台灣資訊電子業上市公司融資決策順位之研究－Ordered-logistic迴歸模式之應用

A Research on Priority of Financing Decision of Taiwan Listed Technology Companies-the Application of Ordered-logistic Regression Model

古永嘉(Yeong-Jia Goo) ； 鄭敏聰(Min-Tsung Cheng) ； 游佳鈴(Jia-Ling You)

《輔仁管理評論》 12卷3期 (2005/10) Pp. 41-69

https://doi.org/10.29698/FJMR.200510.0003

摘要

本文以57家台灣資訊電子業上市公司為研究對象，研究期間為民國86年至90年。在第一階段以Tobit迴歸建立公司資本結構之目標負債比率估計式，實證結果顯示，股票報酬率、市價帳面值比、研發費用比率、公司規模等四項變數符合研究理論預期效果且顯著，故以此四項變數建立最適目標負債比率估計模式。第二階段以Ordered-logistic迴歸探討一般資訊電子業公司趨近目標負債比率與融資順位的狀況，實證結果顯示，台灣資訊電子產業公司之負債比率確實會往目標負債比率移動，而影響公司融資選擇最大的變數為槓桿差異，其次為公司規模、資產報酬率、股票報酬率、研發費用比率，最後為市價帳面值比。另外，在此趨近目標負債比率情況下，其融資決策之順位依序為：普通股、短期負債、海外存託憑證、長期負債、可轉換負債。此結果並不服從融資順位理論，其原因可能與台灣資訊電子產業所擁有的資產特殊性(Asset specificity)較高有關外，亦可能與其所生產的產品通常具有其特殊性或耐久性有關。此外在本文研究期間，台灣資訊電子產業正積極向海外設廠及購併，所以在進行融資時，會較注重投資計畫的獲利能力與營運風險，因此在融資工具選擇方面，會較偏向使用權益融資。

關鍵字

融資順位 ； 目標負債比率 ； Tobit迴歸 ； Ordered-logistic迴歸

並列摘要

The study collects 57 high-tech firms listed in the Taiwan Stock Exchange for 1997 to 2001. It comprehends two phases of regressions, Tobit regressions model to constitute the estimation model of target debt ratio of corporate capital structure, and Order-logistic regressions model to investigate the debt ratio toward the target and firms' financing decision to pecking order. The findings from Tobit model indicate that four variables of return on stock, market value book value, ratio of R&D expenditure and company scale are of significance to construct an optimal target debt ratio estimation model. Upon examining the financing decision among five variations, Order-logistic model predicts that the high-tech firms will adjust their capital structures to the target debt ratio and followed by the greatest variable of leverage difference are company scale, return on asset, return on stock ratio of R&D expenditure and market value book value. To summarize, with the adjustment of debt ratio to the target, the pecking order of financing decision is common stock, short-term debt, depositary receipts, long-term debt and convertible debt. Whereas the results are inconsistent with the pecking order model, the factors may be characteristics of high asset specificity and product's uniqueness and durability in this industry. In addition, as the high-tech firms striving for expansion and mergence during the study period, their financing decisions mostly issue equity by considering profitability and operating risk in investment.

並列關鍵字

pecking order ； target debt ratio ； Tobit regression model ； ordered-logistic regression model

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