1.How many observations are used in this regression? Is this different from the

Question

1.How many observations are used in this regression? Is this different from the number of
observations used in Exhibit D? If yes, why do you think this is the case?

2.Ceteris paribus, on average, if a route has one more direct rivals, what is the expected
difference in business class fares? Compare this number to the expected difference in economy
class fares under the same situation. [Hint: using just Exhibit E may not be enough to answer this
question. Look elsewhere, utilize what Carly inspires you.]

3.Obviously, the authors of this paper has done a lot more regressions and analyses. What
are some factors, in your opinion, that may also affect prices of tickets? Please list three of those.
For each one, illustrate how that variable may affect prices, and give some ideas on the possible
sign for that particular coefficient.

3,144 217.04 0.0000 0.0646 Adj R-squared0.0643 444.33 Source df MS Number of obs F (1, 3142) 1 42849947.5 Prob >F 42849947.5 620314200 Model Residual 3,142 197426.544 R-squared Total 663164147 3,143 210997.183 Root MSE biz fare Coef. Std. Err (95% Conf. Interval] -168.7618 11.45518 -14.73 0.000 69.72 0.000 num_car_dir 191.2222 -146.3015 1088.258 cons 1058.491 15.1813 1028.725

Explanation / Answer

1)

from the table clearly no of observations is 3144

2)

with one unit increase in numne rof direct rivals, the business class fare reduces by 168.76

there will be a similar drop however the amout will be <168 as there is not so much margin on economy compared to business class

3)

other variables can be

a)price of oil as pirice of oil increases fare should increase

b) season of booking in rush season flights will be expensive

c) day of the week flights will cost more on weekends

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