Earnings Quality and International IPO Underpricing Thomas J. Boultona,*, Scott B. Smartb, Chad J. Zutterc a
Farmer School of Business, Miami University, Oxford, OH 45056, USA Kelley School of Business, Indiana University, Bloomington, IN 47405, USA c Katz Graduate School of Business, University of Pittsburgh, Pittsburgh, PA 15260, USA b
Draft: August 2010
Abstract This study examines the impact of country-level earnings quality on IPO underpricing. Examining 10,783 IPOs from 37 countries, we find that IPOs are underpriced less in countries where public firms produce higher quality earnings information. This finding persists after controlling for other deal- and country-specific factors that affect IPO underpricing, and it is driven neither by the large and relatively transparent markets in the U.S. and U.K. nor by the relatively opaque Japanese market. The impact of low earnings quality on underpricing is partially offset by the use of a top-tier underwriter. JEL classification: G15; G24; G30; G32; G34 Keywords: international finance; earnings quality; initial public offerings; underpricing. Data Availability: Data used in this study are available from public sources.
For valuable comments, the authors express their thanks to Steven Kachelmeier (senior editor), Mark
Trombley (editor), two anonymous reviewers, Oya Altinkiliç, Utpal Bhattacharya, Ting Chen, Robin Grieves, Robert Jennings, Kenneth Lehn, Gershon Mandelker, Jay Ritter, Shawn Thomas, Greg Udell, Xiaoyun Yu, and seminar participants at the 20th Annual Conference on Financial Economics and Accounting (Rutgers), Financial Management Association meetings (Orlando), Central Michigan University, Duquesne University, Louisiana Tech University, Marquette University, Miami University, Oklahoma State University, Seton Hall University, Texas A&M University, University of Nebraska, University of Oklahoma, University of Otago, University of Pittsburgh, West Virginia University, and Wright State University. Any remaining errors or omissions remain the responsibility of the authors. * Corresponding author. Tel.: + 1-513-529-1563; fax: + 1-513-529-8598. E-mail address:
[email protected] (T. Boulton).
Electronic copy available at: http://ssrn.com/abstract=972694
Earnings Quality and International IPO Underpricing
Abstract This study examines the impact of country-level earnings quality on IPO underpricing. Examining 10,783 IPOs from 37 countries, we find that IPOs are underpriced less in countries where public firms produce higher quality earnings information. This finding persists after controlling for other deal- and country-specific factors that affect IPO underpricing, and it is driven neither by the large and relatively transparent markets in the U.S. and U.K. nor by the relatively opaque Japanese market. The impact of low earnings quality on underpricing is partially offset by the use of a top-tier underwriter. Keywords: international finance; earnings quality; initial public offerings; underpricing Data Availability: Data used in this study are available from public sources.
1 Electronic copy available at: http://ssrn.com/abstract=972694
I. Introduction Few corporate events garner more attention from researchers, practitioners, the media, and the public than initial public offerings (IPOs). Generally, the focus is on the large, sometimes spectacular, first-day gains to new issues observed not only in the U.S., but in virtually all of the world’s stock markets. Summarizing the findings of dozens of studies, the majority of which focus on underpricing in a single country, Loughran et al. (1994) confirm that IPOs earn positive first-day returns everywhere, and that underpricing varies dramatically across countries. However, what drives underpricing differences across markets is still a largely unexplored question. Theoretical explanations of the underpricing phenomenon often propose that underpricing arises from information asymmetries among participants in the IPO process. To cite just one prominent example, Rock (1986) shows that when investors have different information sets, underpricing is necessary to induce less informed investors to bid for IPO shares in equilibrium.1 Asymmetric information theories receive considerable empirical support. In a recent survey of the empirical evidence, Ljungqvist (2007, p. 380) concludes that information asymmetries ―have a first-order effect on underpricing.‖ We investigate whether some of the cross-country underpricing variation documented in the literature may be driven by differences in the quality of information available to investors in different markets. Specifically, we are interested in whether international differences in the quality of accounting information (i.e., earnings quality) help explain the international cross-section of IPO initial returns (i.e., IPO underpricing).
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Other information-based underpricing theories endow different participants in the IPO process with
superior information. For example, in Baron (1982) investment bankers know more about an IPO firm’s true value than the issuer does, and underpricing becomes a solution to the resulting principal-agent problem. In Allen and Faulhaber (1989), Grinblatt and Hwang (1989), and Welch (1989), issuers use their information advantage to signal firm quality, whereas in Benveniste and Spindt (1989), underpricing induces well-informed investors to reveal what they know before the offer price is set.
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We draw upon the extant literature for several proxies for earnings quality and to ask whether those proxies influence underpricing across firms in different countries. There is ample evidence in both the accounting and finance literatures that the earnings quality measures in our tests are correlated with a wide range of capital market outcomes. For example, Bhattacharya et al. (2003) find that, in countries with greater earnings opacity, firms face a higher cost of capital. Biddle and Hilary (2006) establish that better accounting information leads to more efficient firm-level investment decisions, particularly in countries where financing comes through arms-length transactions rather than through relationships with creditors. Gelos and Wei (2005) find that emerging markets mutual fund managers invest more heavily in countries with greater transparency. Jin and Myers (2006) argue that greater opacity leads to lower firm-specific risk borne by investors and more synchronous stock prices, indicating that the relative amount of firm-level information (as opposed to market-level information) that is capitalized into stock prices is lower in more opaque countries. These findings, combined with the central role that information asymmetries play in IPO underpricing, give rise to our earnings quality hypothesis—do firms endure higher underpricing when they go public in countries where the quality of earnings information is relatively low? We approach this question in an international setting for several reasons. First, as noted above, underpricing varies dramatically across countries, though relatively little work has been done to understand why this is the case. Second, within a single country, firms operate in the same legal and regulatory environment, and that environment likely imposes some limit on the variability of earnings quality across firms within a country. Thus, it is plausible that the quality of accounting information varies more across markets than within a single market. Third, in most cases, very little accounting information is available about a particular firm prior to its IPO. An IPO prospectus typically offers little more than two years of pre-IPO financial information. This limits the ability to capture cross-sectional earnings quality differences as of the IPO date. In contrast, the country-level earnings quality measures that we use draw upon several years of data generated
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by many different firms. While these measures do not provide specific information on the quality of earnings from one IPO to another in a given country, they do capture differences in the information environment in which firms from different countries go public. Fourth, we are interested in whether reputable financial intermediaries, such as top-tier investment banks, play a role in mitigating the information asymmetries related to earnings quality. Given the global scope of the investment banking industry, and given the difficulties in identifying cross-sectional earnings quality variance in a single country, the question of whether investment banks mitigate earnings-related information asymmetries seems ideally suited to an international sample. Although the advantages of studying underpricing using an international sample are numerous, we must mention two caveats associated with our research design. First, underpricing differences across countries could be influenced by omitted variables, such as differences in offering methods, which could be correlated with our earnings quality measures. We have taken many steps to minimize this possibility, for example by controlling for country and deal characteristics such as the offering method. In addition, we appeal to evidence that IPO pricing methods around the world are converging over time, with the U.S. bookbuilding approach dominating in most countries. For instance, Ljungqvist et al. (2003) find that, in a sample of 2,143 IPOs from 65 countries, 46.2 percent were priced using the bookbuilding method in 1994, but by the end of their sample period (the first seven months of 1999), the fraction of new issues priced via bookbuilding rose to 80 percent. Similarly, Jagannathan and Sherman (2006) examine the use of auctions and bookbuilding in 46 countries and find that in all but four countries, auctions have been abandoned entirely, and auctions are rare in the few countries that still use them. In contrast, they find that the bookbuilding method has been gaining market share over time and has become the dominant pricing method in most countries. So while we cannot rule out the possibility of an omitted variables problem in our analysis, the timeliness of our sample (1998-2008) combined with our regression control variables and robustness tests reduce this problem to the extent possible.
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The second caveat is that private firms can presumably mitigate asymmetric information problems by providing high-quality accounting information leading up to their IPOs, but we do not have data on pre-IPO disclosures of private firms. Our country-level measures are intended to quantify, in a broad sense, the quality of information generally provided by public firms in a given country, but these measures may or may not represent a good characterization of the reporting practices of private firms prior to their IPOs. Ball and Shivakumar (2005), for example, find that the reporting done by private U.K. firms more closely resembles the disclosures provided by firms in code-law countries than those of U.K. public companies. Even so, it seems likely that as firms execute their plans to go public, they adapt their reporting practices to align with those of existing public firms. In that case, IPO firms would not resemble other private firms in terms of their reporting strategies. In either case, there may be limits to the benefits that a given firm can capture by adopting reporting practices superior to those that are common in its home country. For example, Doidge et al. (2007) find that firms in countries where corporate governance practices are relatively poor find it difficult to credibly commit themselves to better governance. Examining 10,783 IPO events, we find evidence of a statistically and economically significant association between country-level earnings quality and IPO-firm-level underpricing. Comparing two countries that differ in earnings quality by one standard deviation reveals that firms going public in the country with better earnings information experience 7.8 percentage points lower underpricing (the sample mean initial return is 36.5 percent).2 Our regression models control for many deal-specific (e.g., offer size, industry, underwriter, and underwriting method) and country-specific (e.g., market returns, liquidity, and IPO activity) variables that influence underpricing, and our results are robust to accounting for price stabilization activities and various minimum offer price screens. Furthermore, the link between earnings quality and underpricing is 2
This statement is based on the standard deviation of aggregate EM reported in Table 3 and the
regression estimate of aggregate EM reported in Table 5.
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driven neither by the large and relatively transparent U.S. and U.K. markets nor by the relatively opaque market in Japan. Finally, we find evidence that top-tier underwriters mitigate the effect of poor country-level earnings quality on IPO underpricing, such that firms listing in countries with relatively low earnings quality experience a marginal reduction in underpricing if they are backed by top-tier underwriters. Section II highlights previous research on earnings quality and IPOs related to this study. Section III describes our sample construction and descriptive statistics. Section IV contains our primary results on the relations between the quality of earnings and IPO underpricing and illustrates that many of the conventional variables used in single-country studies of IPO underpricing also explain the international cross-section. Section V summarizes and concludes.
II. Earnings quality and IPOs A number of researchers have studied the link between accounting information disclosed in the IPO prospectus and the market value of going-public firms. Essentially, this strain of the literature asks whether IPO firms manipulate their financial statements to obtain a higher share price. Early studies offer modest affirmation for this hypothesis (e.g., Clarkson et al. 1992; Aharony et al. 1993; Friedlan 1994). Teoh et al. (1998) report that IPO firms have high issue-year earnings and abnormal accruals, followed by poor long-run earnings and negative abnormal accruals and that abnormal accruals at the IPO help explain subsequent poor stock returns. Similarly, Teoh et al. (1998) find that IPO firms that are the most aggressive in using accruals to report cash flows in excess of earnings earn 20 percent lower stock returns in the three years after the IPO compared to the firms reporting the most conservative earnings figures.3 However, Fan (2007) reports that discretionary accruals are indeed highest in the IPO year, consistent with the notion that IPO issuers manage earnings, but she finds no evidence of a negative relation between 3
Aharony et al. (2000), DuCharme et al. (2001), and Teoh and Wong (2002) also find evidence of pre-
IPO earnings manipulation.
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IPO earnings management and subsequent stock returns. Further, Venkataraman et al. (2008) examine pre-IPO financial statements and find that pre-IPO accruals tend to be negative and less than post-IPO accruals. In the same vein, Ball and Shivakumar (2008) find that firms’ reporting practices become more conservative when they transition from private to public status through an IPO. All of these studies focus on the extent to which earnings manipulation leading up to the IPO influence the firm’s stock price. They do not look at underpricing (i.e., the difference between the IPO offer price and the market price established once trading begins), which is our focus. The accounting literature offers several insights regarding the influence of accounting disclosures on IPO underpricing. In a study of micro-cap Nasdaq IPOs, Willenborg and McKeown (2001) find that firms going public with going-concern audit opinions are more likely to delist within two years of the IPO, but these firms also endure less underpricing, consistent with the notion that the audit opinion reduces information asymmetries between issuers and investors. Jog and McConomy (2003) examine the impact of voluntary disclosure of management earnings forecasts in the IPO prospectus on IPO valuation and performance. They find higher underpricing for IPOs that do not include earnings forecasts, though this difference is concentrated among small firms. Schrand and Verrecchia (2005) study the relation between underpricing and the frequency of pre-IPO disclosure, finding lower underpricing for firms with more frequent disclosures prior to the IPO. An exception is Internet firms, where this relation is reversed. They also find that more frequent disclosure ameliorates adverse selection in the aftermarket, with lower bid-ask spreads and greater depths for firms that disclose more frequently pre-IPO. Finally, Leone et al. (2007) find that IPO underpricing decreases when issuers disclose more specific information in the ―uses of proceeds‖ section of the prospectus. Collectively, these studies, all of which focus on IPOs in a single country, suggest that accounting disclosures influence underpricing.
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Our study extends this analysis to a multi-country setting to determine if earnings quality at the country level influences underpricing costs borne by firms going public in different markets. In so doing, we add to the very limited evidence on the determinants of cross-country underpricing variation as well as contribute to another strain of the literature on the quality and value of accounting information in different countries. For example, DeFond et al. (2007) find that earnings announcements are more informative in countries with better overall earnings quality. Bhattacharya et al. (2003) study the extent to which cross-country variation in the quality of accounting information influences the cost of capital and trading volume in international equity markets. Using data from 34 countries covering 1985-1998, they measure three dimensions of earnings opacity for each country—earnings aggressiveness, loss avoidance, and earnings smoothing. They find robust evidence that an increase in overall earnings opacity leads to an increase in the required return demanded by shareholders and a decrease in trading activity. In a similar vein, Leuz et al. (2003) examine earnings management practices in 31 countries and find that firms engage in greater earnings management in countries with weaker investor protections.4 These studies and others suggest that the quality of earnings information available to outside investors influences information asymmetries in the market. Given the central role of asymmetric information in theories of IPO underpricing, we anticipate that differences in earnings quality across countries will influence the underpricing costs that firms going public in different countries face. Recognizing that earnings quality is a multi-faceted concept and that no single measure can capture all aspects of earnings quality, we employ a wide range of earnings quality measures drawn from the extant literature and study their association with firm-level underpricing. The measures we use are designed to capture elements of earnings quality such as earnings smoothing, loss avoidance, and earnings aggressiveness, among others. Below, we 4
Bushman and Piotroski (2006) construct earnings quality measures based upon accounting
conservatism and link those measures to cross-country variation in legal and political institutions. See also Hung (2000) and Ball et al. (2003).
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construct and use the earnings quality measures in Leuz et al. (2003) and Bhattacharya et al. (2003) to test our earnings quality hypothesis.
III. Sample construction and descriptive statistics
Sample construction We begin our sample construction by retrieving each IPO with a valid offer price and offer size for all countries reported in the Thomson Financial SDC Platinum New Issues database from 1998 through 2008. We exclude financial firms, rights offerings, unit offerings, closed-end funds, trusts, limited partnerships, and depository receipts. This initial extraction from SDC results in 13,390 IPOs from around the world. Next we attempt to match each IPO firm with the Datastream database to collect the secondary market prices that we need to calculate IPO initial returns. This matching process is done in two steps: (1) we use the SEDOL firm identifier included in both the SDC and Datastream databases, and (2) we hand match any firm that does not have a SEDOL reported in both databases. We are able to match 74.4 percent of the SDC IPOs using the SEDOL and an additional 16.2 percent by hand, for a total of 12,122 IPOs matched with Datastream. We next drop 950 IPOs that do not have a valid ―first-day‖ secondary market closing price in Datastream. We define a valid secondary market closing price as a price observation in Datastream with positive trading volume (i.e., a transaction price). The first-day secondary market closing price is the first valid closing price that occurs within -3 to +60 days of the SDC IPO issue date.5 From the remaining 11,172 IPOs, we drop an additional 161 deals due to incomplete or missing data for our earnings quality measures or control variables. 5
In 39 cases, representing less than 0.4% of our sample, there is an apparent error in the SDC IPO date
because the first closing price of the firm found in Datastream occurs 1, 2, or 3 days prior to the SDC IPO date. For France, Greece, and Taiwan we use the tenth valid price, rather than the first, because in these
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For 11,011 IPOs from around the world, we calculate the initial return as the first-day secondary market closing price divided by the IPO offer price, minus 1.6 To eliminate the impact of outliers, we trim our sample by removing the top and bottom one percent based on initial returns.7 Finally, we exclude countries with fewer than five IPOs during our sample period. These steps result in a final sample of 10,783 IPOs listed in 37 countries. Table 1 summarizes the sample selection process. [Place Table 1 about here] Although common in the IPO literature, we do not impose a minimum offer price restriction. For example, Ritter (1991) evaluates U.S. IPOs with a minimum offer price of $1 to mitigate the bid-ask bounce effect. However, imposing this filter would not only greatly reduce the number of IPOs in many countries, but it would also eliminate some countries entirely. Applying a $1 minimum offer price (converting local currency to U.S. dollars based on the exchange rate as of the IPO date) eliminates over one-third of the sample events. Thus, the main analysis presented here imposes no minimum offer price, but we do verify that our results are unaffected by the inclusion of IPOs with very low offer prices.
Descriptive statistics Figure 1 displays the average IPO underpricing and number of IPOs by year. The figure clearly illustrates the slowdown in equity offerings following the decline in equity markets in 2000. IPO volume falls more than 56 percent from 2000 to 2001, then remains relatively flat for 2002 and 2003. The number of new issues rebounds sharply to 1,206 deals in 2004 and remains above 1,100 issues per year through 2007. The worldwide financial crisis of 2008 had a
countries secondary prices are initially constrained by daily volatility limits for a few days following the IPO. 6
When calculating initial returns, closing and offer prices are in the IPO firm’s local currency.
7
Initial returns at the 1st and 99th percentiles cutoffs are -36 and 388 percent, respectively.
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significant negative impact on IPO issuance worldwide, with only 444 firms going public. Consistent with the ―hot issues market‖ phenomenon (e.g., Ritter 1984), average underpricing is positively correlated with yearly IPO volume (correlation = 0.51). [Place Figure 1 about here] Coffee (1999, 2002) suggests that firms list abroad to bond themselves to foreign listing standards. For example, firms listing in the U.S. subject themselves to SEC oversight, agree to meet generally accepted accounting principles (GAAP), and face the scrutiny of financial intermediaries involved in the security markets. While most of our IPOs originate and list in the same country, some companies choose to list outside their home country. We exclude depositary receipts from our sample, but retain firms that list their shares directly in a foreign market. Most of these firms list in the U.S. or the U.K. Because listing abroad can bond management to the listing country’s standards, the country where the firm lists is the relevant location for this study.8 Table 2 shows the IPO volume, aggregate gross IPO proceeds, average underpricing, and the average value of each earnings quality variable for each country in our sample. Not surprisingly, the U.S. has the most IPOs in the sample, followed closely by Japan, the U.K., and Australia. The aggregate gross proceeds for the entire sample is about $1.12 trillion, of which the U.S. represents about 29 percent. Table 2 confirms that IPO firms are underpriced, on average, in every country, and that average underpricing varies widely across countries. First-day returns range from 120.7 percent in China to less than 2 percent in Argentina. For each country and each year, we calculate several earnings quality measures, described in more detail in the next section. One such measure is a country’s aggregate earnings management (aggregate EM) score, which is constructed such that a higher score implies greater earnings management, and therefore lower quality earnings. The average aggregate EM scores indicate that the countries with the least (most) earnings management are Australia, South Africa, and the 8
Unreported robustness tests confirm that our results are not sensitive to the exclusion of firms that
choose to list in a foreign country.
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U.S. (China, Indonesia, and Taiwan). An alternative earnings quality measure is earnings opacity. The average earnings opacity scores indicate that the countries with the most transparent (opaque) earnings are Norway, the U.S., and Canada (China, India, and Hong Kong).9 At the bottom of Table 2 we report the simple correlations between the average IPO underpricing and earnings quality measures. The positive correlations are consistent with our earnings quality hypothesis, which predicts greater underpricing in countries with lower quality earnings. [Place Table 2 about here] Figure 2 offers preliminary evidence that earnings quality influences underpricing. Figure 2 groups countries into earnings quality quartiles based on their average yearly aggregate earnings management score for the sample period. Countries with the highest aggregate EM are in the lowest earnings quality quartile and those with the lowest aggregate EM are in the highest earnings quality quartile. Figure 2 reports the average underpricing and average aggregate EM across IPOs within an earnings quality quartile. Average underpricing is almost 77 percent higher (or over 21 percentage points higher) in the lowest earnings quality quartile compared to the highest quartile. Across earnings quality quartiles, the simple correlation between average IPO underpricing and average aggregate EM is 76 percent. Of course, many differences in the IPO process and in the types of firms going public exist across countries, so in the next section we test for a link between earnings quality and IPO underpricing while holding constant deal-level and other country-level characteristics. [Place Figure 2 about here] Table 3 provides descriptive statistics for the variables used in our regression analysis, starting with various earnings quality measures drawn from Leuz et al. (2003) and Bhattacharya
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To provide a check of our earnings quality variables against those published in other studies, we
compared our calculations to those published in Table 1 of Bhattacharya et al. (2003). For comparable variables, the correlation between ours measures and theirs (which were taken from a slightly different time period) is 0.87.
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et al. (2003). For these measures, we provide up-to-date, yearly calculations (described below) for each of our sample countries and scale these measures such that a higher value indicates lower earnings quality. The unit of observation in our regressions is the IPO firm, and the dependent variable is the first-day return. The sample mean initial return equals 36.5 percent, which is roughly double the 18.7 percent mean reported by Loughran and Ritter (2004) for 6,391 IPOs issued in the U.S. between 1980 and 2003. The cross-sectional standard deviation of initial returns is 61.2 percent, indicating large variations in IPO returns. Unquestionably, some of this variation can be explained by deal-specific and market-specific factors not related to earnings quality, so we use the remaining variables listed in Table 3 to control for these effects. Because the extent to which an IPO is underpriced may be influenced by the quality of the underwriter, we create an indicator variable to identify top-tier underwriters. Underwriters listed in the top 25 of SDC’s global league tables for the issue year are coded as top-tier underwriters. Table 3 indicates that 22.5 percent of our IPOs employ a top-tier underwriter.10 In some countries, underwriters can engage in price support once trading begins. Underwriters may have incentives to engage in price stabilization, particularly when an IPO’s market price begins to fall below the IPO offer price. If underwriters engage in price support to limit the occurrence of negative initial returns, then the first-day returns distribution will have a higher mean than it would have in the absence of price support. We do not have detailed data on the regulations and practices with respect to price stabilization in all countries, so we attempt to control for price stabilization activity in two ways. First, we construct a country-level proxy for price stabilization activity. If price stabilization is widespread, then we expect to see an unusually
10
In unreported tests, we controlled for underwriter reputation using country-level or global market
share measures. These measures are consistent with Megginson and Weiss (1991), who use market share to proxy for underwriter reputation. Our results are broadly similar when these measures are used to proxy for underwriter reputation.
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large probability mass in the distribution of first-day returns at and just to the right of zero and an unusually small probability mass immediately to the left of zero. Therefore, for each country, we calculate the difference in the number of IPOs with initial returns between zero and one percent and the number of IPOs with initial returns between zero and negative one percent, and then divide the difference by the total number of IPOs. The more prevalent is price stabilization in a given market the higher should be this ratio, and the higher should be average underpricing. Table 3 reports a mean price stabilization ratio of 0.007, indicating a slightly greater incidence of small positive initial returns than small negative returns. A second approach to control for price stabilization exploits the fact that underwriters typically provide price support for a very limited time. Because stabilization activities are short lived, the effects of stabilization activities on the IPO returns distribution should diminish over time. Later, in Table 6, we calculate the IPO initial return based on the market price roughly one month (22 trading days) after the first trading day, and test to see if our regression results are robust to this change. As suggested in numerous studies, including Ritter (1984), underpricing tends to be higher when IPO volume is high and when overall stock market returns are high. We include two variables to control for these ―hot market‖ effects. First, our IPO activity measure equals the number of IPOs in a given country in each year divided by the total number of listed equities in Datastream for that country in 2008. Therefore, this measure takes the same value for all IPOs from a single country in a particular year, but within a country it varies across time, and within a single year it varies across countries. Second, for each IPO, we calculate the return on the Datastream market index in the three months leading up to the offer. Consequently, two firms will share the same market return value only if they go public at the same time in the same country. Ellul and Pagano (2006) suggest that IPOs in less liquid markets will exhibit larger initial returns. Higher underpricing compensates IPO investors for the illiquidity risk that they bear. To control for differences in liquidity across national markets, we include a country-level stock
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market turnover ratio, which is defined by Beck et al. (2000) as the ratio of total value of shares traded to market capitalization.11 Hence, this measure captures a stock market’s liquidity relative to its size, and we expect lower initial returns in more liquid markets. The climate for entrepreneurship varies from one country to another due to a variety of factors such as tax rates, government regulations, corruption, and many others. To control for some of these differences, we include the Index of Economic Freedom, which is produced by the Heritage Foundation and The Wall Street Journal. The index is an aggregate of several different measures of economic freedom, including: (1) the ease of starting a new business, (2) the level of trade barriers, (3) the top marginal income tax rate, (4) government spending as a percentage of GDP, (5) the inflation rate, (6) the ease with which foreigners can invest in a given country, (7) the extent of government control of the banking system, (8) legal protection of property rights, (9) corruption, and (10) the ability of a business to hire and fire workers without restrictions. 12 A higher index value indicates greater economic freedom. Because of the literature spawned by the work of La Porta et al. (2000) illustrating the importance of various investor protections on a range of capital market outcomes, we also attempt to control for variation in governance across our sample countries. The index of economic freedom, given its constituent parts, should provide one measure of control for differences in country-level governance. A second control variable aimed at holding constant the effects of governance, is the antidirector rights index from La Porta et al. (1998). The antidirector rights index is based on a collection of legal and regulatory variables related to a nation’s stance regarding the protection of shareholders. Boulton et al. (2010) report a positive relation between 11
Beck et al. (2000) report the ratio of total value of shares traded to market capitalization for the
period 1999-2004. Since our sample period is 1998-2008, we take the average of all years reported for a country by Beck et al. as our measure of country-level stock market turnover. 12
Moeller and Schlingemann (2005) use this index to proxy for the restrictiveness of the institutional
environment related to corporate acquisitions, and they find that in cross-border acquisitions, bidder returns are higher when targets come from countries with greater freedom.
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the antidirector rights index and IPO underpricing, which they suggest is a cost incurred by insiders to maintain control in countries with legal systems that offer stronger protections to investors. Most IPO underpricing studies include measures designed to capture information asymmetries, including the natural logarithm of the offer size. Because the amount of money that IPO firms raise varies widely across countries, we also construct an offer size measure that captures the size of an IPO relative to other deals in the same country, which we report in Table 3. This offer size ratio equals the offer size for a particular IPO divided by the mean offer size for IPOs in a given country.13 We obtain broadly similar results with both absolute and relative dealsize measures, so in Table 3 and in subsequent regressions we simply include the offer size ratio for each IPO. In addition to offer size, we also include a measure of stock return volatility to control for information asymmetry. Our stock return volatility measure is the standard deviation of returns over the first 30 (calendar) days following the IPO. [Place Table 3 about here] Bradley et al. (2004) report that IPOs with integer prices experience higher underpricing. To explain this pattern, they propose a ―negotiation hypothesis‖ in which underwriters and issuers bargain over finer offer price increments as the uncertainty surrounding firm value declines. Thus, for IPOs that are particularly difficult to value, and hence should have higher underpricing, offer prices tend to fall on integers. Fifty percent of our IPOs have an integer price, which compares to 76 percent of U.S. IPOs as reported in Bradley et al. We include in our regression an indicator variable equal to one when the offer price is an integer.14
13
All offer sizes are measured in millions of CPI-adjusted 2008 U.S. dollars. CPI data is from the U.S.
Bureau of Labor Statistics website. SDC reports offer size in U.S. dollars. 14
In Japan all IPOs are priced on an integer. For Japanese IPOs, our integer indicator equals one if the
offer price (in yen) is perfectly divisible by 100.
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Sherman (2005) notes that methods for taking firms public worldwide are converging towards the traditional U.S. bookbuilding approach, and she argues that bookbuilt offers are associated with lower underpricing than offers conducted via auctions. Sherman argues that book building reduces the risk faced by IPO issuers and investors, and therefore should lead to less underpricing. However, she also notes that book building affords issuers discretion over information expenditures, which she suggests can lead to either more or less underpricing depending on the issuer’s preferences. Ritter (1987) provides evidence that firm commitment IPOs are underpriced less than best efforts IPOs. Sixty-one percent of the firms in our sample are taken public through a bookbuilt offering, while 56 percent of the deals are firm commitment offerings. Deals that are both firm commitment and bookbuilt represent 31.6 percent of the sample. We include indicator variables for bookbuilt deals and for firm commitment offerings. Schipper and Smith (1986) and Prezas et al. (2000) provide evidence that equity carve-outs are underpriced less than original IPOs. To capture this effect, we include an indicator variable for carve-outs.
IV. Earnings quality
Country-level earnings quality and IPO underpricing In this section, we ask whether earnings quality affects underpricing. We calculate two different sets of well established earnings management measures that are intended to capture the variation in the quality of earnings information across our sample countries. Our premise is that information asymmetry and earnings quality are inversely related. The basic tenet of our earnings quality hypothesis is that managers can take various actions to obscure the true earnings distribution, and that these actions increase information asymmetries and underpricing. To construct our earnings quality measures, we use financial statement data on firms in each country that are already publicly traded. In this way, we attempt to characterize the earnings management
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practices that are common in each country rather than capturing earnings management behavior for each IPO firm. We use firm-level data from Compustat Global over the years 1993 to 2007 for all nonfinancial firms with a minimum of three consecutive years of accounting data. Each country included in the sample has a minimum of 200 firm-year observations from Compustat Global. Each earnings management measure is constructed annually over the 1998-2008 sample period using accounting data from the prior five years. Thus, our earnings quality variables vary over time and across countries. Our first set of earnings quality measures come from Leuz et al. (2003). They construct four country-level earnings management measures. The first of these, denoted EM1, is an earnings smoothing measure equal to the median value in each country of the ratio of the firm-level standard deviation of operating earnings divided by the standard deviation of cash flow from operations. Their second measure, EM2, also attempts to capture earnings smoothing behavior. EM2 equals the cross-sectional correlation in country i in year t between the change in accruals and the change in cash flows (both scaled by assets). We transform our EM1 and EM2 measures by multiplying their values by -1, so that for EM1, EM2, and all other earnings quality measures, higher values correspond to more aggressive earnings management. Thus, our earnings quality hypothesis predicts a positive coefficient on the earnings quality measures in underpricing regressions, meaning that more earnings management leads to greater information asymmetry and higher underpricing. The third measure, EM3, is the median value in each country of the absolute value of firms’ accruals scaled by the absolute value of cash flow from operations. A higher value of EM3 indicates greater earnings management. The final metric, EM4, measures loss avoidance behavior. EM4 equals the ratio of the number of firms reporting small profits over the sum of the number of firms reporting small losses and small profits. In this context, ―small‖ means a ratio of net income to assets of plus or minus one percent. The intuition for this measure is that if managers manipulate earnings to avoid showing losses, then there will be a missing probability
18
mass in the earnings distribution just to the left of breakeven, and a higher-than-expected frequency of firms reporting earnings just above zero (see Degeorge et al. 1999). Therefore, the higher is the loss avoidance ratio, the greater is the incidence of loss avoidance behavior in a given country and the more opaque are the country’s earnings figures. Finally, Leuz et al. (2003) calculate an overall earnings management figure, aggregate EM, for each country by ranking each country on each of the four earnings management measures and then taking the average ranking, where higher rankings signify more earnings management. In addition to calculating two earnings management measures that replicate measures from Leuz et al. (2003), Bhattacharya et al. (2003) construct two additional earnings quality measures that focus on aspects of earnings opacity. The first unique measure is their earnings aggressiveness measure, defined as the tendency to accelerate the recognition of gains and delay the recognition of losses. Earnings aggressiveness for country i in year t is equal to the median value of the ratio of total accruals divided by lagged assets. A higher value of this ratio implies more aggressive (and more opaque) earnings. The second unique measure is the Bhattacharya et al. earnings opacity measure. They construct a single aggregate earnings opacity measure for each country based on a ranking methodology. Specifically, deciles are constructed for each of three earnings quality measures and then the decile ranks are averaged across the three measures to arrive at an overall earnings opacity ranking for each country. Countries that earn a higher average ranking have more opaque earnings. In the regression analyses that follow, we estimate the relation between each earnings quality measure and IPO underpricing. Table 4 reports regressions that examine the relation between earnings quality and underpricing on a country-year basis. The dependent variable in the Table 4 regressions is the average IPO initial return in a given country and year. The control variables are country-year averages across all IPOs. There are 320 unique country-year combinations in our sample. The primary variables of interest in Table 4 are our aggregate EM measure in Model 1 and earnings opacity score in Model 2, where higher values are indicative of more earnings management. Our
19
earnings quality hypothesis predicts a positive relation between our earnings management measures and IPO initial returns. [Place Table 4 about here] The Table 4 results support the prediction of our earnings quality hypothesis. Average underpricing is positively related to both aggregate EM and earnings opacity. The aggregate EM coefficient in Model 1 (0.004) implies that a one standard deviation improvement in a country’s average aggregate EM measure is related to a reduction in average underpricing of 4.45 percentage points. The control variables in Table 4 are broadly consistent with expectations. The positive coefficients for IPO activity and market return are consistent with the ―hot markets‖ effect. We also find that underpricing is positively correlated with the level of protection afforded to minority shareholders (as captured by the antidirector rights index) and stock return volatility. Underpricing is negatively correlated with the index of economic freedom. To further examine the association between country-level earnings quality and IPO underpricing, in Table 5 we run pooled cross-sectional regressions of firm-level IPO underpricing on country-level measures of earnings quality and a variety of country- and firm-level controls.15 In Models 1-4, we estimate regressions with each Leuz et al. (2003) earnings measure separately. In Model 5, we consider the aggregate earnings management measure. To the extent that earnings quality is related to information asymmetry, we expect poorer earnings quality to be associated with higher underpricing, on average. [Place Table 5 about here] Recall that for EM1, EM2, EM3, EM4, and the overall AggEM variable, a higher value means more earnings management. Therefore, our earnings quality hypothesis predicts positive coefficients for all these measures of earnings quality. The results from Models 1-4 provide 15
Because underpricing is likely to be correlated across IPOs within a country and across time, we
construct two-way cluster-robust standard errors as outlined in Gow et al. (2010) for all firm-level IPO underpricing regressions.
20
support for the earnings quality hypothesis. Each of the earnings management measures enters the regression with a positive coefficient, as expected, although only two of the four coefficients are significant. When it is common practice in a country for managers to engage in activities to manipulate earnings, IPO underpricing is higher. Given the tendency of the individual earnings management variables to link to underpricing as expected, it is not surprising that, in Model 5, the aggregate EM score also indicates that poor earnings quality is associated with higher IPO underpricing. In Table 5, Models 6 and 7, we examine the influence of the Bhattacharya et al. (2003) earnings aggressiveness and earnings opacity measures on IPO underpricing. These measures are constructed such that a higher value implies more opaque earnings. Therefore, we expect positive signs in the regressions. Indeed, both coefficients are positive and significant, consistent with the hypothesis that underpricing is higher in countries where investors receive lower quality accounting information.16 Although many of the control variables in Table 5 do not show a statistically significant link to underpricing, the variables that are significant generally have the expected sign. For example, IPOs taken public after a period of high market returns or those that display greater price volatility after trading begins have higher underpricing. Consistent with Boulton et al. (2010), initial returns tend to be greater for IPOs issued in countries offering stronger protections for minority shareholders, as indicated by the positive coefficient on the antidirector rights index. As expected, equity carve outs are underpriced less than other IPOs, on average, and so are firms going public in countries with greater economic freedoms. The adjusted R-square values indicate that our models explain between 18 and 23 percent of the variation in the international underpricing cross-section. 16
If we estimate the relation between underpricing and earnings quality in the presence of country-
level fixed effects, the coefficients on the earnings quality measures are positive and significant about half the time.
21
Economically, the earnings quality effects presented in Table 5 are quite dramatic. The results in Model 5 suggest that, for a one standard deviation increase in a firm’s country-level aggregate EM measure, underpricing increases by roughly 7.8 percentage points. This increase is more than one-fifth of the sample mean initial return of 36.5 percent. As a point of reference, consider that the aggregate EM measure for the India is slightly more than one standard deviation above that of the United Kingdom. Clearly, country-level earnings quality has a considerable influence on underpricing around the world.
Robustness of country-level earnings quality and IPO underpricing In unreported regressions, we confirm that the results presented in Tables 4 and 5 are robust to a variety of alternative specifications. In particular, we attempt to eliminate concerns regarding the price stabilization activity of underwriters, which can vary across countries, minimum offer price restrictions, which screen out the smallest IPOs, and the effects of large countries, which tend to be either very transparent or very opaque. To confirm that our results are not sensitive to variations in price stabilization activity across countries, we replace the one-day initial return measure used in Table 5 with the IPO initial return measured as the percentage difference between the offer price and the secondary market closing price 22 trading days after the first trading date. The intuition for this alternative measure is that the effects of price stabilization dissipate over time, generally within a month of the IPO, as reported in Ruud (1993) and elsewhere. Thus, if price stabilization temporarily obscures the left tail of the IPO returns distribution, then our finding that lower quality earnings leads to higher underpricing might be the result of greater price support in countries with lower earnings quality. We find that measuring the initial return over a longer horizon does not fundamentally change our results. In other tests, we impose increasingly stringent restrictions on our country-level sample by imposing a minimum offer price cutoff. In particular, we exclude the bottom 2, 5, 10, and 20
22
percent of offer prices from respective country-level samples. In terms of the U.S. distribution of offer prices, these cutoffs correspond to minimums of $5, $6, $7, and $9. Increasing the minimum offer price reduces the odds of finding spurious results driven by market microstructure effects. In all cases, the results indicate that an economically and statistically significant increase in underpricing occurs when earnings quality deteriorates, and the magnitude of this effect is similar to our estimates in all prior regressions. We also exclude each of the three largest IPO markets in our sample, the U.S., the U.K, and Japan. We do this to verify that the earnings quality results are not driven exclusively by these large markets. Excluding any of these three countries, lower earnings quality is still associated with higher underpricing.
Earnings quality and the certification effect of financial intermediaries The previous section presented evidence that lower earnings quality is associated with higher underpricing. In the larger context of the IPO literature, we suggest that investors face greater uncertainty regarding the values of IPO firms when earnings quality is low. One mechanism that could mitigate this uncertainty is the presence of a reputable intermediary who, in effect, certifies the earnings of IPO firms. Carter and Manaster (1990), Megginson and Weiss (1991), and Barry et al. (1990) all report results consistent with a certification effect (i.e., lower underpricing) when firms go public with the assistance of reputable underwriters or venture capital investors.17 However, recent underpricing studies, such as Loughran and Ritter (2004), find a positive relation between underwriter quality and initial returns. Why IPOs underwritten by more prestigious investment banks are underpriced more remains an unanswered question, but in spite of this general effect, it may be possible for high quality underwriters to mitigate the effects of poor country-level earnings quality by providing a certification effect at the firm level.
17
Due to missing data, reported results do not control for venture capital backing. Unreported tests
indicate that all results are robust to controlling for venture capital backing where available.
23
Table 6 includes interactions between our top-tier underwriter variable and mean-adjusted earnings quality measures. In Model 1, the top-tier underwriter indicator variable is interacted with the mean-adjusted aggregate EM measure, while in Model 2 the interaction is with our earnings opacity measure. If top-tier underwriters certify the earnings of IPO firms and thereby reduce the uncertainty faced by investors, then we expect the interaction terms to have the opposite sign of the relevant earnings quality measure. In both regression specifications in Table 6, the coefficient on the interaction between top-tier underwriter and earnings quality is significant and takes the opposite sign of the earnings quality coefficient. [Place Table 6 about here] The coefficients on the interaction terms indicate that, the less transparent a country’s earnings, the more IPO issuers benefit from underwriter quality. To illustrate the economic significance of this result, consider an issuer in Italy, the country with the median average earnings opacity score (average earnings opacity score = 5.49). The coefficient on the interaction term in Model 2 of Table 6 is -0.069 and indicates that an Italian IPO firm using a top-tier underwriter would underprice nearly 1.13 percentage points less than a similar Italian IPO firm not using a top-tier underwriter. Considering that the average IPO listed in Italy is underpriced by 10.46 percent, this result implies that the presence of a top-tier underwriter reduces underpricing by more than 10 percent for new issues in Italy. The effect of a top-tier underwriter is even more pronounced for issuers from countries with higher average earnings opacity scores. Table 6, Model 2 indicates that a Chinese IPO-firm (average earnings opacity score = 8.03) would underprice nearly 18.66 percentage points less when using a top-tier underwriter as opposed to an underwriter not identified as top-tier. This represents a 15 percent decrease based on the average underpricing of Chinese IPOs (120.72 percent). We obtain similar results when examining the interaction between the other proxies for earnings quality and top-tier underwriters. These results are consistent with the presence of a top-tier underwriter acting as certification for new issues and are particularly important in countries with lower earnings quality.
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V. Conclusion Our primary contribution is to study how country-level differences in earnings quality influence IPO underpricing. Using a wide range of earnings quality measures, we find higher IPO underpricing in countries with poorer quality earnings information, even after controlling for many country- and deal-specific characteristics. This evidence is consistent with asymmetric information explanations for underpricing. Just as other researchers have found that poor accounting information can lead to a higher cost of capital, our evidence suggests that the cost of going public rises when investors have greater difficulties interpreting financial information. However, financial intermediaries, such as investment banks, play a role in mitigating the effects of low earnings quality on IPO underpricing.
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60.00%
1800
1600
50.00% 1400
1200
1000 30.00% 800
20.00%
Number of IPOs
Average Underpricing
40.00%
600
400 10.00% 200
0.00%
0 1998
1999
2000
2001
2002
2003
Average Underpricing
2004
2005
2006
2007
2008
Number of IPOs
Fig. 1. Average underpricing and number of IPOs by year. Bar heights show the average underpricing by year. Line points show the number of IPOs by year.
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50.00%
35.00
45.00% 30.00 40.00%
Average Underpricing
30.00% 20.00 25.00%
15.00 20.00%
15.00%
Average Aggregate EM
25.00
35.00%
10.00
10.00%
5.00 5.00%
0.00%
0.00
Lowest earnings quality quartile
Highest earnings quality quartile
Average Underpricing
Average Aggregate EM
Fig. 2. Average underpricing and average aggregate EM by earnings quality quartiles. Sample countries are sorted into quartiles based on their average aggregate EM score over the 1998-2008 sample period. Countries with the highest aggregate earnings management are in the lowest earnings quality quartile and those with the lowest aggregate earnings management are in the highest earnings quality quartile. Bar heights reflect the average underpricing across all IPOs within a quartile. Line points reflect the average aggregate EM score across all IPOs within a quartile.
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TABLE 1 Sample Construction IPO Sample Selection Procedure: (1) Pull IPOs for all countries from SDC New Issues database. (2) Drop IPOs that cannot be matched with the Datastream database. (3) Drop IPOs that do not have a valid first-day secondary market closing price. (4) Drop IPOs from countries not covered by LLSV antidirector rights index (except for IPOs from China). (5) Drop IPOs from countries for which earnings quality measures cannot be calculated for the 5 years prior to the IPO. (6) Drop IPOs with an initial return in the 1st or 99th percentile. (7) Drop IPOs from countries with less than 5 IPOs. This table presents the sample construction process for the entire sample of 10,783 IPOs listed in 37 countries.
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Number of IPOs Dropped 1,268 950 140 21 223 5
Remaining IPOs 13,390 12,122 11,172 11,032 11,011 10,788 10,783
TABLE 2 Country-level Descriptive Statistics Country Argentina Australia Austria Belgium Brazil Canada China Denmark Finland France Germany Greece Hong Kong India Indonesia Ireland Israel Italy Japan Malaysia
N 5 1,009 31 61 46 421 686 27 43 495 366 109 583 169 60 7 9 156 1,259 309
Aggregate Gross Proceeds (US$ MM) 247.73 26,659.45 7,278.92 14,515.28 16,982.60 13,138.84 58,730.82 2,341.67 6,063.64 71,490.92 59,422.92 5,272.99 79,494.15 16,974.68 5,260.06 2,735.77 251.67 50,044.99 85,327.98 5,944.56
Average Underpricing 1.43% 23.06% 6.10% 10.19% 6.17% 48.61% 120.72% 7.09% 26.14% 15.84% 36.63% 58.33% 16.69% 40.21% 39.32% 3.85% 24.28% 10.46% 55.85% 34.32%
Average EM1 -0.73 -0.74 -0.32 -0.37 -0.57 -0.60 -0.37 -0.40 -0.47 -0.39 -0.43 -0.29 -0.36 -0.47 -0.31 -0.63 -0.40 -0.28 -0.37 -0.44
Average EM2 0.78 0.81 0.94 0.93 0.90 0.88 0.96 0.89 0.91 0.97 0.95 0.90 0.96 0.98 0.95 0.95 0.94 0.93 0.94 0.91
35
Average EM3 0.48 0.47 0.69 0.66 0.51 0.51 0.70 0.57 0.46 0.58 0.64 0.63 0.75 0.45 0.83 0.42 0.70 0.67 0.63 0.78
Average EM4 0.89 0.62 0.75 0.78 0.67 0.66 0.97 0.76 0.94 0.76 0.79 0.93 0.74 0.83 0.75 0.84 0.78 0.77 0.79 0.74
Average Aggregate EM 14.60 7.46 31.44 29.75 14.17 14.13 35.87 24.12 24.01 28.55 27.68 33.17 33.08 26.71 35.26 19.75 29.94 32.13 30.37 28.51
Average Earnings Aggressiveness -0.06 -0.04 -0.06 -0.07 -0.02 -0.05 -0.01 -0.04 -0.04 -0.04 -0.06 0.01 -0.02 -0.02 -0.04 -0.03 -0.03 -0.04 -0.03 -0.02
Average Earnings Opacity 3.88 4.10 4.73 4.58 5.99 3.86 8.03 4.65 5.57 5.54 4.97 6.00 6.60 7.58 5.64 6.03 5.58 5.49 6.40 6.27
TABLE 2 – continued Country Mexico Netherlands New Zealand Norway Philippines Portugal Singapore South Africa South Korea Spain Sweden Switzerland Taiwan Thailand Turkey UK US
N 11 46 36 96 22 10 462 8 517 38 76 69 547 142 16 1,044 1,792
Aggregate Gross Proceeds (US$ MM) 3,113.55 14,118.38 2,191.18 14,112.62 1,831.36 6,242.68 14,389.05 1,082.68 21,252.00 27,860.74 17,718.82 24,351.77 10,382.86 11,492.59 3,870.52 91,006.69 325,125.95
Correlation with average underpricing: p-value
Average Underpricing 7.69% 28.48% 10.45% 3.74% 12.32% 15.95% 27.08% 8.53% 46.63% 14.76% 9.21% 11.49% 22.96% 17.31% 7.22% 17.69% 33.90%
Average EM1 -0.46 -0.42 -0.57 -0.59 -0.43 -0.28 -0.39 -0.59 -0.37 -0.36 -0.60 -0.41 -0.36 -0.41 -0.69 -0.59 -0.57
Average EM2 0.84 0.92 0.60 0.32 0.84 0.94 0.96 0.79 0.92 0.97 0.90 0.93 0.97 1.00 0.84 0.88 0.68
Average EM3 0.43 0.51 0.39 0.66 0.76 0.66 0.80 0.42 0.64 0.54 0.52 0.52 0.79 0.65 0.67 0.49 0.46
Average EM4 0.71 0.74 0.69 0.60 0.69 0.80 0.71 0.53 0.75 0.86 0.65 0.83 0.75 0.74 0.80 0.69 0.63
Average Aggregate EM 15.61 22.67 9.53 13.50 27.59 33.88 32.22 7.94 28.04 30.64 14.33 25.81 34.01 31.96 20.83 14.92 8.67
Average Earnings Aggressiveness -0.03 -0.05 -0.04 -0.06 -0.04 -0.05 -0.03 -0.04 -0.04 -0.04 -0.04 -0.05 -0.03 -0.05 0.03 -0.05 -0.04
Average Earnings Opacity 5.30 4.60 4.71 3.30 5.19 5.30 6.18 4.23 5.70 6.15 4.91 5.46 6.49 5.95 5.64 4.52 3.63
0.30 (0.075)
0.25 (0.139)
0.23 (0.177)
0.40 (0.014)
0.36 (0.030)
0.31 (0.060)
0.49 (0.002)
This table presents country-level descriptive statistics for the entire sample of 10,783 IPOs. N is the number of sample IPOs listing in the country over the 1998-2008 sample period. Aggregate gross proceeds is the sum of CPI-adjusted offer value in 2008 U.S. dollars for the country of listing. Underpricing is the first-day secondary market closing price divided by the final offer price, minus one. EM1 is the median ratio in country i of the firm-level standard deviations of operating earnings over the cash flow from operations (both scaled by lagged total assets), multiplied by -1. EM2 is the cross-sectional correlation in country i between the change in accruals and change in cash flows from operations (both scaled by lagged total assets), multiplied by -1. EM3 is the median ratio in country i of the absolute value of accruals over the absolute value of cash flow from operations. EM4 is the ratio in country i of the number of firms reporting small profits over the sum of the number of firms reporting small losses and small profits. A small profit (loss) is defined as a value of net earnings scaled by lagged total assets in the range [0, 0.01] ([-0.01, 0)). AggEM is the average country i ranking across the following four earnings management measures: EM1, EM2, EM3, and EM4. Earnings aggressiveness is the median ratio in country i of total accruals over the lagged total assets. Earnings opacity is the average country i decile ranking across the following three earnings management measures: EM2, EM4, and earnings aggressiveness. The final two rows report the correlation between the average earnings quality measure and average underpricing and the p-value from a test of the null hypothesis that the correlation is equal to zero.
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TABLE 3 IPO Sample Descriptive Statistics Variable EM1 EM2 EM3 EM4 Aggregate EM Earnings aggressiveness Earnings opacity Initial return Top-tier underwriter Price stabilization IPO activity Market return Stock market turnover ratio Index of economic freedom Antidirector rights index Offer size ratio Stock return volatility Integer offer price Bookbuilt Firm commitment Equity carve-out
N 10,783 10,783 10,783 10,783 10,783 10,783 10,783 10,783 10,783 10,783 10,783 10,783 10,783 10,783 10,783 10,783 10,708 10,783 10,198 10,707 10,699
Mean -0.480 0.876 0.592 0.728 22.388 -0.036 5.326 0.365 0.225 0.007 0.045 0.030 1.109 72.568 3.834 1.000 0.048 0.500 0.612 0.560 0.034
Std Dev 0.139 0.150 0.131 0.103 11.145 0.015 1.392 0.612 0.418 0.019 0.029 0.112 0.638 9.738 1.199 4.861 0.040 0.500 0.487 0.496 0.181
Minimum -0.844 -0.402 0.275 0.367 4.750 -0.100 2.867 -0.360 0.000 -0.074 0.001 -0.488 0.074 44.858 0.000 0.000 0.000 0.000 0.000 0.000 0.000
Maximum -0.173 1.000 0.996 1.000 45.000 0.206 8.667 3.862 1.000 0.125 0.146 1.132 2.946 91.367 5.000 351.819 1.571 1.000 1.000 1.000 1.000
This table presents descriptive statistics for the entire sample of 10,783 IPOs. EM1 is the median ratio in country i of the firm-level standard deviations of operating earnings over the cash flow from operations (both scaled by lagged total assets), multiplied by -1. EM2 is the cross-sectional correlation in country i between the change in accruals and change in cash flows from operations (both scaled by lagged total assets), multiplied by -1. EM3 is the median ratio in country i of the absolute value of accruals over the absolute value of cash flow from operations. EM4 is the ratio in country i of the number of firms reporting small profits over the sum of the number of firms reporting small losses and small profits. A small profit (loss) is defined as a value of net earnings scaled by lagged total assets in the range [0, 0.01] ([0.01, 0)). AggEM is the average country i ranking across the following four earnings management measures: EM1, EM2, EM3, and EM4. Earnings aggressiveness is the median ratio in country i of total accruals over the lagged total assets. Earnings opacity is the average country i decile ranking across the following three earnings management measures: EM2, EM4, and earnings aggressiveness. Initial return is the secondary market closing price divided by the final offer price, minus one. Top-tier is an indicator variable set to 1 for IPOs underwritten by an investment bank appearing in the top 25 of SDC’s league tables in the issue year, and zero otherwise. Price stabilization is the difference in the number of IPOs with small positive first day returns (greater than zero and less than or equal to one percent) and the number of IPOs with small negative first day returns (less than zero and greater than or equal to negative one percent) divided by the total number of IPOs issued in the country of listing. IPO activity is the ratio of the total number of IPOs in the issue year divided by the number of Datastream listed equities for the country of listing as of 2008. Market return is the return on the Datastream index for the country of listing over the three months preceding the offering. Stock market turnover ratio equals the ratio of the total value of shares traded to aggregate market capitalization and reported in Beck et al. (2000). Index of economic freedom is a product of The Heritage Foundation and The Wall Street Journal and is an aggregate measure covering the following ten freedoms: business, trade, monetary, freedom from government, fiscal, property rights, investment, financial, freedom from corruption, and labor. Antidirector rights index measures shareholder rights by considering the following issues: (1) vote by mail, (2) shares not blocked or deposited prior to shareholder meetings, (3) cumulative voting in director elections, (4) oppressed minority mechanisms, (5) pre-emptive rights to new issues, and (6) minimum capital requirements and is reported in La Porta et al. (1998) and Allen et al. (2005). Offer size ratio is the CPI-adjusted offer value in millions of U.S. dollars divided by the average of this value across all IPOs in the country of listing. Stock return volatility is the standard deviation of returns over the first 30 calendar days following the offering. Indicator variables are set equal to one for integer offer price, bookbuilt, firm commitment, and equity carve-out deals.
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TABLE 4 Country-year Underpricing Regressions on Earnings Quality Intercept Aggregate EM Earnings opacity Top-tier underwriter Price stabilization IPO activity Market return Stock market turnover ratio Index of economic freedom Antidirector rights index Offer size ratio Stock return volatility Integer offer price Bookbuilt Firm commitment Equity carve-out Adjusted R-square Number of observations
Model 1 0.392 0.004**
Model 2 0.105 0.063*** 0.064 -0.396 1.675*** 0.757*** 0.022 -0.008*** 0.026* -0.001 3.777*** 0.012 -0.077 0.005 -0.035
0.060 -0.219 1.839*** 0.740*** 0.026 -0.010*** 0.041*** 0.000 3.558*** -0.013 -0.093* 0.044 -0.016 27.64% 320
29.90% 320
This table presents OLS regressions of IPO underpricing on country-level earnings quality measures. The dependent variable is the average IPO initial return measured at the country-year level. Initial return is calculated by dividing the secondary market closing price by the final offer price, minus one. The dependent variables are averaged at the country-year level and are defined in the notes to Table 3. Regressions control for industry composition. Industry classifications reflect those reported by Dyck and Zingales (2004). Respectively, ***, **, and * denote significance of the coefficient at the 1, 5, and 10 percent level.
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TABLE 5 Underpricing Regressions on Earnings Quality Measures Intercept EM1 EM2 EM3 EM4 Aggregate EM Earnings aggressiveness Earnings opacity Top-tier underwriter Price stabilization IPO activity Market return Stock market turnover ratio Index of economic freedom Antidirector rights index Offer size ratio Stock return volatility Integer offer price Bookbuilt Firm commitment Equity carve-out Adjusted R-square Number of observations
Model 1 1.606** 0.455***
Model 2 1.293*
Model 3 1.282*
Model 4 -0.684
Model 5 1.171*
Model 6 1.526**
Model 7 0.699
0.183 0.304 1.796*** 0.007** 5.002*** 0.044 2.237 0.321 0.892*** -0.041 -0.020** 0.079** -0.001 3.949*** -0.008 -0.149 0.001 -0.045 18.43% 10,045
0.050 1.862 -0.019 0.881*** -0.043 -0.020** 0.062* -0.001 3.967*** -0.004 -0.136 0.016 -0.059** 17.95% 10,045
0.047 2.019 0.124 0.875*** -0.037 -0.021** 0.071* -0.001 4.048*** -0.002 -0.121 -0.004 -0.052* 18.05% 10,045
0.076 1.928 0.432 0.866*** -0.004 -0.011** 0.086** -0.002 3.949*** 0.035 -0.126* 0.011 -0.056** 22.54% 10,045
0.054 2.467 0.183 0.876*** -0.028 -0.020** 0.085* -0.001 4.027*** 0.004 -0.135 -0.015 -0.051* 18.60% 10,045
0.052 1.484 0.057 0.906*** -0.036 -0.018** 0.040 -0.001 3.870** -0.011 -0.093 0.000 -0.054** 19.06% 10,045
0.080** 0.066 2.573 0.139 0.868*** -0.014 -0.017** 0.069* -0.001 4.002*** 0.019 -0.109 -0.049 -0.058** 19.57% 10,045
This table presents OLS regressions of IPO underpricing on country-level earnings quality measures. The dependent variable is the IPO initial return, which is the secondary market closing price divided by the final offer price, minus one. All other variables are defined in the notes to Table 3. Regressions include industry indicators. Industry classifications reflect those reported by Dyck and Zingales (2004). Respectively, ***, **, and * denote significance of the coefficient at the 1, 5, and 10 percent level measured using two-way cluster-robust standard errors (country and issue year) as outlined in Gow et al. (2010).
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TABLE 6 Underpricing Regressions on Earnings Quality with Underwriter Certification Intercept Aggregate EM Earnings opacity Top-tier underwriter Top-tier underwriter * earnings measure Price stabilization IPO activity Market return Stock market turnover ratio Index of economic freedom Antidirector rights index Offer size ratio Stock return volatility Integer offer price Bookbuilt Firm commitment Equity carve-out Adjusted R-square Number of observations
Model 1 1.133* 0.008***
Model 2 0.590
0.042 -0.007** 2.122 0.247 0.873*** -0.041 -0.020** 0.080* -0.001 4.022*** 0.006 -0.128 -0.009 -0.047*
0.096*** 0.048 -0.069* 2.145 0.225 0.870*** -0.027 -0.016** 0.061 -0.001 4.023*** 0.022 -0.098 -0.045 -0.054*
18.86% 10,045
19.93% 10,045
This table presents OLS regressions of IPO underpricing on country-level earnings quality measures and the interaction of underwriter reputation and earnings quality. The dependent variable is the IPO initial return, which is the secondary market closing price divided by the final offer price, minus one. All other variables are defined in the notes to Table 3. Regressions include industry indicators. Industry classifications reflect those reported by Dyck and Zingales (2004). Respectively, ***, **, and * denote significance of the coefficient at the 1, 5, and 10 percent level measured using twoway cluster-robust standard errors (country and issue year) as outlined in Gow et al. (2010).
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