scholarly journals Regional Differentials in Multidimensional Poverty in Nepal: Rethinking Dimensions and Method of Computation

SAGE Open ◽  
2019 ◽  
Vol 9 (1) ◽  
pp. 215824401983745 ◽  
Author(s):  
Srinivas Goli ◽  
Nagendra Kumar Maurya ◽  
Moradhvaj ◽  
Prem Bhandari
Keyword(s):  
Poverty Reduction ◽  
Multidimensional Poverty ◽  
Standard Of Living ◽  
Income Poverty ◽  
Poverty Index ◽  
Multidimensional Poverty Index ◽  
Economic Progress ◽  
Education And Health ◽  
Development Policies ◽  
Nationally Representative

This article examines the extent of regional inequality in multidimensional poverty in Nepal using the nationally representative Nepal Demographic Health Survey (2011) data. The authors present a more robust method of multidimensional poverty index (MPI), particularly in terms of the procedure of estimation and aggregation of the indicators as compared with previous studies. The findings suggest that despite the relatively better economic progress and a considerable reduction in education and health poverty, there is a wide inequality across the regions. Far less has been achieved in the case of reducing the standard of living poverty, that is, wealth poverty and inequalities across the regions. The article finds that global MPI tends to inflate poverty estimates in the case of Nepal. It also suggests that development policies and poverty reduction programs in Nepal must aim to reduce multidimensional poverty, of which deprivation in education, health and basic amenities must be an integral component, along with their efforts to improve economic growth and reduce income poverty.

scholarly journals Measuring multidimensional poverty in the state of Minas Gerais, Brazil: looking beyond income

2018 ◽  
Vol 52 (3) ◽  
pp. 386-416
Author(s):  
Murilo Fahel ◽  
Leticia Ribeiro Teles
Keyword(s):  
Health Education ◽  
Human Development ◽  
Multidimensional Poverty ◽  
Minas Gerais ◽  
The State ◽  
Standard Of Living ◽  
Sample Survey ◽  
Amartya Sen ◽  
Poverty Index ◽  
Multidimensional Poverty Index

Abstract The multidimensional poverty index (MPI) was developed by the Oxford Poverty & Human Development Initiative (Ophi) in 2010. The MPI is established on indicators of health, education and standard of living. The concept of multidimensionality is anchored on the theory of poverty and human development elaborated by the indian economist Amartya Sen in the 1980s. The methodology used for the modeling of this study is based on Alkire and Foster - AF (2011) and analyzes the incidence and intensity of poverty. The purpose of this paper focuses on the application of the MPI in the state of Minas Gerais, Brazil and uses the Household Sample Survey produced by João Pinheiro Foundation (FJP) in 2009, 2011 and 2013. The results indicate that the MPI is relativaly low, 0.0329 (2009), 0.0226 (2011) and 0.0155 (2013), indicating there is a tendency for decreasing along the years.

scholarly journals Multidimensional Relative Poverty of Farmers in Tibetan Areas – Based on a Data Analysis on Micro Surveys

2021 ◽  
Vol 4 (6) ◽  
pp. 84-90
Author(s):  
Shilian Zhu
Keyword(s):  
Poverty Reduction ◽  
Multidimensional Poverty ◽  
Poverty Index ◽  
Absolute Poverty ◽  
Relative Poverty ◽  
One Dimensional ◽  
Multidimensional Poverty Index ◽  
Head Of Household ◽  
Multidimensional Deprivation ◽  
Per Capita

In 2020, the issue of absolute poverty has been solved, and China is building a well-off society in an all-round way. The issue of relative poverty is an important content of poverty reduction. Based on a survey data from Danba County in October 2020, this paper uses the AF method to calculate the incidence of multidimensional poverty and the multidimensional poverty index. The results showed that 44.65% of the farmers have multidimensional deprivation of any three indicators of relative poverty, and 2.79% of the farmers have serious multidimensional deprivation; the incidence of one-dimensional poverty in terms of “educational level index of head of household,” “per capita non-transfer income of households in 2019,” and “per capita household income in 2019” is the highest; at the same time, the contribution rate of the three indicators to the multidimensional poverty index is also higher than other indicators. Therefore, several suggestions have been put forward to alleviate the multidimensional relative poverty in the region from the aspects of industry development and education.

A Critical Examination of Inter-temporal Spatial Poverty Trends in Bangladesh

2018 ◽  
Vol 19 (1) ◽  
pp. 108-123 ◽  
Author(s):  
Shadlee Rahman
Keyword(s):  
Poverty Reduction ◽  
Temporal Trends ◽  
Multidimensional Poverty ◽  
Critical Examination ◽  
Income Poverty ◽  
Multidimensional Poverty Index ◽  
National Division ◽  
Spatial Dimensions ◽  
Poverty Levels ◽  
East West

This article examines the nature of spatial dimensions of poverty in Bangladesh by undertaking an in-depth investigation of inter-temporal divergence and convergence in poverty levels. Based on the estimations of Alkire–Foster Multidimensional Poverty Index (A–F MPI) for selected years, the article compares trends in broader dimensions of spatial poverty in Bangladesh with income poverty trends available for corresponding periods. The article scrutinizes the validity of the so-called ‘East–West divide’ in view of poverty levels in Bangladesh. The results evince a number of interesting insights. First, trends of income poverty in Bangladesh are not aligned with those of multidimensional poverty. Second, the levels of inter-temporal poverty as per MPI are relatively higher for the rural–urban divide and also at sub-national (division) levels. Third, inter-temporal trends of divergence–convergence in terms of income poverty relating to the East–West divide do not match corresponding movements in MPI. It is argued that while income poverty dimensions remain important, policymakers should pay more attention to broader issues of deprivations to address challenges of poverty in Bangladesh. Therefore, addressing causes of deprivations as captured in MPIs will help achieve balanced spatial development, accelerated poverty reduction and lower income inequality in Bangladesh. JEL: R11, R12, I32, C22

scholarly journals Provincial Poverty in Nepal

Patan Pragya ◽  
2020 ◽  
Vol 7 (1) ◽  
pp. 66-77
Author(s):  
Gokarna Prasad Gyanwali
Keyword(s):  
Poverty Reduction ◽  
Multidimensional Poverty ◽  
Poverty Index ◽  
Daily Lives ◽  
Middle Income ◽  
Specific Data ◽  
Multidimensional Poverty Index ◽  
The People ◽  
Reduction Strategies ◽  
Economic Imperative

Poverty is not only the severe economic condition of people but it is also the cultural, ethical, social, political, psychological and economic imperative of mankind. It is one of the distressing circumstances of people in developing countries have to contend with in their daily lives. It is common among the low and middle income class in these countries like Nepal. This research is based on the multidimensional poverty index (MPI) such as those related to education, health, material wellbeing, energy, water and sanitation, structure of house, and access to other services, varies considerably in seven provinces of Nepal. It illustrates the importance of location-specific data in the development of effective poverty reduction strategies of federal and provincial governments. The MPI shows that, the 28.6%of the people of Nepal are still multi-dimensionally poor meaning that their lives are battered by several deprivations simultaneously. This paper also discusses about the trends and measurement of poverty in Nepal as well as the provincial socio-economic conditions and distribution of poverty.

scholarly journals Estimates of multidimensional poverty for India using NSSO-71 and -75

2021 ◽  
Author(s):  
Venugopal Mothkoor ◽  
Nina Badgaiyan
Keyword(s):  
Rural Areas ◽  
Urban Areas ◽  
State Level ◽  
Multidimensional Poverty ◽  
National Sample ◽  
Standard Of Living ◽  
Sample Survey ◽  
Poverty Index ◽  
Multidimensional Poverty Index ◽  
National Sample Survey Organization

We measure multidimensional poverty in India using National Sample Survey Organization data from 2014–15 to 2017–18. We use income, health, education, and standard of living to measure the multidimensional poverty index (MPI). The MPI headcount declined from 26.9 to 13.75 per cent over the study period. The all-India estimates indicate that 144 million people were lifted from poverty during this period. We include different health dimensions, factoring in insurance, institutional coverage, antenatal care, and chronic conditions. Income is the dominant instrument with the highest contribution to the MPI, followed by insurance. Cooking, sanitation, and education also have significant weights. The decline in deprivation is steeper in rural areas than urban areas. Our state-level estimates reveal that 20 states report less than 10 per cent headcount poverty, up from six states. COVID-19 may lead to reversals of these gains, with poverty rising to pre-2014–15 levels, rising more steeply in rural areas.

scholarly journals MULTIDIMENSIONAL POVERTY AND INEQUALITY IN ZAWLNUAM BLOCK OF MAMIT DISTRICT, MIZORAM

2021 ◽  
pp. 20-27
Author(s):  
C.Lalnunmawia ◽  
Dr. Lalhriatpuii
Keyword(s):  
Poverty Reduction ◽  
Sampling Technique ◽  
Multidimensional Poverty ◽  
Primary Data ◽  
Poverty Index ◽  
Multidimensional Poverty Index ◽  
Multi Stage ◽  
Poverty And Inequality ◽  
Low Degree ◽  
Reduction Strategies

Purpose: The study intends to examine the incidence and intensity of multidimensional poverty and inequality in Zawlnuam RD. Block of Mizoram, India. The core objective of the study is to compute Multidimensional Poverty Index (MPI) and compare and contrast the result across the study area. We also examined the degree of inequality in deprivations among people using variance of the deprivation scores. Methodology: This study was based on primary data which was collected through a multi-stage sampling technique. At the first stage, Zawlnuam RD. Block was selected. The second stage involved random selection of 5 villages from the RD, Block. Requisite data were then collected randomly through structured questionnaires which was designed based on the requirement for computation of Multidimensional Poverty Index. From the collected data, the incidence of poverty (headcount ratio), the intensity of poverty, and MPI were computed using Alkire-Foster Method. The study follows the ‘Global MPI Brief Methodological Note, 2017’ (Alkire & Roble, 2017 ) in the choice of dimensions, indicators, thresholds and weights assigned to each indicator. Results: From the result of the analysis, the multidimensional poverty in the study area is moderate. Decomposition of MPI by population sub-group reveals that poverty is most severe in Kolalian village followed by Thinghlun village, while Decomposition of MPI by component indicators show malnutrition as the most prevailing deprivation in the study area. The degree of inequality measured by variance of deprivation score ranges between 0.03 and 0.12 indicating low degree of inequality. Applications of this study: The findings of the study can be based for formulation of government poverty reduction policies and can be used effectively in improving the existing poverty reduction strategies in the state. KEY WORDS: Multidimensional Poverty, Inequality, Zawlnuam RD Block, Mizoram.

scholarly journals Measuring Vulnerability to Multidimensional Poverty

2019 ◽  
Vol 148 (1) ◽  
pp. 67-103 ◽  
Author(s):  
Mauricio Gallardo
Keyword(s):  
Multidimensional Poverty ◽  
Risk Behaviour ◽  
Poverty Measurement ◽  
Multidimensional Space ◽  
Poverty Index ◽  
Cross Sectional ◽  
Multidimensional Poverty Index ◽  
Wide Range ◽  
Vulnerability Indicators ◽  
Vulnerability To Poverty

Abstract A method to measure vulnerability to multidimensional poverty is proposed under a mean–risk behaviour approach. We extend the unidimensional downside mean–semideviation measurement of vulnerability to poverty towards the multidimensional space by incorporating this approach into Alkire and Foster’s multidimensional counting framework. The new approach is called the vulnerability to multidimensional poverty index (VMPI), alluding to the fact that it can be used to assess vulnerability to poverty measured by the multidimensional poverty index (MPI). The proposed family of vulnerability indicators can be estimated using cross-sectional data and can include both binary and metric welfare indicators. It is flexible enough to be applied for measuring vulnerability in a wide range of MPI designs, including the Global MPI. An empirical application of the VMPI and its related indicators is illustrated using the official MPI of Chile as the reference poverty measurement. The estimates are performed using the National Socioeconomic Characterisation Survey (CASEN) for the year 2017.

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