We model a boundedly rational agent who suffers from limited attention. The agent considers each feasible alternative with a given (unobservable) probability, the attention parameter, and then chooses the alternative that maximises a preference relation within the set of considered alternatives....

Using a unique dataset on U.S. beer consumption, we investigate brand preferences of consumers across various social group and context related consumption scenarios (“scenarios”). As sufficient data are not available for each scenario, understanding these preferences requires us to share...

It is well known that random parameters specifications can generate upward sloping demands for a subset of products in the data. Nevo (2001), for example, found 0.7 percent of demands to be upward sloping. Possibly less well known is that demand system estimates can imply margins outside of the...

This paper measures the economic impact of social pressure to share income with kin and neighbors in rural Kenyan villages. The authors conduct a lab experiment in which they randomly vary the observability of investment returns. The goal is to test whether subjects reduce their income in order...

The paper compares different estimation strategies of ordered response models in the presence of non-random unobserved heterogeneity. By running Monte Carlo simulations with a range of randomly generated panel data of differing cross-sectional and longitudinal dimension sizes we assess the...

Estimation of demand is at the heart of many recent studies that examine questions of market power, mergers, innovation, and valuation of new brands in differentiated‐products markets. This paper focuses on one of the main methods for estimating demand for differentiated products:...

We consider an adaptive importance sampling approach to estimating the marginal likelihood, a quantity that is fundamental in Bayesian model comparison and Bayesian model averaging. This approach is motivated by the difficulty of obtaining an accurate estimate through existing algorithms that...

This article discusses the use of Bayesian methods for estimating logit demand models using aggregate data, i.e. information solely on how many consumers chose each product. We analyze two different demand systems: independent samples and consumer panel. Under the first system, there is a...