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題名 A prediction model for housing investment probability
作者 Chiou, Y.-S.;Chou, M.-L.;Chang, Chin-Oh
張金鶚
貢獻者 地政系
關鍵詞 Homebuyer`s behavior; Housing investor; Probability prediction model
日期 2013-06
上傳時間 21-May-2015 16:49:05 (UTC+8)
摘要 This study investigates the government-conducted "Housing Demand Survey" from 2006Q4 to 2007Q3 to establish a binary logit model to analyze the housing attributes, search behaviors, and investors and owner-occupiers` personal characteristics for financial institutions prediction in determining house buyer motivation and reducing the loss incurred when payment is not advanced or is defaulted. The empirical results show that the locations, prices, sizes, and types of houses are the dominant factors affecting investment probability. Investors tend to select houses located downtown with high unit prices and small in size. They also tend to buy pre-sale, resold, and auction houses. The individual attributes of buyers, such as gender, age, occupation, and income, also play an important role in investment decisions. The proposed model has the highest prediction accuracy when the probability cutoff point is 0.7 and the investors` hit rate is 65.52% in contrast to the owneroccupiers` 84.51%, as indicated by the out-sample test. This study also determines that financial institutions incur the least loss with a cutoff point of 0.7 under different weights, when payment is not advanced or is defaulted.
關聯 NTU Management Review, 23(2), 1-28
資料類型 article
DOI http://dx.doi.org/10.6226/NTURM2013.JUN.R10018
dc.contributor 地政系
dc.creator (作者) Chiou, Y.-S.;Chou, M.-L.;Chang, Chin-Oh
dc.creator (作者) 張金鶚zh_TW
dc.date (日期) 2013-06
dc.date.accessioned 21-May-2015 16:49:05 (UTC+8)-
dc.date.available 21-May-2015 16:49:05 (UTC+8)-
dc.date.issued (上傳時間) 21-May-2015 16:49:05 (UTC+8)-
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/75249-
dc.description.abstract (摘要) This study investigates the government-conducted "Housing Demand Survey" from 2006Q4 to 2007Q3 to establish a binary logit model to analyze the housing attributes, search behaviors, and investors and owner-occupiers` personal characteristics for financial institutions prediction in determining house buyer motivation and reducing the loss incurred when payment is not advanced or is defaulted. The empirical results show that the locations, prices, sizes, and types of houses are the dominant factors affecting investment probability. Investors tend to select houses located downtown with high unit prices and small in size. They also tend to buy pre-sale, resold, and auction houses. The individual attributes of buyers, such as gender, age, occupation, and income, also play an important role in investment decisions. The proposed model has the highest prediction accuracy when the probability cutoff point is 0.7 and the investors` hit rate is 65.52% in contrast to the owneroccupiers` 84.51%, as indicated by the out-sample test. This study also determines that financial institutions incur the least loss with a cutoff point of 0.7 under different weights, when payment is not advanced or is defaulted.
dc.format.extent 2544555 bytes-
dc.format.mimetype application/pdf-
dc.relation (關聯) NTU Management Review, 23(2), 1-28
dc.subject (關鍵詞) Homebuyer`s behavior; Housing investor; Probability prediction model
dc.title (題名) A prediction model for housing investment probability
dc.type (資料類型) articleen
dc.identifier.doi (DOI) 10.6226/NTURM2013.JUN.R10018
dc.doi.uri (DOI) http://dx.doi.org/10.6226/NTURM2013.JUN.R10018