The total economic value of threatened, endangered and rare species: An updated meta-analysis

Abstract

This paper updates a 1996 meta-analysis of studies using the Contingent Valuation Method (CVM) to value threatened, endangered and rare species published in this journal by Loomis and White. A variable for studies conducted in or after 1995 was added to the model to test if new studies are systematically different from old studies and identify which explanatory variables influencing willingness-to-pay (WTP) for these species have changed over time. Generally newer studies yielded higher WTP. Variables such as the change in the size of the species population, payment frequency, survey mode, response rate, type of respondent, type of species, and a new variable for whether a species is a ‘charismatic megafauna’ or not, whether the species has use and nonuse value versus nonuse value only and year of the study, were found to significantly influence WTP. This model is used in a benefit transfer example and a comparison of original study estimates and model estimates is made to compare its accuracy. The average within sample benefit transfer error was 34–45%.

Introduction

Biodiversity is increasingly threatened given current trends in human population growth and development with the number as well as the rate of plant and animal extinctions on the rise. According to the World Conservation Union's 2007 Red List, one in four mammals, one in eight birds, one third of all amphibians, and 70% of the worlds assessed plants are now endangered. There is an awareness of the problems that arise with the loss of biodiversity and this is reflected in the Endangered Species Act (ESA) in the U.S.A. and similar legislation in numerous countries around the world.

Currently, economic analyses may not be incorporated in species listing decisions under the Endangered Species Act but can be incorporated in designating critical habitats and developing recovery plans after a species is listed. However, there has been considerable concern about how these economic analyses are conducted for critical habitat. For instance, Defenders of Wildlife and their Conservation Economics Program has argued that the Fish and Wildlife Service's current practice of monetizing costs while qualitatively describing benefits under the ESA is flawed. They call for more consistent measures of the benefits provided by species (Defenders of Wildlife, 2004). In addition, in 2004, the National Wildlife Federation released a report documenting how the Bush administration used flawed economic data to cut in half critical habitat designations under the ESA, overestimating the costs while ignoring many of the benefits of proposed designations (National Wildlife Federation, 2004). These concerns provide justification for the need of a consistent measure of benefits provided by threatened, endangered and rare species.

The Total Economic Value of the majority of these species consists of both recreational use and nonuse (existence and bequest) values, which can be measured by eliciting willingness-to-pay (WTP) for the preservation of a particular species. However, it is important to note that some species have nonuse values only. Currently, one of the most accepted methods used to estimate the Total Economic Value provided by species is the Contingent Valuation Method (CVM). This method employs the use of surveys outlining a hypothetical market or referendum (Mitchell and Carson, 1989). It has been found that people are willing to pay a small portion of their income towards the protection of endangered or rare species for a variety of reasons. While numerous CVM studies valuing threatened and endangered (T&E) species have been conducted, especially over the last 30 years, performing an original study to value every single species would be costly and time-consuming.

An important alternative is benefit transfer, a form of secondary research which has been used extensively in the past couple of decades. Rosenberger and Loomis (2003) define this term as the use of existing data or information in settings other than for what it was originally collected. The two forms of benefit transfers are value transfer and function transfer. In the former, a single estimate or average of multiple estimates, is transferred from the original site where primary research was conducted (called the study site) to a site with similar species that are being evaluated (called the policy site). In a function transfer, a statistical function is estimated based on the original studies and then this function is applied to the study site to calculate a value tailored to the study site. Function transfers are generally viewed as more accurate than value transfers because they can be tailored to account for differences in the site characteristics (Rosenberger and Loomis, 2003).

The two types of function transfers include demand functions and meta-regression analysis functions. The focus of this paper is on the meta-analysis, which helps to statistically explain the variation in the values obtained in different studies. For instance, looking at various CVM studies valuing threatened or endangered species, this method will help control for the effect of different study variables, such as question format, payment frequency, or type of respondent, to calculate WTP for that type of species. This information and its use in benefit transfer may assist in improving quantification of the economic benefits of critical habitat.

The purpose of this paper is to: (1) update information on the economic valuation of threatened, endangered, and rare species first published by Loomis and White in this journal more than twelve years ago. Using their same model, the first goal is to add new or overlooked CVM studies valuing threatened and endangered species conducted in the U.S.; (2) add a variable to the model to test if WTP from the new studies (conducted in or after 1995) are systematically different from old studies (conducted prior to 1995). This will help to identify whether people's valuation of threatened and endangered species has changed over time; (3) test new specifications, such as how a species ‘charisma’ affects the value placed on it, to identify an effective model which can be used in benefit transfer; (4) outline an example of how meta-analysis regression functions can be used in benefit transfer to estimate the value of various threatened and endangered species.