_Table 10_ : Malawi – Drivers of over-expectation

|**Malawi (maize)**|(1)<br>IHP|(2)<br>S19|(3)<br>IHP|(4)<br>S16|(5)<br>IHP|(6)<br>S13|(7)<br>IHP|(8)<br>S10|
|---|---|---|---|---|---|---|---|---|
||Base|Overexp.|Base|Overexp.|Base|Overexp.|Base|Overexp.|
|Community reported drought in last 2|-0.169|0.0694|-0.237|-0.472|-0.103|0.273|-0.211|-0.315**|
||(0.298)|(0.151)|(0.384)|(0.471)|(0.154)|(0.188)|(0.184)|(0.143)|
|Community reported flood in last 2y|-0.272|-0.133|1.515***|0.952*|-0.136|1.058|-0.184|0.170|
||(0.265)|(0.115)|(0.426)|(0.514)|(0.643)|(0.698)|(0.262)|(0.179)|
|log Plot area (ha)|0.363|0.0870|0.432|0.443|-0.0356|-0.316**|-2.174***|-0.591|
||(0.422)|(0.582)|(0.375)|(0.649)|(0.267)|(0.145)|(0.429)|(0.398)|
|Intercropped|-0.0330|-0.159|-0.0593|-0.435|0.105|-0.0713|0.241|0.437**|
||(0.139)|(0.193)|(0.233)|(0.273)|(0.123)|(0.107)|(0.230)|(0.208)|
|Soil fertility index|-0.101|-0.165**|-0.185|-0.0698|-0.0719|0.00453|-0.0278|0.145**|
||(0.0996)|(0.0640)|(0.277)|(0.289)|(0.136)|(0.158)|(0.103)|(0.0685)|
|Precipitation of Wettest Month (mm)|-0.00365|-0.000472|0.000458|0.00362|0.00392|-0.00251|0.00436|0.00668|
||(0.00651)|(0.00457)|(0.0100)|(0.0116)|(0.00862)|(0.00565)|(0.00561)|(0.00538)|
|Plot has improved maize variety|0.0298|-0.0248|0.0311|-0.123|||||
||(0.123)|(0.146)|(0.205)|(0.247)|||||
|Dependency Ratio|0.0360|-0.000936|0.0601|0.0347|0.0231|-0.0943|0.0685|0.0155|
||(0.118)|(0.104)|(0.116)|(0.143)|(0.0756)|(0.0952)|(0.0764)|(0.0673)|
|Any HH member has primary edu|0.265*|0.204|0.180|0.441*|0.111|-0.226|0.0150|-0.0541|
||(0.132)|(0.143)|(0.327)|(0.261)|(0.119)|(0.175)|(0.175)|(0.168)|
|Ag Asset Index|-0.324|-0.443|-1.757**|-1.686***|-0.0168|0.192|-1.134***|-0.748*|
||(0.330)|(0.276)|(0.670)|(0.622)|(0.251)|(0.259)|(0.338)|(0.395)|
|HH wealth index|-0.753*|-0.378|0.0155|0.696|-0.495|-0.712*|-0.641*|-0.848*|
||(0.443)|(0.351)|(1.055)|(1.012)|(0.357)|(0.363)|(0.367)|(0.471)|
|HH head has wage employment|-0.0261|-0.0727|0.149|-0.241|0.255|0.361*|-0.132|0.0977|
||(0.172)|(0.192)|(0.416)|(0.368)|(0.164)|(0.187)|(0.150)|(0.130)|
|HH member owns non-ag enterprise|0.231|0.102|0.234|0.218|-0.156|-0.0367|-0.161|-0.187|
||(0.176)|(0.125)|(0.241)|(0.263)|(0.115)|(0.159)|(0.175)|(0.140)|
|Female plot manager|0.103|-0.152|-0.0189|0.197|-0.0552|0.0582|-0.162|0.0647|
||(0.102)|(0.116)|(0.226)|(0.314)|(0.120)|(0.120)|(0.129)|(0.120)|
|Plot manager age|-0.000786|-0.00153|0.00427|0.00146|0.000357|0.00523|0.00129|0.00765|
||(0.00430)|(0.00404)|(0.00774)|(0.00981)|(0.00443)|(0.00315)|(0.00372)|(0.00481)|
|Manager has primary education|-0.110|-0.000140|-0.0524|-0.346|-0.169|-0.0710|-0.0150|0.241|
||(0.179)|(0.167)|(0.216)|(0.290)|(0.114)|(0.102)|(0.189)|(0.149)|
|Constant|0.990|0.888|0.151|0.132|-1.001|1.086|-0.524|-1.195|
||(1.570)|(1.196)|(2.905)|(3.234)|(2.130)|(1.384)|(1.471)|(1.513)|
|Observations|568|296|493|297|442|199|842|306|
|Adjusted R-squared|0.029|0.078|0.088|0.242|-0.001|0.078|0.150|0.498|
|District FE<br>Note: Regressions of the log of the ratio<br>parentheses. *** p<0.01, ** p<0.05, * p|YES<br>of expectati<br><0.1.|YES<br>ons (+1) to rea|YES<br>lizations (+1)|YES<br>on a number|YES<br>of potential co|YES<br>rrelates. Clust|YES<br>ered standard|YES<br>errors in|

# <u>What do we conclude and still need to know?</u>

From our analysis, farmers’ self-reported harvest expectations generally prove fair, albeit likely endogenous, proxies of the attainable harvest. Expectations align relatively well with harvest realizations as long as both rely on the same underlying “mental model” (are both self-reports) and therefore likely share the same biases. We find limited evidence for an association between overexpectation and loss occurrence when comparing direct measures of losses (planted area and plant productivity losses) to the gap between expected and realized harvest. Consequently, there remains a sizeable “black box” of (behavioral) factors explaining farmers’ expectation building and thus driving the expectation gap. Here, further research drawing on a (quasi-) experimental set-up is 32