it’s odd to leap to things like housing markets and consumer debt without considering the demographics of startup employees. i believe your graphs are national averages, so are these employees expected to hold more or less debt relative to average? more or less likely to be homeowners v.s. renters? more or less likely to live in specific regions of the country?
the initial shock of covid 3.5 years ago was just massive. i get that it was in many ways transformative and not strictly destructive, but still hypotheticals like “a hundred billion decrease in VC funding” just seem so miniscule in comparison. simultaneously we see how the impacts of a sharp shock got dispersed pretty far across time with covid, and this VC bubble popping isn’t nearly as sharp a shock as we’ve known (call it 18mo, based on those burn rates, vs 2mo over which covid hit the whole country).
cascading failures are notoriously difficult to predict. seems to me the real worry is not the title of this post but that the systems which have arrested cascading failures may be eroding. good for bringing up national debt, actually, would be interesting to just embrace this fully and consider food/energy security & geopolitics — but that would make for a pretty different piece.
I attempted to address this in the article. As I mentioned: “The average startup employee earns around $95,000 a year, roughly 70% higher than the median wage in the US.”
So yes, a key part of my argument is that because of this higher average wage within this sub-section of the labor market, there are more significant “knock-on effects” if this portion of the labor market sees a sudden spike in unemployment. Those effects would likely impact:
consumer spending (higher disposable income)
consumer debt (I point out that they would be more likely to hold more consumer debt than the average due to higher discretionary income)
housing (being high-income earners but not wealthy, they are more likely to own a home and are likely to have a mortgage that is reliant on current income)
Also, projected VC funding in 2023 is less than $140B (over $200B less than 2021) and less than the total funding in 2020. VC funds themselves are also finding it MUCH more difficult to raise new capital and I believe that is going to continue to be the case for several years (that could be an entire other post as well).
This is certainly a possibility. I hope you’re right. Perhaps the impact of all those startups that raised capital in the bubble and won’t be able to raise again will not be as significant as I predict. However, my (admittedly simplistic) correlation analysis between historical funding and employment levels, and the extrapolation of that to today’s likely employment levels, would suggest a few million high-paying jobs are potentially at risk of being lost over the next 12-18 months. My argument is essentially: 1) that there is an underappreciated RISK (not a certainty) that those millions of additional jobs that were enabled through VC funding during its peak bubble could be lost as that runway runs out, and 2) that those workers might have a harder time than in the past finding a new job. If that does occur, then it would have a dramatic impact on the economy.
I try to explain the logic of this in the chart I shared comparing funding and employment levels. IF you accept the following logic, then the prospect of millions of job being at risk is pretty straightforward:
There is a direct correlation between the amount of annual VC investments in startups and the total employment of individuals by those startups.
VC funding more than doubled in 2021 compared to 2020.
Therefore, employment by those companies likely doubled.
VC funding for 2023 is projected to be less than 2020
Therefore employment by those companies is likely to drop and revert back to something closer to 2020 levels.
Fair point. Perhaps I should write a post just on the potential inability of the US government to effectively respond to any economic downturn (regardless of its causes).
Thanks for the comments! Really appreciate the feedback.
it’s odd to leap to things like housing markets and consumer debt without considering the demographics of startup employees. i believe your graphs are national averages, so are these employees expected to hold more or less debt relative to average? more or less likely to be homeowners v.s. renters? more or less likely to live in specific regions of the country?
the initial shock of covid 3.5 years ago was just massive. i get that it was in many ways transformative and not strictly destructive, but still hypotheticals like “a hundred billion decrease in VC funding” just seem so miniscule in comparison. simultaneously we see how the impacts of a sharp shock got dispersed pretty far across time with covid, and this VC bubble popping isn’t nearly as sharp a shock as we’ve known (call it 18mo, based on those burn rates, vs 2mo over which covid hit the whole country).
cascading failures are notoriously difficult to predict. seems to me the real worry is not the title of this post but that the systems which have arrested cascading failures may be eroding. good for bringing up national debt, actually, would be interesting to just embrace this fully and consider food/energy security & geopolitics — but that would make for a pretty different piece.
I attempted to address this in the article. As I mentioned: “The average startup employee earns around $95,000 a year, roughly 70% higher than the median wage in the US.”
So yes, a key part of my argument is that because of this higher average wage within this sub-section of the labor market, there are more significant “knock-on effects” if this portion of the labor market sees a sudden spike in unemployment. Those effects would likely impact:
consumer spending (higher disposable income)
consumer debt (I point out that they would be more likely to hold more consumer debt than the average due to higher discretionary income)
housing (being high-income earners but not wealthy, they are more likely to own a home and are likely to have a mortgage that is reliant on current income)
Also, projected VC funding in 2023 is less than $140B (over $200B less than 2021) and less than the total funding in 2020. VC funds themselves are also finding it MUCH more difficult to raise new capital and I believe that is going to continue to be the case for several years (that could be an entire other post as well).
This is certainly a possibility. I hope you’re right. Perhaps the impact of all those startups that raised capital in the bubble and won’t be able to raise again will not be as significant as I predict. However, my (admittedly simplistic) correlation analysis between historical funding and employment levels, and the extrapolation of that to today’s likely employment levels, would suggest a few million high-paying jobs are potentially at risk of being lost over the next 12-18 months. My argument is essentially: 1) that there is an underappreciated RISK (not a certainty) that those millions of additional jobs that were enabled through VC funding during its peak bubble could be lost as that runway runs out, and 2) that those workers might have a harder time than in the past finding a new job. If that does occur, then it would have a dramatic impact on the economy.
I try to explain the logic of this in the chart I shared comparing funding and employment levels. IF you accept the following logic, then the prospect of millions of job being at risk is pretty straightforward:
There is a direct correlation between the amount of annual VC investments in startups and the total employment of individuals by those startups.
VC funding more than doubled in 2021 compared to 2020.
Therefore, employment by those companies likely doubled.
VC funding for 2023 is projected to be less than 2020
Therefore employment by those companies is likely to drop and revert back to something closer to 2020 levels.
Fair point. Perhaps I should write a post just on the potential inability of the US government to effectively respond to any economic downturn (regardless of its causes).
Thanks for the comments! Really appreciate the feedback.