Economic impacts of professional training in the informal sector : the case of the labor force training program in Cote d'Ivoire

The authors address the economic impact of the labor force training program (PAFPA) developed for the informal sector in Côte d'Ivoire. The data contain a subsample of the participants in the agricultural sector, tailoring sector, and the electronics sector, and a comparable control group of nonparticipants. The data have been analyzed using standard program evaluation tools, namely difference-in-difference estimators, in order to detect potential program impacts. The authors find positive economic impacts as a result of training received for some groups, namely women, the agricultural and electronics sectors, firms employing 1-3 individuals, and firms with 10 or more employees.

Lessons Learned on Gender Equality

The purpose of this evaluation study is twofold: Firstly, to compile lessons learned from Danida evaluations, evaluation studies and other evaluation publications, and secondly, to distil a set of recommendations relevant to the roll-out of The Right to a Better Life (2012), more particularly the planned update of Danida's strategy, Gender Equality in Danish Development Cooperation (2004). The evaluation study was carried out between June and September 2013. The methodology is based on a desk review of Danida evaluation publications carried out between 2004 and 2013, and comprises three interconnected phases:1. Screening of a long list of 104 evaluation publications2. Analysis of 26 shortlisted evaluations3. Reporting findings and recommendatio

Atomic Data for Permitted Resonance Lines of Atoms and Ions from H to Si, and S, Ar, Ca and Fe

We list vacuum wavelengths, energy levels, statistical weights, transition probabilities and oscillator strengths for permitted resonance spectral lines of all ions of 18 astrophysically important elements (H through Si, S, Ar, Ca, Fe). Using a compilation of experimental energy levels, we derived accurate wavelengths for 5599 lines of 1828 ground-term multiplets which have gf-values calculated in the Opacity Project. We recalculated the Opacity Project multiplet gf-values to oscillator strengths and transition probabilities of individual lines. For completeness, we added 372 resonance lines of NeI, ArI, FeI and FeII ions which are not covered by the Opacity Project. Intercombination and forbidden lines are not included in the present compilation.Comment: 6 pages of text, latex, 1 figure, 4 tables; tables in ASCII format available at ftp://asta.pa.uky.edu/dima/lines/ or at http://www.pa.uky.edu/~verner/atom.html Accepted by Atomic Data Nucl. Data Table

What factors influence world literacy? is Africa different?

Ninety-five percent of the world’s illiterate people live in developing countries, and about 70 percent are women. Female illiteracy rates are particularly high in Sub-Saharan Africa. In Niger and Burkina Faso, for example, more than 90 percent of women are illiterate. This paper presents a model of literacy. It shows that the main determinants of worldwide literacy are enrollment rates, average years of schooling of adults, and life expectancy at birth. Income has a weak nonlinear effect, negatively affecting literacy until a threshold level of per-capita income of about $2200 a year is reached and positively affecting literacy thereafter. Finally, African countries do not have a significantly higher literacy rate when controlling for other factors.Public Health Promotion,Education Reform and Management,Nonformal Education,PrimaryEducation,Curriculum&Instruction,Primary Education,Gender and Education,Curriculum&Instruction,Education Reform and Management,Nonformal Education

Poverty in the Brazilian Amazon: an assessment of poverty focused on the State of Para

The states in the Brazilian Amazon have made progress in reducing poverty and improving social indicators in the last decade. Despite this progress, the poverty rate in the Amazon is among the highest in Brazil. As of 2000, rural poverty is the greatest challenge. In Par?, not only is the headcount poverty rate of 58.4 percent in rural areas more than 55 percent higher than headcount poverty in urban areas, but also poverty is much deeper in rural areas. The fall in infant mortality and adult illiteracy corroborate the improvement in measured income poverty. Census data from 2000 and 1991 reveal that more people left Par? than came to live in the state during the 1970s, the opposite of the 1980s. In 2000, the Gini coefficient for Par?, as in the Amazon as a whole, was 0.60. The poverty profile reveals that indigenous peoples experience a higher poverty incidence than other groups. Census 2000 data reveal that living in rural areas in Par? does not by itself affect the probability of being poor. Individual and household characteristics are more important than geographical location. The largest statistical differences in poverty reduction between rural and urban areas are found in the effect of education, sector of employment, gender, and family size. PNAD data from 2001 reveal that living in urban areas in Par? does not by itself affect the probability of falling below the poverty line in urban areas in Brazil. The strongest poverty correlates are education, experience, race, rural location, gender, and labor market association.Health Economics&Finance,Public Health Promotion,Health Monitoring&Evaluation,Environmental Economics&Policies,Health Indicators,Achieving Shared Growth,Environmental Economics&Policies,Health Economics&Finance,Health Monitoring&Evaluation,Poverty Assessment

Labor markets in rural and urban Haiti--based on the first household survey for Haiti

This paper addresses labor markets in Haiti, including farm and nonfarm employment and income generation. The analyses are based on the first Living Conditions Survey of 7,186 households covering the whole country and representative at the regional level. The findings suggest that four key determinants of employment and productivity in nonfarm activities are education, gender, location, and migration status. This is emphasized when nonfarm activities are divided into low-return and high-return activities. The wage and producer income analyses reveal that education is key to earning higher wages and incomes. Moreover, producer incomes increase with farm size, land title, and access to tools, electricity, roads, irrigation, and other farm inputs.Rural Poverty Reduction,Population Policies,,Rural Development Knowledge&Information Systems

Rural poor in rich rural areas : poverty in rural Argentina

Rural poverty remains a crucial part of the poverty picture in Argentina. This paper used a rural dataset collected by the World Bank in 2003. Findings show that extreme income poverty in rural areas reached 39 percent of the people or 200,000-250,000 indigent families. These families tend to: be large, and young, and to escape from poverty as they mature and children leave the household (life cycle); live largely in dispersed areas where basic service provision is often weak and delivery is difficult (in particular school attendance beyond 11 years of age falls off very rapidly compared with grouped rural or urban areas); and be more likely to be small landholders than landless laborers. The structure of poverty in rural Argentina shows that larger households are poorer than smaller households, female-headed households are poorer than male-headed households, young households/household heads are poorer than older households/household heads, the poor tend to work more in the informal sector, and a greater share of those engaged in agriculture are poor. However, poverty is by no means strictly an agricultural problem. Furthermore, the deepest poverty is among the poorly educated and young household heads with children. Without interventions to improve their opportunities and assets, their plight is likely to worsen.Rural Poverty Reduction,Population Policies,Achieving Shared Growth,Services&Transfers to Poor