博碩士論文 111461012 詳細資訊




以作者查詢圖書館館藏 以作者查詢臺灣博碩士 以作者查詢全國書目 勘誤回報 、線上人數:22 、訪客IP:3.16.69.29
姓名 李詠萱(YUNG-XUAN LI)  查詢紙本館藏   畢業系所 管理學院碩士在職現役軍人營區專班
論文名稱 影響住宅自有或租賃的因素: 以1976 – 2021《家庭收支調查》資料分析
相關論文
★ 傳產企業轉型發展自有品牌過程探討─以S公司為例★ 人員離職傾向之存活分析─以融資租賃業之T公司為例
★ NB代工業生產基地配置之成本效益分析─以C公司赴越南設廠為例★ A公司ODM Phase Gate系統使用狀況及評價探討
★ 表面黏著技術(SMT)自動化取代人力之效益探討─以W公司為例★ 雙佔廠商研發決策分析:考慮研發外溢與角解
★ 女性勞動參與和薪資決定之年群分析★ 台灣婚姻配對模式及其效率性檢定
★ 1978-2004台灣勞動力失業週數之期間分析★ 家戶內共居行為對所得分配之影響
★ 小型開放經濟、人口內生與經濟成長★ 與配偶認識方式之期間分析:台灣與中國之實證研究
★ 工資不均度與流動性之分析:台灣與美國實證結果比較★ 偏見環境下的婚配市場
★ 影響國中學習表現之因素分析★ 影響參試者努力程度之理論分析
檔案 [Endnote RIS 格式]    [Bibtex 格式]    [相關文章]   [文章引用]   [完整記錄]   [館藏目錄]   [檢視]  [下載]
  1. 本電子論文使用權限為同意立即開放。
  2. 已達開放權限電子全文僅授權使用者為學術研究之目的,進行個人非營利性質之檢索、閱讀、列印。
  3. 請遵守中華民國著作權法之相關規定,切勿任意重製、散佈、改作、轉貼、播送,以免觸法。

摘要(中) 本研究為了解在台灣社會中,影響買房及租屋的因素以及有房或租屋的家戶分別有甚麼特性,使用了 1976 – 2021行政院主計總局的家庭收支調查,彙整原始資料並分析歷年與家庭住宅所屬相關之變數,如家庭結構、家庭可支配所得、戶長特性、戶長工作地等,透過橫跨 46 年之歷史資料,去理解台灣人如何在住宅所屬上做出選擇,以及透過羅吉斯模型迴歸得出勝算比估計值,提供讀者一個可量化的參考點,如家庭可支配所得增加多少,有房的機率會上升多少。
住宅所屬共有四個類型 : 自有、租屋、配住、其他,又因配住及其他歷年佔總數僅6.8%,故本研究將依自有及租屋兩種住宅型態為研究主軸。
家庭結構歷經46年的變遷有巨幅的改變,如今以核心家庭、夫婦二人家庭及單人家庭為主,三代同堂雖以非當今家庭結構多數,但在歷年的資料中顯示房屋為自有的機率很高。
家庭可支配所得本研究以中位數為基準將前 50% 定義為有錢家戶,後 50% 定義為沒錢家戶,而不論有沒有錢在房屋自有的部分都是很高的。
另外本研究考量戶長工作地如在七都中負擔較大,可能會影響戶長選擇自有或租屋,因此將工作地的變項也加入分析,在迴歸結果中也顯示工作地在七都者有房的機率較非七都來得低。
最後加入了建坪及實付、設算租金的描述性統計分析,顯示自有的平均建坪一般較租屋大,而有錢有房的人居住建坪最大,有錢沒房 (租屋) 的人平均每坪年租金最高,沒錢沒房 (租屋) 的人居住面積最小,而沒錢有房的人建坪僅次於有錢有房者,但是平均每坪年租金卻是最少的。
摘要(英) In order to understand the factors that affect buying and renting a house in Taiwanese society, as well as the characteristics of households that own or rent a house, this study used the 1976-2021 Household Income and Expenditure Survey of Directorate-General of Budget, Accounting and Statistics (DGBAS), and compiled original data. It also analyzes variables related to family residence ownership over the years, such as family structure, family disposable income, characteristics of the head of household, work location of the head of household, etc., and uses historical data spanning 46 years to understand how Taiwanese people make decisions about residence ownership. The choice is made, and the odds ratio estimate is obtained through Logistic model regression, providing readers with a quantifiable reference point. For example, how much a family′s disposable income increases, how much the probability of owning a house will increase.
There are four types of housing: self-owned, rented, refers to residential buildings allocated by service units, and others. Since refers to residential buildings allocated by service units and other have only accounted for 6.8% of the total over the years, this study will focus on the two types of housing, self-owned and rented.
The family structure has undergone tremendous changes over the past 46 years. Nowadays, nuclear families, couple families and single-person families are the main ones. Although three generations living under the same roof are not the majority of today′s family structures, data over the years show that houses are self-contained that the probability of owning a house is very high.
Household disposable income: This study uses the median as a benchmark to define the top 50% as wealthy households and the bottom 50% as households without money. Regardless of whether there is money or not, the self-owned portion of the house is very high .
In addition, this study considers that if the household head’s workplace is in the city and the burden is greater, it may affect the household head’s choice of owning or renting a house. Therefore, the variable of workplace is also added to the analysis. The regression results also show that people whose workplace is in the city have a lower chance of owning a house than those who work in non-urban areas.
Finally, a descriptive statistical analysis of the floor space and actual paid and imputed rent was added, which shows that the average floor space of self-owned houses is generally larger than that of rented houses, and those with money and houses have the largest floor space . People who have money but don’t own a house (rent a house) have a higher average annual rent per square meter.People who have no money and no house (rent a house) have the smallest living area. People who don’t have money and own a house live in a square meter second only to those who have money and a house, but the average annual rent per square meter is the smallest.
關鍵字(中) ★ 租屋
★ 自有
★ 住宅所屬
關鍵字(英)
論文目次 中文摘要.........................................................................................................................................................................................................i
英文摘要.......................................................................................................................................................................................................ii
誌謝.................................................................................................................................................................................................................iii
目錄..................................................................................................................................................................................................................iv
圖目錄.............................................................................................................................................................................................................v
表目錄............................................................................................................................................................................................................vi
第一章 緒論..............................................................................................................................................................................................1
第二章 文獻回顧..................................................................................................................................................................................3
2.1 租屋市場狀況.................................................................................................................................................................................3
2.2 購屋決策.............................................................................................................................................................................................3第三章 資料描述與分析結果....................................................................................................................................................4
3.1 家庭結構組成與家庭人口數變數.................................................................................................................................5
3.2 家庭可支配所得變數............................................................................................................................................................10
3.3 經濟戶長工作地變數............................................................................................................................................................12
3.4 戶長特性..........................................................................................................................................................................................14
3.5 建坪與實付租金、設算租金變數................................................................................................................................18
第四章 迴歸分析模型與結果.................................................................................................................................................22
4.1 模型概要..........................................................................................................................................................................................22
4.2 迴歸結果..........................................................................................................................................................................................22
第五章 結論...........................................................................................................................................................................................34
5.1 研究結果..........................................................................................................................................................................................34
5.2 未來研究方向..............................................................................................................................................................................34
參考文獻 張雅惠(2012), “租賃住宅之需求彈性及所得彈性”, 國立成功大學碩士論文。
朱元瑄(2021), “租屋者對住宅租買需求之探討-以屏東市為例”, 國立屏東大學碩士論文。
陸炤廷(2015), “影響首購族購買房屋之決策偏好探討-以高雄地區為例”, 國立高雄應用
科技大學碩士論文。
邱德弘(2020), “購屋動機需求與決策因素暨訊息管道研究”, 國立台北科技大學碩士論文。
賴素珍(2021), “購屋動機與購屋者特質對購屋決策影響之研究”, 國立宜蘭大學碩士論文。
學術調查研究資料庫,家庭收支調查, 2024年9月29日, 取自
Survey Research Data Archive (sinica.edu.tw)
指導教授 鄭保志(Cheng, P.C. Roger) 審核日期 2025-1-3
推文 facebook   plurk   twitter   funp   google   live   udn   HD   myshare   reddit   netvibes   friend   youpush   delicious   baidu   
網路書籤 Google bookmarks   del.icio.us   hemidemi   myshare   

若有論文相關問題,請聯絡國立中央大學圖書館推廣服務組 TEL:(03)422-7151轉57407,或E-mail聯絡  - 隱私權政策聲明