The approach seems to be along the following lines:<p>1. Fit a model (in the case Zipf's law) to a semi-related field (the size of non-financial companies).<p>2. Find that the model doesn't fit reality in the field you're interested in (financial companies).<p>3. Posit that your model is correct and reality is wrong, and invent over $30 trillion worth of invisible activity to account for the difference.<p>Alternatively... your model is just wrong?
This is off topic, but does anyone else have a "This Week’s Top 5 Posts" section smack in the middle of the article?<p>Is that something new Medium are automatically injecting? If so, I don't like it. I do like the idea of being pushed to more content _after_ I've finished reading, not _during_ the middle.
One thing about Power Law distributions -- they work really great except at the outliers (ie, top 10). You can't always say that because incumbent #10 is x, #1 is 10x, especially when dealing with organizations that are huge conglomerates of different services, branches and sub-companies.<p>Look at Market Caps of companies (something that we have public signals about): <a href="https://en.wikipedia.org/wiki/List_of_corporations_by_market_capitalization#2013" rel="nofollow">https://en.wikipedia.org/wiki/List_of_corporations_by_market...</a><p>The difference between #1 and #10 is <2x, and #3-#10 all vary by just a few percent. Power Law distributions are great, but they tend to fail at the top end.
The study takes on-balancesheet assets as a proxy for company size and fits a model to it that largely works. Fine so far.<p>But the implication that this works at the top end is either that the companies are hugely mis-stating their on-balancesheet assets or that there are other companies, much bigger than FNMA, that have balancesheets with multiples of the GDP of the States.<p>Neither of these explanations are plausible even if you believe that they're all lying, thieving scumbags. The numbers are just too big.<p>However, there is another explanation. That on-balancesheet assets isn't a good proxy for size for big financial institutions. And all of a sudden the problem is solved because on-balancesheet assets isn't a good proxy for size for big financial institutions.<p>Apart from anything else many of them run huge assets and liabilities off-balancesheet. BTW that doesn't make them secret, they hit the accounts just the same, it just means that the proxy in the study won't work.<p>And for what it's worth, this is wholly orthogonal to the size of Shadow Banking, how much stuff is hidden in the Caymans etc etc. Fascinating and worrying subjects in themselves.
I've got a fun mathematical model supporting controversial assertions about banks. Yes, I could test those assertions against fact by reading the contingent liabilities sections of large banks' financial reports. But accounting is boring. And, let's face it, we all know that I'd just deal with negating evidence by arguing "accounting trickery" is just hiding Truth.
<i>"The shadow banking system is vastly bigger than regulators had thought, say econophysicists who have developed a powerful new way to measure its hidden impact"</i><p>I had to read this a couple of times before I realised what was wrong, but apparently "Econophysics" really is a thing:<p><i>"Econophysics is an interdisciplinary research field, applying theories and methods originally developed by physicists in order to solve problems in economics, usually those including uncertainty or stochastic processes and nonlinear dynamics. Its application to the study of financial markets has also been termed statistical finance referring to its roots in statistical physics."</i> [1]<p>[1] <a href="http://en.wikipedia.org/wiki/Econophysics" rel="nofollow">http://en.wikipedia.org/wiki/Econophysics</a>
"On the Forbes Global 2000 list of the world’s largest companies, the first non-financial firm is General Electric, which ranks 44th."<p>This is even scarier than the apparent fact that econophysics is a real thing. I'd like to know the history of the Forbes Global 2000 to get an idea over time of how dominant financial companies have been. I have a hunch they have always had a part (JP Morgan Chase anyone?) but surely this is a new phenomenon to be so dominated by companies that don't actually produce much.
See the "Inside Job" (2010) documentary movie - (at least in USA) there were attempts to regulate the now unregulated banking activities. The banks' lobby was just too powerful and in result not only the banks remained unregulated, but the regulation system was reduced in staff and weakened.
It may be that the scale-free preferential attachment model doesn't hold in the generality claimed. The modeling technique of Doyle and Willinger may be more relevant [1].<p>1. Walter Willinger , David Alderson , John C. Doyle. Mathematics and the Internet: A Source of Enormous Confusion and Great Potential. Notices of the AMS. Volume 56, Number 5. May 2009. <a href="http://www.ams.org/notices/200905/rtx090500586p.pdf" rel="nofollow">http://www.ams.org/notices/200905/rtx090500586p.pdf</a>
econophysicists? Wtf?<p>If you want to avoid the term "economics" because most people associate it with "made up financial bollocks based on applying completely inappropriate models from unrelated disciplines", then why include the "econo" part.<p>Also, you appear to be trying to be modelling a financial phenomenon by applying a completely inappropriate model from an unrelated discipline.
Under the broad meaning of Shadow Banking System, everyone speculating in any of the securities market would be a member of it. In my opinion this is very misleading and not really targeting the core feature, which is being a borrower and a lender of higher forms of money (reserves or deposits, not securities).