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This thesis investigates, theoretically and empirically, the impact of financial (FL) and trade liberalisation (TL) on the rate of economic growth in Bangladesh using annual data from 1975-1995. This thesis also explores the determinants of unofficial market (UM) exchange rates in Bangladesh using quarterly data from 1976q2-1995q2. The literature survey in chapter two argues that both FL and TL raise the rate of economic growth. After reviewing financial and trade policies in Bangladesh in chapter three, a theoretical model has been developed and applied to Bangladesh in chapter four in order to examine the effect of FL on the rate of economic growth. This model incorporates per capita real income, investment in both physical and human capital, financial deepening and real interest rates. The theoretical and empirical models reveal that investment in human capital, financial deepening and interest rate liberalisation positively affect the rate of economic growth. However, the impact of interest rates is very low. The simultaneous impact of financial development and TL on the rate of economic growth in Bangladesh is also explored theoretically and empirically in chapter six. Results reveal that both FL and TL jointly raise the rate of economic growth. Finally, the determinants of UM exchange rates are identified in chapter eight in order to examine the causes of distortions in the foreign exchange markets and to explore the roles of both FL and TL policies in removing these distortions. It is observed that trade restrictions with overvalued exchange rates and an increase in money supply generate UMs for foreign exchange in Bangladesh.

The purpose of this study is to investigate the nature and role of organisational commitment among public sector employees in Saudi Arabia. The aim is to develop the public sector to accommodate the rapid growth in the number of employees. This is regarded as one of the most important challenges facing both sectors (public and private). Additionally, this study attempts to identify significant influences on organisational commitment in the public sector in Saudi Arabia. The selected variables are: personal factors (gender, age, level of education, income, marital status, experience); job characteristics (autonomy, skill variety, task identity, feedback and friendship opportunities); work environment (supervision, co-workers, company identification, physical work conditions and financial rewards). The questionnaire in this study was designed to obtain respondents' views in relation to commitment. It was distributed to 900 employees in the public sector in Saudi Arabia (male and female) at all Saudi ministries. The results of this study have indicated that: 1) The five personal variables (gender, age, nationality, marital status and income) have a negative relationship with organisational commitment, while education has a positive and significant relationship with organisational commitment. Experience has a poor relationship with organisational commitment. 2) Variables related to job characteristics (skill, task identity, friendship opportunity, feedback and autonomy) have a positive relationship with organisational commitment. 3) Work environment variables (company identification, co-workers, physical work conditions and financial rewards) have a positive and significant relationship with organisational commitment but supervision has a negative relationship with organisational commitment. The possible contributing factors to these findings were analysed. This study also investigates the feasibility of improving the level of organisational commitment among public sector employees in Saudi Arabia. Finally, recommendations are provided to improve organisational commitment among public sector employees and future areas for research are suggested.

This thesis investigates, theoretically and empirically, the relationship among economic growth, financial liberalisation and poverty reduction in Pakistan, between 1970' and 2000, with the aid of a rigorous co-integration analysis. A literature review provides an account of the existing models and other poverty reduction strategies in Pakistan. An analysis of poverty trends (1970-2000) in Pakistan shows large variations in poverty indices during all three decades under observation, at both provincial and intra -provincial levels. Ruman development indices show that poverty is highly concentrated in rural areas. Among provinces, the rural areas of Sindh and Balochistan provinces are worst affected. The trend of poverty shows a high rise during the 1990s, a decade of slow economic growth in Pakistan. The rural poverty nexus is correlated to the agricultural land reforms and weak institutional mechanism. Ineffective public services delivery to the poor has been the result of weak institutional response. The gender poverty is also all pervasive in Pakistan, as rural women are found to be more vulnerable to poverty shocks. Institutional failure has been found to be the main cause of the rising poverty in Pakistan. To analyse the relationship between economic growth and poverty reduction in Pakistan, we used the Dollar and Kraay model (2000) that predicts that economic growth reduces poverty. Using annual data sets for Pakistan from 1970 to 2000, our results show a positive relationship between economic growth and poverty reduction in Pakistan. We also tested the impact of financial development and growth in Pakistan. The McKinnon-Shaw hypothesis (1973) implies that increase in real rate of interest will increase savings and investment, which will lead to higher economic growth. The co-integration tests of the McKinnon-Shaw model (1970-2000) for Pakistan could not substantiate the prediction of the model. With a significant increase in savings over the period under observation, investment failed to rise. However, overall financial intermediation plays a significant and positive role in boosting economic growth. Authoritarian governments and the nationalisation policies are largely responsible for the inability to transform savings into investment.

This dissertation represents an attempt at demonstrating the process of technology transfer from developed countries to developing countries by focusing on the role of the multinational companies in such transfer in the car industry in Egypt. Apart from in-depth discussion of the theoretical issue of technology transfer and multinational firms, this study, based on the Egyptian experience as well as experiences of other countries in the 20[sup]th century, has attempted to criticise traditional technology transfer models by first reinterpreting technologies as knowledge in general and secondly by offering a new model of technology transfer within the context of today's globalised world economy. The thesis charts the history of Egyptian industrialisation from the 19[sup]th century to the late 20[sup]th century. It addresses questions about government policy toward industrialisation, private sector development and general macroeconomic policies of the Egyptian government since the 1950's. The thesis attempts a detailed analysis of the car industry in Egypt in the context of both national aspiration and the role of multinational companies in the transfer of technology in the car industry in Egypt. The thesis offers insights both on the practical intricacies of the technology transfer process and the theoretical aspects of this process.

This thesis consists of three chapters in Bayesian financial econometrics. The first chapter proposes new dynamic component models of returns and realized covariance (RCOV) matrices based on timevarying Wishart distributions. Bayesian estimation and model comparison is conducted with a range of multivariate GARCH models and existing RCOV models from the literature. The main method of model comparison consists of a term-structure of density forecasts of returns for multiple forecast horizons. The new joint return-RCOV models provide superior density forecasts for returns from forecast horizons of 1 day to 3 months ahead as well as improved point forecasts for realized covariances. Global minimum variance portfolio selection is improved for forecast horizons up to 3 weeks out. The second chapter proposes a full Bayesian nonparametric procedure to investigate the predictive power of exchange rates on commodity prices for 3 commodity-exporting countries: Canada, Australia and New Zealand. I examine the predictive effect of exchange rates on the entire distribution of commodity prices and how this effect changes over time. A time-dependent infinite mixture of normal linear regression model is proposed for the conditional distribution of the commodity price index. The mixing weights of the mixture follow a Probit stick-breaking prior and are hence time-varying. As a result, I allow the conditional distribution of the commodity price index given exchange rates to change over time nonparametrically. The empirical study shows some new results on the predictive power of exchange rates on commodity prices. The third chapter proposes a flexible way of modeling heterogeneous breakdowns in the volatility dynamics of multivariate financial time series within the framework of MGARCH models. During periods of normal market activities, volatility dynamics are modeled by a MGARCH specification. I refer to any significant temporary deviation of the conditional covariance matrix from its implied GARCH dynamics as a covariance breakdown, which is captured through a stochastic component that allows for changes in the whole conditional covariance matrix. Bayesian inference is used and I propose an efficient posterior sampling procedure. Empirical studies show the model can capture complex and erratic temporary structural change in the volatility dynamics.

This dissertation includes two essays. In the first essay, I proposed an alternative estimator for multivariate densities. This estimator can be characterized as a transformation based estimator. The first stage estimates each marginal density separately. In the second stage, the joint density of estimated marginal cumulative distribution functions (CDF) are approximated by the exponential series estimator. The final estimate is then obtained as the product of the marginal densities and the joint density estimated in the second stage. Extensive Monte Carlo studies show the proposed estimator outperforms kernel estimators in joint density and tail distribution estimation. An illustrative example on estimating the conditional copula density between S & P 500 and FTSE 100 given Hangseng and Nikkei 225 is also discussed. In the second essay, I extended the semiparametric model by Chen and Fan [X. Chen, Y. Fan, Estimation of copula-based semiparametric time series models, Journal of Econometrics 130 (2006) 307-335], and studied a class of univariate copula-based nonparametric stationary Markov models in which the copulas and the marginal distributions are estimated nonparametrically. In particular, I focused on the stationary Markov process of order 1 with continuous state space because it has the beta-mixing property for the analysis of weakly dependent processes. The copula density functions for time series models are approximated by the series estimate on sieve spaces. In this study, a finite dimensional linear space spanned by a sequence of power functions is treated as the sieve space where the estimation space of the copula density function is based. This sieve series estimator can be characterized as the exponential series estimator under mild smoothness conditions. By using the beta-mixing properties, I showed that the copula density function approximated by the exponential series estimator for stationary first-order Markov processes has the same convergence rate as the i.i.d. data. The Monte Carlo simulations show that the proposed estimator outperforms the kernel estimator in the conditional density estimation, except for the Frank copula-based Markov model. In addition, the proposed estimator considerably dominates the the kernel estimator when used in the one-step-ahead forecast.

In a market economy the rate of return on capital plays a decisive role for resource allocation. High profits in an industry stimulate expansion of production in existing firms and entry of new firms. The product price will hence tend to fall, and in the long run there is a tendency for rates of profit to become equalized across industries. The rate of profit also has an important impact on productivity growth. On the other hand, high profitability may lead to the growth of slack, which would imply that the rate of productivity growth is a decreasing function of profit rate. This dissertation is devoted to studying a dynamic model of a market adjustment process, where the rate of profit affects both production and productivity. Central questions asked are: What determines the rate of profit in an industry? What determines productivity development? These questions are answered by pointing to factors like the degree of competition and the rate of growth of demand. The analysis is mainly theoretical. The behavioural asumptions are subjected to empirical testing in a final chapter. / Diss. Stockholm : Handelshögsk.

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