Analysing Potential Effects of Preferential Liberalisation in Some Asian Emerging Economies

Abstract

This paper examines the ex-ante effects of possible trade liberalisation of some Asian emerging economies through forming a regional economic bloc called BIMSTEC by adopting SMART and GTAP models. Based on estimated export supply elasticity, the results of SMART simulation reveal that the highest net trade effect takes place for India, the biggest economy in the bloc, followed by Bangladesh for tariff elimination. The two countries also derive substantial welfare gains. The proportionate revenue loss is remarkably higher for smaller countries such as Nepal, Myanmar and Bangladesh. GTAP simulation suggests that Bangladesh incurs a net welfare loss by joining the FTA. The overall intra-bloc export is likely to increase. These results imply that there is a need for designing proper compensation mechanism and technical support for the smaller economies to offset the possible adverse effects.

Keywords:

• Regionalization
• trade liberalization
• economic modelling

JEL CLASSIFICATIONS :

• F15
• F19
• C53

Notes

¹Kabir and Salim (2010) reveal that export enhancement effect of BIMSTEC is 28.53%.

²Summers (1991) argues that when the members of trading arrangements are natural trading partners, i.e. they trade substantially with each other and are geographically proximate; the risk of trade diversion becomes minimal. However, Bhagwati and Panagariya (1996) systemically demonstrate that the hypothesis of natural trading partners does not have any analytical basis.

³It comprises 87 regions and 57 sectors and specifically Bangladesh, India, Sri Lanka and Thailand of the BIMSTEC members separately and Myanmar, Bhutan and Nepal in the other regional groups.

⁴SMART adopts the partial equilibrium model described in Laird and Yeats (1986, 1990). In the literature, the model is frequently referred to be ‘SMART model’.

⁵A similar model has been adopted by Milner et al. (2005) who use the estimated values of demand elasticity by Stern et al. (1976) and rely on Armington's elasticity of substitution.

⁶The procedure of calculating XRER is as follows. At the first stage, the bilateral exchange between individual countries (i) and their major export countries (j) (listed in Appendix Table 2), ER _ij , is calculated. This is used to calculate real bilateral exchange rate in the following way:

where, D _j and D _i are GDP deflators of destination and local countries respectively. Then an RER index has been calculated, taking 1995 as base year as follows:

Finally, the weighted average of RERI _ij is used to construct an export-weighted XRER for home countries according to their export shares such that .

⁷Pesaran and Shin (1999) show that both FMPH-OLS and ARDL estimators are applicable in small sample (even for n=20). However, based on Schwarz Criterion (SC) ARDL performs better than FMPH-OLS. As they notice, ‘The ARDL-SC procedure when combined with the Δ-method of computing the standard errors of the long-run parameters generally dominates the Phillips-Hansen estimator in small samples. This is in particular true of the size-power performance of the tests on the long-run parameter’ (Pesaran & Shin, 1999, p. 374).

⁸The results of the tests are not reported in the paper. However, these can be made available upon e-mail request to the corresponding author.

⁹The bounds test is a simple F-test to determine the joint significance of the lagged variables.

¹⁰The explanatory variables have not been found to be cointegrated for any of the BIMSTEC countries, which meets the requirement of the FMPH-OLS (Pesaran & Pesaran, 1997).

¹¹The full results can be made available upon request.

¹²By definition, the terms of trade effect is the effect of a tariff on the relative price of a country's exports on world market compared with its imports. When a large country imposes a tariff, it causes a reduction of import demand and thus reduces the price of the imported goods relative to its exports, and improves its terms of trade.

¹³Panagariya (1999a) also argues that ROOs may counteract trade diversion. By stepping ahead, Duttagupta and Panagariya (2007) demonstrate that ROOs can improve the political viability of FTAs.

¹⁴The base year of the data is 2004. See, Narayan and Walmsley (2008) for details on the database.

¹⁵In the GTAP database, the subsidy variables for BIMSTEC countries are: (i) percentage ad valorem rate of output subsidies in region r; (ii) percentage ad valorem rate of export subsidies; (iii) MFA export subsidy equivalent; (iv) ordinary export subsidy; and (v) ordinary output subsidy.