Valuing agricultural externalities in Canterbury rivers and streams: three essays
Authors
Date
2010
Type
Thesis
Fields of Research
Abstract
This thesis adds to the literature on non-market valuation of agricultural externalities in rivers and streams. The thesis is a combination of three empirical articles; each article focuses on a particular practical element of valuation survey implementation.
Rural water quality and quantity concerns in New Zealand are intrinsically related to agriculture. Valuation of preferences for mitigating agricultural impacts on rivers and streams is generally lacking in policy debate. The first essay focuses on a choice experiment employed to estimate economic values of agricultural impacts on rivers and streams in the Canterbury region of New Zealand where increasing transformation of dry land pastoral and arable farming for water intensive practices have placed pressure on water resources. Three impacts are considered: health risks of pathogens from animal waste, ecological effects of excess nutrients, and low-flow impacts of irrigation. This study provides a valuation of outcomes for public agri-environmental policy implemented in Canterbury such as The Dairy and Clean Streams Accord, Living Streams, and The Restorative Programme for Lowland Streams. Significant differences are found between willingness-to-pay estimates derived from multinomial logit and random parameter logit models for some water quality attributes. Based on the results from the random parameter logit model, the average five year present value compensating surplus for improvements to rivers and streams in Canterbury provided by agri-environmental policy is $185,000,000.
The second essay presents a comparison of internet and mail survey modes for non-market valuation. The aim of the paper is to investigate the capability of internet surveying to provide robust welfare estimates of environmental goods. Results from a choice experiment conducted using traditional mail mode and the internet are compared based on three main testing procedures. Chi-square tests of respondent characteristics provide an indication of the impact of sample frame and self-selection bias. A test of parameter equality across mail and internet random parameter logit models is then conducted employing the Swait and Louviere (1993) approach. Finally, differences in the derived welfare estimates are assessed using the Poe (2005) Complete Combinatorial method. Some evidence of framing and additional self-selection bias in the internet sample is found. The null hypothesis of parameter equality across survey modes is rejected, however this difference in cognitive processes between samples does not translate into significantly different willingness-to-pay or compensating surplus estimates. Overall this case study supports the use of internet sampling to obtain viable welfare estimates of environmental policy.
The third essay explores possible sources of spatial heterogeneity in welfare estimates. The spatial distribution of agri-environmental policy benefits has important implications for efficient allocation of management effort. The practical convenience of relying on sample mean values of individual benefits for aggregation can come at the cost of biased aggregate estimates. The main objective of this paper is to test spatial hypotheses regarding respondents’ local water quality and quantity and their willingness-to-pay for improvements in water quality attributes. This paper combines choice experiment and spatially related water quality data via Geographical Information System to develop a method that evaluates the influence of local water quality on respondents’ willingness-to-pay for river and stream conservation programs in Canterbury. The results show that those respondents whose local waterway is of low quality are willing to pay more for improvements relative to those whose local waterway is of high quality. The study also finds that disregarding the influence of respondents’ local water quality data has a significant impact on the magnitude of welfare estimates and hence, causes substantial underestimation of aggregated benefits.