The purpose of this master’s thesis is to investigate the relationship between renewable and non-renewable energy consumption, economic growth and carbon dioxide emissions per capita in Sweden in the period of 1970-2018. As indicators, the economic indicator will be represented by the per capita gross domestic product, GDP, as the environmental indicator this study will use carbon dioxide emissions per capita, CO2, and the energy use per capita will represent the energy consumption variable.  The research hypothesis is based on the idea of the classical EKC, the Environmental Kuznets Curve. Multivariate Vector Error Correction Model (VECM) approach which makes possible to evaluate non-stationary and cointegrating variables, while overcoming the omitted variable bias was used for the methodology part. Econometrics tests such as Augmented Dickey-Fuller Test and Johansen co-integration test are included, and the Granger causality test will provide four hypothesizes for the potential causalities between the included variable in this study.

Real estate industry plays a significant role in high speed of economic development in China. However, with increasingly high housing price and scare land resources, real estate development is caught in a vicious circle. A large number of families could not afford their housing while housing prices have no trend to decrease which leads to huger gap between the rich and the poor and causes indirectly instability of society. Therefore, creating a healthy and stable real estate investment market is extremely urgent. The purpose of the thesis is to research the relationship between leading index of macro economy prosperity and real estate investment based on the reality. We found that leading indicator Granger causes real estate investment while real estate investment Granger causes leading indicator at the same time. Based on that, this paper also forecasts the real estate investment with VAR models in the following 7 years which was proved to a circle of real estate market. In the light of our research, some target suggestions are pointed out at last.

Real estate industry plays a significant role in high speed of economic development in China. However, with increasingly high housing price and scare land resources, real estate development is caught in a vicious circle. A large number of families could not afford their housing while housing prices have no trend to decrease which leads to huger gap between the rich and the poor and causes indirectly instability of society. Therefore, creating a healthy and stable real estate investment market is extremly urgent. The purpose of the thesis is to research the relationship between leading index of macro economy prosperity and real estate investment based on the reality. We found that leading indicator Granger causes real estate investment while real estate investment Granger  causes leading indicator at the same time. Based on that, this paper also forecasts the real estate investment with VAR models in the following 7 years which was proved to a circle of real estate market. In the light of our research, some target suggestions are pointed out at last.

This study empirically examines the relationship between financial development and economic growth in Nigeria. It employs statistical techniques such as the Autoregressive Distributed Lag approach as well as a short and long run Granger Causality test on time series data spanning from 1960-2016. Empirical results reveal that the financial development indicators have a long run relationship with economic growth in Nigeria and the existence of unidirectional and bidirectional Granger causality was also discovered. This study recommends that policy should be geared towards promoting financial development in the country as well as encouraging more financial depth and openness – in order to foster economic growth in Nigeria.

The environmental Kuznets curve (EKC) hypothesis describes the relationship between economic growth and environmental degradation through an inverted U-shape where environmental degradation first increases with economic growth, to later stagnate and decline as economic growth reaches specific threshold limits. The aim of this study is to investigate the EKC hypothesis when environmental degradation is measured through a country’s renewable energy implementation. This is achieved through multiple scatterplots and a Granger causality test, and the key finding are (1) that a consensus regarding the relationship between economic growth and energy consumption is missing, (2) that countries seems to significantly increase their consumption of renewable energy between US$ 30 000 - 50 000 when measured in real GDP per capita, (3) that the theoretical shape of the EKC holds for most countries, (4) a unidirectional causality running from economic growth to fossil fuel consumption for a panel of developing countries, and (5) a unidirectional causality running from economic growth to both fossil fuel and renewable energy consumption as well as a unidirectional causality running from renewable energy consumption to fossil fuel consumption for a panel of developed countries. When the EKC is measured though a country’s renewable energy implementation the hypothesis seems to hold for most countries. However, the decrease in environmental degradation is so far limited to developed countries with smaller economies and populations. These countries also need to ensure that decreases in environmental degradation is a result of underlying mechanisms like energy efficiency improvements and not other more counterproductive behaviors like outsourcing and deindustrialization.

The indebtedness of Swedish households has more than doubled in the last ten decades despite the implementation of a mortgage ceiling and stricter amortization requirements. This study takes form to investigate how it is possible that debt related to housing is rising while new regulations against it has been set and how housing prices continues to increase when lending is supposed to be harder.This analysis estimates whether there are indications of an existing price bubble in the housing market of Stockholm. It is done by testing fundamental economic factors to the price index of housing in Stockholm, to see if they support the price development. If the analysis shows that housing prices cannot be predicted by the fundamental economic factors, it is possible that the price is a self-running series1 which could be an indicator of a price bubble. If fundamental factors that are being used as control variables seem to follow the same trend as the price development of the housing market, the speculation of price bubble will be rejected.

Biomarker discovery and statistical modeling reveals the brain activity that supports brain function and dysfunction. Detecting abnormal brain activity is critical for developing biomarkers of disease, elucidating disease mechanisms and evolution, and ultimately improving disease course. In my thesis, we develop statistical methodology to characterize neural activity in disease from noisy electrophysiological recordings. First, we develop a modification of a classic statistical modeling approach - multivariate Granger causality - to infer coordinated activity between brain regions. Assuming the signaling dependencies vary smoothly, we propose to write the history terms in autoregressive models of the signals using a lower dimensional spline basis. This procedure requires fewer parameters than the standard approach, thus increasing the statistical power. we show that this procedure accurately estimates brain dynamics in simulations and examples of physiological recordings from a patient with pharmacoresistant epilepsy. This work provides a statistical framework to understand alternations in coordinated brain activity in disease. Second, we demonstrate that sleep spindles, thalamically-driven neural rhythms (9-15 Hz) associated with sleep-dependent learning, are a reliable biomarker for Rolandic epilepsy. Rolandic epilepsy is the most common form of childhood epilepsy and characterized by nocturnal focal epileptic discharges as well as neurocognitive deficits. We show that sleep spindle rate is reduced regionally across cortex and correlated with poor cognitive performance in epilepsy. These results provide evidence for a regional disruption to the thalamocortical circuit in Rolandic epilepsy, and a potential mechanistic explanation for the cognitive deficits observed. Finally, we develop a procedure to utilize delta rhythms (2-4 Hz), a sensitive biomarker for Angelman syndrome, as a non-invasive measure of treatment efficacy in clinical trials. Angelman syndrome is a rare neurodevelopmental disorder caused by reduced expression of the UBE3A protein. Many disease-modifying treatments are being developed to reinstate UBE3A expression. To aid in clinical trials, we propose a procedure that detects therapeutic improvements in delta power outside of the natural variability over age by developing a longitudinal natural history model of delta power. These results demonstrate the utility of biomarker discovery and statistical modeling for elucidating disease course and mechanisms with the long-term goal of improving patient outcomes.

This essay explores how adolescent girls in two pieces of children’s fiction are portrayed in children’s literature from the start and end of the 20th century to examine how they perform their gender in relation to expectations as informed by the Angel in the House discourse. Anne of Green Gables and the Harry Potter series were published at the start and end of the twentieth century, and both texts engage with the discourse. Using Judith Butler’s theory of Gender Performativity, this essay demonstrates that the Angel in the House discourse continues to influence expectations of how adolescent girls should behave, particularly with regards to being responsible for upholding the moral code to ensure the social standing of their family. However, they differ in regard to other aspects of the discourse, indicating that parts of the discourse appear to have lessened over the course of the 20th century.

Foreign direct investment flows are an important theme in the analysis of global capital flows. The study aims to analyse the effect a withdrawal of FDI has on the economy of Brazil. This is based on the sharp decrease FDI inflows have seen during 2020. The study is based on the theory of David Ricardo and microeconomic and macroeconomic FDI theories. A vector autoregressive model (VAR) was applied using the Toda andYamamoto methodology. The findings show that FDI inflows are positively affected by an increase in GDP and negatively affected by an increase in real average monthly wages. Furthermore, no effect of FDI on any of the considered variables could be determined. This can be attributed to the complexity of the Brazilian economy during the considered period of March 2012 – October 2021, as well as a possible omitted variable bias. This thesis is intended to serve as an avenue for further research on the effect FDI withdrawals have on the Brazilian economy.

This thesis investigates the impact of financial intermediation on economic growth in two regions: the East African Community (EAC) countries (Burundi, Kenya, Tanzania, Rwanda, and Uganda) and North African countries (Algeria, Egypt, Morocco, and Tunisia). The study analyzes the regions employing a Granger causality test and explores if financial intermediation influences economic growth. An index that measures financial intermediation is created using Principal Component Analysis (PCA) and is used to capture the effect it has on economic growth in the two regions. The data used in the study is from 1990 to 2018. The results show that there is a short-run unidirectional relationship between financial intermediation and economic growth in EAC countries while financial intermediation does not Granger cause economic growth in North African countries. The result also shows that inflation has a short-run impact on growth in the North African countries.