Board of Governors of the Federal Reserve System

International Finance Discussion Papers

Number 691

December 2000

INFORMATION COSTS AND HOME BIAS:

AN ANALYSIS OF U.S. HOLDINGS OF FOREIGN EQUITIES

Alan G. Ahearne, William L. Griever, and Francis E. Warnock

NOTE: International Finance Discussion Papers are preliminary materials circulated to stimulate

discussion and critical comment. References in publications to International Finance Discussion Papers

(other than an acknowledgment that the writer has had access to unpublished material) should be cleared

with the author or authors. Recent IFDPs are available on the Web at www.federalreserve.gov/pubs/ifdp/.
INFORMATION COSTS AND HOME BIAS:

AN ANALYSIS OF U.S. HOLDINGS OF FOREIGN EQUITIES

Alan G. Ahearne, William L. Griever, and Francis E. Warnock*

Abstract: We aim to provide insight into the observed equity home bias phenomenon by analyzing the

determinants of U.S. holdings of equities across a wide range of countries. In particular, we explore the role

of information costs in determining the country distribution of U.S. investors’ equity holdings using a

comprehensive new data set on U.S. ownership of foreign stocks. We find that U.S. holdings of a country’s

equities are positively related to the share of that country's stock market that is listed on U.S. exchanges, even

after controlling for capital controls, trade links, transaction costs, and historical risk-adjusted returns. We

attribute this finding to the fact that foreign firms that list on U.S. exchanges are obliged to provide

standardized, credible financial information, thereby reducing information costs incurred by U.S. investors.

This obligation stems from U.S. investor protection regulations, which include stringent disclosure

requirements, reconciliation of financial statements to U.S. standards, and an investor-friendly regulatory

environment. Our results support the hypothesis that information costs are an important source of home bias:

Foreign countries whose firms do not alleviate information costs by listing on a U.S. exchange are more

severely underweighted in U.S. equity portfolios.

JEL Classification: G11, G15, M40, K00

Keywords: information asymmetries, investor protection, accounting standards, portfolio choice

*

 The authors thank Stanley Black, Rob Dekle, Andrew Karolyi, Philip Lane, Tim McCormick, Darius Miller,

Assaf Razin, Helene Rey, Sergei Sarkissian, participants at seminars at the IF Monday Workshop and the

IMF Institute, and participants at the Washington Area Finance Association, Southern Economic Association,

and Western Economic Association conferences for helpful comments and discussions; Jean Tobin of the

NYSE for providing information on non-U.S. NYSE-listed firms; Eric Richards for help with the CompuStat

database; and Nancy Baer, Chad Cleaver, Molly Mason, and Yvonne Nickens for research assistance. All

errors are our own. The views in this paper are solely the responsibility of the authors and should not be

interpreted as reflecting the views of the Board of Governors of the Federal Reserve System, or of any other

person associated with the Federal Reserve System. Corresponding author: frank.warnock@frb.gov
1

 In Figure 1, the two data points marked with asterisks, March 1994 and December 1997,

are the only dates for which actual data on U.S. holdings of foreign equities exist; for all other

periods, the Bureau of Economic Analysis (BEA) estimates holdings based on flows and

valuation adjustments.

2

 The interested reader will note from Figure 1 that the share of foreign equities in U.S.

portfolios rose sharply between 1987 and 1994. Between 1987 and 1990, the increase was due to

sluggish growth in U.S. stock markets; between 1992 and 1994, strong increases in U.S. holdings

of foreign equities outpaced increases in U.S. market capitalization. Since 1994, U.S. investors

have continued to add foreign stocks to their portfolios, but the share of foreign stocks has

leveled off, reflecting gains in U.S. stock prices.

I. Introduction

The international version of the classical capital asset pricing model (ICAPM), based on

traditional portfolio theory developed by Sharpe (1964) and Linter (1965), predicts that to

maximize risk-adjusted returns investors should hold the world market portfolio of risky assets,

irrespective of their country of residence. In practice, however, the proportion of foreign assets

in investors’ portfolios tends to be very small. In the case of equities, foreign stocks make up a

disproportionately small share of investors’ equity holdings when one considers relative stock

market capitalizations. Equivalently, there is evidence of large gains from international portfolio

diversification; see, for example, Lewis (1999). The phenomenon whereby individuals hold too

little of their wealth in foreign assets relative to the predictions of theory, commonly referred to

as the home bias puzzle, is discussed by among others French and Poterba (1991), Cooper and

Kaplanis (1994), and Tesar and Werner (1995).

Figure 1 shows the share of foreign stocks in the equity portfolio of U.S. investors,

compiled using data from U.S. Flow of Funds statistics.1

 The figure indicates that although the

degree of home bias in U.S. equity portfolios lessened between the mid-1980s and the mid1990s, it remained relatively large. As of end-1997, foreign equities comprised roughly 10

percent of U.S. equity holdings, a greater share than the estimated 2 percent in the late 1980s, 

but far short of the 52 percent of world stock market capitalization accounted for by foreign

stocks.2

The ICAPM prediction that individuals hold equities from around the world in proportion

to market capitalizations is based on the assumption that there are no barriers to international

investment. In practice, such barriers do exist, although many have fallen substantially over the

past few decades. Direct barriers--such as capital controls, foreign taxes, and transactions costs--
3

 Bordo, Eichengreen, and Irwin (1999) note that the U.S. railroad industry received a

disproportionately large share of portfolio investment flows from Britain in the late 19th century. 

They argue that this was because information about the railroad sector was more readily available

and of better quality, due in large part to standardized accounting principles, disclosure

requirements of the New York Stock Exchange (NYSE), and regulation by the Interstate

2

have been lowered significantly, and in some cases completely eliminated. That the foreign

equity share of U.S. investors’ portfolios is still so low has led researchers to search for other

possible causes of home bias. In particular, researchers have increasingly focused on the

potential role of indirect barriers.

 One type of indirect barrier that has received considerable attention recently is

information costs. A number of recent empirical studies provide evidence that information costs

affect the composition of investors’ portfolios. For example, there is evidence that foreign equity

portfolios are skewed towards the equities of large firms, for which more information is readily

available; see Kang and Stulz (1997) for evidence on foreign investment in Japanese securities

and Treasury Department (1998) for evidence on foreign investment in U.S. securities. Portes

and Rey (1999) provide evidence that information flows are an important determinant of crossborder equity transactions. Even within countries, there is evidence that investors tend to hold

stocks of local companies, about which they presumably have more information. For example,

Coval and Moskowitz (1999) show that U.S. investment managers exhibit a strong preference for

locally-headquartered firms. Each of these studies suggests that asymmetric information between

local and non-local investors may be an important factor for investment decisions.

In this paper, we provide additional evidence that information asymmetries are an

important determinant of the observed home bias of U.S. investors. In particular, we explore the

role of information asymmetries that arise from differences in accounting standards, disclosure

requirements, and regulatory environments across countries. When investors contemplate

purchasing equity in a foreign company, they must glean from published accounts information

that is based on accounting principles and disclosure requirements that may differ greatly from

those in their home country. Moreover, the credibility of this information is determined to a

large extent by the regulatory environment, which also varies considerably from country to

country.3

 Cross-country differences in accounting principles, disclosure requirements, and
Commerce Commission, a precursor to the Securities and Exchange Commission (SEC).

4

 We are not suggesting that Level 1 ADRs reduce information costs to U.S. investors. 

Level 1 ADRs trade on the OTC market as pink sheets, are relatively illiquid, and are not subject

to the stringent regulatory requirements. In number, the vast majority of ADR programs are

Level 1; by market capitalization, exchange-listed (Levels 2 and 3) ADRs are much greater. See

Karolyi (1998) and Miller (1999) for excellent discussions of ADR programs.

3

regulatory environments--which together can be thought of as investor protection regulations--

give rise to information costs that must be borne by foreign investors. Information costs

associated with investing in some countries may be significantly higher than in others. 

Some foreign firms effectively alleviate information costs facing U.S. investors by listing

their stocks on U.S. exchanges, either directly or as Level 2 or Level 3 American Depositary

Receipts (ADRs). To list on U.S. exchanges, the foreign firm must reconcile its accounts with

U.S. generally accepted accounting principles (GAAP), meet the SEC’s stringent disclosure

requirements, and subject itself to the associated regulatory burden, tasks that are by no means

costless to the firm.4

We are not the first to suggest that cross-listing can alleviate information asymmetries. 

For example, Lins, Strickland, and Zenner (2000) argue that firms from developing countries that

list on U.S. exchanges gain enhanced access to capital markets due to a reduction in information

asymmetries that reflects greater disclosure requirements, shareholder rights protection, liquidity,

and analyst following. Similarly, Baker, Nofsinger, and Weaver (2000) find a cross-listing on

the NYSE is associated with increased analyst coverage and decreased cost of capital, and that

these benefits are greater than for foreign firms that list on the London Stock Exchange, partially

offsetting the higher costs associated with a NYSE listing. Stulz (1999) argues that firms from

countries with lower disclosure requirements cannot credibly communicate their prospects to

investors. To raise external funds, such firms might cross-list on an exchange with higher

disclosure standards, thereby sending a positive signal to investors. A similar rationale for crosslisting on a market with greater regulatory strictness appears in Fuerst (1998). Finally, La Porta,

Lopez-de-Silanes, and Shleifer (1999) analyze ownership concentration in 27 wealthy economies

and find that firms from countries with poor shareholder protection are less widely held. They
4

conclude that these firms can improve their access to external capital by listing on a U.S.

exchange. 

Our work also focuses on the role of listing on U.S. exchanges in reducing information

asymmetries, but from the perspective of investors. We argue that firms that do not reduce

information costs to U.S. investors by listing on U.S. exchanges are more likely to be

underweighted in U.S. portfolios. By extension, countries whose firms tend not to list on U.S.

exchanges will be more severely underweighted in U.S. portfolios, resulting in home bias at an

aggregate level.

To explore the implications of information costs for the home bias puzzle, we use a

comprehensive new data set on U.S. investors' holdings of foreign equities, covering 164

countries, of which we include the largest 48 in our statistical analysis. We find that the share of

a country's stock market that is listed on U.S. exchanges--and hence the share of that country’s

firms that have alleviated information costs associated with differences in financial standards,

requirements, and regulations--helps explain the country-distribution of U.S. investors' equity

portfolio, even after controlling for other variables such as trade flows, foreign ownership

restrictions, transaction costs, and reward-to-risk ratios. 

The remainder of the paper is organized as follows. Section 2 presents an illustrative

model and discusses in more detail sources of information asymmetries, focusing on differences

in accounting standards across countries. Section 3 describes our data set on U.S. investors’

holdings of foreign equities. The main results of statistical analysis on U.S. investors' holdings

of foreign equities are presented in Section 4. Section 5 presents further regression results and

Section 6 concludes. 

II. Role of Asymmetric Information

Information Costs and Home Bias: A Model

It is well known that there are costs associated with investing abroad. Some of these

costs are explicit, such as transaction fees, taxes, commissions, and the costs of gathering

information. In addition, investors face implicit costs, including costs that arise from

informational disadvantages vis-a-vis local residents. Both types of costs serve to lower
5

 Seminal papers modeling the effects of barriers to international investment are Black

(1974) and Stulz (1981).

6

 Many researchers note that proportional costs are not likely to inhibit cross-border

investment because Tesar and Werner (1995) showed that the turnover rates on foreign portfolios

are quite high. However, using holdings data from U.S. benchmark surveys, Warnock (2000)

shows that this result was based on published, official holdings estimates that grossly

underestimated cross-border holdings.

5

expected net returns on foreign investment. For example, investors who are considering which

stocks to purchase in a particular foreign country will want to differentiate between firms in that

country with good profit prospects and those whose prospects are poor. To the extent that lax

disclosure requirements--or lax enforcement of disclosure requirements--makes such

differentiation difficult, these investors may end up holding more foreign “lemons” than local

insiders who have better information.

To fix ideas, we present a model of international portfolio allocation drawn from Cooper

and Kaplanis (1986). The model includes country-specific proportional investment costs,

representing both explicit and implicit costs of investing abroad.5

 Proportional costs are a valid

representation of the information costs we envision because it is not sufficient to merely learn the

accounting standards of the foreign country (which would be a fixed cost). Given differences in

disclosure requirements and regulatory environments, in many countries the true picture of

earnings is available only to insiders. While one could argue that the cost of becoming an insider

is fixed at the firm level, the number of firms is not fixed, so the cost could still be represented by

a proportional cost at the country level.6

Under standard ICAPM assumptions, the ith investor’s optimization problem is to choose

xi, the allocation of her wealth among risky securities in n countries, to maximize expected

returns net of costs, or:

max (x k

i R  x ki ci

)

subject to 

x k

i Vxi v
7

 Here, h is the Lagrange multiplier on the constraint . x k

i Vxi v

6

x k

i I 1

where

xi is a column vector, the nth element of which, xin, is the proportion of

individual i’s wealth invested in securities in country n

R is a column vector of pre-cost expected returns

ci is a column vector, the nth element of which, cin, is the cost to investor i of

holding securities in country n

v is a constant

V is the variance/covariance matrix of the gross (pre-cost) returns of the

securities

I is a unity column vector

Wi is the proportion of world wealth owned by country i

M is a column vector, the ith element of which, Mi, is the proportion of world

market capitalization in country i’s market

For simplicity, assume that the covariance matrix, V, is diagonal with all variances equal to s2. 

Imposing the world capital market clearing condition, , the solution to this problem ˆ Wixi M

simplifies to7

hs (1) 2 (xinMn ) cin  bn  ai  d

where

a (weighted average marginal cost for investor i) i zkci

b (world weighted average cost in country n) n ˆ Mjcjn

d zkˆ M (world weighted average cost) ici

and

z V (global minimum variance portfolio) 1 I / (IkV 1 I)
8

 The discussion of accounting practices in this section borrows heavily from Breeden

(1994).

7

In the case with no costs to investing, ci

 is a zero vector and the right-hand side of (1) is

zero. Hence ; that is, investor x i allocates his wealth across countries according to in Mn

market capitalizations.

In the more general case with non-zero and non-uniform costs, if the actual cost to

investor i of investing in country n (cin) is high relative to investor i’s average cost to investing

(ai) or relative to all investors’ costs to investing in country n (bn), then the right-hand side of (1)

is likely negative and investor i will underweight country n in his portfolio. The higher are costs

in a particular foreign market, the more severely underweighted that country will be in the

investor’s portfolios. Moreover, since investors do not face such costs in their home market,

equation (1) predicts an overweighting of domestic stocks--the equity home bias--when costs

exist in other countries.

Listing on a U.S. Exchange: Reducing the Information Costs for U.S. Investors8

The model in the preceding section shows that investment costs, including implicit costs

arising from information asymmetries, can result in some countries being underweight in

investors’ portfolios. One implication is that investors are likely to underweight countries for

which it is costly to gather and analyze firm-level information. 

In this section we discuss in greater detail one particular source of information about a

firm's financial condition and prospects: published financial statements. As mentioned earlier,

accounting practices differ greatly around the world. In some countries, accounting practices are

thought to favor company insiders over investors, while, in other countries, especially the United

States, accounting rules are geared towards investor protection. To list on a U.S. exchange, the

SEC requires non-U.S. firms to make full disclosure and provide a reconciliation of foreign

financial statements to U.S. GAAP. This allows investors to compare companies more easily

across industries, irrespective of geography; without this requirement U.S. investors would be

confronted with financial statements prepared under at least 40 different sets of accounting

principles. Reconciliation of foreign financial statements to U.S. GAAP imposes a significant
9

 Under U.S. GAAP the event must be probable and estimable before a reserve may be

booked. 

10 Listing in the U.S. also reduces transactions costs faced by U.S. investors. We discuss

this further in Section V. 

8

burden on the foreign company, and at the same time represents a saving for U.S. investors,

whose cost of acquiring information about the company is greatly reduced. 

Perhaps more important than reconciliation to U.S. GAAP are the SEC’s stringent

disclosure requirements. U.S. investors benefit when foreign firms list on U.S. exchanges

because problems associated with lax disclosure requirements--or lax enforcement of disclosure

requirements--that often cloud the true picture of a firm’s financial condition are alleviated. The

case of Daimler Benz’s listing on the NYSE in 1993 is illustrative. Accounting rules in Germany

give companies wide latitude in how they choose to portray current earnings or financial

conditions. In particular, under German GAAP the firm can, with few restrictions, substantially

understate or overstate earnings by creating hidden reserves, or provisions. In good times,

reported income can be reduced by creating provisions for potential future adverse events.9

 In

bad times, the company can release reserves into current income in a way that masks current

losses. 

To list on the NYSE, Daimler-Benz had to reconcile its financial statements going back

three years. In doing so, the DM200 million profit for the first half of 1993 it had reported under

German GAAP became a DM1 billion loss under U.S. GAAP. The difference was an

undisclosed release of DM1.5 billion in provisions into income, clearly shown in Daimler’s

reconciliation to U.S. GAAP. Under German GAAP, only insiders such as the firm’s board

members--which typically include managers from German banks--knew its true financial

condition without the smoothing out by provisions.

Our hypothesis in this paper is that foreign firms that list on U.S. exchanges, and thereby

reduce information costs for U.S. investors, are more likely to be held by U.S. investors. At the

country level, we expect the extent to which a country’s firms list in the U.S. to be an important

determinant of its share in the U.S. foreign equity portfolio.10 
11 Details on data and sources are also provided in the Data Appendix.

12 The only other such survey was conducted in 1943.

13 Smaller custodians and institutional investors were sampled, but 99 percent of the data

was from the major reporters.

9

III. Data11

In the past, the approach taken by researchers (and by the U.S. government) to estimating

U.S. portfolio investment in foreign equity securities involved making a guess of the initial stock,

which was then updated using subsequent flow data, perhaps price-adjusting along the way; see

for example French and Poterba (1991), Tesar and Werner (1995), Cooper and Kaplanis (1994). 

Warnock and Mason (2000) show, however, that estimates of country-level holdings

using flow data can be wildly off the mark, likely due to some combination of inadequacies in the

flow data and inappropriate valuation adjustments. Country-level valuation adjustments can be

incorrect if calculated using a market index when U.S. investors hold a portfolio that differs

significantly from the market. The flow data can be incorrect because, for the United States, data

on transactions in foreign equities are collected based on the country of the transactor, not the

country of the security. When the country of the transactor differs from the country of the

security--as is often the case with trades through financial centers such as the United Kingdom

and Hong Kong--the country distribution is distorted in the transactions data.

Our data set is subject to neither of these problems. We use data drawn from the U.S.

Treasury Department’s comprehensive surveys of U.S. holdings of foreign securities, conducted

as of March 31, 1994 and December 31, 1997.12 The surveys collected detailed information at

the individual security level for U.S.-held foreign equities; the country attribution of each

security was determined using both commercial and respondent data. Reporting to the survey

was mandatory, with penalties for noncompliance, and the data received were subjected to

extensive analysis and editing before they were accepted as accurate. The reporters consisted

mainly of large custodians and large institutional investors, both of which were universally

included in the sample.13 Holdings of U.S. private investors were included inasmuch as they

were through U.S. mutual funds or are entrusted to U.S.-resident custodians for safekeeping. 
14 This is equivalent to normalizing U.S. holdings in a country by the country’s market

capitalization and then dividing by a constant (the share of overall U.S. holdings in the

worldwide market capitalization).

10

Further details of the 1997 survey, including findings and methodology, are discussed in

Treasury Department and Federal Reserve Board (2000).

Table 1 presents our data on the share of U.S. holdings of equities by country as of end1997. Column 1 of the table shows the strong preference by U.S. investors for domestic equities

over foreign equities -- almost 90 percent of the U.S. equity portfolio consists of U.S. stocks. For

foreign equities, the United Kingdom was the country of choice for U.S. investors, with U.K.

stocks comprising almost 2 percent of the U.S. equity portfolio, followed by Japan, the

Netherlands, France and Canada. U.S. holdings of foreign equities are quite concentrated, with

the top 15 countries accounting for almost four-fifths of total U.S. holdings of foreign equities.

Table 1 (column 2) also presents what we refer to as benchmark shares--hypothetical

shares of U.S. equity holdings against which we can compare the actual holdings. By

construction, these benchmarks are simply the weights of each country's stock market

capitalization in world stock market capitalization at end-1997. Moreover, these benchmarks are

exactly the shares predicted by the ICAPM model in Section II. That is, these benchmarks are

the shares of U.S. equity holdings by country in a hypothetical world in which global capital

markets were complete and investors in all countries had identical preferences and chose

portfolios optimally based on standard portfolio theory. For example, given the size of U.S.

stock markets at end-1997, the model in Section 2 predicts that domestic equities should have

made up just less than half of U.S. investors' equity portfolios. 

Comparing actual holdings to the benchmark shares gives an indication of the degree to

which U.S. investors underweight different foreign countries. As expected, for all countries

other than the United States, U.S. holdings are less than those predicted by ICAPM. The extent

of the underweighting is shown in column 3, which presents the ratio of actual shares observed at

end-1997 to the benchmark.14 Interestingly, there is a significant amount of variation in values
15 If the size of the foreign market was the only determinant of the country distribution of

U.S. holdings, this measure would not vary across countries. 

11

across countries.15 For example, both the Netherlands and Mexico score roughly 0.44, indicating

that U.S. investors’ holdings of stocks from these countries at end-1997 were 44 percent of what

traditional portfolio theory would have predicted. On the other hand, the degree of

underweighting appears more severe against countries such as Japan and Germany, where U.S.

investors hold 12 and 15 percent, respectively, of the ICAPM levels.

We proceed by constructing a measure of U.S. investors’ home bias against each country,

defined as one minus the ratio of actual-to-benchmark holdings. Hence, a greater value of this

measure corresponds to a higher degree of bias. Figure 2 presents this measure of home bias for

our sample of the 48 largest foreign markets. The bias measure varies from 0.98 for China,

where our holdings are 2 percent of the benchmark, to 0.44 for Ireland, where our holdings are 56

percent of the benchmark. Our main goal in this paper is to explain the distribution of this

measure of U.S. investors’ home bias across countries.

The final column in Table 1, which presents our data on the portion of firms in each

country that are also listed on U.S. exchanges, will be discussed in the next section.

IV. Statistical Analysis

This section explores possible determinants of the distribution of U.S. home bias across

countries presented in Figure 2. The empirical specifications used in the paper are generally of

the following form:

BIASi

 = α + βXi + εi

where BIAS is the degree of U.S. investors’ home bias against country i and X is a vector of

independent variables that includes information costs, trade, transactions costs, capital controls,

and historical risk-adjusted returns. The precise definitions of these variables and the reasons for

including them in our regression equation will be discussed next. 
12

Description of Explanatory Variables

Motivated by recent theoretical developments in the home bias literature and our

discussion in Section II, we begin by exploring the importance of asymmetric information in

accounting for variation in the degree of U.S. investors’ home bias across countries. If

asymmetric information is an important factor in explaining the home bias puzzle, then we would

expect to see some correlation between variations in the degree of home bias across countries and

proxies for informational segregation.

With this in mind, we construct a variable, USLISTED, that measures the share of a

country's stock market that is listed on U.S. exchanges, either directly or as a Level 2 or Level 3

ADR. As discussed earlier, to the extent that listing on a U.S. exchange makes a foreign

company's stock more attractive to U.S. investors by lowering information costs, we would

expect U.S. investors to hold a relatively larger share of equities from countries that have higher

shares of their stock markets listed on U.S. exchanges. Values for the shares of countries’ stock

markets that were listed on U.S. exchanges as of end-1997 are reported in the last column of

Table 1. We note that the share of stocks that trade on U.S. exchanges varies widely by country,

with the Netherlands leading the way at 81 percent, followed by Ireland, Portugal, and Argentina,

which are each over 50 percent.

Figure 3 plots the share of each foreign country's stock market listed on U.S. exchanges

versus the degree of home bias, BIAS. Recall that BIAS is one minus the ratio of actual to

theoretical holdings; when BIAS is equal to zero there is no home bias, and as the measure

increases the bias (or underweighting) is more severe. A striking feature of the pattern in Figure

3 is the strong negative correlation between a country’s propensity to list on U.S. exchanges and

the degree of bias; the correlation is negative 0.76. 

 Another possible determinant of the distribution of bias across countries is international

trade. For example, it may well be that by purchasing goods and services produced by foreign

firms, U.S. investors glean information about these companies. At the very least, investors may

be more inclined to hold the stocks of foreign companies with whose products they are most

familiar. 
13

To control for the familiarity effects associated with trade, we include two measures of

trade links. The first and broadest is TRADE, the amount of trade with the United States as a

share of each country’s GDP. This variable is plotted in Figure 4. Our second measure of trade

links, FDI Sales, is perhaps more relevant from the perspective of information available to U.S.

investors. When a foreign firm sets up operations in the United States, not only are U.S.

investors more familiar with it products, but they may well work for the firm or live in the

proximity of the plant. This represents an even greater familiarity with the firm. To capture this

effect we use the data on sales by foreign direct investment (FDI) affiliates in the United States,

again deflated by the foreign country’s GDP. FDI Sales is available for only 32 of the 48

countries in our sample, and is shown in Figure 5. The difference between FDI Sales and other

measures of trade links is highlighted by the values for the Netherlands. As a percent of GDP,

trade with the United States is rather small for the Netherlands, but sales by Dutch affiliates in

the United States are some 30 percent of Dutch GDP.

The measures discussed above represent indirect barriers to international investment. 

Direct barriers – such as capital controls – can also affect international portfolio decisions. 

While direct barriers have fallen considerably over the past few decades, they can still be

important. For example, the time line in Bekeart and Harvey (1999) indicates that in 1997

foreign ownership restrictions for two of the largest Korean stocks, Korea Electric Power and

Pohang Iron and Steel, were repeatedly binding, relaxed, and binding again. 

Capital controls likely affect the distribution of home bias across countries; looking at

Figure 2, it is probably not a coincidence that some of the countries U.S. investors underweight

most (for example, China) maintain substantial barriers to foreign investment. One difficulty of

including capital controls in our regression equation is that no widely accepted cross-country

measure of foreign ownership restrictions suitable for empirical work currently exists. There are

many measures of capital controls in the literature, ranging from dummy variable based on

restrictions reported in the IMF’s Annual Report on Exchange Arrangements and Exchange

Restrictions to coefficient estimates from Feldstein-Horioka (1980) regressions to coefficients

from excess returns regressions. 
16 See Edison and Warnock (2000) for a more complete discussion of this measure of

foreign ownership restrictions and a comparison with other methods of quantifying capital

controls.

17 The IFC does not compute Investable indexes for industrial countries. Absent other

information, we assume that for these countries the Investable and Global indexes are identical

and, therefore, that foreign ownership restrictions are zero in industrial countries.

14

In this paper we choose to piggyback on the work of the International Finance

Corporation (IFC). Our measure of foreign ownership restrictions, RESTRICT, constructed

using data from the IFC’s emerging market indexes, is one minus the ratio of the market

capitalizations of the IFC’s Investable and Global indices. The Investable index is comprised of

all stocks in the Global index that are deemed by the IFC to be available to foreign investors. 

Hence, if the market capitalizations of the two indexes are equal, there are no restrictions and our

measure is zero.16 As shown in Figure 6, this measure varies greatly across developing countries,

with about 10 percent of China’s market available to foreigners in 1997, compared to 98 percent

of South Africa’s.17 In general, it is apparent from the figure that countries with more severe

foreign ownership restrictions are more underweight in U.S. portfolios.

Finally, we consider the role of historical risk-adjusted returns. If portfolio decisions are 

based partly on past returns, then U.S. investors might tend to underweight countries whose stock

markets have performed poorly. To capture this type of “returns-chasing” behavior, we construct

a reward-to-risk ratio, shown in Figure 7, which is the mean monthly return over its standard

deviation. As the figure shows, risk-adjusted returns were quite high for a number of European

countries, but were negative for Japan and the East Asian crisis countries. The figure also

appears to suggest a weak negative relationship between risk-adjusted returns and bias. 

Regression Results

Our main results are presented in Table 2a. The top half of the table presents results for

the 1997 survey; the bottom half is for the 1994 survey. The most striking feature of our results

is that in every specification of our regression equation, there exists a strong negative relationship

between BIAS and USLISTED. This result coincides with our prior, and we interpret it to mean
18 This contrasts with the results of Honohan and Lane (2000), who find that trade is the

main determinant of the composition of Ireland’s foreign securities portfolio. 

19 Obstfeld and Rogoff (2000) construct a two-country model in which trade costs in

goods markets give rise to home bias in both portfolio and consumption decisions. In their

model, equilibrium portfolio shares are proportional to consumption shares, and home bias arises

because households face “iceberg” costs of trade on goods shipped abroad. Extending this

intuition into a multi-country framework, we suspect that any explanation of home bias based on

trading costs in goods markets would likely imply a positive correlation between U.S. purchases

of foreign equities and goods across countries, an implication seemingly at odds with our finding

that trade links are unrelated to home bias.

15

that the reduction in information costs associated with listing on a U.S. exchange is an important

determinant of the distribution of home bias across countries in our sample. The negative

coefficient on USLISTED implies that countries whose firms do not alleviate information

asymmetries by listing on a U.S. exchange are more severely underweighted in U.S. equity

portfolios. We argued above that the information asymmetries may reflect differences in

accounting standards, disclosure requirements, and regulatory environments across countries. 

Focusing on the 1997 results, we see in column 2 that RESTRICT, our measure of foreign

ownership restrictions, is negatively related to BIAS and is statistically significant. As expected,

U.S. investors are more underweight against countries with more extensive foreign ownership

restrictions. Both measures of trade links, TRADE and FDI Sales, have the expected sign

(columns 3 and 4), but neither is statistically significant. While it is true that U.S. investors are

less underweight against the two countries most closely linked to the United States, Mexico and

Canada, on average we find no significant relationship between trade and home bias.18 The use

of alternative measures of trade links--for example, U.S. imports from each country as a share of

that country’s GDP--does not alter this result.19 Our measure of risk-adjusted returns,

REWRISK, turns up positively related to BIAS, but with a t-statistic near zero.

Returning to the USLISTED variable, roughly speaking, the estimated value of the

coefficient on this variable in column 3 implies that if, for example, German firms were listed on

U.S. exchanges to the same extent as Dutch firms, we would expect the bias against Germany to

be significantly lower, falling from 0.85 to 0.57. 
20 It is perhaps interesting to note that Warnock and Mason (2000) find that if bias is

computed using holdings estimated from transactions data and valuation adjustments, trade

becomes significant.

21 The one exception is Poland, a developing country that had no foreign ownership

restrictions.

16

Our results appear robust across the two sample dates. For 1994, the story is very similar

to 1997, although REWRISK and FDI Sales, while still not significant, gain some explanatory

power. USLISTED is still positive and explains about 50 percent of the variation in home bias. 

Trade remains insignificant.20

In Tables 2b-2d we present a series of robustness checks in which the sample is limited to

countries with particular characteristics. In Table 2b we restrict the sample to those countries

that have at least one listing on a U.S. exchange. For the 1997 regressions, dropping the ten

countries without U.S. listings does not substantially affect the results: A little over 50 percent of

the variation in home bias is explained by USLISTED, RESTRICT has some explanatory power,

and the measures of trade links and REWRISK have no explanatory power. In 1994, only 27

countries had listings on U.S. exchanges. Possibly because of this sharply reduced sample size,

the results for the 1994 regressions reported in Table 2b are noticeably different than those

reported in Table 2a. Specifically, RESTRICT loses its explanatory power--possibly because

most of the countries with foreign ownership restrictions did not have U.S. listings in 1994 and

thus were not included in the regression--as do FDI Sales and REWRISK. 

In Tables 2c, we limit the sample to those countries with foreign ownership restrictions,

effectively all of the developing countries in our sample.21 In Table 2c we see that among

countries with foreign ownership restrictions, trade links seem to matter more, at least for the

1997 regressions. Somewhat surprisingly, in 1997, among this group of developing countries,

U.S. investors seemed to favor countries with lower reward-to-risk ratios. The results for 1994

regressions for these countries are qualitatively similar to those for the full sample (Table 2a):

RESTRICT regains its explanatory power, trade becomes insignificant, and FDI Sales and

REWRISK are once again significant and negative. Since the sample size is quite small in these

regressions, the results should be interpreted cautiously. 
17

Table 2d presents results with the sample limited to those countries without foreign

ownership restrictions. The results for this group of developed countries are broadly consistent

with those from Tables 2a and 2c: USLISTED is highly significant, FDI Sales is marginally

significant, and TRADE and REWRISK are insignificant. Some differences are noticeable. For

example, the point estimates for USLISTED are consistently smaller than for the developing

countries (Table 2c), although the differences are not statistically significant. Once again, we

caution that the sample sizes in these regressions are small.

In Table 3 we examine the extent to which we can explain changes in home bias from

1994 to 1997. Given the results for the levels regressions, we focus on USLISTED and do not

report results for the other explanatory variables. Controlling for the initial (1994) levels of bias

and U.S. listings, we generally find that the greater the increase in listings between 1994 and

1997, the greater is the reduction in bias. More specifically, the results in Table 3 show that the

decrease in bias over the 1994 to 1997 period is greatest for countries that had a high degree of

bias and low amount of U.S. listings in 1994 and subsequently increased U.S. listings. 

Not all variables are significant in every sample in Table 3. For example, an increase in

U.S. listings is associated with a decrease in bias in every sample but the one limited to industrial

countries (column 3). The level of U.S. listing in 1994 matters for this sample, but not for the

one consisting of only countries with listings in the United States. The one variable that is

significant across samples is the 1994 level of bias, suggesting that there was some catching up in

the 1994-1997 period: The more underweight were U.S. investors in a country in 1994, the

greater was the move towards the ICAPM benchmark from 1994 to 1997.

Caveats

We note that the main independent variable in our regression equations, the portion of the

foreign market that is cross-listed on U.S. exchanges, might be endogenous. Due to the high

costs involved with listing in the United States, only firms that anticipate that the listing will be

met by strong investor demand will choose to list. For example, the listing fee alone can be $2

million on the NYSE, on top of which must be added the considerable costs of reconciling

financial accounts with U.S. GAAP, costs that can amount to greater than $1 million for large
22 Other studies on why firms cross-list are Karolyi (1998) and Saudagaran (1988). 

18

firms from industrial countries. Hence, it could be argued that the causality goes from

prospective U.S. demand to U.S. listings. However, we would argue that this prospective

demand is conditional on listing on a U.S. exchange. Supporting our view is the evidence that

foreign stocks experience abnormal returns just after the announcement of a U.S. listing

(Miller,1999) and during the process of regulatory and exchange approval (Foerster and Karolyi,

1999); if U.S. demand was already present, abnormal returns should not be evident.

It may also be that third factors determine both bias and listing. We control for some of

these in our regressions. For example, firms that have high ratios of U.S. to total sales may be

more likely to list here, and U.S. investors may naturally have more information on these firms

and hence may be more likely to hold their stocks. Evidence supporting the first link, from high

foreign sales to cross-listing, is provided by Pagano, Roell, and Zechner (1999) and Sarkissian

and Schill (1999).22 We controlled for this familiarity effect by including measures of trade links

and sales by foreign affiliates in the United States. 

V. Extensions

In this section we extend our analysis to directly address the roles of transaction costs,

accounting standards, and regulatory environments in the country distribution of U.S. investors’

home bias. Due to data and degrees of freedom limitations, these variables are not included in

the main regressions reported above.

Transaction Costs

The role of transaction costs in home bias has been downplayed in the literature. For

example, French and Poterba (1991) and Cooper and Kaplanis (1986) conclude that costs would

have to be implausibly high to explain the observed home bias. Moreover, Tesar and Werner

(1995) provide evidence that investors turn over their foreign portfolios more frequently than

their domestic portfolios, which is inconsistent with transaction costs being large enough to
23 High turnover rates on foreign equity portfolios are not evident using updated holdings

estimates; see footnote 6.

24 Market impact costs, or liquidity costs, are intended to measure the deviation of the

transaction price from the price that would have prevailed had the trade not occurred; see

Willoughby (1998) for a discussion.

19

significantly impede international investment.23 None of these studies, however, use data on

transaction costs to reach their conclusions, perhaps because such data did not exist across a wide

range of countries until 1996.

To control for the effects of transaction costs we use the Elkins-McSherry Co. measure of

trading costs across 41 foreign markets. This measure, shown in Figure 8 and analyzed in

Willoughby (1997) and Domowitz, Glen, and Madhaven (2000), is comprised of three

components: commissions, fees, and market impact costs.24 As the figure shows, it is difficult to

discern a relationship between trading costs and our measure of bias across the 41 countries for

which the measure is available. Among all but the highest cost countries, however, it does

appear that higher cost countries are more underweight in U.S. portfolios.

Table 4 analyzes the effects of trading costs on home bias more formally. In bivariate

regressions, trading costs are either insignificantly different from zero (with t-stats less than 0.5)

or, in the sample limited to industrial countries (column 3), negative and significant. That is, the

simple bivariate relationship suggests that higher cost developed countries are less underweight

in U.S. portfolios, but that in the full sample and other cuts of the data, no relationship is

apparent.

Since trading costs are low on the NYSE--the U.S. exchange on which over 80 percent

(by market capitalization) of non-U.S. stocks are listed--firms from high cost countries can

effectively lower trading costs in their stock and, hence, broaden their shareholder base by listing

in the United States. To capture the effect of the reduction in trading costs associated with a U.S.

listing, Table 4 also reports regressions that include an interaction term combining (one minus)

costs and listings. Costs are still not positive and significant in these regressions, but the positive

coefficient on the interaction term (in all but the developing country regression, which suffers

from collinearity) is evidence that high cost countries with a high portion of U.S. listings are less
25 We thank Trevor Harris for bringing this point to our attention.

20

underweight in U.S. portfolios. That is, countries whose firms tend to list on U.S. exchanges are

less underweight in U.S. portfolios and high cost countries get an extra boost in U.S. portfolios

from the listing. Overall, the results in Table 4 indicate that one way that listing on a U.S.

exchange, particularly on the NYSE, reduces home bias is through reduced transaction costs.

Accounting Standards

While listing on U.S. exchanges tends to reduce home bias to some extent through lower

transaction costs, this cannot explain why U.S. investors’ bias is severe against countries with

low trading costs. The story we tell in this paper is one in which a U.S. listing helps alleviate

information costs borne by U.S. investors due to differences in accounting standards, disclosure

requirements, and regulatory environments across countries. Direct testing of this hypothesis is

difficult for a number of reasons. First, any numeric scoring of accounting standards across

countries is likely inadequate for our purposes. For example, these measures are calculated based

on the inclusion or omission of certain items, but these items vary in importance across sectors.25

Second, as Fuerst (1998) puts it, it is not just the information itself -- Harris et al (1998) shows us

how to compare information generated from different accounting standards -- but its credibility. 

We use the measure of the quality of accounting standards presented by La Porta, Lopezde-Silanes, Shleifer, and Vishny (1998), available for 37 countries in our sample. These

measures are imperfect for our purpose because they are based on 1990 standards and do not

include differences in disclosure requirements, but are nonetheless useful. Since high accounting

standards do not likely improve the quality of information available to investors if the regulatory

environment is lax, we also include a broad measure of the rule of law, which we take from the

same source. Preferable would be a measure of the extent to which securities laws are enforced.

Since the accounting standards measure, ACCT, is only available for 1990 and standards

have changed in many countries in the 1990s, we only analyze the 1994 level of bias in this

section. The first two columns of Table 5 indicate that while there is only weak evidence that

higher accounting standards are associated with less bias, the evidence is stronger that countries
21

with higher scores on rule of law (ROL) are less underweight in U.S. portfolios. When we

include USLISTED (column 3), the t-statistics on ACCT and ROL fall toward zero. In the fourth

column we include interaction terms. The story that emerges is that countries that are less

underweight in U.S. portfolios (i) tend to list on U.S. exchanges, (ii) have both high accounting

standards and high scores on rule of law, (iii) have low accounting standards but list on U.S

exchanges. That the interaction of high standards and high rule of law is associated with lower

bias, but that by themselves accounting standards and rule of law have positive coefficients,

underscores the importance of the credibility of the information, not just the quantity.

VI. Conclusion

The results presented in this paper suggest that information costs are an important factor

behind the home bias phenomenon. To list on a U.S. stock exchange, a foreign firm must

reconcile its financial statements with U.S. GAAP, comply with stringent SEC disclosure

requirements, and subject itself to the strict U.S. regulatory environment. Doing so alleviates a

significant information cost to the U.S. investor. We find, based on a comprehensive data set of

U.S. holdings of foreign equities, that countries with a greater share of firms that list on U.S.

exchanges, either directly or as exchange-traded ADRs, tend to be less severely underweighted in

U.S. equity portfolios. We find that this effect is much stronger than the effects of trade links or

direct barriers such as foreign ownership restrictions. We also find some evidence that firms

from countries with low accounting standards or high trading costs can improve their prospects

with U.S. investors by listing on a U.S. exchange.

We restricted our focus in this paper to the determinants of U.S. investors holdings of

foreign equities. One avenue for future research might be to consider a broader class of assets,

including, for example, U.S. investors holdings of foreign bonds, both sovereign and corporate. 

Along these same lines, an even more wide-ranging study of U.S. investors' exposure to foreign

economies might include cross-border bank lending as well as U.S. investors’ holdings of

equities of U.S. multinationals. Moreover, while our focus was on U.S. portfolios, it would also

be interesting to explore other countries' foreign portfolios.
22

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25

Data Appendix

We include the 48 largest countries (excluding the United States) by 1997 market capitalization. 

The smallest country in sample is Pakistan (market capitalization of $11 billion); the largest

country excluded is Oman ($7 billion). Data exist for most variables for each of these countries,

unless noted.

U.S. holdings of foreign equities are available at www.treas.gov/fpis/ for March 1994 and

December 1997.

Data on worldwide market capitalizations of non-U.S. stocks listed on U.S. stock markets

are compiled from various sources. For NYSE-listed firms, year-end data were provided by the

NYSE, compiled from data from FactSet and Bloomberg. For the 1994Q1 regressions, we use

end-1993 NYSE values. Data for non-U.S. firms listed on Nasdaq and Amex are from

CompuStat. For all ADRs in the 1997 sample, cross-checks were made using Bank of New York

(BONY) ADR Index data for 1998.

Country-level market capitalization data, which are of domestic firms listed on the domestic

market, are from IFC Emerging Markets Factbook 1998 and the International Federation of Stock

Exchanges (www.fibv.com). The coverage of IFC is better; FIBV data were used as a crosscheck. Differences between the two sources were for the most part small or nonexistant, except

for in the data for Ireland, Australia, and New Zealand, where the IFC number was based on an

incorrect currency conversion. 

Trade data are from IMF Direction of Trade Statistics Yearbook, 1999.

FDI Sales data, available for 32 countries, are from the BEA Survey of Current Business, Tables

23.2 (August 1999) and 21.1 (July 1996) Selected Data of Nonbank U.S. Affiliates by Country of

Ultimate Beneficial Owner.

The measure of foreign ownership restrictions is one minus the ratio of the market

capitalizations of the IFC Investable and Global Indexes (IFC, 1998). The measure is assumed to

be zero for industrial countries that do not have IFCI indexes.

Transaction costs for 41 countries are from Elkin-McSherry Co. (www.elkins-mcsherry.com).

Reward/risk is the mean return over the standard deviation of returns, where returns are changes

in the country’s MSCI Price Index calculated over the periods of 15 quarters preceding 1994Q1

and 1997Q4. Data were obtained from www.mscidata.com.

Accounting standards are for 1990 as compiled by the Center for International Financial

Analysis and Research. Rule of law is for 1982 to 1995 as compiled by the International

Country Risk rating agency. Both are taken from La Porta et al (1998). 
Table 1

U.S. Portfolio Holdings and International Stock Market Measures (as of end-1997 )

Country Actual U.S.

Holdings

(% of total U.S.

holdings)

Benchmark

(% of world market

capitalization)

Actual over

Benchmark

U.S. Listed

(% of market

capitalization)

Major industrial

countries

United States 89.9 48.3 1.86 100.0

United Kingdom 1.82 8.5 .21 38.7

Japan 1.14 9.4 .12 27.2

France 0.71 2.9 .25 29.3

Canada 0.59 2.4 .25 44.4

Germany 0.54 3.5 .15 17.6

Italy 0.35 1.5 .24 42.5

Other advanced

countries

Netherlands 0.89 2.0 .45 80.7

Switzerland 0.52 2.5 .21 1.3

Sweden 0.32 1.2 .28 34.0

Spain 0.21 1.2 .17 39.2

Ireland 0.12 0.2 .56 64.2

Finland 0.12 0.3 .40 32.4

Norway 0.08 0.3 .28 23.1

Denmark 0.07 0.4 .19 21.5

Portugal 0.06 0.2 .35 61.9

Israel 0.06 0.2 .31 41.5
Table 1 (continued)

U.S. Portfolio Holdings and International Stock Market Measures as of end-1997 

Country Actual U.S.

Holdings

(% of total U.S.

holdings)

Benchmark

(% of world market

capitalization)

Actual over

Benchmark

U.S. Listed

(% of market

capitalization)

Belgium 0.05 0.6 .09 7.2

Luxembourg 0.04 0.1 .31 26.0

Austria 0.03 0.2 .20 0.0

Greece 0.01 0.2 .09 0.4

Australia 0.26 1.3 .21 42.7

Hong Kong 0.23 1.8 .13 10.0

Singapore 0.09 0.5 .19 4.5

Taiwan 0.04 1.2 .03 5.5

Korea 0.04 0.2 .21 24.5

New Zealand 0.04 0.1 .35 42.7

Developing

Countries

Latin America

Mexico 0.29 0.7 .44 33.6

Brazil 0.26 1.1 .24 24.1

Argentina 0.11 0.3 .43 56.5

Chile 0.04 0.3 .12 38.9

Peru 0.02 0.1 .26 38.6

Venezuela 0.02 0.1 .27 13.3
Table 1 (continued)

U.S. Portfolio Holdings and International Stock Market Measures as of end-1997 

Country Actual U.S.

Holdings

(% of total U.S.

holdings)

Benchmark

(% of world market

capitalization)

Actual over

Benchmark

U.S. Listed

(% of market

capitalization)

Colombia 0.01 0.1 .07 10.2

Asia

India 0.05 0.6 .09 0.0

Malaysia 0.04 0.4 .10 0.0

Indonesia 0.02 0.1 .17 20.0

Phillippines 0.02 0.1 .18 6.5

China 0.02 0.9 .02 1.3

Thailand 0.02 0.1 .18 0.0

Pakistan 0.01 0.1 .21 0.0

Central and

eastern Europe

Russia 0.07 0.5 .13 0.7

Hungary 0.03 0.1 .46 33.3

Czech Republic 0.01 0.1 .12 0.0

Poland 0.01 0.1 .26 0.0
Table 1 (continued)

U.S. Portfolio Holdings and International Stock Market Measures as of end-1997 

Country Actual U.S.

Holdings

(% of total U.S.

holdings)

Benchmark

(% of world market

capitalization)

Actual over

Benchmark

U.S. Listed

(% of market

capitalization)

Other

Developing

South Africa 0.08 1.0 .08 12.2

Turkey 0.05 0.3 .19 0.0

Egypt 0.01 0.1 .07 0.0

Morocco 0.01 0.1 .04 0.0

Sources: Treasury Department and Federal Reserve Board (2000); International Finance

Corporation (1998); NYSE; CompuStat; authors’ calculations.

Definitions: Actual U.S. Holdings refers to country’s share of U.S. equity holdings; ICAPM

Benchmark refers to portfolio shares predicted by ICAPM, i.e. shares determined by country

market capitalization; U.S. Listed refers to share of country’s stock market that is listed on U.S.

exchanges.
Table 2a

Results: Full Sample

(1) (2) (3) (4) (5)

1997

USLISTED -0.43***

(0.06)

-0.39***

(0.06)

-0.39***

(0.06)

-0.41***

(0.08)

-0.37***

(0.06)

RESTRICT 0.08**

(0.04)

0.08**

(0.04)

0.08*

(0.05)

0.09*

(0.05)

TRADE -0.08

(0.12)

-0.10

(0.13)

FDI SALES -0.12

(0.13)

REWRISK 0.01

(0.08)

N 48 48 48 32 43

Adjusted R2 0.52 0.53 0.53 0.53 0.49

1994

USLISTED -0.56***

(0.07)

-0.47***

(0.07)

-0.48***

(0.08)

-0.42***

(0.07)

-0.46***

(0.07)

RESTRICT 0.08**

(0.04)

0.08**

(0.04)

0.06

(0.05)

0.10**

(0.05)

TRADE -0.09

(0.13)

0.02

(0.10)

FDI SALES -0.21

(0.16)

REWRISK -0.18

(0.13)

N 44 39 39 27 31

Adjusted R2 0.51 0.54 0.53 0.50 0.58

Notes. Dependent variable is BIAS. Constants are included but not reported. USLISTED is the share of the

foreign market that is cross-listed on U.S. exchanges. RESTRICT is a measure of foreign ownership restrictions;

see text for description. TRADE and FDI SALES are expressed as a share of the foreign country’s GNP. 

REWRISK is the mean over standard deviation of monthly returns calculated over a 15-quarter period. White

(1980) standard errors are in parentheses. ***,

**, and *

 indicate significance at the 1%, 5%, and 10% levels,

respectively.
Table 2b

Results: Sample Limited to Countries with Listings on U.S. Exchanges

(1) (2) (3) (4) (5)

1997

USLISTED -0.48***

(0.06)

-0.45***

(0.07)

-0.45***

(0.06)

-0.43***

(0.09)

-0.43***

(0.09)

RESTRICT 0.08*

(0.04)

0.09**

(0.04)

0.07

(0.05)

0.07

(0.05)

TRADE -0.15

(0.15)

-0.19

(0.16)

FDI SALES -0.14

(0.14)

REWRISK -0.05

(0.08)

N 38 38 38 30 36

Adjusted R2 0.53 0.53 0.54 0.53 0.57

1994

USLISTED -0.49***

(0.08)

-0.45***

(0.07)

-0.47***

(0.10)

-0.41***

(0.10)

-0.45***

(0.10)

RESTRICT 0.05

(0.07)

0.05

(0.07)

0.01

(0.08)

0.10

(0.11)

TRADE -0.14

(0.15)

-0.01

(0.11)

FDI SALES -0.20

(0.20)

REWRISK -0.15

(0.17)

N 27 25 25 21 23

Adjusted R2 0.45 0.45 0.44 0.37 0.42

Notes. Dependent variable is BIAS. Constants are included but not reported. USLISTED is the share of the foreign

market that is cross-listed on U.S. exchanges. RESTRICT is a measure of foreign ownership restrictions; see text

for description. TRADE and FDI SALES are expressed as a share of the foreign country’s GNP. REWRISK is the

mean over standard deviation of monthly returns calculated over a 15-quarter period. White (1980) standard errors

are in parentheses. ***,

**, and *

 indicate significance at the 1%, 5%, and 10% levels, respectively.
Table 2c

Results: Sample Limited to Countries with Foreign Ownership Restrictions

(1) (2) (3) (4) (5)

1997

USLISTED -0.51***

(0.08)

-0.47***

(0.08)

-0.48***

(0.08)

-0.71***

(0.18)

-0.50***

(0.09)

RESTRICT 0.05

(0.05)

0.05 

(0.06)

0.05

(0.05)

0.07

(0.06)

TRADE -0.24*

(0.14)

-0.28

(0.15)

FDI SALES -0.30

(0.22)

REWRISK 0.15

(0.10)

N 25 25 25 11 20

Adjusted R2 0.56 0.56 0.58 0.59 0.60

1994

USLISTED -0.70***

(0.15)

-0.60***

(0.13)

-0.61***

(0.13)

-1.67***

(0.28)

-0.43***

(0.12)

RESTRICT 0.17***

(0.07)

0.17***

(0.06)

0.18***

(0.06)

0.20**

(0.08)

TRADE -0.23

(0.27)

-0.03

(0.25)

FDI SALES -0.27***

(0.03)

REWRISK -0.26*

(0.14)

N 20 20 20 9 13

Adjusted R2 0.38 0.51 0.51 0.90 0.62

Notes. Dependent variable is BIAS. Constants are included but not reported. USLISTED is the share of the foreign

market that is cross-listed on U.S. exchanges. RESTRICT is a measure of foreign ownership restrictions; see text

for description. TRADE and FDI SALES are expressed as a share of the foreign country’s GNP. REWRISK is the

mean over standard deviation of monthly returns calculated over a 15-quarter period. White (1980) standard errors

are in parentheses. ***,

**, and *

 indicate significance at the 1%, 5%, and 10% levels, respectively.
Table 2d

Results: Sample Limited to Countries without Foreign Ownership Restrictions

(1) (2) (3) (4) (5)

1997

USLISTED -0.34***

(0.09)

-0.34***

(0.09)

-0.37***

(0.09)

-0.32***

(0.08)

TRADE 0.03

(0.09)

0.02

(0.10)

FDI SALES -0.17

(0.12)

REWRISK -0.06

(0.11)

N 23 23 21 23

Adjusted R2 0.41 0.38 0.46 0.35

1994

USLISTED -0.48***

(0.09)

-0.48***

(0.09)

-0.45***

(0.08)

-0.47***

(0.10)

TRADE -0.01

(0.07)

0.00

(0.08)

FDI SALES -0.21

(0.14)

REWRISK -0.00

(0.18)

N 19 19 18 18

Adjusted R2 0.58 0.56 0.55 0.49

Notes. Dependent variable is BIAS. Constants are included but not reported. USLISTED is the share of the foreign

market that is cross-listed on U.S. exchanges. RESTRICT is a measure of foreign ownership restrictions; see text

for description. TRADE and FDI SALES are expressed as a share of the foreign country’s GNP. REWRISK is the

mean over standard deviation of monthly returns calculated over a 15-quarter period. White (1980) standard errors

are in parentheses. ***,

**, and *

 indicate significance at the 1%, 5%, and 10% levels, respectively.
Table 3

Results: Change in Home Bias

(1)

Full Sample

(2)

Countries

with 

Foreign

Ownership

Restrictions

(3)

Countries

without

Foreign

Ownership

Restrictions

(4)

Countries

with U.S.

Listings

1994 - 1997

BIAS 1994 -0.22***

(0.09)

-0.24**

(0.11)

-0.26**

(0.08)

-0.21**

(0.08)

USLISTED 1994 0.11*

(0.07)

0.01

(0.12)

0.17**

(0.09)

0.06

(0.06)

∆USLISTED -0.18**

(0.07)

-0.27***

(0.07)

-0.02

(0.09)

-0.26***

(0.07)

N 44 24 20 35

Adjusted R2 0.41 0.19 0.61 0.50

Notes. Dependent variable is the change in BIAS from 1994 to 1997. The change in USLISTED

is also from 1994 to 1997. See notes to Table 2a for more complete descriptions. Constants are

included but not reported. White (1980) standard errors are in parentheses. ***,

**, and *

 indicate

significance at the 1%, 5%, and 10% levels, respectively.
Table 4

Results: Transaction Costs

(1)

Full Sample

(2)

Countries with Foreign

Ownership Restrictions

(3)

Countries without Foreign

Ownership Restrictions

(4)

Countries with U.S. Listings

3

1)

0.13

(0.11)

-0.03

(0.15)

-0.14

(0.25)

-0.48*

(0.25)

-0.16

(0.17)

-0.06

(0.11)

0.15

(0.13)

-1.01***

(0.25)

-0.30

(0.81)

-0.74***

(0.22)

-1.11***

(0.27)

 1.69**

(0.70)

-0.66

(2.48)

1.07

(0.70)

1.82**

(0.76)

1 41 19 19 22 22 35 35

.0 0.54 0.0 0.46 0.16 0.58 0.0 0.53

997. See notes to Table 2a. COSTS are relative transaction costs, calculated by normalizing the Elkins

 the highest cost country (Korea). Constants are included but not reported. White (1980) standard errors are in

* indicate significance at the 1%, 5%, and 10% levels, respectively.
Table 5

Results: Accounting Standards and Rule of Law

(1) (2) (3) (4)

1994

ACCT -0.16

(0.15)

0.07

(0.13)

-0.38

(0.33)

ROL -0.02***

(0.01)

-0.01

(0.01)

0.04*

(0.03)

USLISTED -0.52***

(0.09)

-1.56***

(0.34)

ACCT * ROL -0.08*

(0.05)

ACCT * USLISTED 2.38***

(0.91)

ROL * USLISTED -0.55

(0.46)

N 37 39 37 37

Adjusted R2 0.0 0.13 0.51 0.52

Notes. ACCT is 1990 accounting standards as compiled by the Center for International Financial

Analysis and Research. ROL is 1982 to 1995 rule of law as compiled by the International

Country Risk rating agency. Both ACCT and ROL are taken from La Porta et al (1998). 

Dependent variable is the level of BIAS in 1994. Constants are included but not reported. White

(1980) standard errors are in parentheses. ***,

**, and *

 indicate significance at the 1%, 5%, and

10% levels, respectively.
Figure 1: Share of Foreign Equities in the U.S. Stock Portfolio

0%

2%

4%

6%

8%

10%

12%

14%

1952195719621967197219771982198719921997

Notes: The two data points marked with asterisks, March 1994 and December 1997, are the only

data points for which there are actual data on U.S. holdings of foreign securities. U.S. stock

portfolio is U.S. market capitalization plus U.S. holdings of foreign stocks less foreign holdings

of U.S. stocks.

Source: Flow of Funds Accounts of the United States

(www.federalreserve.gov/releases/z1/current/data.htm)
0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Figure 2: Country Bias in U.S. Equity Holdings

Note: Country Bias = 1 - Actual U.S. Holdings ÷ ICAPM Benchmark. See Table 1.
0.4 

0.5 

0.6 

0.7 

0.8 

0.9 

1 

Bias

0.0 0.2 0.4 0.6 0.8 1.0 

PL

ATPK

MY

MA

CZ

TH

EG

TR

INGR

RU

CN

CH

SG

TW

PH

BE

HK

COZA

VE

DE

ID

DK

NO

BR

KR

LU

JP

FR

FI

HU

MX

SE

PE

GB

CL

ES

IL

IT

AU

NZ

CA

AR

PT

IE

NL

Share of Foreign Market Listed on U.S. Exchanges

Figure 3: Share of Foreign Market Listed on U.S. Exchanges, 1997
0.4 

0.5 

0.6 

0.7 

0.8 

0.9 

1 

Bias

0 0.1 0.2 0.3 0.4 0.5 0.6 

GR

PL

ES

PT

RU

AT

DK

MA

CZ

FRIT

AR

TR

DE

IN

BR

FI

HU

NO

JP

PK

ZA

AU

SE

LU

CHGB

PE

NZ

EG

ID

NL

CN

BE

CL

KR

CO

TH

IL

HK

IE

TW

PH

VE

MY

SG

MX

CA

Figure 4: Trade, 1997

Trade

Note: TRADE for country i is country i’s total trade with the United States as a proportion of

country i’s GNP.
0.4 

0.5 

0.6 

0.7 

0.8 

0.9 

1 

Bias

0 0.1 0.2 0.3 0.4 

PH

CN

ES

BR

ID

AT

IT

MY

MX

DK

IL

NZ

TW

HK

SG

KR AU

NO

FI

ZA

DE

BE

FR

JP

SE

IE

GB

VE

CA

LU

NL

CH

Figure 5: Sales by FDI Affiliates in the U.S., 1997

FDI Sales

Note: FDI SALES for country i is sales by country i’s affiliates in the United States as a

proportion of country i’s GNP.
0.4 

0.5 

0.6 

0.7 

0.8 

0.9 

1 

Bias

0 0.2 0.4 0.6 0.8 1 

CN

IN

CZ

TW

PHTH

KR

RU

COEG

MA

BR

PK

PT

VE

MY

PE

MX

ID

CL

IL

ZA

HU

AR

GR

HKJP

IE

ITFR

FI

ES

NL

LU

GB

DK

DE

CH

PL

CA

BE

SE

SG

AU

TRAT

NO

NZ

Figure 6: Foreign Ownership Restrictions, 1997

Foreign Ownership Restrictions
0.4 

0.5 

0.6 

0.7 

0.8 

0.9 

1 

Bias

-0.4 -0.2 0 0.2 0.4 0.6 

TH

KR

TR

PH

MY

ID

JP

PK

CN

IN

PL

SG

AT

CO

MX

IL

HK

TW

CL

AR

ZA

IT

VE

AU

BR

PE

GR

FR

FI

NO

CA

DE

PT

SE

ES

DK

BE

GBCH

NL

IE

Figure 7: Reward-to-Risk Ratio, 1997

Reward-to-Risk
0.4 

0.5 

0.6 

0.7 

0.8 

0.9 

1 

Bias

0 0.2 0.4 0.6 0.8 1 

FRIT

SE

DE

CH

NL

ES

FI

BE

NO

JP

DK

AT

NZ

AUGB

CA

HK

MX

BR

PT

GRIN

SG

TW

AR

TR TH

MY

CO

CL

LU

ID

PE

ZA

PH

CZ

IE

VE

HU

KR

Figure 8: Relative Transaction Costs, 1997

Relative Transaction Costs