while considering South as the source of export, the per capita GDP of the emerging South countries has the largest positive effect among all country groups on the export from South. Interesting, the per capita GDP of the North countries doesn’t have any significant effect. Also, though the per capita GDP of LDCs has a positive effect on the export from South that of the SVEs doesn’t have any statistically significant effect.

Gravity modeling results also suggest that, considering South as the home, the distance factor has the largest negative effects on exports from the Emerging South countries and SVEs to South countries; and distance factor has the largest negative impact on South’s export to Emerging South among all country groups as destinations for South’s export. In the case of common language dummy, while considering exports to South from all country groups, this dummy has the largest positive effect on export from North countries, and while considering export from South, common language has the largest positive effect on the export to South Excluding Emerging South countries. In the case of land lock dummy for home country, considering South as the home, this dummy has mixed effects on exports from different country groups; for example, it has negative impacts on exports from LDCs and North, while it has a positive impact on export from South Excluding Emerging South. Also, this dummy has only negative effect on the export from South to North among all country groups as destinations for South’s export. In the case of land lock dummy for partner country, when South is the home, among all country groups, this dummy has the largest negative effect on the export from the South; however, when South is the export source, this dummy has the largest negative effect on South’s export to Emerging South countries. In the case of island dummy for home country, considering South as the home, the export from the island countries will be reduced, if those countries are either North or SVEs. Also, South’s export to Emerging South countries will be reduced most of the South countries are the island countries. In the case of island dummy for partner country, considering South as the home, the export from LDCs is mostly affected among exports from all country groups if LDCs are island countries. Also, if South countries are island countries, then their export is mostly affected in the Emerging South countries. When South is the export destination, common border dummy has the largest positive effect on the export from South countries in general, and among different groups of South countries, this dummy has the largest positive effect on the export from LDCs. However, this dummy has a negative effect on the export from North to South.

Augmented gravity modeling results suggest that, in general, South’s tariff rate has the largest negative effect on the export from SVEs. North’s tariff is most restrictive on the export from South in general and South Excluding Emerging South in particular. LDCs’ tariff rate affects mostly the export from SVEs and LDCs. SVEs’ tariff rate affects mostly the export from South Excluding Emerging South counters. Tariff rates of Emerging South and South Excluding Emerging South have the largest negative effect on export from SVEs. As far as South is considered as the export destination, trade cost in South affect mostly the export from South. Trade cost in North has the largest negative effect on export from LDCs, and it seems that such negative effect is higher than the negative effect on export from North to LDCs due to trade cost in LDCs. While the trade costs between LDCs and Emerging South countries are compared, trade costs in Emerging South countries seem to be more restrictive on export from LDCs, as compared to the negative effect of trade cost in LDCs on the export from Emerging South. Similar observations are hold for SVEs, while comparing the restrictive effect of their trade cost with those of North and Emerging South.

CGE modeling results suggest that a scenario of LDCs and SVEs receiving duty-free market access in emerging south countries would lead to some significant rise in welfare for all LDCs and SVEs, which would, for some countries, in terms of the percent of their GDPs, be quite high. For example, for Nepal such welfare gain would be 3.2 of its GDP. The least benefitted country in this regard would be Botswana and its welfare gain would be only 0.01 percent of its GDP. All LDCs and SVEs would also experience rise in exports. However, different LDCs and SVEs would experience rise in export by different magnitudes. The largest rise in export, in terms of percentage change, would be for Nepal followed by Rest of South Asia. The lowest rise in export would be for Botswana. . All LDCs and SVEs would experience some re-direction of their exports towards the Emerging South countries. Such as scenario would not lead to large rise in export from LDCs and SVEs, which indicates to the fact that tariff preferences in the Emerging South countries alone would not be enough to help LDCs and SVEs to increase their export to the Emerging South countries. Such a scenario would lead to marginal effects on the export from other developing countries, some countries would experience very small rise and some counties would experience very small fall.

The CGE modeling results also suggest that the welfare effects of a scenario of FTA among Emerging South, LDCs and SVEs and other developing countries would lead to some large welfare gains, both in terms of volume and percent share of GDP, for most of the Emerging South countries. There would be mixed effects among the other developing countries. LDCs and SVEs would also see mixed effects. Such a scenario would lead to some significant rise in exports from most of the Emerging South, other developing countries and LDCs and SVEs. Such a scenario would enhance South-South trade significantly. Most of the South countries would experience rise in export to other South countries. The incremental rises in exports of these countries would be destined to other South countries.

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