住宅為兼具消費及投資之雙重功能財貨，因此若從購屋動機劃分購屋族群，可以分為自住者及投資者，近年來受到國內房市呈現生氣蓬勃之景象及利率持續走低等總體經濟因素影響之下，出現越來越多以投資為主要目的之投資型購屋者，對於金融機構之購屋貸款業務來說，投資者之還款行為相較於自住者是比較不穩定的。故本文之研究目的即藉由探討自住者及投資者之購屋特徵異同，建立投資者之機率預測模型，預測某購屋者成為投資者之機率，提供一較為客觀之機率預測模型，供作金融機構放貸參考準則。接著進一步探討在不同機率界限（cutoff point）下之預測準確率，找出預測準確率最高之機率界限值，提高本模型之預測準確度；並探討金融機構在不同經營方針下之較適機率界限值。 / 本文使用台灣住宅需求動向季報之已購屋者問卷，建立二元羅吉特模型。研究結果顯示，區位在中心都市、高單價、小面積產品及大面積產品、預售屋及拍賣屋市場屬於投資型產品，而搜尋時間短、搜尋間數少、年齡較長、男性、無固定職業及家庭平均月收入較高者成為投資者之機率較高。接著，運用貝氏定理計算出預測準確率最高之機率界限值，結果當機率界限值為0.70時預測準確率最高，投資者達72.22%，自住者達80.07%。此外，並使用2007Q4的資料作樣本外驗證，投資者命中率為65.52%，自住者命中率為84.51%。最後，為提供金融機構運用，本文模擬兩種預測誤差在不同權重下對於金融機構所造成的損失，找出損失最少的機率界限值，結果皆是以0.70為最適機率界限值。 / Housing is dual function goods, consumption and investment, so if we separate the home buyers by their motives, they can be defined as two groups, owner-occupiers and investors. Recently, because the housing market is vigorous inland and the rates are fairly low, there are more and more home buyers buying houses for investment. To financial institutions, their payment behaviors are more instable, compare to owner-occupiers. So this article is aim to build a probability predictive model of housing investors by discussing the different home buying characters between owner-occupiers and investors. Therefore we can provide financing institutions a more objective method evaluating if they should lend money to the home buyers. Then we discuss the predictive accuracy with different cutoff points, finding the cutoff point with highest predictive accuracy, therefore we can elevate the model`s predictive accuracy. Besides, we also discuss the most optimal cutoff point for financial institutions under different administration principles. / This article builds binary logit model by the data of “Housing Demand Survey in Taiwan”. Our results suggests that if the houses in downtown、high unit price、big and small acreage、presale and court auction housing market belong to investing houses. And short search duration、few search items、older、male、non-constant job、higher income are getting higher probability to be housing investors. Then, we use Bayesian Theorem to figure out the cutoff point with highest predictive accuracy, and Our results suggests that 0.70 cutoff point with highest predictive accuracy , at that time, investor predictive accuracy is 72.22%, owner-occupier is 80.07%. Besides, we also do the out-sample test by the 2007Q4 data, the investor`s hit-rate is65.52%, the owner-occupier`s hit-rate is 84.51%. At the end, in order to provide financial institution to use, we give two predictive deviation different weights, to find the smallest loss cutoff point, the result all suggest that 0.70 is the most optimal cutoff point.

住宅選擇是每一個家戶都會面臨到的問題，過去文獻發現購屋者先選擇租屋或購屋，若決定購屋，則先決定於何區位購屋，然後再決定購買何種房屋類型之房屋，然而卻未曾提及購屋者於不同市場類型住宅間之選擇。預售屋、新成屋以及中古屋等不同市場類型之住宅，各自隱含不同的效用及風險，影響著購屋者之選擇，因此本研究試圖討論購屋者於不同市場類型住宅間之選擇與偏好。 本研究採用內政部營建署「住宅需求動向調查」資料，利用混合多項羅吉特模型探討不同限制條件下，預售屋、新成屋與中古屋之個體選擇行為。實證結果顯示，投資者較偏好於購買知覺風險較高之預售屋，期待以高知覺風險換取高的報酬；教育程度較高者，因對居住品質要求愈高，因此傾向於選擇設備新穎之預售屋與新成屋；家戶平均月所得較高之購屋者，負擔能力較高，因此選擇總價較高之預售屋機率較高，其次為新成屋。此外，搜尋頻率愈高者，選擇預售屋之機率愈高，因預售屋無實體存在，預售屋購屋者為降低其知覺風險，將花費更高之搜尋成本。在價格彈性分析部分，實證結果顯示預售屋之競爭力最高，但預售屋之受衝擊力亦最高，而中古屋之競爭力於三種市場類型中居次，但中古屋衝擊力最小，因此，當單價屬性發生變動時，較不影響中古屋購屋者之選擇，但卻大幅影響預售屋購屋者之選擇機率。 / Every household would face housing choice, the past housing choice study founded that households decided tenure choice first, if they decides to buy a house, they first decided on what location, and then decided what type of housing to buy, but it has not been mentioned the housing choice among different residential market types. Pre-sale houses, newly constructed houses and existing houses implied different effectiveness and risks, affecting the choice of homebuyers. This article tried to discuss homeowners’ choice among different residential market types. This study use Construction and Planning Agency, "Housing Demand Survey of 2009" data, use mixed multinomial logit model, investigated under different constraints, housing choice behavior among pre-sale houses, newly constructed houses and existing houses. The empirical results showed that investors prefer higher perceived risk in buying pre-sale housing, looking for a high perceived risk and high rewards; higher education level, due to the higher quality requirements for living, so they preferred pre-sale houses and newly constructed houses. Homebuyers which have higher average monthly household income, have more affordable ability, so the probability of choosing pre-sale houses are much higher, followed by the newly constructed houses. In addition, the higher search frequency were more likely to choose pre-sale houses because pre-sale houses for sale no physical presence, pre-sale housing homebuyers in order to reduce their perceived risk, would spend more search costs. In the price elasticity analysis, empirical results showed that the pre-sale houses had the highest competitiveness, but the impact force was also the highest, while the existing houses market, the competitiveness of the third types was the second place, and the competitiveness of the existing houses was the smallest. Thus, when a change in unit price attribute, does not affect existing houses homebuyers, but significantly affected the choice probability of pre-sale houses homebuyers.

過去有關土地使用分區管制與地價兩者間關係之研究，往往假設地價在實施規劃管制過程中呈中立性，且過去在探討土地使用分區管制與地價二者間關係之研究時，多著重在探討土地使用分區管制施行後對地價之影響上，對於土地使用分區管制決策是否受到土地市場中地價之影響，則僅在少數的研究中被探討。故本研究首先透過國內外相關文獻之回顧與分析，得知規劃管制決策者有時為求得最大之政治支持，有可能會以規劃管制為其尋求最大政治利益之工具，而扭曲規劃管制之原意，使得土地使用分區管制決策可能受到土地市場中地價之影響，然而地價於實際經濟社會中是否會影響土地使用分區管制決策，則有待進一步的探討與驗證。 是以本研究以公共選擇理論與消費者效用理論為基礎，透過台北縣市土地使用分區管制決策過程與內涵之探討，利用羅吉特(logit)迴歸分析模型，以台北市為實證範圍，並以其72至81年度之房地移轉買賣實際調查資料，進行分年橫斷面分析方式，求取選擇性偏誤訂正項後，再納入地價方程式中估計，以求地價函數一致性估計，據以逐年檢驗地價對土地使用分區管制決策之影響情形。再以台北市信義計畫區為個案分析之對象，檢視於現實社會中地價對土地使用分區管制決策之影響情形。 經由上述之實證與個案分析，得到以下之結論： 一、土地使用分區管制決策在執政者追求最大政治利益之假設下，將可能受到利益團體等相關者之壓力，而做出只利於少數人之土地使用分區管制決策。 二、土地使用分區管制決策可能會受土地市場中地價之影響。 三、地價對土地使用分區管制決策之影響不穩定。 四、對土地使用分區管制決策時應有制度性之建立以審慎考量規劃管制之旨意。 / In the literatures, the study on. the relationship between land price and zoning control was assumed that land price is neutral. Moreover, the studies of land price and zoning control are more on the impact of land use control upon land price. The issue that impact of land prices upon the decision making of zoning control is rarely investigated. Based upon the theories of public choice and consumer's utility, this study discusses the process and content of zoning control decision-making. Then, by Logit model, the transaction data of property in Taipei City from 1983 to 1992 are employed to test the impact of land price upon the decision making of zoning control. Furthermore, a case study of Shin-I Planning District in Taipei City is analyzed so as to examine the impact of land price upon zoning control decision-making in the real operation. The major findings of this study are that, land price may affect the decision making of zoning control in the long term. However, the impact of land price upon the zoning control decision-making is unstable. Finally, based upon the public choice theory, the empirical results are discussed so as to apply the findings to the land policy.