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)

R ² = 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

1. The third quarter of 1977
2. The fourth quarter of 1977 (forecast D _1t = D _2t = D _3t = 0)
3. The first quarter of 1978
4. The second quarter of 1978
5. How much confidence can we have in these forecasts? What could cause the forecasting error to be very large?

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