A unique environmental augmented household-level livelihood panel dataset from Nepal
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A unique environmental augmented household-level livelihood panel dataset from Nepal. / Walelign, Solomon Zena; Smith-Hall, Carsten; Rayamajhi, Santosh; Chhetri, Bir B.K.
In: Data in Brief, Vol. 42, 108168, 2022.Research output: Contribution to journal › Journal article › Research › peer-review
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TY - JOUR
T1 - A unique environmental augmented household-level livelihood panel dataset from Nepal
AU - Walelign, Solomon Zena
AU - Smith-Hall, Carsten
AU - Rayamajhi, Santosh
AU - Chhetri, Bir B.K.
N1 - Publisher Copyright: © 2022
PY - 2022
Y1 - 2022
N2 - 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).
AB - 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).
KW - Assets
KW - Dynamics
KW - Environment
KW - Income
KW - Livelihoods
KW - Panel data
KW - Poverty
KW - South Asia
U2 - 10.1016/j.dib.2022.108168
DO - 10.1016/j.dib.2022.108168
M3 - Journal article
C2 - 35510264
AN - SCOPUS:85129457799
VL - 42
JO - Data in Brief
JF - Data in Brief
SN - 2352-3409
M1 - 108168
ER -
ID: 308108278