We proceed in two steps. First we decompose the observed reduction in poverty into the simplest three elements: the consumption-to-income ratio, the number of adults as a share of the total number of household members and the income per adult. This allows us to explore all possible combinations and paths and to estimate Shapley values (Shapley value decomposition). We then further decompose the observed reduction in poverty by decomposing the elements of the income per adult in each case (Barros decomposition).

# **Results**

The three countries we analyze, Bangladesh, Peru and Thailand, all experienced fast growth and poverty reduction. Panel A in Table 3 show the changes in poverty in the last decade for relevant international poverty rates<sup>11</sup> and the extreme and moderate poverty rates defined by the respective institutes of statistics. Panel B in Table 3 show the results of the most aggregate Shapley value decomposition. The most important contributor to poverty reduction in each country has been growth in income per adult (which captures all labor market outcomes without distinguishing if they are through earnings or more employment plus any non-labor income). Regardless of the decomposition path used, we find that growth in income per adult from all sources explains over 50 percent of the reduction in the Bangladesh poverty headcount using the national moderate and extreme poverty lines, and over 60 percent using the US$1.25 poverty line. Income per adult explains over 85 percent of the reduction in poverty observed in Peru and Thailand, regardless of which poverty line is used (Figure 8 and Table 3). Changes in the share of adults per household (i.e. the decline in dependency rates) are another important factor behind poverty reduction in Bangladesh and Thailand. Finally, these initial decompositions suggest that if households had continued to consume the same share of income in the final period as what was observed in the initial period, then poverty would have fallen even more in the case of Bangladesh and Thailand. In other words, the fact that households are consuming a smaller share of their incomes in the final period implies that poverty—as measured by consumption aggregates—is higher than if the consumption-to-income ratio had remained constant. This result is particularly important in Thailand. In the case of Peru, by contrast, a higher consumption-toincome ratio contributed to the observed decline in poverty.

Results using different decomposition paths are in most cases invariant to the order in which the decompositions are done. The differences are particularly small in terms of the contribution that income per adult has on observed poverty reduction.<sup>12</sup> These results give us some confidence to further decompose total income per adult into subcomponents using a single path, instead of calculating all potential paths—which would require 5,040 separate decompositions.

To explore the multiple channels behind the changes in poverty depicted in Figure 1, we further disaggregate total income per adult into its subcomponents. The key result that emerges is that

> 11 The relevant international poverty lines are US$1.25 and US$2.50 for Bangladesh and US$2.50 and US$4 for Peru and Thailand.

> 12 We found similar small differences in the results of alternative paths when decomposing the poverty gap and the severity of poverty.

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