When Economics Meets Life Decisions

Sammanfattning

This thesis explores the relationship between macroeconomic variables and human behavior, specifically how sick leave and birth rates are influenced by different macroeconomic variables. These two phenomena are not only relevant for labor markets and welfare planning but are also linked to economic cycles and uncertainty, as demonstrated by global events such as economic recessions. Despite the wide existence of literature examining economic impacts on human behavior, few studies have tried to model the relationship between macroeconomic variables and these behavioral outcomes over time in a Swedish context. This thesis addresses that gap by applying a linear regression approach to construct a model aimed to explain these relationships, using monthly data from 2005 to 2024. The models are built by using data from SCB, Försäkringskassan and Ekonomifakta, while also accounting for demographic changes and economic changes, such as population changes and COVID-19. The method used involved a variety of different steps, including: A residual analysis, multicollinearity checks, Cook's distance for discovering influential points, best subset selection and cross-validation to evaluate the final model. This resulted in two models consisting of very significant relationships between the two response variables and the macroeconomic variables. These discoveries imply that especially fiscal policies and inflation play a significant role in shaping individual life decisions. The results can teach policymakers about the effects of economic policies on demographic and health-related behaviors. These models aren't absolute facts though and should be taken with a grain of salt because of the different assumptions that need to be upheld. The models would also benefit significantly if more data points were available which would strengthen the validity of the analysis. Finally, future research could focus on involving data from other countries, use a broader dataset and perhaps even incorporate non-linear methods to further understand the relationship between macroeconomic variables and human behavior.