This thesis addresses the question, whether the impact of financial development on the relative and absolute indicators of poverty is dependent on the levels of the human capital present in an economy. To answer this question, first we develop a theoretical framework to explain the growth process in the context of financial development assuming that human capital is heterogeneous in terms of the skills and education people have. Then, by using the data sets based on five-year averages over 1960-2010 and 1980-2010, covering 107 developed and developing countries, we empirically investigate the extensions of the theoretical framework developed earlier. These extensions cover the relationships between: 1. Income inequality and economic growth 2. Financial development, human capital and income inequality, and 3. Financial development, human capital and poverty We provide empirical evidence using modern panel data techniques of dynamic and static GMM. The findings elucidate that income inequality and economic growth are inter-dependent on each other. There exists an inverse relationship between initial inequality and economic growth. The changes in income inequality follow the pattern identified by Kuznets (1955) known as Kuznets’ hypothesis. The results also show that financial development helps in reducing income inequalities and in alleviating poverty, only when there is a sufficient level of human capital available. On the basis of our findings we develop the term "effective financial development" which means that financial development is effective in accelerating growth levels, reducing income inequalities and alleviating poverty only if there is a sufficient level of human capital available. The empirical study covers multiple aspects of financial development like private credit extended by banks and other financial institutions, liquid liabilities and stock market capitalization. The results of the empirical investigations are robust to multiple data sets and various indicators of income inequality, financial development, poverty and human capital. The study also provides marginal analysis, which helps in understanding the impact of financial development on inequality and poverty at different levels of human capital. This research study of effective financial development can be a useful learning paradigm for the academics and researchers interested in growth economics and keen to learn how poverty and income inequality can be reduced effectively. This study can also be useful for the policy makers in the financial institutions, because it provides robust empirical evidence that shows that financial development cannot help in alleviating poverty and in reducing inequalities unless there is a sufficient level of human capital available. The findings can be useful for policy makers, particularly in the developing countries where high levels of income inequalities and poverty are big problems. This study explains the mechanism of how effective financial development can be used to reduce income inequalities and to alleviate poverty. It also explains the process of inter-linkages between financial development, human capital, inequality, economic growth and financial instability. The policy makers can also take advantage from the marginal analyses that illustrate the minimum levels of private credit and primary and secondary schooling above which the effects of financial development and human capital become significant in reducing inequalities and poverty.

This thesis is in two parts. The first part considers a theoretical relationship between the natural variability of a stochastic model and its response to a small change in forcing. Over a large enough scale, both the real climate and a climate model are characterised as stochastic dynamical systems. The dynamics of the systems are encoded in the probabilities that the systems move from one state into another. When the systems’ states are discretised and listed, then transition matrices of all these transition probabilities may be formed. The responses of the systems to a small change in forcing are expanded in terms of the eigenfunctions and eigenvalues of the Fokker-Planck equations governing the systems’ transition densities, which may be estimated from the eigenvalues and eigenvectors of the transition matrices. Smoothing the data with a Gaussian kernel improves the estimate of the eigenfunctions, but not the eigenvalues. The significance of differences in two systems’ eigenvalues and eigenfunctions is considered. Three time series from HadCM3 are compared with corresponding series from ERA-40 and the eigenvalues derived from the three pairs of series differ significantly. The second part analyses a model of the coupled climate-economic system, which suggests that the pace of economic growth needs to be reduced and the resilience to climate change needs to be increased in order to avoid a collapse of the human economy. The model condenses the climate-economic system into just three variables: a measure of human wealth, the associated accumulation of greenhouse gases, and the consequent level of global warming. Global warming is assumed to dictate the pace of economic growth. Depending on the sensitivity of economic growth to global warming, the model climate-economy system either reaches an equilibrium or oscillates in century-scale booms and busts.

The most essential questions in economics is what determines economic growth? In theory FDI led to economic growth (Mello 1997), but empirical evidences indicate that the relationship is ambiguous (Masahiro & Iwasaki 2014). This thesis uses contemporary growth theories and econometric methods to empirically test for the association between foreign direct investment and economic growth in the six countries that form the Gulf Cooperation Council (GCC). The analysis indicates a positive relationship concerning FDI and GDP growth in the panel of GCC. The result furthermore supports the endogenous growth theory and provide insights on the regions progress towards income diversification whit respect to hydrocarbons.

For several years, the literature has discussed whether a country’s particular economic circumstances should be taken into account in competition law and policy design. This thesis discusses whether economic growth should be considered as the guiding principle for Latin American Emerging Economies’ competition law and policy design. It specifically explains why having economic growth as competition policy’s guiding principle makes a difference in choosing superior rules and standards, among the large range of efficient rules. In order to explain how economic growth as a guiding principle has an impact on competition policy design, this thesis studies whether the analysis and application of the prohibitions and standards of abuse of dominance in emerging Latin American economies are appropriate, and why, having regard to economic growth, a different approach might be justified. To engage in the study of such questions this thesis centres on the regulation of dominance and the law governing abuse of dominance, in particular on predatory pricing and excessive pricing. After a careful analysis of such institutions, an optimal rule for the regulation of pricing abuses in these emerging economies is proposed. Similarly, having regard to economic growth as the policy’s guiding principle, the mainstream standards on excessive pricing and price predation are evaluated and a different approach is found to be justified. It is concluded that economic growth should be the principle guiding Latin American emerging economies’ competition law and policy design and it is demonstrated that this will grant these economies policy soundness and identity.

In this study an attempt has been made to explore the role of technology transfer in the economic growth of Iraq, through the change in the technology itself for the period 1960-1978. For this purpose the economy was disaggregated into seven sectors. The experience of developed countries has shown that technical change is one of the most important factors of economic growth alongside, or even overshadowing, such factors as labour and capital. In the light of technology transfer, developing countries have the advantage of introducing high levels of advancement of knowledge which can be used to induce domestic technical change at later stages. Technical change is normally defined as a shift in the production function, and for this reason two forms of production function were estimated and tested, i. e. the constant elasticity of substitution and the Cobb-Douglas function. Also two specifications (constant and variable) were assigned to technical change. To validate the use of these, statistical tests were conducted to establish the optimum fit. Then the selected form was used to simulate output levels for comparison with actual figures. The techniques used for estimation are both linear and non-linear. Data used are time series in real terms of capital stock and output, as well as number of persons employed. Furthermore in order to judge the importance of technical change to the growth of output on aggregate and sectoral levels, as regards economic growth, comparisons were drawn with existing data from other developed and developing countries, including centrally planned economies.

This thesis complements current studies by focusing on developed OECD countries as they are the major sources and recipients of world FDI and current studies relating to developed countries using aggregate country FDI data are limited. This study empirically tests the determinants of FDI inflows and outflows and their relationship with economic growth using 2SLS simultaneous equations model between 1981 and 2008 for a sample of 20 developed OECD countries. The empirical findings suggest that FDI inflows do not contribute to economic growth in the host country and economic growth positively affects FDI inflows. In addition, trade openness and flexible employment protection legislation in the host country attract FDI inflows. In terms of FDI outflows, the results show that FDI outflows reduce economic growth in the home country, while economic growth in the home country increases FDI outflows. Moreover, high past level of outward FDI stock, trade openness, low labour cost and currency depreciation in the home country provide incentives for domestic firms to invest abroad. Therefore, this study does not support offering special incentives to foreign investors to attract FDI inflows or offering promotional policies to domestic firms to encourage FDI outflows. Instead, government should provide incentives for domestic investment and other sound policies to increase economic growth, which in itself provides a good environment to attract FDI inflows and to encourage FDI outflows. Keywords: FDI inflows, FDI outflows, two stage least squares simultaneous equations, economic growth, labour market flexibility.

This paper uses Bayesian Model Averaging (BMA) to find robust determinants of economic growth in a new dataset of 255 European regions between 1995 and 2005. The paper finds that income convergence between countries is dominated by the catching-up of regions in new member states in Central and Eastern Europe (CEE), whereas convergence within countries is driven by regions in old EU member states. Regions containing capital cities are growing faster, particularly in CEE countries, as do regions with a large share of workers with higher education. The results are robust to allowing for spatial spillovers among European regions.

A Research Report presented to the Graduate School of Business Leadership University of South Africa. In partial fulfilment of the requirements for the MASTERS DEGREE IN BUSINESS LEADERSHIP, UNIVERSITY OF SOUTH AFRICA / The purpose of this research is to analyse the changes in housing values in Windhoek, Namibia over the past ten years and explore links in property value variation to macroeconomic changes during that period. The objectives of this research are twofold. Firstly this research compiles and assesses the movement of housing values over the past ten years. Secondly this research assesses if there is a causal relationship between changes in macroeconomic factors and housing values, and to define the nature of this relationship. The timing and magnitude of response by housing values to changes in macroeconomic factors are investigated. The primary data requirements for this study are a monthly relative value index of housing prices for the Windhoek area and macroeconomic factors. Macroeconomic data collected relates to macroeconomic conditions within Namibia that could have an effect on housing prices. This includes information on housing supply, GDP, population levels, inflation and interest rates. The results of this study explore the relationship between these factors and changes in housing prices as reflected by changes in the housing index. The most significant result of this study is the effect of housing availability on housing values. Changes in the total supply of housing as estimated by the number of houses built in a month affect changes in housing values after 5 and 6 months. A total of 20.5% of the change in housing values can be explained by the change in total housing supply. The effect of interest rates found by this study was lower than the theory and literature reviews would have led us to expect. The results of the Pearson correlation test for the relationship between percentage changes in interest rates and percentage changes in future housing values found that a relationship exists 8 months after the change in interest rates occurred. Interest rates were found to explain 5.5% of the change in housing values 8 months later. No significant effects were noted for changes in inflation. For population and income changes there was insufficient data to perform more than a high level look at possible interactions with the level of housing prices. / Graduate School of Business Leadership / MBL

The importance of tax system structure for economic growth in OECD countries - Extreme Bounds Analysis Abstract The thesis examines the importance of tax system structures for economic growth in OECD countries. It aims to find out whether a revenue-neutral tax reform can promote economic growth. In other words, its objective is to identify taxes which are most harmful for economic growth and suggest tax policy implications accordingly. The extreme bounds analysis is employed to examine the robustness of relationship between particular taxes and the growth rate. This method consists in running a number of regressions and observing how the coefficients respond to various model alterations. The results suggest that taxes levied on personal income have a robust negative impact on economic growth. On the other hand, consumption and property taxes appear to be non-significant predictors of economic growth. The policy implication is drawn that a revenue-neutral tax reform shifting the tax burden from personal income towards consumption and property is likely to boost the economy. JEL classification: H21, H24, H27, O11, O47 Key words: tax system structure, economic growth, extreme bounds analysis, tax reform

Doctor of Philosophy / Department of Economics / Lance J. Bachmeier / This dissertation consists of three essays in nonlinear macroeconomic modeling and econometrics. In the first essay, we decompose oil price movements into oil demand (stock market) shocks and oil supply (oil-market) shocks, and examine the response of the stock market to these shocks. We find that when oil prices are “net-increasing”, a stock market shock that causes the S&P 500 to rise by one percentage point will cause the price of oil to rise approximately 0.2 percentage points, with a statistically significant positive effect one day after the stock market shock. On the other hand, the response of the stock market to an oil market shock is a decline of 6.8 percent when the price of oil doubles. For other days, the initial response of the oil market to a stock market shock is the same as in the net oil price increase case (by construction). We then analyze the response of monetary policy to the identified stock market and oil market shocks and find that short-term interest rates respond to the stock market shocks but not the oil market shocks. Finally, we evaluate the predictive power of the decomposed stock market and oil shocks relative to the change in the price of oil. We find statistically significant gains in both the in-sample fit and out-of-sample forecast accuracy when using the identified stock market and oil market shocks rather than the change in the price of oil. The second essay revisits the statistical specification of near-multicollinearity in the logistic regression model using the Probabilistic Reduction approach. We argue that the ceteris paribus clause invoked with near-multicollinearity is rather misleading. This assumption states that one can assess the impact of near-multicollinearity by holding the parameters of the logistic regression model constant, while examining the impact on their standard errors and t-ratios as the correlation (\rho) between the regressors increases. Using the Probabilistic Reduction approach, we derive the parameters (and related statisitics) of the logistic regression model and show that they are functions of \rho , indicating the ceteris paribus clause in the traditional account of near multicollinearity is unattainable. Monte carlo simulations in the paper confirm these findings. We also show that traditional near-multicollinearity diagnostics, such as the variance inflation factor and condition number can fail to detect near-multicollinearity. Overall, the paper finds that near-multicollinearity in the logistic model is highly variable and may not lead to the problems indicated by the traditional account. Therefore, unexpected, unreliable or unstable estimates and inferences should not be blamed on near-multicollinearity. Rather the modeler should return to economic theory or statistical respecification of their model to address these problems. The third essay examines the correlations between income inequality and economic growth using a panel of income distribution data for 3,109 counties of the U.S. We examine the non-spatial dynamic correlations between county inequality and growth using a System GMM approach, and find significant negative relationships between changes in inequality in one period and growth in the subsequent period. We show that this finding is robust across different sample sizes. We further argue that because the space-specific time-invariant variables that affect economic growth and inequality can differ significantly across counties, failure to incorporate spatial effects into a model of growth and inequality may lead to biased results.We assume that dependence among counties only arises from the disturbance process, hence the estimation of a spatial error model. Our results indicate that the bias in the parameter for inequality amounts to about 2.66 percent, while that for initial income amounts to about 21.51 percent.