KNT Presentation Notes

Certain 1 rather uncertain leaning left 2 very

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Unformatted text preview: ght (5); Don Know ( t 999) For ‡at prior ( 999) ) fP i ;A (p ) = 1= j j = :2 for every p Conditional on prior not being ‡at, we further enquire: Q2: How large is your margin of uncertainty? Certain (1); Rather uncertain, leaning left (2); Very uncertain, left (3); Rather uncertain, leaning right (4); Very uncertain, right (5) Kendall, Nannicini & Trebbi (2014): “How Do Voters Respond to Information?” Motivation Empirical model Experimental design Reduced-form results Model estimation Marginal distributions (contd.) De…ne: (Increasing) tightness of the prior ) s 2 P ;s modal density ) P ;1 = 1= = :2; = f1; :::; 4g P ;4 =1 Skewness of the prior ) z 2 f 1; 1g if s = 2; 3 Assumption 1= j j P ;2 1 fP i ;A (p 6= p ) = ^ g P ;s ; z P ;3 1= j j (p p ) ^ 0 1 s=1 s = 2; 3 s=4 As for g (:) ) P 1 P ;s density in direction of asymmetry with 2 [1=2; 1] and linear decay in both directions P Kendall, Nannicini & Trebbi (2014): “How Do Voters Respond to Information?” Conclusion Motiva...
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