A presentation by Wenefrida Widyanti, Asep Suryahadi, Sudarno Sumarto, and Athia Yumna from the 2009 BASIS Conference on "Escaping Poverty Traps: Connecting the Chronically Poor to the Economic Growth Agenda."
The document summarizes the impacts of a 2007 flood in Bojonegoro, Indonesia. Over 800 houses were severely damaged, over 1,850 were mildly to moderately damaged, and 31 people died. The flood displaced over 229,000 people and submerged 16 of 27 sub-districts up to 3 meters deep. A study found the flood led to increased prevalence of infectious diseases and malnutrition in children. It caused on average €240 in economic losses per household, over 5 months of average expenditures. Flooded households reported significantly lower quality of life than non-flooded households.
Access to cancer medications in low and middle income countries 2013.03.27gilberto lopes
This document discusses access to cancer medications in low and middle income countries. It notes that cancer kills more people yearly than other major diseases globally, but most cases and deaths occur in developing nations which represent a small portion of global cancer costs. Access to newer targeted therapies and genomic sequencing is currently only an aspiration for these countries. Barriers to access include lower health spending and high drug costs. Potential solutions discussed include increased use of generics, price discrimination, universal healthcare coverage, and public-private partnerships to improve funding. With better patient selection, cost-effective treatments, and global collaboration, it is hoped that control of cancer can be improved worldwide.
Rationale and Procedure for Oncology Pricing and Reimbursement in England Tow...Office of Health Economics
The Biotherapy Development Association convened a two-day workshop in January 2014 to assess access to innovative cancer medicines in Europe. This presentation by OHE's Adrian Towse covers the situation in England, examining challenges that are peculiar to England as well as the English experience with issues common across countries.
Indonesia Economy Profile 2015 | Doing Business In Indonesia | World Bank GroupHenky Hendranantha
Indonesia ranks 114 out of 189 economies on the ease of doing business, according to the latest World Bank report. While its ranking has improved slightly compared to the previous year, rising 3 places, its absolute score on regulatory practices for businesses improved only modestly, increasing by 1.05 points. The report provides data on Indonesia's business environment, regulations, and rankings in key areas like starting a business, dealing with construction permits, getting electricity, and enforcing contracts. It compares Indonesia's performance to other economies in the region and income group, finding that while reforms have been made, opportunities still exist to strengthen regulations to better support local entrepreneurs.
Indonesia is the largest economy in Southeast Asia with a population of over 237 million people. It has experienced steady economic growth of around 6% annually in recent years. Major opportunities for U.S. companies exist in the energy, infrastructure, healthcare and education sectors. The U.S. Commercial Service assists American businesses looking to access the Indonesian market through services like market research, partner searches and promoting single companies.
Health financing strategies uhc 27 09 12Vikash Keshri
This document discusses health financing strategies for universal health coverage. It begins by defining universal health coverage and providing historical perspectives. It then discusses the current state of health financing in India, including low public spending, high private out-of-pocket expenditures, and variations between states. The document outlines that achieving universal health coverage requires raising sufficient funds, removing financial barriers, and using resources efficiently. It examines strategies for generating more health resources, utilizing resources effectively to prevent waste, and proposes the key recommendations of India's High Level Expert Group on universalizing access to affordable healthcare.
A presentation by Andy McKay from the 2009 BASIS Conference on "Escaping Poverty Traps: Connecting the Chronically Poor to the Economic Growth Agenda."
Scaling-up Microfinance Products for Weather Risk Management: Three Proposals...BASIS AMA Innovation Lab
A presentation on Microfinance by Michael Carter, Professor in the Department of Agricultural & Resource Economics at University of California, Davis and the Director of the Feed the Future BASIS Assets & Market Access Research Program & I4 Index Insurance Innovation Initiative.
(From the AFD-FERDI Workshop, Paris on June 24, 2014)
The document summarizes the impacts of a 2007 flood in Bojonegoro, Indonesia. Over 800 houses were severely damaged, over 1,850 were mildly to moderately damaged, and 31 people died. The flood displaced over 229,000 people and submerged 16 of 27 sub-districts up to 3 meters deep. A study found the flood led to increased prevalence of infectious diseases and malnutrition in children. It caused on average €240 in economic losses per household, over 5 months of average expenditures. Flooded households reported significantly lower quality of life than non-flooded households.
Access to cancer medications in low and middle income countries 2013.03.27gilberto lopes
This document discusses access to cancer medications in low and middle income countries. It notes that cancer kills more people yearly than other major diseases globally, but most cases and deaths occur in developing nations which represent a small portion of global cancer costs. Access to newer targeted therapies and genomic sequencing is currently only an aspiration for these countries. Barriers to access include lower health spending and high drug costs. Potential solutions discussed include increased use of generics, price discrimination, universal healthcare coverage, and public-private partnerships to improve funding. With better patient selection, cost-effective treatments, and global collaboration, it is hoped that control of cancer can be improved worldwide.
Rationale and Procedure for Oncology Pricing and Reimbursement in England Tow...Office of Health Economics
The Biotherapy Development Association convened a two-day workshop in January 2014 to assess access to innovative cancer medicines in Europe. This presentation by OHE's Adrian Towse covers the situation in England, examining challenges that are peculiar to England as well as the English experience with issues common across countries.
Indonesia Economy Profile 2015 | Doing Business In Indonesia | World Bank GroupHenky Hendranantha
Indonesia ranks 114 out of 189 economies on the ease of doing business, according to the latest World Bank report. While its ranking has improved slightly compared to the previous year, rising 3 places, its absolute score on regulatory practices for businesses improved only modestly, increasing by 1.05 points. The report provides data on Indonesia's business environment, regulations, and rankings in key areas like starting a business, dealing with construction permits, getting electricity, and enforcing contracts. It compares Indonesia's performance to other economies in the region and income group, finding that while reforms have been made, opportunities still exist to strengthen regulations to better support local entrepreneurs.
Indonesia is the largest economy in Southeast Asia with a population of over 237 million people. It has experienced steady economic growth of around 6% annually in recent years. Major opportunities for U.S. companies exist in the energy, infrastructure, healthcare and education sectors. The U.S. Commercial Service assists American businesses looking to access the Indonesian market through services like market research, partner searches and promoting single companies.
Health financing strategies uhc 27 09 12Vikash Keshri
This document discusses health financing strategies for universal health coverage. It begins by defining universal health coverage and providing historical perspectives. It then discusses the current state of health financing in India, including low public spending, high private out-of-pocket expenditures, and variations between states. The document outlines that achieving universal health coverage requires raising sufficient funds, removing financial barriers, and using resources efficiently. It examines strategies for generating more health resources, utilizing resources effectively to prevent waste, and proposes the key recommendations of India's High Level Expert Group on universalizing access to affordable healthcare.
A presentation by Andy McKay from the 2009 BASIS Conference on "Escaping Poverty Traps: Connecting the Chronically Poor to the Economic Growth Agenda."
Scaling-up Microfinance Products for Weather Risk Management: Three Proposals...BASIS AMA Innovation Lab
A presentation on Microfinance by Michael Carter, Professor in the Department of Agricultural & Resource Economics at University of California, Davis and the Director of the Feed the Future BASIS Assets & Market Access Research Program & I4 Index Insurance Innovation Initiative.
(From the AFD-FERDI Workshop, Paris on June 24, 2014)
Using an Agroenterprise: Learning Alliances for Inclusive Value Chain SupportBASIS AMA Innovation Lab
CRS implemented Agroenterprise Learning Alliances over 5 years to help shift smallholder farmers from subsistence agriculture to competitive agroenterprise. The goal was to provide a bridge from relief to development by linking farmers to markets, diversifying crops, strengthening access to finance and services, and improving food security. Key aspects included participatory value chain development, multi-skill training for farmer groups, savings mobilization, strengthening local service providers, and integrating infrastructure, training and marketing linkages. Case studies in navy beans in Ethiopia and chickpeas in Tanzania showed increases in farmers, crops, and collective marketing. Challenges remained around skills transfer, farmer organization, value chain analysis, access to finance and information for rural
A presentation by John Hoddinott from the 2009 BASIS Conference on "Escaping Poverty Traps: Connecting the Chronically Poor to the Economic Growth Agenda."
Before and After the Drought: Evidence on the Impact of Index Insurance on Sm...BASIS AMA Innovation Lab
BASIS Director Michael Carter (working collaboratively with Ghada Elabed and Sarah Janzen) presented at the OECD meeting in Paris, September 2015 on the topic of index insurance and its impact on small farm investment and social protection.
This document discusses issues related to analyzing poverty dynamics and growth. It notes that chronic poverty is best characterized by both continuous or frequent spells in poverty as well as low, flat, or negative consumption growth. The document also stresses that attrition in panel survey data could affect results if not random, and that more thorough checks for non-random attrition are needed, including considering how dropping out of the lowest or highest households could mislead analyses of chronic poverty.
Impact of Mothers' Intellectual Human Capital and Long-Run Nutritional Status...BASIS AMA Innovation Lab
A presentation by Jere Behrman, Alexis Murphy, Agnes Quisumbing, and Kathryn Yount from the 2009 BASIS Conference on "Escaping Poverty Traps: Connecting the Chronically Poor to the Economic Growth Agenda."
Presentation by BASIS PI Travis Lybbert and Abbie Turiansky, along with Jean Claude O Fignole, Alix Percinthe, Sarah Belfort, Barry Shelly from OXFAM at the OXFAM Brown Bag series, February 22, 2016
Measuring the Quality of Agricultural Index Insurance: Concepts and Safe Mini...BASIS AMA Innovation Lab
A presentation on Agricultural Index Insurance by Professor Michael Carter of the University of California, Davis, and Director of the Feed the Future BASIS Assets and Market Access Innovation Lab (http://basis.ucdavis.edu). This presentation was given at a World Bank "Brown Bag" seminar on May 21, 2015.
DFID and Social Exclusion: the Use and Otherwise of a Concept in Internationa...BASIS AMA Innovation Lab
A presentation by Arjan de Haan and Andrew Shepherd from the 2009 BASIS Conference on "Escaping Poverty Traps: Connecting the Chronically Poor to the Economic Growth Agenda."
Pharma Market OTC & Nutrition Situation MAT 2013 Q2Danny D. Kosasih
Indonesia's pharmaceutical market grew 12% in 2013Q2 to IDR 4,755 OKU YEN, driven by 15% growth in the large over-the-counter (OTC) sector. The lifestyle category, including multivitamins and tonics, accounted for 19% of OTC and nutrition sales. Vitamin products, mainly from local manufacturers, were the top subcategory and heavily advertised products promising benefits like increased stamina and immunity. The growing OTC market is expected to continue expanding due to economic growth and more retail outlets selling these products.
Assisting the Poorest in Bangladesh: Learning from BRAC's Targeting the Ultra...BASIS AMA Innovation Lab
A presentation by David Hulme from the 2009 BASIS Conference on "Escaping Poverty Traps: Connecting the Chronically Poor to the Economic Growth Agenda."
The document summarizes a study examining whether there is evidence of a "culture of dependency" among social grant recipients in South Africa. The study found that grant recipients highly valued work and the unemployed were strongly motivated to find jobs. However, high unemployment was primarily due to lack of job opportunities rather than lack of motivation to work. The study concluded there was no evidence that grants caused dependency on welfare or reduced incentives to work.
The document discusses the benefits of exercise for mental health. Regular physical activity can help reduce anxiety and depression and improve mood and cognitive function. Exercise causes chemical changes in the brain that may help protect against mental illness and improve symptoms for those who already suffer from conditions like depression and anxiety.
Indonesia represents a growing market opportunity in healthcare due to its large and growing population, expanding middle class, and underserved healthcare sector. With 235 million people and over 80 million in the growing middle class, consumer spending and confidence are rising. This creates demand for quality healthcare as the population ages and chronic diseases become more prevalent. Private healthcare expenditures also continue to increase steadily. The growing and resilient economy makes Indonesia an attractive target for healthcare investments focused on mid-market consumer products and services, corporate healthcare, and digital health applications.
- The document outlines Thailand's health system and recent reforms towards universal health coverage.
- Key aspects include establishing the National Health Security Office in 2003 to provide quality healthcare access for all Thai citizens. The Universal Coverage scheme was launched, replacing the previous 30 Baht policy.
- Community hospitals and health centers play an important role in implementing healthcare policies and providing easily accessible primary care services at the local level.
A presentation by Cheryl Morden from the 2009 BASIS Conference on "Escaping Poverty Traps: Connecting the Chronically Poor to the Economic Growth Agenda."
At the Workshop on Innovations in Index Insurance to Promote Agricultural and Livestock Development, December 3rd, 2015 in Addis Ababa Ethiopia, Chris Barret of Cornell University presented on the favorable impacts of implementing index-based livestock insurance.
Savings, Subsidies, and Technology Adoption: Field Experimental Evidence from...BASIS AMA Innovation Lab
1) The study examines the interaction between temporary input subsidies and formal savings programs on technology adoption in rural Mozambique.
2) It finds that the impact of subsidies on fertilizer use persists for two seasons in areas without savings programs, but disappears after one season in areas with basic or matched savings programs.
3) Savings programs led to substantial increases in formal savings balances, suggesting resources may have been diverted from fertilizer to savings in post-subsidy periods in savings areas. However, all treatment areas experienced similar consumption gains of around 8%.
Neri conference 2015 income volatility and economic securityJason Loughrey
This document summarizes Jason Loughrey's presentation on constructing an economic security index for Ireland. It discusses measuring household income volatility in Ireland from 2006-2012 using survey data. Income volatility was highest for households in the bottom third of the income distribution and increased during the recession. The document also outlines the components of an economic security index, including a household's ability to maintain living standards during a 25% drop in income. Constructing such an index for Ireland is challenging due to data limitations but could provide insights into economic insecurity.
Dr. Emmanuel Orkoh_2023 AGRODEP Annual Conference - Parallel Session IIIaAKADEMIYA2063
This document summarizes a study on the impact of Namibia's COVID-19 Emergency Income Grant on household food security. The study used a survey of 250 households to collect data. Key findings include:
1) The income grant benefited 39% of households, with higher receipt among female-headed and less educated households.
2) Propensity score matching estimates found the grant significantly improved household food security, as measured by two indices.
3) Effects were larger for female-headed households, suggesting the grant particularly helped vulnerable groups.
4) Over half of households reported being satisfied with the income grant policy. Satisfaction levels were similar across demographic groups.
In 3 sentences, this summary
STAT200 Introduction to Statistics Dataset for Written Assig.docxwhitneyleman54422
STAT200 Introduction to Statistics
Dataset for Written Assignments
Description of Dataset:
The data is a random sample from the US Department of Labor’s 2016 Consumer Expenditure Surveys (CE) and provides information about the
composition of households and their annual expenditures (https://www.bls.gov/cex/). It contains information from 30 households, where a survey
responder provided the requested information; it is all self-reported information. This dataset contains four socioeconomic variables (whose names start
with SE) and four expenditure variables (whose names start with USD).
Description of Variables/Data Dictionary:
The following table is a data dictionary that describes the variables and their locations in this dataset (Note: Dataset is on second page of this document):
Variable Name Location in Dataset Variable Description Coding
UniqueID# First Column Unique number used to identify each survey
responder
Each responder has a unique
number from 1-30
SE-MaritalStatus Second Column Marital Status of Head of Household Not Married/Married
SE-Income Third Column Annual Household Income Amount in US Dollars
SE-AgeHeadHousehold Fourth Column Age of the Head of Household Age in Years
SE-FamilySize Fifth Column Total Number of People in Family (Both Adults
and Children)
Number of People in Family
USD-Annual Expenditures Sixth Column Total Amount of Annual Expenditures Amount in US Dollars
USD-Housing Seventh Column Total Amount of Annual Expenditure on Housing Amount in US Dollars
USD-Electricity Eighth Column Total Amount of Annual Expenditure on
Electricity
Amount in US Dollars
USD-Water Ninth Column Total Amount of Annual Expenditure on Water Amount in US Dollars
How to read the data set: Each row contains information from one household. For instance, the first row of the dataset starting on the next page shows
us that: the head of household is not married and is 53 years old, has an annual household income of $97,681, a family size of 4, annual expenditures of
$56,124, and spends $18,676 on housing, $1,468 on electricity, and $551 on water.
https://www.bls.gov/cex/
UniqueID# SE-MaritalStatus SE-Income SE-AgeHeadHousehold SE-FamilySize USD-AnnualExpenditures USD-Housing USD-Electricity USD-Water
1 Not Married 97681 53 4 56124 18676 1468 551
2 Not Married 96727 39 2 56440 18376 1441 542
3 Not Married 95432 51 1 55120 18391 1458 548
4 Not Married 96928 43 3 55932 18701 1479 520
5 Not Married 94929 59 2 55247 18483 1451 546
6 Not Married 95744 52 4 55963 18435 1465 555
7 Not Married 95366 48 2 57082 18576 1478 538
8 Not Married 96697 49 2 56453 18520 1469 545
9 Not Married 96572 59 2 56515 18648 1480 552
10 Not Married 96653 51 4 56488 18838 1470 535
11 Not Married 96664 53 3 55558 18502 1478 553
12 Not Married 96621 54 2 55746 18149 1455 540
13 Not Married 96886 44 2 55321 18312 1450 523
14 Not Married 96244 56 4 56051 18484 1457 539
15 Not Married 94867 60 1 55512 .
Using an Agroenterprise: Learning Alliances for Inclusive Value Chain SupportBASIS AMA Innovation Lab
CRS implemented Agroenterprise Learning Alliances over 5 years to help shift smallholder farmers from subsistence agriculture to competitive agroenterprise. The goal was to provide a bridge from relief to development by linking farmers to markets, diversifying crops, strengthening access to finance and services, and improving food security. Key aspects included participatory value chain development, multi-skill training for farmer groups, savings mobilization, strengthening local service providers, and integrating infrastructure, training and marketing linkages. Case studies in navy beans in Ethiopia and chickpeas in Tanzania showed increases in farmers, crops, and collective marketing. Challenges remained around skills transfer, farmer organization, value chain analysis, access to finance and information for rural
A presentation by John Hoddinott from the 2009 BASIS Conference on "Escaping Poverty Traps: Connecting the Chronically Poor to the Economic Growth Agenda."
Before and After the Drought: Evidence on the Impact of Index Insurance on Sm...BASIS AMA Innovation Lab
BASIS Director Michael Carter (working collaboratively with Ghada Elabed and Sarah Janzen) presented at the OECD meeting in Paris, September 2015 on the topic of index insurance and its impact on small farm investment and social protection.
This document discusses issues related to analyzing poverty dynamics and growth. It notes that chronic poverty is best characterized by both continuous or frequent spells in poverty as well as low, flat, or negative consumption growth. The document also stresses that attrition in panel survey data could affect results if not random, and that more thorough checks for non-random attrition are needed, including considering how dropping out of the lowest or highest households could mislead analyses of chronic poverty.
Impact of Mothers' Intellectual Human Capital and Long-Run Nutritional Status...BASIS AMA Innovation Lab
A presentation by Jere Behrman, Alexis Murphy, Agnes Quisumbing, and Kathryn Yount from the 2009 BASIS Conference on "Escaping Poverty Traps: Connecting the Chronically Poor to the Economic Growth Agenda."
Presentation by BASIS PI Travis Lybbert and Abbie Turiansky, along with Jean Claude O Fignole, Alix Percinthe, Sarah Belfort, Barry Shelly from OXFAM at the OXFAM Brown Bag series, February 22, 2016
Measuring the Quality of Agricultural Index Insurance: Concepts and Safe Mini...BASIS AMA Innovation Lab
A presentation on Agricultural Index Insurance by Professor Michael Carter of the University of California, Davis, and Director of the Feed the Future BASIS Assets and Market Access Innovation Lab (http://basis.ucdavis.edu). This presentation was given at a World Bank "Brown Bag" seminar on May 21, 2015.
DFID and Social Exclusion: the Use and Otherwise of a Concept in Internationa...BASIS AMA Innovation Lab
A presentation by Arjan de Haan and Andrew Shepherd from the 2009 BASIS Conference on "Escaping Poverty Traps: Connecting the Chronically Poor to the Economic Growth Agenda."
Pharma Market OTC & Nutrition Situation MAT 2013 Q2Danny D. Kosasih
Indonesia's pharmaceutical market grew 12% in 2013Q2 to IDR 4,755 OKU YEN, driven by 15% growth in the large over-the-counter (OTC) sector. The lifestyle category, including multivitamins and tonics, accounted for 19% of OTC and nutrition sales. Vitamin products, mainly from local manufacturers, were the top subcategory and heavily advertised products promising benefits like increased stamina and immunity. The growing OTC market is expected to continue expanding due to economic growth and more retail outlets selling these products.
Assisting the Poorest in Bangladesh: Learning from BRAC's Targeting the Ultra...BASIS AMA Innovation Lab
A presentation by David Hulme from the 2009 BASIS Conference on "Escaping Poverty Traps: Connecting the Chronically Poor to the Economic Growth Agenda."
The document summarizes a study examining whether there is evidence of a "culture of dependency" among social grant recipients in South Africa. The study found that grant recipients highly valued work and the unemployed were strongly motivated to find jobs. However, high unemployment was primarily due to lack of job opportunities rather than lack of motivation to work. The study concluded there was no evidence that grants caused dependency on welfare or reduced incentives to work.
The document discusses the benefits of exercise for mental health. Regular physical activity can help reduce anxiety and depression and improve mood and cognitive function. Exercise causes chemical changes in the brain that may help protect against mental illness and improve symptoms for those who already suffer from conditions like depression and anxiety.
Indonesia represents a growing market opportunity in healthcare due to its large and growing population, expanding middle class, and underserved healthcare sector. With 235 million people and over 80 million in the growing middle class, consumer spending and confidence are rising. This creates demand for quality healthcare as the population ages and chronic diseases become more prevalent. Private healthcare expenditures also continue to increase steadily. The growing and resilient economy makes Indonesia an attractive target for healthcare investments focused on mid-market consumer products and services, corporate healthcare, and digital health applications.
- The document outlines Thailand's health system and recent reforms towards universal health coverage.
- Key aspects include establishing the National Health Security Office in 2003 to provide quality healthcare access for all Thai citizens. The Universal Coverage scheme was launched, replacing the previous 30 Baht policy.
- Community hospitals and health centers play an important role in implementing healthcare policies and providing easily accessible primary care services at the local level.
A presentation by Cheryl Morden from the 2009 BASIS Conference on "Escaping Poverty Traps: Connecting the Chronically Poor to the Economic Growth Agenda."
At the Workshop on Innovations in Index Insurance to Promote Agricultural and Livestock Development, December 3rd, 2015 in Addis Ababa Ethiopia, Chris Barret of Cornell University presented on the favorable impacts of implementing index-based livestock insurance.
Savings, Subsidies, and Technology Adoption: Field Experimental Evidence from...BASIS AMA Innovation Lab
1) The study examines the interaction between temporary input subsidies and formal savings programs on technology adoption in rural Mozambique.
2) It finds that the impact of subsidies on fertilizer use persists for two seasons in areas without savings programs, but disappears after one season in areas with basic or matched savings programs.
3) Savings programs led to substantial increases in formal savings balances, suggesting resources may have been diverted from fertilizer to savings in post-subsidy periods in savings areas. However, all treatment areas experienced similar consumption gains of around 8%.
Neri conference 2015 income volatility and economic securityJason Loughrey
This document summarizes Jason Loughrey's presentation on constructing an economic security index for Ireland. It discusses measuring household income volatility in Ireland from 2006-2012 using survey data. Income volatility was highest for households in the bottom third of the income distribution and increased during the recession. The document also outlines the components of an economic security index, including a household's ability to maintain living standards during a 25% drop in income. Constructing such an index for Ireland is challenging due to data limitations but could provide insights into economic insecurity.
Dr. Emmanuel Orkoh_2023 AGRODEP Annual Conference - Parallel Session IIIaAKADEMIYA2063
This document summarizes a study on the impact of Namibia's COVID-19 Emergency Income Grant on household food security. The study used a survey of 250 households to collect data. Key findings include:
1) The income grant benefited 39% of households, with higher receipt among female-headed and less educated households.
2) Propensity score matching estimates found the grant significantly improved household food security, as measured by two indices.
3) Effects were larger for female-headed households, suggesting the grant particularly helped vulnerable groups.
4) Over half of households reported being satisfied with the income grant policy. Satisfaction levels were similar across demographic groups.
In 3 sentences, this summary
STAT200 Introduction to Statistics Dataset for Written Assig.docxwhitneyleman54422
STAT200 Introduction to Statistics
Dataset for Written Assignments
Description of Dataset:
The data is a random sample from the US Department of Labor’s 2016 Consumer Expenditure Surveys (CE) and provides information about the
composition of households and their annual expenditures (https://www.bls.gov/cex/). It contains information from 30 households, where a survey
responder provided the requested information; it is all self-reported information. This dataset contains four socioeconomic variables (whose names start
with SE) and four expenditure variables (whose names start with USD).
Description of Variables/Data Dictionary:
The following table is a data dictionary that describes the variables and their locations in this dataset (Note: Dataset is on second page of this document):
Variable Name Location in Dataset Variable Description Coding
UniqueID# First Column Unique number used to identify each survey
responder
Each responder has a unique
number from 1-30
SE-MaritalStatus Second Column Marital Status of Head of Household Not Married/Married
SE-Income Third Column Annual Household Income Amount in US Dollars
SE-AgeHeadHousehold Fourth Column Age of the Head of Household Age in Years
SE-FamilySize Fifth Column Total Number of People in Family (Both Adults
and Children)
Number of People in Family
USD-Annual Expenditures Sixth Column Total Amount of Annual Expenditures Amount in US Dollars
USD-Housing Seventh Column Total Amount of Annual Expenditure on Housing Amount in US Dollars
USD-Electricity Eighth Column Total Amount of Annual Expenditure on
Electricity
Amount in US Dollars
USD-Water Ninth Column Total Amount of Annual Expenditure on Water Amount in US Dollars
How to read the data set: Each row contains information from one household. For instance, the first row of the dataset starting on the next page shows
us that: the head of household is not married and is 53 years old, has an annual household income of $97,681, a family size of 4, annual expenditures of
$56,124, and spends $18,676 on housing, $1,468 on electricity, and $551 on water.
https://www.bls.gov/cex/
UniqueID# SE-MaritalStatus SE-Income SE-AgeHeadHousehold SE-FamilySize USD-AnnualExpenditures USD-Housing USD-Electricity USD-Water
1 Not Married 97681 53 4 56124 18676 1468 551
2 Not Married 96727 39 2 56440 18376 1441 542
3 Not Married 95432 51 1 55120 18391 1458 548
4 Not Married 96928 43 3 55932 18701 1479 520
5 Not Married 94929 59 2 55247 18483 1451 546
6 Not Married 95744 52 4 55963 18435 1465 555
7 Not Married 95366 48 2 57082 18576 1478 538
8 Not Married 96697 49 2 56453 18520 1469 545
9 Not Married 96572 59 2 56515 18648 1480 552
10 Not Married 96653 51 4 56488 18838 1470 535
11 Not Married 96664 53 3 55558 18502 1478 553
12 Not Married 96621 54 2 55746 18149 1455 540
13 Not Married 96886 44 2 55321 18312 1450 523
14 Not Married 96244 56 4 56051 18484 1457 539
15 Not Married 94867 60 1 55512 .
This document summarizes current models of out-of-home care in Australia, including the supports available for different types of care. It finds that relative/kinship care is the most common type of care but these carers often receive the least support. Expenditure is disproportionately higher for residential care placements despite these making up a small percentage of children in care. The document calls for increased financial and practical supports for relative/kinship carers to better meet the needs of children in their care.
1. Chakechake district lies in southern Pemba region and has four constituencies and 29 shehias. It has a population of around 109,926 people and is bordered by other districts and the Indian Ocean.
2. The district has five main livelihood zones: semi-coral fishing, semi-fertile soil with no fishing, deep fertile soil with and without fishing, and a peri-urban area. Agriculture, livestock, and fishing are important economic activities but many adults have shifted to other sectors.
3. Both food insecurity and poverty have increased in the district over time. The proportion of the population below the food poverty line rose from 15.9% to 19.1%
[Workshop en économie de développement:"Pertinence des politiques publiques d...Université de Dschang
[Workshop en économie de développement:"Pertinence des politiques publiques de développement dans les pays d'Afrique subsaharienne" ]Pr noumba powerpoint dschang
Is Public Health on a Treadmill of Inequality?
Paul McGill
IPH, Open, Conference, Belfast, Northern, Ireland, Dublin, Titanic, October, 2014, Health Public
The ESRI, in collaboration with Pobal, have launched a report examining the economic impacts of the COVID-19 pandemic on people living in disadvantaged areas in Ireland, as defined by the Pobal Haase Pratschke Deprivation Index. The report, titled ‘Pandemic Unemployment and Social Disadvantage in Ireland’, shows that people living in deprived areas, when compared to those living in more affluent areas, experienced greater disruption to their employment.
The Pandemic Unemployment Payment (PUP) was a social welfare payment for employees and self-employed people who lost all their employment due to the COVID-19 public health emergency and the resulting economic impact of lockdowns and restrictions. The payment was designed as income replacement to mitigate the short-term impact on financial wellbeing that pandemic-related job interruption would cause. This research examines the economic repercussions of the pandemic and the extent to which the proportion and duration of Pandemic Unemployment Payment (PUP) are related to area-level deprivation.
Read more key findings: https://www.esri.ie/news/people-in-disadvantaged-areas-experienced-greater-employment-disruption-during-the-covid-19
Read the report: https://www.esri.ie/publications/pandemic-unemployment-and-social-disadvantage-in-ireland
income Inequality in four provinces of pakistanShanö Jaan
This document discusses income inequality in Pakistan's four provinces based on data from household surveys. It finds that:
1) Balochistan has the lowest level of income inequality, with the lowest 9% of the population receiving 5% of total income, based on Lorenz curve analysis.
2) The other three provinces have higher inequality, with the lowest 9-18% of populations receiving only 2.5-9% of income.
3) A graph of the Lorenz curves for each province directly compares their levels of inequality, showing Balochistan closest to the line of perfect equality.
This document analyzes the impact of epilepsy and nodding syndrome on social exclusion in 4 counties of Western Equatoria state, South Sudan. Data was collected from 1,754 people and analyzed using statistical models to examine the relationship between activities of daily living and independent variables like age, sex, education level and livelihood status. The results found that over half of patients were male aged 11-20 years old, with most having no formal education. While 89% of patients were independent, 11% required assistance, indicating nodding syndrome can cause social exclusion through loss of independence. The study aims to understand how to better support people living with epilepsy and nodding syndrome.
Determinants of food insecurity in addis ababa city, ethiopiaAlexander Decker
This study examined the determinants of food insecurity among households in Addis Ababa, Ethiopia using survey data from 140 households. The Tobit regression model identified several significant determinants of food insecurity. Household size, income, age and education level of the household head, income from remittances/gifts, and ownership of a bank account were found to increase or decrease the likelihood of food insecurity. Policy recommendations include addressing the challenges faced by larger households and improving income generation opportunities to reduce food insecurity.
11.determinants of food insecurity in addis ababa city, ethiopiaAlexander Decker
This document summarizes a study that examined the determinants of food insecurity among households in Addis Ababa, Ethiopia. The study used a survey of 140 households and a Tobit regression model to analyze the data. The regression found that 6 of the 11 independent variables had a significant impact on household food insecurity. Larger household size, lower household income, older household head age, lower education level of the head, not having a bank account, and less income from remittances/gifts were associated with greater food insecurity. The study aimed to identify the key factors influencing food insecurity in urban areas to help policymakers address the problem.
Measuring employment and consumption in household surveys: Reflections from t...IFPRI-PIM
Webinar organized the CGIAR Research Program on Policies, Institutions, and Markets, led by IFPRI, on July 13, 2021.
Presentations:
- Are we done yet? Response fatigue and rural livelihoods (Sylvan Herskowitz, Research Fellow, IFPRI)
- Assessing response fatigue in phone survey: Experimental evidence on dietary diversity in Ethiopia (Kibrom Abay, Research Fellow, IFPRI)
- Telescoping causes overstatement in recalled food consumption: Evidence from a survey experiment in Ethiopia (Kalle Hirvonen, Senior Research Fellow, IFPRI)
Discussant: Andrew Dillon, Clinical Associate Professor of Development Economics within Kellogg's Public-Private Interface Initiative (KPPI); Director of Research Methods Cluster in the Global Poverty Research Lab, Northwestern University.
Moderator: Kate Ambler, Research Fellow, International Food Policy Research Institute (IFPRI).
More info and full recording: https://bit.ly/2TrpaNF
This document is a thesis submitted by Jessica Clark to the University of North Dakota in partial fulfillment of the requirements for a Master of Science degree in Applied Economics. The thesis examines the relationship between income inequality and health indicators in the United States at the county level from 2006 to 2010, a period that includes the Great Recession. The thesis provides background on rising income inequality in the US and reviews previous literature finding links between inequality and poorer health outcomes. The objective is to re-examine this relationship at the county level and during a time of economic crisis to add new insights to the topic. The thesis presents data sources and methodology for analyzing the relationship while controlling for other factors.
income Inequality in four provinces of pakistanShanö Jaan
This document discusses income inequality in Pakistan's four provinces based on data from household surveys. It presents Lorenz curves and Gini coefficients to measure inequality in each province. The key findings are:
1) Balochistan has the lowest income inequality, with its Lorenz curve closest to the line of perfect equality. In Balochistan, the bottom 9% receive 5% of income.
2) The other three provinces have higher inequality. In Punjab, the bottom 27% receive 11.15% of income. In Sindh, the bottom 18.2% receive 8.3% of income. In KP, the bottom 9.1% receive 4.3% of income.
3
income Inequality in four provinces of pakistanShanö Jaan
This document discusses income inequality in Pakistan's four provinces based on data from household surveys. It presents Lorenz curves and Gini coefficients to measure inequality in each province. The key findings are:
1) Balochistan has the lowest income inequality, with its Lorenz curve closest to the line of perfect equality. In Balochistan, the bottom 9% receive 5% of income.
2) The other three provinces have higher inequality. In Punjab, the bottom 27% receive 11.15% of income. In Sindh, the bottom 18.2% receive 8.3% of income. In KP, the bottom 9.1% receive 4.3% of income.
3
This document discusses tuberculosis (TB) in Northern Ireland, including risk factors, epidemiology, and social determinants. It finds that non-UK born individuals and those living in deprived areas or crowded conditions have higher rates of TB. A case study examines a TB cluster among migrant workers from Timor-Leste living in poor housing and working conditions. The document calls for improved collection of health data and consideration of how social factors influence disease.
Similar to Household Dynamics, Chronic Poverty and Social Protection in Indonesia (20)
ASSESSMENT OF THE BURKINA FASO PROJECT: THE SAFE MINIMUM STANDARDS (SMS) METH...BASIS AMA Innovation Lab
Thomas Barré, Michael Carter & Quentin Stoeffler presented at the GAN Knowledge Sharing Forum: “Assessing value from index insurance products”, September 16, 2015.
BASIS Director, Michael Carter, presented on the topic of temporary subsidies, savings and the adoption of improved technologies at the USAID Ag Sector Forum in March of 2015.
A Public Reinsurance Facility for Uncertain Risk Layers: A Modest Proposal?BASIS AMA Innovation Lab
This document discusses the potential for a public reinsurance facility to address the private sector's excess sensitivity to tail risk and uncertainty about tail risk. It presents three alternative models for public-private partnerships in reinsurance: Model A subsidies the full private contract to lower prices, Model B has the public sector reinsure just the severe risk layer at fair price while the private sector handles moderate risk, and Model C is similar to B but spends the subsidy on lowering the severe risk layer price. The document argues that a public entity could more neutrally price uncertain tail risk, crowding in private interest for less severe layers and limiting their liability, acting as a transitional strategy as risk knowledge grows over time.
The Design and Implementation of Index Insurance Inititatives: 3 Challenges f...BASIS AMA Innovation Lab
BASIS Director, Michael Carter, presented at the workshop on Developing Policy Innovations for the Pastoralist Rangelands, hosted by ILRI, Nairobi in June of 2015.
Financial Instruments for Managing Risk and Food Insecurity in the Arid Pasto...BASIS AMA Innovation Lab
A presentation by BASIS Director, Michael Carter, from the Climate Smart Agriculture Workshop: Building Resilience to Climate Change in Milan, Italy in August of 2015.
Social Protection in the Face of Climate Change: Targeting Principles and Fin...BASIS AMA Innovation Lab
BASIS Director Michael Carter and BASIS researcher, Sarah Janzen (Professor, Montana State University), presented in December 2015 on the importance of social protection mechanisms in the face of climate change.
Behavioral Economics and the Design of Agricultural Index Insurance in Develo...BASIS AMA Innovation Lab
UC Davis Professor Michael Carter presented, "Behavioral Economics and the Design of Agricultural Index Insurance in Developing Countries" at the 2014 International Agricultural Risk, Finance, and Insurance Conference (IARFIC).
Index Insurance for Small-holder Agriculture: What We Have Learned about Impa...BASIS AMA Innovation Lab
Michael Carter discusses key learnings from index insurance projects for smallholder farmers. Three main points:
1) Studies in Ghana, Mali, and Kenya found that index insurance increased investment and reduced reliance on costly coping strategies during droughts, showing it can have real development impacts by reducing risk.
2) However, basis risk from poorly correlated indexes undermines trust and impacts. New solutions using satellite data and dual-scale contracts have shown promise in reducing basis risk.
3) Behavioral experiments revealed farmers' aversion to ambiguity and compound risk reduces demand, while willingness to pay increased with contracts framing the premium as forgivable in bad years. Better understanding farmer behavior can improve uptake and impact.
Escaping Poverty Traps: Connecting the Chronically Poor to Economic GrowthBASIS AMA Innovation Lab
The agenda for the BASIS conference on Escaping Poverty Traps: Connecting the Chronically Poor to Economic Growth, held in Washington D.C. on February 26-27, 2009.
Former Senator Richard G. Lugar's remarks for the 2009 BASIS Conference on "Escaping Poverty Traps: Connecting the Chronically Poor to the Economic Growth Agenda."
A presentation by Shanta Devarajan from the 2009 BASIS Conference on "Escaping Poverty Traps: Connecting the Chronically Poor to the Economic Growth Agenda."
For Protection and Promotion: The Design and Implementation of Effective Safe...BASIS AMA Innovation Lab
A presentation by Margaret Grosh, Carlo del Ninno, Emil Tesliuc, and Azedine Ouerghi from the 2009 BASIS Conference on "Escaping Poverty Traps: Connecting the Chronically Poor to the Economic Growth Agenda."
Poverty and Landownership: Quasi-experimental Evidence from South AfricaBASIS AMA Innovation Lab
A presentation by Michael Carter, Klaus Deininger and Malcom Keswell from the 2009 BASIS Conference on "Escaping Poverty Traps: Connecting the Chronically Poor to the Economic Growth Agenda."
A presentation by the Chronic Poverty Research Centre from the 2009 BASIS Conference on "Escaping Poverty Traps: Connecting the Chronically Poor to the Economic Growth Agenda."
Contributi dei parlamentari del PD - Contributi L. 3/2019Partito democratico
DI SEGUITO SONO PUBBLICATI, AI SENSI DELL'ART. 11 DELLA LEGGE N. 3/2019, GLI IMPORTI RICEVUTI DALL'ENTRATA IN VIGORE DELLA SUDDETTA NORMA (31/01/2019) E FINO AL MESE SOLARE ANTECEDENTE QUELLO DELLA PUBBLICAZIONE SUL PRESENTE SITO
Food safety, prepare for the unexpected - So what can be done in order to be ready to address food safety, food Consumers, food producers and manufacturers, food transporters, food businesses, food retailers can ...
This report explores the significance of border towns and spaces for strengthening responses to young people on the move. In particular it explores the linkages of young people to local service centres with the aim of further developing service, protection, and support strategies for migrant children in border areas across the region. The report is based on a small-scale fieldwork study in the border towns of Chipata and Katete in Zambia conducted in July 2023. Border towns and spaces provide a rich source of information about issues related to the informal or irregular movement of young people across borders, including smuggling and trafficking. They can help build a picture of the nature and scope of the type of movement young migrants undertake and also the forms of protection available to them. Border towns and spaces also provide a lens through which we can better understand the vulnerabilities of young people on the move and, critically, the strategies they use to navigate challenges and access support.
The findings in this report highlight some of the key factors shaping the experiences and vulnerabilities of young people on the move – particularly their proximity to border spaces and how this affects the risks that they face. The report describes strategies that young people on the move employ to remain below the radar of visibility to state and non-state actors due to fear of arrest, detention, and deportation while also trying to keep themselves safe and access support in border towns. These strategies of (in)visibility provide a way to protect themselves yet at the same time also heighten some of the risks young people face as their vulnerabilities are not always recognised by those who could offer support.
In this report we show that the realities and challenges of life and migration in this region and in Zambia need to be better understood for support to be strengthened and tuned to meet the specific needs of young people on the move. This includes understanding the role of state and non-state stakeholders, the impact of laws and policies and, critically, the experiences of the young people themselves. We provide recommendations for immediate action, recommendations for programming to support young people on the move in the two towns that would reduce risk for young people in this area, and recommendations for longer term policy advocacy.
UN WOD 2024 will take us on a journey of discovery through the ocean's vastness, tapping into the wisdom and expertise of global policy-makers, scientists, managers, thought leaders, and artists to awaken new depths of understanding, compassion, collaboration and commitment for the ocean and all it sustains. The program will expand our perspectives and appreciation for our blue planet, build new foundations for our relationship to the ocean, and ignite a wave of action toward necessary change.
Donate to charity during this holiday seasonSERUDS INDIA
For people who have money and are philanthropic, there are infinite opportunities to gift a needy person or child a Merry Christmas. Even if you are living on a shoestring budget, you will be surprised at how much you can do.
Donate Us
https://serudsindia.org/how-to-donate-to-charity-during-this-holiday-season/
#charityforchildren, #donateforchildren, #donateclothesforchildren, #donatebooksforchildren, #donatetoysforchildren, #sponsorforchildren, #sponsorclothesforchildren, #sponsorbooksforchildren, #sponsortoysforchildren, #seruds, #kurnool
Working with data is a challenge for many organizations. Nonprofits in particular may need to collect and analyze sensitive, incomplete, and/or biased historical data about people. In this talk, Dr. Cori Faklaris of UNC Charlotte provides an overview of current AI capabilities and weaknesses to consider when integrating current AI technologies into the data workflow. The talk is organized around three takeaways: (1) For better or sometimes worse, AI provides you with “infinite interns.” (2) Give people permission & guardrails to learn what works with these “interns” and what doesn’t. (3) Create a roadmap for adding in more AI to assist nonprofit work, along with strategies for bias mitigation.
Jennifer Schaus and Associates hosts a complimentary webinar series on The FAR in 2024. Join the webinars on Wednesdays and Fridays at noon, eastern.
Recordings are on YouTube and the company website.
https://www.youtube.com/@jenniferschaus/videos
Household Dynamics, Chronic Poverty and Social Protection in Indonesia
1. Household Dynamics,
Chronic Poverty and
Social Protection in Indonesia
Wenefrida Widyanti†
, Asep Suryahadi,
Sudarno Sumarto and Athia Yumna
The SMERU Research Institute
www.smeru.or.id
2. 2
Outline
1. Introduction
2. Data
3. Poverty and Chronic Poverty in Indonesia
4. Household Composition Change and Chronic Poverty
5. Household Dynamics as a Protection Instrument
6. Economic Viability and Chronic Poverty
7. Household Dynamics and the Concept of Chronic Poverty
8. Household Dynamics and Social Protection
9. Conclusion
3. 3
Introduction
A typical household usually consists of several individuals with different
characteristics, including their economic capacities, which in the end
determines the economic capacity of the household as a unit.
A change in household composition will affect the economic capacity and
economic condition of a household and most likely entail simultaneously
both positive and negative effects on a household’s economic capacity and
economic condition.
The direction of causation can also go in the opposite direction. A change in
the economic condition of a household can induce the household to change
its household composition.
The existence of relationships between household composition and
household’s economic capacity and condition indicates that household
composition may play an important role in explaining why some households
fall into chronic poverty (i.e. severe and persistent poverty).
4. 4
Data
Indonesia Family Life Survey (IFLS) Data from RAND, a longitudinal
household survey with a sample which is representative of about 83
percent of the Indonesian population (13 provinces in Indonesia):
IFLS1 was conducted in 1993/94 by RAND in collaboration with the
Demographic Institute of the University of Indonesia (LDUI) 7,224
households (over 22,000 individuals) were interviewed.
IFLS2 was subsequently conducted in 1997 by RAND in collaboration with
UCLA and LDUI 94% of IFLS1 households were relocated and re-
interviewed + 878 split-off households (over 33,000 individuals) were
interviewed.
IFLS3 was fielded in 2000, conducted by RAND in collaboration with the
Centre for Population and Policy Studies, Gadjah Mada University (PSKK-
UGM) 10,400 households (around 39,000 individuals) were interviewed.
A complete panel of 6,403 households were interviewed in IFLS1, IFLS2 and
IFLS3.
5. 5
Poverty and Chronic Poverty in Indonesia (1)
Table 1. Poverty Indicators of Panel Data Households (%)
Indicator 1993 1997 2000
Poverty headcount (P0) 23.05 14.56 15.02
Poverty gap (P1) 6.79 3.87 3.70
Poverty severity (P2) 2.92 1.56 1.37
Number of observations (N) 6,403 6,403 6,403
Source: Authors’ calculation using IFLS data
There was clear improvement in the household welfare between 1993 and
1997; however, due to the advent of an economic crisis starting in the
second half of 1997, there was stagnation in household welfare between
1997 and 2000.
6. 6
Poverty and Chronic Poverty in Indonesia (2)
Table 2. Poverty Dynamics of Panel Data Households
Poverty Pattern 1993 1997 2000 Incidence (%)
Always poor Poor Poor Poor 4.23
Poor Poor Not poor 4.33
Poor Not poor Poor 3.56
Twice poor
Not poor Poor Poor 2.00
9.89
Poor Not poor Not poor 10.93
Not poor Poor Not poor 4.00
Once poor
Not poor Not poor Poor 5.23
20.16
Never poor Not poor Not poor Not poor 65.72
Number of observations (N) 6,403
Source: Authors’ calculation using IFLS data
Always poor + twice poor chronic poor (14.1%)
Once poor vulnerable (20.2%)
Never poor non-poor (65.7%)
7. 7
Household Composition Change and Chronic Poverty (1)
Table 3. Household Distribution by Poverty Groups across the Existence of Household
Composition Change (%)
Existence of Household Composition
Change
Chronic
Poor
Vulnerable Non-poor N
No change in composition 15.00 19.10 65.90 2,173
Experienced change in composition 13.66 20.71 65.63 4,230
Total 14.12 20.16 65,72 6,403
Source: Authors’ calculation using IFLS data
The distributions by poverty groups of both households that
experienced household composition change and those that did not
are similar to each other as well as to the total distribution
Household composition change is not a major cause of the chronic
poverty phenomenon in Indonesia
8. 8
Household Composition Change and Chronic Poverty (2)
Table 4. Household Distribution by Poverty Groups across the Types of Household Composition
Change (%)
Type of Composition Change
Chronic
Poor
Vulnerable Non-poor N
Death of breadwinner 0.00 33.33 66.67 12
Death of other household member 15.00 15.00 70.00 20
Birth of a child 11.81 15.28 72.92 288
Divorce or separation 21.43 14.29 64.29 14
Additional working adult 14.34 20.58 65.08 1,074
Additional non-working adult 13.92 21.30 64.78 2,723
Others 5.05 22.22 72.73 99
Total 13.66 20.71 65.63 4,230
Source: Authors’ calculation using IFLS data
The distributions by poverty groups of the households which experienced
household composition change by the type of the composition change that
occurred are similar to the total distribution (except divorce or separation but based
on a small number of observations) There is no evidence that certain types of
household composition change cause a higher probability for households to be
chronically poor
9. 9
Household Dynamics as a Protection Instrument
Table 5. The Proportions of Households Having a Bad State in Previous Period among
Those which Experienced Household Composition Change (%)
Bad State in Previous Period 1997 2000
Poverty:
- Poor in previous period 21.99 14.59
- Not poor in previous period 78.01 85.41
N 4,230 4,230
Unemployment:
- Head unemployed in previous period 15.26 20,52
- Head employed in previous period 84.74 79,48
N 4,155 4,006
Source: Authors’ calculation using IFLS data
The proportion of bad state households among those that experienced a change in
household composition is similar to the total households There is no evidence
that households change their composition to cope with poverty and unemployment.
10. 10
Economic Viability and Chronic Poverty
Table 8. Results of Ordered Probit of the Effects of Household Composition on the Probability
to be Chronic Poor or Vulnerable
Chronic Poor VulnerableIndependent
Variable Coefficient Std. Error Coefficient Std. Error
Household composition:
Husband-wife with
children households
0.01592 0.02367 0.01416 0.02190
Single male/father with
and without children
households
0.08498 0.06077 0.05223 * 0.02562
Single female without
children households
-0.11640 ** 0.00477 -0.21484 ** 0.00591
Single mother with
children households
0.01100 0.03290 0.00901 0.02580
Other household
compositions
0.06705 * 0.03200 0.04668 ** 0.01784
Household
characteristics:
Number of household
members
0.02383 ** 0.00188 0.02035 ** 0.00174
Dependency ratio -0.00003 0.00004 -0.00002 0.00003
Proportion of male in a
household
-0.00008 0.00019 -0.00007 0.00016
Proportion of adult in a
household
0.03525 0.02767 0.03011 0.02368
Proportion of working
household members
0.02319 * 0.01204 0.01981 * 0.01028
Proportion of household
members with secondary
education or higher
-0.61423 ** 0.02719 -0.52458 ** 0.03156
Note: The independent variables used in the model are based on 1993 data.
** Significant at 1%
* Significant at 5%
Single female without children
households have the lowest
probability to be either
chronically poor or vulnerable,
while single father households
have the highest probability to
be vulnerable.
The larger the number of
household members, the higher
the probability a household to be
chronically poor or vulnerable.
Higher proportion of household
members with senior secondary
or higher education reduces the
probability of a household to be
either chronic poor or
vulnerable.
11. 11
Household Dynamics and the Concept of Chronic Poverty
Table 9. Poverty Headcount Rates for Various Household Groups in the Data (%)
Poverty Headcount (%)
Population Group
1993 1997 2000
N
First round households:
- First round households in the
complete panel
23.05 14.56 15.02 6,403
- First round households visited in the
second round but not visited in the
third round
14.93 5.97 – 201
- First round households not visited in
the second round but visited in the
third round
12.07 – 10.34 232
- First round households not visited in
the second and third rounds
10.00 – – 300
- Total first round households
21.92
(N=7,136)
14.29
(N=6,604)
14.86
(N=6,635)
7,136
Second round households:
- New households in the second
round visited in the third round
– 8.94 11.91 705
- New households in the second
round not visited in the third round
– 13.39 – 224
- Total second round households –
10.01
(N=929)
11.91
(N=705)
929
Third Round Households:
- New households in the third round – – 9.30 2,818
All Households in the Data
21.92
(N=7,136)
13.77
(N=7,533)
13.11
(N=10,158)
10,883
Source: Authors’ calculation using IFLS data
The complete panel
households are poorer than
the total sample in each
round:
The households dropped
out of sample are less
poor
The new households
added into sample are
less poor
The use of household as the
unit of analysis for poverty
may undermine the
conceptualisation &
measurement of chronic
poverty.
12. 12
Household Dynamics and Social Protection
Poverty status in general does not increase the probability of receiving assistance,
except for the vulnerable in receiving basic need assistance.
Change in household composition does not increase the probability of receiving
assistance either.
Table 12. Results of probit analysis of household participation in government social
protection programmes in 2000 (%)
Basic needs assistance Other assistances
Independent variable
Coefficient Std. Error Coefficient Std. Error
Poverty status:
Chronically poor 0.33698 0.22719 0.12199 0.42655
Vulnerable 0.29597 ** 0.10773 -0.02686 0.20418
Poor in 1993 0.03295 0.10902 -0.13284 0.20336
Poor in 1997 -0.06977 0.10596 -0.08762 0.20563
Poor in 2000 0.12706 0.10269 -0.09073 0.19605
Change in household
composition:
Change in household
composition 1993-1997
0.07934 0.04978 0.07779 0.08664
Change in household
composition 1997-2000
0.01345 0.04076 -0.00663 0.07303
Household characteristics:
13. 13
Conclusion (1)
Household composition change is not a major cause of the
chronic poverty phenomenon in Indonesia.
There is no evidence that certain types of household
composition change cause a higher probability for households
to be chronically poor.
There is no evidence that households change their composition
to cope with poverty as well as unemployment.
Husband-wife households have the highest probability to be
non-poor, while single mother households have a higher
probability to be non-poor than single father households.
14. 14
Conclusion (2)
The larger the number of household members, the higher the
probability a household to be chronically poor or vulnerable.
A higher proportion of household members with senior
secondary or higher education reduces the probability of a
household to be either chronic poor or vulnerable.
Because of household dynamics, the use of household as the
unit of analysis for poverty could undermine the
conceptualisation & measurement of chronic poverty.
Poverty status and change in household composition in general
do not increase the probability of a household to receive an
assistance.