Table 3: Effects of Belief Update Intervention

||Unscaled||S|caled||
|---|---|---|---|---|---|
|||Equa|lity of|Pat|h Shape|
||(1)|Means<br>(2)|Medians<br>(3)|Triangle<br>(4)|Half Circle<br>(5)|
|Potential Good News|-10.74|-34.24|-30.59|-28.65|-32.48|
||(20_._97)|(20_._43)<sup>_∗_</sup>|(20_._57)|(20_._65)|(20_._53)|
|Good News|-68.01|-54.30|-56.22|-58.10|-55.43|
||(36_._80)<sup>_∗_</sup>|(26_._85)<sup>_∗∗_</sup>|(28_._40)<sup>_∗∗_</sup>|(29_._44)<sup>_∗∗_</sup>|(27_._69)<sup>_∗∗_</sup>|
|Potential Bad News|-10.14|-21.60|-18.07|-16.53|-19.68|
||(8_._82)|(16_._79)|(14_._65)|(13_._55)|(15_._60)|
|Bad News|-14.55|-27.82|-24.61|-23.06|-26.14|
||(9_._66)|(18_._09)|(15_._86)|(14_._70)|(16_._85)|
|Scaling Factor _λ_|-|_E_(_d_<sup>_T_ </sup>)_/E_(_d_<sup>_P_ </sup>)|_M_(_d_<sup>_T_ </sup>)_/M_(_d_<sup>_P_ </sup>)|1_/_<br>_√_<br>2|2_/π_|
|_Control Means_||||||
|_wij_|11,772|11,772|11,772|11,772|11,772|
|Potential Good News|8|7|7|7|7|
|Potential Bad News|14|8|9|9|9|
|Observations|3,566|3,566|3,566|3,566|3,566|
|Of Which Pot. Good/Bad News|939_/_2435|1764_/_1802|1596_/_1824|1566_/_2000|1759_/_1807|

**Notes:** The table reports ordinary least squares estimates based on specification (13). The dependent variable _wij_ is the willingness-to-pay of the participant _i_ for another farmer _j_ . _Potential Good News_ is equal to the absolute value of the difference between true and rescaled perceived distance in walking minutes if the difference is positive, _|d_<sup>_T_</sup> _ij_<sup>_−λdP_</sup> _ij_<sup>_|_if</sup> _d_<sup>_T_</sup> _ij_<sup>_λ −dP_</sup> _ij_<sup>_>_0.</sup><sup>_PotentialBadNews_isequaltotheabsolutevalueofthedifferencebetweentrueandrescaledperceived</sup> distance in walking minutes if the difference is negative, _|d_<sup>_T_</sup> _ij_<sup>_−λdP_</sup> _ij_<sup>_|_if</sup><sup>_dT_</sup> _ij_<sup>_−λdP_</sup> _ij_<sup>_<_0.</sup><sup>_Good(Bad)News_is equal to</sup><sup>_Potential_</sup> _Good (Bad) News_ multiplied by a treatment indicator _Td_ equal to 1 if the true distance was revealed to the participant. Column (1) reports unscaled estimates (or _λ_ = 1). In column (2) _λ_ solves _E_ ( _d_<sup>_T_</sup> _ij_<sup>)=</sup><sup>_λE_(</sup><sup>_dP_</sup> _ij_<sup>);sotheperceiveddistanceis</sup> rescaled to have mean equal to the true distance. In column (3) _λ_ solves _Median_ ( _d_<sup>_T_</sup> _ij_<sup>)=</sup><sup>_λMedian_(</sup><sup>_dP_</sup> _ij_<sup>);sotheperceived</sup> distance is rescaled to have median equal to the true distance. In column (4) _λ_ solves _d_<sup>_T_</sup> _ij_<sup>=</sup><sup>_λdP_</sup> _ij_<sup>,</sup><sup>_dT_</sup> _ij_<sup>isthehypotenuseof</sup> an isosceles right triangle and _d_<sup>_P_</sup> _ij_<sup>istwiceeachcathetus,(</sup><sup>_dT_</sup> _ij_<sup>)2=(</sup><sup><u>1</u></sup> 2<sup>_dP_</sup> _ij_<sup>)2+ (</sup><sup><u>1</u></sup> 2<sup>_dP_</sup> _ij_<sup>)2.Incolumn(5)</sup><sup>_λ_solves</sup><sup>_dT_</sup> _ij_<sup>=</sup><sup>_λdP_</sup> _ij_<sup>,</sup> _d_<sup>_T_</sup> _ij_<sup>isthediameterofacircleand</sup><sup>_dP_</sup> _ij_<sup>ishalfofacircumference,2</sup><sup>_dP_</sup> _ij_<sup>=2</sup><sup>_π_</sup> _d_ 2<sup>_T_</sup> _ij_<sup>.Then</sup><sup>_λ_=2</sup><sup>_/π_.ValuesareinUgandan</sup> Shillings. All specifications include participant fixed effects. Robust standard errors are given in round brackets; *** (**) (*) indicates significance at the 1% (5%) (10%) level.

cathetus: _λ_ =<sup>1</sup> _/√_ 2. This allows me to examine the scenario depicted in Figure A.3, where the solid line between A and B is the as-the-crow-flies distance and the dotted line is the walking path a farmer has in mind. Similarly, in column (5) I set _λ_ such that the true distance is the diameter of a circle and the perceived distance _d_<sup>_P_</sup> _ij_<sup>ishalfacircumference:</sup> _λ_ =<sup>2</sup> _/π_ . In this case, the farmer has in mind a semi-circular walking path between two plots, while the as-the-crow-flies distance is the diameter.

Scaling results in more dyads having potential good news and fewer dyads having potential bad news relative to the unscaled analysis; in the last row of columns (2) - (5) 27