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Regional Housing Market Spatial Dynamics in Central Europe. Slavomír Ondoš, Gunther Maier. Introduction. Introduction. Housing sector has been dramatically transformed in the post-socialist Central European countries.
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Regional Housing Market Spatial Dynamics in Central Europe Slavomír Ondoš, Gunther Maier
Introduction • Housing sector has been dramatically transformed in the post-socialist Central European countries. • Transition has also fundamentally changed the social and economic frameworks: from previous based on the allocation managed by the state into one relying on the market principles, gradually introduced since the 1990s.
Introduction • History of the housing sector has been determined by its role in the socialist orthodoxy, one which designated housing as a social rather than an economic sector: a right to which all citizens were entitled (Hegedüs et al. 1996). • The gap between the declining schemes and establishment of the new lasted several years. Data illustrate a decline in the number of completed dwellings after a peak in the 1980s.
Introduction • Differentiation in performance of regional economies as rather a reintroduced than a new phenomenon. • Number of issues relating to the causes for regional disparities, the efficiency of labor market mechanisms such as wage flexibility, migration and new firm creation in equilibrating regional labor markets and appropriate policies to deal with the uneven development of regions in transition arise (Huber 2007).
Introduction • Czechoslovakia existed, with exception of the WWII, since 1918. Since 1968 it was a federation consisting of two states. This federal state was divided and independent countries were created from the two parts in 1993. • It is widely believed to have been conditioned by the more negative economic developments in Slovak Republic than the Czech Republic (Garner and Terrell 1998).
Introduction: Questions • The question: Is the regional housing supply level directly related to the regional economic performance and the regional demographic dynamics in the two Central European countries? Specifically: Is the housing investment intensity directly related to the average unemployment, income, migration and natural increase levels? Do the relationships change with the ongoing transition?
Introduction: Questions • The question: Is the hypothesis of conditional convergence valid in the spatial dynamics aspect? Do the regions with high initial level of housing investment grow faster or slower in compare to the regions with a low level of housing investment? • Besides the socio-economic mechanism, our interest is in search for spatial effects in regional differentiation.
Methods and data • Housing starts is the first dependent variable in regression focused on the housing market supply side Hi,t = DSi,t / Pi,t Hi,tis the average annual regional housing investment intensity; DSi,t is the total number of dwellings started in the region i during the year t; Pi,tis the responding mid-year region`s population.
Methods and data • In order to define a dynamic version to the first variable we consider a ratio hi,t+T of the two horizons in annual regional housing intensities hi,t+T = Hi,t+T / Hi,t
Methods and data • Based on the level and growth alternatives of the housing supply we specify the two empirical models Hi,t = fH ( Ui,t; Ii,t; Mi,t; Ni,t; Ai,t ) hi,t+T = fh ( Hi,t; Ui,t; Ii,t; Mi,t; Ni,t; Ai,t ) Ui,t; Ii,t; Mi,t; Ni,t and Ai,t are the vectors of economic, demographic and accessibility explanatory variables.
Methods and data • Accessibility proxy Ai,t is the sum of model interactions between a region i and all regions j in an n-regional system Ai,t = Si,j=1n ( Pi,t . Pj,t / dij); i≠j Distancedij = [ ( xi – xj )2 + ( yi – yj )2 ]1/2between the centroids` coordinates [xi; yi] and[xj; yj] of the regions iandj.
Methods and data • The OLS models, the spatial lag models and the spatial error models to be calibrated are Hi,t = aH + bHUUi,t + b HIIi,t + b HMMi,t + b HNNi,t + b HAAi,t + uH hi,t+T = a h + b hHHi,t + b hUUi,t + b hIIi,t + b hMMi,t + b hNNi,t + b hAAi,t + uh Hi,t = a H + rHWHi,t + b HUUi,t + b HIIi,t + b HMMi,t + b HNNi,t + b HAAi,t + uH hi,t+T = a h + r hWhi,t + b hHHi,t + b hUUi,t + b hIIi,t + b hMMi,t + b hNNi,t + b hAAi,t + uh Hi,t = a H + b HUUi,t + b HIIi,t + b HMMi,t + b HNNi,t + b HAAi,t + lHWeH + uH hi,t+T = a h + b hHHi,t + b hUUi,t + b hIIi,t + b hMMi,t + b hNNi,t + b hAAi,t + lhWeh + uh
Extension • Annual reformulation, explaining annual difference DHi,t+1 = Hi,t+1 – Hi,tinstead of the previously used growth ratio to avoid numerous missing values appearing in case of annual hi,t+T DHi,t+1 = aDH + bD HHHi,t + bD HUUi,t + bD HIIi,t + bD HMMi,t + bD HNNi,t + bDHAAi,t + uDH D Hi,t+1 = aD H + rDHWDHi,t+1 + bD HHHi,t + bD HUUi,t + bD HIIi,t + bD HMMi,t + bD HNNi,t + bD HAAi,t + uDH DHi,t+1 = aD H + bD HHHi,t + bD HUUi,t + bD HIIi,t + bD HhMMi,t + bD HNNi,t + bD HAAi,t + lDHWeDH + uDH
Conclusions (Unemployment) • Predictability growth of regional differentiation according to the set of predictors is observed during the transition. • Unemployment is a significant negative factor, except the last Czech model. Diminishing unemployment in conditions of economic growth approaches zero effect but stays significant. Regions with high unemployment tend to have lower housing supply level than regions with low unemployment.
Conclusions (Income) • Income is an insignificant factor, except some Slovak models in the end of the estimated period. In compare to availability of jobs, income is statistically less important but it grows with time. Income differentiation gains the importance in explanation of the housing supply with decrease in unemployment significance.
Conclusions (Population) • Migration is significant factor, except the first Slovak model. The effect of migration on housing supply is positive and growing. The more a region attracts migrants, the more its housing investment is activated and the market supply response strengthens with time. • Natural population dynamics is significant in one country and insignificant in the other. Positive natural dynamics has positive significant effect. If natural dynamics is negative, the effect is statistically insignificant.
Conclusions (Accessibility) • Larger regions and regions closer to larger regions tend to have lower housing supply than smaller regions and regions far from larger regions in one country while it is reverse in the other country. • This results from the development pattern with systematic oscillations between positive and negative effect in both countries.
Conclusions (Spatial effects) • Regional housing supply levels are related with the housing supply levels in surrounding regions according to four r parameters. Housing supply tends to spill-over to the neighbors in the Slovak system in the latter years. The spatial error parameter l is also significant for the latter Slovak models, as well as the first Czech model. Housing supply did spread across the regional systems early in case of the Czech regional system and late in case of the Slovak regional system.
Conclusions (Supply growth) • Significant negative effect from starting level of regional housing supply suggests convergence in the regional system concerning the housing market. Relative high housing supply level regions grow less than regions with relative low housing supply level. • Significant negative effect is found from unemployment. Positive effect of migration is significant in the Czech regional dynamics. Spatial effects are positive on the Slovak side.
Conclusions (Annual change) • Model performance varies in relation to the general development of the markets pointing at peaks and smooth intervals. • Regional convergence is supported, except the sub-periods of continuing increase, when systems tend to turn divergent. • Negative effect of unemployment on housing supply change lost significance. The effect is generally stronger during the periods when the market is slowing down and weakens when the market speeds up.
Conclusions (Annual change) • Income tends to be identified as a significant positive factor affecting housing supply change only exceptionally. • Migration has a significant positive influence in general while there is a short connection found between the influence of regional unemployment and migration. • Spatial effects are found significant in 2005 for both countries, having opposite direction.
Forschungsinstitut für Raum- und Immobilienwirtschaft Research Institute for Spatial and Real Estate Economics Nordbergstraße 15, 1090 Vienna, Austria MGR. SLAVOMÍR ONDOŠ T +43-1-313 36-5764 F +43-1-313 36-705 slavomir.ondos@wu-wien.ac.at www.wu.ac.at/immobilienwirtschaft
