Why do some countries trade more than others?

Theoretically, trade liberalization results in productivity gains through increased competition, efficiency, innovation and acquisition of new technology. In particular, the changing relative prices induced by trade liberalization cause a re-allocation of resources from less efficient to more efficient uses. Trade liberalization is also thought to expand the set of economic opportunities by enlarging the market size and increasing knowledge spillover effects. Empirical research on international trade also shows that, in general, larger trade-orientation and freer trade, with supporting policies and institutions, can lead to higher welfare for a country than otherwise.

However, a major question remains some way unclear – why do some countries trade more than others? More specifically, does country size matter? How does differences in per capita income affect trade-orientation among countries? Does human capital make any difference? How does tariff liberalization promote trade-orientation? Moreover, does foreign direct investment (FDI) affect trade performance? Furthermore, does geographical location have a bearing, i.e., being an island country or a landlocked country? Also, does membership of the GATT/WTO raise trade-orientation? Finally, does institution matter in trade-orientation?

In order to answer these questions, fixed effect panel regressions using a database covering the period between 1981 and 2014 for 128 countries were conducted. We have defined country’s trade to GDP ratio as the country’s trade-orientation. We want to explain why some countries have higher trade-GDP ratio than others. The explanatory variables are the size of population (to represent country size), per capita real GDP, an index of human capital, domestic average applied tariff rate, and FDI to GDP ratio. Data for all these variables, except human capital, are taken from the World Bank’s WDI, and the data of the human capital is taken from the PWT-8.1. All variables are expressed in natural logarithm. The regression results show that all explanatory variables are statistically significant.

The negative coefficient estimate of the size of population reveals that larger countries tend to be less trade-oriented than their counterparts, as 1% rise in the size of the population is associated with 0.2% fall in the trade-GDP ratio. The reason is that countries with a large population find a ready domestic market and can substitute imports by producing for the internal market. The positive coefficient of the per capita GDP shows that a rise in the real GDP per capita by 10% is associated with a rise in the trade-GDP ratio by 2.2%. The reason behind such an association could be related to domestic producers, with the rise in per capita GDP, becoming more efficient in competing and integrating with their foreign counterparts in the world market. As expected, domestic tariff liberalization is positively associated with higher trade-GDP ratio, as a cut in tariff rate by 10% is associated with a rise in trade-GDP ratio by 0.7%.

The positive coefficient of the FDI-GDP ratio suggests that greater FDI orientation is positively associated with greater trade orientation, and a rise in the FDI-GDP ratio by 10% is positively associated with a rise in the trade-GDP ratio by 0.3%. FDI is assumed to have a positive impact on the export-orientation of any economy, as much of FDI is directed towards the export-oriented sectors. The success stories of East and South East Asian countries have suggested that FDI is a powerful tool of export promotion because multinational companies, through which most FDI is undertaken, have established-contacts and up-to-date information about foreign markets. FDI may also lead to increasing imports in the recipient country as foreign owners tend to have a higher propensity to obtain their inputs from abroad than do their domestically owned counterparts.

Finally, in the case of human capital variable, a rise in the index of human capital by 10% is associated with a rise in the trade-GDP ratio by 9%. This is not surprising! A higher level of human capital is likely to have a positive impact on the perception of the people, as well as on the policy making of the government, in integrating their economy with the world market.

The findings of the LSDV models show that landlocked countries and island countries are 194% and 284% respectively more trade oriented than their counterparts. Both for island and landlocked countries, international trade plays a crucial role in their economic lives as most of these countries are dependent, to an unusual degree, on imported goods and services, including foodstuffs, fuel, equipment and industrial material as well as a wide range of manufactured products. However, interestingly, being a member of the GATT/WTO doesn’t make any difference in terms of trade-orientation.

We have also explored the association between trade-orientation and different institutional variables. The data of these institutional variables are derived from the ICRG database. The fixed effect regression results suggest that countries with better bureaucracy quality, larger democratic accountability, and sounder investment profile are associated with higher trade-orientation. These results are also consistent with findings from studies on the determinants of trade flows which argue distortions or costs placed on firms under inefficient institutions and poor governance can negatively affect trade flows.

Bangladesh’s trade-GDP ratio was only 19.2% in 1981, which increased to 44.5% by 2014. Despite the fact that Bangladesh has been able to raise its trade-GDP ratio by more than two-fold during this period, in 2014, out of the 166 countries, Bangladesh ranked 150th in terms of higher trade-GDP ratio. This suggests, greater trade-orientation in Bangladesh would require further cut in tariff rates, larger FDI-orientation, investment in human capital and improvement in institutional quality.

Published at the Thinking Aloud on 1 June 2016

Published at The Daily Star on 13 June 2016


Unearthing Bangladesh’s Comparative Advantages

Selim Raihan and Md. Jillur Rahman

The analysis of comparative advantage is important from the policy perspective. Trade policies of a country should be tuned to promote export items where the country has comparative advantage.  The Revealed Comparative Advantage (RCA) analysis, suggested by Bela Balassa in 1965, is an ex post analysis of comparative advantage and has been used in many studies. RCA index is used to calculate the relative advantage, disadvantage and trade potential of a certain product in a country.

The RCA index is measured as the ratio of a product’s share in the country’s total export relative to its share in the world’s total export. The formula for the RCA is equal to (Xij/Xit)/(Xwj/Xwt) where, Xij and Xwj are country i’s export and world export of product j respectively, while Xit and Xwt are country i’s total export and world total export respectively. If RCA is greater than unity, the country is said to have comparative advantage in that product; and if RCA is less than unity, the country has comparative disadvantage in that product. The RCA index is popular because of its simplicity, availability of data and for cross-country comparisons. The index is consistent with country’s factor endowment and productivity.

In this article, we are interested to know in which products Bangladesh has comparative advantage, and the dynamic changes of its comparative advantage. We have calculated RCA at 6-digit level of the harmonized system (HS) of classification for the periods between 2001 and 2013. RCA indices for Bangladesh are calculated using the data of export volumes of Bangladesh and the world from the Trade Map database.

Before going into the RCA analysis, let’s first explore how many products Bangladesh exports. At the 6-digit HS code level, there are approximately 5300 products. Figure 1 shows that in 2001, Bangladesh exported 896 products, which, by 2013, increased to a number of 2038. In 2012, Bangladesh exported 2126 products which was the highest among the years under consideration. This suggests that, not only in terms of volume but also in terms of number of products, Bangladesh’s export capacity increased by more than double during 2001 and 2013. On a year-to-year basis, some new products were added to the export basket and some were ceased to be exported. However, there were 375 common products which Bangladesh exported all the years under consideration.


Figure 2 presents the numbers of products at 6-digit HS code where Bangladesh had comparative advantage during 2001 and 2013. In 2001, the number of products with RCA>1 was 316, which, with some year-to-year fluctuations, increased to 382 by 2013. The highest number of RCA>1 was observed in 2007 consisting 483 products. Figure 2 also suggests that the percentage share of RCA>1 products in total number of products declined over time: from 35% in 2001 to 19% in 2013. However, as a percentage of total exports, throughout those years, Bangladesh enjoyed comparative advantage in more than 97% of its total export. Furthermore, over those years, comparative advantage had been consistent for 130 products at the 6-digit level among which 115 products were from readymade garment industries. All these suggest that although Bangladesh was able to expand its export basket during 2001 and 2013, the number of products it had comparative advantage didn’t increase proportionately, which indicates escalated concentration of RCA in certain products.


The escalated concentration of RCA in certain products during the period under consideration is manifested by the fact that Bangladesh’s RCAs had been concentrated around the products in the HS codes 03 (fish and shrimp), 41 (raw hides and skins and leather), 52 (cotton yarn), 53 (raw jute), 61 (knitted readymade garments), 62 (woven readymade garments) and 63 (home textile and jute hessian bags). However, a close look at Figure 3 suggests that Bangladesh’s comparative advantage has been highly concentrated around the readymade garments sector. In 2013, number of products with RCA>1 under the HS codes 61, 62 and 63 accounted for 57% of the total number of products with RCA>1. In 2007, such number was 43%. It should also be mentioned here that, readymade garments account for more than 80% of total export earnings of Bangladesh in recent years.


Although RCA had been concentrated around the readymade garments sector, the average value of RCA declined. The maximum value of RCA in the readymade garments was 495 in 2001, which declined to 184 by 2013. Bangladesh had also been losing the very high comparative advantage it had in garments exports. Figure 4 suggests that, in 2001, Bangladesh enjoyed very high RCA (RCA>100) in 18 garments products, which declined to only 3 in 2013. In contrast, the number of products with RCA less than or equal to 30 increased over time: from 142 in 2001 to 181 in 2013.


Similar analysis, with respect to the leather and leather goods, suggests that there had not been much variations in the number of products having RCA in this sector. And, as in readymade garments sector, Bangladesh had been losing very high comparative advantage it had in this sector. In contrast, Bangladesh had been enjoying consistently very high comparative advantage in jute and jute products, where, in all of 6 products, RCA ranged between 53 and 1068.

The aforementioned analysis shows that during the period under consideration, Bangladesh’s comparative advantage had been concentrated around low-skilled labor intensive readymade garments exports. However, in recent years, compared to early 2000s, there had been some products where Bangladesh gained comparative advantage. These include edible fruits, animal and vegetable fats and oil, preparations of cereals, flour, starch or milk and pastry cooks’ products, preparation of vegetable, fruits, nuts, residues from food industries, rubber and rubber products, copper and copper products, and furniture. However, Bangladesh lost comparative advantage in fertilizers, printing industry’s products, articles of iron and steel, and miscellaneous manufactured articles.

Finally, we are interested to know how tariff rates, both at home and partner country, affect Bangladesh’s revealed comparative advantage at the sectoral level. For this exercise, we have constructed a panel data at 6-digit HS code level for the period between 2001 and 2013. The dependent variable is the RCA which is a binary variable, where it takes a value of 1 if RCA is greater than unity and zero otherwise. The first explanatory variable is the domestic tariff rate at 6-digit HS code level, which is the effectively applied tariff rate and its data is taken from the WITS database. The second explanatory variable is the partner country’s tariff rate, which is calculated as the weighted average of simple tariff rates imposed by top export destination partners of Bangladesh namely USA, EU, Canada and India. Data of partner countries’ tariff rates are taken from the WITS and OECD-WTO database. The fixed effect panel logit regression results suggest that domestic tariff rate is negatively associated with RCA and the coefficient is statistically significant. This suggests that a cut in domestic tariff raises the likelihood of RCA greater than unity among the sectors. In contrast, the coefficient of the partner countries’ weighted tariff rate is not statistically significant. The reason behind the non-association between the RCA and partner countries’ tariff rate could be because of the fact that the large part of Bangladesh’s export to its major partner countries are under different preferences schemes; for example, Bangladesh’s exports enjoy the duty free and quota free market access in the EU market.

Published at the Thinking Aloud on 1 June 2016