How good are ex ante program evaluation techniques? : the case of school enrollment in PROGRESA /
This paper evaluates a microsimulation technique by comparing the simulated outcome of a program with its actual effect. The ex ante evaluation is carried out for a conditional cash transfer program, where poor households were given money if the children attended school. A model of occupational choi...
Clasificación: | Libro Electrónico |
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Autor principal: | |
Autor Corporativo: | |
Formato: | Electrónico eBook |
Idioma: | Inglés |
Publicado: |
Washington, D.C. :
International Monetary Fund,
©2009.
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Colección: | IMF working paper ;
WP/09/187. |
Temas: | |
Acceso en línea: | Texto completo |
Tabla de Contenidos:
- Cover Page; Title Page; Copyright Page; Contents; I. Introduction; II. Ex Ante Evaluation:Theory; A.A Model of Occupational Choice; B. Estimation and Identification; C. Impact Simulation; III. Ex Ante Evaluation: Results; Table 1: Weekly Earnings and Per Capita Household Income; Table 2: Reported Status; Table 3: Sample Means; A. Estimation of the Earnings Vector; Table 4: Estimation of Earnings Equation; Table 5: Actual and Imputed Earnings; B. Estimation of the Choice Model; Table 6: Estimation of the Multinomial Logit Model; Table 7: Accuracy of Model Prediction (K=1).
- Table 8: Estimation of Structural Parameters (K=1)Table 9: Accuracy of Model Prediction (K 0.5); C. Impact Simulation; Table 10: PROGRESA Transfer Scheme; Table 11: Estimated Transition Matrix; IV. The Benchmark: Ex post Analysis; A. Pre-Program Differences; Table 12: Pre-Program Differences: Boys; Table 13: Pre-Program Differences: Girls; B. Difference Estimation; Table 14: Difference Estimator: Boys; Table 15: Difference Estimator: Girls; Figure 1: Enrollment Ratio: Actual Effect of PROGRESA, D and DD Estimator; V. Comparison of Results and Discussion.
- Figure 2: Simulated effect and D estimateTable 16: Simulation, D and DD Estimates, and Sensitivity to K; Table 17: Transition to Secondary School; VI. Concluding Remarks; VIII. Appendix; A. Key Elements of PROGRESA; B. Data Description; C. Method for Drawing Choice-consistent Residuals; D. Bootstrap Mechanism; VII. References; Footnotes.