You are tasked with estimating Rent-a-Car's demand function and intend to examine two separate measures: QE (number of economy class contracts initiated each week) and Contract_length (average length of the contracts initiated in each week). You have data on eleven potentially relevant explanatory variables:

PownE- Average daily rate Rent-a-Car charged for its economy cars in a given week

PownL Average daily rate Rent-a-Car charged for its luxury cars in a given week

Pcomp Average daily rate of the only competitor across all vehicle categories

Session Indicator for if college is in session

Weather Number of days in a week with severe weather

Unempl Number of unemployed workers in a county as of Tuesday each week

FlghtWk Number of flights (in and out) serving the local airport that week

CancWk Number of departing flights cancelled that week

Holiday Indicator for whether the week contained a holiday (long weekend)

TotalAd Amount spent on local advertising each week

BedTax Amount collected from the 1% local hospitality tax in the county (reported on a monthly basis)

Estimate two separate regressions in Excel. For the first one, include QE as the dependent variable. For the second one, include Contract_length as the dependent variable. Include all 11 potential explanatory variables. You might consider first predicting what sign you expect these variables to take. (1) How many economy class contracts can Rent-a-Car expect to receive in an average week? What will be the average length of the contract? (2) Is the demand for rental cars elastic or inelastic at the average price? How can you tell? What does this suggest Rent-a-Car should do? (3) How are Rent-a-Car's economy and luxury cars related? What about Rent-a-Car's economy cars and the competitor's cars? (4) Re-estimate the regression equations without accounting for advertising and local taxation. How has demand changed?