Thesis (Ph.D.)--Tufts University, 1980. / Submitted to the Dept. of Economics. Access restricted to members of the Tufts University community. Also available via the World Wide Web;

Thesis (Ph. D.)--University of Michigan, 1989. / Includes bibliographical references.

Thesis (Ph. D.)--University of California, Santa Barbara, 1994. / Vita. Includes bibliographical references (leaves 98-100).

No description available.

This dissertation presents a theoretical framework to analyze and evaluate aggregation biases. These biases measure the information lost when macro relations evaluated in terms of aggregates do not capture all of the distributional properties of micro relations. The framework is developed in the context of producer theory, but it may be used to determine the biasedness of any representative agent model and to study general relationships between exact-aggregation macro parameters and their microfoundations. The model is based on a stochastic interpretation of the production characteristics which encompasses that of previous stochastic aggregation models (Houthakker, 1955; Hildenbrand, 1981; Stoker, 1984; Lewbel, 1986a). It admits the construction of "true" aggregate relations which can be compared to pre-specifed macro relations. Many of Theil's (1954, 1971) statistical results concerning the relations between micro and macro parameters then can be formalized at the population level and generalized to non-linear functions. A moments decomposition of the "true" aggregate relation makes it possible to identify the sources and causes of potential aggregation biases. Thus, the functional-form restrictions of exact-aggregation models (Gorman, 1968a; Blackorby and Schworm, 1984, 1988) are found to be neither necessary nor sufficient conditions for consistent aggregation, if the aggregates are taken to be the usual totals or averages. Traditionally, similarity among firms, either as a maintained hypothesis or as the long-run outcome of perfect competition, has proved to ensure exact aggregation. Here, economic diversification may also provide an alternative set of circumstances under which the aggregation biases may be minimized. In the case of an average-representative firm, the output aggregation bias is explicitly derived. Empirical analyses confirm that the magnitude of the bias increases as higher moment terms in the production characteristics increase in importance. Conditions under which exact-aggregation macro parameters possess stable microdefinitions are obtained; they explain Fisher's (1971) simulation results. Empirical results show that such macro parameters are relatively stable (within the estimated confidence intervals) when based on periods of relative economic stability. Finally, theoretical implications for macroeconometric modeling and policy evaluation are explored. / Arts, Faculty of / Vancouver School of Economics / Graduate

Row crop production can be characterized by constant change. Agricultural technology is responsible for most of the changes in productivity observed at the field level since the advent of mechanized farm equipment. Genetically modified (GM) cotton varieties have changed many aspects of cotton production in the United States. The advent of GM varieties has been the source of altered cropping practices in cotton production. The rapid adoption of GM cotton varieties in Mississippi has allowed producers to alter certain aspects of their farming operation because of added flexibility, increased yields, and other benefits of GM varieties. This study analyses the effects of certain changes in some of the most relevant components of cotton production on yield that stem from the adoption of GM varieties in Mississippi by estimating and comparing regional production functions from 1996 to 2005.

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Xu Nan. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2006. / Includes bibliographical references (leaves 47-49). / Abstracts in English and Chinese. / Chapter 1. --- Introduction --- p.1 / Chapter 2. --- Various Preference and Technology Specifications and Indeterminacy --- p.5 / Chapter 2.1 --- CES Preference and Cobb-Douglas Technology --- p.7 / Chapter 2.2 --- Separable Utility and CES Technology --- p.16 / Chapter 2.3 --- Summary --- p.20 / Chapter 3. --- Capacity Utilization and Indeterminacy --- p.20 / Chapter 3.1 --- Separable Utility and Capacity Utilization --- p.21 / Chapter 3.2 --- Non-separable Utility and Capacity Utilization --- p.26 / Chapter 4. --- Production Depending on Average Consumption and Capital and Indeterminacy --- p.30 / Chapter 4.1 --- Production Depending on Aggregate Consumption and Capital --- p.32 / Chapter 4.2 --- Equivalence between the Two Settings --- p.36 / Chapter 5 . --- Concluding Remarks --- p.39 / Chapter 6. --- Appendix --- p.42 / Chapter 6.1 --- Properties of CES Utility Function --- p.42 / Chapter 6.2 --- Proof of Proposition 1 --- p.43 / Chapter 6.3 --- Derivation of Production Function in Section 3 --- p.45 / Chapter 6.4 --- Derivation of Depreciation Rate in subsection 3.2 --- p.46 / References --- p.47

Choi Hak. / Thesis (M.Phil.)--Chinese University of Hong Kong. / Bibliography: leaves 185-193.

Thesis (Ph. D.)--Syracuse University, 2005. / Vita. Includes bibliographical references.