My post today is about a macroeconomic accounting mystery. Macroeconomic statistics attempt to measure impossibly big, complicated systems. For my dissertation research, I focus on national income statistics (the National Income and Product Accounts, the UN System of National Accounts, etc.) which try to measure the value of the production of all the goods and services in a given region. But I’m also fascinated by some of the companion statistics to national income/GDP like unemployment and inflation, both of which are measure by particular surveys (in the US, the Current Population Survey and the Consumer Expenditures Survey, among others). There are fascinating stories behind and around all of these practices (check out last week’s NYTimes Magazine on the GDP’s history for a starting place, or a new book by Thomas Stapleford about cost of living statistics).

There’s another big macroeconomic data set in the US that gets a lot less attention than the three I listed above: the Flow of Funds Accounts (or FoF) produced by the Federal Reserve Board of Governors. The Flow of Funds attempt to track the movement of money between various sectors and subsectors – banks and other financial firms, large and small industrial corporations, households, and government entities. The Flow of Funds tracks the movement of money by attempting to balance the flows in and out of each sector, and by attempting to balance the buying and selling of every kind of asset (or ‘instrument’). So, for example, F.110 looks at flows of money in and out of US-chartered commercial banks. F.220 tracks the buying and issuing of commercial mortgages. In addition to tracking flows, the FoF tracks levels – L.220 looks at how many commercial mortgages are outstanding in total and which sectors have them, rather than looking at changes.

Like the NIPA, and unlike unemployment and inflation statistics, the Flow of Funds are cobbled together using all sorts of heterogeneous data rather than being based on some single survey. Trying to track all of the money (much like trying to track all the production) is not a task easily accomplished with a sample. And so, because the Flow of Funds are cobbled together, they have some… quirks. My favorite quirk concerns the category “Unidentified Miscellaneous Financial Claim” (F.231 and L.231). What, you might ask, is an unidentified miscellaneous financial claim? We don’t know! Here’s the entirety what the Federal Reserve says in its description of the table from the Guide to the Flow of Funds Accounts:

For many sectors, unidentified miscellaneous financial claims are determined indirectly as the residual after the total of changes in individual ‘‘identified’’ asset or liability items for the sector (which appear on other instrument tables in the flow of funds accounts) has been subtracted from the change in total assets or liabilities reported by the sector. For other sectors (nonfarm noncorporate business, the federal government, bank personal trusts and estates, private pension funds, and mutual funds, for miscellaneous assets; and nonfarm noncorporate business, for miscellaneous liabilities), the amount of such claims is obtained directly as the total amount reported by original sources as ‘‘other’’ assets or liabilities.

In most cases, the nature of the items in this category is truly unidentified. In some cases, however, items that are identified separately in original documents are included here because the items are not significant enough from an analytical viewpoint to be classified as individual transaction categories. Examples are interest accrued by, prepaid expenses of, and real estate acquired for banking-house purposes by the Federal Reserve System (the major component of the monetary authority sector), as reported in the System’s Annual Report; and the intangible assets of U.S.-chartered commercial banks, as reported in their quarterly reports of condition. [Emphasis added.]

So, to reiterate, the Federal Reserve has not identified most of what’s in this class of instruments. Ok, but it’s a residual category – it’s probably small, right? Enh… you be the judge. In 2007, the “Net Change in Assets” in this category was $1.5 trillion. In 2008, that collapsed to a still large $365.3 billion. The level outstanding at the end of 2009 – $11.7 trillion dollars. There are more than 11 trillion dollars in assets that we’ve identified as existing, but not what kind of asset they are! And this category has grown tremendously – at the end of 1997, for example, there were a measly $4 trillion in outstanding “Unidentified Miscellaneous Financial Claims”.

So readers, I ask you – what could be in this category? What would have made it grow so much in the 90s and 2000s?

One possible type of asset that could be in this instrument is goodwill. Goodwill is an accounting term that attempts to capture the value of a firm purchased by another firm above and beyond the value of the assets of the first firm. E.g. if firm A buys firm B for $2 million, but firm B is only worth $1 million on its books, what happens to the balance sheet of the new firm A+B? A shelled out $2 million in real assets, but seems to have only gotten $1 million in return. There have been a number of solutions to this problem over time – one option was just to write-off the difference as an accounting loss. Another was to put the difference on the books of the new firm as “goodwill”, to represent the value of the purchased firm above and beyond its book value (in terms of ideas and synergies and future earnings potential from a brand name and all that) and then amortize the loss over a number of years. More recent solutions are more complicated, and involve keeping the goodwill. (Check out this 2007 paper by Ding et al. for a bit of the history of goodwill.)

But is that the whole story to this missing $11 trillion? What else could be in this category? And how would we figure it out?

In thinking about financial innovation, retail banking is not the first thing that comes to mind. Derivatives, global deals, complex portfolios — yes. But ATMs? Bank branches? As an ex-banker from Citigroup used to say to me years ago, “branches are a dead weight.”

Branches, however, are what makes the work of Zsuzsanna Vargha so interesting. Zsuzsi is finishing her Ph.D. in sociology at Columbia, and her dissertation examines a massive shift that has occurred across the Atlantic. She writes

Banks, after pursuing electronic banking, are once again
investing in the face-to-face encounter. This re-personalization of
finance is particularly well observable in post-socialist Hungary.
Banks individualize services to keep their share of profitable
clients, and reach out to new populations in person.

What do these changes mean for the future of retail finance? To address that, Zuzsi conducted ethnographic research on the Customer Relationship Management (CRM) software used to recommend products to bank clients. She then examined a savings and loan-type bank that used a direct selling organization, not unlike the “thundering herd” of salespeople that Merrill Lynch used to have. Her first findings are available in the first paper to come out her dissertation, “Markets from interactions: the technology of mass personalization in consumer banking.”

Zsuzsi’s study comes at a particularly timely juncture. Now that proprietary trading no longer seems to an option for American banks, these institutions need to reimagine their identity as something exciting and innovative … but distinct from Wall Street. Zsuzsi’s conception of retail banking as a high-tech service could well be the way to go.

We’re lucky to have Zsuzsi as guest blogger at Socializing Finance for the coming week.

Download vargha-2009-markets-from-interactions

Prem Sikka, who is a well-known critic of the current accounting system, is providing yet another list of companies who are now failing financial, but receiving a ‘clean bill of health’ from the auditors regarding their latest annual reports. We cannot argue with the facts, of course, but when it comes to explaining the reasons, or perhaps the mechanisms behind the auditing failures, we may have to dig deeper. Sikka is saying that

auditors are expected to be independent of the companies that they audit [yet] Auditors continue to act as advisers to the companies that they audit. They are hired and remunerated by the very organisations that they are supposed to be auditing. The auditor’s dependence for fees on corporate barons makes it impossible for them to be independent.

The dynamic implied in this described structural set of affairs is that there is self-censorship on the account of the auditor. Auditors realize that things are wrong with the companies they audit, yet – fearing for their auditing and consulting fees – they let things slip, hoping that there won’t be a complete collapse. I guess that the main concern I have here is empirical. The picture described sounds plausible, especially if remember the cases of Enron and WorldCom, but to establish the theory we would need to examine cases of auditors who did try to ‘test their clients’. That is, what would happen to an auditing firm that would not give a ‘clean bill of health’ to a large client? Would they lose lucrative consulting contracts with that client? Maybe even have their auditing contract withdrawn? If it can be shown empirically that such organisational set of norms on the part of the auditors’ clients exists and brings about effective results (i.e. auditors yield to their clients’ wills) then the theory of the auditor’s structural dependence on the client can be strengthened.   

Furthermore, in boiling down the role of the auditor to an agent that simply has to make the decision of either being independent (and then, possibly, pay the prices), or play along with the client, we portray a picture of reality that is too simplistic. For example, it can be assumed that there are different mechanisms in which a client and an auditor interact and surely not all of them bring about the same result of independence or, as Sikka suggests, the lack thereof.


The British Bankers’ association’s London Interbank Offered Rate (LIBOR), the rate at which banks loan money to each other, is a good indication of how risky is the world is seen to leading banks. In the case of the US dollar rate, there sixteen banks on the panel that determines the LIBOR (see here for a great description of how LIBOR is determined

The LIBOR is the beating heart of the interbank system, and reacts instantly to new information. However, it also shows how risk perceptions, and following these, a potential recession, come about.

The LIBOR rates for the first 29 days of September show this vividly. The line marked O/N (you can disregard the S/N as the graph is for USD) is the overnight rate at which banks are ready to loan money to each other – the shortest period of loan. The jump on 16th of September to the 18th indicates the flight to look at the jittery. The longer periods follow suit (1 week, 2 week, etc), as can be seen, but more moderately. The jump is dramatic, of course, but more ominous is the longer-term change that the graph reveals. First, LIBOR rates have moved up from about 2.5% to almost 4%. This indicates the higher degree of risk assigned to loans. This on its own is important, but even more telling is the spread of rates across the different periods. While on 1st of September, the range between the lowest and the highest rate was 0.8%, (not taking into account the very volatile overnight rate), the range on 29th of September is only 0.09%! This shows that not only that banks see their environment as riskier than before, but they also distinguish less between more and less risky loans. In fact, they tend to see all loans, regardless of the period for which they were taken, as risky. Such, diminished distinction is a sure sign of flight to liquidity – institutional risk avoidance, but it is also a reflection, if it continues, of a slowdown in macroeconomic activity. If all loans are seen as high risk, less loans are going to be granted.

Session Title: Market Devices: Understanding the Underbelly of Financial Markets
Submission Type: Symposium | Session Sponsor(s): (OMT, MOC, TIM)
Date & Time: Monday, Aug 11 2008 from 10:40AM – 12:00PM
Location: Anaheim Marriott, Grand Ballroom – Salon F

Session Title: How financial issues impact our organizations?
Submission Type: Paper Session | Session Sponsor(s): (PNP)
Date & Time: Monday, Aug 11 2008 from 10:40AM – 12:00PM
Location: Anaheim Marriott, Platinum 1

Session Title: Market Formation and Construction Processes: What we Know and the Questions we Ask
Submission Type: Symposium | Session Sponsor(s): (AAS)
Date & Time: Monday, Aug 11 2008 from 12:20PM – 2:10PM
Location: Anaheim Marriott, Grand Ballroom – Salon E

Session Title: When Financiers become Entrepreneurs: Understanding Institutional Entrepreneurship in Finance
Submission Type: Symposium | Session Sponsor(s): (OMT, ENT, BPS)
Date & Time: Monday, Aug 11 2008 from 2:30PM – 3:50PM
Location: Anaheim Convention Center, 210D

Session Title: Financial Markets: An Economic Sociology Perspective
Submission Type: Symposium | Session Sponsor(s): (BPS, OMT)
Date & Time: Tuesday, Aug 12 2008 from 8:30AM – 10:10AM
Location: Anaheim Convention Center, 202A

From Bodies to Black-Scholes

A Two-day Workshop on Performativity and the Social Studies of Finance

Organized by Daniel Beunza (Columbia U.) and Yuval Millo (LSE)

Columbia Business School, New York, 28-29 April 2008

The Social Studies of Finance (SSF) is one of the fastest-growing and most intriguing new fields in the social sciences today. Born from the intersection of sociology of science, economic sociology, management and critical accounting, SSF offers a new vantage point for the analysis of financial markets and their dynamics.

This intensive two-day workshop is convened by Daniel Beunza from Columbia Business School and Yuval Millo from the London School of Economics. It is aimed at presenting the field to newcomers, and is directed at research students and early-career researchers in accounting, finance, management, political science and sociology.

To allow effective discussion, the group size is limited to 12 participants. The workshop’s fee is US$ 200. To apply for the workshop, please send by February 29th a CV and a one-page description of your research and how it relates to SSF to

For more details see:

An upcoming conference at Columbia Business School may be of interested to social studies of finance researchers. This coming January 18th, the Geofinance conference will address an issue that has been of long interest in this blog: what makes financial capitals, and how is the competition between New York, London and others evolving?

Here’s an excerpt from the conference:

What’s driving the decision to locate particular financial activities or functions in particular places? How are these decisions being influenced by technological advances, regulation and the rise of emerging markets? What matters most in the competition between New York and London to become the capital of international capital?

The conference is organized by Columbia Business School and the Wharton School.

I have long been surprised by the lack of novelty in financial visualization. Even as maps, video-games and operating systems become more and more adept at 3D, colors, layers and animation… the screens of Wall Street keep showing the exact same graphs as usual. Last week, in a panel on financial visualization, I learned the reasons for this lack of innovation. And I made an argument for the opposite.

Consider just how puzzling the existing status quo is with regards to visualization. Bloomberg, the market leader in analytics, offers the same 1980s-style aesthetics that it did two decades ago. Tickers, that ineffective relic of the pre-Internet era, continue to grace the screens of CNBC and the streets around Times Square. Yahoo and Google offer the same graph that retail investors have been using for years — a plain-vanilla price chart. Even Apple’s iPhone (supposedly, the epitome of the cool) has the same chart.

This is surprising, because existing visualizations do not support profitable trading strategies. Indeed, most systems are based on timely news and time series of stock prices and volume. And yet, we know from basic financial economics that both past prices and news are a bad predictor of future stock prices. As for the ticker… the animated display of selected stock prices is a low-bandwidth visualization born in the era of the telegraph. That’s right: 19th C. Nowadays, information can travel much faster, and one does not need to wait for “my stock” to come up on the ticker.

Why this un-innovativeness? That was the question I asked myself as I took the subway to downtown Mantattan. The panel was organized by the New York chapter of the Usability professionals (essentially: designers), joint with NYC Wireless. The presentations of the rest of the panelists — all three very smart, very sophisticated professionals — made very clear the difficult situation that designers suffer as soon as they start to work for a Wall Street firm.

One of the presenters, a brilliant and charismatic designer, was responsible for the Intranet at a major credit card company. According to her, 70% of Wall Street intranets are just numbers. Why? Other concerns prevail over graphic sophistication. First, in finance, heavy regulation forces different parts of the firms not to be able to see the same information. So firewalls are very important. Second: designers get little training. “How can you communicate with the bankers,” the presenter asked, “with only a 20-minute online tutorial on risk management?” Third, mistakes “cost millions.” And fourth, convenience is everything: “we had to completely redesign the system so that the bankers could read it on a pdf on their way home to Westchester.”

The second panelist, an acclaimed designer in his “previous life” and now head of visualization at a major Wall Street bank, abounded on these issues. The bank, he said, had more people working in IT than the entire employees of Adobe. But visualization has only arrived to two percent of software, and most of it to its intranet — the hidden part. How come? “Traders are very busy. They make an incredible amount of money, and their time is very valuable. They cannot commit to meet you at such-and-such time to discuss changes in the system.” The designer finally found a way to work with them, but even this is very telling: “I say to them, ‘I’ll come to your desk tomorrow at nine, and when you have a minute, tell me what we do.” In addition to this, traders are very practical and resist innovation. “If there is a yellow button on the left for the escape function, they need to see it in the next version of the software.”

In short, the picture of Wall Street designers that comes across is revealing. The designers in are smart, able, savvy. But they make up an distinct community of practice, one with lower status, limited financial knowledge and one that does not seem to fully communicate with the traders and bankers. In terms of innovation, they also seem to be paralyzed by the needs of their users. As as we know from Christensen’s “The Innovator’s Dilema,” users are a conservative group.

What, then, is the way ahead? I believe that innovation will happen. But it may not come from the internal design teams on Wall Street. Along with Christensen, I expect that it will come from some low-end entrant to the industry. (And it is interesting that there were people in the room from the entertainment industry.) My own presentation discussed some potential avenues for innovation, based on my curatorial work on art that is based on finance. Please see below a PDF document of the presentation.

The latest ‘Chinese toothpaste’ panic and the way ‘China’ is constructed in the American public discourse reminded me of another episodes of economically driven or perhaps, economically reflected jingoism, that of the 1980s American car industry (see, for example, here and here). There are many similarities between what we are experiencing now with regard to ‘Chinese Import’ in general and between the ‘Japan is going to overtake Detroit’ of the 1980s. A quick look at both cases shows that transformation process took place whereby products, production methods, wholesale and retail practice were reduced into a national character. Hence, those were not Toyota or Nissan who were threatening the dominance of GM or Ford in the American auto market. Instead, those Japanese’ were gaining dominance over ‘an American industry’. Of course, the social and, indeed, societal processes that unfolded were much too complex for a blog post. Nevertheless, the fact that we see again, 20 years after that wave of jingoism, the emergence of another one should raise some question marks about the omnipotent power that we tend to assign to global economic factors. After all, if globalization in general and ‘the global economy’ in particular have gained dominance, why does the question of where exactly the cars or the toothpaste come from make headlines?

The NY Times is asking whether NY is still the ‘capital of capital’ mentioning that, among other things, the largest mutual funds are not based in the city, the biggest securities trading floor is no longer that of the NYSE (see here about the demise of open outcry trading and here more discussion about it):

[I]n today’s burgeoning and increasingly integrated global financial markets — a vast, neural spaghetti of wires, Web sites and trading platforms — the N.Y.S.E. is clearly no longer the epicenter. Nor is New York. The largest mutual-fund complexes are in Valley Forge, Pa., Los Angeles and Boston, while trading and money management are spreading globally. Since the end of the cold war, vast pools of capital have been forming overseas, in the Swiss bank accounts of Russian oligarchs, in the Shanghai vaults of Chinese manufacturing magnates and in the coffers of funds controlled by governments in Singapore, Russia, Dubai, Qatar and Saudi Arabia that may amount to some $2.5 trillion, according to Stephen Jen, a Morgan Stanley economist.

However, as financial markets become more distributed, we should re-evaluate the connections between geographical location and capital.

One potential direction that is hinted in the NY Times story is the preferred location for IPOs (initial public offering). The article refers to the fact that nine out the ten largest out-of-country IPOs (IPOs done outside the country where the company is incorporated) in the last year were held outside the US. IPOs, of course, are the fundamental building blocks of financial markets as through them new stocks enter the market. Knowing that NY is the traditional location for IPOs, we can pretty much equate US with NY. The meaning of this figure is that NY does not attract to the same degree it used to the types of people and institutions that perform IPOs. Instead, the story tells us, new urban ‘financial-attraction’ centres are rising (at least as far as IPOs go). Hong Kong seems to be one of New York’s major rivals, as are some European cities.    

So, what are the conditions that attract IPOs to a particular urban centre? The immediate conceptual candidates are human capital (experienced underwriters, for example), institutions, liquid capital and, inevitably, a social network that binds these ingredients together effectively. All of this may sound fairly basic to a sociologist, but in spite of the fact that there is considerable research about urban financial centres, to best of my knowledge the crucial element of IPOs has not been studied empirically from a sociological perspective. Having said that, a paper by Richard Florida analyses the demographic conditions that induce creativity among urban populations and thus may help to conceptualise the question of where IPOs are likely to take place. It can be that one of the reasons for this relative lack of academic attention is the fact that to understand what makes IPOs happen, one needs to witness the inner mechanisms of the process and these are not easily accessible, as this classic ethnography-like Fortune magazine story about Microsoft’s IPO shows.