Double-Robust Identification for Causal Panel Data Models / Dmitry Arkhangelsky, Guido W. Imbens.

Format:

Book

Author/Creator:

Arkhangelsky, Dmitry.

Contributor:

National Bureau of Economic Research.

Imbens, Guido W.

Series:

Working Paper Series (National Bureau of Economic Research) no. w28364.

NBER working paper series no. w28364

Language:

English

Physical Description:

1 online resource: illustrations (black and white);

Place of Publication:

Cambridge, Mass. National Bureau of Economic Research 2021.

Summary:

We study identification and estimation of causal effects in settings with panel data. Traditionally researchers follow model-based identification strategies relying on assumptions governing the relation between the potential outcomes and the unobserved confounders. We focus on a novel, complementary, approach to identification where assumptions are made about the relation between the treatment assignment and the unobserved confounders. We introduce different sets of assumptions that follow the two paths to identification, and develop a double robust approach. We propose estimation methods that build on these identification strategies.

Notes:

Print version record

January 2021.