Ten-Year Impacts of Burkina Faso’s BRIGHT Program

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IV: FINDINGS MATHEMATICA POLICY RESEARCH decreases for higher grades after primary school. In addition, we show in results presented in Appendix C (Table C.5) that statistically controlling for either the age of the school or the number of grades offered does not diminish the observed treatment effect on test scores. This indicates that even within villages which have had a school for the same number of years or which offer the same grade levels, the BRIGHT program still causes students in selected villages to have higher test scores. Figure IV.3. Ten-year impacts of BRIGHT on enrollment and test scores, by age 0.6 0.6 Estimated impacts on enrollment 0.5 0.4 0.3 0.2 0.1 0 -0.1 -0.2 0.5 0.4 0.3 0.2 0.1 0 -0.1 -0.2 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 Age Enrollment Test scores Estimated impacts on test scores Sources: Mathematica household survey (2015) and Mathematica school survey (2015). To better understand the effect of the BRIGHT program on different cohorts of students over time, we further disaggregate the estimated impacts on the probability of completing each grade level. Figure IV.4 presents estimated impacts and 95 confidence bands by grade level for three groups: children ages 6 to 12 in 2008, children 6 to 12 in 2015, and teens 13 to 19 years old in 2015. The 2008 survey data showed that the BRIGHT program resulted in more children ages 6 to 12 completing grades 1 through 3, but it had no clear impact on later grades. This was consistent with the fact that BRIGHT I program focused on grades 1 through 3. Following the same cohort of children seven years later (ages 13 to 19 in 2015), the program improved grade completion throughout primary school. This impact steadily declined but remained positive through secondary school. However, there was no significant impact on completion of high school grade levels. For children ages 6 to 12 in 2015, the program had positive effects on grade completion through all primary school grades, but the magnitudes of the effects are substantially smaller than those observed for children of the same age group in 2008. This suggests that the program was less effective at improving grade completion of primary school grade levels for more recent cohorts of children (who were going through primary school after the end of the BRIGHT program) than for earlier cohorts. 44
IV: FINDINGS MATHEMATICA POLICY RESEARCH Figure IV.4. Ten-year impacts of BRIGHT on the probability of grade completion Estimated impact on grade achievement 0.24 0.22 0.2 0.18 0.16 0.14 0.12 0.1 0.08 0.06 0.04 0.02 0 -0.02 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 Probability of studying up to grade X 2008 survey: ages 6-12 2015 survey: ages 6-12 2015 survey: ages 13-19 Sources: Mathematica household survey (2015), Mathematica school survey (2015) and Kazianga et al. (2013). Notes: Children in the 2008 survey are recorded as having completed grade 7 if they are reported to have been enrolled in any secondary school. Our data in 2008 does not allow us to distinguish between having completed individual grades within secondary school. Note that those who were ages 13-19 in the 2015 survey are recorded as having completed grade 13 if they are reported to have been enrolled in any postsecondary schooling. The effect on test scores does seem to be related to grade progression. Figure IV.5 presents estimated impacts on the highest grade achieved by age, along with the test score effects from Figure IV.3 for reference. The two sets of impacts line up very closely for children and youth ages 12–19, implying that the magnitude of the effect on test scores is correlated with the magnitude of the effect on grade progression. This suggests that the improvements in academic skills of students who went through primary school during the BRIGHT program, may—in terms of test scores—be explained by the program causing students to progress farther in school than they otherwise would. In addition, estimates in Appendix Table C.5 further support this conclusion by demonstrating that once we directly control for the highest grade that a student achieves, the difference in test scores between selected and unselected villages was greatly reduced. It is important to note that none of these results provide a definitive explanation. There are other possible explanations for these results that are consistent with the possibility of the BRIGHT program having an effect on students’ test scores through channels other than grade progression, such as through providing a better quality education at each grade level. This may be particularly true for the youngest children, for whom the association between grade progression and test scores is less strong. However, when taken together, the results do strongly 45
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Ten-Year Impacts of Burkina Faso’
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ACKNOWLEDGEMENTS This report is the
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CONTENTS ACRONYMS .................
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TABLES ES.1 ES.2 ES.3 ES.4 ES.5 ES.
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FIGURES I.1 Gross enrollment ratios
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ACRONYMS AMEs - Association de Mèr
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EXECUTIVE SUMMARY The BRIGHT progra
Page 15 and 16: EXECUTIVE SUMMARY MATHEMATICA POLIC
Page 23 and 24: I. INTRODUCTION From 2005 through 2
Page 25 and 26: I. INTRODUCTION MATHEMATICA POLICY
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Page 39 and 40: II. EVALUATION DESIGN AND DATA COLL
Page 51 and 52: III. IMPLEMENTATION SUMMARY Under t
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Page 55 and 56: IV. FINDINGS In this chapter, we pr
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Page 73 and 74: V. COST-EFFECTIVENESS AND COST-BENE
Page 89 and 90: VI. SUMMARY OF FINDINGS AND DISCUSS
Page 95 and 96: REFERENCES Abeberese, Ama Baafra, T
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Page 103 and 104: APPENDIX A STATISTICAL MODEL FOR IM
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Page 107 and 108: APPENDIX B VALIDATION OF REGRESSION
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Page 113 and 114: APPENDIX C ROBUSTNESS OF IMPACT EST
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APPENDIX C MATHEMATICA POLICY RESEA
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APPENDIX D DETAILS ON COST-BENEFIT
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APPENDIX D MATHEMATICA POLICY RESEA
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APPENDIX E SURVEY FORMS
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APPENDIX E MATHEMATICA POLICY RESEA
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APPENDIX E BURKINA FASO MATHEMATICA
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APPENDIX E MATHEMATICA POLICY RESEA
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HOUSEHOLD LISTING FORM Village ID:
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ENROLLMENT MODULE VILLAGE ID: ___ _
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CHILD LABOR MODULE VILLAGE ID: ___
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YOUNG ADULT MODULE VILLAGE ID: ___
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ASSESSMENT CONSENT LANGUAGE: PLEASE
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MATH ASSESSMENT VILLAGE ID: ___ ___
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MATH ASSESSMENT VILLAGE ID: ___ ___
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FRENCH ASSESSMENT VILLAGE ID: ___ _
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FRENCH ASSESSMENT VILLAGE ID: ___ _
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BURKINA FASO SCHOOL INFORMATION PAN
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A: SCHOOL CHARACTERISTICS SC SC9. D
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C: SCHOOL PHYSICAL STRUCTURE SS SS5
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APPENDIX F MATHEMATICA POLICY RESEA
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Ten-Year Impacts of Burkina Faso’s BRIGHT Program

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