Significant growth rates are in many times associated with countries embracing the ongoing globalization and openness to the international market of exchanging goods and services as well as ideas and technologies. Many researchers believe that participating in an international economy is a primary source of growth. The question is how strong the relationship between openness and growth is and has interested many researchers. This paper aims to investigate the effects of trade openness on economic growth in the long run and begins from Adam smith`s discussion on absolute advantage and specialization to discussions on trade organizations and policies. This study explores the relationship between trade openness and economic growth using a sample of 3 developed countries over the period (1970 – 2006) in a panel data analysis. The fixed effects model analysis indicates that trade openness has a positive and significant effect on economic growth.

This thesis is concerned with volatility estimation using financial panels and bias-reduction in non-linear dynamic panels in the presence of dependence. Traditional GARCH-type volatility models require large time-series for accurate estimation. This makes it impossible to analyse some interesting datasets which do not have a large enough history of observations. This study contributes to the literature by introducing the GARCH Panel model, which exploits both time-series and cross-section information, in order to make up for this lack of time-series variation. It is shown that this approach leads to gains both in- and out-of-sample, but suffers from the well-known incidental parameter issue and therefore, cannot deal with short data either. As a response, a bias-correction approach valid for a general variety of models beyond GARCH is proposed. This extends the analytical bias-reduction literature to cross-section dependence and is a theoretical contribution to the panel data literature. In the final chapter, these two contributions are combined in order to develop a new approach to volatility estimation in short panels. Simulation analysis reveals that this approach is capable of removing a substantial portion of the bias even when only 150-200 observations are available. This is in stark contrast with the standard methods which require 1,000-1,500 observations for accurate estimation. This approach is used to model monthly hedge fund volatility, which is another novel contribution, as it has hitherto been impossible to analyse hedge fund volatility, due to their typically short histories. The analysis reveals that hedge funds exhibit variation in their volatility characteristics both across and within investment strategies. Moreover, the sample distributions of fund volatilities are asymmetric, have large right tails and react to major economic events such as the recent credit crunch episode.

This thesis focuses on the relationship between crime and education, as well as macroeconomic and demographic factors such as police efficiency, GDP per capita, employment rate, population density, age and sexual composition of the society. We use the data of fourteen regions of the Czech Republic from 2000 to 2012. First, we apply the fixed-effect model in the data analysis, and further we use GMM for the estimation of new dynamic panel dataset. In addition, taking the possible time effects into account, we also add the time dummies in both regression models. Our finding finds the unexpectedly positive effects of secondary education with A-level exam, GDP per capita and the proportion of population aged 30-59 years old on most of criminal offences. On the other hand, the male ratio in population and the clearance rate are found to influence crimes negatively. Higher education and employment rate are also found to be related negatively with economic crimes. JEL Classification A14, E69, I21, I23, I25, I29, J19, R19 Keywords education, crime, employment, GDP, gender ratio, age, the Czech Republic, panel data, fixed-effect, GMM Author's e-mail cindy1114@livemail.tw Supervisor's e-mail brizova.ies@seznam.cz

The subject of this thesis is the relationship that exists between deflation and the macroeconomic stability of the economy. Much literature has been published on this topic, but there is still a dearth of quantitative research based on strong empirical work. In the present work I have used a set of large panel data composed of 18 countries over 34 years in order to analyze the relationship between changes in inflation and output growth in a more complete and rigorous fashion. I use 3 different econometric models, namely fixed effects, random effects and the generalized method of moments. I chose these models in order to more appropriately examine the contemporaneous and lagged correlation between prices and output of countries. I also introduced foreign direct investment as a control variable to avoid the presence of potential bias. The empirical work presented in this paper leads to several findings. First, there is an insignificant relationship between a country's GDP growth and its deflation rate. Second, the relation between inflation and GDP growth is significant, and this relation becomes even positive when the econometric model is conducted on the data excluding outliers. Third, FDI positively contributes to and is partly responsible for the level of economic growth of the countries...

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Determinants of financial development Abstract The paper studies effects of country level determinants on the rate of financial development and, in particular, assesses the empirical question whether democracy and political freedom can enhance financial development, as measured by Bank Private Credit to GDP and Liquid Liabilities to GDP. Using Fixed Effects estimation techniques and a panel data for a list of 39 countries over the period 1990 to 2011, we provide evidence that suggests positive link between political openness and financial development. The empirical evidence also confirms financial openness and real per capita income to be positively correlated to financial deepening and in contrast, we find that size of financial sector does not spur the rate of financial development.

The aim of this thesis is to incorporate the effects of the indirect trade into the gravity model for Czech Republic. Using data from the recently released OECD-WTO TiVA database, a panel of 56 countries in 5 years between 1995 and 2009 is constructed. The traditional approach of estimating the log- linear form of the equation is questioned and in line with current academic research, the Poisson Pseudo Maximum Likelihood method is applied. The empirical analysis does not reveal any unambiguous effect of adjusting the gross exports for their foreign content; it rather confirms that Czech ex- ports are significantly driven by the demand for German exports and finds that they are the higher the greater is the share of services value added. Furthermore, it is found that the destination of Czech exports is not signif- icantly determined by target country's participation in global value chains. JEL Classification C13, C23, C67, F14, F60 Keywords gravity model, indirect trade, trade in value added, Czech Republic, Poisson regression, panel data Author's e-mail marek.wlazel@gmail.com Supervisor's e-mail vsemerak@yahoo.com

This thesis investigates the question if the estimation of gravity model of in- ternational trade based on the logarithmic transformation of the model is ad- visable when panel data are employed for the estimation. We have derived theoretically that in the presence of heteroskedasticity the logarithmic trans- formation causes inconsistency of the estimated coefficients. According to the literature, we have recommended rather the Poisson pseudo maximum likeli- hood estimation technique for the empirical research of the gravity model. We have also provided an empirical analysis of Czech and German panel data sets based on the comparison of the performance of traditional and Poisson estima- tion approaches. This analysis confirrms Poisson pseudo maximum likelihood estimation method as a more proper method for estimating the coefficients of the gravity equation.

The thesis aims at identifying the reasons behind the heterogeneous inflation performance of countries across Central and Eastern Europe. The impact of a large number of variables is being assessed in a dynamic panel data model covering 20 countries over the period 2003-2013. The empirical results suggest that cross-country differences in inflation are attributed to the structure of the economy, to the capital deepening effects and openness. Along with the structural factors, cyclical positions also prove to be of particular importance in explaining inflation across the region, since during the last decade most of the Central and Eastern European countries have experienced fast GDP growth, a credit boom and increased domestic demand that in turn fueled inflation.

One of the most visible signs of the globalization of the world economy is the increase of Foreign Direct Investment (FDI) inflows across countries. This past decade the trend of FDI has shifted from developed countries to emerging economies, which is most notably in the BRICS countries. However, as BRICS reputation has been damaged these past years due to its weak growth outlook in the early 2010s, investors are shifting to the new economic grouping acronym, the MINT (Mexico, Indonesia, Nigeria and Turkey) countries for better future prospects of FDI destination. Since the MINT countries have emerged as a popular destination of FDI, it is necessary to investigate what are the key factors that make these four countries attractive as FDI destinations. Hence, this paper analyzes what are the determinants of inward FDI into the MINT countries during the time period from 1990 to 2014. To be able to answer the research question and demonstrate the effect of the seven independent variables (market size, economic instability, natural resources availability, infrastructure facilities, trade openness, institutional stability and political stability) on FDI as a dependent variable, the study uses a panel data analysis. The data is based on secondary data, which is collected from the World Bank dataset. The empirical finding from the study illustrates that market size, economic instability, infrastructure facilities, trade openness, institutional stability, and political stability are significant as determinants FDI inflows to the MINT countries, meanwhile, natural resources availability appears to be an insignificant determinant of FDI inflows to the MINT countries.