Valuation Methods in Stated Preference Analysis
Summary
Stated preference analysis is a suite of survey-based techniques designed to estimate the value individuals place on non-market goods and services. At its core lie contingent valuation and choice experiment methods. In contingent valuation, respondents state their maximum willingness to pay for a defined change in a good or service, whereas choice experiments present respondents with alternative bundles characterised by varying attributes and prices, from which marginal valuations are inferred. Both approaches draw on random utility theory, modelling choice probabilities as functions of attributes and price. Advances in experimental design—such as efficient experimental designs, scale-adjusted latent class models and incorporation of behavioural insights—have enhanced the precision and validity of value estimates. Persistent challenges include hypothetical bias, strategic misreporting and design sensitivity, which researchers address through de-biasing procedures such as cheap-talk scripts, certainty scales and iterative bidding formats. Integration with revealed preference data and application of correction techniques are extending the robustness of welfare estimates for environmental, health and public policy appraisal on a global scale.
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Valuation Methods in Stated Preference Analysis publication trend
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Technical terms
Contingent valuation: A survey method in which individuals directly state their maximum willingness to pay for a specified change in the provision of a good or service.
Choice experiment: A discrete choice method presenting alternatives defined by attribute levels and prices, from which marginal valuations are derived via choice probabilities.
Willingness to pay (WTP): The maximum monetary amount an individual is prepared to sacrifice to obtain a specified improvement or avoid a detriment in a good or service.
Hypothetical bias: The divergence between stated willingness to pay in hypothetical scenarios and actual economic behaviour, often leading to overestimation of values.
Random utility model: A theoretical framework assuming that individuals choose the alternative with the highest utility, where utility comprises a systematic component and a random error term.
References
- Enhancing the face validity of choice experiments: A simple diagnostic check. Ecological Economics (2024).
- Testing hypothetical bias in a choice experiment: An application to the value of the carbon footprint of mandarin oranges. PLOS ONE (2022).
- Social desirability bias in the environmental economic valuation: An inferred valuation approach. Ecological Economics (2021).
- Stated versus revealed preferences: An approach to reduce bias. Health Economics (2021).
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