In the academic debate there is a broad consensus that house price fluctuations have a substantial impact on financial stability and real economic activity. Therefore, it is important to have timely information on actual and expected house price developments. The aim of this paper is to measure...

In the academic debate there is a broad consensus that house price fluctuations have a substantial impact on financial stability and real economic activity. Therefore, it is important to have timely information on actual and expected house price developments. The aim of this paper is to measure...

In this paper, we evaluate the forecasting ability of 145 indicators and ten types of forecast combination schemes to predict housing prices and rents in 71 German cities. We are interested in whether local business confidence indicators facilitate substantial improvements of the forecasts,...

We analyze the impacts of alternative submarket definitions when predicting house prices in a mass appraisal context, using both ordinary least squares (OLS) and geostatistical techniques. For this purpose, we use over 13,000 housing transactions for Louisville, Kentucky. We use districts...

Purpose – We use a large and rich data set consisting of over 123,000 single-family houses sold in Switzerland between 2005 and 2017 to investigate the accuracy and volatility of different methods for estimating and updating hedonic valuation models.Design/methodology/approach – We apply six...

In this study we use property-level transaction data to construct several different out-of-sample forecasts for the sales of individual homes in 10 counties in Florida. We utilize a number of common forecast combination methods and analyze the properties of their forecast errors. The results...

We augment linear pricing models for the housing market commonly used in the literature with google trends data in order to assess whether or not crowd-sourced search query data can improve the forecasting ability of the models. We compare various performance measures of the augmented linear...

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...

We evaluate a number of real estate sentiment indices to ascertain current and forward-looking information content that may be useful for forecasting demand and supply activities. Analyzing the dynamic relationships within a Vector Auto-Regression (VAR) framework and using the quarterly US data...

We show that house prices from Aberdeen in the UK improve in- and out-of-sample oil price forecasts. The improvements are of a similar magnitude to those attained using macroeconomic indicators. We explain these forecast improvements with the dominant role of the oil industry in Aberdeen. House...