It’s an incredible result; stunning, really. I just wish it didn’t make me so depressed.

I salute the innovation and cheer on the profits. That is capitalism at its finest and we need more of it.

It’s that f***king mountain of cash (now up to $100 billion) that concerns me, because it’s symptomatic of what is holding America (and Britain) in the economic doldrums.

The return Apple will be getting on that cash will be miniscule, if it’s positive at all, and conceivably negative.  Standing next to that, their return on assets excluding cash is phenomenal.

Why aren’t they doing something with the cash? Are they not able to expand profits still further by expanding quantities sold, even in new markets? Are there no new internal projects to fund? No competitors to buy out? Why not return it to shareholders via dividends or share buybacks?

Logically, a company holds cash for some combination of three reasons: (a) they use it to manage cash flow; (b) they can imagine buying an outside asset (a competitor or some other company that might complement them) in the near future and they want to be able to move quickly (and there’s no M&A deal that’s agreed upon faster than an all cash deal); or (c) they want to demonstrate a degree of security to offset any market perceived risk with their debt.

Apple long ago surpassed all of these benefits.  The net marginal value of Apple holding an extra dollar of cash is negative because it returns nothing and incurs a lost opportunity cost.  So why aren’t their shareholders screaming at them for wasting the opportunity?

The answer, so far as I can see, is because a significant majority of AAPL’s shareholders are idiots with a short-term focus. They have no goddamn clue where else the money should be and they’re just happy to see such a bright spot in their portfolio.  Alternatively, maybe the shareholders aren’t complete idiots — Apple’s P/E ratio has been falling for a while now – but the fundamental point is that they have a mountain of cash that they’re not using.

In 2005 that wouldn’t have been as much of a problem because the shadow banking system was in full swing, doing the risk/liquidity/maturity transformation thing that the financial industry is meant to do and so getting that money out to the rest of the economy.[*] Now, the transformation channel is broken, or at least greatly impaired, and so nobody makes any use of Apple’s billions. They just sit there, useless as f***, while profitable SMEs can’t raise funds to expand and 15% of all Americans are on food stamps.

Don’t believe me?  Here’s a graph from the Bank of England showing year-over-year changes in lending to small- and medium-sized enterprises in the UK.  I can’t be bothered looking for the equivalent data for the USA, but you can rest assured it looks similar.  The report it’s from can be found here (it was published only a few days ago).  The Economist’s Free Exchange has some commentary on it here (summary:  we’re still in trouble).

So what is happening to all that money?  Well, Apple can’t exactly stick it in a bank account, so they repo it, which is a fancy way of saying that they lend it to a bank (or somebody else in the financial industry) and temporarily take some high quality asset like a US government bond to hold as collateral.  They repo it because that’s all they can do now — there are no AAA-rated, actually safe, CDO tranches being created by the shadow banking system any more, they’re too big to make use the FDIC’s guarantee (that’s an excellent paper, btw … highly recommended) and so repo is all they have left.

But the financial industry is stuck in a disgusting mess like some kid’s hair with chewing gum rubbed through it. They’re all just as scared as the next guy (especially of the Euro problems) and so they’re parking it in their own accounts at the Fed and the BoE.  As a result, “excess” reserves remain at astronomical levels and the real economy makes no use of Apple’s billions.

That’s a tragedy.

[*] Yes, the shadow banking industry screwed up. They got caught up in real estate fever and sent (relatively) too much money towards property and too little towards more sustainable investments. They structured things in too opaque a manner, failed to have public price discovery and operated under distorted incentives. But they operated. Otherwise useless cash was transformed into real investment and real jobs. Unless that comes back, America and the UK will stay in their slow, painful household deleveraging cycle for another frickin’ decade.

The phrase “X is consistent with Y” is actually a very, very weak statement.  All it’s saying is that X doesn’t provide evidence against Y.  Here’s a handy flow chart:

X is … Y:    ”consistent with” < “suggestive of” < “evidence for” < “proof of”

The crisis of 2007/2008 and the present Euro-area difficulties may both be interpreted, from a policymaker’s viewpoint, as a combination of two related events: an exogenous change in the relative supplies of high- and low-risk assets and, subsequently, a classic liquidity crisis. A group of assets that had hitherto been considered low risk suddenly became viewed as high risk. The increased supply of high-risk assets pushed down their price, while the opposite occurred in the market for low-risk assets. Unsure of their counterparties’ exposure to newly-risky assets, the suppliers of liquidity then withdrew their funding. Note that we do not require any change in financial intermediaries’ risk-aversion (their risk appetite) in this story. Tightening credit standards, common to any downturn, serve only to amplify the underlying shock.

Central banks responded admirably to the liquidity crises, supplying unlimited quantities of the stuff and generally at Bagehot’s recommended “penalty rate”. In response to the first problem, and being concerned primarily with effects on the real economy, central banks initially lowered overnight interest rates, trusting markets to correspondingly reduce low-risk and, in turn, high-risk rates. When overnight rates approached zero and central banks were unwilling to permit them to become negative, they turned to QE, mostly focusing on forcing down low-risk rates (out of a concern for distorting the allocation of capital across the economy) and allowing markets to bring down high-risk rates.

Consequently, QE tightens spreads over overnight interest rates and since spreads over blew out during the crisis, this is commonly seen as a positive outcome and even a sign that the overall problem is being resolved. However, such an interpretation misses the possibility, if not the fact, that broader spreads are rational market reactions to an underlying shift in the distribution of supply. In such a case, QE cannot help but distort otherwise efficient markets, no matter what assets are purchased.

Indeed, limiting purchases to low-risk assets may serve to further distort any “mismatch” between the distributions of supply and demand. Many intermediaries operate under strict, and slow moving, institutional mandates that limit their exposure to long-term, high-risk assets. Such market participants are simply unable, even in the medium term, to participate in the portfolio rebalancing that CBs seek. The efficacy of such a strategy may therefore decline as those agents that are able to participate become increasingly saturated in their purchases of high-risk debt (and in so doing are seen as risky themselves and so unable to raise funds from the constrained agents).

Furthermore, QE in the form of open market purchases of bonds, no matter whether they are public or private, automatically implies a bias towards large corporates and away from households and small businesses that rely exclusively on bank lending for credit. Bond purchases directly lower interest rates faced by large corporates (through portfolio rebalancing), but only indirectly stimulate small businesses or households via bank funding costs. In an environment with reduced competition in banking and perceived fragility in the financial industry as a whole, funding costs may not decline in response to QE and even if they do, the decline may not be passed on to borrowers.

In any event, a direct consequence of QE at the ZLB must be a reduction in the expected profitability of the financial industry as a whole and with it, a corresponding decline in the industry’s ability to withstand negative shocks. Given this trade-off, optimal policy at the ZLB should expressly consider financial system fragility in addition to inflation and the output gap, and when the probability of a negative shock rises, the weight given to such consideration must correspondingly increase.

How, then, to stimulate the real economy? Options to mitigate such a trade-off might include permitting negative nominal interest rates, at least for institutional investors; engaging in QE but simultaneously acting to improve financial industry resilience by, for example, mandating industry-wide constraints on dividends or bonuses; or, perhaps most importantly, acting to “correct” the risk distribution of long-term assets. The first of these is not without its risks, but falls squarely within the existing remit of most central banks. The second would require coordination between monetary and regulatory policy, a task eminently suited to the Bank of England’s new role. The third requires addressing the supply shock at its source and so its implementation would presumably be legislative and regulatory.

If further QE is deemed wise, it may also be necessary to grit one’s teeth and shift purchases out to (bundles of) riskier assets, if only maximise their effect. Given the distortions that already occur with low-risk purchases, this may not be as bad as it first seems.

Active monetary research can help inform all of these options, but more broadly, should perhaps focus not just on identifying the mechanisms of monetary transmission but also consider their resilience.

Forecast GDP:  Actual + no further shocks

Natural GDP:  Forecast + full utilisation (i.e. no current or residual shocks, either)

Potential GDP:  Natural + fully flexible prices

Efficient GDP:  Potential + no market power

That then gives three different versions of an output gap:  Actual minus Natural, Potential or Efficient.

For some models, there is no difference between Natural GDP and Potential GDP.  I don’t like those models.

At present, in order to meet sudden surges in demand, power companies have to bring additional generators online at a moment’s notice, a procedure that is both expensive and inefficient. If there were enough electric vehicles around, though, a fair number would be bound to be plugged in and recharging at any given time. Why not rig this idle fleet so that, when demand for electricity spikes, they stop drawing current from the grid and instead start pumping it back?

Apparently it’s all called vehicle-to-grid (V2G).  That (wikipedia) link has some great extra detail over the Economist piece.  If you want more again, here is the research site of the University of Delaware on it.  If you want more again (again), I’ve included links to the UK study by Ricardo and National Grid referenced in the Economist piece below.

After reading about the idea of V2G, a friend of mine asked a perfectly sensible question:

If having batteries connected up to the grid is a good thing for coping with spikes in demand, then why wouldn’t the power companies have dedicated batteries installed for this purpose?

I presume that power companies don’t install massive battery packs to obviate demand spikes because the cost of doing so exceeds the cost they currently incur to deal with them: having X% of their gross capacity sitting idle for most of the time.

In particular, the energy density of batteries isn’t great, and batteries do have a fairly low limit on the number of charge-discharge cycles they can go through.

Interestingly, another part of the cost associated with battery packs will be in the form of risk and uncertainty [*], which are exemplified by precisely this idea.  If a power company were to purchase and install massive battery packs at the site of the generator only to see a tipping-point-style adoption of electric vehicles that, when plugged in, serve as batteries for hire situated at the site of consumption (i.e. can offer up power without transmission loss), they would have to book a huge loss against the batteries they just installed.

Technological innovation and adoption is disruptive and frequently cumulative, meaning that any market power created by it is likely to be short-lived, which in turn creates a short-run focus for companies that work in that space.  For an infrastructure supplier more used to thinking about projects in terms of decades, that creates a strong status quo bias:  by not acting now, they retain the option to act tomorrow once the new technologies settle down.

Anyway, I’m a huge fan of this idea.  For a start, I’ve long been a huge fan of massively distributed power generation.  Every household having an ability to sell juice back to the grid is just one example of this, but I think it should be something we could aim to scale both up and down.  Imagine a world where anything with a battery could be used to transport and sell power back to the grid.  My pie-in-the-sky dream is that I could partially pay for a coffee at my local cafe by letting them use some of my mobile phone’s juice for 0.00001% of their power needs for the day.

More realistically, the other big benefit of this sort of thing is that because the grid becomes better able to cope with demand spikes without being supplied by the uber generators, the benefit to the power company of maintaining that surplus capacity starts to fall.  As a result, the balance would swing further towards renewable energy being economically (and not just environmentally) appealing.

At a first guess, I suspect that this also means that it is against the interests of existing power station owners for this sort of thing to come about, which ends up as another argument in favour of making sure that power generators and power distributors are separate companies.  The distributor has a strong economic incentive to have a mobile supply that, on average, moves to where the demand is located (or better yet, moves to where the demand is going to be); the monolithic generator does not.

Back in December 2007 (i.e. when the financial crisis had started but not reached it’s Oh-God-We’re-All-Going-To-Die phase), Doctors Willett Kempton and Nathaniel Pearre reckoned a V2G car could produce an income of $4,000 a year for the owner (including an annual fee paid to them by the grid, about which I am highly sceptical).  The Economist quite rightly points out that V2G, like so many things in life, would experience decreasing marginal value, but apparently it wouldn’t fall so far as to make it meaningless:

Of course, as the supply of electric vehicles increases, the value of each to the power company will fall. But even when such vehicles are commonplace, V2G should still be worthwhile from the car-owner’s point of view, according to a study carried out in Britain by Ricardo, an engineering firm, and National Grid, an electricity distributor. The report suggests that owners of electric vehicles in Britain could count on it to be worth as much as £600 ($970) a year in 2020, when an electric fleet 2m strong could provide 6% of the country’s grid-balancing capacity.

If you’re interested in the study by Ricardo and National Grid, the press release is here.  That page also has a link to the actual report, but they want you to give them personal information before you get it.  Thankfully, the magic of Google allows me to offer up a direct link to a PDF of the report.

The ever-sensible Economist also raises the upfront cost of capital installation by the distributor as something to keep in mind:

There is, it must be admitted, the issue of the additional cost of the equipment to manage all this electrical too-ing and fro-ing, not least the installation of charging points that can support current flows in both directions. But if the decision to make such points bi-directional were made now, when little of the infrastructure needed to sustain a fleet of electric vehicles has yet been built, the additional cost would not be great.

I can’t remember a damn thing from the “Electrical Engineering” part of my undergraduate degree [**], but despite the report from National Grid, I’m fairly sure that there would still be significant technical challenges (by which I mean real engineering problems) to overcome before rolling out a power grid with multitudes of mobile micro-suppliers, not to mention the logistical difficulties of tying your house, your car and your mobile phone battery to the same account and keeping track of how much they each give or take from any location, anywhere.

If I were a government wanting to directly subsidise targeted research to combat climate change I’d be calling in the deans of Electrical Engineering departments and heads of power distribution companies for a coffee and a chat.  I’d casually mention some numbers that would make make them salivate a little and then I’d talk about open access and the extent to which patents are ideal in stimulating innovation. [***]

[*] By which I mean known unknowns and unknown unknowns respectively.

[**] Heck, I can’t remember a damn thing from the “Electronic Engineering” or the “Computing Engineering” parts, either.

[***] But that’s a topic for another post.

I’m also a new (Teaching) Fellow in the school, which means that a) I’m now a formal academic advisor (my advisees are yet to be determined); and b) I’m technically part of the academic staff at LSE (even though I’m only part-way through my Ph.D.).  That last point gets me access to the Senior Common Room (where the profs have lunch) and into USS, the pension scheme for academics at most UK universities.

Here’s what’s amazing about USS:  It’s a final salary scheme!  I’m honestly amazed that there are any defined-benefit schemes still open to new members.  Well, there you go.  I’m in one now.

People who live in countries where disease is rife may have lower IQs because they have to divert energy away from brain development to fight infections, scientists in the US claim.

The controversial idea might help explain why national IQ scores differ around the world, and are lower in some warmer countries where debilitating parasites such as malaria are widespread, they say.

Researchers behind the theory claim the impact of disease on IQ scores has been under-appreciated, and believe it ranks alongside education and wealth as a major factor that influences cognitive ability.

[...]

The actual research article: http://rspb.royalsocietypublishing.org/content/early/2010/06/29/rspb.2010.0973.full?sid=f65fe5b5-b8d4-4e62-82ee-60c7bd44e3d3

Abstract

In this study, we hypothesize that the worldwide distribution of cognitive ability is determined in part by variation in the intensity of infectious diseases. From an energetics standpoint, a developing human will have difficulty building a brain and fighting off infectious diseases at the same time, as both are very metabolically costly tasks. Using three measures of average national intelligence quotient (IQ), we found that the zero-order correlation between average IQ and parasite stress ranges from r = ?0.76 to r = ?0.82 (p < 0.0001). These correlations are robust worldwide, as well as within five of six world regions. Infectious disease remains the most powerful predictor of average national IQ when temperature, distance from Africa, gross domestic product per capita and several measures of education are controlled for. These findings suggest that the Flynn effect may be caused in part by the decrease in the intensity of infectious diseases as nations develop.

For reference, the Flynn effect:  http://en.wikipedia.org/wiki/Flynn_effect

The Flynn effect describes an increase in the average intelligence quotient (IQ) test scores over generations (IQ gains over time). Similar improvements have been reported for other cognitions such as semantic and episodic memory.[1]  The effect has been observed in most parts of the world at different rates.

The Flynn effect is named for James R. Flynn, who did much to document it and promote awareness of its implications. The term itself was coined by the authors of The Bell Curve.[2]

The effect’s increase has been continuous and approximately linear from the earliest years of testing to the present. There are numerous explanations to the Flynn effect and also some criticism. There is currently a discussion if the Flynn effect has ended in some developed nations since the mid 1990s.

It’s about political comics (cartoons) drawn to depict John Law and the Mississippi Bubble of the early 1700s.  It also speaks to subtlely different meanings of the words “alchemy” and “occult” than we are used to today. Here is an early paragraph in the paper:

Non-transparency induces a hierarchy of knowledge. The most extreme form of that sort of hierarchy might be called the cult of expertise in which expertise is said to be accompanied by godlike powers, the ability to unbind scarcity of matter and time. The earliest debates over hierarchy focused on whether such claims are credible or not.

Here is the abstract:

Economists have occasionally noticed the appearance of economists in cartoons produced for public amusement during crises. Yet the message behind such images has been less than fully appreciated. This paper provides evidence of such inattention in the context of the eighteenth century speculation known as the Mississippi Bubble. A cartoon in The Great Mirror of Folly imagines John Law in a cart that flies through the air drawn by a pair of beasts, reportedly chickens. The cart is not drawn by chickens, however, but by a Biblical beast whose forefather spoke to Eve about the consequences of eating from the tree of the knowledge. The religious image signifies the danger associated with knowledge. The paper thus demonstrates how images of the Mississippi Bubble focused on the hierarchy of knowledge induced by non-transparency. Many of the images show madness caused by alchemy, the hidden or “occult.”

Hat tip: Tyler Cowen.

Abend attempts to take the measure of a particularly profound form of difference that might be postulated within the domain of world sociology: the idea that different national traditions of sociology may embody different epistemological frameworks that make their results genuinely incommensurable.

[...]

Consider this tabulation of results on the question of the role of evidence and theory taken by the two sets of articles:

[...]

Here is a striking tabulation of epistemic differences between the two samples:

Abend believes that these basic epistemological differences between U.S. and Mexican sociology imply a fundamental incommensurability of results:

To consider the epistemological thesis, let us pose the following thought experiment. Suppose a Mexican sociologist claims p and a U.S. sociologist claims not-p.  Carnap’s or Popper’s epistemology would have the empirical world arbitrate between these two theoretical claims. But, as we have seen, sociologists in Mexico and the United States hold different stances regarding what a theory should be, what an explanation should look like, what rules of inference and standards of proof should be stipulated, what role evidence should play, and so on. The empirical world could only adjudicate the dispute if an agreement on these epistemological presuppositions could be reached (and there are good reasons to expect that in such a situation neither side would be willing to give up its epistemology). Furthermore, it seems to me that my thought experiment to some degree misses the point. For it imagines a situation in which a Mexican sociologist claims p and a U.S. sociologist claims not-p, failing to realize that that would only be possible if the problem were articulated in similar terms. However, we have seen that Mexican and U.S. sociologies also differ in how problems are articulated—rather than p and not-p, one should probably speak of p and q.  I believe that Mexican and U.S. sociologies are perceptually and semantically incommensurable as well. (27)

Though Abend’s analysis is comparative, I find his analysis of the epistemological assumptions underlying the U.S. cases to be highly insightful all by itself.  In just a few pages he captures what seem to me to be the core epistemological assumptions of the conduct of sociological research in the U.S.  These include:

• the assumption of “general regular reality” (the assumption that social phenomena are “really” governed by underlying regularities)
• deductivism
• epistemic objectivity
• a preference for quantification and abstract vocabulary
• separation of fact and value; value neutrality

There is a clear (?) parallel dispute in the study of economics as well, made all the more complicated by the allegations leveled at economics as a discipline as a result of the global financial crisis.