Identification for Prediction and Decision

By Charles F. Manski. 2008

513 citations recorded by the source corpus.

Subfields: Control and Systems Engineering

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Citations in the corpus

Causal Inference through a Witness Protection Program (2014, methodology): “As Manski emphasizes [11], this is the price for making fewer assumptions.”
External Validity: From Do-Calculus to Transportability Across Populations (2014, background): “The notion of “external validity” as deﬁned by Manski (2007) (footnote 1) corresponds to Direct Transportability, for it requires that R re-tains its validity without adjustment, as in equation (3.2).”
Efficient Policy Learning (2017, background): “In this case, the utility of deploying a policy π(·) relative to treating no one is (Manski, 2009)”
Environmental Policy and Directed Technological Change: Evidence from the European Carbon Market (2012, unknown): “Even if we use the upper-bound estimate (in-sample firms filed 500 additional low-carbon patents), the out-of-sample firms would have to have filed 562 extra low-carbon patents, or at 23 This bound is analogous to the sharp bounds derived by Manski (2007) for situations with missing data.”
Does patenting help high-tech start-ups? (2011, background): “The nonlinear form of the Inverse Mills ratio is based crucially on the normal-linear assumptions of the model and any deviations from it would affect how E(4y|x, s = 1) changes as a consequence of marginal changes in x making it a tenuous approach to addressing selection (Manski, 2007).7”
Causal inference and the data-fusion problem (2016, background): “Special cases of transportability can be found in the literature under different rubrics such as “ lack of external validity ” (46, 47), “ heterogeneity ” (48), and “ meta-analysis ” (49, 50).”
Communicating uncertainty about facts, numbers and science (2019, background): “Manski CF. 2016 Credible interval estimates for official statistics with survey nonresponse.”
The Causal Foundations of Structural Equation Modeling (2012, background): “Remarkably, the theory of external validity has not advanced since Donald Campbell and Julian Stanley recognized and defined the term (Campbell and Stanley, 1966), While several efforts were attempted in economics (Manski, 2007) and psychology (Shadish et al.”
Stratification Trees for Adaptive Randomization in Randomized Controlled Trials (2018, background): “For example, Simester et al. (2006), Karlan and Zinman (2008), and Karlan and Wood (2017) all feature a multi-stage structure, and Karlan and Appel (2016) advocate the use of pilot experiments to help avoid potential implementation failures when scaling up to the main study.”
A General Algorithm for Deciding Transportability of Experimental Results (2013, background): “ not formally articulated until very recently [1–3]. Although the problem has been discussed in many areas of statistics, economics, and the health sciences, under rubrics such as “external validity” [4, 5], “meta-analysis” [6–8], “overgeneralization” [9], “quasi experiments” [10, 11 (Ch. 3)], “hete”
Adjustment Criteria for Generalizing Experimental Findings (2019, background): “Special cases of transportability are found in the literature under different rubrics, including “lack of external validity” (Campbell and Stanley, 1963; Manski, 2007), “heterogeneity” (Höfler et al.”
Contemporary Guidance for Stated Preference Studies (2017, methodology): “(Manski 1977; Hanemann 1984; Maddala 1986; McConnell 1990; Adamowicz et al. 1998).56 The core model for these applications remains the multinomial logit (MNL; also called conditional logit) model and its variants, although similar models such as multinomial probit may also be applied.”
Inferring Optimal Peer Assignment From Experimental Data (2009, background): “This implies a connection between this article and the recent literature on set-valued identification in econometrics, c.f. Manski (2008) for a reasonably comprehensive bibliography.”
Transportability of Causal Effects: Completeness Results (2012, background): “…been discussed in many areas of statistics, economics, and the health sciences, under rubrics such as “external validity” [Campbell and Stanley, 1963; Manski, 2007], “meta-analysis” [Glass, 1976; Hedges and Olkin, 1985; Owen, 2009], “heterogeneity” [Hofler, Gloster, and Hoyer, 2010],…”
The Statistics of Causal Inference: A View from Political Methodology (2015, unknown): “Critically, the selection on observables assumption is nonrefutable, insofar as it cannot be veriﬁed with observed data (Manski 2007).”