**Research**

*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.