Automated valuation modelling: a specification exercise

Abstract

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in AbstractMarket value predictions for residential properties are important for investment decisions and the risk management of households, banks, and real estate developers. The increased access to market data has spurred the development and application of Automated Valuation Models (AVMs), which can provide appraisals at low cost. We discuss the stages involved when developing an AVM. By reflecting on our experience with md*immo, an AVM from Berlin, Germany, our paper contributes to an area that has not received much attention in the academic literature. In addition to discussing the main stages of AVM development, we examine empirically the statistical model development and validation step. We find that automated outlier removal is important and that a log model performs best, but only if it accounts for the retransformation problem and heteroscedasticity.

The Hedonic Modelling of Rental Values of Properties in Nasarawa, Nigeria

“…Table 4 explains 68% variations in rental values, while Table 5 explains 64% variations in rental values. Unlike many empirical analysis that reveal the benefit of log transformation of the dependent variable with an enhancement in goodness of fit [18,25], the result in this study reveals otherwise. The quality of data used in this assessment would not permit a categorical statement on the best functional form specification for the local market.…”

“…Yang [24] used the Box-Cox, linear and semi-log specifications on 226 apartments in Beijing, China and found the semi-log model as the most preferred form. Schulz et al [25] used 18,444 property sales stratified into development step (sales from 2000 to 2005 (8,429 observations)) and validation step (sales from 2006 to 2011 (10,015 observations)) in Berlin, Germany. The results reveal the semi-log to provide a better fit.…”

A GIS-based hedonic price model for agricultural land

“…The former measures the discrepancies between the predicted values and the actual observations whiles the latter measures scaled discrepancies. Such measures have been also used in other case studies 23,30 . Furthermore, in order to measure how the error deviates, the absolute percentage error estimated which called forecasting error (FE) 17 .…”

“…Hedonic regression modeling is the oldest statistical calibration methodology has been utilized for estimating property values gained the most attention since 60s early 70s 27 until nowadays 28,29,30 . As noted earlier, it is based on multiple regression analysis (MRA) which is one of the most well-known statistical methods with huge range of applications especially for prediction and forecasting.…”

Real Estate valuation and forecasting in non-homogeneous markets: A case study in Greece during the financial crisis

“…Traditional valuation methods include various expressions of linear regression including multiple, stepwise, quantile, robust and additive regression approaches using hedonic models incorporating features of the property such as its age, square feet of living space, number of bedrooms, plot size, and others, (Brunauer et al, 2013;Caples et al, 1997;Coleman and Larsen, 1991;Janssen et al, 2001;Isakson, 2001;Mark and Goldberg, 1988;Pagourtzi et al, 2003;Reichert, 1990;Schulz et al, 2014). The underlying hypothesis of these models is that the valuation of the residence can be related to a specific set of the propertys characteristics, (Kummerow, 2000).…”