Question

PART 2 PURPOSE The purpose of this the skill to estimate a demand function using statistical software and interpret the findings. assignment is to provide the student with REQUIREMENT Household Manufacturing has collected the following data on quantity sold (Q). price (P), income (I), and advertising (A). Period Quantity, Q Price, P Income, Advertising, A 120 165 120 165 180 8.0 4.0 7.0 4.0 10.0 4.0 19 18 25 150 190 160 10.2 9.3 5.0 10 35 9.5 a Use the multiple regression package such as SPSS or other regression packages to estimate the inear relationship between quantity as the dependent variable and price, income, and advertising as independent variables. Write the linear equation that you find. 5 Marks b What is the coefficient of determination? Explain what it 2 Marksl c. Do the signs of the coefficients make economic sense? Which of the coefficients are significant? (alpha 0.025 df- 6, critical t-statistic- 2.447) 2 Marks d If Price-2.0, Income 35 and Advertising-9.5, what is the predicted quantity sold? 2 Marks] e. Find the price and income elasticities using the information above (d). Interpret the answers. 2 Marksl r. Explain how the above model can be used as a forecasting technique. Show how it is done. 12 Marksl Total: 15 Marks]

Answer 1

Answering only first four parts as per HomeworkLib policy

a) Now Reg^n eq^n Y rightarrow Q, X_1 = Price, X_2 = M, X_3 = A beta_0 beta_1 beta_2 beta_3 Y = 205.862 - 12.2 + 17 X_1 + 1.41400 X_2 - 3.3443 + X_3] b) R^2 = 9.728518676 times 10^-1 = .9728 Thus it implies that variation in dp, about 97.28% of variation in O/P can be explained by changes in prices, Income & advertising expenditure c) Now sign of price & Income is correct, but sign of A is wrong, as Advertising uparrow, the O/P sold (demanded) should rise. st. significance. d) Now P = 2, M = 35, A = 9.5, Then Y = 205.862 - 12.2417 times 2 + 1.414 times 35 - 3.3443 times 9.5 = 205.862 - 24.4834 + 49.49 - 31.77085 = 199.09775 almostequalto 199 \r\n c) Now from Results, t statistic of beta_1 = -8.79, t for beta_3 = -1.7077 t for beta_2 = 2.93, thus t_computed > t_critical, for beta_1 & beta_2, so, only coeff. of Advertisement is Insignificant