Exploring the Time-Series Implications of Dynamic Models in Economics and Finance

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This project carries out work on three topics pertaining to the time series implications of a variety of dynamic models in economics and finance. Research under the first topic is aimed at developing and applying new methods of estimation and inference for nonlinear continuous time processes. These methods will be used to study alternative continuous time models of asset pricing. Research under the second topic will assess the performance of a variety of stochastic discount factor models of asset pricing. New diagnostics for dynamic asset pricing models will be developed, new measures of the magnitude of specification errors for a variety of such models will be provided, and new methods of identification and estimation will be explored. The third topic will continue development of model solution methods for and quantitative analysis of a rich class of recursive linear models of dynamic economies. Within the context of these models, there will be investigations of optimal dynamic taxation, seasonality, aggregation-over-time and income distribution. This project has had an enormous influence on the way empirical research is conducted in economics. The investigator, in collaboration with others, has developed new methods for using data to rigorously estimate dynamic economic relationships that now dominate most empirical research in economics. This project builds on the results of past research by developing better methods for studying dynamics in such areas of research as asset pricing, taxation and income distribution. The project undertakes a new line of research on nonlinear models of continuous time processes. This is important because econometric and statistical methods designed for estimating or testing the extensive body of theoretical research on these models have been slow to develop. This project will expand the existing set of methods and use them to obtain important new substantive insights into the performance of security markets.