MOB methodology, further partitioning of the global sample into geographic regions is not necessary. When estimating the poverty rate for India, in addition to the poverty derived from the 0.67 pass-through rate, we also present a range of poverty estimates derived using the 95 percent confidence band for the 0.67 pass-through rate.

Our preferred pass-through rate of 0.67 is in line with the broader literature on India. Sen (2000) finds that the ratio of survey mean to consumption in national accounts to be between 0.6 and 0.7 for the period 1972 to 1997. For the same period, Datt and Ravallion (2002) find that the ratio between the survey mean and consumption in national accounts to be between 0.575 and 0.645 – depending upon, as discussed above, which national accounts series (new or old) one uses. Ravallion (2003) estimates this ratio for 1997 in India to be 0.55. The author also finds that, using 22 survey spells of South Asian countries in the 1980s and 1990s, β=0.525.<sup>26</sup> Deaton and Kozel (2005) estimate the ratio between the two sources to be “currently around” 0.667. The implied pass-through estimate for fiscal year 2014/15 using the poverty rates from the survey-to-survey estimation by Newhouse and Vyas (2018) is around 0.65.<sup>27</sup> The ratio of survey mean to per capita HFCE using all available CES surveys for India is 0.751, and this ratio using comparable spells is 0.765.<sup>28</sup>

# **4.3. Concerns over National Accounts growth rates**

There have been recent debates around the soundness of the official GDP growth rates. A. Subramanian (2019) argues that the official GDP growth for the 2011-2016 period might have been overestimated by as much as 2.5 percentage points due to methodological changes that the Central Statistics Office (CSO) undertook in 2011. According to A. Subramanian (2019), the CSO switched the calculation of national statistics from a volume-based index to a value-based system of accounting. Value-based accounting is sensitive to price fluctuations, and hence a double pricediscounting is generally recommended for these indexes. However, the CSO adopted a single deflation in prices of national statistics.<sup>29</sup>

> 26 Ravallion (2003) finds a pass-through rate of 0.752 with a standard error of 0.563 when employing a regression as in equation (5) but with a non-zero intercept; the author finds a pass-through rate of 0.525 with a standard error of 0.258 on a regression setting the intercept equal to zero. For the global sample consisting of 142 spells, setting the intercept to zero the author finds a pass-through rate of 0.499.

> 27 For a detailed discussion on the survey-to-survey methodology see the sub-section above. The national pass-through rate in India for the period 2012-2015 is 0.65. The 0.65 national pass-through rate is calculated as the populationweighted average of the rural pass-through rate (0.699) and urban pass-through rate (0.551). The rural and urban passthrough rates are calibrated using the poverty estimates from Newhouse and Vyas (2018) for 2014/15 (for more details, see Chen et al. (2018)).

> 28 The available CES surveys for India are 1977/78, 1983, 1987/88, 1993/94, 2004/05, 2009/10, and 2011/12, of which 1993/94, 2004/05, 2009/10, and 2011/12 surveys are comparable. Using per capita GDP growth instead of per capita HFCE growth yields pass-throughs of 0.639 for the full sample and 0.768 for the comparable spells.

> 29 Sengupta (2016) provides similar arguments that highlight the measurement issues created by the choice of accounting methods used by the CSO.

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