Question: In Q_t = 1.2789 – 0.1647 in P_t + 0.5115 in I_t + 0.1483 in P’_t

(-2.14) (1.23) (0.55)

-0.0089T – 0.0961D_1t - 0.1570D_2t – 0.0097D_3t

(-3.36) (-3.74) (-6.03) (-0.37)

R² = 0.80 D – W = 2.08

Where Q_t = quantity (in pounds) of coffee consumed per capita (for population over 16 years of age) in quarter t

P_t = relative price of coffee per pound in quarter t, at 1967 prices

Y_t = per capital disposable personal income in quarter t, in thousand of 1967 dollars

P’_t = relative price of tea per quarter pound in quarter t, at 1967 prices

T = time trend, T = 1 for first quarter of 1963 to T = 58 for second quarter of 1977

D_1t = dummy variable equal to 1 for first quarter (spring) and 0 otherwise

D_2t = dummy variable equal to 1 for second quarter (summer) and 0 otherwise

D_3t = dummy variable equal to 1 for third quarter (fall) and 0 otherwise

The numbers in parentheses below the estimated coefficients are t statistics.

Using the above estimated regression equation for the seasonal demand for coffee in the US and predicting that the values of the independent or explanatory variables in the demand equation from the third quarter of 1977 to the second quarter of 1978 are those indicated in the following table, forecast the demand for coffee for

(a) The third quarter of 1977

(b) The fourth quarter of 1977 (forecast D_1t = D_2t = D_3t = 0)

(c) The first quarter of 1978

(d) The second quarter of 1978

(e) How much confidence can we have in these forecasts? What could cause the forecasting error to be very large?