I have collected real data on the sale of a microwavable cup of soup across 20 different cities for the same time period (a month). The variables in the dataset (also attached) are:
Quantity sold in the city for that month: Measured in thousands of units
Price: measured in dollars
Average Income in the city: Measured in thousands of dollars
Ads: Average number of ads run in stores for that city during that month.
Price of a substitute product: measured in dollars
Population of the city: measured in thousands of people
Using Excel or any other statistical software, please answer the following questions:
- Describe the patterns in quantity sold and own and rival prices during this time period using basic descriptive statistics. Graphs are welcome as well.
- Take the logs of the variables, and estimate the demand function.
- Interpret the R-square.
- Interpret the coefficients for logP and logPsub
- Interpret the p-values associated with each independent variable
- Are consumers price sensitive? Why or why not? (be as precise as you can – you have estimates!). Does this price sensitivity make sense given the good we are examining?
- How sensitive are our consumers to changes in the rival good’s price? Explain in detail.
- Suppose we decide to charge a per ounce price of $2, while at the same time our rival charges a price of $2.15. All else equal, what would you expect sales to be? How confident are you in your forecast?
- Suppose we are charging a price of $2 and our current marginal cost is $1.50 Are we maximizing profits at this price? If not, should we raise or lower price? Why?
A few notes:
- Try to produce a polished report: have well labeled and presented graphs and tables, and refer to them in your answers.
- Be sure to answer all aspects of the questions – do not leave parts unanswered.
Cup Of Soup