Evaluating Pollution Control Policies Using a Farm-level Dynamic Model: An Application to Large Dairy Farms in California
AbstractAnimal waste from concentrated animal feeding operations (CAFOs) is a significant contributor to the nitrate contamination of groundwater. Some manures also contain heavy metals and salts that may build up either in cropland or groundwater. To find cost-effective policies for pollution reduction at the farm level, an environmental-economic modeling framework for representative CAFOs is developed, where the owner of the operation is a profit-maximizer subject to environmental regulations. The model incorporates various components such as herd management, manure handling system, crop rotation, water sources, irrigation system, waste disposal options, and pollutant emissions. Decision rules from the optimization problem demonstrate best management practices for CAFOs to improve their economic and environmental performance. Results from policy simulations suggest that direct quantity restrictions of emission or incentive-based emission policies such as a field emission tax are much more cost-effective than the standard approach of limiting the amount of animal waste that may be applied to fields. Furthermore, incentive-based emission policies are shown to have advantages over direct quantity restrictions under certain conditions. We also demonstrate the importance of taking into account the integrated effects of water, nitrogen, and salinity on crop yield and nitrate leaching as well as the spatial heterogeneity of nitrogen/water application when designing policy mechanisms.
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Bibliographic InfoPaper provided by Agricultural and Applied Economics Association in its series 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington with number 124623.
Date of creation: Feb 2012
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pollution control; policy mechanism; animal waste; crop production; nitrate; groundwater; dynamic optimization; Crop Production/Industries; Environmental Economics and Policy; Farm Management; Livestock Production/Industries;
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