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Refinements to the FAO methodology for estimating the prevalence of undernourishment indicator

Year of publication 2014

Place of publication Rome, Italy ;

Pages 35 p.

Author Wanner, N., Cafiero, C., Troubat, N., Conforti, P.

Publisher FAO ;

Product type Book (series)

Series title FAO Statistics Working Paper Series

Series number No. 14-05

Edition 1

Synopsis (short abstract) The FAO prevalence of undernourishment (PoU) indicator monitors progress towards Millennium Development Goal target 1C of halving, between 1990 and 2015, the proportion of people suffering from hunger. Estimates of the number of undernourished (NoU) - calculated by multiplying the PoU by the size of the reference population - are used to monitor progress towards the World Food Summit goal of reducing by half the number of people suffering from undernourishment. The PoU indicator is defined a s the probability that a randomly selected individual from the reference population is found to consume less than his/her calorie requirement for an active and healthy life. This paper reports on refinements to the methodology for estimating the Prevalence of Undernourishment that were adopted during the preparation of the State of Food Insecurity in the World Report 2014. The paper reviews the method adopted for selecting the functional form of the probability density function for the calculati on of the PoU, which uses a data-driven criterion. It proposes revised methods for estimating the variability (CV) and asymmetry (SK) parameters from available household survey, based on a leave-out-one cross validation approach. This approach is shown to be more conservative and stable across different country datasets than alternative methods. Following, the paper describes a regression approach for controlling for excess variability due to differences between food acquisition and consumptio n in surveys, which allows for a seasonality adjustment. Finally, the paper introduces an updated regression for computing variability measures in the absence of reliable household surveys, which incorporates the effect of food prices along with those of per capita income levels and inequality.

Language English

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