967 resultados para Agricultural and Resource Economics


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Current policy issues surrounding management of the Great Artesian Basin - historical development of existing legislation and institutions - hydrological and historical background information - development of concerns over unsustainable use of resources and possible adverse environmental impacts - recent developments associated with the general reforms to water law and policy initiated by the Council of Australian Governments (COAG) - comparison of issues surrounding the Murray-Darling Basin and the Great Artesian Basin.

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The purpose of this research is to study the commercialization of Fairtrade and Organic coffee in the Bolivia. Fairtrade and Organic coffee are alternative trade systems designed to promote the equitable and environmentally sustainable production of coffee. However, these alternative trading systems often fail to meet these goals. The producers and environment these systems are intended to protect remain marginalized. These failures are due to a number of local institutions. In order to better understand these institutions, this research conducted interviews of various stakeholders including producers, cooperative leaders, organic/Fair Trade certifiers, government agencies and private buyers. All these stakeholders influence the success of the alternative trade systems. By better understanding how these stakeholders impact the commercialization of coffee in Bolivia; new policies can be develop to improve the outcomes of alternative trade, to benefit both producers and the environment. This is especially critical in Bolivia because of the environmentally sensitive area in which coffee is grown, the potentially damaging impact of coca on the region and, the devastating economic impact to farmers.

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In this dissertation I quantify residential behavior response to interventions designed to reduce electricity demand at different periods of the day. In the first chapter, I examine the effect of information provision coupled with bimonthly billing, monthly billing, and in-home displays, as well as a time-of-use (TOU) pricing scheme to measure consumption over each month of the Irish Consumer Behavior Trial. I find that time-of-use pricing with real time usage information reduces electricity usage up to 8.7 percent during peak times at the start of the trial but the effect decays over the first three months and after three months the in-home display group is indistinguishable from the monthly treatment group. Monthly and bi-monthly billing treatments are not found to be statistically different from another. These findings suggest that increasing billing reports to the monthly level may be more cost effective for electricity generators who wish to decrease expenses and consumption, rather than providing in-home displays. In the following chapter, I examine the response of residential households after exposure to time of use tariffs at different hours of the day. I find that these treatments reduce electricity consumption during peak hours by almost four percent, significantly lowering demand. Within the model, I find evidence of overall conservation in electricity used. In addition, weekday peak reductions appear to carry over to the weekend when peak pricing is not present, suggesting changes in consumer habit. The final chapter of my dissertation imposes a system wide time of use plan to analyze the potential reduction in carbon emissions from load shifting based on the Ireland and Northern Single Electricity Market. I find that CO2 emissions savings are highest during the winter months when load demand is highest and dirtier power plants are scheduled to meet peak demand. TOU pricing allows for shifting in usage from peak usage to off peak usage and this shift in load can be met with cleaner and cheaper generated electricity from imports, high efficiency gas units, and hydro units.

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This dissertation focuses on the greenhouse and nursery industry in the United States. Two major issues are explored: irrigation and plant disease. The first two essays examine wireless soil-moisture sensor networks, an emerging technology that measures soil moisture and optimizes irrigation levels in real time. The first essay describes a study in which a nationwide survey of commercial growers was administered to generate estimates of grower demand and willingness to pay for sensor networks. We find that adoption rates for a base system and demand for expansion components are decreasing in price, as expected. The price elasticity of the probability of adoption suggests that sensor networks are likely to diffuse at a rate somewhat greater than that of drip irrigation. In the second essay, yields, time-to-harvest, and plant quality were analyzed to measure sensor network profitability. Sensor-based irrigation was found to increase revenue by 62% and profit by 65% per year. The third essay investigates greenhouse nursery growers’ response to a quarantine imposed on the west coast of the United States from 2002 to present for the plant pathogen that causes Sudden Oak Death. I investigate whether growers choose to 1) improve their sanitation practices, which reduces the underlying risk of disease without increasing the difficulty of detecting the pathogen, 2) increase fungicide use, which also prevents disease but makes existing infections much harder to detect, or 3) change their crop composition towards more resistant species. First, a theoretical model is derived to formalize hypotheses on grower responses to the quarantine, and then these predictions are empirically tested using several public data sources. I do not find evidence that growers improve their sanitation practices in response to the quarantine. I do, however, find evidence that growers heavily increase their fungicide use in response to a quarantine policy that requires visual (as opposed to laboratory) inspection for the disease before every crop shipment, suggesting that the quarantine may have the adverse effect of making the pathogen harder to identify. I also do find evidence that growers shift away from susceptible crops and towards resistant crops.

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Nonpoint sources (NPS) pollution from agriculture is the leading source of water quality impairment in U.S. rivers and streams, and a major contributor to lakes, wetlands, estuaries and coastal waters (U.S. EPA 2016). Using data from a survey of farmers in Maryland, this dissertation examines the effects of a cost sharing policy designed to encourage adoption of conservation practices that reduce NPS pollution in the Chesapeake Bay watershed. This watershed is the site of the largest Total Maximum Daily Load (TMDL) implemented to date, making it an important setting in the U.S. for water quality policy. I study two main questions related to the reduction of NPS pollution from agriculture. First, I examine the issue of additionality of cost sharing payments by estimating the direct effect of cover crop cost sharing on the acres of cover crops, and the indirect effect of cover crop cost sharing on the acres of two other practices: conservation tillage and contour/strip cropping. A two-stage simultaneous equation approach is used to correct for voluntary self-selection into cost sharing programs and account for substitution effects among conservation practices. Quasi-random Halton sequences are employed to solve the system of equations for conservation practice acreage and to minimize the computational burden involved. By considering patterns of agronomic complementarity or substitution among conservation practices (Blum et al., 1997; USDA SARE, 2012), this analysis estimates water quality impacts of the crowding-in or crowding-out of private investment in conservation due to public incentive payments. Second, I connect the econometric behavioral results with model parameters from the EPA’s Chesapeake Bay Program to conduct a policy simulation on water quality effects. I expand the econometric model to also consider the potential loss of vegetative cover due to cropland incentive payments, or slippage (Lichtenberg and Smith-Ramirez, 2011). Econometric results are linked with the Chesapeake Bay Program watershed model to estimate the change in abatement levels and costs for nitrogen, phosphorus and sediment under various behavioral scenarios. Finally, I use inverse sampling weights to derive statewide abatement quantities and costs for each of these pollutants, comparing these with TMDL targets for agriculture in Maryland.

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This dissertation is composed of three essays covering two areas of interest. The first topic is personal transportation demand with a focus on price and fuel efficiency elasticities of mileage demand, challenging assumptions common in the rebound effect literature. The second topic is consumer finance with a focus on small loans. The first chapter creates separate variables for fuel prices during periods of increasing and decreasing prices as well as an observed fuel economy measure to empirically test the equivalence of these elasticities. Using a panel from Germany from 1997 to 2009 I find a fuel economy elasticity of mileage of 53.3%, which is significantly different from the gas price elasticity of mileage during periods of decreasing gas prices, 4.8%. I reject the null hypothesis or price symmetry, with the elasticity of mileage during period of increasing gas prices ranging from 26.2% and 28.9%. The second chapter explores the potential for the rebound effect to vary with income. Panel data from U.S. households from 1997 to 2003 is used to estimate the rebound effect in a median regression. The estimated rebound effect independent of income ranges from 17.8% to 23.6%. An interaction of income and fuel economy is negative and significant, indicating that the rebound effect may be much higher for low income individuals and decreases with income; the rebound effect for low income households ranged from 80.3% to 105.0%, indicating that such households may increase gasoline consumption given an improvement in fuel economy. The final chapter documents the costs of credit instruments found in major mail order catalogs throughout the 20th century. This study constructs a new dataset and finds that the cost of credit increased and became stickier as mail order retailers switched from an installment-style closed-end loan to a revolving-style credit card. This study argues that revolving credit's ability to decrease salience of credit costs in the price of goods is the best explanation for rate stickiness in the mail order industry as well as for the preference of revolving credit among retailers.

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As the agricultural non-point source pollution(ANPSP) has become the most significant threat for water environmental deterioration and lake eutrophication in China, more and more scientists and technologists are focusing on the control countermeasure and pollution mechanism of agricultural non-point source pollution. The unreasonable rural production structure and limited scientific management measures are the main reasons for acute ANSPS problems in China. At present, the problem for pollution control is a lack of specific regulations, which affects the government's management efficiency. According to these characteristics and problems, this paper puts forward some corresponding policies. The status of the agricultural non-point source pollution of China is analyzed, and ANSPS prevention and control model is provided based on governance policy, environmental legislation, technical system and subsidy policy. At last, the case analysis of Qiandao Lake is given, and an economic policy is adopted based on its situation.

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Accurate price forecasting for agricultural commodities can have significant decision-making implications for suppliers, especially those of biofuels, where the agriculture and energy sectors intersect. Environmental pressures and high oil prices affect demand for biofuels and have reignited the discussion about effects on food prices. Suppliers in the sugar-alcohol sector need to decide the ideal proportion of ethanol and sugar to optimise their financial strategy. Prices can be affected by exogenous factors, such as exchange rates and interest rates, as well as non-observable variables like the convenience yield, which is related to supply shortages. The literature generally uses two approaches: artificial neural networks (ANNs), which are recognised as being in the forefront of exogenous-variable analysis, and stochastic models such as the Kalman filter, which is able to account for non-observable variables. This article proposes a hybrid model for forecasting the prices of agricultural commodities that is built upon both approaches and is applied to forecast the price of sugar. The Kalman filter considers the structure of the stochastic process that describes the evolution of prices. Neural networks allow variables that can impact asset prices in an indirect, nonlinear way, what cannot be incorporated easily into traditional econometric models.

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In the Uruguay Round Agreement on Agriculture, so-called 'blue box' support measures were exempted from reduction commitments, provided they were delivered under 'production-limiting' programs. Although classified as 'blue box', the EU system of direct payments (DP) to beef farmers imposes 'claim-limiting' restrictions rather than 'production-limiting' restrictions, allowing farmers to keep additional animals over and above the number upon which they are eligible to claim DP. The present paper provides empirical evidence that EU direct payments capitalise into the market prices of male calves and young steers in Ireland. It is also likely that DP capitalises into the prices of beef cows and heifers. Given this capitalisation process, some farmers can obtain 'capitalised' DP on animals produced over and above the 'claim-limiting' restrictions, by selling these animals through auction markets. Thus, 'capitalised' DP probably encourages production over and above the limiting measures.

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An approach to incorporate spatial dependence into stochastic frontier analysis is developed and applied to a sample of 215 dairy farms in England and Wales. A number of alternative specifications for the spatial weight matrix are used to analyse the effect of these on the estimation of spatial dependence. Estimation is conducted using a Bayesian approach and results indicate that spatial dependence is present when explaining technical inefficiency.