An Analysis on the Norwegian Housing Market: How can we explain recent changes in the housing prices in Norway? A regional approach.

Recent increases in housing prices in Norway, especially in the capital, Oslo, has once again raised discussions on how long the prices in the housing market can continue to rise before a major correction might take place. In this thesis, I analyze the underlying fundamental driving forces in the Norwegian housing market in order to identify the main factors attributing to changes in the prices. The aim is to find the fac- tors influencing the housing market, how they contribute to changes in the housing prices and, in the end, help understand what might hap- pen in the future. The strength of the empirical approach, compared to previous studies on the Norwegian housing market, is that it tries to capture the demographic effects by using a difference-in-differences approach. The selection of the explanatory variables is inspired by the results of the models constructed by Jacobsen & Naug (2004) and Levin et al. (2009). The analysis relies on their approach in order to find the vari- ables associated with changes in the housing prices in three major cities in Norway. The cities analyzed are Oslo, Kristiansand and Stavanger, and they are chosen based on their characteristics and the availability of data. The results suggest that the interest rate, unemployment rate and the oil prices are the explanatory variables for either some or all three cities. The interest rate affect the housing prices in all three cities, the unemployment rate affects only Oslo and Kristiansand, while the oil price only affects Stavanger. Further my results suggest that income, the Consumer Confidence index and demographic changes do not have a significant effect on the housing prices for either city. I also find that the level of debt might have a positive effect on the housing prices in Kristiansand and Sta- vanger, while changes in the housing stock might influence the housing prices in Oslo. However, uncertainties regarding the two last variables makes them difficult to interpret. Finally, by combining the results from the estimations with data on the expected future development for the explanatory variables, I dis- cuss what might happen with the housing prices in near future