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- What question do the authors claim they are addressing?
- Why? Is it an interesting question?
- What’s new about this question? Does it use theory that extends beyond what we have studied?
empirical methodology – read but skip the really technical stuff
- look at Table III Summary Statistics
- big data set?
- lots of “control” variables?
- what can’t they “observe” (important but not in their data)
- Difference-in-differences? look at two groups before and after some change
- Dummy variables? Shareit = αi + β0 1[Post]t … indicates a yes/no variable coded as 0 or 1.
- scan initial sentences in sections that appear unduly technical
- example: read only the first sentence of “Section VII: Robustness Checks” (which includes Table XI that at first glance is part of the “Section VIII: Conclusion”)
What do the authors claim they find?
Does their analysis really lend itself to their conclusion
What do they leave out? what qualifications do they make? etc. Do they believe their conclusion?
- count the asterisks!
- graphs: two groups and before/after. can you eyeball?
- with lots of ups/downs, letting the computer “see” for you is surely more reliable? or do you see what the computer sees?