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Bayes-féle Panel Eseménytanulmány×A különbség-különbségek (Diff-in-Diff) módszer×
TudományterületOksági következtetésÖkonometria
MódszercsaládRegression modelRegression model
Keletkezés éve2010s–2020s1994
MegalkotóDeveloped from panel event-study literature (Sun & Abraham 2021; Freyaldenhoven et al. 2021) combined with Bayesian estimation frameworksCard & Krueger (canonical 1994 application); Angrist & Pischke (textbook treatment)
TípusBayesian causal panel estimatorCausal inference / panel regression
AlapműFreyaldenhoven, S., Hansen, C., Shapiro, J. M., & Teso, E. (2021). Visualization, Identification, and Estimation in the Linear Panel Event-Study Design. NBER Working Paper No. 29170. National Bureau of Economic Research. link ↗Angrist, J. D., & Pischke, J.-S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355
Alternatív nevekBayesian event-study estimator, Bayesian dynamic DiD, Bayesian panel ES, Bayes event studydiff-in-diff, DiD, Farkların Farkı (Diff-in-Diff)
Kapcsolódó45
ÖsszefoglalóBayesian Panel Event Study is a causal inference design that estimates dynamic treatment effects around a datable event using panel data, replacing classical frequentist estimation with Bayesian posterior inference. It produces period-by-period effect estimates with full probability distributions, enabling principled uncertainty quantification, regularization of noisy pre-trend coefficients, and probabilistic tests of parallel trends.Difference-in-Differences is a causal-inference method that estimates the effect of an intervention by comparing how a treatment group and a control group change over time. Made famous by Card and Krueger's 1994 minimum-wage study and developed in Angrist and Pischke's Mostly Harmless Econometrics, it isolates the treatment effect as the difference between the two groups' before-after changes.
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ScholarGateMódszerek összehasonlítása: Bayesian Panel Event Study · Difference-in-Differences. Letöltve 2026-06-15, forrás: https://scholargate.app/hu/compare