Mr. Darcy’s Ten Thousand a Year

On popular demand, I’m reviving a reoccurring theme of mine: teaching economic history through the lens of popular culture. Today: bonds, yields and 18th century English financial planning.

In what is probably my favourite piece ever written, I tried to estimate exactly how rich Mr. Darcy was – Mr. Darcy, of course, of Jane Austen’s classic novel Pride & Prejudice. I showed that whatever method you use to translate incomes to the present, all characters in Austen’s captivating story are astonishingly rich. But, as we well know today, there are large differences even among the superrich; compare Bernie Sanders (small-time millionaire) with George Lucas and Steven Spielberg (single-digit billionaires) or Jeff Bezos (wealthiest man alive).

Using Pride & Prejudice to illustrate some economic point is hardly unconventional (Piketty did this in his Capital in the Twenty-First Century), so let me similarly discuss 18th and 19th century British financial markets using the characters in this well-known tale.

The starting point is the following musing, courtesy of former Oxford Economist Martin Slater’s (2017: 52) The National Debt; how come “female characters in nineteenth-century novels always seem to have a suspiciously exact income of ‘so many pounds per year'”? Where does this money come from? Why is it so exact? And what’s the reason Piketty uses this particular literary example to illustrate the permanence and steady stream of income that capital somehow just throws off?

Consols and Financial Markets

Financial markets are truly awesome – not just in their impressive scope or potential devastation, but in the many different needs they simultaneously fulfil for many different people. Slater ably guides us through the confusing mishmash that is the 17th and 18th century English public finance, but what emerges by 1757, after Henry Pelham’s consolidation of government debt, is two main – and for our purposes, equivalent – securities: the Consolidated 3% Annuities (and the ‘Reduced annuities’), affectionately named ‘Consols’. These were permanent government bonds with annual interest payments of 3%. This means that they had no maturity date, i.e. the holder of the security could expect the government to keep paying 3% of the face value for all future (a Churchill-issued subsequent Consol was actually repaid and retired just a few years ago, after almost a century in service).

Two cool things happen. First, the “initial value” – the face value – of debt running in perpetuity becomes almost irrelevant, since all that matters for the issuer is the ability to maintain interest rate payments; there is no presumption of future repayment. Second, creditors – that is, holders of the Consols who receive the regular interest payments – may trade that asset on financial markets. Since the plethora of different debt assets were now condensed into a single, credible, identical and easily-identified asset, the market for 3% Consols in London developed into a very large and liquid market. With such ease of access and predictable and stable payoffs, the Consols became the instrument of saving for well-off families in Austen’s time.

A note on yields

The Consols, essentially a piece of paper with a face value of £100, entitled the owner to a perpetual stream of payments by the government, in this case 3% – or £3. Now, the actual price at which this paper could be sold in London fluctuated extensively depending on the conditions of the financial market and, most prominently in Austen’s lifetime, the Napoleonic wars. As the £3 annual pay was serviced by the British government, and financial strain during the war increased the risk for defaults (through a foreign invasion or British government itself), the price of Consols was chiefly reflecting the military success.

When the market price of a debt falls below its face value, the effective interest rate (the “yield”) that a prospective investor receives increases; paying £50 for a Consol with face value of £100 and a £3 perpetual interest payment, effectively earns the investor 6% interest instead of 3% (3/50 = 0.06). Since the Consols were the most dominant asset on the largest financial market in the world, their price became “the single most important asset price in the world economy” as Klovland (1994: 165) called it. Here’s the yield on Consols during Austen’s life:

JA, yield on 3%

It reached a low of 3.11% in 1792 (almost at par), and a high of 6.22% in 1798 (below £50) after the suspension of the gold standard.

The Bennets and the fortunes of handsome young men

The families of Pride & Prejudice made good use of this thriving financial market – not specifically for trading but for financial planning (others, such as British economist David Ricardo, and the banking families of Rothschild and Barings, made some of their fortune trading Consols).

In the novel, Mr. Bennet – the protagonist Lizzy’s father – has an income of £2,000 a year (again, see my 2016 piece for three different attempts at “translating” these sums into today’s money). It is not clear what his income comes from, but it’s a fair guess that it stems, like many other landed gentry of the time, from renting out farm lands belonging to the family home Longbourne. In addition, we know that Mrs. Bennet’s portion to the family home is a £5,000 contribution which is the sole inheritance the (five) Bennet daughters are entitled to.

Now, the way well-off families like the Bennets would make use of Consols was to ensure that non-inheriting children had at least some source of income after the passing of their father. The underlying concern in Pride & Prejudice, causing Mrs. Bennet to worry so about fortunate marriages for her daughters, is that the Bennet estate is entailed away to Mr. Collins – and with it the presumed rental income of £2,000 a year. That would leave the girls homeless, reduced to living off Mrs. Bennet’s inheritance of £5,000.

Austen began writing First Impressions (the initial title for Pride & Prejudice) in October 1796. During the decade leading up to this, the yield on Consols had been firmly within the interval 3.5-4.5%, hovering around 4% for years. It should thus not surprise us that Mrs. Bennet’s fortune of £5,000 presumably consisting of Consols, would have been purchased at around £75, predictably yielding the family an annual return of 4%. Indeed, the characters of Pride & Prejudice seem to be squarely set on 4% being the general norm. For instance, in a desperate attempt to enhance his already-inane proposal to Lizzy, Mr. Collins explicitly says:

“To fortune I am perfectly indifferent, and shall make no demand of that nature on your father, since I am well aware that it could not be complied with; and that one thousand pounds in the 4 per cents, which will not be yours till after your mother’s decease, is all that you may ever be entitled to.”

(Chapter 19, p. 133 in the 2009 HarperCollins edition)

Here we see the great use that Consols offered families like the Bennets. Once the Bennet parents pass away, the £5,000 of Consols could be divided equally among her children; Lizzy’s share would be a thousand pounds, which earns her an annual 4% interest return, or £40 (although maybe several year’s earnings for a regular worker, this was a rather small sum for such rich families – in contemplating Lizzy’s sister Lydia’s imprudent marriage, we learn that Mr. Bennet spent almost £100/year on Lydia’s purchases and pocket money alone). Being liquid financial assets, dividing up the Consols among children was very easy, and their steady income stream ensured that they would have at least some income. Bar Napoleonic conquest, the interest payment on the Consols would reliably show up year after year.

As for the handsome young men, Mr. Bingley’s case is easier than Mr. Darcy’s. We know that Bingley’s income is not agricultural, but investments from a fortune of almost  £100,000 inherited from his father, who had not yet acquired an estate. The fortune was “acquired by trade”, where (being from the North) cotton or shipping are prime candidates, but the slave trade is also a possibility. We also know that the ambiguity of his annual income (£4,000 or £5,000) lies well within the return from a fortune of that size invested in Consols. Indeed, for Bingley to hold that kind of fortune, earn that income and still not have an estate of his own, suggests that his financial wealth consists predominantly of Consols – perhaps complemented with some other stock (Bank of England or East India Company stock are plausible candidates). Clearly, new money.

Mr. Darcy, on the other hand, is plainly old money. And a lot of it. There are subtle hints in the novel that Pemberley has been in the Darcy family for generations. What we don’t know is precisely how his £10,000 a year is earned. When visiting Pemberley in Derbyshire with her aunt and uncle, Lizzy is told by the housekeeper that Mr. Darcy is such a generous and fair man: “ask any of his tenants”, she says, which indicates that Mr. Darcy, has a fair number of them – as one would expect from a sizeable estate like Pemberley. Now, what we don’t know is if the entirety of his £10,000 a year is reaped from rental income; it could be that some of his income is financial – or that either his financial or rental income is excluded from this rumoured number. Beyond a mention of his sister, Georgiana’s, fortune of £30,000 – which for convenience would likely be held in Consols – we know very little about the personal finances of Mr. Darcy.

The use and abuse of Consols

The financial market for government debt in the late-18th and early 19th century was not created with financial planning in mind, but by incremental improvements to previous government funding problems. The outcome, however, was a striking success for Britain, whose thriving financial market in no small part accounted for Britannia’s Century until WWI.

Moreover, as contemporary economists from Ricardo and John Stuart Mill to Malthus and Lauderdale observed, the recurring interest payments, funded by taxes, may have had quite large macroeconomic consequences. Taxing ‘productive’ investments and trade in order to fund ‘unproductive’ holders of government debt was, it was argued, harmful to the country – and in a time where government expenditures largely consisted of the military and debt maintenance, the impacts of funding the debt was of prime political interest.

Piketty’s use of Austen’s England (and Balzac’s France) was used for precisely the same distinction. Wealth, in Piketty’s view, perpetuates itself, and effortlessly earns its return (never mind the work, risk and selection issues involved). By continually paying the interest on its debt, the governments of Austen’s Britain financed the leisurly lifestyles of the rich, just as the “natural” return of the modern-day rich contribute and maintain today’s inequality.

The Consol was a revolutionary invention, but it might not have been part of Mr. Darcy’s Ten Thousand a Year.

Let’s Find Out – or: the Power of Reference

The core message of a number of books I’ve recently had the great pleasure to read has been fairly simple. Have a look. Check it out. Put your numbers in perspective. In a world awash with statistics and cognitive biases imploring us to cheer mindlessly for our own team, having the skill and wherewithal to step back and carefully ask: “can this really be so?” is golden.

One of recently passed celebrity professor and YouTube phenomenon Hans Rosling’s most profound advice for countering misinformation about the state of the world is precisely this: put all numbers in perspective. Never accept unaccompanied numbers – never believe the numerator without checking the denominator. What matters, as Bryan Caplan never ceases to emphasize as the GMU Economics creed, “are statistics, not emotions – and arguments, not stories.”

But, a statistic may never be left alone, Rosling maintains, but always compared to other relevant numbers. What share of its total category does this statistic represent? What was it last year, 5 or 10 or 20 years ago? Is there some self-evident change in associated behavior that is relevant or ought to explain it? A century ago street cars used to kill and injure hundreds of people every year, but since very few American cities make use of street cars today, the casualty is fortunately much lower. If we keep in mind that miles travelled by cars far outnumber miles travelled by street cars, reporting the number of street car deaths – while probably correct – entirely miss the point when discussing traffic safety. In How Not To Be Wrong, Mathematics professor Jordan Ellenberg quipped

Dividing one number by another is mere computation ; knowing what to divide by what is mathematics.

Here’s another example. If I told you about 23 000 individual deaths and spent a brief 10 second on each of them, going through the list would take me almost three days. On a personal level like that, 23 000 deaths is an absurd, insane, catastrophe-style event that few people are emotionally equipped to handle – essentially the size of my hometown, wiped out in a single year. If I told you those 23 000 deaths were due to antibiotic resistant diseases in the U.S. last year, the pandemic scenarios working through your mind quickly escalate. That many! Let’s find the nearest bunker!

If I then told you that cancer and heart diseases (each!) claim the lives of about 20x that, the fear of lethal apocalyptic germs consuming the world ought to quickly recede. Oh.

Here’s another example. It is entirely correct to point out that the number of people killed in worldwide airplane accidents in 2018 (556 people) was much higher than the year before (44 people) and the year before that (325 people). Would one be excused for believing that air travel is getting more risky and dangerous? Forbes, for instance, ran a roughly accurate story claiming that airline fatalities increased by 900%.

Not in the slightest. The number of fatalities from air travel has been falling for decades, all while the number of flights and miles travelled have increased exponentially, meaning that the per-flight, per-mile or per-passenger risk of death has kept dropping. Not to mention that alternative modes of travelling like driving is magnitudes more dangerous.

While Rosling teaches us to figure out what the base rate is, i.e. putting our statistic into appropriate perspective, one of Philip Tetlock’s tricks for becoming a ‘Superforecaster’ is to use Bayesian updating of one’s beliefs. This picks up precisely where Rosling’s idea left off. Once we know where to start, we have to amass more information, numbers and observations from other points of view – Bayesian updating is a popular method to incorporate and synthesize new information with the old.

In short “Calculation, like logic, is your friend” (Landsburg 2018: 44). Statistics matter and numbers can deceive. In order to better understand our realities and see through mistakes that others make – either intentionally to deceive or persuade, or unintentionally through ignorance – we must embrace the core message of people like Ellenberg, Tetlock, Duffy, Rosling or Pinker.

Always Be Comparing Thy Numbers. Never accept an unaccompanied statistic. Never trust numerators without denominators.

The Nonsensical Meaning of Sustainability

Along with ‘Inequality’ and ‘Democratic socialism’, ‘Sustainability‘ is one of the words that captures the essence of my generation. A sustainable project, event or business is met with “wow”s and “oooh!”s, an indicator of its owner’s moral righteousness and altogether praiseworthy character.

But its meaning is far from clear from all but its most fervent supporters. Dealing with the extraction of resources, the use of ecological reserves or harvesting of crops, a process is allegedly ‘sustainable’ if the naturally occurring regeneration exceeds the current levels of extraction. Simply put, don’t use more than what is (annually?) renewed. Moreover, a process branded as sustainable usually involve a mix of some other virtue signalling activities of our time: carbon emission neutrality or offsetting; at least a superficial concern for one’s environmental impact; energy produced in ‘renewable’ ways (read: nothing but solar, wind or hydro); or the use of recycled materials.

If this sounds unobjectionable and self-evident to you, this piece is for you. Despite the fancy branding, the SDGs, the fervor of self-proclaimed do-gooders, is the ‘sustainability’ of an activity really what we care about?

There are at least two major confusions with the assessment of activities as sustainable or its despised opposite: unsustainable. First, and most frequently occurring, is the belief that we aim to pursue our current endeavor in the same way for all eternity. If you think about it, the indignant objection of unsustainability is often quite meaningless, worthy of nothing but a ‘so what?’ response; everything we do at any given moment is in a sense “unsustainable”:

  • if I keep typing on my computer I will eventually starve;
  • if I keep lifting weights or endlessly running on that treadmill, I will collapse;
  • if I keep eating this chocolate cake of mine, I will be sick.

So? Everyone who has ever engaged in those activities understand that there are ends to them, that we’re only doing them for a particular purpose for a certain period of time, and that extrapolating snapshots of reality is quite silly; I do not intend to continue this activity until the brink of whatever physical boundary there might – or might not – be. Until I approach some “safe” distance to that brink, I’ll happily indulge in my chocolate cake, lift my weights or type away at my keyboard. In economic speak we are trading off one resource for another, until saturation or the fulfillment of some other aim becomes more important (prime example is Environmental Kuznets Curves).

The other confusion is to believe that economic systems cannot change and that humans cannot adapt. It is emphatically irrelevant that there is a physically limited amount of oil in the ground, since price systems and their incentives effectively ration oil use according to urgently-induced needs and encourage substitutes when those are needed. More importantly, the price system for raw materials incorporate and incentivize technological improvements that 1) through discovering new deposits literally expands “the” amount of resources,  2) shape cost-effective processes to hard-to-access deposits we couldn’t profitably exploit before, 3) improve the bang for our buck, i.e. how much output we can squeeze out of a given quantity of material. Thus, there might ultimately be a physical limit, but not an economic limit.

Let me give an iconic example: chopping down trees quicker than the forest grows. Such an activity seem pretty ‘unsustainable’ since the declining size of the forest implies that one day there will no longer be a forest. So what? There might be urgent present reasons for doing that (say, for instance, no other source of heat/fuel for cooking or no other source of income) that are very likely to change in a fairly short time frame (ie, before complete deforestation has occurred); the current prices of pulp or firewood may be meaningfully higher than their anticipated future prices (‘selling’ off some capital assets would therefore be fairly prudent); there might be future technological innovations that a) (re-)grows forests quicker, b) offers a better substitute to the current use of wood, c) allows us to cheaply make use of more from what we chop down.

Almost any practice taken as a snap-shot in time is literally ‘unsustainable’. Naively believing that they will mindlessly continue linearly into the future is quite silly; hailing processes that don’t as righteous and ‘sustainable’ is similarly silly. Human societies and their economic process are dynamic systems capable of (read: constantly) change.

By saying that something is unsustainable, my generation wants to convey the idea that these activities are immoral and that they shouldn’t continue. It’s a naive and erroneously nonsensical conviction.

The Paradox of Prediction

In one of famous investor Howard Marks’ memos to clients of Oaktree Capital, the eccentric and successful fund manager hits on an interesting aspect of prediction markets and probability alike. In 1993 Marks wrote:

Being ‘right’ doesn’t lead to superior performance if the consensus forecast is also right. […] Extreme predictions are rarely right, but they’re the ones that make you big money.

Let’s unpack this.

In economics, the recent past is often a good indicator for the present: if GDP growth was 3% last quarter, it is likely around 3% the next quarter as well. Similarly, since CPI growth was 2.4% last year and 2.1% the year before, a reasonable forecast for CPI growth for 2019 is north of 2%.

If you forecast extrapolation like this, you’d be right most of the time – but you won’t make any money, neither in betting markets nor financial markets. That is, Marks explains, because the consensus among forecasters are also hoovering around extrapolations from the recent past (give or take some), and so buyers and sellers in these markets price the assets accordingly. We don’t have to go as far as the semi-strong versions of the Efficient Market Hypothesis which claim that the best guesses of all publicly available information is already incorporated into the prices of securities, but the tendency is the same.

  • if you forecasted 5% GDP growth when most everyone else forecasted 3%, and the S&P500 increased by say 50% when everyone estimated +5%, you presumably made a lot more money than most through, say, higher S&P500 exposure or insane bullish leverage.
  • If you forecasted -5% GDP growth when most everyone else forecasted 3%, and the S&P500 fell 40% when everyone estimated +5%, you presumably made a lot more money than most through staying out out S&P500 entirely (holding cash, bonds or gold etc).

But if you look at all the forecasts over time by people who predicted radically divergent outcomes, you’ll find that they quite frequently predict radically divergent outcomes – and so they would be spectacularly wrong most of the time since extrapolation is usually correct. But occasionally they do get it right. In hammering the point home, Marks says:

the fact that he was right once doesn’t tell you anything. The views of that forecaster would not be of any value to you unless he was right consistently. And nobody is right consistently in making deviant forecasts.

The forecasts that do make you serious money are those that radically deviate from the extrapolated past and/or current consensus. Once in a while – call it shocks, bubble mania or creative destruction – something large happens, and the real world outcomes land pretty far from the consensus predictions. If your forecast led you to act accordingly, and you happened to be right, you stand the make a lot of money:

Predicting future development of markets thus put us in an interesting position: the high-probability forecasts of extrapolated recent past are fairly useless, since they cannot make an investor any money; the low-probability forecasts of radically deviant change can make you money, but there is no way to identify them among the quacks, charlatans, and permabears. Indeed, the kind of people who accurately call radically deviant outcomes are the ones who frequently make such radically deviant projections and whose track record of accurately forecasting the future are therefore close to zero.

Provocatively enough, Marks concludes that forecasting is not valuable, but I think the bigger lesson applies in a wider intellectual sense to everyone claiming to have predicted certain events (market collapses, financial crises etc).

No, you didn’t. You’re a consistently bullish over-optimist, a consistent doomsday sayer, or you got lucky; correctly calling 1 outcome out of 647 attempts is not indicative of your forecasting skills; correctly calling 1 outcome on 1 attempt is called ‘luck’, even if it seems like an impressive feat. Indeed, once we realize that there are literally thousands of people doing that all the time, ex post there will invariably be somebody who *predicted* it.

Stay skeptical.

Monetary Progression and the Bitcoiner’s History of Money

In the world of cryptocurrencies there’s a hype for a certain kind of monetary history that inevitably leads to bitcoin, thereby informing its users and zealots about the immense value of their endeavor. Don’t get me wrong – I laud most of what they do, and I’m much looking forward to see where it’s all going. But their (mis)use of monetary history is quite appalling for somebody who studies these things, especially since this particular story is so crucial and fundamental to what bitcoiners see themselves advancing.

Let me sketch out some problems. Their history of money (see also Nick Szabo’s lengthy piece for a more eloquent example) goes something like this:

  • In the beginning, there was self-sufficiency and the little trade that occurred place took place through barter.
  • In a Mengerian process of increased saleability (Menger’s word is generally translated as ‘saleableness’, rather than ‘saleability’), some objects became better and more convenient for trade than others, and those objects emerged as early primative money. Normally cherry-pick some of the most salient examples here, like hide, cowrie shells, wampum or Rai stones.
  • Throughout time, precious metals won out as the best objects to use as money, initially silver and gradually, as economies grew richer, large-scale payments using gold overtook silver.
  • In the early twentieth century, evil governments monopolized the production of money and through increasingly global schemes eventually cut the ties to hard money and put the world on a paper money fiat standard, ensuring steady (and sometimes not-so-steady) inflation.
  • Rising up against this modern Goliath are the technologically savvy bitcoiners, thwarting the evil money producing empires and launching their own revolutionary and unstoppable money; the only thing that stands in its way to worldwide success are crooked bankers backed by their evil governments and propaganda as to how useless and inapt bitcoin is.

This progressively upward story is pretty compelling: better money overtake worse money until one major player unfairly took over gold – the then-best money – replacing it with something inferior that the Davids of the crypto world now intents to reverse. I’m sure it’ll make a good movie one day. Too bad that it’s not true.

Virtually every step of this monetary account is mistaken.

First, governments have almost always defined – or at least seriously impacted – decisions over what money individuals have chosen to use. From the early Mesopotamian civilizations to the late-19th century Gold Standard that bitcoin is often compared to, various rulers were pretty much always involved. Angela Redish writes in her 1993 article ‘Anchors Aweigh’ that

under commodity standards – in practice – the [monetary] anchor was put in place not by fundamental natural forces but by decisions of human monetary authorities. (p. 778)

Governments ensured the push to gold in the 18th and 19th centuries, not a spontaneous order-decentralized Mengerian process: Newton’s infamous underpricing of silver in 1717, initiating what’s known as the silver shortage; Gold standard laws passed by states; large-scale network effects in play in trading with merchants in those countries.

Secondly, Bills of Exchange – ie privately issued debt – rather than precious metals were the dominant international money, say 1500-1900. Aha! says the bitcoiner, but they were denominated in gold or at least backed by gold and so the precious metal were in fact the real outside money. Nope. Most bills of exchange were denominated in the major unit of account of the dominant financial centre at the time (from the 15th to the 20th century progressively Bruges, Antwerp, Amsterdam and London), quite often using a ghost money, in reference to the purchasing power of a centuries-old coins or social convention.

Thirdly, monetary history is, contrary to what bitcoiners might believe, not a steady upward race towards harder and harder money. Monetary functions such as the medium of exchange and the unit of account were seldomly even united into one asset such as we tend to think about money today (one asset, serving 2, 3 or 4 functions). Rather, many different currencies and units of accounts co-emerged, evolved, overtook one another in response to shifting market prices or government interventions, declined, disappeared or re-appeared as ghost money. My favorite – albeit biased – example is early modern Sweden with its copper-based trimetallism (copper, silver, gold), varying units of account, seven strictly separated coins and notes (for instance, both Stockholms Banco and what would later develop into Sveriges Riksbank, had to keep accounts in all seven currencies, repaying deposits in the same currency as deposited), as well as governmental price controls for exports of copper, partly counteracting effects of Gresham’s Law.

The two major mistakes I believe bitcoiners make in their selective reading of monetary theory and history are:

1) they don’t seem to understand that money supply is not the only dimension that money users value. The hardness of money – ie, the difficulty to increase supply – as an anchoring of price levels or stability in purchasing power is one dimension of money’s quality – far from the only. Reliability, user experience (not you tech nerds, but normal people), storage and transaction costs, default-risk as well as network effects might be valued higher from the consumers’ point of view.

2) Network effects: paradoxically, bitcoiners in quibbling with proponents of other coins (Ethereum, ripple, dash etc) seem very well aware of the network effects operating in money (see ‘winner-takes-it-all’ arguments). Unfortunately, they seem to opportunistically ignore the switching costs involved for both individuals and the monetary system as a whole. Even if bitcoin were a better money that could service one or more of the function of money better than our current monetary system, that would not be enough in the presence of pretty large switching costs. Bitcoin as money has to be sufficiently superior to warrant a switch.

Bitcoiners love to invoke history of money and its progression from inferior to superior money – a story in which bitcoin seems like the natural next progression. Unfortunately, most of their accounts are lacking in theory, and definitely in history. The monetary economist and early Nobel Laureate John Hicks used to say that monetary theory “belongs to monetary history, in a way that economic theory does not always belong to economic history.”

Current disputes over bitcoin and central banking epitomize that completely.

Asking questions about women in the academy

Doing the economist’s job well, Nobel Laureate Paul Romer once quipped, “means disagreeing openly when someone makes an assertion that seems wrong.”

Following this inspiration guideline of mine in the constrained, hostile, and fairly anti-intellectual environment that is Twitter sometimes goes astray. That the modern intellectual left is vicious we all know, even if it’s only through observing them from afar. Accidentally engaging with them over the last twenty-four hours provided some hands-on experience for which I’m not sure I’m grateful. Admittedly, most interactions on twitter loses all nuance and (un)intentionally inflammatory tweets spin off even more anger from the opposite tribe. However, this episode was still pretty interesting.

It started with Noah Smith’s shout-out for economic history. Instead of taking the win for our often neglected and ignored field, some twitterstorians objected to the small number of women scholars highlighted in Noah’s piece. Fair enough, Noah did neglect a number of top economic historians (many of them women) which any brief and uncomprehensive overview of a field would do.

His omission raised a question I’ve been hooked on for a while: why are the authors of the most important publications in my subfields (financial history, banking history, central banking) almost exclusively male?

Maybe, I offered tongue-in-cheek in the exaggerated language of Twitter, because the contribution of women aren’t good enough…?

Being the twenty-first century – and Twitter – this obviously meant “women are inferior – he’s a heretic! GET HIM!”. And so it began: diversity is important in its own right; there are scholarly entry gates guarded by men; your judgment of what’s important is subjective, duped, and oppressive; what I care about “is socially conditioned” and so cannot be trusted; indeed, there is no objectivity and all scholarly contribution are equally valuable.

Now, most of this is just standard postmodern relativism stuff that I couldn’t care less about (though, I am curious as to how it is that the acolytes of this religion came to their supreme knowledge of the world, given that all information and judgments are socially conditioned – the attentive reader recognises the revival of Historical Materialism here). But the “unequal” outcome is worthy of attention, and principally the issue of where to place the blame and to suggest remedies that might prove effective.

On a first-pass analysis we would ask about the sample. Is it really a reflection of gender oppression and sexist bias when the (top) outcome in a field does not conform to 50:50 gender ratios? Of course not. There are countless, perfectly reasonable explanations, from hangover from decades past (when that indeed was the case), the Greater Male Variability hypothesis, or that women – for whatever reason – have been disproportionately interested in some fields rather than others, leaving those others to be annoyingly male.

  • If we believe that revolutionising and top academic contributions have a long production line – meaning that today’s composition of academics is determined by the composition of bright students, say, 30-40 years ago – we should not be surprised that the top-5% (or 10% or whatever) of current academic output is predominantly male. Indeed, there have been many more of them, for longer periods of time: chances are they would have managed to produce the best work.
  • If we believe the Greater Male Variability hypothesis we can model even a perfectly unbiased and equal opportunity setting between men and women and still end up with the top contribution belonging to men. If higher-value research requires smarter people working harder, and both of those characteristics are distributed unequally between sexes (as the Greater Male Variability hypothesis suggests), then it follows naturally that most top contributions would be men.
  • In an extension of the insight above, it may be the case that women – for entirely non-malevolent reasons – have interests that diverge from men’s (establishing precise reasons would be a task for psychology and evolutionary biology, for which I’m highly unqualified to assess). Indeed, this is the entire foundation on which the value of diversity is argued: women (or other identity groups) have different enriching experiences, approach problems differently and can thus uncover research nobody thought to look at. If this is true, then why would we expect that superpower to be applied equally across all fields simultaneously? No, indeed, we’d expect to see some fields or some regions or some parts of society dominated by women before others, leaving other fields to be overwhelmingly male. Indeed, any society that values individual choice will unavoidably see differences in participation rates, academic outcomes and performance for precisely such individual-choice reasons.

Note that none of this excludes the possibility of spiteful sexist oppression, but it means judging academic participation on the basis of surveys responses or that only 2 out of 11 economic historians cited in an op-ed were women, may be premature judgments indeed.

In Defense of Not Having a Clue

Timely, both in our post-truth world and for my current thinking, Bobby Duffy of the British polling company IPSOS Mori recently released The Perils of Perception, stealing the subtitle I have (humbly enough) planned for years: Why We’re Wrong About Nearly Everything. Duffy and IPSOS’s Perils of Perception surveys are hardly unknown for an informed audience, but the book’s collection and succint summary of the psychological literature behind our astonishingly uninformed opinions, nevertheless provide much food for thought.

Producing reactions of chuckles, indignation, anger, and unseeming self-indulgent pride, Duffy takes me on a journey of the sometimes unbelievably large divergence between the state of the world and our polled beliefs about the world. And we’re not primarily talking about unobservable things like “values” here; we’re almost always talking about objective, uncontroversial measures of things we keep pretty good track of: wealth inequality, share of immigrants in society, medically defined obesity, number of Facebook accounts, murder and unemployment rates. On subject after subject, people guess the most outlandish things: almost 80% of Britons believed that the number of deaths from terrorist attacks between 2002 and 2016 were more or about the same as 1985-2000, when the actual number was a reduction of 81% (p. 131); Argentinians and Brazilians seem to believe that roughly a third and a quarter of their population, respectivelly, are foreign-born, when the actual numbers are low single-digits (p. 97); American and British men believe that American and British women aged 18-29 have had sex as many as 23 times in the last month, when the real (admittedly self-reported) number is something like 5 times (p. 57).

We can keep adding astonishing misperceptions all day: Americans believe that more than every third person aged 25-34 live with their parents (reality: 12%), but Britons are even worse, guessing almost half (43%) of this age bracket, when reality is something like 14%; Australians on average believe that 32% of their population has diabetes (reality more like 5%) and Germans (31% vs 7%), Italians (35% vs 5%), Indians (47% vs 9%) and Britons (27% vs 5%) are similarly mistaken.

The most fascinating cognitive misconception is Britain’s infected relationship with inequality. Admittedly a confusing topic, where even top-economists get their statistical analyses wrong, inequality makes more than just the British public go bananas. When asked how large a share of British household wealth is owned by the top-1% (p. 90), Britons on average answered 59% when the reality is 23% (with French and Australian respondents similarly deluded: 56% against 23% for France and 54% against 21% for Australia). The follow-up question is even more remarkable: asked what the distribution should be, the average response is in the low-20s, which, for most European countries, is where it actually is. In France, ironically enough given its current tax riots, the respondents’ reported ideal household wealth proportion owned by the top-1% is higher than it already is (27% vs 23%). Rather than favoring upward redistribution, Duffy draws the correct conclusion:

“we need to know what people think the current situation is before we ask them what they think it should be […] not knowing how wrong we are about realities can lead us to very wrong conclusions about what we should do.” (p. 93)

Another one of my favorite results is the guesses for how prevalent teen pregnancies are in various countries. All of the 37 listed countries (p. 60) report numbers around less than 3% (except South Africa and noticeable Latin American and South-East Asian outliers at 4-6%), but respondents on average quote absolutely insane numbers: Brazil (48%), South Africa (44%) Japan (27%), US (24%), UK (19%).

Note that there are many ways to trick people in surveys and report statistics unfaithfully and if you don’t believe my or Duffy’s account of the IPSOS data, go figure it out for yourself. Regardless, is the take-away lesson from the imagine presented really that people are monumentally stupid? Ignorant in the literal sense of the world (“uninstructed, untututored, untaught”), or even worse than ignorant, having systematically and unidirectionally mistaken ideas about the world?

Let me confess to one very ironic reaction while reading the book, before arguing that it’s really not the correct conclusion.

Throughout reading Duffy’s entertaining work, learning about one extraordinarily silly response after another, the purring of my self-indulgent pride and anger at others’ stupidity gradually increased. Glad that, if nothing else, that I’m not as stupid as these people (and I’m not: I consistently do fairly well on most questions – at least for the countries I have some insight into: Sweden, UK, USA, Australia) all I wanna do is slap them in the face with the truth, in a reaction not unlike the fact-checking initiatives and fact-providing journalists, editorial pages, magazines, and pundits after the Trump and Brexit votes. As intuitively seems the case when people neither grasp nor have access to basic information – objective, undeniable facts, if you wish – a solution might be to bash them in the head or shower them with avalanches of data. Mixed metaphors aside, couldn’t we simply provide what seems to be rather statistically challenged and uninformed people with some extra data, force them to read, watch, and learn – hoping that in the process they will update their beliefs?

Frustratingly enough, the very same research that indicate’s peoples inability to understand reality also suggests that attempts of presenting them with contrary evidence run into what psychologists have aptly named ‘The Backfire Effect’. Like all force-feeding, forcing facts down the throats of factually resistent ignoramuses makes them double down on their convictions. My desire to cure them of their systematic ignorance is more likely to see them enshrine their erroneous beliefs further.

Then I realize my mistake: this is my field. Or at least a core interest of the field that is my professional career. It would be strange if I didn’t have a fairly informed idea about what I spend most waking hours studying. But the people polled by IPSOS are not economists, statisticians or data-savvy political scientists – a tenth of them can’t even do elementary percent (p. 74) – they’re regular blokes and gals whose interest, knowledge and brainpower is focused on quite different things. If IPSOS had polled me on Premier League results, NBA records, chords or tunes in well-known music, chemical components of a regular pen or even how to effectively iron my shirt, my responses would be equally dumbfunded.

Now, here’s the difference and why it matters: the respondents of the above data are routinely required to have an opinion on things they evidently know less-than-nothing about. I’m not. They’re asked to vote for a government, assess its policies, form a political opinion based on what they (mis)perceive the world to be, make decisions on their pension plans or daily purchases. And, quite a lot of them are poorly equipped to do that.

Conversely, I’m poorly equipped to repair literally anything, work a machine, run a home or apply my clumsy hands to any kind of creative or artful endeavour. Luckily for me, the world rarely requires me to. Division of Labor works.

What’s so hard with accepting absence of knowledge? I literally know nothing about God’s plans, how my screen is lit up, my car propels me forward or where to get food at 2 a.m. in Shanghai. What’s so wrong with extending the respectable position of “I don’t have a clue” to areas where you’re habitually expected to have a clue (politics, philosophy, virtues of immigration, economics)?

Note that this is not a value judgment that the knowledge and understanding of some fields are more important than others, but a charge against the societal institutions that (unnaturally) forces us to. Why do I need a position on immigration? Why am I required (or “entitled”, if you believe it’s a useful duty) to select a government, passing laws and dealing with questions I’m thoroughly unequipped to answer? Why ought I have a halfway reasonable idea about what team is likely to win next year’s Superbowl, Eurovision, or Miss USA?

Books like Duffy’s (Or Rosling’s, or Norberg‘s or Pinkers) are important, educational and entertaining to-a-t for someone like me. But we should remember that the implicit premium they place on certain kinds of knowledge (statistics and numerical memory, economics, history) are useful in very selected areas of life – and rightly so. I have no knowledge of art, literature, construction, sports, chemistry or aptness to repair or make a single thing. Why should I have?

Similarly, there ought to be no reason for the Average Joe to know the extent of diabetes, immigration or wealth inequality in his country.