Semiparametric Methods and Applications

Abstract

This dissertation studies semiparametric methods and their applications to economics and marketing problems. We propose a game theoretic model to analyze interactions among individuals in a social network with hierarchy. We find significant asymmetric peer effects among individuals in social networks. High status individuals deliver stronger peer effects on low status individuals than vice versa. Additionally, we investigate semiparametric panel data truncated regression models with fixed effects. We show the identification of our model with primitive assumption, establish the consistency and asymptotic normality of our proposed sieve estimator. We conclude that we can achieve ?n -convergent rate for parametric parameters. Besides theoretical semiparametric methods, we study the dynamic effectiveness of marketing mix variables and the competition among the pioneer and early followers in pharmaceutical industry. With two pharmaceutical categories data, we find dynamic effectiveness of advertising and detailing inputs. Pioneer firms and follower firms have different effectiveness of advertising and detailing inputs in different stages. Our out-of-sample analyses show that when the data is rich, the semiparametric model outperforms the parametric model while it is better to deploy parametric model when the sample size is small.