Citing this, Subramanian argues that the official GDP growth rates have been overestimated by 1.1 percentage points when India is compared with other middle-income countries and by 2.5 percentage points when all countries are included in the comparison. This finding has been refuted by Goyal and Kumar (2019) who defend the official statistics citing methodological and data issues in A. Subramanian (2019).

The estimate of poverty we calculate using the pass-through rate is sensitive to the growth in consumption in national accounts. Any downward adjustment of growth, as the one suggested by A. Subramanian (2019), would lead to an increase in poverty. Hence, we also present poverty estimates adjusting growth downward by 1.1 and 2.5 percentage points. It is important to note that A. Subramanian’s (2019) findings are for the period 2011-2016 and for the GDP growth rate, while our application of the downward adjustment is for the period 2016-2018 and for the growth in per capita HFCE.<sup>30</sup>

# **4.4. Poverty rate estimates**

Table 5 reports poverty estimates for 2017 using our preferred pass-through rate, as well as a passthrough rate of 1, applied to various national accounts growth rates. These poverty estimates assume that growth is distribution-neutral, i.e. all observations in the survey are scaled up by the same growth rate, similar to the standard extrapolation methods that underpin the World Bank’s global poverty numbers (see Prydz et al. (2019)). In all cases, we line up the 2011/12 CES microdata to 2015 using urban/rural-specific growth rates. These growth rates are derived using the implied pass-through rates calibrated from the poverty estimates reported in Newhouse and Vyas (2019).<sup>31</sup> The national poverty estimates are calculated as the weighted sum of the rural and urban poverty rates using the population weights in WDI in the relevant year.<sup>32</sup> The estimates reported in Table 5 use the various pass-through rates after 2015.

In the first row of panel A, we report estimates of poverty derived from the growth in per capita HFCE as reported in WDI using a 0.67 pass-through rate and a range of estimates derived from the 95 percent confidence interval of the 0.67 pass-through rate. In addition, we also report the estimates from applying the raw growth in per capital HFCE (that is, using a pass-through of 1). A higher pass-through implies faster growth in survey consumption and thus a lower poverty rate. The national poverty rate derived from using a 0.67 pass-through is 10.39 percent with a 95 percent confidence interval of [9.97, 10.80], while the national poverty rate derived using a pass-through

> 30 The average ratio between per capita HFCE and per capita GDP for the years 2011-2018 is 0.560 with a standard deviation of 0.003. For the years 2011-2018, the average annual per capita HFCE growth rate was 6.1 percent, and the average annual per capita GDP growth rate was 5.6 percent for the same period. Source: WDI, World Bank. 31 A detailed discussion of estimating poverty rates for the years 2012-2015 in India can be found in Chen et al. (2018). 32 This accounts for changes in rural/urban population shares since the last survey. PovcalNet applies the same methodology to calculate national poverty rates for all countries that have rural/urban surveys, namely China, India and Indonesia. The rural/urban population shares implied by the survey weights may be different from shares in WDI.

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