Modeling of residential property prices index using committees of artificial neural networks for PIGS, the European-G8, and Poland - Wiśniewski, Radosław (Wydawnictwo Uniwersytetu Ekonomicznego we Wrocławiu, 2017)
This paper develops models of residential property prices indices for PIGS, the European-G8 and Poland using a committee of artificial neural networks approach. Quarterly time series data are applied for testing and the empirical results suggest that population growth, unemployment rate, final consumption expenditure, net national income (ANNI), household final consumption expenditure, long-term interest rates, HICP rate of change of housing, water, electricity, gas and other fuels, HICP housing services, HICP actual rentals for housing, and HICP maintenance and repair of the dwelling are the major determinants of the residential property price index in PIGS, the European-G8 and Poland.The developed models show that the economic and financial situation in a given country affects the residential property markets. Residential property markets are connected, despite the fact that they are situated in different parts of Europe. The economic and financial crisis in the countries of the PIGS group affects not only the PIGS markets but also the real estate markets of the European-G8 and Poland.The results also suggest that a methodology based on a committee of artificial neural networks has the ability to learn, generalize, and converge the residential property prices index
Argumenta Oeconomica, 2017, Nr 1 (38), s. 145-194
Keywords: residential property prices index; committee of artificial neural networks; PIGS; G8; Poland