This dissertation consists of three essays on topics in empirical industrial organization. The first essay proposes and estimates a fully dynamic model of generic and brand advertising in a differentiated product oligopoly. It first specifies a nested logit demand system incorporating brand and...

In some product categories, generic advertising is used to increase market demand of the category and at the same time brand advertising is used to entice consumers to choose the advertised brand over competing brands. This paper empirically investigates the optimal levels of brand and generic...

Heterogeneity in choice models is typically assumed to have a normal distribution in both Bayesian and classical setups. In this paper, we propose a semiparametric Bayesian framework for the analysis of random coefficients discrete choice models that can be applied to both individual as well as...

Parametric Stochastic Frontier Models are widely used in productivity analysis and are commonly estimated using FRONTIER, STATA or LIMDEP packages, which only provide point estimates for firm-specific technical efficiency. Confidence intervals for technical efficiencies with superior coverage...

In some product categories, generic advertising is used to increase market demand of the category and at the same time brand advertising is used to entice consumers to choose the advertised brand over competing brands. This paper empirically investigates the optimal levels of brand and generic...

Heterogeneity in choice models is typically assumed to have a normal distribution in both Bayesian and classical setups. In this paper, we propose a semiparametric Bayesian framework for the analysis of random coefficients discrete choice models that can be applied to both individual as well as...

In some product categories, generic advertising is used to increase market demand of the category and at the same time brand advertising is used to entice consumers to choose the advertised brand over competing brands. This paper empirically investigates the optimal levels of brand and generic...

This paper proposes a semiparametric Bayesian framework for the analysis of associations among multivariate longitudinal categorical variables in high-dimensional data settings. This type of data is frequent, especially in the social and behavioral sciences. A semiparametric hierarchical factor...

Parametric Stochastic Frontier Models are widely used in productivity analysis and are commonly estimated using FRONTIER, STATA or LIMDEP packages, which only provide point estimates for firm-specific technical efficiency. Confidence intervals for technical efficiencies with superior coverage...