This document discusses change and rigidity in youth employment patterns in Malawi based on analysis of household survey data from 2004, 2010, and 2016. The key findings are:
1) Agriculture remains the dominant sector of employment in Malawi, accounting for around 88% of those employed.
2) There is little evidence of structural change in employment patterns, with the share of those working in agriculture remaining stable.
3) Youth generally enter the workforce through agriculture like previous generations, with older youth showing some movement into other sectors like services.
Change and Rigidity in Youth Employment Patterns in Malawi, 2004-2016IFPRIMaSSP
Presentation on 'Change and Rigidity in Youth Employment Patterns in Malawi from 2014-2016,' from a study jointly conducted by Bob Baulch (IFPRI Malawi Program Leader), Todd Benson (IFPRI), Alvina Erman (World Bank), and Yanjanani Lifeyo (IFPRI Malawi). This research was presented at a workshop on rural transformation hosted by the CGIAR Research Program on Policies, Institutions and Markets (PIM) at the 30th International Conference of Agricultural Economists on July 28, 2018.
Women’s labour is a rich and valuable resource for a country as it can significantly boost growth prospects and improve socio-economic conditions as also ensure better outcomes for the next generation. Therefore, enhancing women participation in the labour force is a critical endeavour for driving overall social and sustainable development.
Despite positive growth and development parameters in the last 20-25 years, India has experienced a continuous decline in its female labour force participation rate (FLFPR). The total FLFPR declined sharply from 42.7% in 2004-05 to 31.2% in 2011-12 which further declined to 27.4% in 2015-2016. In 2013, International Labour Organization (ILO) ranked India’s FLFPR at 121 out of 130 countries, one of the lowest in the world. India also secured a poor rank in the Global Gender Gap Report 2017 by World Economic Forum, where it was ranked 108 out of 144 economies.
The largest drop in FLFPR took place in rural areas and was specifically prominent in the working age group of 20-44 years. This is a major factor that is responsible for pulling down the overall FLFPR. On the other hand, the urban FLFPR which has been historically lower than the rural FLFPR, has fluctuated.
The economic prosperity of a nation depends on the quality of its workforce. The present study attempts to describe the work force participation rates in India. This study illustrates the spatial and temporal change in the work force participation of persons (males and females) in India, highlighting important differences due to sex, age, place of residence. A striking feature has been a rising trend in the rural female work force participation rates after liberalization (1991) but declining trend in the last decade (2011). This work force distribution also presents data regarding number of main and marginal workers. The time series data on work force distribution by category of workers like cultivators, agricultural laborers, workers in rural Household industries, etc. also presents a picture of structural change occurring in the economy. The temporal analysis of total workers of India explains that the work participation rate has registered continuous increase in the last three decades.
Change and Rigidity in Youth Employment Patterns in Malawi, 2004-2016IFPRIMaSSP
Presentation on 'Change and Rigidity in Youth Employment Patterns in Malawi from 2014-2016,' from a study jointly conducted by Bob Baulch (IFPRI Malawi Program Leader), Todd Benson (IFPRI), Alvina Erman (World Bank), and Yanjanani Lifeyo (IFPRI Malawi). This research was presented at a workshop on rural transformation hosted by the CGIAR Research Program on Policies, Institutions and Markets (PIM) at the 30th International Conference of Agricultural Economists on July 28, 2018.
Women’s labour is a rich and valuable resource for a country as it can significantly boost growth prospects and improve socio-economic conditions as also ensure better outcomes for the next generation. Therefore, enhancing women participation in the labour force is a critical endeavour for driving overall social and sustainable development.
Despite positive growth and development parameters in the last 20-25 years, India has experienced a continuous decline in its female labour force participation rate (FLFPR). The total FLFPR declined sharply from 42.7% in 2004-05 to 31.2% in 2011-12 which further declined to 27.4% in 2015-2016. In 2013, International Labour Organization (ILO) ranked India’s FLFPR at 121 out of 130 countries, one of the lowest in the world. India also secured a poor rank in the Global Gender Gap Report 2017 by World Economic Forum, where it was ranked 108 out of 144 economies.
The largest drop in FLFPR took place in rural areas and was specifically prominent in the working age group of 20-44 years. This is a major factor that is responsible for pulling down the overall FLFPR. On the other hand, the urban FLFPR which has been historically lower than the rural FLFPR, has fluctuated.
The economic prosperity of a nation depends on the quality of its workforce. The present study attempts to describe the work force participation rates in India. This study illustrates the spatial and temporal change in the work force participation of persons (males and females) in India, highlighting important differences due to sex, age, place of residence. A striking feature has been a rising trend in the rural female work force participation rates after liberalization (1991) but declining trend in the last decade (2011). This work force distribution also presents data regarding number of main and marginal workers. The time series data on work force distribution by category of workers like cultivators, agricultural laborers, workers in rural Household industries, etc. also presents a picture of structural change occurring in the economy. The temporal analysis of total workers of India explains that the work participation rate has registered continuous increase in the last three decades.
There are myriads of variables responsible for youth unemployment problem
particularly in Nigeria and other developing countries. Consequently, it is necessary to
obtain comprehensive data on the variables to blame for youth unemployment to chart
direction for further research and provide guide for stakeholders on the pathway to
solving the problem. Factors accountable for youth unemployment problem were
abstracted from literature and presented. Frequency distribution of the factors causing
youth unemployment based on researches unproven opinion showed that, fast population
growth, rural to urban migration and lack of employable skills and experience among the
youth are predominantly factors to blame among other variables. Thus, the information
provided suggest direction from where to start addressing youth unemployment problem
by stakeholders and policy makers while further research is required to pinpoint the
primary causes of the problem with proven evidence
Youth Employment in Sub-Saharan Africa. by Louise FoxIFPRI-PIM
The first PIM’s Brown Bag seminar in 2014 took place on February 27 at IFPRI and was dedicated to the topic of Youth Employment in Sub-Saharan Africa (with a presentation of the recently issued World Bank report on the topic). The session showed great interest among our colleagues working in the area of agricultural and food policies. Presenters included Louise Fox, co-author of the resent World Bank report on the topic, former World Bank Lead Economist and now Visiting Professor at UC Berkeley; Karen Brooks, the report’s contributor and PIM Director; and Frank Byamugisha, author of the book on land rights in Africa “Securing Africa's Land for Shared Prosperity: A Program to Scale Up Reforms and Investments”. More here: http://bit.ly/1g92XTa
Pakistan Rural Investment Climate Survey: Background and Sample Frame Desgnidspak
The main purpose of this paper is to examine the nature of rural non-farm sector in Pakistan. The non-farm sector can absorb a large number of rural labour force in various activities such as, industry, trade/business, craft, and services and thus can play an important role in increasing employment and income. Rural areas of Pakistan are characterized by higher incidence of poverty, lower levels of literacy, poor health status, low access to basic services and amenities, and higher levels underemployment as compared to the Urban areas. The paper presents the nature of rural non-farm sector in Pakistan by analyzing the data of Labour Force Survey and Small and Household Manufacturing Industries
Youth Unemployment in India - Present ScenarioArul Edison
Young Indians face major barriers because of poverty and low levels of human capital. Though educational attainment has risen quickly in recent years, gaining a foothold in the labour market remains elusive for many young Indians. In rural and urban areas, young males are usually employed in casual jobs, while their female counterparts tend to be self-employed. Although a large proportion of young rural women are employed in agriculture, rural males are increasingly turning to the non-farm sector. In comparison, young urban males are largely working in the services sector. This paper highlights youth unemployment in India - present scenario.
Project abstract or effective unemployment of somaliaMohamedAli47986
This project is written by Mohamed Ali from Somalia, in my idea I would be very grateful you to share with you the main causes of Somali youth unemployment.
Abstract: Discouraged Youth’ is defined as those youth who are not working even though they have expressed a desire to work, but due to the fact that they felt that undertaking a job search would be a futile effort, have not continued with the effort to seek a job . The magnitude of this crisis is a cause for concern for Mauritius; hence this study was conducted with the objective of creating a deeper understanding of discouraged youth. Primary data is used for this study, and the survey covers a sample of 500 unemployed youth across the island. The probit regression model is used to analyse the determinants affecting discouraged youth. The findings of the study found that age, age2, marital status, gender and tertiary education, area of study based on friend’s opinion, length of unemployment less than 12 months and prior experience have an impact on discouraged youth. From the analysis it was noted that education and training systems should be revisited to bridge the skills gap.
Keywords: Labour Force, Unemployment, Discouraged Youth, Probit Regression Analysis, Mauritius.
James Thurlow and Valerie Mueller
BOOK LAUNCH
Youth and Jobs in Rural Africa: Beyond Stylized Facts
Co-Organized by IFPRI and the CGIAR Research Program on Policies, Institutions, and Markets
JAN 21, 2020 - 12:15 PM TO 01:15 PM EST
There are myriads of variables responsible for youth unemployment problem
particularly in Nigeria and other developing countries. Consequently, it is necessary to
obtain comprehensive data on the variables to blame for youth unemployment to chart
direction for further research and provide guide for stakeholders on the pathway to
solving the problem. Factors accountable for youth unemployment problem were
abstracted from literature and presented. Frequency distribution of the factors causing
youth unemployment based on researches unproven opinion showed that, fast population
growth, rural to urban migration and lack of employable skills and experience among the
youth are predominantly factors to blame among other variables. Thus, the information
provided suggest direction from where to start addressing youth unemployment problem
by stakeholders and policy makers while further research is required to pinpoint the
primary causes of the problem with proven evidence
Youth Employment in Sub-Saharan Africa. by Louise FoxIFPRI-PIM
The first PIM’s Brown Bag seminar in 2014 took place on February 27 at IFPRI and was dedicated to the topic of Youth Employment in Sub-Saharan Africa (with a presentation of the recently issued World Bank report on the topic). The session showed great interest among our colleagues working in the area of agricultural and food policies. Presenters included Louise Fox, co-author of the resent World Bank report on the topic, former World Bank Lead Economist and now Visiting Professor at UC Berkeley; Karen Brooks, the report’s contributor and PIM Director; and Frank Byamugisha, author of the book on land rights in Africa “Securing Africa's Land for Shared Prosperity: A Program to Scale Up Reforms and Investments”. More here: http://bit.ly/1g92XTa
Pakistan Rural Investment Climate Survey: Background and Sample Frame Desgnidspak
The main purpose of this paper is to examine the nature of rural non-farm sector in Pakistan. The non-farm sector can absorb a large number of rural labour force in various activities such as, industry, trade/business, craft, and services and thus can play an important role in increasing employment and income. Rural areas of Pakistan are characterized by higher incidence of poverty, lower levels of literacy, poor health status, low access to basic services and amenities, and higher levels underemployment as compared to the Urban areas. The paper presents the nature of rural non-farm sector in Pakistan by analyzing the data of Labour Force Survey and Small and Household Manufacturing Industries
Youth Unemployment in India - Present ScenarioArul Edison
Young Indians face major barriers because of poverty and low levels of human capital. Though educational attainment has risen quickly in recent years, gaining a foothold in the labour market remains elusive for many young Indians. In rural and urban areas, young males are usually employed in casual jobs, while their female counterparts tend to be self-employed. Although a large proportion of young rural women are employed in agriculture, rural males are increasingly turning to the non-farm sector. In comparison, young urban males are largely working in the services sector. This paper highlights youth unemployment in India - present scenario.
Project abstract or effective unemployment of somaliaMohamedAli47986
This project is written by Mohamed Ali from Somalia, in my idea I would be very grateful you to share with you the main causes of Somali youth unemployment.
Abstract: Discouraged Youth’ is defined as those youth who are not working even though they have expressed a desire to work, but due to the fact that they felt that undertaking a job search would be a futile effort, have not continued with the effort to seek a job . The magnitude of this crisis is a cause for concern for Mauritius; hence this study was conducted with the objective of creating a deeper understanding of discouraged youth. Primary data is used for this study, and the survey covers a sample of 500 unemployed youth across the island. The probit regression model is used to analyse the determinants affecting discouraged youth. The findings of the study found that age, age2, marital status, gender and tertiary education, area of study based on friend’s opinion, length of unemployment less than 12 months and prior experience have an impact on discouraged youth. From the analysis it was noted that education and training systems should be revisited to bridge the skills gap.
Keywords: Labour Force, Unemployment, Discouraged Youth, Probit Regression Analysis, Mauritius.
James Thurlow and Valerie Mueller
BOOK LAUNCH
Youth and Jobs in Rural Africa: Beyond Stylized Facts
Co-Organized by IFPRI and the CGIAR Research Program on Policies, Institutions, and Markets
JAN 21, 2020 - 12:15 PM TO 01:15 PM EST
Employment prospects for teens and young adults in the nation’s 100 largest metropolitan areas plummeted between 2000 and 2011. On a number of measures—employment rates, labor force underutilization, unemployment, and year-round joblessness—teens and young adults fared poorly, and sometimes disastrously. While labor market problems affected all young people, some groups had better outcomes than others: Non-Hispanic whites, those from higher income households, those with work experience, and those with higher levels of education were more successful in the labor market. In particular, education and previous work experience were most strongly associated with employment.
Policy and program efforts to reduce youth joblessness and labor force underutilization should focus on the following priorities: incorporating more work-based learning (such as apprenticeships, co-ops, and internships) into education and training; creating tighter linkages between secondary and post-secondary education; ensuring that training meets regional labor market needs; expanding the Earned Income Tax Credit; and facilitating the transition of young people into the labor market through enhanced career counseling, mentoring, occupational and work-readiness skills development, and the creation of short-term subsidized jobs.
Putting Children First: Session 1.6.D Alebel Weldesilassie - Towards ensuring...The Impact Initiative
Putting Children First: Identifying solutions and taking action to tackle poverty and inequality in Africa.
Addis Ababa, Ethiopia, 23-25 October 2017
This three-day international conference aimed to engage policy makers, practitioners and researchers in identifying solutions for fighting child poverty and inequality in Africa, and in inspiring action towards change. The conference offered a platform for bridging divides across sectors, disciplines and policy, practice and research.
Planning in the region starts with a vision about what we want to be. It is the aspiration of the Filipinos particularly those from SOCCSKSARGEN Region to have a long-term vision for the region and the country as a whole to become a prosperous, predominantly middle class society where no one is poor. The challenge is how every Filipino can afford to have a “matatag, maginhawa at panatag na buhay by 2040.”
Off-farm employment in rural areas can be a major contributor to rural poverty reduction and decent rural employment. While women are highly active in the agricultural sector, they are less active than men in off-farm employment. This study analyzes the determinants of participation in off-farm employment of women in rural Uganda. The study is based on a field survey conducted in nine districts with the sample size of 1200 individual females. A two-stage Hechman’s sample selection model was applied to capture women’s decision to participate and the level of participation in non-farm economic activities. Summary statistics of the survey data from rural Uganda shows that: i) poverty and non-farm employment has a strong correlation, implying the importance of non-farm employment as a means for poverty reduction; and ii) there is a large gender gap to access non-farm employment, but the gender gap has been significantly reduced from group of older age to younger generation. The econometric results finds that the following factors have a significant influence on women’s participation in off-farm employment: education level of both the individual and household head (positive in both stages); women’s age (negative in both stages); female-headed household (negative in first stage); household head of polygamous marriage (negative in both stages); distance from major town (negative in the first stage); household size (positive in the second stage); dependency ratio (negative in the second stage); access to and use of government extension services (positive in the first stage); access to and use of an agricultural loan (negative in the second stage); and various district dummies variables. The implications of these findings suggest that those policies aimed at enhancing the identified determinants of women off-farm employment can promote income-generating opportunities for women groups in comparable contexts. In order to capitalize on these positive linkages, policies should be designed to improve skills and knowledge by providing education opportunities and increasing access to employment training, assistance services and loans for non-farm activities and by targeting women in female-headed, large and distant households. The government should increase investments in public infrastructure and services, such as roads, telecommunications and emergency support.
Disrupted Futures 2023 | The YOUTHshare projectEduSkills OECD
This presentation from the OECD Disrupted Futures 2023: International lessons on how schools can best equip students for their working lives conference looks at Delivering effective career guidance “The YOUTHshare project: real-time monitoring and expanded training for young people from the European South”. Presented by Georgios Chatzichristos, Fotini Vlachaki and Stelios Gialis.
Discover the videos and other sessions from the OECD Disrupted Futures 2023 conference at https://www.oecd.org/education/career-readiness/conferences-webinars/disrupted-futures-2023.htm
Find out more about our work on Career Readiness https://www.oecd.org/education/career-readiness/
Cash transfers and intimate partner violence: Case studies from Ethiopia and ...IFPRI-PIM
Webinar organized by the CGIAR Research Program on Policies, Institutions, and Markets (PIM) and the Cash Transfer and Intimate Partner Violence Research Collaborative in support of the annual 16 Days of Activism against Gender-Based Violence campaign. More information and full recording available at https://bit.ly/3pOlJx0
African Farmers, Value Chains, and African DevelopmentIFPRI-PIM
PIM Webinar/Book Launch, December 9, 2021.
At first glance, African smallholder farmers might seem unproductive, as their crops yield much less than potential and are often of variable quality. A new PIM-supported book “African Farmers, Value Chains, and Agricultural Development” argues that in fact they are largely producing following rational economic decisions, and that this situation is a consequence of the economic and institutional environment in which they produce. The authors Alan de Brauw and Erwin Bulte discuss ways that different types of transaction costs limit their market opportunities in general, including transport costs but also costs related to different sources of risks, trust, market power, liquidity, and even storage.
More information and full webinar recording: https://bit.ly/3rMpdTi
Tenure Security and Landscape Governance of Natural ResourcesIFPRI-PIM
PIM Webinar recorded on December 7, 2021. For more information and the recording of the webinar, and to access the briefs, visit https://bit.ly/3xZDBs6
COVID-19 and agricultural value chains: Impacts and adaptationsIFPRI-PIM
PIM Webinar recorded on November 29, 2021.
Presenters: Ben Belton - Global Lead, Social and Economic Inclusion, WorldFish
Diego Naziri – value chain and postharvest specialist, International Potato Center (CIP); Leader of “Nutritious Food and Value Added through Post-harvest Innovation” research flagship in the CGIAR Research Program on Roots, Tubers and Bananas (RTB)
Gashaw Tadesse Abate - Research Fellow at the International Food Policy Research Institute (IFPRI).
Abut Hayat Md. Saiful Islam – Professor at Department of Agricultural Economics at Bangladesh Agricultural University in Mymensingh, Bangladesh.
Marcel Gatto – Agricultural Economist at the International Potato Center (CIP).
Humnath Bhandari - Senior Agricultural Economist and Country Representative, IRRI Bangladesh.
G.M. Monirul Alam - Professor, Faculty of Agricultural Economics and Rural Development, Bangabandhu Sheikh Mujib Rahman Agricultural University, Gazipur, Bangladesh.
Full recording of the webinar available at https://bit.ly/3DN18in
Inclusive and Efficient Value Chains: Innovations, Scaling, and Way ForwardIFPRI-PIM
In the CGIAR Research Program on Policies, Institutions, and Markets (PIM), market and related aspects have been mostly addressed by PIM Flagship 3: Inclusive and Efficient Value Chains. The team has been focusing on the evolving international, regional, and local contexts for agricultural markets, and investigating how value chains (VC) can be strengthened to generate more benefits for smallholders and small and medium enterprises (SMEs), with differentiated opportunities for women, men, and youth. In this webinar on 22 November 2021, the team presented key findings from the Flagship’s work in 2017-2021 in three areas: 1) value chain innovations, 2) use of value chains for scaling CGIAR solutions, and 3) interactions between research and practice for value chain development.
For more information about this webinar and to access the full recording, visit https://bit.ly/3c6siV5.
Agricultural extension and rural advisory services: From research to actionIFPRI-PIM
PIM Webinar, 11 November 2021 // Presentation of innovative interventions that can be applied and adapted to enhance extension performance // Summary of agricultural extension research supported by the CGIAR Research Program on Policies, Institutions, and Markets (PIM).
Event page (full recording): https://bit.ly/3jRTRWy
See more on www.pim.cgiar.org
Methods for studying gender dynamics in value chains beyond the production no...IFPRI-PIM
PIM Webinar recorded on Oct. 28, 2021. Presenters: Jessica Leight (IFPRI); Emily Gallagher (CIFOR); and Kate Ambler (IFPRI). More information at https://bit.ly/GDVCweb
Gender dynamics in value chains: Beyond production node and a single commodit...IFPRI-PIM
1st webinar in the series summarizing results of the Gender Dynamics in Value Chain project, supported by the CGIAR Research Program on Policies, Institutions, and Markets (PIM) in 2019-2021. More information: https://bit.ly/GDVCweb
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
Webinar about the new book "Value Chain Development and The Poor: Promise, delivery, and opportunities for impact at scale" (eds. Jason Donovan, Dietmar Stoian, and Jon Hellin), recorded on June 17, 2021. For more information and video recording, visit https://bit.ly/3goPP5r
Feminization of agriculture: Building evidence to debunk myths on current cha...IFPRI-PIM
This PIM webinar recorded on Jun 10, 2021 presents the findings from five projects that comprised a set of PIM grants on Feminization of Agriculture: Building evidence to debunk myths on current challenges and opportunities. Research teams from across CGIAR worked since 2018 to explore the dynamics and impacts of migration, including male-outmigration, on gender relations in agriculture and natural resource domains. More info: https://bit.ly/FemofAg1
Beyond agriculture: Measuring agri-food system GDP and employmentIFPRI-PIM
Webinar with James Thurlow (IFPRI/CGIAR-PIM) presenting a new approach for measuring agri-food system GDP and employment. (Recorded on April 8, 2021)
More info and full recording: https://bit.ly/mafsGDP
Webinar: COVID-19 risk and food value chains (presentation 3)IFPRI-PIM
Presentation "COVID-19 Impacts on Fish Value Chains in Nigeria" by Ben Belton, MSU/WorldFish.
More info and recording of this webinar:
https://bit.ly/COVID-FVC
Webinar: COVID-19 risk and food value chains (presentation 2)IFPRI-PIM
Presentation "COVID-19 risk and food value chains: Insights from India" by Sudha Narayanan, Indira Gandhi Institute of Development Research.
More info and full recording of this webinar:
https://bit.ly/COVID-FVC
Webinar: COVID-19 risk and food value chains (presentation 1)IFPRI-PIM
Presentation "Food Consumption and Food Security during the COVID-19 Pandemic in Addis Ababa" by Kalle Hirvoven, International Food Policy Research Institute (IFPRI).
PUBLISHING AGRICULTURAL DEVELOPMENT RESEARCH IN SOCIAL SCIENCE JOURNALS:WRITI...IFPRI-PIM
This webinar, the 3rd and final in the series “Publishing Agricultural Development Research in Social Science Journals”, focuses on the specifics of the referee process—how (and why) to do good reviews, and how to respond to referee comments received. The session includes sample “revise and resubmit” reviews.
More info about the series: https://bit.ly/PublishingAgRes
PUBLISHING AGRICULTURAL DEVELOPMENT RESEARCH IN SOCIAL SCIENCE JOURNALS: Advi...IFPRI-PIM
This webinar, the 2nd in the series “Publishing Agricultural Development Research in Social Science Journals”, offers a panel discussion amongst editors or associate editors of leading journals, addressing what they look for in submissions, how to avoid “desk rejections”, how to handle reviews, proofing, and publicizing articles.
More info about the series and full recordings: https://bit.ly/PublishingAgRes
Nutraceutical market, scope and growth: Herbal drug technologyLokesh Patil
As consumer awareness of health and wellness rises, the nutraceutical market—which includes goods like functional meals, drinks, and dietary supplements that provide health advantages beyond basic nutrition—is growing significantly. As healthcare expenses rise, the population ages, and people want natural and preventative health solutions more and more, this industry is increasing quickly. Further driving market expansion are product formulation innovations and the use of cutting-edge technology for customized nutrition. With its worldwide reach, the nutraceutical industry is expected to keep growing and provide significant chances for research and investment in a number of categories, including vitamins, minerals, probiotics, and herbal supplements.
Richard's entangled aventures in wonderlandRichard Gill
Since the loophole-free Bell experiments of 2020 and the Nobel prizes in physics of 2022, critics of Bell's work have retreated to the fortress of super-determinism. Now, super-determinism is a derogatory word - it just means "determinism". Palmer, Hance and Hossenfelder argue that quantum mechanics and determinism are not incompatible, using a sophisticated mathematical construction based on a subtle thinning of allowed states and measurements in quantum mechanics, such that what is left appears to make Bell's argument fail, without altering the empirical predictions of quantum mechanics. I think however that it is a smoke screen, and the slogan "lost in math" comes to my mind. I will discuss some other recent disproofs of Bell's theorem using the language of causality based on causal graphs. Causal thinking is also central to law and justice. I will mention surprising connections to my work on serial killer nurse cases, in particular the Dutch case of Lucia de Berk and the current UK case of Lucy Letby.
Deep Behavioral Phenotyping in Systems Neuroscience for Functional Atlasing a...Ana Luísa Pinho
Functional Magnetic Resonance Imaging (fMRI) provides means to characterize brain activations in response to behavior. However, cognitive neuroscience has been limited to group-level effects referring to the performance of specific tasks. To obtain the functional profile of elementary cognitive mechanisms, the combination of brain responses to many tasks is required. Yet, to date, both structural atlases and parcellation-based activations do not fully account for cognitive function and still present several limitations. Further, they do not adapt overall to individual characteristics. In this talk, I will give an account of deep-behavioral phenotyping strategies, namely data-driven methods in large task-fMRI datasets, to optimize functional brain-data collection and improve inference of effects-of-interest related to mental processes. Key to this approach is the employment of fast multi-functional paradigms rich on features that can be well parametrized and, consequently, facilitate the creation of psycho-physiological constructs to be modelled with imaging data. Particular emphasis will be given to music stimuli when studying high-order cognitive mechanisms, due to their ecological nature and quality to enable complex behavior compounded by discrete entities. I will also discuss how deep-behavioral phenotyping and individualized models applied to neuroimaging data can better account for the subject-specific organization of domain-general cognitive systems in the human brain. Finally, the accumulation of functional brain signatures brings the possibility to clarify relationships among tasks and create a univocal link between brain systems and mental functions through: (1) the development of ontologies proposing an organization of cognitive processes; and (2) brain-network taxonomies describing functional specialization. To this end, tools to improve commensurability in cognitive science are necessary, such as public repositories, ontology-based platforms and automated meta-analysis tools. I will thus discuss some brain-atlasing resources currently under development, and their applicability in cognitive as well as clinical neuroscience.
A brief information about the SCOP protein database used in bioinformatics.
The Structural Classification of Proteins (SCOP) database is a comprehensive and authoritative resource for the structural and evolutionary relationships of proteins. It provides a detailed and curated classification of protein structures, grouping them into families, superfamilies, and folds based on their structural and sequence similarities.
Richard's aventures in two entangled wonderlandsRichard Gill
Since the loophole-free Bell experiments of 2020 and the Nobel prizes in physics of 2022, critics of Bell's work have retreated to the fortress of super-determinism. Now, super-determinism is a derogatory word - it just means "determinism". Palmer, Hance and Hossenfelder argue that quantum mechanics and determinism are not incompatible, using a sophisticated mathematical construction based on a subtle thinning of allowed states and measurements in quantum mechanics, such that what is left appears to make Bell's argument fail, without altering the empirical predictions of quantum mechanics. I think however that it is a smoke screen, and the slogan "lost in math" comes to my mind. I will discuss some other recent disproofs of Bell's theorem using the language of causality based on causal graphs. Causal thinking is also central to law and justice. I will mention surprising connections to my work on serial killer nurse cases, in particular the Dutch case of Lucia de Berk and the current UK case of Lucy Letby.
Earliest Galaxies in the JADES Origins Field: Luminosity Function and Cosmic ...Sérgio Sacani
We characterize the earliest galaxy population in the JADES Origins Field (JOF), the deepest
imaging field observed with JWST. We make use of the ancillary Hubble optical images (5 filters
spanning 0.4−0.9µm) and novel JWST images with 14 filters spanning 0.8−5µm, including 7 mediumband filters, and reaching total exposure times of up to 46 hours per filter. We combine all our data
at > 2.3µm to construct an ultradeep image, reaching as deep as ≈ 31.4 AB mag in the stack and
30.3-31.0 AB mag (5σ, r = 0.1” circular aperture) in individual filters. We measure photometric
redshifts and use robust selection criteria to identify a sample of eight galaxy candidates at redshifts
z = 11.5 − 15. These objects show compact half-light radii of R1/2 ∼ 50 − 200pc, stellar masses of
M⋆ ∼ 107−108M⊙, and star-formation rates of SFR ∼ 0.1−1 M⊙ yr−1
. Our search finds no candidates
at 15 < z < 20, placing upper limits at these redshifts. We develop a forward modeling approach to
infer the properties of the evolving luminosity function without binning in redshift or luminosity that
marginalizes over the photometric redshift uncertainty of our candidate galaxies and incorporates the
impact of non-detections. We find a z = 12 luminosity function in good agreement with prior results,
and that the luminosity function normalization and UV luminosity density decline by a factor of ∼ 2.5
from z = 12 to z = 14. We discuss the possible implications of our results in the context of theoretical
models for evolution of the dark matter halo mass function.
What is greenhouse gasses and how many gasses are there to affect the Earth.moosaasad1975
What are greenhouse gasses how they affect the earth and its environment what is the future of the environment and earth how the weather and the climate effects.
Professional air quality monitoring systems provide immediate, on-site data for analysis, compliance, and decision-making.
Monitor common gases, weather parameters, particulates.
Change and Rigidity in Youth Employment Patterns in Malawi
1. 1
Change and Rigidity in Youth
Employment Patterns in Malawi
PIM Workshop on Rural Transformation
Vancouver
28 July 2018
Bob Baulch, Todd Benson, Alvina Erman*,
and Yanjanani Lifeyo
IFPRI and *World Bank
2. 2
Agriculture in Malawi’s economy
Agriculture contributed 26 percent of Malawi’s
GDP in 2017.
Down from 50 percent of the economy 50 years
ago. Growing production of services.
Malawi is among the 15 most agriculture-
dependent countries in the world
Small manufacturing sector; few non-agricultural
natural resources to exploit
88 percent of those of working age (15 to 64 years)
and employed work in agriculture (2016 IHS)
3. 3
Population growth & education in Malawi
Malawi’s population projected to be 43.1 million
by 2050, up from 19.1 million in 2018
Malawi has one of the youngest age structures in the
world: 45% of population <15 years old
Result is increasing pressure to use all available land
for agriculture
Primary education has been free since 1994
Program has been subject to continual criticism
for poor quality of education provided
But years of education completed for the 15 to 24
year old age-cohort increased from 5.0 in 1998 to
7.3 in 2016
4. 4
Motivation for this study
How have changes in, and the interplay of
these factors, affected the employment
choices of Malawians, particularly for youth?
Do we see some movement of labor out of
agriculture into other sectors?
Are youth central to any changes occurring in
employment patterns in Malawi?
Are Malawi’s youth entering the work force in a
different manner than did previous generations?
5. 5
Analytical approach
Use Malawi Integrated Household Survey data series -
IHS-2 (2004), IHS-3 (2010), & IHS-4 (2016)
Focus is on working-age population (aged 15 to 64 years)
Further distinguish younger youth (15 to 24 years), older youth (25 to 34),
and non-youth (35 to 64)
Three principal analyses
Cross-sectional analysis of employment of working-age population in 2016
Temporal analysis of changes in employment patterns between 2004,
2010, and 2016
Multivariate analysis of determinants of employment and type of
employment in 2016
IHS-2 IHS-3 IHS-4
Sample size, households 11,280 12,271 12,0447
Working age (15 - 64 years of age) sample size, ind. 25,144 27,842 27,475
Survey administration period March 2004 to
March 2005
March 2010 to
March 2011
April 2016 to
April 2017
6. Structure of employment in 2016
Dominance of agriculture for those employed
88 percent of those employed work in agriculture
Over 60 percent of older youth and non-youth work in
agriculture
45% of younger youth are students (so, not economically
active) while 33% work in agriculture
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7. Structural change in employment?
2004 2010 2016
Annual
growth,
2004-16, %
Working age population, ‘000s 5,975 6,871 8.264 2.7
Employed, % share of working age population 76.7 72.8 60.7 0.8
Agriculture, % share of employed 85.3 87.1 87.8 0.7
Industry, % share of employed 5.8 3.2 2.3 -6.8
Services, % share of employed 8.9 9.7 9.9 1.3
Not economically active, % share of working age pop. 8.6 10.1 19.2 9.8
Students, % share of not economically active 13.9 15.7 17.7 4.8
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Services - growth in share of employed
Industry – absolute decline in workers employed
Agriculture – share of workers stable to slightly down
(lower growth than that of working age population)
No strong evidence that process of structural
change in employment now gaining momentum
8. 8
Structural change in employment? –
disaggregated (1)
Agriculture
94 percent of all employed women worked on-farm between 2004 to
2016; 80 percent of men. Stable pattern
No sign of FISP induced changes in agricultural employment
Services
Non-youth especially account for growth in employment in services
Suggests that capital accumulation and work experience, rather than
educational attainment, may be more important driving factors in
movement of labor out of agriculture into services
Industry
Significant drop in employment, despite national accounts data over
period showing performance of sector to be generally positive
9. 9
Structural change in employment? –
disaggregated (2)
Students – Largest jump seen in share of working age
individuals who are students
Particularly among younger youth (ages 15 to 24 years): Share who
are students rose from 35 percent in 2004 to 45 percent in 2016
Reduced share of younger youth who are employed over this period.
But if employed, work on-farm
Puzzle that 2.7 percent growth rate of working age
population is lower than 3.0 percent population growth rate
Some suggestion in data that emigration of male older male youth
from Malawi part of explanation. But only limited data on this.
10. Determinants of employment
10
Examine factors associated with working and
sector of employment at individual level:
Logit followed by Multinomial logit regression
Use different employment
categories than ILO
scheme used earlier
Categories allow for individ-
uals to be employed in
more than one sector (inter-
section in diagram)
Also distinguish informal
(household enterprises) from
formal (wage labor) employ-
ment (not shown in diagram) n=25,384 individuals
Employed in
agriculture
only
Industry
or services
only
Agriculture
and
industry
or
services
Not
economically
active
11. Logit on Labor Force Participation
Males significantly more likely to be
employed or looking for work than females
Younger youth (<24 years) less likely but
older youth (30-34 years) are more likely to
be working than non-youth (35-64 years)
Higher levels of education associated with
higher probabilities of employment
Other northern ethnic groups and residents of
Lower Shire Valley also more likely to be
economically active
11
12. Multinomial logit (MNL) regression
12
Five category dependent variable:
Explanatory variables used in MNL include:
1. Employed in agricultural sector only;
2. Employed both in agricultural sector
and in household enterprise(s) in the
industry or services sectors;
3. Employed both in agricultural sector
and in wage employment in the
industry or services sectors;
4. Only employed in household
enterprise(s) in industry or
services sectors;
5. Only employed for wages in
the industry or services
sector;
o Demographic characteristics,
including youth age ranges;
o Ethnicity;
o Educational attainment,
o Household wealth;
o Agriculture-related factors;
o Physical access to markets; and
o Recent experiences of economic
shocks.
13. 13
Multivariate analysis on employment (1)
Youth:
Up to 24 years, either in agriculture or are not economically active
Those aged 25 to 29 years are in a transitional period in terms of
the nature of their employment
Oldest youth aged 30 to 34 years more likely to be employed in
both agriculture and the non-farm sectors
However, youth are not in the vanguard of those Malawians taking
up employment, whether informal or formal, in the services and
industrial sectors and abandoning agriculture.
Sex: Males dominate employment outside of agriculture
Dependents: dependents within a household, less likely to be
economically active (primarily students) or works outside agriculture
14. 14
MNL results on employment (2)
Education: Greater educational attainment results in much higher
probabilities of working outside of agriculture and in formal, wage-
based employment
Household wealth: Strong association between the level of
household wealth and engagement in non-farm employment.
Land: Larger agricultural landholdings associated with a lower
propensity to be in non-farm wage employment
Market access: strong inverse association between distance to
largest urban centers and whether individual engaged in non-farm
employment.
Shocks: Individuals in communities that experience idiosyncratic
shocks more likely to engage in some non-farm employment
15. 15
Summary of analyses on youth and
employment in Malawi
Little evidence of change in how youth enter the work force:
Pattern of employment of older youth similar to the non-youth
Younger youth extending period remain in school, but generally enter
the work force through agriculture
Structural transformation?
Share of those of working age in agriculture grew from 2004 to 2016.
Increase in share of older youth and non-youth in services, but
decline in industry.
Only faint indications of structural transformation processes
The structure of employment in Malawi remains dominated by
agriculture, as it has been for generations
16. 16
Policy implications
Maintain level of investments in education – Good returns,
both socially and individually
But the now better trained Malawians not finding good jobs
Such jobs needed to pull people out of farming and to grow and
diversify the economy.
Public investment needed to supply such job opportunities
Provide incentives to private sector for the supply of such jobs
Foreign direct investment likely a principal channel for providing the
associated technology and creating demand for such jobs
To attract such investment requires good transport infrastructure,
reliable energy supplies, and significant urban development
Agriculture probably will remain at core of economy
So need to continue to invest to increase agricultural productivity
Growth in industry and services likely to be most readily achieved by
strengthening linkages of those sectors to a vibrant agricultural sector
19. Population Projections for Malawi
19
1964 2018 2050
Population
(estimated)
3,963,423 18,860,963 43,154,607
Source: https://populationpyramid.net/malawi/2018/
20. Population Pyramid for Malawi, 2017
20
Source: https://populationpyramid.net/malawi/2017/
Editor's Notes
Describe the talk:
Based on a draft chapter for an edited OUP book produced by IFPRI on youth and employment in developing countries. Structural transformation of national economies is what motivates the book, examining such processes from changing patterns in labor force participation.
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Orange bars shows that 60% of older youth (25-34) and non-youth (35-64) work in agriculture
Green bar shows 45% of younger youth are students