Econometrics of Uncertainty

Paper Session

Friday, Jan. 6, 2017 8:00 AM – 10:00 AM

Hyatt Regency Chicago, Grand Suite 3
Hosted By: American Economic Association
  • Chair: Laurent Ferrara, Bank of France

Understanding the Sources of Macroeconomic Uncertainty

Tatevik Sekhposyan
,
Texas A&M University
Barbara Rossi
,
ICREA-Pompeu Fabra University, Barcelona GSE and CREI

Abstract

We propose a decomposition to distinguish between Knightian uncertainty (ambiguity) and risk, where the first measures the uncertainty on the probability distribution generating the data, while the second measures uncertainty about the odds of particular outcomes when the probability distribution is known. We use Survey of Professional Forecaster's (SPF) density forecasts to quantify overall uncertainty as well as the evolution of the different components of uncertainty over time and investigate their importance for macroeconomic fluctuations. We also study the impact effect of the components of our decomposition in a structural model that features ambiguity and risk.

Economic Policy Uncertainty Spillovers in Booms and Busts

Giovanni Caggiano
,
University of Padua
Efrem Castelnuovo
,
University of Melbourne
Juan Manuel Figueres
,
University of Padua

Abstract

We estimate a nonlinear VAR to quantify the impact of economic policy uncertainty shocks originating in the U.S. on the Canadian business cycle in booms and busts. We find strong evidence in favor of asymmetric spillover effects. Uncertainty shocks originating in the U.S. explain about 12% of the variance of the 2-year ahead forecast error of the Canadian unemployment rate in periods of slack vs. just 2% during economic booms. Counterfactual simulations lead to the identification of a novel "economic policy uncertainty spillovers channel". According to this channel, spikes in U.S. economic policy uncertainty foster economic policy uncertainty in Canada in first place and, because of the latter, lead to a temporary increase in the Canadian unemployment rate. This channel is shown to work only in periods of slack. U.S. EPU shocks are shown to induce nonlinear unemployment responses in all G7 economies plus Brazil.

Macroeconomic Uncertainty Through the Lens of a Mixed-Frequency Panel Markov-Switching Model

Francesco Ravazzolo
,
Free University of Bozen-Bolzano
Roberto Casarin
,
University of Venice
Claudia Foroni
,
Norges Bank
Massimiliano Marcelino
,
Bocconi University

Abstract

We propose a Bayesian panel model for mixed frequency data whose parameters can change over time according to a Markov process. We develop a proper MCMC algorithm for sampling from the joint posterior distribution of the model parameters and test its properties in a simulation experiment. We use the model to study the effects of macroeconomic uncertainty, measured as forecast disagreement, and financial uncertainty, measured as stock market volatility, on a set of variables in a multi-country context including the US, several European countries and Japan. We find that for most of the variables financial uncertainty dominates macroeconomic uncertainty. Furthermore, we show that uncertainty coefficients differ if the economy is in a recession regime or an expansion regime.

What are the Macroeconomic Effects of High-Frequency Uncertainty Shocks?

Laurent Ferrara
,
Bank of France
Pierre Guerin
,
Bank of Canada

Abstract

This paper evaluates the effects of high-frequency uncertainty shocks on a set of low-frequency macroeconomic variables representative of the U.S. economy. Rather than estimating models at the same common low-frequency, we use recently developed econometric models, which allows us to deal with data of different sampling frequencies. We find that credit and labor market variables react the most to uncertainty shocks in that they exhibit a prolonged negative response to such shocks. When looking at detailed investment sub-categories, our estimates suggest that the most irreversible investment projects are the most affected by uncertainty shocks. We also find that the responses of macroeconomic variables to uncertainty shocks are relatively similar across single-frequency and mixed-frequency data models, suggesting that the temporal aggregation bias is not acute in this context.
Discussant(s)
Todd Clark
,
Federal Reserve Bank of Cleveland
James D. Hamilton
,
University of California-San Diego
John Rogers
,
Federal Reserve Board
Jonathan Wright
,
Johns Hopkins University
JEL Classifications
  • C0 - General
  • E0 - General