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We propose a new method for studying environments with unobserved individualheterogeneity. Based on model-implied pairwise inequalities, the methodclassifies individuals in the sample into groups defined by discrete unobservedheterogeneity with unknown support. We establish conditions under which thegroups are identified and consistently estimated through our method. We showthat the method performs well in finite samples through Monte Carlo simulation.We then apply the method to estimate a model of lowest-price procurementauctions with unobserved bidder heterogeneity, using data from the Californiahighway procurement market.

Estimating Unobserved Individual Heterogeneity Using Pairwise Comparisons