Question 1- In a study of the determinants of direct airfares to Cleveland, Paul W. Bauer and Thomas J. Zlatoper obtained the following regression results (in tabular form) to explain one-way airfare for first class, coach, and discount airfares. (The dependent variable is one-way airfare in dollars).
The explanatory variables are defined as follows:
Carriers = the number of carriers
Pass = the total number of passengers flown on route (all carriers)
Miles = the mileage from the origin city to Cleveland
Pop = the population of the origin city
Inc = per capita income of the origin city
Corp = the proxy for potential business traffic from the origin city
Slot = the dummy variable equaling 1 if the origin city has a slot-restricted airport
= 0 if otherwise
Stop = the number of on-flight stops
Meal = the dummy variable equaling 1 if a meal is served
= 0 if otherwise
Hub = the dummy variable equaling 1 if the origin city has a hub airline
= 0 if otherwise
EA = the dummy variable equaling 1 if the carrier is Eastern Airlines
= 0 if otherwise
CO = the dummy variable equaling 1 if the carrier is Continental Airlines
= 0 if otherwise
The results are given in Table 6-11.
a. What is the rationale for introducing both carriers and squared carriers as explanatory variables in the model? What does the negative sign for carriers and the positive sign for carriers squared suggest?
b. As in part (a), what is the rationale for the introduction of miles and squared miles as explanatory variables? Do the observed signs of these variables make economic sense?
Question 2-Table 6-12 on the textbook's Web site gives nonseasonally adjusted quarterly data on the retail sales of hobby, toy, and game stores (in millions) for the period 1992: I to 2008: II.
Consider the following model:
Salest = B1 + B2D2t + B3D3t + B4D4t + ut
where D2 =1 in the second quarter, = 0 if otherwise
D3 =1 in the third quarter, = 0 if otherwise
D4 =1 in the fourth quarter, = 0 if otherwise
a. Estimate the preceding regression.
b. What is the interpretation of the various coefficients?
c. Give a logical reason for why the results are this way.
d. How would you use the estimated regression to deseasonalize the data?
Question 3 -Use the data of question 2 but estimate the following model:
Salest = B1D1t + B2D2t + B3D3t + B4D4t + ut
In this model there is a dummy assigned to each quarter.
a. How does this model differ from the one given in question 2?
b. To estimate this model, will you have to use a regression program that suppresses the intercept term? In other words, will you have to run a regression through the origin?
c. Compare the results of this model with the previous one and determine which model you prefer and why.
Attachment:- Tables.rar