Exam Two Economics 414:

Exam Two Economics 414: Open book, open note, no help from others. Version “A”
Using demand function: Q_a=200-10P_a+2P_b-6P_c-0.0005I where P_a,P_(b,) P_c are product prices and I is household income with current market conditions set to P_a=$10.00, P_b=$8.00, P_c=$6, and I=$40,000. Please do the following:

Calculate the own price elasticity for product “a” and interpret the result?

Calculate the cross price elasticity for product “c” to product “a” and interpret the result?

Calculate the Income elasticity of product “a”

Use excel to create a dynamic elasticity table from a demand formula and test it using a specific P_a to Q_a combinations.

You have a child with two sources of entertainment “video games” (vg) and “television” (tv). Using the equation 〖MU〗_vg/P_vg =〖MU〗_tv/P_tv , currently in equilibrium.
Explain, using consumer utility theory, how this child maximized entertainment satisfaction.

Now suppose the price of “video games” increases, how should the child respond to maintain entertainment equilibrium. Only a through explanation will yield full credit.

Find below regression output for a demand equation where “P” is own price “Pa” and “Pb” prices of potentially related goods and “I” is income.

Which variables are statistically different from zero? Why?

How about the overall goodness of fix?

Write the “all else equal” demand equation when, “Pa=$2”, “Pb=$8.70”, and “I=$50”.

Using the equation, you derived in part “c”, what is the own price elasticity of demand when price is P=$9.00.

Knowing the elasticity calculated in part “d” above, how might you maximize total revenue using “P”?

SUMMARY OUTPUT

Regression Statistics
Multiple R 0.98
R Square 0.97
Adjusted R Square 0.94
Standard Error 3.50
Observations 10.00

ANOVA
df SS MS F Significance F
Regression 4 1705.1 426.27 34.77 0.00077
Residual 5 61.3 12.26
Total 9 1766.4

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0%
Intercept 165.39 55.42 2.98 0.03 22.93 307.86 22.93 307.86
P -3.81 1.85 -2.06 0.09 -8.56 0.95 -8.56 0.95
Pa -4.54 11.81 -0.38 0.72 -34.90 25.83 -34.90 25.83
Pb -1.56 0.70 -2.24 0.08 -3.36 0.23 -3.36 0.23
I 0.0036 0.90 0.00 1.00 -2.31 2.31 -2.31 2.3

Complete this question in excel and email me your answer. Using the time series data below calculate the 13th month forecast with excel for each of the methods below:
A three month moving average
A three month weighted moving average using weights 0.5, 0.3 and 0.2
Exponential Smoothing using alpha of 0.4
Regression
Month Sales
1 133
2 155
3 165
4 171
5 194
6 231
7 274
8 312
9 313
10 333
11 343
12 350

Which of the four methods best forecast Sales?

Manages regularly face the choice of increasing advertising expense or reducing price to improve profit.
Suppose you have the following information.
Current product price equal $24.00
Current sales level equal 30,000 units
The advertising department expects the next $20,000 in ad spend should increase sales by 1,000 units to 31,000 while maintaining the current price of $24.00.
The finance department predicts dropping the price by $2.00 will increase sales by 3,000 to 33,000 units next year.

Which action should you take next year (increase advertising or drop price)? Show your work and explain your answer

Explain the basic difference in each choice with respect to the theory of consumer demand (the demand curve).