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The importance of social learning for non-market valuation


Grainger, D and Stoeckl, N, The importance of social learning for non-market valuation, Ecological Economics, 164 pp. 1-9. ISSN 0921-8009 (2019) [Refereed Article]


Copyright Statement

© 2019 The Authors. Licensed under Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)

DOI: doi:10.1016/j.ecolecon.2019.05.019


Neoclassical valuation methods often measure the contribution that non-market goods make to utility as income compensations. This circumvents Arrow's impossibility (AI) –a theoretical proof establishing the impossibility of social preferences – but those methods cannot be used in all settings. We build on Arrow's original proof, showing that with two additional axioms that allow for social learning, a second round of preference elicitation with a social announcement after the first, generates logically consistent social preferences. In short: deliberation leads to convergence. A ‘web-game’ aligning with this is trialed to select real world projects, in a deliberative way, with the board of an Australian Aboriginal Corporation. Analysis of the data collected in the trial validates our theory; our test for convergence is statistically significant at the 1% level. Our results also suggest complex social goods are relatively undervalued without deliberation. Most non-market valuation methods could be easily adapted to facilitate social learning.

Item Details

Item Type:Refereed Article
Keywords:social welfare, non-market valuation, deliberative valuation, deliberative institutions, cost benefit analysis, Arrow's impossibility
Research Division:Economics
Research Group:Applied economics
Research Field:Environment and resource economics
Objective Division:Economic Framework
Objective Group:Microeconomics
Objective Field:Market-based mechanisms
UTAS Author:Stoeckl, N (Professor Natalie Stoeckl)
ID Code:136181
Year Published:2019
Web of Science® Times Cited:5
Deposited By:College Office - CoBE
Deposited On:2019-12-05
Last Modified:2021-03-30
Downloads:3 View Download Statistics

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