Thanks for sharing this work! It’s very interesting to see how you do this and good to see Monte Carlo in action.
The cost-effectiveness of subsidised solar lights comes out as very high, which invites scrutiny. If solar lamps are such a good deal, why don’t people buy them at full price (in which case cash transfers would be better)? Lack of cash on hand could be a barrier, but a 35% subsidy would presumably only make a difference for a small subset of people.
You clearly signpost this as a “simplified” calculation, so this is slightly nitpicky. A few things that may be overly optimistic in the model:
NBaum is based on the amount households would spend on batteries etc. Is this really what people would do? Seems crazy that people would pay $40/year or 20% of one person’s income on batteries. Also, it seems likely that there’s a strong correlation between income and amount spent on batteries and other lighting sources. The poorest people may be more likely to burn wood for light or spend longer in the dark, and hence would save less money by having a solar lamp
This $200/year income is pivotal to your cost-effectiveness, so ideally this should be modelled with uncertainty in the Monte Carlo. There may be correlational issues here also, where the people who can afford the subsidised lamp are less likely to be among the poorest.
Fattrib seems high. Could the subsidies really increase the chance of uptake by 30-90%?
You don’t model the out-of-pocket cost to the recipient (as far as I can tell)
NPVsum of 4.5 − 11 may also be high. Do the lamps have a track record of lasting a long time, especially in low-tech areas? In a more complex model I would also seek to account for the chance that the lamp becomes obsolete, for example if the area gets access to electricity. Electrification in Africa has been slow, but there is at least a push to expand access.
You’re welcome to interpret my questions as hypothetical—no need to fully justify everything about your organisation!
I’d be willing to help you build this into a slightly more complex model in Dagger if you like.
Hi Stan: Thanks for the great comments and questions.
You are completely correct on noting that I need to subtract the cost that the customer pays from the present value net benefits. I have edited the post to incorporate that correction.
BUT the benefits of the solar lights is still very high, and therefore it continues to invite scrutiny.
Trying to address your other points:
THE key reason, the solar lights from our intervention produce benefits that are so much higher for other solar lights, is because, we use a battery technology that is currently not used at all in solar lighting systems because it is quite a bit more expensive than other battery technologies. The technology is lithium titanate battery chemistry. And the cycle-life of that battery tech is about 10 TIMES longer than lithium ion batteries and lead-acid batteries which dominate the market.
If you look at the “Rechargeable characteristics” at:
You will see that regular lithium ion which is listed as lithium cobalt-oxide has a cycle life of 500 to 1000 cycles, while lithium titanate has a cycle life of 6,000 to 10,000 cycles.
BTW, we are currently installing subsidized small solar lighting systems to about 1000 to 2000 household per year.
The much much longer cycle life allows for a much more long-lasting solar light, which is what produces the huge benefit. One expects the market to normally equilibrate where the benefits approximately equal the cost. So perhaps it is not surprising if you introduce a technology into the market which lasts 10 times longer than the current market equilibrium, and then subsidize the cost so that the price is about the same as the low-quality technology, then the net benefit is 8 times the cost of the old technology, which is what our analysis indicates.
As for people getting access to electricity and making the lights obsolete. In Malawi, where we work, this is pretty unlikely. Many people do have power lines nearby, but people use so little electricity, and the cost of connecting is so high, that very few people connect to the grid. And the electric company does not like connecting folks and may take over a year to satisfy a request for a connection even when someone pushes hard to have one. That is because the cost of connecting and serving low-use customers to the grid is subsidized, and the national electric company is often having budget problems.
Looking at World Bank statistics, perhaps this dynamic is working at a larger scale in Africa. For example, if we look at the World Bank data for electricity access in rural SubSaharan Africa (SSA):
We see that access has increased from 12% to 30% from the year 2000 to 2021 in rural SSA. I think it is safe to say that more than half of rural SSA will still be largely without electricity access by 2030.
This is evidence that it is fairly likely that hundreds of millions of rural Africans will be able to benefit from more beneficial off-grid solar lighting for several decades to come.
Addressing some of the other points.
Re: the amount people spend on batteries and cell phone charging. We have done surveys. See:
I have discussed with people in village in Malawi how crazy it is that they spend so much on batteries. This argument makes it pretty easy to market the subsidized solar systems. But people live very hand-to-mouth in rural Malawi. So they will spend to buy something every week rather than invest to reduce a cost if the investment takes more than six months or a year to pay back.
I agree that the $200 income should be modeled with the Monte Carlo. But we can also target the subsidies to areas where incomes are lower. So the analysis indicates in my mind that the subsidies should be targeted to households that have incomes of $200 or less.
We do need to do more work assuring that the lighting systems are guaranteed to last 5 to 15 years, but from an engineering perspective, there is no reason the system cannot last that long given the battery we are using. The remaining engineering issue is going to be how to make sure all of the other parts are very durable, or very cheap and easy to replace.
Thanks again. I hope that answers most of your questions and concerns.
Thanks for sharing this work! It’s very interesting to see how you do this and good to see Monte Carlo in action.
The cost-effectiveness of subsidised solar lights comes out as very high, which invites scrutiny. If solar lamps are such a good deal, why don’t people buy them at full price (in which case cash transfers would be better)? Lack of cash on hand could be a barrier, but a 35% subsidy would presumably only make a difference for a small subset of people.
You clearly signpost this as a “simplified” calculation, so this is slightly nitpicky. A few things that may be overly optimistic in the model:
NBaum is based on the amount households would spend on batteries etc. Is this really what people would do? Seems crazy that people would pay $40/year or 20% of one person’s income on batteries. Also, it seems likely that there’s a strong correlation between income and amount spent on batteries and other lighting sources. The poorest people may be more likely to burn wood for light or spend longer in the dark, and hence would save less money by having a solar lamp
This $200/year income is pivotal to your cost-effectiveness, so ideally this should be modelled with uncertainty in the Monte Carlo. There may be correlational issues here also, where the people who can afford the subsidised lamp are less likely to be among the poorest.
Fattrib seems high. Could the subsidies really increase the chance of uptake by 30-90%?
You don’t model the out-of-pocket cost to the recipient (as far as I can tell)
NPVsum of 4.5 − 11 may also be high. Do the lamps have a track record of lasting a long time, especially in low-tech areas? In a more complex model I would also seek to account for the chance that the lamp becomes obsolete, for example if the area gets access to electricity. Electrification in Africa has been slow, but there is at least a push to expand access.
You’re welcome to interpret my questions as hypothetical—no need to fully justify everything about your organisation!
I’d be willing to help you build this into a slightly more complex model in Dagger if you like.
Thanks again for sharing.
Hi Stan: Thanks for the great comments and questions.
You are completely correct on noting that I need to subtract the cost that the customer pays from the present value net benefits. I have edited the post to incorporate that correction.
BUT the benefits of the solar lights is still very high, and therefore it continues to invite scrutiny.
Trying to address your other points:
THE key reason, the solar lights from our intervention produce benefits that are so much higher for other solar lights, is because, we use a battery technology that is currently not used at all in solar lighting systems because it is quite a bit more expensive than other battery technologies. The technology is lithium titanate battery chemistry. And the cycle-life of that battery tech is about 10 TIMES longer than lithium ion batteries and lead-acid batteries which dominate the market.
If you look at the “Rechargeable characteristics” at:
https://en.wikipedia.org/wiki/Comparison_of_commercial_battery_types
You will see that regular lithium ion which is listed as lithium cobalt-oxide has a cycle life of 500 to 1000 cycles, while lithium titanate has a cycle life of 6,000 to 10,000 cycles.
BTW, we are currently installing subsidized small solar lighting systems to about 1000 to 2000 household per year.
The much much longer cycle life allows for a much more long-lasting solar light, which is what produces the huge benefit. One expects the market to normally equilibrate where the benefits approximately equal the cost. So perhaps it is not surprising if you introduce a technology into the market which lasts 10 times longer than the current market equilibrium, and then subsidize the cost so that the price is about the same as the low-quality technology, then the net benefit is 8 times the cost of the old technology, which is what our analysis indicates.
As for people getting access to electricity and making the lights obsolete. In Malawi, where we work, this is pretty unlikely. Many people do have power lines nearby, but people use so little electricity, and the cost of connecting is so high, that very few people connect to the grid. And the electric company does not like connecting folks and may take over a year to satisfy a request for a connection even when someone pushes hard to have one. That is because the cost of connecting and serving low-use customers to the grid is subsidized, and the national electric company is often having budget problems.
Looking at World Bank statistics, perhaps this dynamic is working at a larger scale in Africa. For example, if we look at the World Bank data for electricity access in rural SubSaharan Africa (SSA):
https://data.worldbank.org/indicator/EG.ELC.ACCS.RU.ZS?locations=ZG
We see that access has increased from 12% to 30% from the year 2000 to 2021 in rural SSA. I think it is safe to say that more than half of rural SSA will still be largely without electricity access by 2030.
This is evidence that it is fairly likely that hundreds of millions of rural Africans will be able to benefit from more beneficial off-grid solar lighting for several decades to come.
Addressing some of the other points.
Re: the amount people spend on batteries and cell phone charging. We have done surveys. See:
https://www.researchgate.net/publication/325131559_Preliminary_impact_analysis_Kuyere_solar_system_distribution_MChinji_Malawi
I have discussed with people in village in Malawi how crazy it is that they spend so much on batteries. This argument makes it pretty easy to market the subsidized solar systems. But people live very hand-to-mouth in rural Malawi. So they will spend to buy something every week rather than invest to reduce a cost if the investment takes more than six months or a year to pay back.
I agree that the $200 income should be modeled with the Monte Carlo. But we can also target the subsidies to areas where incomes are lower. So the analysis indicates in my mind that the subsidies should be targeted to households that have incomes of $200 or less.
We do need to do more work assuring that the lighting systems are guaranteed to last 5 to 15 years, but from an engineering perspective, there is no reason the system cannot last that long given the battery we are using. The remaining engineering issue is going to be how to make sure all of the other parts are very durable, or very cheap and easy to replace.
Thanks again. I hope that answers most of your questions and concerns.
Thank you for the very thorough reply!! Really interesting.