1) “We hence conservatively assume that a skilled investor can achieve 7% expected real returns” – I’m an investor (hopefully a skilled one), but I would certainly not think of 7% as conservative. Yes, historically real equity returns have been c.5%. That is indeed the correct prior to use when forecasting, but you then need to overlay other things about the future. Importantly, while the historically real risk-free was up around 2% for much of the period you quote (source: http://www.econ.yale.edu/~shiller/data/chapt26.xlsx), it is now less than −1% (source: https://www.federalreserve.gov/releases/h15), which should lower your estimate straight away from 5% to 2%. You can boost expected returns through leverage (though as you correctly say, this does have a cost). I would disagree about venture capital investment being higher returns. This may be the case on a post-tax basis, but is not on a pre-tax basis (which is what is most relevant for non-profits). I would not assume you are able to capture any premium from ‘information’. There is a whole industry competing for this and it is hard to do.
2) Your Guesstimate model assumes exogenous learning of +9.3% p.a. This input dwarfs all other variables, so it would be helpful if you could expand on how you reached it. It’s hard to critique something that is not explain (at least as far as I can see), but I think you may have fallen into the trap of looking at historical efficiency improvements brought about by scaling up of technology. As technology improves, the price comes down. But that price only comes down if you develop and manufacture the technology. Moore’s Law didn’t start until humanity built the first computers.
A couple of points:
1) “We hence conservatively assume that a skilled investor can achieve 7% expected real returns” – I’m an investor (hopefully a skilled one), but I would certainly not think of 7% as conservative. Yes, historically real equity returns have been c.5%. That is indeed the correct prior to use when forecasting, but you then need to overlay other things about the future. Importantly, while the historically real risk-free was up around 2% for much of the period you quote (source: http://www.econ.yale.edu/~shiller/data/chapt26.xlsx), it is now less than −1% (source: https://www.federalreserve.gov/releases/h15), which should lower your estimate straight away from 5% to 2%. You can boost expected returns through leverage (though as you correctly say, this does have a cost). I would disagree about venture capital investment being higher returns. This may be the case on a post-tax basis, but is not on a pre-tax basis (which is what is most relevant for non-profits). I would not assume you are able to capture any premium from ‘information’. There is a whole industry competing for this and it is hard to do.
2) Your Guesstimate model assumes exogenous learning of +9.3% p.a. This input dwarfs all other variables, so it would be helpful if you could expand on how you reached it. It’s hard to critique something that is not explain (at least as far as I can see), but I think you may have fallen into the trap of looking at historical efficiency improvements brought about by scaling up of technology. As technology improves, the price comes down. But that price only comes down if you develop and manufacture the technology. Moore’s Law didn’t start until humanity built the first computers.