Conditional Cash Transfer (CCT) programs are a recent and popular approach in developing countries to improve health and education prospects of poor families through conditional financial incentives. However, due to sub-optimal transfers and administrative difficulties in identifying needy families, many CCT programs suffer from incomplete coverage of needy families and/or low financial efficiencies. De Janvry and Sadoulet (2003) have shown that their targeting method (the DJS method), which uses binary regression models to identify needy families and optimal transfer amounts, can effectively overcome these problems. This dissertation tackles two issues encountered in implementing the DJS method: the need for an appropriate methodology to compare binary models, and the need to develop binary models with high external validity. For targeting of CCT programs, binary models need to be analyzed comprehensively beyond the overall goodness-of-fit. For example, policy makers may need to know the rates of false positive and false negative predictions of various models and choose the most appropriate model for given policy priorities.
Die Inhaltsangabe kann sich auf eine andere Ausgabe dieses Titels beziehen.
Dr. Suguru Mizunoya has been worked for various international organisations including the World Bank, the UNICEF, the ILO focusing on the economic and financial analysis of social policies including education, social protection, and social security. Currently, he is the Chief of the Education and Young People Section of UNICEF Kenya.
„Über diesen Titel“ kann sich auf eine andere Ausgabe dieses Titels beziehen.
Anbieter: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Deutschland
Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Conditional Cash Transfer (CCT) programs are a recent and popular approach in developing countries to improve health and education prospects of poor families through conditional financial incentives. However, due to sub-optimal transfers and administrative difficulties in identifying needy families, many CCT programs suffer from incomplete coverage of needy families and/or low financial efficiencies. De Janvry and Sadoulet (2003) have shown that their targeting method (the DJS method), which uses binary regression models to identify needy families and optimal transfer amounts, can effectively overcome these problems. This dissertation tackles two issues encountered in implementing the DJS method: the need for an appropriate methodology to compare binary models, and the need to develop binary models with high external validity. For targeting of CCT programs, binary models need to be analyzed comprehensively beyond the overall goodness-of-fit. For example, policy makers may need to know the rates of false positive and false negative predictions of various models and choose the most appropriate model for given policy priorities. 232 pp. Englisch. Bestandsnummer des Verkäufers 9783846548608
Anzahl: 2 verfügbar
Anbieter: moluna, Greven, Deutschland
Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Mizunoya SuguruDr. Suguru Mizunoya has been worked for various international organisations including the World Bank, the UNICEF, the ILO focusing on the economic and financial analysis of social policies including education, social p. Bestandsnummer des Verkäufers 5498305
Anzahl: Mehr als 20 verfügbar
Anbieter: Books Puddle, New York, NY, USA
Zustand: New. Bestandsnummer des Verkäufers 26134593733
Anzahl: 4 verfügbar
Anbieter: Majestic Books, Hounslow, Vereinigtes Königreich
Zustand: New. Print on Demand. Bestandsnummer des Verkäufers 141689626
Anzahl: 4 verfügbar
Anbieter: Biblios, Frankfurt am main, HESSE, Deutschland
Zustand: New. PRINT ON DEMAND. Bestandsnummer des Verkäufers 18134593743
Anzahl: 4 verfügbar
Anbieter: preigu, Osnabrück, Deutschland
Taschenbuch. Zustand: Neu. Improving Targeting of Conditional Cash Transfer Programs | Through Posterior Simulation and Multilevel Modeling | Suguru Mizunoya | Taschenbuch | 232 S. | Englisch | 2011 | LAP LAMBERT Academic Publishing | EAN 9783846548608 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Bestandsnummer des Verkäufers 106724446
Anzahl: 5 verfügbar
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Conditional Cash Transfer (CCT) programs are a recent and popular approach in developing countries to improve health and education prospects of poor families through conditional financial incentives. However, due to sub-optimal transfers and administrative difficulties in identifying needy families, many CCT programs suffer from incomplete coverage of needy families and/or low financial efficiencies. De Janvry and Sadoulet (2003) have shown that their targeting method (the DJS method), which uses binary regression models to identify needy families and optimal transfer amounts, can effectively overcome these problems. This dissertation tackles two issues encountered in implementing the DJS method: the need for an appropriate methodology to compare binary models, and the need to develop binary models with high external validity. For targeting of CCT programs, binary models need to be analyzed comprehensively beyond the overall goodness-of-fit. For example, policy makers may need to know the rates of false positive and false negative predictions of various models and choose the most appropriate model for given policy priorities. Bestandsnummer des Verkäufers 9783846548608
Anzahl: 1 verfügbar
Anbieter: Revaluation Books, Exeter, Vereinigtes Königreich
Paperback. Zustand: Brand New. 232 pages. 8.66x5.91x0.53 inches. In Stock. Bestandsnummer des Verkäufers __384654860X
Anzahl: 1 verfügbar
Anbieter: Revaluation Books, Exeter, Vereinigtes Königreich
Paperback. Zustand: Brand New. 232 pages. 8.66x5.91x0.53 inches. In Stock. Bestandsnummer des Verkäufers 384654860X
Anzahl: 1 verfügbar