Vertaile menetelmiä

	Ecosystem-Service Choice Experiment	Benefit Transfer Valuation
Tieteenala	Environmental Economics	Environmental Economics
Menetelmäperhe	Regression model	Process / pipeline
Syntyvuosi	1998	2015
Kehittäjä	Nick Hanley, Robert E. Wright & Vic Adamowicz	Robert J. Johnston, John Rolfe, Randall S. Rosenberger & Roy Brouwer
Tyyppi	Random-utility discrete-choice model for stated-preference valuation	Pipeline for transferring existing valuation estimates to new policy sites
Alkuperäislähde	Hanley, N., Wright, R. E., & Adamowicz, V. (1998). Using Choice Experiments to Value the Environment. Environmental and Resource Economics, 11(3-4), 413-428.	Johnston, R. J., Rolfe, J., Rosenberger, R. S., & Brouwer, R. (Eds.). (2015). Benefit Transfer of Environmental and Resource Values: A Guide for Researchers and Practitioners. Springer.
Rinnakkaisnimet	Discrete Choice Experiment for Ecosystem Services, Stated-Preference Choice Modelling, Attribute-Based Environmental Valuation, Choice Modelling of Ecosystem Services	Value Transfer, Benefits Transfer, Environmental Value Transfer, Function Transfer
Liittyvät	3	3
Tiivistelmä	A discrete choice experiment is a survey-based, stated-preference method for valuing changes in ecosystem services that have no market price. As set out by Hanley, Wright and Adamowicz in 1998, respondents are shown a series of choice sets, each offering alternatives described by a common set of attributes — including environmental features such as water quality, biodiversity, or habitat area, and a cost or price attribute — and asked to pick their preferred option. Grounded in random utility theory and Lancaster's view of goods as bundles of attributes, the method models each choice as the selection of the highest-utility alternative and estimates how much utility each attribute contributes. Dividing an attribute's coefficient by the cost coefficient yields the marginal willingness to pay for that attribute, allowing economists to put a monetary value on ecosystem-service improvements.	Benefit transfer is the practice of using economic value estimates from existing valuation studies to estimate the value of an environmental change at a new policy site where conducting a fresh primary study is not feasible. As systematized in Johnston, Rolfe, Rosenberger and Brouwer's 2015 guide, it ranges from simple unit-value transfer — borrowing a willingness-to-pay figure from a similar study — to function transfer, in which an estimated value function is applied using the characteristics of the new site and population, and meta-analytic transfer that pools many studies into a single predictive function. Because primary valuation through choice experiments or travel-cost studies is expensive and slow, benefit transfer is the workhorse of routine policy appraisal, allowing analysts to value ecosystem-service changes quickly while explicitly managing the error introduced by adapting evidence across contexts.