本文旨在探索美國次級房貸風暴對高科技產業營業收益的影響以及資本結構對公司因應外來衝擊的優劣情勢。
實證研究首先利用事件分析法，以臺灣地區高科技產業25家公司的營收為標的，運用自我迴歸模型進行計量模型估計，用以計算代表公司表現的營業收益異常值，比較各類別產業內樣本公司的表現。
   其次運用縱橫資料分析法以事件期間內樣本公司淨值、長期負債、短期負債、應付帳款對資產總額的比率四種資本結構變數為解釋變數，以營收異常值之原始值與經標準化之營收異常值為被解釋變數，進行實證估計。
   最後以事件期間內之累積營收異常值為被解釋變數，以期間內四種資本結構之平均數為解釋變數，並加入多種不同的公司治理變數與公司其他相關變數為控制變數，進行橫斷面迴歸估計，探索影響公司於整個事件期間的經營表現。
    實證估計結果顯示，短期內，僅應付帳款比對高科技產業的營收具有統計上顯著性的正面影響，顯示凡能夠與上游供應商保持良好的相互融通關係者，較易克服風暴的負面影響。然而，在長期下，四種資本結構的影響不具統計上的顯著性。

This thesis aims at exploring the roles played by the capital structures in helping companies coping with the adverse effects brought about by the financial turmoil. We examine operating revenues collected from 25 high-tech companies in Taiwan, comparing and testing their performance as well as exploring how their performance are affected by the different capital structures represented by the ratios of net worth, long term debts, short term debts and account payables to the total assets during the period of 2008 financial storm.
Event study methodological approach is adopted to evaluate the consequences of the effects of the financial crisis whereas an autoregressive model is estimated using the pre-crisis revenues data of each of the 25 companies and then is used for calculating the abnormal revenues during the 24 months period immediate after the breaking out of the financial crisis on August 2008. The abnormal revenues are the focus of the empirical studies.
Empirical studies involve with comparing and testing the performance of each companies during the event dates, and is regressed on the four capital structures indicators to find out how these indicators is affecting the performance of the sample companies.
Our estimations have shown that account payables significantly affect positively the performance of the high-tech industry in the short run, meaning that companies with good relationships with their upstream suppliers are easier to cope with the negative effects of the financial storm. The relationships between all four capital structure variables and the business revenues disappeared in the long run.

目錄
誌謝辭	I
中文摘要 II
英文摘要 III
目錄	V
表目錄	VI
圖目錄	VII
第一章 緒論	1
第一節	研究動機	1
第二節	臺灣高科技產業概述	2
第三節	本文架構	4
第二章 文獻回顧	6
第一節	金融風暴衝擊的研究	6
第二節	資本結構理論大要	7
第三節	本文研究方法	11
第三章 當前高科技產業發展簡介	13
第一節	高科技產業的特徵	13
第二節	高科技產業的分類	15
第三節	本文樣本公司簡介	18
第四章 實證研究與結果	29
第一節	本文資料來源與敘述統計	29
第二節	事件分析結果	36
第三節	資本結構的影響	55
第五章 結論	61
參考資料	63
 
表目錄
表3.3.1  25家樣本公司概況	27
表4.1.1  本文統計資料定義與來源	29
表4.1.2  25家樣本公司月營收基本統計	30
表4.1.3  25家樣本公司之資本結構基本統計	32
表4.2.1  營業收益自我迴歸模型估計結果	38
表4.2.2  事件期間營收遭受負面影響公司恢復常態與反彈時間彙總	47
表4.2.3  事件前後半導體業營收異常比較分析	48
表4.2.4  事件前後光電業營收異常比較分析	50
表4.2.5  事件前後通信網路業營收異常比較分析	51
表4.2.6  事件前後電子零件業營收異常比較分析	52
表4.2.7  事件前後電腦週邊業營收異常比較分析	53
表4.2.8  事件前後比較分析彙總	54
表4.3.1  事件期間各季營收異常值縱橫資料分析	57
表4.3.2  事件期間累計營收異常值分析	59
表4.3.3  事件期間累計營收異常值分析	60
 
圖目錄
圖1.1.1 臺灣電子零組件與電腦、電子及光學製品產值佔製造業總產值比重	1
圖4.2.1 事件前後各24個月內半導體業實際營收值與模型預測值	42
圖4.2.2 事件前後各24個月內光電業實際營收值與模型預測值	43
圖4.2.3 事件前後各24個月內通信網路業實際營收值與模型預測值	44
圖4.2.4 事件前後各24個月內電子零件業實際營收值與模型預測值	45
圖4.2.5 事件前後各24個月內電腦週邊業實際營收值與模型預測值	46

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