**Table 6: Comparison of shock incidences during survey year across household categories** **<u>(share of households that experienced shocks)</u>**

|Shock|_Income&_<br>_assetpoor_|_Income rich& _<br>_assetpoor_|_Income poor& _<br>_asset rich_|_Income& _<br>_asset rich_|Test<br>statistics<sup>a</sup>|
|---|---|---|---|---|---|
||||||<sup>2</sup>=16.08*|
|Income shock|0.14|0.08|0.10|0.09|*|
|Asset shock|0.06|0.04|0.06|0.05|NS|
|Labor shock|0.12|0.11|0.12|0.13|NS|
||||||<sup>2</sup>=15.7|
|Anytype of shock<sup>b</sup>|0.27|0.19|0.23|0.22|1**|
|N|2863|801<br>|801<br>|2864||

*, **, *** Significantly different at 0.1, 0.05 and 0.01 level, NS=Not significant.<sup>a</sup> Kruskal-Wallis test of difference between the groups.<sup>b</sup> Share of households that experienced any of the above shocks.

We observe only small differences for the three other poverty groups. We expected a higher incidence of (income) shocks among the _income poor & asset rich_ compared with the _income & asset rich_ , i.e., that a higher prevalence of shock could help explain why some asset rich become income poor. This is not the case, and it might suggest that most of the asset rich households have sufficient means to deal with the shock. Further, the shocks – even if classified as severe – may not be sufficiently large to make the asset rich fall below the income poverty line.<sup>17</sup> Overall, the findings suggest that income shocks – not unexpectedly – have a negative impact on observed income, and in particular for the asset poor. The results also suggest that the asset rich might have more means to reduce the negative impacts of an income shock.

# **5 Vulnerability across poverty categories**

## **5.1 Household income and environmental reliance**

Income and asset poor households are the most vulnerable, i.e., more sensitive to shocks with lower adaptation and coping capacities. In addition to the vulnerability due to their overall income and asset positions, we ask if there are some systematic patterns that make income and/or asset poor households more vulnerable to shocks, or, alternatively, make them in a relative better position to cope with shocks. We first look at the overall income composition, and the environmental reliance (income share) in particular. A high environmental reliance is suggestive that households have access to and the skills to use environmental resources as a possible coping mechanism (next section). This is confirmed in the econometric analysis of self-reported shocks in Noack et al. (2015): a high forest income share (at the village level) has a positive effect on households’ choice to use forest or wild products as a coping strategy. Furthermore, there are reasons to believe that forest income – at least in the short/medium term - might be less sensitive to climate change compared to crop income, cf. section 2.2.

> 17 To further test the impact of shock on observed income, we regressed the error term in the income prediction regressions (section 3.3), i.e. the difference between the observed and the predicted income, on different types of shock (dummies). The overall power of the model was weak (F-test), although the coefficient for income shocks was negative and statistically significant.

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