Essays on pricing dynamics, price dispersion, and nested logit modelling

The body of this dissertation comprises three standalone essays, presented in three respective chapters.; Chapter One explores the possibility that local market power contributes to the asymmetric relationship observed between wholesale costs and retail prices in gasoline markets. I exploit an original data set of weekly gas station prices in Southern California from September 2002 to May 2003, and take advantage of highly detailed station and local market-level characteristics to determine the extent to which spatial differentiation influences price-response asymmetry. I find that brand identity, proximity to rival stations, bundling and advertising, operation type, and local market features and demographics each influence a station's predicted asymmetric relationship between prices and wholesale costs.; Chapter Two extends the existing literature on the effect of market structure on price dispersion in airline fares by modeling the effect at the disaggregate ticket level. Whereas past studies rely on aggregate measures of price dispersion such as the Gini coefficient or the standard deviation of fares, this paper estimates the entire empirical distribution of airline fares and documents how the shape of the distribution is determined by market structure. Specifically, I find that monopoly markets favor a wider distribution of fares with more mass in the tails while duopoly and competitive markets exhibit a tighter fare distribution. These findings indicate that the dispersion of airline fares may result from the efforts of airlines to practice second-degree price discrimination.; Chapter Three adopts a Bayesian approach to the problem of tree structure specification in nested logit modelling, which requires a heavy computational burden in calculating marginal likelihoods. I compare two different techniques for estimating marginal likelihoods: (1) the Laplace approximation, and (2) reversible jump MCMC. I apply the techniques to both a simulated and a travel mode choice data set, and find that model selection is invariant to prior specification, while model derivatives like willingness-to-pay are notably sensitive to model choice. I also find that the Laplace approximation is remarkably accurate in spite of the potential for nested logit models to have irregular likelihood surfaces.