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Journal of Applied Corporate Finance

F A L L 1 9 9 6 V O L U M E 9 . 3

A Practical Approach to Calculating Costs of Equity

for Investments in Emerging Markets

by Stephen Godfrey and Ramon Espinosa,

Bank of America



80JOURNAL OF APPLIED CORPORATE FINANCE

A PRACTICAL APPROACH

TO CALCULATING COSTSOF EQUITY FOR INVESTMENTS INEMERGING MARKETS

by Stephen Godfrey and Ramon Espinosa,Bank of America

80BANK OF AMERICA JOURNAL OF APPLIED CORPORATE FINANCE

countries. For instance, investments in developingcountries face political or sovereign risks such asexpropriation or capital controls, and they are alsotypically forced to contend with more volatile busi-ness environments and multiple currency expo-sures. Moreover, the measurement of risk premia inthese environments is complicated by a scarcity of reliable data, which in turn limits the use of statisti-cal analysis.

In this paper, we propose a practical framework

that multinational corporations (MNCs) can use todetermine the discount rates for evaluating invest-ment opportunities in emerging markets. We arguethat there are three major types of risk that affect mostdeveloping-country investments: (1) political, or“sovereign,” risk; (2) commercial, or “business,” risk(as reflected in the volatility of the local businessenvironment); and (3) currency risk. Sovereign risk,as we will propose below, can be assessed by observing the yield spreads on sovereign bondsdenominated in a common reserve currency such asU.S. dollars. Business risk can be measured by comparing the volatility of local equity markets to the

volatility of the U.S. market. Currency risk can beaccounted for by performing the analysis in U.S.dollars (or the home currency)that is, by convert-ing local-currency cash flows into USD at an appro-priate exchange rate, and then discounting thosedollars flows at the appropriate, risk-adjusted USDdiscount rate.

1. Stocks, Bonds, Bills and Inflation, 1995 Yearbook, Market Results for 1926-1994, Ibbotson Associates.

n performing a Net Present Value (NPV)analysis of an investment, project cashflows are discounted at a risk-adjustedrate to estimate the expected present

value of the project. Discount rates play a central rolein the analysis by permitting distinctions to be madebetween projects with similar expected cash flowsbut different risks. Riskier projects will carry higherdiscount rates and, therefore, have lower NPVs.

In practice, discount rates are computed as the

weighted average of the relevant debt and equity costs. Estimations of the cost of equity are typically based on the Capital Asset Pricing Model (CAPM).According to the CAPM, the equity market is ex-pected to return a premium over risk-free assetssuch as U.S. Treasury notes or bonds to compen-sate investors for the additional risks involved inholding equity investments. In fact, Ibbotson Asso-ciates has estimated that, over the period 1926 tothe present, the U.S. equity market has returned apremium over 30-year Treasuries that has averagedbetween 5.0% and 8.4% per year, depending on thetime horizon (and on whether you use the geomet-

ric or the arithmetic mean).1While determining the proper discount rate for

evaluating a domestic investment is not easy, calcu-lating discount rates for foreign direct investment and, in particular, emerging-market projectsiseven more challenging. Projects in these countriesface more varied risks than projects in developed

I




intended to be rough approximations at best. Higherlevels of precision will require more detailed analysisof the probable cash-flow consequences associated

with various local political and economic risks.2Moreover, just as market perceptions of domesticrisks change constantly, the fundamental economicand credit conditions of emerging markets can alsobe expected to change, and the model for estimatingdiscount rates should allow for periodic updating toreflect such changes.

When establishing discount rates for emergingmarkets, the two dimensions of risk that need to beincorporated into the analysis are (1) credit quality ,which captures sovereign risks, and (2) business volatility , which reflects primarily the commercialrisks of operating in a given country.3 In ourmodel, sovereign or credit quality risk is accountedfor by an upward adjustment of the U.S. (or home-country) risk-free discount rate. Business volatility is captured by an additional risk premiumonethat is analogous to the market risk premium in aCAPM-framework. But instead of using a country’sbeta , which reflects the expected covariance of thelocal stock market’s return with the returns of theworld (or home-country) equity market, we recom-mend use of a measure of local business volatility that reflects the volatility of the local stock marketrelative to the volatility of the domestic (U.S.)

market.Thus, our model for calculating the equity discount rate (k) for evaluating an emerging-marketinvestment can be summarized in the followingequation:

k = [RFUS + Credit Spread] + [β × (US Equity Premium)].

The first of the two terms on the right reflects thecredit quality spread and the second term representsthe local volatility premium. As we also explainbelow, to the extent that the credit spread and theequity premium reflect the same underlying sources

of uncertainty and volatility, such measures of coun-try risk will involve “double counting” and hencerequire a downward adjustment.

This equation, whose components we describein more detail below, yields the equity cost for an

investment of average risk in a given country; that is,it provides a measure of country risk rather thanproject risk. Arriving at a project-specific discount

rate requires an additional adjustment to capture any difference between the project’s risk and that of theaverage investment in that economy.

CURRENCY EXPOSURE

As stated earlier, currency effects should becaptured in the analysis not by adjusting thediscount rate, but rather by translating foreigncurrency cash flows into USD (or the base cur-rency).4 To accomplish this several approachescan be used. Foreign currency cash flows can beconverted into domestic flows using forwardexchange rates, rate scenarios based on currentmanagement practices (in the case of pegged ormanaged currencies), or exchange rates adjustedfor purchasing power parity (PPP).

Exchange rate regimes can be classified intothree broad categories. The first consists of freely-floating currencies supported by fully developedinterest-rate and forward-exchange markets. In thiscategory (for a list of specific countries, see Table1), multi-year forward contracts and cross currency swaps are available for hedging currency expo-sures. Although forward exchange rates are not

good predictors of future spot rates, they can beused in project valuation analyses to convert for-eign currency flows into the base currency. Themain justification for such a procedure is that theexistence of forwards allows the project managerto lock in the base currency value of the foreigncurrency flows.

The second category consists of currenciesthat are pegged to other currencies or managed(see Table 1). For projects involving these curren-cies, currency risks are associated with the chancethat the current management practice will change.For several reasons, however, we recommend that

such risks be handled by adjusting the project’scash flows rather than by modifying the discountrate. First, in many cases, the risk of change in thecurrent management practice may be one-direc-tionalin Argentina, for example, the risk is of a

2. Donald Lessard, among others, argues that modeling the cash flow impactsof a currency devaluation, hyperinflation, or a decrease in product demand offersmore insight than adjusting the discount rate for these “country-specific” or“nonsystematic” risks. See Donald Lessard, “Incorporating Country Risk in theValuation of Offshore Projects,” MIT working paper, 1994.

3. As we discuss later, however, these two categories are not completely separable; in fact, there is likely to be a significant overlap.

4. See Lessard (1994), cited earlier, as well as footnote 2.



VOLUME 9 NUMBER 3 FALL 1996

83

CATEGORY 1 COUNTRIES

1. Free floating currencies with fully developed interest and forward exchange rate markets

US Dollar Japanese Yen German Mark Australian Dollar Canadian Dollar Italian Lira New Zealan

Franc Swedish Krona UK Pound

1A. Managed or pegged currencies with partially or fully developed interest rate and forward exchange markets

Greek Drachma (Managed float) Malaysian Ringgit (Trade weighted basket) Norwegian Krone (Managed float) Singapore

Dollar (Trade weighted basket) Thai Baht (Undisclosed basket) Austrian Schilling (European Exchange Rate Mechanism)

Belgian Franc (ERM) Danish Krone (ERM) Finnish Markka (ERM) French Franc (ERM) Irish Punt (ERM) Netherlands

Guilder (ERM) Portuguese Escudo (ERM) Spanish Peseta (ERM)


2. Managed or pegged currencies with limited interest rate and exchange rate markets

Argentine Peso(Pegged to USD)

Brazilian Real(Pegged to USD)

Chilean Peso(Pegged to USD, DEM & JPY)

Chinese

Renminbi (Managed float) Czech Koruna (Pegged to 65% DEM and 35% USD) Indian Rupee (Real effective exchange rate)

Indonesian Rupiah (Crawling peg to USD) Hong Kong Dollar (Pegged to USD) Jordanian Dollar (Pegged to SDR) Pakistan

Rupee (Managed float) Polish Zloty (Crawling peg to basket) Sri Lankan Rupee (Managed float) South Korean Won (USD)

Taiwan Dollar (Managed float) Venezuelan Bolivar (Managed to inflation)

2A. Managed or floating currencies with limited interest rate and forward exchange rate markets

Mexican Peso Colombian Peso Peruvian Sol Philippine Peso South African Rand Zimbabwe Dollar

Naira (Dual currency with official rate pegged to USD)


3. Hyper-inflationary Economies

Turkish Lira

devaluation, not a revaluation, of the pesoandthe change may have fairly well-defined implica-tions for project cash flows. Accordingly, it makessense to incorporate this risk into the cash flows.Second, the temporal profile of the risk may vary from that implied by the constant compounding of the discount rate. For example, the risk of a changein management practice may be greater in the nearterm than in the longer term. For this reason aswell, it seems appropriate to deal with the currency risk by adjusting the cash flows.

A third category consists of the currencies of

countries experiencing hyperinflation (of whichTurkey, among our sample of 48 countries, is theonly current representative). The cash flows of projects in hyperinflationary economies are usually either denominated in a “hard” currency, such as theUSD, or are projected to keep pace with the local rateof inflation. Moreover, the exchange rates between

the currencies of such countries and currencieswithout hyperinflation tend to follow PPP fairly closely. Therefore, if such cash flows are denomi-nated in local currency, one can project them toincrease at the local rate of inflation and thentranslate these local flows into USD using a PPP-adjusted exchange rate.

In summary, exchange risk can be incorporatedinto offshore project valuation by translating localcash flows into USD using one of three basicexchange rate assumptions: (1) the forward ex-change rates (for freely-floating currencies); (2) ex-

change rate scenarios (for currencies managed by local government officials); or (3) the PPP-adjustedexchange rates (for currencies experiencinghyperinflation). Moreover, as we illustrate below,the approach for converting foreign currencies intoUSD can also be used to translate the USD-based costof capital into a local-currency version.5

TABLE 1 CATEGORICAL SEPARATION OF CURRENCIES

5. See Arnold Miyamoto, “Linking the Domestic and Foreign Cost of Capital,”Bank of America Research Monograph Number 50, Winter 1996. Miyamoto argues

that the currency of an NPV analysis should not affect the result. That is, a project,whether analyzed in JPY or USD, should yield the same result.

Although an MNC’s shareholders may be willing to accept lower rates of return on

emerging-markets projects because of the expected portfolio diversification benefits,

the managements of MNCs are likely to find that using higher discount rates for such

investments provides a more effective discipline for both the planners who evaluate

such investments and the operating managers who run the overseas units.




STEP ONE: ADJUSTING THE RISK-FREE RATEFOR CREDIT QUALITY

With the project cash flows expressed in U.S.dollars, estimating the appropriate discount rate re-quires only the measurement of a country creditspread and calculation of a premium for businessvolatility. To assess the country credit spread, ana-lysts may look to the markets for sovereign debt. Ingeneral, the difference in the yields on the publicdebt of two countries reflects the expected changesin the exchange rate between the two countries’ cur-rencieswhich in turn reflects differences in expectedrates of inflation, economic policies, and other fun-damental determinants of exchange ratesand thedifference in country risk premia, which in turn willreflect the uncertainty associated with exchange ratemoves and any differences in relative credit quality.

By focusing on sovereign debt denominated ina common currency, however, any yield differentialassociated with currency fluctuations can be elimi-nated, and the credit spread can thus be isolated. Asan illustration, consider the case of the Philippines.While the 10-year U.S. Treasury bond (which many U.S. companies use as their benchmark risk-freerate) currently yields about 6.25%, 10-year Philip-pine government bonds currently yield 15.25%.Because the U.S. bond is denominated in dollars and

the Philippine bond in pesos, the 9% yield differen-tial reflects both the perceived difference in creditquality between the U.S. and the Philippines andexpectations about the movement in the peso versusthe dollar. To isolate the credit spread, we mightconsider the yield on the Philippines’ Brady bonds,which are denominated in U.S. dollars. Currently, thePhilippines’ Par bond is trading at a stripped spread6

of 255 basis points over U.S. Treasuries. This spreadincorporates no (direct) currency effects, and thusoffers a measure of the Philippines’ credit spread.

With emerging countries boosting their issu-ance of external debt to finance external deficits and

take advantage of low funding costs in industrialcountries,7 sovereign issues now trade in severalsectors of the global debt market, and those issues

serve as useful sources of information about creditspreads. Emerging countries, for instance, haveissued U.S. dollar-denominated Yankee bonds, dol-

lar-denominated Euro-bonds, and dollar-denomi-nated Brady bonds (for examples of the spreads onthese issues, see Figure 1). In addition, emergingcountries are also issuing in the Samurai market, andtaking advantage of low funding costs in the Euro-DEM and other Euro-markets.

While differences between the yields on emerg-ing-country sovereign bonds and comparable U.S.Treasuries (or JGBs or Bunds, in the case of Samu-rai or Euro-DEM issues) can provide insight intothe market’s recent assessment of the appropriatecredit spread for selected emerging countries, de-termining the appropriate spread for a particularproject still leaves several challenges for the ana-lyst. First, while international bond issuance is onthe rise, not all emerging countries have dippedinto international markets. For those countries, anindependent measure of risk must be used to inferan appropriate credit spread from the spreads avail-able for other countries. Second, while many coun-tries have issued dollar-denominated debt, some of it is relatively illiquid (e.g., Euro-bond issues, whichtend to be small), and hence the spreads on thoseissues may not be representative of credit quality.Third, for those countries with liquid U.S.-denomi-

nated debt, volatility in the spreads can complicatethe determination of the “appropriate” spread. Overthe course of 1996, for instance, the stripped spreadsover U.S. Treasuries of many Brady bonds havenarrowed sharply (see Figure 2). This developmentraises the question of whether this narrowing hasextended too far (and thus will reverse itself), canbe expected to stabilize, or will extend further.Finally, for countries with multiple Euro- and Brady bonds, different issues may trade at different spreadsto U.S. Treasuries (in Figure 2, notice the differencein the spreads on the Argentine Euro and ArgentineBradies). These differences may be explained by

differences in the terms and characteristics of thevarious issues, or more technical anomalies in themarkets. Regardless, while international bond

6. In Brady-style debt reschedulings, the rescheduling country is required tohold US Treasuries as collateral against the principal and a part of the interest dueon their Brady bonds. As a result of this collateral, the yield on Brady bonds arelower than they would be if there were no collateral backing for the bonds. Thestripped yield adjusts the regular Brady bond yield to exclude the effect of thiscollateral. As a result, the stripped yields tend to exceed the regular yields on Brady bonds.

7. The Institute for International Finance estimates that international bondissued by emerging countries exceeded $57 billion during the first eight monthsof 1996. For 1995 as a whole, such issues amounted to about $45 billion, down from1994’s record level of $61 billion.




85

TABLE 2 RECENT PUBLIC EURO, SAMURAI AND YANKEE ISSUES

Country Description Issue Date Maturity Spread

Argentina $1 bln, 11% Coupon Oct 1996 10 years 4.45% (US Treasury)

Colombia (BBB–) $400 mln, 8% Coupon May 1996 5 years 1.50% (US Treasury)

Greece (BBB) 40 bln JPY, 3.35% Coupon Aug 1996 6 years 0.75% (Japanese Govt)

50 bln JPY, 4.30% Coupon Aug 1996 12 years 1.02% (Japanese Govt)

40 bln JPY, 5.00% Coupon Aug 1996 20 years 0.65% (Japanese Govt)

Hungary (BB+) 40 bln JPY, 5.20% Coupon Dec 1995 15 years 1.70% (Japanese Govt)

Indonesia (BBB) $400 mln, 7.75% Coupon July 1996 10 years 1.00% (US Treasury)Italy (AA) $1.5 bln, 7% Coupon Sep 1996 5 years 0.24% (US Treasury)

Philippines (BB) $635 bln, 8.75% Coupon (Brady Bond swap) Sep 1996 10 years 2.25% (US Treasury)

Poland (BB) 250 mln DEM, 6.125% Coupon Jul 1996 5 years .65% (German Bunds)

South Africa (BB+) $300 mln, 8.375% Coupon Oct 1996 10 years 1.95% (US Treasury)

By focusing on sovereign debt denominated in a common currency, any yield

differential associated with currency fluctuations is eliminated, and the credit spread

for a country can be isolated.

FIGURE 2BRADY STRIPPED YIELDSPREADS

Source: Richard Gray, Bank of America Emerging Market Research.

Source: Richard Gray, Bank of America Emerging Market Research.

FIGURE 1EMERGING MARKETSPREADS




spreads can serve as the starting point for thedetermination of appropriate credit spreads, addi-tional analysis is likely to be required.

STEP TWO: CALCULATING THE PREMIUMFOR BUSINESS VOLATILITY

As we noted earlier, the Capital Asset PricingModel is based on the assumption that an asset’scovariance with the market, as measured by thetraditional beta, is the appropriate measure of risk forpricing assets. According to the CAPM, becauseinvestors can diversify away unsystematic risks,expected equity premia should reflect only theundiversifiable, or systematic, risk of an investment.

Mathematically, the statistical measure of anasset’s systematic risk, or beta, is calculated asfollows:

Beta = cov (r i,r m)/s2m = r i,m × [si/sm],

whereσiandσ

iare the volatilities of the asset and the

market, respectively; cov(ri, r

m) is the covariance

between the asset and the market portfolio of allrisky assets; and ρ

i,mis the correlation between the

asset and the market portfolio.As the equation shows, beta is the product of the

correlation between the investment and the market,

and the ratio of the asset’s volatility to the volatility of the market. The latter ratio can be interpreted asan indication of the relative risk of the asset versusthe market. If this ratio is greater than one, the assetis more volatile than the market; if it less than one,it is less volatile than the market. The correlationcoefficient, ρ, is a measure of the degree of co-movement between the asset and the market. Betathus adjusts the individual stand-alone risk (the ratio-of-volatilities term) to reflect only the non-diversifiable(the correlation term) aspects of the risk.

Because correlation is defined to fall only between –1 and 1, beta can be greater than one only

when the ratio of the volatilities is greater than one.However, a ratio larger than one does not guaranteea large beta because beta can be less than one if the correlation between the market and the security is very low .

Measuring Covariance Risk. To consider therelevance of the CAPM to our problem, we calculate“country betas” by regressing the equity returns of

individual countries against a world equity portfolio.The results of this exercise are presented in Figure3, which ranks 48 countries according to the degreeof their equity market’s correlation with the worldequity portfolio.8 As shown in the figure, all devel-oped countries examined have betas that are higherthan 0.5. By contrast, 15 of the 26 emerging market-countries have betas below 0.5. Moreover, four suchcountries have betas that are negative , thus implyingdiscount rates below the risk-free rate! The reason forthe low betas for emerging markets is the lowcorrelations (represented in Figure 3 by the bars)between each of these countries and the worldequity portfolio.

Measuring Total Risk. By contrast, if we nextrank the same 48 countries by return volatility, theresults (as shown in Figure 4) suggest a very differentrelationship. While emerging equity markets tend tohave lower betas than developed markets, they alsotend to have considerably higher levels of volatility.Therefore, except for the very low correlation terms,the betas for many emerging-markets countrieswould be significantly greater than one.

So, how do we reconcile the CAPM perspectivewith the higher total risks associated with emerging

markets? In the CAPM framework, beta is the appro-priate measure of risk because an investor can hold the market portfolio . The low betas of emergingmarkets suggest that these countries offer diversifi-cation benefits and thus should earn lower rates of return, on average. In practice, however, the manag-ers of MNCs are often interested in measuring risksindependently of their investors’ home portfolios orthe world market portfolio. For instance, the perfor-mance of local managers is likely to be evaluatedagainst rate-of-return benchmarks that are compa-rable to those held out for U.S. managersthat is,benchmarks that give managers little credit for any

diversification benefits their operations may bestowon the company’s investors.

Moreover, even when management considersthe diversification benefits of a project, they prob-ably do not think in terms of diversification relative

8. Except for the countries listed below, the results in Figure 3 are based uponmonthly data from Datastream. For Brazil, Chile, China (Datastream, Aug., 1991),Colombia (Feb., 1991), Czech Republic (Dec., 1993), Hungary (Dec., 1993), India(Nov., 1992), Jordan, Nigeria, Pakistan (Mar., 1991), Peru (Sep., 1993), Philippines,

Poland (Dec., 1993), South Korea (Jan., 1992), Sri Lanka (Sep., 1993), Venezuela(Jan., 1990), Zimbabwe (Oct., 1993), the data come from the International FinanceCorporation (IFC). Unless noted, the starting date is January 1989. Figure 4 is basedon data from March, 1991 to the present.




87

to the world equity portfolio. Instead, they are likely to view it relative to their company’s portfolio of productive and financial assets, which in most cases

will differ significantly from the global portfolio.Accordingly, the use of a correlation-based

“world equity” beta is likely to produce a discountrate that fails to capture the full extent of the risksperceived by management in investing abroad.Although some of these risks can be incorporatedinto the analysis by adjusting the projected cashflows, such adjustments are likely to have littlequantitative basis. The alternative of raising thediscount rate to reflect such risks may seem equally

arbitrary. But, given the heightened uncertainty associated with such investments, and the practicalreality of capital budgeting in large corporations, the

use of higher discount rates for emerging marketsmay better accomplish the aim of capital budgetingsystemsnamely, to send strategic planners clearsignals indicating the full extent of project risks andprovide a basis for higher standards of profitability.

Given that the low correlation between emerg-ing equity markets and the global market biasesemerging-market betas downward, and that MNCsare often not interested in their investors’ ability todiversify, we suggest the following simple rule of

FIGURE 3 CORRELATION AND BETA (WITH THE WORLD EQUITY PORTFOLIO)

FIGURE 4 MEAN EQUITY MARKET RETURNS (RANKED FROM HIGHEST TO LOWEST VOLATILITY)

σ σ

All of the developed countries in our sample have betas that are higher than 0.5. By

contrast, 15 of the 26 emerging market-countries have betas below 0.5. Moreover,

four such countries have betas that are negative, thus implying discount rates below

the risk-free rate!




thumb: In calculating the equity/business premium to be included in the discount rate, use an “adjusted” beta that is equal to the ratio of an indi-

vidual country’s equity volatility to that of the U.S.marketin essence, assume that the correlation coefficient is equal to one. In equation form,

Adjusted Beta = σi/ σUS,

To value this risk for the purpose of generating thebusiness or commercial risk premium, then simply multiply this adjusted beta by the U.S. equity marketrisk premium.

In addition to its simplicity and its grounding inthe U.S. (or home-country) cost of capital, theprimary advantage of this approach to calculatingemerging-market discount rates is the focus on totalrisk. This approach seems particularly appropriate toemerging-country projects because it is in thesecountriesmany of them in the midst of profoundeconomic and political transformationsthat theoverall risks are greatest.

These relatively greater risks are suggested by thedata in Figure 4, which show the averages and thevolatilities of the returns of a large set of countries. If we divide the exhibit into a high-volatility group of countries (almost exclusively emerging markets) anda low-volatility group, we find that though the average

returns for both groups are similar, the dispersion of theaverage returns is greater for the high-volatility group(the standard deviation is 3.0%) than for the low-volatility group (with a standard deviation of 1.2%).

Figure 4 also suggests that there is little system-atic relationship between the average returns and thevolatilities of emerging markets. Because of this, wesuspect that efforts to quantify the relationships be-tween returns and risks to emerging-market instru-ments will yield little. But, we also suspect that, wheninvestors establish standards for emerging-marketassets, they include a premium for the perceivedvolatility (or total risk) of the emerging market.

STEP THREE: ACCOUNTING FOR THEINTERDEPENDENCE BETWEEN CREDIT RISK AND BUSINESS/EQUITY VOLATILITY

Our approach defines emerging market equity risk along two dimensions: credit quality and busi-

ness or equity volatility. Credit quality can be as-sessed using the spreads on sovereign debt, andequity risk can be measured by comparing local

equity market volatility to that of the U.S. Since wesimply add these two measures to arrive at a country discount rate, our method effectively assumes thatthe two measures are independent of one another.

In reality, however, fundamental economic andpolitical developments are likely to affect both acountry’s credit quality and the volatility of the localequity market. To the extent these two measures of riskderive from the same source of risk, our method of combining both measures of risk will result in some“double counting.” The question is, how much?

For developed countries, where both creditspreads and business/equity volatility premia tend tobe small, this problem of double counting is likely to be trivial. For emerging countries, however, boththe credit spreads and business volatility premia arelarger, and there is a greater risk of double counting.In fact, one recent study finds that 40% of thevariation in equity volatility can be explained by variation in credit quality.9 This finding suggests that,for countries with significant credit spreads (that is,for emerging countries), our method may overstatethe premia for business/equity risk by about 40%. Inlight of this finding, a possible (but, we admit, ad hoc ) adjustment for this problem of double counting

would be to reduce the adjusted betas (or thebusiness/equity volatility premia) by 40%.Reducing the adjusted betas by 40% could also

be interpreted as using traditional betas in which thecorrelation coefficients are equal to 0.60. The datapresented in Figure 3 show that the average correla-tion for developed countries is in fact about 60%.

CONCLUSION

In this paper, we have outlined a practicalframework for estimating costs of capital that canbe used to evaluate projects or other investments in

emerging markets. The guiding principals havebeen to construct a framework that is systematicand easily understood.

Fundamentally, cross-border investments facedifferent risks than domestic investments because of their setting in foreign economic and political envi-ronments. The former may add uncertainty to the

9. Claude B. Erb, Campbell R. Harvey and Tadas E. Viskanta, “Country Riskand Global Equity Selection”, The Journal of Portfolio Management , Winter 1995,

pp. 74-83. As their measure of credit quality, this study uses a bi-annual survey of bank country ratings conducted and published by Institutional Investor .




89

marginal risk that remains after the recognition of potential diversification benefits, our business vola-tility premia are based on measures of total risk.

Finally, because estimating equity premia andcosts of capital are challenging tasks even forprojects located in industrial countries, let alone foremerging markets where data is likely to be scarce,this framework is intended to generate only rough

benchmarks for evaluating emerging market projects.The use of risk-adjusted discount rates generated inthis manner should not substitute for the carefulanalysis of project cash flows and risks.

ESTIMATED COSTS OF EQUITY FOR SELECTED EMERGING MARKET COUNTRIES

Annualized

Credit Spread Equity Market Adj. Beta Cost of Equity (percent) Volatility = .6 * σσσσσi /σσσσσUS = R US+ (1) +Country (1) (σσσσσi ) (2) (2)*EqPrem US

Argentina 4.0 54.74% 3.39 28.7

Turkey 2.7 58.17% 3.60 28.5

Brazil 4.1 53.75% 3.33 28.4

Poland 0.9 59.83% 3.71 27.3

Hungary 1.6 56.86% 3.52 27.0

Czech Republic 0.8 48.32% 2.99 23.3

Mexico 3.8 36.56% 2.26 22.3

Philippines 2.0 32.05% 1.99 18.9

India 1.6 29.95% 1.86 17.8

Thailand 0.6 30.91% 1.91 17.1Indonesia 1.0 27.19% 1.68 16.3

South Korea 0.8 25.53% 1.58 15.5

Malaysia 0.6 23.76% 1.47 14.7

South Africa 2.0 19.58% 1.21 14.7

United States - 9.68% 1 11.5

Note: Estimates based upon R US = 6.00%, EqPremUS = 5.5%, and country Euro spreads. To ensure consistency, the volatilities and EqPremUS are estimatedusing data from March 1991 to August 1996.

levels of project cash flows, while the latter may introduce uncertainty about the ability to repatriatethose earnings. Because of these risks, our frame-work proposes two basic modifications to moretraditional U.S. dollar-based cost of capital calcula-tions: (1) a credit spread is added to the U.S. dollarrisk-free rate to reflect transfer risks; and (2) acountry-specific business volatility premium is used

to reflect risks associated with the local businessenvironment. Moreover, because management atsome level is likely to be concerned with the totalrisks of cross-border projects, rather than simply the

The above table presents USD-based, country-specific costs of equity calculated using the frame-work described in the accompanying article. Math-

ematically, ki = R f,us + Credit Spreadi + 0.6 * σi/σUS* Equity PremiumUS. In the case of Brazil, forexample,

STEPHEN GODFREY AND RAMON ESPINOSA

are, respectively, Vice President and Risk Analyst, and VicePresident and Economist, at Bank of America.

Given the heightened uncertainty associated with such investments, the use of

higher discount rates for emerging markets may better accomplish the primary aims

of a capital budgeting systemnamely, to send strategic planners clear signals of the

full extent of project risks and to provide a basis for holding up higher standards

of profitability.

kBrazil = 6.00 + 4.1 + 0.6 * 5.55 * 5.50 = 28.4.Note that the inclusion of the premia for business riskalso reduces the correlation between simple credit

spread and the total cost of equity. For instance,despite a lower credit spread, Poland receives a highercost of equity than Mexico.



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