which underlie this paper’s estimates of unit costs of implementing surveys is expanded. Moreover, costs will vary depending on the level of detail of a given survey.<sup>21</sup> In order to improve our understanding about the price of household survey data, it is important to systematically collect both ex-ante cost estimates during the survey design phase as well as ex-post actual costs for survey implementation and technical assistance.

Related to this, it is important to undertake further analyses to understand why the survey implementation cost in Africa is so high. Our current database suggests that household survey implementation in Africa costs at least USD 300 per household, which is easily five times more than the comparable figure in other regions, such as Europe and Central Asia (ECA) and Latin America and Caribbean (LAC), with more developed countries. One reason may be that the selected surveys in Africa are more complex than those implemented in ECA and LAC. If this is the case, an important question is what level of complexity we should aim to maintain. Increasing the complexity of a survey may raise survey implementation costs and exert potentially adverse effects on data quality if increased complexity is not met with commensurate resources for technical assistance. Another reason may be that hiring of qualified and well-educated enumerators in Africa may be costlier than in other regions.<sup>22</sup> While the average enumerator compensation in Africa may be lower, finding well-educated and highly qualified enumerators might be more difficult. The scarcity of qualified enumerators might in turn increase labor costs and thus survey implementation costs in Africa. If this is the case, improving training quality for enumerators and simplifying data collection via new technologies will be critical for reducing survey costs and increasing country’s ability to self-finance survey implementation.

Support to data production alone will not be sufficient to alleviate weaknesses in survey methods underlying sustainable development data. The World Bank Household Survey Strategy notes that if poor quality and limited comparability of the available survey data are considered, the crosscountry outlook of data deprivation would worsen. There are stark cross-country differences in the methods for measuring household consumption expenditures, income, and a multitude of

> 21 The cost estimates include neither the resources that are required to strengthen the internal expertise at the World Bank nor the resources required from the countries and the international development partners at large for financing the expertise and ancillary data for statistical and economic analyses that need to be conducted with the data. Also beyond the scope of this study is a discussion of funding mechanisms, which must include an over-time increasing share of survey implementation costs covered by the countries, complemented by IDA funds, IBRD loans, trust funds and other bilateral financing arrangements between the countries and the broader donor community. The required funding could come from considering a soft commitment of 1% of each IDA replenishment towards data production, as suggested by the World Bank Household Survey Strategy. The regional IDA loan to support the harmonization of household surveys in West African Economic Monetary Union countries is a good example of securing funding on a multi-annual basis to support the production of household surveys in a number of countries in a harmonized and costeffective fashion.

> 22 In private communication, Geoffrey Greenwell of Paris21 indicated that in the study undertaken by UNSDSN (2015), the transportation and personnel costs were highest in Africa, and were, respectively, 3 times and 2.4 times above the average.

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