Characterization of the asymptotic distribution of semiparametric M-estimators

By Hidehiko Ichimura, Sokbae Lee. 2006

88 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/9a69b97b7af80fd2b64156ede7c07800ea722679

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In Statistics and Probability

Citations in the corpus

Uniform convergence of weighted sums of non and semiparametric residuals for estimation and testing (2014, methodology): “See e.g. Assumption 2.4 in Chen, Linton, and van Keilegom (2003) and Assumption 3.4(b) in Ichimura and Lee (2010).”
SEMIPARAMETRIC ESTIMATION WITH GENERATED COVARIATES (2014, methodology): “Using the path-derivative approach of Newey (1994), Hahn and Ridder (2013) derived the form of the influence function of a hypothetical estimator in this problem that is assumed to satisfy an asymptotic linearity condition.”
A Practical Asymptotic Variance Estimator for Two-Step Semiparametric Estimators (2012, methodology): “A long line of theoretical literature derives expressions for semiparametric asymptotic variances of two-step estimators (Newey, 1994; Andrews, 1994; Newey & McFadden, 1994; Ai & Chen, 2007; Chen, Linton, & van Keilegom, 2003; Ichimura & Lee, 2010, to name a few).”
The Value of Knowing the Propensity Score for Estimating Average Treatment Effects (2016, background): “4Such assumptions are commonly made in the literature on the properties of “two-step” estimators that depend on a nonparametrically estimated function; see for example Newey (1994), Newey and McFadden (1994), Chen, Linton, and Van Keilegom (2003), or Ichimura and Lee (2010).”
A Simple Estimator for Binary Choice Models with Endogenous Regressors (2015, methodology): “Alternatively, we could first obtain an estimate of α̂ by estimating E (D | V1 + V2α, X, Z) using a conditional linear index model estimator such as Ichimura and Lee (2006), or just by weighted average derivative estimation of α = E [ ∂E (D | V1, V2, X, Z) /∂V2 ] / [ ∂E (D | V1, V2, X, Z) /∂V1 ] if…”
Pseudo-likelihood estimation and bootstrap inference for structural discrete Markov decision models (2008, methodology): “When some elements of xi are continuously distributed, we apply the framework of Section B.1 of Ichimura and Lee (2006), who build on van der Vaart and Wellner (1996) (VW hereafter).”
A SINGLE-INDEX QUANTILE REGRESSION MODEL AND ITS ESTIMATION (2012, background): “Ichimura and Lee (2006) and Chen and Pouzo (2009) both considered a two-step M-estimator for θ0, which minimizes n ∑ i=1 ρ(Yi −mn(Xi ,θ)), where mn(.,θ) is the estimated link function for any fixed θ , obtained through either approximating the link function with a tensor product sieve or smoothed…”
Identification and estimation of semiparametric two‐step models (2016, methodology): “Escanciano, Jacho-Chávez and Lewbel (2014). We obtain the same limiting distributions that would be found using more well-known approaches such as Newey and McFadden (1994, p. 2197), Chen, Linton, and van Keilegom (2003) and Ichimura and Lee (2010), but under weaker conditions.”
Locally Robust Semiparametric Estimation (2016, methodology): “unction adjustment. These conditions diﬀer from other previous work in semiparametric estimation, as in Andrews (1994), Newey (1994), Newey and McFadden (1994), Chen, Linton, and van Keilegom (2003), Ichimura and Lee (2010), Escanciano et al. (2016), and Chernozhukov et al. (2018), that are not base”
Semiparametric Estimation and Inference Using Doubly Robust Moment Conditions (2013, background): “The first order asymptotic properties of semiparametric two-step estimators have been studied extensively (e.g. Newey, 1994; Newey and McFadden, 1994; Andrews, 1994; Chen, Linton, and Van Keilegom, 2003; Ichimura and Lee, 2010), and are widely used to justify large sample inference procedures.”