BUS613: Advanced International Business

Prior to observing the potential long- and short-run impact of infrastructure on export and trade deficit, it is essential to create the order of integration among the selected variables because if the variable(s) are integrated of order I(2) the results do not remain valid. For this reason, Levine et al. and Im et al.  unit root tests are employed to examine the order of integration among the chosen variables. The results in Table 2 point out that all variables are either integrated of order I(1) or I(0) and no one of the variables is integrated of order I(2) or above, which clearly support the Pooled Mean Group (PMG) estimation procedure rather than other alternative cointegration technique.

Table 2 Unit root test results

The descriptive statistics of the explanatory variables is shown in Appendix 2. Appendix 3 presents the Pearson correlation coefficients among all the selected variables of the present study. It can be seen from Appendix 2 that there is strong positive correlation between the export and all others explanatory variables. On the other hand, there is a strong negative correlation between trade deficit and all other independent variables. In the subsequent regression, in order to alleviate the interference of multicollinearity on the regression results, there is no multicollinearity problem in our selected variables.

The empirical results in Table 3 show the outcomes of the PMG heterogeneous panel procedure. The result exhibits notable variations subject to the method of estimation. The PMG estimation result shows that a plausible long-run impact of aggregate and sub-indices of infrastructure (transport, telecommunication, energy, and financial sector) on export is positive and significant at 1% level in selected South Asian economies. The significant role of aggregate and all other sub-indices of infrastructure in exports confirm the findings of Donaubauer et al. and Brooks and Menon. Thus we reject the null hypothesis of no impact of independent variables on dependent variables, rather we accept alternative hypotheses. The empirical results are consistent with the opinion that, infrastructure matters to trade mainly because they decrease the cost of trade and ensure the ease of doing business in host economies. Lower trade costs raise the potential for increased export markets. This study uses the South Asian economies which are less developed countries. So, Garsous argues that the larger the number of developing countries in the sample, the more likely a positive impact of infrastructure on trade is likely to be observed. This would lead to the conclusion that the less developed the country, the more likely infrastructure will matter. Andrés et al. and Asif and Rehman found that infrastructure development has been a main determinant in reducing Asia's trade costs and thereby export expansion. Among the infrastructure the effects of other control variables, i.e., exchange rate (ln_EXR), human capital (ln_HC), per capita GDP (ln_PGDP), institutional quality index (ln_IQ) on exports is significant in all columns. It indicated that the undermentioned control variables increase the export significantly, except exchange rate which is consistently negative and significant in the present results. It presents that, when the  exchange rate of a host economy increases, automatically the price seems to be high. So export will decrease. The results are in the line of Sahoo and Dash and Ayogu. Similarly, institutional quality has a significant positive impact on export. It signifies that better quality of institutions significantly encourage export in the domestic economy. These empirical results negate the claim of Khan et al. that institutional quality does not contribute to export in South Asian economies. Furthermore, it can be seen in the lower half of Table 3, that in the short run, most independent variables are insignificant except aggregate infrastructure (ln_GINFRA), which is significant in both the short and long run.. The values of ECT₍₋₁₎ in Table 3 show slow adjustment to equilibrium position by exports. Likewise, in the present study, most of the developing countries experience persistent low economic growth; it is very likely that such a long-run relationship exists. However, there is little evidence to suggest their speed of adjustment to the long-run steady state should be the same.

Table 3 Pooled Mean Group method results (export is dependent variable)