Research

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Time-Varying Uncertainty and the Credit Channel

(co-authored with Victor Dorofeenko and Gabriel Lee)

Abstract

We extend the Carlstrom and Fuerst (1997) agency cost model of business cycles by including time varying uncertainty in the technology shocks that affect capital production. We first demonstrate that standard linearization methods can be used to solve the model yet second moments enter the economy's equilibrium policy functions. We then demonstrate that an increase in uncertainty causes, ceteris paribus, a fall in investment supply. We also show that persistence of uncertainty affects both quantitatively and qualitatively the behavior of the economy.

A New Algorithm for Solving Dynamic Stochastic Macroeconomic

(co-authored with Victor Dorofeenko and Gabriel Lee)

Abstract

We introduce a new algorithm that can be used to solve stochastic dynamic general equilibrium models. This approach exploits the fact that the equations defining equilibrium can be viewed as set of differential algebraic equations in the neighborhood of the steady-state. Then a modified recursive upwind Gauss Seidel method can be used to determine the global solution. This method, within the context of a standard real business cycle model, is compared to projection, perturbation, and linearization approaches and demonstrated to be fast and globally accurate. This comparison is done within a discrete state setting with heteroskedasticity in the technology shocks. It is shown that linearization methods perform poorly in this environment even though the unconditional variance of shocks is relatively small.

 

Show Me the Money: Taking the Monetary Implications of a Monetary Model Seriously
(co-authored with Kristin Van Gaasbeck)

Abstract

It has become common practice in applied monetary economics to posit an interest rate rule, i.e. a variant of the Taylor rule, as a component of the economic environment. Since the general equilibrium setting also imposes a money demand relationship (e.g. placing real balances in the utility function or imposing a cash-in-advance setup), the interest rate rule implies that the money supply is endogenous. Rarely are the properties of the money supply implied by the model compared to the data. In this paper, we take the monetary implications of a monetary model seriously (we use a variant of the Christiano, Eichenbaum, and Evans (1997) limited participation model that permits both technology and money shocks) by first modeling the money supply as an exogenous Markov process and then calibrating the parameters of the Markov process to the data. We then examine whether the model produces an interest rate rule similar to the Taylor rule relationship observed in the data. The results from this exercise are instructive: the model is able to duplicate qualitatively the relationship between inflation and nominal interest implied by the Taylor rule but fails dramatically to replicate the correlation between nominal interest rates and output.