The effects of SFAS 131 geographic segment disclosures by US multinational companies on the valuation of foreign earnings

Abstract

Foreign operations are becoming increasingly important for US companies. We investigate whether the market's valuation of foreign earnings is a function of the firm's geographic segment disclosures. Specifically, we examine the effects of an increase in the number of geographic segments disclosed and the inclusion of earnings measures in geographic segment disclosures following the adoption of SFAS 131. We find strong evidence that our proxies for increased disclosure are positively associated with the valuation of foreign earnings. Our results are robust to a number of sensitivity analyses. Taken together, our results suggest that the pricing of foreign earnings is associated with important aspects of the firm's information environment.

INTRODUCTION

Prior research provides evidence that expansion into international markets increases the complexity of information processing for investors (Callen, Hope, & Segal, 2005; Thomas, 1999), analysts (Duru & Reeb, 2002; Herrmann, Hope, & Thomas, 2008; Tihanyi & Thomas, 2005), and managers (Birkinshaw, Toulan, & Arnold, 2001; Egelhoff, 1991; Kim & Mauborgne, 1995; Schulz, 2001).¹ Possible reasons to explain the increased complexity of international operations include differences in cultures, growth opportunities, competition, governmental regulations, labor relations, tax laws, business practices, and market conditions across countries (Dunning, 1993). In addition, Dunning (1998) argues that, with increased geographical dispersion of firm assets, the structure and content of the location portfolio of firms becomes more critical to their global competitive positions. With the dramatic increase in multinational operations in recent years,² it is becoming increasingly important to gather information related to the firm's foreign operations. This is true for both US and foreign multinational enterprises operating internationally. Thus it becomes even more critical for management and investors to understand better the impact of foreign operations on the overall performance of the firm. Acquiring high-quality financial information about foreign operations of US and foreign-based multinational enterprises is complicated, especially given differences in accounting practices worldwide, as will be discussed below. For US-based multinational enterprises, an important source of information is geographic segment disclosures provided in the firm's annual report filed with the Securities and Exchange Commission (SEC). However, the lack of detailed guidance provided by accounting standard-setters on the disclosure of geographic segment information has resulted in a wide variety of disclosure quality across firms.

This study investigates the potential impact of a change in geographic segment disclosure requirements on US-based multinational enterprises from an investor's perspective. Specifically, we relate investors' pricing of foreign earnings of US multinational enterprises to certain aspects of Statement of Financial Accounting Standards No. 131 (SFAS 131). SFAS 131 introduces two important changes to the disclosure of geographic information. First, in an attempt to provide more disaggregated disclosure, it encourages firms to disclose country-level geographic information for “material” countries. SFAS 131 allows immaterial countries to be aggregated into a single “Other Foreign” segment. Prior to SFAS 131, most firms disaggregated their foreign operations into a couple of broad regions (e.g., Western Europe) or continents (e.g., Asia) (Boatsman, Behn, & Patz, 1993). Thus implementation of SFAS 131 may result in more disaggregation (i.e., higher-quality disclosure) for firms that claim to have material countries or less disaggregation for companies that claim individual countries are not material.³ Second, SFAS 131 allows firms to no longer disclose earnings for secondary segments. Firms that define their primary operating segments on any basis other than geographic area (e.g., line of business) are required to disclose only sales and assets for geographic operations. Prior to SFAS 131, firms were required to disclose sales, assets, and earnings by geographic area. Herrmann and Thomas (2000) document that only 16% of the companies in their sample continue to report geographic earnings after implementation of SFAS 131. Thus, to the extent that geographic operations differ in risk, profitability, and growth potential (Bodnar, Hwang, & Weintrop, 2003; Herrmann et al., 2008; Thomas, 2000), non-disclosure of geographic earnings may hinder investors' ability to understand foreign operations.

To the extent that changes in geographic disclosures coinciding with SFAS 131 improve (worsen) the ability of investors to assess foreign operations, we expect the valuation of foreign earnings to increase (decrease). Prior theoretical and empirical research provides support for the positive relation between the price of earnings and quality of disclosure (e.g., Diamond, 1985; Easley & O'Hara, 2004; Holthausen & Verrecchia, 1988; Kim, 1993; Lambert, Leuz, & Verrecchia, 2007). Consistent with this research, we find strong evidence that geographic segment disclosure practices relate to the pricing of foreign earnings. Firms that increase their number of reported geographic segments or that continue to disclose geographic earnings have foreign earnings that are priced higher than those of firms that do not increase the number of geographic segments or that discontinue the reporting of geographic earnings. The results suggest that higher-quality geographic segment disclosures allow investors to relate reported performance better to underlying foreign operations.

We implement a number of important features into our research design that allow us to directly link cross-sectional variations in geographic segment disclosures to the pricing of foreign earnings. First, our main results are based on “difference-in-differences” tests. Specifically, we compare the differential pricing of foreign earnings in the post-SFAS 131 period while controlling for any differential pricing of foreign earnings in the pre-SFAS 131 period. For all of our tests, we find no evidence that in the pre-SFAS 131 period foreign earnings are priced differently between firms that eventually opt not to disclose more segments or geographic earnings compared with firms that do. The evidence is consistent with differential pricing of foreign earnings relating only to cross-sectional differences in disclosure around the implementation of 131.

Second, all of our tests include a “within-firm control”, in that we also test for whether geographic segment disclosures affect the pricing of domestic earnings. Since the quality of geographic disclosures relates exclusively to foreign operations, we would not expect cross-sectional differences in geographic disclosure quality to affect the ability of investors to process information related to domestic operations. We find evidence consistent with our expectation. The pricing of domestic earnings does not vary with an increase in the number of reported geographic segments or the disclosure of geographic earnings. This increases our confidence that cross-sectional differences in geographic disclosure practices are not related to some other correlated omitted variable.

Third, we include four control variables in addition to the within-firm control: extent of foreign operations, differential growth rates between domestic and foreign operations, firm size, and number of reported business segments. Fourth, since the number of disclosed geographic segments is expected to relate positively to business combinations and negatively to divestitures, we test whether our results are affected by structural changes related to mergers and acquisitions, internal growth, or divestitures. We find no evidence that these factors affect our primary results.

Finally, we consider that the decision to increase or decrease disclosure is likely related to the trade-off between the proprietary costs of these additional disclosures and the potential valuation benefits resulting from mitigating the information asymmetry between managers and investors and/or between different investors. To do this, we estimate two-stage Heckman self-selection models. In these tests, the first stage models the decision to provide more (or less) information, and the second stage tests whether controlling for self-selection bias affects results. The results for all of these tests are consistent, and suggest that the pricing of foreign earnings is associated with important aspects of the firm's information environment. For all tests, we continue to find significant evidence that higher-quality geographic disclosures are associated with higher-priced foreign earnings.

Our study is the first to establish a link between cross-sectional differences in geographic segment disclosure practices and the valuation of foreign earnings. Our results are consistent with Lang and Lundholm (1996), Lundholm and Myers (2002), and Gelb and Zarowin (2002), who conclude that disclosure quality is linked to the ability of investors to predict firm performance. More generally, our findings provide support for the views of the Financial Accounting Standards Board (FASB) that disaggregation of segment data would have capital market benefits (Berger & Hann, 2007). In addition, we provide evidence that reinforces equity investors' contention that such disclosures are value-relevant.

Although our study focuses on the disclosure practices of US multinational companies, we believe our findings are relevant also outside the US. As mentioned above, differences in accounting standards worldwide complicate the ability of investors to obtain high-quality, comparable information about geographic operations of multinational enterprises from different countries. However, the International Accounting Standards Board (IASB, 2006) recently adopted SFAS 131 almost verbatim (IFRS 8 Operating Segments). Thus many international firms will likely change the number of geographic segments they disclose after implementation of the new standard. Like SFAS 131, IFRS 8 includes the option of not disclosing geographic earnings when operating segments are defined along lines other than geographic area. With the option of not having to disclose geographic earnings, many firms around the world likely will discontinue disclosure, as companies have in the US. However, this depends on how different countries decide to implement IFRS 8.

The remainder of the paper is organized as follows. In the next section we provide background on segment disclosures and develop our hypotheses. The third section defines the earnings and abnormal stock return variables we use, describes the sample selection, and provides descriptive statistics. The empirical results are provided in the fourth section, and the final section concludes.

BACKGROUND AND HYPOTHESES DEVELOPMENT

Investors and analysts often assert that segment disclosures are among the most important information provided by firms. For example, in a Chartered Financial Analyst (CFA) Institute survey (Global corporate financial reporting quality, 27 October 2003), 71% of investment professionals rated segment disclosures as either “very” or “extremely” important. SFAS 14 (Financial Reporting for Segments of a Business Enterprise) came under severe criticism from various user groups. Perhaps most importantly, the CFA Institute (formerly the Association for Investment Management and Research, or AIMR) issued a position paper in 1993 requesting that financial statement information be disaggregated to a much greater degree (AIMR, 1993).⁴ Similarly, the AICPA Special Committee on Financial Reporting (1994) listed improved segment information as its number one recommendation. Thus SFAS No. 131 (Disclosures about Segments of an Enterprise and Related Information), which superseded SFAS 14, became effective for fiscal years beginning after 15 December 1997 (FASB, 1997).

Under SFAS 14, firms were required to disclose segment information by both line of business and geographic area, with no specific link to the internal organization of the company. SFAS 131 fundamentally changes the manner in which firms provide segment information (Behn, Nichols, & Street, 2002; Herrmann & Thomas, 2000; Street, Nichols, & Gray, 2000). The standard requires companies to report disaggregated information about reportable operating segments based on management's organization of the enterprise (the “management approach”). In addition, SFAS 131 requires supplemental “enterprise-wide disclosures” about products and services, geographic areas, and major customers if they are not already included as part of the operating segment disclosures. For companies that do not define operating segments on the basis of geographic location, SFAS 131 requires the disclosure of geographic information for each material country.⁵ This represents a major difference from SFAS 14, under which firms were allowed to disclose geographic information by geographic region. Many users complained that the regional disclosures were of limited use.

Herrmann and Thomas (2000) document an overall increase in the number of geographic segments reported following adoption of SFAS 131, with more country-level segments and fewer regional segments. However, they also note that many firms had no change in disclosure, and some actually decreased the number of reported geographic segments. The decrease in the number of reported segments occurs primarily because SFAS 131 allows firms to aggregate immaterial countries into a single “Other Foreign” segment. Some firms no longer disclose even broad, regional segments but choose to aggregate all foreign operations into a single foreign segment. Thus cross-sectional variation in geographic segment disclosures exists.

We are interested in the impact that cross-sectional variation in geographic disclosure has on the pricing of foreign earnings.⁶ Specifically, we predict that as disclosure quality increases (e.g., disclosure of more geographic segments), then the pricing of foreign earnings will increase.⁷ This prediction follows prior theoretical research, which provides at least three explanations for the relation between improved geographic disclosures and the higher pricing of foreign earnings.⁸ First, Holthausen and Verrecchia (1988) suggest that the price reaction to the release of information is negatively related to the noisiness of the information signal. If geographic disclosures provide a noisy set of information about valuation-relevant future cash flows, then price changes associated with a given amount of unexpected foreign earnings will be smaller. To the extent that improved geographic disclosures can reduce the noise in foreign earnings, the price response to unexpected foreign earnings should increase significantly. Collins and Salatka (1993) test the model of Holthausen and Verrecchia (1988) following the adoption of SFAS 52 by multinational firms. SFAS 52 was meant to improve foreign currency accounting compared with that under SFAS 8. They find that the response to unexpected earnings increases substantively after implementation of SFAS 52, suggesting that investors perceive earnings under the new standard to be a less noisy measure of future cash flows.

Second, higher-quality disclosures decrease the information asymmetry component of the cost of capital, reducing the discount applied by investors to stocks for which limited information is available (Leuz & Verrecchia, 2000). Information asymmetry arises either between the firm and investors or among investors (e.g., Francis, LaFond, Olsson, & Schipper, 2004). Regarding information asymmetry between the firm and investors, Lambert et al. (2007) show how poor-quality disclosure creates information risk. Investors anticipate this and demand a higher risk premium (i.e., they charge a higher cost of capital). Regarding information asymmetry among investors, Easley and O'Hara (2004) show that, in a model with informed and uninformed investors, the information risk faced by the uninformed investors is not diversifiable and therefore will be priced. The information risk is reduced with the precision of firm disclosures.⁹ Regardless of its source, if information asymmetry is especially severe for foreign operations (as the extant literature suggests), then the risk-adjusted discount rate for foreign earnings should decrease when the information environment improves.

Third, when the amount or quality of publicly available information about a firm is low, investors must undergo the cost of gathering and processing private information. This additional cost increases investors' required return. As the firm's information environment improves, investors' information acquisition cost is reduced because they can now free-ride on the information that the firm produces (e.g., Diamond, 1985; Kim, 1993). The more the firm discloses, the more investors free-ride. Thus an improvement in geographic segment disclosures should reduce investors' private information search costs related to foreign earnings, reducing the expected return.¹⁰

Hypothesis 1:

• An increase in the number of geographic segments (ΔGSEG) is positively related to the pricing of foreign earnings.

As we shall discuss in detail below, we compare the pricing of foreign earnings in the post-SFAS 131 period between firms that increase their number of reported geographic segments and firms that do not. We compare any differential pricing of foreign earnings in the post-SFAS 131 period with that in the pre-SFAS 131 period. This “difference-in-differences” test controls for a number of unobservable firm characteristics that could impact on the pricing of foreign earnings but which are not included in the model.

We also test whether an increase in the number of reported geographic segments relates to the pricing of domestic earnings. Since changes in the number of geographic earnings relate solely to the information provided about foreign operations, there is no reason to expect an association between geographic earnings quality and the pricing of domestic earnings. In fact, if we find an association, one should question the extent to which our disclosure quality measure (i.e., change in number of reported geographic segments) may proxy for some “other” factor related to the pricing of the firm's overall earnings. Thus our test of the pricing of foreign earnings, while also testing for the pricing of domestic earnings, provides a within-firm research design that should enhance the reliability of our results.

A second interesting aspect of SFAS 131 relates to which specific items are required to be reported for enterprise-wide disclosures. When firms define operating segments on any basis other than geographic area, SFAS 131 requires disclosure only of revenues from external customers and long-lived assets for each reported segment. Under SFAS 14 firms were required to disclose sales, assets, and earnings. Since most firms define their operating segments along industry lines, most firms are no longer required to disclose geographic earnings, and most do not (Herrmann & Thomas, 2000; Street et al., 2000). Although not the only factor, earnings are the single most important explanation of firms' stock returns over the long run and a significant determinant even in the short run (e.g., Givoly, Hayn, & D'Souza, 1999). Therefore, consistent with the ideas expressed in Hypothesis 1, we suggest that disclosure of geographic earnings in the post-SFAS 131 period represents higher-quality disclosure (compared with non-disclosure of geographic earnings) and will therefore result in the higher pricing of foreign earnings.

Non-disclosure of geographic earnings potentially hampers the firm's information environment, resulting in an increase in information asymmetry, information acquisition costs, and noisiness of reported foreign earnings. A couple of recent studies provide evidence consistent with this idea. Hope, Thomas, and Winterbotham (2008), in a test of the Kim and Verrecchia (1997) model, find that firms that discontinue disclosing geographic earnings following implementation of SFAS 131 experience a significant decline in abnormal trading volume around subsequent quarterly earnings announcements. Their results are consistent with non-disclosure of geographic earnings reducing the ability of investors to utilize or generate private information in conjunction with the public announcement of quarterly earnings, which dampens trading. Consistent with the monitoring role of geographic segment disclosures, Hope and Thomas (2008) find that managers of firms that no longer disclose geographic earnings following SFAS 131 are more likely to engage in foreign empire building. Specifically, they find that non-disclosing firms, relative to firms that continue to disclose geographic earnings, experience greater expansion of foreign sales and long-lived assets, produce lower foreign profit margins, and have lower firm value. The above discussion leads to our second hypothesis:

Hypothesis 2:

• The disclosure of geographic earnings (GEARN) is positively related to the pricing of foreign earnings.

For the reasons discussed above, we predict that the pricing of overall foreign earnings will be negatively affected by non-disclosure of specific geographic earnings, relative to firms that continue to disclose. An equivalent way of stating this prediction is that the pricing of foreign earnings will be positively related to the disclosure vs non-disclosure of geographic earnings. So that each of our hypotheses is stated in a similar manner and with the explicit prediction of a positive relation between disclosure quality and the pricing of earnings, we state the second hypothesis in terms of the pricing effects of disclosure of geographic earnings (but keeping in mind that this is equivalent to predicting a negative effect of non-disclosure).

Similar to our test for Hypothesis 1, we use a difference-in-differences test. The differential pricing of foreign earnings between firms that do and firms that do not disclose geographic earnings in the post-SFAS 131 is compared with the differential pricing in the pre-SFAS 131 period. We also examine whether the disclosure of geographic earnings affects the pricing of domestic earnings. No relation is expected.

VARIABLE DEFINITIONS AND SAMPLE SELECTION

In this section, we describe how we compute the earnings and abnormal stock return variables. We then explain our sample selection and discuss descriptive statistics. Finally, we report on an investigation of a random set of firms that had a decrease or an increase in the number of geographic segments around adoption of SFAS 131. The purpose of this investigation is to establish that an increase in the number of segments, in fact, did represent improved (i.e., finer) disclosure.

Earnings Measures

The SEC mandates the disclosure of pretax earnings and taxes for both domestic and foreign operations. All firms must report total foreign earnings according to SEC Regulation §210.4–08(h). This is true both before and after implementation of SFAS 131. Our empirical tests measure the pricing of foreign earnings as reported in the SEC footnote conditional on the reporting of geographic earnings in the segment footnote.

Using the Compustat Annual database (both active and inactive firms), we compute foreign earnings as pretax foreign income (#273) adjusted for foreign taxes, where foreign taxes are measured as the sum of foreign income taxes (#64) and deferred foreign taxes (#270). Domestic earnings are the difference between pretax domestic income (#272) and domestic taxes (total income taxes (#16) less foreign taxes). We then compute earnings changes by differencing the earnings measures. To facilitate cross-sectional and temporal comparisons, we standardize the foreign and domestic earnings changes by stock price at the beginning of the fiscal year.¹¹

Abnormal Stock Return Measure

We compute abnormal stock returns by following a procedure similar to Bodnar and Weintrop (1997). We extract stock returns inclusive of dividends from the CRSP monthly returns file. If the firm is delisted during a specific month, we use the delisting return provided by CRSP, if it is available. To compute annual abnormal returns for the current fiscal year, we proceed as follows. First, we require that 36 monthly returns preceding the current fiscal year be available to estimate the market model parameters. The market model is estimated using CRSP value-weighted market returns. Second, we cumulate the monthly returns starting the 4th month after the previous fiscal year end and ending 3 months after the termination of the current fiscal year:

where UR is the current cumulative annual abnormal return, R_i,j is the raw monthly return for firm i and month j, α̂ _i and β̂ _i are the firm-specific parameters of the market model estimated over the previous 36 months, and R_m,j is the CRSP value-weighted monthly market return corresponding to month j.¹²

Sample Selection and Descriptive Statistics

For our main tests using observations following the adoption of SFAS 131, our sample spans the period from 1998 to 2004.¹³ The sample selection procedures follow Bodnar and Weintrop (1997). We include only firms that are incorporated in the United States, have both current and lagged observations for domestic and foreign annual income, and have necessary return data to compute the market model abnormal returns. These restrictions yield a sample of 5456 observations (1507 firms). After requiring that our sample firms have data available also in the pre-SFAS 131 period (for the difference-in-differences tests), and after eliminating the top and bottom half percentile of abnormal returns and standardized domestic and foreign earnings changes,¹⁴ our final sample consists of 3240 observations (719 firms).¹⁵ Panel A of Table 1 details our sample selection procedures. Panel B shows that approximately 24% of the sample firms increase the number of geographic segments and 33% include earnings measures in the geographic segment disclosure when they adopt SFAS 131.¹⁶

Table 1 Sample description

Panel A of Table 2 presents descriptive statistics for the full sample as well as for firms that increase (do not increase) the number of geographic segments disclosed and for firms that include (do not include) earnings measures in their geographic segment disclosures. Segment data are obtained from the Compustat Segment files. As sample firms are multinationals, they are relatively large, with a median (mean) market value of equity of $927 million ($4.8 billion). By comparison, the median (mean) market value of all Compustat firms for the sample period is $70 million ($1.2 billion). Foreign revenues as a percentage of total revenues have median (mean) values of 35% (37%), illustrating the importance of foreign operations for the average sample firm. As in Bodnar and Weintrop (1997), the growth rate of foreign sales exceeds that of domestic sales, consistent with foreign markets exhibiting greater average growth opportunities than domestic markets.¹⁷

Table 2 Descriptive statistics and correlations

The descriptive statistics for the subsamples show that they are relatively similar in several respects. In particular, there are no significant differences between subsamples in terms of abnormal returns, domestic and foreign earnings changes, firm size, or differential growth of foreign and domestic operations. Not surprisingly, the ΔGSEG=1 group reports significantly more geographic segments than the ΔGSEG=0 group (with means of 4.59 and 3.39, respectively). Firms that disclose geographic earnings (GEARN=1) report fewer industrial segments than do firms that do not disclose geographic earnings (GEARN=0). We control for these factors in our sensitivity analyses.

Panel B of Table 2 presents Pearson correlations among the dependent variable, test variables, and control variables. Domestic and foreign earnings changes are positively and significantly correlated with abnormal returns (with correlation coefficients of 0.151 and 0.155, respectively). Domestic and foreign earnings changes are only weakly positively correlated (0.032, significant at the 10% level).¹⁸ ΔGSEG is positively correlated (0.082) with the percentage of foreign revenues.

Investigation of Firms that Increase or Decrease Their Number of Geographic Segments Following Implementation of SFAS 131

A premise of our study is that an increase in the number of geographic segments represents increased information quality. In other words, holding all else constant, the disclosure of more geographic segments provides more information to decision-makers than does disclosure of less geographic segments. Such a conclusion follows logically from the fineness theorem, which states that information set X has higher quality than information set Y as long as every signal from X is fully contained in a signal from Y (Demski, 1973). While this is an obvious conclusion, we provide empirical support by selecting 50 (80) firms that had a decrease (increase) in the number of reported geographic segments around adoption of SFAS 131. For this sample of 130 companies, we could not identify a single instance where a smaller number of segments would be interpreted as higher-quality information compared with a greater number of segments for the same firm. Nearly all of the decrease-segment firms represent cases where the firm was disclosing regional segments but now discloses only a single “Total Foreign” segment. For the increase-segment firms, a common disaggregation included disclosing a continent (e.g., Europe) in the pre-SFAS 131 period but now disclosing a country (e.g., the UK) and the rest of the continent (e.g., Other Europe) in the post-SFAS 131 period.

Based on this extensive review of annual report disclosures, we conclude that an increase in the number of reported geographic segments can be interpreted as higher-quality information (and likewise, a decrease in the number of geographic segments represents lower-quality information).

RESEARCH DESIGN AND EMPIRICAL RESULTS

In this section, we report the results of our hypotheses tests, including several sensitivity analyses. These tests center on whether the foreign earnings response coefficient (ERC) is an increasing function of disclosures related to foreign operations. To facilitate comparisons with prior research, in particular Bodnar and Weintrop (1997), we first present results of a regression of abnormal returns (UR) on domestic earnings changes (ΔDomEarn) and foreign earnings changes (ΔForEarn):

The results are reported in Table 3. β₁₃ is the foreign ERC. Reported significance levels are two-sided and based on Newey–West standard errors that correct for both heteroskedasticity and autocorrelation (Newey & West, 1987). All models also include fixed-year effects (not tabulated for brevity). Consistent with Bodnar and Weintrop (1997), coefficients on both ΔDomEarn and ΔForEarn are positive and significant at less than the 1% level, suggesting that investors view both earnings streams as value relevant.¹⁹

Table 3 Regressions of unexpected stock returns on changes in domestic and foreign earnings (post-131 period)

Research Design Issues

In this section, we test whether the pricing of foreign earnings varies with geographic segment disclosure practices following implementation of SFAS 131. Similar to other research involving voluntary disclosure, a possible concern is that disclosure choices under SFAS 131 are endogenous to the model. To address this issue, we implement several important research design features. First, while we test for differences in foreign ERCs between disclosure groups in the post-SFAS 131 period, we also consider whether these groups had differential foreign ERCs in the pre-SFAS 131 period (i.e., before implementation of SFAS 131). If foreign ERCs are as different in the pre-SFAS 131 period as they are in the post-SFAS 131 period, then it is hard to argue that cross-sectional disclosure practices under SFAS 131 relate to the pricing of foreign earnings. Therefore, to provide more reliable conclusions, we base our main results on the difference in ERCs in the post-SFAS 131 period minus the difference in ERCs in the pre-SFAS 131 period (i.e., a “difference-in-differences” test).

Second, our tests include a “within-firm control” in that we also test whether geographic segment disclosures affect the pricing of domestic earnings. Since the quality of geographic disclosures relates exclusively to foreign operations, we would not expect cross-sectional differences in geographic disclosure quality to affect the pricing of domestic earnings. If it does, then the quality of geographic disclosure practices likely reflects some other firm characteristic that affects the pricing of overall earnings.

Third, firms' decisions on whether to increase the number of reported geographic segments and/or to disclose earnings measures for each geographic segment are affected not only by the requirements of SFAS 131, but also by voluntary decisions. These decisions relate to the trade-off between the proprietary costs of these additional disclosures and the potential valuation benefits resulting from mitigating the information asymmetry between managers and investors and/or between different investors.²⁰ Hence our conclusions may suffer from self-selection biases. That is, firms' decisions to increase the number of reported geographic segments and/or include earnings measures may be caused by a host of other factors. And it could be these other factors, rather than higher-quality geographic segment disclosure, that lead to differences in foreign ERCs. We address this concern by conducting two-stage Heckman self-selection models.

As additional sensitivity analyses we also report results of tests including a set of control variables and after excluding firms that have undergone structural changes.

Difference-in-Differences Tests

We first test whether the foreign ERC is positively associated with the change in the number of geographic segments disclosed after implementation of SFAS 131 (hypothesis 1):

where ΔGSEG is an indicator variable that takes the value of 1 if there is an increase in the number of geographic segments in the fiscal year in which the firm adopts SFAS 131 (0 otherwise).

To control for “within-firm effects,” we also provide results where we control for the effects of geographic segment disclosure on the pricing of domestic earnings:

As illustrated in Panel A of Table 4, the coefficients on ΔDomEarn and ΔForEarn are positive and statistically significant. As predicted, the estimated coefficient on the interaction of ΔGSEG and ΔForEarn is positive and significant at the 1% level. The pricing of foreign earnings relates positively to the quality of geographic disclosures.²¹ Table 4 further shows that the estimated coefficient for the interaction between ΔGSEG and ΔDomEarn is small and statistically insignificant, and that the previous inference related to ΔForEarn is unaffected. The insignificant relation between ΔGSEG and the pricing of domestic earnings increases our confidence that cross-sectional differences in geographic disclosure practices are not related to some other firm characteristic related to the pricing of overall earnings.

Table 4 Difference-in-differences results

As a further test of whether differential foreign ERCs relate to uncontrolled firm characteristics rather than to ΔGSEG, we estimate foreign ERCs in the pre-SFAS 131 period.²² The pre-SFAS 131 period acts as a control period in our cross-sectional analysis. If differences in foreign ERCs existed prior to implementation of SFAS 131, then results are confounded. As shown in Panel B of Table 4, the interaction between ΔGSEG and ΔForEarn is insignificant in the pre-SFAS 131 period, suggesting that the effect observed in the post-SFAS 131 period (Panel A) is not related to firm characteristics that existed in the pre-SFAS 131 period.²³ Furthermore, Panel C shows that the difference between the interaction of ΔGSEG and the foreign ERC in the post- vs pre-SFAS 131 period is significantly positive (at the 5% level). There is no significant association between ΔGSEG and the domestic ERC in either the post- or pre-SFAS 131 period, and the difference-in-differences test in Panel C is also not statistically significant for the domestic ERC. These results lend additional support that evidence in favor of our hypothesis is not driven by correlated omitted variables.

We next turn to tests of geographic earnings disclosures (Hypothesis 2). To determine whether the foreign ERC is greater for firms that include earnings (GEARN) in their geographic segment disclosures, we estimate the following models (excluding and including the interaction with domestic earnings, respectively):

where GEARN is an indicator variable that takes the value of 1 if the firm discloses geographic earnings following implementation of SFAS 131 (zero otherwise). Results are reported in Table 4. The coefficient on the interaction between ΔForEarn and GEARN is positive and statistically significant at the 1% level (Panel A), supporting Hypothesis 2 and suggesting a positive relation between the pricing of foreign earnings and the extent of geographic segment disclosures. As discussed above, this is equivalent to a negative effect on pricing of non-disclosure of geographic earnings. The results for Eq. (4b) show that the interaction between ΔDomEarn and GEARN is insignificant, and the significant relation between ΔForEarn and GEARN remains. We repeat the tests in the pre-SFAS 131 period. Panel B shows that there is no relation between GEARN and foreign ERCs (or domestic ERCs) in the pre-SFAS 131 period. This suggests that the pricing of foreign earnings in the pre-SFAS 131 period did not differ between eventual disclosers and non-disclosers of geographic earnings. Panel C reports that the difference in coefficients between the post- and pre-SFAS 131 periods is significant at the 5% level for the interaction of ΔForEarn and GEARN but not for the interaction of ΔDomEarn and GEARN.

To investigate whether the inclusion of geographic earnings has incremental value relevance to investors over and above the change in the number of geographic segments disclosed, we estimate the following combined models:

The empirical results of this regression are reported in the rightmost columns of Table 4. The interactions of ΔForEarn with both ΔGSEG and GEARN are positive and significant,²⁴ suggesting that both disclosure effects are incrementally value-relevant. The interactions with ΔDomEarn are not significant. Again, we observe no significant associations between disclosure choices (ΔGSEG or GEARN) and the pricing of earnings (ΔForEarn or ΔDomEarn) in the pre-SFAS 131 period, and the difference-in-differences results are significant only for the interactions with ΔForEarn.

The results reported in Table 4 are consistent with prior research showing that segment disclosures enhance security valuation (e.g., Berger & Hann, 2003; Ettredge, Kwon, Smith, & Zarowin, 2005; Kinney, 1971).²⁵ The documented effects of disclosure differences on the foreign ERC are probably due to a combination of three factors. First, improved disclosures reduce the perceived noise in the earnings signal, consistent with the theoretical models of Holthausen and Verrecchia (1988) and the empirical findings of Collins and Salatka (1993). Consistent with our findings, Collins and Salatka (1993) find that the earnings response coefficient increased substantively following the introduction of SFAS 52, a standard that improved the reporting of foreign currency accounting. Specifically, Collins and Salatka (1993, Table 6) document an increase in earnings response coefficients of 0.917 from the pre- to the post-SFAS 52 period.²⁶

Second, improved geographic segment disclosures decrease the information asymmetry component of the cost of capital (e.g., Easley & O'Hara, 2004), allowing earnings to be capitalized at a higher rate. In other words, with greater disclosure, information risk is reduced and hence investors demand a lower risk premium. Finally, greater segment disclosures reduce investors' information acquisition costs (e.g., Diamond, 1985). That is, improved disclosure enables investors to “free-ride” on the information the firm produces and reports, and this lowers investors' discount rate.²⁷

Controlling for Other Factors that Might Affect the Pricing of Foreign Earnings

Results to this point are consistent with increased geographic segment disclosures leading to higher valuations for foreign earnings. In this section, we repeat the difference-in-differences tests after including controls for four factors potentially affecting our regression results: percentage of foreign revenues, firm size, differential growth rates, and number of reported industry segments. First, it is possible that investors pay more attention to foreign earnings when these operations are more important for a given firm (as measured by percentage of foreign revenues), which in turn could affect the pricing of foreign earnings. Second, ERCs may vary with firm size, as firm size relates to overall disclosure level (e.g., Lang & Lundholm, 1996) and the extent of sophisticated investor following (Callen et al., 2005; Thomas, 2004). Third, differential revenue growth between foreign and domestic operations (i.e., foreign minus domestic year-to-year revenue growth) may also explain differences in earnings response coefficients (Bodnar & Weintrop, 1997). Finally, we control for the change in the number of reported industry segments from the pre- to post-SFAS 131 period (from Compustat), as these segments potentially provide an alternative source of information for investors.

Table 5 shows that no inferences are affected after controlling for these factors. Specifically, none of the interactions between the control variables and the foreign ERC is significant. Furthermore, the interactions are also not significant in the pre-SFAS 131 period (not tabulated for brevity). More importantly, the relations between ΔGSEG and the foreign ERC and between GEARN and the foreign ERC remain positive and significant, and the difference-in-differences results remain significant for the foreign ERC (and insignificant for the domestic ERC). These findings suggest that our results are not due to lack of control for the relative magnitude of foreign operations, firm size, growth, or industry segment reporting.^28,29

Table 5 Difference-in-differences tests including control variables

Structural Changes

If a firm doubles in size through a merger or acquisition (or through organic growth), its number of geographic segments may very well increase. In such a situation it is not clear that an increase in the number of geographic segments implies an enhanced information environment. Regarding the decision to report geographic earnings (GEARN), it is less clear what effect corporate structural changes would have. Nevertheless, to ensure that our results are not driven by corporate structural changes, we eliminate firms with a greater than 25% increase or decrease in total assets.³⁰ Table 6 shows that results are similar after eliminating firms that undergo major structural changes, and no inferences are affected.

Table 6 Difference-in-differences tests with controls for structural changes (removing firms with absolute ΔAssets>25%)

Self-Selection Tests

To address endogeneity issues due to self-selection, we follow a similar research design as Leuz and Verrecchia (2000) and use a two-stage Heckman (1979) estimation approach. In the first stage, we use probit estimation to model the decision to increase the number of geographic segments disclosed or to disclose geographic earnings after adoption of SFAS 131. In the second stage, we estimate Eqs. (3) and (4) after controlling for the inverse Mills ratios computed using the first-stage results.³¹

In the probit models, we introduce 11 variables that proxy for external demands to reduce information asymmetries between managers and users of financial statements and among investors.³² Following Cohen (2006), we compute a variable OWNER defined as the (industry-adjusted) natural logarithm of the number of common shareholders. We also include a variable, ASYMMETRY, which measures the asymmetry of information between managers and analysts (Botosan & Harris, 2000). This variable is computed as the coefficient of variation of analysts' earnings forecasts from 3 months before the announcement of annual earnings as reported by IBES.³³

Highly indebted firms may be under greater pressure to disclose more, since debtholders need more information for monitoring. We compute LEVERAGE as total liabilities (#181) divided by total assets (#6). In addition, we include the current ratio (current assets #4 divided by current liabilities #5) as a proxy for LIQUIDITY.³⁴ Low-liquidity firms may be under different pressures to disclose than are other firms.

As proxies for proprietary costs of disclosure, we include a measure of capital intensity (CAPIT), computed as (industry-adjusted) capital expenditures (#128) divided by net sales (#12), and the Herfindahl Index (HERF). Following the extant literature, we include the industry concentration ratio (HERF) to control for the effects of industry-specific competition on disclosure (Berger & Hann, 2007; Verrecchia, 1983). HERF equals ∑_i=1ⁿ(s _i /S)², where s _i is the segment's sales, S is the sum of sales for all segments in an industry (defined by two-digit SIC code), and n is the number of firms (segments) in the industry. To obtain a firm-specific measure of this index, we compute the weighted average across firms' segments using the segments' sales as weights.

We control for future growth opportunities with the market-to-book ratio (MB) and for firm performance with return on equity (ROE) as well as domestic and foreign profit margins (PM_DOM, PM_FOR), since previous research associates firm performance with disclosure strategies (e.g., Lang & Lundholm, 1996). Finally, we control for SIZE using the natural logarithm of total assets (#6).

We thus estimate separately in the first stage the following two probit models for our two disclosure choices:

In the second stage, we estimate regressions (3b) and (4b) and control for the inverse Mills ratios computed from the first stage.³⁵

Table 7 presents the empirical results of estimating these self-selection models.³⁶ Both first-stage models are significant, with likelihood ratio p-values less than 1% (Panel A). For the ΔGSEG model, OWNER, ASYMMETRY, LEVERAGE, CAPIT, and MB are significant explanatory variables. For the GEARN model, ASYMMETRY, LEVERAGE, MB, and ROE are significant. More importantly, the second-stage results are consistent with our main test results. We provide both pooled and Fama and MacBeth (1973) results in Panel B.³⁷ Both ΔGSEG and GEARN are positively and significantly associated with the foreign ERC after controlling for self-selection bias.

Table 7 Self-selection tests (Heckman, 1979)

Other Sensitivity Analyses

We first check whether our results are robust to limiting the sample to a 2, 3 or 4 year before and after the implementation of SFAS 131. Second, to ensure that the inclusion of geographic earnings measures is voluntary and not mandated by SFAS 131 (i.e., that the geographic segments are not operating segments), we re-run tests after excluding (the small number of) firms that report capital expenditures and depreciation (both required for operating segments) in their geographic disclosures. Third, we consider alternative specifications where ΔGSEG is either a continuous measure or a percentage measure of the change in segments disclosed (instead of an indicator variable as in tabulated results). No inferences are changed with these alternative specifications.

As discussed above, our main tests are based on standard errors that are corrected both for autocorrelation and heteroskedasticity (Newey & West, 1987), and our models also include year fixed effects. As a final robustness test, we repeat the difference-in-differences tests using the Fama and MacBeth (1973) methodology (similar to what we do for the self-selection tests). No inferences are affected in these sensitivity tests.

CONCLUDING REMARKS

Our research attempts to answer disclosure questions related to the international operations of US firms, where relatively little research currently exists. Because of the growing importance of the multinational operations of US firms, our results should be of increased interest to regulators and investors.

SFAS 131 brought about significant changes in the disclosure of information related to geographic segments and therefore foreign earnings. Our study investigates whether geographic segment disclosures are positively related to the pricing of foreign earnings. Using difference-in-differences tests, we document that the foreign earnings response coefficient is increasing with (1) the increase in the number of geographic segments disclosed and (2) the inclusion of earnings measures in geographic segments following adoption of SFAS 131. Our results are robust to a number of sensitivity analyses (including Heckman self-selection tests), and provide standard-setters with evidence supporting the benefit of such disclosures. These benefits include reduced noise in the foreign earnings signal (e.g., Holthausen & Verrecchia, 1988), reduced information asymmetry (e.g., Easley & O'Hara, 2004), and reduced information acquisition costs for investors (e.g., Diamond, 1985).

Our study is the first to establish a link between cross-sectional differences in geographic segment disclosure practices and the valuation of foreign earnings. We thus provide evidence that reinforces equity investors' contention that such disclosures are value-relevant, supporting FASB's view that disaggregation of segment data would have capital market benefits.

Diamond (1985) argues in favor of the welfare role of public disclosure because it obviates the need for each individual investor to expend resources on costly information-gathering. In other words, disclosure essentially turns private information into public information. In the models of Merton (1987) and Fishman and Hagerty (1989), disclosure reduces the cost of becoming informed, thereby increasing the pool of potential investors and lowering the firm's cost of capital (see also Easley & O'Hara, 2004). With respect to voluntary disclosure of earnings measures in geographic segments, our findings indicate that investors find such disclosures to be value-relevant. Non-disclosure of geographic earnings may be especially detrimental to the firm's information environment as foreign operations continue to represent a growing portion of overall operations of US firms. Critics of SFAS 131 have argued that the lack of mandatory earnings disclosure is one of its shortcomings.

Finally, although we examine the disclosure practices of US multinational companies, our findings may also be of interest outside the US. In 2006, the IASB adopted IFRS 8 Operating Segments, which converges international segment reporting standards with those in the US. If firms around the world adopt IFRS 8, we may see widespread non-disclosure of geographic earnings like that in the US. Firms are required to implement IFRS 8 in 2009, although earlier application is permitted. As firms begin to implement IFRS 8, researchers can gather additional information on firms' choices of segment disclosure and its value relevance.