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Travellers dilemma (Ariel Rubenstein 2004). Imagine you are one of the players in the following two-player game: Each of the players chooses an amount between $180 and $300 Both players are paid the lower of the two chosen amounts
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Travellers dilemma (Ariel Rubenstein 2004) • Imagine you are one of the players in the following two-player game: • Each of the players chooses an amount between $180 and $300 • Both players are paid the lower of the two chosen amounts • Five dollars are transferred from the player who chose the larger amount to the player who chose the smaller one. • In the case that both players choose the same amount, they both receive that amount and no transfer is made. • How much would you choose?
Ex ante testing of carbon trading policies in the SA Murray Darling Basin John Ward, Brett Bryan, Darran King, Neville Crossman June 2007
Context • The SA region of the Murray Darling Basin has seen over 80 years of land clearance and agricultural production • Prominent signs of environmental degradation – Surface and ground Water, Water quality, Land, Biota • Government policy - Integrated Natural Resource Management • INRM plan based on resource condition targets and actions • SA MDB Integrated NRM targets are multi-objective and include: • Biodiversity • River Salinity • Wind Erosion • Establish on-ground investment priorities for NRM actions on private land • Evaluate the potential of market based Instruments
Research programme: calibrating multi-agent models for policy optimisation in the SA MDB • Identify and evaluate market based incentives to encourage revegetation • At the farm scale, estimate the economic viability and contribution to resource targets of biomass energy and carbon trading • Survey dryland farmers to elicit farming styles and describe relationships between current community attitudes and land management actions. • Use experimental economics to quantify behavioural responses by landholders to market incentives in revegetation decision environments • Use the survey and experimental data to calibrate a multi-agent dynamic simulation of revegetation actions over fifty years • Implement four simulation scenarios of revegetation policy which estimate carbon, natural resource and economic outcomes • Describe the relationships between policy variables and NRM and economic outcomes to inform policy making processes prior to implementation.
Economic Viability Carbon • Mallee community - €10 / tonne • Mallee community - €20 / tonne • Mallee community - €30 / tonne • Mallee community - €40 / tonne • Viable areas - €10 / tonne • Viable areas - €20 / tonne • Viable areas - €30 / tonne • Viable areas - €40 / tonne One € = A$1.62
The quest for a behavioural epsilon:which version of “rational behaviour” to model? H.reciprocans H.economicus H.psychologicus Chi squared test of experimental cluster frequencies cf with survey sample= 0.659 (not sig dif α =0.05)
Principle components factor analysis and hierarchical cluster analysis innovative farm business managers socially influenced farmers time and capital constrained conservation managers life style hobby farmers
Cluster spatial (centroid) distribution • RBi = Atti + Ii + Sni + PCi + Oppi + wBj • Where for land holder i: RB: represents current revegetation behaviour • Atti: represents vector of attitudes • Ii: represents intended reveg action • Sni: represents influence of social norms on i decision making • PCi: represents a vector of perceived controls • Oppi: represents current opportunity cost • wj: represents decayed weighted influence of nearest neighbour j for behaviour and • w = 1/distance i-j
Experimental design and metrics Experimental metrics Individual and aggregate carbon production Individual and aggregate income: Player payments Decision making Market behaviour
Farm decision making: visual cue (map) of all catchment decisions
Dynamic simulations of SA MDB revegetation • Four farm scale decision making scenarios • Where an individual agent selects one cleared ha per annum to revegetate for a period of 50 years Random Lowest opportunity cost to highest Highest biodiversity value to lowest According to social diffusion. • If neighbour revegetates, then agent revegetates (influence is a decaying distance function) • assumes 5% are innovators and the probability of revegetation for all agents increases with time.
Bringing empirically based behavioural data into NRM policy testing • Calibrate the social diffusion model based on empirical data • Higher initial levels of innovation (31% not 5% as previously assumed) • Quantify policy that includes dissemination of catchment wide decisions • Quantify variable learning capacities, responses and transaction costs of novel choices • Complement pre-existing norms and institutions • Effect on policy performance by targeting observed farming segments • Enumerate the effects of policy that matches the motivations of cluster segments: attitudinal and temporal sequencing • Ex ante modelling of policies that address the likely effects of global warming: addressing regional vulnerability and resilience
Total recharge results a a ac d cd e e Dunnett’s T3 post hoc test: Homogeneity of variance (Levine statistic) p < 0.05; ANOVA coefficients: F (7, 142) = 98.600; p< 0.05; Treatment means with the same letter were not statistically different at =0.05
“Life is animated water” (Vernadsky 1986) • Email: j.ward@csiro.au • Phone 83038685