The application of Hierarchical Linear Model on the analysis of Housing Character and Price model of Chupei erea

• Main Authors: Bing-Ying Lin, 林秉穎
• Other Authors: Chich-Ping Hu
• Format: Others
• Language: zh-TW
• Published: 2014
• Online Access: http://ndltd.ncl.edu.tw/handle/gufkw2

碩士 === 中華大學 === 建築與都市計畫學系碩士班 === 102 === The housing characteristic and price model has often been applied to the model of estimating the housing price in the past; including, other than the characteristics of a residence itself and the external environment, the regional properties where the residence is located which are all major factors with an influence on the housing price. In the real estate research field, the characteristic and price approach mostly serves as the scope of the research domain. However, issues concerning the space autocorrelation and heterogeneity are often neglected during the research process. Therefore, this study focuses on the northern Hsinchu area as the study scope, with a multi-level model to investigate the correlations of the influential factors with an influence on the housing price, and a multi-level architecture to build a two-level characteristic price model. The first level is the residence level, including: the total housing price, residential area of a residence, public facility area of a residence, and the floor number; the second level is the community level, including: the school district for famous junior high schools, and High Speed Rail stations, etc. In addition, three models such as the random effect model, random regression coefficient model, and intercept and slope model are applied to serve as the scope of this study. A multi-level model is also referred to as a HLM (Hierarchical Linear Modeling) model, by applying a single-level analytical concept to the nested processing and engaging in data analysis. Its research result shows the interpretation variables of the community level indicate an obvious influence on the housing price.