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Instrumental Variable Quantile Regression

Victor Chernozhukov, Christian Hansen, Kaspar Wuthrich

arXiv 28 Aug 2020 · Econometrics · 49 citations (OpenAlex)

arXiv:2009.00436 · PDF · DOI · OpenAlex · Extracted main text

Abstract

This chapter reviews the instrumental variable quantile regression model of Chernozhukov and Hansen (2005). We discuss the key conditions used for identification of structural quantile effects within this model which include the availability of instruments and a restriction on the ranks of structural disturbances. We outline several approaches to obtaining point estimates and performing statistical inference for model parameters. Finally, we point to possible directions for future research.

Citation extraction

61
references
124
in-text mentions
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distinct cited
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self-citations
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main-text words

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Most heavily cited references

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.

ReferenceIntensityMentionsSectionsMain text
1Abadie, A., Angrist, J., Imbens, G (2002) Instrumental variables estimates of the effect of subsidized training on the quantiles of trainee earnings1.000103100%
2Chernozhukov, V., Hansen, C (2005) An IV model of quantile treatment effects self1.00095100%
3Imbens, G. W., Newey, W. K (2009) Identification and estimation of triangular simultaneous equations models without additivity1.00083100%
4Chernozhukov, V., Hansen, C (2006) Instrumental quantile regression inference for structural and treatment effect models self0.87482100%
5Andrews, I., Mikusheva, A (2016) Conditional inference with a functional nuisance parameter0.87462100%
6Chernozhukov, V., Hansen, C (2008) Instrumental variable quantile regression: A robust inference approach self0.87462100%
7Chernozhukov, V., Hansen, C., Jansson, M (2009) Finite sample inference for quantile regression models self0.73732100%
8Chernozhukov, V., Hansen, C (2013) Quantile models with endogeneity self0.73732100%
9Wüthrich, K (2014) A comparison of two quantile models with endogeneity, working Paper, Universität Bern, Department of Economics0.73732100%
10Chernozhukov, V., Hong, H (2003) An mcmc approach to classical estimation self0.69351100%

Showing the top 10 of 61 scored citations.

Cited by, within the corpus

arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.

Citing paperIntensityMentionsSections
1Decentralization Estimators for Instrumental Variable Quantile Regression Models0.73732
2Smoothed GMM for quantile models0.58531
3Smoothed instrumental variables quantile regression0.51121
4Interpreting Quantile Independence0.40511
5Learning non-smooth models: instrumental variable quantile regressions and related problems0.40511
61909.125920.40511
7Averaging estimation for instrumental variables quantile regression0.40511
8A first-stage representation for instrumental variables quantile regression0.40511
9Inference on Individual Treatment Effects in Nonseparable Triangular Models0.40511
10Minimax Instrumental Variable Regression and $L_2$ Convergence Guarantees without Identification or Closedness0.40511