Using poverty maps to improve the design of household surveys: the evidence from Tunisia.

Abstract

In this paper we aim to propose a new method for improving the design effect of household surveys based on a two-stage design in which the first stage clusters, or Primary Selection Units (PSUs), are stratified along administrative boundaries. Improvement of the design effect can result in more precise survey estimates (smaller standard errors and confidence intervals) or in the reduction of the necessary sample size, i.e. a reduction in the budget needed for a survey. The proposed method is based on the availability of a previously conducted poverty maps, i.e. spatial descriptions of the distribution of per capita consumption expenditures, that are finely disaggregated in small geographic units, such as cities, municipalities, districts or other administrative partitions of a country that are directly linked to PSUs. Such information is then used to select PSUs with systematic sampling by introducing further implicit stratification in the survey design, so as to maximise the improvement of the design effect. Since per capita consumption expenditures estimated at PSU level from the poverty mapping are affected by (small) standard errors, in the paper we also perform a simulation study in order to take into account this addition variability.