of a rural household. Failing to adjust by cost-of-living differences would over-estimate poverty in rural areas, and under-estimate them in urban areas.

International poverty rates in the region in most cases are based on welfare aggregates that are not spatially deflated. While all South Asian countries carry out spatial deflation when calculating their national poverty estimates, the World Bank currently only spatially deflates the welfare measures in Nepal and Bhutan when calculating international extreme poverty rates. Bhutan uses a survey-based price index (S-SPI) to deflate prices. In this case, the spatial price indices are derived using information derived from the survey. Similarly, Bangladesh and Nepal use the Implicit Spatial Price Index (I-SPI) to deflate prices. The implicit spatial price index is constructed using regional specific poverty lines to determine the cost-of-living differences (Deaton and Muellbauer, 1980).<sup>14</sup> Table 7 shows the international poverty rates using the nominal and spatially deflated national consumption aggregates. Overall, the absence of spatial deflation in calculating the international extreme poverty rates seems might have a minor effect on the estimation of country-level international poverty rates, but it can have substantial impacts on international poverty measurement across regions within countries. In most countries, except for Nepal, the impact of spatial deflation is non-trivial. Without spatial deflation, urban areas have less poverty, and rural areas have more poverty **_._** For example, in Nepal, if the consumption aggregates were not spatially deflated, then urban international extreme poverty rate would be 4.3 percentage points higher and rural poverty would be 7.1 percentage points lower. If Bangladesh spatially deflated its consumption aggregates, then it would see urban international extreme poverty rate 3.3 percentage points higher and rural extreme international poverty rate 4.7 percentage points lower.

**Table 7. International extreme poverty rate in urban and rural areas,** **<u>with and without spatial deflation</u>**

||**Inter**<br>**povert**|**national**<br>**y rate (%)**|**Urban i**<br>**povert**|**nternational**<br>**y rate (%)**|**Rural in**<br>**povert**|**ternational**<br>**y rate (%)**|
|---|---|---|---|---|---|---|
||**Nominal**|**Spatially**<br>**Deflated**|**Nominal**|**Spatially**<br>**Deflated**|**Nominal**|**Spatially**<br>**Deflated**|
|Bangladesh|18.51|16.0|6.7|10.0|22.8|18.1|
|Bhutan|2.17|2.2|0.21|0.22|3.4|3.1|
|India|21.56|19.4|13.4|26.4|24.8|16.5|
|Maldives|7.25|7.3|3.9|5.8|10.2|9.2|
|Nepal|19.99|14.89|4.7|9.0|23.4|16.3|
|Pakistan*|8.28|7.0|2.8|3.1|10.7|9.0|
|Sri Lanka|1.92|1.7|0.3|0.4|2.3|2.0|

Source: Authors’ own estimates based on South Asia Harmonized Micro Dataset (SARMD). Pakistan’s values are from 2010.

# _Intertemporal deflation_

> 14 As an illustrative example, consider a country with two regions. The poverty line (PL) in a region can be interpreted as the cost of achieving a reference utility level in that region. The ratio between the poverty lines in two regions can be interpreted as a true-cost-of-living index, that is, as a spatial price index. Thus, the ratio between the regional poverty lines gives the cost of achieving the reference utility level in region 1 relative to region 2. This method makes strong assumptions, namely that the unobserved reference utility level underlying the poverty lines is constant across regions.

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