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| Type | Master's Thesis |
| Scope | Discipline-based scholarship |
| Title | Estimating a Stock-Flow Model for the Swiss Housing Market and its Regions |
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| Institution | University of Zurich |
| Faculty | Faculty of Business, Economics and Informatics |
| Number of Pages | 56 |
| Date | 2016 |
| Zusammenfassung | The real estate market plays a crucial role in a country’s economy. Real estate satisfies not only a basic need, but it also accounts for a large part of wealth. However, the housing sector has also been the source of crises. It is therefore important to understand the functioning of real estate markets. Real estate is characterized by a set of special features, according to which it differs significantly from other economic goods. These characteristics also impact the functionality of real estate markets. Since real estate is a highly durable good, the dynamic operation of housing markets is often modeled within a stock-flow framework. In this approach, the housing stock – defined as the level of the stock in the previous period, net of depreciation and the amount of new construction – is distinguished from the flow of residential investment. The objective of this Master’s thesis is to analyze the determinants of the Swiss housing market. However, large regional disparities exist, as shown by variations in migration flows and diverging housing construction rates. Thus, a disaggregation at the regional level might help to better identify the impacts of these important determinants. The Swiss housing market has not yet been analyzed at the regional level using a stock-flow framework. Therefore, this thesis aims to close this research gap. To this end, a stock-flow model is estimated at the aggregate national level as well as at the regional level. Moreover, the model is used to address the question of overbuilding. The thesis estimates the long-run level of housing stock and residential investment as well as price adjustments and investment dynamics. For the econometric implementation, an error correction model is used. This approach is widely used in the empirical housing market literature. Error correction models distinguish between long-run equilibrium and short-term changes. The estimation results suggest that the long-run demand for residential housing stock is determined by real housing prices, GDP per capita, real wages and population. The same is found at the regional level, however, the effects of the different determinants vary among the eight market regions. The results further reveal that price changes are significantly dependent on the level of residential stock imbalances at the aggregate level as well as in the majority of the regional markets. Moreover, in the short-run, changes in mortgage rates have a significant and strong influence on price changes. The estimation results indicate that the long-run level of residential investment is determined by real housing prices, construction costs and real mortgage rates. However, in some regions other determinants such as population and income per capita impact the long-run level of residential investment. The results further suggest that, depending on the region, between 30% and 54% of the divergences of actual investment from the estimated long-run level are corrected in the following year. The results suggest that, at the aggregate national level, the actual investment is slightly higher than the equilibrium level predicted by the model. However, at the regional level, the results are distinct. Currently, half of the regions experience overbuilding, while in one region the opposite is true. In two market regions, the actual residential investment is in line with the estimated long-run level of investment. Finally, there is one market region which exhibits ambiguous results, depending on the approach taken. |
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