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Title: | Localised estimates and spatial mapping of poverty incidence in the state of Bihar in India—An application of small area estimation techniques |
Other Titles: | Not Available |
Authors: | Hukum Chandra Kaustav Aditya U.C. Sud |
ICAR Data Use Licennce: | http://krishi.icar.gov.in/PDF/ICAR_Data_Use_Licence.pdf |
Author's Affiliated institute: | ICAR::Indian Agricultural Statistics Research Institute |
Published/ Complete Date: | 2018-06-07 |
Project Code: | Not Available |
Keywords: | Small area estimation |
Publisher: | PLOS ONE |
Citation: | Chandra H, Aditya K, Sud UC (2018) Localised estimates and spatial mapping of poverty incidence in the state of Bihar in India—An application of small area estimation techniques. PLoS ONE 13(6): e0198502. https://doi.org/ 10.1371/journal.pone.0198502 |
Series/Report no.: | Not Available; |
Abstract/Description: | Poverty affects many people, but the ramifications and impacts affect all aspects of society. Information about the incidence of poverty is therefore an important parameter of the population for policy analysis and decision making. In order to provide specific, targeted solutions when addressing poverty disadvantage small area statistics are needed. Surveys are typically designed and planned to produce reliable estimates of population characteristics of interest mainly at higher geographic area such as national and state level. Sample sizes are usually not large enough to provide reliable estimates for disaggregated analysis. In many instances estimates are required for areas of the population for which the survey providing the data was unplanned. Then, for areas with small sample sizes, direct survey estimation of population characteristics based only on the data available from the particular area tends to be unreliable. This paper describes an application of small area estimation (SAE) approach to improve the precision of estimates of poverty incidence at district level in the State of Bihar in India by linking data from the Household Consumer Expenditure Survey 2011–12 of NSSO and the Population Census 2011. The results show that the district level estimates generated by SAE method are more precise and representative. In contrast, the direct survey estimates based on survey data alone are less stable. |
Description: | Not Available |
ISSN: | Not Available |
Type(s) of content: | Research Paper |
Sponsors: | Not Available |
Language: | English |
Name of Journal: | PLOS ONE |
NAAS Rating: | 8.74 |
Volume No.: | 13(6) |
Page Number: | 1-14 |
Name of the Division/Regional Station: | Not Available |
Source, DOI or any other URL: | https://doi.org/10.1371/journal.pone.0198502 https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0198502&type=printable |
URI: | https://doi.org/10.1371/journal.pone.0198502 http://krishi.icar.gov.in/jspui/handle/123456789/8015 |
Appears in Collections: | AEdu-IASRI-Publication |
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