Evaluating the Effect of Training on Wages in the Presence of Noncompliance, Nonemployment, and Missing Outcome Data

DSpace/Manakin Repository

Evaluating the Effect of Training on Wages in the Presence of Noncompliance, Nonemployment, and Missing Outcome Data

Show simple item record

dc.contributor.author Frumento, Paolo
dc.contributor.author Mealli, Fabrizia
dc.contributor.author Pacini, Barbara
dc.contributor.author Rubin, Donald B.
dc.date.accessioned 2012-07-18T18:11:28Z
dc.date.issued 2012-07-18
dc.identifier.citation Frumento, Paolo, Fabrizia Mealli, Barbara Pacini, and Donald B. Rubin. 2012. Evaluating the effect of training on wages in the presence of noncompliance, nonemployment, and missing outcome data. Journal of the American Statistical Union 107(498): 450-466. en_US
dc.identifier.issn 0162-1459 en_US
dc.identifier.uri http://nrs.harvard.edu/urn-3:HUL.InstRepos:9275635
dc.description.abstract The effects of a job-training program on both employment and wages are evaluated, using data from a randomized study. Principal stratification is used to address, simultaneously, the complications of noncompliance, wages that are only partially defined because of nonemployment, and unintended missing outcomes. The first two complications are of substantive interest, whereas the third is a nuisance. The objective is to find a parsimonious model that can be used to inform public policy. We conduct a likelihood-based analysis using finite mixture models estimated by the EM algorithm. We maintain an exclusion restriction assumption for the effect of assignment on employment and wages for noncompliers, but not on missingness. We provide estimates under the Missing at Random assumption, and assess the robustness of our results to deviations from it. The plausibility of meaningful restrictions is investigated by means of scaled log-likelihood ratio statistics. Substantive conclusions include the following. For compliers, the effect on employment is negative in the short term; it becomes positive in the long term, but these effects are small at best. For always employed compliers, i.e., compliers who are employed whether trained or not trained, positive effects on wages are found at all time periods. Our analysis reveals that background characteristics of individuals differ markedly across the principal strata. We found evidence that the program should have been better targeted, in the sense of being designed diffrently for different groups of people, and specific suggestions are offered. Previous analyses of this data set, which did not address all complications in a principled manner, led to less nuanced conclusions about Job Corps. en_US
dc.description.sponsorship Statistics en_US
dc.language.iso en_US en_US
dc.publisher American Statistical Union en_US
dc.relation.isversionof doi:10.1080/01621459.2011.643719 en_US
dc.relation.hasversion http://www.cide.info/conf/2009/iceee2009_submission_258.pdf en_US
dash.license OAP
dc.subject EM algorithm en_US
dc.subject finite mixture models en_US
dc.subject missing at random en_US
dc.subject noncompliance en_US
dc.subject partially defined outcomes en_US
dc.subject principal stratification en_US
dc.subject Rubin causal model en_US
dc.subject training en_US
dc.subject wages en_US
dc.title Evaluating the Effect of Training on Wages in the Presence of Noncompliance, Nonemployment, and Missing Outcome Data en_US
dc.type Journal Article en_US
dc.description.version Accepted Manuscript en_US
dc.relation.journal Journal of the American Statistical Union en_US
dash.depositing.author Rubin, Donald B.
dc.date.available 2012-07-18T18:11:28Z

Files in this item

Files Size Format View
361.pdf 215.1Kb PDF View/Open

This item appears in the following Collection(s)

  • FAS Scholarly Articles [7470]
    Peer reviewed scholarly articles from the Faculty of Arts and Sciences of Harvard University

Show simple item record

 
 

Search DASH


Advanced Search
 
 

Submitters