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Monetary Policy, Term Premia, and Macro Volatility

Paper Session

Sunday, Jan. 6, 2019 8:00 AM - 10:00 AM

Atlanta Marriott Marquis, International B
Hosted By: Society for Nonlinear Dynamics and Econometrics
  • Chair: Hilde C. Bjørnland, BI Norwegian Business School

Fluctuations in Global Macro Volatility

Danilo Leiva-Leon
,
Bank of Spain
Lorenzo Ductor
,
Middlesex University London

Abstract

This paper investigates the dynamics, propagation and drivers of macroeconomic volatility from an global perspective. A hierarchical volatility factor model is designed to estimate and decompose the time-varying volatility of output growth across countries into global, regional, and idiosyncratic components. We fi nd that the global volatility component has been systematically declining over time, which is consistent
with a "global moderation" pattern of international business cycles. However, the influence of such global component on the output volatility across countries signifi cantly increased since the Great Recession. The volatility of exchange rate and total factor productivity, along with the level of trade openness, seem to be the main explanatory factors of changes in output volatility worldwide.

Time-varying Price Flexibility and Inflation Dynamics

Ivan Petrella
,
University of Warwick
Emiliano Santoro
,
University of Copenhagen
Lasse de la Porte Simonsen
,
Birkbeck College

Abstract

We study how and to what extent inflation dynamics is shaped by time variation in the capacity of nominal demand to stimulate price setting. In doing so, we use microdata underlying the UK consumer price index, and estimate a generalized Ss model of lumpy price adjustment. We document sizable time variation in the behavior of price flexibility, which shoots up in the aftermath of the Great Recession and rapidly falls thereafter, with both sharp movements reflecting into increased inflation volatility. These features map into a marked non-linearity of inflation dynamics with respect to the degree of price flexibility, with mean reversion being remarkably faster when prices are relatively flexible. State dependence plays a major role for price setting, with the extensive margin of price adjustment becoming prominent when inflation is particularly high and volatile. Neglecting these facts may severely limit our understanding of inflation dynamics.

(Un)expected Monetary Policy Shocks and Term Premia

Martin Kliem
,
Deutsche Bundesbank
Alexander Meyer-Gohde
,
Goethe University Frankfurt

Abstract

We analyze an estimated stochastic general equilibrium model that replicates key macroeconomic and financial stylized facts during the Great Moderation of 1983-2007. Our model predicts a sizeable and volatile nominal term premium - comparable to recent reduced-form empirical estimates - with real risk two times more important than inflation risk. The model enables us to address salient questions about the effects of monetary policy on the term structure of interest rates. We find that distinguishing
between different monetary policy actions - an ongoing challenge for empirical models - is important and can rationalize many opposing findings in the empirical literature.

The Yield Curve and the Stock Market: Mind the Long Run

Goncalo Faria
,
Catholic University of Portugal
Fabio Verona
,
Bank of Finland

Abstract

We extract cycles in the term spread (TMS) and study their role for predicting the equity risk premium (ERP) using linear models. The low frequency component of the TMS is a strong and robust out-of-sample ERP predictor. It obtains out-of-sample R-squares (versus the historical mean benchmark) of 2.09% and 22.9% for monthly and annual data, respectively. It forecasts well also during expansions and outperforms several variables that have been proposed as good ERP predictors. Its predictability power comes exclusively from the discount rate channel. Contrarily, the high and business-cycle frequency components of the TMS are poor out-of-sample ERP predictors.
Discussant(s)
Domenico Giannone
,
Federal Reserve Bank of New York
Yoosoon Chang
,
Indiana University
Jenny Tang
,
Federal Reserve Bank of Boston
Kevin Lansing
,
Federal Reserve Bank of San Francisco
JEL Classifications
  • E3 - Prices, Business Fluctuations, and Cycles
  • C5 - Econometric Modeling