Essays on corruption, inequality, and economic growth.
PhD thesis, University of Glasgow.
Full text available as:
This thesis investigates novel and unique avenues of corruption in an attempt to reach a better understanding of the causes of corruption. In particular, the thesis theoretically and empirically examines the implication of the military in politics in breeding corruption and the importance of financial development in reducing corruption. The thesis also improves our understanding of cross-country variations in inequality and economic growth by providing a deeper analysis of growth-inequality relationship with a particular focus on the role of globalisation and domestic policy reforms.
To achieve this aim, the thesis contains four core chapters (essays) in addition to an introductory chapter, literature review chapter and a concluding chapter. The four core chapters can be viewed different from one another. The first two core chapters address the causes of corruption. In particular, the first of these two chapters assess the role of military in politics in determining corruption levels, and investigate how important financial development is for corruption. The other two core chapters provide deeper understanding of cross-country variations in inequality, poverty and economic growth.
Recent theoretical developments and case study evidence suggests a relationship between the military in politics and corruption. In the third chapter, this study contributes to this literature by analyzing theoretically and empirically the role of the military in politics and corruption for the first time. By drawing on a cross sectional and panel data set covering a large number of countries, over the period 1984-2007, and using a variety of econometric methods substantial empirical support is found for a positive relationship between the military in politics and corruption. In sum, our results reveal that a one standard deviation increase in the military in politics leads to a 0.22 unit increase in corruption index. This relationship is shown to be robust to a variety of specification changes, different econometric techniques, different sample sizes, alternative corruption indices and the exclusion of outliers. This study suggests that the explanatory power of the military in politics is at least as important as the conventionally accepted causes of corruption, such as economic development.
The importance of financial market reforms in combating corruption has been highlighted in the theoretical literature but has not been systemically tested empirically. In the fourth chapter, we provide a first pass at testing this relationship using both linear and non-monotonic forms of the relationship between corruption and financial intermediation. Our study finds a negative and statistically significant impact of financial intermediation on corruption. Specifically, the results imply that a one standard deviation increase in financial intermediation is associated with a decrease in corruption of 0.20 points, or 16 percent of the standard deviation in the corruption index and this relationship is shown to be robust to a variety of specification changes, including: (i) different sets of control variables; (ii) different econometrics techniques; (iii) different sample sizes; (iv) alternative corruption indices; (v) removal of outliers; (vi) different sets of panels; and (vii) allowing for cross country interdependence, contagion effects, of corruption.
In the fifth chapter, we examine the impact of globalisation on cross-country inequality and poverty using a panel data set for 65 developing counties, over the period 1970-2008. The role of globalisation in increasing inequality in economies with financial markets imperfections has been highlighted in the theoretical literature but has not been systemically tested empirically. We provide a first pass at testing this relationship between globalisation and inequality in the presence of underdeveloped financial markets. Our study finds a negative and statistically significant impact of globalisation on poverty in economies where financial systems are relatively developed, however, inequality-reducing effect of globalisation in these economies is limited. The other major findings of the study are five fold. First, a non-monotonic relationship between income distribution and the level of economic development holds in all samples of countries. Second, both openness to trade and FDI do not have a favourable effect on income distribution in all selected developing countries. Third, high financial liberalization exerts a negative and significant influence on income distribution in developing countries. Fourth, inflation seems to distort income distribution in all sets of countries. Finally, the government emerges as a major player in impacting income distribution in developing countries.
In the last core chapter, we analytically explore and empirically test the relationships between economic growth, inequality and trade. This study contributes in the existing literature by answering the question why growth effects of income inequality and trade are not definitely positive or negative. This study determines the positive effects of inequality and trade on growth both in the short run and long run. However, the growth effect of inequality is substantially influenced by the domestic context in terms of the prevalence of credit market imperfections. The study identifies credit market imperfections in low-income developing countries as the likely reason for a positive relationship between inequality and economic growth. Similarly, growth effect of trade is found to be negative in economies where inequalities are comparatively high. The results show that inequality does matter for economic growth, but in different ways for different regions at different levels of economic development. The inequality-growth nexus is significantly negative for the low-income group but strongly significantly positive for the high-income one. The findings of the study are robust to alternative econometric techniques, specifications, control of nonlinearity, inclusion of additional control variables, exclusion of outliers and sub-samples.
Actions (login required)