year is divided by the June CPI in each province for observations in semester 1 and the December CPI in each province for observations in semester 2.<sup>14</sup> One notable aspect of the province-specific CPIs is that they are all equal to 100 in the base year (2012=100). This allows tracking of differences in the evolution of the cost of living across provinces over time but does not allow for identification of the difference in the cost of living across provinces in the base year.<sup>15</sup> The poverty line (z) used in this paper is determined using the level of PCE in 2003 corresponding to the official poverty rate of 24.9% in 2003.<sup>16</sup>

**Shock Measure** :  A wind model based on Boose et al. (2004) for the Philippines is employed to estimate local wind speeds at any particular locality where a tropical typhoon directly passes over or nearby.<sup>17</sup>

An additional distinguishing feature of this study is the fact that it uses the Philippines Standard Geographic Codes (PSGC) of the barangays (smallest administrative units) or residence of the households sampled by the FIES. Access to the PSGC of barangays, allows the wind model to be more granular in the sense that estimates of the wind speed associated with any given typhoon can be derived for the geographic location of each barangay. This provides a much better estimate of the wind speed experienced by any given household during a typhoon and thus the basis for a more realistic assessment of the impact of wind speed on household consumption. Anttila-Hughes and Hsiang (2013), did not have access to the barangay-level codes, and thus had to estimate windspeeds at the province level. This, in turn, implies that all households in each of the 81 provinces were assigned the same wind speed irrespective of a household’s distance from the typhoon’s path.

Figure 2 below presents the total number of typhoons (defined as windspeeds over 119mph) by barangay between 2000-2015, whereas Figure 4, presents the total number of barangays experiencing windspeeds over 119mph by year. Clearly, moving from the southern tip of the Philippines towards the north, more and more barangays experience windspeeds over 119 mph, and many barangays in the northeastern tip of the archipelago experience such extreme windspeeds many times (up to 21 times) between 2000 and 2015 (see figure 2). Also, the number of barangays experiencing windspeeds over 119mph varies significantly by year (see figure 3).

14 The CPI by province, year, and month was downloaded from the PSA OpenStat website: <u>http://openstat.psa.gov.ph/PXWeb/pxweb/en/DB/DB__2M/?tablelist=true&rxid=bdf9d8da-96f1-4100-ae09-18cb3eaeb313.</u> 15 To check the sensitivity of the estimates to a better accounting of the spatial cost of living differences, we have also tried an alternative approach that consists of first regressing the log of nominal PCE on a complete set of interactions across three sets of binary variables identifying the semester of interview of the household within a calendar year (2 in total), the year of interview (5 in total) and the region of residence (17 in total). This amounts to a total of 170 different dummy variables. The residual from such a regression is the “adjusted” lnPCE at any given point in time and region, that is expenditures comparable to the nominal expenditures in the reference time period (2003 semester 1) and region (region 1, which is the Ilocos region). The results were practically the same as to those reported in tables 1 and 2.

16 Annex 1 provides an estimate of the evolution of the poverty rate in the Philippines, based on the household PCE measure adjusted by the year/month province specific CPI used in this study.

> 17 A more detailed description of the wind model used is contained in Annex 2.

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