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News, Information and the Business Cycle

Paper Session

Sunday, Jan. 7, 2018 1:00 PM - 3:00 PM

Pennsylvania Convention Center, 203-B
Hosted By: American Economic Association
  • Chair: Moto Shintani, Vanderbilt University

The Effects of Federal Reserve Forward Guidance and Asset Purchases on Financial Markets: Which Worked Better?

Eric Swanson
University of California-Irvine


I extend the methods of Gurkaynak, Sack, and Swanson (2005) to separately identify the effects of Federal Reserve forward guidance and large-scale asset purchases (LSAPs) during the 2009–15 U.S. zero lower bound (ZLB) period. I find that both forward guidance and LSAPs had substantial and highly statistically significant effects on medium-term Treasury yields, stock prices, and exchange rates, comparable in magnitude to the effects of the federal funds rate before the ZLB. Forward guidance was more effective than LSAPs at moving short-term Treasury yields, while LSAPs were more effective than forward guidance and the federal funds rate at moving longer-term Treasury yields, corporate bond yields, and interest rate uncertainty. However, the effects of forward guidance were not very persistent, with a half-life of 1–4 months. The effects of LSAPs seem to be more persistent. I conclude that, overall, LSAPs were a more effective policy tool than forward guidance during the ZLB period.

News or Noise? The Missing Link

Kyle Jurado
Duke University
Ryan Chahrour
Boston College


The macroeconomic literature on belief-driven business cycles treats news and noise as distinct representations of people's beliefs about economic fundamentals. We prove that these two representations are empirically the same. Our result allows us to determine the importance of beliefs as an independent source of fluctuations. Using three prominent models from this literature, we show that existing research has understated the importance of independent shocks to beliefs. This is because news shocks mix the fluctuations due independently to beliefs with the fluctuations due to fundamentals. Our result also implies that structural vector autoregression analysis is equally applicable to models with news or noise shocks. We demonstrate this in a sample of postwar U.S. data, and find that productivity shocks are only responsible for 7 percent of the fluctuations in aggregate consumption. Any model in which beliefs about productivity are the main determinant of consumption must therefore involve fluctuations in beliefs about productivity that are mostly unrelated to productivity itself.

News Shocks Under Financial Frictions

Christoph Gortz
University of Birmingham
John Tsoukalas
University of Glasgow
Francesco Zanetti
University of Oxford


We examine the dynamic effects and empirical role of TFP news shocks in the context of frictions in financial markets. We document two new facts using VAR methods. First, a (positive) shock to future TFP generates a significant decline in various credit spread indicators considered in the macro-finance literature. The decline in the credit spread indicators is associated with a robust improvement in credit supply indicators, along with a broad based expansion in economic activity. Second, it is striking that VAR methods also establish a tight link between TFP news shocks and shocks that explain the majority of un-forecastable movements in credit spread indicators. These two facts provide robust evidence on the importance of movements in credit spreads for the propagation of news shocks. A DSGE model enriched with a financial sector of the Gertler-Kiyotaki-Karadi type generates very similar quantitative dynamics and shows that strong linkages between leveraged equity and excess premiums, which vary inversely with balance sheet conditions, are critical for the amplification of TFP news shocks. The consistent assessment from both methodologies provides support for the traditional `news view' of aggregate fluctuations.

Components of Uncertainty

Vegard Høghaug Larsen
Norges Bank


Uncertainty is frequently highlighted as a source of economic fluctuations. Does
the type of uncertainty matter for the economy’s response to an uncertainty shock?
This paper introduces an identification strategy to disentangle different types of
uncertainty. I use machine learning techniques to classify different types of news
instead of specifying a set of keywords. I show that, depending on the source,
uncertainty may have different effects on the same macroeconomic variables. I find
that both good (positive response) and bad (negative response) types of uncertainty
JEL Classifications
  • E3 - Prices, Business Fluctuations, and Cycles