<p>The aim of this master thesis was to examine whether the noticed effect of Black Monday October 1987 on stock market volatility has also influenced the predictive power of the single factor CAPM and the Fama French three factor CAPM, in order to conclude whether the models are less effective after the stock market crash. I have used an OLS regression analysis and a Monte Carlo Simulation technique. I have applied these techniques on 12 industry portfolios with US data to draw a conclusion whether the predictability of the single and three factor model has changed after October 1987. My research confirms that the single factor CAPM performs better before October 1987 and also found evidences that support the same hypothesis of Black Monday effect on the predictive power of the Fama French three factor model.</p>

This thesis deals with the compilation of an econometric model for the response variable Sales in the energy industry. For the compilation of an econometric model Gretl program is used, data for analysis were taken on the Internet server Eurostat.eu. Cross-sectional data for the year 2010 were used. Resulting multiple regression model is interpreted and evaluated. Part of the thesis also contains a review of literature, which deals with the development of a common energy policy in the EU countries, the current situation in this area and future development plans. Also there are listed sources of energy that are located on the territory of the EU and the issue of energy dependence on other non-member countries is discussed.

Sukuk are an important mode of financing in the Islamic financial system. As usury (interest) is prohibited in Islam, conventional bonds are not suitable for investors in Islamic countries. Since their launch in the 1980s, Sukuk have gained recognition and popularity as a substitute for conventional bonds. However, their unique features mean that Sukuk are not always clearly understood. The aim of this study is to analyse the differences and similarities between Sukuk and conventional bonds in terms of their risk and return characteristics.

The aim of this diploma thesis is to identify factors that influence the profitability of companies in the food industry. The work focuses on the relationship between asset profitability and inventory, receivables and liabilities turnover. Data was obtained from Orbis database. In the empirical analysis is Pearson's correlation coefficients and multi-dimensional regression models compiled. There is a sepa-rate model for each Member State. Examined period is the year 2016.

In recent decades, the night lights data of the Earth’s surface derived from the Defense Meteorological Satellite Program’s Operational Linescan System (DMSP/OLS) have been used to detect the human settlements and human activities, because the DMSP/OLS data is able to supply the information about the urban areas  and non-urban areas on the Earth which means it is more suitable for urban studies than usual satellite imagery data.   The urban development is closed linked to the human society development. Therefore, studies of urban development will help people to understand how the urban changed and predict the urban change. The aim of this study was to detect Beijing’s urban development from 1992 to 2012, and find the contributions to the urban sprawl from socio-economic factors. Based on this objective, the main dataset used in this thesis was night lights images derived from the DMSP/OLS which was detected from  1992 to 2012. Due to the lacking of on-board calibration on OLS, and the over-glow of the lights resources, the information about the night lights cannot be extracted directly. Before any process, the night lights images should be calibrated. There is a method to calibrate the night light images which is called intercalibration. It is a second order regression model based method to find the related digital number values. Therefore, intercalibration was employed, and the threshold values were determined to extract urban areas in this study. Threshold value is useful for diffusing the over-glow effect, and finding the urban areas from the DMSP/OLS data. The methods to determine the threshold value in this thesis are empirical threshold method, sudden jump detection method, statistic data comparison method and k-mean clustering method. In addition, 13 socio-economic factors which included gross domestic product, urban population, permanent population, total energy consumption and so on were used to build the regression model. The contributions from these factors to the sum of the Beijing’s lights were found based on modeling.   The results of this thesis are positive. The intercalibration was successful and all the DMSP/OLS data used in this study were calibrated. And then, the appropriate threshold values to extract the urban areas were figured out. The achieved urban areas were compared to the satellite images and the result showed that the urban areas were useful. During the time certain factors used in this study, such as mobile phone users, possession of civil vehicles, GDP, three positively highest contributed to urban development were close to 23%, 8% and 9%, respectively.

Denna uppsats ämnar undersöka om det föreligger ett samband mellan hållbarhetsredovisning och lönsamhet hos svenska små och medelstora företag (SMF). Studien avser vidare att enbartinkludera svenska SMF inom branscherna tillverkning och industri, partihandel och transport. Anledningen till att dessa branscher är till föremål för studien är på grund av att branscherna bidrar med stor andel av koldioxidutsläpp i Sverige. Vi har vidare valt att rikta in oss på SMF som inte lyder under lagstiftad hållbarhetsrapport, enligt 10§ kap. 6 ÅRL (SFS 1995:1554). Tidigare forskning visar blandade resultat. Exempel på det är, att SMF gynnas positivt i lönsamhet (Enderle 2004; Shields &amp; Shelleman 2015) men också studier som visar att SMF inte gynnas positivt i lönsamhet, då de har mindre resurser än stora företag (Aggarwal 2013; Shields &amp; Shelleman, 2015; Klewitz &amp; Hansen, 2014; Jayeola 2015). Detta i samband med dagens klimatkris är avsikten med studien: Att undersöka huruvida SMF gynnas eller inte gynnas av att engagera sig i hållbarhetsredovisning genom ett lönsamhetsperspektiv. Enligt vår mening är det ett viktigt ämnesområde att studera då det kan krävas incitament för SMF att inkludera miljöåtgärder samt hållbarhetsredovisning i verksamheten. Detta i och med att de besitter mindre resurser än stora företag. Om inte engagemang för miljöåtgärder bidrar till bättre lönsamhet, då är frågan vad SMF har förincitament till hållbarhetsredovisning är. Detta har diskuterats utifrån en teoretisk utgångspunkt med hjälp av The Signaling Theory och Legitimitetsteorin. Detta är en kvantitativ studie, där vi tillämpar Ordinary Least Squares (OLS) och logistisk regression för att bringa svar i frågan. Studien innehåller även en total kartläggning utav deutvalda branscherna, inom gränsen för frivillig hållbarhetsredovisning. Avsikten med detta är att ge insikt för vilka hållbarhetsredovisningsmetoder, tid av hållbarhetsredovisning och trender som finns hos respektive bransch. Kartläggningen gav information för att formulera välriktade hypoteser angående lönsamhet för små och medelstora företag. Via hypoteserna studerar vi vikten av hållbarhetsredovisningsmetod, tidsaspekten och branschskillnader gentemotlönsamhet och dess stabilitet.

Habitat loss and fragmentation are major threats to biodiversity. Geostatistical methods, especially kriging, are widely used in ecology. Bird counts data often fail to show normal distribution over an area which is required for most of the kriging methods. Hence choosing an interpolation method without understanding the implications may lead to bias results. United Kingdom’s Exprodat Consulting Ltd had set an Exploratory Spatial Data Analysis (ESDA) workflow for optimising interpolation of petroleum dataset. This workflow was applied in this study to predict capercaillie bird species over whole Sweden. There was no trend found in the dataset. Also the dataset was not spatially auto-correlated. A completely regularized spline surface model was created with RMSE 1.336. Medium to high occurrences (8-16) were found over two very small areas, within Västerbottens county and Västra Götlands county. Low occurrences (1-3) were found all over Sweden. Urban areas like Stockholm city and Malmö city had low occurrences. Another kriging prediction surface was created with RMSE 1.314 to compare the results. There were no prediction values from 5 to 16 in kriging surface. In-depth studies were carried out by selecting three areas. The studies showed that the results of local kriging surfaces did not match with the results of global surface. Uncertainty in GIS may exist at any level. Having low RMSE value does not always mean a good result. Hence ESDA before choosing interpolation method is an effective way. And a post result field investigation could make it more valid. Regression analysis is also widely used in ecology and there are certain different methods that are available to be used. Ordinary Least Squares is the first method that was tested upon bird counts data set. Adjusted R-squared value was 0.008616 which indicated that explanatory variables pine, spruce, roads, urban areas and wetlands were just contributing to 0.8% to the dependent variable bird counts. It was also found that there was no linear relationship between dependent and explanatory variables. Logistic regression was the next step as it had the capability to work with nonlinear data also. The Spatial Data Modeller (SDM) tool was used to perform logistic regression in ArcGIS 9.3. Initially results of logistic regression were unexpected, hence focal statistics was performed upon all the independent variables. Logistic regression with these new independent variables generated meaningful results. This time the probability of occurrence of birds had weak positive relationship with all the independent variables. Coefficients of pine, spruce, roads, urban areas and wetlands were found to be 0.39, 0.23, 0.13, 0.24 and 0.14 respectively. Pine and spruce are natural attractors for birds, hence results were quite acceptable. But the overall model performance remained poor. Positive coefficient for roads, urban areas and wetlands may well be due to redundancy in these datasets or observer bias in bird species reporting. IDRISI Andes also came up with almost the same results when logistic regression with same dependent and independent variables was performed. IDRISI Andes output contained the pseudo R-square value, found to be 0.0416. This was an indication of biasness in the dataset also. The results of in-depth studies by selecting three areas also showed that LR with focal statistics were having better results than LR without focal statistics, but the overall performance remained poor. The SDM tool is a good choice for performing logistic regression on small scale datasets due to its limitation. Comparison of results between the two geostatistical methods, interpolation and regression depicts the similarity at discrete places; an unbiased dataset might have resulted in a better comparison of two methods.

Deteriorating air quality has attracted the interest of policymakers in most parts of the world. Poor air quality is behind many severe health problems on both a global and a local scale. While decarbonization is the primary driver behind the push for broader adoption of electric cars, we hypothesize the presence of significant co-benefits from adopting electric cars, such that electrifying the mode of transportation might reduce air pollution. To test this hypothesis, we evaluated panel data for the stock of electric cars and emissions of nitrogen oxides (NOX) from Swedish municipalities between 2010-2019 using OLS models with fixed effects. The analysis suggests a significant negative correlation between the stock of electric cars and emissions of NOX. The presence of co-benefits suggests a stronger case for subsidizing the adoption of electric cars, beyond the level climate considerations warrant.

Denna studie utförs med bakgrund i det demokratiska styrelseskickets dominanta status i världen och avser att blottlägga orsakerna bakom demokratiska regimers fortlevnad. Syftet med uppsatsen är att pröva trovärdigheten av instrumentella demokratiargument. I studien tillämpas en statistisk analys, i form av OLS-regression, för undersöka huruvida tillfredställelsen med demokratiskt styre kan förklaras utifrån individens välmående. Analysen är mestadels baserad på intervjudata från World Values Survey 2017–2020: Wave 7 och avser att generalisera till en global kontext. Resultaten finner stöd för sambandet och därmed även för instrumentella demokratiargument, då individens välmående förknippas med praktiska resultat och måluppfyllelse. Till skillnad från tidigare forskning analyseras dessutom effekterna av nationell stolthet, likaså effekterna av medborgliga rättigheters konsolidering. Nationell stolthet visar sig ha en positiv effekt på tillfredställelsen med demokratiskt styre och bör därför undersökas närmare vid framtida studier.

This thesis focuses on impacts of expenditures on construction of infrastracture, distribution networks of elektricity, gas, fresh water and construction of sewerage and also expenditures on education and healthcare on economical development of federal states of Brazil in time period 1985-2013. The thesis uses OLS methods, cluster analysis and panel analysis. Results of expenditures showed that spendings conected with healhcare and education had positive econimical impact in all observed states of brazilian federation. On the other hand expenditures spent on construction od infrastracrure and enginnering networks had positive economical impact only in case of poor, undeveloped federal units in northern, central and northeast regions of Brazil.