Efficient estimation of average derivatives in NPIV models: simulation comparisons of neural network estimators

DOI10.1016/j.jeconom.2022.12.014arXiv2110.06763MaRDI QIDQ6108330

Jiafeng Chen, Elie Tamer, Xiaohong Chen

Publication date: 29 June 2023

Published in: Journal of Econometrics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2110.06763

zbMATH Keywords

sigmoidartificial neural networkssemiparametric efficiencyweighted average derivativesendogenous demandnonparametric instrumental variablesefficient influenceoptimal sieve minimum distancerelu

Mathematics Subject Classification ID

Statistics (62-XX) Game theory, economics, finance, and other social and behavioral sciences (91-XX)

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Cites Work

• Unnamed Item
• Estimation of possibly misspecified semiparametric conditional moment restriction models with different conditioning variables
• Sieve semiparametric two-step GMM under weak dependence
• The semiparametric efficiency bound for models of sequential moment restrictions containing unknown functions
• Instrumental variable methods for recovering continuous linear functionals
• Contributions to a general asymptotic statistical theory. With the assistance of W. Wefelmeyer
• Testing for neglected nonlinearity in time series models. A comparison of neural network methods and alternative tests
• Multilayer feedforward networks are universal approximators
• Error bounds for approximations with deep ReLU networks
• Penalized sieve GEL for weighted average derivatives of nonparametric quantile IV regressions
• Examples of \(L^2\)-complete and boundedly-complete distributions
• Asymptotic Statistics
• Universal approximation bounds for superpositions of a sigmoidal function
• Optimal sup-norm rates and uniform inference on nonlinear functionals of nonparametric IV regression
• Sieve Wald and QLR Inferences on Semi/Nonparametric Conditional Moment Models
• Measuring the price responsiveness of gasoline demand: Economic shape restrictions and nonparametric demand estimation
• Improved rates and asymptotic normality for nonparametric neural network estimators
• Double/debiased machine learning for treatment and structural parameters
• Semiparametric Efficiency Bounds for Microeconometric Models: A Survey
• Semi-Nonparametric IV Estimation of Shape-Invariant Engel Curves
• Instrumental Variable Estimation of Nonparametric Models
• Efficient Estimation of Models with Conditional Moment Restrictions Containing Unknown Functions
• Neural network approximation: three hidden layers are enough