We now turn to the distribution of the impact of rainfall shocks across the regions of the Philippines, as well as across differences in access to infrastructure and diversification of activities in the municipalities of the FIES.

# Table 5

Table 5 displays the impact of rainfall shocks across regions. To help understand the results and the geographic distribution of the impact, column (1) presents the island where the regions are. Column (2) presents the regions. We have grouped some regions that were close to each other, in particular when the occurrence of one type of shock was very low and, as a consequence, likely not to be meaningful.<sup>17</sup> The average impact of each type shock in each region is presented in column (4). These are not marginal effects compared to an omitted region. The -0.095 coefficient on the negative shock in Ilocos means that in this region, compared to rainfall within one-standard deviation of the long-run average, a negative shock decreases household consumption by 9.5%. The regions mainly affected by negative rainfall shocks are Ilocos, which is in the North-Western part of Luzon as well as Western Visayas Islands. In Bicol, while it is estimated with less precision, the negative rainfall shock also has a large negative coefficient.

Comparing the magnitude of negative rainfall shocks to that of positive shocks, we see that Western Visayas is the region most at risk with respect to climate change, with an impact of negative shocks of 9% versus no impact of positive shocks. By contrast, and even though positive shocks are not estimated with precision, in Central Visayas and Eastern Visayas, the magnitudes of the coefficients on positive and negative shocks are close and there is no asymmetry between them. This is also true in Ilocos. In the case of Mimaropa, it is hard to predict anything because it did not experience a negative shock during the time of the surveys we use but it is region where an increase in rainfall is predicted due to climate change and it seems to benefit from positive shocks on rainfall.<sup>18</sup>

# Table 6

The results for infrastructure variables and their interactions with the rainfall shocks are in table 6. Due to high correlation between distance to the highway and distance to a ground line, we include them separately. We first examine the interaction of the distance to the highway with the rainfall shock, in columns (1) to (3) and then examine distance to a fixed line phone in columns (4) and (5) and finally include the measures together with distance to a cell phone signal as well as access to electricity in the municipality. The summary of table 6 is that the impact of negative rainfall shocks increases with an increase in the

> 17 When a type of shock was affecting fewer than 100 households in a given region, we grouped the region with another one on the same island.

> 18 We need to point out the negative coefficient on positive shocks in Central Luzon is misleading and due to a small number of households benefitting from positive shocks over the period in that region: only 140. We have not merged in our estimates Central Luzon with another region because it is a key region for rice production and our criterion to merge region was to have fewer than 100 households affected by a given outcome. However, this result is likely driven by the small number of observations.

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