1.1 Research Purpose and Motivation
Public offering represents a stage in the growth phase of a corporation and, therefore, all private firms with growth prospects eventually go public to finance investments. Jain and Kini (1994) and Mikkelson (1997) provide evidence that US start-up companies go public to finance expansion. This is especially important for biotech company, which burns money to conduct research, and they basically unprofit when they go public offering. Besides, the biotech industry is growing fast and its products under development are novel. Thus, there is the large information asymmetry between managers and investors and it is difficult for investors to evaluate the value of the biotech firms. So how biotech company raise money? One way that biotech companies have tried to moderate investors’ concern is to provide more information to investors.
When investors know more about company and can evaluate the value the company, they are willing to finance firms. More money support biotech firms, firms performance better in the future.
Therefore, there is a negative association between the ex ante uncertainty about the value of an initial public offering and its expected long-term performance.
Subsequently, there is a great deal of literature that uses different measurement as a proxy for exante uncertainty including the information disclosed in the prospectus.
Disclosure of use-of-proceedsor risk factors in the prospectus is regarded as a proxy for ex-ante uncertainty. Beatty and Ritter (1986) finds that issues for which there is greater ex ante uncertainty tend to have greater the number of use-of-proceeds listed.
According to previous research, this study regards disclosure of risk factors as a proxy for ex-ante uncertainty. Three major issues surrounding corporate disclosure of information are actively researched in accounting and related fields: (1) the presumed objectives of disclosure, (2) the determinants of how much and by what means firms disclose, and (3) the consequences of corporate disclosure.The third issue is essentially empirical. The typical methodology is to examine the association between a disclosure index constructed by the researcher (Botosan 1997), or a quality of disclosure indicator publicly available (Lang and Lundholm 1996, and Sengupta 1998), and the presumed consequences of disclosure represented by cost of capital estimates or information asymmetry proxies, such as bid-ask spreads, stock return volatility, or dispersion of analysts' forecasts. In my research, I use path to profitability after IPO to measure consequences of disclosure. I will discuss the association between disclosure and
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probability of profitability of firms after IPO.
In order to measure risk factors in the prospectus, two approaches are applied. The first approach that counting the number of captioned risks in the risk factors section is similar with past study. In addition to the quantity of disclosure, this study also focuses on the content and description of risk factors which is coded on the basis of four-class index to be disclosure score under the second approach. Therefore, this study examines the association between disclosure of risk factors and long-term performance of firms by the number of risk factors and disclosure score separately. Moreover, because there are not only way to classify the risk factor, I will use two kinds of classification to analyze association between risk factors and long-term performance of firms.
Based on above discussion, this study analyzes biotech firms of IPOs in America during 1997-2012 to examine the effect of disclosure of risk factors on the long-term performance of biotech firms.
1.2 Research Questions
According to the research purpose and motivation, the research questions of this study are as follows:
1. How do different kinds of risk factors effect firm’s long-term performance?
2. How detail firm describe in prospectors effect firm’s long-term performance?
The remainder of this paper is organized as follows. Section 2 presents relevant literatures. Research methodology is described in Section 3. In Section 4, the study presents the empirical results. Finally, conclusion is provided in Section 5.
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1.3 Research Structure
My research structure has seven steps. First, I will identify research questions, and go to find related literature. After studying a wide range of literatures, I develop my hypothesis, that more certain kinds of disclosures in the prospectus lead to better performance of firms. Morever, stating more clearly also contributed to probability of profitability of firms. Second, knowing my hypothesis, I can start to collect data. My data comes from SDC and IPO prospectors. In order to know each description of risk factors item and score them, I need to read each firm’s risk factors one by one. It was kind of a big work. After collecting all data I need, instead of linear regression, I use Cox Proportional Hazards models to test whether risk factors identified by my theoretical framework significantly impact the probability of post-IPO profitability as a function of time. Dependent variable is the logarithm of the hazard rate, a positive coefficient on an explanatory variable in the CPH model indicates that an increase in the variable is associated with an increase in the hazard rate and consequently lower duration. In the context of my application, a positive (negative) coefficient indicates that an increase in the variable leads to an increase (decrease) in the probability of attaining profitability and a decrease (increase) in the time-to-profitability. At last, after running data through Stata, I finally get my empirical results. I will analyze them and do conclusions. The research structure in this study is presented as follows:
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Figure 1-1. Research Structure
Identify Research Question
Review Related Literature
Develope Hypothesis
Collect Data
Conduct Empirical Study
Analyze Empirical Results
Conclusions and Disclosures
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2.1 Asymmetric Information when IPO
Conventional wisdom suggests that the public offering represents a stage in the growth phase of a corporation and, therefore, all private firms with growth prospects eventually go public to finance investments. It is, therefore, not surprising that the empirical evidence on the `stage in the growth' motive for public offerings is also mixed.
For instance, Jain and Kini (1994) and Mikkelson (1997) provide evidence that US start-up companies go public to finance expansion. On the other hand, Pagano et al.
(1998), using a sample of Italian IPOs, find evidence that suggests that companies go public not to finance growth but rather to rebalance their accounts after a period of high investment and growth. Rydqvist and Hogholm (1995) and Planell (1995) document similar results for Swedish IPOs and Spanish IPOs, respectively.
Besides, information asymmetry at IPO—a time when no prior statutory disclosures are available to investors—is abnormally high. The reasons for high ex ante uncertainty are different. One of causes is the risks IPO firms encounter. There are generally no established histories of sales, earnings or cash flows for the firms going public. The biotech firms, particularly, face greater uncertainty and risk in IPO market because of intense competition, long period in research and development and great need for capital. Besides, in biotech IPOs the primary assets are intangibles which are notoriously difficult to value (Guo 2005). So how to lessen this kind of uncertainty?
There are some ways that firms use to signal to investors that they have good future.
First, Megginson and Weiss (1991) use firm age as a control for the degree of information asymmetry. Similar to Muscarella and Vetsuypens(1989), there is a significantly negative relationship between the age of the firm and information asymmetries. In general, more public information is available about the value of older firms, which can reduce information asymmetries. This implies that older firms have a lower degree of information asymmetry than do younger firms.
Second, Beatty and Ritter (1986) use the inverse of the gross proceeds to be a proxy for ex ante uncertainty because smaller offerings are more speculative, on average, than larger offerings. Hence, offering size can send signals to the market about the relative quality and stability of an offering (Ibbotson and Ritter 1995). And the empirical analysis indicates that smaller offerings, ceteris paribus, have substantially higher information asymmetry (Beatty and Ritter 1986).