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Social Identity as Determinant of Real Estate Economy in Manhattan

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Statistical Methods for Spatial Planning and Monitoring

Part of the book series: Contributions to Statistics ((CONTRIB.STAT.))

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Abstract

This paper tells about a procedure for investigating the coherence of the relationship between a “wide” concept of spatial distance and the geographical variation of real estate value.

Such coherence is analyzed taking a special attention to the “multiple identity”.

That characterizes some urban places.

Many authors consider that real estate value of similar housing units can depend mainly on distance from some reference points; furthermore, its variation can be considered roughly linear.

On this basis the use of geo-statistical approaches based on kriging techniques has been developed in mass appraisal.

A second relevant point of view underlines the relationship between the presence of higher real estate value in those places where several amenities are coexisting.

But in those urban realities where the number of central points and the number of amenities are high, the complexity does not support the construction of models, and this complexity leads to a different concept of identity as synthesis of distance, borders and concentration.

In this complexity maybe further aspect can arise. In the case of study, that is to say New York, it is possible to investigate the effect of racial steering on ethnic dissemination and real estate variation. Born as a symbol of racial discrimination, in the nowadays city it assumes an identity character that affect in a singular way the housing market. The aim of this paper is to demonstrate this hypothesis. [The paper is the result of a joint effort: Oliva wrote Sect. 7.1 and Torre wrote Sect. 7.2. The conclusions are due to both authors.]

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Correspondence to Carmelo M. Torre .

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Torre, C.M., Oliva, P. (2013). Social Identity as Determinant of Real Estate Economy in Manhattan. In: Montrone, S., Perchinunno, P. (eds) Statistical Methods for Spatial Planning and Monitoring. Contributions to Statistics. Springer, Milano. https://doi.org/10.1007/978-88-470-2751-0_7

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