Stubbing out hypothetical bias: improving tobacco market predictions by combining stated and revealed preference data
In health, stated preference data from discrete choice experiments (DCEs) are commonly used to estimate discrete choice models that are then used for forecasting behavioral change, often with the goal of informing policy decisions. Data from DCEs are potentially subject to hypothetical bias. In turn...
Main Authors: | , |
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Format: | Journal article |
Language: | English |
Published: |
Elsevier
2019
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