Joseph Vavra, Assistant Professor of Economics, studies macroeconomics and monetary economics, labor, and computational economics. In his recent research he argues that monetary policy is less effective during volatile recessions. He also has work studying how durable consumption responds to stimulus, and how prices respond to exchange rate movements.
Vavra holds multiple degrees (Ph.D., M.Phil., M.A.) all in economics from Yale University. Additionally, he earned a B.A. (magna cum laude) in math, mathematical economic analysis, and statistics from Rice University.
In addition to Vavra’s teaching fellow and research assistant positions, he has experience working as an intern at the White House Council of Economic Advisors. His interests outside of economics include scuba diving, food, and travel.
2014 - 2015 Course Schedule
||Applied Macroeconomics: Heterogeneity and Macro
Food, scuba diving, snowboarding
My research interests are in empirical macroeconomics, business cycles and monetary policy, with a particular focus on the implications of microdata for aggregate phenomenon and on whether the same policies may have different effects if engaged during different phases of the business cycle.
REVISION: Inflation Dynamics and Time-Varying Volatility: New Evidence and an Ss Interpretation
Is monetary policy less effective at increasing real output during periods of high volatility than during normal times? In this paper, I argue that greater volatility leads to an increase in aggregate price flexibility so that nominal stimulus mostly generates inflation rather than output growth. To do this, I construct price-setting models with "volatility shocks" and show these models match new facts in CPI micro data that standard price-setting models miss. I then show that these models imply
REVISION: Dynamics of the U.S. Price Distribution
Allowing for price adjustment probabilities that vary with the number of periods since an item last adjusted ('duration-dependence') provides a significantly better fit of observed price spells in CPI and grocery store micro data than the Calvo model, even if the latter is extended to incorporate item-specific adjustment probabilities. Furthermore, extending the Calvo model to match both duration-dependence and cross-item heterogeneity, as observed in the micro data, leads to an increase of 100-