7 resultados para Comprehensive economic and financial analysis

em Digital Commons at Florida International University


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Marine Areas for Responsible Artisanal Fishing (AMPR) have emerged as a new model for co-managing small-scale fisheries in Costa Rica, one that involves collaboration between fishers, government agencies and NGOs. This thesis aims to examine the context for collective action and co-management by small-scale fishers; evaluate the design, implementation, and enforcement of AMPRs; and conduct a linguistic analysis of fisheries legislation. The present work relies on the analysis of several types of qualitative data, including interviews with 23 key informants, rapid rural assessments, and legal documents. Findings demonstrate the strong influence of economic factors for sustaining collective action, as well as the importance of certain types of external organizations for community development and co-management. Additionally, significant enforcement gaps and institutional deficiencies were identified in the work of regulating agencies. Legal analysis suggests that mechanisms for government accountability are unavailable and that legal discourse reflects some of the most salient problems in management.

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This study analyzed the health and overall landcover of citrus crops in Florida. The analysis was completed using Landsat satellite imagery available free of charge from the University of Maryland Global Landcover Change Facility. The project hypothesized that combining citrus production (economic) data with citrus area per county derived from spectral signatures would yield correlations between observable spectral reflectance throughout the year, and the fiscal impact of citrus on local economies. A positive correlation between these two data types would allow us to predict the economic impact of citrus using spectral data analysis to determine final crop harvests.

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Financial innovations have emerged globally to close the gap between the rising global demand for infrastructures and the availability of financing sources offered by traditional financing mechanisms such as fuel taxation, tax-exempt bonds, and federal and state funds. The key to sustainable innovative financing mechanisms is effective policymaking. This paper discusses the theoretical framework of a research study whose objective is to structurally and systemically assess financial innovations in global infrastructures. The research aims to create analysis frameworks, taxonomies and constructs, and simulation models pertaining to the dynamics of the innovation process to be used in policy analysis. Structural assessment of innovative financing focuses on the typologies and loci of innovations and evaluates the performance of different types of innovative financing mechanisms. Systemic analysis of innovative financing explores the determinants of the innovation process using the System of Innovation approach. The final deliverables of the research include propositions pertaining to the constituents of System of Innovation for infrastructure finance which include the players, institutions, activities, and networks. These static constructs are used to develop a hybrid Agent-Based/System Dynamics simulation model to derive propositions regarding the emergent dynamics of the system. The initial outcomes of the research study are presented in this paper and include: (a) an archetype for mapping innovative financing mechanisms, (b) a System of Systems-based analysis framework to identify the dimensions of Systems of Innovation analyses, and (c) initial observations regarding the players, institutions, activities, and networks of the System of Innovation in the context of the U.S. transportation infrastructure financing.

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Federal transportation legislation in effect since 1991 was examined to determine outcomes in two areas: (1) The effect of organizational and fiscal structures on the implementation of multimodal transportation infrastructure, and (2) The effect of multimodal transportation infrastructure on sustainability. Triangulation of methods was employed through qualitative analysis (including key informant interviews, focus groups and case studies), as well as quantitative analysis (including one-sample t-tests, regression analysis and factor analysis). ^ Four hypotheses were directly tested: (1) Regions with consolidated government structures will build more multimodal transportation miles: The results of the qualitative analysis do not lend support while the results of the quantitative findings support this hypothesis, possibly due to differences in the definitions of agencies/jurisdictions between the two methods. (2) Regions in which more locally dedicated or flexed funding is applied to the transportation system will build a greater number of multimodal transportation miles: Both quantitative and qualitative research clearly support this hypothesis. (3) Cooperation and coordination, or, conversely, competition will determine the number of multimodal transportation miles: Participants tended to agree that cooperation, coordination and leadership are imperative to achieving transportation goals and objectives, including targeted multimodal miles, but also stressed the importance of political and financial elements in determining what ultimately will be funded and implemented. (4) The modal outcomes of transportation systems will affect the overall health of a region in terms of sustainability/quality of life indicators: Both the qualitative and the quantitative analyses provide evidence that they do. ^ This study finds that federal legislation has had an effect on the modal outcomes of transportation infrastructure and that there are links between these modal outcomes and the sustainability of a region. It is recommended that agencies further consider consolidation and strengthen cooperation efforts and that fiscal regulations are modified to reflect the problems cited in qualitative analysis. Limitations of this legislation especially include the inability to measure sustainability; several measures are recommended. ^

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This dissertation addressed two broad problems in international macroeconomics and conflict analysis. The first problem in the first chapter looked at the behavior of exchange rate and its interaction with industry-level tradable goods prices for three countries, USA, UK and Japan. This question has important monetary policy implications. Here, I computed to what extent changes in exchange rate affected prices of consumer, producer, and export goods. I also studied the timing of these changes in these prices. My results, based on thirty-four industrial prices for USA, UK and Japan, supported the view that changes in exchange rates significantly affect prices of industrial and consumer goods. It also provided an insight to the underlying economic process that led to changes in relative prices. ^ In the second chapter, I explored the predictability of future inflation by incorporating shocks to exchange rates and clearly specified the transmission mechanisms that link exchange rates to industry-level consumer and producer prices. Employing a variety of linear and state-of-the-art nonlinear models, I also predicted growth rates of future prices. Comparing levels of inflation obtained from the above approaches showed superiority of the structural model incorporating the exchange rate pass-through effect. ^ The second broad issue addressed in the third chapter of the dissertation investigated the economic motives for conflict, manifested by rebellion and civil war for seventeen Latin American countries. Based on the analytical framework of Garfinkel, Skaperdas and Syropoulos (2004), I employed ordinal regressions and Markov switching for a panel of seventeen countries to identify trade and openness factors responsible for conflict occurrence and intensity. The results suggested that increased trade openness reduced high intensity domestic conflicts but overdependence on agricultural exports, along with a lack of income earning opportunities lead to more conflicts. Thereafter, using the Cox Proportional Hazard model I studied “conflict duration” and found that over-reliance on agricultural exports explained a major part of the length of conflicts in addition to various socio-political factors. ^

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Hydrophobicity as measured by Log P is an important molecular property related to toxicity and carcinogenicity. With increasing public health concerns for the effects of Disinfection By-Products (DBPs), there are considerable benefits in developing Quantitative Structure and Activity Relationship (QSAR) models capable of accurately predicting Log P. In this research, Log P values of 173 DBP compounds in 6 functional classes were used to develop QSAR models, by applying 3 molecular descriptors, namely, Energy of the Lowest Unoccupied Molecular Orbital (ELUMO), Number of Chlorine (NCl) and Number of Carbon (NC) by Multiple Linear Regression (MLR) analysis. The QSAR models developed were validated based on the Organization for Economic Co-operation and Development (OECD) principles. The model Applicability Domain (AD) and mechanistic interpretation were explored. Considering the very complex nature of DBPs, the established QSAR models performed very well with respect to goodness-of-fit, robustness and predictability. The predicted values of Log P of DBPs by the QSAR models were found to be significant with a correlation coefficient R2 from 81% to 98%. The Leverage Approach by Williams Plot was applied to detect and remove outliers, consequently increasing R 2 by approximately 2% to 13% for different DBP classes. The developed QSAR models were statistically validated for their predictive power by the Leave-One-Out (LOO) and Leave-Many-Out (LMO) cross validation methods. Finally, Monte Carlo simulation was used to assess the variations and inherent uncertainties in the QSAR models of Log P and determine the most influential parameters in connection with Log P prediction. The developed QSAR models in this dissertation will have a broad applicability domain because the research data set covered six out of eight common DBP classes, including halogenated alkane, halogenated alkene, halogenated aromatic, halogenated aldehyde, halogenated ketone, and halogenated carboxylic acid, which have been brought to the attention of regulatory agencies in recent years. Furthermore, the QSAR models are suitable to be used for prediction of similar DBP compounds within the same applicability domain. The selection and integration of various methodologies developed in this research may also benefit future research in similar fields.

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The purpose of this research was to determine what challenges small-scale organic farmers face in choosing their particular production, marketing, and organizational strategies in Miami-Dade County. Rapid soil assessments were used on six organic farms to determine the effects of soil nutrient management in terms of pH, soil organic matter (SOM), and phosphorus (P). Potential costs of inputs were documented for each farm to determine the largest challenges facing the profitability of organic farms. A production, marketing, and organizational analysis determined how farmers shape their inter-farm competitive and cooperative relations. Preliminary findings from soil, input, labor, marketing, and organizational factors indicate that soil health varies dramatically from farm to farm, inputs and labor constitute significant costs, and marketing, production, and organizational strategies show no signs of immediate growth.