This thesis investigates the role of the real estate market as a driver of economic growth. It will do so by analyzing the relationships between the real estate price index and Gross Domestic Product (GDP) in the United States and Sweden during the period 1993 to 2024. The study will use a quantitative econometric framework, incorporating unit root tests, Granger Causality analysis, and Ordinary Least Squared (OLS) regression. In addition to the real estate prices, the study will also incorporate other macroeconomic variables of relevance, such as interest rates, inflation, and residential investment.

The empirical results indicate that in Sweden, fluctuations in real estate prices have a statistically significant and positive correlation with GDP, reflecting a wealth effect and demand-driven growth. In contrast, in the United States, residential investment, rather than price fluctuations, that demonstrates a closer correlation with GDP. This in turn can possibly be connected to the macroeconomic relevance of the physical construction activity that is involved during residential investment. Granger causality tests further reinforce these differences and reveal predictive relationships solely in the case of U.S residential investment.

In conclusion, the study highlights the differing macroeconomic roles that real estate has and provides important insight for economic forecasting and policy development.