Sample Selection Bias as a Specification Error (with an Application to the Estimation of Labor Supply Functions)

By James J. Heckman. 1977

Subfields: Natural Language Processing, Economics & Operations Research

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Citations in the corpus

Learning Robust Global Representations by Penalizing Local Predictive Power (2019, background): “…have addressed various formulations of DA (Bridle and Cox, 1991; Ben-David et al., 2010a) dating in the ML and statistics literature to early works on covariate shift Shimodaira (2000) with antecedents classic econometrics work on sample selection bias (Heckman, 1977; Manski and Lerman, 1977).”
Detecting and Correcting for Label Shift with Black Box Predictors (2018, background): “Heckman (1977) addresses sample selection bias, while (Manski & Lerman, 1977) investigates estimating parameters under choice-based and endogenous stratiﬁed sampling , cases analogous to a shift in the label distribution.”
Domain Adaptation with Asymmetrically-Relaxed Distribution Alignment (2019, background): “For example, under the covariate shift assumption (Heckman, 1977; Shimodaira, 2000), although the input marginals can vary between source and target ( p S ( x ) (cid:54) = p T ( x )), the conditional distribution of the labels (given features) exhibits invariance across domains ( p S ( y | x ) = p…”
Firm size and growth in the United Kingdom life insurance industry (2002, methodology): “To allow for the possibility of bias from this source, we estimated the firm size-growth equation for each period in a sample-selection framework, using the Heckman twostage method (Heckman, 1979) to deal with the problem of survivorship bias.”
The Gender Gap between Earnings Distributions (2019, unknown): “24 Also noted in Machado (2012), the number of children is used as an explanatory variable in the shadow price function in Heckman (1974), “one of the seminal works on female selection,” and an IV in the participation equation in Heckman (1980).”
Micro Data, Heterogeneity, and the Evaluation of Public Policy: Nobel Lecture (2001, unknown): “Butler and Heckman (1977) first raised this issue.”
Limits of Estimating Heterogeneous Treatment Effects: Guidelines for Practical Algorithm Design (2018, background): “Moreover, D n would generally exhibit sample selection bias ( Heckman, 1977), because the treatment assignment mechanism (decided by p ( x ) ) creates a discrepancy between the feature distributions of the treated/control population and the overall population.”
Semi-Supervised Learning of Class Balance under Class-Prior Change by Distribution Matching (2012, background): “However, this de facto standard assumption is often violated in realworld problems, caused by intrinsic sample selection bias or inevitable non-stationarity (Heckman, 1979; QuiñoneroCandela et al., 2009; Sugiyama & Kawanabe, 2012).”
Changes in intrahousehold labor allocation to environmental goods collection (2000, unknown): “Heckman's two-step estimation method is employed to control for sample selection in these equations (Heckman 1979, 1980).”