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Modeling Real Estate Data

Wolfgang A. Brunauer

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ISBN 10: 3838126971 / ISBN 13: 9783838126975
Published by Sudwestdeutscher Verlag Fur Hochschulschriften AG
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Paperback. 124 pages. Dimensions: 8.7in. x 5.9in. x 0.3in.The statistical analysis of real estate data has received increasingly more attention during the last decade. Property owners, investors and banks are looking for cost-effective and reliable means to assess the value of single properties or even property portfolios. Additionally, building operating charges have turned out to be a major determinant of profitability of real estate investment, and the Europe-wide introduction of the energy certification for buildings in 2002 enhances the importance of accurate assessment of the energy efficiency of buildings even more. The main purpose of this thesis is to apply approaches that address nonlinearity and spatial or cluster-specific heterogeneity simultaneously on real estate price and cost data. A particularly broad and rich framework for semiparametric modeling is provided by structured additive regression (STAR) models. In STAR-models, continuous covariates are modeled as P(enalized)-splines. Furthermore, possibly correlated discrete random effects for spatial indexes, functions of two dimensional surfaces and (spatially) varying coefficient terms may also be estimated using this methodology. This item ships from multiple locations. Your book may arrive from Roseburg,OR, La Vergne,TN. Bookseller Inventory # 9783838126975

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Bibliographic Details

Title: Modeling Real Estate Data

Publisher: Sudwestdeutscher Verlag Fur Hochschulschriften AG

Binding: Paperback

Book Condition:New

Book Type: Paperback

About this title

Synopsis:

The statistical analysis of real estate data has received increasingly more attention during the last decade. Property owners, investors and banks are looking for cost-effective and reliable means to assess the value of single properties or even property portfolios. Additionally, building operating charges have turned out to be a major determinant of profitability of real estate investment, and the Europe-wide introduction of the energy certification for buildings in 2002 enhances the importance of accurate assessment of the energy efficiency of buildings even more. The main purpose of this thesis is to apply approaches that address nonlinearity and spatial or cluster-specific heterogeneity simultaneously on real estate price and cost data. A particularly broad and rich framework for semiparametric modeling is provided by structured additive regression (STAR) models. In STAR-models, continuous covariates are modeled as P(enalized)-splines. Furthermore, possibly correlated discrete random effects for spatial indexes, functions of two dimensional surfaces and (spatially) varying coefficient terms may also be estimated using this methodology.

About the Author:

DI (FH) Mag. Dr. Wolfgang A. Brunauer: Research analyst in the Immobilien Rating GmbH, Vienna. Studies of Facility Management (Kufstein) and Economics (Innsbruck), 2010 doctorate at the University of Innsbruck. Refereed Papers inter alia in the Journal of Real Estate Finance and Economics and the Journal of Property Investment and Finance.

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