Regression modelQuasi-experimental / causal inference

Dinamički estimator uparivanja

Dinamički estimator uparivanja proširuje standardne metode uparivanja na situacije u kojima se tretman dodeljuje sekvencijalno tokom više perioda. Umesto jedne odluke o tretmanu, jedinice primaju ili odbijaju tretman u svakoj vremenskoj tački, a estimator identifikuje kauzalne efekte celokupnih istorija tretmana uparivanjem po vremenski promenljivim kovarijatama i prošlim putanjama tretmana, pod pretpostavkama sekvencijalne uslovne nezavisnosti.

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Izvori

  1. Lechner, M., & Miquel, R. (2010). Identification of the effects of dynamic treatments by sequential conditional independence assumptions. Empirical Economics, 39(1), 111-137. DOI: 10.1007/s00181-009-0297-3
  2. Heckman, J. J., Ichimura, H., & Todd, P. (1998). Matching as an Econometric Evaluation Estimator. Review of Economic Studies, 65(2), 261-294. DOI: 10.1111/1467-937X.00044

Kako citirati ovu stranicu

ScholarGate. (2026, June 3). Dynamic Matching Estimator for Sequential Treatment Effects. ScholarGate. https://scholargate.app/sr/causal-inference/dynamic-matching-estimator

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Citirana u

ScholarGateDynamic Matching Estimator (Dynamic Matching Estimator for Sequential Treatment Effects). Preuzeto 2026-06-15 sa https://scholargate.app/sr/causal-inference/dynamic-matching-estimator · Skup podataka: https://doi.org/10.5281/zenodo.20539026