The Monetary Valuation of Environmental Externalities through the Analysis of Real Estate Prices

Abstract

This paper proposes a theoretical model of evaluation of environmental externalities based on the analysis of real estate prices. This issue is included in regional planning policies which include activities and interventions that produce economic and non-economic effects. The monetary assessment of economic and non-economic effects can be expressed as a forecast (ex ante) and/or following (ex post) such activities and interventions. The assessment of the economic impact, with particular reference to interventions and infrastructure work, is widely based on procedures which make use of market prices. The proposed model was applied to an actual case, considering the effects of noise pollution, produced by traffic from the Naples Beltway, on residential property.

Rough Set Theory for Real Estate Appraisals: An Application to Directional District of Naples

“…[33]. However, the relationship between objects and rules in the application of RST for mass appraisal purposes represents a way and a perspective of research partially unexplored yet.…”

Assessing the Impact of Urban Improvement on Housing Values: A Hedonic Pricing and Multi-Attribute Analysis Model for the Historic Centre of Venice

“…HPM has been applied to very different urban contexts: in cities such as Geneva [7][8][9] or Glasgow [10]; metropolises such as Naples [11,12], Tokyo [13], Chicago, Denver, Philadelphia, Baltimore, Washington DC [14,15], or Seoul [16]; and in informal settlements in Asian cities such as Bangkok and Jakarta [17]. Studies have either focused on one specific local context [18,19], or compared various local environments ranging over wide territorial areas to estimate the effect of the proximity to natural attractions [20][21][22], or big infrastructures such as airports [23].…”

Real Estate Appraisals with Bayesian Approach and Markov Chain Hybrid Monte Carlo Method: An Application to a Central Urban Area of Naples

“…The relationship between sales price and explanatory variables can be examined with a semi-parametric additive model, characterized by the combination of a generalized additive model, which expresses the relationship between non-linear response of model and explanatory variables, and a linear mixed effects model, which expresses the spatial correlation of observed values [8,9,11,12,16]:…”

“…In particular, is it understood that the minimum dimension of real estate sample necessary to implement a statistical inference model is correlated to the number of independent variables explaining real estate characteristics [3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18].…”