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題名：台灣房地產景氣循環之研究-生產時間落差、宣告效果、總體經濟之影響
作者：彭建文 引用關係
作者(外文)：PENG CHIEN - WEN
校院名稱：國立政治大學
系所名稱：地政學系
指導教授：張金鶚
學位類別：博士
出版日期：2000
主題關鍵詞：房地產景氣；生產時間落差；宣告效果；總體經濟變數；預期；共整合；real estate cycles；construction lags；preannouance effect；macroeconomic variables；expectation；cointegration
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本研究主要依據國內房地產市場的特性，以生產時間落差、預期景氣與宣告效果、以及總體經濟等三個項目為主軸，針對房地產市場的景氣現象進行探討。首先，由生產階段的生產時間落差為出發點，探討房地產景氣與政府政策衝擊對生產時間落差的影響。再來，探討房地產次市場間的互動關係，瞭解預期景氣與宣告效果對不同房地產次市場景氣的影響。最後，探討總體經濟對房地產景氣的影響。在上述理念體系下，本研究進行各項理論的推演與實證分析，所得結論說明如下：
一、房地產景氣對生產時間影響部份
本文以建照面積與使照面積數量之波動關係，分析房地產景氣對生產時間落差之影響，結果發現使照面積與建照面積間存在穩定的長期關係，但建照可能因景氣不佳而取消，此使得長期建照面積大於使照面積，且建商會視房地產景氣的變動而調整興建速度。當房地產市場景氣時，興建速度較快，不景氣時興建速度較慢，使得生產時間落差會因房地產景氣變動而有所不同。另外，建照面積與使照面積間的關係亦會因政府相關政策的改變而產生衝擊，進而改變生產時間落差的長短。
由此觀之，國內房地產市場應較無預售制度的國家有較佳的市場調整機制，不過國內房地產景氣的波動卻依然劇烈，其原因可能在於政府決策與執行有相當長的時間落差，往往造成介入市場的時機不恰當，使得政府政策不但未能發揮反景氣循環的功能，反而成為助漲、助跌的促媒。另外，建築投資業缺乏健全管理亦是可能的原因之一，造成市場良莠不齊，在未經協調而彼此競爭下，往往錯誤評估個別預期銷售額而惡性競爭所造成。
二、預期景氣與宣告效果對房地產景氣影響部份
透過不同次市場的連結，本文發現當政府政策提前宣告時，將會有明顯的宣告效果產生，使得建商雖面對節節高昇的空屋率，依然大量搶建，但建照面積的增加則會促使房價與租金下跌。當前房地產市場的長期不景氣，政府未充分掌握房地產市場的景氣波動，並審慎評估政策的可能衝擊可說是問
題的關鍵。此也意味，若政府日後真有必要再對房地產市場實施類似管制措施時，實應於事前進行謹慎的評估，並慎選實施的時機。
其次，市場參與者的預期在市場運作過程中扮演相當重要的角色，對於不同次市場景氣之影響亦不相同，當預期資本利得愈高時，會使房價上漲，但租金卻會減少，因為屋主願意以相對較低的租金將房屋出租，並由長期的資本利得中獲得補償，此可解釋為何國內長期租金與房價比長期偏低的現象。不過，近年來房地產市場面臨相當長時間的不景氣，加以921大地震對於國人傳統「有土斯有財」的理財觀念應有相當程度的衝擊，在預期資本利得相當微薄、甚至為負的情況下，未來租金可能回到較合理的水準。
三、總體經濟度房地產景氣之影響部份
本文檢視總體經濟變數對不同地區房地產景氣的影響，發現不論台北市或台北縣的預售屋房價與貨幣供給、空屋數、建照面積等變數均具有長期均衡關係存在，表示房地產景氣會因總體經濟變數與房地產市場本身供需變化而調整，但在考量結構變遷下，預售屋房價與建照面積間之關係已有所改變，意味未來在分析兩者間之關係時必須更加慎重。
其次，空屋數對於預售屋房價的影響彈性相對大於貨幣供給以及建照面積的影響，且相關變數對於台北市預售屋房價的影響相對大於台北縣，但台北縣預售屋房價消弭均衡誤差的速度較台北市為快，此乃因台北市住宅供給與需求彈性相對較小，當其他影響變數發生變動時，其預售屋房價受到的影響相對較大，故一旦偏離均衡時，必須花費較長的時間來調整。此結果亦顯示，要解決房地產市場長期的不景氣，從消化空餘屋著手最為有效。另外，不論台北市或台北縣預售屋房價與其他變數間的短期領先或落後關係並不明顯，此可能是因房地產市場自1986-1990年這一波房地產景氣後，已產生結構性變遷所造成。
This dissertation consisted of three relative essays about real estate cycles. The first paper explores the influence of the real estate cycles on construction lags by analyzing the fluctuations of total floor areas of building permits and usage permits as a reflection of construction lags. Results support that a long-run equilibrium is existing between them; however, building permits may be dropped during a downswing market. In addition, the duration of construction lags is affected by changes in the real estate cycles and by the impacts of policies. During a time of strong market, the duration of construction lags is cut shorter and is extended when the market is depressed.
The second paper presents a simultaneous equation to examine how expectation of market participants and preannouncement of zoning control influence real estate cycles through three housing submarkets: rental market, sales market, and new construction market. One interesting finding is that, before the government announced a change in its zoning policy, builders constructed at maximum capacity despite fact that the real estate market was already depressed. Such construction only worsens the real estate market condition and extends the duration of depressed period. Another interesting finding is that the expected real estate cycles have different effects on rent and housing price. Although high capital gain expectations drive up the housing price, rent continues to decrease. A high vacancy rate, although decreasing the housing price, has little influence on construction starts.
The last paper examines the long-term relationships between real estate cycles and macroeconomic variables by using cointegration test and error correction model. I found that both housing price of Taipei City and Taipei County do have long-term relationships with money supply, vacant houses, and new construction, but when considering market structure change, the relationship between housing price and new construction will change. I also found that the vacant houses have more influence on housing price than that of money supply and new construction, and the influences of these three variables on housing price are more sensitive in Taipei City than Taipei County. These results reflect the market structure of Taipei City and Taipei County is different, and the importance to solve vacant houses problem. Another surprise finding is that short-term lead or lag relationships among these variables are not significant. One possible reason is the structure change of real estate market after 1990.
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