近年來，台灣許多縣市的住宅價格不斷高漲，身為政經重鎮之台北市首當其衝，於2008~2009年金融海嘯時期，政府為維持經濟發展而全面將遺產及贈與稅調降為單一稅率10% 後尤然。以產品價值而言，此波上漲很可能來自於「逢低買進，逢高賣出」之投資心理造成。由於不動產最終用途為使用，當真實需求者無力負擔時將導致房市泡沫，更因房市的經濟佔額高，進而可能引發經濟泡沫。為檢視台北市住宅價格的合理性，鑒於出租住宅需求者動機單純，本文以租價關係探討台北市住宅價格是否已有偏離實際使用需求之現象；且是否因未來的住宅價格在預期之引導下，使房價似遵循著過去價格的成長而逐步提高，有不效率之現象。實證結果顯示，台北市住宅價格與租金間已然背離，在金融海嘯過後種種非理性現象更為嚴重，導致房價有偏離其合理結構之虞，成交總價越高的住宅、偏離情況越為明顯，而存在泡沫化危機。 / In recent years, the housing market has been awash with funds. The phenomenon resulted in domestic housing prices in Taipei rising year by year, especially after the Subprime mortgage crisis. From the viewpoint of economics, the price is decided by supply and demand. However, with regard to the value of product, this rising of housing price probably comes from the artificial demand. In other words, this kind of demand is just like "buy low and sell high". In addition, real estate is a special commodity, except as an investment good, it is also a necessary consumption good. Furthermore, real estate is expense, making housing the biggest item among households’ assets. Once housing price is too high and the actual demanders cannot burden with; that is likely to trigger a market bubble, which caused the imbalance of trade market. According to the aforementioned, this study will observe whether the housing price has deviated from the fundamentals in Taipei City. Since the demand of rent is only for living, we probing into the relationship between housing price and rent in order to observe the rationality of housing price; and if the future housing price in the anticipated guided, the price seems to follow the historical trend, and the higher the housing price of an area, the more significant. The empirical results show that, the housing price seems to prevail in unreasonable investment in Taipei City, which may lead into a bubble crisis.

自2002年，澳門政府開放賭權後，博彩業成為澳門重要的經濟命脈，伴隨著澳門經濟迅速發展，澳門住宅價格亦因此高速飛漲。故此，本研究係以澳門為主要研究對象，探討自澳門政府批出三份博彩經營權後，總體經濟、博彩業與澳門主住宅市間之關係。選取二零零一年第一季至二零一四年第四季之季資料，運用單根檢定、因果關係檢定與共整合檢定等研究方法進行實證分析，檢定變數間的因果關係是否有長短期均衡關係與是否有領先落後的效果。 根據實證結果顯示，存款利率、外來投資金額、外地僱員及飯店入住率領先住宅價格之變動，所得及博彩稅收與住宅價格則呈現雙向因果關係，而外來投資金額、外地僱員、飯店入住率皆屬於博彩旅遊相關之變數，顯示博彩業蓬勃發展能推動澳門住宅價格，使房價高漲。此外，博彩稅收、外來投資金額、外地僱員及飯店入住率皆對所得具有單向影響，故此，可推斷博彩業開放後為澳門帶來巨大的經濟衝擊。另一方面，澳門經濟發展高度依賴博彩業，中小企業亦因租金持續高漲、人力資源短缺等問題，面臨極大的成本壓力，嚴重排擠中小企業生存空間。 / In the year of 2002, after the gambling are allowing by the government in Macau, gambling has already become a pillar industry. Accompanying with the rapid development of economy, housing price has risen at high speed in Macau. Therefore, this paper aims to investigate the research of interactive relationship between the real estate market, macroeconomic and gambling industry variables on the basis of Granger causality test since the gambling concession was granted out to three companies. Our sample period starts from Q1 of 2001 to Q4 of 2014 with quarterly data. The research uses ADF Test, Granger Causality Test, and Cointegration Test model that we verify the relationship between macroeconomic variables and the real estate prices. The paper hopes to find out that whether the long-term steady changes between the real estate market and macroeconomic variables will be a leading or lagging effect. The empirical result shows that, deposits rate, foreign direct investment (FDI), non-resident workers (NRW) and hotel occupancy rate (HOR), are in the lead of variation of housing price, income and tax revenue from gaming presents a causal relationship with housing price. FDI, NRW and HOR belong to the variations of the gambling industry which reveal flourishing gambling industry cam promote the housing price in Macau. Moreover, tax revenue from gaming, FDI, NRW and HOR leads income. Thus, it can infer after the gambling are allowed, it brings a great impact on the economy in Macau. On the other hand, the economy of Macau too dependent on gambling. Medium-sized and small enterprises face lot of cost pressure such as the raising rent and short of hands, so that excluding vivo sphere of medium-sized and enterprises.

自1990年代起，專業估價實務通用規範（USPAP）中即規定，估價師必須同時考慮有形與無形資產對整體價格的影響，並將價值分配到不同的要素成分。以往國外文獻探討無形資產對不動產價格所產生之影響，多將焦點放在收益性不動產上，綜觀諸研究文獻之結論，皆肯定無形資產對其整體價格將會產生影響，且佔有重要的地位，但相對地，針對住宅不動產的交易價格中是否含有無形資產價值之研究文獻則相當少見；而國內對此之探討著墨更少，僅有部分文獻提及建設公司商譽對住宅產品之價格所可能產生的影響，但亦僅止於文字敘述，無任何文獻透過實證分析，以證明商譽對住宅交易價格之影響力。因此，國內住宅不動產的交易價格是否會受到建設公司商譽的影響，仍有待實證研究加以探討。 鑑此，本研究擬探討建設公司商譽對住宅交易價格之影響，期望透過實證分析釐清商譽對價格的影響力。在研究內容上，商譽因素是否存在於住宅類型之產品中？哪些因素會影響商譽對交易價格的影響力？皆是本研究所欲討論的面向。藉由實證分析與探討，本研究之結論如下： 一、商譽價值確實存在於住宅不動產中，惟其影響並不一定具有普遍性，尚須其他特定因素（屋齡、區域發展特性）同時成立，商譽始會對住宅價格造成顯著的影響。 二、透過實證結果之分析可知，案例所屬的特定因素不同時，將會使得商譽影響價格的顯著與否產生變化。當案例屬於屋齡在一定年數以內之新屋，且其區域發展特性愈傾向以單純住宅區為主要發展型態時，此時商譽對價格的影響將具有顯著水準；反之，當案例屬於中古屋，或是其區域發展特性愈複雜時，則商譽對價格的影響力將消失。

台灣各都會區因經濟與社會發展程度不同，使各都會區房地產市場特性有所差異，住宅價格波動情形亦有所不同。過去於台灣雖已有許多文獻探討過區域經濟與社會變數和區域住宅價格之關聯，卻少有文獻討論不同區域彼此間住宅價格差異與區域經濟與社會變數差異關係，且多數探討區域房地產市場文獻亦僅將研究範圍限縮在單一都會區，對於全國都會區之綜合性討論較為缺乏。是故，本文以台灣六大都會區為研究對象，探討各都會區彼此間住宅價格差異時間與空間變動情形，分析其與各都會區彼此間經濟與社會發展差異關係，進一步釐清當中之主要影響因素。 本研究使用台北市、新北市、桃竹都會區、台中都會區、台南都會區與高雄都會區等六大都會區由1993年至2010年共270筆住宅價格兩兩相除之比例資料，透過縱橫資料模型(Panel Data Model)探討國內六大都會區，兩兩間住宅價格比例變動於經濟與社會面的主要影響因素。實證顯示，當兩兩都會區經常性所得、知識密集服務業就業機會、公共投資、交通可及性、辦公室使用執照樓地板面積、治安狀況與空氣品質差異越大，住宅價格差異亦隨之擴張。且各都會區知識密集服務業就業機會、公共投資、交通可及性與經常性所得落差對住宅價格差異影響最大。此外，兩兩都會區住宅價格差異亦受到其地區特性與景氣影響。建議政府可透過於弱勢都會區發展適宜知識密集服務業發展之環境，吸引相關產業進駐，提供當地更多知識密集服務業就業機會，降低國內都會區所得落差。此外，應合理分配各都會區公共投資金額，強化弱勢都會區大眾運輸服務水準，以降低國內各都會區住宅價格懸殊情形。 / In Taiwan, because of the dissimilar levels of urban development, housing prices in different metropolitan areas change in sundry ways. This paper uses panel data analysis to identify the relationship between the development gap and the difference in housing prices in metropolitan areas of Taiwan during 1993-2010. The empirical results reveal that the income gap, the employment of knowledge-intensive services gap, the mobility gap, the public investment gap, the office quantity gap, the public security gap, and the air quality gap had significant effects on the difference in housing prices, and the difference in housing prices is also influenced by local characteristics and real estate cycles. Besides, we also discover that the employment of knowledge-intensive services gap and the public investment gap are two key determinants of the difference in housing prices.

大眾捷運系統帶來之快捷與便利，使其成為許多都會區民眾依賴之交通工具。捷運系統對鄰近不動產交通可及性提升，所伴隨之便利性將透過資本化效果反映於其價格之上，帶動周邊不動產價格上漲，過去不論國內外關於捷運對周邊房價影響之研究，實證結果亦多支持捷運對於房價有正面影響，且該影響隨著與捷運車站距離增加而遞減。捷運房價效果的區位差異與類型差異過去雖已有研究論及，但對捷運房價效果差異與其變化趨勢未能有明確細緻描述。此外，該等研究均忽略空間相關因素，將影響其估計結果。 　　本文使用國內某金融機構2007、2008年間台北都會區內台北捷運初期路網沿線車站周邊住宅為實證對象，應用空間迴歸模型檢視捷運系統對鄰近住宅價格之影響效果。實證結果顯示，就整體樣本而言捷運對房價確有正向影響但並不如想像之大，且該影響隨區位與類型之不同確有差異。 / Many previous studies have showed that metro system has a positive impact on the property values due to its accessibility benefits and the effect should decline as distance increases. While the pattern of the change and its difference between stations located in different locations has yet not been fully discussed, most of the studies failed to allow for spatial autocorrelation over space. This research uses spatial econometrics to estimate a residential housing model that considers spatial autocorrelation. The empirical results show the difference in the price effect of metro stations between urban and suburban areas does exist. The effect tends to get stronger in certain area, the closer the property lies within to the suburban area the greater the effect is. Also, we find price gaps between different metro station categories. Generally, underground stations and transfer stations have greater positive effect on residential property values.

住宅市場因其內容包括各類住宅次市場，又因為實質住宅單位難以衡量，以及實證資料難以蒐集等原因，使得住宅需求分析較為複雜。 本研究主要在探討何種函數形式較適合使用於住宅需求模型，而該種函數形式必須能對實際的住宅需求變動情形充分說明，並非如一般住宅需求模型之建立忽略了函數形式與模型之間的關連性；以外本文對不同所得階層、不同區位對位宅需求是否有明顯的影響之課題作一深入探討。而值得注意的是，不論對不同所得或位於不同區位的住宅需求來說，利率對住宅消費性需求的影響並不顯著，有別於一般利率對住宅需求有明顯影響力的印象。 本研究共分為五章，摘要內容如下： 第一章：介紹本文的動機、目的，研究限制與架構，並界定本研究之研究對象為住宅消費性、有效需求。 第二章：針對發展較成熟的國外文獻作一回顧整理，藉以發現一般在研究住宅需求相關課題時可能遇到的問題；此外介紹建構本文之基礎理論。 第三章：在對國外文獻進行回顧之後，本研究尚對國內住宅需求模型作驗證分析，探討造成各模型差異甚大的原因；並特別針對住宅價格資料之課題作比較分析。 第四章：在以Stone-Geary 效用函數以及目的變數建立住宅需求模型之後，以台北市為實證範圍，進行縱斷面的迴歸分析，發現以Stone-Geary 效用函數建立的住宅需求模型，頗能說明台北市住宅需求的變動情形。 第五章：針對國內外文獻處理以及實證分析結果，提出本研究之結論建議與後續研究。

過去由於國內住宅市場的資訊並不流通，以致市場上出現的價格資訊相當混亂，就價格的種類來看，各種名目住宅價格間的差異未有明確釐清，使一般人常會對不同的住宅價格產生誤解。就時間序列來看，不同的時間、地區及住宅類型，到底住宅價格的變動如何，也未能有一嚴謹且量化之指標表示。 　　本研究運用標準住宅的概念編製住宅價格指數，所謂標準住宅乃是指一定時間、地區、類型，市場上成交的住宅中，典型的住宅屬性及其數量的組合，也就是說，觀察市場上成交典型住宅的價格變動情形，作為指數編製的基礎，以控制住宅的異質性，再以特徵價格法來求得各屬性的單價以進一步控制品質。另外，由於住宅成交數量變動較大，因此運用裴氏公式作為指數公式，使加權權重的誤差不致太大。 　　由各地區的指數變動趨勢可得到以下幾點結論：首先，一般所認為的三次房地產價格高峰期（62至63年、68至70年、76至78年），從指數的變動來看並不明顯，只有76至78年的上漲趨勢較明顯，在經過幣值平減後，長期趨勢更顯平緩；其次，長期來看，住宅價格持續上漲，部分時期持平或下跌，但幅度及持續時間有限，故所謂房價下跌，其實跌的是上漲率；最後，就上漲幅度來看，台北縣、市的幅度最大，除台北市外，非都市地區（非省轄市）房價的上漲速度較都市地區（省轄市）為高。 　　最後歸納二個造成一般人對住宅價格變動之錯誤印象的原因。主要是品質未加控制，由於品質會影響住宅價格，且消費的住宅品質及數量會隨時間而改變，一般人未察覺此點，而造成對房價上漲的誤解。其次是未考慮幣值，由於「今天的一塊錢不等於明天的一塊錢」，因此以名目價格觀察住宅價格變動的作法，也會造成對房價變動的誤解。

由於住宅價格變動毫無預警制度，人民往往憑著個人主觀的判斷而決定何時購屋或售屋，而此種主觀判斷住宅市場利多及利空的觀念，對住宅市場的供需會產生失衡現象，因此是否可從經濟面的訊息找到住宅價格變動的答案，使住宅價格在尚未變動前，政府即已掌握資訊，提前做好穩定住宅價格的因應對策，使民眾依其需要而購屋，則是本研究之主要目的。 　　本研究從文獻中整理出影響住宅價格變動的七個總體經濟變數，這些總體經濟變數包含工資、物價、所得、貨幣供給額、股價、匯率及利率等，並利用向量自我迴歸模式(VAR)進行實證，以便較客觀的獲得變數間的落後期數及暸解變數間雙向、單向及領先、同步、落後情形，且進一步探討住宅價格與每一個總體經濟變數間影響程度大小及影響情形，以釐清各變數之間的關係。 　　本研究利用VAR模型進行住宅價格與總體經濟變數關係的研究，經由實證，得到下列的結論： 　　一、實證結果方面 　　本研究之實證主要有因果關係檢定與分析、變異數分解之分析及衝擊反應之分析三方面，其實證結果如下所述。 　　（一）因果關係檢定與分析 　　由因果關係檢定與分析中，得到股價、物價、匯率、貨幣供給額及利率均能做為住宅價格變動的領先指標。 　　（二）變異數分解之分析 　　由住宅價格之變異數分解中，得知住宅價格自身的解釋程度僅占三分之一，另三分之二被其他的總體經濟變數所解釋，顯示住宅價格受總體經濟變數的影響相當大；而從其他總體經濟變數之變異數分解中，得知住宅價格變動會干擾到總體經濟變數，而使總體經濟變數受干擾而變動變動。 　　（三）衝擊反應之分析 　　從總體經濟變數對住宅價格的衝擊反應分析圖中可以明顯看出除工資外，其餘總體經濟變數變動對住宅價格造成的衝擊均相當明顯，但匯率及利率對住宅價格的衝擊是負向的。 　　住宅價格對所得、股價、匯率及利率的衝擊相當明顯，而其對匯率的衝擊是負向。 　　二、政策應用方面 政府的決策過程中常會有時間落後的現象，而本研究實證的目的則是要使政府能事先掌握住宅價格的變動，並提前做好穩定住宅價格的因應對策，減少政府決策過程的時間落後現象，而實證結果應用至政策方面的內容則由以下說明之。 　　（一）藉由因果關係檢定與分析的實證內容，可以縮短政府對住宅價格不合理變動問題認定落後的時間。 　　（二）從變異數分解之分析的實證內容中，可以使決策者在解決住宅價格問題時，將行動落後的時間減少。 　　（三）由衝擊反應之分析中，可以使政府在執行穩定住宅價格政策時，將衝擊落後的時間縮小。 / Since there is no alarm system in the change of housing prices, people often decide when to buy or when to sell based on personal and subjective judgement. Such concept to judge subjectively whether the housing market is bull or bear will cause unequilibrium in the supply and demend of the housing market. There it is possible to find out the answers to the change of housing prices from economic side so that the government can have enough information and can be prepared in the reaction to stabilizing the housing prices, and so that the public can buy house according to their needs is the main purpose of this project. 　　Seven variables in macroeconomics influencing the change of housing prices have been taken from reative literature, including wage, commodity price, income, money supply, stock price, exchange rate, and interest rate. VAR has been employed to verify so that the more objective lagging period among variable can be known, and the bi-directional, uni-directional, leading, contemporaneous, and lagging situation among variables can be understood. Furthermore, the degree and the status of influence of each macroeconomic variable to the housing price will be investigated to clarify the relations among the variables. 　　The present project investigate the relations between housing price and macroeconomic variables. We have the following findings: 　　I、In Empirical Study: 　　The empirical study in this project includes causal relation test and analysis, the analysis of variable decompositon, and the analysis of impact response. The results are shown in the following: 　　(I) Causality Test and Analysis 　　In the causality test and analysis, we find out that stock price, commodity price, exchange rate, money supply and interest rate all can be the leading indicators in the change of housing prices. 　　(II) The Analysis of Variable Decomposition 　　It is learned from the variable decomposition of housing prices that housing price can only explain one third of the cause in its change, the other two thirds are explained by other macroeconomic variables. It shows that housing prices are subject to the influence of macroeconomic variables greatly. 　　From the variable decomposition of other macroeconomic variables, we know that the change in housing prices will affect macroeconomic variables so that the macroeconomic variables will change. 　　(III) The Analysis of Impact Response 　　It can be obviously seen from the analysis figure of the impact response of the macroeconomics to housing prices, all macroeconomic variables will cause obvious impact to housing prices expect for wage. However, both exchange rate and interest rate have negative impact to housing prices. 　　Housing prices' impact to income, stock prices, exchange rate and interest rate is quite obvious, among which, the impact to exchange rate is negative. 　　II、Policy Application 　　It is a common phenomenon that there often will be lagging in time in government's decision making. The purise of the empirical study in this project is to let the government to know in advance the change of housing prices and to let the government to know in advance the change of housing prices and to let the government be prepared in the reaction of stabilizing the housing prices to minimize the lagging in the decision making process. The contents of application of the empirical study to policy are explained in the following: 　　(I) With the empirical results of the change of the causality test and analysis, the time for the government to recognize the unreasonable changes in housing prices can be shortened. 　　(II) With the empirical results of the analysis of variable decomposition, the decision makers' lagging in the action responding to housing pricescan be minimized. 　　(III) With the analysis in impact response, the lagging in impact will be minimized when the government executing her housing price stabilizing policy.

城市化意味着城市的經濟結構、社會結構和空間結構變遷。隨着中國大陸城市化的推進，城市人口遷移、建成區面積增長，城市發展質量逐步提高，而同期內城市商品住宅價格亦呈現普遍而明顯的上漲趨勢。 過去雖有許多國內外文獻對全國城市商品住宅價格的影響因素進行了探討，但少有文獻從城市化的層面着眼進行研究；在部分集中討論城市化效應的文獻中，亦存在以省域代替城市作爲研究對象，以及採用橫截面數據進行實證研究，未能體現不同城市化和社會經濟發展階段之變動趨勢的缺憾。 有鑑於此，本文使用中國大陸2003年至2011年不同規模城市的相關追蹤資料，以“人口城市化”“土地城市化”和城市發展質量優化作爲城市化的主要體現，用從業人口、建設用地面積、房地產開發投資額等一系列指標作爲自變數構建追蹤資料固定效應模型，分析城市化對不同規模城市商品住宅價格的影響，探究中國大陸社會經濟重要發展來源的城市化能否繼續維持城市商品住宅市場的穩定。實證結果顯示，城市化發展對城市商品住宅價格上漲的貢獻明顯，而人口城市化的作用較之土地城市化更爲顯著；大城市和中小城市在城市化發展過程中商品住宅價格影響因素亦有所不同，城市發展中由政府主導的城市土地開發利用與基礎設施建設應集約化發展，土地城市化必須與人口城市化以及城市發展質量提升相互協調。 / Urbanization means changes of cities ‘economic structure, social structure and spatial structure. With the development of Chinese urbanization, the urban population and construction land area is growing, the urban development quality is improving gradually, in the same period city residential housing prices also presents common and obvious rising trend. In the past, although there were many domestic and external literature focusing on the influence factors of the national urban residential housing prices, but there were few literature based the study on the impact of urbanization; many of literatures in which the urbanization effect discussed, also taken provincial data as the research object instead of city , using cross-sectional data for empirical research, so failed to reflect changes in different stages of urbanization and social and economic development trend. In light of this, this article refer to mainland China from 2003 to 2011, 213 level panel data, related to "land urbanization" and "population urbanization" quality optimization as the main embodiment of urbanization, taking urban working population, construction land area, real estate investment and a series of indicators as independent variables to construct panel fixed effects model, in order to analyze the effect of urbanization on the urban residential property prices. We expect to explore whether if mainland China's urbanization, which is a source of important social and economic development of the nation, will continue to maintain the stability of the urban residential market. Empirical results indicates that the influence of urbanization on city residential housing price is evident, besides population urbanization plays a more important role than land urbanization. In the process of urbanization, the influential factors of residential housing price varying in metropolis and small cities, therefore development of urban land dominated by local government ought to realize intensification, and land urbanization should be coordinated with population urbanization and city development quality.

近年來影城結合商場、娛樂及餐飲，如雨後春筍般出現，建商售屋亦常以影城為吸睛廣告，對消費者而言，影城對周邊住宅價格影響是否存有關聯性係其購屋選擇關心條件之一，然而現今影城的類型大不相同，且觀察到影城大多座落於商圈內或是與百貨商場結合。因此，本研究將影城、商圈與住宅價格的相關程度做交叉分析，以初步了解其關聯程度，並應用集群分析以控制異質樣本，使得形成同質性的房屋屬性來看影城效果，再透過複迴歸模型分析，探討不同類型的影城、商圈與周邊住宅價格之影響關係。 透過複迴歸模型實證結果得知，影城對台北市周邊住宅價格是有影響的，以總價1,000萬元房屋，平均而言，正向的價差介於41萬元至310萬元之間，負向的價差則介於30萬元至271萬元之間，並且正向的價差高於負向的價差。進一步將影城依經營模式及服務方式分類進行實證，採連鎖經營模式的影城周邊房價價差約為40萬元，而提供複合式服務或僅提供單一式服務的影城，對房價的影響差別不大。該結果可提供消費者在評估購買房屋時之參考，亦可作為開發商與銷售業者在預售屋訂價策略及廣告遵循原則。 此外，由於消費型態的改變，消費者習慣將看電影結合其他休閒活動，這些由百貨公司以及電影院異業結盟的商圈更得消費者青睞，影城進駐與商圈發展之關係相輔相成，進而影響新北市周邊住宅價格，以總價1,000萬元房屋，平均來說，影城進駐商圈後能提升房價139萬元。 / These years combination-area of cinemas, malls, recreation and catering are springing up as well as being the eye-catching advertisement of building-contractors. In terms of house-buyers, the correlation between cinemas and the neighborhood housing price is one of the conditions they care. Nevertheless, with the variety of the cineplex-cinema currently and mostly locate in business districts and department stores, our study make a cross analysis between cineplex, cinema, business districts with residential price for their correlation. With cluster analysis to control the heterogeneous samples and to evaluate the price-effect of cineplex-cinemas under the homogeneous housing. Furthermore to multiple regression analyze cinema stationed-in commercial-district and their neighborhood housing price. Our study confirmed the cineplex-cinemas are influential to the Taipei City surrounding-area residential price. For the ten million house, averagely the positive-impact is between four hundred ten thousand to 3.1 million. Negative-impact is between three hundred thousand to 2.71 million. Besides, the housing price different positive effect is higher than the negative one. Further to verify type-mode cinemas: the price difference in neighborhood-area is four hundred thousand with franchise management type-mode. However, there is no price difference with complex and single-service type-mode. Housing-buyer can take the result as consideration during purchasing houses as well as real estate developers and salesman in pricing strategy and advertisement principles of pre-sale houses. Additionally, with the change of consumption patterns, consumers get use to watch movies together with other recreation. Thus commercial-districts combining with department stores and cinemas are more favored. The cinema stationed-in and commercial-district development are complemented each other, therefore to affect the neighborhood housing price in New Taipei City. For the ten million house, averagely, the positive price-different effect is one million and three hundred nighty thousand after the cinema stationed-in.