Work detail

Best predictors of apartment prices: Empirical Evidence from Czechia

Author: Bc. Ondřej Šváb
Year: 2019 - summer
Leaders: Petr Pleticha
Consultants:
Work type: Bachelors
Language: English
Pages: 64
Awards and prizes:
Link: https://is.cuni.cz/webapps/zzp/detail/202571/
Abstract: It is essential to control for property price determinants since there could be created the price
bubble, and its burst would have harmful effects on the economy. Thus, this bachelor thesis aims
to show the best determinants and models for forecasting the apartment prices in Czechia and its
regions with the use of panel data and time series from the Czech Statistical Office. After stating
hypotheses of variable’s expected impacts on apartment prices, the most important determinants
appeared to be the average wage, unemployment rate, natural population growth, and the building
plot price. The best results are found by using econometric regressions as the fixed effects, the
first differences or the classical ordinary least squares method. I also use the heteroskedasticity
and autocorrelation consistent standard errors for better robustness of coefficients. Moreover,
the lasso method is applied for dealing with multicollinearity and over-fitting, which are fixed by
the variable selection. In most cases, the lasso improved prediction accuracy. However, the first
difference regressions worsen the forecasts after the lasso penalisation.
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