Distributional Impact Analysis of Climate Variability in Rural Indonesia To assess the effect of delayed onset on consumption using the SUSENAS core data, we estimated the following equation: Where, as before, _Cit_ represents the per capita expenditure of household _i_ in year _t_ and O represents monsoon onset measured in standard deviations. Z contains a vector of household characteristics that are assumed to be unaffected by rainfall shocks (gender, age, and education of the household head). _DP_ is a set of province dummy variables, and _Dt_ is a set of year dummies. As with the IFLS estimates, we also estimated versions of equation (5) that included two lags of monsoon onset. The results are shown in Tables 13, 14 and 16 in Annex 1.

**Variation in onset has little effect on household per capita consumption.** Table 15 (Annex 1) shows that delayed onset the previous year has virtually no effect on per capita expenditure when estimated for all years and provinces in the sample. Neither does early onset affect per capita expenditure. The estimates are sufficiently precise to rule out negative effects larger than 1.3 percent with 95 percent confidence.  The decomposition of the effect of monsoon onset on total household consumption and household size are presented in Table 16. As we would expect from earlier results, monsoon onset has little effect either on total household consumption or household size.

**Delayed onset two years ago has virtually no effect on consumption when using the SUSENAS.** The positive association between delayed onset two years ago and per capita consumption found in the IFLS analysis is not robust to the use of SUSENAS. In the full rural sample, delayed onset two years ago is associated with a less than a one half percent reduction in log per capita consumption, and can rule out effects larger than 1.5 percent.

**Late onset has a larger negative effect when the sample is limited to IFLS years and provinces.** IFLS data covers only a subset of the provinces and years covered by the SUSENAS.  To test the importance of this limited coverage, we re-estimated the effect on variation in monsoon onset using the SUSENAS, but limited the sample to only the provinces and years covered by the IFLS.  Table 17 shows that there is a substantially larger negative effect of delayed onset on per capita consumption, equal to 8.2 percent, when the SUSENAS sample is limited to IFLS years and provinces.

**The negative correlation between delayed onset and consumption in the cross-section appears to be especially strong in IFLS years.** When the sample is extended to all provinces but limited to IFLS years, delayed onset reduces consumption by 6.6 percent. On the contrary, the negative effect of delayed onset disappears when the sample is extended to all years but only IFLS-provinces are included. This evidence suggests that the negative effect of delayed onset on household expenditure is not consistent across years.

**IFLS years contain disproportionately few cases of late monsoon onset.** In 1993 approximately 4.6 percent of households experienced onset that was at least 0.5 standard deviations late; in 1997, none of the households did and in 2000, 10 percent of the households did. For all years, the corresponding proportion is 26.5 percent.

**The nature of the IFLS survey, which disproportionately represents older heads, may also overstate the impact of delayed onset.** The IFLS makes no effort to re-contact persons born after 1968 that exited households after 1993, unless they were the two children of the head in 1993 that were selected as “main

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