scholarly journals Measuring Rural Poverty and Inequality Among Rural Households in Gedeo Zone, SNNP Region, Ethiopia

2020 ◽  
Keyword(s):  
Rural Households ◽  
Rural Poverty ◽  
Poverty And Inequality

Forest Income and Rural Livelihoods in West Bengal, India

2021 ◽  
pp. 232102222110243
Author(s):  
Biswajit Ray ◽  
Promita Mukherjee
Keyword(s):  
Developing Countries ◽  
Rural Areas ◽  
West Bengal ◽  
Rural Households ◽  
Rural Poverty ◽  
Rural Livelihoods ◽  
Safety Net ◽  
The Poor ◽  
Forest Income ◽  
Poverty And Inequality

To what extent forests contribute to rural livelihoods in developing countries? To find a plausible answer for this, this article explores whether inclusion of forest income to rural households’ total income accounts reduces poverty and income inequality, and also enables rural households to cope with shocks. To this end, we conducted household surveys in eight forest-dependent villages in the Indian state of West Bengal between August 2016 and August 2017. Using data from 407 sample households, we measured forest income of a household as the aggregate monetary value of resources extracted solely from forest ecosystem and compared this with other economic activities of the households. We calculated poverty indices and Gini coefficient with and without forest income, and we employed regression and Gini decomposition techniques to assess the safety net role and relative contribution of forest income to reducing rural poverty and inequality when compared to other sources of income. We found that the addition of forest income to household accounts significantly reduces measured poverty and inequality. Besides, the sample households, especially the poor, extract more from forests to cope with severe covariate shocks due to greater income certainty and thus adopt forest-dominated coping strategy in time of shocks and crises. The implication is that forest income needs to sustainably flow to the poor along with the development of better safety nets in forested rural areas in order to improve the forest-based rural livelihoods in developing countries like India. JEL Codes: Q23, Q56, Q57

Switch in Livelihood Strategies and Social Capital Have a Role to Play in Deciding Rural Poverty Dynamics: Evidence from Panel Data Analysis from Eastern India

2019 ◽  
Vol 55 (1) ◽  
pp. 76-94
Author(s):  
Sunil Khosla ◽  
Pradyot Ranjan Jena
Keyword(s):  
Social Capital ◽  
Panel Data ◽  
Panel Data Analysis ◽  
Rural Households ◽  
Rural Poverty ◽  
State Level ◽  
Multinomial Logit Model ◽  
Poverty Dynamics ◽  
Eastern India

Rural households continuously move into and out of poverty due to various factors; and in response to this phenomenon, these rural households adopt several strategies. The purpose of the present paper was to examine the role of livelihood diversification and social capital in the movement of these households into and out of poverty in Eastern rural India. The present study classified households into four poverty groups (called poverty dynamics) based on the panel data gathered from 1353 rural households between 2004–2005 and 2011–2012. The study used the Sustainable Livelihoods Approach (SLA) and the multinomial logit model (MLM) to examine the poverty outcome between 2004–2005 and 2011–2012. As per the data collected, at the state level, 25.26% of households were chronic poor and 37.04% of households ascended out of poverty, while 8.20% of households descended into poverty between 2004–2005 and 2011–2012. Further, it was found out from the SLA that there is a positive relationship between the phenomena of non-farm activities and escaping poverty. The result from the MLM shows that social capital in the form of group membership in different saving schemes and social groups helps to ascend out of poverty.

scholarly journals Cities and Rural Transformation

2019 ◽  
pp. 172-204
Author(s):  
Xinshen Diao ◽  
Peixun Fang ◽  
Eduardo Magalhaes ◽  
Stefan Pahl ◽  
Jed Silver
Keyword(s):  
Rural Areas ◽  
Rural Households ◽  
Rural Poverty ◽  
Economic Transformation ◽  
Small Cities ◽  
Rural Transformation ◽  
Rural Employment ◽  
Technological Adoption ◽  
Urbanized Areas ◽  
The City

The chapter focuses on answering four broad questions relevant to economic transformation in Ghana. First, are patterns of rural employment changing with urbanization and do these changes have any spatial patterns that are associated with proximity to cities of different sizes? Secondly, what are the impacts of rural transformation on the youth in the rural areas? Thirdly, what are the impacts of urbanization on agricultural intensification for youth and non-youth? Finally, what are the welfare or income implications of the rural transformation that has created heterogeneous livelihood opportunities? Proximity to cities has a strong effect on the exit of rural households from agriculture, and this trend is stronger with increases in the size of the city. Only when considering youth-headed rural households, do they become more likely to exit agriculture everywhere including in northern districts with small cities. Technological adoption is higher among youth in the more urbanized areas. Rural poverty rates appear consistently lower among non-agricultural households.

scholarly journals Poverty in Pakistan: A Region-Specific Analysis

2017 ◽  
Vol 22 (2) ◽  
pp. 139-163
Author(s):  
Muhammad Idrees
Keyword(s):  
Urban Poverty ◽  
Rural Households ◽  
Rural Poverty ◽  
Poverty Line ◽  
Household Size ◽  
Urban Households ◽  
Rural And Urban ◽  
Specific Analysis ◽  
Poverty Lines

Most of the earlier literature on poverty in Pakistan uses a single poverty line for the whole country or, at most, relies on a rural-urban divide. This segmentation fails to incorporate differences across provinces. This study estimates different poverty lines for the rural and urban segments of each province and region. Its estimated food, nonfood and overall poverty lines show that, with the exception of the capital territory of Islamabad, the urban poverty line is higher in all regions. The estimates of poverty show that, with the exception of Islamabad Capital Territory, rural poverty is much higher than urban poverty in all regions. We find that 25 percent of urban households and nearly 37 percent of rural households fall below the poverty lines we have defined. The study also finds that poverty measured in terms of households ignores household size and thus suppresses poverty figures.

Sign in / Sign up

Export Citation Format

Share Document