فایل ورد کامل خطر سقوط شرکت، محیط اطلاعاتی و سرعت تنظیم اهرم

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تعداد صفحات این فایل: ۵۰ صفحه

بخشی از مقاله انگلیسیعنوان انگلیسی:Firm Crash Risk, Information Environment, and Speed of Leverage Adjustmen~~en~~

Abstract

This paper examines the effect of a firm’s crash-risk exposure on its speed of leverage adjustment (SOA), and how this effect is influenced by the information environment of the country in which the firm is located. We employ a panel of 19,247 firms across 41 countries from 1989 to 2013, and we find that firms with a higher crash-risk exposure tend to adjust their financial leverages more slowly toward their targets. This evidence supports the dynamic trade-off theory that firms with larger transaction costs adjust their capital structures less often. Equally important, we document that the negative link between crash-risk exposure and SOA is less pronounced in countries with a more transparent information environment.

۱ Introduction

Existing capital structure theories demonstrate that information asymmetry is an important determinant of optimal leverage. For example, Myers (1984) and Myers and Majluf (1984) show that firms with high information asymmetry face large external financing costs. The signaling theory of capital structure suggests that the stock market positively (negatively) reacts to an announcement of debt (equity) issuance (Ross (1977) and Noe (1988)). Moreover, the dynamic trade-off theory allows firms to take into account a trade-off between a suboptimal financial structure and leverage adjustment costs (Fischer, Heinkel, and Zechner (1989), Goldstein, Ju, and Leland (2001), and Strebulaev (2007)). Therefore, it predicts that firms with higher transaction costs tend to adjust their leverage ratios more slowly toward their targets.

One anecdotal example is the stock-price crash of Olympus in 2011 caused by its accounting scandal. The Japanese company paid inflated advisory fees to takeover advisers in order to hide investment losses in the 1990s. After its former president and CEO, Michael C. Woodford, questioned the fees of the Gyrus acquisition, Olympus’ stock fell 70% within three weeks (from mid-October to November 8, 2011), reflecting investors’ concerns about the company’s actual prospects. In particular, Olympus’ shareholders were worried about the company being delisted from the Tokyo Stock Exchange, which could restrict access to external equity financing. In addition, the company’s credit rating was downgraded, suggesting that its creditworthiness had deteriorated considerably. In this case, reactions from capital-market participants were in accord with the prediction that external financing costs increase crash risk (The Wall Street Journal, December 6, 2011).

In this paper, we investigate how a firm’s crash-risk exposure affects its leverage adjustment decision. We argue that firms exposed to a high crash risk are presumably those with extreme information asymmetry between inside managers and outside investors, which is consistent with the evidence of a significant positive relationship between crash risk and extreme information asymmetry in the existing literature (Jin and Myers (2006), Hutton, Marcus, and Tehranian (2009), and Kim, Li, and Zhang (2011a)). Thus, we hypothesize that a firm’s crash-risk exposure tends to decrease its speed of leverage adjustment (SOA).

More importantly, we expect that the negative crash-risk effect on leverage adjustment is attenuated by a transparent information environment because the impact of the macro information environment on different aspects of financial markets, including institutional shareholding (Li, Moshirian, Pham, and Zein (2006)), foreign investor shareholding (Haw, Hu, Hwang, and Wu (2004), Gelos and Wei (2005), and Leuz, Lins, and Warnock (2009)), and leverage adjustment (Oztekin and Flannery (2012)), has been well documented. To test our hypotheses, we employ an international sample of 41 countries from 1989 to 2013. Using international data has two advantages. First, our sample includes a large number of crash events. Second, multi-country data allows us to examine the effect of information environments on the relationship between crash risk and capital structure adjustment.

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