Suchergebnisse

Will the biotechnology revolution improve the living standards of poor rural farmers in developing countries? The Green Revolution showed that the economic and social structures in a society play a larger role in determining how innovations affect people than the scientific content of the innovations. Social and economic structures within developing countries and within the international community will determine what crops are enhanced using biotechnology, which traits of the crops are altered, and how the new seeds and plantlets will be distributed. The fact that the private sector is taking the lead in biotechnology rather than public sector institutions has important implications for developing countries. Crops with high public benefits will not be developed by the private sector if they are not profitable. The public sector and nonprofit sector, in collaboration with the private sector, have important roles to play to ensure that the benefits of biotechnology are available to the poor in developing countries.

1. Einleitung -- 2. Die Beschreibung des Verfahrens und dessen theoretische Grundlagen -- 3. Der Transportvorgang in der Trennscheibe -- 4. Die Versuchsergebnisse der Trennung bei kontinuierlicher Entnahme und Vergleich mit der Theorie für den Gleichgewichtstrennfaktor -- 5. Die Versuchsapparatur -- 6. Versuchsdurchführung und Meßmethode -- 7. Zusammenfassung -- 8. Literaturverzeichnis -- Abbildungsanhang.

Bangladesh's Food for Education Program (FFE), which provided free food to poor families if their children attended primary school, was successful in increasing children's school enrollment, especially for girls. However, this success came at a price as class sizes increased. This paper uses a rich data set that includes school achievement test scores, information on schools, and household data to explore the impact of FFE on the quality of education. The analysis focuses on the impact of FFE on the achievement test scores of students who did not receive benefits. The authors find evidence for a negative impact of FFE on the test scores of non-beneficiary students through peer effects rather than through classroom crowding effects. (DSE/GIGA)

The low contraceptive prevalence rate and the existence of unmet demand for family planning services present a challenge for parties involved in family planning research in Tanzania. The observed situation has been explained by the demand-side variables such as socioeconomic characteristics and cultural values that maintain the demand for large families. A small, but growing body of research is examining the effect of supply-side factors such as quality of care of family planning services on the demand for contraceptives. This paper analyses the demand and supply factors determining contraceptive use in Tanzania using the Tanzania Service Availability Survey (1996) and the Tanzania Demographic and Health Survey (1996) data sets. The results show that access to family planning services and quality of care of services are important determinants of contraceptive use in Tanzania even after controlling for demand-side factors.

This study aims to analyze and decompose the gap between White and non-White students' test scores observed in the Brazilian National Evaluation System of Basic Education (SAEB)—2015. To do so, proficiency equations were estimated for each student race group (White, Brown, Black, and Indigenous) using the recentered influence function method, which generalizes the Oaxaca–Blinder decomposition to any point in the grade distribution. The proficiency of White students is higher than the other groups of students, and this difference increases throughout the distribution. Black students exhibit the lowest average test score, behind the Indigenous and then the Brown students. At the lower and middle levels of the math test score distribution, the racial gap is mainly due to the characteristics effect, which represents the part of the proficiency differential that is explained by the differences in observable characteristics of students. However, the gap at the upper level of grade distribution is mainly due the structural effect, which results from non-observable issues, such as discrimination and stereotype threats.