Uncertainty and the Environment

Uncertainty and the Environment

Implications for Decision Making and Environmental Policy

New Horizons in Environmental Economics series

Richard Young

This thought provoking book is concerned with the need to deal adequately with uncertainty in environmental decision making. The author advances a critique of the use of traditional models and then develops an alternative model of decision making under uncertainty, based on the work of George Shackle.

Appendix 4: Summary of results from regression of weighting/ascendancy function

Richard Young

Subjects: economics and finance, environmental economics, environment, environmental economics


Appendix 4: Summary of results from regression of weighting/ ascendancy function When the qualitative and quantitative results of the 23 respondents used in the analysis were collected together and analysed, two were discarded (respondents G&H) due to inconsistencies in the responses. In both cases the qualitative response to the questions asking them which gain and which loss scenarios they would weight highest (Q17 and Q18) was not consistent with the scenarios to which they had allocated the greatest weight quantitatively (Q19 and Q20). In both cases at the time of the interviews, in comparison to the other interviewees, much less time was taken during the weighting exercise, suggesting that little attention had been paid to the questions. 215 Weighting Respondent function Model diagnostics Intercept significant yes no correct correct yes no 0.83 (0.79) 0.62 (0.37) 0.93 (0.87) 0.84 (0.80) 0.80 (0.66) No problems No problems No problems yes (0.03) 0.91 (0.84) 0.54 (0.42) 0.71 (0.51) 0.97 (0.95) 0.75 (0.68) 0.69 (0.49) No problems no Possible multicollinearity DW inconclusive DW inconclusive no y not correct correct correct correct correct y not correct correct y not correct x yes, y not no y not correct no, (x = 0.052) y not no yes yes no, (x = 0.051) y not yes yes yes no (0.09) yes yes no yes Equation significant Coefficient F-test signs Coefficients significant (0.05) R-sq. (Adjusted R-sq.) A: all gain φ = 0.64x0.5–0.06y2 φ = 0.41x0.5–0.03y2 loss φ = 0.70x0.5–0.09y2 B: all gain φ = 0.66x0.5–0.09y2 φ = 0.62x0.5–0.07y2 loss...

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