Problem - There is quarterly information from 2010 to 2013 about the FlyingHigh (FH) airline.

This data is reported in the following table:

Where: QD is the average number of seats in economy class in FH; PFH is the average price (in US dollars) of the seat in economy class of FH; PR is the average price (in US Dollars) of the seat in the economic class of the competitor closest; and, M is the income level (in thousands of American dollars) of the region where FH operates and its main competitor. According to this:

1- Show the correlations between QD, PFH, PR, and, M. Relief the signs of the correlations that has QD with the rest of variables. According to economic theory have, Did you sense these signs?

Convert the data into logarithms and run the following specification:

Ln(QD)_t = a + b * Ln(PFH)_t + c * Ln(PR)_t + d * Ln(M)_t + error_t

 Expected signs b < 0 by the demand law and c > 0. a is the intercept, and, t: 1, 2, 3, .... , 16.

2- With Minimum Ordinary Squares (MCO), using Excel (Data Analysis Regression), run the regression of the previous specification and show the estimates of a, b, c, y,d. Present a summary of your "outcome"

3- Indicate if the estimates have the expected signs. Use the definitions of elasticities?

4- Indicate if the estimates are statistically significant at 0.1%, 1%, 5% or 10%.

5- Interpret the coefficient of determination (R-squared) and the test F.

6- How does QD change, if PFH goes up by 10%? Is FH an inelastic good? Explain. Is it a good decision to raise the price?

7- How does QD change, if PR drops by 11%?

8- How does QD change, if M goes up by 5%?