This paper concentrates on the primary theme of USE THE DATA IN AIRFARE1.DTA FOR THIS QUESTION. CONSIDER THE FOLLOWING PANEL REGRESSION MODEL [1-1] in which you have to explain and evaluate its intricate aspects in detail. In addition to this, this paper has been reviewed and purchased by most of the students hence; it has been rated 4.8 points on the scale of 5 points. Besides, the price of this paper starts from £ 40. For more details and full access to the paper, please refer to the site.
Use the data in airfare1.dta for this question. Consider the following panel regression model
[1-1] log(fareit) =qt+b0+b1concenit+b2log(passenit)+b3log(disti)+b4[log(disti)]2+vi+eit,
where fareit is the average one-way fare, concenit measures market concentration (proxied by the market share of the biggest carrier), disti is the distance in miles and passenit denotes the average number of passengers per day. Note that qt means allowing for different year intercepts ( to 2000) and the unobserved effect vi contains characteristics of each of the 1149 flight routes.
- Report and interpret the RE estimation result on equation [1-1], being sure to include year dummies.
Name a couple of characteristics of a route (other than distance). Discuss if these characteristics might be correlated with concenit and/or passenit.
Report and interpret the FE estimation result on equation [1-1]. Compare the result with that obtained in (a). Perform the Hausman Test (FE vs. RE).
Report and interpret the Hausman-Taylor estimation result on equation [1-1], treating “log(passenit)” as the only endogenous variable in the regression.
Report and interpret the CRE estimation result on [1-1].