Sample selection bias as a specification error

By James J. Heckman. 1979

Subfields: Statistics and Probability, Statistical Learning Theory

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Citations in the corpus

The offset tree for learning with partial labels (2008, background): “Transformations from partial label problems to fully supervised problems can be thought of as learning methods for dealing with sample selection bias [8], which is heavily studied in Economics and Statistics.”
Lifelong Learning for Sentiment Classification (2015, background): “Liu (2012) and Pang and Lee (2008) provided good surveys of the existing research.”
MSeg: A Composite Dataset for Multi-Domain Semantic Segmentation (2020, background): “This is known as covariate shift [32] or selection bias [13], and can be tackled in the adaptation or the generalization setting.”
A Sample Selection Approach to Censored Demand Systems (2006, methodology): “Yen (2005) recently proposed a maximum likelihood (ML) procedure for the multivariate sample selection model (MSSM), an extension of the bivariate sample selection model (Heckman 1979), which had motivated the procedures of Heien and Wessells (1990) and Shonkwiler and Yen (1999).”
Information Technology and Business-Level Strategy: Toward an Integrated Theoretical Perspective (2013, background): “…high gains, yet the effects of their decisions are measured ex post against the performance of a control group composed of mixed high-and low-impact investment opportunities, a classic confound between the selection and treatment effects (Ashenfelter 1978; Heckman 1979; Heckman and Robb 1985).”
Of Religion and Redemption: Evidence from Default on Islamic Loans (2014, background): “10 As in these papers we do not observe loan need and/or demand to account for the “double” selection bias, in the spirit of Heckman (1979), as in Cerqueiro (2009), Chakravarty and Yilmazer (2009), and Ongena and Popov (2011) for example.”
Impact of small‐scale irrigation on household poverty: empirical evidence from the Ambo district in Ethiopia (2011, methodology): “An empirical model widely used to overcome such problems is the selectivity model suggested by Heckman (1979). According to Heckman’s model, there are two equations of interest that should be modelled.”
Entrepreneurial Finance and Moral Hazard: Evidence from Token Offerings (2020, methodology): “Finally, it is noteworthy that the inverse Mill’s ratio is significant in model 1, suggesting that sample selectivity would bias the results in the absence of the Heckman (1979) procedure.”
Tariffs and non-tariff frictions in the world wine trade (2016, background): “The Heckman (1979) specification can handle sample selection induced by zero flows.”
Knowledge Maturity and the Scientific Value of Innovations (2017, unknown): “Fourth, to account for selection bias in the decision to rely on mature knowledge, we ran a two-stage model (Heckman, 1979).”
Export propensity, export intensity and firm performance: The role of the entrepreneurial founding team (2012, methodology): “We therefore use the Heckman (1979) approach which 9 In practice, Roper et al (2006) observe that the signs and significance levels obtained using the fractional response model are very similar to those obtained using Tobit.”