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Next, determine how each of the components of the cash flow is driven by changes in the macroeconomic variables. Link these items to the macroeconomic variables, so that when the macroeconomic scenario is changed the cash-flow items adjust automatically.
After the macroeconomic variables are linked, think about industry scenarios. Constructing industry scenarios is basically the same in emerging markets as in developed markets, with a few variations. One difference is that industries in emerging markets may be more driven by government actions. Another difference is the dependence on markets outside the company's home country for either revenues or inputs. When constructing the model, make sure that the industry scenarios take the macroeconomic environment into consideration.
An example of a recent outside-in valuation of Pao de Ajucar, a Brazilian retail grocery chain, demonstrates how such scenarios can be built. In this example, Merrill Lynch devised three macroeconomic scenarios in September
Exhibit 19.7 Scenarios—Pao de A^ucar
Base case Austerity Devaluation
International support Protracted higher interest Dramatic devaluation
and fiscal reform rates and continued volatility with results similar to
Macrocconomic with unemployment austerity scenario
assumptions, 1999 rising to 14%
1999 year end FX rate Average interest rates Real GDP growth Inflation 1.3 18.0% 0.4% 12% 1.3 20.0% -3.0% 0.0% 2.25 30.0% -5.0% 30.0%
Company assumptions, 1999
Supermarket sales growth 17.2% 1.7% 42.6%
Nominal same store sales growth 1.2% -8.2% 33.3%
Consumer lending Slightly declining balances with higher interest rates in short term Declining balances but with higher spreads Credit dries up in short term
Exhibit 19.8 Scenario Values—Pao de A^ucar
DCF value Probability Weighted value
Base case 1,577 33-50% 525-788
Austerity 901 30-33% 270-300
Devaluation 1,145 20-33% 229-381
Probability-weighted value 1,207-1,288
Market value as of September 1998 1,171
1998 (Exhibit 19.7). The base case scenario assumed that Brazil would enact significant fiscal reforms and enjoy continued international support and that as a result, the economy could recover fairly quickly from the Asian crisis. Revenues and margins are quite robust in this scenario.
The second scenario assumes that the Brazilian economy remains in recession for two years with high interest rates and low GDP growth and inflation.
The third scenario assumes a dramatic devaluation (which is what did happen) with inflation rising to 30 percent and the economy shrinking by 5 percent. These scenarios have a significant impact on revenues and margins in the next five years, but in the long run there is convergence to a steady growth path.
Incorporate these scenarios in the cash flows and discount at an industry-specific cost of capital, then adjust for Pao de Ajucar's capital structure and the difference in the Brazilian inflation rate compared with the U.S. inflation rate. Weight the scenarios by probability. Exhibit 19.8 shows the DCF values of the three scenarios and the probability-weighted value. The base case gets a probability of between 33 percent and 50 percent. The others are assigned lower probabilities based on our internal assessments. The DCF value range is about -23 percent to +35 percent of the base case, which is large, because of the uncertain environment at that time.
The resulting value is 1,207 to 1,288 million Reais. The market value at the time of the valuation was 1,171 million Reais. If we use the base-case cash flows with Brazil's country-risk premium, excluding credit risk, at the time of the valuation (September 1998) of 7.8 percent, we find a value of 260 million Reais, far below the market value. If, however, we use a long-term perspective on Brazil's country risk excluding credit risk of 2 percent, the value is a more reasonable 1,044 million Reais.
Calculating the Cost of Capital in Emerging Markets
While calculating the cost of capital in any country can be challenging, in emerging markets the calculation is an order of magnitude higher. In this section, we provide our basic assumptions, background on the important
issues, and a way to estimate the components of the cost of capital that is easy to apply as well as theoretically and empirically correct.
First, we are looking from the perspective of a global investor, either a multinational company or an international investor with a diversified portfolio. Many local markets are not integrated with the global market and frequently there are restraints on the ability of local investors to invest outside their home market. As a result, the cost of capital to a local investor could be considerably different than a global investor. Further, there is not a common framework for estimating the capital cost for local investors.
We assume that the global economy will become fully integrated and that most emerging markets will become open and efficient. This assumption allows application of the CAPM to estimate the cost of equity in emerging markets. We recognize that the degree of integration of emerging markets with developed markets varies significantly and the CAPM is a less robust model for the less-integrated emerging markets. We expect, however, that it will become a better predictor of required equity returns worldwide. We assume that countries with capital controls that restrict local investors' access to a global risk-free rate will eliminate these restrictions in the long run. Since we value cash flows to infinity and assume that it will be a matter of years for most emerging markets to integrate, we believe it is warranted to apply CAPM with minimal adjustments to estimate cost of equity in emerging markets.