Using a structural model, I analyze how changes in the distribution of signals about unknown economic conditions affect real aggregate macrovariables in the business cycle. I focus on two quantifiable properties of the distribution of signals, the signal accuracy and the correlation structure...

We show that several shocks identified without restrictions from a model, and frequently used in the empirical literature, display some persistence. We demonstrate that the two leading methods to recover impulse responses to shocks (moving average representations and local projections) treat...

We propose and develop a dynamic theory of endogenous preference formation in which people adopt worldviews that shape their judgments about their experiences. The framework highlights the role of mindset flexibility, a trait that determines the relative weights the decision maker places on her...

In this paper, we study the statistical properties of heterogeneous agent models with incomplete markets. Using a Bewley-Hugget-Aiyagari model we compute the equilibrium density function of wealth and show how it can be used for likelihood inference. We investigate the identifiability of the...

We study the statistical properties of heterogeneous agent models. Using a Bewley-Hugget-Aiyagari model we compute the density function of wealth and income and use it for likelihood inference. We study the finite sample properties of the maximum likelihood estimator (MLE) using Monte Carlo...

This paper builds an innovative composite world trade cycle index (WTI) by means of a dynamic factor model to perform short-term forecasts of world trade growth of both goods and (usually neglected) services. The selection of trade indicator series is made using a multidimensional approach,...

We develop a dynamic learning model to study money adoption. Agents own an asset that can potentially serve as money. The asset steadily generates stochastic dividends which can be positive or negative. Agents gradually learn about the distribution of dividends and based on the learning outcomes...

Epidemiological models assume gravity-like interactions of individuals across space without microfoundations. We combine a simple epidemiological frame-work with a dynamic model of individual location choice. The model predicts that flows of people across space obey a structural gravity...

Across many fields in economics, a common approach to estimation of economic models is to calibrate a sub-set of model parameters and keep them fixed when estimating the remaining parameters. Calibrated parameters likely affect conclusions based on the model but estimation time often makes a...

We study non-parametric estimation of choice models, which was introduced to alleviate unreasonable assumptions in traditional parametric models, and are prevalent in several application areas. Existing literature focuses only on the static observational setting where all of the observations are...