Pietro Bonifaci

Real estate market and building energy performance: Data for a mass appraisal approach

Mass appraisal is widely considered an advanced frontier in the real estate valuation field. Performing mass appraisal entails the need to get access to base information conveyed by a large amount of transactions, such as prices and property features. Due to the lack of transparency of many Italian real estate market segments, our survey has been addressed to gather data from residential property advertisements. The dataset specifically focuses on property offer prices and dwelling energy efficiency. The latter refers to the label expressed and exhibited by the energy performance certificate. Moreover, data are georeferenced with the highest possible accuracy: at the neighborhood level for a 76.8% of cases, at street or building number level for the remaining 23.2%. Data are related to the analysis performed in Bonifaci and Copiello [1], about the relationship between house prices and building energy performance, that is to say, the willingness to pay in order to benefit from more efficient dwellings.

Depreciated Replacement Cost: Improving the Method Through a Variant Based on three Cornerstones

Abstract Within the scope of real estate appraisal, the Depreciated Replacement Cost method is mostly seen as a solution of last resort, when no other option is available. Nonetheless, it is ever more useful in addressing various estimation needs. In its basic formulation, the method suffers from several simplifications that lead to rather rough results. Here we try to go beyond these limits. To this end, we propose a variant based on the following three cornerstones. The first is the partition of the replacement cost into its fundamental components, at least according to three cost items: building structure, finishes, and installations. The second cornerstone is the formulation of different depreciation curves for each of the cost items mentioned above, by processing distinct data on useful life and residual life. Finally, the third cornerstone is represented by the definition of a complex depreciation function to take into account both the original useful life of the construction and its lengthening due to partial or full refurbishments.

Italian housing market during expansion and downturn: a cluster analysis approach based on spatial data

The residential sector is a crucial segment in Italy, as it represents the most significant component of household wealth, and homeownership greatly prevails (around 73%) in comparison to other European countries. Moreover, the construction sector is an important contributor to domestic economy (about 10% of the GDP), but the last market cycle had a substantial impact on the construction business. The most significant downsizing concerned the constructions, as they have lost more than 10 percent of companies, almost 20 percent of employees and around 30 percent of the gross fixed capital formation. A weak economic prospect hit the property market, dramatically reduced the volume of transactions and bring the house prices down in most cities. This prolonged downturn of the market freeze the capital flow in most of part of the country, but different towns experienced different reactions to the global economic crisis.This paper aims at analysing the particular condition of the Italian residential market of the last 20 years, clustering the Italian cities into groups according to their behaviour and their characterization. The novelty of the approach proposed here lies in using not only market data and socio-economic covariates for the analysed cities, but also trends and dynamics shown by the adjoining and surrounding territorial units, according to the principles of spatial data analysis. Indeed, following the so-called first law of geography (Tobler, 1970), “everything is related to everything else, but near things are more related than distant things”. Therefore, we expect that the real estate market fundamentals in a city are affected, to a certain extent, by what happens in the neighbouring cities.The method has been implemented using the data of the last two market cycles (expansion: 1999 – 2006; recession: 2007 – 2016), employing a variety of demand-side and supply-side variables, such as the number of transactions, house stock, house prices, building permits, quality of life, index of sustainability. The analysis has been conducted considering data organised at NUTS 3 level (Nomenclature of Territorial Units for Statistics), namely, the Provinces. Custer analysis is then used to determine the composition of different submarkets and to characterise them, in order to understand their different conditions and to assess the weakness of the various submarkets during the expansion and the downturn of the market.

The contribution carried by the appraisal discipline for the purpose of disentangling the embodied energy issue

In the disciplinary field of real estate appraisal, the cost estimates of the construction materials and building works are long since well established, and they rely upon a considerable basket of qualified sources. While assessing projects, particularly through the methodological framework which involves the bill of quantities, we are used to referring to exhaustive inventories of the costs to be incurred. Such widely available data sources specify the characteristics of the materials to be employed during the laying process, as well as of the works to be carried out, and report the related costs per unit weight, volume or surface area.In a research we developed, we aimed at deeply examining the relation between the aforementioned costs of building materials and their embodied energy. The latter is defined as the energy load needed to mine the raw materials, to manufacture the semi-finished goods, as well as to transport them to the construction site. As it was expected according to outcomes discussed by the relevant literature, we found evidence of a positive relation between the cost of the construction materials and their embodied energy. Nevertheless, the linear functional form is not appropriate, since such a model does not provide statistically significant results. On the contrary, adopting a log-linear function, the interpolation curve fits much better to the data, hence the cost of the construction materials may be regarded as a reliable predictor of their embodied energy.This research branch requires performing a range of intensive trials, in order to get a more acute awareness of how much the results are generalisable. The preliminary findings bring out several interesting considerations, which in turn entail - or at least suggest - further investigations: firstly, the accuracy level of the model, namely the quality of the interpolation and the stability of the results, significantly increases by defining clusters of the building materials with reference to the sub-sectors they belong to; secondly, the items belonging to the raw material industry show conflicting results, that is to say, an inverse relation between the cost and the amount of embodied energy.