Environmental income improves household-level poverty assessments and dynamics

Research output: Contribution to journalJournal articlepeer-review

Standard

Environmental income improves household-level poverty assessments and dynamics. / Walelign, Solomon Zena; Charlery, Lindy Callen; Smith-Hall, Carsten; Chhetri, Bir Bahadur Khanal; Larsen, Helle Overgaard.

In: Forest Policy and Economics, Vol. 71, 2016, p. 23-35.

Research output: Contribution to journalJournal articlepeer-review

Harvard

Walelign, SZ, Charlery, LC, Smith-Hall, C, Chhetri, BBK & Larsen, HO 2016, 'Environmental income improves household-level poverty assessments and dynamics', Forest Policy and Economics, vol. 71, pp. 23-35. https://doi.org/10.1016/j.forpol.2016.07.001

APA

Walelign, S. Z., Charlery, L. C., Smith-Hall, C., Chhetri, B. B. K., & Larsen, H. O. (2016). Environmental income improves household-level poverty assessments and dynamics. Forest Policy and Economics, 71, 23-35. https://doi.org/10.1016/j.forpol.2016.07.001

Vancouver

Walelign SZ, Charlery LC, Smith-Hall C, Chhetri BBK, Larsen HO. Environmental income improves household-level poverty assessments and dynamics. Forest Policy and Economics. 2016;71:23-35. https://doi.org/10.1016/j.forpol.2016.07.001

Author

Walelign, Solomon Zena ; Charlery, Lindy Callen ; Smith-Hall, Carsten ; Chhetri, Bir Bahadur Khanal ; Larsen, Helle Overgaard. / Environmental income improves household-level poverty assessments and dynamics. In: Forest Policy and Economics. 2016 ; Vol. 71. pp. 23-35.

Bibtex

@article{699a3559812e480e9d1e486ee26d14bb,
title = "Environmental income improves household-level poverty assessments and dynamics",
abstract = "Household-level poverty assessments and analyses of poverty dynamics in developing countries typically do not include environmental income. Using household (n = 427 in 2006, 2009 and 2012) total income panel data sets, with and without environmental income, from Nepal, we analysed the importance of environmental income in household-level poverty assessments (Foster-Greer-Thorbecke indices) and dynamics (movements in the Poverty Transition Matrix). Random effects logit and ordered logit models were applied to estimate variables covarying with poverty categories and compared for annual household incomes with and without environmental income. Using the without environmental income data set significantly changed the number of households classified as poor, as well as rates of movements in and out of poverty. Excluding household-level environmental income also distorted estimation of covariates of poverty incidence and poverty dynamics. Poverty incidence and dynamics models including environmental income perform better than those without. Rural poverty studies based on welfare measures excluding environmental income may thus be inaccurate for environmental reliant communities.",
author = "Walelign, {Solomon Zena} and Charlery, {Lindy Callen} and Carsten Smith-Hall and Chhetri, {Bir Bahadur Khanal} and Larsen, {Helle Overgaard}",
year = "2016",
doi = "10.1016/j.forpol.2016.07.001",
language = "English",
volume = "71",
pages = "23--35",
journal = "Forest Policy and Economics",
issn = "1389-9341",
publisher = "Elsevier",

}

RIS

TY - JOUR

T1 - Environmental income improves household-level poverty assessments and dynamics

AU - Walelign, Solomon Zena

AU - Charlery, Lindy Callen

AU - Smith-Hall, Carsten

AU - Chhetri, Bir Bahadur Khanal

AU - Larsen, Helle Overgaard

PY - 2016

Y1 - 2016

N2 - Household-level poverty assessments and analyses of poverty dynamics in developing countries typically do not include environmental income. Using household (n = 427 in 2006, 2009 and 2012) total income panel data sets, with and without environmental income, from Nepal, we analysed the importance of environmental income in household-level poverty assessments (Foster-Greer-Thorbecke indices) and dynamics (movements in the Poverty Transition Matrix). Random effects logit and ordered logit models were applied to estimate variables covarying with poverty categories and compared for annual household incomes with and without environmental income. Using the without environmental income data set significantly changed the number of households classified as poor, as well as rates of movements in and out of poverty. Excluding household-level environmental income also distorted estimation of covariates of poverty incidence and poverty dynamics. Poverty incidence and dynamics models including environmental income perform better than those without. Rural poverty studies based on welfare measures excluding environmental income may thus be inaccurate for environmental reliant communities.

AB - Household-level poverty assessments and analyses of poverty dynamics in developing countries typically do not include environmental income. Using household (n = 427 in 2006, 2009 and 2012) total income panel data sets, with and without environmental income, from Nepal, we analysed the importance of environmental income in household-level poverty assessments (Foster-Greer-Thorbecke indices) and dynamics (movements in the Poverty Transition Matrix). Random effects logit and ordered logit models were applied to estimate variables covarying with poverty categories and compared for annual household incomes with and without environmental income. Using the without environmental income data set significantly changed the number of households classified as poor, as well as rates of movements in and out of poverty. Excluding household-level environmental income also distorted estimation of covariates of poverty incidence and poverty dynamics. Poverty incidence and dynamics models including environmental income perform better than those without. Rural poverty studies based on welfare measures excluding environmental income may thus be inaccurate for environmental reliant communities.

U2 - 10.1016/j.forpol.2016.07.001

DO - 10.1016/j.forpol.2016.07.001

M3 - Journal article

VL - 71

SP - 23

EP - 35

JO - Forest Policy and Economics

JF - Forest Policy and Economics

SN - 1389-9341

ER -

ID: 163936335