Arbeitspapier

Constrained conditional moment restriction models

Shape restrictions have played a central role in economics as both testable implications of theory and sufficient conditions for obtaining informative counterfactual predictions. In this paper we provide a general procedure for inference under shape restrictions in identified and partially identified models defined by conditional moment restrictions. Our test statistics and proposed inference methods are based on the minimum of the generalized method of moments (GMM) objective function with and without shape restrictions. Uniformly valid critical values are obtained through a bootstrap procedure that approximates a subset of the true local parameter space. In an empirical analysis of the effect of childbearing on female labor supply, we show that employing shape restrictions in linear instrumental variables (IV) models can lead to shorter confidence regions for both local and average treatment effects. Other applications we discuss include inference for the variability of quantile IV treatment effects and for bounds on average equivalent variation in a demand model with general heterogeneity. We find in Monte Carlo examples that the critical values are conservatively accurate and that tests about objects of interest have good power relative to unrestricted GMM.

Language
Englisch

Bibliographic citation
Series: cemmap working paper ; No. CWP14/22

Classification
Wirtschaft
Subject
Shape restrictions
inference on functionals
conditional moment (in)equality restrictions
instrumental variables
nonparametric and semiparametric models
Banach space
Banach lattice
Koltchinskii coupling

Event
Geistige Schöpfung
(who)
Chernozhukov, Victor
Newey, Whitney K.
Santos, Andres
Event
Veröffentlichung
(who)
Centre for Microdata Methods and Practice (cemmap)
(where)
London
(when)
2022

DOI
doi:10.47004/wp.cem.2022.1422
Handle
Last update
10.03.2025, 11:42 AM CET

Data provider

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Object type

  • Arbeitspapier

Associated

  • Chernozhukov, Victor
  • Newey, Whitney K.
  • Santos, Andres
  • Centre for Microdata Methods and Practice (cemmap)

Time of origin

  • 2022

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