Timeline for Data Setup for Differences-in-Differences
Current License: CC BY-SA 3.0
7 events
| when toggle format | what | by | license | comment | |
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| S Apr 5, 2017 at 11:44 | history | suggested | Nick | CC BY-SA 3.0 |
fixed link
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| Apr 5, 2017 at 11:44 | review | Suggested edits | |||
| S Apr 5, 2017 at 11:44 | |||||
| Jan 31, 2014 at 13:33 | history | edited | Andy | CC BY-SA 3.0 |
added 1 characters in body
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| Dec 21, 2013 at 14:29 | comment | added | Andy | Yes, for the first data type you need more and strong assumptions. For the standard errors, the Newey West correction should work. Actually it's analogous to one of the correction methods proposed by Bertrand et al. (they use clustered standard errors). A more recent method uses the bootstrap which works pretty well (see rbnz.govt.nz/research_and_publications/seminars_and_workshops/…). Hope this helps! | |
| Dec 21, 2013 at 14:01 | vote | accept | B_Miner | ||
| Dec 21, 2013 at 13:58 | comment | added | B_Miner | This is great Andy! Can I summarize by saying that both data setups are acceptable but that panel data is the easier to make an argument about the assumptions? That both can be fit by OLS but that the standard errors of (especially the panel data setup I presume) are questionable due to possible serial correlation. Would a panel setup with Newey West SE be a good solution? | |
| Dec 21, 2013 at 7:15 | history | answered | Andy | CC BY-SA 3.0 |