Research

Published Papers

"Time-Varying Volatility and the Housing Market" (with Ayse Sapci)

Accepted for publication by Macroeconomic Dynamics

This paper studies the role of stochastic volatility in a setting where housing serves as an important propagation mechanism. After showing time-varying volatility in U.S. house prices, we estimate a dynamic stochastic general equilibrium model with housing, financial frictions, and stochastic volatility using a nonlinear approximation and Bayesian econometric techniques. Incorporating stochastic volatility into the model greatly improves model fit and accounts for approximately half of the increased volatility in house prices observed during the Great Recession. Increased stochastic volatility escalates uncertainty which has significant effects on macroeconomic variables. While uncertainty in most sectors has negative effects on the economy, uncertainty on collateral constraints has the largest role. Unlike other uncertainty shocks, the housing demand uncertainty creates positive spillovers in the economy. Credit conditions, adjustment costs of capital and housing, and monetary policy are important transmission mechanisms for the stochastic volatility shocks.

"Risk and Uncertainty: The Role of Financial Frictions"

Economic Modelling, 2023

This paper studies the economic impact of financial and uncertainty shocks using an estimated, nonlinear New Keynesian model with financial frictions. While uncertainty shocks have smaller impacts than most first-order shocks, increases in uncertainty surrounding labor supply, capital production and wealth lead to a sizable drop in consumption and investment. Financial frictions play an important role in amplifying the uncertainty shocks. As macroeconomic uncertainty increases, the performance of loans also becomes less certain. This causes financial conditions to tighten and the credit spread to increase, which results in a decline in investment. The filtered states of the model show that the uncertainty of labor supply, capital production and wealth shocks increased in the United States during the 2007–2009 financial crisis. Counterfactual results show that these increases in volatility and uncertainty, especially for the wealth shock, played key roles in causing the Great Recession, accounting for most of the decline in investment and the tightening of credit conditions.

"Financial Frictions and Changing Macroeconomic Volatility"

Journal of Macroeconomics, 2020

A New Keynesian Model with financial frictions is augmented with parameter drift and stochastic volatility. This model is estimated and used to study the causes of the Great Moderation, a period of reduced macroeconomic volatility observed in the U.S. economy from 1984 to 2007. The model finds evidence of stochastic volatility and a decrease in financial frictions, but does not find support for changes in monetary policy. Based on counterfactual studies, the reduction in financial frictions was an important reason for the reduction in volatility observed during the Great Moderation. It also appears that good luck was a factor in reducing consumption volatility during the Great Moderation.

"Estimating General Equilibrium Models with Stochastic Volatility and Changing Parameters"

Economic Modelling, 2017

This paper explores the importance of specification in estimated general equilibrium models with changing monetary policy parameters and stochastic volatility. Simulated data is used to estimate models with incorrectly specified exogenous shocks (time-varying vs. constant variance) and models misspecifying the way Taylor rule parameters change over time (constant vs. drifting vs. regime-switching). The model correctly identifies some changes in monetary policy parameters, even when misspecified. The inclusion of stochastic volatility greatly improves model fit even when the data is generated using constant variance exogenous shocks; this relationship is stronger in data generated from models with changing policy parameters.

Working Papers

"Adaptive Learning in Nonlinear Models"

Two separate branches of research have shown the benefits of nonlinearities in macroeconomic models and bounded rationality, respectively.  This paper joins these two branches of the literature by developing a methodology for estimating DSGE models where expectations are formed by adaptive learning, where agents behave like econometricians when forming expectations, within a nonlinear approximation of a model.  The approach is applied to a standard New Keynesian model estimated using U.S. data.  The nonlinear model with adaptive learning improves model fit and gives different results when studying underlying states compared to the linearized model or the model with rational expectations.  

"Changes in Central Bank Leadership and Inflation Dynamics" (with Irfan Qureshi)

The macroeconomic impact of changing central bank leadership is examined.  We empirically show that frequent changes in central bank leadership are associated with more volatile inflation rates.  To provide a structural explanation, we develop a new technique for estimating a nonlinear New Keynesian model where the central bank varies its response to inflation.  For a mix of developed and developing countries, we find that the stance of monetary policy often changes across governor tenures; these changes explain between 10% - 23% of the variation in inflation.