Alexandre Belloni, Christian Hansen, Whitney Newey
arXiv 21 Dec 2017 · Econometrics · 26 citations (OpenAlex)
arXiv:1712.08102 · PDF · DOI · OpenAlex · Extracted main text
High-dimensional linear models with endogenous variables play an increasingly important role in recent econometric literature. In this work we allow for models with many endogenous variables and many instrument variables to achieve identification. Because of the high-dimensionality in the second stage, constructing honest confidence regions with asymptotically correct coverage is non-trivial. Our main contribution is to propose estimators and confidence regions that would achieve that. The approach relies on moment conditions that have an additional orthogonal property with respect to nuisance parameters. Moreover, estimation of high-dimension nuisance parameters is carried out via new pivotal procedures. In order to achieve simultaneously valid confidence regions we use a multiplier bootstrap procedure to compute critical values and establish its validity.
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The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Eric Gautier and Alexandre Tsybakov (2011) High-dimensional instrumental variables regression and confidence sets | 1.000 | 7 | 3 | 100% |
| 2 | Victor Chernozhukov, Denis Chetverikov, and Kengo Kato (2015) Empirical and multiplier bootstraps for supreme of empirical processes of increasing complexity, and related gaussian couplings | 1.000 | 6 | 3 | 100% |
| 3 | Victor Chernozhukov, Denis Chetverikov, and Kengo Kato (2014) Gaussian approximation of suprema of empirical processes | 0.843 | 3 | 3 | 100% |
| 4 | A. Belloni, D. Chen, V. Chernozhukov, and C. Hansen (2010) Sparse models and methods for optimal instruments with an application to eminent domain | 0.737 | 3 | 2 | 100% |
| 5 | A. Belloni, V. Chernozhukov, A. Kaul, M. Rosenbaum, and A. B. Tsybakov (2016) Pivotal estimation via self-normalization for high dimensional linear models with error-in-variables self | 0.644 | 2 | 2 | 100% |
| 6 | Victor Chernozhukov, Denis Chetverikov, and Kengo Kato (2013) Gaussian approximations and multiplier bootstrap for maxima of sums of high-dimensional random vectors | 0.644 | 2 | 2 | 100% |
| 7 | E. Gautier and A. Tsybakov (2011) High-dimensional instrumental variables rergession and confidence sets | 0.585 | 3 | 1 | 100% |
| 8 | Alexandre Belloni, Victor Chernozhukov, Ivan Fernández-Val, and Chri… (2017) Program evaluation with high-dimensional data self | 0.511 | 2 | 1 | 100% |
| 9 | Victor Chernozhukov, Christian Hansen, and Martin Spindler (2015) Valid post-selection and post-regularization inference: An elementary, general approach self | 0.511 | 2 | 1 | 100% |
| 10 | Victor H. de la Peña, Tze Leung Lai, and Qi-Man Shao (2009) Self-normalized processes | 0.511 | 2 | 1 | 100% |
Showing the top 10 of 31 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
|---|---|---|---|---|
| 1 | High-Dimensional Econometrics and Regularized GMM | 0.894 | 7 | 4 |