Identification and Estimation of Triangular Simultaneous Equations Models without Additivity

By Whitney K. Newey, Guido W. Imbens. 2002

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Subfields: Economics and Econometrics, Statistics and Probability

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Citations in the corpus

Double/De-Biased Machine Learning of Global and Local Parameters Using Regularized Riesz Representers (2018, methodology): “Also for ℓ(d) ≡ 1, Imbens and Newey (2009) showed that θ∗0 = E[T (D)] = E[∂dY (D)], which is an average treatment effect.”
A Simple Estimator for Binary Choice Models with Endogenous Regressors (2015, background): “…choice (Berry and Haile 2009a, 2009b), models of games, including entry games and matching games (Lewbel and Tang 2011, Khan and Nekipelov 2011, Fox and Yang 2012), and a variety of models with (partly) nonseparable errors (Lewbel 2007b, Matzkin 2007, Briesch, Chintagunta, and Matzkin 2010).”
Uniform convergence of weighted sums of non and semiparametric residuals for estimation and testing (2014, methodology): “We propose a semiparametric maximum likelihood estimator for θ0 as in Klein and Spady (1993), but with a nonparametric generated regressor estimated in a first stage.”
Unobserved heterogeneity and endogeneity in nonparametric frontier estimation (2016, methodology): “In Imbens and Newey (2009), the model studied takes into account unobserved heterogeneity and also endogeneity of some explanatory variables since they consider two equations: Y = m(X, ) with X1 linked to (endogeneity issue), and X1 = ψ(W,V ).”
Instrumental variable estimation of nonseparable models (2007, background): “In relation to Blundell and Powell (2003), Chesher (2003), and Imbens and Newey (2003), the model does not require existence of a reduced form with a single disturbance, but does impose that the structural equation has a single disturbance.”
A quantile correlated random coefficients panel data model (2016, neutral): “Σδ(τ, τ ′) = E[Zδ (τ) Zδ (τ ′)] = (min (τ, τ ′)− ττ ′) Γ−1E [ W ′ Λ (τ, τ ′; X) W ∣∣∣X ∈ XM]Γ−1 Pr(X ∈ XM) , (33) and (ii) √ N ( β̂ (·; ·)− β (·; ·) ) also converges in distribution to a mean zero Gaussian process Z (·, ·), where Z (·, ·) is defined by its covariance function”
Nonparametric identification in panels using quantiles (2013, methodology): “1 See also Ma and Kosorok (2005) and Chen and Pouzo (2009, 2013) for other applications of weighted bootstrap; we are grateful to a referee for pointing out the latter references.”
Instrumental variable methods for recovering continuous linear functionals (2011, background): “In related work, Newey et al. (1999), Chesher (2003, 2005, 2007), Imbens and Newey (2009) and Schennach et al. (2007) explore estimation and identification in triangular systems, while Chalak and White (2006) and White and Chalak (2006) study the identification of causal effects.”
Estimating distributions of potential outcomes using local instrumental variables with an application to changes in college enrollment and wage inequality (2009, background): “Taber (2001) suggests that the observed rise in the college premium in the 1980s is just a reflection of the increase in the return to unobserved ability, although Chay and Lee (2000) argue that the latter can account at most for 30 to 40% of the increase in the college premium.”
On Instrumental Variables Estimation of Causal Odds Ratios (2011, methodology): “A further limitation is that all foregoing approaches require the exposure to be continuously distributed (Rothe, 2009); some additionally require the IV to be continuously distributed (Imbens and Newey, 2009).”
Using Instrumental Variables for Inference About Policy Relevant Treatment Effects (2018, positive): “Heterogeneous effects IV models with continuous treatments have been considered by Angrist, Graddy, and Imbens (2000), Chesher (2003), Florens, Heckman, Meghir, and Vytlacil (2008), Imbens and Newey (2009), Torgovitsky (2015), Masten (2015), and Masten and Torgovitsky (2016), among others.”
IDENTIFICATION AND INFERENCE IN NONLINEAR DIFFERENCE-IN-DIFFERENCES MODELS BY (2003, neutral): “They consider the vector containing an individual's history of realizations of x across all periods and assume that agents with any permutation of that vector have the same distribution of unobservables.”
Complementarity and Aggregate Implications of Assortative Matching: A Nonparametric Analysis (2014, neutral): “2In settings where our exogeneity assumption is implausible, other approaches to semiparametrically identifying the production technology may be available (e.g., Matzkin (2008), Imbens and Newey (2009)).”
Instrumental Variable Quantile Regression (2004, methodology): “As in Abadie et al. (2002), the Imbens and Newey (2009) framework does not restrict the evolution of ranks across treatment states.”