The study examines the influence (effects) of export diversification in defining economic growth differences across Africa and it tests its robustness in different samples and estimation techniques compared to other variables of trade namely, trade openness and export growth. It applies an augmented Solow growth model in a cross-section dataset for the period of 1998 to 2009 with all three trade variables tested under a single framework. It is found that countries with more diversified exports generally experienced faster economic growth; therefore, variation in export diversification levels explains the observed growth differences across Africa. The results show that both export diversification and export growth are robust determinants of economic growth rates in the region while trade openness is not. The findings have a strong bearing on trade policy by emphasising the importance of more diversified exports to mitigate the negative impacts of global economic shocks to economic growth in the region.

Does the choice of exchange-rate regime effect the economic growth performance of a country? And does the significance of such a relationship vary across different levels of development? Few questions in international economics, whether it be in academic or policy circles, have inspired as much debate yielding as little consensus. Although both economic growth theory and empirical literatures suggests the existence of direct and indirect channels, through which the choice of regime may indeed impinge the growth rate, neither has managed to provide an unambiguous answer. The aim of this paper is to analyze the theoretical arguments as to the relationship between the choice of exchange-rate regime and economic growth and to empirically investigate if there is an optimal regime, in terms of growth, and if the significance of this impact differs across various levels of country development. Applying a cross-sectional regression estimation of 60 countries over the period 2000-2010, this paper finds that the choice of exchange-rate regime holds no significant explanatory power over economic growth. These findings were robust to dividing the sample based on the level of country development. Although no direct relationship was found, these findings supports the argument that the choice of regime may indeed effect growth indirectly, through its impact on other deterministic growth factors, such as trade, investment and productivity. The findings of this paper are both in accord and discord with previous results and underlines how divergent the empirical research is on this continuously debated issue.

This paper investigates whether national and entrepreneurial framework conditions positively affect economic growth via its effects on entrepreneurial activity more significantly than via its effects on technological innovation intensity1 . The revised GEM conceptual model is tested for a sample of Nordic countries (Norway, Finland, Sweden, Denmark, Iceland), between the years 2005-2014, using path analysis. The variables representing national and entrepreneurial framework conditions, entrepreneurial activity, technological innovation intensity and economic growth are Global Competitiveness Index (which includes also number of procedures to start a business and number of days to start a business, venture capital availability etc.), selfemployed workers (expressed as % of total employed), RD expenditures (expressed as % of GDP) and GDP per capita. In each of the models, the author finds out a positive effect of national and entrepreneurial framework conditions. The hypotheses stating the positive indirect influence of national and entrepreneurial framework conditions on economic growth via entrepreneurial activity (H1) and the positive indirect influence of national and entrepreneurial framework conditions via technological innovation intensity (H2) have been accepted. The calculated total effect on economic growth indicates that the path via entrepreneurship (H1) is more significant (H3).

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This dissertation adds to the literature on least squares model averaging by studying and extending current least squares model averaging techniques. The first chapter reviews existing literature and discusses the contributions of this dissertation. The second chapter proposes a new estimator for least squares model averaging. A model average estimator is a weighted average of common estimates obtained from a set of models. I propose computing weights by minimizing a model average prediction criterion (MAPC). I prove that the MAPC estimator is asymptotically optimal in the sense of achieving the lowest possible mean squared error. For statistical inference, I derive asymptotic tests on the average coefficients for the "core" regressors. These regressors are of primary interest to researchers and are included in every approximation model. In Chapter Three, two empirical applications for the MAPC method are conducted. I revisit the economic growth models in Barro (1991) in the first application. My results provide significant evidence to support Barro's (1991) findings. In the second application, I revisit the work by Durlauf, Kourtellos and Tan (2008) (hereafter DKT). Many of my results are consistent with DKT's findings and some of my results provide an alternative explanation to those outlined by DKT. In the fourth chapter, I propose using the model averaging method to construct optimal instruments for IV estimation when there are many potential instrument sets. The empirical weights are computed by minimizing the model averaging IV (MAIV) criterion through convex optimization. I propose a new loss function to evaluate the performance of the estimator. I prove that the instrument set obtained by the MAIV estimator is asymptotically optimal in the sense of achieving the lowest possible value of the loss function. The fifth chapter develops a new forecast combination method based on MAPC. The empirical weights are obtained through a convex optimization of MAPC. I prove that with stationary observations, the MAPC estimator is asymptotically optimal for forecast combination in that it achieves the lowest possible one-step-ahead second-order mean squared forecast error (MSFE). I also show that MAPC is asymptotically equivalent to the in-sample mean squared error (MSE) and MSFE. / Thesis (Ph.D, Economics) -- Queen's University, 2013-07-17 15:46:54.442

Using data from the Global Entrepreneurship Monitor, I explored the long-term effect of entrepreneurial activities on economic growth. With both cross-sectional and panel analysis, I found that it is not the overall participation in entrepreneurial activities that relates to economic growth but only the portion engaged in opportunity-motivated entrepreneurship that explains higher growth. On the contrary, the necessity-driven entrepreneurship negatively impacts economic growth. Further, I found that the positive effect of opportunity-motivated entrepreneurship is stronger for countries that are more developed and with better gender balance in entrepreneurial business. The positive effect is also bigger in more recent time periods.

Economic integration starts to be achieved faster through the international labor mobility than due to international trade or capital movements. Remittances, important international capital flows, became one of the most discussed topics in world. The migrant's transfers have become the primary source of existence in Moldova. This paper using data on transfer of funds for the period 1995-2010, attempts to examine the relationship between remittances and financial development, economic growth and investment level of Republic of Moldova. The main finding of this study is that remittances influence significantly the economic growth, the investment level. Moreover, these funds substitute for a shortage of development of the financial system and therefore promote growth. Keywords: Remittances, migrant, financial development, investment, economic growth, formal and informal channel. Author's e-mail: oti_marculescu@mail.ru Supervisor's e-mail: cahlik@fsv.cuni.cz