Poverty assessment as a multidimensional socio-economic concept: the case of the Rawalpindi region in Pakistan

Khan, Atta Ullah; Saboor, Abdul; Hussain, Abid; Sadiq, Shumaila; Mohsin, Abdul Qayyum

doi:10.1080/02185385.2013.844724

Cited by 22 publications

(20 citation statements)

References 14 publications

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“…While MPI identifies those who actually fail to meet the accepted conventions of minimum needs or functioning, the latter measures poverty from the angle of the income necessary for meeting certain basic needs. There is well-established literature on the poverty measure in its multidimensional aspect (Alkire and Foster 2011;Alkire and Santos 2014;Atkinson 2003;Bourguignon and Chakravarty 2003;Chakravarty et al 1998;Deutsch and Silber 2005;Khan et al 2014;Maasoumi and Xu 2015;Tsui 2002;Whelan et al 2014).…”

Section: Issues In Poverty and Inequality Measurement And Analysismentioning

confidence: 99%

“…The study further shows that multidimensinal poverty had a non-linear relationship with age of the household head and family size. Khan et al (2014) investigated the incidence of multidimensional poverty in the Rawalpindi region of Pakistan considering three dimensions: education, health, and housing. They used 10 variables to construct MPI.…”

Section: Issues In Poverty and Inequality Measurement And Analysismentioning

confidence: 99%

“…A multidimensional approach to measuring poverty thus plays a prominent role in tracking and showing all channels through which poverty may be manifested. Recently, empirical work is emerging in the study of poverty using this approach (Chakravarty et al 1998;Khan et al 2014;Maasoumi and Xu 2015;Nussbaum 2003).…”

Section: Introductionmentioning

confidence: 99%

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A Distributional Analysis of Uni-and Multidimensional Poverty and Inequalities in Ethiopia

Bersisa

Heshmati

2021

Soc Indic Res

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This study analyzes uni-and multidimensional poverty and inequalities in rural and small towns in Ethiopia. Unlike the unidimensional measure, the multidimensional measure of poverty shows all the channels through which poverty may manifest itself; it also shows the extent of deprivation. The analysis uses 6 dimensions with 14 indicators to construct a multidimensional index of poverty and inequalities using Ethiopian Households’ Socioeconomic Survey dataset. The study also uses multiple correspondence analyses for determining relative weights in computing a multidimensional index and conducts a stochastic dominance analysis of distribution of poverty for different population segments. The paper sheds light on the degree of inequalities in consumption expenditure and multidimensional deprivations. In addition, it also compares the degree of poverty using the conventional measure of poverty and the multidimensional approach. It also examines the determinants of household poverty status using both unidimensional and multidimensional measures using the logit model. The results show that the intensity, severity, and depth of poverty varies substantially across the 2 measures. The unidimensional measure of poverty shows that 36 percent of the households were poor as compared to 46 percent multidimensionally poor households. Moreover, demographic, regional, and household heads’ characteristics also affect households’ poverty status.

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Section: Issues In Poverty and Inequality Measurement And Analysismentioning

confidence: 99%

Section: Issues In Poverty and Inequality Measurement And Analysismentioning

confidence: 99%

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A Distributional Analysis of Uni-and Multidimensional Poverty and Inequalities in Ethiopia

Bersisa

Heshmati

2021

Soc Indic Res

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“…This study employed a multi stage sampling procedure. In First stage different number of Union Councils selected on the random sampling basis from sub district (on proportionate basis) and in second stage from each Union Council, DATA AND METHODOLOGY Sabir & Saboor (2006), Qureshi and Arif, (2001) Khan, et al, (2013); Khan et al, (2014); Arif and Farooq (2012); Alam and Hussain (2013); Haq et al (2015), Akhtar et al, (2007); Sikandra and Ahmad, (2008); Cheema and Naseer (2013); Awan et. al.…”

Section: Background Literature Reviewmentioning

confidence: 99%

Documentation of Rural Poverty Profile and its Correlates in Pakistan. A Sub-District Level Analysis through Consumption Approach

Alam

2018

JISR-MSSE

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Finding magnitude and Identification of factors that are strongly linked with the rural poverty is an important aspect in developing successful strategies intended for poverty. In this study we have also estimated poverty incidence, intensity and severity among the rural households in Athara Hazari (one of four sub district of Jhang, Punjab Province) along with the other demographic , social and socioeconomic factors of households that affect the poverty. The analysis of the study carried out on the basis of primary data and the same was collected through the structured and specifically designed questionnaires and document analysis. Multi-stage random sampling technique was employed to select 1000 household head as respondents from the different villages of study area. This study used poverty line Rs. 2478/which was calculated by the Planning Commission of Pakistan. According to the survey conducted in 2017, 40.3% are below the Poverty line (15% people are extremely poor). Depth and severity are 34% and 11% respectively. Majority of families were headed by farmer, illiterate and aged persons and also all three measures, headcount index, depth and severity of poverty were worse among these households. Results of the logistic regression suggest that an increase in the landholding, livestock and total assets of the household have considerably decreasing the probability of being poor in the study area.

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“…Therefore, it is necessary to establish a scientific and feasible national or regional SDG indicator system as soon as possible to enable more comprehensive monitoring and evaluation of the SDG process [11][12][13][14][15] and provide a better reference for regional, mid-and long-term, sustainable development planning. A wealth of results has been obtained regarding the construction of a poverty index assessment system [16][17][18][19][20][21]. Scholars suggest that poverty has multidimensional attributes.…”

Section: Introductionmentioning

confidence: 99%

Evaluation and Analysis of Poverty-Stricken Counties under the Framework of the UN Sustainable Development Goals: A Case Study of Hunan Province, China

Wang

Huang

et al. 2021

Remote Sensing

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Eliminating all forms of poverty in the world is the first United Nations Sustainable Development Goal (SDG). Developing a scientific and feasible method for monitoring and evaluating local poverty is important for the implementation of the SDG agenda. Based on the 2030 United Nations SDGs, in this paper, a quantitative evaluation model is built and applied to all poverty-stricken counties in Hunan Province. First, based on the SDG global index framework and local index system of China, a local SDG index system for poverty-related goals is designed, and the weights of the indexes are derived using an entropy method. The scores obtained for counties and districts with data available are then taken as the true value for the poverty assessment. Second, using National Polar-orbiting Visible Infrared Imaging Radiometer Suite (NPP-VIIRS) nighttime light images and land use and digital elevation model data, six factors, including socioeconomic, land cover, terrain and traffic factors, are extracted. Third, we then construct multiple linear evaluation models of poverty targets defined by the SDGs and machine learning evaluation models, including regression trees, support vector machines, Gaussian process regressions and ensemble trees. Last, combined with statistical data of poverty-stricken counties in Hunan Province, model validation and accuracy evaluation are carried out. The results show that the R2 and relative error of the localized, multiple linear evaluation model, including all six factors, are 0.76 and 19.12%, respectively. The poverty-stricken counties in Hunan Province were spatially aggregated and distributed mainly in the southeastern and northwestern regions. The proposed method for regional poverty assessment based on multisource geographic data provides an effective poverty monitoring reference scheme for the implementation of the poverty eradication goals in the 2030 agenda.

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Poverty assessment as a multidimensional socio-economic concept: the case of the Rawalpindi region in Pakistan

Cited by 22 publications

References 14 publications

A Distributional Analysis of Uni-and Multidimensional Poverty and Inequalities in Ethiopia

A Distributional Analysis of Uni-and Multidimensional Poverty and Inequalities in Ethiopia

Documentation of Rural Poverty Profile and its Correlates in Pakistan. A Sub-District Level Analysis through Consumption Approach

Evaluation and Analysis of Poverty-Stricken Counties under the Framework of the UN Sustainable Development Goals: A Case Study of Hunan Province, China

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