In the process, we will argue that a company’s exposure to country risk should not be determined by where it is incorporated and traded.
By that measure, neither Coca-Cola nor Nestlé are exposed to country risk. Exposure to country risk should come from a company’s operations, making country risk a critical component of the valuation of almost every large multinational corporation.
If we accept the proposition of country risk, the next question that we have to address relates to the exposure of individual companies to country risk. Should all companies in a country with substantial country risk be equally exposed to country risk? While intuition suggests that they should not, we will begin by looking at standard approaches that assume that they are. We will follow up by scaling country risk exposure to established risk parameters such as betas (β), and complete the discussion with an argument that individual companies should be evaluated for exposure to country risk.
The Bludgeon Approach
The simplest assumption to make when dealing with country risk, and the one that is most often made, is that all companies in a market are equally exposed to country risk. The cost of equity for a firm in a market with country risk can then be written as:
Cost of equity = Risk-free rate + β (Mature market premium) + Country risk premium
Thus, for Brazil, where we have estimated a country risk premium of 4.43% from the melded approach, each company in the market will have an additional country risk premium of 4.43% added to its expected returns. For instance, the costs of equity for Embraer, an aerospace company listed in Brazil, with a beta1 of 1.07 and Embratel, a Brazilian telecommunications company, with a beta of 0.80, in US dollar terms would be:
Cost of equity for Embraer = 3.80% + 1.07 (4.79%) + 4.43% = 13.35%
Cost of equity for Embratel = 3.80% + 0.80 (4.79%) + 4.43% = 12.06%
Note that the risk-free rate that we use is the US treasury bond rate (3.80%), and that the 4.79% figure is the equity risk premium for a mature equity market (estimated from historical data in the US market). It is also worth noting that analysts estimating the cost of equity for Brazilian companies, in US dollar terms, often use the Brazilian ten-year dollar-denominated rate as the risk-free rate. This is dangerous, since it is often also accompanied with a higher risk premium, and ends up double counting risk.
The Beta Approach
For those investors who are uncomfortable with the notion that all companies in a market are equally exposed to country risk, a fairly simple alternative is to assume that a company’s exposure to country risk is proportional to its exposure to all other market risk, which is measured by the beta. Thus, the cost of equity for a firm in an emerging market can be written as follows:
Cost of equity = Risk-free rate + β (Mature market premium + Country risk premium)
In practical terms, scaling the country risk premium to the beta of a stock implies that stocks with betas above 1.00 will be more exposed to country risk than stocks with a beta below 1.00. For Embraer, with a beta of 1.07, this would lead to a dollar cost of equity estimate of:
Cost of equity for Embraer = 3.80% + 1.07 (4.79% + 4.43%) = 13.67%
For Embratel, with its lower beta of 0.80, the cost of equity is:
Cost of equity for Embratel = 3.80% + 0.80 (4.79% + 4.43%) = 11.18%
The advantage of using betas is that they are easily available for most firms. The disadvantage is that while betas measure overall exposure to macroeconomic risk, they may not be good measures of country risk.
The Lambda Approach
The most general, and our preferred, approach is to allow for each company to have an exposure to country risk that is different from its exposure to all other market risk. For lack of a better term, let us term the measure of a company’s exposure to country risk to be lambda (λ). Like a beta, a lambda will be scaled around 1.00, with a lambda of 1.00 indicating a company with average exposure to country risk and a lambda above or below 1.00 indicating above or below average exposure to country risk. The cost of equity for a firm in an emerging market can then be written as:
Expected return = Rf + β (Mature market equity risk premium) + λ (Country risk premium)
Determinants of Lambda
Most investors would accept the general proposition that different companies in a market should have different exposures to country risk. But what are the determinants of this exposure? We would expect at least three factors (and perhaps more) to play a role.
Revenue source: The first and most obvious determinant is how much of the revenues a firm derives from the country in question. A company that derives 30% of its revenues from Brazil should be less exposed to Brazilian country risk than a company that derives 70% of its revenues from Brazil. Note, though, that this then opens up the possibility that a company can be exposed to the risk in many countries. Thus, the company that derives only 30% of its revenues from Brazil may derive its remaining revenues from Argentina and Venezuela, exposing it to country risk in those countries. Extending this argument to multinationals, we would argue that companies like Coca-Cola and Nestlé can have substantial exposure to country risk because so much of their revenues comes from emerging markets.
Production facilities: A company can be exposed to country risk, even if it derives no revenues from that country, if its production facilities are in that country. After all, political and economic turmoil in the country can throw off production schedules and affect the company’s profits. Companies that can move their production facilities elsewhere can spread their risk across several countries, but the problem is exaggerated for those companies that cannot move their production facilities. Consider the case of mining companies. An African gold mining company may export all of its production but it will face substantial country risk exposure because its mines are not movable.
Risk management products: Companies that would otherwise be exposed to substantial country risk may be able to reduce this exposure by buying insurance against specific (unpleasant) contingencies and by using derivatives. A company that uses risk management products should have a lower exposure to country risk–a lower lambda–than an otherwise similar company that does not use these products.
Ideally, we would like companies to be forthcoming about all three of these factors in their financial statements.
The simplest measure of lambda is based entirely on revenues. In the last section, we argued that a company that derives a smaller proportion of its revenues from a market should be less exposed to country risk. Given the constraint that the average lambda across all stocks has to be 1.0 (someone has to bear the country risk!), we cannot use the percentage of revenues that a company gets from a market as lambda. We can, however, scale this measure by dividing it by the percentage of revenues that the average company in the market gets from the country to derive a lambda.
(λj – % of revenue in countryCompany) ÷ % of revenue in countryAverage company in market
Consider the two large and widely followed Brazilian companies–Embraer, an aerospace company that manufactures and sells aircraft to many of the world’s leading airlines, and Embratel, the Brazilian telecommunications giant. In 2002, Embraer generated only 3% of its revenues in Brazil, whereas the average company in the market obtained 85% of its revenues in Brazil.2 Using the measure suggested above, the lambda for Embraer would be:
λEmbraer = 3% ÷ 85% = 0.04
In contrast, Embratel generated 95% of its revenues from Brazil, giving it a lambda of
λEmbratel = 95% ÷ 85% = 1.12
Following up, Embratel is far more exposed to country risk than Embraer and will have a much higher cost of equity.
The second measure draws on the stock prices of a company and how they move in relation to movements in country risk. Bonds issued by countries offer a simple and updated measure of country risk; as investor assessments of country risk become more optimistic, bonds issued by that country go up in price, just as they go down when investors become more pessimistic. A regression of the returns on a stock against the returns on a country bond should therefore yield a measure of lambda in the slope coefficient. Applying this approach to Embraer and Embratel, we regressed monthly stock returns on the two stocks against monthly returns on the ten-year dollar-denominated Brazilian government bond and arrived at the following results:
ReturnEmbraer = 0.0195 + 0.2681 ReturnBrazil dollar-bond
ReturnEmbratel = –0.0308 + 2.0030 ReturnBrazil dollar-bond
Based upon these regressions, Embraer has a lambda of 0.27 and Embratel has a lambda of 2.00. The resulting dollar costs of equity for the two firms, using a mature market equity risk premium of 4.79% and a country equity risk premium of 4.43% for Brazil are:
Cost of equity for Embraer = 3.80% + 1.07 (4.79%) + 0.27 (4.43%) = 10.12%
Cost of equity for Embratel = 3.80% + 0.80 (4.79%) + 2.00 (4.43%) = 16.49%
What are the limitations of this approach? The lambdas estimated from these regressions are likely to have large standard errors; the standard error in the lambda estimate of Embratel is 0.35. It also requires that the country have bonds that are liquid and widely traded, preferably in a more stable currency (dollar or euro).
Risk Exposure in Many Countries
The discussion of lambdas in the last section should highlight a fact that is often lost in valuation. The exposure to country risk, whether it is measured in revenues, earnings, or stock prices, does not come from where a company is incorporated but from its operations. There are US companies that are more exposed to Brazilian country risk than is Embraer. In fact, companies like Nestlé, Coca-Cola, and Gillette have built much of their success on expansion into emerging markets. While this expansion has provided them with growth opportunities, it has also left them exposed to country risk in multiple countries.
In practical terms, what does this imply? When estimating the costs of equity and capital for these companies and others like them, we will need to incorporate an extra premium for country risk. Thus, the net effect on value from their growth strategies will depend upon whether the growth effect (from expanding into emerging markets) exceeds the risk effect. We can adapt the measures suggested above to estimate the risk exposure to different countries for an individual company.
We can break down a company’s revenue by country and use the percentage of revenues that the company gets from each emerging market as a basis for estimating lambda in that market. While the percentage of revenues itself can be used as a lambda, a more precise estimate would scale this to the percentage of revenues that the average company in that market gets in the country.
If companies break earnings down by country, these numbers can be used to estimate lambdas. The peril with this approach is that the reported earnings often reflect accounting allocation decisions and differences in tax rates across countries.
If a company is exposed to only a few emerging markets on a large scale, we can regress the company’s stock price against the country bond returns from those markets to get country-specific lambdas.
A key issue, when estimating costs of equity and capital for emerging market companies relates to how this country risk premium should be reflected in the costs of equities of individual companies in that country. While the standard approaches add the country risk premium as a constant to the cost of equity of every company in that market, we argue for a more nuanced approach where a company’s exposure to country risk is measured with a lambda. This lambda can be estimated either by looking at how much of a company’s revenues or earnings come from the country—the greater the percentage, the greater the lambda—or by regressing a company’s stock returns against country bond returns—the greater the sensitivity, the higher the lambda. If we accept this view of the world, the costs of equity for multinationals that have significant operations in emerging markets will have to be adjusted to reflect their exposure to risk in these markets.
1 We used a bottom-up beta for Embraer, based upon an unlevered beta of 0.95 (estimated using aerospace companies listed globally) and Embraer’s debt-to-equity ratio of 19.01%. For more on the rationale for bottom-up betas, read the companion paper on estimating risk parameters, “Measuring Country Risk.”
2 To use this approach, we need to estimate the percentage of revenues both for the firm in question and for the average firm in the market. While the former may be simple to obtain, estimating the latter can be a time-consuming exercise. One simple solution is to use data that are publicly available on how much of a country’s gross domestic product comes from exports. According to the World Bank data in this table, Brazil got 23.2% of its GDP from exports in 2008. If we assume that this is an approximation of export revenues for the average firm, the average firm can be assumed to generate 76.8% of its revenues domestically. Using this value would yield slightly higher betas for both Embraer and Embratel.