Ten-Year Impacts of Burkina Faso’s BRIGHT Program

V. COST-EFFECTIVENESS AND COST-BENEFIT ANALYSIS MATHEMATICA POLICY RESEARCH
The details of the calculation of the monetary benefits of each additional grade are described
in detail in Appendix D. To perform these calculations, we examine the relationship between
the highest grade achieved and earnings using data from the National Household Surveys in
Burkina Faso conducted in 1994, 1998, 2003, 2010, and 2014. This provides estimates of the
increase in earnings per grade level of between 7 and 16 percent. As a result, we consider
two cases: a high-return case in which the returns to an additional grade are 16 percent and a
low-return case in which the returns are 7 percent. 50
10. Finally, we assume a discount rate of 10 percent to estimate the value of costs and benefits
at the start of the intervention in 2006 to calculate the benefit-cost ratio.
We use these assumptions to proceed in three steps. First, unlike with the cost-effectiveness
analysis, we estimate the costs over the full 40-year life span of the BRIGHT schools. Second,
we estimate how long children in the past and future have been exposed to BRIGHT during this
40-year period. Finally, we use this information to calculate the change in earnings due to this
exposure. The total value of the earnings then provides our estimate of the benefits of the
BRIGHT program.
It is important to note that although we calculate the benefits using only increases in
earnings, the benefits to BRIGHT are likely more expansive. Better-educated individuals are
more productive, but they may also be better able to take care of their own health, take care of
their children, and educate their children. However, although these benefits are possible and
could be important, they could also be small. Also, we cannot be certain that these potential
benefits would accrue from this intervention in the Burkinabé context without further evidence.
Finally, research simply does not yet exist that allow us to convert these possible gains into a
monetary value. As a result, one should consider these estimates to be a lower bound on the true
benefits of the BRIGHT program.
Starting with the costs, we estimate the cost of the BRIGHT and the traditional government
schools for each year in the 40-year period from 2006 to 2045. We follow the same procedure for
calculating the costs of both BRIGHT and traditional government schools. After the initial fixed
costs of building school complexes are incurred in 2006, cost for teacher salaries and take-home
rations are incurred annually in each of the 40 years. Also, periodic maintenance costs are
incurred every five years after the start of the intervention, in 2010, 2015, and so on. Then, as we
did for the costs in the cost-effectiveness analysis, we use these costs to construct the costs by
year for selected and unselected villages at the discontinuity, based on the fraction of villages
with a BRIGHT school, a traditional government school, or neither. In other words, the
differential cost for a given year is estimated as the difference in costs of schools in villages
selected for BRIGHT and in villages not selected, at the cutoff point. We then take the costs for
each year and construct the net present value of the costs in 2006 for both the high-cost and low-
50
Choosing this large range of estimates for the returns to schooling allows us to explore the sensitivity of the
analysis to several assumptions: First, it captures uncertainty in the estimation of this parameter. Second, it captures
uncertainty in whether or not the highest grade achieved captures the full academic benefit of being in a selected
village. And third, we also capture uncertainty related to the possible biases inherent in the Mincer estimates used to
estimate the returns to schooling described in Section C.2 of Appendix D.
62