Firm value and cross listings: The impact of stock market prestige

Cetorelli, Nicola; Peristiani, Stavros Article Firm value and cross listings: The impact of stock market prestige Journal of Risk and Financial Management Provided in Cooperation with: MDPI – Multidisciplinary Digital Publishing Institute, Basel Suggested Citation: Cetorelli, Nicola; Peristiani, Stavros (2015) : Firm value and cross listings: The impact of stock market prestige, Journal of Risk and Financial Management, ISSN 1911-8074, MDPI, Basel, Vol. 8, Iss. 1, pp. 150-180, https://doi.org/10.3390/jrfm8010150 This Version is available at: https://hdl.handle.net/10419/178558 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. 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Risk Financial Manag. 2015, 8, 150-180; doi:10.3390/jrfm8010150 Journal of Risk and Financial Management ISSN 1911-8074 www.mdpi.com/journal/jrfm Article Firm Value and Cross Listings: The Impact of Stock Market Prestige Nicola Cetorelli * and Stavros Peristiani Federal Reserve Bank of New York, 33 Liberty Street, Main 3, New York, NY 10045, USA; E-Mail: [email protected] * Author to whom correspondence should be addressed; E-Mail: nicola[email protected]; Tel.: +1-212-720-5071. Academic Editor: Christian Brownlees Received: 27 October 2014 / Accepted: 9 March 2015 / Published: 23 March 2015 Abstract: This study investigates the valuation impact of a firm’s decision to cross list on a more (or less) prestigious stock exchange relative to its own domestic market. We use a network analysis methodology to derive broad market-based measures of prestige for 45 country or regional stock exchange destinations between 1990 and 2006. We find that firms cross listing in a more prestigious market enjoy significant valuation gains over the five-year period following the listing. In contrast, firms cross listing in less prestigious markets experience a significant valuation discount over this post-listing period. The reputation of the cross-border listing destinations is therefore a useful signal of firm value going forward. Our findings are consistent with the view that cross listing in a prestigious market enhances firm visibility, strengthens corporate governance, and lowers informational frictions and capital costs. Keywords: cross-listings; network analysis JEL classifications: G15, G20 OPEN ACCESS J. Risk Financial Manag. 2015, 8 151 1. Introduction Prior to the onset of the global financial crisis in 2008, one of the most important issues debated in the financial press was whether U.S. stock markets were still the dominant destination for global financial services. U.S. stock exchanges assumed the mantle of the world’s leading financial center in the years following World War II [1], becoming the primary destination of global equity activity, especially from other important financial centers. However, bolstered by the significant pace of globalization in the early 1990s, an increasing number of alternative destinations have emerged to achieve the level of sophistication needed to compete for these equity activities. This evolution has brought with it potential consequences for the geography of financial activity and has affected the hierarchy of international financial centers. As financial conditions return to a more normal mode of operations following the recent crisis, this issue of competitiveness is likely to re-emerge as international stock markets attempt to solidify their position in the hierarchy of global finance. Many of these emerging financial centers have experienced higher volumes of domestic equity offerings that in previous years would have “migrated” to foreign destinations. At the same time, they were more successful in attracting foreign firms that in past would have preferred to list in more traditional destinations. In light of these changing dynamics of increased globalization in equity markets, our study analyzes the potential effects on companies that implement cross-listing activities around the world. A company’s decision to have a foreign listing has attracted great interest in the financial literature. Research analyzing the proliferation of these foreign listings focuses on the underlying motives and cost-benefit calculus of companies listing outside their home market [2–5]. Among the benefits, cross listings can reduce market-segmentation problems [6,7], enhance firm visibility and lessen informational asymmetries [8], lower the cost of capital and improve liquidity [9], strengthen investor protection [10,11], and improve the capacity of controlling shareholders to transfer ownership [12]. Several empirical studies document that foreign firms cross listing on U.S. exchanges have enjoyed significant valuation gains vis-à-vis those without such a listing (see, for example, [13–16]). Greater competition from overseas financial centers also raises the possibility that foreign firms could also attain these valuation benefits by cross listing in other prominent destinations. Roosenboom and Van Dijk [17] document the importance of the stock market destination by showing that cross listings in United States and London have generated greater cumulative abnormal returns for shareholders. In this paper we look at broad patterns in valuation effects from global cross-listing activity, but we posit that future valuation may be affected by where the cross-listing company is coming from and where it is cross listing to. More precisely, we conjecture that the reputation of the destination (more formally defined as prestige in the next section) is a signal that the market uses to update information regarding the future value of the cross-listing firm. This conjecture is consistent with the view that foreign listings enhance firm visibility, lowering informational frictions and capital costs. This premise, which is based on the “investor recognition” hypothesis developed in Merton [18], has been explored by several studies [8,19–21]. We expand on this hypothesis by arguing that this information update should also depend on the company’s own market of origin. Among other benefits, cross listing on a prestigious foreign stock exchange may boost visibility, improve corporate governance and firm transparency, and ameliorate J. Risk Financial Manag. 2015, 8 152 capital costs. These improvements in valuation, however, should be stronger for firms originally listed in a less prestigious location that does not offer these economic and certification benefits. In contrast, firms originally listed in a relatively prestigious location are already enjoying these benefits. In fact, cross listing in a location with lower prestige might alarm investors and harm firm value. The challenging task of our premise is to derive a measure of market reputation that reflects these potential certification benefits. We propose a social network measure of market prestige. This index produces a ranking of the popularity of each stock market as a location of destination for equity issuance activities. The ranking is determined by taking into account simultaneously both the popularity of each given location as the destination of choice for foreign companies seeking to raise capital through an initial public offering (IPO) and the relative popularity of the locations of origin of the issuing firms. Using a methodology common in network analysis, we are able to derive a time-varying measure of prestige for 45 global stock exchanges and test the impact on valuation for companies cross listing between 1990 and 2006. We find evidence that cross listing has a substantial impact on firm valuation, once we condition the analysis on the ex ante prestige of both markets of origin and destination. Firms that choose to have foreign listings in more prestigious markets relative to their own domestic market enjoy significant valuation gains over the five years following the listing. Moreover, foreign listings in markets that had been less prestigious than the market of origin are associated with declining valuations over the following five years. We also find valuation effects from the evolution of the destination market. Irrespective of whether a firm chooses a less or more prestigious destination at the time of the cross-listing event, its valuation increases (decreases) if the host market subsequently improves (deteriorates) its global status. Our results are consistent with the findings of Doidge, Karolyi, and Stulz [13,14] that document valuation gains from listing on U.S. exchanges over the past two decades. Over this period, U.S. exchanges—as we formally show in a later section—have been arguably the most prestigious destination markets; thus, by focusing on U.S. cross listings, we virtually condition on a rise in prestige. The rest of the paper proceeds as follows. Section 2 presents the methodology used to assess market prestige. Section 3 describes the data sources and sample construction. Section 4 outlines our model specification, and Section 5 reviews findings analyzing the impact of cross listings on firm valuation. 2. Data To formally analyze the impact of a cross listing on firm valuation, we use information from Osiris Bureau Van Dijk. This database, which provides comprehensive standardized financial information for publicly traded companies around the world, is the building block for the underlying panel structure for analyzing the relationship between firm performance and cross listings during the period 1990–2006. Over this entire sample period, Osiris tracks around 40,000 publicly-traded firms from roughly 125 countries. The primary focus of our analysis is the subset of the 45 larger country and stock exchange combinations that had significant inflows or outflows of IPO issuance over this period and for which we can estimate accurate network-based measures of stock market prestige. In addition, our analysis requires that publicly listed companies in our sample have non-missing information on financials and J. Risk Financial Manag. 2015, 8 153 stock market valuation variables. The final panel with complete financial information, for which we can compute a network prestige ranking, includes roughly 29,000 firms. As expected, more than 20 percent (or about 6225 companies) of this firm sample is domiciled in United States. However, consistent with most of literature, the core group of interest in the empirical analysis is the remaining 22,775 non-U.S. companies. The non-U.S. panel of firms is distributed across an array of countries representing the largest economies and financial centers (for example, Japan, the United Kingdom, Australia, Canada, China, Taiwan, and France). The second step in our sample design is to ascertain all cross-listing activities for the firms included in the panel. A cross-listing represents a publicly traded company’s listing on an exchange other than its primary stock exchange. Firms can use this cross listing to raise capital (referred to as a Level III listing on U.S. stock exchanges) but often simply opt to list trading shares. Our sample of cross-listings also includes American depository receipts (ADRs) and their Global depository receipts (GDRs) counterparts. The task of identifying cross listings is nontrivial because there is no consolidated source of information on these activities. The typical information on initial or secondary issuance available from various vendors only captures firms that issue domestically or outside their home market but does not fully identify all cross-listing activities. To flag cross listings for each firm in the sample, we bring together listings information from several sources for the period between 1990 and 2006. Ultimately, the goal is to determine whether a company included in the panel had cross listed at some point during 1990–2006. A broad overview of a firm’s cross-listing activity is available from Datastream, which allows us to distinguish and match foreign listings using company ISIN or SEDOL numbers. We also collected information on foreign listings from a variety of other sources. A very good source of information for companies listing on mostly U.S. stock exchanges is provided by the depository receipt service departments of Bank of New York, JPMorgan Chase, Citibank, and Deutsche Bank. Collectively, these ADR programs report Level II and III listings on major U.S. stock exchanges as well as Level I OTC, 144a, and Regulation S foreign issues. To better identify cross-listing activities outside the United States, we also collected information, where available, from some of the larger international stock markets (for example, the London Stock Exchange, Deutsche Börse, Euronext, and Hong Kong). Most of the aforementioned sources of information help identify individual foreign listings outside their home countries. One drawback of pooling information from these various sources is that the database is sometimes fragmented. To consolidate our listings information, we compiled a complete timeline for all cross-listed firms using information from Bloomberg Financial and Capital IQ. Both sources offer a more complete timeline of a firm’s listing activity over its entire public life cycle, allowing us not only to verify the presence of a cross listing but also to accurately date and order the sequence of multiple foreign listings. All the company-level searches in Bloomberg and Capital IQ were done manually based on the company’s name. J. Risk Financial Manag. 2015, 8 154 Table 1. Cross Tabulation of Home and Destination Country Markets. Home Market Host Market Argentina Australia Austria Canada China Euronext Germany Hong Kong India Ireland Israel Italy Japan Korea Luxembourg Malaysia Mexico N Zealand Norway OMX Other Singapore S Africa Spain Switzerland Taiwan U.K. U.S. Total Argentina 1 1 1 1 4 Australia 3 2 1 2 1 1 30 1 3 2 13 5 64 Austria 1 1 3 1 1 7 Canada 10 2 1 1 1 1 9 42 67 China 1 2 3 Euronext 8 3 7 13 6 1 45 4 10 5 3 2 22 20 149 Germany 10 1 5 20 1 2 9 3 5 3 2 1 2 4 14 82 Hong Kong 94 2 2 98 India 1 1 2 2 6 Ireland 1 2 16 19 Israel 1 1 4 6 Italy 5 1 1 7 Japan 1 1 1 1 7 9 20 Korea 1 1 2 3 1 8 Luxembourg 7 2 44 5 9 4 71 Malaysia 1 2 1 4 Mexico 1 2 3 N Zealand 44 1 1 14 60 Norway 4 2 1 1 1 2 3 14 OMX 2 1 1 2 3 15 1 4 2 5 36 J. Risk Financial Manag. 2015, 8 155 Table 1. Cont. Home Market Host Market Argentina Australia Austria Canada China Euronext Germany Hong Kong India Ireland Israel Italy Japan Korea Luxembourg Malaysia Mexico N Zealand Norway OMX Other Singapore S Africa Spain Switzerland Taiwan U.K. U.S. Total Other 1 4 1 3 6 15 Singapore 6 5 7 1 1 4 94 1 5 2 8 134 S. Africa 1 2 3 11 17 Spain 1 1 1 10 19 32 Switzerland 1 3 7 23 17 3 2 1 4 17 52 130 Taiwan 2 1 1 1 1 6 U.K. 2 65 3 42 12 96 77 44 37 12 34 28 2 2 6 9 1 7 50 71 6 18 29 6 31 125 815 U.S. 20 115 13 304 53 116 48 18 73 15 79 26 188 8 8 18 56 7 12 49 198 36 39 15 5 41 214 1774 Total 22 244 30 381 173 280 151 29 167 56 102 73 245 11 30 124 76 38 36 148 315 52 74 51 20 86 339 298 3651 J. Risk Financial Manag. 2015, 8 156 Table 1 summarizes the flow of cross listings across the major regions representing the home countries and their respective stock exchanges. Given the large number of home-country locations—our sample includes 45 countries or regions—the information is cross-tabulated for the largest home-country locations and host-market destinations. The remaining countries or host markets with relatively sparse cross-listing activity are grouped in the “other” category. Looking at the sample that had available financial information during 1990–2006, we observe that there are over 3650 foreign listings, including multiple listings by the same firm and Level I issues in United States. This sample of foreign listings is comparable to those compiled by other recent studies analyzing cross listings (see, for example, Fernandes and Giannetti [22] and Sarkissian and Schill [23]), although their sample periods are somewhat different. Table 2 tabulates multiple cross-border listings by the location of the host market. The table excludes Level I OTC listings and private placements. Most firms have just a single foreign listing with only about 10 percent of the sample opting for a second foreign listing. Table 2. Destinations for the Sample of Cross-Listed Firms. Host Market First Listing Second Listing Third Listing Argentina 2 2 Australia 59 4 1 Austria 4 2 1 Canada 62 1 4 China 3 Euronext 136 8 5 Germany 53 18 11 Hong Kong 97 1 India 6 Ireland 19 Israel 6 Italy 3 2 2 Japan 17 1 2 Korea 8 Luxembourg 45 25 1 Malaysia 4 New Zealand 56 4 Norway 17 1 OMX 35 1 Singapore 129 5 South Africa 17 Spain 26 5 1 Switzerland 111 10 9 Taiwan 6 U.K. 664 51 17 U.S. 937 81 1 Other Markets 15 1 2 Total 2537 222 58 Notes: This table presents the number of official foreign listings for all major stock market destinations. The order of the listings is not chronological but reflects more the importance of the host destination. The table excludes Level I listings in the United States. The table also does not include the large number of unofficial cross listings on German stock exchanges. Information on cross listings was compiled from Datastream, various ADR Programs, Capital IQ, and Bloomberg. J. Risk Financial Manag. 2015, 8 157 Tables 1 and 2 illustrate the dominance of U.S. stock exchanges as the most preferred destination by overseas companies, which is well documented by earlier literature (for example, [13]). Another important market appearing to attract a large number of foreign issues is the United Kingdom, essentially represented by the London Stock Exchange. Doidge, Karolyi, and Stulz [14] and Peristiani [24] note that most of the growth in foreign listings stems from micro-cap companies listing on the Alternative Investment Market (AIM) segment of the London Stock Exchange 1. The new-listings activity on the London Stock Exchange, excluding these very small AIM firms, is actually substantially lower over this period and is in line with other stock exchanges. A unique feature of our database is that we make concerted effort to trace the decision to cross list over a firm’s public life cycle. Using information provided by Osiris, we estimate the age of the firm over its public life cycle. Age is an important factor in a company’s decision to cross list. The top panel in Table 3 reveals that, for most firms, the decision to cross list is tied closely to their IPOs. In particular, more than half of the cross listings are initiated within four years of going public. Many of the stock listings in our sample become inactive for a variety of reasons. Firms may simultaneously delist from their home-country exchange and foreign host markets because of corporate reorganization events (such as a merger, bankruptcy, etc.). In other instances, a company may voluntarily deregister its foreign-listed security for a variety of reasons or it may be dropped by the host market. We attempted to trace the life cycle of each listing by collecting information on the date it became inactive, using data from Datastream, the various ADR depositary program lists, and certain stock exchanges, where available. This information is at times also provided by Bloomberg Financial and Capital IQ. Admittedly, the exercise of accurately dating the termination of each foreign listing is very difficult because of the large number of possible termination scenarios. More important, it is almost impossible to determine and control for the underlying cause that forced the firm to delist (a merger, reorganization, bankruptcy, etc.). The close proximity between foreign listings and the IPO is not surprising because most firms would prefer financing early in their public life cycle (usually via an international equity offering), when the need for capital to finance growth is greatest. Table 3 summarizes, by geographic regions, the age distribution of firms conditional on the decision to cross list. We observe, for instance, that Asian and European firms prefer to cluster their primary listing (IPO) with secondary foreign listings. In contrast, cross listing for U.S. and Australian companies is less closely linked to the IPO, as the decision to cross list can be made several years after the primary offering. 1 AIM was first launched in 1995 primarily to attract small companies around the world that are often backed by venture capital. Since its inception, AIM has been very successful in attracting more than 2,500 companies that raised about $2.8 billion in new capital. An AIM listing is very appealing to many of these foreign companies because of its simplified regulatory environment specifically designed for the needs of smaller companies. Most of the AIM-listed companies would find it difficult to list on the more established international stock exchanges because of their more rigorous listing requirements. J. Risk Financial Manag. 2015, 8 164 More broadly, Table 4 illustrates that, together, the three major U.S. exchanges were the most influential stock market destinations among all competing locations throughout the whole time period, scoring significantly higher than the rest of the top-tier cluster of competitors, such as the London Stock Exchange, the Deutsche Börse, the Hong Kong Stock Exchange, and Euronext. At the same time, the table also reveals significant changes over time in the ranking across a consistent number of competing locations. We use this ranking reshuffling for identification purposes. Three main factors contribute to the ability of U.S. exchanges to maintain the highest ranking in global equity activity. The first factor is related to size. The main driver of the massive volume of IPO activity generated by U.S. companies is certainly the size of the U.S. economy. There may be various reasons why most firms continue to issue IPOs domestically (for example, the home-bias hypothesis), but the end result is that they continue to do so even when they could migrate abroad instead. Hence, the sheer size of equity activity continues to make U.S. capital markets very liquid and thus contributes to making U.S. exchanges very attractive to foreign companies. The second factor is that U.S. exchanges are the destination of choice for companies from most locations. According to the micro data, companies in 33 out of our 45 locations chose U.S. exchanges in 2006, and most of the remaining twelve locations were very minor to begin with. The third factor is that these exchanges are the destination of choice for many companies that originally were from very prestigious locations. In fact, in 2006, more than 83 percent of total IPO activity on U.S. exchanges was generated by companies from the top five most prestigious locations, while only 72 percent of London volumes, and 45 percent of Deutsche Börse volumes, came from the same cluster of locations. As argued earlier, these factors affecting a location’s prestige should be reflected in terms of potential benefits from expanded visibility, lower informational frictions and capital costs, with the reverse also possibly true, if a firm cross lists in a less visible location than the one of origin. 4. Specification of the Firm Valuation Model An approach commonly used for analyzing the aftermarket performance of cross-listing events is to focus on effects in firm value. Consistent with most of the financial literature, we proxy the value of firm (i) in year (t) by Tobin’s q ratio, or qti, where the numerator is defined by (Total Assets-Book Value Equity + Market Value Equity) and the denominator is equal to total assets (all variables are denominated in local currency). The first phase of our analysis looks at the most straightforward specification primarily designed to analyze firm valuation across many countries. In this framework, a company’s q ratio is determined by countryand firm-specific factors. More precisely, the model can be defined as: ti 0 1 t 2 C 3 I tC ti ti qIIqzx.         (2) The explanatory variable It is a binary indicator capturing time (yearly) variation and IC controls for country effects. Like many studies in the cross-listing literature that control for industry effects, the regressor qI represents the average q ratio of the NAICS industry in which the company is classified. The explanatory vector ztC⦁ represents country-specific controls that vary over time (for example, corporate governance scores and macroeconomic variables), and the vector xti⦁ controls for variation observed across the panel of firms. J. Risk Financial Manag. 2015, 8 165 The above model can be easily extended to analyze the impact of international listings. Our version of this broader model examining the impact of cross listings is defined by: ti 0 1 t 2 C 3 I 4 V tC ti MOTC ti M ti OTC ti ti qIIqIzx LL L .             (3) The explanatory variable Lti is a binary indicator of whether the firm has an existing foreign listing in year (t). In addition to this firm-level indicator of a primary cross listing, the variable IV is an indicator variable that controls for the specific calendar year of a firm’s cross listing and therefore intends to capture whatever degree of variability in the data is associated with specific cross-listing “vintages.” Some large internationally active companies choose to have multiple international listings. The dummy variable M to L gauges the importance of these multiple listings.3 The major U.S. stock exchanges (NYSE, AMEX, and NASDAQ) are the most popular primary cross-listing destinations, though many non-U.S. firms opt for a Tier I listing usually on the OTC Bulletin Board or a 144a private placement (Karolyi [35] provides an extensive discussion of foreign listings in the United States). While the principal goal of our analysis is to investigate the official cross listings on international exchanges having formal regulations and disclosure rules, we also include a dummy variable OTC ti L indicating the presence of these lower tier listings in United States.4 We investigate a more dynamic version of the above model by decomposing the aggregate effect of Lti into year dummy variables that capture potential firm valuation benefits of the listing over time and then examine whether these gains are more sustainable. The model specification can be adopted to trace the evolution of Tobin’s q K years after the cross listing: ti 0 1 t 2 C 3 I 4 V tC ti K MOTC j t j,i M ti OTC ti ti j0 qIIqIzx LLL.               (4) Essentially, this broader model decomposes the explanatory variable Lti into K+1 yearly dummy variables tracing the aftermath on firm value at the time of the foreign listing and K years after the event. As noted earlier, the primary goal of this paper is not only to analyze the impact of the listing action but also to understand the consequences of listing to a more or a less prestigious stock exchange. To achieve this goal, the specification uses two ways to capture the directional efficiency gains from listing in a more prestigious host market. First, we hypothesize that a firm will experience a positive (negative) valuation benefit after cross listing in a more (less) prestigious market. For simplicity, we standardize the time variable for each firm panel to be zero at the year of the cross listing. At t = 0, assume that the host market H for firm (i) has a prestige score H 0i P, while the prestige score for the domestic market D is D 0i P. The gap in prestige between the host and domestic markets is defined as 3 As shown in the descriptive section, most cross-listed companies in the sample typically have a single foreign listing (excluding unofficial listings in Germany, Level I U.S. listings, and private placements). 4 While the regression specification controls for the presence of an OTC U.S. listing, it does not track German unofficial listings. During the sample period, there were roughly more than 9,000 foreign unofficial listings on the Deutsche Börse and the regional German stock exchanges. J. Risk Financial Manag. 2015, 8 166 H,D H D 0i 0i 0i Gap P P (that is, the absolute value in the difference in the prestige scores between the host and domestic markets). To better capture the directional effects of cross listing on a more reputable stock exchange, we trace the impact after the cross listing by the explanatory variables H,D H,D tj,i tj,i 0i 0i MORE L Gap I    where H,D H D 0i 0i 0i I1ifPP0;   0  otherwise. Similarly, we define a move to a less prestigious stock exchange as H,D H,D tj,i tj,i 0i 0i LESS L Gap (1 I )    . While the explanatory variables tj,i MORE and tj,i LESS  are constructed to capture the valuation effect of moving to a more or less prestigious stock market destination, it is important to note that these are relative comparisons that eliminate all the synchronous economic cycles shared by global equity markets. For instance, if both origin and destination are going through a hot IPO issuance period, the relative difference in prestige rankings may not vary, meaning that the measures tj,i MORE  and tj,i LESS would remain fairly unchanged and should not influence firm value. Second, we argue that a company may benefit if it cross lists in a more reputable market abroad, but also that investors might further reward a firm for the subsequent improvements in prestige of its host market. We measure the improvement in prestige by K HHH ti ti 0i t1 I MPROVE P P .    (5) In effect, the variable H tj,i IMPROVE measures the evolution in the reputation of the host market after the cross listing ( t0). The current version of this improvement variable calibrates the ex post performance of the host-market destination.5 With these additional variables measuring the relative importance between the host and domestic markets, the final regression specification is written as MOTC ti 0 1 t 2 C 3 I 4 V tC ti M ti OTC ti KK H MORE, j t j,i LESS, j t j,i IMPROVE ti ti j0 j0 qIIqIzxLL MORE LESS IMPROVE .                  (6) Given the current specification, our regression analysis aims to test the following hypotheses: Hypothesis 1: A company will potentially garner significant valuation gains after cross listing in a host market with a higher prestige than its domestic market. A strong form of this maintained hypothesis asserts that 0MORE,j H: 0 versus the alternative that 1MORE,j H: 0.   A weaker version of this premise is defined by 0MORE H: 0 versus the alternative that 1MORE H: 0 , such that K MORE MORE, j 0(K 1)  ; that is, under the alternative hypothesis, the average valuation gain from cross listing over the post-listing period is positive. Hypothesis 2: By extension, we argue that a firm with a domestic listing on a prestigious market that opts to have a foreign listing on a less prestigious exchange will not enjoy any valuation benefits 5 However, it is conceivable that, even before the foreign listing, investors might consider ex ante improvements in the host’s prestige based on the historical performance of the host market. To accommodate this possibility, we also considered a version of H ti Iwhere the baseline is shifted from the year of the foreign listing (t = 0) to the first year that the firm had available public data. Overall, our empirical findings were very similar. J. Risk Financial Manag. 2015, 8 167 and could be adversely affected by this action. This hypothesis can be defined as 0LESS,j H: 0   versus the alternative that 1LESS,j H: 0 . Similarly, the weak form of this hypothesis is defined by 0LESS H: 0 versus the alternative that 1LESS H: 0  , where K LESS LESS, j 0(K 1)     . In addition to these direct gains of cross listing, we argue that a company may profit from listing on a host stock exchange that rises in prestige throughout the post-listing period. Hypothesis 3: A company with a foreign listing on a stock exchange that rises in prominence is likely to experience a boost in firm valuation. The null hypothesis of no improvement is defined by 0IMPROVE H: 0 versus the alternative 1 IMPROVE H: 0  . 4.1. Countryand Firm-Specific Controls To test these different hypotheses, our analysis includes a fairly comprehensive set of explanatory variables that includes country or stock market characteristics and measures of firm growth prospects. Furthermore, our analysis is the first to control for the life cycle of the firm that is an important determinant of value. The country-specific controls, denoted by the explanatory vector ztC⦁, include the gross domestic product per capita as a proxy for a country’s economic development (GDP_CAPITAL). In addition, the regression controls for a country’s scale of financial integration using the Penn Table index of trade openness (OPENNESS), measured by the sum of exports and imports divided by real GDP. The overall reputation of a location is likely to depend ultimately by the underlying institutional governance structure in a country. In order to test that our prestige measure does not simply reflect a country’s governance, we added into the regression the composite Heritage World Freedom Index (FREEDOM_SCORE). This index rates countries according to the degree of freedom they have across several dimensions (regulation, trade, fiscal, government, monetary, investment, financial, property rights, and corruption) and is similar in scope to other measures of “rule of law” protection such as those proposed by La Porta, Lopez-de-Silanes, Shleifer, and Vishny [36,37]. Levine and Zervos [38] show a strong link between various measures of financial development, banking development, and long-run economic growth. A convenient feature of the FREEDOM_SCORE is that it is measured yearly for every country or region in our sample. The explanatory vector xti⦁ controls for several firm characteristics. To allow for the possibility of nonlinear relationships, we use a quadratic functional form for both firm age (AGE) and size (SIZE). A firm’s size is proxied by total assets and its age is measured from year of incorporation. Both AGE and SIZE are good indicators of a firm’s life cycle. Although newly created smaller companies are riskier, they are expected to garner, on average, larger q valuations because of their higher growth potential. The specification includes two direct measures of the company’s financial strength: sales growth (SALES_GROWTH), measured by the change in logarithm of total sales, and the return-on-assets ratio (ROA). J. Risk Financial Manag. 2015, 8 168 Table 5. Definitions and Summary Statistics for Regression Variables. Explanatory Variables Definition Cross-Listed Non-CrossListed Difference Dependent Variable ti q Tobin’s q Tobin’s q ratio = (Total Assets − Book Value Equity + Market Value Equity)/Total Assets (percent) 144.61 135.54 −9.07 *** Country Controls tC Z  FREEDOM_SCORE Composite Heritage World Freedom Index (percent) 68.94 69.18 0.22 *** GDP_CAPITAL GDP per capita (percent) 83.81 75.95 −7.86 *** OPENNESS Trade openness (exports and imports)/real GDP (percent) 3.65 3.64 −0.009 Firm Controls ti x  SIZE Total assets (in $ millions) 4680.9 2055.8 −2625 *** AGE Age from time of incorporation (in years) 30.59 29.87 −0.728 *** ROA Return on assets (percent) 0.526 1.082 0.554 GROWTH_SALES Change in logarithm of total sales 0.1293 0.0478 −0.081 *** Cross Listing OTC t i L = 1 if firm (i) has a Level I U.S foreign issue at year (t); 0 otherwise 0.079 0.0216 −0.057 *** ti L =1 if firm (i) has cross listing at year (t); 0 otherwise 0.691 M t i L =1 if firm (i) has multiple listings at year (t); 0 otherwise 0.101 ti IMPROVE Cumulative improvement in the reputation of the host market after the cross listing −0.053 H,D H,D tj,i tj,i 0i 0i MORE L Gap I    Indicator (j) years after firm cross listed on a more prestigious exchange multiplied by the prestige score gap (percent) 0.577 H,D H,D tj,i tj,i 0i 0i LESS L Gap (1 I )    Indicator (j) years after firm cross listed on a less prestigious exchange multiplied by the prestige score gap (percent) 0.037 Firm-Year Observations 19,879 160,412 Notes: H 0i P= prestige index of the host market of firm (i) at the time of cross listing (t = 0). D 0i P=prestige index of the domestic market of firm (i) at the time of the cross listing (t = 0). H,D H D 0i 0i 0i Gap P P. H,D H D 0i 0i 0i I 1if P P 0; 0 otherwise. The symbols (*), (**), and (***) indicate statistical significance at the 10, 5, and 1 percent levels, respectively. Because of missing values, the number of year-firm observations varies by the variable. The table reports the maximum available number of firm-year observations. By definition, non-cross-listed firms do not have official listings; therefore they have missing values for cross-listing information. J. Risk Financial Manag. 2015, 8 169 Table 5 provides summary statistics for all the variables used in our regression analysis. We observe that firms that chose to have a cross listing attain higher Tobin’s q valuations relative to companies without any foreign listings. Firms with a foreign listing are domiciled in countries with higher GDP per capita, but generally have somewhat similar Freedom Index and openness scores. Not surprisingly, firms with cross listings are larger, with greater financial visibility and name recognition to complete a cross-border transaction. Consistent with their higher firm valuations, cross-listed companies also have significantly higher sales growth. 5. The Relationship between Firm Value and Cross Listings: Empirical This section discusses the impact of cross listings on firm value outlined by the regression specifications in the previous section. Our analysis focuses on the subset of companies that opted to have an international listing. This conditional approach provides the most effective way for assessing the valuation gains (losses) from cross listing in a more (less) prestigious market. The first column in Table 6 presents the baseline specification described by Equation (2) that focuses on the basic relationship between a country’s macroeconomic conditions and firm-specific factors and the q ratio during the period 1990–2006. This specification establishes a useful benchmark for assessing the contribution of an international listing. The coefficient estimates of this basic model confirm a strong link between the q ratio and the country’s underlying economic fundamentals. Companies operating in countries with better economic growth (measured by real GDP per capital) experience significantly larger valuation gains as investors expect these firms to be more profitable. Table 6. Conditional Regressions for Firms with Cross Listings Dependent Variable: Firm’s Tobin’s q. Firm Valuation Models: Explanatory Variables (2) (3) (4) (5) Intercept −16.355 −15.279 −17.560 −15.587 I q 1.066 *** 1.060 *** 1.057 *** 1.037 *** Country Controls tC Z FREEDOM_SCORE 1.568 *** 1.517 *** 1.559 *** 1.583 *** GDP_CAPITAL 2.769 *** 2.734 *** 2.756 *** 2.806 *** OPENNESS −0.318 *** −0.316 *** −0.321 *** −0.318 *** Firm Controls ti x SALES_GROWTH 1.029 ** 1.036 ** 0.981 ** 1.029 ** log(AGE) 0.955 1.497 3.649 3.129 log(AGE) 2 −0.768 * −0.839 * −1.150 * −1.054 * log(SIZE) −11.155 *** −10.929 *** −11.020 *** −10.991 *** log(SIZE) 2 0.576 *** 0.546 *** 0.555 *** 0.536 *** ROA 0.527 *** 0.527 *** 0.529 *** 0.532 *** J. Risk Financial Manag. 2015, 8 170 Table 6. Cont. Firm Valuation Models: Cross-Listing Effects OTC ti L −6.180 *** −6.047 *** −4.815 *** M ti L 5.336 *** 5.466 *** 5.325 *** ti L 3.568 ti IMPROVE 1.435 *** t0 , i L  :10.94 *** t0 , i MORE :0.904 *** t1 , i L  :5.15 ** t1 , i MORE :0.625 *** t2 , i L  :0.275 t2 , i MORE :0.372 ** t3 , i L  :1.154 t3 , i MORE :0.478 *** t4 , i L  :–0.643 t4 , i MORE :0.406 ** t5 , i L  :0.560 t5 , i MORE :0.420 ** t0 , i LESS :0.802 t1 , i LESS :−1.680 t2 , i LESS :−2.067 ** t3 , i LESS :−1.929 ** t4 , i LESS :−2.635 *** t5 , i LESS :−0.945 Hypothesis Testing: F-tests Hypothesis 1: 0MORE ,j H: 0,j 0, ,5 8.38 *** Hypothesis 1: 0MORE H: 0 45.69 *** Hypothesis 2: 0LESS ,j H: 0,j 0, ,5 3.23 *** Hypothesis 2: 0 LESS H: 0 10.71 *** Number of Observations 14,734 14,734 14,734 14,734 R-square 0.213 0.215 0.216 0.219 Notes: I q= average q ratio of the NAICS industry in which the company is classified. The remaining regression variables are defined in Table 5. In addition to these explanatory variables, the regression model includes year dummy effects, country fixed effects, and vintage effects (calendar year in which the firm does its cross listing). Standard errors are clustered by home country and year. The regression models were also estimated controlling for firm level fixed-effects. Overall, the findings were very similar. However, in this case the estimation sample is reduced because of the unbalanced nature of the panel. The symbols (*), (**), and (***) indicate statistical significance at the 10, 5, and 1 percent levels, respectively. Numbers in parentheses represent t-statistics. The empirical findings also reveal a strong positive relationship between the FREEDOM_SCORE and firm value, affirming the importance of financial structure and corporate governance. In particular, the strong link between the freedom score and the q ratio indicates that companies operating in an environment governed by strong economic and political principles enjoy higher valuations. This finding is consistent with the bonding hypothesis arguing that cross listings enable companies to strengthen outside investor protection by raising capital in a market with more rigorous laws and regulations and better corporate governance principles [10,11]. In addition to the Freedom index, the regression also controls for the impact of international economic integration (OPENNESS), measured J. Risk Financial Manag. 2015, 8 171 by the sum of exports and imports divided by real GDP. We observe a negative relationship between trade openness and firm value. This result appears somewhat surprising given that the freedom index and trade openness are positively correlated. However, these two indexes produce different country rankings, which might account for their differential effect. For instance, Japan ranks in the top tier in terms of economic freedom, but achieves very low trade openness scores that are more comparable to those of India. Firm characteristics and financial performance are also key components of valuation, as investors are expected to aggressively price any changes in these factors. The regression model controls for these nonlinear life cycle effects by including AGE (time from the year of incorporation) and AGE2.6 A company’s age is an important determinant because younger companies with a much better growth outlook are often rewarded with higher q ratios. Indeed, we discover that the relationship between firm age and firm value is concave, dissipating as the company gets older. In comparison, we observe a convex relationship between a firm’s size and value. The importance of company growth is also seen in the significant and positive coefficient of SALES_GROWTH, a finding that is consistent with several other studies in the literature. The second and third columns in Table 5 summarize the parameter estimates of the regression specifications defined by Equations (3) and (4). In addition to firmand country-specific effects, these models also investigate the impact of foreign listings. We observe that the simple binary variable Lti, indicating the presence of a cross listing, is not statistically significant, although it is positively related with firm value. To better gauge the timing of investor response, we decompose the single cross-listing dummy into six yearly indicators that trace the effect over a five-year period after the cross listing (including year 0, representing the time of the foreign listing). Consistent with the findings of Doidge, Karolyi, and Stulz [13] and Sarkissian and Schill [23], the results of this more dynamic specification appear to suggest that the benefits of cross-border listings are concentrated primarily at years 0 and 1. In particular, the coefficient estimate of year 0 reveals an immediate boost in valuation of 10.94 percent from the foreign listing. These valuation gains appear to be transient, however, as they dissipate and are not statistically significant in the years following the cross listing. Another interesting finding of the regression results is that firms cross listing in multiple locations experience a significant increase in their q ratios. More specifically, the presence of a multiple listing raises the q ratio by about 5.4 percent. As illustrated in Table 2, however, multiple listings are uncommon with only about 240 firms in our sample opting to have more than one foreign listing in official market destinations. Considering the relatively low frequency of multiple listings, it is more difficult to decompose M ti L by year to further understand the timing of these gains. In general, most of these additional foreign listings occurred after the primary foreign listing. One reason for the strong positive impact is that multiple listings are a good proxy for a company’s intensity of internationalization and global growth opportunities. 6 An alternative approach is to measure age from the time of the IPO. As shown previously, a firm’s public age is closely linked with the decision to cross list. However, measuring age from the time it was established is perhaps more closely linked with the q ratio because it captures more accurately a firm’s growth life cycle and value creation. J. Risk Financial Manag. 2015, 8 172 To better understand the importance of host-market prestige, the last column in Table 6 summarizes the findings of the specification that controls for the directional benefit of listing on a more or a less prestigious market, measured by the explanatory variables tj,i MORE  and tj,i LESS , respectively. Furthermore, we decompose these directional variables to trace the response at time 0 (year of foreign listing) and over the five years following the listing. As expected, companies are inclined to cross list on more reputable exchanges; therefore, more than 75 percent of the primary foreign listings are placed in more prestigious host markets. Given our large sample of foreign listings, however, there are an adequate number of observations for estimating the parameters of the tj,i LESS variables. More important, the gap in prestige between the host and domestic markets H,D 0i Gap is evenly distributed across these two directional variables.7 The regression results highlight a significant difference in the response of firm value to cross listing on a more (or less) prominent stock exchange. The benefits of a foreign listing on a prestigious market are positive and very significant, not just around the time of the listing but also for some time thereafter as firms continue to reap higher valuations over the five years following their foreign listing. In contrast, we observe that companies with a foreign listing on a less prestigious stock market experience a significant decline in their q ratios. At the bottom of Table 6, we report Wald F-statistics that test Hypotheses 1 and 2. Based on these formal statistical tests, we cannot reject the alternative hypotheses that either 1MORE,j H: 0 or 1LESS,j H: 0  . These results underscore the significant disparity in valuations between companies cross-listed on a more or a less prestigious stock exchange. To better understand the economic effect of these directional variables, we need to adjust for the scale of the gap between the host and domestic markets. The average effect over this six-year post-listing period MORE  is 0.53. A one-standard-deviation increase in H,D 0i Gap (around 10 percent) produces roughly a five percent boost in firm value. Similarly, we find that LESS  is roughly around −1.4, meaning that firms opting for a less prestigious market suffer a comparatively more significant decline in their q ratios. The valuation discount is particularly large one to four years after the cross listing. Interestingly, investors appear to be less punishing on companies cross listing on less reputable destinations at (t = 0). The response to a one-standard-deviation increase in the prestige gap between host and domestic markets is about −14.5 percent, representing a substantial drop in firm value. The significant higher valuation signified by some of the positive coefficients of MORE, j  is not surprising given the large number of studies cited previously outlining several potential benefits of cross listing on a more reputable stock market (for example, improved firm visibility, lower cost of capital, enhanced liquidity, and stronger investor protection). In contrast, the reasons behind the significant decline in the q ratio indicated by the negative value of LESS are less clear. Why should investors be concerned whether a firm cross-lists on a less prestigious exchange? For one, companies with a primary listing in a prestigious market should already enjoy the certification and financial access benefits domestically irrespective of whether they elect to have a secondary foreign 7 The average H,D 0i Gap over the entire sample is 8.9 percent. The maximum gap of 25 percent represents a cross listing from Ireland to the United States, while the minimum gap score of −21 percent corresponds to a cross listing from the United Kingdom to South Africa (recall that U.S. companies’ overseas listings are excluded from our analysis). J. Risk Financial Manag. 2015, 8 173 listing in a less prestigious location. However, their choice to cross-list on a stock exchange with poor financial infrastructure and inferior investor protection rules could be alarming to some investors. In fact, our regression analysis provides additional evidence that the valuation discount for firms that cross list in lesser stock markets is not spurious. The negative coefficient on OTC ti L indicates that Level I listings on the OTC in the United States are poorly received by investors, lowering a firm’s q ratio by about 6.2 percent. This finding reinforces the view that market perceptions are indeed influenced by the reputation of the host destination. Most of the OTC foreign listings are sponsored or unsponsored ADRs that have minimal reporting SEC requirements. Foreign companies listing on the OTC are not required to publish reports in compliance to U.S. GAAP and generally such a listing would not be expected to provide any certification benefits. Foreign firms with Level I listings generally do not have access to U.S. capital markets and are therefore unable to raise capital at lower cost to enhance growth opportunities. Arguably, a U.S. OTC listing by foreign firms could be counterproductive, creating the impression that they are not capable of satisfying more prudent disclosure requirements. This adverse market reaction to cross listing in a destination with minimal disclosure requirements is not unique to the U.S. OTC market. Sarkissian and Schill [16] examine the impact of foreign listings on several large international stock exchanges. They find a negative valuation effect in Luxemburg, arguably not a very reputable host destination with weak disclosure requirements given its off-shore and tax-heaven status. Cross listing in a less prestigious market could also indicate a weaker financial outlook. These firms can be viewed as lacking the financial strength and prospects to move to a more prestigious destination. However, the empirical evidence is not very supportive of this premise. Generally, we find that firms cross listing in less reputable markets are actually more profitable than their peers that cross listed in more prestigious markets. Our empirical evidence is therefore more supportive of the premise that a secondary listing in a less prestigious market could distort a firm’s financial visibility and corporate governance profile, resulting in a valuation discount. The decrease in firm value may also be consistent with the presence of agency problems [39]. Agency theories argue that overoptimistic managers with misaligned incentives are more likely to squander the firm’s cash flows on riskier negative net-present-value projects. Claessens and Schmukler [40] document a close link between the company’s foreign sales ratio and the likelihood of a foreign listing. Thus, a firm’s move to a less prestigious destination may also be followed by an expansion of its operations in that host market. Investors might be troubled by the possibility that the company might decide to operate and invest in a host destination with greater uncertainty. When we turn our attention to analyzing the importance of the post-listing improvement in the prestige index of the host market (Hypothesis 3), the parameter estimate of H ti IMPROVE is positive and statistically significant. The ability of an exchange to improve its reputation among its competitors therefore has a positive influence on its own cross-listed companies. The overall impact is not large compared to the actual cross listing on a more prestigious market. A one-standard-deviation increase in H ti IMPROVE generates about a 1.5 percent increase in the q ratio. Our evidence so far has revealed a strong asymmetric investor response to companies with cross-border listings on host markets that are more or less prestigious. Many of the earlier studies analyzing the various facets of international listings have focused primarily on foreign firms (non-U.S. J. Risk Financial Manag. 2015, 8 180 31. Brin, S.; Page, L. The Anatomy of a Large-Scale Hypertextual Web Search Engine. Proc. Seventh Int. Conf. World Wide Web 1998, 7, 107–117. 32. Carter, R.; Manaster, S. Initial Public Offerings and Underwriter Reputation. J. Finance 1990, 45, 1045–1068. 33. Carter, R.; Dark, F.; Singh, A. Underwriter Reputation, Initial Returns and Long-Run Performance of IPO Stocks. J. Finance 1998, 53, 285–311. 34. Fang, L.; Yasuda, A. The Effectiveness of Reputation as a Disciplinary Mechanism in Sell-Side Research. Rev. Financ. Stud. 2009, 22, 3735–3777. 35. Karolyi, A. Why Do Companies List Shares Abroad? A Survey of the Evidence and its Managerial Implications. Financ. Markets, Institutions, and Instruments, 1998, 7, 1–60. 36. La Porta, R.; Lopez-de-Silanes, F.; Shleifer, A.; Vishny, R. Legal Determinants of External Finance. J. Finance 1997, 52, 1131–1150. 37. La Porta, R.; Lopez-de-Silanes, F.; Shleifer, A.; Vishny, R. Law and Finance. J. Polit. Econ. 1998, 106, 1113–1155. 38. Levine, R.; Zervos, S. Stock Markets, Banks, and Economic Growth. Am. Econ. Rev. 1998, 88, 537–558. 39. Jensen, M. Agency Costs of Free Cash Flow, Corporate Finance, and Takeovers. Am. Econ. Rev. 1986, 76, 323–329. 40. Claessens, S.; Schmukler, S. International Financial Integration through Equity Markets: Which Firms from Which Countries Go Global? J. Int. Money Finance 2007, 26, 788–813. 41. Krigman, L.; Shaw, W.; Womack, K. Why Do Firms Switch Underwriters? J. Financ. Econ. 2001, 60, 245–284. 42. O’Brien, P.; Bhushan, R. Analyst Following and Institutional Ownership. J. Acc. Res. 1990, 28, 55–65. 43. Falkenstein, E. Preferences of Stock Characteristics as Revealed by Mutual Fund Portfolio Holdings. J. Finance 1996, 51, 111–135. 44. Chung, K.; Jo, H. The Impact of Security Analysts’ Monitoring and Marketing Functions on the Market Value of Firms. J. Financ. Quant. Anal. 1996, 31, 493–512. 45. Committee on Capital Markets Regulation. Interim Report of the Committee on Capital Markets Regulation. Available online: http://www.capmktsreg.org/ (accessed on 17 March 2015 .). © 2015 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/4.0/).