26 Nov 2018Working Paper Summaries

Demand Estimation in Models of Imperfect Competition

by Alexander MacKay and Nathan H. Miller

The study shows how knowledge about firm behavior can be modeled to better predict demand. Firms tend to raise prices in response to higher demand, so observed relationships between price and quantity can be quite misleading. The authors provide an adjustment that can be used when price experiments or instrumental variables are not available.

Author Abstract

We consider the identification and estimation of demand systems in models of imperfect competition. Under standard assumptions about demand and supply, the bias that arises from price endogeneity can be resolved without the use of instruments. We provide a constructive identification result where the causal price parameter can be expressed as a function of the covariance of unobserved shocks. The function is estimated efficiently by the output of ordinary least squares regression. Thus, with a covariance restriction on unobservable shocks, structural parameters can be point identified. Further, it can be possible to place bounds on the structural parameters without imposing a covariance restriction. We illustrate the methodology with applications to ready-to-eat cereal, cement, and airlines.