Empirical models of demand for - and, often, supply of - differentiated products are widely used in practice, typically employing parametric functional forms and distributions of consumer heterogeneity. We re view some recent work studying identification in a broad class of such models. This...

Empirical models of demand for–and, often, supply of–differentiated products are widely used in practice, typically employing parametric functional forms and distributions of consumer heterogeneity. We review some recent work studying identification in a broad class of such models. This work...

Empirical models of demand for -- and, often, supply of -- differentiated products are widely used in practice, typically employing parametric functional forms and distributions of consumer heterogeneity. We review some recent work studying identification in a broad class of such models. This...

Empirical models of demand for-and, often, supply of-differentiated products are widely used in practice, typically employing parametric functional forms and distributions of consumer heterogeneity. We review some recent work studying identification in a broad class of such models. This work...

Empirical models of differentiated products demand (and often supply) are widely used in industrial organization and other fields of economics. We review some recent work studying identification in a broad class of such models. This work shows that the parametric functional forms and...

A recent literature considers the identification of heterogeneous demand and supply models via "quasi-experimental'' variation, as from instrumental variables. In this paper we establish nonparametric identification of differentiated products demand when one has "micro data'' linking...

A recent literature considers the identification of heterogeneous demand and supply models via "quasi-experimental'' variation, as from instrumental variables. In this paper we establish nonparametric identification of differentiated products demand when one has "micro data'' linking...