Victor Chernozhukov, Christian Hansen, Martin Spindler
arXiv 13 Jan 2015 · Statistics — Applications · publishedAmerican Economic Review (2015) · 208 citations (OpenAlex)
arXiv:1501.03185 · PDF · DOI · OpenAlex · Extracted main text
In this note, we offer an approach to estimating causal/structural parameters in the presence of many instruments and controls based on methods for estimating sparse high-dimensional models. We use these high-dimensional methods to select both which instruments and which control variables to use. The approach we take extends BCCH2012, which covers selection of instruments for IV models with a small number of controls, and extends BCH2014, which covers selection of controls in models where the variable of interest is exogenous conditional on observables, to accommodate both a large number of controls and a large number of instruments. We illustrate the approach with a simulation and an empirical example. Technical supporting material is available in a supplementary online appendix.
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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 | Belloni, Chen, Chernozhukov \ Hansen (2012) `Sparse Models and Methods for Optimal Instruments with an Application to Eminent Domain', Econometrica 80, 2369–2429 self | 0.928 | 4 | 3 | 100% |
| 2 | Belloni, Chernozhukov \ Hansen (2014) `Inference on Treatment Effects After Selection Amongst High-Dimensional Controls', Review of Economic Studies 81, 608–650 | 0.843 | 3 | 3 | 100% |
| 3 | Belloni, Chernozhukov, Fernández-Val \ Hansen (2013) `Program Evaluation with High-Dimensional Data', arXiv:1311.2645 | 0.737 | 3 | 2 | 100% |
| 4 | Berry, Levinsohn \ Pakes (1995) `Automobile Prices in Market Equilibrium', Econometrica 63, 841–890 | 0.644 | 4 | 1 | 100% |
| 5 | Belloni \ Chernozhukov (2013) `Least Squares After Model Selection in High-dimensional Sparse Models', Bernoulli 19(2), 521–547 | 0.405 | 1 | 1 | 100% |
| 6 | Belloni, Chernozhukov \ Hansen (2010) `Inference for High-Dimensional Sparse Econometric Models', Advances in Economics and Econometrics | 0.405 | 1 | 1 | 100% |
| 7 | Belloni, Chernozhukov, Hansen \ Kozbur (2014) `Inference in High Dimensional Panel Models with an Application to Gun Control', arXiv:1411.6507 | 0.405 | 1 | 1 | 100% |
| 8 | Gillen, Shum \ Moon (2014) `Demand Estimation with High-Dimensional Product Charateristics', Advances in Econometrics | 0.405 | 1 | 1 | 100% |
| 9 | Bai \ Ng (2009) `Selecting Instrumental Variables in a Data Rich Environment', Journal of Time Series Econometrics 1(1) | 0.405 | 1 | 1 | 100% |
| 10 | Belloni, Chernozhukov \ Hansen (2010) LASSO Methods for Gaussian Instrumental Variables Models | 0.405 | 1 | 1 | 100% |
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