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Measuring and Mapping Disaggregate Level Disparities in Food Consumption and Nutritional Status via Multivariate Small Area Modelling

Saurav Guha () and Hukum Chandra ()
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Saurav Guha: ICAR-Indian Agricultural Statistics Research Institute
Hukum Chandra: ICAR-Indian Agricultural Statistics Research Institute

Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, 2021, vol. 154, issue 2, No 11, 623-646

Abstract: Abstract Although India has progressed significantly on several health outcomes but the state of food and nutrition security in the country still requires sustained efforts to accelerate achievement. Existing data based on socio-economic surveys conducted by National Sample Survey Office (NSSO) produce precise measures of food and nutrition security status at state and national level. However, these surveys cannot be used directly to produce reliable district or further smaller domain level estimates because of small sample sizes which lead to high level of sampling variability. Decentralized administrative planning system in India demands the availability of disaggregate (e.g. district) level statistics for target oriented effective policy planning and monitoring, as food and nutrition security is often unevenly distributed among the subsets of relatively small areas. But, due to lack of district level estimates, the mapping and analyse related to food and nutrition security measures are restricted to state and national level. As a result, disaggregate level dissimilarity and variability existing in food and nutrition security are often masked. This article delineates multivariate small area estimation (SAE) technique to obtain reliable and representative estimates of food consumption and nutrition status at district level for the rural areas of state of Uttar Pradesh in India by combining latest round of available Household Consumer Expenditure Survey 2011–2012 data of NSSO and the Indian Population Census 2011. The empirical evidence indicate that the estimates generated by SAE approach are reliable and representative. Spatial maps showing district level inequality in distribution of food and nutrition security in Uttar Pradesh is also produced. The disaggregate level estimates and spatial maps of food and nutrition security are directly relevant to sustainable development goal indicator 2.1.2—severity of food insecurity. The estimates and maps of food insecurity indictors are anticipated to offer irreplaceable information to administrative decision-makers and policy experts for identifying the regions requiring more attention. Government of India has recently launched number of schemes for the benefit of rural population in the country and these estimates will be useful for fund allocation as well as in the monitoring of these schemes.

Keywords: Household consumer expenditure survey; NSSO; Census; Multivariate small-area estimation; Joint modelling (search for similar items in EconPapers)
Date: 2021
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DOI: 10.1007/s11205-020-02573-8

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