2 y is millions of boxes per year, Px and Py are dollars per box, Ps is dollars

Question

2 y is millions of boxes per year, Px and Py are dollars per box, Ps is dollars per quart, and A per year. A. You are told that this year, Px = $2, l = S4, PY = $2.50, PM-31, and A $2. Calculate sales (0x) for this year B. Estimate sales for next year given that Px is reduced by 10 percent, I rises by 5 percent, Py is reduced by 10 percent, PM remains unchanged, and A is increased by 20 percent. The ensticities are Ep, E1.5, Exy 0.5, Ex-0.75 and EA-0.5. 5 Here are the results of the regression of the quantity demanded of product X (Qx) on its own price (P), consumer income (Y) and the price of a complementary good (Pz) Qx 121.86-9.50Px + 0.04Y-2.21Pz (-5.12) (2.18) (0.68) N-20 R2 09633 F-167.33 The numbers in parentheses are t-statistics. Evaluate the results (A) in terms of the signs and values of the coefficients, (B) for the statistical significance of the coefficients, and (C) the explanatory power of the regression. This assignment is due in class on Tuesday, January 30.

Explanation / Answer

5)

A) The demand is negatively related to its own price Px. The coefficient implies if the price of good x increases by one dollar then demand on average will fall by 9.50units.

The demand is positively related to income this implies that the good is a normal good. The coefficient tells that if the income increases by one dollar then the demand will increase by 0.04 units.

The demand is negatively related to the price of complementary goods. This implies that if the price of complementary goods increases then the demand for good x will decrease . the coefficient tells if the price of good z increase by 1 dollar then demand will fall by 2.21 units.

B) The coefficient for Px and Y are statistically significant but for Pz is not statistically significant as the t- value is very small for Pz and sufficiently large for Px and Y.

C) The R-square tells that the independent variables explains 96.33% of the variation in dependent variable i.e. the demand for good x. thus is also the power of the regression.

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