relatively well off are less well represented in surveys) then we may well find higher inequality.<sup>3</sup> However, we currently have no basis correcting for this problem in either China or India.

Poverty monitoring in India since the 1960s has been mainly based on the household expenditure surveys done as part of the National Sample Surveys (NSS). The salient features are that household consumption expenditure per person is used as the individual welfare indicator and the poverty line that is intended to have a fixed real value across time and space (urban and rural areas of states) is determined by combined geographic and inter-temporal deflators. The main data issue is that assessing what has been happening to poverty and inequality in India during the 1990s has been clouded by a comparability problem between the two main surveys available for the 1990s.<sup>4</sup> There are concerns about how well surveys measure incomes or consumptions. Surveybased consumption and income aggregates for nationally representative samples typically do not match the aggregates obtained from national accounts (NA). This is to be expected for GDP, which includes non-household sources of domestic absorption. Possibly more surprising are the discrepancies found with both the levels and growth rates of private consumption in the NA aggregates; Ravallion (2003) provides evidence. The discrepancies between levels and growth rates of consumption as measured by India’s NSS and NA have been of particular concern, Yet here too it should be noted that (as measured in practice) private consumption in the NA includes sizeable and rapidly growing components that are typically missing from surveys (Deaton, 2005).<sup>5</sup> However, aside from differences in what is being measured, surveys do encounter problems of under-reporting (particularly for incomes; the problem appears to be less serious for consumptions) and the aforementioned problems of selective non-response.<sup>6</sup> There are also a number of data problems in making comparisons between these countries. These include that fact that China has traditionally used household income (per capita) as the ranking variable while India has used consumption (per capita). (We return to this point when we compare inequality measures.) Also, the available data on spatial differences in the cost-of-living are still rather weak in both countries. And purchasing power comparisons between the two countries are confounded by a number of concerns about the underlying price data and standard index-number problems. We will largely ignore these data problems in this paper, although that is not because we think them unimportant; rather, it is because this paper is not the place to dwell on them.

> 3 This is not necessarily the case, but there is supportive evidence for the US (Korinek et al., 2006). 4 The comparability problem is discussed in Deaton (2001), Datt and Ravallion (2002) and Sen and Hiamnshu (2004a). 5 Deaton and Kozel (2005) provide a useful compilation of papers on this and related issues of poverty measurement in India. 6

> In measuring poverty some researchers have replaced the survey mean by the mean from the national accounts (GDP or consumption per capita); see, for example, Bhalla (2002) and Sala-i-Martin (2002). This assumes that the discrepancy is distribution neutral, which is unlikely to be the case; for example, selective non-response to surveys can generate highly non-neutral errors (Korinek et al., 2005). For further discussion in the context of poverty measurement in India see Ravallion (2000).

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