Reducing bias in difference-in-differences models using entropy balancing

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Tác giả: Matthew Cefalu, Michael Dworsky, Christine Eibner, Federico Girosi, Brian G Vegetabile

Ngôn ngữ: eng

Ký hiệu phân loại: 526.75 Mathematical geography

Thông tin xuất bản: 2020

Mô tả vật lý:

Bộ sưu tập: Metadata

ID: 165567

Comment: 20 pages, 7 figures, 4 tablesThis paper illustrates the use of entropy balancing in difference-in-differences analyses when pre-intervention outcome trends suggest a possible violation of the parallel trends assumption. We describe a set of assumptions under which weighting to balance intervention and comparison groups on pre-intervention outcome trends leads to consistent difference-in-differences estimates even when pre-intervention outcome trends are not parallel. Simulated results verify that entropy balancing of pre-intervention outcomes trends can remove bias when the parallel trends assumption is not directly satisfied, and thus may enable researchers to use difference-in-differences designs in a wider range of observational settings than previously acknowledged.
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