Geyer Judy, Davis Mikal, Narayan Tulika
1 Abt Associates, Cambridge, MA, USA.
2 Mathematica Policy Research, Washington, DC, USA.
Eval Rev. 2016 Dec;40(6):526-545. doi: 10.1177/0193841X16659834. Epub 2016 Aug 11.
: This article offers important statistics to evaluators planning future evaluations in southeast Africa. There are little to no published statistics describing the variance of southeast African agricultural and household indicators.
: We seek to publish the standard deviations, intracluster correlation coefficients (ICCs), and Rs from outcomes and covariates used in a 2014 quasi-experimental evaluation of the Millennium Challenge Corporation's Mozambique Farmer Income Support Project (FISP) and thus guide researchers in their calculation of design effects relevant to future evaluations in the region.
: We summarize data from a roughly 168-item farmer survey conducted in 1,227 households during June-July 2014 in coconut-farming regions of the Zambezia province in Mozambique. We report descriptive statistics, estimates of ICC, and Rs obtained from linear regression models with cluster random effects. We consider three different cluster definitions.
: We report ICCs for a range of different specifications. For the FISP evaluation, the average design effect for education outcomes is 1.16. Average design effects for wealth measures based on consumption are 1.23. For agricultural-related outcomes, 1.05 is the average design effects for income measures, 1.47 for knowledge, and 1.64 for sales of specific crops.
: We offer a detailed picture of the variance structure of agricultural and other outcomes in Mozambique. Our results indicate that the design effect associated with these outcomes is less than the rule-of-thumb design effect (2.0) used in nutrition studies which are commonly cited in the studies of this region.
