Economics Insights @ CBS

Marketing variables that are included in consumer discrete choice models are often endogenous. Extant treatments using likelihood-based estimators impose parametric distributional assumptions, such as normality, on the source of endogeneity. These assumptions are restrictive because misspecified distributions have an impact on parameter estimates and associated elasticities. The normality assumption for endogeneity can be inconsistent with some marginal cost specifications given a price-setting process, although they are consistent with other specifications.

We propose a tractable, data-driven demand estimation procedure based on the use of maximum entropy (ME) distributions, and apply it to a stochastic capacity control problem motivated from airline revenue management. Specifically, we study the two fare-class "Littlewood" problem in a setting where the firm has access to only potentially censored sales observations. We propose a heuristic that iteratively fits an ME distribution to all observed sales data, and in each iteration selects a protection level based on the estimated distribution.

We develop a theoretical framework in which political and economic cycles are jointly determined. These cycles are driven by three political economy frictions: policymakers are non-benevolent, they cannot commit to policies, and they have private information about the tightness of the government budget and rents. Our first main result is that, in the best sustainable equilibrium, distortions to production emerge and never disappear even in the long run.