We develop a general framework for measuring biases in expectation formation. The method is based on the insight that biases can be inferred from the response of forecast errors to past news. Empirically, biases are measured by flexibly estimating the impulse response function of forecast...

The use of various moving average (MA) rules remains popular with financial market practitioners. These rules have recently become the focus of a number empirical studies, but there have been very few studies of financial market models where some agents employ technical trading rules of the type...

We discuss recent work on bounded rationality and learning in relation to Soros' principle of reflexivity and stress the empirical importance of non-rational, almost self-fulfilling equilibria in positive feedback systems. As an empirical example, we discuss a behavioral asset pricing model with...

We introduce a simple equilibrium model of a market for loans, where house- holds lend to firms based on heterogeneous expectations about their loan default probability. Agents select among heterogeneous expectation rules, based upon their relative performance. A small fraction of pessimistic...

Rational expectations assumes perfect, model consistency between beliefs and market realizations. Here we discuss behaviorally rational expectations, characterized by an observable, parsimonious and intuitive form of consistency between beliefs and realizations. We discuss three case-studies....

This essay links some of my own work on expectations, learning and bounded rationality to the inspiring ideas of Jean-Michel Grandmont. In particular, my work on consistent expectations and behavioral learning equilibria may be seen as formalizations of JMG's ideas of self-fulfilling mistakes....

We propose a smooth shadow-rate version of the dynamic Nelson-Siegel (DNS) model to analyze the term structure of interest rates during the recent zero lower bound (ZLB) period. By relaxing the no-arbitrage restriction, our shadow-rate model becomes highly tractable with a closed-form yield...

We introduce a new model for time-varying spatial dependence. The model extends the well-known static spatial lag model. All parameters can be estimated conveniently by maximum likelihood. We establish the theoretical properties of the model and show that the maximum likelihood estimator for the...

The multivariate analysis of a panel of economic and financial time series with mixed frequencies is a challenging problem. The standard solution is to analyze the mix of monthly and quarterly time series jointly by means of a multivariate dynamic model with a monthly time index: artificial...

Many empirical studies have shown that factor models produce relatively accurate forecasts compared to alternative short-term forecasting models. These empirical findings have been established for different macroeconomic data sets and different forecast horizons. However, various specifications...