Exact(60)
They used the below equation to predict WTP in Mexico: {text{WTP}}_{text{Mexico}} = {text{WTP}}_{{{text{Country}},{text{A}}}} left[ {{text{Income}}_{text{Mexico}} /{text{Income}}_{{{text{Country}},{text{A}}}} } right]^{varepsilon } where ε represents the income elasticity of WTP, that is the percentage change in WTP corresponding to a 1%% change in income and Country A is the US.
These findings suggest that being a woman or a man does not bring differences in WTP but the differences in their endowments that are associated with WTP.
Additionally, the pattern of declining WTP per QALY estimates for more severe health states may be due in part to the insensitivity to scale in WTP [ 37, 38].
A significant difference in WTP among occupational groups was observed.
Differences in WTP were investigated according to various demographic variables including income and education.
Significant differences in WTP were found across regions and income levels.
Results, in WTP terms, from analyzing the entire sample are graphically illustrated in Fig. 1.
This implies that increase in WTP is not monotonic with income and contribution.
No statistical differences in WTP for the different feedstocks were found.
Results illustrate heterogeneity in WTP associated with environmental and social attitudes, and family concerns.
Market opinion clusters play a significant role in WTP for emission reductions through purchases of E85.
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