Essays on self-fulfilling expectations and business cycles
Date
2018
Authors
Dai, Wei
Editors
Advisors
Weder, Mark
Groshenny, Nicolas
Wong, Jacob
Groshenny, Nicolas
Wong, Jacob
Journal Title
Journal ISSN
Volume Title
Type:
Theses
Citation
Statement of Responsibility
Conference Name
Abstract
This thesis studies the self-fulfilling business cycles in a dynamic stochastic
general equilibrium model with financial market frictions. It consists of three
papers.
The first paper uncovers a series of belief shocks (a.k.a animal spirits) that
drive the U.S. economy from both financial markets data and the structure of
a financial accelerator model with borrowing constraint. It finds that the computed belief shocks are well identified and resemble the observable proxy in the
real world. Furthermore, the model economy in which only sunspot shocks matter performs at least as well as a standard real business cycle model driven by
technology shocks in replicating major U.S. business cycle facts and it outperforms the real business cycle model in some other dimensions.
The second paper investigates the role of people's animal spirits in an estimated artificial economy with financial market frictions via Bayesian methods.
It demonstrates that people's animal spirits are prime drivers of U.S. business
cycle fluctuations. Animal spirits shocks account for well over a third of output
fluctuations over the period from 1955 to 2014. Financial friction and technology shocks are considerably less important. It also finds that a substantial
part of aggregate output's contraction during the Great Recession was caused
by adverse shocks to expectations.
The third paper follows the path of Adelman and Adelman (1959), applying
the classical business cycle method proposed by Burns and Mitchell (1946) to
evaluate the cyclical properties of an animal spirits model that is estimated
in the second paper. In particular, the paper examines whether the model
can reproduce qualitative features of U.S. business cycle. The results indicate an adequately high degree of coincidence in main macroeconomic aggregates
between the business cycle features identified in actual time series data and
those found in model economy.
School/Discipline
School of Economics
Dissertation Note
Thesis (Ph.D.) (Research by Publication) -- University of Adelaide, School of Economics, 2018
Provenance
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