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dc.contributor.advisorKing, Gary
dc.contributor.authorLam, Patrick Kenneth
dc.date.accessioned2013-10-18T15:30:20Z
dc.date.issued2013-10-18
dc.date.submitted2013
dc.identifier.citationLam, Patrick Kenneth. 2013. Estimating Individual Causal Effects. Doctoral dissertation, Harvard University.en_US
dc.identifier.otherhttp://dissertations.umi.com/gsas.harvard:11150en
dc.identifier.urihttp://nrs.harvard.edu/urn-3:HUL.InstRepos:11181234
dc.description.abstractMost empirical work focuses on the estimation of average treatment effects (ATE). In this dissertation, I argue for a different way of thinking about causal inference by estimating individual causal effects (ICEs). I argue that focusing on estimating ICEs allows for a more precise and clear understanding of causal inference, reconciles the difference between what the researcher is interested in and what the researcher estimates, allows the researcher to explore and discover treatment effect heterogeneity, bridges the quantitative-qualitative divide, and allows for easy estimation of any other causal estimand.en_US
dc.description.sponsorshipGovernmenten_US
dc.language.isoen_USen_US
dash.licenseLAA
dc.subjectPolitical Scienceen_US
dc.subjectStatisticsen_US
dc.subjectcausal inferenceen_US
dc.titleEstimating Individual Causal Effectsen_US
dc.typeThesis or Dissertationen_US
dash.depositing.authorLam, Patrick Kenneth
dc.date.available2013-10-18T15:30:20Z
thesis.degree.date2013en_US
thesis.degree.disciplineGovernmenten_US
thesis.degree.grantorHarvard Universityen_US
thesis.degree.leveldoctoralen_US
thesis.degree.namePh.D.en_US
dc.contributor.committeeMemberAlt, Jamesen_US
dc.contributor.committeeMemberGlynn, Adamen_US
dc.contributor.committeeMemberSpirling, Arthuren_US
dc.data.urihttp://hdl.handle.net/1902.1/22427en_US
dash.contributor.affiliatedLam, Patrick


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