The Sarbanes–Oxley act and cross-listed foreign private issuers

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The Sarbanes-Oxley act and cross-listed foreign private issuers Xi Li

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Received date: 6 March 2008 Revised date: 13 May 2014 Accepted date: 22 May 2014 Cite this article as: Xi Li, The Sarbanes-Oxley act and cross-listed foreign private issuers, Journal of Accounting and Economics, http://dx.doi.org/10.1016/j. jacceco.2014.05.001 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting galley proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

The Sarbanes-Oxley Act and cross-listed foreign private issuers

Xi Li

Hong Kong University of Science and Technology Clear Water Bay, Hong Kong Phone: 1-852-2358-7560 E-mail: [email protected]

This Draft: May 14, 2014

JEL classification: G15, G18, G38, M41, M47

Keywords: Sarbanes-Oxley, Foreign private issuer, Deregistration, Corporate governance, Law and finance, Cross-listing, ADR

I am grateful for suggestions from Bill Christie, Art Durnev, Larry Fauver, Zhigang Feng, Reinier Kraakman, Jennifer Marietta-Westberg, Ronald Masulis, Giovanna Nicodano, Jordan Siegel, Jeff Sutthoff, Tracy Wang, T. J. Wong, seminar participants at the Chinese University of Hong Kong, Clark University, the Federal Reserve Board, Rutgers University, the Hong Kong University of Science and Technology, Singapore Management University, the University of Hong Kong, the 22nd Annual Conference on Finance, Economics, and Accounting, the European Corporate Governance Institute Conference at the University of Sheffield, the Finlawmetrics Conference at Bocconi University, the 2007 China International Finance Conference in Chengdu, the 2007 Conference of the Chinese Finance Association, the 2007 Conference on Empirical Legal Studies at New York University, and the University of Miami, and especially Tracy CarMichael at the British Columbia Securities Commission, Elliot Staffin at the Securities and Exchange Commission, Gennaro Bernile, Mingyi Hung, Guochang Zhang, Robert Holthausen (the editor), and an anonymous referee for helpful comments. Any errors are my responsibility.

The Sarbanes-Oxley Act and cross-listed foreign private issuers

I examine the short- and long-term impact of the 2002 Sarbanes-Oxley Act (SOX) on cross-listed foreign private issuers. Both short- and long-term test results suggest that the costs of SOX compliance significantly exceed its benefits and reduce the net benefits of cross-listings.

1. Introduction In 2002, in the wake of a series of corporate scandals, the U.S. Congress by an overwhelming majority passed the Sarbanes-Oxley Act (SOX) to strengthen corporate governance and financial reporting. SOX aims to restore investor confidence in U.S. markets, which include U.S. companies, as well as the more than 1,300 foreign private issuers (FPIs) that have reporting obligations to the Securities and Exchange Commission (SEC). Hailed as the single most important piece of legislation on corporate governance, financial disclosure, and the practice of public accounting since the Great Depression (Hitt, 2002), SOX is also one of the most controversial business laws in U.S. history. Critics deplore it as a rushed political response to high profile corporate malfeasance that creates substantial net costs for issuers (Perino, 2003).1 My paper examines the short- and long-term impact of SOX on shareholders of cross-listed FPIs. FPIs are an important component of U.S. markets, accounting for about 20 percent of the common stocks listed on the NYSE. By cross-listing in the U.S., FPIs generally gain increased visibility, prestige, and trading liquidity. At the same time, their presence enhances the status of U.S. markets as the world’s financial center. Because FPIs are usually of higher quality than other issuers in home markets, crosslistings provide an easy and inexpensive way for U.S. investors to diversify geographically. SOX appears, however, to drive FPIs away from U.S. markets.2 To assess the short-term impact of SOX, I compare the U.S. and home market stock returns of a comprehensive sample of cross-listed FPIs with the FPI-free home country index returns around 23 events related to the passage and implementation of SOX. Because SOX affects all U.S. listed issuers, U.S. stock market indexes are contaminated benchmarks for both cross-listed FPIs and U.S. issuers. To

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Various surveys of public companies indicate that the costs of compliance exceed the benefits. In addition to direct costs such as auditor expenses, indirect costs are likely to be much greater. Examples of indirect costs are distraction due to SOX compliance, exposure of proprietary information, reduction in the flexibility critical to robust growth, and overly risk-averse managers and independent directors. 2 FPIs’ varying backgrounds and potentially different mix of agency problems (as compared with diversely owned U.S. firms) likely make their compliance especially costly. Citing higher compliance costs, more FPIs go public only on home markets in the post-SOX period and many FPIs exit U.S. markets (Karmin and Lucchetti, 2006).

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construct cleaner benchmarks, I create FPI-free home country indexes using all the firms in each foreign market, which are not affected by SOX. I also exclude the home market returns of FPIs with SEC reporting obligations for the period during which they are cross-listed or over-the-counter (OTC) traded in the U.S., as these returns are highly correlated with their U.S. returns, which are affected by SOX. I find aggregate abnormal returns for cross-listed FPIs of -10% on average in the U.S. and home markets, which suggests substantial destruction in the market value of FPIs during these events. The similar results in the U.S. and home markets that differ in market structure, investor sophistication and protection, and liquidity suggest that these differences and issues such as asynchronous trading cannot explain my results. However, concerns could arise that these negative short-term market reactions are due to differences between FPIs that access U.S. markets and those that do not (e.g., size or growth opportunities), cross-sectional correlation and clustering of events, the measure of abnormal returns, or benchmark weighting schemes. Because all these concerns should affect both the event and non-event abnormal returns of a given FPI, to address them, I base my inferences on the empirical distributions and related bootstrapped p-values obtained by bootstrapping abnormal returns on non-event days during the 2002–2003 period. I find that these negative short-term reactions are significant at the 1% level. To further ensure that these reactions are due to SOX, I conduct two additional short-term tests. First, I examine the event period reactions of both a sample of OTC-traded FPIs with SOX compliance and a sample of OTC-traded FPIs exempt from SOX compliance. If the reactions of cross-listed FPIs are due to SOX, only the former type of OTC-traded FPIs should react to SOX-related events. Given that OTC-traded FPIs may have less liquid trading in the U.S., I examine both their U.S. and home market reactions. These two types of FPIs differ from cross-listed FPIs and from each other. Therefore, different reactions may not prove that the reactions of cross-listed FPIs are due to SOX. Thus, I base my inferences for both types of FPIs on their own bootstrapped abnormal returns on non-event days. I find, in both markets, significantly negative event period reactions for OTC-complying FPIs and insignificant reactions for OTC-exempt FPIs.

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Second, in cross-sectional analysis of the event period reactions of cross-listed FPIs, the reactions generally vary negatively with FPIs’ governance quality (i.e., country-level corporate and securities laws and firm-level institutional monitoring). Given SOX’s far-reaching impact on governance, this variation is expected and it provides further support that these reactions are due to SOX. Combined with the negative aggregate reactions, the generally negative relation suggests that SOX compliance is especially detrimental to better-governed FPIs. The reactions are also less negative if FPIs are more likely to go dark in the U.S.; that is, voluntarily delist and deregister to eliminate the SEC reporting obligations and in turn SOX compliance, suggesting that investors view escaping from SOX compliance favorably. Taken together, the short-term results suggest that SOX creates substantial net costs for cross-listed FPIs. As for the long-term impact of SOX, I document three results using a comprehensive sample of going-dark FPIs during the 1995–2006 period.3 First, many more FPIs go dark after the passage of SOX than in the pre-SOX period. Second, going-dark returns (i.e., abnormal returns around delisting and deregistration announcements) are negative before the passage of SOX but positive after its passage, with the difference being highly significant. Third, for the average FPI that goes dark in the post-SOX period, all FPI characteristics (e.g, governance quality and growth potentials) improve from the pre- to the postdark phase, a finding not observed in the pre-SOX period. Although the first result is not a clear test of SOX as it may be explained by reduced growth potentials, increased agency problems, or increased compliance costs due to SOX, the last two results can only be consistent with the average FPI going dark in the post-SOX period to escape costly compliance. Otherwise, I should observe lower going-dark returns as shareholders vote with their feet to escape FPIs with increased agency problems and reduced growth potentials, as well as deterioration of governance quality and growth potentials from the pre- to the post-dark phase. The last two results indicate that the net costs created by SOX may have offset the net cross-listing benefits for the average going-dark FPI.

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For brevity, unless otherwise stated, I define “going dark” as going dark in the U.S. while maintaining home market listings and reporting obligations.

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Short-term uncertainty or biases associated with short-term tests cannot explain either the longterm results or the combined results of the several short-term tests, whereas long-term global trends such as improved stock returns, liquidity, and governance in foreign markets are less likely to explain the short-term results. Overall, my short- and long-term results are consistent with each other and corroborate that SOX induces significant net costs, especially for better-governed FPIs. My paper contributes to the long-standing fundamental debate on the impact of regulation (Landis, 1938; Coase, 1960; Stigler, 1964; Becker, 1968).4 It also complements studies of SOX’s impact on U.S. issuers by examining the law’s impact on FPIs and by exploring SOX-related issues pertinent to several unique features of FPIs. In addition, it complements a few related studies of SOX’s impact on cross-listed FPIs by providing more unambiguous and consistent evidence of SOX’s negative effect. Its stronger inferences are attributable to more comprehensive and precise samples, a more thorough understanding of SEC rules on listings and registrations, and a broader set of unique features related to the impact of SOX. Further, I show that less than 20% of cross-listed FPIs have controlling shareholders. Although the broad literature on FPIs focuses on the controlling shareholder agency problems in firms with concentrated ownership, this finding suggests that future studies of FPIs should also examine the managerial agency problems in diversely owned firms. The remainder of the paper is organized as follows. Section 2 provides a comparison with the literature. Section 3 describes the data, Section 4 presents the results, and Section 5 concludes.

2. Relation to the literature Several contemporaneous studies examine SOX’s impact on cross-listed FPIs. However, their evidence yields inconclusive inferences about the impact of SOX. For short-term impact, Litvak (2007) finds significantly negative event period reactions for a sample of cross-listed FPIs during mostly preSOX events. However, Litvak finds only a weak relation between these reactions and governance 4

Evidence about the value of regulation is inconclusive. For example, evidence on the impact of mandatory disclosure requirements is mixed (see Healy and Palepu, 2001 for a review), resulting in calls to significantly modify or repeal U.S. securities market regulation (e.g., Palmiter, 1999).

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characteristics. In addition, she finds significantly negative event period reactions for her sample of OTC-exempt FPIs. The last two results make it difficult to attribute the short-term reactions of crosslisted FPIs to SOX. As for long-term impact, Marosi and Massoud (2008) find a greater number of going-dark FPIs in the post-SOX period, but no difference in going-dark returns between the pre- and post-SOX periods, making it difficult to conclude that SOX has an impact. Hostak et al. (2013) focus on the pre-dark characteristics of non-Canadian FPIs voluntarily delisted in the post-SOX period. However, the lack of comparison between pre- and post-SOX periods makes it difficult to infer SOX’s impact. My paper provides more unambiguous evidence of the detrimental impact of SOX for two reasons. The first reason is the more comprehensive and precise nature of my analysis. For the shortterm impact, my sample of cross-listed FPIs for event period reactions is 36% greater than that of Litvak (2007). In addition, Litvak (2007) includes few post-SOX implementation events in her analysis of shortterm impact. My paper includes all of the major post-SOX implementation events (12 out of 23 SOXrelated events), as well as a more comprehensive sample of pre-SOX events, as prior research emphasizes the importance of considering how law and regulation are implemented and enforced (Holthausen, 2009). In addition, my paper examines the prevalence of controlling shareholders in cross-listed and going-dark FPIs. For the long-term impact, I use evidence gathered after FPIs go dark in the U.S. and compares their pre- and post-dark characteristics to see how their behavior changes. Further, I find that more than half of the potential going-dark sample FPIs delist in home countries, become private, are acquired, or are financially distressed or liquidated within a year of U.S. delisting or deregistration. Unlike the other longterm studies, I eliminate these FPIs to obtain a more “pure” going-dark sample. If an FPI’s motivation to go dark is only to escape U.S. compliance, it does not need to take such actions in home markets so soon. However, given the proximity in time of delistings or deregistrations in the U.S. and home markets, it is difficult to tell whether the going-dark effects are due to the removal of the U.S. or home listings and registrations. Also, financial hardship may have forced FPIs to quit doing almost everything inessential to survival, including listing and registration in the U.S., and exchanges often force distressed firms to

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delist, making these delistings unlikely to be voluntary. Distressed FPIs also have few filings by the time of U.S. deregistration, making it difficult to determine whether deregistration was voluntary. The second reason is my more complete reliance on SEC rules on registrations and deregistrations in the research design. For example, the broad literature on FPIs treats all OTC-traded FPIs as exempt from SOX compliance. In reality, however, a large number of OTC-traded FPIs have to comply with SEC regulation. For example, about 35% of FPIs with SEC reporting and SOX compliance obligations are OTC-traded in 2001.5 This more nuanced understanding of SEC rules may explain the insignificant reactions that Litvak (2007) finds for OTC-traded FPIs.

As mentioned earlier, the

insignificant reactions for OTC-traded FPIs make it difficult to attribute the short-term reactions of crosslisted FPIs to SOX.6 My paper complements the literature that finds mixed evidence about the impact of SOX on U.S. issuers (Jain and Rezaee, 2006; Zhang, 2007; Li et al., 2008; Chhaochharia and Grinstein, 2007; Marosi and Massoud, 2007; Leuz et al., 2008). FPIs are an important component of U.S. markets. However, conclusions in the literature about U.S. issuers may not be directly applicable to FPIs because the more concentrated ownership structure of FPIs means that they may face a different mix of agency problems. Further, several distinct features of FPIs make them a unique entity to examine the impact of SOX: cleaner benchmarks such as FPI-free home country indexes, the availability of two more comparable OTC control samples (OTC-traded U.S. issuers are tiny in size compared with listed U.S. issuers, whereas OTC-traded FPIs are relatively more comparable in size to listed FPIs), greater precision in identifying going-dark FPIs, the availability of the U.S. and home market reactions and of post-dark data, and a richer set of cross-sectional characteristics at both firm and country levels.

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A lesser-known fact by the broad literature on FPIs is that OTC-traded FPIs do not really have U.S. listings. I find significant reactions to SOX-related events on the part of all OTC-traded FPIs, similar to the results of Litvak (2007), if I pool my samples of OTC-traded FPIs with and without SOX compliance. Also, given that OTC complying FPIs are likely to be among the largest non-cross-listed FPIs, the size-matched samples for exchangelisted FPIs in Litvak (2007) are likely to include these FPIs, which should produce smaller event period reactions in magnitude for cross-listed FPIs as in her paper. 6

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3. Data 3.1. The short-term impact of SOX: Abnormal returns around SOX-related events The first part of my analysis examines the abnormal returns of all cross-listed FPIs around SOXrelated events. I compile all legislative events before final passage of SOX from the Library of Congress’ Bill Summary & Status for the 107th Congress on H.R. 3763 and S.2673. I collect all SEC rulemaking events related to implementation of SOX provisions in the post-SOX period from the SEC website on Sarbanes-Oxley rulemaking and reports (http://www.sec.gov/spotlight/sarbanes-oxley.htm).

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The

selection of events does not involve subjective judgments. I exclude SEC rules exclusively related to auditors, lawyers, and investment companies, as well as SOX provisions for which the SEC is not required to implement rules. Table 1 provides a complete list of events and summarizes each SEC rule and the exemptions applicable to FPIs. The final sample consists of 23 events, for a total of 82 trading days. The pre-SOX event sample is similar to those used in other studies of U.S. and foreign issuers. 8 [Insert Table 1 near here] I identify Level II and Level III American Depositary Receipts (ADRs) between January 1, 1999 and December 31, 2003 with share codes between 30 and 39 from the Center for Research in Security Prices (CRSP). I identify Canadian and Israeli firms directly listed in the U.S. with Compustat country codes 9 and 49.

Combining the two samples produces the sample of cross-listed FPIs.

I obtain

information on country of incorporation from the Bank of New York Depositary Receipt Services and Compustat. Cross-checking with the SEC website yields corrections for several FPIs that incorporate in tax havens such as Bermuda. I identify OTC-complying FPIs from the SEC website. I also obtain the list

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The SEC usually first solicits comments on a proposed rule and then issues a final rule after the commenting period ends. The SEC also typically issues a press release, with a brief summary of the proposed or final rule, a few days before the official releases. Consultations with SEC staff indicate that detailed information about rules is unavailable until the official release dates. Thus, I include the dates of the press releases and official releases for both proposed and final rules. To the extent that final rules closely resemble proposed rules, or official release does not change investor expectations much relative to the press release, inclusion of all these dates only biases against finding any significant abnormal returns. 8 I include event days (0, +1) for each event. The results are similar for alternative event windows.

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of all OTC-traded FPIs from the Bank of New York Depositary Receipt Services, the OTC Bulletin Board, and the National Quotation Bureau’s Pink Sheets. For cross-listed FPIs, I obtain accounting data from Compustat, U.S. stock returns from CRSP, and home country stock returns from Datastream. For OTC-traded FPIs, I get U.S. and home country stock returns from Datastream. Specifically, I download data in U.S. dollars from Datastream for all the companies for which I can calculate at least one daily return from any country for the period between January 1, 1999 and December 31, 2003. I create an equal-weighted FPI-free home country index for each country. A total of 658 FPIs are listed in the U.S. on January 1, 2002. I require sample FPIs to have returns on all 82 event days to maintain consistency in the cross-sectional regressions. I further require that FPIs be selected from the 49 countries examined by La Porta et al. (1998) to ensure availability of country-level governance variables. This yields a final sample of 524 cross-listed FPIs with U.S. return data.9 Matching these FPIs by company name and country produces a final sample of 376 cross-listed FPIs with home country return data. Using similar requirements, I generate a final sample of 96 OTCcomplying FPIs with U.S. return data and 164 with home country return data, as well as a final sample of 603 OTC-exempt FPIs with U.S. return data and 523 with home country return data. The differences between the U.S. and home samples are due to data availability.

3.2. The short-term impact of SOX: Variables used for cross-sectional analysis The second part of the analysis examines cross-sectional variation in the event period reactions of cross-listed FPIs. The focus here is on country- and firm-level governance characteristics. I use four country-level corporate law measures from La Porta et al. (1998): Shareholder rights, which measures protection from corporate laws; Judicial efficiency, which is produced by Business International Corp. and measures law enforcement quality; Rule of law, which is produced by International Country Risk and assesses the law and order tradition; and Accounting standard, which is produced by the Center for 9

I adopt these restrictions to generate a consistent sample. The results are stronger without the restrictions.

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International Financial Analysis and Research (CIFAR) and measures disclosure quality via corporate financial reports. I take two securities law measures from La Porta et al. (2006): Public enforcement, which is an index of the characteristics and power of the main government agency supervising stock exchanges; and Disclosure standard, which is an index of disclosure requirements related to insider compensation and ownership, irregular contracts, major shareholders, prospectuses, and related-party transactions. I include two firm-level variables related to institutional monitoring: II block represents institutional blockholdings at the end of 2001 obtained from Form 20-F and proxy filings, and Analyst coverage is the number of analysts covering each issuer in 2001 from the Institutional Brokers’ Estimate System (I/B/E/S).10 For each of these variables, the larger the variable, the better the investor protection. In addition to governance characteristics, I include several control variables. Log (GDP), a common measure of country-level financial development, is the natural logarithm of average per capita gross domestic product (GDP) between 1999 and 2001 obtained from the World Bank’s World Development Indicators database (www.worldbank.org). FPIs from countries with more developed financial markets should find raising capital in home markets easier. Thus, such FPIs should be less adversely affected if SOX compliance forces them to exit U.S. markets. Non-II block is the percentage of non-institutional blockholdings, obtained from Form 20-F and proxy filings.11 Log (TA) is the natural logarithm of total assets and controls for firm size. SOX compliance is more costly for small firms if it entails a significant fixed cost. However, given the generally large size of cross-listed FPIs, this effect may not be pronounced. PPEPCT is property, plant, and equipment as a percentage of total assets, and it controls for information asymmetry. For example, a negative impact of SOX should be exacerbated by higher information asymmetry as measured by lower PPEPCT. Sales growth, one-year sales growth,

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Because I hand-collect shareholdings from Form 20-F and proxy filings, and these filings generally do not report owners of less than 5% and sometimes less than 10% of total shareholdings (especially for many Canadian issuers), the reported holdings in this paper are blockholdings. The holdings include cases in which related parties jointly possess blockholdings even if each individually owns less than 5%. 11 Non-II Block represents the control rights of both insiders and outsiders such as management, family, and multinational corporations. Using cash flow rights or excluding outsiders without board representation does not change the conclusion but would result in a lower level of reported non-institutional blockholdings.

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controls for growth opportunities. SOX compliance is likely to hurt high-growth firms by constraining financial and operational flexibility. I also include four market friction measures. Short sale, which comes from Bris et al. (2007), is an indicator variable that takes the value of one when investors cannot sell shares short in a particular country and zero otherwise. Short-sale constraints are likely to reduce negative reactions. Time zone, the absolute number of time zones separating a country’s main stock exchange from New York, controls for asynchronous trading. Illiquidity, the Amihud (2002) firm-level illiquidity measure for the U.S. market, is the average ratio of daily absolute returns to dollar trading volume on a given day (multiplied by 10 6). Synchronicity, a measure of information-based barriers proposed by Morck et al. (2000), assesses the extent to which stocks in a given country move together. No clear prediction can be made about Illiquidity or Synchronicity. For example, Illiquidity may deter large investors from investing and, therefore, hinder investor sentiment from being reflected in stock prices. However, it may also enable investors to influence stock price with less trading. Part of the cross-sectional analysis also includes the going-dark probability obtained from a probit model that I describe in Subsection 4.2. The corporate and securities law measures are independent variables. If better-governed FPIs are more likely to go dark, that would suggest that SOX is excessively costly and may be forcing out better-governed FPIs. I also include non-institutional blockholdings. If SOX is detrimental to controlling shareholders, FPIs with such shareholders would be more likely and more easily to go dark, suggesting a positive coefficient estimate for this variable. I include four additional variables, Cross-listing market cap, U.S. volume, Sales growth, and Log (TA), and expect negative coefficient estimates for all of them.

Cross-listing market cap is the market value of equity

from CRSP, which represents the market value of FPIs in the form of cross-listed shares in the U.S. divided by company market value from Compustat. Missing data are supplemented with data handcollected from Form 20-F or proxy filings. U.S. volume is U.S. dollar trading volume as a proportion of FPIs’ total trading volume in 2001. Negative coefficient estimates on the first three of the four variables would underscore the importance of U.S. markets to cross-listed FPIs. Because smaller firms can more

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easily go dark according to the SEC deregistration regulation, I expect a negative coefficient estimate on Log (TA).

3.3. The long-term impact of SOX: The going-dark sample To obtain the list of cross-listed FPIs that went dark over the 12-year sample period (1995–2006), I first compile all cross-listed FPIs between January 1995 and December 2005 using CRSP and Compustat.12 The sample ends in 2005 to allow time for FPIs to deregister, because meeting the asset and shareholder requirements for deregistration usually takes some time after delisting even if FPIs intend to deregister sooner. In addition, an investigation of post-dark FPI characteristics requires several post-dark years. After I exclude cross-listed FPIs that delist due to mergers, bankruptcies, or liquidations according to CRSP delisting codes, I identify 141 FPIs that could have delisted voluntarily. Requiring sample FPIs to have filed Form 15 to deregister by the end of 2006 eliminates 12 FPIs. 13 I determine the earliest dates of delisting and deregistration announcements from press releases and newswire announcements, as documented by ProQuest and Factiva, or from SEC filings such as Form 6K and proxy statements. Examination of these documents reveals that many FPIs announce their intention to delist and deregister before the official delisting and deregistration dates. Examining these documents also eliminates 67 FPIs that delist in home countries, become private, are acquired, or are liquidated within a year of either official U.S. delisting or deregistration. I further eliminate six FPIs whose stock price is less than one unit of the home country currency at the time of announcement due to likely financial distress. These 73 eliminations (67 + 6) are an important distinction from Hostak et al. (2013) and Leuz et al. (2008). I exclude four more FPIs due to lack of return data. I obtain the home market stock returns for the final sample of 52 going-dark FPIs from Datastream.14

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Although OTC-complying FPIs can also go dark, I focus on the FPIs once listed on U.S. stock exchanges, due to data availability. 13 For FPIs that filed multiple Form 15s, I use the date of first filing. 14 The relatively small number of going-dark FPIs is consistent with the claim that exiting from U.S. reporting obligations is difficult for FPIs.

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Going-dark FPIs are unique in that they continue to report to home country securities authorities, which allows me to obtain and compare their pre- and post-dark characteristics. I include five variables based on company financials in the six fiscal years around the going-dark fiscal year, from Worldscope, Form 20-F, or annual report filings.15 Tobin’s Q, a common measure of valuation, is the sum of total assets and market value of equity minus book equity, divided by total assets. Sales growth is the most recent year’s sales growth and proxies for growth opportunities. ROA is earnings before interest, taxes, depreciation, and amortization (EBITDA) divided by total assets, and ROE is EBITDA net of interest expenses and preferred dividends and then divided by book equity. Both proxy for operating performance. Following Leuz et al. (2008), Earnings management, a measure of earnings quality, is the absolute value of accruals divided by the absolute value of operating cash flows.

I also include three board

characteristics and three blockholder variables obtained from Form 20-F or proxy filings, all drawn from the year before and the third year after going dark. Board size is the number of directors; Non-executive directors is the proportion of non-executive directors; and Independent chairman is an indicator for FPIs whose chairman is not also the chief executive officer (CEO). I also include Largest holding, the holding by the largest blockholder, as well as II block and Non-II block. I include four analyst forecast-related characteristics from I/B/E/S, based on the 24 months of data around the going-dark months.

Forecast dispersion is the 12-month average of the standard

deviation of analysts’ earnings forecasts. Forecast error is the absolute value of the 12-month average of actual earnings minus the median analyst forecast. Forecast dispersion and Forecast error are both deflated by the stock price at the beginning of the fiscal year. Revision volatility is the standard deviation of 12 monthly forecast revisions. Revisions are the current-month median forecast minus the previousmonth median forecast. Analyst coverage is the number of analysts covering a given FPI. Following Lesmond et al. (1999), Liquidity is the proportion of days with zero returns during the 24 months surrounding the going-dark months. The data requirements for company financials and governance

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I use fiscal years 2005–2007 (2006–2007) as the post-dark years for FPIs that deregister in 2005 (2006) due to sample size concerns.

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quality over several years further reduce the sample by three FPIs, which disappear from home country registrations less than two years after going dark.

3.4. Summary statistics Table 2 reports summary statistics by country for the sample of cross-listed FPIs in the analysis of SOX’s short-term impact. Panel A of Table 2 reports the mean and standard deviation of the measures of corporate and securities laws from La Porta et al. (1998, 2006) across all sample FPIs. For brevity, I do not reproduce these measures by country here. Panel B reports the mean of the rest of the variables across the firms within a country and for the whole sample. The sample FPIs are from 36 countries. Canada (139 FPIs), Israel (69), and the United Kingdom (66) have far more FPIs than any other country, as the country with the fourth-highest number of FPIs is France (23 FPIs). The sample FPIs are geographically diverse and somewhat diverse in legal origin, according to the classifications of La Porta et al. (1998). Prior studies have used some of these variables, but a few summary statistics are worth noting. Although approximately 17% (6 out of 36) of the sample countries have short-sale constraints, few sample FPIs (3%) are from those countries. About 44% of the total market cap and 31% of the total trading volume of sample FPIs are in the U.S., underscoring the importance of U.S. markets to these FPIs. Although controlling shareholders is prevalent in some foreign countries, average Non-II block for cross-listed FPIs is only about 9%. [Insert Table 2 near here] Given the paucity of comprehensive studies of the presence of controlling shareholders in FPIs after cross-listings, Panel C presents the distribution of non-institutional (non-II) blockholdings for all cross-listed FPIs in 2001 and for going-dark FPIs in the 1995–2006 period. The first two columns break down the distribution of non-II blockholdings for the 490 cross-listed FPIs used in cross-sectional analysis. Non-II blockholders are absent in 387 FPIs, and they own more than 20% in only 63, or 12.9% (= 63 / 490), of my sample FPIs. Although prior studies of FPIs in general have focused only on the controlling shareholder agency problem in firms with concentrated ownership, these results suggest that

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future studies of FPIs should also consider the managerial agency problem in diversely owned firms. Thus, I use agency problems to refer to both managerial and controlling shareholder agency problems throughout the rest of the paper unless otherwise specified. La Porta et al. (1998), by contrast, document an average ownership share of more than 45% on the part of the three largest owners in the ten largest non-financial domestic firms across 49 countries. The difference between my findings and theirs could be due to different sample periods or self-selection of FPIs (i.e., more diversely owned FPIs are more likely to cross-list, and FPIs reduce ownership concentration after cross-listing). Columns 3–6 present the distribution of non-II blockholdings for the FPIs that go dark in the preand post-SOX periods. About 36% and 21% of going-dark FPIs have no non-II blockholdings in the preand post-SOX period, respectively, whereas about 55% and 63% of going-dark FPIs have total non-II blockholdings of greater than 20%.

The higher proportion of going-dark FPIs with sizable non-II

blockholdings than in the all-FPI sample suggests that controlling shareholders may play a significant role in going-dark decisions, as FPIs with large non-II blockholdings are unlikely to have gone dark without these blockholders’ consent. The proportion of going-dark FPIs with controlling shareholders is not significantly different in the pre- and post-SOX periods at conventional levels. Further, the lack of substantial non-II blockholdings in many going-dark FPIs suggests that escaping from minority shareholder protections, even if sometimes present, may not be the only reason FPIs go dark.

4. Tests and results 4.1. The short-term impact of SOX: Abnormal returns around SOX-related events This subsection examines the aggregate abnormal returns of a sample of cross-listed FPIs surrounding SOX-related events. Following Brown and Warner (1985), I measure abnormal returns with market model adjusted returns as follows: Ai,t = Ri,t — αi — Ei Rm,t,

(1)

14

where Rm,t is the day t return on the benchmark index, and αi and Ei are ordinary least squares estimates of the market model estimation for the period between January 1, 1999 and December 31, 2001. Also, following the suggestion of Brown and Warner (1985), I use equal-weighted FPI-free home country indexes as benchmarks. While I provide the Brown and Warner (1985) t-statistic, I use bootstrapped pvalues for inferences following Lo (2003) and Zhang (2007). Specifically, I draw non-event days over the 2002–2003 period equal in number to the duration of each event and calculate the cumulative abnormal returns on these non-event days. I repeat the drawing with replacement 10,000 times to obtain an empirical distribution for the event period abnormal returns. The one-tailed p-values are the proportion of the 10,000 abnormal returns drawn from non-event days that are greater than the event period abnormal returns. I double these proportions to obtain two-tailed p-values. To track the development of SOX-related events, I divide them into three groups: pre-SOX events (Events 111), SEC proposed rule events (Events 12, 13, and 15–18), and SEC final rule events (Events 14 and 19–23). For brevity, the following discussion focuses on the aggregate abnormal returns and on the abnormal returns of the three groups of events. 16 The trading periods for the U.S. and home markets are asynchronous for many FPIs. For example, when a SOX-related event is announced in the U.S., markets outside of the Americas are likely to respond to the news the next trading day, given their brief overlap in hours of operation, if at all, with U.S. markets. Asynchronous trading can be a problem in calculating U.S. abnormal returns for FPIs from countries outside of the Americas because the benchmark is FPI-free home country index. Thus, I match the U.S. returns of FPIs from the Americas on a given day with same-day FPI-free home country index returns and those of FPIs from other regions with next-day home country index returns.17

16

I do not interpret the abnormal return of each event for two reasons. First, because the reaction to any event is likely to build on reactions to previous events, which in turn represents accumulated investor expectations up to the previous event, the reaction to any event says nothing about SOX-related legislation and implementation associated with the event. Second, selecting and interpreting events on the basis of anecdotal evidence can be arbitrary and controversial, and aggregate abnormal returns are much more important. 17 Matching in different ways or adding up to three-day leading and lagging benchmark returns to Eq. (1) yields similar results.

15

Table 3 reports cumulative abnormal returns around SOX-related events for cross-listed FPIs in both the U.S. and home markets. It suggests a large and negative impact of SOX on cross-listed FPIs. The aggregate abnormal return is -9.63% for the U.S. sample of 524 cross-listed FPIs and -12.97% for the home sample of 376 cross-listed FPIs. Tracking the development of SOX-related events, the abnormal returns for pre-SOX legislative events are -9.55% and -11.05% in the U.S. and home markets, respectively, which suggests extreme investor pessimism about the significant costs imposed on FPIs by SOX. The abnormal returns for events related to the SEC’s proposed rules are 3.59% and 2.11% in the U.S. and home market, respectively. The modest price rebounds in both markets indicate that the rules proposed by the SEC to implement SOX provisions raised some hope among investors that the SEC would be able to reduce certain costly SOX compliance requirements, moderating the damage caused by the passage of SOX. Most of the optimism fizzled, however, as the final releases of SEC rules yield abnormal returns of -3.67% and -4.04% in the U.S. and home market, respectively. The abnormal returns are all significant at the 1% level, according to both Brown and Warner t-statistics and the bootstrapped abnormal returns from the non-event period. 18 The proportion of the sample with negative reactions suggests that the results are not due to outliers.19 [Insert Table 3 near here] These results are in line with the large negative abnormal returns for U.S. companies during events mostly leading up to the passage of SOX documented in Zhang (2007). Her sample events with significant reactions for U.S. issuers are roughly equivalent to Events 8–10 in my sample. Except for the insignificant reaction of Event 10, Events 8 and 9 are among my sample events with the largest reactions.

18

In untabulated results, signed tests and signed rank tests on median abnormal returns, as well as binomial tests with the null hypothesis that the proportion of negative abnormal returns is 0.5, yield similar results. 19 Including only proposed rule events or only press release events for the post-SOX implementation events yields similar results. Although the U.S. stock market indexes are contaminated benchmarks, I include them in the market model estimation in addition to the FPI-free home country indexes, given that they are likely to affect the stock returns of cross-listed FPIs to some extent. Either way, the conclusions are the same in untabulated results.

16

Unlike Zhang’s results, however, the large number of events with large and significant abnormal returns suggests that the impact of SOX on cross-listed FPIs is not driven by a small number of events.20 The signs and significance are similar for the abnormal returns in the U.S. and home markets across most individual events, with only Event 1 having different signs for its insignificant reactions. At first glance, the aggregate abnormal returns in the U.S. markets seem to be smaller in magnitude. This difference is due to the relatively less negative reactions of U.S. sample FPIs without home market returns. In untabulated results, the aggregate U.S. abnormal return of these FPIs is -4.45%, whereas that of the other FPIs is -11.67%.21 The magnitude of aggregate U.S. abnormal returns for the 376 FPIs with both U.S. and home market returns is only 1.30% smaller [= -12.97% – (-11.67%)], and this difference is statistically insignificant. Because OTC-traded FPIs with SEC reporting obligations must comply with SOX and the OTCtraded FPIs without SEC reporting obligations are exempt from SOX compliance, SOX-related events should affect the returns of the first group in ways consistent with those of cross-listed FPIs but should not affect the returns of the second group. I therefore examine OTC-complying FPIs and OTC-exempt FPIs. Panel A of Table 4 shows the abnormal returns of OTC-complying FPIs as -5.45% and -5.17% in the U.S. and home market, respectively, both statistically significant at the 1% level according to bootstrapped p-values. In addition, the abnormal returns of FPIs without SOX compliance are -1.02% and -1.26% in the U.S. and home market, respectively, both statistically insignificant. The significantly negative reactions of OTC-complying FPIs and the little reactions of OTC-exempt FPIs to SOX-related events both support the conclusion that the significantly negative abnormal returns of cross-listed FPIs are due to SOX compliance.22

20

Zhang (2007) finds four events with large and significant abnormal returns among her 17 sample events spanning from January to July 2002. 21 Compared with other cross-listed FPIs, the FPIs that are in the U.S. but not the home country sample are much smaller. Their average total assets are $212 million, compared with $2.3 billion for other cross-listed FPIs. 22 The abnormal return differences between cross-listed and OTC-exempt FPIs, and between OTC-complying and OTC-exempt FPIs, are significant at the 1% level. The much smaller magnitude of abnormal returns for OTCcomplying FPIs in comparison with cross-listed FPIs may be due to the smaller firm size of OTC-complying FPIs. It would be much easier for the smaller OTC-complying FPIs to go dark as stipulated by the SEC deregistration

17

[Insert Table 4 near here]

4.1.1.Additional tests on abnormal returns around SOX-related events I conduct robustness tests of inferences about the event period reactions of cross-listed FPIs. For brevity, I report only the aggregate abnormal returns across all 23 events. First, I create 36 equalweighted country portfolios, using sample FPIs within each country, and evaluate their abnormal returns. This approach adjusts for within-country cross-sectional correlation. The first row of Table 4, Panel B shows that these abnormal returns are negative and significant at the 1% level in both the U.S. and home markets.23 The second row of Panel B reports the results after excluding any Datastream daily return for cross-listed FPIs that exceeds 25% in absolute value, following Morck et al. (2000). I recreate the FPIfree home country index returns by trimming all the returns from Datastream. For consistency, because CRSP data also contain large daily returns, I trim the U.S. stock returns of cross-listed FPIs from CRSP. The results are similar to those in Table 3. Using other trimming thresholds does not affect the results. Thus, return outliers are unlikely to drive the results. Directly listed Canadian and Israeli FPIs account for about 40% of the sample. Such FPIs could behave differently from ADRs (e.g., the SEC historically has given more exemptions to Canadian FPIs). The third row shows that my conclusions are robust to excluding these FPIs. I also use Morgan Stanley Capital International (MSCI) country indexes as benchmarks. The drawbacks of MSCI indexes are that they are value-weighted and that their inclusion of FPIs subject to SOX compliance makes them contaminated benchmarks for my purposes. However, these drawbacks allow for addressing concerns

regulation. Investors may also expect some SOX provisions to be implemented with a delay or exempted for the smaller OTC-complying FPIs. 23 The abnormal returns are smaller in magnitude for country portfolios than those for Table 3. The difference is likely to result from the fact that the country portfolio analysis in Table 4 gives equal weight of 1/36 to each country portfolio and, thus, a weight of 1/(36N) to each stock in a country with N stocks. This weighting scheme means that FPIs from countries with a larger number of cross-listing would have a much lower weight than FPIs from countries with a smaller number of cross-listings. In comparison, each FPI is given an equal weight in the FPIlevel analysis in Table 3. Because Table 2 shows that more FPIs are from countries with better governance and Table 5 reports that FPIs from countries with better governance have significantly more negative abnormal returns during SOX-related events, the country portfolio analysis effectively gives less weight to FPIs with more negative abnormal returns, thus reducing the magnitude of observed abnormal returns.

18

related to benchmark-weighting schemes and for estimating the lower bound of the magnitude of abnormal returns.

The fourth row reports that the abnormal returns are still highly significant.

Unsurprisingly, the magnitude of the abnormal returns is smaller than that in Table 3.24 The fifth row shows that when I use market-adjusted returns, Ai,t = Ri,t — Rm,t, to measure abnormal performance, the conclusions are not affected. The sixth row shows the results when I also use the cross section of market-adjusted returns during the event period, instead of those of the estimation period, to estimate its variance. Brown and Warner (1985) recommend using this procedure to control for potential variance increases during the event period. Because this procedure ignores the estimation period data, it has weaker power if variance does not increase substantially. Nonetheless, the abnormal returns are still significant at the 1% level. Many other countries have also conducted legislative or code reforms of corporate governance. These reforms are generally in the spirit of SOX but more limited in scope. 25 Few legislative reforms elsewhere overlap with SOX-related events. In untabulated results, I find qualitatively the same results by excluding cross-listed FPIs on the days of their home reforms. Overall, my results hold for various robustness checks.

4.2. The short-term impact of SOX: Cross-sectional analysis Given my finding in Subsection 4.1 that SOX has a detrimental effect on cross-listed FPIs, exploring which firms are more affected can be interesting.

Given SOX’s far-reaching impact on

governance, if the abnormal returns around SOX-related events are attributable to SOX, I expect them to have significant relation with the firm-specific and country-level governance characteristics discussed in Subsection 3.2. I, however, have no prediction about the sign of the relation for a specific characteristic.

24

Although MSCI country indexes are supposed to include about 85% free float-adjusted market capitalization in a country, gauging whether MSCI offers more far-reaching coverage of international stock markets than Datastream is difficult. 25 See Appendix 2 of Li (2011) for details.

19

A positive (negative) sign for a characteristic would suggest that SOX has a relatively less detrimental impact on better-governed (worse-governed) FPIs along the dimension of that characteristic. Anecdotal evidence suggests that better-governed FPIs suffer more from SOX. When Congress first introduced SOX in 2002, foreign companies and governments expressed grave concern about its application to cross-listed FPIs on the grounds that it could contradict or interfere with FPIs’ home country regulation and substantially increase the cost of U.S. listings. Western European countries, which generally enjoy better governance, expressed the strongest resistance. Despite these objections, Congress granted the SEC only limited power to accommodate FPIs’ home country requirements. In Table 5, Panel A reports the results of cross-sectional analysis of the abnormal returns of individual FPIs on the 82 event days. I cluster standard errors within countries.26 Given the different scales of independent variables, I focus on a variable’s marginal effect, calculated as its coefficient estimate in Panel A of Table 5 multiplied by its standard deviation in Table 2, in my interpretation of the results. Marginal effects measure the percentage point change in abnormal returns given a one-standard deviation increase in a variable of interest. [Insert Table 5 near here] My discussion first focuses on the significant variables for U.S. abnormal returns in column (1), and then compares them to those for the home country abnormal returns in column (2). Three corporate law measures have highly significant impacts on the U.S. abnormal returns. Shareholder rights has a coefficient estimate of 5.31. Given a standard deviation of 1.37, its marginal effect is 7.27% (= 5.31 * 1.37%). Similarly, Judicial efficiency and Rule of law have marginal effects of -3.99% and -9.28%, respectively. Both securities law measures and both institutional monitoring measures have significant impacts on the U.S. abnormal returns. Public enforcement and Disclosure standard have marginal effects

26

Additional analysis using bootstrapped p-values to gauge the significance level yields similar results.

20

of -0.07% and -5.67%, respectively.27 II block and Analyst coverage have marginal effects of -0.30% and -2.61%, respectively. The significant relation between the governance measures and the event period reactions of crosslisted FPIs are consistent with the idea that these event period reactions are attributable to SOX. All the significant governance measures are negatively related to abnormal returns except for Shareholder rights, which suggests that SOX is more detrimental or less beneficial for better-governed FPIs. When combined with the substantial decline in the market value of cross-listed FPIs, this generally negative relation suggests that SOX is more detrimental for better-governed FPIs. My results suggest that combined with existing regulatory and firm-level governance mechanisms in the U.S. and in home countries, these new measures related to SOX are likely to have pushed the level of investor protection beyond the optimum. The coefficient estimates on the going-dark probability are positive and significant at the 10% level, which suggests that SOX imposes excessive costs and that FPIs that are more likely to go dark may be able to avoid these costs. Non-II block has a negative effect, which is likely due to SOX targeting managerial agency problems in diversely owned U.S. issuers and thus producing less effective and more costly solutions for cross-listed FPIs with relatively more controlling shareholder agency problems. The results of governance-related variables shown in Column 2 for home market abnormal returns are similar to those for U.S. abnormal returns. Specifically, the differences are that disclosure standard is insignificant, that Rule of law and Analyst coverage are less significant, and that Judicial efficiency is more significant. Further, the statistically significant control variables are largely the same in Columns 1 and 2, and they have the expected signs. Financial development and short-sales restrictions reduce the negative event period reactions, and firms with greater information asymmetry and growth opportunity experience more negative event period reactions.28

27

Because the governance variables are correlated, I also examine them individually. The results are similar, except that the coefficient estimate on Accounting standard is negative and significant at the 10% level. 28 Because only 3% of the sample FPIs is from countries with short-sale constraints, the economic significance of short-sale constraints is much smaller than the magnitude of this coefficient estimate suggests. The insignificant impact of Time zone suggests that asynchronous trading between the U.S. and home markets should not affect the results of U.S. abnormal returns in Subsection 4.1.

21

I obtain the going-dark probability used in Panel A with a probit model whose dependent variable is an indicator that equals one for the 24 FPIs and the 18 FPIs with available data for my U.S. and home sample, respectively, that go dark by the end of 2006 and zero otherwise. In addition to producing the going-dark probability, this analysis yields some inferences about the determinants of FPIs’ going-dark decisions. Panel B of Table 5 reports that all the statistically significant independent variables have coefficient estimates with predicted signs.

Specifically, Accounting standard and non-institutional

blockholdings have positive coefficient estimates, and Cross-listing market cap, Sales growth, and Log (TA) have negative coefficient estimates.

Thus, firms with better accounting standard and more

controlling shareholdings are more likely to go dark, and firms relying more on U.S. capital markets are less likely to go bark. Overall, the results in this subsection suggest that SOX is more detrimental to better-governed FPIs.

4.3. The long-term impact of SOX: Delisting and deregistration of cross-listed FPIs that go dark This subsection examines firms’ and shareholders’ long-term responses in the years following the passage of SOX. It compares across the pre- and post-SOX periods the number of going-dark FPIs, their going-dark returns, and their characteristics such as governance, growth, and performance to determine whether SOX increases the cost of compliance substantially. The top half of Table 6, Panel A reports the annual number of going-dark FPIs that delist or deregister. During the three and a half years leading up to the passage of SOX, 12 FPIs delist and 11 FPIs deregister voluntarily. By comparison, 38 FPIs delist and 40 deregister voluntarily in the three and a half years after passage. The substantial post-SOX increase in going-dark FPIs is consistent with the findings of Leuz et al. (2008) and Marosi and Massoud (2008). More FPIs decide to leave the U.S. market and regulatory regime after the passage of SOX. [Insert Table 6 near here] The growing number of going-dark FPIs is unlikely due to an increase in either total listings or delistings. The lower half of Table 6, Panel A presents annual numbers of new listings and delistings, as

22

well as annual totals of cross-listed FPIs. Both delistings and total listings have declined after 2002. Meanwhile, going-dark FPIs as a percentage of delistings and of total listings increase in the post-SOX period, as shown in the top half of Table 6, Panel A. Further, new listings declined substantially in the post-SOX period. The 3.5-year periods preceding and following the passage of SOX have 292 and 156 new listings, respectively. Although listings and delistings may be affected by other factors, the overall evidence suggests that they are not driving the increase in going-dark FPIs in the post-SOX period. The increase in going-dark FPIs in the post-SOX period cannot in itself reveal anything about the impact of SOX, due to possible alternative explanations discussed below. Thus, I further examine the going-dark returns and changes in FPI characteristics from the pre- to the post-dark phase. Those characteristics fall into the categories of operating performance, earnings and governance quality, institutional environment, liquidity, growth opportunities, and valuation. The increase in going-dark FPIs in the post-SOX period could be due to more reduced growth potentials, more severe agency problems, or increased compliance costs due to SOX (Leuz et al., 2008). Compared with the pre-SOX period, if the explanation for FPIs going dark is increased compliance costs, I would predict both (1) relatively higher going-dark returns as FPIs escape costly compliance, and (2) similar or improved changes in all FPI characteristics from the pre- to the post-dark phase during the postSOX period. In comparison, if the explanation for FPIs going dark is more reduced growth potentials, I would predict relatively lower going-dark returns as investors realize that future growth will be more subdued and worse changes in post-dark growth potentials but similar or improved changes in other FPI characteristics in the post-SOX period. If increased agency problems is the explanation, I would predict relatively lower going-dark returns as (minority) shareholders vote with their feet for fear of exploitation, worse changes in post-dark governance characteristics, and similar or improved post-dark changes in other characteristics in the post-SOX period. Evidence from any of the above tests could be relatively weak because small samples do not allow controls for other effects with multivariate regressions and these are not mutually exclusive

23

explanations. However, if the results from these largely independent tests are highly consistent with one explanation, I may be able to draw stronger inferences. Panel B of Table 6 reports the value-weighted home market returns of going-dark FPIs at the delisting and deregistration announcements, adjusted by the returns of the respective MSCI home country indexes using a market model. The estimation period is the (-510, -11) event day window. The panel reports results for the periods before and after July 30, 2002, the date of SOX’s final passage. It also provides the number of observations with positive abnormal returns. I examine both delisting and deregistration abnormal returns because at the time of delisting announcements investors may expect going-dark FPIs to eventually deregister. FPIs also frequently announce their intention to deregister at the time of delisting. For 25 sample FPIs, the delisting and deregistration dates are separated by at least a month. I use home market returns because they are free of issues such as asynchronous trading and because FPIs are rarely traded in the U.S. after deregistration due to the lack of Rule 12g3-2(b) exemption (see Appendix A for details). Also, trading in the U.S. is usually limited prior to going dark. Most FPIs cite limited trading and liquidity in U.S. markets as the main reasons to go dark. Panel B shows that the delisting and deregistration abnormal returns of going-dark FPIs are both negative in the pre-SOX period. The same returns in the post-SOX period are not only relatively higher than those in the pre-SOX period, but they are also positive. The abnormal returns are large in magnitude but generally statistically insignificant, possibly due to the small sample size. Tests indicate that the differences between abnormal returns in the pre- and post-SOX periods are significant at the 5% level. The number of positive abnormal returns for delistings (deregistrations) is three and 24 (three and 26) for the pre- and post-SOX period, respectively. Given that about half of my sample has different delisting and deregistration dates, my results are consistent with Leuz et al. (2008), who show that delistings and deregistrations are separate events. In untabulated results, I find similar results for different event windows around the announcement dates. Thus, the results for going-dark returns are consistent with the explanation of increased compliance costs due to SOX.

24

Panel C of Table 6 reports the median characteristics of FPIs before and after they go dark, as well as changes in these characteristics. To formally gauge the impact of SOX, Column 7 reports the significance level of the difference between changes in FPI characteristics from the pre- to the post-dark phase in the pre-SOX period in Column 3 and those in the post-SOX period in Column 6. Relative to going-dark FPIs in the pre-SOX period, those in the post-SOX period exhibit a larger reduction in noninstitutional blockholdings, forecast dispersion, and revision volatility, a greater increase in ROA, ROE, and Tobin’s Q, a smaller increase in earnings management, and a smaller reduction in liquidity from the pre- to the post-dark phase. Thus, going-dark FPIs in the post-SOX period exhibit more favorable changes on many dimensions.29 These results are consistent with the explanation of increased compliance costs due to SOX. To further gauge the impact of SOX, I compare the pre-dark characteristics of going-dark FPIs in the pre- and post-SOX periods (Column 1 versus Column 4). Better pre-dark characteristics in the postSOX period would be consistent with increased compliance costs, not the two alternative explanations (more reduced growth potentials or more severe agency problems). This is the case for every pre-dark characteristic that is significantly different between the pre- and post-SOX periods as reported in Column 8 of Table 6: relatively better sales growth and operating performance, smaller magnitude of the largest blockholdings, forecast errors, forecast dispersion, and greater magnitude of institutional blockholdings. These characteristics show no sign of either reduced growth potentials or agency problems in the pre-dark phase during the post-SOX period.

29

Although going-dark FPIs in the post-SOX period exhibit a smaller reduction in forecast errors and a smaller increase in growth opportunities, it is likely that these FPIs already have far superior growth opportunities and smaller forecast errors before going dark, leaving less room for further improvement. For example, the forecast errors of going-dark FPIs in the post-SOX period drop from about 0.27 to 0.18 between the pre- and post-dark periods, and those in the pre-SOX period drop from about 0.69 to 0.24. After a much deeper drop from a much higher level of forecast errors, going-dark FPIs in the pre-SOX period still exhibit much larger forecast errors than going-dark FPIs in the post-SOX period during the post-dark phase. For sales, in the pre-SOX period, after a steep pre-dark decline of about 34%, a 35% post-dark sharp increase would still not help fully recover the pre-dark decline in sales for going-dark FPIs. In contrast, the post-SOX period witnesses a mild pre-dark increase in sales for goingdark FPIs, and the increase experiences a substantial post-dark acceleration.

25

As a robustness check, I examine a sample that includes FPIs distressed at delisting but deregistered through the voluntary conditions. The untabulated results, including six additional such FPIs with available data, are qualitatively the same. In summary, the results suggest not only that SOX imposes net costs on shareholders in goingdark FPIs, but also that the net costs more than offset the extant net benefits from cross-listing for these FPIs.30 Although the evidence from any single test is relatively weak, the consistent results of all the independent tests jointly provide stronger inferences.

5. Conclusion I examine the short- and long-term impact of the Sarbanes-Oxley Act on cross-listed FPIs. Both short- and long-term results suggest that the costs of SOX compliance significantly exceed its benefits and reduce the net benefits of cross-listings. The results also suggest a need to consider both managerial and controlling shareholder agency problems in the studies of cross-listings.

30

Due to the small sample size, I conduct t-tests on mean abnormal returns, signed tests, and signed rank tests on median abnormal returns and binomial tests with the null hypothesis that the proportion of negative abnormal returns is 0.5. All the results in this subsection are similar. Although it is ideal to use cross-sectional regressions to control for other FPI characteristics, I find insignificant difference for most FPI characteristics examined above, probably due to the small sample size.

26

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Li, H., Pincus, M., Rego, S., 2008. Market reaction to events surrounding the Sarbanes-Oxley Act of 2002. J. of Law and Econ. 51, 111–134. Li, X., 2011. An examination of the impact of the Sarbanes-Oxley Act on cross-listed foreign private issuers and the legal bonding hypothesis. Working paper. Litvak, K., 2007. The effect of the Sarbanes-Oxley Act on non–US companies cross-listed in the U.S. J. of Corp. Financ. 13, 195–228. Lo, K., 2003. Economic consequences of regulated changes in disclosure: The case of executive compensation. J. of Account. and Econ. 35, 285–314. Marosi, A., Massoud, N., 2007. Why do firms go dark? J. of Financ. and Quant. Anal. 42, 421–442. Marosi, A., Massoud, N., 2008. “You can enter but you cannot leave…”: U.S. securities markets and foreign firm. J. of Financ. 63, 2477–2506. Morck, R., Yeung, B., Yu, W., 2000. The information content of stock markets: Why do emerging markets have synchronous stock price movement. J. of Financ. Econ. 58, 215–260. Palmiter, A., 1999. Toward disclosure choice in securities offerings. Columbia Bus. Law Rev. 1, 1–135. Perino, M., 2003. American corporate reform abroad: Sarbanes-Oxley and the foreign private issuer. European Bus. Organ. Law Rev. 4, 213–244. Stigler, G., 1964. Public regulation of the securities market. J. of Bus. 37, 117–142. Zhang, X., 2007. Economic consequences of the Sarbanes-Oxley Act of 2002. J. of Account. and Econ. 44, 74–115.

28

Appendix A. How do FPIs acquire SEC reporting obligations and how can they go dark? U.S. and foreign issuers listed or traded in the U.S. markets are required to comply with SOX provisions if they have Section 13(a) reporting obligations to the SEC. Under the current rules, an issuer attains Section 13(a) reporting obligations mainly by 1) listing on national securities exchanges and registering the securities under Section 12(b); 2) registering a class of equity securities under Section 12(g) either voluntarily or because it has 500 or more record holders and more than $10 million in total assets and, if an FPI, more than 300 U.S. beneficial holders; or 3) raising and registering debt or equity capital in the U.S. under Section 15(d). Trading on Pink Sheets does not guarantee an exemption from the SEC. Under Rule 12g3-2(a), these FPIs are exempt from SEC reporting and other obligations if the number of worldwide record holders is below 300 (or with fewer than 500 worldwide record holders and less than $10 million assets). These FPIs are also exempt if the number of U.S. beneficial holders is below 300 (or with fewer than 500 U.S. beneficial holders and less than $10 million assets). To identify beneficial holders, issuers have to look through record holders such as financial institutions to determine ownership. Discussions with SEC staff indicate flexibility in the SEC’s granting of exemptions. The SEC usually exempts FPIs if they do not substantially exceed the above thresholds, i.e., some FPIs that would have to register according to the above thresholds are exempt from registration. Under Rule 12g3-2(b), these FPIs are exempt if they furnish to the SEC on an ongoing basis information they have made public or distributed or are required to make public or distribute under the laws and regulation that they are subject to outside of the U.S. The exempt firms do not have to deregister because they have never registered. Regarding the FPIs with SEC reporting obligations, the deregistration regulation changed with the passage of Section12h-6 and amendments to 12(g) in March 2007. Before the new regulation, if FPIs have raised capital in the U.S., as in case 3) above, they can only suspend, not terminate, their obligation to file periodic reports under Section 12h-3. They must always meet the asset and shareholder threshold requirements of 12(g) to avoid reporting. If FPIs have listed shares only in the U.S., as in case 1), they can terminate Section 12(b) reporting obligations by delisting. However, they are automatically subject to the 12(g) reporting obligations if they meet the criterion of 12(g). These delisted FPIs [under Rule 12g4(a)], as well as reporting OTC FPIs (under 12h-3), can deregister only if they do not exceed the asset and shareholder thresholds.31 After deregistration, FPIs are not eligible for Rule 12g3-2(b) exemptions for at least 18 months according to Rule 12g3-2(d)(1). Rule 12g3-2(b) exempts FPIs from registration even if they exceed the asset and shareholder thresholds. The lack of exemptions creates two significant complications for

31

Under Exchange Act Rule 12g-4(a)1, FPIs and U.S. issuers can deregister if they have fewer than 300 holders of record worldwide (or fewer than 500 worldwide record holders and with assets totaling less than $10 million). Under Exchange Act Rule 12g-4(a)2, FPIs can also deregister under the same conditions, except that the holders are defined as U.S. beneficial holders.

29

deregistered FPIs. First, these FPIs have to renew registration if they exceed the asset and shareholder thresholds within 18 months.

Second, without Rule 12g3-2(b) exemptions, meeting Rule 15c2-11

requirements for trading on Pink Sheets is difficult. Because a market maker rarely quotes the shares of deregistered FPIs on Pink Sheets without the exemption, these FPIs usually have to wait 18 months before their shares can be traded in the U.S. again, even if they want to be traded on Pink Sheets. The new 12h-6 issued in March 2007 provides a second way to deregister in addition to Rule 12g-4(a). It further allows all reporting FPIs [FPIs under 12(b), 12(g), or 15(d)] to deregister if the U.S. average daily trading volume (ADTV) of the class of securities in the U.S. over a recent 12-month period is no greater than 5% of the worldwide ADTV. Upon deregistration through 12h-6, FPIs are immediately eligible for Rule 12g3-2(b) exemptions. The amended 12(g) in March 2007 also allows 15(d) FPIs to deregister under asset and shareholder thresholds. The new regulation has also relaxed deregistration process in several other important ways. In February 2008, the SEC issued proposed rules to further amend 12(g) to streamline the Rule 12g3-2(b) exemption process, as well as affording 15(d) FPIs immediate eligibility for Rule 12g3-2(b) exemptions upon deregistration through Rule 12g-4(a). Examples of pre-SOX accommodations made by the SEC for foreign private issuers Before the enactment of SOX, the SEC made considerable accommodations for FPIs. In general, governance issues were left to home jurisdictions, while reporting rules were applied with extensive reductions in requirements. Since 1979, the SEC has exempted FPIs from quarterly financial reports, Sections 14a–14c proxy rules, Section 14f tender offer rules, and Section 16 short swing profit rules. In 1999, the SEC adopted exemptive rules for cross-border and exchange offers, business combinations, and rights offerings related to the securities of FPIs. In 2000, the SEC exempted FPIs from Regulation Fair Disclosure (Regulation FD) when it was adopted. The SEC has also adopted procedures to accommodate the scheduling needs of FPIs and policies allowing for confidential treatment of filings that would be public for U.S. issuers. Further, the SEC has created separate forms with less disclosure for FPIs, instead of requiring that they file the same forms as U.S. issuers. For example, since 1979, the SEC has allowed FPIs to file Form 20-F instead of Form 10-K. Since 1982, FPIs can use Forms F-1, F-2, and F-3 for initial public offerings, instead of Forms S-1, S-2, and S-3. In 1985, when the SEC introduced Form S-4 for certain reclassifications, mergers, consolidations, and acquisitions, it allowed FPIs to file Form F-4. Canadian issuers have additional exemptions. Canadian firms file Form 40-F instead of Form 10-K. Since 1991, although still governed by U.S. antifraud rules, the top end of the Canadian market can use Canadian forms for registration.

30

Appendix B. Variable definitions B.1. Variables used in cross-sectional regression analysis Shareholder rights Strength of corporate laws to protect shareholder rights from La Porta et al. (1998). Judicial efficiency Efficiency and integrity of the legal environment from La Porta et al. (1998). Rule of law Law and order tradition assessment from La Porta et al. (1998). Accounting standard Index to determine the quality of financial disclosures from La Porta et al. (1998). Public enforcement Index of the characteristics and the power of the main government agency in charge of supervising stock exchanges from La Porta et al. (2006). Disclosure requirements Index of disclosure requirements from La Porta et al. (2006). Log (GDP) Natural logarithm of average per capita GDP for a country from 1999 through 2001 . Log (TA) PPEPCT Sales growth

Natural logarithm of total assets in millions of dollars. Property, plant, and equipment as a percentage of total assets. One-year sales growth.

Cross-listing market cap U.S. volume Non-II block II block Analyst coverage Short sale Time zone

Market value of FPIs in the U.S. as a proportion of FPIs’ total market value. U.S. dollar volume as a proportion of FPIs’ total trading volume. Percentage of stockholding by non-institutional blockholders. Proportion of a firm’s common shares held by institutional blockholders. Number of analysts covering each issuer from I/B/E/S. Indicator for countries prohibiting investors from selling shares short Absolute number of time zones separating a given country’s main stock exchange from New York. Amihud (2002) stock illiquidity. Country-level measure of information-based barriers from Morck et al. (2000). Predicted probability of FPIs voluntarily delisting and deregistering

Illiquidity Synchronicity Going-dark probability

B.2. Additional variables used in going-dark analysis Board size Number of directors. Non-executive directors Proportion of non-executive directors. Independent chairman Indicator for FPIs with the chairman being different from the CEO. Largest holding Holding by the largest blockholder. Earnings management Absolute value of accruals divided by the absolute value of operating cash flows. Forecast dispersion 12-month average of the standard deviation of analysts’ earnings forecasts deflated by the stock price at the beginning of the fiscal year. Forecast error Absolute value of the 12-month average of actual earnings minus the median analyst forecast deflated by the stock price at the beginning of the fiscal year. Forecast revision Standard deviation of 12 monthly forecast revisions, with revisions being the currentmonth median forecast minus previous month median forecast. Liquidity Proportion of days with trading from Lesmond et al. (1999). ROA EBITDA divided by total assets. ROE EBITDA net of interest expenses and preferred dividends divided by book equity. Tobin’s Q Sum of total assets and market value of equity minus book equity, divided by total assets.

31

Table 1. Events pertaining to passage of the 2002 Sarbanes-Oxley Act and related Securities and Exchange Commission (SEC) rules Event 1

Date 1/17/2002

2

11

2/11–12/2002 2/14/2002 4/22/2002 4/24/2002 4/25/2002 6/11/2002 6/12/2002 6/18/2002 6/25/2002 7/3/2002 7/8–12/2002 7/15/2002 7/16/2002 7/19/2002 7/24/2002 7/25/2002 7/30/2002

12

8/2/2002

13

8/6/2002

14

8/27/2002

15

8/29/2002 10/16/2002

16

10/18/2002 10/22/2002 10/30/2002

3

4 5 6 7 8

9 10

11/4/2002 11/5/2002

Description SEC chairman Harvey Pitt recommends establishing an accounting oversight board. Legislation to be introduced in the House. Introduction of H.R. 3763 to the House. Committee report issued on H.R. 3763. House of Representatives passed H.R. 3763. Senate Judiciary Committee approves legislation. Progress reported on Senate legislation. Mark-up of Sarbanes bill to occur. Senate Banking Committee approves S.2673. Introduction of S. 2673 to the Senate. Committee reports on S.2673. Senate deliberation on S. 2673. Senate passed S. 2673. House introduced H.R. 5118. House passed H.R. 5118. Conference committee meeting. Conference report issued. Congress passed conference report. Bush reportedly will sign the bill. Bush signed into law the Sarbanes-Oxley Act of 2002. Final rules to implement Section 304 (forfeiture of compensation and securities related profits) and Section 402 (prohibition on personal loans) became effective immediately. SEC approves and releases proposed rules to implement Section 302 (management certification of financial statements). SEC, in a departure from the original statute, decides to include foreign private issuers for Section 302 compliance as required by SOX. SEC approves and releases proposed rules to implement Section 403(a) (accelerated insider transaction reports). SEC approves final rules to implement Sections 302 and 403(a). SEC releases final rules to implement Section 403(a). SEC releases final rules to implement Section 302. SEC approves proposed rules to implement Sections 303 (prohibition of actions designed to improperly influence auditors), 404 (internal controls and procedures), 406 (code of ethics), and 407 (financial experts on audit committee). SEC releases proposed rules to implement Section 303. SEC releases proposed rules to implement Sections 404, 406, and 407. SEC approves proposed rules to implement Sections 401(a) (disclosure of off-balance sheet arrangements), 401(b) (also called Regulation G, conforming to Generally Accepted Accounting Principles), and 306(a) (prohibition of insider trading during pension plan blackout periods). SEC releases proposed rules to implement Section 401(a). SEC releases proposed rules to implement Section 401(b).

32

Event window 1/17–18 2/11–15 4/22–26

6/11–13 6/18–19 6/25–26 7/3–5 7/8–17

7/19–22 7/24–26 7/30–31

8/2–5

8/6–7 8/27–30

10/16– 23

10/30–31, 11/4–7

Table 1 – Continued Event Date Exemptions:

17

12/18/2002

18

12/20/2002 1/8/2003 Exemptions:

19

1/15/2003 Exemptions:

20 21

22

23

1/22/2003 1/28/2003 4/1/2003 4/9/2003 Exemptions:

4/24/2003 5/7/2003 5/20/2003 5/27/2003 6/5/2003 Exemptions:

Description Section 401(a): No exemption. Since FPIs file only annually with SEC, their cost should be lower. Section 401(b): Limited exemption for disclosure other than documents such as 20-F. Section 306(a): 1) Does not apply to management employee directors. 2) Use a different calculation (15%+50% tests) to determine insider trading prohibition. SEC approves proposed rules to implement Section 403 (electronic filing of insider ownership reports). SEC releases proposed rules to implement Section 403. SEC approves and releases proposed rules to implement Section 301 (compliance with the audit committee requirements). 1) The rules do not apply to non-management employees on board, where board means supervisory or non-management board in two-tier board system. 2) The entire board can be designated audit committee without setting up separate committee. 3) Controlling shareholders can send one observation member to the audit committee. 4) Foreign government can send a representative to be one member of the audit committee. In 3) and 4), the member needs to be a non-management member. 5) Bodies such as board of auditors can substitute for auditor committee if requirements are met, e.g., as in Japan. 6) There is also an exemption for the board of a dual holding company. SEC approves and releases final rules to implement Sections 306 (a), 401(b), 406, and 407. Section 406: Disclose changes to code of ethics only in annual reports. Section 407: Foreign companies can disclose whether financial expert is independent later along with Section 301 requirements. SEC approves final rules to implement Section 401 (a). SEC releases final rules to implement Section 401 (a). SEC approves final rules to implement Section 301. SEC releases final rules to implement Section 301. 1) Compliance by July 31, 2005, rather than 10/31/2004, the deadline for U.S. issuers. 2) Expanded exemption for dual holding company. 3) Amend Section 407 rules and set date of compliance to be July 31, 2005. If exemptions taken, need to disclose. SEC approves final rules to implement Sections 303 and 403. SEC releases final rules to implement Section 403. SEC releases final rules to implement Section 303. SEC approves final rules to implement Section 404. SEC releases final rules to implement Section 404. U.S. issuers must comply by 6/15/2004, whereas foreign issuers must comply by 4/15/2005.

33

Event window

12/18–21

1/8–9

1/15–16

1/22–23, 1/28–29 4/1–2, 4/9–10

4/24–25, 5/7–8, 5/20–21 5/27–28, 6/5–6

Table 2 Summary statistics Panel A. Summary statistics of country-level measures of investor protection # of FPIs

Shareholder rights

Mean

524

3.78

Standard deviation

524

1.37

Judicial efficiency

Rule of law

Accounting standard

8.86

8.09

68

0.60

0.73

1.46

2.09

8.52

0.21

0.17

34

Public enforcement

Disclosure

Table 2 – Continued Panel B. Mean of other independent variables across the firms within a country and for the whole sample Log Log PPE- Sales Short Time Illiqui- Synchro US US Non-II II Cover -nicity cap volume block block -age # of (GDP) (TA) PCT growth sale zone dity (%) (%) (%) (%) (%) FPIs (%) Country Argentina

9

8.78 8.01

55.11

0.18

0

2

0.59

0.17 18.56

54.80

1.00

0 5.11

Australia

13

9.92 7.98

27.96 -13.59

0

15

0.15

0.02 11.04

15.32

3.42

1.75 1.54

Austria

1 10.12 8.84

59.42 -10.40

0

6

0.06

0.06

0.77

10.96

0

0

0

Belgium

1 10.05 9.28

34.89

11.88

0

6

0

0.07 17.46

16.69

0

0

0

Brazil

8

8.03 8.33

53.49

-9.06

0

2

0.09

0.24 28.97

41.72

16.17

0 8.75

139 10.02 6.07

38.00

26.44

0

0

0.29

0.14 86.27

42.82

16.60

1.91 10.32

52.23

-3.15

0

1

0.29

0.08 12.69

64.80

10.63

0.31 4.89

2 10.34 6.64

25.14 -11.93

0

6

0.26

0.07 38.51

4.12

0

0 1.00

Finland

3 10.09 9.27

43.98

1.80

0

7

0.04

0.11

4.07

4.02

19.00

0 1.00

France

23 10.06 7.89

17.89

29.48

0

6

0.33

0.11 13.27

20.32

6.37

1.76 1.61

Germany

17 10.08 7.58

23.00

4.42

0

6

2.18

0.14 13.45

27.84

3.24

5.12 1.88

Canada Chile Denmark

19

8.44 7.17

Greece

4

9.31 8.07

31.04

-7.49

1

7

0.28

2.30

9.63

7.64

0

0

Hong Kong

5 10.10 6.71

42.98

35.19

0

13

0.30

0.04 15.90

16.12

0

0 0.20

0.16

0.03 20.05

29.13

3.36

3.49 1.00

India

11

6.14 6.61

21.77

37.36

0 10.5

Indonesia

2

6.59 7.87

56.20

68.27

1

12

0

Ireland

9 10.20 7.54

17.98

19.35

0

5

0

0

7.81

16.94

1.00

0.17

0.04 47.62

73.94

7.78

Israel

69

9.75 4.53

16.24

-2.24

0

7

1.38

0.11 89.28

68.58

4.55

0.49 3.77

Italy

10

9.89 8.37

24.47

0.98

0

6

0.23

0.24 13.75

14.82

0

2.50 2.10

Japan

16 10.44 8.90

23.87

7.60

0

14

0.42

0.02

4.72

4.39

0.73

6.80 0.38

Mexico

22

8.68 7.73

42.06

7.07

0

1

0.35

0.51 26.46

51.06

21.94

0 5.77

Netherlands

15 10.11 8.87

22.51

1.05

0

6

0.11

0.14 12.22

9.41

19.60

5.87 3.93

New Zealand

3

9.57 7.49

62.69

4.18

0

14

0.25

0.03

6.65

11.20

0

0 1.00

Norway

5 10.55 9.06

58.50

5.06

0

7

0.37

0.08

2.32

2.67

10

0 0.20

Peru

2

7.63 7.11

53.35

-1.19

1

0

0.19

0.10 20.34

87.04

0

0 6.50

Philippines

2

6.88 6.68

80.01

-7.15

0

12

0.58

0.04 24.83

46.17

0

0 2.50

Portugal

2

9.31 10.25

31.37

18.67

0

5

0.07

0.09

2.60

0.42

Singapore

2

9.97 7.21

59.59 -57.59

1

13

0.04

0.73

5.07

47.92

0

South Africa

5

7.91 7.19

69.44

-1.20

0

6

0

0.04 21.85

43.56

0 22.20 1.60

South Korea

7

9.26 9.31

49.42

19.30

1

14

0.83

0.03 13.87

12.67

2.43

0.57 1.29

Spain

7

9.60 10.93

26.93

19.55

0

6

0.04

0.19

5.29

7.41

1.86

0.86 2.57

Sweden

7 10.19 8.23

17.53

16.94

0

6

0.21

0.13

4.17

6.97

36.02

0 5.14

11 10.49 8.86

14.34

3.23

0

6

0.05

0.14

3.22

4.79

0.64

0 1.27 0 2.20

Switzerland

0 18.00

Taiwan

5

9.45 8.23

57.12 -31.18

0

13

0.06

0.04

5.13

7.31

2.80

Turkey

1

7.87 8.17

50.19 -19.69

0

7

0.01

0.06

2.63

4.77

0

United Kingdom

0 10.50

0

0

21.87

15.60

0

5

0.40

0.10 10.98

13.13

3.48

4.52 2.14

1

8.42 8.64

72.76

15.60

1

1

0

0.01 45.36

93.07

0

0 9.00

Mean

524

9.70 7.03

31.14

12.34 0.03 4.79

0.49

0.15 43.71

30.91

8.81

2.35 4.93

Standard deviation

524

0.82 2.54

25.96

74.50 0.18 4.25

1.90

0.21 44.17

31.22

23.24

7.56 7.68

Venezuela

66 10.13 7.80

0

35

Table 2 – Continued Panel C. Sample distribution of non-institutional blockholdings for all the cross-listed FPIs in 2001 and for all the going-dark FPIs over the 1995–2006 period

All cross-listed FPIs in 2001

Going-dark FPIs Pre-SOX period

Post-SOX period

(3) N

(4) % of sample

(5)

N

(2) % of sample

387

79.0

4

0% – 10%

22

4.5

10% – 20%

18

20% – 30%

N

(6) % of sample

36.4

8

21.1

0

0.0

0

0.0

3.7

1

9.1

6

15.8

13

2.7

1

9.1

2

5.3

30% – 40%

5

1.0

0

0.0

0

0.0

40% – 50%

7

1.4

0

0.0

2

5.3

> 50%

38

7.8

5

45.5

20

52.6

Total

490

100

11

100

38

100

(1) Range of blockholdings 0%

See Appendix B for variable definitions.

36

Table 3 Abnormal stock returns of cross-listed foreign private issuers (FPIs) around 2002 Sarbanes-Oxley Act (SOX)-related legislative and implementation events U.S. return – FPI-free home index

Event number

Abnormal return (%)

t-stat.

Home return – FPI-free home index

% of negative Abnormal  return (%) return

t-stat.

% of negative return

Total (1-23)

-9.63 ***

-8.63

68.5

-12.97 ***

-10.68

75.3

Pre-SOX (1-11)

-9.55 ***

-10.34

70.8

-11.05 ***

-13.07

71.0

3.59 ***

3.08

50.6

2.11 ***

3.07

40.2

-3.67 ***

Proposed rule (12-13, 15-18) Final rule (14, 19-23)

-6.13

61.5

-4.04 ***

-6.58

58.2

1

0.11

0.53

49.6

-0.43

-1.86

49.5

2

0.11

1.50

50.0

0.23

1.72

36.2

3

-2.55 ***

-6.92

67.7

-2.11 ***

-6.02

63.8

4

-1.61 ***

-4.06

59.5

-1.48 **

-5.60

60.1

5

-1.13 **

-4.31

63.7

-0.45

-1.15

49.7

6

-0.82

-2.04

53.2

-0.26

-0.65

52.1

3.39

43.7

0.05

0.11

49.5

7

1.03 *

8

-2.97 ***

-9.76

68.7

-3.60 ***

-11.65

66.0

9

-2.26 ***

-12.51

69.3

-3.46 ***

-20.14

74.5

10

-0.69

-0.35

50.4

-0.38

-0.14

52.9

0.86

3.57

35.9

-8.75

58.5

11

1.21 **

4.98

44.3

12

-1.99 ***

-8.76

64.1

13 14

1.75 *** -0.43

-1.72 ***

9.80

35.5

1.26 **

7.69

45.5

-2.33

60.5

-1.27 **

-4.79

58.5

15

1.00 ***

0.64

53.1

0.69 **

0.34

42.0

16

3.66 ***

7.03

41.4

2.59 ***

7.45

30.6

17

-3.18

61.1

-0.70 *

-1.95

60.9

18

-1.03 ** 0.21

-0.45

53.8

-0.01

-0.11

52.7

19

-0.64

-3.91

62.4

-0.11

-1.35

54.5

20

-1.78 ***

-4.71

61.1

-1.43 ***

-5.11

62.8

21

1.08 **

3.76

44.8

2.24

35.4

22

-3.55 ***

-10.46

73.9

-3.28 ***

-9.73

68.6

23

1.64 ***

4.11

44.1

1.51 ***

4.69

33.0

Number of observations

524

0.54

376

***, **, and * indicate that estimates are significant at the 1%, 5%, and 10% level, respectively, according to the bootstrapped abnormal returns on the non-event days during the 2002 to 2003 period. t-stat. is the Brown and Warner (1985) t-statistic during the SOX-related events. Abnormal returns are based on market model adjusted returns with the period from January 1999 to December 2001 as the estimation period.

37

Table 4 Additional tests on abnormal stock returns around 2002 Sarbanes-Oxley Act (SOX)-related legislative and implementation events U.S. return – FPI-free home index

Home return – FPI-free home index

Abnormal return (%)

Abnormal return (%)

t-stat.

t-stat.

Panel A. OTC-traded FPIs 1. OTC-traded FPIs with SOX compliance

-5.45 ***

-8.46

-5.17 ***

-9.17

2. OTC-traded FPIs without SOX compliance

-1.02

-0.66

-1.26

-0.81

1. 36 country portfolios instead of stock returns

-4.59 ***

-2.59

-8.58 ***

-4.79

2. Trim daily returns beyond -25% and +25%

-8.93 ***

-7.72

-15.59 ***

-11.65

3. Excluding direct listings from Canada and Israel

-5.07 ***

-4.61

-15.47 ***

-10.45

4. MSCI country indexes as benchmarks

-9.53 ***

-8.08

-14.00 ***

-11.60

5. Use estimation period market-adjusted returns to estimate standard error

-9.53 ***

-5.11

-14.00 ***

-6.82

6. Use event period market-adjusted returns to estimate standard error

-5.48 ***

-4.42

-6.74 ***

-5.10

Panel B. Additional robustness tests

***, **, and * indicate that estimates are significant at the 1%, 5%, and 10% levels, respectively. The estimation period is January 1999 to December 2001. Except for Row 4 of Panel B, where I use Morgan Stanley Capital International (MSCI) country index as the benchmark, I use foreign private issuer (FPI)-free home country index as the benchmark. Except for rows 5 and 6 of Panel B, I use market model adjusted returns.

38

Table 5 Cross-sectional analysis of going-dark probability and 2002 Sarbanes-Oxley Act (SOX)-related abnormal returns Panel A. Cross-sectional analysis of SOX-related abnormal returns with ordinary least squares Dependent variable = U.S. abnormal return (1) Category

Independent variable

Coeff.

t-stat.

Dependent variable = home abnormal return (2) Coeff.

t-stat.

Main variables Corporate law

Securities law Institutional monitoring

Shareholder rights

5.31 ***

4.60

3.99 ***

2.75

Judicial efficiency

-2.73 *

-1.81

-5.33 ***

-2.65

Rule of law

-4.44 ***

-5.68

-2.10 **

-2.20

Accounting standard

-0.06

-0.23

Public enforcement

-0.31 ***

-2.96

Disclosure standard

-33.36 ***

-3.32

II block

-0.04 *

-1.91

-0.27 *

-1.65

Analyst coverage

-0.34 **

-2.24

-0.56 **

-2.20

1.61 *

1.91

1.82 *

1.93

-0.17 *

-1.95

0.18 -0.79 *** -14.77

0.63 -6.05 -0.90

Going-dark in the U.S.

Going-dark probability

Controlling shareholders

Non-II block

-0.15 **

-2.00

Financial development

Log (GDP)

12.09 ***

5.36

Firm size

Log (TA)

-1.74 ***

-2.68

-1.57 *

-1.83

Fixed assets

PPEPCT

0.18 ***

3.49

0.15 *

1.70

Growth opportunities

Sales growth

-0.07 ***

-3.58

-0.09 ***

-4.80

Market friction

Short sale

46.95 ***

4.20

66.84 ***

3.48

Control variables 6.46 ***

2.69

Time zone

0.45

1.38

0.53

0.90

Illiquidity

3.59 ***

2.39

9.41

1.51

-23.65 ***

-4.08

Synchronicity

-25.95 ***

Intercept

6.30

Adjusted-R2

0.25

0.26

Number of observations

459

360

39

0.30

30.60

-2.50 0.81

Table 5 – Continued Panel B. Probit model estimating the likelihood of FPIs going-dark in the U.S. Dependent variable = 1 if FPIs go dark

Category

Independent variable

Corporate law

Home country sample

(1)

(2)

Coeff.

t-stat.

Coeff.

t-stat.

Shareholder rights

-0.16

-1.26

-0.16

-1.08

Judicial efficiency

-0.15

-1.42

-0.23

-1.57

Rule of law

-0.02

-0.21

0.02

0.15

0.06 **

2.04

Accounting standard Securities law

U.S. sample

0.07 ***

2.50

Public enforcement

-0.73

-1.04

-0.45

-0.50

Disclosure standard

-0.07

-0.05

0.04

0.02

Blockholdings

Non-II block

Firm characteristics

Cross-listing market cap U.S. volume

0.12 **

2.17

0.15 **

2.21

-0.01 ***

-3.17

-0.02 ***

-3.13

0.01

0.85

0.01

0.85

Sales growth

-0.01 ***

-2.12

-0.01 **

-1.97

Log (TA)

-0.22 ***

-3.70

-0.33 ***

-4.08

Intercept

-1.78

-1.35

-0.57

-0.36

Pseudo-R2

0.36

0.37

Number of observations

459

360

***, **, and * indicate that t-statistics are significant at the 1%, 5%, and 10% levels, respectively. See Appendix B for variable definitions. I cluster standard errors within country in Panels A and B.

40

Table 6 Going-dark foreign private issuers (FPIs) Panel A. Yearly statistics of going-dark FPIs and all FPIs SOX passed in July 2002 1995 1996 1997 1998 1999 2000 2001 2002 2002 2003 2004 2005 Total 1:7 8:12 Going-dark FPIs Delisting Number

0

1

0

1

1

4

3

4

4

10

7

17

52

% of all delisting

0.0

4.0

0.0

1.6

1.4

5.3

3.8 12.1

11.1 16.1 16.7 26.6

9.4

% of total listing

0.0

0.2

0.0

0.1

0.1

0.5

0.4

0.5

0.5

1.3

0.9

2.2

0

1

0

0

1

2

3

5

4

11

8

17

52

% of all delisting

0.0

4.0

0.0

0.0

1.4

2.7

3.8 15.2

11.1 17.7 19.0 26.6

9.4

% of total listing

0.0

0.2

0.0

0.0

0.1

0.2

0.4

0.6

0.5

1.5

1.1

2.2

New listing

66

123

109

74

74

140

64

14

21

31

46

58

762

Delisting

25

25

38

61

74

75

80

33

36

62

42

64

551

555

653

737

773

786

852

841

796

796

758

742

757

Deregistration without distress Number

All FPIs

Total listing

Panel B. Five-day home market going-dark abnormal returns of FPIs before and after passage of SOX Delisting returns Deregistration returns without distressed delistings Event window Before July30, 2002 After July30, 2002 Before July30, 2002 After July30, 2002 Ret. t-stat. % of + (-5, +5) # of obs.

-5.11 14

-1.99

21.4

Ret. t-stat. % of + 2.22

0.62

63.2

38

Ret. t-stat. % of + -6.41 -1.60 12

41

25.0

Ret. t-stat. % of + 2.21 40

0.81

65.0



# of observation

Liquidity

42

11

86.31

Liquidity

Valuation

Days with trading (%)

-33.65

Sales growth (%)

1.04

5.60

Analyst coverage

Tobin’s Q

0.19

Revision volatility

-12.43

0.39

Forecast dispersion

ROE (%)

0.69

Forecast errors

-1.50

0.43

Earnings management

Operating performance ROA (%)

1.89

II block (%)

potentials

32.00

Largest holding (%)

Growth opportunities

33.67

Non-II block (%)

Growth

55.56

Independent chairman (%)

Analyst forecasts

67.14

Non-executive directors (%)

characteristics

9.00

Board size

Earnings quality

(1)

Variables

Earnings

Blockholdings

Board characteristics

Governance

characteristics

Subcategory

Category

Pre

11

52.04

1.20

-12.87

-1.38

35.48

5.55

0.45

0.47

0.24

2.54

6.89

26.00

34.33

77.78

74.54

9.00

(2)

Post

Go dark

-34.27

0.16

-0.43

0.12

69.13**

-0.05

0.26**

0.08

-0.45*

2.11***

5.00

-6.00

0.66

22.22

7.40*

0.00

(3)

38

80.00

1.40

-0.75

2.69

3.57

7.19

0.15

0.21

0.27

0.52

11.33

21.00

35.53

65.00

64.27

9.00

(4)

Pre 8.00

(5)

Post

38

72.50

1.83

8.13

6.85

26.58

6.19

0.12

0.20

0.18

0.60

14.68

20.00

27.38

75.00

66.98

Go dark

-7.50

0.42***

8.88***

4.16***

23.01***

-1.00

-0.03

-0.02*

-0.09

0.08

3.35

-1.00

-8.15***

10.00

2.71

-1.00

(6)

Change

After July30, 2002

FPIs that go dark

Change

Before July30, 2002

Panel C. Characteristics of cross-listed FPIs before and after going-dark in the U.S.

Table 6 – Continued

***

*

*

*

**

**

**

***

***

**

(7)

***

**

***

*

**

**

**

**

(8)

Signi- Significance ficance

Diff. of Diff. of (3) & (6) (1) & (4)





43

***, **, and * indicate that t-statistics or signed rank statistics are significant at the 1%, 5%, and 10% levels, respectively. The data are from January 1993 through December 2006. The going-dark returns in Panel B are adjusted by the respective Morgan Stanley Capital International home country index returns using a market model with the estimation period of the (-510, -11) event day window, and % of + is percentage of the sample with positive abnormal returns. Ret. stands for Returns and Diff. stands for difference. See Appendix B for variable definitions.

Table 6 – Continued