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This study explores the implications of using spatially aggregated data when testing for supplier differentiation in the market for audit services. I present a statistical model that identifies the nature and sources of aggregation bias when important variation exists within aggregate units, and then subject it to empirical analysis. I find, as predicted, a tendency for aggregation to exacerbate bias from relevant omitted factors and to cause researchers to overestimate the impact of market leadership on audit quality. My analysis thus offers guidance for choosing among alternative levels of aggregation in auditing.