Chaos theory has touched on such fields as biology, cognitive science, and physics. By providing a unified and complete explanation of new statistical methods that are useful for testing for chaos in data sets, Brock, Hsieh, and LeBaron show how the principles of chaos theory can be applied to...

This paper explores the time series implications of introducing credit constraints into a production based asset pricing model. Simulations are performed choosing parameter values which generate reasonable values for aggregate fluctuations. These results show that mean reversion in simulated...

This paper seeks to develop a structural model that lets data on asset returns and trading volume speak to whether volatility autocorrelation comes from the fundamental that the trading process is pricing or, is caused by the trading process itself. Returns and volume data argue, in the context...

This paper contributes to the policy evaluation literature by developing new strategies to study alternative policy rules. We compare optimal rules to simple rules within canonical monetary policy models. In our context, an optimal rule represents the solution to an intertemporal optimization...

This paper considers the observational implications of social influences on adoption decisions for an environment of perfect foresight adopters. We argue that social influences can produce two observable effects: 1) discontinuities in unconditional adoption curves and 2) pattern reversals in...

This paper provides a systematic analysis of identification in linear social interactions models. This is both a theoretical and an econometric exercise as the analysis is linked to a rigorously delineated model of interdependent decisions. We develop an incomplete information game that...

This paper provides a systematic analysis of identification in linear social interactions models. This is both a theoretical and an econometric exercise as the analysis is linked to a rigorously delineated model of interdependent decisions. We develop an incomplete information game that...

This paper presents a framework for understanding the limits that exist in optimal policy design in dynamic contexts. We consider the design of policies in the context of dynamic linear models. Fundamental design limits exist for policy rules in such environments in the sense that any policy...

This paper explores ways to integrate model uncertainty into policy evaluation. We first describe a general framework for the incorporation of model uncertainty into standard econometric calculations. This framework employs Bayesian model averaging methods that have begun to appear in a range of...