Table 5: Test of model predictions: Disaggregated shocks

||(1)<br>Solicited<br>Extension|(2)<br>Solicited<br>Extension|(3)<br>Solicited<br>Extension|(4)<br>Solicited<br>Extension|(5)<br>Solicited<br>Extension|
|---|---|---|---|---|---|
|AgShock|0.061<sup>_∗∗∗_</sup>|0.063<sup>_∗∗∗_</sup>|0.061<sup>_∗∗∗_</sup>|0.062<sup>_∗∗∗_</sup>|0.060<sup>_∗∗∗_</sup>|
||(0.001)|(0.001)|(0.001)|(0.001)|(0.001)|
|NonAgShock|0.025<sup>_∗∗∗_</sup><br>(0.007)|||||
|NonAgShock (Health only)||0.022<sup>_∗∗_</sup><br>(0.030)|||0.017<sup>_∗_</sup><br>(0.066)|
|NonAgShock (Income only)|||0.055<sup>_∗∗∗_</sup><br>(0.008)||0.049<sup>_∗∗_</sup><br>(0.013)|
|NonAgShock (Crime only)||||0.046<sup>_∗∗_</sup><br>(0.020)|0.041<sup>_∗∗_</sup><br>(0.041)|
|HH FE|yes|yes|yes|yes|yes|
|Wave FE|yes|yes|yes|yes|yes|
|Controls|yes|yes|yes|yes|yes|
|Observations|19,653|19,653|19,653|19,653|19,653|
|R-squared (within)|0.026|0.025|0.026|0.026|0.027|

_Source:_ Authors’ analysis based on survey data from the LSMS-ISA database (World Bank, 2018). _∗ ∗∗ ∗∗∗ Notes: p <_ 0 _._ 10, _p <_ 0 _._ 05, _p <_ 0 _._ 01. _p_ -values in parentheses. Standard errors are clustered at the stratum level (consisting of 24 clusters defined as region _×_ rural). Included shock items are as follows: Health (“Illness or accident of HH member”, “Death or disability of HH member”), Income (“Loss of employment”, “Reduction in non-farm income”, “End of assistance/remittances”), Crime (“Theft of money/valuables”, “Conflict/violence”). As controls, full sets of dummies are included for the following variables: adults, children, education of HH head, age of head, male head.

Additional robustness checks with respect to clustering of standard errors, alternative variable definitions, and exclusion of household fixed effects are reported in Appendix C. As shown in Table A5, the model predictions hold when standard errors are clustered along both stratum and wave dimensions (“2-way”), when clustered at the district level (there are 158 districts), as well as for the cluster wild bootstrap procedure described in Cameron et al. (2008) to take into account the small number of clusters when clustering at the “stratum” level. Table A6 tests the robustness of the model predictions to alternative variable definitions. In columns (1) and (4), the extension indicators exclude advice which was provided by other farmers, because this constitutes a somewhat different approach to extension. In columns (2) and (5), the non-agricultural shock variable also contains the shock item “increase in prices for food”, which was previously not classified. In columns (3) and (6), the food price shock item is instead included in the agricultural shock variable. For all specifications, the shock variables remain significant. Table A7 shows that the model predictions also hold when no household fixed effects and no householdlevel controls are included (see columns 1-4; columns differ in their way of dealing with clustering), and when only the household-level controls are included but not the household fixed effects (columns 5-8). In particular, comparing the results in Table A7 with those in Table 4 shows that adding household fixed effects changes the point estimates of the 23