This document provides information on multidimensional poverty in India based on a 2005 national household survey. It finds that:
- 53.7% of Indians are multidimensionally poor, meaning they are deprived in at least one third of ten living standards indicators. The average proportion deprived across multiple indicators (intensity) is 52.7%.
- Rural areas (28.6% MPI poor) have higher multidimensional poverty than urban areas (18.1%). Nutrition and child mortality contribute most to poverty nationally and in rural areas, while education contributes most in urban areas.
- Poverty varies significantly across states, from over 60% in Uttar Pradesh and Bihar to under 5% in Delhi,
The Multidimensional Poverty Index (MPI) provides a comprehensive measure of poverty by considering multiple deprivations across three dimensions: education, health, and standard of living. The MPI identifies anyone as multidimensionally poor if they are deprived in at least 30% of weighted indicators. Half of the world's poor according to the MPI live in South Asia, with India home to the largest number at over 400 million. Within India, states such as Bihar, Uttar Pradesh, and Jharkhand have very high levels of multidimensional poverty.
Multidimensional Poverty For Monitoring Development ProgressUNDP Eurasia
This document discusses multidimensional poverty measurement and the Alkire Foster methodology. It provides an overview of why measuring multiple dimensions of poverty is important, describes the key aspects of the AF methodology including identification of poverty, aggregation of measures, and generation of the Multidimensional Poverty Index. It then illustrates the MPI results for over 100 countries, how the methodology can be applied at the national level, and ideas for further research using panel data to analyze dynamics of chronic and transient poverty over time.
This document discusses multidimensional approaches to measuring poverty that go beyond income alone. It notes that Mexico and Colombia have established official multidimensional measures. The document outlines dimensions and indicators that could be used to develop a multidimensional poverty index, including housing/sanitation, education, employment, and more. It also addresses challenges in measuring these dimensions and the need for better comparable data across countries in Latin America.
This document summarizes a study that assesses vulnerability to poverty among rural households in Oromiya, Ethiopia. The study uses secondary data from 2004/05 surveys to examine the extent and determinants of vulnerability. An estimate shows that 17.93% of non-poor households are highly vulnerable, with a mean vulnerability of 0.62. Logistic regression finds that larger household size and an illiterate head significantly increase the probability of vulnerability. The study concludes that poverty reduction strategies need both ex-ante measures to prevent vulnerability as well as ex-post measures to alleviate existing poverty.
This document summarizes Nuru's use of the Multidimensional Poverty Assessment Tool (MPAT) to measure poverty in Kenya. It conducted a baseline MPAT survey in 15 villages in 2011, then followed up in 2013. While 7 of the 10 components measured improved, indicating lower poverty, the results cannot necessarily be attributed to Nuru's programs due to lack of a comparison group. The MPAT provides a complementary measure to traditional monitoring and evaluation but not a replacement. Lessons included the importance of a comparison group for attribution of changes to an intervention.
This document provides information on multidimensional poverty in India based on a 2005 national household survey. It finds that:
- 53.7% of Indians are multidimensionally poor, meaning they are deprived in at least one third of ten living standards indicators. The average proportion deprived across multiple indicators (intensity) is 52.7%.
- Rural areas (28.6% MPI poor) have higher multidimensional poverty than urban areas (18.1%). Nutrition and child mortality contribute most to poverty nationally and in rural areas, while education contributes most in urban areas.
- Poverty varies significantly across states, from over 60% in Uttar Pradesh and Bihar to under 5% in Delhi,
The Multidimensional Poverty Index (MPI) provides a comprehensive measure of poverty by considering multiple deprivations across three dimensions: education, health, and standard of living. The MPI identifies anyone as multidimensionally poor if they are deprived in at least 30% of weighted indicators. Half of the world's poor according to the MPI live in South Asia, with India home to the largest number at over 400 million. Within India, states such as Bihar, Uttar Pradesh, and Jharkhand have very high levels of multidimensional poverty.
Multidimensional Poverty For Monitoring Development ProgressUNDP Eurasia
This document discusses multidimensional poverty measurement and the Alkire Foster methodology. It provides an overview of why measuring multiple dimensions of poverty is important, describes the key aspects of the AF methodology including identification of poverty, aggregation of measures, and generation of the Multidimensional Poverty Index. It then illustrates the MPI results for over 100 countries, how the methodology can be applied at the national level, and ideas for further research using panel data to analyze dynamics of chronic and transient poverty over time.
This document discusses multidimensional approaches to measuring poverty that go beyond income alone. It notes that Mexico and Colombia have established official multidimensional measures. The document outlines dimensions and indicators that could be used to develop a multidimensional poverty index, including housing/sanitation, education, employment, and more. It also addresses challenges in measuring these dimensions and the need for better comparable data across countries in Latin America.
This document summarizes a study that assesses vulnerability to poverty among rural households in Oromiya, Ethiopia. The study uses secondary data from 2004/05 surveys to examine the extent and determinants of vulnerability. An estimate shows that 17.93% of non-poor households are highly vulnerable, with a mean vulnerability of 0.62. Logistic regression finds that larger household size and an illiterate head significantly increase the probability of vulnerability. The study concludes that poverty reduction strategies need both ex-ante measures to prevent vulnerability as well as ex-post measures to alleviate existing poverty.
This document summarizes Nuru's use of the Multidimensional Poverty Assessment Tool (MPAT) to measure poverty in Kenya. It conducted a baseline MPAT survey in 15 villages in 2011, then followed up in 2013. While 7 of the 10 components measured improved, indicating lower poverty, the results cannot necessarily be attributed to Nuru's programs due to lack of a comparison group. The MPAT provides a complementary measure to traditional monitoring and evaluation but not a replacement. Lessons included the importance of a comparison group for attribution of changes to an intervention.
There are three main measures of poverty:
1. The headcount index, which measures the proportion of the population that is poor in a simple count.
2. The poverty gap index, which adds up how far individuals fall below the poverty line on average, expressing this as a percentage of the poverty line.
3. The squared poverty gap index, which is a measure of poverty that takes into account inequality among the poor by weighting poverty gaps by the gaps themselves.
Economic conditions and lived poverty in BostwanaAfrobarometer
In this presentation, the citizens of Botswana speak about their economic conditions. Round 6 Afrobarometer data show that 5 in 10 (56%) say that their living conditions are “fairly bad” to “very bad”. Check out this and also the lived poverty data here.
Presentation used in the Working Group on Ageing and Care of ESN (European Social Network) to introduce the Active Ageing Index in regional policymaking.
Policy Uses of Well-being and Sustainable Development Indicators in Latin Ame...StatsCommunications
Métricas que Marcan la Diferencia: Uso de los Indicadores de Bienestar y del Desarrollo Sostenible en América Latina y el Caribe/Metrics that Make a Difference: Policy Uses of Well-being and Sustainable Development Indicators in Latin America and the Caribbean, 23-24 October 2019, Bogotá, Colombia. More information at: www.oecd.org/statistics/lac-well-being-metrics.htm
The document provides an overview of poverty concepts, measurement, and trends in India. It discusses:
- How poverty is defined and measured using the poverty line concept, which sets an absolute threshold for income/consumption below which people are considered poor.
- Trends showing that while India's growth has reduced poverty, benefits have not been widespread and poverty remains a significant problem, with over 27% of the population below the poverty line as of 2004-05.
- Poverty varies greatly across states and social groups, with some states and Scheduled Tribes facing particularly high rates of poverty.
4a Co-Living - Tiago Miranda - Social design projectsCasa Netural
This document provides context about the healthcare system in Colombia and the Caldas region. It notes that 46% of Colombia's population lives below the poverty line, with high inequality. In Caldas, 61.6% of the population is classified as poor according to the SISBEN scale. The document then introduces Bienestar Familia, a social business project in Caldas addressing healthcare issues, and notes the team's goal to understand challenges and explore design solutions to improve the existing pilot model.
The document is a summary of the 2014 UN Human Development Report. It discusses increasing vulnerabilities globally from factors such as overlapping deprivations affecting over 2.2 billion people, lack of social protections, and precarious employment. It emphasizes building resilience through universal basic social services, social inclusion, responsive institutions, full employment, and social protection systems. Achieving inclusive, resilient, and sustainable human progress requires collective action at both the national and global levels.
This document analyzes multidimensional poverty in rural Pakistan using data from the Pakistan Rural Household Survey. Key findings include:
- 73% of rural Pakistanis are multidimensionally poor based on measures of education, health, living standards and wealth.
- Major causes of poverty are low assets, lack of education, clean water, sanitation, and health facilities.
- The largest contributors to poverty are lack of land/assets, low education levels, and use of dirty cooking fuels.
- Poverty rates vary regionally, with DG Khan, Hyderabad, Multan and Thatta having the highest percentages of poor households.
The document discusses the Human Poverty Index (HPI), which was developed by the UN to measure deprivation in developing countries. The HPI focuses on deprivation in health, education, and standard of living. It was later supplemented by the HPI-2 for developed countries, which also includes a measure of social exclusion. The document provides details on how the HPI and HPI-2 are calculated, including the formula and weighting used. Examples are given of HPI values for various SAARC and OECD countries. The choice of an alpha value of 3 in the calculation is explained.
The document discusses several indices for measuring poverty:
1) The Human Poverty Index (HPI) measures poverty in developing countries (HPI-1) and developed countries (HPI-2) based on longevity, knowledge, and standard of living.
2) The Multidimensional Poverty Index (MPI) introduced in 2010 replaces HPI and identifies multiple deprivations at the household level in health, education, and standard of living.
3) The Gender Development Index (GDI) measures gender gaps in health, knowledge, and living standards by showing female HDI as a percentage of male HDI.
The world is ageing rapidly. Globally, there are already more older people than children under the age of five. By 2030 older people will outnumber those aged 10. Despite this, current data systems are not fit for purpose in today's ageing world. Data on older women and men is often not collected. When it does exist, it is not fully analysed, reported or used, leading to older people being neglected in policies and development interventions.
HelpAge International held a unique side event at the Cartagena Data Festival on 20 April 2015 - the only one to focus on the emerging issue of ageing.
Our panel reviewed the progress and challenges of making data on older age more visible, with a view to highlighting gaps and good practice, including making national and global data more accessible.
Part 1 - Global data, demographic change and inequality
Chair: Danny Sriskandarajah, Secretary General and CEO, CIVICUS: Opening comments on importance of use of data by citizens of all ages.
Sabina Alkire, Director OPHI: Multi-dimensional poverty measurement: What lessons can be drawn to improve age- disaggregated data?
Edilberto Loaiza, UNFPA: Population dynamics and SDGs in the context of the "data revolution".
Jane Scobie, HelpAge International: Global AgeWatch Index and the invisibility of data on older people.
The Human Development Index (HDI) is a summary measure of average achievement in three key dimensions: health, education, and standard of living. It assesses health using life expectancy, education with mean years of schooling and expected years of schooling, and standard of living with GNI per capita. The HDI is the geometric mean of normalized indices for each dimension, allowing comparisons between countries' human development progress.
1. The document discusses poverty measurement in India, including definitions of poverty and key indicators used to measure poverty such as head count ratio, poverty gap index, and squared poverty index. It also discusses income and non-income indicators of poverty like the Human Development Index.
2. The Indian economy has undergone structural changes with a shift to a more market-oriented development strategy in the 1990s. This has led to a decline in the share of the primary sector (agriculture) and rising shares of the secondary (industry) and tertiary (services) sectors. Services have become the major driver of growth in India's economy.
3. Factors like the growth of IT and knowledge industries, and rising demand
Economics: Poverty, Inequality & Development Lilliene Alleje
The document discusses various methods for measuring poverty and inequality, including Lorenz curves, Gini coefficients, and the Multidimensional Poverty Index. It also examines the relationship between economic growth, inequality, and poverty reduction. Key growth typologies include traditional sector enrichment, modern sector enrichment, and modern sector enlargement. While growth may initially worsen inequality according to Kuznet's hypothesis, policies like progressive taxation, asset redistribution, and direct transfers can help address poverty and inequality.
Equity in the Basic Education Opportunities in EgyptEman Refaat
This document analyzes equity in basic education opportunities in Egypt by comparing rates of children who have never attended school or dropped out before completing basic education at the national, rural, and poorest village levels. At the national level, 2.3% of children aged 10-15 have never attended school, compared to 3.3% at the rural level and 6.8% at the poorest village level. Girls, children with disabilities, and those from poorer households are more likely to have never attended school. The document uses logistic regression to analyze factors associated with lack of school attendance and survival analysis to examine factors related to dropping out.
This report provides a global update on multidimensional poverty in 2023, finding that 1.1 billion people across 110 developing countries experience multiple deprivations in health, education, and living standards. Nearly half of poor people live in Sub-Saharan Africa and over a third live in South Asia. The poorest regions and groups tend to experience the most intense poverty, with 485 million people experiencing severe poverty. While most countries have reduced poverty over time, children are being left behind in many places and population growth outpaced poverty reduction in 15 countries. The report calls for more recent data to fully understand poverty during and after the COVID-19 pandemic.
14 Development Definitions And Measuring DevelopmentEcumene
There are several ways to measure development including economic, social, and environmental indicators. Economic indicators include GDP, GNP, and PPP but have limitations in capturing how wealth is distributed or environmental/social impacts. Social indices like the HDI and HPI provide a more holistic view by combining factors like education, health, and standard of living. Multiple component indices are useful for comparisons but don't show imbalances in their underlying indicators. An accurate overall assessment requires considering various factors from different perspectives.
When the 1938 "Somewhere in Dreamland" cartoon on child poverty during the Great Depression is still relevant today, what does it say about our progress? Read more in our blog!
This document discusses various concepts and definitions related to poverty. It defines absolute poverty as having income less than $2 per day, while relative poverty compares one's economic status to others in the society. Both concepts fail to consider non-income aspects of poverty. Other definitions discussed include income poverty, extreme poverty of less than $1 per day, and India's poverty lines. Causes and impacts of poverty are also outlined. Various poverty indices like the Human Poverty Index and Global Hunger Index are explained. Strategies to address hidden hunger and malnutrition are provided.
There are three main measures of poverty:
1. The headcount index, which measures the proportion of the population that is poor in a simple count.
2. The poverty gap index, which adds up how far individuals fall below the poverty line on average, expressing this as a percentage of the poverty line.
3. The squared poverty gap index, which is a measure of poverty that takes into account inequality among the poor by weighting poverty gaps by the gaps themselves.
Economic conditions and lived poverty in BostwanaAfrobarometer
In this presentation, the citizens of Botswana speak about their economic conditions. Round 6 Afrobarometer data show that 5 in 10 (56%) say that their living conditions are “fairly bad” to “very bad”. Check out this and also the lived poverty data here.
Presentation used in the Working Group on Ageing and Care of ESN (European Social Network) to introduce the Active Ageing Index in regional policymaking.
Policy Uses of Well-being and Sustainable Development Indicators in Latin Ame...StatsCommunications
Métricas que Marcan la Diferencia: Uso de los Indicadores de Bienestar y del Desarrollo Sostenible en América Latina y el Caribe/Metrics that Make a Difference: Policy Uses of Well-being and Sustainable Development Indicators in Latin America and the Caribbean, 23-24 October 2019, Bogotá, Colombia. More information at: www.oecd.org/statistics/lac-well-being-metrics.htm
The document provides an overview of poverty concepts, measurement, and trends in India. It discusses:
- How poverty is defined and measured using the poverty line concept, which sets an absolute threshold for income/consumption below which people are considered poor.
- Trends showing that while India's growth has reduced poverty, benefits have not been widespread and poverty remains a significant problem, with over 27% of the population below the poverty line as of 2004-05.
- Poverty varies greatly across states and social groups, with some states and Scheduled Tribes facing particularly high rates of poverty.
4a Co-Living - Tiago Miranda - Social design projectsCasa Netural
This document provides context about the healthcare system in Colombia and the Caldas region. It notes that 46% of Colombia's population lives below the poverty line, with high inequality. In Caldas, 61.6% of the population is classified as poor according to the SISBEN scale. The document then introduces Bienestar Familia, a social business project in Caldas addressing healthcare issues, and notes the team's goal to understand challenges and explore design solutions to improve the existing pilot model.
The document is a summary of the 2014 UN Human Development Report. It discusses increasing vulnerabilities globally from factors such as overlapping deprivations affecting over 2.2 billion people, lack of social protections, and precarious employment. It emphasizes building resilience through universal basic social services, social inclusion, responsive institutions, full employment, and social protection systems. Achieving inclusive, resilient, and sustainable human progress requires collective action at both the national and global levels.
This document analyzes multidimensional poverty in rural Pakistan using data from the Pakistan Rural Household Survey. Key findings include:
- 73% of rural Pakistanis are multidimensionally poor based on measures of education, health, living standards and wealth.
- Major causes of poverty are low assets, lack of education, clean water, sanitation, and health facilities.
- The largest contributors to poverty are lack of land/assets, low education levels, and use of dirty cooking fuels.
- Poverty rates vary regionally, with DG Khan, Hyderabad, Multan and Thatta having the highest percentages of poor households.
The document discusses the Human Poverty Index (HPI), which was developed by the UN to measure deprivation in developing countries. The HPI focuses on deprivation in health, education, and standard of living. It was later supplemented by the HPI-2 for developed countries, which also includes a measure of social exclusion. The document provides details on how the HPI and HPI-2 are calculated, including the formula and weighting used. Examples are given of HPI values for various SAARC and OECD countries. The choice of an alpha value of 3 in the calculation is explained.
The document discusses several indices for measuring poverty:
1) The Human Poverty Index (HPI) measures poverty in developing countries (HPI-1) and developed countries (HPI-2) based on longevity, knowledge, and standard of living.
2) The Multidimensional Poverty Index (MPI) introduced in 2010 replaces HPI and identifies multiple deprivations at the household level in health, education, and standard of living.
3) The Gender Development Index (GDI) measures gender gaps in health, knowledge, and living standards by showing female HDI as a percentage of male HDI.
The world is ageing rapidly. Globally, there are already more older people than children under the age of five. By 2030 older people will outnumber those aged 10. Despite this, current data systems are not fit for purpose in today's ageing world. Data on older women and men is often not collected. When it does exist, it is not fully analysed, reported or used, leading to older people being neglected in policies and development interventions.
HelpAge International held a unique side event at the Cartagena Data Festival on 20 April 2015 - the only one to focus on the emerging issue of ageing.
Our panel reviewed the progress and challenges of making data on older age more visible, with a view to highlighting gaps and good practice, including making national and global data more accessible.
Part 1 - Global data, demographic change and inequality
Chair: Danny Sriskandarajah, Secretary General and CEO, CIVICUS: Opening comments on importance of use of data by citizens of all ages.
Sabina Alkire, Director OPHI: Multi-dimensional poverty measurement: What lessons can be drawn to improve age- disaggregated data?
Edilberto Loaiza, UNFPA: Population dynamics and SDGs in the context of the "data revolution".
Jane Scobie, HelpAge International: Global AgeWatch Index and the invisibility of data on older people.
The Human Development Index (HDI) is a summary measure of average achievement in three key dimensions: health, education, and standard of living. It assesses health using life expectancy, education with mean years of schooling and expected years of schooling, and standard of living with GNI per capita. The HDI is the geometric mean of normalized indices for each dimension, allowing comparisons between countries' human development progress.
1. The document discusses poverty measurement in India, including definitions of poverty and key indicators used to measure poverty such as head count ratio, poverty gap index, and squared poverty index. It also discusses income and non-income indicators of poverty like the Human Development Index.
2. The Indian economy has undergone structural changes with a shift to a more market-oriented development strategy in the 1990s. This has led to a decline in the share of the primary sector (agriculture) and rising shares of the secondary (industry) and tertiary (services) sectors. Services have become the major driver of growth in India's economy.
3. Factors like the growth of IT and knowledge industries, and rising demand
Economics: Poverty, Inequality & Development Lilliene Alleje
The document discusses various methods for measuring poverty and inequality, including Lorenz curves, Gini coefficients, and the Multidimensional Poverty Index. It also examines the relationship between economic growth, inequality, and poverty reduction. Key growth typologies include traditional sector enrichment, modern sector enrichment, and modern sector enlargement. While growth may initially worsen inequality according to Kuznet's hypothesis, policies like progressive taxation, asset redistribution, and direct transfers can help address poverty and inequality.
Equity in the Basic Education Opportunities in EgyptEman Refaat
This document analyzes equity in basic education opportunities in Egypt by comparing rates of children who have never attended school or dropped out before completing basic education at the national, rural, and poorest village levels. At the national level, 2.3% of children aged 10-15 have never attended school, compared to 3.3% at the rural level and 6.8% at the poorest village level. Girls, children with disabilities, and those from poorer households are more likely to have never attended school. The document uses logistic regression to analyze factors associated with lack of school attendance and survival analysis to examine factors related to dropping out.
This report provides a global update on multidimensional poverty in 2023, finding that 1.1 billion people across 110 developing countries experience multiple deprivations in health, education, and living standards. Nearly half of poor people live in Sub-Saharan Africa and over a third live in South Asia. The poorest regions and groups tend to experience the most intense poverty, with 485 million people experiencing severe poverty. While most countries have reduced poverty over time, children are being left behind in many places and population growth outpaced poverty reduction in 15 countries. The report calls for more recent data to fully understand poverty during and after the COVID-19 pandemic.
14 Development Definitions And Measuring DevelopmentEcumene
There are several ways to measure development including economic, social, and environmental indicators. Economic indicators include GDP, GNP, and PPP but have limitations in capturing how wealth is distributed or environmental/social impacts. Social indices like the HDI and HPI provide a more holistic view by combining factors like education, health, and standard of living. Multiple component indices are useful for comparisons but don't show imbalances in their underlying indicators. An accurate overall assessment requires considering various factors from different perspectives.
When the 1938 "Somewhere in Dreamland" cartoon on child poverty during the Great Depression is still relevant today, what does it say about our progress? Read more in our blog!
This document discusses various concepts and definitions related to poverty. It defines absolute poverty as having income less than $2 per day, while relative poverty compares one's economic status to others in the society. Both concepts fail to consider non-income aspects of poverty. Other definitions discussed include income poverty, extreme poverty of less than $1 per day, and India's poverty lines. Causes and impacts of poverty are also outlined. Various poverty indices like the Human Poverty Index and Global Hunger Index are explained. Strategies to address hidden hunger and malnutrition are provided.
This document discusses various methods for measuring poverty. It begins by explaining that poverty is typically defined based on a poverty line which represents a minimum level of income needed for basic needs. The most common measure is the headcount ratio, which calculates the percentage of people below the poverty line. However, this does not account for how far below the line people are. Other measures like the poverty gap ratio and income gap ratio aim to capture the depth of poverty. The Foster-Greer-Thorbecke index incorporates both the headcount ratio and gaps. Multidimensional poverty indexes also exist to measure non-income aspects of poverty.
This document summarizes a study that evaluates pro-poor growth in India across multiple dimensions of poverty, not just income. It outlines the methodology used, including measuring multidimensional poverty based on the Alkire Foster framework and extending the growth incidence curve approach to non-income indicators. Key findings include that unidimensional poverty declined on most dimensions from 2004-05 to 2009-10, while multidimensional poverty measures like poverty gap and severity increased over this period, posing the question of whether growth was truly pro-poor across dimensions. Analysis of pro-poor growth rates for different dimensions in rural and urban India then shows mixed results depending on the indicator used.
On 1 January 2016, the world officially began implementation
of the 2030 Agenda for Sustainable Development—the
transformative plan of action based on 17 Sustainable
Development Goals—to address urgent global challenges
over the next 15 years.
This agenda is a road map for people and the planet that will
build on the success of the Millennium Development Goals
and ensure sustainable social and economic progress worldwide.
It seeks not only to eradicate extreme poverty, but also
to integrate and balance the three dimensions of sustainable
development—economic, social and environmental—in a
comprehensive global vision.
The Sustainable Development Goals Report 2016Peerasak C.
Foreword
On 1 January 2016, the world officially began implementation of the 2030 Agenda for Sustainable Development—the transformative plan of action based on 17 Sustainable Development Goals—to address urgent global challenges over the next 15 years.
This agenda is a road map for people and the planet that will build on the success of the Millennium Development Goals and ensure sustainable social and economic progress worldwide. It seeks not only to eradicate extreme poverty, but also to integrate and balance the three dimensions of sustainable development—economic, social and environmental—in a comprehensive global vision.
It is vital that we begin implementation with a sense of opportunity and purpose based on an accurate evaluation of where the world stands now.
That is the aim of this report. It presents an overview of the 17 Goals using data currently available to highlight the most significant gaps and challenges.
The latest data show that about one in eight people still lived in extreme poverty, nearly 800 million people suffered from hunger, the births of nearly a quarter of children under 5 had not been recorded, 1.1 billion people were living without electricity, and water scarcity affected more than 2 billion people.
These statistics show how important coordinated global data-generation efforts will be in supplying reliable and timely data for systematic follow-up and progress reviews.
The Goals apply to all societies. Even the wealthiest countries have yet to fully empower women or eliminate discrimination.All nations will need to build the Sustainable Development Goals into their national policies and plans if we are to achieve them.
This first report is a starting point. With collective global action, we can seize the opportunities before us and, together,fulfill the pledge of the 2030 Agenda to leave no one behind.
BAN Ki-Moon
Secretary-General, United Nations "The new agenda is a promise by leaders to all people everywhere. It is a universal, integrated and transformative vision for a better world. It is an agenda for people, to end poverty in all its forms. An agenda for the planet, our common home. An agenda for shared prosperity, peace and partnership. It conveys the urgency of climate action. It is rooted in gender equality and respect for the rights of all. Above all, it pledges to leave no one behind."
BAN Ki-Moon
Secretary-General, United Nations
The Sustainable Development Goals Report 2016Richard Hong
This document provides an overview and summary of progress towards achieving the 17 Sustainable Development Goals based on currently available data. It finds that while progress has been made in some areas, significant challenges and gaps remain. Key findings include: nearly 800 million people still suffer from hunger; over 600 million lack access to clean water; 1.1 billion lack electricity access; and girls and women around the world still face barriers to education, employment and political participation. The document concludes coordinated global data efforts are needed to effectively monitor progress, ensure accountability and achieve the 2030 goals.
The new agenda is a promise by leaders to all people everywhere. It is a universal, integrated and transformative vision for a better world. It is an agenda for people, to end poverty in all its forms. An agenda for the planet, our common home. An agenda for shared prosperity, peace and partnership. It conveys the urgency of climate action. It is rooted in gender equality and respect for the rights of all. Above all, it pledges to leave no one behind.
BAN Ki-Moon
Secretary-General, United Nations
The document provides information on the Millennium Development Goals (MDGs) and Sustainable Development Goals (SDGs). It discusses the 8 goals of the MDGs from 2000-2015 related to poverty, education, gender equality, health, and environmental sustainability. It then outlines the 17 goals of the SDGs adopted in 2015 to build on the MDGs and address social, economic, and environmental issues globally in a more comprehensive manner through 2030. Key differences between the MDGs and SDGs include their scope, focus areas, targets, indicators, financing, and emphasis on quality of life and sustainability.
This document outlines a convergence plan of action for poverty reduction in Sitio Traan Leteng, Brgy. Kematu, Municipality of T'boli from 2017-2019. It begins with an introduction and rationale for the convergence program. It then provides demographic and socioeconomic profiles of the target community based on a survey of 96 households. The main body of the document presents the convergence framework, which includes key result areas, responsibilities, and targets for dimensions of livelihood & employment, food security & nutrition, health, education, environment, and spatial integration. Indicators, current realities, vision-reality gaps, and targets are outlined for each dimension. The document concludes with an overview of the convergence implementation phases.
An Interdisciplinary Perspective on Global Health and the SDGs - Prof. Sir An...LIDC
1) The document discusses progress made towards the Millennium Development Goals and limitations, such as many countries not reporting on indicators and a fragmented approach.
2) It then summarizes the 17 Sustainable Development Goals and 169 targets agreed upon by the UN, including goals and targets related to health, the environment, and their interlinkages.
3) Challenges in implementing and measuring progress towards the SDGs are discussed, such as developing robust indicators and integrating different goals and sectors like health and the environment.
Similar to IAOS 2018 - Global Multidimensional Poverty Index in Jordan, M. Dawas (20)
Globally inclusive approaches to measurement_Shigehiro Oishi.pdfStatsCommunications
This document discusses measurement issues in comparing well-being and culture across countries. It covers 5 main issues: 1) Response styles may not fully explain differences in life satisfaction scores between countries. 2) Well-being items do not always function the same way across cultures, though lack of measurement equivalence only partly explains score differences. 3) Self-presentation and 4) judgmental/memory biases may also contribute to differences to a small-moderate degree. 5) The meaning and desirability of happiness differs across cultures, which can further impact scores. The document also advocates developing indigenous well-being measures that are meaningful within each local context.
Globally inclusive approaches to measurement_Erhabor Idemudia.pdfStatsCommunications
This document discusses considerations for developing quality of life measures from an African perspective. It notes that many existing QoL instruments were developed for Western populations and do not account for cultural differences. In Africa, concepts like happiness are more closely tied to collective well-being and social harmony rather than individualism. The document also outlines some key African beliefs, like Ubuntu, which emphasizes interconnectedness. It argues that QoL measures for Africa must assess both objective and subjective domains, and be grounded in cultural values like family, community, and spirituality rather than only Western individualistic norms. Developing culturally appropriate QoL measures is important for capturing well-being in a meaningful way.
Globally inclusive approaches to measurement_Rosemary Goodyear.pdfStatsCommunications
Stats NZ has taken several steps to incorporate Māori perspectives when measuring quality of life and well-being in New Zealand. This includes developing the Te Kupenga Māori social survey, incorporating some concepts from Te Kupenga into the General Social Survey, working with partners on using administrative data for Māori, and trialling iwi-led data collections for the Census. Te Kupenga uses frameworks like Whare Tapu Whā and focuses on cultural well-being areas like spirituality, customs, te reo Māori, and social connectedness. It provides statistics on these areas as well as demographics, paid work, health, and other topics from a Māori
A better understanding of domain satisfaction: Validity and policy use_Alessa...StatsCommunications
The document discusses Italy's inclusion of domain satisfaction indicators in its framework for measuring well-being (BES). It provides background on Italy's system of social surveys and outlines the development of the BES project, which aims to measure equitable and sustainable well-being. The BES framework includes 12 domains of well-being and over 150 indicators, including subjective well-being indicators and indicators measuring satisfaction within other domains like health, work, relationships, safety, environment and more. The document presents examples of domain satisfaction indicators and trends over time in areas like friends relations and landscape satisfaction.
A better understanding of domain satisfaction: Validity and policy use_Anthon...StatsCommunications
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Session in https://budapestdata.hu/2024/04/kaxil-naik-astronomer-io/ | https://dataml24.sessionize.com/session/667627
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This is the webinar recording from the June 2024 HubSpot User Group (HUG) for B2B Technology USA.
Watch the video recording at https://youtu.be/5vjwGfPN9lw
Sign up for future HUG events at https://events.hubspot.com/b2b-technology-usa/
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A long time ago, we suffered at Spotify from fear of changing pipelines due to not knowing what the impact might be downstream. We made plans for a technical solution to test pipelines end-to-end to mitigate that fear, but the effort failed for cultural reasons. We eventually solved this challenge, but in a different context. In this presentation we will describe how we test full pipelines effectively by manipulating workflow orchestration, which enables us to make changes in pipelines without fear of breaking downstream.
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IAOS 2018 - Global Multidimensional Poverty Index in Jordan, M. Dawas
1. Paris, September 19 – 21, 2018
Global Multidimensional
Poverty Index in Jordan
Maha Dawas
Department of Statistic
Head of Poverty Statistic Division
Jordan
2. Introduction
The Oxford Poverty and Human Development Initiative
(OPHI) of Oxford University and the Human Development
Report Office of the United Nations Development Programme
(UNDP) launched in July 2010 a new poverty measure that
gives a “multidimensional” picture of people living in poverty
which its creators say could help target development resources
more effectively.
3. What is the global MPI?
The global Multidimensional Poverty Index (MPI) is an
international measure of acute poverty covering over 100
developing countries. It complements traditional income-
based poverty measures by capturing the severe
deprivations that each person faces at the same time with
respect to education, health and living standards.
4. What does the global MPI measure
The MPI uses 10 indicators to measure three critical dimensions of
poverty at the household level: education, health and living standard in 104
developing countries.
The MPI also reflects the intensity of poverty – the sum of weighted
deprivations that each household faces at the same time. A person who is
deprived in 70% of the indicators is clearly worse off than someone who is
deprived in 40% of the indicators.
6. Dimension Indicator Deprived if….. Weight
Education
Years of Schools
No household member aged 10 years or older has completed five
years of schooling. 1/6
Child School
Attendance
Any school - age child is not attending school up to the age at
which he/she would complete class 8. 1/6
Health
Child Mortality
Any child has died in the family in the five-year period preceding
the survey. 1/6
Nutrition
Any adult under 70 years of age or any child for whom there is
nutritional information is undernourished in terms of weight for
age.
1/6
Living
Standard
Electricity The household has no electricity. 1/18
Improved Sanitation
The household’s sanitation facility is not improved is improved but
shared with other households. 1/18
Improved Drinking
Water
The household does not have access to improved drinking water
(according to MDG guidelines) or safe drinking water is at least a
30-minute walk from home, round trip. 1/18
Flooring
The household has a dirt, sand, dung, or ‘other’ (unspecified)
type of floor. 1/18
Cooking Fuel The household cooks with dung, wood, or charcoal. 1/18
Assets Ownership
The household does not own more than one of these assets: radio,
TV, telephone, bicycle, motorbike, or refrigerator, and does not
own a car or truck.
1/18
7. How to Apply the Alkire Foster Method
11 Steps to a Multidimensional Poverty Measure:
Step 1: Choose Unit of Analysis. The unit of analysis
is most commonly an individual or household but
could also be a community, school, clinic, firm,
district, or other unit.
Step 2: Choose Dimensions.
Step3: Choose Indicators. Indicators are chosen for
each dimension on the principles of accuracy (using as
many indicators as necessary so that analysis can
properly guide policy).
8. Step 4: Set Poverty Lines. A poverty cutoff is set for each
dimension. This step establishes the first cutoff in the
methodology. Every person can then be identified as
deprived or non deprived with respect to each dimension.
Step 5: Count the Number of Deprivations for Each
Person.
Step 6: Set the Second Cutoff. Assuming equal weights for
simplicity, set a second identification cutoff, k, which gives
the number of dimensions in which a person must be
deprived in order to be considered multidimensionally
poor.
Count./
9. Step 7: Apply Cutoff k to Obtain the Set of Poor
Persons and Censor All Non poor Data. The focus is
now on the profile of the poor and the dimensions in
which they are deprived. All information on the non
poor is replaced with zeros (0).
Step 8: Calculate the Headcount, H. Divide the
number of poor people by the total number of people.
Step 9: Calculate the Average Poverty Gap, A. A is
the average number of deprivations a poor person
suffers.
Count./
10. Step 10: Calculate the Adjusted Headcount, M0.
Multidimensional poverty is measured by the adjusted
headcount, M0, which is calculated as H times A. Headcount
poverty is multiplied by the „average‟ number of dimensions in
which all poor people are deprived to reflect the breadth of
deprivations.
Step 11: Decompose by Group and Break Down by Dimension.
The adjusted headcount M0 can be decomposed by population
subgroup (such as region, rural/ urban, or ethnicity). After
constructing M0 for each subgroup of the sample, we can break
M0 apart to study the contribution of each dimension to overall
poverty.
Count./
11. Source of Data
The data used for MPI modeling are
from the DHS Survey for Jordan,
collected in 2009 and 2012.
13. 8/27/201813
Multidimensional
Poverty Index
(MPI=H*A)
Percentage of Poor People (H)
)K = 33.3%(
Average Intensity Across the
Poor(A)
0.006 1.7% 35.0%
Table show that Jordan‟s multidimensional poverty rate for 2012 is
1.7 per cent of the population. The average intensity of deprivation,
which reflects the share of deprivations each poor person
experiences on average, is 35 per cent. Since MPI is the product of
the percentage of poor people (H) and the average intensity of
poverty (A), it yields an index of 0.006, which shows that poor
people in Jordan experience 6/10th of the deprivations that would be
experienced if all people were deprived in all indicators.
14. 8/27/201814
Region MPI = (H*A)
H (Incidence )
K = 33.3%
A (Intensity)
Central 0.005 1.6% 34.9%
North 0.006 1.8% 35.5%
South 0.008 2.2% 34.2%
15. Urban/Rural MPI = (H*A)
H (Incidence )
K = 33.3% A (Intensity)
Urban 0.006 1.7% 34.7%
Rural 0.007 1.8% 36.2%
16. Time period
Region
MPIT HT (Incidence ) AT (Intensity)
2007
National
0.013 3.6 35.5
2009 0.011 3.1 34.6
2007
Urban
0.012 3.4 35.0
2009 0.010 2.8 34.5
2007
Rural
0.017 4.5 37.1
2009 0.015 4.3 34.9