Evaluating continuous training programmes by using the generalized propensity score
By Jochen Kluve, Hilmar Schneider, Arne Uhlendorff, Zhong Zhao. 2012
205 citations recorded by the source corpus.
Subfields: Economics and Econometrics, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/5ef8141344b00c12f1c434fc3f189098c5be1af5
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Citations in the corpus
- Entropy Balancing for Continuous Treatments (2020, background): “Examples include the evaluation of job training programs with varying duration (Choe, Flores-Lagunes, and Lee 2015; Flores et al. 2012; Kluve et al. 2012; Li and Fraser 2015) or quality (Galdo and Chong 2012) and subsidies of different magnitude to firms or entire regions (Becker, Egger, and von Ehr”
- Evaluating the impact of improved maize varieties on food security in Rural Tanzania: Evidence from a continuous treatment approach (2014, unknown): “As indicated above, the main purpose of estimating the GPS is to ensure that the covariates are balanced across treatment categories; so that as long as sufficient covariate balance is achieved, the exact procedure for estimating the GPS is of secondary importance (Kluve et al. 2012).”
- Estimating the Effects of Length of Exposure to Instruction in a Training Program: The Case of Job Corps (2012, methodology): “However, contrary to recent parametric applications of the GPS in a continuous treatment setting (Hirano and Imbens, 2004; Kluve et al., 2007; Mitnik, 2008; Bia and Mattei, 2008), our estimators are semiparametric in the sense that we control for the estimated GPS nonparametrically in the estimation”
- Migration and Trade (2012, unknown): “Applications of the generalized - continuous - propensity score deal with labor market programs (see Kluve et al. 2007), regional transfer schemes (see Becker et al. 2010), and FDI (see Du and Girma, 2009).”