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The study examines the development of telecommunications and its impacts on Chinese economic growth since telecommunications has been undergoing dramatic reforms in the 1980s. On November 2001, China was officially the WTO member to open the market for foreign investors. It is obvious that the telecommunications infrastructure development can play a key role in economic growth in China. Furthermore, China has become the world’s single largest telecommunications market since 2002. In this research, I present evidence that it empirically not only investigates the telecommunications development and its impacts on economic growth, but also tests their relationship with initial economic condition, fixed investment, population growth, foreign direct investment as well as telecommunications infrastructure development using the panel data approach with a dynamic fixed effect model for the span of time from 2003 to 2008. I find that that mobile phone user density to be the new proxy for telecommunications infrastructure in China contributes in a major way to the economic growth. It means that mobile communication systems do have positive impact and effect on the regional economy of China. It is a crucial determinant as findings indicate a significant and positive correlation between telecommunications development and regional growth in China, after controlling for a number of other factors. Results also show that investment in telecommunications is subject to diminishing returns.

Dissertation deals with the food industry. First, the economy of the sector in the branch structure and size of businesses is evaluated. The main attention is paid to the drawing subsidies by the food industry in the context of EU funds. The main objective of this thesis is to evaluate the effect of the subsidies on the economy of the food business. For the analysis fixed effect model was used. According to the results, there are significant differences in the impact of subsidies on the individual branches of the food industry. In most fields was demonstrated their ineffective use to increase business performance.

Sedan 2000-talets början har avkastningen på icke-kognitiva förmågor ökat på arbetsmarknaden till följd av bland annat skill-biased technological change. Grupper som besitter höga icke-kognitiva förmågor bör därför gynnas på arbetsmarknaden. Givet att ett antal studier finner evidens för att kvinnor har högre icke-kognitiva förmågor än män, undersöker uppsatsen i vilken grad detta återspeglas i kvinnors relativlön. Syftet är att se om kvinnor gynnas av att avkastningen på icke-kognitiva förmågor har ökat i termer av att deras relativlön har ökat. För att undersöka detta tillämpas en regressionsanalys med fixa effekter på en komunpanel, där två olika mått på icke-kognitiv förmåga förekommer. Måtten grundar sig i mönstringsdata respektive O’net-data (Occupational information network). Effekten på kvinnors relativlön studeras under tidsperioden 2008–2018 samt 2014–2018 för Sveriges samtliga 290 kommuner. Resultaten uppvisar ett negativt samband mellan ökad efterfrågan på icke-kognitiv förmåga och kvinnors relativlön, vilket innebär att när efterfrågan ökar så minskar kvinnors relativlön. / Since the beginning of the 21st century, there has been a surge in the returns to non-cognitive abilities in the labor market, due to the influence of skill-biased technological change. This has led to a preference for groups with higher non-cognitive skills in the labor market. In light of some studies revealing that women exhibit greater non-cognitive skills than men, this study aims to investigate whether this phenomenon translates into a corresponding increase in women’s salaries, thus examining whether women are beneficiaries of the amplified returns to non-cognitive skills. To achieve this objective, a fixed-effects regression analysis is employed, using two different metrics to assess non-cognitive capacity, across one municipal panel. The research examines the effect on women's relative salaries from 2008–2018 and 2014–2018, encompassing all 290 municipalities in Sweden. The results demonstrate a negative association between increased demand for non-cognitive skills and women's relative salaries, indicating that as demand increases, women's relative salaries decrease.

The thesis analyzes the determinants of pharmaceutical expenditures on cardiovascular diseases with particular focus on Central Europe. We show how the pharmaceutical expenditure varies across the countries. We try to empirically verify that factors such as age, GDP, total health expenditure, education and prevalence of a particular disease cause the variation. Applying the fixed effect model on selected countries in the period 2000-2009, we find that the increase in pharmaceutical expenditures on cardiovascular diseases is explained mainly by aging population and prevalence of the diseases. Additionally, countries with higher GDP tend to also have somewhat higher pharmaceutical expenditures on cardiovascular diseases. Key words Pharmaceutical expenditures, cardiovascular diseases, GDP, health expenditure, fixed effect model, prevalence of a disease, aging of population.

This study examines the determinants of inward foreign direct investment to OECD countries. The focus is on horizontal FDI. The purpose of the research is to contribute to the ongoing research, and adding value. This is done by using a dynamic perspective of time, and controlling for country-specific characteristics. The thesis uses panel data covering all 36 OECD countries over a 23 year long time period, 1995-2017. Three regressions have been done using a linear fixed effects model, as well as four addition regressions testing the robustness of the results. Earlier studies have received spread results, as have this study. It found market size, economic stability, trade openness, and currency value as significant determinants of the inward flow of FDI to OECD countries.

The purpose of this research is to understand and explain the TFT LCD industry phenomenon of oversupply vs. shortage and its impacts on the prices and quantities of individual TFT LCD makers. Also, to look for any fixed effects (if any exist) due to specific company and due to specific time. We employ a fixed effect model to estimate impacts of individual traded quantity on price and impacts of individual price on traded quantity. Using the panel data covering 16 makers and 24 months, our results reveal that the TFT LCD panel is highly quantity inelastic of the traded price but greatly price elastic of the traded quantity. With regard to fixed effect, the empirical result reveals there were significant time effects of price for some periods of time while there were significant time effects of quantity for some sizes of panels. Supply and demand could be one of the factors determining the time effects. As to the company fixed effect, most of company fixed effects of quantity prices were found significant whereas company fixed effects of price were not. Market shares and country of origin can be significant factors determining the company fixed effect of quantity. Keywords: Panel Data, Fixed Effect Model, Quantity Elasticity, Price Elasticity, Company Fixed Effect, Time Fixed Effect, TFT LCD

The objective of this study is to conduct a marketing mix modeling to measure the effectiveness of past marketing activities on the product sales using a time-varying effect model (TVEM) approach. The longitudinal intensive data for this study has come from a large ice cream manufacturer in USA. Traditionally, static regression models have been used to measure the effectiveness of marketing mix variables to predict sales. And, these models used to find the time independent effect of the covariate on the dependent variable. On the other hand, a dynamic model such as time-varying effect model takes time into consideration. Researchers can model the changes in the relationship between dependent and independent variables over time using time-varying effect model. This is the first study, where a time-varying effect model approach has been used to measure the effectiveness of marketing mix elements in the ice cream industry. In addition, we have compared the predictive validity of both static and dynamic models using this data set.

In ecological risk assessment, mechanistic effect models (MEMs) are thought to overcome the limitation of standard laboratory single species test by accurately extrapolating the models to population-level. This review introduces the basic theory of MEMs-dynamic energy budget theory which can connect with toxicokinetic/ toxicodynamic models to describe the interaction of toxicants and organisms. This review summarizes some typical MEMs which simulate different scenarios, pesticides and species, and compared their modelling performance according to the guidance on good effect models of European Food Safety Authority, in order to judge if it is accounting for all modelling steps. In addition, a summary of the linkage of MEMs in pesticides ecological risk assessment have been discussed, especially evaluating the linkage results of ‘MODELINK’ workshop. However, there is no genuine application of MEMs in pesticides ecological risk assessment in real world today, because there is no validated model built with acceptable predictive power to motivate the ecological assessors or shareholders to use effect models confidently. Therefore, there is still a long way to develop an effect model which is valid enough and has strong prediction power.

Master of Science / Department of Statistics / Shie-Shien Yang / In fitting linear models, R[superscript]2 statistic has been wildly used as one of the measures to assess the goodness-of-fit and prediction power of the model. Unlike fixed linear models, at this time there is no single universally accepted measure for assessing goodness-of-fit and prediction power of a linear mixed model. In this report, we reviewed seven different approaches proposed to define a measure analogous to the usual R[superscript]2 statistic for assessing mixed models. One of seven statistics,Rc, has both conditional and marginal versions. Association mapping is an efficient way to link the genotype data with the phenotype diversity. When applying the R[superscript]2 statistic to the association mapping application, it can determine how well genetic polymorphisms, which are the explanatory variables in the mixed models, explain the phenotypic variation, which is the dependent variation. A linear mixed model method recently has been developed to control the spurious associations due to population structure and relative kinship among individuals of an association mapping. We assess seven definitions of R[superscript]2 statistic for the linear mixed model using data from two empirical association mapping samples: a sample with 277 diverse maize inbred lines and a global sample of 95 Arabidopsis thaliana accessions using the new method. R[superscript]2[subscript]LR statistic derived from the log-likelihood principle follows all the criterions of R[superscript]2 statistic and can be used to understand the overlap between population structure and relative kinship in controlling for sample relatedness. From our results,R[superscript]2[subscript]LR statistic is an appropriate R[superscript]2 statistic for comparing models with different fixed and random variables. Therefore, we recommend using RLR statistic for linear mixed models in association mapping.