Integrating economic values and catchment modelling

Integrated catchment policies are widely used to manage natural resources in Australian catchments. Decision support tools available to aid integrated catchment management are often limited in their integration of environmental processes with socio-economic systems. Fully integrated models are required to support assessments of the environmental and economic trade-offs of catchment management changes. A Bayesian Network (BN) model is demonstrated to provide a suitable approach to integrate environmental modelling with economic valuation. The model incorporates hydrological, ecological and economic models for the George catchment in Tasmania. Information about the non-market costs and benefits of environmental changes is elicited using Choice Experiments, allowing an assessment of the efficiency of alternative management scenarios.Integrated catchment modelling, Bayesian networks, Uncertainty, Environmental values, Non-market valuation, Choice Modelling.,

Designing choice experiments to Test for Anchoring and Framing Effects

Choice experiments (CE) are increasingly used as a stated preference technique to value changes in non-market goods. Respondents to a CE survey are asked to make repeated choices between alternatives. Each alternative is described by a number of attributes – the attributes levels vary across alternatives and choice sets. A monetary attribute is typically included so that marginal values for changes in the non-market attributes presented can be estimated. The monetary attribute has central importance. However, there has been limited research on the impacts on respondents’ choices of changing the (range in) levels of the monetary attribute presented in CE surveys. This is known as the ‘anchoring’ effect. The ‘framing’ of non-market attributes may also affect value estimates. Attribute framing refers to the context in which the attributes are presented to respondents in a CE survey. The challenge for CE practitioners is to identify how particular attribute frames may influence respondents’ choices. This research report provides a review of anchoring and framing effects in CEs. A CE questionnaire is described to incorporate tests for anchoring and framing effects. Ten hypotheses are developed about the impacts of various attribute ‘anchors’ and ‘frames’ on respondents’ choices and subsequent values estimated.choice experiments, valuation, anchoring effect, starting point bias, Environmental Economics and Policy, Research Methods/ Statistical Methods,

Using choice experiments to value river and estuary health in Tasmania with individual preference heterogeneity

Choice experiments (CE – otherwise known as Choice Modelling) have become a widespread approach to environmental valuation in Australia, with many examples assessing the tradeoffs between river catchment management and socio-economic impacts. There is, however, limited information on the values of Australian estuaries. Furthermore, none of the existing valuation studies address catchment management changes in Tasmania. The CE study reported in this paper aims to elicit community preferences for the protection of the rivers and estuary of the George catchment in north-eastern Tasmania. Results from conditional and mixed logit models show that respondents are, on average, willing to pay between $2.47 and$4.46 for a km increase in native riverside vegetation and between $9.35 and$10.97 per species for the protection of rare native plants and animals, ceteris paribus. The results are ambiguous about respondents’ preferences for estuary seagrass area. This study further shows significant differences between logit models when accounting for individual heterogeneity and repeated choices made by individual respondents.River condition, Estuary condition, Environmental values, Non-market valuation, Choice Experiments, Tasmania,

Using Choice Experiments to value River and Estuary Health in Tasmania with Individual Preference Heterogeneity

Choice experiments (CE), also known as choice modelling (CM), are now used widely in environmental valuation in Australia. Many examples assess the trade-offs between river catchment management and socio-economic impacts. There is, however, limited information about the values of Australian estuaries and none of the existing valuation studies addresses catchment management changes in Tasmania. The CE study described in this report aims to elicit community preferences for protecting the rivers and estuary of the George catchment in north-eastern Tasmania. Results from conditional and mixed logit models show that respondents are, on average, willing to pay between $2.47 and$4.46 for a one kilometre increase in native riverside vegetation, and between $9.35 and$10.97 per species for the protection of rare native plants and animals, ceteris paribus. The study results are ambiguous about respondents’ preferences for estuary seagrass area. It also shows significant differences between logit models when accounting for individual heterogeneity, and repeated choices made by individual respondents.Choice experiments, Preference heterogeneity, Mixed Logit models, River health, Estuary health, Tasmania, Environmental valuation, Environmental Economics and Policy, Land Economics/Use, Research Methods/ Statistical Methods,

The Impacts of Attribute Level Framing and Changing Cost Levels on Choice Experiments Value Estimates

Choice Experiments (CE) are increasingly used to estimate the values of environmental goods and services. CE questionnaires represent the environmental good under valuation by varying levels of non-market attributes. Inclusion of a cost attribute enables the estimation of monetary values for changes in the non-market attributes presented. The ways in which the levels of the attributes are described in the survey - the ‘attribute frame’ - may affect respondents’ choices. Furthermore, varying levels of the cost attribute may impact CE value estimates. The challenge for CE practitioners is to identify the ‘appropriate’ attribute frames and cost levels. In this paper, the impacts of changing cost levels and the impacts of describing non-market attributes as absolute levels or in relative terms are assessed. These tests were performed using data from a CE on catchment management in Tasmania, Australia. Contrary to a priori expectations, including explicit information cues about relative attribute levels in the choice sets is found not to affect stated preferences. However, comparisons between different split samples provide evidence that respondents’ preferences are impacted by changing the range in cost attribute levels, with higher levels leading to significantly higher estimates of WTP for one of the three environmental attributes.Choice Experiments, Environmental Valuation, Bias, Tasmania, Environmental Economics and Policy,

Integrated Hydro-Economic Modelling: Challenges and Experiences in an Australian Catchment

Integrated catchment policies are widely used to manage natural resources in Australian catchments. Integration of environmental processes with socio-economic systems is often difficult due to the limitations of decision support tools. To support assessments of the environmental and economic trade-offs of changes in catchment management, fully integrated models are needed. This research demonstrates a Bayesian Network (BN) approach to integrating environmental modelling with economic valuation. The model incorporates hydrological, ecological and economic models for the George catchment in Tasmania. Choice experiments were used to elicit information about the non-market costs and benefits of environmental changes. This allows the efficiency of alternative management scenarios to be assessed.Hydro-economic modelling, Integrated catchment modelling, Ecological modelling, Valuation, Bayesian networks, Water quality, Community/Rural/Urban Development, Environmental Economics and Policy, Land Economics/Use,

Investigating the Effects of Attribute Level Framing and Changing Cost Levels in Choice Experiments

Choice experiments (CE) are increasingly used to estimate the values of non-market goods and services. A cost attribute is typically included in a CE questionnaire to estimate monetary values for changes in the non-market attributes presented. Although the cost attribute is centrally important, there has been limited research into the impacts of varying cost attribute levels on respondents’ choices in CE surveys. The context in which non-market attributes are presented to respondents (the ‘attribute frame’) may also affect value estimates. The challenge for CE practitioners is to identify the ‘appropriate’ attribute frames and cost level range. Results from a CE study in Tasmania show that respondents’ preferences are not impacted by describing an attribute in ‘presence’ versus ‘loss’. The absolute attribute levels, therefore, were most important in this study. Comparisons between different split samples are evidence that changing the cost attribute level does affect respondents’ preferences – higher levels lead to significantly higher estimates of willingness to pay for one of the three environmental attributes.Choice experiments, Mixed Logit models, Environmental valuation, Attribute framing, Cost bias, Environmental Economics and Policy, Research Methods/ Statistical Methods,

Developing a Questionnaire for Valuing Changes in Natural Resource Management in the George Catchment, Tasmania

review, expert interviews, biophysical modelling and focus group discussions were used to design a Choice Modelling (CM) questionnaire. This questionnaire was used to value changes in natural resource management in the George catchment, Tasmania. This report describes the questionnaire development, the selection of George catchment attributes and the assessment of attribute levels. The (experimental) design and delivery of the questionnaire are also presented.choice experiments, valuation, survey development, Tasmania, catchment management, Environmental Economics and Policy, Land Economics/Use,

An Integrated Assessment approach to linking biophysical modelling and economic valuation tools

Natural resource management (NRM) typically involves complex decisions that affect a variety of stakeholder values. Efficient NRM, which achieves the greatest net environmental, social and financial benefits, needs to integrate the assessment of environmental impacts with the costs and benefits of investment. Integrated assessment (IA) is one approach that incorporates the several dimensions of catchment NRM, by considering multiple issues and knowledge from various disciplines and stakeholders. Despite the need for IA, there are few studies that integrate biophysical modelling tools with economic valuation. In this paper, we demonstrate how economic non-market valuation tools can be used to support an IA of catchment NRM changes. We develop a Bayesian Network model that integrates: a process-based water quality model; ecological assessments of native riparian vegetation; estimates of management costs; and non-market (intangible) values of changes in riparian vegetation. This modelling approach illustrates how information from different sources can be integrated in one framework to evaluate the environmental and economic impacts of NRM actions. It also shows the uncertainties associated with the estimated welfare effects. By estimating the marginal social costs and benefits, a cost-benefit analysis of alternative management intervention can be gained and provides more economic rationality to NRM decisions.Bayesian networks, bio-economic modelling, catchment management, cost-benefit analysis, environmental values, integrated assessment and modelling, non-market valuation, riparian vegetation, Environmental Economics and Policy, Research Methods/ Statistical Methods,

Effects of Great Barrier Reef Degradation on Recreational Demand: A Contingent Behaviour Approach

Agricultural run-off from the Great Barrier Reef catchment area may cause degradation of coral reefs, affecting the tourism sector that relies on healthy reefs for its income generation. A Contingent Behaviour approach is used to determine the effect of reef degradation on demand for recreational dive and snorkel trips, for a case study of the Great Barrier Reef (GBR) in Australia. We assessed how reef degradation affects GBR tourism and to what extent reef-trip demand depends on the visitors' socio-economic characteristics. A count data model is developed, and results indicate that an average visitor would undertake about 60% less trips to the GBR per year, given a combined 80%, 30% and 70% decrease in coral cover, coral diversity and fish diversity, respectively. This corresponds to a decrease in tourism expenditure for reef trips in the Great Barrier Reef Marine Park area of about A$ 136 million per year.Coral reef, Recreation, Contingent Behaviour model, Count data models, Resource /Energy Economics and Policy, Q26, Q51, Q57,