Testing preference formation in learning design contingent valuation (LDCV) using advanced information and repetitive treatments

Claudia Aravena; W. George Hutchinson; Fredrik  Carlsson; David I. Matthews

Testing preference formation in learning design contingent valuation (LDCV) using advanced information and repetitive treatments

Claudia Aravena, W. George Hutchinson, Fredrik Carlsson , David I. Matthews

School of Biological Sciences

Research output: Chapter in Book/Report/Conference proceeding › Chapter (peer-reviewed)

Abstract

Policymakers have largely replaced Single Bounded Discrete Choice (SBDC) valuation by the more statistically efficient repetitive methods; Double Bounded Discrete Choice (DBDC) and Discrete Choice Experiments (DCE) . Repetitive valuation permits classification into rational preferences: (i) a priori well-formed; (ii) consistent non-arbitrary values “discovered” through repetition and experience; (Plott, 1996; List 2003) and irrational preferences; (iii) consistent but arbitrary values as “shaped” by preceding bid level (Tufano, 2010; Ariely et al., 2003) and (iv) inconsistent and arbitrary values. Policy valuations should demonstrate behaviorally rational preferences. We outline novel methods for testing this in DBDC applied to renewable energy premiums in Chile.

Original language	English
Title of host publication	School of Business, Economics and Law, Goeteborg University. Working Papers in Economics
Place of Publication	Gothenburg
Pages	1-43
Number of pages	44
Volume	No. 619
ISBN (Electronic)	1403-2465
Publication status	Published - Apr 2015

Publication series

Name	Working Papers in Economics
Publisher	University of Gothenberg
Volume	No. 615
ISSN (Print)	1403-2473
ISSN (Electronic)	1403-2465

Bibliographical note

No. 619 in a monographic series

Keywords

Contingent valuation;
double bounded discrete choice
repetitive learning.
advanced information learning
bid dependency.
theories of preference formation

UN SDGs

This output contributes to the following Sustainable Development Goal(s)

Access to Document

https://gupea.ub.gu.se/handle/2077/38652

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Aravena, C., Hutchinson, W. G., Carlsson , F., & Matthews , D. I. (2015). Testing preference formation in learning design contingent valuation (LDCV) using advanced information and repetitive treatments. In School of Business, Economics and Law, Goeteborg University. Working Papers in Economics (Vol. No. 619, pp. 1-43). (Working Papers in Economics; Vol. No. 615).. https://gupea.ub.gu.se/handle/2077/38652

Aravena, Claudia ; Hutchinson, W. George ; Carlsson , Fredrik ; Matthews , David I. / Testing preference formation in learning design contingent valuation (LDCV) using advanced information and repetitive treatments. School of Business, Economics and Law, Goeteborg University. Working Papers in Economics . Vol. No. 619 Gothenburg , 2015. pp. 1-43 (Working Papers in Economics).

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abstract = "Policymakers have largely replaced Single Bounded Discrete Choice (SBDC) valuation by the more statistically efficient repetitive methods; Double Bounded Discrete Choice (DBDC) and Discrete Choice Experiments (DCE) . Repetitive valuation permits classification into rational preferences: (i) a priori well-formed; (ii) consistent non-arbitrary values “discovered” through repetition and experience; (Plott, 1996; List 2003) and irrational preferences; (iii) consistent but arbitrary values as “shaped” by preceding bid level (Tufano, 2010; Ariely et al., 2003) and (iv) inconsistent and arbitrary values. Policy valuations should demonstrate behaviorally rational preferences. We outline novel methods for testing this in DBDC applied to renewable energy premiums in Chile. ",

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author = "Claudia Aravena and Hutchinson, {W. George} and Fredrik Carlsson and Matthews, {David I.}",

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language = "English",

isbn = "1403-2473",

volume = "No. 619",

series = "Working Papers in Economics",

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Aravena, C, Hutchinson, WG, Carlsson , F & Matthews , DI 2015, Testing preference formation in learning design contingent valuation (LDCV) using advanced information and repetitive treatments. in School of Business, Economics and Law, Goeteborg University. Working Papers in Economics . vol. No. 619, Working Papers in Economics, vol. No. 615, Gothenburg , pp. 1-43. <https://gupea.ub.gu.se/handle/2077/38652>

Testing preference formation in learning design contingent valuation (LDCV) using advanced information and repetitive treatments. / Aravena, Claudia; Hutchinson, W. George; Carlsson , Fredrik ; Matthews , David I.

School of Business, Economics and Law, Goeteborg University. Working Papers in Economics . Vol. No. 619 Gothenburg , 2015. p. 1-43 (Working Papers in Economics; Vol. No. 615).

Research output: Chapter in Book/Report/Conference proceeding › Chapter (peer-reviewed)

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AB - Policymakers have largely replaced Single Bounded Discrete Choice (SBDC) valuation by the more statistically efficient repetitive methods; Double Bounded Discrete Choice (DBDC) and Discrete Choice Experiments (DCE) . Repetitive valuation permits classification into rational preferences: (i) a priori well-formed; (ii) consistent non-arbitrary values “discovered” through repetition and experience; (Plott, 1996; List 2003) and irrational preferences; (iii) consistent but arbitrary values as “shaped” by preceding bid level (Tufano, 2010; Ariely et al., 2003) and (iv) inconsistent and arbitrary values. Policy valuations should demonstrate behaviorally rational preferences. We outline novel methods for testing this in DBDC applied to renewable energy premiums in Chile.

KW - Contingent valuation;

KW - double bounded discrete choice

KW - repetitive learning.

KW - advanced information learning

KW - bid dependency.

KW - theories of preference formation

M3 - Chapter (peer-reviewed)

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VL - No. 619

T3 - Working Papers in Economics

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EP - 43

BT - School of Business, Economics and Law, Goeteborg University. Working Papers in Economics

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