In Simple Words
Imagine a multiple-choice survey where 10% of participants choose answer A or B by flipping a coin without reading; by mathematically separating the random coin flippers from the attentive readers, researchers isolate the true choices of attentive participants.
Research question
Online job application field experiments suffer from participant inattention and accidental clicks, which threaten to distort structural logit choice parameters and bias economic estimates.
Participants
N = 1,152 unemployed applicants across 80 U.S. metropolitan areas in a nationwide hiring experiment.
Study Design
Two-component mixture logit model ($Pr(1[h_i]=1|e_{ih}) = P_e(1-\alpha) + (1-P_e)\alpha$) where the inattention rate ($2\hat{\alpha} = 10.6\%$) is empirically identified from post-choice job detail recall errors.
Results
Inattention affects choice variance without biasing central tendencies; the inattention-corrected flow value parameter ($\tilde{z} = 0.58, s.e. = 0.04$) matches the standard logit baseline ($\tilde{z} = 0.58, s.e. = 0.04$) identically across all hour choices.
Takeaway
Implement mixture choice models incorporating empirical error recall rates to verify whether cognitive noise distorts structural economic parameters.