Market demand and supply
Q1 Table 1: Widgets and Gadgets
|
Price of Widgets ($)
|
10
|
20
|
30
|
40
|
50
|
|
Quantity of Widgets
|
5
|
4
|
3
|
2
|
1
|
|
Quantity of Widgets
|
1
|
2
|
3
|
4
|
5
|
|
Quantity of Gadgets
|
3
|
6
|
9
|
12
|
15
|
Refer to Table 1:
(1a.) Considering all prices, plot the market transactions for widgets.
( b.) What is the price elasticity of demand for widgets when the price goes up from $20 to $30? Briefly explain what will most likely happen to total revenue (in percentage terms) if a manager decides to increase price by 2 percent.
(c) Estimate the cross-price elasticity coefficient when the price of widgets falls from $40 to $30. What is the meaning of your elasticity coefficient?
Estimating a demand Function
Q2. A demand function is specified in terms of omitted variables and an inverse and linear relationship between quantity demanded and an endogenous variable, price. Suppose the average price is $4000 when omitted variables account for 6000 units, derive the total revenue function.
(b) Plot the marginal revenue, demand, and total revenue curves.
(c) What is the range of price change that is required to maximize total revenue?
(d) What is the marginal revenue, in monetary terms, when quantity changes by 1000 units?
Q3. Refer to the following regression results:
Dependent Variable: Quantity of sugar packets demanded
Method Ordinary Least Squares (double log)
Included observations 44
Adjusted R2 = 0.985
Coefficient Std. error
C 31.5
Price (sugar) - 0.73 0.08
Advertising Cost 0.12 0.06
Total cost 0.17 0.21
Income 0.22 0.02
Specify the regression model and interpret the regression coefficients (b) Explain why the variables are individually significant or insignificant. (c) Apart from the omitted variable bias, explain why the model has a significant structural weakness.