Table 3 - uploaded by Adam Banai
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Context 1
... prepare an estimate for each municipality type (Budapest, cities and villages) both for the pre-2008 and post-2008 samples. We divided the database into sub-samples representing the old and the new structures in order to use the broadest possible information base for both of these periods, while breaking down the backcasting by municipality type was warranted by the significantly diverging property size distributions in the individual municipality types (Table 3). The models which were run on data between 1990 and 2007 included the following explanatory variables: property price, quarter dummy, property type (house or flat), legal status of the municipality, category variables for county, agglomeration and seasonal property area and per capita income for the municipality. ...
Context 2
... a more precise view may also help market participants in their investment decisions or portfolio evaluations. Figure 18 Partial effect of the interaction between NIA and property type in a model specified for Budapest 5 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100 105 110 115 120 125 130 135 140 145 Partial effect of the interaction between NIA and property type in a model specified for municipalities ...
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Citations
... In Hungary, three well-known indices are published quarterly: the MNB House Price Index, the Hungarian Central Statistical Office (HCSO) index, and the Takarékbank index. The MNB House Price Index, created by Banai et al. (2017) using hedonic regression and period pair estimates, offers an aggregate index for the entire country, along with a detailed breakdown by region and settlement size. Since this breakdown is essential to produce regional results, the MNB index was used during the analysis. ...
The paper analyses the Loss Given Default (LGD) rates of residential mortgages, using a model based on stochastic collateral value. The implementation of the model is based on exponential Ornstein-Uhlenbeck processes fitted to the Hungarian regions' house price indices. According to the model results, in case of a mortgage with a 80% loan-to-value ratio at origination, the expected LGD is around 30–40%, depending on the region. The highest LGD rates are estimated for villages, while the lowest rates are expected in Budapest and cities in the middle of the country. The range of the regional differences can reach 7 percentage points. According to the LGD Risk index based on the aggregated model, the LGD risk profile of recently issued mortgages has improved significantly since 2009 in Hungary.
Due to the strong negative relation between the house prices and mortgage default rates, the expected return on defaulted collateral value tends to be low. The results could be relevant for credit institutions in their mortgage origination decisions and enhance analysis of lending processes and the associated risks.
... The real estate market reflects the social and economic changes that take place in the economy on a national and global scale. The real estate market is constantly changing, resulting from the relationships and dependencies between its participants, which include primarily investors and lenders, as well as developers, renters, tenants, etc. as discussed by Banai et al. (2017). The real estate market is quite specific, since the price is determined not only by the features directly characterizing a given property. ...
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In the book, an attempt was made to catalogue knowledge concerning the importance of research into the dynamics of housing prices for social and economic development. The analysis of the experience of countries with well-developed real estate markets in the aspect of building price indexes was carried out. Based on original databases of asking and transaction prices, price indexes were built, which were then subjected to numerous resistance tests. The aims of these research tasks were as follows: 1) to examine the quality of offers for sale as a source of information about changes in the real estate market, 2) to find out whether the repeat sales method can be used for building price indexes and to critically assess this method in terms of the stability of the obtained results, 3) to analyze hedonic methods and indicate the preferred one in terms of the ratio of the quality of results to how time-consuming and cost-intensive it is to build such indexes, 4) to establish the importance of methods and sources of information for building price indexes in different time horizons, 5) to identify how important it is for the fluctuation of price indexes if the cooperative property right to a flat is not taken into account. In order to perform the research tasks and accomplish the goals scopes of the work were defined. The subject followed the aim of the study and refers to prices in the secondary housing market, encompassing both the property right and cooperative property right to a flat or house. The broad scope concerns the discussion in the general part, being narrowed down to the secondary market of flats located in multi-family and single-family buildings. The time scope covers the years 2000-2015, which is connected to the range of empirical studies carried out. They focused both on actual transactions and on offers of flats for sale. On this basis, we built databases which served as the starting point for further analyses. The study involved transactions and offers in the area of Poznan.
