Modelling economic-environmental trade-offs of maintaining nitrate pollution standards
MetadataShow full item record
The main objective of this research was to develop the methods and procedures to more accurately quantify the trade-offs between improving production risk and environmental degradation using state-contingent theory to quantify economic and environmental risk with empirical distributions. The first step in developing the economic-environmental trade-offs is to model the risk efficiency of fertiliser applications through the development of a utility maximisation programming model. Separate state-contingent nitrogen maize yield response functions estimated from simulated crop yields for each state of nature characterise production risk empirically. The unexplained variability not captured by the response function is taken into account by adding the residuals to the expected response to produce a stochastic response function. The same procedure quantified the environmental fate of fertiliser applications. An upper partial moment (UPM) ensured that the optimised farmers’ response complied with an environmental pollution goal of 28kg/ha. The upper frequency method (UFM) was developed to ensure a stricter probability bound which was used to determine the conservativeness of the UPM. The results showed that the state-contingent representation of production risk were able to capture the changes in outcome variability without any distributional assumptions. More importantly, fertiliser can act as a risk-reducing input, risk-increasing input or both depending on soil choice while not considering the environment. The risk-reducing nature of fertiliser emphasises the importance of taking risk preferences into account when modelling economicenvironmental trade-offs. The UPM results indicated that an environmental constraint hold substantial compliance costs for agricultural producers. To minimise compliance costs producers had to make extensive and intensive margin changes to ensure compliance. Soil choice is identified as being more important than fertiliser application method in reducing compliance costs. An interesting finding is that environmental compliance resulted in fertiliser being a risk-reducing input. Comparison of the modelling results of the UPM and UFM showed that the UPM is very conservative in estimating the economic-environmental trade-offs. The size of the conservativeness is very situation specific and is determined by the combination of fixed resources used, fertiliser application method, compliance probability and the conservativeness measure used. The main conclusion is that state-contingent theory provides the opportunity to model the impact of management decisions on outcome variability due to the effect of the state of nature in which the production decision is made and not due to the input use decision. The state-contingent theory is therefore the more appropriate mechanism to model the influence of uncertainty on production risk and more importantly environmental risk. The application of the state-contingent theory requires transformation functions, which captures the relationship between management decisions and outcome variability due to the state of nature. Much more research is necessary on the development of appropriate transformation functions.