2- Demand Estimation

Project

Demand estimation
Q=f (price, income)
Linear Specification
Q=α+β_1 P+β_2 I
α=intercept
β_1=price coefficient
β_2=income coefficient

Using the data provided to you in excel file, estimate the demand equation or specification provided above. The data consists of the quantity and price (per case) of Fanta (soft drink) sold in each state, as well as the average income (in thousands of dollars) of consumers living in various regions of each state. Please note there are multiple tabs at the bottom of the spreadsheet, each refers to one of the seven states selling the Fanta.

Assuming that the underlying demand relation is a linear function of price and income, use your spreadsheet program to obtain least squares estimates of one of the state’s demand for Fanta.

Based on your results or output, complete the following questions.

Copy and paste the regression result here.
Write the estimated equation consistent with the specification given above

Q=__________+______P+________I

What is the R-square value? What does it show?
Are all the estimated equations significant?
What will happen to the quantity demanded for Fanta if its price goes up by $1?
What will happen to the demand for Fanta if the income of a consumer goes up by $100?

Q#2 If the goal is to reduce the total demand for residential heating fuel in your state. You must choose one of three legislative proposals designed to accomplish this goal:
(a) a tax that would effectively increase the price of residential heating fuel by $1;
(b) a subsidy that would effectively reduce the price of natural gas by $3; or
(c) a tax that would effectively increase the price of electricity (produced by hydroelectric facilities) by $4.

To assist you in your decision, you estimated the demand for residential heating fuel using a linear demand specification. The regression results are presented below.

SUMMARY OUTPUT

Regression Statistics
Multiple R 0.76
R Square 0.57
Adjusted R Square 0.49
Standard Error 47.13
Observations 25

Analysis of Variance
Degrees of Freedom Sum of Squares Mean Square F Significance F
Regression 4 60936.56 15234.14 6.86 0.03
Residual 20 44431.27 2221.56
Total 24 105367.84

Coefficients Standard Error t Stat P-value Lower 95% Upper 95%
Intercept 136.96 43.46 3.15 0.01 50.60 223.32
Price of
Residential Heating Fuel -91.69 29.09 -3.15 0.01 -149.49 -33.89
Price of Natural Gas 43.88 9.17 4.79 0.00 25.66 62.10
Price of Electricity -11.92 8.35 -1.43 0.17 -28.51 4.67
Income -0.05 0.350 -0.14 0.90 -0.75 0.65

Based on this information, which proposal would you favor? Show your work and explain

1. A tax that would effectively increase the price of residential heating fuel by $1.

2. A subsidy that would effectively reduce the price of natural gas by $3.
3. A tax that would effectively increase the price of electricity by $4.