Title: Integration of unemployed immigrants into the labor market in Gävle Authors: Ibrahim Adan Issack and Ekaterina Ivanova The aim of this study was to investigate unemployed immigrant’s description of how they perceive the labor market in Gävle. Qualitative method face-to-face interviews were used to gather data. The results of this study shows that an unemployed immigrant seems to encounter hinders and opportunities in the labor market. The following five issues were described as being most important in influencing immigrants’ employment opportunities in Gävle: Swedish language knowledge, previous education, discrimination, social network and family situation. Ecological system theory and previous research were used to analyze the gathered results.  Key words: integration, immigrant, labor market.

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This thesis contributes to our knowledge of the behaviour of the Chinese stock market by offering an empirical investigation into issues such as market segmentation, inter‐relationships between Chinese stock markets and inter‐relationships with foreign stock markets. Basic questions which have been typically analysed for developed stock markets are considered in this thesis. These include an analysis of core concepts such as volatility; causal links with economic variables and the reasons why the theoretical stock price may be different from the actual stock price. Methodological methods include; cointegration, generalised autoregressive heteroscedastic modelling (GARCH), vector autoregressive framework modelling (VAR) and panel data analysis. Both daily and monthly observations are used over a time period from 1996 to 2006. The results indicate that there is a rich set of reasons why we may observe phenomena such as a discount on B shares and a relationship between A shares and B shares. The findings also suggest that China is not isolated from the rest of the world and that there is evidence of inter‐relationships with foreign stock markets and that Chinese stock market prices are close to their fundamental value. This is not generally the finding for developed stock markets. Overall, it appears that the methodological approaches usually associated with developed stock markets can serve us well as useful tools in creating a deeper understanding of the underlying fundamentals describing the Chinese stock market.

This thesis studies the relationship between technology and industrial structure in the context of a growing market economy. Chapters 2 and 5 develop some general equilibrium models which permit a study of the relationship between quality competition, market structure and growth. Both market structure and the rate of growth are determined endogenously as functions of underlying parameters describing the pattern of technology and tastes, and the institutional environment. It is argued that quality competition constitutes an economic mechanism of primary importance, which provides essential incentives for innovation at the industry level, while also contributing to aggregate technological progress by way of R&D spillover effects. A related theme of the thesis is that constraints on quality competition are detrimental to growth. Chapter 3 presents a theoretical model which explains certain statistical regularities regarding cohort survival patterns, the persistence of firm turnover, and the appearance of shakeouts during an industry life cycle. By treating the market as comprising a number of strategically independent submarkets, this analysis separates the strategic interaction effects which occur at the submarket level, from the independence effects which operate across submarkets. Chapter 4 studies competition between two cohorts of radically different but substitutable technologies. By analyzing the entry of new-technology- based firms, the exit of incumbents and subsequent quality competition, this chapter explores the impact of a radical innovation on market structure and on the turnover of firms. Two critical levels of the parameter which measures the efficiency of the new technology are identified: the first must be attained for 'creative destruction' to take place, while the second must be attained for this 'creative destruction' process to take a 'drastic' form which involves the complete replacement of currently active firms by a wave of new entrants.

Estimation of stochastic volatility (SV) models is a formidable task because the presence of the latent variable makes the likelihood function difficult to construct. The model can be transformed to a linear state space with non-Gaussian disturbances. Durbin and Koopman (1997) have shown that the likelihood function of the general non-Gaussian state space model can be approximated arbitrarily accurately by decomposing it into a Gaussian part (constructed by the Kalman filter) and a remainder function (whose expectation is evaluated by simulation). This general methodology is specialised to the estimation of SV models. A finite sample simulation experiment illustrates that the resulting Monte Carlo likelihood estimator achieves full efficiency with minimal computational effort. Accurate values of the likelihood function allow inference within the model to be performed by means of likelihood ratio tests. This enables tests for the presence of a unit root in the volatility process to be constructed which are shown to be more powerful than the conventional unit root tests. The second part of the thesis consists of two empirical applications of the SV model. First, the informational content of implied volatility is examined. It is shown that the in- sample evolution of DEM/USD exchange rate volatility can be accurately captured by implied volatility of options. However, better forecasts of ex post volatility can be constructed from the basic SV model. This suggests that options implied volatility may not be market's best forecast of the future asset volatility, as is often assumed. Second, the regulatory claim of a destabilising effect of futures market trading on stock market volatility is critically assessed. It is shown how volume-volatility relationships can be accurately modelled in the SV framework. The variables which approximate the activity in the FT100 index futures market are found to have no influence on the volatility of the underlying stock market index.

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