The following regression model was estimated to forecast the value of the Indian rupee (INR): INR_t = a₀ + a₁INT_t + a₂INF_t _- ₁ +

\mu

_t,
Where INR is the quarterly change in the rupee, INT is the real interest rate differential in period t between the U.S. and India, and INF is the inflation rate differential between the U.S. and India in the previous period. Regression results indicate coefficients of a₀ = .003; a₁ = -.5; and a₂ = .8. Assume that INF_t _- ₁ = 2%. However, the interest rate differential is not known at the beginning of period t and must be estimated. You have developed the following probability distribution:
$The following regression model was estimated to forecast the value of the Indian rupee (INR): INRt = a0 + a1INTt + a2INFt - 1 + \mu t, Where INR is the quarterly change in the rupee, INT is the real interest rate differential in period t between the U.S. and India, and INF is the inflation rate differential between the U.S. and India in the previous period. Regression results indicate coefficients of a0 = .003; a1 = -.5; and a2 = .8. Assume that INFt - 1 = 2%. However, the interest rate differential is not known at the beginning of period t and must be estimated. You have developed the following probability distribution: The expected change in the Indian rupee in period t is: A) 3.40%. B) 0.40%. C) 3.10%. D) 1.70%. E) none of the above$ The expected change in the Indian rupee in period t is:
A) 3.40%.
B) 0.40%.
C) 3.10%.
D) 1.70%.
E) none of the above

Which of the Following Forecasting Techniques Would Best Represent the Sole

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