Order from us for quality, customized work in due time of your choice.
I have collected real data on the sale of a microwavable cup of soup across 20
d
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 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
The dataset is on Canvas and, using Excel or any other statistical software,
please answer the following questions:
1. Describe the patterns in the following variables: quantity sold,
price, average income, ads, price of a substitute, and population. Be
sure to include a table of descriptive statistics as well as important
scatterplots (along with a written summary of the information contained
in these visuals).
2. Take the natural log of the variables, and estimate the demand function
in log form. If you are unsure what the dependent variable is go back
to module 2 notes where we discuss a demand function (along with the
problem set for that module).
a. Interpret the R-square.
b. Interpret the coefficients for the independent variables – be
precise in your interpretations.
c. Interpret the p-values associated with each independent variable
3. 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? Explain fully.
4. How sensitive are our consumers to changes in price of the substitute?
Explain in detail.
5. Suppose we decide to charge a per ounce price of $2, while at the same
time our rival (P sub) charges a price of $2.15. Further, assume I =
30, A = 5, Pop = 100. What would you expect sales to be? How
confident are you in your forecast – provide a range of forecasts we
would expect to see. Explain fully.
6. If I increased from 30 to 33 with all else equal, what would the new
demand curve be? What would the new predicted Q sold be? How income
sensitive are consumers based on this work? Please use precise
calculations
7. 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:
Write this as a REPORT, not as a problem set where you are answering
individual questions. Have an introduction and a conclusion that are
not tied to any specific question above, and then label each section of
the body of the report to corresponding with the questions above. Keep
the ordering – do not answer question 6 before question 2 for example.
Do not turn in the dataset itself – I already know it.
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.
Finally, refer back to module 2 for insights about elasticity, demand
functions, and all the economic concepts. Module 3 – particularly the
concluding video – is particularly helpful for the econometrics,
especially estimating and interpreting a log regression.
I have attached a word doc that has my answers to each questions can you just turn my answers into a report.
Order from us for quality, customized work in due time of your choice.