The interaction of the housing market with the wider economy has been seen as an important mechanism by which macroeconomic factors are expressed and transmitted. Housing market is an important component of total private investment, playing a significant role in business cycles. It is also an important sector for the financial side of the economy, labour market, construction industry and policy making. Thus, the working of the housing market is of great importance for the economy and it needs to be analysed thoroughly.
The growth in house prices has been very significant in Norway in the last few decades. House prices have risen by over 50% since 1993. This increase in house price has caused housing investment to increase as well.
Due to the huge upswing in house prices, housing investment has also increased significantly. “According to figures for the building industry, housing starts came about 31,600 in 2005, which represent a 5.4 percent increase on the previous year. By way of comparison, the increase was as high as 29.4 percent in 2004. The upswing has continued into 2006, and preliminary figures show that housing starts are 4.8 percent higher in the first four months of this year compared with the same period one year earlier. According to the preliminary national accounts figures, housing investment expanded by 14.5 percent in 2005 supported by strong growth in real income and lower real interest rates. The strong housing start figures at the end of 2005 and the beginning of 2006 point to a sustained, high level of housing investment again in 2006”.
Different reasons have been given for the rising house prices in most of the developed European countries including Norway. This unusual upswing in house prices and housing starts have motivated me to analyse the housing market in Norway. Since housing market is an important sector for major industries and policy making, it is important to know which factors affect this industry.
Thus, the primary objective of this paper is to model real house prices and investment. We want to know how the existing housing stock affects housing investment decision, and what other factors determine housing investment. Apart from this we also want to know the determinants of housing demand, hence house prices.
The paper models the housing market in Norway for the sample period 1973-2005 using Tobin’s q-theory of housing investment and an error correction model (ECM). The q-theory of housing investment identifies the factors that may cause fluctuations in the market value of the housing stock. Using these factors, I will try to find out which of these factors affect the housing investment in Norway most and are responsible for the cyclical behaviour of housing market. In this regard, I consider both the supply and demand side of the housing market separately. This distinction is necessary because, unlike many other goods, production represents an increment to an existing stock of housing capital, while demand for housing can be either for the asset, or for the implied flow of services derived from living in a house. The paper also takes into account the structural breaks that can affect the housing market, like credit market deregulation in the mid 1980s and tax reforms in 1992. The paper also estimates short and long term elasticity and the error correction speed of adjustment coefficients. The model, estimated over the period 1973-2005, consists of a system with an inverted housing demand equation and an investment supply equation. The results and the diagnostic tests indicate that the model specification is satisfactory. The estimations and tests are carried out using PCGIVE 10.The secondary objective of the paper is to investigate if changes in house prices can be predicted? I.e. can the stock flow model be used for forecasting and can it beat a random walk model? Using the model and running the data in PCGIVE 10, we find out that among all determinants of housing demand and supply, interest rate and housing stock are the two variables that affect both sides of the housing market. The other significant determinants of housing demand are real house prices, and real disposable income. The supply side is most affected by investment in housing market and house price relative to construction cost. Among all the significant variables, some are significant either in short run or long run, while others are in both cases. Apart from that, the regression results show that demand side fit better the model compared to the supply side. This is evident from the R-square of the two sides.
The study is structured in the following sections: Section 2 presents a review of some earlier studies. Section 3 represents the theoretical considerations for modelling the real house prices in Norway. Section 4 deals with the ECM methodology applied in the study. Section 5 presents the empirical results on house prices and investment functions for Norway. Section 6 presents the forecasting evaluation of Norway. A comparison with naïve auto-regressive alternatives is carried out and section 7 concludes.