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Sharp Bounds on Functionals of the Joint Distribution in the Analysis of Treatment Effects

This article proposes an identification and estimation method that allows researchers to bound continuous functionals of the joint distribution of potential outcomes from the literature on treatment effects. The focus is on a model where no restrictions are imposed on treatment selection. The method can sharply bound interesting parameters when analytical bounds are difficult to derive, can be used in settings in which instruments are available, and can easily accommodate additional model constraints. However, computational considerations for the method are found to be important and are discussed in detail.

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Informasi Detail

Judul Seri

JOURNAL OF BUSINESS AND ECONOMIC STATISTICS; Vol.39 No.2 April 2021

No. Panggil

-

Penerbit

: .,

Deskripsi Fisik

p. 532-546

Bahasa

English

ISBN/ISSN

-

Klasifikasi

NONE

Tipe Isi

-

Tipe Media

-

Tipe Pembawa

-

Edisi

-

Subjek

LINEAR PROGRAMMING
CONVEX OPTIMIZATION
PARTIAL IDENTIFICATION
OPTIMAL TRANSPORT
RANDOM SET THEORY

Info Detail Spesifik

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Pernyataan Tanggungjawab

Thomas M. Russell

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