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Tabelle Abbildung 1 Aus der Forschung

Die Freigabekarte für gestaffelte Difference-in-Differences

Geben Sie das Estimand erst frei, wenn Kohorte, Zeit, Vergleich, Aggregation und Inferenz benannt sind.

FreigabefeldErforderliche EingabeZulässiger SatzAbbruchsignal
Kohorte und ZeitErstbehandlungsgruppe, Kalenderperiode, Ereigniszeit„Dies ist der Effekt für Kohorte g zur Zeit t.“Der Beitrag sagt nur „der Behandlungseffekt“.
VergleichNie behandelte oder noch nicht behandelte Gruppe mit Bedingungen„Dieser Vergleich liefert den benannten Kontrast.“Bereits behandelte Einheiten dienen still als Kontrolle.
Ergebnis und HorizontErgebniseinheit, Messfenster, Nachbehandlungshorizont„Das Ergebnis betrifft diese Einheit über diesen Horizont.“Das Ergebnis wechselt zwischen Abschnitten.
AggregationKohorten, Perioden und Gewichte des Gesamtwerts„Dieses Ergebnis beantwortet diese gewichtete Frage.“Die Zusammenfassung wird als natürlicher ATT gelesen.
Inferenz und SensitivitätZuweisungsebene, Unsicherheitsmethode, Trend- und Heterogenitätstests„Unsicherheit und Sensitivität wurden an dieser Grenze geprüft.“Ein Vortrendtest gilt als Beweis.

Bei breiten Tabellen horizontal wischen oder scrollen.

Zitieren Einbetten

Referenz & Evidenz

Quelle: Freigaberahmen des Autors, begründet mit Callaway und Sant'Anna (2021), Goodman-Bacon (2021), Roth et al. (2023) und Wooldridge (2023). Die Fragen sind synthetisch und enthalten keine Effektschätzung.

Jede Zeile ist eine geprüfte Aussage aus dem Prüfregister des Journals, beim Build aus dem Register aufgelöst. Das Register wird auf Englisch geführt.

  • A The parameter, named: "the disaggregated causal parameter that we call the group time average treatment effect i e the average treatment effect for group g at time t where a group is defined by the time period when units are first treated" Callaway & Sant'Anna. (2021) · CS21-C1
  • A Parallel trends is the identifying assumption: comparison groups "would have followed parallel paths over time which is the so called parallel trends assumption" Callaway & Sant'Anna. (2021) · CS21-C2
  • A The aggregation step and the inference are separate contributions, both the authors' own: "We also propose different aggregation" schemes that highlight treatment-effect heterogeneity, and they prove the validity "of a computationally convenient bootstrap procedure to conduct asymptotically valid simultaneous (instead of pointwise) inference" Callaway & Sant'Anna. (2021) · CS21-C3
  • A With variation in treatment timing, the two-way fixed-effects DD estimator is a weighted average of 2-by-2 comparisons, in the paper's own words: "This paper shows that the two-way fixed effects estimator equals a weighted average of all possible two-group/two-period DD estimators in the data" Goodman-Bacon. (2021) · GB21-C1
  • A The comparisons include already-treated units as controls, and the weights can go negative: "Some compare units treated at two different times, using the later-treated group as a control before its treatment begins and then the earlier-treated group as a control after" its treatment begins, so "TWFEDD estimates a variance-weighted average of treatment effect parameters sometimes with" negative weights, and "Negative weights only arise when average treatment effects vary over time" Goodman-Bacon. (2021) · GB21-C2
  • A A conventional two-way fixed-effects coefficient therefore need not equal a simple average treatment effect under staggered adoption: a causal reading of two-"way fixed effects DD estimates requires both a parallel trends assumption and treatment" "effects that are constant over time" Goodman-Bacon. (2021) · GB21-C3
  • A A synthesis with advice attached: "this paper synthesizes recent advances in the econometrics of difference in differences did and provides concrete recommendations for practitioners" Roth, Sant'Anna, Bilinski & Poe. (2023) · RSP23-C1
  • A TWFE is the baseline it complicates: the ATT "can be consistently estimated using a two way fixed effects twfe regression specification" under the canonical assumptions, and recent advances are classified as relaxing those Roth, Sant'Anna, Bilinski & Poe. (2023) · RSP23-C2
  • A The recommendation is to choose deliberately: the paper begins "by articulating a simple set of canonical assumptions under which the econometrics of did are well understood" and then relaxes them one at a time Roth, Sant'Anna, Bilinski & Poe. (2023) · RSP23-C3
  • A The paper develops simple nonlinear difference-in-differences strategies for panel data with staggered interventions and optional covariates: "I allow for general staggered interventions, with and without covariates" Wooldridge. (2023) · WOO23-C1
  • A Under an index version of parallel trends, cohort-by-time effects are identified: "Under an index version of parallel trends, I show that average treatment effects on the treated (ATTs) are identified for each cohort and calendar time period in which a cohort was subjected to the intervention" Wooldridge. (2023) · WOO23-C2
  • A The estimators extend familiar linear ideas but make the response specification a choice that has to be stated: "The pooled quasi-maximum likelihood estimators in the linear exponential family extend pooled ordinary least squares" Wooldridge. (2023) · WOO23-C3

Prüfgrade: A, gegen die gedruckte Seite der Primärquelle geprüft · B, Primärquelle, nur Textebene · C, belastbare Sekundärquelle · D, berichtet.

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