Over the past several decades there has been extensive research done in an attempt to determine what demographic characteristics affect economic growth, measured in GDP per capita. Understanding what influences the growth of a country will vastly help policy makers enact policies to lead the country in a positive direction. This research focuses on isolating a new variable, women in the work force. As well as isolating a new variable, this research will modify a preexisting variable that was shown to be significant in order to make the variable more robust and sensitive to recessions. The intent of this thesis is to explore the relationship between several demographic characteristics and their effect on the growth rate of GDP per capita. The first step is to reproduce the work done by Barlow (1994) to ensure that the United States follows similar rules as the countries in his research. Afterwards, we will introduce new variables into the model, comparing the goodness of fit through the methods of R-squared, AIC and BIC. There have been several models developed to answer each of the research questions independently.

There is substantive literature surrounding the impact of price controls on the research and development (R&D) of new pharmaceutical products. The European Union (EU) and United States (US) are often studied in contrast to examine the influence of price controls as the US has fewer pharmaceutical price controls than the EU. We find moderate evidence that the US spent more on annual domestic pharmaceutical R&D than the EU between 2004 and 2021, on average, before and after adjusting for GDP growth per capita and year. We find strong evidence that the US increased annual domestic R&D spending at a faster rate than the EU between 2004 and 2021, on average, before and after adjusting for GDP growth per capita. Prior studies have asserted that increased US R&D spending leads to the production of more pharmaceutical products. Our study aims to quantify the differences in US and EU orphan drug development. Orphan drugs are pharmaceutical products that treat rare diseases. Both the EU and US aim to stimulate orphan drug production with policies including national grants, tax credits, and extended periods of market exclusivity. Our study gives indication that these policies in the US and EU are effective at spurring rare disease drug creation. We find evidence that orphan drug market authorizations increased annually, on average, in both the US and EU from 2004 to 2021, before and after adjusting for GDP growth rate per capita and the interaction between year and region. We find the same when isolating market authorizations for new orphan drugs. The US awarded more annual orphan drug market authorizations and market authorizations for new orphan drugs than the EU every year from 2004 to 2021, except in 2007. We find evidence that from 2004 to 2021, the US awarded more annual orphan drug market authorizations and market authorizations for new orphan drugs than the EU, on average, before and after adjusting for GDP growth per capita and year. There is also evidence that the US increased the number of these authorizations at a faster rate annually than the EU, on average, before and after adjusting for GDP growth per capita. Our results suggest an association between EU price controls and reduced pharmaceutical innovation. This is seen in the form of less annual R&D spending growth, orphan drug market authorizations, and new orphan drugs compared to the US, on average. However, the benefits of this innovation may not reach patients, as US consumers pay higher pharmaceutical prices due to limited price controls. This may contribute to the expansion of existing health inequities in the US. We are also unsure if the quality of US innovation exceeds that of the EU and if increased innovation is truly the result of lower price controls.

This study has applied a geographical perspective with the ambition of evaluating the presence of the Sell in May effect, January effect and monthly anomalies in the Nordic stock markets. In extension the study examines the relationship between corporate size and the returns of calendar anomalies. The study has conducted statistical tests based on Newey-West regressions as well as a Generalized Auto-Regressive Conditional Heteroscedasticity model. The findings suggest that the Sell in May and January are present in the Nordic region and partially abide by theory and results of previous research. The findings suggest that the Sell in May and January effect are independent, however, tendencies when the January effect has a considerable influence on the Sell in May effect are also evident. Additionally, the “April Effect” is an unexpected outlier with positive excess returns that was identified through this study.