Why must women be different?

The overwhelming majority of start-ups that are funded have White, male founders. Just 1% are Black, 8% are female and 12% are Asian. Photo: ReutersThe overwhelming majority of start-ups that are funded have White, male founders. Just 1% are Black, 8% are female and 12% are Asian. Photo: Reuters

As an economist, I was trained in the late eighties as a ‘free marketeer’—one who believes that markets are essentially ‘efficient’, that human beings behave rationally in their own self interest, and that capital and labour flow seamlessly to where they see opportunity. This is a body of economics that places high value on empirical data, and the need to prove any hypothesis regarding economic behaviour with sophisticated mathematical and statistical modelling techniques that can be independently replicated by a set of reviewers before that proof can be published in lofty academic publications such as the Journal of Financial Economics.

Many theories of modern financial economics have made it through this brutal ‘peer review’ process before they have seen the light of day, including the famed theory that stock and investment markets are efficient, promulgated by such leading lights of financial economics as Eugene Fama—commonly called The Father of Finance—Merton Miller, Franco Modigliani, Myron Scholes, Fischer Black and others. Some of these theories of financial economics eventually even won the Nobel prize for their promulgators; Fama, Scholes, Modigliani, and Miller were all Nobel laureates—many of them winning the coveted honour during the 1980s and 1990s.

The issue with this generation of economists is that they completely ignored the ‘behaviouralists’ who argued that humans do not always react in a mathematically rational way when it comes to making investments. In the 1980s, the 1990s and in the noughties, these behaviouralists were forced to focus their efforts in the fields of psychology or sociology—and were not considered classical economists by any measure. The elegance of the empiricists’ mathematical formulations, backed by statistics and data that had been massaged and modelled to support their formulations was a strong deterrent to any behavioural economist who tried to posit that human beings are not always mathematically rational automatons, and tend to react differently and individualistically to data and information presented to them—often through filters of past experience, their socio-economic status, upbringing and, unfortunately, also their ingrained prejudices.

This efficient market theory of the empiricists also found support in the fact that market anomalies were swiftly corrected. As I have touched on in an earlier column focused on computing latency, investment banking firms created program trading desks—essentially desks that were capable of trading on computer programs which were trained to look for arbitrage opportunities in the stock markets—and swiftly execute trades in favour of the investment bank that owned them until the market anomaly—or arbitrage opportunity—was closed.

Current economic thinking is beginning to reverse this trend, and a school of behavioural economists has made a resurgence. They now have data to back them up. In my experience, such data is available in plenty whenever one starts to look at areas of sustained socio-economic prejudicial behaviour. Take, for instance, the behaviour of start-up investors when it comes to businesses founded by people from a different socio-economic background. According to The New York Times, venture capital firms invest only in about 1% of the Silicon Valley start-up firms that pitch to them. And when one looks at this successful 1%, the statistics are arresting. The overwhelming majority of start-ups that are funded have White, male founders. Just 1% are Black, 8% are female and 12% are Asian.

Let’s leave aside the racial undertones for a moment and hone in simply on one statistic. Women make up 50% of the world’s population. One has to believe that a larger proportion than 8% of firms are founded by women. So why this anomaly? At a recent IBM-sponsored event run by the non-profit SonderConnect, co-founded by a group of successful Indian businesswomen including my wife, the IBM executive sponsoring the event, Sandy Carter, presented a formidable statistic. She said that IBM’s research before the event had shown that women led start-ups are likely to be 15% more profitable on average, but are 40% less likely to be funded. This flies in the face of the efficient market theorists. If markets are indeed completely efficient, and human beings invested without prejudice, this arbitrage gap would have been closed by now!

I am still a free marketeer, but age and experience have softened my stance. There is no doubt that market anomalies such as the one discussed by the IBM executive are bound to be closed, but they will not be closed on their own. They require an intermediary to crank up the efficient market machine by greasing the gears and create rational outcomes by closing such anomalies. In the 1980s and 1990s, program trading was one such oil-can; it greased the workings of the machine enough to cause millisecond anomalies to be closed, but that was in a world of faceless trades on securities that traded on the floor of a stock exchange.

In the start-up world, where the face of the founder is inseparable from the business, it will take the workings of such informal networks such as Indian/Asian/Black entrepreneurial associations, and non-profits such as SonderConnect that act for women, to help close the gap. Such associations, will function much like the old-boys’ clubs that have long been established for those who today win most of the funding in the razor sharp competition for seed and venture funding.

One thing is for sure. I see a huge arbitrage opportunity. Any investment bets I make in the start-up world are going to go to women-led businesses. Who wouldn’t want to back someone with a 15% higher chance of success? And the self-interested free marketeer in me thinks the investment might even be at a discount, given that they have a 40% lower chance of securing funding!

Siddharth Pai is a management and technology consultant.


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