James J. Heckman shared the 2000 Nobel Memorial Prize in Economic Sciences for developing theory and methods for analyzing selective samples.
Heckman showed how researchers can obtain misleading conclusions when the people or observations in a dataset are selected in a non-random way. For example, observed wages may come only from people who choose to work, so analyzing those wages without accounting for participation can create selection bias. His methods help economists model both the selection process and the outcome of interest.
Heckman shared the 2000 prize with Daniel L. McFadden, whose award recognized theory and methods for analyzing discrete choice. The two contributions are related but distinct: Heckman focused on selection problems, while McFadden developed tools for choices among alternatives. Heckman’s work became important in labor economics, education research, treatment evaluation, and many other areas using observational data.