ASSIGNMENT- Jordan
a. Carry out a multiple regression using linear specification, with quantity as the dependent (left-hand side) variable and own price, other good's price, income, and temperature as explanatory (right-hand side) variables.
b. How do the estimated own-price coefficients compare to those estimated previously without other variables included? Has the statistical significance changed for either good? What is the R-squared?
c. The summer is fast approaching, and experts are disagreeing over how hot the summer is going to be. Some are forecasting an unusually hot summer, with average high temperatures predicted to reach 90 degrees in July. Others are predicting an unusually cool summer, with an average high temp in July of only 78. The owners of iScream would like to know how this difference in possible temperatures will affect their sales. At the averages of all other variables, use the regression estimates to predict the number of units sold in a month of each good under two scenarios: 1) the monthly high averages 90 degrees; 2) the monthly high averages 78 degrees. Note that because the data are in monthly sales by region (of which there are 8), you'll need to multiply the number of units predicted from the regression equation by 8 in order to get total predicted units sold in a month.
d. Calculate the (own-price) elasticities at the average quantities again using the coefficient estimates. The owners of iScream are interested in knowing what would happen to revenue from their original ice cream cones if they increase its price slightly from the average price of the good in the data (holding everything else constant). Based on the estimated elasticity, would revenue increase, decrease, or stay about the same? Similarly, they are interested in knowing how revenue from their organic product would change if they were to increase its price slightly from the average (holding everything else constant). Would revenue increase, decrease, or stay about the same?
e. Are the goods normal or inferior goods? Calculate the income elasticity of demand for both goods, at the average income and quantity in the dataset.
f. Are the goods substitutes or complements? For which good are sales more sensitive to the other good's price? Calculate the cross-price elasticities at the average price and quantity. Interpret these elasticities.
Attachment:- Iscream-Data-2018.rar