ECON 3020

ECON 3020

Rent-A-Car Project Datasets and description for the case assignments: http://www.washburn.edu/sobu/dnizovtsev/RentacarCase.html 1. Estimate the demand for â
€œeconomy” vehicles using variables provided, you might also derive data from other resources and combine with the dataset. Choose the best model. 2. Forecast the
demand for the “economy” vehicles in Week 30. 3. Our customers who choose to keep a car for an extra day are currently paying the same base daily rate. Do you
see any potential in exploring alternative schemes? If so, what changes should we implement-shall we change the price for extra days? What considerations are involved
in this decision? Provide your thoughts on this issue. 4. What other issues or news you would pay attention to adjust your price and managerial strategies?
Reference: Chulkov, D. and Nizovtsev, D. 2012. “Rent-A-Car: an integrated team-based case study for managerial economics” , 2013 ASSA Annual Meeting, San Diego, CA,
Paper 2013-454.2995
Project: Demand estimation model selection guidelines
1. Find a model with adjusted R-squared above 0.7
2. Coefficient for PownE should be negative and significant (|t|>2)
3. At least half of the coefficients should bear the correct signs (you should be able to explain the signs) and be statistically significant (|t|>2)
Please note if any of the three criteria is not met, one point will be taken off. Totally 4 points could be awarded to the demand estimation part.
Rent-A-Car: Description of the variables in the data set

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 vehicles in a given week
Pcomp Average daily rate of the only competitor across all vehicle categories
Session Binary variable with 1 indicating weeks when college is in session
Weather Number of days in a week with severe weather
Unemployment Number of unemployed workers in the county as of Tuesday each week
FlghtWk Number of flights (in- and outbound) serving the local airport that week
CancWk Total number of flights cancelled that week
Holiday Binary variable with 1 indicating weeks of national holidays (long weekends)
Wrecks Number of major accidents that week
Discount Number of customers in a given week using the 15 percent discount off the base rate offered through our affiliate partner, a credit card company
Upgrade Number of customers who received a free upgrade to a luxury vehicle due to the unavailability of economy vehicles
TotalAd Amount spent on local advertising each week
AdBlbd Weekly spending on billboard ads
AdPaper Weekly spending on ads in local newspapers, including the online version
AdTV Weekly spending on ads placed with local TV
QE Number of rental contracts initiated each week in the economy category
Q_length Number of paid days of rentals, grouped by the agreement starting date
Age<25 Number of rental agreements in a given week for which the person listed as the primary driver on the rental agreement was less than 25 years old
Age25_50 Number of rental agreements for which the person listed as the primary driver on the rental agreement was between 25 and 50 years of age
Age51+ Number of rental agreements in a given week for which the person listed as the primary driver on the rental agreement was 51 years of age or older
FleetAge Average age of our fleet measured in weeks
BedTax Amounts collected from the 1% local hospitality tax in the county – this information is reported only on a monthly basis

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