and for Colombia from 2008 to 2010 it is 16.8 percent. About 24.2 and 13.8 percent of households in Chile and Colombia, respectively, are in high flood risk areas.

**Table 1. Summary statistics, Chile and Colombia**

||Count|Mean|SD|Min|Max|
|---|---|---|---|---|---|
|**Panel A: Chile**||||||
|Poor in 2011 (1 = yes, 0 = no)|44,614|0.096|0.295|0.000|1.000|
|Poor in 2015 (1 = yes, 0 = no)|61,433|0.039|0.193|0.000|1.000|
|Probability from poor to nonpoor between 2011 and 2015|36,035|0.731|0.101|0.485|0.930|
|Log of population size in 2015|36,035|10.887|1.334|7.432|14.434|
|High flood risk (1 = yes, 0 = no)|36,035|0.242|0.429|0.000|1.000|
|**Panel B: Colombia**||||||
|Poor in 2008 (1 = yes, 0 = no)|188,801|0.276|0.447|0.000|1.000|
|Poor in 2010 (1 = yes, 0 = no)|190,344|0.241|0.428|0.000|1.000|
|Probability from poor to nonpoor between 2008 and 2010|119,692|0.168|0.076|0.053|0.399|
|Log of population size in 2010|119,692|12.745|0.923|7.988|14.546|
|High flood risk (1=yes, 0=no)|119,692|0.138|0.345|0.000|1.000|

_Sources_ : Based on CASEN 2011 and 2015 and GEIH 2008 and 2010.

_Note_ : Poverty measure is based on per capita household income, with a threshold of US$5.50 per day. The probability of changing poverty status from poor to nonpoor is estimated based on the synthetic panel approach described in Annex B). We classify the areas with top 25 percent flood depth in each country as high flood risk areas (see Section 3.1.3). SD = Standard deviation.

Table 2 presents the summary statistics of key variables for Indonesia. Households’ poverty (1 = nonpoor; 0 = poor) and vulnerability (1 = neither poor nor vulnerable; 0 = poor or vulnerable) status are dummy variables used as the outcome variables for our regression analysis. Around 88 percent of household observations in our five-wave panel data are nonpoor, while 69 percent are neither poor nor vulnerable. The urban location typology—metro core, periphery urban, other urban, and the rural area—are also defined as dummy variables. Around 45 percent of household observations are from periphery urban, followed by other urban (19.2 percent), rural (18.6 percent), and metro core areas (17.4 percent). Households’ movements across locations between each of the five IFLS waves are summarized in Table A5. About 5.9 percent of households are in SPEI-dry areas, 90.7 percent in areas with SPEI-normal, and 3.4 percent in areas that experienced heavy rains. About 25 percent of households are exposed to high flood risks.

**Table 2. Summary statistics, Indonesia**

||Count|Mean|SD|Min|Max|
|---|---|---|---|---|---|
|Nonpoor (1 = yes, 0 = no)|47,796|0.877|0.328|0.000|1.000|
|Neither poor nor vulnerable (1 = yes, 0 = no)|47,796|0.690|0.462|0.000|1.000|
|City: Metro Core (1 = yes, 0 = no)|47,796|0.174|0.379|0.000|1.000|
|City: Periphery urban (1 = yes, 0 = no)|47,796|0.448|0.497|0.000|1.000|
|City: Other urban (1 = yes, 0 = no)|47,796|0.192|0.394|0.000|1.000|
|City: Rural (1 = yes, 0 = no)|47,796|0.186|0.389|0.000|1.000|
|SPEI: Dry (SPEI < −2) (1 = yes, 0 = no)|47,796|0.059|0.235|0.000|1.000|
|SPEI: Normal (1 = yes, 0 = no)|47,796|0.907|0.290|0.000|1.000|
|SPEI: Rainy (SPEI > 2) (1 = yes, 0 = no)|47,796|0.034|0.182|0.000|1.000|
|High flood risk (1=yes, 0=no)|47,796|0.251|0.433|0.000|1.000|

_Source:_ Based on IFLS 1993, 1997/98, 2000, 2007/8, and 2014/15. _Note:_ Poverty is measured with the national poverty line; vulnerability is measured with the vulnerability line, which is set at 1.5 times the poverty line. We classify the areas with top 25 percent flood depth in each country as high flood risk areas (see Section 3.1.3).

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