Essays in Quantitative Economics

Abstract

This thesis contains essays on quantitative economics. It focuses on understanding capital markets and macroeconomics through general equilibrium models and econometric tools. In the second chapter, I propose a two-sector production-based dynamic stochastic general equilibrium model to study the interaction between R&D activities and firm heterogeneity. I argue that the different business risks faced by R&D and non-R&D firms, could be an important source of heterogeneity in asset prices between R&D and non-R&D firms. In the third chapter, co-authored with Riccardo Colacito and Mariano Massimiliano Croce, we characterize the equilibrium of a complete market economy with multiple agents featuring a preference for the timing of the resolution of uncertainty. We provide conditions under which the solution of the planner's problem exists, and it features a nondegenerate invariant distribution of Pareto weights. In the fourth chapter, I define a first-order good uncertainty measure. I then incorporate it into the DSGE model to evaluate the aggregate effects of both good and bad uncertainty. In the final chapter, I propose a buffered double autoregressive (BDAR) time series model to depict the buffering phenomenon of conditional mean and conditional variance in time series. I first prove strict stationarity and geometric ergodicity of the BDAR model under several sufficient conditions. I then propose a quasi-maximum likelihood estimation procedure and study its nontrivial asymptotic property. Furthermore, a model selection criteria and its asymptotic property have been established. I evaluate the model's performance, using both simulated and real data.