Forecasting the Finnish house price returns and volatility: a comparison of time series models

Purpose The purpose of this paper is to compare different models’ performance in modelling and forecasting the Finnish house price returns and volatility. Design/methodology/approach The competing models are the autoregressive moving average (ARMA) model and autoregressive fractional integrated moving average (ARFIMA) model for house price returns. For house price volatility, the exponential generalized autoregressive conditional heteroscedasticity (EGARCH) model is competing with the fractional integrated GARCH (FIGARCH) and component GARCH (CGARCH) models. Findings Results reveal that, for modelling Finnish house price returns, the data set under study drives the performance of ARMA or ARFIMA model. The EGARCH model stands as the leading model for Finnish house price volatility modelling. The long memory models (ARFIMA, CGARCH and FIGARCH) provide superior out-of-sample forecasts for house price returns and volatility; they outperform their short memory counterparts in most regions. Additionally, the models’ in-sample fit performances vary from region to region, while in some areas, the models manifest a geographical pattern in their out-of-sample forecasting performances. Research limitations/implications The research results have vital implications, namely, portfolio allocation, investment risk assessment and decision-making. Originality/value To the best of the author’s knowledge, for Finland, there has yet to be empirical forecasting of either house price returns or/and volatility. Therefore, this study aims to bridge that gap by comparing different models’ performance in modelling, as well as forecasting the house price returns and volatility of the studied market.

The false promise of homeownership: Homeowner societies in an era of declining access and rising inequality

In the late 20th century, homeownership became entrenched in a wider societal project that sought to transform the economy and increase social inclusion. This project focused on mortgaged owner-occupation as a means not only to acquire a stable home, but also to realise greater economic security via asset accumulation. The underlying ideology featured an implicit promise that homeownership would be widespread, equalising and secure. Despite transformations in market conditions, such narratives have continued to underscore policy approaches and housing marketisation. This article directly confronts this promise. It first unpacks its key tenets before investigating their currency across three classic ‘homeowner societies’: the US, the UK and Australia. Our empirical findings reveal declining access to homeownership, increasing inequalities in concentrations of housing wealth and intensifying house-price volatility undermining asset security. The article contends that the imperative of homeownership that has sustained housing policy since the 1970s may be increasingly considered a ‘false promise’. Our analyses expose contemporary housing market dynamics that instead appear to enhance inequality and insecurity.

Towards Understanding the Volatility of Housing Prices and Exploring the Tourism Demand Impact

Using an Exponential Generalized Autoregressive Conditional Heteroskedasticity model (EGARCH), the volatile nature of residential property prices in New Zealand is examined. The model investigates the extent to which macroeconomic fundamentals and a combined population shift/visitor factor called "tourism" impact residential property values and capture variations in volatility across different regions. We find that fundamentals have different impacts across regional property markets. In line with the literature, the bigger metropolitan regions like Auckland and Christchurch are more sensitive to macroeconomic factors than smaller regions. Additionally, we find house price volatility in southern regions is affected by macroeconomic fluctuations more than northern areas. Novel to the literature, we discover that "tourism" has significant impact on house price volatility as well, particularly in popular touristic areas. These results imply that to better understand the determinants of house price volatility and mitigate its effects, policy makers should consider a coordinated approach, taking a regional perspective and the interaction of several variables into account.

Determinants of house price volatility in Namibia

Purpose This paper aims to test the volatility and analyses the macroeconomic determinants of house price volatility in Namibia over the period 2007 Quarter 1 to 2017 Quarter 2. It further explores the causal relations between house price volatility and its determinants. Design/methodology/approach The study used autoregressive conditional heteroskedastic and generalized autoregressive conditional heteroskedastic models to test for volatility. The vector error correction model was used to analyse the determinants and causal relations. Findings The results support the hypothesis that house prices in Namibia exhibits persistent volatility. It was further established that past period volatility’ GDP and mortgage loans are the key determinants of house price volatility. Additionally’ there exists unidirectional causality from GDP and mortgage loans to house price volatility. Practical implications Policy implications emanating from the study implies that macroeconomic fundamentals should be monitored closely to mitigate the issues of house price volatility. Originality/value The study is the first of its kind in Namibia to address the pertinent issues of ever increasing housing prices.