The dissertation comprises an introductory Chapter, four papers and
a summary Chapter.
First, a new class of Bayesian dynamic partition models for the Nelson-
Siegel family of non-linear state-space Bayesian statistical models is developed.
This class is applied to studying the term structure of government
yields. A sequential time series of Bayes factors, which is developed from
this approach, shows that term structure could act as a leading indicator of
economic activity.
Second, we develop a class of non-MCMC algorithms called “Direct
Sampling”. This Chapter extends the basic algorithm with applications to
Generalized Method of Moments and Affine Term Structure Models.
Third, financial economics is characterized by long-standing problems
such as the equity premium and risk free rate puzzles. In the chapter
titled “Bayesian Learning, Distributional Uncertainty and Asset-Return Puzzles” solutions for equilibrium prices under a set of subjective beliefs
generated by Dirichlet Process priors are developed. It is shown that the
“puzzles” could disappear if a “tail thickening” effect is induced by the representative
agent. A novel Bayesian methodology for retrospective calibration
of the model from historical data is developed. This approach shows
how predictive functionals have important welfare implications towards
long-term growth.
Fourth, in “Social Discounting Using a Bayesian Nonparametric model”
the problem of how to better quantify the uncertainty in long-term investments
is considered from a Bayesian perspective. By incorporating distribution
uncertainty, we are able to provide confidence measures that are less
“pessimistic” when compared to previous studies. These measures shed a
new and different light when considering important cost-benefit analysis
such as the valuation of environmental policies towards the resolution of
global warming.
Finally, the last Chapter discusses directions for future research and
concludes the dissertation. / text
| Identifer | oai:union.ndltd.org:UTEXAS/oai:repositories.lib.utexas.edu:2152/ETD-UT-2012-05-5034 |
| Date | 13 July 2012 |
| Creators | Zantedeschi, Daniel |
| Source Sets | University of Texas |
| Language | English |
| Detected Language | English |
| Type | thesis |
| Format | application/pdf |
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