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Value of Improved Information about Environmental Protection Values: Toward a Benefit–Cost Analysis of Public-Good Valuation Studies

Published online by Cambridge University Press:  01 June 2020

Jon Strand  and
Sauleh Siddiqui
Jon Strand*
Affiliation:
Development Research Group, Sustainability and Infrastructure Team (DECSI), The World Bank, Washington, DC, USA, e-mail: Jstrand1344@gmail.com
Sauleh Siddiqui
Affiliation:
Department of Environmental Science, American University, Washington D.C. 20016, USA
*
*e-mail: Jstrand1344@gmail.com
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Abstract

What is the benefit from obtaining more precise values of environmental or other public goods through surveys or other information gathering? In the value of information (VOI) problem studied here, a buyer who wishes to preserve a resource sets a price to offer a seller without knowing precisely its protection value, B, nor its value to the seller, V. The VOI from more precise information about B is important for environmental and natural resource valuation, but is typically not quantified nor compared to valuation costs. More precise environmental values reduce the frequency of two types of mistakes (protecting the resource when it should not be; and not protecting it when it should), and increases ex ante welfare. We apply our analysis to Amazon rainforest protection, focusing on the “value of perfect information,” VOPI, which, we show through simulations, typically exceeds realistic valuation costs, justifying significant valuation expenditures. VOPI also depends on the nature of buyer–seller interactions, and takes its highest value when the buyer has full concern for the seller’s outcome. Our paper proposes and prepares the base for a new, needed, field in applied welfare economics, the “benefit–cost analysis of public-good valuation studies.”

Keywords

benefit–cost analysisenvironmental valuationpublic goodsrainforestsvalue of information.
Type
Article
Information
Journal of Benefit-Cost Analysis , Volume 11 , Issue 3 , Fall 2020 , pp. 418 - 440
Copyright
© Society for Benefit-Cost Analysis, 2020

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