Ten-Year Impacts of Burkina Faso’s BRIGHT Program

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V. COST-EFFECTIVENESS AND COST-BENEFIT ANALYSIS MATHEMATICA POLICY RESEARCH Once we have the increased earnings for each cohort, we add up the additional earnings gained by all cohorts in the given year. So, for example, in 2009, only the 1994 cohort experiences an increase in earnings, whereas in 2010, the 1994 and 1995 cohorts are earning more. We then use the 10 percent discount rate to calculate the net present value of these earnings (as we did for the costs in each year); we present them in the second row of panels A and B in Table V.8. Finally, we can compare the costs and benefits. First, we calculate the net benefits by subtracting the costs from the benefits. These are presented in the third row of each panel. The relative costs and benefits can also be compared by dividing the benefits by the costs to produce the benefit-cost ratio, which is presented in the fourth row of each panel. If the benefits exceed the costs, the net benefits are positive and the benefit-cost ratio is greater than one. Based on these estimates, benefits do not exceed costs for any of the scenarios. Table V.8. Benefit-cost estimates of the BRIGHT program per village Benefit scenarios Cost scenarios High return to schooling Low return to schooling Panel A: High traditional government school cost Total six-year marginal benefits in 2006 $86,959 $37,607 Total six-year marginal costs in 2006 $126,742 $126,742 Net benefits a -$40,783 -$89,135 Benefit-cost ratio b 0.68 0.30 ERR c 8% 4% Panel B: Low traditional government school cost Total six-year marginal benefits in 2006 $86,959 $37,607 Total six-year marginal costs in 2006 $194,650 $194,650 Net benefits a -$108,691 -$157,043 Benefit-cost ratio b 0.44 0.19 ERR c 6% 3% Note: The estimates of benefits and costs are carried out at the village level, which was the level of implementation of the BRIGHT program. a Calculated by subtracting total costs from total benefits. b Calculated by dividing total benefits by total costs. c This is the discount rate at which the net benefits are equal to zero. As explained in Section A of this chapter, these estimates assume a fixed discount rate. A different way to calculate the relative gain from the project is to determine the discount rate that is large enough that the net benefits are equal to zero. This is the discount rate at which the net present value of the costs equals the benefits. To do this, we take the costs and benefits for each year calculated for the benefit-cost ratio as we describe above, but instead of using a discount rate of 10, we determine the discount rate that balances the net present value of each. These values are provided in the fifth row of both panels in Table V.8. The estimated ERRs range between 3 percent and 8 percent. When we assume that the return to schooling is high, the ERRs are 8 percent in the high-cost traditional government schools scenario and 6 percent in the low-cost traditional school scenario. For the assumption of 64
V. COST-EFFECTIVENESS AND COST-BENEFIT ANALYSIS MATHEMATICA POLICY RESEARCH low returns to schooling, the respective returns are 4 percent for the high-cost scenario and 3 percent for the low-cost traditional government school scenario. Thus, the ERR estimates are higher when the returns to schooling is high irrespective of the cost-scenario. As described earlier, the ERR can be interpreted as the return to investments of a program; if the ERR is too low, the program may be deemed insufficiently productive to justify. For developing countries, the MCC considers 10 percent the threshold during the planning phase to determine whether its investments in a compact country will yield sufficient returns for the country’s citizens (MCC 2013). These results suggest that the additional costs spent to construct BRIGHT schools in selected villages, rather than the schools available in unselected villages, may not yield returns above MCC’s threshold. However, the estimated ERRs are just below the threshold under the high returns to schooling assumptions in the high-cost scenario. Unfortunately, we do not know the true value of an additional grade level, but given the other values in the estimates, the return to schooling would have to be at least 21.78 percent to yield an ERR of at least 10 percent in the high-cost scenario and at least 33.15 percent in the low-cost scenario. 65
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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
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EXECUTIVE SUMMARY MATHEMATICA POLIC
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I. INTRODUCTION From 2005 through 2
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I. INTRODUCTION MATHEMATICA POLICY
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I: INTRODUCTION MATHEMATICA POLICY
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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
Page 57 and 58: IV: FINDINGS MATHEMATICA POLICY RES
Page 73 and 74: V. COST-EFFECTIVENESS AND COST-BENE
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Page 89 and 90: VI. SUMMARY OF FINDINGS AND DISCUSS
Page 95 and 96: REFERENCES Abeberese, Ama Baafra, T
Page 97 and 98: REFERENCES MATHEMATICA POLICY RESEA
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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Page 125 and 126: 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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