BUS613: Advanced International Business

To assess the impact of infrastructure on exports and trade deficit over the period of 1990–2017, we rely on a new Global Infrastructure Index used by Donaubauer et al.. The detail regarding this infrastructure index is given by Donaubauer et al.. Most importantly the devised index contains further four sub-indices of infrastructure, i.e., transport, telecommunication, financial and energy to better understand the role of physical infrastructure in enhancing exports and decreasing trade deficit in selected South Asian countries (i.e., Bangladesh, Bhutan, Nepal, India, Pakistan, Sri Lanka). This new Global Infrastructure Index contains 30 indicators in order to cover all the important dimensions of quality and quantity infrastructure. The Unobserved Components Model (UCM) is used to determine the weight given to each component in the construction of the index. Similarly, we uses Quality of Institution Index (ln_QI), which is a composite index constructed on data collected from the International Country Risk Guide (ICRG). The developed index takes six variables of institutional quality like, law and order situation, corruption, government stability, investment profile, bureaucratic quality and democratic accountability are taken into consideration for the aim of to cover all the key extents of institution quality, by taking the average of all these six variables. The details about this index are found in Rehman and Ding. 

Furthermore, this is a panel data study and heterogeneity would be a major concern since the panel is a combination of time-series and cross-sectional data. The size of the countries in the present study is not homogenous, thus, we convert the selected monetary variables into per capita form such as export, trade deficit, exchange rate and per capita GDP. In the case of the nominal form of the monetary variables, the variation of the variables might also be due to the change in price. Thus, the analysis fails to capture the actual impact of the variables on trade. So the undermentioned variables are divided by their respective country's population.

The selected variables naming, Global Infrastructure Index and trade deficit consist of negative values which we convert into positive by dividing − 1 before taking natural log (LN). It is important to standardize the measurement of the variables, as it will improve fitness and homogeneity. The natural logarithm is a reliable method of the many methods. This study has taken the initiative to standardize the measurement in order to gain better and more meaningful interpretation as well. Table 1 presents the selected dependent and independent variables, notation, data description in braces and the sources. Moreover, all variables are converted into natural logs.