The Colors of Investors’ Money: Which Firms AttractInstitutional Investors From Around the World?∗

Miguel A. Ferreira†

ISCTE Business School-LisbonCEMAF

Pedro P. Matos‡

Marshall School of BusinessUniversity of Southern California

This Version: February 2006

Abstract

We study institutional investors’ stock holdings around the world using a compre-hensive data set from 27 countries. Three groups of institutions based on their geo-graphic origin (U.S., non-U.S. foreign, and domestic managers) have equal importancein the shareholder base of non-U.S. corporations. Thus, we offer a global (non-U.S.centric) view on what firm- and country-level characteristics attract investment by in-stitutional investors. We find that all institutions reveal a strong preference for largeand liquid stocks with good governance practices. There is, however, a substantialdiversity between domestic and foreign institutions with respect to other firm charac-teristics. Foreign investors overweight stocks that are cross-listed in the U.S., membersof the MSCI indexes, and globally visible through high foreign sales or analyst coverage.Domestic institutions, in contrast, seem to underweight these same stocks. The cross-listing effect is not concentrated in the holdings of ADRs as a significant increase in theholdings of local shares by foreigners is found, which sheds some light on “multi-markettrading” and the ”flow-back” phenomena. Our results show an important characteris-tic of modern international capital markets as firm and investor actions take place ininter-connected markets. Finally, we find that foreign institutional ownership has realeffects as it is positively associated with higher firm valuation.

∗We thank Andrew Karolyi, Michael Schill, and seminar participants at the University of SouthernCalifornia for helpful comments. This research is supported by FCT/POCI 2010.

†Address: Complexo INDEG/ISCTE, Av. Prof. Anibal Bettencourt, 1600-189 Lisboa, Portugal. Phone:+351.21.795.8607. Fax: +351.21.795.8605. Email: miguel.ferreira@iscte.pt.

‡Address: Hoffman Hall-701, MC-1427, 701 Exposition Blvd., Ste. 701, Los Angeles, CA 90089-1427,USA. Phone: 213.740.6533. Fax: 213-740-6650. Email: pmatos@marshall.usc.edu.

1. Introduction

A key element in modern capital markets is the interplay between firms that increasingly

raise capital internationally, and institutional investors that manage growing pools of assets.

Many individual investors around the world are selecting mutual funds, pension funds, or

retirement products offered by insurance companies and banks, as their main investment

vehicle. Institutional investors managed over US$ 35 trillion of assets (stocks and bonds)

in Organization for Economic Co-operation and Development (OECD) countries in 2001

(OECD (2003)), which represents a substantial share of these countries’ retirement savings

and other wealth. The importance of institutional investors is also rapidly increasing in

emerging market countries (e.g., International Monetary Fund (2004), and Khorana, Servaes,

and Tufano (2005)). These professional money managers allocate a significant share of their

assets in the stock market. They have become major players in their domestic stock markets,

and they are more likely to invest abroad than individual investors. Most publicly-traded

corporations in many countries have now institutional investors as their largest (minority)

shareholders. These institutional investors could be a U.S.-based mutual fund manager, a

domestic pension fund, or a global professional money manager.

This paper uses a novel database on institutional investor holdings around the world to

study the stock preferences of institutional investors from 27 countries. What firm char-

acteristics attract institutional investors including domestic institutions as well as foreign

(U.S. and non-U.S.) institutions? Our ultimate goal is to study the impact of institutional

investors in the shareholder base of corporations. The data set contains stock-level holdings

from more than 3,000 institutions (more than 22,000 funds) from 27 countries, with posi-

tions totaling US$ 6.8 trillion in more than 25,000 stocks as of December 2004. This research

focus on the preferences of institutional investors when investing in non-U.S. stocks, which

account for US$ 2.6 trillion of the holdings in December 2004. U.S. institutions hold, on

aggregate, over US$ 0.9 trillion overseas in non-U.S. stocks. This is matched by non-U.S.

institutional investors that hold US$ 0.9 trillion overseas in non-U.S. stocks, and an addi-

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tional US$ 0.8 trillion in their domestic markets in local stocks. Thus, while most previous

academic research has looked at U.S. investors as the primary source of capital, modern

corporations worldwide are finding that three pools of professional investors (U.S., non-U.S.,

and domestic) have approximately equal pocket sizes.

We study the revealed stock preferences of these three different institutional investor

clienteles, and investigate what firm- and country-level characteristics attract these insti-

tutions as shareholders. First, we find that all institutional investors, irrespective of their

geographic origin, share a preference for large, liquid, and widely-held stocks (i.e., with-

out large controlling blockholders). Second, all institutions reveal a preference for stocks of

countries with strong disclosure standards and geographically close to their home market.

Third, foreign institutional investors have a strong bias for firms that are members of the

Morgan Stanley Capital International (MSCI) All Country World Index and that are cross-

listed in the U.S. market by the way of an American Depositary Receipt (ADR). Domestic

institutions, in contrast, underweight these same stocks. Foreign and domestic institutional

investors display other divergences in their stock preferences. Foreign institutions tend to

avoid high dividend-paying firms, while these same firms are favored by domestic institu-

tions. Foreign asset managers exhibit higher demand for firms with “name value” and foreign

visibility (i.e., high foreign sales and analyst coverage). Finally, U.S. and non-U.S. foreign

investors disagree on holding value versus growth stocks and on what are their favorite target

markets. U.S. institutions show a clear preference for English-speaking countries and less

developed markets when they decide to go abroad, while non-U.S. investors hold relatively

more stocks in non-English-speaking countries and more developed markets. We conduct

several robustness checks on these findings and examine in more detail stock preferences by

investors from different geographical regions.

Overall, there are both similarities and diversity in the revealed stock preferences of the

various groups of institutional investors based on their geographic origin. The analysis is

conducted on a sample of worldwide institutional investors’ individual stock holdings over

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the 2000-2004 period. Thus, our findings are not hampered by studying: foreign ownership

in firms from a single country (Japan as in Kang and Stulz (1997) or Sweden as in Dahlquist

and Robertsson (2001)); foreign ownership by investors from a single origin country (U.S. in-

vestors as in Aggarwal, Klapper, andWysocki (2005), Ammer, Holland, Smith, andWarnock

(2005), and Leuz, Lins, andWarnock (2005)); institutional holdings using country-level port-

folio allocations (Chan, Covrig, and Ng (2005)); institutional holdings from just one class of

institutions (mutual funds as in Chan et al. (2005) and Covrig, Lau, and Ng (2005)); insti-

tutional holdings using a single year of observations (as in Ammer et al. (2005), Chan et al.

(2005), and Covrig et al. (2005)). In addition, our data set also contains U.S. stock holdings,

which allows us to investigate U.S. institutions behavior at home, and match many of the

stylized facts documented in Gompers and Metrick (2001) in their study of U.S. domestic

institutional holdings.

We find evidence of diversity between foreign and domestic investors preferences (and

also between U.S. and non-U.S. investors when they invest abroad). Thus, corporations

can attract foreign capital more effectively by cross-listing their shares in major financial

centers in which institutional investors operate. One of the most prominent mechanisms in

recent years has been to list shares in the U.S. market by the way of an ADR program.

The argument is that the firm can tap into the pool of assets managed by U.S. investors

who do not venture abroad because of transaction costs or unfamiliar practices, or even into

the pool of assets managed by non-U.S. investors who prefer to trade in the U.S. market.

The shares of cross-listed firms can potentially become more liquid and the firm can have

access to external funds at a lower cost in the future. A countervailing argument, however,

is that there may be very few U.S. institutional investors who cannot invest directly overseas

(Financial Times (2004)). We test whether there is indeed a cross-listing effect, i.e., whether

a firm is able to expand its foreign shareholder base when it cross-lists in the U.S. We

find evidence of a significant increase in U.S. institutional holdings when a firm launches

an ADR program. Moreover, firms are also able to capture a higher fraction of non-U.S.

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foreign institutional investors. In total, foreign investors hold 5 percentage points more of

the market capitalization of cross-listed firms than they would hold otherwise. We account

for the potential selection bias as firms that decide to cross-list can be the type of firms that

foreign investors would tend to hold regardless of the cross-listing.

To further investigate this endogeneity issue, we isolate the 101 firms that launched an

ADR during our sample period (2000-2004). We find evidence that these firms experience an

increase in their shareholder base around the time of the cross-listing in the U.S. Although

foreign investors already have holdings in local shares of those firms prior to the ADR, they

substantially increase their position at the time of the cross-listing in the U.S. Interestingly,

however, the increase mainly accrues in local shares holdings rather than in the ADR shares

directly. This finding sheds light on the ADRs “flow-back” phenomenon, i.e., after an initial

blip in U.S. trading of ADR shares, trading moves back to the more liquid domestic exchange

(Karolyi (2003) and Halling, Pagano, Randl, and Zechner (2004)). Even though trading is

not retained by the U.S. exchanges, cross-listed firms attract extra foreign investors on board

(both U.S. and non-U.S.) who are making the trip to the firm’s home market and invest in

local shares.

In a concluding analysis, we investigate whether the presence of foreign and domestic in-

stitutional ownership drives up firm’s valuation and, consequently, reduces its cost of capital.

Following the related literature (e.g., Lins (2003), Doidge, Karolyi, and Stulz (2004), and

Durnev and Kim (2005)), we regress firm’s Tobin’s Q ratio on firm-, industry-, and country-

level variables, including the fraction of shares held by foreign or domestic institutional

investors as a potential determinant of firm valuation. We find that foreign institutional

ownership has a significant positive impact on firm valuation, unlike domestic institutional

ownership. Because institutional ownership is likely to be jointly determined with firm’s

Tobin’s Q ratio and driven by other firm characteristics, we re-estimate the Tobin’s Q and

institutional ownership equations as a system of simultaneous equations. We find that the

effect prevails and accordingly there exists a strong positive relation between institutional

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foreign ownership and firm valuation.

Our empirical results provide evidence of the real effects of a firm’s shareholder base in an

international capital markets setting. Our findings are consistent with market segmentation

theories (Merton (1987)) that firms held by a larger investor base have lower expected returns

demanded on their stocks. Other papers have analyzed how investor recognition reduces the

cost of capital, whether by cross-listing or firm’s foreign visibility (Foerster and Karolyi

(1999) and Doidge et al. (2004)). Our results, however, go one step further and offer a

direct link between foreign (institutional) shareholder presence and firms’ valuations. Our

findings support the idea that the expansion of the foreign institutional ownership base is

one of the channels by which cross-listing in the U.S. market reduces firms’ cost of capital.

An alternative interpretation of our findings, however, is that firms that attract foreign

investors can become overvalued. The rise in firm valuations can also be evidence of price

pressure effects when a foreign investor clientele buys into a stock. It is empirically difficult

to distinguish between these two interpretations. Recent literature on cross-listing argues

that firm valuation benefits of internationalization are transitory and dynamic (Levine and

Schmukler (2005) and Sarkissian and Schill (2005)).

The results here also give additional insights to the issue of whether country-level gov-

ernance and firm-level governance are substitute or complementary mechanisms. Recent

research (Doidge, Karolyi, and Stulz (2005) and Stulz (2005)) finds evidence that firm-level

governance levels are in large part driven by country characteristics. We find, however, that

foreign and domestic investors decisions are largely driven by firm characteristics (and more

so, than by country-level characteristics). Institutions’ stocks preferences show that investors

engage in firm-level analysis, and they dedicate particular attention to several firm-level

governance indicators. In addition, we find that institutions are more sensitive to firm-level

governance mechanisms in countries with weak country-level investor protection and qual-

ity of institutions. These findings support a substitute role between firm and country-level

mechanisms, rather than a complementary role. Thus, investors track firm-level governance

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indicators (besides country-level governance), and there is ”hope” for a ”good” firm in a

”bad” country.

The remainder the paper is organized as follows. Section 2 presents the institutional hold-

ings data, the sample of firms, and the determinants of institutional ownership. In section 3,

we conduct our tests on what firm and country characteristics attract institutional investors.

We also present a detailed investigation of the cross-listing effect on institutional ownership,

in particular foreign ownership. In section 4, we study the valuation effects of foreign and

domestic institutional ownership. Section 5 concludes and discusses the implications of our

work.

2. Data Description

2.1. Institutional Investors Holdings Data

The institutional investors holdings data are drawn from the FactSet/LionShares ownership

database, which is the leading information source for global institutional share ownership.

FactSet/LionShares data feeds leading financial information providers such as Reuters, MSN

Money, and brokers like E-Trade. Additionally, major information providers of ADRs, such

as The Bank of New York (www.adrbny.com) and J.P. Morgan (www.adr.com) also rely on

FactSet/LionShares as the source for institutional holdings of ADRs.

FactSet/LionShares data sources are public filings by investors, companies, and security

agencies around the world. Institutions have discretionary control over assets under manage-

ment and are frequently required to publicly disclose their holdings. For securities traded on

major U.S. exchanges, FactSet/LionShares gathers institutional ownership information via

the mandatory 13F filings with the Securities and Exchange Commission (SEC) as well as by

“rolling up” the sum of shares held by the individual mutual funds (N-30D filings with the

SEC) managed by a particular fund management company. FactSet/LionShares also uses

the “rolling up” method to gather ownership data for securities that are traded outside the

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U.S. (i.e., shares traded in local markets). Additionally, a data collection center in France fa-

cilitates the collection of ownership data from non-U.S.-based institutions such as European

and offshore mutual funds, from sources such as stock exchange announcements, data feeds,

proxies, and annual reports. Finally, it uses data from the mutual fund industry directories

(e.g., European Fund Industry Directory) and country-specific regulatory agencies, and a

variety of other property resources.

We use the historical filings of the FactSet/LionShares database. The historical coverage

extends from January 2000 to December 2004. We consider all stock holdings (ordinary

shares, preferred shares, ADR, GDR, and dual listings) and handle the issue of different

report frequency by institutions from different countries by getting the latest holdings update

at each quarter-end. The data comprises institutions located in 27 different countries (K)

and stock holdings from 48 destination markets (J).1 This data set offers a unique worldwide

K × J panel data (when aggregated at the country-level) for each quarter of the last fiveyears. As of December 2004, FactSet/LionShares has holdings data on each firm 25,502

stocks, of which 18,474 are issued outside the U.S., for a total market value of US$ 6.8

trillion. The holdings are for each of 22,111 individual funds run by a total of 3,031 different

institutions (such as mutual fund companies, pension funds, bank management divisions,

and insurance companies). To our knowledge, this is the most comprehensive data set on

institutional holdings available.

While the holdings data is at the each security, each fund level, we compare the total

holdings per country and year with other country-level aggregate data sources. Some official

statistics aggregate all institutional investors categories (OECD (2003b)) or just the mutual

fund industry segment (European Fund and Asset Management Association (2005) statistics,

Chan et al. (2005), and Khorana et al. (2005)). For most countries, our holdings exceed the1For a group of 21 other countries (such as Argentina, Brazil, China, and Czech Republic) Lion-

Shares/Factset does not have institutional holdings coverage but contains stock holdings from foreign insti-tutions on local stocks. We keep these foreign stock positions in our tests, but the main results of the paperdo not change if we restrict the sample to the 27 countries for which both institutions and stocks coverageis available. Results are available from the authors upon request.

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values reported in those sources for just the mutual fund / Sicav industry segment, and are

close to the OECD aggregate numbers for all institutional investor stock holdings. A detailed

comparison is available from the authors.

To summarize the coverage of the institutional holdings data, Table A.1 in Appendix A

presents the total equity assets held by institutions domiciled in each country at the end of

each of the sample years from 2000 to 2004. U.S.-based institutions are by far the largest

group of professional managers of equity assets. When we detail the top five institutions by

equity assets under management (i.e., the largest 13F entities) in December 2004, we find

leading mutual fund families such as Fidelity, Capital Research and Management, Vanguard,

and Wellington, but also the largest U.S. pension fund manager, TIAA-CREF. The Fact-

Set/LionShares data also details stock holdings at the individual fund level and we find that

TIAA-CREF’s Stock Fund exceeds in assets the largest stock mutual fund (Vanguard’s 500

Index Fund).

Other countries with large institutional investors are the U.K., Germany, Canada, and

France followed by other nations for a total of 27 countries for which FactSet/LionShares

gathers institutional stock holdings data. Most of the leading managers in each country

are well-known financial institutions. While some of countries’ leading fund managers are

divisions of banks like Deutsche Bank’s DWS for Germany, or CDC IXIS and BNP Paribas

for France, in other countries the largest equity managers are public pension funds, like in

Canada where the largest entity is the Canada Pension Plan or Ontario Teacher’s Pension

Plan, and Norway where the largest entity is the State’s Petroleum Fund managed by Norges

Bank. Domicile of the managing institution and of the individual fund can differ as shown by

the large number of international funds, and relatively less institutions, that are domiciled

in Luxembourg.

FactSet/LionShares comprises holdings of domestic and foreign securities for institutions

across all countries listed in Table A.1. To summarize the stock allocations by country of

origin of the institution (in row) and country of destination (in column), Panel A of Table

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A.2 presents the holdings data, as of December 2004, in matrix form. Institutions as a whole

managed a total of US$ 6.8 trillion of equity assets, with almost US$ 2.2 trillion invested

cross-border (the sum of the off-diagonal elements in the matrix), or US$ 1.9 trillion of

non-U.S. foreign stock holdings (i.e., excluding the U.S. as destination market).

Focusing on all non-U.S. destination markets, we find that domestic institutional investors

with US$ 829 billion in market value are on equal footing to U.S. foreign institutions (US$

944 billion) and non-U.S. foreign institutions (US$ 927 billion) — see last column of Panel B

of Table A.2. Thus, on aggregate, non-U.S. firms across the world attract money from three

investor clienteles with roughly equal pocket sizes. For example, French firms (column “FR”

in Panel A of Table A.2) attract a total of US$ 261 billion investment from institutional

investors, led by French-based institutions (US$ 77 billion — row “FR”), followed by U.S.-

based asset managers (US$ 66 billion — row “US”) and institutions from Germany and the

U.K. that add up to another US$ 69 billion. This example illustrates how the three type of

institutional investors (domestic, U.S., and non-U.S. foreign investors) are equally important

as shareholders for corporations around the world.

Panel C of Table A.2 shows the fraction of each country’s stock market capitalization that

is held by institutions. FactSet/LionShares institutional stock ownership is the greatest, as

expected, in the U.S. stock market, but global institutional portfolio managers hold large frac-

tions of stock market capitalization in countries such as Canada (25%), Sweden (25%), and

Denmark (18%). However, not all shares issued by corporations can be held by institutions,

as a significant fraction is closely-held by large shareholders in some countries. Correcting for

the market-level percentage of closely-held shares (available from WorldScope), we compute

in Panel D the investable market float per country. If we consider the percentage of market

float held by institutional investors, countries such as Norway (34%), U.S. (32%), Sweden

(32%), Canada (31%), Germany (19%), and France (18%) present the highest institutional

ownership.

The presence of domestic relative to foreign institutions varies across countries, for exam-

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ple foreigners matter more in France (5% of market float is in hands of domestic managers

versus 13% in foreigners) than in the Sweden (21% in domestic versus 11% in foreigners).

And when we breakdown into U.S. institutions versus non-U.S. foreign institutions, U.S. in-

vestors are relatively more present in France (5%) than in Sweden (4%). To provide a feel of

the data, we take the specific cases of the largest French company (Total SA) and the largest

Swedish (Ericsson Telefon AB) as of December 2004 and list their top five institutional

investors:

Total SA Ericsson Telefon AB

Market capitalization = US$ 138 billion Market capitalization = US$ 48 billion

Total institutional ownership = 30% Total institutional ownership = 33%

Top five institutions (country, % held): Top five institutions (country, % held):

. CDC IXIS Asset Mgt (FR, 2.2% local) . Robur Fonder (SE, 2.7% local)

. Fidelity Mgt (U.S., 1.2% ADR) . Fidelity Mgt (U.S., 1.7% ADR)

. Capital Research & Mgt (US, 0.9% local) . Alecta Pensionsforsaking (SE, 1.7% local)

. Norges Bank (NO, 0.7% local) . Nordea (SE, 1.5% local)

. Wellington (U.S., 0.7% ADR) . SEB Fonder (SE, 1.3% local)

This example illustrates how these companies have domestic, U.S., and foreign non-U.S.

institutions among their leading shareholders. Also investors opt differently to have their

holdings through local shares or ADRs.

2.2. Determinants of Institutional Ownership

The main focus of the paper is to examine the determinants of the level of institutional

investors’ participation in international firm’s ownership. We consider both firm-level and

country-level characteristics that attract or deter institutional investment as suggested by

different branches of literature.

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2.2.1. Firm-Level Characteristics

Institutional Trading and Investing Strategies: A first factor determining institu-

tional investment is institutional “preferences”. While this seems somewhat circular, what

we mean is that there are some stylized investment policies documented in the context of

U.S. markets followed by institutional investors that distinguish them from other types of

investors (such as individual investors). There are reasons to expect that some of these pref-

erences are also revealed internationally by U.S. institutions. However, when an institution

invests outside of its domestic stock market it can behave differently. Furthermore, non-U.S.

institutions can act differently from U.S. institutions as they operate in distinct environ-

ments. The major “institutional preferences” previously documented are the following:

• Firm Size (SIZE): Invest in large stocks. The preference for large firms is docu-

mented in Falkenstein (1996) and Gompers and Metrick (2001) who find stock market

capitalization to be a major driver of the level of institutional (and mutual fund) own-

ership in the U.S. Dahlquist and Robertsson (2001) find similar preferences for Swedish

firms. Size may be even more of a factor in international investment, because of greater

concerns investors have over liquidity and transaction costs.

• Book-to-Market (BM): Invest in value stocks. Gompers and Metrick (2001) suggestthat more sophisticated investors such as institutions can exploit the value anomaly.

Thus, institutions should invest in high book-to-market stocks to earn higher excess

returns. Gompers and Metrick (2001) find weak evidence of institutions favoring value

stocks, however. We explore whether this investment strategy is pursued internation-

ally.

• Investment Opportunities (INV OP ): Invest in growing firms. The higher the realinvestment prospects of a firm, the more likely it is to attract institutional investors’

attention. A measure used in previous literature is the annual sales growth rate as

in Doidge et al. (2004) and Durnev and Kim (2005). We investigate whether global

11

institutional investors are attracted by firms with stronger investment opportunities

(and probably more need for external financing).

• Past Return (RET ): Chase recent outperforming stocks. Institutions are potentiallymomentum investors. First, there is some evidence and industry knowledge of the

”momentum effect” in return patterns, i.e., abnormal returns can be obtained by hold-

ing stocks that have performed well in recent times (Gompers and Metrick (2001)).

In addition, many observers have depicted foreign institutions as “hot money” chasing

“hot markets”, while domestic investors tend to be contrarian (Grinblatt and Kelo-

harju (2000)). We entertain this possibility by seeing whether a stock with high recent

stock returns (past 12-month) attracts higher investment from foreign versus domestic

institutions.

• Stock Market Turnover (TURN): Invest in liquid stocks. Institutions demand moreliquidity in their investments than other investors because of being delegated portfolio

managers. They prefer stocks that have a deeper market, where they can enter and

exit easily (Gompers and Metrick (2001)).

”Prudent-Man” Rules: Due to the fiduciary responsibility fund managers have to the

ultimate owners of the assets they manage, many managers are constrained by ”prudent

man” rules that are designed to limit the risk of their investments. These can be just a

set of best practice rules or actual formal investment restrictions written in management

mandates. Del Guercio (1996) studies this in the U.S. context and documents that prudence

considerations are more important for bank-managed funds than mutual funds. Even though

not uniformly across types of funds and, certainly, across different markets (e.g., U.S. versus

German funds), all funds’ investment policies are potentially constrained. The following are

some of the rules that are expected to direct fund managers investment decisions:

• Dividend Yield (DY ): Invest in dividend-paying stocks. For example, many endow-ments in the U.S. have explicit policies to spend only their ”investment income” which

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is many times the money generated by dividends paid by stocks in fund’s portfolio,

instead of partial liquidations of assets. Gompers and Metrick (2001) find that, in

contrast, U.S. mutual funds seem to be averse to stocks with high dividend yields.

In the international context, foreign investors can have a particular dislike for high

dividend-paying stocks for home-country dividend tax withholding issues (Dahlquist

and Robertsson (2001) and Ammer et al. (2005)).

• Return-on-equity (ROE): Invest in profitable firms. Because of the oversight by end-investors, many asset managers are under pressure to justify their choice of stock

investments. One common indicator to justify an investment choice to ultimate owners

of funds is a stock’s past profitability.

• Stock Price Idiosyncratic Volatility (SIGMA): Invest in low risk stocks. Fiduciarymotives can make money managers “prudently” avoid very risky stocks. Gompers

and Metrick (2001) find conflicting evidence in the U.S. as institutions tend to prefer

stocks with high volatility. Moreover, there is a literature that interprets idiosyncratic

volatility as a measure of stock price efficiency (Roll (1988) and Morck, Yeung, and Yu

(2000)). Moreover, high-levels of idiosyncratic volatility have been linked to good cor-

porate investment decision-making (Durnev, Morck, and Yeung (2004)) and to a lower

probability of expropriation of outside investors by insiders (Jin and Myers (2006)).

In this sense, institutional investors could reveal a preference for more efficient stocks,

i.e., with higher idiosyncratic volatility.

• MSCI Membership (MSCI): Invest in MSCI member stocks. The asset manage-

ment industry is characterized by ”indexation”, whether explicit (as in index funds) or

implicit (in that funds performance is benchmarked by a market index). Thus, institu-

tions can have a tendency to invest more in index-member stocks. The Morgan Stanley

Capital International (MSCI) All Country World Index is the leading index used in

international asset management. Foreign investors are likely to overweight stocks that

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are members of the MSCI index. We investigate whether domestic institutions, in

contrast, fill the void in non-MSCI stocks and thus, contrary to foreign institutions,

underweight the MSCI index members.

Current Firm Governance Indicators: Institutions can be particularly responsive to

firm-level governance indicators. Several aspects of the control ownership structure and

financial structure of firms can attract or repel institutional investors:

• Leverage (LEV ): Institutions invest in firms with less debt. Firms with more outstand-ing debt have less need for outsider oversight. As large investors, institutional investors

are potentially outside monitors of managers actions (Gillan and Starks (2003)). Thus,

we expect to find lower institutional ownership in firms that currently have high levels

of debt, and where managers actions are monitored by major debtholders.

• Cash (CASH): Institutions invest in cash-rich firms. Firms with more cash are po-tentially more liable to value-reducing activities by managers (the ”agency costs of

free cash flow” in the Jensen (1986) sense). We explore whether institutional investors

avoid or invest in firms with high levels of cash.

• Fraction of Closely-held Shares (CLOSE): Institutional investors avoid firms withdominant shareholders. Institutional investors tend to hold less shares of firms where

one insider or a group of insiders own a large block of shares. Moreover, institutional

investors can actively avoid firms with concentrated ownership because their interests,

as minority shareholders, can be seconded to those of main blockholders. Leuz et al.

(2005) find that U.S. investors invest less in poorly governed foreign firms (i.e., with

concentrated ownership).

• Corporate Governance Quotient (CGQ): Institutional investors avoid firms with weakinternal governance. Firms with weak governance structures and practices are more

14

likely to expropriate outside investors. In our empirical tests we use the comprehen-

sive ranking from Institutional Shareholder Services (ISS), which assists institutional

investors in evaluating the quality of corporate boards and of governance practices

(e.g., board of directors, audit, charter and bylaw provisions, laws of the state of in-

corporation, executive and director compensation, qualitative factors, ownership, and

director education).

Presence and Visibility of the Firm in World Markets: One particular determinant

of (foreign) institutional investment is investor recognition, as suggested by market segmen-

tation theories (Merton (1987)) − investors have limited information about just a subset ofstocks and direct their investments to these stocks.

• American Depositary Receipt (ADR): Institutional investors are attracted to investin cross-listed firms. The U.S. cross-listing decision is potentially motivated by firms’

efforts to increase information on their stock, spur analyst following (Lang, Lins, and

Miller (2003)), and a means of attracting investment by U.S. investors (Foerster and

Karolyi (1999)). We only consider exchange-listed ADRs as only these firms are re-

quired to follow U.S. GAAP and face corresponding stricter disclosure requirements.

Cross-listing can be a magnet for U.S. investors but can also attract non-U.S. in-

stitutions. In contrast, we expect this cross-listing effect not to hold for domestic

institutional investors which are familiar with local firms.

• Foreign Sales (FXSALES): Institutional investors invest in firms that sell abroadtheir products. A firm that conducts business abroad is more likely to have its name

known among foreign investors and thus induce these investors to consider investing

in the firm’s stock. This argument follows from empirical evidence on the effects of

”familiarity” in investment decisions.

• Analyst coverage (ANALY STS): Institutional investors are attracted to invest infirms with high analyst coverage. The number of analysts following a stock is commonly

15

considered as an indicator of the firm’s visibility in the market. Analyst coverage

can also related to the extent to which information is incorporated into stock prices,

though whether analysts contribute with firm-specific or just market-wide information

is a controversial issue (e.g., Piotroski and Roulstone (2004)).

2.2.2. Country-Level Characteristics

The attractiveness of the destination country where the firm is located is likely to be a

substantial factor in foreign investors’ decisions. We explore country-level characteristics in

addition to the firm-level characteristics as determinants of institutional ownership. Several

country factors also drive the volume of assets managed by domestic institutions in each

market.

Investor Protection: Foreign institutional investors are likely to prefer to invest in coun-

tries where their minority shareholder interests are protected (La Porta, Lopez-de-Silanes,

and Shleifer (2005), and Leuz et al. (2005)). Stronger laws and regulations are also a major

driver of the overall level of domestic capital markets development (La Porta, Lopez-de-Silanes,

Shleifer, and Vishny (1998)), and of the importance of domestic institutional investors. Also,

Khorana et al. (2005) find that legal factors are important determinants of the size of mutual

fund industry around the world.

• Legal (LEGAL): Institutional investors prefer to invest in firms from country with

good legal conditions. We measure the strength of the country’s legal environment

using the product of the anti-director rights index (La Porta et al. (1998)) and the rule-

of-law index following the literature (e.g., Durnev and Kim (2005)). Investors could

avoid stocks of firms located in countries with weak legal environment and investor

protection as they face a higher probability of expropriation by insiders.

• Common Law (COMMON): Institutional investors prefer countries with a commonlaw legal origin. The legal tradition of the country (common versus civil law) has been

16

widely considered an indicator of the level of shareholder protection. Countries with

common law are frequently though to provide shareholders a high degree of protection

(La Porta et al. (1998)).

Distance/Familiarity: Markets that are closer in terms of geographical distance or share

a common language are likely to be overweighted by investors in their international invest-

ments, as shown by mutual fund country-level allocations in Chan et al. (2005).

• Geographic Distance (DISTANCE): Institutional investors prefer to invest in firmslocated in countries that are geographically close. More remote countries are likely to

draw less foreign investment.

• English Language (ENGLISH): Institutional investors prefer to invest in English-speaking countries. One barrier to international investment is language. English is the

international language of business. Investors from English-speaking countries, such as

U.K. and U.S., can be more attracted by this feature relative to other foreign investors.

Size and Development of a Country’s Capital Market: The size and level of de-

velopment of a country’s capital market can be a magnet for investment in stocks of that

country (Chan et al. (2005)). Alternatively, however, investors from developed markets may

prefer to invest abroad in emerging markets because of diversification benefits and growth

opportunities. We consider the following proxies for the level of economic and financial

development (e.g., Doidge et al. (2005)):

• GDP Per Capita (GDP ): Institutional investment is higher in more developed coun-tries.

• Stock Market Capitalization as % of GDP (MCAP ): Institutional investment is higherinto countries with larger stock markets.

17

Table B.1 in Appendix B details the definitions and data sources for each of the variables

introduced in this section.

2.3. Sample of Firms and Summary Statistics

The firm-level financial data are drawn from Datastream (DS, stock market data) andWorld-

Scope (WS, accounting data) for the years of 1999 through 2004. The initial sample includes

all firms in the WS database excluding financial firms (SIC code between 6000-6999). We

merge this sample of firms with the institutional holdings data from FactSet/LionShares at

the end of each calendar year using alternatively SEDOL codes (for non-U.S. firms), CUSIP

codes (for U.S. firms), or ISIN codes. We sum the holdings of all institutions in a firm’s

stock at the end of each calendar year and divide it by the end-of-year market capitalization.

Thus, our variable of interest is the fraction of shares held by institutional investors with a

breakdown by domestic institutions (i.e., institutions domiciled in the same country in which

the stock is issued), and foreign institutions (i.e., institutions domiciled in a country different

from the one where the stock was issued). We further breakdown foreign holdings into U.S.

and non-U.S. domiciled asset managers. We aggregate local shares and ADR positions per

firm to have the total stock ownership regardless of the share type. If a stock in WS is not

held by any institution in FactSet/LionShares then we set institutional ownership variables

to zero, following Gompers and Metrick (2001). We also examine institutional positions in

local and ADR positions separately in subsection 3.3 below.

Our final sample includes 15,656 unique firms, for a total of 46,249 firm-years observations

for which we have data for the main variables of interest (we winsorize financial ratios, such

as return-on-equity and leverage, at the bottom and top 1% levels). The sample is split into

non-U.S. firms, the main focus of this paper, and U.S. firms. The sample of non-U.S. firms

includes 10,951 unique firms, for a total of 31,382 firm-year observations. Table 1 provides

summary statistics of institutional ownership variables, and firm- and country-level control

variables. The average non-U.S. firm (see Panel A) in the sample has a market capitalization

18

of US$ 146 million, 14.6% are MSCI index members, and 3.8% are cross-listed in an U.S.

exchange. About 38% of the observations are from English-speaking countries. The sample

of U.S. firms (see Panel B) includes 4,705 firms, for a total of 14,867 firm-year observations.

Comparing with non-U.S. firms characteristics, we can see that U.S. firms are larger, have

lower book-to-market ratios, and higher trading activity. Average institutional ownership

by domestic institutions is much higher for U.S. firms (15.3%) than it is for non-U.S. firms

(2.7%). To recall, this summary statistics are equally-weighted averages and we know from

previous studies that institutional ownership is higher for larger firms. Indeed, in the last

column of Panel C of Table A.2, we can see that total institutional ownership for the sample

of non-U.S. firms is 10.6%. Furthermore, as discussed in subsection 2.1, when we correct

for shares that are closely-held, total institutional ownership is 15.4% (see Panel D of Table

A.2).

3. Institutional Ownership and Firm and Country Char-

acteristics

This section reports the results of the cross-sectional determinants of the level of institutional

ownership worldwide. The first subsection presents our main tests with respect to what

firm and country-level characteristics attract institutional investors. The second subsection

contains several robustness checks and extensions of our main results. The final subsection

contains an analysis of the effect of U.S. cross-listing in attracting a foreign investor clientele.

3.1. What Attracts Foreign and Domestic Institutions?

Table 2 presents the main tests on which firm- and country-level characteristics matter the

most in attracting different types of institutional investors, as we discussed in Subsection

2.2. In our regressions, we focus on non-U.S. firms (Panel A of Table 2). Panel A has four

subpanels for each group of investors whose fraction of total ownership we explain: all foreign

19

institutions (U.S. plus non-U.S. money managers), only U.S.-based institutions, only non-

U.S.-based foreign investors, and domestic institutions (i.e. managers domiciled in the same

country where the firm’s stock is listed). For each subpanel we estimate three specifications:

(1) with just firm-level variables; (2) with both firm and country-level variables; and (3) with

firm-level variables and country fixed effects.

The main results of Panel A (non-U.S. firms) in general support the conjectured effects

on “institutional preferences”. We find that, on average, institutional investors around the

world, whether foreign or domestic, have a preference for large firms (SIZE) with liquid

shares (TURN). But the three different groups of managers also display asymmetric invest-

ment behavior in terms of other stock characteristics. U.S. institutions prefer value stocks

(high BM), while non-U.S. foreign and domestic institutions prefer growth stocks. U.S. in-

stitutions are also more prone to chase stocks with recent positive stock return performance

(RET ) than are non-U.S. institutions, and domestic investors seem to have a contrarian be-

havior. All institutions seem to load on stocks with strong profitability indicators (ROE and

INV OP ), reflecting some of the “prudent man” rules they are subject to in their investment

decisions. Against these rules, however, foreign institutional investors seem to dislike high-

dividend paying stocks, in contrast to domestic institutions, perhaps for the taxation issues

mentioned in subsection 2.1. Foreigners do not shy away from high idiosyncratic volatility

stocks (SIGMA).

Institutional investors seem to react to firm-level governance practices when they decide

their level of stock ownership in a firm. Institutions hold smaller fractions of firms that are

closely-held or with concentrated control rights (CLOSE), with high levels of debt (LEV ),

and with high levels of cash (CASH). Some of these results are consistent with the role of

institutional investors as outside monitors advocated by the literature on investor activism

(e.g., Gillan and Starks (2003)).

Both U.S. and other foreign investors have a bias for companies that are members of the

MSCI index (MSCI), and that have cross-listed their shares in an U.S. exchange (ADR).

20

The positive MSCI coefficient indicates the importance of this international benchmark for

foreign investors. Thus, there is evidence that international institutional investors load on

index members. The negative MSCI coefficient for domestic institutions (see Panel A.3)

indicates that this investor group fills the void in non-MSCI stocks in their home market. The

positive ADR coefficient for both U.S. and non-U.S. foreign institutional investors illustrates

the positive effect exerted by the cross-listing on their investment decisions. Because of

selection bias issues (i.e., firms with higher foreign ownership are more likely to cross-list),

we analyze in more depth this cross-listing effect in Subsection 3.3 below. In contrast, when

investing domestically (see Panel A.3), institutions do not seem to prefer firms with ADRs,

and there is even evidence that they underweight these stocks.

In terms of country-level variables, all institutions reveal a preference for stocks of coun-

tries with good disclosure standards (DISC) and that are geographically closer to their

local market (DISTANCE). U.S. institutions show a clear preference for English-speaking

countries (ENGLISH), common-law countries (COMMON), and less developed mar-

kets (MCAP ), while non-U.S. investors make relatively more investments in non-English-

speaking countries and more developed markets when they invest abroad. These findings

illustrate that these groups of institutional investors have different reasons for investing

abroad. Good disclosure standards (DISC) and legal environment (LEGAL) are found to

increase the presence of domestic institutional investors, but we find opposite results for in-

vestor protection with respect to attracting foreign institutions. This is inconsistent to what

the law and finance literature would suggest (La Porta et al. (1998)). Our interpretation

is that investors decision to go abroad balances lower shareholder protection against better

investment prospects or diversification benefits. This argument explains why U.S. investors

prefer emerging markets to European markets when investing overseas.

One important observation from Table 2 is that our results show that firm-level character-

istics have substantial explanatory power over country-level variables for foreign institutional

ownership. As we can be seen by comparing the first specification (including only firm-level

21

variables) with the second specification (including firm- and country-level variables), the in-

crease in R-squares of adding country-level variables is marginal in the first three subpanels

(Panels A.1-A.3 for foreign ownership). Institutional investors do more than just country-

level portfolio allocations: they engage in specific stock picking based on firm characteristics.

In Panel A.4 (domestic institutional ownership in non-U.S. firms), however, country factors

are particularly important to explain the cross-sectional variation. This finding is consistent

with the idea that the size and development of the domestic institutional investor segment

is related to the country’s overall quality of institutions (Khorana et al. (2005)).

Panel B of Table 2 considers the level of U.S. institutional investment in U.S. stocks. This

is not at the core of our investigation but is more of a “benchmarking” exercise. Our results

replicate previous findings by Gompers and Metrick (2001). Like these authors, we find a

preference for large and liquid stocks with “value” orientation. As we have seen before, U.S.

institutions have similar stock preferences when investing abroad.

Table 3 extends the previous results on institutional investors preferences in terms of

firm’s foreign visibility and the quality of governance mechanisms. We address in more detail

the role of firm’s visibility by adding as explanatory variables the percentage of foreign sales

(FXSALES) and the number of analysts covering a firm (ANALY STS). We add these

variables separately in the first and second specification in each panel of Table 3 because

of data availability that reduces substantially the sample size. The following findings are

not affected by including these variables simultaneously. We find that firm’s “name” and

visibility abroad entices more foreigners to hold more shares as shown by the positive and

significant coefficients in Panels A.1-A.3. Panel A.4 for domestic institutional ownership in

non-U.S. firms and Panel B for U.S. institutional investment in U.S. stocks show a differential

investment behavior. There is evidence that firm’s visibility indicators are not as important

when institutional investors invest at home, i.e., in familiar stocks. There is even some

evidence that domestic investors tend to underweight highly-visible firms.

The third specification in each panel of Table 3 extends the previous results in terms

22

of the role of firm-level corporate governance quality in investors decisions. We include the

ISS corporate governance ranking (CGQ) as additional explanatory variable.2 We find that

the corporate governance ranking is important for domestic investor but foreigners seem not

to care about these rankings contrary to visibility indicators. In contrast, domestic institu-

tional investors show a preference for firms with good corporate governance mechanisms and

practices as shown by the positive and significant CGQ coefficient. In the next subsection,

we further explore the role of firm-level corporate governance in determining institutions

preferences. In particular, we analyze in more detail whether firm-level governance can

have different impact on the revealed preferences of institutional investors depending on the

country-level quality of institutions and investor protection.

Lastly, we analyze in more detail the different stock investing preferences of the three

institutional investor groups. Table 4 estimates the determinants of the difference in in-

stitutional ownership between foreign and domestic institutions (Panel A) and U.S. versus

non-U.S. foreign institutions (Panel B) on the sample of non-U.S. firms. Specifically, the de-

pendent variable is Panel A is the difference between total foreign and domestic institutional

ownership of a firm’s stock. The dependent variable is Panel B is the difference between U.S.

institutional ownership and non-U.S. foreign institutional ownership.

Panel A of Table 4 shows that preference for size is more pronounced on foreign than

on domestic institutional holders. Similarly, for other factors already disentangled before in

Table 2, we find that foreigners (relative to domestic) are biased towards stocks with high

liquidity, with a “value” orientation, that are members of an MSCI index and that cross-list

their shares in the U.S. market. In Panel B, we document differences in preferences between

U.S. and non-U.S. institutions and find that U.S. investors have a higher (relative) preference

for value stocks and firms with ADRs, but (relatively) lower preference for large firms, MSCI

members, and that are closely-held. Non-U.S. and U.S. portfolio managers venture into

countries with different legal environments and different locations.2Once again, to maximize the sample size we do not include FXSALES and ANALY STS as controls.

Results including all variables are in line with those reported in Table 3.

23

3.2. Robustness Checks and Extensions

We now check the robustness of our main results of the previous subsection by conducting

several alternative regression specifications. The first issue we tackle in Panel A of Table 5 is

to measure institutional ownership as a fraction of shares that are not closely-held (or float)

instead of as a fraction of all shares. As documented in Dahlquist, Pinkowitz, Stulz, and

Williamson (2003), firms in many countries around the world have large fractions of their

shares that are closely-held by blockholders, so there are fewer shares available to outside

investors. We control for this issue in the regressions of Table 2 using the closely held shares

variable (CLOSE). Indeed, CLOSE has a significant negative coefficient in Table 2, mean-

ing that institutional investors as minority shareholders have smaller fraction of shares of

firms with high insider stakes. An alternative way to account for this issue, however, is to al-

ternatively scale institutional ownership by the total market float instead of the total market

capitalization. We rescale all four institutional ownership variables (foreign, U.S., non-U.S.

foreign, and domestic) by one minus CLOSE. Panel A of Table 5 presents the results of the

ownership regressions using the float scaling. Overall, the results corroborate the main find-

ings of Subsection 3.1 with respect to what firm characteristics attract institutional investors.

Institutional investors have a demand for large and liquid stocks when they decide to invest,

but there is also substantial diversity in other stock preferences among the three groups of

institutions. Foreigners weight positively MSCI membership and U.S. cross-listing, while

domestic institutions weight negatively these same stocks. There are also some significant

country-level factors (e.g., U.S. institutions prefer to invest in English-speaking countries),

but the main part of the cross-sectional variation is explained by firm-level characteristics

A second issue is that there are a considerable number of firms that have zero institu-

tional ownership in at least one of our ownership variables (all foreign, U.S., non-U.S. foreign,

and domestic). Because of this potential censoring of the dependent variable in our OLS

results in Table 2, we estimate alternatively a Tobit model. Panel B of Table 5 reports the

results that are mainly in line with our previous findings regarding commonality and diver-

24

sity in institutional stock preferences (size, liquidity, dividends, value/growth, momentum,

profitability, MSCI membership, and cross-listing) among the three groups of institutions.

A third issue is to consider an alternative definition of our dependent variable. We

alternatively take the ratio of the stock weight in the institutions portfolio relative to the

stock weight in its local market portfolio. A positive ratio implies that institutions invest

disproportionately more in a stock relative to the market portfolio (institutions overweight

the stock), while negative values of imply that institutions invest less in a stock relative to

the market portfolio (institutions underweight the stock). Panel C of Table 5 reports the

results that are consistent with our main findings. Institutions overweight large, liquid, and

widely-held stocks, but there is also diversity in other stock preferences among U.S., non-U.S.

foreign, and domestic institutions. Foreign institutions overweight firms that are members

of the MSCI index and with U.S. cross-listing, while domestic institutions underweight these

same firms.

Our results are also robust in other ways. In unreported regressions, we have run year-

by-year regressions like those in Table 2 and find that main results reported above are stable

over the sample years. We have also estimated regressions like in Table 2 using the logarithm

of ownership as dependent variable, including industry and year dummies, using a sample

of firms from only the countries for which institutional holdings are available, and only

including the observations with positive or explicit zero institutional holdings. These results

(not tabulated here) are consistent with our main findings.

To conclude this subsection, we extend our previous results in two important ways: what

is the role of firms and institutions geographic regions in explaining the level of institutional

ownership? what is the role of the country-level investor protection and how interacts with

firm-level characteristics to determine institutional holdings? We have found that familiarity

has an important role in institutional investment decisions. Specifically, institutions tend to

prefer firms to which they are geographically close. Thus, we explore in more detail the

geography of cross-border investments with results presented in Table 6. Within non-U.S.

25

firms, we isolate out firms listed in Asian (Panel A) and European (Panel B) markets. We

then breakdown foreign institutional investors based also on their geographic origin: Asia,

Europe, or North America. We can spot some regional patterns: European investors do not

hold more stocks of an European firm when it has an ADR program, but they hold more

stocks in the case of Asian firms with ADRs. North American investors, however, seem

always to prefer firms with ADRs, regardless the firms is located in Europe or Asia. These

findings strongly support the investor recognition hypothesis for European institutional in-

vestors as they prefer to invest in visible stocks (e.g., stocks with ADR programs) when they

invest abroad, while these characteristics are not relevant when they are investing in familiar

(European) stocks. The MSCI membership seems to be significant for investor preferences

regardless of whether they are investing in a stock market geographically close to their home

or investing overseas.

Finally, we extend our results to consider the role of country-level quality of institutions or

investor protection in explaining the investment preferences of institutional investors around

the world. We focus, in particular, on how investor protection impacts the institutions’

preferences with respect to investor recognition variables (MSCI and ADR) and corporate

governance aspects (CLOSE and CGQ). Our hypothesis is that investor recognition and

the quality of the firm-level corporate governance are particularly important in countries

with weak investor protection. In strong investor protection environments, we expect that

the importance of these firm-level characteristics in investor’s preferences is considerably

mitigated.

Table 7 presents results in which we include an interaction between these firm-level vari-

ables and the country’s investor protection level as measured by the LEGAL variable. We

consider two separate specifications because the CGQ variable has a limited number of obser-

vations. Results indicate that institutional investors dedicate special attention to firm-level

characteristics when they decide to invest in countries with weak environments (i.e., coun-

tries that score low in terms of the LEGAL variable), especially when they decide to invest

26

abroad (see Panels A-C). We find that the interaction of the LEGAL variable with the

MSCI or ADR variables presents with few exceptions a negative and significant coefficient.

The interpretation is that the preference revealed by foreign institutions for stocks that are

members of the MSCI index and cross-listed in the U.S. is attenuated in countries with

strong investor protection. In other words, for firms located in countries with weak investor

protection, MSCI membership, and cross-listing are significant boosters of foreign institu-

tional ownership. With respect to firm-level corporate governance, we find that foreigners

avoid firms with major controlling shareholders and weak corporate governance practices,

especially when these firms operate in environments with weak investor protection. This

finding is supported by the positive and significant coefficient of the CLOSE × LEGALinteraction variable and the negative and significant coefficient of the CGQ × LEGAL in-teraction variable in Panels A-C. The results in Panel D for domestic investors confirm that

this group presents a distinct behavior with respect to these firm-level characteristics. Unre-

ported regression results using alternatively the country’s legal origin (COMMON) in place

of LEGAL also confirm the findings in Table 7.

3.3. A Detailed Analysis of the Cross-listing Effect

Results throughout Tables 2-7 seem to indicate that foreign investors, both U.S. as well as

from other countries, have a distinct preference for holding firms that cross-list in an U.S.

exchange. However, firms that decide to cross-list in the U.S. might be those that would

have higher foreign ownership irrespective of the cross-listing event, so we want to isolate

the extra boost in foreign ownership that is related with the cross-listing decision.

The first methodology we employ is to correct econometrically for this selection bias in

our regressions. We use the “treatment effects” model (Greene (2003) - Chapter 22), where

we estimate jointly the equation of our interest, institutional holdings, with the propensity

to cross-list equation, with a two-step estimator:

27

(Institutional Holdings)j,t = X0j,tβX + δ(ADR)j + ej,t, (1)

Prob(ADRj) = Z0j,tβZ + nj,t. (2)

Note that identification of the model parameters requires at least one instrument that

is related to institutional holdings (enters in Xj,t of equation (1)), but does not determine

the decision to cross-list (does not enter in Zj,t of equation (2)). We identify the system

by considering some of the “institutional preference” variables (stock return, dividend yield,

return-on-equity, MSCI membership) that are usually not considered as determinants of

cross-listing decision by previous research (e.g., Doidge et al. (2004)).

Table 8 presents the results. We focus particularly on the coefficient of the ADR dummy

on institutional ownership variables in each panel (all foreign institutions, U.S. institutions,

non-U.S. foreign institutions, and domestic). Our previous results are confirmed as cross-

listing give an additional boost for U.S. institutions and non-U.S. foreign institutions to invest

in a firm’s stock (consistent with the predictions of Foerster and Karolyi (1999) among oth-

ers). In total, foreign investors hold an extra 5 percentage points of the market capitalization

of firms that have an ADR than they would otherwise, even after one corrects for selection

bias of cross-listing decision. In contrast, we see that domestic institutions actually fill the

void in non-ADR stocks. Estimated coefficients on other explanatory variables in institu-

tional ownership regression are in line with previous results. In terms of the Probit model

results (equation (2)), we find that firms are more likely to cross-list in the U.S. if they are

large, widely-held, and come from countries with weak legal environments. These results are

in line with the findings in Ammer et al. (2005) among others.

The second, perhaps, more direct method to isolate out the cross-listing effect is to study

the dynamics of the institutional ownership structure following the cross-listing event. Given

that we have a sizeable panel data set, we can identify 101 firms that have cross-listed their

28

shares in an U.S. exchange during our sample period between January 2000 and December

2004. We compare the level of foreign institutional ownership in the quarters around the

cross-listing. We thus treat all cross-listings in event time and present the median foreign

institutional ownership in the quarters before and after the cross-listing event in Panel B

of Table 9. We see that, although foreign investors hold local shares of those firms prior to

the cross-listing, they substantially increase their total position from 1.75% of firm’s market

capitalization at quarter -1 to 7.40% in quarter +8. We can conclude that firms that cross-

listed their shares in the U.S. during our sample period experience an increase in their foreign

institutional shareholder base of about 5.65 percentage points (from quarter -1 to quarter

8).

The FactSet/LionShares data allows us to break down holdings into those in local shares

(i.e., direct investments in firms’ shares in its market of origin) and those in ADR shares

(the depositary receipts). As we can observe in Panel B of Table 9 the increase in foreign

institutional ownership mainly occurs in local shares holdings rather than in the ADR shares

directly. This finding sheds light on the “flow-back” phenomenon of ADRs, i.e., after an

initial blip in U.S. trading of ADR shares, trading moves back to the more liquid domestic

exchange (Karolyi (2003) and Halling et al. (2004)). Even though trading is not retained

by the U.S. exchanges, cross-listed firms get extra foreign investors on board (both U.S. and

non-U.S.) who are making the trip to the firm’s home market and invest in the local shares.

Interestingly, it is not only US institutions that increase their holdings on local shares of

firms that cross-list, but also foreign non-US institutions.

4. Institutional Ownership and Firm Valuation

This section investigates the relation between institutional ownership (foreign and domestic)

and firm’s valuation. As in the previous section on investor’s preferences, we focus on

non-U.S. firms. Our goal is to test whether the presence of foreign institutions in a firm’s

29

shareholder base has real effects in terms of effectively reducing the firm’s cost of capital.

The first subsection reports the results of Tobin’s Q regressions for the sample on non-U.S.

firms. The second subsection handles the potential endogeneity issue that firm valuations

and ownership are jointly determined so we estimate a system of simultaneous equations for

ownership and firm’s valuation using three-stage least squares.

To investigate the relation between institutional ownership and firm valuation, we adopt

Tobin’s Q as the valuation measure (as in, for example, Doidge et al. (2004) and Durnev and

Kim (2005)) computed as follows. For the numerator, we add the book value of total assets

to the market value of equity, and subtract book value of equity. For the denominator, we use

total assets. In Table 10, we regress a firm’s Tobin’sQ on variables associated with firm value

such as SIZE, growth opportunities (INV OP ), leverage (LEV ), cash holdings (CASH),

whether a firm is cross-listed in the U.S. (ADR), and median industry Tobin’s Q for the

firm’s global industry. We also include country-level variables that are usually related with

firm’s valuation in the literature such as the legal regime index (LEGAL). In unreported

regressions, we include industry, country, and year dummies without significant impact on

main results. We extend this firm valuation equation by including our variable of interest: the

level of foreign and domestic institutional ownership. Panels A-C consider, respectively, the

ownership of all foreign institutions, U.S. institutions, non-U.S. foreign institutions. Panel

D only considers domestic institutional ownership as well as control variables.

Results in Table 10 show that firms with higher foreign institutional ownership have

higher valuations. The PF coefficient is positive and statistically significant. In contrast,

there is no evidence that higher domestic institutional is associated with higher valuations

as shown by the negative PD coefficient. These results provide evidence of the real effects

of a firm’s shareholder base including foreign institutional investors. Ownership by foreign

investors seems to drive up firm valuations (and thus potentially reduce the firm’s cost of

capital).

Having controlled for either foreign or domestic institutional ownership, we do not find

30

that ADR firms command a valuation premium (indeed, the coefficient is even negative).

Even though foreign investors push up firms valuations, the net effect of cross-listing is

actually slightly negative. This result is consistent with recent literature that after the

cross-listing firms experience a decrease in firm valuations, and that the valuation benefits of

internationalization are transitory and dynamic (Sarkissian and Schill (2005)), and mainly

accrue before the cross-listing. After the cross-listing a decrease in firm valuation is observed.

Other control variables coefficients are in general consistent with predictions and existing

literature. Large cash-rich firms with investment opportunities have higher valuations. More

levered firms have lower valuations.

Institutional ownership is likely to be jointly determined with the firm’s valuation and

driven by similar characteristics. To address this concern, we re-estimate the Tobin’s Q and

institutional ownership equations as a system of simultaneous equations using three-stage

least squares. Identification is achieved by independent variables included in the ownership

equation that are not related to Tobin’s Q.

Table 11 reports the results that also include the usual country-level controls. We find

that the positive effect of foreign institutional ownership (Panel A) on Tobin’s Q ratios is

robust to endogeneity concerns. Over our sample period, we find that for a 1 percentage

point rise in foreign institutional ownership, a firm’s Tobin’sQ would rise, on average, by 2.36

percentage points. Overall, the results using three-stage least squares regression corroborate

the findings in Table 10 with respect to the valuation effects of attracting foreign institutional

investors and expanding the firm’s shareholders base. The results in Table 11 (Panel B) also

confirm that there is no evidence of a positive relationship between domestic institutional

ownership and firm’s valuation.

31

5. Conclusion

In this paper we study the stock holdings of institutional investors around the world using

a novel database that spans the 2000-2004 period. Our data contains a total of US$ 2.7

trillion invested in non-U.S. stocks, of which US$1.9 trillion are cross-border investments,

as of December 2004. We analyze stock-level investments by domestic, U.S.-based, and

non-U.S.-based foreign institutions. We show these three investor groups have equal sized

pockets, and thus we offer a global (non-U.S. centric) view of what attracts international

institutions to invest in corporations around the world. Our tests show that the three groups

of institutional investors exhibit a demand for large and liquid stocks with good governance

practices, but they also exhibit divergent preferences in their investment decisions. There is

substantial diversity in other stock preferences (dividends, value/growth, momentum, and

volatility) among the three groups of institutions. Moreover, foreigners weight positively

MSCI membership and firms that cross-list their shares in an U.S. exchange. There are also

some relevant country-level factors (e.g., U.S. investors prefer English-speaking destinations),

but the main part of the cross-sectional variation is explained by firm-level characteristics,

suggesting that outside investors care about which particular firms to pick instead of just

following country-level allocations.

We analyze how successful are firm efforts to tap into foreign capital by means of an

ADR program. We document that U.S. cross-listing is associated with an increase in foreign

institutional ownership, both from U.S. and other countries foreign institutions. Analyzing

the change in foreign institutional ownership around the time of a cross-listing, we uncover

that the increase does not occur only in ADR stocks but also in foreign holdings of shares in

the firm’s local market. This sheds light on the puzzling “flow-back” of volume back to the

firms’ home market quickly after an ADR listing. Instead of “flow-back” being a symptom of

a failure to capture foreign investors, our results show that it occurs concurrently with many

of the new foreign investors making the trip to the firm’s homemarket. This is one illustration

of how modern international capital markets operate where firm and investor actions take

32

place in connected markets. The extra information and analyst coverage stemming from

a U.S. listing can provide a significant boost to foreign ownership of local shares around

the world. This finding adds to the explanations of multi-market trading of internationally

cross-listed stocks (Baruch, Karolyi, and Lemmon (2005)).

Our third main finding is that foreign ownership is positively associated with higher

firm valuations. This is consistent with an increased investor base lowering the firm’s cost

of capital or better expected cash flows perhaps by better outside monitoring provided by

these institutions. Alternatively, investor price pressure can cause some temporary stock

overvaluation. Distinguishing between these two alternative effects is an important issue,

in light of some of the recent evidence on the transient and dynamics of benefits of firms’

internationalization (Levine and Schmukler (2005) and Sarkissian and Schill (2005)). We

leave this for future work.

One other avenue for future research is to analyze how firms’ financing activities interact

with institutional ownership. One instance is to study other cross-listings beyond ADR

programs, to document whether European or Asian firms regional cross-listings tap into

regional pools of capital, as suggested by proximity preference evidence in Sarkissian and

Schill (2004). A related avenue for future research is how firms’ international capital raising

activities, as studied recently by Henderson, Jegadeesh, and Weisbach (2005), is determined

by the particular pool of investors currently holding a firms’ shares or the potential ones the

firm is trying to tap into. These and other relevant research questions can be explored with

the novel international ownership data set we use in this paper.

33

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37

Table 1Summary Statistics

This table reports mean, median, standard deviation, maximum, minimum, and number of observations (N) of variables. All variables are as defined in Appendix B. Thesample period is from 2000 to 2004. Panel A reports summary statistics for non-US firms and Panel B for US firms. Financial firms are omitted (SIC 6000-6999).

Panel A: Non-US Firms Panel B: US FirmsVariable Mean Median Std Dev Min Max N Mean Median Std Dev Min Max N

Institutional Ownership Variabes (firm-level)Foreign ownership all institutions PFALL 0.024 0.002 0.052 0.000 0.804 31382Foreign ownership US institutions PFUS 0.011 0.001 0.030 0.000 0.571 31382Foreign ownership non-US institutions PFNUS 0.013 0.000 0.033 0.000 0.635 31382Domestic ownership all institutions PD 0.027 0.000 0.069 0.000 0.930 31382 0.153 0.117 0.153 0.000 0.893 14867

Firm-Level Control VariabesMarket capitalization (log) SIZE 11.892 11.783 1.930 4.787 19.418 31382 12.114 12.116 2.401 4.382 19.545 14867Book-to-market (log) BM -0.181 -0.157 0.902 -3.425 3.255 31382 -0.554 -0.521 0.867 -3.419 3.151 14867Investment opportunities INV OP 0.103 0.048 0.299 -0.848 2.899 31382 0.138 0.070 0.357 -0.850 2.914 14867Stock return annual RET 0.000 0.000 0.005 -0.025 0.016 31382 -0.001 0.000 0.007 -0.025 0.016 14867Turnover TURN 0.682 0.326 1.143 0.000 10.387 31382 1.347 0.887 1.422 0.001 10.200 14867Dividend yield DY 0.022 0.015 0.025 0.000 0.145 31382 0.007 0.000 0.016 0.000 0.141 14867Return-on-equity ROE 0.029 0.058 0.277 -3.424 1.252 31382 -0.033 0.058 0.389 -3.728 1.233 14867Idiosyncratic variance SIGMA 0.172 0.095 0.243 0.000 3.752 31382 0.370 0.204 0.469 0.001 3.784 14867MSCI membership dummy MSCI 0.146 0.000 0.353 0.000 1.000 31382Leverage LEV 0.256 0.241 0.180 0.000 1.032 31382 0.251 0.235 0.186 0.000 1.345 14867Cash CASH 0.124 0.088 0.124 0.000 0.902 31382 0.139 0.056 0.185 0.000 0.902 14867ADR listed dummy ADR 0.038 0.000 0.192 0.000 1.000 31382Closely held shares CLOSE 0.461 0.464 0.233 0.000 0.984 31382 0.298 0.255 0.235 0.000 0.983 14867Foreign sales FXSALES 0.411 0.370 0.281 0.000 1.000 13426 0.314 0.282 0.211 0.000 1.000 6641Analysts coverage ANALY STS 6.611 4.000 6.578 1.000 48.000 17532 7.242 5.000 6.700 1.000 42.000 9484Corporate governance ranking CGQ 0.506 0.507 0.279 0.001 0.999 4960 0.499 0.498 0.290 0.000 1.000 12086Tobin’s Q Q 1.333 1.077 0.955 0.406 17.808 32910Global industry Tobin’s Q GLOBAL_Q 1.225 1.142 0.279 0.834 3.014 32910

Country-Level Control VariablesLegal regime quality index LEGAL 29.055 34.280 12.122 0.000 50.000 31382Common law dummy COMMON 0.383 0.000 0.486 0.000 1.000 31382Disclosure index DISC 5.602 5.600 0.627 3.700 6.500 31382Average distance (log) DISTANCE 8.929 9.055 0.250 8.340 9.568 31382English language dummy ENGLISH 0.383 0.000 0.486 0.000 1.000 31382GDP per capita (log) GDP 9.761 10.145 1.076 6.094 11.005 31382Market capitalization to GDP MCAP 1.040 0.816 0.737 0.046 3.749 31382

38

Table 2Determinants of Foreign and Domestic Institutional Ownership

Panel A reports estimates of coefficients of the annual time-series cross-sectional firm-level regression for non-US firms foreign ownership by all institutions, U.S. institutions and non-U.S.institutions, and domestic ownership as a percentage of market capitalization. Panel B reports estimates of coefficients of the annual time-series cross-sectional firm-level regression forU.S. firms domestic ownership as a percentage of market capitalization. The firm-level regressors include equity capitalization (SIZE), book-to-market equity ratio (BM), investmentopportunities (INV OP ), stock return (RET ), turnover (TURN), dividend yield (DY ), return-on-equity (ROE), idiosyncratic variance (SIGMA), MSCI index membership dummy(MSCI), leverage (LEV ), cash holdings (CASH), ADR listed dummy (ADR), and closely held shares (CLOSE). Some specifications include alternatively country dummies or country-level regressors. The country-level regressors include legal regime index (LEGAL), common law dummy variable (COMMON), disclosure index (DISC), average geographic distance,(DISTANCE), English language dummy (ENGLISH), GDP per capita (GDP ), and market capitalization to GDP (MCAP ). Refer to Table B.1 in Appendix B for variable definitions.The sample period is from 2000 to 2004. Robust t-statistics are in parentheses. Coefficients significant at the 5% level are in boldface.

Panel A: Non-US Firms Panel B: US FirmsVariable Pred. Panel A.1: Foreign Ownership Panel A.2: Foreign Ownership Panel A.3: Foreign Ownership Panel A.4: Domestic Ownership Domestic

Sign All Institutions US Institutions Non-US Institutions OwnershipConstant -0.0492 0.0541 -0.0264 -0.0090 -0.0230 0.0622 0.0330 0.8014 -0.1969

(-21.59) (4.74) (-19.58) (-1.38) (-15.00) (8.17) (10.70) (46.61) (-27.04)SIZE + 0.0067 0.0067 0.0069 0.0035 0.0038 0.0038 0.0032 0.0029 0.0032 0.0032 0.0044 0.0045 0.0315

(35.92) (32.63) (33.31) (30.52) (28.63) (28.77) (27.11) (23.08) (24.65) (14.42) (18.29) (18.75) (53.60)BM + -0.0008 0.0008 0.0002 0.0004 0.0016 0.0009 -0.0012 -0.0008 -0.0007 -0.0104 -0.0003 -0.0017 0.0140

(-2.31) (2.22) (0.55) (2.24) (7.59) (4.23) (-5.09) (-3.25) (-2.76) (-23.79) (-0.81) (-4.04) (11.13)INV OP + 0.0064 0.0055 0.0037 0.0017 0.0009 -0.0002 0.0049 0.0048 0.0041 0.0072 0.0021 -0.0006 -0.0255

(6.47) (5.51) (3.79) (3.42) (1.77) (-0.51) (6.53) (6.40) (5.58) (4.80) (1.55) (-0.43) (-9.41)RET + 0.0170 0.1998 0.1750 0.0999 0.1114 0.1253 -0.0825 0.0881 0.0489 -0.5191 -0.4315 -0.3608 0.5147

(0.30) (3.49) (3.13) (3.12) (3.45) (4.00) (-2.10) (2.27) (1.28) (-6.04) (-5.43) (-4.72) (3.41)TURN + 0.0008 0.0010 0.0008 -0.0002 0.0003 -0.0001 0.0011 0.0008 0.0009 -0.0040 0.0017 0.0012 0.0210

(3.38) (4.02) (2.71) (-1.55) (2.41) (-0.46) (5.78) (4.04) (4.41) (-20.69) (8.55) (6.22) (19.33)DY + -0.0283 -0.0440 -0.0541 -0.0128 -0.0357 -0.0270 -0.0161 -0.0089 -0.0275 0.1966 0.0784 0.0891 -1.1286

(-2.71) (-4.01) (-4.89) (-2.03) (-5.17) (-4.22) (-2.40) (-1.31) (-3.80) (10.72) (4.72) (5.43) (-17.27)ROE + 0.0078 0.0071 0.0062 0.0028 0.0031 0.0020 0.0050 0.0040 0.0042 0.0058 0.0085 0.0084 0.0134

(7.44) (6.88) (6.07) (4.63) (5.25) (3.42) (6.84) (5.59) (5.91) (3.65) (5.85) (5.84) (4.92)SIGMA - 0.0048 0.0045 0.0030 0.0027 0.0012 0.0002 0.0022 0.0033 0.0028 0.0119 0.0020 0.0015 -0.0288

(4.51) (4.06) (2.75) (4.99) (2.23) (0.33) (2.59) (3.79) (3.29) (7.44) (1.44) (1.11) (-12.90)MSCI + 0.0232 0.0243 0.0230 0.0103 0.0106 0.0100 0.0129 0.0136 0.0129 -0.0177 -0.0134 -0.0110

(17.84) (18.93) (18.34) (13.25) (13.88) (13.57) (15.96) (17.23) (16.55) (-15.13) (-12.58) (-11.29)LEV - -0.0099 -0.0058 -0.0078 -0.0038 -0.0004 -0.0023 -0.0062 -0.0055 -0.0055 -0.0304 -0.0004 -0.0048 -0.0024

(-6.76) (-3.86) (-5.30) (-4.35) (-0.44) (-2.67) (-6.44) (-5.61) (-5.76) (-15.23) (-0.21) (-2.72) (-0.43)CASH + 0.0093 0.0151 0.0144 0.0068 0.0110 0.0101 0.0025 0.0042 0.0044 -0.0316 0.0047 0.0000 -0.0369

(3.93) (6.12) (6.08) (4.49) (6.77) (6.40) (1.77) (2.87) (3.10) (-9.20) (1.46) (-0.00) (-5.74)ADR + 0.0330 0.0307 0.0279 0.0212 0.0199 0.0191 0.0117 0.0107 0.0087 -0.0044 -0.0147 -0.0170

(12.64) (11.80) (11.17) (12.41) (11.54) (11.77) (8.52) (8.01) (6.53) (-2.60) (-8.90) (-10.49)CLOSE - -0.0252 -0.0264 -0.0289 -0.0147 -0.0114 -0.0114 -0.0105 -0.0150 -0.0175 -0.0780 -0.0437 -0.0338 -0.0805

(-19.74) (-19.55) (-20.26) (-20.28) (-15.42) (-14.90) (-12.35) (-16.54) (-18.06) (-40.66) (-26.95) (-20.14) (-17.69)LEGAL + -0.0006 -0.0001 -0.0004 0.0010

(-12.47) (-6.06) (-13.64) (22.54)COMMON + -0.0015 0.0027 -0.0040 0.0062

(-1.50) (3.87) (-6.90) (8.02)DISC + 0.0093 0.0034 0.0060 0.0219

(8.29) (5.84) (7.69) (21.53)DISTANCE - -0.0157 -0.0048 -0.0108 -0.0954

(-14.04) (-7.03) (-15.48) (-54.52)ENGLISH + -0.0005 0.0038 -0.0045 0.0196

(-0.50) (6.34) (-7.01) (19.50)GDP + -0.0001 0.0005 -0.0006 -0.0106

(-0.16) (1.43) (-1.38) (-20.42)MCAP + 0.0022 -0.0008 0.0030 -0.0100

(4.14) (-2.43) (9.12) (-20.21)Country dum. No No Yes No No Yes No No Yes No No Yes NoR2 0.2230 0.2457 0.2994 0.1789 0.1893 0.2515 0.1433 0.1872 0.2336 0.1158 0.2871 0.3582 0.4256N 31382 31382 31382 31382 31382 31382 31382 31382 31382 31382 31382 31382 14867

39

Table 3Determinants of Foreign and Domestic Institutional Ownership: The Role of Visibility and Governance

Panel A rep orts estimates of co effi cients of the annual tim e-series cross-sectional fi rm -level regression for non-US fi rm s foreign ownersh ip by all institutions, U .S . institutions and non-U .S . institutions, anddomestic ownership as a p ercentage of market capita lization . Panel B rep orts estim ates of co effi cients of the annual tim e-series cross-sectional fi rm -level regression for U .S. fi rm s domestic ownership as ap ercentage of market capita lization . The fi rm -level regressors include equity cap ita lization (SIZE), b ook-to-m arket equity ratio (BM), investm ent opportun ities (INVOP ), sto ck return (RET ), turnover(TURN), d iv idend yield (DY ), return-on-equity (ROE), id iosyncratic variance (SIGMA), MSCI index m embersh ip dummy (MSCI), leverage (LEV ), cash hold ings (CASH), ADR listed dummy (ADR),closely held shares (CLOSE), international sa les as a p ercentage of total sa les (FXSALES), analyst coverage (ANALY STS), and corp orate governance ranking (CGQ). The country-level regressorsinclude legal reg im e index (LEGAL), common law dummy variable (COMMON), d isc losure index (DISC), average geographic distance , (DISTANCE), English language dummy (ENGLISH), GDPper capita (GDP ), and market cap italization to GDP (MCAP ). Refer to Table B .1 in Append ix B for variable definitions. The sample p eriod is from 2000 to 2004. Robust t-statistics are in parentheses.Coeffi cients signifi cant at the 5% level are in boldface.

Panel A : Non-US F irm s Panel B : US Firm sVariable Pred . Panel A .1: Foreign Ownership Panel A .2: Foreign Ownership Panel A .3: Foreign Ownersh ip Panel A .4: Domestic Ownership Domestic

S ign A ll Institutions US Institutions Non-US Institutions Ownersh ipConstant 0.0056 0.1622 -0.0026 -0.0210 0.0230 -0.0389 0.0232 0.1393 0.0364 0.9489 0.9991 0.9817 -0.1160 -0.1738 -0.2064

(0.27) (8 .83) (-0 .05) (-1 .75) (2 .47) (-1 .26) (1 .78) (10.91) (1 .05) (34.17) (40.24) (24.52) (-9 .19) (-10.80) (-23.87)SIZE + 0.0072 0.0022 0.0040 0.0042 0.0019 0.0031 0.0031 0.0003 0.0009 0.0043 0.0020 -0.0045 0.0257 0.0325 0.0320

(22.41) (5 .55) (4 .95) (20.35) (8 .15) (7 .10) (15.49) (1 .14) (1 .71) (10.20) (4 .58) (-6 .21) (27.02) (24.83) (48.47)BM + -0 .0016 0.0000 -0.0024 0.0008 0.0018 0.0008 -0 .0024 -0.0018 -0.0033 -0.0021 0.0003 -0.0008 0.0127 0.0146 0.0163

(-2 .54) (0 .03) (-1 .76) (2 .14) (5 .45) (1 .07) (-5 .41) (-4 .26) (-3 .63) (-2 .68) (0 .46) (-0 .69) (5 .94) (7 .02) (11.11)INV OP + 0.0058 0.0091 0.0156 -0 .0001 0.0023 0.0065 0.0062 0.0068 0.0091 -0 .0010 0.0009 -0.0044 -0.0241 -0.0274 -0.0226

(3 .23) (5 .45) (2 .88) (-0 .08) (2 .67) (2 .14) (4 .37) (5 .74) (2 .88) (-0 .39) (0 .43) (-1 .13) (-4 .80) (-6 .64) (-6 .78)RET + -0.0014 0.5903 0.2271 0.0434 0.3208 0.3102 -0 .0492 0.2715 -0.0831 -0.3837 -0.1695 -0.3191 0.8609 1.1326 0.7144

(-0 .02) (6 .44) (1 .04) (0 .93) (6 .64) (2 .41) (-0 .82) (4 .24) (-0 .61) (-3 .00) (-1 .42) (-1 .95) (3 .33) (4 .62) (4 .10)TURN + 0.0007 0.0023 0.0198 0.0005 0.0007 0.0079 0.0003 0.0016 0.0119 0.0008 0.0026 0.0031 0.0228 0.0255 0.0255

(1 .20) (4 .78) (7 .54) (1 .47) (3 .15) (5 .08) (0 .88) (4 .52) (8 .14) (1 .59) (7 .51) (2 .10) (14.33) (19.58) (21.73)DY + 0.0013 -0.0206 -0.0495 -0.0039 -0 .0280 -0 .0262 0.0044 0.0072 -0.0233 0.2249 0.0794 0.1169 -0.8786 -1.5972 -1.0567

(0 .07) (-1 .13) (-0 .84) (-0 .33) (-2 .58) (-0 .78) (0 .38) (0 .62) (-0 .64) (7 .03) (2 .94) (2 .16) (-7 .85) (-17.10) (-14.37)ROE + 0.0091 0.0090 0.0179 0.0037 0.0038 0.0111 0.0054 0.0052 0.0068 0.0081 0.0064 -0 .0065 0.0111 0.0152 0.0118

(4 .91) (4 .50) (3 .09) (4 .24) (3 .44) (4 .18) (3 .93) (3 .78) (1 .66) (3 .12) (2 .54) (-1 .56) (2 .42) (3 .07) (3 .47)SIGMA - 0 .0001 -0.0003 -0 .0235 -0 .0010 -0 .0022 -0.0103 0.0011 0.0019 -0 .0132 0.0000 0.0010 0.0130 -0.0516 -0.0594 -0.0392

(0 .04) (-0 .10) (-3 .06) (-1 .01) (-1 .98) (-2 .07) (0 .64) (0 .87) (-3 .06) (0 .02) (0 .35) (1 .65) (-11.36) (-11.92) (-13.41)MSCI + 0.0194 0.0147 0.0145 0.0080 0.0059 0.0051 0.0112 0.0088 0.0095 -0.0168 -0.0090 0.0028

(10.74) (10.42) (7 .12) (7 .22) (7 .34) (4 .28) (10.38) (9 .97) (7 .79) (-9 .77) (-7 .37) (1 .81)LEV - -0 .0076 -0.0084 -0.0227 -0 .0002 -0.0005 -0.0084 -0.0074 -0.0078 -0.0143 -0.0089 -0.0034 -0.0071 0.0082 -0.0014 0.0037

(-2 .68) (-3 .66) (-4 .16) (-0 .15) (-0 .42) (-2 .57) (-3 .97) (-5 .19) (-4 .38) (-2 .67) (-1 .25) (-1 .78) (0 .81) (-0 .16) (0 .59)CASH + 0.0113 0.0198 0.0362 0.0120 0.0134 0.0344 -0 .0007 0.0064 0.0018 0.0009 0.0100 0.0110 -0.0445 -0.0380 -0.0442

(2 .75) (5 .07) (3 .30) (4 .58) (5 .75) (4 .91) (-0 .27) (2 .57) (0 .32) (0 .17) (1 .97) (1 .41) (-3 .90) (-4 .14) (-6 .05)ADR + 0.0222 0.0263 0.0217 0.0157 0.0194 0.0132 0.0063 0.0070 0.0085 -0.0266 -0.0142 -0.0061

(6 .86) (9 .48) (6 .30) (7 .11) (10.34) (6 .42) (3 .89) (4 .91) (4 .27) (-11.38) (-7 .58) (-2 .35)CLOSE - -0 .0379 -0.0337 -0.0407 -0.0143 -0.0147 -0.0165 -0.0235 -0.0190 -0.0242 -0.0535 -0.0446 -0.0329 -0.1014 -0.1038 -0.0747

(-16.75) (-16.04) (-8 .00) (-11.92) (-13.00) (-5 .82) (-15.31) (-13.45) (-7 .49) (-19.35) (-18.22) (-8 .58) (-13.34) (-14.76) (-13.85)FXSALES + 0.0199 0.0075 0.0126 0.0014 0.0061

(11.39) (7 .70) (11.00) (0 .65) (0 .84)ANALY STS + 0.0021 0.0009 0.0012 -0.0002 -0.0025

(17.81) (12.13) (17.55) (-1 .86) (-7 .04)CGQ + -0.0014 -0.0023 0.0009 0.0126 0.0188

(-0 .31) (-0 .90) (0 .31) (3 .81) (4 .92)LEGAL + -0 .0005 -0.0004 -0.0011 -0.0001 -0.0001 -0.0004 -0.0004 -0.0003 -0.0008 0.0015 0.0012 0.0011

(-7 .11) (-5 .59) (-7 .70) (-3 .79) (-2 .21) (-4 .45) (-7 .54) (-6 .45) (-8 .53) (19.64) (19.00) (10.47)COMMON + -0 .0053 -0.0114 -0.0188 0.0026 -0.0024 -0 .0001 -0 .0074 -0.0090 -0.0187 0.0162 0.0074 0.0007

(-2 .73) (-6 .28) (-2 .84) (1 .99) (-2 .13) (-0 .03) (-6 .12) (-8 .14) (-4 .83) (9 .12) (5 .78) (0 .21)DISC + 0.0118 0.0082 0.0373 0.0050 0.0029 0.0132 0.0069 0.0053 0.0241 0.0281 0.0284 0.0371

(4 .82) (4 .61) (8 .04) (3 .80) (3 .45) (5 .22) (4 .08) (4 .15) (8 .21) (14.20) (17.62) (11.86)DISTANCE - -0 .0127 -0.0207 -0.0109 -0.0053 -0.0057 -0.0087 -0.0073 -0.0151 -0.0022 -0.1175 -0.1169 -0.1209

(-6 .49) (-12.18) (-1 .95) (-4 .43) (-5 .71) (-2 .59) (-6 .16) (-13.98) (-0 .72) (-41.63) (-47.76) (-30.11)ENGLISH + -0 .0060 0.0026 -0.0092 0.0010 0.0068 0.0032 -0 .0074 -0.0041 -0.0124 0.0142 0.0215 0.0074

(-3 .59) (1 .45) (-1 .71) (0 .91) (6 .54) (1 .00) (-6 .84) (-3 .51) (-4 .13) (9 .20) (14.21) (3 .07)GDP + -0.0001 -0.0014 -0 .0091 0.0004 -0.0001 0.0023 -0.0004 -0.0013 -0.0115 -0.0100 -0.0125 -0 .0048

(-0 .06) (-1 .49) (-1 .97) (0 .53) (-0 .12) (0 .97) (-0 .41) (-2 .04) (-3 .81) (-7 .91) (-15.08) (-1 .64)MCAP + 0.0044 0.0024 0.0145 0.0002 0.0004 0.0048 0.0042 0.0020 0.0097 -0.0144 -0.0116 -0.0066

(4 .91) (2 .49) (6 .35) (0 .48) (0 .72) (3 .61) (7 .08) (3 .26) (6 .62) (-18.39) (-13.45) (-5 .22)R2 0.2876 0.2601 0.2716 0.2178 0.2023 0.1985 0.2328 0.2082 0.2542 0.3304 0.3244 0.4201 0.3569 0.2936 0.4410N 13426 17532 4960 13426 17532 4960 13426 17532 4960 13426 17532 4960 6641 9484 12086

40

Table 4Determinants of Foreign versus Domestic Ownership and US versus Non-US

Foreign Owership

Panel A reports estimates of coefficients of the annual time-series cross-sectional firm-level regression for the difference betweenforeign and domestic institutional ownership in non-U.S. firms as a percentage of market capitalization. Panel A reportsestimates of coefficients of the annual time-series cross-sectional firm-level regression for the difference between non-U.S. andU.S. institutional foreign ownership in non-U.S. firms as a percentage of market capitalization. The firm-level regressorsinclude equity capitalization (SIZE), book-to-market equity ratio (BM), investment opportunities (INV OP ), stock return(RET ), turnover (TURN), dividend yield (DY ), return-on-equity (ROE), idiosyncratic variance (SIGMA), MSCI indexmembership dummy (MSCI), leverage (LEV ), cash holdings (CASH), ADR listed dummy (ADR), and closely held shares(CLOSE). The country-level regressors include legal regime index (LEGAL), common law dummy variable (COMMON),disclosure index (DISC), average geographic distance, (DISTANCE), English language dummy (ENGLISH), GDP percapita (GDP ), and market capitalization to GDP (MCAP ). Refer to Table B.1 in Appendix B for variable definitions. Thesample period is from 2000 to 2004. Robust t-statistics are in parentheses. Coefficients significant at the 5% level are inboldface.

Non-US FirmsVariable Panel A: Difference of Foreign Panel B: Difference of US to

to Domestic Ownership Non-US Foreign OwnershipConstant -0.7473 -0.0712

(-37.53) (-8.61)SIZE 0.0023 0.0008

(8.05) (5.33)BM 0.0012 0.0024

(2.26) (8.74)INV OP 0.0034 -0.0039

(2.07) (-5.08)RET 0.6313 0.0232

(6.83) (0.54)TURN -0.0007 -0.0004

(-2.39) (-2.20)DY -0.1225 -0.0268

(-6.49) (-3.27)ROE -0.0013 -0.0008

(-0.81) (-1.04)SIGMA 0.0024 -0.0020

(1.40) (-2.19)MSCI 0.0377 -0.0029

(24.94) (-3.36)LEV -0.0054 0.0051

(-2.49) (4.55)CASH 0.0104 0.0068

(2.73) (3.70)ADR 0.0453 0.0091

(15.85) (5.48)CLOSE 0.0173 0.0035

(9.04) (3.70)LEGAL -0.0016 0.0003

(-27.21) (8.83)COMMON -0.0076 0.0067

(-6.36) (8.37)DISC -0.0125 -0.0026

(-8.74) (-3.35)DISTANCE 0.0798 0.0060

(39.74) (7.43)ENGLISH -0.0201 0.0084

(-15.00) (11.21)GDP 0.0105 0.0010

(14.29) (2.39)MCAP 0.0122 -0.0038

(17.94) (-9.93)R2 0.2193 0.0515N 31382 31382

41

Table 5Robustness Checks of Determinants of Foreign and Domestic Institutional Ownership

This table rep orts estimates of co effi cients of the annual tim e-series cross-sectional fi rm -level regression for non-US fi rm s foreign ownership by all institutions, U .S . institutions and non-U .S . institutions,and domestic ownership . Panel A rep orts estim ates considering ownership as a p ercentage of float. Panel B estim ates a Tob it model. Panel C reports estimates considering ownership relative to the marketp ortfolio, i.e ., the ratio of the fi rm ’s weight in institutions p ortfo lios by the fi rm ’s lo cal m arket weight. The fi rm -level regressors include equity cap ita lization (SIZE), b ook-to-market equity ratio (BM),investm ent opportunities (INVOP ), sto ck return (RET ), turnover (TURN), d iv idend yield (DY ), return-on-equity (ROE), id iosyncratic variance (SIGMA), MSCI index m embership dummy (MSCI),leverage (LEV ), cash hold ings (CASH), ADR listed dummy (ADR), and closely held shares (CLOSE). The country-level regressors include legal regim e index (LEGAL), common law dummy variab le(COMMON), d isc losure index (DISC), average geographic distance, (DISTANCE), English language dummy (ENGLISH), GDP per capita (GDP ), and market capita lization to GDP (MCAP ).Refer to Table B .1 in Appenid ix for variable definitions. The sample p eriod is from 2000 to 2004. Robust t-statistics are in parentheses. Coeffi cients sign ifi cant at the 5% level are in b oldface .

Panel A : Ownership as % of F loat Panel B : Tob it M odel Panel C : Ownership Relative to Market Portfo lioNon-US Firm s US Firm s Non-US Firm s US F irm s Non-US Firm s US Firm s

Variable Pred. Foreign Foreign Foreign Domest. Domest. Foreign Foreign Foreign Domest. Domest. Foreign Foreign Foreign Domest. Domest.S ign Owner. Owner. Owner. Owner. Owner. Owner. Owner. Owner. Owner. Owner. Owner. Owner. Owner. Owner. Owner.

A ll US Non-US All US Non-US All US Non-USInst. Inst. Inst. Inst. Inst. Inst. Inst. Inst. Inst.

Constant 0.1606 -0.0655 0.2236 1.2990 -0.2365 -0.1309 -0.1761 -0.0263 0.8088 -0.2850 1.1468 -0.0921 2.3720 52.4646 -1.9288(2.75) (-2.39) (5 .81) (38.71) (-10.79) (-6 .71) (-14.45) (-1 .60) (22.98) (-29.37) (3.93) (-1 .44) (7 .38) (44.94) (-26.54)

SIZE + 0.0113 0.0064 0.0050 0.0056 0.0409 0.0156 0.0098 0.0129 0.0184 0.0381 0.1692 0.0370 0.1206 0.3094 0.3113(16.44) (16.26) (11.74) (10.96) (30.13) (49.38) (49.64) (48.20) (34.45) (51.85) (30.93) (28.46) (22.31) (18.65) (53.01)

BM + 0.0078 0.0048 0.0030 0.0014 0.0275 0.0068 0.0060 0.0025 -0.0030 0.0185 0.0082 0.0158 -0.0517 -0.1128 0.1262(5 .65) (6.26) (3 .49) (1 .76) (4 .52) (12.80) (17.68) (5 .75) (-3 .13) (11.24) (0.85) (7 .49) (-4 .76) (-3 .91) (9 .99)

INV OP + 0.0111 0.0031 0.0083 0.0066 -0.0265 0.0083 0.0002 0.0112 0.0036 -0.0321 0.1567 0.0088 0.2047 0.1161 -0.2208(4 .17) (2.18) (4 .64) (2 .20) (-5 .08) (6 .04) (0 .28) (9 .91) (1 .55) (-9 .26) (5.88) (1 .80) (6 .50) (1 .22) (-8 .06)

RET + 0.8785 0.4537 0.4286 -0.7588 0.8843 -0.0385 -0.0036 -0.1419 -0.9169 0.7250 9.2552 1.0613 12.5948 -5.8780 6.0084(3 .81) (3.23) (2 .98) (-4 .15) (3 .02) (-0 .48) (-0 .07) (-2 .11) (-6 .61) (3 .76) (6.04) (3 .31) (7 .25) (-1 .06) (3 .94)

TURN + 0.0022 -0.0003 0.0026 0.0034 0.0244 0.0026 0.0012 0.0019 -0.0028 0.0242 0.0159 0.0031 0.0214 0.0787 0.2012(1 .60) (-0.81) (2 .25) (11.23) (11.29) (6 .85) (5 .13) (6 .19) (-2 .86) (23.93) (2.43) (2 .29) (2 .56) (5 .62) (18.77)

DY + -0.0023 -0.0479 0.0445 0.0824 -1.6591 0.0206 0.0067 0.0305 0.0967 -1.1610 -1.3304 -0.3539 -0.7195 4.7699 -10.9854(-0 .04) (-1.53) (1 .39) (2 .62) (-7 .83) (1 .15) (0 .60) (2 .01) (2 .89) (-14.27) (-4.70) (-5 .18) (-2 .49) (4 .23) (-16.66)

ROE + 0.0171 0.0086 0.0086 0.0176 0.0043 0.0121 0.0064 0.0090 0.0135 0.0113 0.1963 0.0316 0.1616 0.7397 0.1560(4 .18) (3.52) (3 .76) (5 .49) (0 .48) (7 .03) (5 .87) (6 .14) (4 .78) (3 .10) (6.75) (5 .27) (5 .16) (6 .59) (5 .70)

SIGMA - 0.0064 0.0022 0.0043 -0.0006 -0.0585 -0.0004 -0.0032 0.0028 -0.0048 -0.0505 0.1618 0.0126 0.2004 0.3144 -0.2678(1 .99) (1.42) (1 .80) (-0 .21) (-8 .79) (-0 .21) (-2 .41) (1 .63) (-1 .36) (-14.90) (5.41) (2 .34) (4 .59) (3 .20) (-12.22)

MSCI + 0.0605 0.0263 0.0340 -0.0209 0.0180 0.0076 0.0107 -0.0238 0.5760 0.1043 0.5320 -1.0315(8 .46) (6.80) (7 .67) (-11.49) (13.97) (9 .61) (10.53) (-10.51) (17.57) (13.79) (16.10) (-14.15)

LEV - -0 .0126 -0.0024 -0.0102 0.0048 -0.0153 -0.0073 0.0003 -0.0112 -0.0274 -0 .0084 -0.1263 -0.0034 -0.2194 0.0100 -0.0339(-1 .71) (-0.66) (-2 .27) (1 .35) (-0 .70) (-3 .00) (0 .20) (-5 .53) (-6 .41) (-1 .20) (-3.13) (-0 .38) (-4 .95) (0 .08) (-0 .60)

CASH + 0.0321 0.0202 0.0119 0.0162 -0.0452 0.0300 0.0197 0.0208 0.0237 -0.0332 0.3693 0.1084 0.1399 0.0677 -0.4014(4 .01) (4.22) (2 .59) (2 .69) (-2 .60) (8 .62) (9 .02) (7 .21) (4 .04) (-4 .35) (5.81) (6 .76) (2 .30) (0 .31) (-6 .25)

ADR + 0.0741 0.0421 0.0319 -0.0260 0.0253 0.0171 0.0039 -0.0463 0.7435 0.1953 0.4151 -1.0763(4 .64) (5.31) (3 .54) (-10.41) (12.73) (14.02) (2 .51) (-13.26) (11.32) (11.52) (7 .49) (-10.00)

CLOSE - -0.0464 -0.0252 -0.0315 -0.0713 -0.0965 -0.6727 -0.1129 -0.6246 -3.1783 -0.8126(-24.51) (-21.21) (-20.06) (-21.27) (-16.68) (-19.77) (-15.44) (-16.81) (-27.27) (-17.84)

LEGAL + -0.0013 -0.0005 -0.0008 0.0014 -0.0004 0.0000 -0.0004 0.0022 -0.0132 -0.0014 -0.0160 0.0656(-9 .20) (-6.89) (-8 .36) (14.85) (-8 .18) (-0 .73) (-9 .07) (23.71) (-11.76) (-5 .97) (-12.85) (21.79)

COMMON + -0.0216 -0 .0052 -0.0161 0.0054 -0.0047 0.0024 -0.0089 -0.0198 -0.0681 0.0258 -0.2055 0.2476(-3 .96) (-1.56) (-4 .96) (3 .42) (-2 .92) (2 .32) (-6 .54) (-4 .81) (-2.77) (3 .77) (-8 .11) (4 .96)

DISC + 0.0118 0.0077 0.0043 0.0443 0.0124 0.0053 0.0083 0.0616 0.2379 0.0338 0.2558 1.3690(3 .01) (3.49) (1 .71) (20.29) (8 .97) (6 .08) (7 .37) (23.50) (8.47) (5 .93) (7 .67) (21.78)

DISTANCE - -0.0235 0.0012 -0.0245 -0.1634 -0.0178 -0.0030 -0.0206 -0.1839 -0.3688 -0.0467 -0.4219 -6.1842(-4 .99) (0.40) (-9 .57) (-48.19) (-9 .43) (-2 .54) (-12.98) (-55.47) (-13.16) (-6 .96) (-14.55) (-53.01)

ENGLISH + 0.0135 0.0116 0.0015 0.0302 -0.0049 0.0028 -0.0107 0.0479 -0 .0347 0.0375 -0.2303 1.3050(3 .23) (5.41) (0 .60) (15.04) (-2 .85) (2 .60) (-7 .30) (11.64) (-1.39) (6 .28) (-8 .40) (19.76)

GDP + 0.0605 0.0263 0.0340 -0.0209 0.0066 0.0060 0.0021 0.0211 -0 .0110 0.0040 -0.0334 -0.7558(8 .46) (6.80) (7 .67) (-11.49) (8 .42) (12.03) (3 .30) (11.68) (-0.76) (1 .27) (-1 .98) (-21.97)

MCAP + 0.0108 0.0024 0.0085 -0.0157 0.0004 -0.0024 0.0011 -0.0218 0.0900 -0.0074 0.1619 -0.3744(6 .72) (2.45) (8 .69) (-14.52) (0 .60) (-5 .78) (1 .94) (-18.56) (6.49) (-2 .29) (11.23) (-11.10)

R2 0.0605 0.0498 0.0480 0.1882 0.1229 0.2364 0.1884 0.1750 0.2740 0.4210N 30291 30291 30291 30291 13800 31382 31382 31382 31382 14867 31382 31382 31382 31382 14867

42

Table 6Determinants of Foreign Institutional Ownership by Geographical Regions

Panel A reports estimates of coefficients of the annual time-series cross-sectional firm-level regression for Asian firms institutionalforeign ownership as a percentage of market capitalization with breakdown by institution’s geographic region. Panel B reports es-timates of coefficients of the annual time-series cross-sectional firm-level regression for European firms institutional ownership aspercentage of market capitalization with breakdown by institution’s geographic region. The firm-level regressors include equity capi-talization (SIZE), book-to-market equity ratio (BM), investment opportunities (INV OP ), stock return (RET ), turnover (TURN),dividend yield (DY ), return-on-equity (ROE), idiosyncratic variance (SIGMA), MSCI index membership dummy (MSCI), leverage(LEV ), cash holdings (CASH), ADR listed dummy (ADR), and closely held shares (CLOSE). The country-level regressors includelegal regime index (LEGAL), common law dummy variable (COMMON), disclosure index (DISC), average geographic distance,(DISTANCE), English language dummy (ENGLISH), GDP per capita (GDP ), and market capitalization to GDP (MCAP ). Referto Table B.1 in Appendix B for variable definitions. The sample period is from 2000 to 2004. Robust t-statistics are in parentheses.Coefficients significant at the 5% level are in boldface.

Panel A: Asian Firms Panel B: European FirmsForeign Foreign Foreign Foreign Foreign Foreign

Pred. Owner. Owner. Owner. Owner. Owner. Owner.Variable Sign Asian European North-Amer. Asian European North-Amer.

Inst. Inst. Inst. Inst. Inst. Inst.Constant -0.0569 -0.0368 -0.0848 0.0416 0.2774 0.2223

(-5.14) (-4.21) (-3.41) (3.02) (4.73) (6.52)SIZE + 0.0019 0.0019 0.0033 0.0000 0.0033 0.0039

(12.66) (24.80) (21.78) (-0.22) (14.41) (19.54)BM + 0.0009 -0.0003 0.0011 0.0001 -0.0022 0.0012

(2.91) (-2.02) (4.33) (1.90) (-3.99) (3.06)INV OP + 0.0029 0.0014 -0.0002 -0.0001 0.0054 -0.0009

(4.02) (3.45) (-0.38) (-1.20) (4.01) (-1.19)RET + 0.3236 0.0668 0.1083 0.0018 -0.0295 -0.0036

(6.17) (2.44) (3.09) (0.16) (-0.39) (-0.07)TURN + 0.0013 0.0003 -0.0007 0.0001 0.0045 0.0038

(5.36) (3.22) (-4.38) (1.39) (3.50) (4.05)DY + 0.0428 -0.0195 -0.0257 0.0051 -0.0638 -0.0089

(3.93) (-4.07) (-3.11) (0.59) (-4.97) (-0.76)ROE + 0.0022 0.0017 0.0010 0.0000 0.0061 0.0029

(3.36) (4.06) (2.02) (0.55) (4.69) (3.11)SIGMA - -0.0017 0.0009 0.0008 0.0000 0.0016 -0.0018

(-1.16) (2.01) (1.22) (0.25) (0.86) (-1.63)MSCI + 0.0085 0.0079 0.0109 0.0008 0.0128 0.0094

(8.19) (15.47) (13.66) (3.79) (8.03) (6.58)LEV - -0.0066 -0.0047 -0.0061 -0.0002 -0.0021 0.0050

(-6.84) (-8.70) (-7.48) (-0.96) (-0.86) (2.63)CASH + 0.0089 0.0035 0.0084 -0.0003 -0.0005 0.0098

(4.68) (3.52) (4.94) (-1.19) (-0.17) (3.50)ADR + 0.0061 0.0077 0.0179 0.0000 0.0029 0.0184

(2.35) (5.22) (6.26) (0.12) (1.57) (7.51)CLOSE - 0.0009 -0.0030 -0.0030 -0.0004 -0.0301 -0.0162

(0.70) (-5.12) (-3.32) (-1.27) (-16.80) (-12.33)LEGAL + 0.0000 -0.0001 -0.0008 0.0000 0.0001 0.0000

(-0.69) (-2.15) (-8.25) (3.10) (2.76) (0.89)COMMON + -0.0051 0.0008 0.0024

(-7.16) (2.41) (3.00)DISC + -0.0045 -0.0026 0.0046 -0.0001 0.0019 0.0007

(-3.32) (-4.23) (2.96) (-1.04) (1.16) (0.54)DISTANCE - 0.0063 0.0020 0.0015 -0.0047 -0.0444 -0.0408

(4.39) (1.88) (0.46) (-2.94) (-6.08) (-9.05)ENGLISH + 0.0011 0.0010 0.0040 0.0000 -0.0240 -0.0009

(1.61) (2.71) (6.49) (-0.29) (-14.03) (-0.71)GDP + 0.0008 0.0020 0.0038 0.0001 0.0088 0.0093

(1.68) (8.29) (10.27) (0.31) (5.18) (6.61)MCAP + 0.0025 0.0002 0.0014 -0.0002 -0.0020 0.0000

(7.44) (1.18) (3.51) (-2.86) (-2.36) (0.01)R2 0.0853 0.1927 0.2110 0.0037 0.2057 0.2160N 17839 17839 17839 11758 11758 11758

43

Table 7Determinants of Foreign and Domestic Institutional Ownership: The Role of

Investor Protection

This table reports estimates of coefficients of the annual time-series cross-sectional firm-level regression for non-US firms foreignownership by all institutions, U.S. institutions and non-U.S. institutions, and domestic ownership as a percentage of market capital-ization. The firm-level regressors include equity capitalization (SIZE), book-to-market equity ratio (BM), investment opportunities(INV OP ), stock return (RET ), turnover (TURN), dividend yield (DY ), return-on-equity (ROE), idiosyncratic variance (SIGMA),MSCI index membership dummy (MSCI), leverage (LEV ), cash holdings (CASH), ADR listed dummy (ADR), closely held shares(CLOSE), and corporate governance ranking (CGQ). The country-level regressors include legal regime index (LEGAL), commonlaw dummy variable (COMMON), disclosure index (DISC), average geographic distance, (DISTANCE), English language dummy(ENGLISH), GDP per capita (GDP ), and market capitalization to GDP (MCAP ). Refer to Table B.1 of Appendix B for variabledefinitions. The sample period is from 2000 to 2004. Robust t-statistics are in parentheses. Coefficients significant at the 5% levelare in boldface.

Non-US FirmsVariable Pred. Panel A: Foreign Panel B: Foreign Panel C: Foreign Panel D: Domestic

Sign Ownership Ownership Ownership OwnershipAll Inst. US Inst. Non-US Inst.

Constant 0.0722 -0.0044 -0.0096 -0.0397 0.0807 0.0353 0.7341 0.9817(6.26) (-0.08) (-1.43) (-1.30) (10.59) (1.03) (43.54) (24.51)

SIZE + 0.0069 0.0038 0.0037 0.0030 0.0032 0.0008 0.0039 -0.0045(33.07) (4.83) (28.19) (6.98) (24.51) (1.57) (16.20) (-6.21)

BM + 0.0008 -0.0031 0.0016 0.0006 -0.0008 -0.0036 -0.0004 -0.0008(2.14) (-2.25) (7.50) (0.75) (-3.32) (-4.09) (-1.07) (-0.69)

INV OP + 0.0053 0.0149 0.0009 0.0062 0.0045 0.0087 0.0023 -0.0044(5.28) (2.88) (1.83) (2.12) (6.08) (2.83) (1.67) (-1.13)

RET + 0.1827 0.2015 0.1112 0.3001 0.0712 -0.0986 -0.4226 -0.3191(3.21) (0.93) (3.46) (2.36) (1.84) (-0.73) (-5.33) (-1.95)

TURN + 0.0010 0.0215 0.0004 0.0086 0.0007 0.0129 0.0024 0.0031(3.82) (8.19) (2.83) (5.57) (3.48) (8.74) (11.53) (2.11)

DY + -0.0448 -0.0492 -0.0356 -0.0260 -0.0098 -0.0231 0.0750 0.1169(-4.08) (-0.86) (-5.15) (-0.78) (-1.45) (-0.66) (4.57) (2.16)

ROE + 0.0069 0.0182 0.0032 0.0112 0.0038 0.0070 0.0091 -0.0065(6.69) (3.05) (5.26) (4.20) (5.31) (1.65) (6.25) (-1.56)

SIGMA - 0.0043 -0.0266 0.0011 -0.0115 0.0033 -0.0151 0.0011 0.0130(3.95) (-3.48) (2.02) (-2.35) (3.78) (-3.40) (0.82) (1.65)

MSCI + 0.0296 0.0127 0.0066 0.0043 0.0229 0.0083 -0.0044 0.0028(7.82) (6.36) (3.13) (3.70) (9.40) (7.02) (-2.06) (1.82)

LEV - -0.0053 -0.0243 -0.0003 -0.0090 -0.0051 -0.0153 -0.0010 -0.0071(-3.51) (-4.53) (-0.35) (-2.82) (-5.17) (-4.72) (-0.54) (-1.78)

CASH + 0.0152 0.0382 0.0112 0.0352 0.0040 0.0031 0.0047 0.0110(6.16) (3.47) (6.93) (5.01) (2.76) (0.53) (1.47) (1.41)

ADR + 0.0570 0.0187 0.0359 0.0120 0.0211 0.0067 0.0193 -0.0061(7.65) (5.63) (7.79) (6.05) (5.07) (3.45) (6.05) (-2.34)

CLOSE - -0.0420 -0.0452 -0.0084 -0.0183 -0.0335 -0.0269 0.0184 -0.0329(-10.45) (-8.86) (-4.06) (-6.38) (-11.93) (-8.31) (5.39) (-8.54)

CGQ + 0.1245 0.0476 0.0769 0.0126(7.65) (5.40) (7.68) (1.32)

LEGAL + -0.0007 0.0003 -0.0001 0.0002 -0.0006 0.0001 0.0021 0.0011(-8.71) (1.50) (-2.01) (1.93) (-10.97) (0.73) (24.01) (9.05)

COMMON + -0.0012 -0.0061 0.0028 0.0049 -0.0039 -0.0110 0.0058 0.0007(-1.23) (-0.88) (4.03) (1.19) (-6.51) (-2.76) (7.78) (0.20)

DISC + 0.0096 0.0355 0.0034 0.0125 0.0063 0.0231 0.0214 0.0371(8.53) (7.78) (5.83) (4.93) (8.05) (7.98) (21.13) (11.88)

DISTANCE - -0.0170 -0.0156 -0.0049 -0.0105 -0.0120 -0.0051 -0.0918 -0.1209(-15.20) (-2.83) (-7.19) (-3.12) (-17.08) (-1.64) (-53.15) (-30.16)

ENGLISH + 0.0002 0.0053 0.0037 0.0089 -0.0038 -0.0037 0.0166 0.0074(0.19) (0.90) (6.14) (2.57) (-5.82) (-1.13) (16.78) (2.92)

GDP + -0.0005 -0.0071 0.0005 0.0031 -0.0010 -0.0103 -0.0097 -0.0048(-0.91) (-1.60) (1.53) (1.31) (-2.54) (-3.53) (-19.13) (-1.63)

MCAP + 0.0017 0.0095 -0.0007 0.0029 0.0025 0.0066 -0.0086 -0.0066(3.24) (3.99) (-2.28) (2.02) (7.47) (4.36) (-16.94) (-4.85)

MSCI × LEGAL - -0.0002 0.0001 -0.0003 -0.0003(-1.73) (1.92) (-4.97) (-3.68)

ADR× LEGAL - -0.0009 -0.0006 -0.0004 -0.0012(-4.25) (-3.99) (-3.19) (-9.53)

CLOSE × LEGAL + 0.0005 -0.0001 0.0006 -0.0022(4.54) (-1.57) (8.12) (-15.74)

CGQ× LEGAL - -0.0043 -0.0017 -0.0026 0.0000(-8.66) (-6.07) (-8.72) (0.01)

R2 0.2492 0.2909 0.1912 0.2084 0.1944 0.2735 0.2961 0.4201N 31382 4960 31382 4960 31382 4960 31382 4960

44

Table 8Foreign and Domestic Institutional Ownership and Cross-Listing: Selection

Bias

Panel A reports estimates of coefficients of the annual time-series cross-sectional firm-level regression for non-US firms foreignownesrhipby all institutions, U.S. institutions and non-U.S. institutions, and domestic ownership as a percentage of marketcapitalization correcting for selection bias of firms’ decisions to cross-list. We use the ”treatment effects” model (Greene(2003), Chapter 22) and estimate jointly the Probit of firms’ decision to cross-list (first column) and ownership equationby category of investor. The firm-level regressors include equity capitalization (SIZE), book-to-market equity ratio (BM),investment opportunities (INV OP ), stock return (RET ), turnover (TURN), dividend yield (DY ), return-on-equity (ROE),idiosyncratic variance (SIGMA), MSCI index membership dummy (MSCI), leverage (LEV ), cash holdings (CASH), ADRlisted dummy (ADR), and closely held shares (CLOSE). The country-level regressors include legal regime index (LEGAL),common law dummy variable (COMMON), disclosure index (DISC), average geographic distance, (DISTANCE), Englishlanguage dummy (ENGLISH), GDP per capita (GDP ), and market capitalization to GDP (MCAP ). Lambda coeficientsestimate account for the relevance of the selection correction. Refer to Table B.1 of Appendix B for variable definitions. Thesample period is from 2000 to 2004. Robust t-statistics are in parentheses. Coefficients significant at the 5% level are inboldface.

Non-US FirmsVariable Probit Panel A: Foreign Panel B: Foreign Panel C: Foreign Panel D: Domestic

Ownership Ownership Ownership OwnershipAll Inst. US Inst. Non-US Inst.

Constant -8.4557 0.0484 -0.0041 0.0523 0.7720(-10.42) (3.77) (-0.53) (6.32) (42.85)

SIZE 0.4187 0.0062 0.0034 0.0029 0.0060(41.97) (27.51) (24.72) (19.39) (19.09)

BM -0.0008 0.0014 -0.0022 -0.0010(-2.36) (6.46) (-9.74) (-2.02)

INV OP 0.0850(1.53)

RET 0.0017 0.0012 0.0005 -0.0050(3.10) (3.72) (1.53) (-6.79)

TURN 0.0006 0.0003 0.0003 0.0018(2.49) (2.09) (1.89) (5.10)

DY -0.0005 -0.0003 -0.0001 0.0010(-3.96) (-4.98) (-1.36) (5.91)

ROE 0.0000 0.0000 0.0000 0.0001(4.62) (2.88) (4.35) (5.14)

SIGMA 0.0042 0.0006 0.0036 0.0036(3.51) (0.89) (4.55) (2.15)

MSCI 0.0205 0.0092 0.0115 -0.0108(22.14) (16.59) (19.04) (-8.48)

LEV 0.9035 -0.0071 -0.0014 -0.0055 0.0045(8.42) (-4.34) (-1.47) (-5.23) (1.98)

CASH 1.7218 0.0135 0.0095 0.0039 0.0075(13.00) (5.69) (6.69) (2.55) (2.26)

ADR 0.0532 0.0380 0.0153 -0.0764(13.50) (16.18) (5.96) (-14.20)

CLOSE -0.4474 -0.0282 -0.0113 -0.0167 -0.0446(-6.02) (-22.15) (-14.73) (-20.31) (-24.96)

LEGAL -0.0179 -0.0006 -0.0001 -0.0004 0.0010(-8.01) (-14.73) (-5.41) (-17.67) (18.13)

COMMON -0.2949 0.0005 0.0033 -0.0030 0.0088(-3.47) (0.45) (5.30) (-4.51) (6.08)

DISC 0.7039 0.0092 0.0027 0.0066 0.0298(12.30) (9.76) (4.75) (10.82) (22.46)

DISTANCE 0.1519 -0.0149 -0.0048 -0.0100 -0.0962(2.04) (-12.15) (-6.52) (-12.64) (-55.88)

ENGLISH 0.3029 -0.0022 0.0034 -0.0056 0.0159(3.30) (-2.03) (5.08) (-7.82) (10.29)

GDP -0.4038 0.0005 0.0008 -0.0004 -0.0133(-13.71) (0.94) (2.43) (-1.08) (-17.75)

MCAP 0.0058 0.0021 -0.0009 0.0030 -0.0104(0.19) (4.73) (-3.44) (10.56) (-16.65)

Lambda -0.0144 -0.0107 -0.0034 0.0342(-7.03) (-8.81) (-2.56) (12.39)

X 2 11,779.6 4,562.2 9,052.5 12,855.4N 30,245 30,247 30,247 30,247

45

Table 9The Effect of Cross-Listing on Foreign Institutional Ownership

This table presents the impact on the level of institutional ownership of cross-listing in an U.S. exchange by non-U.S. firms. Panel A compares the level ofinstitutional ownership of non-US firms that are cross-listed in an U.S. exchange versus non-cross-listed firms. Figures are calculated for December 2000 andDecember 2004 and represent the average and median percentage of firms’ total stock market capitalization that is held by all foreign institutions, U.S. institutions,and non-U.S. foreign institutions. Panel B presents event study evidence on the change in median foreign institutional ownership for firms that cross-listed in anU.S. exchange in our sample period from 2000 to 2004. Figures are percentages of total stock market capitalization of the event firms.

Panel A: Foreign Institutional Ownership of Cross-Listed versus Non-Cross-Listed Firms (%)Type of Number of All Institutions US Institutions Non-US Institutions

Date Firm Firms Mean Median Mean Median Mean MedianDec-2000 Cross-listed 329 8.61 6.47 5.64 3.59 3.00 2.00

Non-cross-listed 12,886 1.74 0.04 0.96 0.00 0.80 0.00Dec-2004 Cross-listed 419 10.61 8.73 5.76 4.02 4.8 3.60

Non-cross-listed 13,042 2.35 0.20 1.11 0.06 1.20 0.00

Panel B: Change in Median Foreign Institutional Ownership Around Cross-Listing (%)Local Shares ADR Shares Local and ADR Shares

Quarters Number of All US Non-US All US Non-US All US Non-USFirms Institutions Institutions Institutions Institutions Institutions Institutions Institutions Institutions Institutions

-4 101 0.12 0.09 0.00 0.00 0.00 0.00 0.21 0.16 0.00-3 101 0.39 0.15 0.09 0.00 0.00 0.00 1.37 0.30 0.19-2 101 0.67 0.11 0.08 0.00 0.00 0.00 1.22 0.43 0.45-1 101 0.75 0.18 0.12 0.00 0.00 0.00 1.75 0.47 0.270 101 2.92 0.77 0.76 0.03 0.01 0.00 3.97 1.56 1.141 101 3.56 1.19 1.57 0.06 0.04 0.00 5.28 2.11 2.032 100 4.08 1.15 1.97 0.05 0.04 0.00 5.46 2.37 3.053 95 3.64 1.12 2.04 0.05 0.02 0.00 5.32 2.18 2.414 92 4.74 1.44 2.23 0.05 0.02 0.00 6.70 2.53 2.605 88 4.41 1.77 2.36 0.06 0.02 0.00 6.60 2.77 2.626 83 5.18 1.91 2.54 0.04 0.01 0.00 7.74 3.10 3.307 80 6.26 2.07 2.80 0.08 0.03 0.00 7.81 2.97 3.698 78 5.88 2.28 2.86 0.11 0.04 0.00 7.40 3.04 3.40

46

Table 10Firm Valuation and Foreign and Domestic Institutional Ownership

This table reports estimates of coefficients of the annual time-series cross-sectional firm-level regression for non-US firmsvaluation measured by Tobin’s Q. The firm-level regressors include foreign institutional ownership (PF ) with break-down by U.S. and non-U.S. institutions, domestic institutional onwership (PD), equity capitalization (SIZE), invest-ment opportunities (INV OP ), leverage (LEV ), cash holdings (CASH), ADR listed dummy (ADR), and global indus-try Tobin’s Q (GLOBAL_Q). The country-level regressors include legal regime index (LEGAL), common law dummyvariable (COMMON), disclosure index (DISC), average geographic distance, (DISTANCE), English language dummy(ENGLISH), GDP per capita (GDP ), and market capitalization to GDP (MCAP ). Refer to Table B.1 of Appendix B forvariable definitions. The sample period is from 2000 to 2004. Robust t-statistics are in parentheses. Coefficients significantat the 5% level are in boldface.

Non-US FirmsVariable Panel A: Foreign Panel B: Foreign Panel C: Foreign Panel D: Domestic

Ownership Ownership Ownership OwnershipAll Inst. US Inst. Non-US Inst.

Constant -0.1087 -0.0900 -0.1507 0.0343(-0.45) (-0.37) (-0.62) (0.14)

PF 0.6010 0.1857 1.2948(5.18) (0.94) (7.36)

PD -0.1595(-2.33)

SIZE 0.1002 0.1052 0.0997 0.1067(33.30) (36.37) (33.67) (37.71)

INV OP 0.2691 0.2703 0.2679 0.2703(10.43) (10.45) (10.41) (10.44)

LEV -0.0929 -0.0921 -0.0912 -0.0914(-3.64) (-3.60) (-3.58) (-3.58)

CASH 1.1354 1.1463 1.1363 1.1499(17.65) (17.77) (17.70) (17.84)

ADR -0.0814 -0.0646 -0.0761 -0.0626(-2.54) (-2.02) (-2.39) (-1.99)

GLOBAL_Q 0.6601 0.6635 0.6578 0.6644(22.35) (22.52) (22.23) (22.53)

LEGAL -0.0049 -0.0051 -0.0046 -0.0050(-7.79) (-8.29) (-7.41) (-8.01)

COMMON 0.1643 0.1642 0.1672 0.1671(12.49) (12.45) (12.72) (12.63)

DISC 0.1503 0.1568 0.1466 0.1606(11.17) (11.68) (10.87) (11.88)

DISTANCE -0.1652 -0.1763 -0.1585 -0.1943(-7.04) (-7.52) (-6.75) (-7.95)

ENGLISH 0.0961 0.0944 0.1022 0.0991(5.45) (5.32) (5.82) (5.53)

GDP 0.0000 0.0000 0.0000 0.0000(-3.81) (-3.96) (-3.72) (-4.07)

MCAP -0.0419 -0.0409 -0.0439 -0.0436(-4.17) (-4.06) (-4.36) (-4.28)

R2 0.2181 0.2169 0.2192 0.2170N 27890 27890 27890 27890

47

Table 11Firm Valuation and Foreign and Domestic Institutional Ownership:

Three-Stage Least Squares Regression

This table reports estimates of coefficients of the annual time-series cross-sectional firm-level regressions for non-US firmsvaluation measured by Tobin’s Q, and alternatively foreign institutional ownership (PF ) and domestic institutional onwer-ship (PD). The system of equations is estimated using three-stage least squares. The firm-level regressors include equitycapitalization (SIZE), book-to-market equity ratio (BM) investment opportunities (INV OP ), stock return (RET ), turnover(TURN), dividend yield (DY ), return-on-equity (ROE), idiosyncratic variance (SIGMA), MSCI index membership dummy(MSCI), leverage (LEV ), cash holdings (CASH), ADR listed dummy (ADR), closely held shares (CLOSE), and globalindustry Tobin Q (GLOBAL_Q). The country-level regressors include legal regime index (LEGAL), common law dummyvariable (COMMON), disclosure index (DISC), average geographic distance, (DISTANCE), English language dummy(ENGLISH), GDP per capita (GDP ), and market capitalization to GDP (MCAP ). Refer to Table B.1 of Appendix B forvariable definitions. The sample period is from 2000 to 2004. Robust t-statistics are in parentheses. Coefficients significantat the 5% level are in boldface.

Non-US FirmsVariable Panel A: Foreign Panel B: Domestic

Institutions InstitutionsOwnership Valuation Ownership ValuationEquation Equation Equation Equation

Constant 0.0520 -0.1627 0.8449 1.5308(3.80) (-0.78) (46.61) (4.55)

PF 2.3647(5.73)

PD -2.0287(-6.16)

SIZE 0.0064 0.0837 0.0053 0.1136(29.81) (17.72) (18.62) (43.24)

BM -0.0051 0.0054(-13.26) (10.57)

INV OP 0.0050 0.2623 0.0021 0.2679(5.01) (15.04) (1.63) (15.36)

RET 0.0040 -0.0070(6.97) (-9.24)

TURN 0.0005 0.0023(1.68) (6.46)

DY -0.0005 0.0012(-4.26) (7.10)

ROE 0.0000 0.0001(3.32) (4.86)

SIGMA 0.0050 0.0035(3.80) (2.01)

MSCI 0.0209 -0.0135(21.96) (-10.69)

LEV -0.0072 -0.0954 0.0029 -0.0862(-4.24) (-3.76) (1.29) (-3.39)

CASH 0.0107 1.1089 0.0087 1.1574(4.16) (27.46) (2.56) (29.31)

ADR 0.0292 -0.1443 -0.0158 -0.0900(19.34) (-5.37) (-7.90) (-3.88)

CLOSE -0.0294 -0.0419(-21.98) (-23.60)

GLOBAL_Q 0.6473 0.6641(38.54) (39.86)

LEGAL -0.0006 -0.0040 0.0011 -0.0028(-15.12) (-6.13) (20.59) (-3.88)

COMMON -0.0015 0.1636 0.0132 0.1900(-1.38) (9.88) (9.24) (10.94)

DISC 0.0099 0.1302 0.0299 0.2002(10.10) (9.46) (23.01) (13.86)

DISTANCE -0.0149 -0.1299 -0.1059 -0.3937(-11.35) (-5.98) (-61.01) (-9.76)

ENGLISH -0.0015 0.0988 0.0156 0.1454(-1.34) (5.70) (10.22) (7.54)

GDP -0.0002 0.0000 -0.0116 0.0000(-0.34) (-3.37) (-16.03) (-5.71)

MCAP 0.0027 -0.0451 -0.0118 -0.0686(5.86) (-6.51) (-19.01) (-7.87)

R2 0.2553 0.2074 0.2968 0.1961N 27890 27890 27890 27890

48

Appendix A. FactSet/LionShares Institutional Ownership Database

Table A.1Institutional Holdings Data per Country and Year

T h is t a b le c o n t a in s t h e d is t r ib u t io n o f Fa c tS e t / L io n S h a r e s g lo b a l in s t i t u t io n a l ow n e rh s ip d a t a by o r ig in c o u n t r y o f in s t i t u t io n s . M a rke t va lu e o f e q u it ie s m a n a g e d ( in m i l l io n s o f U S $ ) by in s t i t u t io n s f r om e a ch o f t h e 2 7 c o u n t r i e sw h ich a r e c ove r e d by th e d a t a s e t , t h e num b e r o f in s t i t u t io n s , a n d th e num b e r o f in d iv u a l fu n d s p e r c o u n t r y a t t h e e n d o f e a ch ye a r f r om 2 0 0 0 t o 2 0 0 4 a r e s h ow n . T h e c o lum n “ 5 L a rg e s t In s t i t u t io n s ” l i s t s t h e 5 la r g e s t in s t i t u t io n a lm a n a g e r s b y e q u ity a s s e t s h e ld p e r c o u n t r y in D e c em b e r 2 0 0 4 . C o lum n “ 3 L a rg e s t Fu n d s ” l i s t s t h e 3 in d iv id u a l fu n d s w i t h th e la r g e s t m a rke t va lu e o f a s s e t s u n d e r m a n a g em en t p e r c o u n t r y a s o f D e c em b e r 2 0 0 4 . In s t i t u t io n s a n dfu n d s n am e s a r e a b b r e v ia t e d in th e in t e r e s t o f s p a c e .

D e c - 2 0 0 0 D e c -2 0 0 1 D e c - 2 0 0 2 D e c -2 0 0 3 D e c -2 0 0 4 5 L a rg e s t In s t i t u t io n s 3 L a rg e s t Fu n d sU S U n i t e d S t a t e s To t a l e q u i ty a s s e t s 3 ,9 2 5 ,3 4 9 3 ,4 3 7 ,3 5 4 2 ,8 3 5 ,3 2 6 3 ,8 2 3 ,4 8 8 4 ,7 2 0 ,4 2 9 1 : F id e l i ty ( 5 4 8 b i l ) 1 : C R E F S to ck ( 1 0 9 .2 b i l )

N r o f in s t i t u t io n s 1 ,0 9 5 1 ,1 5 8 1 ,1 4 5 1 ,1 2 8 1 ,1 1 0 2 : C a p it a l R &M (5 2 4 b i l ) 2 : Va n g u a rd 5 0 0 In d ex Fu n d ( 1 0 6 .2 b i l )N r o f fu n d s 5 ,6 3 0 6 ,0 6 6 5 ,9 3 3 5 ,7 8 7 5 ,7 5 1 3 : Va n g u a rd ( 3 0 6 b i l ) 3 : A m e r i c a n Fu n d s G row th Fu n d o f A m e r ic a (7 6 .6 b i l )

4 : W e l l in g t o n ( 1 6 3 b i l )5 : T IA A -C R E F (1 5 2 b i l )

U K U n i t e d K in g d om To ta l e q u i ty a s s e t s 2 6 6 ,6 6 3 3 5 4 ,2 0 8 3 6 0 ,3 0 7 5 1 4 ,1 0 0 5 3 6 ,8 3 2 1 : JPM o rg a n F lem in g ( 4 1 b i l ) 1 : IN V E SC O P e rp e tu a l U K Inv t . S e r -H ig h In c om e ( 6 .3 b i l )N r o f in s t i t u t io n s 2 7 7 4 4 8 4 6 0 4 9 2 3 4 4 2 : S ch r o d e r ( 3 8 b i l ) 2 : L e g a l & G en e ra l U K In d e x Tru s t ( 4 .9 b i l )N r o f fu n d s 7 3 4 1 ,3 2 5 1 ,5 3 5 1 ,6 2 4 1 ,2 0 5 3 : F id e l i ty In t l ( 3 4 b i l ) 3 : Fo r e ig n & C o lo n ia l In ve s tm e n t Tru s t ( 4 .1 b i l )

4 : B G I ( 3 4 b i l )5 : IN V E SC O (2 5 b i l )

D E G e rm a ny To ta l e q u i ty a s s e t s 1 1 5 ,5 1 5 2 2 3 ,5 2 1 2 3 1 ,9 0 5 2 8 4 ,5 6 4 2 7 4 ,9 3 1 1 : D e u t ch e DW S (4 1 b i l ) 1 : DW S Ve rm o e g e n s b i ld u n g s fo n d s I ( 7 .5 b i l )N r o f in s t i t u t io n s 1 3 3 3 0 8 3 9 0 3 4 0 2 2 2 2 : D e ka ( 3 6 b i l ) 2 : A r iD e ka ( 6 .2 b i l )N r o f fu n d s 4 9 2 2 ,5 2 4 4 ,2 2 9 3 ,9 0 4 3 ,1 4 6 3 : D e u t s ch e r Inv Tru s t ( 1 9 b i l ) 3 : D ekaFo n d s ( 4 .6 b i l )

4 : D r e sd n e rb a n k ( 1 7 b i l )5 : C om in ve s t ( 1 5 b i l )

C A C a n a d a To t a l e q u i ty a s s e t s 7 6 ,9 4 8 1 7 5 ,3 2 5 1 7 2 ,2 2 2 2 5 5 ,7 3 6 2 4 7 ,1 9 9 1 : C D P (2 6 b i l ) 1 : C a i s s e d e D e p o t e t P la c em en t d u Q u e b e c ( 2 5 .9 b i l )N r o f in s t i t u t io n s 3 0 2 0 5 2 4 2 2 4 6 1 7 2 2 : C P P Inv t B o a rd ( 2 5 b i l ) 2 : C a n a d a P e n s io n P la n ( 2 5 .4 b i l )N r o f fu n d s 1 3 4 1 ,6 4 9 1 ,7 0 6 1 ,7 4 0 1 ,2 5 7 3 : A IM Tr im a rk ( 2 4 b i l ) 3 : O n t a r io Te a ch e r s P e n s io n P la n ( 1 2 .8 b i l )

4 : R B C (1 6 b i l )5 : T D (1 3 b i l )

F R Fra n c e To t a l e q u i ty a s s e t s 2 5 ,2 9 7 5 2 ,0 8 9 9 7 ,9 8 4 2 0 4 ,7 5 5 1 5 0 ,9 9 2 1 : IX IS ( 2 9 b i l ) 1 : B N P P a r ib a s A c t io n s E u ro la n d ( 4 .6 b i l )N r o f in s t i t u t io n s 5 3 1 0 1 1 6 6 1 9 7 1 0 7 2 : B N P Pa r ib a s ( 2 1 b i l ) 2 : E c u r e u i l D y n am ic ( 3 .1 b i l ) 3 : E c u r e u i l In v e s t i s s em e n t s ( 3 b i l )N r o f fu n d s 6 6 2 2 9 6 9 1 9 4 8 7 9 9 3 : A X A (1 1 b i l ) 3 : E c u r e u i l In v e s t i s s em e n t s ( 3 b i l )

4 : S o g é p o s t e ( 1 0 b i l )5 : S o c i é t é G é n é r a le ( 1 0 b i l )

S E Sw ed en To t a l e q u i ty a s s e t s 1 7 ,7 0 1 5 0 ,3 3 3 6 1 ,4 5 0 1 0 9 ,4 0 3 1 4 7 ,1 2 3 1 : R o b u r ( 2 4 b i l ) 1 : A le c ta P e n s io n ( 1 6 .1 b i l )N r o f in s t i t u t io n s 1 6 4 2 4 2 6 0 4 8 2 : A le c t a ( 1 6 b i l ) 2 : Fo r s t a A P Fon d en ( 1 2 b i l )N r o f fu n d s 1 2 2 3 4 3 3 9 6 4 0 4 3 8 1 3 : S E B (1 4 b i l ) 3 : S ka n d ia L iv ( 1 0 .1 b i l )

4 : F ö r s t a A P (1 2 b i l )5 : N o rd e a ( 1 0 b i l )

N O N o rw ay To ta l e q u i ty a s s e t s 1 ,4 4 1 3 0 ,8 9 3 3 8 ,8 8 8 7 0 ,8 3 4 9 4 ,2 5 7 1 : N o rg e s B a n k ( 6 7 b i l ) 1 : N o rg e s B a n k S t a t e n P e t r o le um Fu n d (6 6 .6 b i l )N r o f in s t i t u t io n s 7 2 6 2 8 3 0 2 8 2 : Fo lk e t r y g d fo n d e t ( 7 b i l ) 2 : Fo lk e t ry g d fo n d e t P en s io n Fu n d ( 6 .6 b i l )N r o f fu n d s 2 4 1 4 7 1 5 9 1 7 9 1 7 2 3 : S t o r e b r a n d (5 b i l ) 3 : V it a l Fo r s ik r in g A SA (3 b i l )

4 : V i t a l Fo r s ik r in g ( 3 b i l )5 : D nB (3 b i l )

IT I t a ly To t a l e q u i ty a s s e t s 1 6 ,4 2 0 5 6 ,1 1 6 5 2 ,8 8 7 7 7 ,5 4 6 8 2 ,5 4 1 1 : N e x t r a ( 1 7 b i l ) 1 : N EX T R A A z io n i E u ro p a ( 3 b i l )N r o f in s t i t u t io n s 2 3 5 4 8 7 1 0 0 5 0 2 : S a n P a o lo IM I ( 6 b i l ) 2 : P io n e e r A z io n a r io E u ro p a ( 1 .7 b i l )N r o f fu n d s 1 0 0 4 6 2 6 4 1 6 5 7 5 9 9 3 : A r c a SG R (6 b i l ) 3 : S a n p a o lo A z io n i I t a l i a (1 .6 b i l )

4 : F in e c o ( 5 b i l )5 : A z im u t ( 5 b i l )

C H Sw it z e r la n d To t a l e q u i ty a s s e t s 5 2 ,2 6 9 7 3 ,5 8 8 7 1 ,7 6 9 9 6 ,7 5 6 8 1 ,0 5 2 1 : U B S G lo b a l ( 3 1 b i l ) 1 : U B S E q u ity Fu n d - Sw i t z e r la n d ( 2 .6 b i l )N r o f in s t i t u t io n s 4 9 1 0 2 1 3 7 1 6 5 1 1 9 2 : C a p it a l In t l ( 1 0 b i l ) 2 : U B S 1 0 0 In d e x -Fu n d S w it z e r la n d (2 .3 b i l )N r o f fu n d s 1 0 8 1 6 8 2 0 5 2 5 1 1 6 5 3 : C r e d i t S u i s s e ( 7 b i l ) 3 : X M T CH on SM I ( 2 .2 b i l )

4 : P i c t e t Fu n d s ( 6 b i l )5 : J u l iu s B a e r ( 5 b i l )

J P J a p a n To t a l e q u i ty a s s e t s 1 4 ,7 3 9 1 3 ,1 6 4 1 4 ,9 0 3 6 7 ,8 2 1 7 3 ,1 9 1 1 : F id e l i ty J P (2 0 b i l ) 1 : F id e l i ty JP G row th E q u it i e s O p en M o th e r s Fu n d ( 6 b i l )N r o f in s t i t u t io n s 4 0 6 6 7 6 1 7 1 1 4 7 2 : N om u ra ( 1 1 b i l ) 2 : N om u ra J a p a n e s e S t ra t e g y M o th e r s Fu n d ( 3 .8 b i l )N r o f fu n d s 1 1 3 1 1 4 1 2 3 : JPM o rg a n F lem in g ( 5 b i l ) 3 : F id e l i ty J a p a n O p en Fu n d ( 3 .3 b i l )

4 : D a iw a ( 4 b i l )5 : S ch r o d e r s To s h ikom on (3 b i l )

N L N e th e r la n d s To t a l e q u i ty a s s e t s 3 2 ,9 2 9 3 4 ,4 9 3 4 6 ,3 4 6 6 6 ,7 8 9 6 8 ,3 8 6 1 : IN G (1 9 b i l ) 1 : IN G G lo b a l E q u ity Fo n d s ( 7 .9 b i l )N r o f in s t i t u t io n s 3 2 3 8 4 2 4 8 3 4 2 : A B N AM RO (1 9 b i l ) 2 : R o b e c o N V (7 .3 b i l )N r o f fu n d s 7 3 1 2 2 1 8 2 2 0 1 1 7 8 3 : R o b e c o ( 1 4 b i l ) 3 : IN G E u ro p a Fo n d s ( 3 .4 b i l )

4 : D e lt a L L oy d ( 3 b i l )5 : Fo r t i s ( 3 b i l )

49

Table A.1: continuedD ec -2 0 0 0 D e c -2 0 0 1 D e c -2 0 0 2 D e c -2 0 0 3 D e c -2 0 0 4 5 L a rg e s t In s t i t u t io n s 3 L a rg e s t Fu n d s

N L N e th e r la n d s To t a l e q u i ty a s s e t s 3 2 ,9 2 9 3 4 ,4 9 3 4 6 ,3 4 6 6 6 ,7 8 9 6 8 ,3 8 6 1 : IN G (1 9 b i l ) 1 : IN G G lo b a l E q u ity Fo n d s ( 7 .9 b i l )N r o f in s t i t u t io n s 3 2 3 8 4 2 4 8 3 4 2 : A B N AM RO (1 9 b i l ) 2 : R o b e c o N V (7 .3 b i l )N r o f fu n d s 7 3 1 2 2 1 8 2 2 0 1 1 7 8 3 : R o b e c o ( 1 4 b i l ) 3 : IN G E u ro p a Fo n d s ( 3 .4 b i l )

4 : D e l t a L L oy d ( 3 b i l )5 : Fo r t i s ( 3 b i l )

E S S p a in To t a l e q u i ty a s s e t s 3 ,2 0 7 2 1 ,5 3 2 2 1 ,1 4 9 3 3 ,0 0 1 4 0 ,2 1 3 1 : B SC H (6 b i l ) 1 : Fo n c a ix a B o ls a E u ro , F I ( 1 b i l )N r o f in s t i t u t io n s 2 2 1 7 3 2 7 9 2 5 1 2 1 4 2 : B B VA (5 b i l ) 2 : B B VA B o ls a E u ro p a , F I ( 0 .7 b i l )N r o f fu n d s 9 4 1 ,3 7 2 2 ,9 8 1 3 ,3 6 7 3 ,3 4 0 3 : In ve r c a ix a ( 2 b i l ) 3 : S a n t a n d e r C en t r a l H is p a n o E u ro a c c io n e s , F I ( 0 .6 b i l )

4 : U rq u i jo ( 2 b i l )5 : G e sb a n k in t e r ( 2 b i l )

B E B e lg iu m To ta l e q u i ty a s s e t s 2 4 ,8 7 2 3 0 ,2 2 9 2 6 ,5 5 5 3 8 ,7 6 3 3 9 ,4 8 4 1 : D ex ia ( 1 3 b i l ) 1 : S t a r Fu n d ( 2 .3 b i l )N r o f in s t i t u t io n s 2 2 3 9 3 5 4 3 3 7 2 : K B C (1 1 b i l ) 2 : Fo r t i s B P e n s io n Fu n d ( 1 .8 b i l )N r o f fu n d s 1 8 7 3 1 9 3 4 1 3 6 2 3 5 6 3 : IN G (5 b i l ) 3 : D e x ia Fu l l in v e s t - M ed ium (1 .6 b i l )

4 : Fo r t i s ( 3 b i l )5 : B a n q u e D e g r o o f ( 2 b i l )

H K H o n g K on g To t a l e q u i ty a s s e t s 1 6 ,3 4 4 1 5 ,1 8 5 1 6 ,7 0 1 3 1 ,5 2 4 3 6 ,0 0 4 1 : Tem p le t o n ( 7 b i l ) 1 : Tra ck e r Fu n d o f H o n g K on g ( 3 .9 b i l )N r o f in s t i t u t io n s 4 1 6 4 5 4 5 6 5 2 2 : J F ( 6 b i l ) 2 : J F P a c ifi c S e cu r i t ie s Fu n d ( 0 .5 b i l )N r o f fu n d s 1 6 9 2 7 3 : F id e l i ty H KG 3 : JF J a p a n (Ye n ) Fu n d (0 .4 b i l )

4 : S t a t e S t r e e t (4 b i l )5 : S ch ro d e r H KG (2 b i l )

D K D enm a rk To t a l e q u i ty a s s e t s 4 ,6 3 6 1 0 ,0 9 9 1 7 ,7 5 2 3 4 ,9 6 5 3 5 ,3 5 1 1 : AT P A rb e jd sm a rk ed e t s T i l læ g sp en s io n ( 6 b i l ) 1 : AT P P en s io n Fu n d ( 5 .6 b i l )N r o f in s t i t u t io n s 1 1 2 6 3 6 4 1 2 6 2 : N o rd e a ( 5 b i l ) 2 : D a n ic a P e n s io n ( 2 .6 b i l )N r o f fu n d s 2 7 1 4 5 2 1 9 2 3 9 2 2 7 3 : D a n s ke In ve s t (5 b i l ) 3 : L D P en s io n - L o nm o d ta g e rn e s D y r t id s fo n d ( 2 .4 b i l )

4 : P K A (4 b i l )5 : D a n ic a P e n s io n ( 3 b i l )

IE I r e la n d To t a l e q u i ty a s s e t s 8 ,8 0 6 2 2 ,6 2 9 2 0 ,0 8 4 2 9 ,3 5 5 3 2 ,7 6 8 1 : P io n e e r ( 1 7 b i l ) 1 : N a t io n a l P e n s io n s R e s e r v e Fu n d C om m is s io n ( 1 2 b i l )N r o f in s t i t u t io n s 1 1 1 7 1 6 1 7 1 1 2 : F id eu r am (1 4 b i l ) 2 : D e kaTe am G lo b a lS e l e c t ( 3 .7 b i l )N r o f fu n d s 1 6 4 3 2 7 5 5 5 6 0 2 5 2 3 3 : AG F (1 b i l ) 3 : E T F iS h a r e s D J E u ro ST OXX 50 ( 2 .7 b i l )

4 : M on t g om e ry O p p en h e im (1 b i l )5 : B a n k o f I r e la n d ( 0 .3 b i l )

S G S in g a p o r e To t a l e q u i ty a s s e t s 6 ,7 7 9 9 ,1 3 5 1 0 ,4 2 5 1 9 ,0 6 6 2 5 ,8 1 6 1 : A b e rd e e n (6 b i l ) 1 : A IG - A c o rn s o f A s ia B a la n c e d Fu n d ( 0 .3 b i l )N r o f in s t i t u t io n s 3 6 5 5 5 3 6 4 5 0 2 : Tem p le t o n ( 3 b i l ) 2 : S t r e e tT R AC K S ST I ( 0 .3 b i l )N r o f fu n d s 1 8 1 6 7 3 : S ch ro d e r SG (2 b i l ) 3 : S ch r o d e r A s ia n G row th Fu n d ( 0 .2 b i l )

4 : D eu t s ch e A s s e t M n g t A s ia ( 2 b i l )5 : P io n e e r S in g a p o r e ( 1 b i l )

L U L u x em b o u rg To t a l e q u i ty a s s e t s 1 ,4 1 9 1 1 ,6 9 7 1 0 ,3 6 0 1 9 ,0 2 3 2 2 ,6 7 7 1 : S a n P a o lo IM I L u x ( 7 b i l ) 1 : F id e l i ty S IC AV - E u ro p e a n G row th Fu n d ( 1 8 .2 b i l )N r o f in s t i t u t io n s 8 4 8 6 1 7 7 4 6 2 : N o rd e a B a n k L u x ( 3 b i l ) 2 : C a p i t a l In t l S IC AV -C IF G lo b a l E q u i ty Fu n d ( 6 .1 b i l )N r o f fu n d s 7 5 8 2 ,3 0 6 2 ,8 3 1 3 ,1 6 7 2 ,3 4 3 3 : K r e d i e t r u s t ( 2 b i l ) 3 : Fr a n k l in -Tem p le t o n G row th Fu n d ( 5 .8 b i l )

4 : DW S L u x ( 2 b i l )5 : B a n q u e d e L u x em b o u rg ( 2 b i l )

F I F in la n d To t a l e q u i ty a s s e t s 7 1 0 5 ,1 3 4 9 ,9 9 4 2 2 ,2 9 8 2 2 ,0 7 4 1 : Va rm a -S am p o ( 6 b i l ) 1 : Va rm a S am p o P e n s io n Fu n d ( 5 .5 b i l )N r o f in s t i t u t io n s 6 2 1 2 8 4 1 2 9 2 : I lm a r in e n M u tu a l ( 4 b i l ) 2 : I lm a r in e n M u tu a l P e n s io n In s u r a n c e ( 4 b i l )N r o f fu n d s 3 5 1 5 1 1 7 5 1 9 2 1 9 2 3 : O p s t o ck ( 2 b i l ) 3 : T h e S t a t e P e n s io n Fu n d ( 1 .8 b i l )

4 : S t a t e P en s io n Fu n d ( 2 b i l )5 : M an d a tum R a h a s t oy th t io ( 1 b i l )

Z A S o u th A f r ic a To t a l e q u i ty a s s e t s 1 6 0 2 5 9 4 ,8 0 7 8 ,1 8 7 1 4 ,1 1 6 1 : O ld M u tu a l A s s e t M an a g e r s ( 3 b i l ) 1 : A l la n G ray - E q u ity Fu n d ( 1 .2 b i l )N r o f in s t i t u t io n s 1 4 4 3 4 3 2 1 2 : A l la n G ray U n it Tru s t ( 2 b i l ) 2 : N e d b a n k R a inm a k e r Fu n d ( 0 .9 b i l )N r o f fu n d s 1 8 8 1 6 8 1 4 7 3 : In ve s t e c ( 2 b i l ) 3 : A l la n G ray - B a la n c ed Fu n d ( 0 .8 b i l )

4 : S t a n l ib ( 1 b i l )5 : P o la r i s C a p it a l Z A (1 b i l )

AU A u s t r a l ia To t a l e q u i ty a s s e t s 1 ,0 2 6 1 ,4 8 9 3 ,2 9 1 5 ,7 4 5 7 ,2 7 1 1 : U B S AU (3 b i l ) 1 : U B S AU S h a r e Fu n d ( 2 .6 b i l )N r o f in s t i t u t io n s 7 8 1 4 1 5 1 9 2 : B T Fu n d s AU (1 b i l ) 2 : JBWer e E m e rg in g L e a d e r s P o o le d Fu n d ( 0 .5 b i l )N r o f fu n d s 5 7 6 8 3 : G o ldm a n S a ch s JBWe r e ( 1 b i l ) 3 : JBWer e G lo b a l Sm a l l C om p a n ie s ( 0 .4 b i l )

4 : D eu t s ch e AU (0 .5 b i l )5 : C r ed it S u is s e AU (0 .4 b i l )

AT A u s t r ia To t a l e q u i ty a s s e t s 2 ,3 3 1 3 ,2 7 8 3 ,9 5 7 5 ,3 1 6 6 ,3 9 0 1 : C a p i t a l Inv e s t ( 1 b i l ) 1 : R a iff e i s e n - E u ro p a - A k t ie n f o n d s ( 0 .7 b i l )N r o f in s t i t u t io n s 2 1 3 5 4 5 4 7 4 2 2 : R a iff e i s e n ( 1 b i l ) 2 : R a iff e i s e n - O s t e u r o p a - A k t ie n fo n d s ( 0 .5 b i l )N r o f fu n d s 7 2 1 6 3 2 1 6 2 5 6 2 1 5 3 : Vo lk s b a n ke n ( 1 b i l ) 3 : R a iff e i s e n - U S - A k t i e n fo n d s ( 0 .4 b i l )

4 : E r s t e S p a r inve s t ( 1 b i l )5 : G u tm a n n ( 0 .4 b i l )

50

Table A.1: continuedD ec -2 0 0 0 D e c -2 0 0 1 D e c -2 0 0 2 D e c -2 0 0 3 D e c - 2 0 0 4 5 L a rg e s t In s t i t u t io n s 3 L a rg e s t Fu n d s

IN In d ia To t a l e q u i ty a s s e t s 2 2 6 1 1 9 1 2 3 3 ,8 8 4 5 ,5 5 7 1 : U T I ( 2 b i l ) 1 : Fr a n k l in In d ia B lu e C h ip Fu n d ( 0 .4 b i l )N r o f in s t i tu t io n s 2 3 3 3 1 2 7 2 : Fr a n k l in Tem p le t o n IN (1 b i l ) 2 : U T I - M a s t e rS h a r e U n it S ch em e ( 0 .3 b i l )N r o f fu n d s 1 7 4 1 9 1 3 : H SB C IN (0 .4 b i l ) 3 : U T I - U n it L in ke d In su r a n c e P la n ( 0 .3 b i l )

4 : P ru d en t ia l IC IC I ( 0 .3 b i l )5 : B i r la S u n L i f e ( 0 .3 b i l )

L I L ie ch t e n s t e in To t a l e q u i ty a s s e t s 9 0 1 2 ,3 6 3 2 ,9 2 9 1 : LG T (2 b i l ) 1 : C la s s ic G lo b a l E q u ity Fu n d s ( 0 .9 b i l )N r o f in s t i tu t io n s 1 0 1 2 1 3 2 : L L B (1 b i l ) 2 : L G T E q u i ty Fu n d G lo b a l S e c t o r Tr en d s (U SD ) ( 0 .5 b i l )N r o f fu n d s 6 9 9 1 8 7 3 : C ATAM (0 .1 b i l ) 3 : L G T E q u i ty Fu n d C on t in e n ta l E u ro p e (E U R ) ( 0 .4 b i l )

4 : P r in c ip a l Ve rm o e g e n s ve rw a l t u n g ( 0 .1 b i l )5 : S e r i c a Fo n d s le i t u n g ( 0 .1 b i l )

P T P o r tu g a l To t a l e q u i ty a s s e t s 8 8 1 8 3 4 1 ,1 4 5 2 ,1 8 0 2 ,7 4 1 1 : C A IX AG E ST (0 .5 b i l ) 1 : Tra n q u i l id a d e P PR (0 .2 b i l )N r o f in s t i tu t io n s 9 8 1 9 4 5 3 4 2 : B P I Fu n d o s ( 0 .4 b i l ) 2 : B P I G lo b a l ( 0 .2 b i l )N r o f fu n d s 2 1 2 9 1 0 3 1 5 8 1 8 0 3 : S a n t a n d e r ( 0 .4 b i l ) 3 : A F P PA (0 .2 b i l )

4 : M i l l e n n ium BC P (0 .3 b i l )5 : Tra n q u i l id a d e V id a ( 0 .2 b i l )

G R G re e c e To t a l e q u i ty a s s e t s 3 2 4 1 ,0 6 0 1 ,9 8 5 1 : E FG E u ro b a n k ( 1 b i l ) 1 : H e l le n i c Inv e s tm e n t ( 0 .5 b i l )N r o f in s t i tu t io n s 2 3 1 9 1 8 2 : H e l l e n i c Inv e s tm e n t ( 0 .5 b i l ) 2 : E u ro b a n k Fo rm u la I I Fo r e ig n M u tu a l Fu n d ( 0 .3 b i l )N r o f fu n d s 5 4 5 9 6 0 3 : P ro t o n ( 0 .1 b i l ) 3 : E u ro b a n k C l i ck In t e rn a t io n a l B a la n c e d Fu n d ( 0 .2 b i l )

4 : A lp h a A s s e t M g t ( 0 .1 b i l )5 : A lp h a Tru s t ( 0 .1 b i l )

P L P o la n d To t a l e q u i ty a s s e t s 1 ,1 0 1 1 ,1 2 5 1 : P io n e e r P e ka o ( 0 .5 b i l ) 1 : P io n e e r Z r ow n ow a z o n y F IO (0 .5 b i l )N r o f in s t i tu t io n s 1 6 1 1 2 : DW S P L (0 .2 b i l ) 2 : C U F IO P o l s k ich A kc j i ( 0 .1 b i l )N r o f fu n d s 4 9 2 3 3 : C om m e r c ia l U n io n P L (0 .1 b i l ) 3 : S ka rb ie c -A k c ja ( 0 .1 b i l )

4 : S ka rb i e c ( 0 .1 b i l )5 : M i l l e n n ium (0 .1 b i l )

A l l To t a l e q u i ty a s s e t s 4 ,6 2 7 ,4 6 1 4 ,6 5 3 ,5 9 8 4 ,1 5 8 ,5 2 1 5 ,8 5 8 ,4 0 8 6 ,7 9 8 ,5 7 7N r o f in s t i tu t io n s 1 ,9 5 2 3 ,0 4 9 3 ,5 3 4 3 ,7 9 5 3 ,0 3 1N r o f fu n d s 8 ,8 4 1 1 7 ,8 4 8 2 3 ,4 3 2 2 4 ,9 8 7 2 2 ,1 1 1

51

Table A.2Cross-Country Institutional Investments

T h is t a b l e p r ov id e s th e d is t r ib u t io n o f t o t a l a s s e t s in ve s t e d by 2 7 o r ig in c o u n t r ie s a n d d e s t in a t io n c o u n t r ie s in D e c em b e r 2 0 0 4 . A n e x t r a c a t e g o ry “O th e r ” g r o u p s a l l r em a in in g 2 1 c o u n t r ie s fo r w h ich c ov e r a g e i s s p a r s e a n d a r em o s t ly r e c ip ie n t c o u n t r ie s in t h e Fa c tS e t / L io n S h a r e s d a t a s e t . P a n e l A d e t a i l s t h e p o r t fo l i o a l lo c a t io n s p e r o r ig in c o u n t r y o f in s t i t u t io n ( r ow s ) a n d d e s t in a t io n c o u n t r y o f s t o ck s ( c o lum n s ) . F ig u r e s a r e in b i l l io n U S $ , a n d va lu e sg r e a t e r t h a n U S $ 1 b i l l io n a r e in b o ld fa c e . C o u n t r ie s n am e s a r e a b b r e v ia t e d ( r e f e r t o Tab le A .1 f o r fu l l c o u n t r ie s n am e s ) . P a n e l B p r e s e n t s t h e m a rke t va lu e o f t o t a l s t o ck s o f e a ch c o u n t r y th a t i s h e ld by a l l in s t i t u t io n a l in v e s t o r sf r om a l l c o u n t r i e s in t h e Fa c tS e t / L io n S h a r e s d a t a s e t ( c o r r e sp o n d in g t o c o lum n s o f P a n e l A ) . M a rk e t va lu e (M V ) o f s t o ck s h e ld by d om e s t ic ( i . e . , d om ic i l e d in s am e c o u n t r y a s th e s e c u r i ty i s i s s u e d ) , fo r e ig n a n d th e b r e a k d ow nby n o n -U .S . a n d U .S . f o r e ig n in s t i t u t io n s a r e sh ow n . P a n e l C p r e s e n t s t h e f r a c t io n o f e a ch c o u n t r y ’ s s t o ck m a rk e t t o t a l c a p i t a l i z a t io n th a t i s h e ld by a l l in s t i t u t io n s a n d b r e a k d ow n by g ro u p o f in s t i t u t io n s . P a n e l D p r e s e n t s t h ef r a c t io n o f e a ch c o u n t ry ’s s t o ck m a rk e t fl o a t ( i . e . m a rke t va lu e o f s t o ck th a t i s n o t c lo s e ly - h e ld a n d i s in ve s t a b l e by o u t s id e sh a r e h o ld e r s ) a s o f D e c em b e r 2 0 0 4 . P a n e l D a ls o p r e s e n t s t h e f r a c t io n o f e a ch c o u n t r y ’s fl o a t t h a t i s h e ldby a l l in s t i t u t io n s a n d b r e a k d ow n by g ro u p o f in s t i t u t io n s .

P a n e l A : P o r t fo l io A l lo c a t io n s p e r C o u n t ry o f O r ig in o f In s t i t u t io n a n d D e s t in a t io n C o u n t ry o f S t o ck ( in U S $ b i l l io n s , D e c em b e r - 0 4 )S t o ck C o u n t ry

U S UK D E CA FR SE N O IT C H JP N L E S B E HK DK IE SG LU F I Z A AU AT IN L I P T G R P L O th e r To t a lIn s t i t u t io nC o u n t ryU S 3 ,7 7 6 1 7 6 4 5 8 8 66 1 5 8 1 9 57 1 1 8 5 1 2 2 6 1 8 7 1 4 7 2 1 1 1 0 2 2 4 1 5 0 .0 2 2 1 1 5 9 4 ,7 2 0UK 5 2 2 3 9 2 3 5 32 6 3 1 5 20 3 4 1 6 1 1 4 5 2 5 2 1 4 4 6 2 2 0 .0 1 3 2 3 6 5 3 7D E 3 4 3 1 7 1 1 37 3 1 1 2 13 1 1 2 0 1 4 4 1 0 .8 2 0 .5 0 .8 5 0 .2 1 1 0 .6 0 .0 0 .5 1 0 .6 7 2 7 5C A 5 9 1 1 2 1 4 9 3 0 .7 0 .2 1 2 6 2 0 .9 0 .2 0 .7 0 .5 1 0 .3 0 .1 0 .4 0 .3 2 0 .1 0 .1 0 .0 0 .1 0 .1 0 .0 4 2 4 7FR 1 3 8 1 1 0 .6 77 0 .8 0 .4 6 3 5 7 6 3 0 .6 0 .3 1 0 .1 1 2 0 .3 0 .2 0 .6 0 .2 0 .0 0 .4 0 .7 0 .3 3 1 5 1SE 2 9 1 2 4 0 .8 4 7 3 1 1 5 4 2 2 0 .4 0 .5 1 0 .4 0 .2 0 .8 2 0 .0 0 .5 0 .2 0 .0 0 .0 0 .1 0 .1 0 .2 3 1 4 7NO 2 9 1 2 4 1 6 3 1 3 2 4 5 2 2 0 .7 0 .5 1 0 .6 0 .3 0 .2 1 0 .4 1 0 .3 0 .1 0 .0 0 .3 0 .3 0 .0 3 9 4IT 1 8 9 5 0 .3 7 0 .8 0 .1 2 1 3 7 3 2 0 .6 0 .5 0 .2 0 .3 0 .2 0 .1 0 .9 0 .2 0 .9 0 .1 0 .1 0 .0 0 .1 0 .3 0 .2 2 8 3C H 1 9 7 5 1 5 0 .6 0 .3 2 20 5 4 2 0 .6 0 .5 0 .2 0 .6 0 .1 0 .1 1 .0 0 .5 0 .5 0 .3 0 .2 0 .0 0 .2 0 .1 0 .2 5 8 1JP 3 0 .9 0 .2 0 .2 0 .3 0 .1 0 .0 0 .1 0 .2 6 3 0 .1 0 .1 0 .0 2 0 .1 0 .0 0 .1 0 .0 0 .0 0 .1 0 .2 0 .0 0 .1 0 .0 0 .0 0 .0 0 .0 3 7 3N L 2 0 8 3 0 .6 4 3 0 .4 2 3 4 1 1 1 0 .8 0 .8 0 .3 0 .6 0 .2 0 .1 0 .5 0 .3 0 .5 0 .2 0 .3 0 .0 0 .1 0 .3 0 .1 4 6 8E S 4 3 3 0 .1 4 0 .2 0 .0 1 1 0 .7 2 1 8 0 .3 0 .0 0 .0 0 .1 0 .0 0 .3 0 .6 0 .0 0 .0 0 .0 0 .0 0 .0 0 .3 0 .0 0 .0 0 .6 4 0B E 8 4 3 0 .2 5 0 .5 0 .2 1 2 1 2 2 7 0 .2 0 .1 0 .4 0 .0 0 .2 0 .7 0 .1 0 .1 0 .1 0 .0 0 .0 0 .1 0 .2 0 .0 0 .7 3 9HK 0 2 0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 2 0 .0 0 .0 0 .1 1 0 0 .0 0 .0 2 0 .0 0 .0 0 .3 1 0 .2 2 0 .0 0 .0 0 .1 0 .2 1 5 3 6DK 6 3 1 0 .2 1 1 0 .3 0 .5 1 2 0 .6 0 .7 0 .2 0 .6 1 3 0 .1 0 .1 0 .0 0 .3 0 .0 0 .2 0 .1 0 .3 0 .0 0 .0 0 .0 0 .2 3 3 5IE 6 5 2 0 .0 4 0 .3 0 .1 5 2 2 0 .9 1 0 .4 0 .5 0 .1 0 .7 0 .1 0 .0 0 .1 0 .1 0 .6 0 .0 0 .1 0 .0 0 .0 0 .0 0 .1 2 3 3SG 0 .5 0 .4 0 .1 0 .0 0 .2 0 .0 0 .0 0 .1 0 .1 3 0 .1 0 .1 0 .0 4 0 .0 0 .0 2 0 .0 0 .0 0 .0 2 0 .0 1 0 .0 0 .0 0 .0 0 .1 1 1 2 6LU 5 3 2 0 .2 2 0 .6 0 .1 1 1 2 1 0 .6 0 .3 0 .4 0 .2 0 .3 0 .1 0 .3 0 .5 0 .1 0 .3 0 .1 0 .1 0 .0 0 .0 0 .1 0 .0 1 2 3F I 1 2 1 0 .0 1 2 0 .3 0 .4 0 .8 0 .2 0 .8 0 .4 0 .1 0 .0 0 .2 0 .1 0 .0 0 .0 1 0 0 .0 0 .0 0 .1 0 .1 0 .0 0 .0 0 .0 0 .1 0 .6 2 2ZA 0 .5 1 0 .0 0 .1 0 .0 0 .0 0 .0 0 .0 0 .1 0 .1 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 1 1 0 .1 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .1 1 4AU 0 .6 0 .2 0 .0 0 .3 0 .0 0 .0 0 .0 0 .0 0 .0 0 .2 0 .0 0 .0 0 .0 0 .1 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 5 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .5 7AT 2 0 .6 0 .4 0 .0 0 .4 0 .0 0 .0 0 .1 0 .3 0 .4 0 .3 0 .1 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .1 0 .0 0 .0 0 .7 0 .0 0 .0 0 .0 0 .0 0 .2 1 .0 6IN 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 6 0 .0 0 .0 0 .0 0 .0 0 .0 6L I 0 .8 0 .2 0 .2 0 .0 0 .2 0 .1 0 .0 0 .1 0 .5 0 .4 0 .1 0 .1 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .1 3P T 0 .3 0 .1 0 .2 0 .0 0 .2 0 .0 0 .0 0 .1 0 .0 0 .1 0 .1 0 .1 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 1 0 .0 0 .0 0 .0 3G R 0 .5 0 .1 0 .1 0 .0 0 .1 0 .0 0 .0 0 .0 0 .1 0 .1 0 .1 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .8 0 .0 0 .1 2P L 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 1 0 .0 1O th e r 0 .9 2 0 .3 0 .1 1 0 .4 0 .0 0 .4 0 .9 3 .3 0 .4 0 .2 0 .0 0 .2 0 .1 0 .0 0 .3 0 .0 0 .1 1 0 .2 0 .0 0 .1 0 .0 0 .0 0 .0 0 .1 4 1 6To ta l 4 ,0 8 9 5 3 9 1 8 5 2 4 9 2 6 1 1 1 2 2 9 9 1 1 4 0 2 8 1 1 2 8 8 6 2 8 4 7 2 7 2 8 1 6 7 4 2 2 9 4 5 1 0 2 8 0 7 9 6 2 6 7 6 ,7 8 9

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Table A.2: continuedUS UK D E C A FR SE NO IT C H JP N L E S B E HK DK IE SG LU F I Z A AU AT IN L I P T G R P L O th e r To t a l To t a l

N o n -U S

P an e l B . M a rk e t Va lu e o f S t o ck s H e ld by A l l In s t i t u t io n a l Inv e s t o r s b y C ou n t ry (D e c em b e r 2 0 0 4 )N r . o f s t o ck s h e ld 7 ,0 2 8 2 ,1 4 5 8 3 3 1 ,7 9 1 6 7 4 3 2 7 1 8 8 3 2 2 2 7 0 3 ,5 3 6 1 9 7 1 8 9 2 2 3 7 7 2 1 6 4 7 7 3 4 1 5 7 1 5 5 2 5 8 6 9 2 1 0 8 5 6 5 2 5 6 2 3 3 1 5 4 4 ,1 4 5 2 5 ,5 0 2 1 8 ,4 7 4M V o f s t o ck s h e ld (b i l l i o n s ) 4 ,0 8 9 5 3 9 1 8 5 2 4 9 2 6 1 1 1 2 2 9 9 1 1 4 0 2 8 1 1 2 8 8 6 2 8 4 7 2 7 2 8 1 6 7 4 2 2 9 4 5 1 0 2 8 0 7 9 6 2 6 7 6 ,7 8 9 2 ,7 0 0M V h e ld by d om e s t i c in s t u t io n s 3 ,7 7 6 2 3 9 7 1 1 4 9 7 7 7 3 1 3 2 1 2 0 6 3 1 1 1 8 7 1 0 1 3 1 2 0 1 0 1 1 5 1 6 0 1 1 1 4 4 ,6 0 5 8 2 9M V h e ld by fo r e ig n in s t u t io n s 3 1 3 3 0 1 1 1 4 1 0 1 1 8 5 3 9 1 6 7 0 1 2 0 2 1 8 1 1 6 6 8 2 1 3 6 1 5 2 7 1 4 7 3 1 1 8 4 0 1 0 2 3 0 5 9 5 2 6 4 2 ,1 8 4 1 ,8 7 2M V h e ld by n o n -U .S . fo r e ig n e r s 3 1 3 1 2 5 6 9 1 2 1 1 9 2 3 8 5 1 6 3 1 0 1 6 6 4 6 1 5 1 8 8 1 3 7 5 2 0 8 1 8 6 8 0 3 6 4 1 0 5 1 ,2 4 0 9 2 7M V h e ld by U .S . fo r e ig n e r s 0 1 7 6 4 5 8 8 6 6 1 5 8 1 9 5 7 1 1 8 5 1 2 2 6 1 8 7 1 4 7 2 1 1 1 0 2 2 4 1 5 0 2 2 1 1 5 9 9 4 4 9 4 4

P a n e l C . Fra c t io n o f E a ch C o u n t ry ’ s S t o ck M a rke t To t a l C a p it a l i z a t io n H e ld by A l l I n s t i t u t io n s (D e c em b e r 2 0 0 4 )M a rk e t c a p it a l i z a t io n (b i l l io n s ) 1 4 ,1 6 0 4 ,4 6 8 1 ,6 4 0 9 9 7 2 ,0 8 3 4 4 8 1 8 6 9 7 4 1 ,2 4 6 4 ,4 7 2 1 ,0 7 7 9 0 0 2 9 8 7 8 5 1 5 6 1 7 9 2 3 7 5 7 2 7 2 3 0 3 9 5 5 9 7 3 2 6 3 1 0 4 1 4 2 5 5 2 ,9 8 5 3 9 ,6 0 4 2 5 ,4 4 4% h e ld b y a l l in s t i t u t io n s 2 8 .9 1 2 .1 1 1 .3 2 5 .0 1 2 .6 2 4 .9 1 5 .8 9 .3 1 1 .2 6 .3 1 1 .8 9 .5 9 .5 5 .9 1 7 .6 1 5 .5 6 .9 1 2 .6 1 5 .3 9 .7 4 .7 1 0 .8 8 .7 4 .5 6 .4 6 .6 1 1 .8 9 .0 1 7 .1 1 0 .6% h e ld b y d om e s t i c in s t u t io n s 2 6 .7 5 .3 4 .3 1 4 .9 3 .7 1 6 .3 7 .0 2 .1 1 .6 1 .4 1 .0 2 .0 2 .5 1 .3 8 .3 0 .4 1 .1 0 .6 3 .8 3 .8 0 .5 0 .7 1 .7 1 .1 1 .3 0 .6 1 .9 0 .1 1 1 .6 3 .3% h e ld b y fo r e ig n in s t u t io n s 2 .2 6 .7 6 .9 1 0 .1 8 .9 8 .7 8 .8 7 .2 9 .6 4 .9 1 0 .8 7 .5 7 .0 4 .6 9 .4 1 5 .1 5 .9 1 2 .0 1 1 .5 5 .9 4 .2 1 0 .1 7 .0 3 .4 5 .1 6 .0 1 0 .0 8 .8 5 .5 7 .4% h e ld b y n o n -U .S . fo r e ig n e r s 2 .2 2 .8 4 .2 1 .2 5 .7 5 .2 4 .2 5 .3 5 .0 2 .2 6 .1 5 .1 5 .1 2 .3 4 .9 7 .4 2 .9 8 .5 7 .4 2 .6 1 .9 6 .2 2 .4 3 .1 3 .1 4 .4 8 .1 3 .5 3 .1 3 .6% h e ld b y U .S . fo r e ig n e r s 0 .0 3 .9 2 .7 8 .8 3 .2 3 .4 4 .5 1 .9 4 .6 2 .6 4 .7 2 .4 1 .9 2 .3 4 .4 7 .7 3 .0 3 .5 4 .1 3 .3 2 .3 3 .8 4 .6 0 .3 2 .0 1 .6 1 .9 5 .3 2 .4 3 .7

P a n e l D . Fra c t io n o f E a ch C o u n t ry ’s S t o ck M a rke t F lo a t H e ld by A l l In s t i t u t io n s (D e c em b e r 2 0 0 4 )% o f c lo s e ly h e ld s h a r e s 1 0 .3 1 1 .1 4 0 .7 1 9 .4 3 1 .4 2 1 .1 5 4 .5 3 4 .6 2 6 .0 3 4 .1 2 3 .1 4 0 .6 4 0 .7 6 1 .5 3 7 .4 9 .7 3 8 .6 4 9 .4 1 6 .9 4 2 .6 3 1 .2 5 7 .4 5 8 .6 n .a . 3 8 .0 4 4 .1 5 5 .0 n .a . 2 2 .2 2 9 .6Inv e s t a b le m a rke t fl o a t ( b i l l io n s ) 1 2 ,7 0 0 3 ,9 7 1 9 7 2 8 0 4 1 ,4 2 9 3 5 3 8 5 6 3 7 9 2 2 2 ,9 4 9 8 2 8 5 3 5 1 7 7 3 0 2 9 7 1 6 2 1 4 6 2 9 2 2 6 1 7 4 6 5 7 4 1 1 3 5 n .a . 6 5 7 9 2 5 n .a . 2 8 ,5 0 0 1 5 ,8 0 0% h e ld b y a l l in s t i t u t io n s 3 2 .2 1 3 .6 1 9 .0 3 1 .0 1 8 .3 3 1 .6 3 4 .7 1 4 .3 1 5 .2 9 .5 1 5 .4 1 6 .1 1 6 .0 1 5 .4 2 8 .1 1 7 .2 1 1 .3 2 5 .0 1 8 .4 1 6 .8 6 .9 2 5 .4 2 1 .1 n .a . 1 0 .3 1 1 .7 2 6 .3 n .a . 2 2 .9 1 5 .4% h e ld b y d om e s t i c in s t u t io n s 2 9 .7 6 .0 7 .3 1 8 .5 5 .4 2 0 .6 1 5 .4 3 .3 2 .2 2 .1 1 .3 3 .4 4 .2 3 .4 1 3 .2 0 .4 1 .7 1 .2 4 .5 6 .6 0 .8 1 .7 4 .1 n .a . 2 .1 1 .0 4 .2 n .a . 1 6 .1 5 .2% h e ld b y fo r e ig n in s t u t io n s 2 .5 7 .6 1 1 .7 1 2 .5 1 2 .9 1 1 .0 1 9 .3 1 1 .0 1 3 .0 7 .4 1 4 .1 1 2 .7 1 1 .8 1 2 .0 1 4 .9 1 6 .7 9 .6 2 3 .8 1 3 .9 1 0 .2 6 .1 2 3 .6 1 7 .0 n .a . 8 .2 1 0 .8 2 2 .1 n .a . 6 .7 1 0 .2% h e ld b y n o n -U .S . fo r e ig n e r s 2 .5 3 .1 7 .1 1 .5 8 .3 6 .6 9 .3 8 .1 6 .8 3 .4 8 .0 8 .6 8 .6 6 .0 7 .9 8 .2 4 .6 1 6 .8 8 .9 4 .5 2 .8 1 4 .7 5 .9 n .a . 4 .9 7 .9 1 7 .9 n .a . 4 .0 5 .2% h e ld b y U .S . fo r e ig n e r s 0 .0 4 .4 4 .6 1 1 .0 4 .6 4 .4 1 0 .0 2 .9 6 .2 4 .0 6 .1 4 .1 3 .2 6 .0 7 .1 8 .6 4 .9 6 .9 5 .0 5 .7 3 .3 9 .0 1 1 .1 n .a . 3 .2 2 .8 4 .2 n .a . 2 .8 5 .0

53

Appendix B

Table B.1Variables Definition

Variable DefinitionPanel A: Firm-Level Control Variables

Market capitalization (log) SIZE Log annual market capitalization in US$ (WS item 02999)Book-to-market (log) BM Log of the book-to-market equity ratio (end-of-year market value of equity is from DS

and book value of equity is WS item 03501).Investment opportunities INV OP Two-year geometric average of annual growth rate in net sales in US$ (WS item 01001)Annual stock return RET Annual (end-of-year) geometric stock rate of return (DS item P)Turnover TURN Annual share volume (DS item VO) divided by adjusted shares outstanding (DS items NOSH/AF)Dividend yield DY Dividend yield (WS item 09404)Return-on-equity ROE Return-on-equity (WS item 08301)Idiosyncratic variance SIGMA Idiosyncratic variance estimated from the domestic market model.MSCI membership dummy MSCI MSCI member dummy, which equals one if a firm is a member of the MSCI All-country World IndexLeverage LEV Ratio of total debt (WS item 03255) to total assets (WS item 02999)Cash CASH Ratio of cash and short term investments (WS item 02001) to total assets (WS item 02999)ADR listed dummy ADR ADR dummy, which equals one if a firm is cross-listed on an US exchangeClosely held shares CLOSE Number of shares held by insiders as a proportion of the number of shares outstanding (WS item 08021)Foreign sales FXSALES International annual net sales (WS item 07101) as a proportion of net sales (WS 01001)Number of analysts ANALY STS Number of analysts covering a firm as reported by I/B/E/SCorporate governance ranking CGQ Overall corporate governance ranking by Institutional Shareholder Service (ISS)Tobin’s Q Q Sum of total assets (WS item 02999) plus market value of equity (WS item 02999) less

book value of equity WS item 03501) divided by total assetsGlobal industry Tobin’s Q GLOBAL_Q Median Tobin’s Q of firms in each two-digit SIC global industry

Panel B: Country-Level Control VariablesLegal regime quality index LEGAL Anti-director rights (shareholders rights) multiplied by the rule of law index (LLSV (1998))Common law dummy COMMON Legal origin dummy variable, which equals one if a country has a common law origin (LLSV (1998))Disclosure quality index DISC Accounting transparency index (Global Competitiveness Report)Average distance (log) DISTANCE Average bilateral distance in kilometers (log) between a country capital city and other capital citiesEnglish language dummy ENGLISH English language dummy variable, which equals one when a country’s official language is English (World Factbook)GDP per capita (log) GDP Annual log gross domestic product per capita in US$ (World Bank WDI)Market capitalization to GDP MCAP Annual ratio of stock market capitalization to gross domestic product in US$ (World Bank)

54