Browsing by Author "Douglas K. Pearce, Committee Member"

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Information and Price Response in Storable Commodity Futures Markets: An Application to Lumber Contracts
(2007-08-20) Karali, Berna; Walter N. Thurman, Committee Chair; Douglas K. Pearce, Committee Member; Denis Pelletier, Committee Member; David A. Dickey, Committee Member
Noise Ratio As a Non-Nested Model Selection Tool.
(2009-04-27) Kurmanj, Agir; Atsushi Inoue, Committee Chair; Denis Pelletier, Committee Co-Chair; Negash G. Medhin, Committee Member; Douglas K. Pearce, Committee Member
In this dissertation, we analyze whether the noise ratio statistic of Durlauf and Hall (1989), NRT, can be used as a non-nested model selection tool in a similar fashion to the Rivers and Vuong (2002) framework. For this purpose, we first show that, when scaled by the sample size T, NRT is distributed as a mixture of chi-square random variables, under a null hypothesis of correct specification. Further, we study the asymptotic distribution of functionals of this statistic for model selection purposes, under different assumptions about: i)model specification and ii) the data generating processes of two non-nested RE models, whose parameter vector is estimated either by GMM, in Chapter 1, or by the continuous updating estimator in Chapter 2. In Chapter 3, we use Monte-Carlo simulations to compute the empirical size and empirical power of tests with statistics whose limiting distributions were studied in Chapters 1 and 2 of this dissertation. First, we use a simulation routine and compute the rejection frequency of the tests developed using these statistics, which represents empirical size under a null hypothesis and power under an alternative. Under our null hypothesis, both models are equally good from a goodness of fit perspective. Under the first alternative, the first model is better and under the second alternative hypothesis, the second model is better from a goodness of fit perspective, that. Under all scenarios covered in the first chapter, we use the limit of the noise ratio statistic evaluated at the probability limit of the GMM estimator as our goodness of fit measure. Finally, in Chapter 4, we use the model selection methodology used in Chapter 1 for comparing different formulations of the pure production smoothing model of inventories. The particular models compared are the production smoothing model of inventories and a variant of it covered in Durlauf and Maccini (1995). All statistics used for model comparison are evaluated at the GMM estimator for the corresponding model i = 1; 2.
Revealed Preference and Time Series Analyses of U.S. Macroeconomic Aggregates
(2004-08-17) Maia Filho, Luiz Flavio; John J. Seater, Committee Chair; John S. Lapp, Committee Member; Douglas K. Pearce, Committee Member; Walter N. Thurman, Committee Member
This research extends the literature on the revealed preference analysis of macroeconomic aggregates in multiple ways. The relevance of recent methodological changes in data construction is our first topic, as Varian's (1982, 1983) nonparametric tests are run on U.S. consumption series built under NIPA's old and new methods. The results indicate that previous conclusions on the overall GARP-consistency of data and on weak separability of particular aggregates are affected by the methodological changes in data. Additionally, test results are observed to be sensitive to the adoption of series at different frequencies. The issue of temporal aggregation is examined in two ways. We initially show that those changes do not seem to have significantly altered the univariate time-series properties of aggregates or previous conclusions about the impacts of temporal aggregation on those properties; therefore, the aggregation of economic flows into annual figures is once more found to involve significant losses of information about the dynamic behavior of higher-frequency data. The power of the GARP test in datasets of different frequencies is then investigated from analytical and empirical standpoints. Time aggregation is found to reduce the power of the GARP test. Finally, we apply Varian's tools to study for the first time a dataset including the value of nonmarket services produced inside the household. The modification involves a more detailed picture of consumers' allocation of time, alternatively a source of utility (leisure) or a resource in household production. We observe that the changing number of hours spent on average in household production — due to the increasing participation of women in the civilian labor force over recent decades — can be characterized as a rational decision made by the representative agent in a standard utility maximization model.
Uncertainty and Business Cycles Asymmetries
(2005-07-08) Sepulveda Umanzor, Jean Paul; John Lapp, Committee Member; Douglas K. Pearce, Committee Member; Matthew Holt, Committee Member; John J. Seater, Committee Chair
In this dissertation I investigate how macroeconomic uncertainty behaves during the business cycle, and then I present a model that can reproduce what I find in the data. I first present evidence, from surveys of expectations, that indicates that macroeconomic uncertainty is higher during expected slowdowns than during expected expansions in real GDP. I then, try to explain this theoretically. To do that, I show that the standard stochastic growth model can be expanded to include an endogenous depreciation rate, allowing it to deliver the findings previously discussed. The model generates asymmetric output fluctuations in response to symmetric productivity shocks. Business cycle asymmetries then reproduce the pattern of uncertainty described in the empirical chapter.