Essays in Quantitative Economics

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.