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Sieve Wald and QLR Inferences on Semi/nonparametric Conditional Moment Models

Xiaohong Chen, Demian Pouzo

arXiv 5 Nov 2014 · Mathematics — Statistics Theory · publishedEconometrica (2015) · 108 citations (OpenAlex)

arXiv:1411.1144 · PDF · DOI · OpenAlex · Extracted main text

Abstract

This paper considers inference on functionals of semi/nonparametric conditional moment restrictions with possibly nonsmooth generalized residuals, which include all of the (nonlinear) nonparametric instrumental variables (IV) as special cases. These models are often ill-posed and hence it is difficult to verify whether a (possibly nonlinear) functional is root-$n$ estimable or not. We provide computationally simple, unified inference procedures that are asymptotically valid regardless of whether a functional is root-$n$ estimable or not. We establish the following new useful results: (1) the asymptotic normality of a plug-in penalized sieve minimum distance (PSMD) estimator of a (possibly nonlinear) functional; (2) the consistency of simple sieve variance estimators for the plug-in PSMD estimator, and hence the asymptotic chi-square distribution of the sieve Wald statistic; (3) the asymptotic chi-square distribution of an optimally weighted sieve quasi likelihood ratio (QLR) test under the null hypothesis; (4) the asymptotic tight distribution of a non-optimally weighted sieve QLR statistic under the null; (5) the consistency of generalized residual bootstrap sieve Wald and QLR tests; (6) local power properties of sieve Wald and QLR tests and of their bootstrap versions; (7) asymptotic properties of sieve Wald and SQLR for functionals of increasing dimension. Simulation studies and an empirical illustration of a nonparametric quantile IV regression are presented.

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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
1Blundell, R., Chen, X., and Kristensen, D (2007) Semi-nonparametric iv estimation of shape invariant engel curves self1.000124100%
2Newey, W. and Powell, J (2003) Instrumental variables estimation for nonparametric models1.00053100%
3Chen, X. and Pouzo, D (2012) Estimation of nonparametric conditional moment models with possibly nonsmooth generalized residuals self0.92524879%
4Chen, X. and Pouzo, D (2009) Efficient estimation of semiparametric conditional moment models with possibly nonsmooth residuals self0.891241071%
5Ai, C. and Chen, X (2007) Estimation of possibly misspecified semiparametric conditional moment restriction models with different conditioning variables self0.8746367%
6Ai, C. and Chen, X (2003) Efficient estimation of models with conditional moment restrictions containing unknown functions self0.85819863%
7Chen, X., Linton, O., and van Keilegom, I (2003) Estimation of semiparametric models with the criterion functions is not smooth self0.7374450%
8Chamberlain, G (1992) Efficiency bounds for semiparametric regression0.7374275%
9Graham, B. and Powell, J (2012) Identification and estimation of average partial effects in irregular correlated random coefficient panel data models0.7374275%
10Horowitz, J (2011) Applied nonparametric instrumental variables estimation0.73732100%

Showing the top 10 of 55 scored citations.

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5Inference on Time Series Nonparametric Conditional Moment Restrictions Using General Sieves0.73732
6Penalized GMM Framework for Inference on Functionals of Nonparametric Instrumental Variable Estimators0.73732
7A Unified Framework for Debiased Machine Learning: Riesz Representer Fitting under Bregman Divergence0.65974
8Bootstrap Consistency for Quadratic Forms of Sample Averages with Increasing Dimension0.64422
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10Generalized Bayes in Conditional Moment Restriction Models0.64422