nÃo hà / The purpose of this study is to analyze the survival of companies located in the State of Ceara and beneficiary of tax incentive within the Industrial Development Fund, specifically within the Industrial Development Incentive Program. Such benefit was created in 1979 and is currently the main fundraising tool of the new companies or the expansion tool of the existing companies in the State.The statistical technique of survival analysis of the nonlinear KAPLAN-MEIER nonparametric method was used, comparing the results of the beneficiary companies with the results of the non-beneficiary companies within the Industrial Development Fund/Industrial Development Incentive Program. The study took into consideration the location, the economic activity developed, the percentage of benefit and the turnover of the companies.The results demonstrate that the survival of the beneficiary companies is clearly superior to that of the non-beneficiary companies regardless their location, economic activity or size. The study also points out that segments of activity in which even the beneficiary companies present low survival indicators shall be subject to a scrutinized analysis by policy makers in the development of the State. / O objetivo do presente estudo à analisar a sobrevivÃncia de empresas localizadas no Estado do Cearà e beneficiÃrias de incentivos fiscais no Ãmbito do Fundo de Desenvolvimento Industrial - FDI, especificamente no Programa de Incentivo ao Desenvolvimento Industrial - Provin. Este benefÃcio foi criado em 1979, permanecendo atà hoje como o principal instrumento de captaÃÃo de novas empresas ou ampliaÃÃo das jà existentes no Estado. Foi empregada a tÃcnica estatÃstica de anÃlise de sobrevivÃncia a partir de modelos nÃo-lineares, utilizando-se o estimador nÃo-paramÃtrico de KAPLAN-MEIER, comparando-se, sempre que possÃvel, os resultados das empresas beneficiÃrias com os resultados obtidos para empresas nÃo-beneficiÃrias do FDI/Provin. O estudo levou em conta a localizaÃÃo, a atividade desenvolvida, o percentual do benefÃcio e o nÃvel do faturamento das empresas.Os resultados demonstraram que a sobrevivÃncia das empresas beneficiÃrias à nitidamente superior ao das empresas nÃo-beneficiÃrias, independente de localizaÃÃo, setor de atividade ou tamanho da empresa. Chama atenÃÃo, entretanto, segmentos de atividade nas quais, mesmo as empresas beneficiÃrias, apresentam baixos Ãndices de sobrevivÃncia e que, portanto, devem ser objeto de anÃlise mais acurada por parte dos formuladores das polÃticas de desenvolvimento do Estado.

本研究主要在建立1996-2008年間建商的存活預警模型，探討眾多危機事件中對於建商存活的影響力分析。研究所稱建商包括「建設公司」以及有從事建設業的相關公司。在台灣地區位屬火車頭角色的建設業具有舉足輕重的影響力，但其營運的財務槓桿較其他產業高，營運狀況易受景氣波動的影響，因此在事件的產生時對於投資者、銀行的應變處理便顯得相對重要。 危機事件所指除了證管會、台灣經濟新報資料庫的危機認定外，另加入財務之外的事件研究並加以定義。存活預警模型的建立是先以各種事件的相關性分析以了解各種事件的顯著性，並且量化分類後的影響事件，再進行羅吉特分析與存活分析的比對，選擇較適模型與影響力較大的危機事件進行實證分析。研究實證結果如下： 一 危機事件越多，建商經營越不穩定，存亡事件產生機率越高；影響公司存活的共通因子對於公司危機產生的共同預警變數有一定程度上的共通性，且都具有顯著性。 二 本研究將危機事件分類為財務面、監理面、經營面，存亡事件選定有終止上市、全額交割股、掏空三種。經實證後得知，財務面之外的預警變數亦能提供投資人及銀行產業了解公司經營的穩定度。在眾多預警變數中，又以重整、紓困跳票違約、董監事改選對於終止上市影響較大；對全額交割股的影響則以董監事改選、警示股、景氣因素以及利益輸送影響較大；對掏空的影響則以重整、警示股、財務結構較具顯著性。 三 存活期間與存活機率相關性比較中，以景氣預警變數而言，若產生全額交割事件，則產生存亡事件的機率非常高，公司得以存活期間較短。以重整預警變數而言，公司重整後，產生存亡事件的機率非常高，也就是說公司得以存活的期間較其他預警變數短。 四 景氣循環對於建商經營有非常大的影響，不景氣時產生具顯著性的危機事件，將會在較短期間後產生存亡事件。 / The goal of our study is establishing the survival model in the building construction companies during 1996-2008. The real estate developers in this study included “building construction companies” and the “property stock companies” which operate building construction businesses. Building construction companies are common known as a pivotal role in the power of influence by the general public, but the financial leverage is higher than other industries. Operating condition of construction companies is effected by the real estate cycle; in hence it is relative importance of the investers, banks, which the crisis events occurred. The crisis events in this study are not only the definition of Taiwan Stock Exchange and Taiwan Economic Journal Data Bank but also the events besides financial side. The study of survival model, in the beginning, is to analyze the correlation of crisis events to understand the significance of events, quantify the classified of the entire crisis event, and then to compare the results between the Logistic Analysis and the Survival Analysis. Finally, choose the appropriate model and the more influence crisis events to do the empirical analysis. The empirical analysis results of our study are as follows: 1. The more the crisis events occurred, the more the probability of failure events will occur. 2. Our study classified the crisis events into three different species, financial side, supervision side, business side. We choose company delisting, full delivery stock company, and company emptied as the failure events. 3. Compare the correlation of survival period with survival probability. In terms of company reorganized variable, for example, after reorganizing the building construction company, the probability of failure events are getting higher, and the survival duration get shorter than other crisis events. 4. The real estate cycle impact the building construction companies a lot. If significant crisis events occurred during downturn of the real estate cycle, the failure events will be generated in such a short time.