Addressing endogeneity in aggregate logit models with time-varying parameters for optimal retail-pricing

It is well known that price endogeneity is a severe problem in demand models for market-level data (e.g., aggregate logit models) because it leads to biased estimates and therefore incorrect managerial implications. If the price parameter varies over time, as is usually the case, the relevance of the issue increases because standard methods to correct endogeneity biases (e.g., generalized method of moments) fail. This paper presents a control...