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Cited by 320

The DOI matches its Crossref record; 92 of the 92 references it cites were found in a registry or an index.

Robust inference on average treatment effects with possibly more covariates than observations

Open access
Farrell, Max H.·2015·Journal of Econometrics
DOI 10.1016/j.jeconom.2015.06.017
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Abstract

This paper concerns robust inference on average treatment effects following model selection. Under selection on observables, we construct confidence intervals using a doubly-robust estimator that are robust to model selection errors and prove their uniform validity over a large class of models that allows for multivalued treatments with heterogeneous effects and selection amongst (possibly) more covariates than observations. The semiparametric efficiency bound is attained under appropriate conditions. Precise conditions are given for any model selector to yield these results, and we specifically propose the group lasso, which is apt for treatment effects, and derive new results for high-dimensional, sparse multinomial logistic regression. Both a simulation study and revisiting the National Supported Work demonstration show our estimator performs well in finite samples.

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Citations

Cites

Show all 92 references

Research works printed but not linked: 9

  1. Andrews, 2009, Incorrect asymptotic size of subsampling procedures based on post-consistent model selection estimators, J. Econometrics, 152, 19, 10.1016/j.jeconom.2009.02.001 · doi:10.1016/j.jeconom.2009.02.001
  2. Cattaneo, 2011, vol. 27A, 93
  3. He, 2000, On parameters of increasing dimensions, J. Multivariate Anal., 73, 1201, 10.1006/jmva.1999.1873 · doi:10.1006/jmva.1999.1873
  4. Kolar, 2011, Union support recovery in multi-task learning, J. Mach. Learn. Res., 12, 2415
  5. Kwemou, M., 2012, Non-asymptotic Oracle Inequalities for the Lasso and Group Lasso in High Dimensional Logistic Model. Arxiv preprint arXiv:1206.0710. · arXiv
  6. LaLonde, 1986, Evaluating the econometric evaluations of training programs with experimental data, Am. Econ. Rev., 76, 604
  7. Romano, 2004, On non-parametric testing, the uniform behaviour of the t-test, and related problems, Scand. J. Stat., 31, 567, 10.1111/j.1467-9469.2004.00407.x · doi:10.1111/j.1467-9469.2004.00407.x
  8. Tanabe, 1992, An exact Cholesky decomposition and the generalized inverse of the variance–covariance matrix of the multinomial distribution, with applications, J. R. Stat. Soc. Ser. B Stat. Methodol., 54, 211, 10.1111/j.2517-6161.1992.tb01875.x · doi:10.1111/j.2517-6161.1992.tb01875.x
  9. von Bahr, 1965, Inequalities for the rth absolute moment of a sum of random variables, 1≦r≦2, Ann. Math. Stat., 36, 299, 10.1214/aoms/1177700291 · doi:10.1214/aoms/1177700291

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Metadata

Authors
Farrell, M. H.
Venue
Journal of Econometrics
Publisher
Elsevier BV
Published
2015-11
Volume
189
Issue
1
Pages
1-23
ISSN
0304-4076 (ISSN-L)
DOI
10.1016/j.jeconom.2015.06.017
OpenAlex
W2100532505
Cited by
320
References
92
FWCI
19.56
Type
journal article
Language
en
Open access
green
Licence
  • www.elsevier.com/tdm/userlicense/1.0/ (tdm)
  • www.elsevier.com/legal/tdmrep-license (tdm)

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Farrell, M. H. (2015). Robust inference on average treatment effects with possibly more covariates than observations. Journal of Econometrics. https://doi.org/10.1016/j.jeconom.2015.06.017

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