Working With Econometrics Textbook Solutions: A Practical Guide
I spent about three hours last week going through an economics problem set that referenced Fair and Oster material, specifically around simultaneous equations and identification. The short version: most students looking for an Economics Case Fair Oster Answer Manual aren't actually getting what they need from what's out there. The search results are mostly filler. Here's what I've learned from actually working through these problems. Fair and Oster's contributions to econometrics center on supply-demand identification, particularly their work on the "Fair-Oster" method for testing whether supply and demand can be separately identified from observational data. Their 1980 Journal of Econometrics paper laid out conditions under which you can distinguish the two curves, and most intermediate econometrics courses that touch on this stuff want students to apply those conditions to real datasets. A decent answer manual for cases like this would walk through:
- The identification problem setup with proper notation
- How to determine whether the order and rank conditions are satisfied
- The actual estimation procedure once identification is confirmed
- Interpretation of the resulting coefficients in economic terms
- Common mistakes students make when applying the method
The Actual Problems People Struggle With
The first thing that trips people up is the distinction between the order condition and the rank condition. The order condition is necessary but not sufficient. You can have a model that passes the order condition and still fail identification because the rank condition isn't met. I see this come up constantly in office hours. Students check one box, call it done, and then their estimates come out backwards or nonsensical. The second issue is understanding what excluded instruments actually do. An instrument needs to be correlated with the endogenous regress
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