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A unique environmental augmented household-level livelihood panel dataset from Nepal
This paper presents primary household-level panel data for the investigation of rural livelihoods dynamics in Nepal. The data is environmental augmented through the inclusion of information on environmental resource use allowing estimation of household-level environmental income. The main variables...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9058569/ https://www.ncbi.nlm.nih.gov/pubmed/35510264 http://dx.doi.org/10.1016/j.dib.2022.108168 |
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author | Walelign, Solomon Zena Smith-Hall, Carsten Rayamajhi, Santosh Chhetri, Bir B.K. |
author_facet | Walelign, Solomon Zena Smith-Hall, Carsten Rayamajhi, Santosh Chhetri, Bir B.K. |
author_sort | Walelign, Solomon Zena |
collection | PubMed |
description | This paper presents primary household-level panel data for the investigation of rural livelihoods dynamics in Nepal. The data is environmental augmented through the inclusion of information on environmental resource use allowing estimation of household-level environmental income. The main variables included are: household demographics (individual's age, gender, educational status, marital status), assets (livestock, implements, land, jewellery, saving, debt), income (from the environment, crop production, livestock rearing, business ownership, wage employment, remittances, and other sources), and household shock experiences (e.g., crop failure or livestock loss). Spanning the three main physiographic regions in Nepal, data was collected in the districts of Chitwan (lowland), Kaski (mid-hills), and Mustang (mountains) in 2006 (n = 507), 2009 (n = 446), and 2012 (n = 428), with households randomly sampled, using trained and monitored enumerators. The structured household survey is freely available in Larsen et al. (2014) that also provides complete data collection process details. In each study year, household income data were collected quarterly (using recall periods of 1 or 3 months, depending on the product), while asset data was collected twice (at the beginning and end of each year). Farm-gate prices were used to value products whenever possible; subsistence products were valued using substitute product prices or the opportunity cost of time (i.e., local wage labour rate). Basic distributional statistics indicated that estimated values have acceptable properties allowing their use as prices. The dataset can be reused for analyses across a range of topics (e.g. focused on forests or livestock), data types (e.g. income or asset), and temporal scales (static or selected years). |
format | Online Article Text |
id | pubmed-9058569 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-90585692022-05-03 A unique environmental augmented household-level livelihood panel dataset from Nepal Walelign, Solomon Zena Smith-Hall, Carsten Rayamajhi, Santosh Chhetri, Bir B.K. Data Brief Data Article This paper presents primary household-level panel data for the investigation of rural livelihoods dynamics in Nepal. The data is environmental augmented through the inclusion of information on environmental resource use allowing estimation of household-level environmental income. The main variables included are: household demographics (individual's age, gender, educational status, marital status), assets (livestock, implements, land, jewellery, saving, debt), income (from the environment, crop production, livestock rearing, business ownership, wage employment, remittances, and other sources), and household shock experiences (e.g., crop failure or livestock loss). Spanning the three main physiographic regions in Nepal, data was collected in the districts of Chitwan (lowland), Kaski (mid-hills), and Mustang (mountains) in 2006 (n = 507), 2009 (n = 446), and 2012 (n = 428), with households randomly sampled, using trained and monitored enumerators. The structured household survey is freely available in Larsen et al. (2014) that also provides complete data collection process details. In each study year, household income data were collected quarterly (using recall periods of 1 or 3 months, depending on the product), while asset data was collected twice (at the beginning and end of each year). Farm-gate prices were used to value products whenever possible; subsistence products were valued using substitute product prices or the opportunity cost of time (i.e., local wage labour rate). Basic distributional statistics indicated that estimated values have acceptable properties allowing their use as prices. The dataset can be reused for analyses across a range of topics (e.g. focused on forests or livestock), data types (e.g. income or asset), and temporal scales (static or selected years). Elsevier 2022-04-14 /pmc/articles/PMC9058569/ /pubmed/35510264 http://dx.doi.org/10.1016/j.dib.2022.108168 Text en © 2022 The Author(s). Published by Elsevier Inc. https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Data Article Walelign, Solomon Zena Smith-Hall, Carsten Rayamajhi, Santosh Chhetri, Bir B.K. A unique environmental augmented household-level livelihood panel dataset from Nepal |
title | A unique environmental augmented household-level livelihood panel dataset from Nepal |
title_full | A unique environmental augmented household-level livelihood panel dataset from Nepal |
title_fullStr | A unique environmental augmented household-level livelihood panel dataset from Nepal |
title_full_unstemmed | A unique environmental augmented household-level livelihood panel dataset from Nepal |
title_short | A unique environmental augmented household-level livelihood panel dataset from Nepal |
title_sort | unique environmental augmented household-level livelihood panel dataset from nepal |
topic | Data Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9058569/ https://www.ncbi.nlm.nih.gov/pubmed/35510264 http://dx.doi.org/10.1016/j.dib.2022.108168 |
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