**Table 1. Stylized comparison of different price data sources**

||Market price survey|CPI price data|Unit values|
|---|---|---|---|
|Nationally<br>representative|(+)<br>(but a potentially large<br>number of missing values)|(−)<br>(often only urban,<br>purposive sampling)|(+)<br>(but potentially biased toward<br>purchasing households)|
|Representative<br>for survey<br>strata|(+)<br>(but a potentially large<br>number of missing values)|(−)<br>(data collection delinked<br>from household survey)|(+)|
|Sample<br>size/number<br>of<br>observations|(−)<br>(only few price<br>observations per item and<br>cluster, missing values)|(−)<br>(limited number of price<br>observations per item)|(+)<br>(large number of price<br>observations, especially for<br>diary surveys)|
|Food and non-<br>food coverage|(+)<br>(often only few non-food<br>items)|(+)|(−)|
|Precisely<br>defined items|(+)<br>(if enumerators are well<br>instructed)|(+)<br>(typically well-trained<br>enumerators, every month)|(−)<br>(generally not, especially<br>recall surveys with aggregated<br>item list)|
|Direct<br>measurement|(+)|(+)|(−)<br>(computed as value divided by<br>quantity)|
|Collection<br>process|(−)<br>(especially with nonresident<br>enumerators)|(−)<br>(nonresident enumerators)|(+)<br>(based on actual transactions)|

_Source:_ Gaddis (2016, 10) Although not many Sub-Saharan African countries have conducted market price surveys (see the list of countries in Table A1 in Appendix A), those price data are potentially a good source for spatial price adjustment. The market price surveys are often conducted in a sample of communities or market centers close to the enumeration areas (EAs) in parallel with official nationally representative budget surveys. Typically, only one price is recorded for each item in each community. A major disadvantage of market price surveys is the lack of detailed quality information. Without detailed information about item descriptions, it is not possible to compare prices of the same products across regions. Gibson, Le, and Kim (2017) explain that Vietnam’s price survey was carefully designed to record detailed information for each product.

As stated earlier, CPI price data are another potential source for spatial price adjustment. Unlike market price surveys, CPI price data exist in almost all countries (Berry et al. 2019). Since the CPI is an indicator of inflation, it does not indicate spatial differentials in costs of living.<sup>10</sup> However, it is possible to calculate the spatial price index by using the CPI price data (not CPI values per se). The problem is that many countries collect price information only in urban areas (see Table A2 in Appendix A). Nevertheless, if the geographic coverage of the data is adequate, using the same price data for spatial and temporal price adjustment can be an efficient approach in terms of the data collection costs, and it could also enhance consistency between temporal and spatial price patterns.<sup>11</sup> In addition, compared to market price surveys, a wide variety of food and non-food price information is collected in the CPI data, and the data collection is frequent (for example, monthly). A well-known issue is that the basket used for the calculation of the CPI is often skewed toward higher-income households. For

> 10 Some countries report regional CPIs. Such regional CPIs still do not indicate price differences across regions as they only indicate inflation in each region and do not utilize the data for determining spatial variations in cost of living across the regions.

> of living across the regions. 11 Inconsistency in temporal and spatial price movements is not uncommon. Let us consider a spatial price index at year 0 ( ) and year 1 ( ). By applying the regional CPIs between _t_ 0 and _t_ 1 to , one can obtain another spatial price index ( ∗ ). This index ∗ often deviates from . tt0 tt1 tt0 SSPPSS SSPPSS SSPPSS tt1 tt1 tt1 SSPPSS SSPPSS SSPPSS

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