combine split households—single households in 2005 that have divided into multiple households in 2012—into a single household. For these households, consumption and income are computed as the weighted average (by household size) of the income and consumption of the component households. This adjustment affects 12 percent of the households in the balanced panel.

**<u><mark>Table 2. Sample Size</mark></u>**

|**Year**|**Indiv**<br>**Observations**|**iduals**<br>**Expanded**<br>**observations**|**Households**<br>**Observations**<br>**Expanded**<br>**observations**|
|---|---|---|---|
|2005|163668|966495179|30327<br>182818331|
|2012|171648|1012300000|30327<br>182818331|

Source: IHDS, 2005 and 2012 The sample is restricted further as follows. First, we restrict ourselves to households with positive total income (which are 98.5 percent of the sub-sample), thereby excluding households with substantial agricultural or business losses.<sup>8</sup> Second, outliers (0.57 percent) are identified using the _blocked adaptive computationally efficient outlier nominators_ algorithm (Billor et al., 2000) on all sources of income and the consumption aggregate, and then eliminated from the sample. Third, households with consumption-income ratios above the 95<sup>th</sup> percentile are dropped to reduce measurement error (4.9 percent),<sup>9</sup> as are households with missing values in our variables of interest (0.04 percent). All these adjustments reduce the sample by an additional 6.3 percent, which leaves us with a balanced panel of 30,343 households. Table 2 shows the size of the sample by year, and the number of expanded observations using panel-adjusted weights.<sup>10</sup>

# _3.1. The distribution of income and consumption growth_

The period of 2005-2012, according to IHDS data, shows an interesting pattern of distributional change. In looking at how income and consumption growth have been distributed across the population, the distinction between anonymous and non-anonymous measures is important. Anonymous growth incidence curves (GIC), which show the annual percentage change in income or consumption for every centile of the distribution (dotted lines in Figure 1), are flat for both consumption and income, at a level well above zero. This implies that growth has been significant with almost no impact on the overall distribution of consumption and income, which is also consistent with negligible change in the Gini coefficients for these indicators (Table 3).

> 8 For capital gains we convert all negative income sources to zero because these might reflect losses in a particular year but not in the long-run. All incomes and consumptions are converted to 2005 prices and adjusted for spatial price differences (at the State level).

> 9 Households with high consumption income ratios are likely to be those under-reporting income, or experiencing losses in business incomes.  Most are in the top decile of the consumption distribution, and their exclusion has little impact on decompositions focused on the lower tail of the distribution.

> 10 Even though the restrictions imposed by data reduce the full sample by around 13 percent, in Table A3 in the Appendix we show that that the poverty estimates we obtain using the full sample are consistent with those obtained from using our balanced-panel sample. Therefore, the results we present here are indicative of what would have been obtained with the full, nationally representative, sample.

6