Political Institutions and the Incidence of FDI in South Asia

Abstract

This paper attempts to empirically analyse the potential effect of political institutions on the inward foreign direct investments (FDIs) in five developing nations from South Asia, namely, Pakistan, Nepal, India, Bangladesh and Sri Lanka. Making FDI implies committing resources for a long time in the host economy. Therefore, availability of stable political institutions is one of the essential foreign location requisites for the multinationals' operations. Analysing annual aggregate data for years 1970 to 2009 through random effect panel estimation technique it is found that institutional indicators which count the most for foreign direct investors in SAARC nations are democratic accountability, absence of military and religious influences in politics, corruption-free and honest public office holders, and efficient bureaucracy. The results clearly indicate that changes in institutional variables do not make a significant positive impact on inward FDIs when aggregate measures of political institutional efficiency are employed. However, when these collective measures are disaggregated to a more clearly focused set of factors, their increased effectiveness significantly leads to additional FDI inflows. These results suggest that the findings are robust to alternative proxies of institutional strength, but sensitive to using catch-all composite measures of institutions.

Factors Affecting Commercial Banks Profitability in Pakistan

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Does governance quality matter for FDI-led tourism development? A supply-side perspective

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“…The summary of all the descriptive statistics for the variables used in the analysis are given as table Hausman(1978) specification test statistic of 45.69 showed a significant difference, as pvalue was less than 1% and hence H 0 is rejected in favour of H 1, implying that only fixed effect estimator is appropriate (Shah& Khan, 2018).Breush-Pagan/Cook-Weisberg test revealed the presence of heteroscedasticity (Shah, 2017b). Thus, robust standard errors are reported in all the estimations (Shah & Afridi, 2015).Initially,Variance Inflation Factor (VIF) test revealed that multicollinearity is severe .…”