Edward Norton
@healtheconnort1
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Health economist and Professor at the University of Michigan.
Joined October 2018
RT @AndrewMIbrahim: We’re always trying to push new methods that are more efficient and robust. Today, @UMichCHOPFellow we took a deep dive…
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Participants will also have the chance to engage with faculty and current students.
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RT @BradyJPost: He gave the coup de grace to odds ratios and now he's FLEXing on the diff in diff lit. @healtheconnort1 feeling buff in 2024
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RT @AndrewMIbrahim: Cider donuts and propensity score matching! #FallinAnnArbor Every two weeks our analyst meet to learn new methods and…
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RT @jmwooldridge: @hagertynw @healtheconnort1 No, we're not restricting individual-level heterogeneity. We're making a conditional parallel…
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RT @jmwooldridge: @hagertynw @healtheconnort1 Our assumptions are stated in terms of a population. If you put an i subscript on everything,…
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Here is the link to the Dropbox where you can download the Stata code and data sets. @jmwooldridge
Our approach is simple and transparent. It is easy to know how identification is achieved, which treatment obs. are compared to which control obs., and how many parameters are estimated. We call it FLEX: it is a flexible linear model estimated by OLS with covariates (X).
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Our approach is simple and transparent. It is easy to know how identification is achieved, which treatment obs. are compared to which control obs., and how many parameters are estimated. We call it FLEX: it is a flexible linear model estimated by OLS with covariates (X).
Furthermore, our FLEX estimates are identical to those from the Borusyak et al. (2024) imputation estimator extended to the case that allows for treatment-effect heterogeneity by group and time (not simply cohort and time). @jmwooldridge
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Furthermore, our FLEX estimates are identical to those from the Borusyak et al. (2024) imputation estimator extended to the case that allows for treatment-effect heterogeneity by group and time (not simply cohort and time). @jmwooldridge
We prove that FLEX treatment effect parameter estimates are asymptotically unbiased estimates of the group-time heterogeneous treatment effects that can be obtained in the repeated cross-section setting by an imputation method. @jmwooldridge
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We prove that FLEX treatment effect parameter estimates are asymptotically unbiased estimates of the group-time heterogeneous treatment effects that can be obtained in the repeated cross-section setting by an imputation method. @jmwooldridge
Our theoretical contribution: a linear-in parameters regression specification with flexible functional form with group by-time treatment effects, two-way fixed effects, and interaction terms yields consistent estimates of heterogeneous treatment effects under general conditions.
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Our theoretical contribution: a linear-in parameters regression specification with flexible functional form with group by-time treatment effects, two-way fixed effects, and interaction terms yields consistent estimates of heterogeneous treatment effects under general conditions.
Estimating treatment effects in difference-in-differences designs in which the treatment start is staggered over time and effects are heterogeneous by group, time, and covariates, and when the data are repeated cross-sections, from Partha Deb, @healtheconnort1, Jeffrey M. Wooldridge, and Jeffrey E. Zabel
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Partha Deb, Jeff Wooldridge @jmwooldridge , Jeff Zabel, and I are pleased that our new difference-in-differences paper is available as an NBER working paper.
Estimating treatment effects in difference-in-differences designs in which the treatment start is staggered over time and effects are heterogeneous by group, time, and covariates, and when the data are repeated cross-sections, from Partha Deb, @healtheconnort1, Jeffrey M. Wooldridge, and Jeffrey E. Zabel
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RT @AndrewMIbrahim: When to apply robust standard errors vs vce cluster? Great discussion at CHOP Data and Donuts 📊 🍩 🙏 Dr. @healtheconnor…
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RT @JAMAHealthForum: Price reductions from Oregon’s hospital payment caps are associated with reduced enrollee out-of-pocket spending at th…
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"Requiem for Odds Ratios" in @hsr_hret by @healtheconnort1, Bryan Dowd, @GarridoMelissa, and Matt Maciejewski.
My new blog post, An Odds Ratio Paradox, in which I introduce the paradox and don't solve it:
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Their name is Mud
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RT @JournalofLTC: Did Avoiding Post-Acute Skilled Nursing Facility Care During the COVID-19 Pandemic Save Lives? 🦠 In our latest article,…
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