Elicitation Effects in Contingent Valuation: Comparisons to a Multiple Bounded Discrete Choice Approach

1998 ◽  
Vol 36 (2) ◽  
pp. 170-185 ◽  
Author(s):  
Michael P Welsh ◽  
Gregory L Poe
Author(s):  
Lincoln Quillian

This article contrasts traditional modeling approaches and discrete-choice models as methods to analyze locational attainment—how individual and household characteristics (such as race, socioeconomic status, age) influence the characteristics of neighborhoods of residence (such as racial composition and median income). Traditional models analyze attributes of a neighborhood as a function of the characteristics of the households within them; discrete-choice methods, on the other hand, are based on dyadic analysis of neighborhood attributes and household characteristics. I outline two problems with traditional approaches to residential mobility analysis that may be addressed through discrete-choice analysis. I also discuss disadvantages of the discrete-choice approach. Finally, I use data from the Panel Study of Income Dynamics to estimate residential mobility using traditional locational attainment and discrete-choice models; I show that these produce similar estimates but that the discrete-choice approach allows for estimates that examine how multiple place characteristics simultaneously guide migration. Substantively, these models reveal that the disproportionate migration of black households into lower-income tracts amounts to sorting of black households into black tracts, which on average are lower income.


Author(s):  
Tim Haab ◽  
Lynne Lewis ◽  
John Whitehead

The contingent valuation method (CVM) is a stated preference approach to the valuation of non-market goods. It has a 50+-year history beginning with a clever suggestion to simply ask people for their consumer surplus. The first study was conducted in the 1960s and over 10,000 studies have been conducted to date. The CVM is used to estimate the use and non-use values of changes in the environment. It is one of the more flexible valuation methods, having been applied in a large number of contexts and policies. The CVM requires construction of a hypothetical scenario that makes clear what will be received in exchange for payment. The scenario must be realistic and consequential. Economists prefer revealed preference methods for environmental valuation due to their reliance on actual behavior data. In unguarded moments, economists are quick to condemn stated preference methods due to their reliance on hypothetical behavior data. Stated preference methods should be seen as approaches to providing estimates of the value of certain changes in the allocation of environmental and natural resources for which no other method can be used. The CVM has a tortured history, having suffered slings and arrows from industry-funded critics following the Exxon Valdez and British Petroleum (BP)–Deepwater Horizon oil spills. The critics have harped on studies that fail certain tests of hypothetical bias and scope, among others. Nonetheless, CVM proponents have found that it produces similar value estimates to those estimated from revealed preference methods such as the travel cost and hedonic methods. The CVM has produced willingness to pay (WTP) estimates that exhibit internal validity. CVM research teams must have a range of capabilities. A CVM study involves survey design so that the elicited WTP estimates have face validity. Questionnaire development and data collection are skills that must be mastered. Welfare economic theory is used to guide empirical tests of theory such as the scope test. Limited dependent variable econometric methods are often used with panel data to test value models and develop estimates of WTP. The popularity of the CVM is on the wane; indeed, another name for this article could be “the rise and fall of CVM,” not because the CVM is any less useful than other valuation methods. It is because the best practice in the CVM is merging with discrete choice experiments, and researchers seem to prefer to call their approach discrete choice experiments. Nevertheless, the problems that plague discrete choice experiments are the same as those that plague contingent valuation. Discrete choice experiment–contingent valuation–stated preference researchers should continue down the same familiar path of methods development.


Author(s):  
Jose Osiris Vidana-Bencomo ◽  
Esmaeil Balal ◽  
Jason C. Anderson ◽  
Salvador Hernandez

2016 ◽  
Vol Volume 10 ◽  
pp. 2217-2228 ◽  
Author(s):  
Rieke Alten ◽  
Klaus Krüger ◽  
Julian Rellecke ◽  
Julia Schiffner-Rohe ◽  
Olaf Behmer ◽  
...  

2020 ◽  
Vol 10 (4) ◽  
pp. 756-767 ◽  
Author(s):  
James B. Tidwell

Abstract Significant investment is needed to improve peri-urban sanitation. Consumer willingness to pay may bridge some of this gap. While contingent valuation has been frequently used to assess this demand, there are few comparative studies to validate this method for water and sanitation. We use contingent valuation to estimate demand for flushing toilets, solid doors, and inside and outside locks on doors and compare this with results from hedonic pricing and discrete choice experiments. We collected data for a randomized, controlled trial in peri-urban Lusaka, Zambia in 2017. Tenants were randomly allocated to discrete choice experiments (n = 432) or contingent valuation (n = 458). Estimates using contingent valuation were lower than discrete choice experiments for solid doors (US$2.6 vs. US$3.4), higher for flushing toilets ($3.4 vs. $2.2), and were of the opposite sign for inside and outside locks ($1.6 vs. $ − 1.1). Hedonic pricing aligned more closely to discrete choice experiments for flushing toilets ($1.7) and locks (−$0.9), suggesting significant and inconsistent bias in contingent valuation estimates. While these results provide strong evidence of consumer willingness to pay for sanitation, researchers and policymakers should carefully consider demand assessment methods due to the inconsistent, but often inflated bias of contingent valuation.


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