Robert Sherman develops estimators of causal effects in regression models with data subject to various deficiencies, such as misreporting or nonresponse, as well as other types of model misspecification. In particular, he is interested in determining the large sample behavior of such estimators. More recently, Sherman has been working on procedures that estimate causal effects in correlated random coefficient panel data models.