房地產泡沫化模型之探討

A study of Real Estate Bubble Models

曹昌勝(Chang-Shen Tsao)

指導教授 ： 湯明哲

國立臺灣大學/管理學院/國際企業學研究所/碩士(2007年)

https://doi.org/10.6342/NTU.2007.02969

摘要

本論文目的為發展一套模型來描述台灣房地產的泡沫化特性。此模型係結合總體經濟及個體經濟理論，研究方法及發現如下：
(一) 本研究係研究歷年來台灣之房地產泡沫化情形。研究期間為1980年第一季~2006年第二季，以台灣地區之房地產為研究範圍，研究方法為以多變量分析結合CUSUM(Cumulative Sum)方法，從現有有關文獻中諸影響因素整理，先將影響房地產泡沫化之總體經濟因素歸納為4大項12個因子，先以多變量分析方法藉SPSS軟體找出影響因素之間迴歸關係，再以CUSUM法測試營建業企業財務之時間序列變化，嘗試從幾次的台灣房地產起伏過程中找出其中的關係，並建立一套房地產泡沫分析模型。
(二) 房地產泡沫化之研究應包括總體經濟因素及總體經濟因素之因素，若只包含總體經濟因素之指標，或個體經濟因素(營建業個別企業)之財務研究變數，模型解釋能力令人不甚滿意，顯示尚需納入其他非財務因素。
(三) 從研究發現台灣房地產市場過去的確發生泡沫現象，將實際上的房地產景氣循環與本研究結果比較發現，兩者之間存在下列現象：
A.時間差(Time lag)：房地產上漲時，房地產領先指標大約慢1季到過5季後才產生正泡沫現象，顯見實際市場泡沫現象的發生仍然比同時指標資訊提早或落後一些，顯示房地產的泡沫觀察除了參考領先指標外，也應參考同時指標。
B. 市場預期領先：谷底發生時間大約前2季~5季即有產生負泡沫現象，實際市場部份泡沫現象的發生有時比領先指標資訊超前，可見實際市場資訊比領先指標提早反應，顯然市場人士的房地產投資決策不完全參考政府或研究機構公告的房地產指標。
C. 泡沫危機發生機率的不準律：正泡沫現象經常在房地產景氣高峰時發生，但不一定會產生嚴重正泡沫或正泡沫危機。而嚴重負泡沫現象也多發生房地產景氣谷底，即使跌到谷底，不一定會產生嚴重負泡沫或負泡沫危機。
(四) 以CUSUM法測試上市上櫃的營建業在房地產波動期間的營運狀況財務指標作為驗證，依據模型測試結果發現，大致於房地產泡沫化發生後四~六李，可偵測出營建業產業中各別公司之財務危機發生狀況，惡化的轉折點及其趨勢。透過常態性檢定結果發現台灣地區的營建業公司之財務比率大部分不符合常態分配之假設。只有一小部分符合常態分配之假設。
本研究目的為嘗試建立一種房地產泡沫預測機制，供學術及實務參考之用。

關鍵字

房地產 ； 泡沫 ； 累積和管制圖 ； 財務危機

並列摘要

In recent years, real estate has boomed in most of the world, and in many countries, real estate prices were raised abnormally, whether real estate market is a bubble has becomes a key issue for both governments and contractors.
The purpose of this dissertation is to develop models to explore the characteristics of real estate bubbles in the last twenty-six years in Taiwan.
This research develops decision models for evaluating a contractors’ risk in handling real estate bubbles. By employing multivariable analysis and CUSUM charts, including both macroeconomic and microeconomic measure. We find that there are 12 macroeconomic principle variables which influence the results of real estate bubbles. And there are 28 microeconomic principle variables which influence the results of real estate. In addition, 23 samples are taken from the construction corporations in Taiwan. The statistical analysis from 6 failure companies and 17 healthy companies is used to identify the significance of financial variables and overcoming the static analysis shortcomings of traditional precautionary models. Then, using the time series analysis of vector Auto-Regressive Moving-Average model (VARMA), it is shown that it is possible to integrate VARAM with the multivariable CUSUM model.
The tests of models verify that models are able to interpret the real situation of the contractors’ risk handling decision. In addition, because the CUSUM chart could provide the “Real-time function,” the precision and practicality of the predicting model is increased significantly. The model could be a reference for the financial adjusting strategies in domestic construction companies and further assist governmental policies to regulate and manage the construction industry.

並列關鍵字

Real estate ； bubble ； CUSUM Chart ； Financial Distress

參考文獻

[2]Allen , F. Morris , S. and Postlewaite , A. , 1993 ,“Finite Bubbles with Short Sale Constraints and Asymmetric Information”, Journal of Economic Theory , Vol.61 , P206 ~229.

[3]Allen,F. andGale,D. ,1998,“Bubbles and Crises”, Working Paper , The Wharton School , University of Pennsylvania. P33~P45.

[4]Campbell , J. Y. and Kyle , A. S. , 1988 ,“Smart Money , Noise Trading , and Stock Price Behavior”, NBER Technical Working Paper 72.

[5]DeLong,J. B. ,Shleifer,A. ,Summers,L. H. andWaldmann,R. J. 1990,“Positive Feedback Investment Strategies and Destabilizing Rational Speculation”, The Journal of Finance , Vol. 45 , P379 ~395.

[6]Flavin , Marjorie , 1983 ,“Excess Volatility in the Financial Markets : a Reassessment of the Empirical Evidence”, Journal of Political Economy , Vol. 91 , P929 ~956.