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Sentiment and the US Business Cycle

Relatore: Prof. Fabio Milani, California University, Irvine. Il Prof. Milani è ospite del Dipartimento nell’ambito del progetto Visiting dell’Università di Perugia.
Introduce: Cristiano Perugini
martedì 15 settembre 2015
ore 14.00
Aula 23


Psychological factors are commonly believed to play a role on cyclical economic fluctuations,
but they are typically omitted from state-of-the-art macroeconomic models.
This paper introduces “sentiment” in a medium-scale DSGE model of the U.S. economy and
tests the empirical contribution of sentiment shocks to business cycle fluctuations.
The assumption of rational expectations is relaxed. The paper exploits, instead, observed data
on expectations in the estimation. The observed expectations are assumed to be formed from a
near-rational learning model. Agents are endowed with a perceived law of motion that resembles the
model solution under rational expectations, but they lack knowledge about the solution’s reducedform
coefficients. They attempt to learn those coefficients over time using available time series
at each point in the sample and updating their beliefs through constant-gain learning. In each
period, however, they may form expectations that fall above or below those implied by the learning
model. These deviations capture excesses of optimism and pessimism, which can be quite persistent
and which are defined as sentiment in the model. Different sentiment shocks are identified in
the empirical analysis: waves of undue optimism and pessimism may refer to expected future
consumption, future investment, or future inflationary pressures.
The results show that exogenous variations in sentiment are responsible for a sizable (above
forty percent) portion of historical U.S. business cycle fluctuations. Sentiment shocks related to
investment decisions, which evoke Keynes’ animal spirits, play the largest role. When the model is
estimated imposing the rational expectations hypothesis, instead, the role of structural investmentspecific
and neutral technology shocks significantly expands to capture the omitted contribution of

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