Question
Tommy runs a company named Wanderland Travel. He hired an econometrician to calculate various elasticities of demand. The econometrician calculated a value of -0.203 for
Tommy runs a company named Wanderland Travel. He hired an econometrician to calculate various elasticities of demand. The econometrician calculated a value of -0.203 for the price elasticity of demand, 0.0289 for the cross price elasticity of demand of Wanderland Travel Services to good Y, 3.613 for the income elasticity of demand of Wanderland Travel Services and 0.813 for the advertising elasticity of demand of Wanderland Travel Services.
a) Lets assume that the demand function has a linear form. Construct a linear model for the demand for Wanderlust Travel Services. Suppose variable X denotes Wanderlust Travel Services. Denote demand for Wanderlust Travel Services by Qx. Suppose Ax represents the amount of advertising spent on X, Px denotes the price of one unit of good X, PY denotes the price of one unit of good Y, M denotes income. First, write the model with the coefficients to be computed.
b) Suppose the price of good Wanderland Travel Service is $450, good Y sells for $40, the company utilizes 3,000 units of advertising, and consumer income is $20,000 and quantity demanded for Wanderland Travel Service is 5,535. Compute the coefficients of the linear model. Show your work.
c) Is the demand for Wanderland Travel Services is elastic or inelastic or perfectly elastic or perfectly inelastic or unit elastic? Why?
d) Based on your answer in c), do you expect Wanderland Travel Services to be a must good or necessity or luxury? Why?
e) If Frank decide to increase the price of the travel service, what will happen to his total revenue following this price increase? Why?
f) What are the most fundamental determinants of demand elasticity?
g) Do the customers have more choices in the short run or in the long run? Why?
h) Is monthly demand curve for Wanderland Travel Services different from the daily demand curve? If yes, what is the difference and what is the reason of the difference?
i) If Frank raises prices, is the expected quantity change lower in the short run demand curve or in the long run demand curve?
j) Which of the daily demand curve and the monthly demand curve for Wanderland Travel is steeper?
k) Can you compare the price elasticity of demand for Wanderland Travel Services with that of the Wanderland Train Travel Services? Which one do you expect to be more elastic and why?
l) How are Wanderland Travel Services and good Y are related? Are they substitutes or complements or unrelated?
m) Is the demand for Wanderland Travel Services normal good or inferior good? Why?
n) If Wanderland Travel Services increases the price by 10% and income of customers increase by 20%, find the total combined percentage change in the quantity demanded for Wanderland Travel Services
o) If Wanderland Travel Services increases the price by 10% and income of customers increase by 20%, find the new value of the quantity demanded for Wanderland Travel Services
p) When we use a linear function for demand, we get the same increase in demand by cutting the price in half (Ex: from 4 to 2), or if from half price we give the product away for free (Ex: from 2 to 0). A more reasonable model may be a power function (non-linear) where decreasing the price by a fixed percentage increases consumption by a fixed percentage. Construct a nonlinear model (log-linear) for the demand for Wanderlust Travel Services. Suppose variable X denotes Wanderlust Travel Services. Denote demand for Wanderlust Travel Services by Qx. Suppose Ax represents the amount of advertising spent on X, Px denotes the price of one unit of good X, PY denotes the price of one unit of good Y, M denotes income. First, write the model with the coefficients to be computed.
q) Suppose the price of good Wanderland Travel Service is $4500, good Y sells for $4, the company utilizes 300 units of advertising, and consumer income is $200 and quantity demanded for Wanderland Travel Service is 6 billion. Compute the coefficients of the loglinear model
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