住宅變異性對居住穩定性影響分析

Analysis on Inhabitation Stability with Influence from Housing Variation

住宅是個人努力工作最重要追求的目標。選擇一個適合自己家庭的住宅，必須兼顧居住空間需求與家庭需要的滿足。住宅具有不可移動性、異質性、價格昂貴及鄰近環境設施，除非重大因素，住戶不會經常遷移，居住具有穩定性。但是對於弱勢家戶而言，生活負擔沉重，缺乏財務支持下，往往會選擇犧牲居住安定，以求溫飽。本文定義家戶屬性與住屋屬性間的共變量為住宅典型因子，並且在住戶穩定居住決策中扮演重要的角色。為了分析住宅典型因子與相關變數對居住穩定性的影響性質與程度，本文利用二階段估計方法建立居住穩定性模型。第一階段利用「典型相關分析」，經由官方統計資料得到「家戶」與「住屋」特徵與屬性資料，作為操作模型的投入變數，並且檢定典型因子的顯著性。住宅變異性，則是依二組住宅典型因子得點值計算標準化之數值差異值取絕對值後而得。第二階段則進一步利用「binary logit 模型」分析住宅變異性及家戶夫妻共變量與政府補助對住戶穩定居住決策的影響性質與程度。研究結果發現，除了夫妻間年齡差異顯著正向影響居住穩定性，其他的夫妻共變量、住宅變異性與政府補助皆顯著負向影響居住穩定性。

A suitable house for individuals is the most important object to accomplish with one’s efforts. Owning a comfortable house for a family should always consider to meet between living space demand and family need. Households will not often relocate for the reason that living is stable associated with the housing properties of immobility, heterogeneity, high using cost, and environmental quality need only if inevitable requirements take place. But for the disadvantaged families will always be forced to sacrifice stable residence situation to be survived due to considerable living burden and supportive financial lack. This research defines the covariate between household attributes and dwelling attributes as housing canonical factor playing the role to affect the decision of inhabitation stability. For the interpretation of influenced property and level on inhabitation stability from housing canonical factor and relative variables, this research applies two stage estimation to establish investigative model. In the first stage, the canonical correlation analysis method is used to find the covariate between household attributes and dwelling attributes as the input for the calculation of housingcanonical factor score with statistical significance test by official data in Taiwan area. Housing variation can be derived for absolute value of the gap between two standardized housing canonical factors selected for the calculation of factor scores by canonical equations. In the second stage, the Binary Logit model is then used to investigate the affected properties and level on inhabitation stability from housing variation, couple’s covariates, and government subsidy policy. The result shows that inhabitation stability is negatively affected by other couple’s covariates, housing variation, and government subsidy only if it is positively affected by couple’s ages gap.