Francesco Tajani

An evaluation model of the financial feasibility of social housing in urban redevelopment

Purpose – The purpose of this paper is to develop an evaluation model to support the decisions made by Public Administrations that influence urban regeneration and social housing to be implemented with the involvement of private investors. Design/methodology/approach – Carried out with reference to an Italian regional territory, the model, subject to the constraint of financial feasibility for the private investor and the conditions of the local real estate market, allows to define: the maximum amount of social housing, as a percentage of the housing planned, to be sustained by the private investors; the administered price of sale and/or lease of the social housing; the exchange-factor of the area to be redeveloped. Findings – The outcome of the research highlights the utility of the model as a tool to support the decisions made by Public Administrations in relation to urban planning. Practical implications – The model, in addition to being simple to use, is extremely flexible and can be applied without a...

Evaluation of vacant and redundant public properties and risk control: A model for the definition of the optimal mix of eligible functions

Purpose The purpose of this paper is to propose a decision-support methodology for public and private subjects involved in the enhancement of public properties. In particular, with reference to cases in which the disused public property can be sold and the range of functions that define the highest and best use of the conversion was identified, the developed model allows for the assessment of the financial feasibility of the initiatives, in relation to the corresponding investment risks. Design/methodology/approach The proposed model integrates the mathematical logic of goal programming for the evaluation of the financial conveniences of the parties (public and private) involved in the enhancement of a public property with statistical approaches (value at risk+exponentially weighted moving average) so as to determine the investment risk of the private investor. The application of the model to a real case study highlighted the potentialities of the proposed methodology. Findings The model allows to determine: the optimal mix of intended uses to be realized in the public property under analysis; the fair value of the public property for the parties involved in the transaction; and the Pareto-optimal frontier of the expected profits, as a function of the risk appetite of the private investor. Practical implications The defined model responds to the growing international interest in the enhancement of public buildings, satisfies the objectives of the substantial reduction of soil sealing and urban sustainability, stimulates the urban regeneration of deprived areas of the cities through the reactivation of large buildings that have been disused or underused for too long. Originality/value The present research allows to provide effective evaluation tools capable of outlining the opportunities of redevelopment initiatives and examines the risk factors that often invalidate the initial forecasts of the private entrepreneur and/or stop the activation of investments.

Bare ownership evaluation. Hedonic price model vs. artificial neural network

In the current downturn of European real estate market, the sale of the bare ownership is creating a growing interest of market operators. The attention to this formula is not only local, but also comes from foreign investors, attracted by the substantial saving on the purchase price, the revaluation of the property over time, as well as the breakdown of the tax burden and the costs of management and maintenance. The aim of this research is, first of all, to deepen the knowledge of the bare ownership market of residential properties. Secondly, it is to develop an effective tool for estimating the bare ownership. Therefore, on the same database and with reference to the same explanatory variables of the price of bare ownership, two estimation models are implemented, one based on hedonic prices theory and another using artificial neural networks ANN, in order to compare the respective performance.

Least median of squares regression and minimum volume ellipsoid estimator for outliers detection in housing appraisal

In the real estate sector, regression analysis is the most used method for interpretative and predictive purposes. However, the presence of outliers in the estimative sample can lead to ordinary last squared regression models that do not represent the investigated market phenomenon, with the consequence of producing unreliable assessments. In the present research, the issues of the identification and the removal of outliers are discussed. The outliers identified by the least median of squares (LMS) regression and the minimum volume ellipsoid (MVE) estimator are compared in order to test the coincidence or the diversity. A complete diagnosis of the data of the initial estimative sample is carried out, combining the robust residuals obtained with LMS and the robust distances obtained with MVE. The data are classified into regular observations, vertical outliers, good leverage points and bad leverage points, and cases to delete and those to keep in the sample are identified.

Building Investments for the Revitalization of the Territory: A Multisectoral Model of Economic Analysis

Following the crisis generated by the financialization of private real-estate, construction prices have gradually decreased depriving the housing market of the necessary growth stimuli. Many countries have set up measures to revive this highly strategic area for the national economy. With reference to the Campania Region Law n. 19 dated 28 December 2009, known Housing Plan, this work has two objectives: to recognize the fundamental estimation problems that need to be solved in the implementation of the Campania Housing Plan; in addition, predict the effects of the regulations on the regional economy, both in overall terms as well as for each production sector, with particular attention being given to the construction industry. Regarding the first objective, the contents of the law are analysed on the basis of the principles that govern the appraisal. The consequences of the Campania Housing Plan on the economic system are then evaluated using input-output matrices, which are able to capture the structural relationships that exist among the various productive sectors. The numerical calculations require a preliminary investigation aimed at collecting a list of interventions approved by local governments in accordance to the Housing Plan. The cost of the works, as proposed in the applications submitted to the local administrations, is the input data for the implementation of the Social Accounting Matrix 2010 of the Campania Region.

Fuzzy logic and coherence control in multi-criteria evaluation of urban redevelopment projects

In the decision-making process of urban regeneration projects, the lack of transparency is one of the most frequent causes of the deceleration and the stopping of initiatives. In the present work, with reference to a multi-criteria model recently developed for the municipality of Rome Italy, a solution to this issue has been proposed. Borrowing the formal logic of fuzzy systems, the possibility to assign a different importance to the parameters which explain the objectives of the redevelopment, to compare the projects submitted by different operators, as well as to make it clear the phase in which the public administration evaluates the priorities of the projects, has been introduced. A measure of the coherence of the projects submitted by private operators with the importance of the objectives of redevelopment set by the public administration has been computed. The result is a flexible structure of the algorithm developed, able to adapt to the specificities of the case study and to the changes that, over time, could arise in the evaluation mechanism of the decision maker.

Estimative Analysis of a Segment of the Bare Ownership Market of Residential Property

Estimative analysis of the property market aims to identify the parameters, economic variables and mechanisms at the basis of negotiations that take place in the market. The aims are explanatory and predictive. In this work, a multiple regression analysis is carried out to evaluate a segment of the bare ownership market of residential properties in a district of an Italian city. In particular, using regression, the explanatory variables in the price of the bare ownership are selected among those initially identified with the empirical observation of this phenomenon, the hedonic prices and weights of the explanatory variables are estimated, the estimation function of the bare ownership price is specified as well as the average depreciation rate determined by the usufruct. The discrepancy between the depreciation rates estimated with the regression and those set out by the law for tax purposes, but applied when estimating the bare ownership value, leads to distrusting the practical use of the latter in matters other than tax purposes.

The rational quantification of social housing: an operative research model

This work has addressed the issue of the urban redevelopment of brownfield sites. It has developed an evaluation model for the quantification of the social housing component that the private investor must make in favor of the public administration. The protocol is based on finding a balance between the interests of the parties involved in urban redevelopment. The algorithm is constructed by borrowing techniques from Operations Research Linear Programming. The objective function is to maximize the social housing quota. The constraints formalize the utility functions of the two contracting parties (public and private). The result is a simple to use mathematical process, which can be implemented in any local context, in order to make choices consistent with the potential of the local housing markets. The algorithm developed is applied to a case located in a municipality of the Agro-Nocerino-Sarnese (SA). The output returned enhances the rationality of the model, capable of contributing to the feasibility of the redevelopment of disused areas.

Break Even Analysis for the Financial Verification of Urban Regeneration Projects

The involvement of the private investor in urban regeneration projects makes the verification of the financial feasibility of the initiative inevitable. Thus, the applicability of Break Even Analysis (BEA) is tested in this study. BEA is a financial analysis technique that allows to study the impact that technical, economic and organizational decisions may have on the financial feasibility of the project. The main methodological and operational aspects of BEA are discussed, with the application of an urban regeneration of a former brownfield site located in a city of Southern Italy being developed. The success of the experiment confirms the possibility to use BEA for the financial analysis of projects, especially in the early design stages.

Urban Redevelopment: A Multi-criteria Valuation Model Optimized through the Fuzzy Logic

In decision-making processes related to urban redevelopment, the clarity and the transparency play a primary role. In these contexts, the multi-criteria techniques, despite having a wide application, are not always adequate to represent and to quantify the quality effects of the urban initiatives, as well as to compare the alternatives for choosing the best solution, phases in which the logical rules followed by the decision-maker are not usually explicited. In the present work, with reference to a multi-criteria model recently developed for the municipality of Rome (Italy) to streamline and make more transparent the definition of urban regeneration projects, a solution to these issues is proposed, through the use of a fuzzy logic system. Using linguistic variables and expressions of ordinary language, logical rules followed by the decision-maker in performing the evaluations have been formalized. The result is a decision-making process clear and easy to understand, with positive effects on the legitimacy of the decisions of the Public Administration.