Determinants of house prices in Turkey: Hedonic regression versus artificial neural network |
| |
| Authors: | Hasan Selim |
| |
| Affiliation: | 1. College of Computer Science, Chongqing University, Chongqing 400030, China;2. College of Software Engineering, Chongqing University, Chongqing 400030, China;1. Institute of Agricultural and Resource Economics, Faculty of Social Sciences, University of Agriculture Faisalabad, University Road, Faisalabad, 38040, Pakistan;2. Department of Rural Sociology, Faculty of Social Sciences, University of Agriculture Faisalabad, University Road, Faisalabad, 38040, Pakistan;1. Department of Civil Engineering, Zhejiang University, Hangzhou, 310058, China;2. Center for Real Estate Studying, Zhejiang University, Hangzhou, 310058, China;3. Department of Building and Real Estate, Hong Kong Polytechnic University, Hong Kong, China;1. National Technical University of Athens, Laboratory of Transportation Engineering, 9, Iroon Polytechneiou, Zografou, 15780 Attica, Greece;2. École Polytechnique Fédérale de Lausanne, Transport and Mobility Laboratory, Station 18, CH-1015 Lausanne, Switzerland |
| |
| Abstract: | Determinants of house prices in Turkey are examined in this paper using the 2004 Household Budget Survey Data. In property valuation and housing market research, the locational value is usually analyzed by hedonic methods that use multiple regression techniques on large data sets and require a formality based on microeconomic theory in the analyses. Because of potential non-linearity in the hedonic functions, artificial neural network (ANN) is employed in this study as an alternative method. By comparing the prediction performance between the hedonic regression and artificial neural network models, this study demonstrates that ANN can be a better alternative for prediction of the house prices in Turkey. |
| |
| Keywords: | |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
