Economics of Angel Investing

After writing the last post I thought a bit about the further development of innovation. What would be if we could predict successful companies (ideas) with high probability? That would allow to reallocate human capital faster and thus leading to more successes.
And one idea is a prediction market for startups. You may think that sites like AngelList go in this direction. I’m not entirely sure about this. I will first take a view on Angel Investing from an economic standpoint.

Angle Investor and Entrepreneur
This is a typical Principal-agent problem. The Entrepreneur has more information than the Investor. Often happens exactly what you will expect and that is that the Investor will look for commitments of the Entrepreneur which reveal information about his private information. Examples for these commitments are quitting one’s job, using one’s own money for funding or buying an expensive domain. Furthermore, of course, they try to grasp personal attributes of the Entrepreneur and his team.

Angel Investor and other Angel Investors
This stage is more interesting. Let’s say that our Entrepreneur got his first funding from one Angel Investor. Depending on the status of the first Angel Investor there are two different scenarios.
Firstly, assume the first Angel Investor isn’t famous. The next Angel Investor will probably see that this investment could possible be profitable but he will with a high probability go to stage one again and use his own judgment.
Secondly, now assume that the first Angel Investor is famous, a top notch one. The second Angel Investor will probably trust the judgment of the first Angel Investor so much that he will skip the first stage or neglect some flaws that he found. This is herding and leads to incorrect pricing and maybe a bubble.

We could either try to make these investments anonymously but this would be impractical. However, we could at least correct the pricing allowing short selling.
This all sounds like a stock exchange and they have a similar function, i.e. funding companies.

However, I think there’s one problem of stock exchanges for Angel Investment and that is that the expectations of the participants are different. Some Investors want 2x exists, some 5x exists, some want it in the next two years other in the next five. This is totally OK if we use these mechanisms for allocating capital.

Yet, the goal is to predict future successes and here I think prediction markets are more suitable because there are clear goals. E.g. “Company X will reach 5m in sales by 31 December, 2016.” Prediction markets do these things really good. One of the biggest problems will be liquidity which can be partially solved using aggregation or even better attracting more people to the market.

Want Innovation? Lower the initial investment.

I read an article a few months ago where the author complained that there isn’t much innovation outside of web and mobile applications. I thought about what makes them special and came to the conclusion that their initial investment is extremely low. I’m part economists therefore investment shouldn’t just be viewed as monetary investment. There are different costs and factors. I will take web application development as an example for this reasoning.

Educational Cost These include the costs of learning the techniques of your trade. Today, you can build simple web or mobile apps in less than a year without previous knowledge of programming. For programmers it’s even faster, maybe two or one month.

Capital requirements This is was a business major understands under initial investment. In the case of a web app it’s probably a hosting space and a domain. Maybe $5 per Month.

Administrative Cost Do you need any special certificates or are they any regulations? For web apps there aren’t any special restrictions.

Social Cost of Failure I think this is an important factor in more risk averse cultures, like in Europe. Let’s say you build a web app for two months, launch it and it fails. OK, happens often, no big thing.

Let’s compare this to some other, less innovative, industries like mechanical engine design. The educational costs are high, often you need some sort of advanced degree. The capital requirements are tremendous, you’ll need a work shop with very expensive equipment and so are the administrative costs with insurances, worker safety. The social cost of failure is increased because of the high capital requirements.

So how can these factors be reduced? One thing are definitely hacker spaces or shared work spaces. BioCurious provides the required equipment for the biotech endeavors (capital requirements). Furthermore, they provide classes to learn how to use this equipment (educational cost). This will also lower the social cost of failure.

I can imagine that this concept will be transfered to other industries like mechanical engineering, chemical processing, etc.