PurposeIn the literature there are numerous tests that compare the accuracy of automated valuation models (AVMs). These models first train themselves with price data and property characteristics, then they are tested by measuring their ability to predict prices. Most of them compare the effectiveness of traditional econometric models against the use of machine learning algorithms. Although the latter seem to offer better performance, there is not yet a complete survey of the literature to confirm the hypothesis.Design/methodology/approachAll tests comparing regression analysis and AVMs machine learning on the same data set have been identified. The scores obtained in terms of accuracy were then compared with each other.FindingsMachine learning models are more accurate than traditional regression analysis in their ability to predict value. Nevertheless, many authors point out as their limit their black box nature and their poor inferential abilities.Practical implicationsAVMs machine learning offers a huge advantage for all real estate operators who know and can use them. Their use in public policy or litigation can be critical.Originality/valueAccording to the author, this is the first systematic review that collects all the articles produced on the subject done comparing the results obtained.
The appraisal of large amounts of properties is often entrusted to Automated Valuation Models (AVM). At one time, only econometric models were used for this purpose. More recently, also machine learning models are used in mass appraisal techniques. The literature has devoted much attention to assessing the performance capabilities of these models. Verification tests first train a model on a training set, then measure the prediction error of the model on a set of data not met before: the testing set. The prediction error is measured with an accuracy indicator. However, verification on the testing set alone may be insufficient to describe the model’s performance. In addition, it may not detect the existence of model bias such as overfitting. This research proposes the use of cross validation to provide a more complete and effective evaluation of models. Ten-fold cross validation is used within 5 models (linear regression, regression tree, random forest, nearest neighbors, multilayer perception) in the assessment of 1,400 properties in the city of Turin. The results obtained during validation provide additional information for the evaluation of the models. This information cannot be provided by the accuracy measurement when considered alone.
The recent economic global crisis has raised the default rate of mortgage loans. Real estate assets -buildings or areas-set as collateral for mortgages encounter numerous difficulties during the liquidation phase. They can remain in disuse without meeting any possible purchaser or they can be sold at an auctioned price much lower than the book value. However, some developers may see investment opportunities in these areas and undertake processes of value extraction.. These subjects undertake processes of value extraction from these areas. This research aims to investigate whether the strategies and experiences of urban transformation can find valid strategies for the valorisation of these assets. Information derived from transformation works on unfinished buildings have been used as data set. For the purposes of the investigation, the stalled real estate investments were the closest representative comparable to the characteristics of real estate collaterals in non performing loans. The result is the elaboration of a grounded theory that theorizes three intervention guidelines for these assets, not based only on market indicators but also exploiting the potential of urban planning tools such as the transfer of development rights.
The public/private partnerships have been a successful innovation in the implementation of urban plans and they became an ordinary instrument in city planning and management. In the partnerships, agreements on zoning allow more advantageous planning rules. The corresponding economic gain is shared between the administration and the property. Research has devoted attention to the nature of the economic gain, investigating its nature and how it should be shared. Less effort has been devoted instead to understand how general norms have found application in the administrative action of public authorities. The research focuses on these aspects and investigates methodologies and techniques with which public administrations have evaluated public/private partnerships in cities development projects. The study identified Veneto Region as a privileged area of research. We examined the administrative acts approved by the municipalities with regard to the public/private partnerships allowed by Veneto planning law (LR 11/2004) and by decree 380/2001 derogatory building permits. Attention was paid to provincial capitals and, in order to have a representative sample of smaller towns, the survey considered all the municipalities of the Vicenza province. Conclusions of the research are controversial. The economic issue seems well managed: local administrations acquired the economic ratio of the agreements and the necessity of sharing the gain resulting from administrative decisions between public authorities and landlords. Local acts focus on valuation methodologies, in particular on automatic or quasi-automatic valuations, with debatable outcomes: the application of automatic procedures does not necessarily lead to quality results. Lastly, in territories substantially homogeneous, only a few kilometers away, levy rates can be very different, posing obvious and relevant problems of effectiveness and fairness.
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