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Following prior work, we manipulate the compromise effect by varying the middle options of each multiple price list and then estimate risk preferences without modelling the compromise effect.
One of the most well-known examples of preference construction is the compromise effect.
These naïve parameter estimates are not robust: they change as the compromise effect is manipulated.
To eliminate this bias, we incorporate the compromise effect directly into our econometric model.
This method can be applied to other settings that exhibit the compromise effect.
The compromise effect arises when options near the "middle" of a choice set are more appealing.
Similar(38)
Consistent with the hypotheses, the results indicate that (1) brands tend to gain share when they become compromise alternatives in a choice set; (2) attraction and compromise effects tend to be stronger among subjects who expect to justify their decisions to others; and (3) selections of dominating and compromise brands are associated with more elaborate and difficult decisions.
Thus, since the CE is evidently less prevalent in the more realistic binding choice setting, compromise effects must be considered overrated to a certain degree in the previous studies on hypothetical decisions.
Additionally, in accordance with observations for murine ATG16L1 [14], we observed an inhibitory, or at least functionally compromised, effect mediated by N-terminal tagged human ATG16L1.
We show that this method generates robust estimates of risk preference parameters that are no longer sensitive to compromise-effect manipulations.
Per-protocol analysis would address this issue but would compromise the effect of random allocation and therefore was not used.
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