Information Theoretic Approaches to Inference in Moment Condition Models

By Guido W. Imbens, R. Spady, P. Johnson. 1995

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Citations in the corpus

Approximate residual balancing: debiased inference of average treatment effects in high dimensions (2016, methodology): “|X admits a well-specified logistic model the methods of Graham et al. (2012, 2016) and Hainmueller (2012) are doubly robust (Zhao and Percival, 2017); see also Hirano et al. (2001), Imbens et al. (1998) and Newey and Smith (2004).”
Robustness, Infinitesimal Neighborhoods, and Moment Restrictions (2009, background): “understood (see, for example, Kitamura and Stutzer (1997), Smith (1997), Imbens, Spady, and Johnson (1998) , and Newey and Smith (2004)).”
An MCMC approach to classical estimation (2003, unknown): “Simple and practical sufficient conditions for Lemma 2 are given in Qin and Lawless (1994), Imbens et al. (1998), Kitamura (1997), Kitamura and Stutzer (1997), including stationary weakly dependent data, Newey and Smith (2001), and Christoffersen et al. (1999).”
The MM, ME, ML, EL, EF and GMM approaches to estimation: a synthesis (2002, background): “Golan and Judge (1996), Imbens (1997), Imbens et al. (1998), and, Qin and Lawless (1994) proposed a different objective function motivated by entropy or the Kullback-Leibler information criterion (KLIC).”
Improved JIVE Estimators for Overidentified Linear Models with and without Heteroskedasticity (2009, background): “A number of papers have demonstrated attractive theoretical properties of this class of estimators, even under heteroskedasticity; for example, Qin and Lawless (1994), Kitamura and Stutzer (1997), Imbens, Spady, and Johnson (1998), and Newey and Smith (2004).”
Robust inference with GMM estimators (2001, background): “…prediction has been stressed by many authors both in the statistical and econometric literature; cf. for instance, Hampel (1974), Koenker and Bassett (1978), Huber (1981), Koenker (1982), Hampel et al. (1986), Peracchi (1990, 1991), Markatou and Ronchetti (1997), Krishnakumar and Ronchetti (1997).”
Nonparametric likelihood ratio model selection tests between parametric likelihood and moment condition models (2007, methodology): “The empirical likelihood estimator optimizes the following sample analog of the population saddle point objective function (cf. Qin and Lawless (1994), Imbens, Spady, and Johnson (1998))”
RELIABLE INFERENCE FOR GMM ESTIMATORS? FINITE SAMPLE PROPERTIES OF ALTERNATIVE TEST PROCEDURES IN LINEAR PANEL DATA MODELS (2005, methodology): “Imbens et al. (1998) focus primarily on their test of overidentifying restrictions, NJ ET and only briefly consider the performance of DETRU for some specific nonlinear models.”
Finite Sample Evidence Suggesting a Heavy Tail Problem of the Generalized Empirical Likelihood Estimator (2006, background): “The heavy computational burden and unreliability of minimization routines for GEL estimators has been widely recognized, see, e.g., Hansen et al. (1996), Imbens et al. (1998), and Mittelhammer et al. (2005).”
Globally efficient non-parametric inference of average treatment effects by empirical balancing calibration weighting (2015, unknown): “When ρ.v/=− exp.−v/, the weights are equivalent to the implied weights of exponential tilting (Kitamura and Stutzer, 1997; Imbens et al., 1998).”
Generalized Method of Moments and Macroeconomics (2002, methodology): “Qin and Lawless (1994) and Imbens, Spady, and Johnson (1998) developed EL estimation for independent observations and general overidenti ed nonlinear moment equations.”
Using price distributions to estimate search costs (2006, methodology): “Jin and Kato (2002) investigate the increased incidence of adverse selection in online markets due to the buyers' lack of opportunities to inspect products.”