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Disaggregate level estimates and spatial mapping of food insecurity in Bangladesh by linking survey and census data

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  • Md Jamal Hossain
  • Sumonkanti Das
  • Hukum Chandra
  • Mohammad Amirul Islam

Abstract

Food insecurity is an important and persistent social issue in Bangladesh. Existing data based on socio-economic surveys produce divisional and nationally representative food insecurity estimates but these surveys cannot be used directly to generate reliable district level estimates. We deliberate small area estimation (SAE) approach for estimating the food insecurity status at district level in Bangladesh by combining Household Income and Expenditure Survey 2010 with the Bangladesh Population and Housing Census 2011. The food insecurity prevalence, gap and severity status have been determined based on per capita calorie intake with a threshold of 2122 kcal per day, as specified by the Bangladesh Bureau of Statistics.The results show that the food insecurity estimates generated from SAE are precise and representative of the spatial heterogeneity in the socioeconomic conditions than do the direct estimates. The maps showing the food insecurity indicators by district indicate that a number of districts in northern and southern parts are more vulnerable in terms of all indicators. These maps will guide the government, international organizations, policymakers and development partners for efficient resource allocation.

Suggested Citation

  • Md Jamal Hossain & Sumonkanti Das & Hukum Chandra & Mohammad Amirul Islam, 2020. "Disaggregate level estimates and spatial mapping of food insecurity in Bangladesh by linking survey and census data," PLOS ONE, Public Library of Science, vol. 15(4), pages 1-16, April.
    • Handle: RePEc:plo:pone00:0230906
    DOI: 10.1371/journal.pone.0230906
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    1. Foster, James & Greer, Joel & Thorbecke, Erik, 1984. "A Class of Decomposable Poverty Measures," Econometrica, Econometric Society, vol. 52(3), pages 761-766, May.
    2. Nikos Tzavidis & Nicola Salvati & Monica Pratesi & Ray Chambers, 2008. "M-quantile models with application to poverty mapping," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 17(3), pages 393-411, July.
    3. Hukum Chandra & Nicola Salvati & U. C. Sud, 2011. "Disaggregate-level estimates of indebtedness in the state of Uttar Pradesh in India: an application of small-area estimation technique," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(11), pages 2413-2432, January.
    4. Sumonkanti Das & Ray Chambers, 2017. "Robust mean‐squared error estimation for poverty estimates based on the method of Elbers, Lanjouw and Lanjouw," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 180(4), pages 1137-1161, October.
    5. Hukum Chandra, 2013. "Exploring spatial dependence in area-level random effect model for disaggregate-level crop yield estimation," Journal of Applied Statistics, Taylor & Francis Journals, vol. 40(4), pages 823-842.
    6. Chris Elbers & Jean O. Lanjouw & Peter Lanjouw, 2003. "Micro--Level Estimation of Poverty and Inequality," Econometrica, Econometric Society, vol. 71(1), pages 355-364, January.
    7. Sumonkanti Das & Stephen Haslett, 2019. "A Comparison of Methods for Poverty Estimation in Developing Countries," International Statistical Review, International Statistical Institute, vol. 87(2), pages 368-392, August.
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    1. Mst. Maxim Parvin Mitu & Khaleda Islam & Sneha Sarwar & Masum Ali & Md. Ruhul Amin, 2022. "Spatial Differences in Diet Quality and Economic Vulnerability to Food Insecurity in Bangladesh: Results from the 2016 Household Income and Expenditure Survey," Sustainability, MDPI, vol. 14(9), pages 1-16, May.
    2. Saurav Guha & Hukum Chandra, 2021. "Measuring disaggregate level food insecurity via multivariate small area modelling: evidence from rural districts of Uttar Pradesh, India," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 13(3), pages 597-615, June.

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