This note revisits the long-standingtension between qualitative and quantitative approaches topoverty analysis, with reference to social assessments andprogram evaluation. It presents a summary of recent work inSt. Lucia and Colombia, where innovative efforts were madeto integrate the guiding principles of quantitativeapproaches with the practice of qualitative approaches.While neither case should be seen as ideal or a substitutefor a more comprehensive analysis, they nonetheless presenta series of strategies for generating some meaningful anduseful results in environments where, for any number ofreasons, formal data is weak or absent. Such environments,of course, are all too common in low-income countries. Thefirst case, a social assessment of poverty, comes from St.Lucia. The task manager had funds sufficient to cover keyinformant and focus group interviews in sixteen communitiesaround the island. Given this small number, he elected notto work with a "random sample" as such but ratherto maximize coverage on as many key variables as possible(rural/urban, access to clean water, distance to main road,level of poverty, etc). Our St Lucia-based colleagueshappened to have access to a 1990 census, but it did notcontain data on the full set of variables that would haveenabled us to generate a final sample meeting all our criteria.
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