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• W4313266711 abstract "Purpose. Food insecurity maps reveal the spatial variability of relevant indicators in relevant units in geographically disaggregated levels. This study is based on a systematic analysis of the least studied areas related to food insecurity in Pakistan, such as district-level Small Area Estimation (SAE) analysis of food insecurity by integrating several well-established datasets, including PSLM 2014–2015 and HIES 2015–2016.&#x0D; Methodology / approach. We investigate the food insecurity situation at the district level in Pakistan by applying the household level technique of SAE method. The geographically disaggregated indicators of welfare are estimated by using SAE that integrates the census and survey datasets. This study estimates incidence and density indictors at the district level of food insecurity. The accessibility aspect of food security is taking into account by calculating monthly equivalent food expenditure per adult. In addition, the food insecurity headcount ratio is calculated to identify the food insecurity incidence at district level, and density are visualized using ‘spmap’ in STATA 14.&#x0D; Results. The results of this study indicate that the districts with low food insecurity incidence are dense in terms of food insecure people. The second least food insecure district, according to food insecurity incidence estimates, has become the most food insecure in terms of food insecurity density. However, the most food insecure district with respect to food insecurity incidence has been identified as one of the least food insecure districts in terms of food insecure people. For instance, Washuk district in Balochistan, has been identified as the most food insecure district with almost 93 % food insecurity incidence. However, Washuk has only 0.17 million food insecure people according to food insecurity density estimates.&#x0D; Originality / scientific novelty. The study highlighted the importance of food insecurity density estimates in addition to the food insecurity incidence for targeted policy interventions. In this study we have integrated a large and relatively smaller data set that covers most of the districts from all provinces of Pakistan for addressing the small sample issue which have been identified in previous studies. The variables that are common to both data sets are included after a screening process that include Variance Inflation Factor for multicollinearity, forward – backward selection criterion with model adjustment criterion either adjusted R2, Akaike Information Criterion (AIC) or Bayesian Information Criterion (BIC), least absolute shrinkage and selection operator (LASSO).&#x0D; Practical value / implications. The results of the study indicate that the policy makers should consider both the density and incidence of food insecurity for targeted policy interventions. This is because several districts with low food insecurity incidence are found to be dense with food insecure people. Moreover, the obtained results can be complemented by the results of the Integrated Food Security Phase Classification (IPC) which is based on relatively very small samples from few districts of three provinces. This can be useful in efficient implementation of food security policy and programs in targeted areas. Furthermore, the results highlight that the efforts reduce food insecurity should be targeted at district level in Pakistan." @default.
• W4313266711 created "2023-01-06" @default.
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• W4313266711 date "2022-12-20" @default.
• W4313266711 modified "2023-10-01" @default.
• W4313266711 title "Policy-oriented food insecurity estimation and mapping at district level in Pakistan" @default.
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• W4313266711 doi "https://doi.org/10.51599/are.2022.08.04.02" @default.
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