surveys are correct on average and focuses instead on the problem of survey comparability, for which purpose the poverty measures are anchored to the national accounts data.

Under certain conditions, one can derive a defensible method of mixing NAS and survey data. The idea is to treat the NAS data as the Bayesian prior, and the survey as the new information. Chen and Ravallion (2009) show that if consumption is log-normally distributed with a common variance between the prior and the new data, then the mixed (posterior) estimator is the geometric mean of the survey mean and its predicted value based on consumption per person from the NAS. These are strong assumptions; in particular, the prior based on the NAS may well have a different degree of inequality to the survey. However, this result does at least offer a clear foundation for a sensitivity test, given the likely heterogeneity in surveys. The predicted values were based on date-specific cross-country regressions (Chen and Ravallion, 2009) _Poverty lines:_ There are also differences in the way poverty is measured from surveys in these countries. The poverty lines used in each country do not have the same purchasing power with Brazil’s national poverty line having a real value appreciably higher than India’s and China’s. It is compelling to apply a common standard, such that any two people with the same purchasing power over commodities are treated the same way—both are either poor or not poor, even if they live in different countries.<sup>48</sup> The main international line used here is $1.25 a day at purchasing power parity (PPP) in terms of household consumption in 2005; this is the average poverty line found in the poorest 15 countries in a data set on national poverty lines across 75 developing countries.<sup>49</sup> Key summary statistics are also given for a line of $2.00 a day at 2005 PPP, which is the median poverty line for all developing counties with the available data.

_Consumption versus income:_ A further difference is in the way household welfare is measured for deciding who is poor. India’s NSS uses consumption rather than income, as used in Brazil and China; due to consumption smoothing, income inequality tends to be higher than consumption inequality. The level of income inequality in India is likely to be higher than consumption inequality. The NSS does not include incomes, but one estimate based on incomes (though from a different survey to the NSS) found a Gini index of income inequality in India in 2004/05 of 0.53—still lower than in Brazil, but not by much, and higher than in China (Lanjouw and Murgai, 2009).

So there are two potentially offsetting data problems in comparing poverty in India with that in Brazil and China. Average consumption from India’s surveys may well underestimate mean income but it may well underestimate inequality too.

_National accounts:_ This paper reports World Bank data on the NAS aggregates (GDP and PCE), which are based on official sources. These too can be questioned. Here the country that has figured most prominently in the debates in the literature is China, for which it has been argued that official estimates over-estimate the growth rate of GDP. In particular, Maddison

> 48 One argument against this view is that people care about relative deprivation relative to the norms within their own country. For a critical discussion of this view see Ravallion (2008a).

> 49 See Ravallion et al. (2009). On the differences between this line and the prevailing official line in India see Ravallion (2008b). Note that India’s and China’s official poverty lines are closer to $1.00 per day at 2005 PPP.

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