Huber, Martin Mellace, Giovanni 2015 In many empirical problems, the evaluation of treatment effects is complicated by sample selection so that the outcome is only observed for a non-random subpopulation. In the absence of instruments and/or tight parametric assumptions, treatment effects are not point identified, but can be bounded under mild restrictions. Previous work on partial identification has primarily focused on the ‘always observed’ (irrespective of the treatment). This paper complements those studies by considering further populations, namely the ‘compliers’ (observed only if treated) and the observed population. We derive sharp bounds under various assumptions and provide an empirical application to a school voucher experiment. application/pdf https://folia.unifr.ch/global/documents/307033 https://folia.unifr.ch/documents/307033/files/sharpboundsoncausaleffectsundersampleselectionoxfordbulletinofeconomicsandstatistics771129-1512015_0.pdf eng info:eu-repo/semantics/altIdentifier/doi/10.1111/obes.12056 info:eu-repo/semantics/openAccess License undefined Oxford bulletin of economics and statistics. - 2015, vol. 77, no. 1, p. 129-151 causal inference principal stratification nonparametric bounds sample selection info:eu-repo/classification/udc/33 Sharp bounds on causal effects under sample selection http://purl.org/coar/resource_type/c_6501