Sun, Liyang;
Singh, Rahul;
(2023)
Double robustness for complier parameters and a semi-parametric test for complier characteristics.
Econometrics Journal
, Article utad019. 10.1093/ectj/utad019.
(In press).
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Abstract
We propose a semi-parametric test to evaluate (a) whether different instruments induce subpopulations of compliers with the same observable characteristics, on average; and (b) whether compliers have observable characteristics that are the same as the full population, treated subpopulation, or untreated subpopulation, on average. The test is a flexible robustness check for the external validity of instruments. To justify the test, we characterise the doubly robust moment for Abadie’s class of complier parameters, and we analyse a machine learning update to weighting that we call the automatic weight. We use the test to reinterpret Angrist and Evans' different local average treatment effect estimates obtained using different instrumental variables.
| Type: | Article |
|---|---|
| Title: | Double robustness for complier parameters and a semi-parametric test for complier characteristics |
| DOI: | 10.1093/ectj/utad019 |
| Publisher version: | https://doi.org/10.1093/ectj/utad019 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | Semiparametric and Nonparametric Methods, Instrumental Variables (IV) Estimation, Neural Networks and Related Topics |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL SLASH UCL > Provost and Vice Provost Offices > UCL SLASH > Faculty of S&HS UCL > Provost and Vice Provost Offices > UCL SLASH > Faculty of S&HS > Dept of Economics |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10177886 |
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