Abstract
With the exception of a living place, the house is an asset which needs to be estimated the future price and possibility of being sold. Main purpose of this paper is to estimate the prediction of the selling possibility of houses. Selling possibility of apartments in every city depends on qualitative and quantitative characteristics of houses. The area of per sq. m., number of rooms, the distance from the city center, located floor in building, and some quality indicators as the repair, parquet, furniture, distance to metro station, availability of documents, equipment with natural gas, project type, etc. are explanatory variables of our model. Dependent variable of the model was called as G score. This score was coded “0” when the house has not been sold during the period; otherwise “1”. On the base of this database, we calculated G score and found that, if the computed G value is equal to or greater than 0.33, then the house is considered with high possibility of selling. If the score is less than 0.33; it is classified as low-selling chance or illiquid. This estimation instrument might be useful for real-estate brokers, commercial banks, or even financial market participants working with real-estate-based derivatives.
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Notes
This characteristic is very important in housing market in Baku, because most of houses which have been observed are located in new buildings do not have the official documents ownership (has only sale contract).
This test can be used to measure the predictive power of such models. The value of this test is as follows: \( K = \frac{{\sum f_{0} - \sum f_{e} }}{{N - \sum f_{e} }}, \) where k—the value of kappa test, \( \mathop \sum \nolimits f_{0} \)—sum of frequency on both observed classification, \( \mathop \sum \nolimits f_{e} \)—sum of frequencies on both expected classification, and N—size of observation. The computed value of Kappa test is examined within 6 (six) significance interval: \( k \le 0 \) (very small compliance), \( 0 < k \le 0.20 \) (small compliance), \( 0.21 < k \le 0.40 \) (acceptable compliance), \( 0.41 < k \le 0.60 \) (medium strong compliance), \( 0.61 < k \le 0.80 \) (significant compliance), and \( 0.81 < k \) (almost perfect compliance). We also found the application of this test in some papers which have been introduced by Cohen (1968), Kraemer (1980), Sprcic et al. (2013).
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Acknowledgements
I would like to thank Mr. Elchin Gulaliyev and Mr. Murad Yusifov (Economists at the Central Bank of Azerbaijan) for their editorial support.
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Abbasov, J. The estimation of selling possibility of houses. Asian J Civ Eng 19, 827–837 (2018). https://doi.org/10.1007/s42107-018-0066-8
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DOI: https://doi.org/10.1007/s42107-018-0066-8