No description available.

Thesis (M.Sc.(Agric.))(Agricultural Economics)--University of Pretoria, 2005. / Includes summary. Includes bibliographical references.

The overall objective of this study is to develop a framework to predict the impacts of government policies on agricultural production in Albania. The specific goal of this study is to provide some empirical estimates of the farmers' short-run supply response to government policies that effect output and input prices. Different theoretical approaches to integrating the questions this study purports to answer were considered. Two models were deemed as most appropriate for Albanian agriculture. The first is a semi-commercial farm household model and the second is the well-known indirect profit function model. The first model was preferred. However, the second was used instead, due to the lack of information necessary for an empirical application of the semi-commercial farm household model. A quadratic functional form was selected to approximate the profit function. It satisfied the Taylor series approximation convergence test. Two approaches were used to estimate the empirical model. In the first, the traditional approach, the symmetry and homogeneity conditions were imposed beforehand and then the system of equations was estimated using the ITSUR procedure in SAS. Following common practice, a joint Rao test of these conditions was conducted, implicitly assuming that the test statistic has a Fisher distribution or, stated differently, assuming that parameter estimators are normally distributed. The test results indicate that the conditions are met. A second approach, proposed by McGuirk, et al., was also used in this study. The approach proposed by McGuirk, et al., requires that, before imposing and/or testing any theoretical assumption, the unrestricted model is estimated and tested to see if all the underlying statistical assumptions of the linear regression are met. The misspecification tests suggested that the model is not statistically adequate. This finding indicated that the theoretical test conducted in the traditional approach was invalid. An alternative estimation procedure is proposed in the study for cases when a statistically adequate model cannot be specified. Named the sub-sample or the bootstrapping method, this procedure consists of randomly selecting a large number of sub-samples from the cross-sectional sample and running a regression for each of them. The large number of estimates for each of the coefficients serves as a basis for estimating 95-percent confidence intervals. An inspection of the supply and input demand elasticities calculated based on coefficients estimated through the sub-sample method revealed that half of them have wide 95 percent confidence intervals. Therefore, predicting policy impacts across all output and input equations is not possible. However, elasticities that have narrow confidence intervals and make economic sense can be used to predict isolated policy impacts, if Albania returns to the conditions that prevailed before the political turmoil of 1997. / Ph. D.

Ninety Merino ewes, divided into three equal groups, were kept on natural highveld grazing for 42 weeks. Group M received a mineral supplement continuously, averaging 28 g per day. The other groups received commercial protein supplements, group RDP a mainly rumen degradable supplement and group RUP, a mainly rumen undegradable supplement. These supplements had crude protein (CP) levels of 29% and 28% respectively and were supplied at strategic times during the reproductive cycle, at 250 g per ewe per day for 14 days before mating, at 350 g per ewe per day for 42 days, starting 21 days before lambing and at 500 g per ewe per day for 56 days, starting 21 days after lambing. Grazing was randomized to minimize differences in nutrition and parasite challenge, and had an average CP of 8.8%. Lambing rates were: RUP 96%, RDP 89% and M 76%. Lamb survival rates at 11 and 17 weeks post lambing were 75%&63% for RUP, 64%&57% for RDP and 55% and 48% for M respectively (P< 0.05). Wool production parameters were similar for all groups, as were mean faecal egg counts: 685 (RUP), 371 (RDP) and 465 (M). Body weights, body condition scores and FAMACHA scores were also similar for all three groups. Income per ewe, calculated at 11 and 17 weeks post lambing, was highest for RUP at R147.80&R132.87, lowest for M at R117.86&R111.13, and in between for RDP (R129.85&R121.38). However, the gross margin was the highest for M at both points (R114.35&R107.77) compared to RUP (R70.43&R54.93 – P < 0.03&P < 0.008 respectively), as well as RDP (R82.96&R74.12). Strategic supplementation with protein improved performance but the additional income was not sufficient to cover feed costs under prevailing conditions and neither supplement could therefore be economically justified. / Dissertation (MMedVet)--University of Pretoria, 2002. / Production Animal Studies / unrestricted

This dissertation is centered on applying `nonlinearity' across various fields, a decision informed by the understanding that linear models frequently fail to capture the full extent of real-world complexities. This approach is driven by the distinct insights that nonlinearity offers, insights crucial for a more profound and precise understanding of diverse phenomena. In this regard, I have explored a variety of empirical methodologies and theoretical frameworks, each chosen for its effectiveness in unraveling and accurately depicting the complexity inherent in different subjects. The first paper, "Warming Temperatures and Potential Adaptation through Breeding: Evidence from U.S. Soft Winter Wheat," examines the impact of climate change on wheat production. Given wheat's role as a major staple for much of the global population, its susceptibility to rising temperatures presents significant challenges to food security. Despite its importance, comprehensive production data for wheat considering extensive U.S. regions is relatively scarce. To address this, I compiled a unique dataset on wheat production comprising 35,000 observations over 50 years from USDA-ARS hard-copy publications. Findings obtained through the mixed-effects model reveal significant variations in the influence of nonlinearly specified temperature on wheat production. This analysis identifies a decline not only in wheat yield across various U.S. farming sites but also in wheat quality, an aspect often neglected in similar studies. The issue is further compounded by simulations I conducted, which predict worrying decreases in both yield and quality due to rising temperatures. Despite these challenges, my analysis of varietal improvements indicates modest yet significant progress in countering the effects of warming, offering viable strategies for agricultural adaptation. In the second chapter, "Semiparametric Analysis of Out-farm Migration in China," I explore the nonlinear relationship between sectoral migration and the income gap within China. This work builds on my co-authored publication, "Intersectoral Labor Migration and Agriculture in the United States and Japan," published in Agricultural Economics. While the earlier study employed discrete thresholds and kink approaches to explore migration patterns in developed countries such as Japan and the United States, it did not reveal significant nonlinear relationships. This led me to investigate whether the results were influenced by the economic development status of the countries in question. Focusing on China, a developing country with distinct labor dynamics, I employ semiparametric methodologies to assess migration patterns, diverging from the linear assumptions common in existing literature. By using nationally representative data, it suggests a potential nonlinear relationship between farmers' sectoral migration and the income gap, providing new insights into labor migration in developing contexts. The last chapter, "Enhanced Salience of Nonlinear Pricing and Energy Conservation," explores the energy consumption of residents of Hanoi in Vietnam, using a large-scale randomized control trial. I study whether enhancing salience of information with respect to the nonlinear pricing can help energy conservation. The novelty of the project lies in its experimental design and the utilization of digital tools such as smart meters and mobile apps, adopting technologies with the potential to alter consumer behavior. Currently, we are in the post-intervention data collection phase. Supported by the International Growth Centre (IGC), the project aims to bridge the research gap in energy consumption behavior in developing countries, thereby contributing to policymaking in energy management and development in these regions. Through these diverse yet interconnected chapters, I attempt to use the varied applications of nonlinearity in studying economic and environmental issues. The main objective is to contribute to both academic knowledge and practical policymaking in these fields, addressing complexities that are often oversimplified. This approach aims to provide a more comprehensive understanding of the intricate dynamics in these areas. / Doctor of Philosophy / This dissertation focuses on the application of `nonlinearity' across various fields, acknowledging that linear models often fail to fully capture the complexities of real-world scenarios. This approach yields essential insights for a more precise understanding of diverse phenomena, incorporating a range of empirical methods and theoretical models, each selected for their efficacy in accurately depicting complexities in various subjects. The first part of my dissertation examines the agricultural sector, specifically the impact of weather on crop yields. Instead of traditional methods that use basic temperature data like minimum, maximum, or average values, I use a nonlinear approach that aligns with the specific growth stages of crops. In the area of labor economics, the dissertation explores migration patterns in China. It questions the traditional linear relationship between migration and income disparities, suggesting a more complex model that better represents the dynamics of a developing economy. The final chapter addresses the field of energy policy, examining consumer responses to nonlinear electricity pricing models in practice. This section explores the challenges faced by individuals in understanding such policies and assesses the impact of providing real-time information about nonlinear pricing on promoting energy conservation.

A cidade de São Paulo, que abriga 11 milhões de habitantes, sofre constantemente os efeitos dos alagamentos provocados pelas precipitações intensas. Esses alagamentos ocorrem todo verão, em diversas partes da cidade. Além das perdas e inconvenientes sofridos pelos residentes, os alagamentos produzem prejuízos que ultrapassam as fronteiras da cidade, afetando a renda e o produto da região metropolitana, de outras partes do estado e do país. O objetivo desse estudo é avaliar os impactos econômicos dos alagamentos na cidade de São Paulo por meio do uso de um modelo espacial de Equilíbrio Geral Computável, integrado a informações georreferenciadas relacionadas à localização dos pontos de alagamento e às firmas dentro dos raios de influência. Estima-se que os alagamentos contribuem para a redução do crescimento da cidade e do bem estar de seus residentes, além de prejudicar a competitividade local nos mercados doméstico e internacional. Foi identificada uma taxa de dano intra-cidade de 2,1, e uma taxa de impacto total de 4,9 para a economia brasileira. / The city of São Paulo, home to 11 million people, suffers constantly the effects of flooding caused by extreme precipitation. Localized floods occur every summer in various parts of the city. Besides the losses and inconvenience felt by the residents, floods produce damages that cross the city boundaries, affecting income and output in the metropolitan area as well as in other parts of the state and the country. The objective of this study is to evaluate the economic impacts of floods in the city of São Paulo through the use of a spatial Computable General Equilibrium model integrated to GIS information related to the location of points of floods and the firms within their influence. It is estimated that floods contributed to reduce city growth and residents welfare, as well as to hamper local competitiveness in both domestic and international markets. An intra-city total impact-damage ratio of 2.1 and an economy-wide total impact-damage ratio of 4.9 were found.

O setor primário da região de Marília tem passado por crises periódicas, em função do comportamento cíclico de preços e produção do café, sua principal atividade agropecuária. Com isso, a receita dos cafeicultores está sujeita a sensíveis oscilações a cada ano, sugerindo um elevado nível de risco econômico. Como parte do Projeto de Apoio à Competitividade Global da Cultura do Maracujazeiro na Região de Vera Cruz, SP - AFRUVEC/Bioex-CNPq essa dissertação tem como objetivo avaliar o comportamento dos cafeicultores da região de Marília na presença do risco. Uma vez que o grau de aversão ao risco dos agricultores é refletido na escolha dos planos de exploração agropecuária, inicialmente desenvolveu-se uma metodologia para identificar os sistemas de produção de café existentes na região. Essa identificação baseou-se na elaboração e análise de grupos focais e validação dos resultados através de análise discriminante. Assim, foram identificados os sistemas "monocultura de café", "cafeicultura e pecuária" e "pequena propriedade diversificada". Posteriormente, selecionou-se uma propriedade típica de cada sistema para o estudo do comportamento dos agricultores perante o risco. A programação linear foi a técnica utilizada na modelagem dos sistemas de produção. Para a geração das fronteiras de eficiência, que refletem o trade-off entre rendimento e risco, foi empregado o MOTAD. Os resultados dessa pesquisa indicam que o produtor do sistema cafeicultura e pecuária é mais averso ao risco do que o monocultor. Esse comportamento era esperado, pois as margens brutas da pecuária são negativamente correlacionadas com as do café, indicando que a combinação dessas atividades é eficiente do ponto de vista da redução do risco. No entanto, constatou-se que o pequeno produtor diversificado é menos averso ao risco do que o monocultor, contrariando as hipóteses iniciais do trabalho. Esse comportamento pode ser explicado pela estratégia de diversificação adotada pelo agricultor, que optou por investir em diversas espécies frutíferas e na cafeicultura. Grande parte das frutas possui maior grau de risco que o café e, além disso, muitas dessas atividades são positivamente correlacionadas, o que reduz a eficiência da diversificação na minimização dos riscos do sistema. Com isso, pode-se afirmar que o objetivo principal da diversificação da pequena propriedade é a elevação da margem bruta do sistema, pois somente com a cafeicultura o produtor não obteria renda suficiente para permanecer na atividade. A grande contribuição dessa pesquisa é mostrar e divulgar a situação dos pequenos cafeicultores, a importância da diversificação para os mesmos e abrir espaço para a realização de outros estudos na região de Marília. É muito importante que futuras pesquisas levantem alternativas de cultivo para elevar a renda dos pequenos produtores da região, considerando estudos de mercado e identificação de canais de comercialização. Por outro lado, também seria interessante aprofundar o estudo da situação dos pequenos produtores inseridos em outros sistemas que não incluam a cafeicultura, para se ter uma visão mais abrangente dos problemas enfrentados e definir ações efetivas para o desenvolvimento regional. / Marília's region primary sector has passed for periodic crises because of coffee prices and cyclical production behavior. The coffee farmers' income is subject to sensible oscillations each year, suggesting a high level of economic risk. As part of the Passion Fruit Global Competitiveness Support Project in the region of Vera Cruz, SP - AFRUVEC/Bioex-CNPq, the objective of this thesis is to evaluate risk behavior of the Marília's region coffee farmers. Once the degree of farmers' aversion to risk is reflected in the choice of the farming plans, a methodology was initially developed to identify the coffee production systems in the region. This identification was based on focus groups analysis and the results validated through discriminant analysis. Thus, three production systems were identified: "single crop farm coffee", "coffee and cattle" and "small diversified farm". A typical farm for each system was selected for analysing farmers' behavior in the presence of risk. Linear programming technique was used for modeling production systems. MOTAD was used for generating the efficiency frontiers that reflect the trade-off between income and risk. The results indicate that the farmer of "coffee and cattle" system is more averse to risk than that of the "single crop farm". This was an expected behavior, because cattle gross margins are negatively correlated to the coffee ones, indicating that the combination of these activities is efficient in reducing risk. However, it was shown that the small diversified farmer is less averse to risk than the "single crop farm", as opposed to the initial hypotheses of the study. This behavior can be explained by the diversification strategy adopted by the farmer which has chosen to invest in a variety of fruit crops species and coffee. A great part of fruit crops have higher risk degree than the coffee crop, and many of these activities are positively correlated, what reduces the diversification efficiency in the quest of minimum system risk. So it can be stated that the main objective of the small farm diversification system is raising the gross margins, because the farmer would not earn enough income to remain in the activity by just cropping coffee. The major contribution of this research is to show and divulge the importance of the diversification for small coffee farmers. It is very important that future researches could provide farm alternatives to raise the income of small farmers of the region, considering market studies and identification of trading channels. On the other hand, it would also be interesting to deepen the analysis of the situation of small producers in other systems which not include coffee, to have a wider vision of the problems and to define effective actions to ensure the regional development.

The aim of remanufacturing is to retrieve a product’s inherent value when the product no longer fulfils the user’s desired needs. By taking advantage of this inherent value through different product recovery alternatives, there is a potential for both economically and environmental advantageous recovery of products. Remanufacturing is a complex business due to the high degree of uncertainty in the production process, mainly caused by two factors: the quantity and the quality of returned products. These factors have implications both on the external processes, e.g. coordinating input of returned products with the demand for remanufactured products, as well as the internal processes that coordinates the operations within the factory walls. This additional complexity needs to be considered when organising the remanufacturing system. The objective of this dissertation is to explore how remanufacturing companies can become more competitive through analysing and managing material flows and remanufacturing processes. The first issue discussed in this dissertation is the drivers that make companies interested in remanufacturing products in the first place. The conclusion is that the general drivers are profit, company policy and the environmental drivers. In a general sense, the profit motivation is the most prevalent business driver, but still there are situations where this motivation is secondary to policy and environmental drivers. Secondly, the need to balance the supply of returned products with the demand for remanufactured products shows that the possible remanufacturing volumes for a product are dependent on the shape of the supply and demand distributions. By using a product life cycle perspective, the supply and demand situations can be foreseen and support is given on possible strategies in these different supply and demand situations. Thirdly, how used products are gathered from customers is categorised by seven different customer relationship types. These types all have different effects on the remanufacturing system, and the characteristics of these relationships are disused in detail. When considering the remanufacturing process within the factory walls, a generic remanufacturing process was developed that divides the remanufacturing process into five different phases; pre-disassembly, disassembly, reprocessing, reassembly and the post-assembly phase. These different phases are separated by three different key decision points in the process that also have a major impact on the material planning of the process. For the remanufacturing material planning and production planning, the possibility to apply lean principles can be difficult. One foundation for implementing lean principles in new production is the existence of standardised processes that are stable and predictable. In the remanufacturing system, the possibilities to realise a predictable process is limited by the “normal” variations in quantity and the quality of the returned cores. Even though lean principles can be problematic to implement in the remanufacturing environment, this dissertation proposes a number of solutions that can be used to make the remanufacturing process leaner.

As concern grows about energy and environment issues, energy and environmental modeling and related policy analysis are critical issues for today's society. Polluting firms such as coal power plants play an important role in providing electricity to drive the U.S. economy as well as producing pollution that damages the environment and human health. This dissertation is intended to model and estimate polluting firms' production using nonparametric methods. First, frontier production function of polluting firms is characterized by weak disposability between outputs and pollutants to reflecting the opportunity cost to reduce pollutants. The StoNED method is extended to estimate a weak disposability frontier production function accounting for random noise in the data. The method is applied to the U.S. coal power plants under the Acid Rain Program to find the average technical inefficiency and shadow price of SO2 and NOx. Second, polluting firms' production processes are modeled characterizing both the output production process and the pollution abatement process. Using the law of conservation of mass applied to the pollution abatement process, this dissertation develops a new frontier pollutant function which then is used to find corresponding marginal abatement cost of pollutants. The StoNEZD method is applied to estimate a frontier pollutant function considering the vintage of capital owned by the polluting firms. The method is applied to estimate the average NOx marginal abatement cost for the U.S. coal power plants under the current Clean Air Interstate Rule NOx program. Last, the effect of a technical change on marginal abatement costs are investigated using an index decomposition technique. The StoNEZD method is extended to estimate sequential frontier pollutant functions reflecting the innovation in pollution reduction. The method is then applied to estimate a technical change effect on a marginal abatement cost of the U.S. coal power plants under the current Clean Air Interstate Rule NOx program.

Diss. (sammanfattning). Uppsala : Sveriges lantbruksuniv., 2004. / Härtill 4 uppsatser.