Interpreting pre-trends as anticipation: Impact on estimated treatment effects from tort reform
By Anup Malani, J. Reif. 2015
150 citations recorded by the source corpus.
Subfields: Economics and Econometrics, Pharmacy
View Paper: https://www.semanticscholar.org/paper/914ec60209d578f5801d9d639b9e996d532130c8
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In Economics and Econometrics
- Jonathan Roth
- Liyang Sun
- S. Abraham
- Pedro H. C. Sant’Anna
- Bernard S. Black
- V. Atanasov
- T. Deryugina
- Alexander Mackay
In Pharmacy
Citations in the corpus
- The Long-Run Dynamics of Electricity Demand: Evidence from Municipal Aggregation (2020, background): “Failing to account for anticipation effects in a difference-in-differences framework can lead to biased treatment effect estimates when consumers are forward-looking (Malani and Reif, 2015).”
- Estimating dynamic treatment effects in event studies with heterogeneous treatment effects (2018, background): “.e. E»Ye i;e+‘ Y 1 i;e+‘ jE i = e…=0 for all e 2supp„E i”and all ‘<0. Assumption 2 requires potential outcomes in any ‘periods before treatment to be equal to the baseline outcome on average as in Malani and Reif (2015) and Botosaru and Gutierrez (2018). This is most plausible if the full treatme”
- Shock-Based Causal Inference in Corporate Finance and Accounting Research (2015, background): “82See, for example, Morck et al. (2011) (“If we use the popular instrumental variables legal origin, latitude, and major religion to estimate exogenous components of our bank control measures, and use these to re-estimate the tables in second stage regressions, we obtain qualitatively similar result”
- Anticipation, Tax Avoidance, and the Price Elasticity of Gasoline Demand (2015, unknown): “For example, Malani and Reif (2015) use a similar single‐equation IV approach to model tort reforms not targeted at physicians, but likely anticipated by them.”
- The Impact of Price Caps and Spending Cuts on U.S. Postsecondary Attainment (2017, unknown): “Since pre-trends can be interpreted as evidence of anticipation effects (e.g. Malani and Reif 2015), one possible concern is that students may time enrollment decisions in response to anticipated price changes.”
- Efficient Estimation for Staggered Rollout Designs (2021, background): “This assumption is plausible in many contexts but may be violated if individuals learn of treatment status beforehand and adjust their behavior in anticipation (Abbring and van den Berg 2003; Lechner 2010; Malani and Reif 2015).”
- What’s trending in difference-in-differences? A synthesis of the recent econometrics literature (2022, unknown): “This is important for identification of τ 2 , since otherwise the changes in the outcome for the treated group between period 1 and 2 could reflect not just the causal effect in period t = 2 but also the anticipatory effect in period t = 1 (Abbring and van den Berg, 2003; Malani and Reif, 2015).”