This paper presents a parsimonious model for forecasting and analysing euro area house prices and their interrelations with the macroeconomy. A quarterly vector error correction model is estimated over 1970-2009 using supply and demand forces central to the determination of euro area house...

This paper defines a measure of net housing demand or supply which allows the calculation of a long, high frequency time series, whose principal use is intended to be in a multivariate residential property price forecasting model. The series is easily and inexpensively replicable. We formulate...

This paper presents a parsimonious model for forecasting and analysing euro area house prices and their interrelations with the macroeconomy. A quarterly vector error correction model is estimated over 1970-2009 using supply and demand forces central to the determination of euro area house...

This article provides the in-sample estimation and evaluates the out-of-sample conditional mean and volatility forecast performance of the conventional Generalized Autoregressive Conditional Heteroscedasticity (GARCH), Asymmetric Power Autoregressive Conditional Heteroscedasticity (APARCH) and...

This paper follows the recent literature on real estate price prediction and proposes to take advantage of machine learning techniques to better explain which variables are more important in describing the real estate market evolution. We apply the random forest algorithm on London real estate...

Housing markets display several correlations to multiple economic sectors of an economy. Their enormous impact on economies’ health, wealth, and stability is uncontroversial. Interestingly, the forms of financing residential property vary widely between the different countries in terms of...

For several decades, theorists and researchers have emphasized investigating and analyzing the likelihood of contagion of turbulence among markets. The behavior of the housing market is also essential because of the impact of housing prices on the loan portfolios of banks and other financial...

Cokriging is a multivariate spatial method to estimate spatial correlated variables. This method allows spatial estimations to be made and interpolated maps of house price to be created. These maps are interesting for appraisers, real estate companies, and bureaus because they provide an...

We employ a 10-variable dynamic structural general equilibrium model to forecast the US real house price index as well as its turning point in 2006:Q2. We also examine various Bayesian and classical time-series models in our forecasting exercise to compare to the dynamic stochastic general...

We implement several Bayesian and classical models to forecast housing prices in 20 US states. In addition to standard vector-autoregressive (VAR) and Bayesian Vector Autoregressive (BVAR) models, we also include the information content of 308 additional quarterly series in some models. Several...