Financial Crisis in Sweden during the 1990s

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Previous Studies

Regional Differences

According to Wheaton & DiPasquale (1996), the regional house prices vary according to size, quality, character of unit’s structure and location. Hence, the difference of regional economies is also of crucial importance. First, there are no interregional currency differences. This means that without monetary policies, regions cannot control the economic dynamics to stimulate or slow down the economy. Secondly, the regional economies are open since they have no tariffs or quotas between them. Some regions are more attractive than others due to climate, firm innovation and cost competitiveness. This allows for in-out migration between specialized trade regions and allows certain regions to expand whilst others contract. Thus, slow growing regions save rather than invest and let the excess funds go to growing regions, contributing to even further to urbanization
The economic regional differences are also present in Sweden when measuring for age population and education which are prerequisites for economic growth. In addition, the differences are projected to increase in Sweden where population will increase by 10-30% in the larger regions1. In order to distinguish economic activities between regions, the 290 municipalities are divided into 72 so-called Functional Analysis (FA) regions. The regional FA divisions are made by Tillväxtverket2 and are meant to be analyzed in the long-term for regional studies and forecast estimations. Municipalities are graded according to certain criteria, where it can be regarded as self-sufficient in terms of employment. If so, it can be considered an independent centre for local labour markets. The measurements are made by observing commuting trends between regions and long-term investments and structural changes. Some regions are divided into sub regions of the larger FA regions where these regions can partly serve as self-sufficient.

Regional House Prices

Owner-occupied homes compose a major part of private-sector wealth (Englund & Ioannides, 1997). Thus the price of housing has a major social and economic significance since it partly generates the economic activity. The demand for housing is more volatile than supply, with four important factors: the number of households wanting to purchase houses, income levels, the cost of housing and the expectations of new housing costs. The ability to locally provide housing depends on the availability of existing stock, as well as new housing depends on the availability of land (Maher, 1994). This study puts emphasis on the regional importance of house prices since housing markets are dynamic and complex, with location-specific responses. Therefore, prices do not just change temporally, but also spatially with significant and growing differences between regions due to different responses of supply and demand. Thus, to know how the housing market is operating, one should investigate it at the regional-level (Maher, 1994). Furthermore, Drake (1995) and Carol & Barrow (1994) claim that particular regional responses to fluctuations in the macro economy are important since they have an impact on the distribution of wealth. Thus, experiences of economic restructuring in the 1990s have had major impact on the location of employment and hence on the distribution of income (Maher, 1994) .Regional data vary distinctively from national data and are thus more informative about determining house Statistical analysis of regional differences by Statistics Sweden, 2003 tillvaxtverket.se prices and the affecting factors. Hence, regional house price models have many advantages provided good data exist (Cameron, Muellbauer & Murphy, 2006). For instance, a study by Maher (1994) found differences in the rate of change of prices between Australian cities and also between neighbourhoods within cities. Therefore he used an eight-region classification of Australian areas that had internal similarity in property prices and were disaggregated spatially. He points out that suburbs of large cities and its inner regions have a higher house price mean than those of the outer suburbs in general. Therefore it is important to recognize that regional house prices may differ to some extent from each other. In this thesis the author takes into account some regional differences between larger Swedish regions such as Stockholm Gothenburg and Malmö against other peripheral regions. To further stress the importance of regional differences one can also consider the changes in other countries. Giussani and Hadjimatheou (1991) found that since the early 1980s, the UK has experienced a widening gap in terms of incomes and employment opportunities between the rich South and the less- prosperous North. Hamnett (1989) drew his attention to rapid house price inflation where prices in the southern regions tended to increase faster than the national average. In the UK case, the London market acts relatively independently to the other UK regions (Carol & Barrow, 1994). An important explanation to this could be London’s greater awareness of the investment potential of housing, together with fewer new buildings and lower level of unemployment. London therefore benefits from dominance in banking, insurance and finance in the economy (Giussani and Hadjimatheou, 1991). Drake (1995) also explains that London is a common workplace for much of the population and has a large mobility of labour throughout the commuting belt around London. In contrast, prices rise slower in the peripheral regions because the proportion of high income earners is lower and because the supply of owner-occupied housing is less restricted in other regions (Hamnett, 1989). Cameron (2005) discovers that migration between regions plays a central role in the workings of regional housing and labour markets. The differences in migration to and from London have somewhat different responses to unemployment in other regions. When making a location choice, people will contemplate between job opportunities and high relative earnings against house prices and credit constraints. Maher (1994) also states that population growth and migration movements are important when considering changes in housing demand. Migration can be divided into two different terms. First, the rate of immigration and second that of the interregional movements within the country.

The Ripple Effect

For a regional house price model it is necessary to address regional issues such as The Ripple Effect (Cameron, Muellbauer & Murphy, 2006). The Ripple Effect describes the observed tendency of house prices to rise sooner and faster in the more economically active regions, where demand is buoyant, and then spread to the rest of the country in waves associated with particular time lags. Some previous empirical studies by Macdonald Taylor (1993), Giussani & Hadjimatheou, (1991) and Carol & Barrow (1994) shows evidence of The Ripple Effect in the UK, where house prices in the London area cause price movements in the other regions. Carol & Barrow (1994) claims that the regional transmission of house prices could be due to geographical proximity which indicate that migration is an important factor. Also, wave movements could reflect a pattern of changing volumes of economic activity with time.

Financial Deregulations

The background section described the deregulations and other important factors that contributed to the Swedish financial crisis of the 1990s. Here, the author reflects on the economic liberalization emphasis on the world economy as a whole. Apart from Sweden, other countries have been affected by the growing trend of an economically deregulated environment. Some significant changes were the growing globalisation, the mobility of capital and the increased demand for financial and business services. But a financial liberalization increases the probability of a banking crisis in credit creation (Goodhart & Hofman, 2007). For instance, Maher (1994) studies similar effects in Australia which also had a long -term economic and social restructuring in the 1980s. The structural changes contribute to an understanding of the difference in housing prices between and within cities. According to Maher (1994) there is little doubt that deregulation of financial intermediaries in Australia played a major role in the credit availability-asset price surge of the late 1980s, but also that the timing was important. He demonstrates that global, social and economic change, together with fiscal and monetary policy and consumer expectations of house price inflation, all combined to produce a house price boom.
The government is also important since its intervention helps to provide more affordable housing and can impose growth policy on limited land availability Mankiw & Weil (1989). Hence, government is important for influences in both macro-economic and spatial policies and has contributed to variations in demand for housing, and consequently to impacts on prices (Maher, 1994).
Other studies on the causes of financial crises in other countries during the 1990s can be drawn parallel to those on house price boom in Sweden. For example, Mankiw & Weil (1989) analysed demographic changes that affected the U.S. housing market and saw a large and sudden drop in housing prices and real estate investments that led to macroeconomic instability. Hamnett (1989), Maher (1994) and Mankiw & Weil (1989) studied the 1970s post-War baby boom in different countries which led to high demands in houses, followed by sudden drops in demand years later during the baby bust. Cameron, Muellbauer and Murphy (2006) found that the evolution of regional prices in the UK during this period can be largely explained by the combination of strong income growth, higher population growth (partly from in-migration) and lower interest rates. Jud & Winkler (2002) states that real house price appreciation in the U.S. is strongly influenced by the growth of population and real changes in income, construction costs and interest rates.

Household Expectations of House Prices

It is also important to know that real estate market participants affect and are affected by their own expectations of house prices. There are three different expectations that can be observed between participants. First, the exogenous expectations, that means that future prices can grow and overshoot construction but later diminishes to a new equilibrium level by gradually decreasing from the overshooting. Second, there are the adaptive expectations that base future prices on past prices, leading to construction and stock fluctuations. Third, the rational expectations, which expect that there is perfect information about market operations predicting correct market responses to unforeseen shocks. This can be compared with exogenous expectations however with less overshooting (Wheaton & DiPasquale, 1996).

Theory

Wheaton & DiPasquale (1996) present a view of the housing prices dynamics. Within the housing market there are clear distinctions of the market for location (the property market) and the market for assets (the asset market). Owner-occupiers of real estate can have the role as a user or/and as an investor. The four quadrant model in Figure 1 divides the real estate market into both the asset and the property market. In the model, the markets interact in order to restore the equilibrium of house price dynamics.
The first square, A, means how much space would be demanded at a particular rent level. Thus, space demand (D) must be equal to the stock (S) . An upward shift due to for example economic growth extends the dynamics to the new dashed line seen in the figure.
B is the model for the capitalization rate (ratio of rent-to-price) and is exogenously determined by macroeconomic factors (interest rates, growth in rents, risks of rental income stream and taxes). Here, the property market is connected with asset market when the rent is divided by the capitalization rate to derive the asset price of real estate. High capitalization rate means counter clockwise rotation of the line.
C uses the expression f(C) which means the replacement costs through new construction. The asset price intersects with the minimum dollar value (per unit of space) required to get some new development underway. If supply can be provided with almost the same cost the line becomes vertical. Horizontal line means inelastic construction supply. Construction occurs at level (C) and asset price P should be equal to replacement cost f(C).
In D, (C) is converted into long-run stock of real estate space, were the changes in stock equals the new constructions minus depreciation of existing stock. The horizontal axis means the level of stocks that requires an annual level of construction. For replacement cost to be equal to that of the vertical axis, ΔS should be 0 if construction is constant.
The lines can have different slopes at different times which mean that the economy can be more sensitive in some cases than others. The price effects can either be endogenous economic variables (prices, sales and output) and exogenous economic forces (interest rates, world trade, climate, better economy leading to better income and number of households).

Hedonic Price

Goodman (1977) claims that when determining house prices, assumptions are often made that they are long-lived durable goods existing in a market with a long-run equilibrium. What has not been taken into account is the so-called hedonic price coefficients or “shadow prices” that reflect streams of returns from given attributes or characteristics of each house. These coefficients can be plugged in models that present any budget constraint regarding demands in house markets. Wheaton & DiPasquale (1996) defines it as a relationship between housing unit attributes and market prices that divides housing expenditure to reflect both changes in unit price as well as average unit quality. The separation of these makes it a quality controlled house price. Hence the demand estimations and its elasticity can be rearranged due to the differences in house attributes or characteristics. This allows for a model that deals with determining various real estate prices with respect to smaller number of attributes or components.

Introduction
Purpose
Outline
Financial Crisis in Sweden during the 1990s
Deregulations of the credit and exchange system
Tax reforms
Other reforms
The post 1990s crisis
Previous Studies
Theory
Data and Methodology
Regional Division
Regression Model
Hypotheses 
Results & Analysis
Conclusions
Suggestions for Further Research
References
Appendix
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Formation of House Prices in Sweden

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