Small area estimation of food insecurity prevalence for the state of uttar pradesh in India

Author:

Chandra Hukum,Verma Bhanu

Abstract

The 2nd Sustainable Development Goal (SDG) of the United Nations attempt to eliminate the potential hunger and food insecurity issues by 2030, but in the plight of COVID19 pandemic it has become far more critical and persistent issue globally as well as in India. The nation-wide socio-economic surveys of National Sample Survey Office (NSSO) in India are designed to produce reliable and representative estimates of important food insecurity parameters at state and national level for both rural and urban sectors separately but these surveys cannot be used directly to generate reliable district level estimates. Whereas, efficient and representative disaggregated level estimates for the extent (or incidence) of food insecurity prevalence has direct impact on strategizing effective policy plans and monitoring progress towards eliminating food insecurity. In this backdrop, the paper outlines small area estimation approach to estimate the incidence of food insecurity across the districts of rural Uttar Pradesh in India by linking data from the 2011–12 Household Consumer Expenditure Survey of NSSO, and the 2011 Indian Population Census. A spatial map has been generated showing spatial disparity for the incidence of food insecurity in Uttar Pradesh. These disaggregated level estimates are relevant and purposeful for SDG indicator 2.1.2 – severity of food insecurity. The estimates and map of food insecurity incidences are expected to deliver invaluable information to the policy-analysts and decision-makers.

Publisher

IOS Press

Subject

Applied Mathematics,Modeling and Simulation,Statistics and Probability

Reference14 articles.

1. Exploring spatial dependence in area level random effect model for disaggregate level crop yield estimation;Chandra;Journal of Applied Statistics,2013

2. Small area estimation of survey weighted counts under aggregated level spatial model;Chandra;Survey Methodology,2019

3. Small area estimation of proportions in business surveys;Chandra;Journal of Statistical Computation and Simulation,2012

4. Small area estimation under a spatially non-linear model;Chandra;Computational Statistics and Data Analysis,2018

5. Small area prediction of counts under a non-stationary spatial model;Chandra;Spatial Statistics,2017

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