Guest editorial

Citation

Ooi, J. and Mori, M. (2015), "Guest editorial", Journal of Property Investment & Finance, Vol. 33 No. 4. https://doi.org/10.1108/JPIF-04-2015-0023

Guest editorial

Article Type: Guest editorial From: Journal of Property Investment & Finance, Volume 33, Issue 4

We are honoured to serve as guest editors for this special issue of the Journal of Property Investment & Finance on issues related to the application of quantitative techniques to real estate.

The application of quantitative techniques covers various methods of measuring and analysing data in order to understand the numbers and draw conclusions, which in turn leads to more informed business or policy decision making. For example, real estate researchers have used quantitative techniques to estimate the effect of one or more factors, such as crime rates or quality of nearby schools, on property prices; and to understand real estate market dynamics by analysing trends and forecasting future price movements.

Apart from pure theoretical papers, it is hard to envisage a piece of research getting published in a good peer-reviewed journal nowadays without any supporting data or numbers. From the start, doctoral students in the social sciences are trained to adopt a scientific approach of enquiry. This process includes the importance of stating the hypotheses clearly and then testing them with empirical data using appropriate statistical and econometric techniques. They are taught that data collection involves drawing relevant information from an unbiased sample so that inferences could be made on the larger population. Data analysis, on the other hand, involves using appropriate statistical techniques to estimate whether a relationship exists between two variables and whether the relationship is significant. While ordinary least squares (OLS) regressions may be sufficient in the past to identify relationships, researchers of today are more fixated with identifying cause-and-effect relationships.

Led by the editors and reviewers of top journals in the social sciences who are cautious of jumping into quick conclusions, many researchers have adopted the stance that simply finding a relationship between two variables is not sufficient evidence that the relationship is causal. Accordingly, the identification problem is becoming a recurring theme in applied quantitative research. Parallel to this obsession, the quantitative techniques are also becoming more sophisticated. For example, randomized selection methods, matching and propensity score methods, instrument variable techniques, difference-in-differences, and regression discontinuity design are now common tools of trade to address selection bias, identify causality, and evaluate the outcomes of public policy interventions.

This special issue covers a small sample of papers that have applied quantitative techniques to study real estate issues. The first academic paper applies a Bayesian Belief Network modelling approach to strategic decision making in corporate real estate management of three organizations in Belgium and the Netherlands. The second paper compares the adequacy of five alternative modelling techniques to forecast UK commercial property rents with the aim of answering a simple question, does complex forecasting techniques outperform simple ones. The third paper compares the usefulness of simulation, namely input-output (IO) and computable general equilibrium (CGE) models, for analysing the economic impact of mixed-used property redevelopment projects in Colorado, USA. The fourth paper employs cointegration tests to examine how direct and indirect property markets in Australia adjust to an equilibrium long-term relationship. Finally, a practice paper provides practitioners with a familiar and flexible tool that allows explicit incorporation of a broad range of uncertainty into the DCF model.

Dr Joseph Ooi and Dr Masaki Mori, Department of Real Estate, National University of Singapore, Singapore