Author ORCID Identifier

https://orcid.org/0000-0001-5576-7098

Year of Publication

2017

Degree Name

Doctor of Philosophy (PhD)

Document Type

Doctoral Dissertation

College

Agriculture, Food and Environment

Department

Agricultural Economics

First Advisor

Dr. Wuyang Hu

Abstract

Contingent Valuation (CV) methods are a primary tool in environmental economics to ascertain non-use or other values not observable through existing market mechanisms. Because common CV approaches typically rely on hypothetical answers from surveys in order to generate welfare estimates, these are often labelled stated preferences. Results from stated preference methods often diverge from those obtained when actual preference or behavior are involved. This divergence is commonly known as Hypothetical Bias (HB). This dissertation addresses HB as it applies to environmental applications. To begin, a meta-analysis using a sample of studies many times larger than previous works was performed. Its results identify which study protocols exacerbate HB, and which may mitigate it. Furthermore, the meta-analysis establishes the efficacy of some popular techniques to mitigate HB. The second essay focuses on understanding and addressing two important topics to environmental economics, distance decay and charismatic species conservation. These effects have not been investigated with respect to HB. We implement a field survey of monarch and viceroy butterfly conservation, creating survey treatment conditions involving both real payment and hypothetical scenarios in order to establish the extent of HB. The key finding is that while HB is present for both butterflies, HB in distance decay exists for monarchs. There is also additional HB for monarchs compared to viceroys, which we attribute to the former’s charisma. The final endeavor studies the usefulness of consequentiality, a relatively new tactic to reduce HB. Consequentiality is the degree to which respondents believe their answers may affect policy outcomes. Relying on the monarch field survey, we find that using a technique known as ex ante consequentiality may exacerbate HB. Another approach known as ex post consequentiality is more effective at reducing the extent of HB in the data. Lastly, some elements of the studies’ results showcase that HB is not always present and can also explain some of the mixed results found on the efficacy of HB mitigating methods reported in previous studies.

Digital Object Identifier (DOI)

https://doi.org/10.13023/ETD.2017.275

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