Journal
QUANTITATIVE ECONOMICS
Volume 13, Issue 1, Pages 29-61Publisher
WILEY
DOI: 10.3982/QE826
Keywords
Influence function; semiparametric estimation; NPIV; C13; C14; C20; C26; C36
Categories
Funding
- JSPS [15H05692, 20H00072]
- NSF [SES 1132399, 1757140]
- Direct For Social, Behav & Economic Scie
- Divn Of Social and Economic Sciences [1757140] Funding Source: National Science Foundation
- Grants-in-Aid for Scientific Research [20H00072, 15H05692] Funding Source: KAKEN
Ask authors/readers for more resources
This article discusses the nonparametric first steps of various economic parameters and the application of influence functions in local policy analysis and estimator evaluation.
There are many economic parameters that depend on nonparametric first steps. Examples include games, dynamic discrete choice, average exact consumer surplus, and treatment effects. Often estimators of these parameters are asymptotically equivalent to a sample average of an object referred to as the influence function. The influence function is useful in local policy analysis, in evaluating local sensitivity of estimators, and constructing debiased machine learning estimators. We show that the influence function is a Gateaux derivative with respect to a smooth deviation evaluated at a point mass. This result generalizes the classic Von Mises (1947) and Hampel (1974) calculation to estimators that depend on smooth nonparametric first steps. We give explicit influence functions for first steps that satisfy exogenous or endogenous orthogonality conditions. We use these results to generalize the omitted variable bias formula for regression to policy analysis for and sensitivity to structural changes. We apply this analysis and find no sensitivity to endogeneity of average equivalent variation estimates in a gasoline demand application.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available