Explanations of why changes in the relative quantities of safe debt seem to affect asset prices often appeal informally to a portfolio balance mechanism. I show how this type of effect can be incorporated in a general class of structural, arbitrage-free asset-pricing models using a numerical...

We propose an affine term structure model which accommodates non-linearities in the drift and volatility function of the short-term interest rate. Such non-linearities are a consequence of discrete beta-distributed regime shifts constructed on multiple thresholds. We derive iterative closed form...

The traditional causality relationship proposed by Granger (1969) assumes the relationships between variables are short range dependent with the same integrated order. Chen (2006) proposed a bi-variate model which can catch the long-range dependent among the two variables and the series do not...

We develop a quantitative business cycle model with search complementarities in the inter-firm matching process that entails a multiplicity of equilibria. An active equilibrium with strong joint venture formation, large output, and low unemployment coexists with a passive equilibrium with low...

This paper assessed the quantitative impact of ambiguity on historically observed financial asset returns and growth rates. The single agent, in a dynamic exchange economy, treats the conditional uncertainty about the consumption and dividends next period as ambiguous. We calibrate the agent's...

This paper develops a dynamic general equilibrium model with heterogeneous firms that face search complementarities in the formation of vendor contracts. Search complementarities amplify small differences in productivity among firms. Market concentration fosters monopsony power in the labor...

We model the learning process of market traders during the unprecedented COVID-19 event. We introduce a behavioral heterogeneous agents' model with bounded rationality by including a correction mechanism through representativeness (Gennaioli et al., 2015). To inspect the market crash induced by...

This paper develops a simulation-based solution method to solve large state space macrofinance models using machine learning. We use a neural network (NN) to approximate the expectations in the optimality conditions in the spirit of the stochastic parameterized expectations algorithm (PEA)....