Asymptotic efficiency in estimation with conditional moment restrictions

By Gary Chamberlain. 1987

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Citations in the corpus

Counterfactual Prediction with Deep Instrumental Variables Networks (2016, background): “Moreover, assuming homoskedastic errors, the instruments are the “right ones”: they are plug-in estimates of the infeasible optimal instruments, E[ηk(xi, p)|xi, zi] [Chamberlain, 1987].”
Double/debiased machine learning for treatment and structural parameters (2017, unknown): “…[ m(W ; θ0, β0)m(W ; θ0, β0) ′ ] leads to the efficient score in the sense of yielding an estimator of θ0 having the smallest variance in the class of GMM estimators (Hansen, 1982), and, in fact, to the semiparametrically efficient score; see Levit (1975), Nevelson (1977), and Chamberlain (1987).”
Efficient Estimation of Average Treatment Effects Using the Estimated Propensity Score (2000, unknown): “…in the discrete pre-treatment v ariable case, and since the formulation of the bound does not rely on discreteness, one might expect using the same reasoning as Chamberlain 1987 in the context of GMM estimation, that the estimator is also eecient when the pre-treatment variables are continuous.”
Locally Robust Semiparametric Estimation (2016, background): “3 of Newey and McFadden (1994) and can also be shown using the argument in Chamberlain (1987).”
Panel Data With Measurement Errors: Instrumental Variables And Gmm Procedures Combining Levels And Differences (2000, background): “''For a more general treatment of asymptotic efficiency in estimation with moment conditions, see Chamberlain (1987) and Newey and McFadden (1994).”
The optimal choice of moments in dynamic panel data models (2009, methodology): “The optimal instrument is the instrumental variable with which we can achieve the semiparametric efficiency bound (Chamberlain (1987, 1992)).”
Local Identification of Nonparametric and Semiparametric Models (2011, background): “Parametric models (i.e., models when 0 is finite dimensional) of this form are well known from the work of Hansen (1982), Chamberlain (1987), and others.”
Automobile Prices in Market Equilibrium (1995, methodology): “Using an i.i.d. sampling scheme and other mild regularity conditions Chamberlain (1986) shows that the efficient set of instruments when we have only conditional moment restrictions is equal to the conditional expectation of the derivative of the conditional moment condition with respect to the…”
Asymptotically Efficient Estimation of Models Defined by Convex Moment Inequalities (2014, background): “This paper is also part of the literature on efficient estimation in econometrics, which has primarily studied finite dimensional parameters identified by moment equality restrictions; see Chamberlain (1987, 1992), Brown and Newey (1998), Ai and Chen (2009), and references therein.”