I have collected real data on the sale of a microwavable cup of soup across 20

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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.