Over the past 20 years, growing water demand in Spain has greatly reduced river flows into Portugal. Increasing pressures are expected on northern regions of Portugal, such as the Entre Douro e Minho (EDM), to reduce water use and improve quality. Two models, one theoretical and the other empirical, are developed to analyze water use by EDM agriculture. The theoretical model considers firms consuming and polluting water with multiple inputs, outputs, emissions, interdependent externalities, and transaction costs. The empirical model considers a flexible quadratic restricted profit model of representative farms for the region. A programming approach is followed. The Maximum Entropy technique is used to recover the profit model. An unrestricted profit function is obtained from the restricted profit function. The theoretical results show that when water externalities are interdependent it is not efficient to control each externality independently. Several policies exist to control interdependent externalities. All policies can be cost-effective, in theory. In practice, the policies have many transaction costs. The links between inputs, emissions, and ambient effects often are unknown. The focus then is on reducing farm use of inputs causing externalities. The empirical results show an inelastic response to prices. Nitrogen and water are complements. Coordination is required to reduce the use of each input. The decline of the Common Agricultural Policy (CAP) supports reduces pressure on water resources. At prices expected in 2000, the subsidies required to maintain farm profits range from three million contos (20% nitrogen reduction) to twelve million contos (20% nitrogen reduction plus 30% water reduction). However, total predicted expenditure for the subsidy program is only 3.3 million contos, which is clearly insufficient. The marginal value of water is only 5.6 esc/m3. Receiving 50 esc/m3, EDM agriculture will release 450 hm3 of water, 60% of its use.

This dissertation focuses on econometric methodology and its applications in insurance and the stock market. The second chapter proposes a new semiparametric estimator for binary-choice single-index models. The estimator makes use of a "parametric start" idea from the statistics literature and applies it to econometric model estimation. Even though the chapter only focuses on binary-choice models, it is expected that the introduction of this idea to the econometrics literature is going to contribute to semiparametric estimation of econometric models in general, especially when one has (only) a rough initial guess about the shape of the unknown function. Consistency of the estimator is shown and the simulation results indicate that even though the parametric start is not correct in any of the simulation designs, the estimator's performance is very promising in the estimation of coefficients and probabilities. The third chapter successfully applies this proposed estimator along with competing parametric and semiparametric estimators and is expected to expand our understanding of private insurance company involvement in the U.S. crop insurance program. This chapter stands almost alone in the literature as an overwhelming majority of other studies examine the involvement of producers in the program. Although preliminary, the results of this chapter show that the insurance company involvement in this program may be too costly to justify and that the program may not be as efficient in terms of premium rates and rating practices of the federal government. The fourth chapter examines market volatility taking into account the New York Stock Exchange trading collar. The trading collar restricts certain forms of trade in component stocks of the S&P500 stock price index when there is "excess" volatility in the market. This important feature of the market has been ignored in the large volatility modeling literature and it is expected that this chapter contributes to this literature by showing that after some data manipulation it is straightforward to incorporate this feature into standard econometric models. Another contribution of this chapter is the successful use of a polynomial specification to capture the well documented U-shaped pattern of intraday market volatility instead of a computationally more difficult two-step procedure.

Arizona apple producers compete with Washington for fresh apple markets. As Arizona's apple production increases, its market share should also increase. Using quadratic programming to determine the spatial equilibrium between the wholesale markets of Los Angeles and Denver, the timing and quantity of apple sales from Arizona to these two wholesale markets are determined for current and potential fresh apple production in Arizona. The quadratic programming model is used to determine the feasibility of controlled atmosphere storage for Arizona. The quantity of apples sold monthly to Los Angeles and Denver wholesale markets are determined given restrictions on the percentage of the wholesale markets that Arizona apple producers could supply. Revenue from controlled atmosphere storage exceeds the variable costs associated with storage, marketing, and storage of apples.

Previous variability studies in both U.S. and worldwide agriculture have indicated that crop production has been accompanied by increasing variation. In this research, four different variability indexes were estimated in order to evaluate the production variability associated with the major Arizona field crops. Results show that major Arizona field crops, which are all irrigated, did not have a uniform production variability over the last 24 years and the variability of these crops did not generally increase between the periods of 1967-1978 and 1979-1990. Although biological factors (e.g. pests, weather) influenced variability, the variation of crop production measures over time also was related to market factors (e.g. prices), government farm programs, producers' crop management experience, and the geographical area selected for the analysis. Crops covered by government farm programs usually varied more in harvested acreage and fluctuated less in yield per acre than vegetable crops.

Many studies have proposed expansion of photosynthetic biomass "sinks" as a method of controlling atmospheric carbon dioxide. A defect in most of these studies is that biomass growth is assumed to be linear. In this thesis, optimal control theory is applied to an economic analysis of the interactions between global photosynthetic biomass growth and atmospheric CO2. The model assumes society starts with a fossil fuel resource endowment, which is used to supply energy. One goal is to determine numerically, using a "natural" model of the system, whether a steady state is reached in, the interactions between the biosphere and the atmosphere once the use of fossil fuel ceases. The thesis also determines, through a planet-level numeric simulation, optimal biomass and CO2 levels, and their associated "shadow prices" that would be required to ensure an efficient outcome in the presence of negative externalities associated with atmospheric CO2 (the "global warming problem"). The optimal solution is tested for sensitivities to changes in parameter values, including a "policy variable" of CO2 "tolerance". Biological growth is modeled by the logistic function, and CO2 sequestration is based on a non-linear C3 plant CO2 "fertilization" scheme. Alternative model structures to the logistical function are proposed and discussed. The model structure and numerical analysis derives some of its parameters from previous studies and estimations, but mainly the work of Hirofumi Uzawa.

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<p> This dissertation investigates the dairy farming industry in the Northeastern United States and, in particular, the key drivers of economic viability and competitive advantage for small and midscale commercial dairy producers. The research approach employed was a literature review combined with primary case study observation and data collection. Historical perspective has been presented to provide an overarching contextual framework for this study. Four dairy farms were purposefully selected for case study research because they represented various aspects of a pre-defined set of variables and because they demonstrated relevant similarities as well as significant differences in terms of alternative business strategy. The classical business opportunity analytical process has been customized for practical use application by small and midscale dairy farmers. This tailored process has been validated using research findings; it offers a fresh way of identifying a strategic approach in pursuit of economic viability and competitive advantage that best fits an operation's unique set of characteristics. This process is intended for practical use application on a broader scale by dairy farmers in the Northeast to facilitate their understanding of challenging industry dynamics, of emergent market opportunity and inherent potency, and of both internal and external hurdles to be overcome. Finally, recommendations for next steps have been presented.</p>

Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2006. / Source: Dissertation Abstracts International, Volume: 68-02, Section: A, page: 0652. Adviser: Amy W. Ando. Includes bibliographical references (leaves 145-154) Available on microfilm from Pro Quest Information and Learning.

Thesis (Ph.D.)--University of California, Davis, 2005. / (UnM)AAI3191201. Source: Dissertation Abstracts International, Volume: 66-10, Section: A, page: 3746. Adviser: Richard Howitt.

Thesis (Ph.D.)--Washington State University, 2005. / (UMI)AAI3242022. Adviser: Jan R. Busboom. Source: Dissertation Abstracts International, Volume: 67-11, Section: B, page: 6127.