I worry that this presents the case for entrepreneurship as much stronger than it is[1]
The sample here is companies that went through Y-Combinator, which has a 2% acceptance rate[2]
As stated in the post, roughly all of the value comes from the top 8% of these companies
To take it one step further, 25% of the total valuation comes from the top 0.1%, i.e. the top 5 companies (incl. Stripe & Instacart)
So at best, if a founder is accepted into YC, and talented enough to have the same odds of success as a random prior YC founder, $4M/yr might be a reasonable estimate of the EV from that point. But I guess my model is more like Stripe and Instacart had great product market fit and talented founders, and this can make a marginal YC startup look much more valuable than it is.
I know you’re not explicitly saying that the EV of quitting one’s job to start a company is $4M/yr, but I think it’s worth spelling out more explicitly how far removed this reference class is from that hypothetical.
A couple of nitpicky things, which I don’t think change the bottom line, and have opposing sign in any case:
In most cases, quite a bit of work has gone in prior to starting the YC program (perhaps about a year on average?) This might reduce the yearly value by 10-20%
I think the 12% SP500 return cited is the arithmetic average of yearly returns. The geometric average, i.e. the realized rate of return should be more like 10.4%
#1 seems like a bigger deal if the optimal strategy is to do some startup work, then discontinue if you’re not in the top 2 percent as evaluated by YC (because that assessment heavily updates your EV). Presumably there is some cost there—at a minimum, the discontinuers could have been earning-to-give at a higher-paying job during that time. So I think the analysis could critically hinge on how accurately one can gauge their odds of being in the top 2 percent in a low-cost manner.
I don’t want to put words in your mouth, but I think you might be modeling this as something like “2.5% chance of $4M, 97.5% chance of zero, therefore all numbers should be multiplied by 0.025”, and that’s not correct. E.g. I was rejected from YCombinator, but still had returns roughly similar to what’s estimated here.
I think you might also be implying that the average EA is less qualified than the average YCombinator participant, even conditional on them being accepted to YCombinator. I have less data here, but of the two EA-ish companies I know that went through YCombinator, one had a ~$0 exit, and the other $500 million. At least within this (admittedly tiny) data set, the returns look pretty good.[1]
You list Stripe’s founders as being exceptional, which they surely are, but I could imagine Patrick explicitly earning to give if he had been born 10 years later.
I’m definitely not suggesting a 98% chance of zero, but I do expect the 98% rejected to fare much worse than the 2% accepted on average, yes. The data as well as your interpretation show steeply declining returns even within that top 2%.
I don’t think I implied anything in particular about the qualification level of the average EA. I’m just noting that, given the skewedness of this data, there’s an important difference between just clearing the YC bar and being representative of that central estimate.
I worry that this presents the case for entrepreneurship as much stronger than it is[1]
The sample here is companies that went through Y-Combinator, which has a 2% acceptance rate[2]
As stated in the post, roughly all of the value comes from the top 8% of these companies
To take it one step further, 25% of the total valuation comes from the top 0.1%, i.e. the top 5 companies (incl. Stripe & Instacart)
So at best, if a founder is accepted into YC, and talented enough to have the same odds of success as a random prior YC founder, $4M/yr might be a reasonable estimate of the EV from that point. But I guess my model is more like Stripe and Instacart had great product market fit and talented founders, and this can make a marginal YC startup look much more valuable than it is.
I know you’re not explicitly saying that the EV of quitting one’s job to start a company is $4M/yr, but I think it’s worth spelling out more explicitly how far removed this reference class is from that hypothetical.
The post does allude to this, but I think it’s worth flagging more explicitly.
A couple of nitpicky things, which I don’t think change the bottom line, and have opposing sign in any case:
In most cases, quite a bit of work has gone in prior to starting the YC program (perhaps about a year on average?) This might reduce the yearly value by 10-20%
I think the 12% SP500 return cited is the arithmetic average of yearly returns. The geometric average, i.e. the realized rate of return should be more like 10.4%
#1 seems like a bigger deal if the optimal strategy is to do some startup work, then discontinue if you’re not in the top 2 percent as evaluated by YC (because that assessment heavily updates your EV). Presumably there is some cost there—at a minimum, the discontinuers could have been earning-to-give at a higher-paying job during that time. So I think the analysis could critically hinge on how accurately one can gauge their odds of being in the top 2 percent in a low-cost manner.
Thanks!
I don’t want to put words in your mouth, but I think you might be modeling this as something like “2.5% chance of $4M, 97.5% chance of zero, therefore all numbers should be multiplied by 0.025”, and that’s not correct. E.g. I was rejected from YCombinator, but still had returns roughly similar to what’s estimated here.
I think you might also be implying that the average EA is less qualified than the average YCombinator participant, even conditional on them being accepted to YCombinator. I have less data here, but of the two EA-ish companies I know that went through YCombinator, one had a ~$0 exit, and the other $500 million. At least within this (admittedly tiny) data set, the returns look pretty good.[1]
You list Stripe’s founders as being exceptional, which they surely are, but I could imagine Patrick explicitly earning to give if he had been born 10 years later.
I’m definitely not suggesting a 98% chance of zero, but I do expect the 98% rejected to fare much worse than the 2% accepted on average, yes. The data as well as your interpretation show steeply declining returns even within that top 2%.
I don’t think I implied anything in particular about the qualification level of the average EA. I’m just noting that, given the skewedness of this data, there’s an important difference between just clearing the YC bar and being representative of that central estimate.