Citation

Soto JJ, Rizzi LI, Ortuzar JD. Accid. Anal. Prev. 2023; 190: e107171.

Copyright

(Copyright © 2023, Elsevier Publishing)

DOI

10.1016/j.aap.2023.107171

PMID

37329841

Abstract

Estimating the value of non-market goods, such as reductions in mortality risks due to traffic accidents or air pollution, is typically done using stated choice (SC) data. However, issues with potential estimation biases due to the hypothetical nature of SC experiments arise, as protest choices are common and survey engagement is not constant across respondents. Further, if respondents choose to use different choice mechanisms and this is not considered, the results may also be biased. We designed an SC experiment to estimate the willingness to pay (WTP) for mortality risk reductions, that allowed us to simultaneously estimate the WTP to reduce the risk of traffic accident deaths and cardiorespiratory deaths due to air pollution. We formulated and estimated a multiple heuristic latent class model that also considered two latent constructs: Institutional Belief, to consider protest responses, and survey Engagement as a class membership covariate. We found, first, that individuals with lower institutional belief gave a higher probability of choice to the status-quo alternative, shying away from programs involving governmental action. Second, that not identifying respondents who do not appropriately engage in the experiment, biased the WTP estimators. In our case WTP decreased up to 26% when two different choice heuristics were allowed for in the model.

Language: en

Keywords

Willingness to pay; Choice Heuristics; Latent Classes; Latent Variables; Risk Reductions; Statistical Value of Life; Survey Engagement