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Interpreting pre-trends as anticipation: Impact on estimated treatment effects from tort reform
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“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).”
From What's trending in difference-in-differences? A synthesis of the recent econometrics literature (2023) · cites this paper as Malani and Reif, 2015
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“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).”
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“.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 treatment paths are not kn…”
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Deming, D., & Walters, C. (2017) · doi:10.3386/w23736 · Cited by 181
“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.”
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“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).”
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“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).”
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“Slemrod, 1995; Scholes, Wilson, and Wolfson, 1992), tort reform (Malani and Reif, 2014), and welfare reform in the UK (Blundell, Francesconi, and van der Klaauw, 2010).”
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“The announcement’s effect on viewers’ behaviors tends to be transient, and we assume that it subsides when the promotion is in use (Malani and Reif, 2015).”
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“Malani and Reif (2015) explain that such pre-trends should not discard the analysis as these could be seen as policy anticipation effects that arise naturally out of many theoretical models.”
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“…in the specification to test whether there are differential effects prior to policy changes.23 In the absence of anticipation effects (Alpert 2016; Malani and Reif 2015), meaningful and statistically significant relationships between policy leads and the outcome suggest that the empirical…”
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“These are the same biases that can affect most controlled before-after studies, including: 1) impacts on pre-intervention outcomes due to the anticipation of the intervention before the intervention is officially implemented (34); 2) impacts on control regions (35) (i.”
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“…assumption’ (that people hold unbiased expectations given the information available), but it is not appealing because of the a priori parameter restrictions which must be imposed in order to structure estimation, such as exponential discounting or ‘quasi-myopia’ (see Malani and Reif 2015).”
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“As Anup and Reif (2015) discuss, one should not automatically attribute pretrends to endogeneity, as not allowing for anticipation effects can also lead to an underestimation of the (total) treatment effect of interest.”
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“Alternatively, anticipation could occur on the basis of uncertain future treatments, 16 as in Malani and Reif (2015).”
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“This may be due to an anticipatory effect where the expectation of treatment results in behavior changes related to the treatment target (Malani & Reif, 2015).”
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“In addition, the anticipation of the policy change may affect the trend and bias the estimates (Malani and Reif 2015).”
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“Anticipatory effects may exist when individuals are forward-looking, get access to information on future treatments and there is a benefit to taking actions ahead of a treatment (Malani & Reif 2015).”
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“As discussed in Malani and Reif (2015), two effects are taken into account in the context of anticipation, including the ex-post effect and the ex-ante effect.”
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“This assumption of the DID method states that if the intervention did not exist, the time trajectory of the outcome variable should be parallel between the treated and control groups [45].”
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Metadata
- Authors
- Malani, A., & Reif, J.
- Affiliations
- University of Illinois Urbana-Champaign (US)
- Corresponding author
- Reif, Julian
- Venue
- Journal of Public Economics
- Publisher
- Elsevier BV
- Published
- 2015-04
- Volume
- 124
- Pages
- 1-17
- ISSN
- 0047-2727 (ISSN-L)
- OpenAlex
- W2075162239
- Cited by
- 178
- References
- 57
- Citations by year
- 2026: 26 · 2025: 16 · 2024: 17 · 2023: 21 · 2022: 19 · 2021: 19 · 2020: 12 · 2019: 3 · 2018: 18 · 2017: 8 · 2016: 13 · 2015: 3
- FWCI
- 12.46
- Type
- journal article
- Language
- en
- Open access
- green
- autopapers.ssrn.com
- Locations
- Journal of Public Economics (publishedVersion)
- bepress Legal Repository (submittedVersion)
- SSRN Electronic Journal (submittedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Law, Economics, and Judicial Systems
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Healthcare Policy and Management
- Keywords
- anticipation effects, endogeneity, treatment effects, tort reform, physician supply, instrumental variables, physician expectations, medical malpractice liability
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