Yearly Archives: 2009

Banks, Central Banks and Money

One misconception about the mechanics of money that I mentioned in my last post is the idea that banks can hoard their reserves at the central bank* rather than lending them out.

Here I will explain why this idea simply does not make sense, but no more casinos and gaming chips. No more senior croupiers and casino cashiers. I will dispense with the metaphor and instead stick to a more prosaic explanation, looking at interactions between banks and central banks.

All banks have their own accounts with the central bank. Often these are called “reserve accounts”, although in Australia they are called “exchange settlement accounts” (ESAs). As the Australian terminology suggests, the primary function of these accounts is to facilitate settlement of transactions that take place between banks. To keep it simple here, I will stick to the terminology of “reserve accounts”.

To see how this works, imagine I make a $100 purchase from a shop on my credit card. If the shop banks with the same bank as I do, all that happens is that our bank increases the balance of my credit card by $100 and also increases the balance in the shop’s bank account by $100. With a couple of simple accounting entries and no movement of any physical currency, the transaction is complete. In fact, as was discussed in the casino money post, this simultaneous $100 loan advance to me and $100 deposit raising for the shop has effectively “created” an additional $100 of money in the economy that was not there before.

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How Money Works

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Over the last couple of years as the global financial crisis unfolded, a subject I have spent a lot of time thinking about is the nature of money. I have been planning a blog post on the topic and the time has finally come.

The catalyst for finally writing this post was attending last week’s 16th national conference on unemployment at the University of Newcastle, hosted by the Centre of Full Employment and Equity (CofFEE). I found myself there because the centre’s director, Professor Bill Mitchell, is the author of billy blog, which I read regularly. Bill’s research and advocacy in the area of unemployment and underemployment is firmly rooted in a detailed understanding of how money works in a modern economy (hence the appeal for me) and the implications these mechanics have for government spending policy. This theme also underpinned many of the talks at the conference and the program included a panel discussion on the subject of “Modern Monetary Theory”. The panel comprised Bill Mitchell, Randy Wray and Warren Mosler, all strong advocates of what is sometimes referred to as “chartalism”. Along with another billy blog regular, Ramanan, I was invited to participate by providing a brief wrap-up at the end of the discussion.

But how hard can it really be to understand how money works? You earn it and you spend it or save it. Or, as the textbooks would have it, money serves as both a medium of exchange and a store of wealth. Is there anything more to say?

In fact there is. Most people and, indeed, many economists have not given very much thought to the mechanics of money and this leads to a number of misconceptions, all of which have made frequent appearances in the press and in political debate around the world over the course of the financial crisis. One example is the suggestion that the UK government could run out of money, an idea given further credence by the decision of rating agency Standard & Poor’s to put the UK’s rating on “negative outlook”. Even Barack Obama seems to be saying that the US is running out of money. The fact is, governments in many developed countries simply cannot run out of money. China could (but it is very unlikely) and so could member states of the European Monetary Union, but the US, UK, Japan and Australia could not. I will explain why here. In later posts I will continue the theme of the mechanics of money and will look at other misconceptions such as the idea that banks can “hoard” their reserves at central banks or that government deficits inexorably lead to high interest rates (the short answer to this one is: look at Japan).

In this post I will start with the basics of how money works and cover the following points:

how lending can “create” money
the limits to money creation
the difference between “fiat” money and money that is convertible on demand

A useful parallel to money in a real economy can be found in gaming chips in a casino. So, imagine a fairly standard sort of casino. You walk in, James Bond-style, hand over a thousand dollars to the cashier and get a pile of chips in return. The chips are marked with various denominations and total one thousand. This is an old-fashioned sort of casino: every game is played on a green felt table, there is not a poker machine in sight and, of course, you need your chips to play. To make your stay easy, you can also use your chips to buy drinks and snacks. When you have finished your evening’s play, you can redeem any chips you have not gambled away for cash.

There might be hundreds of thousands of dollars worth of chips circulating around the casino, but so far behind every chip is a corresponding amount of money sitting in the cashier’s safe. If we call this money the casino’s “reserves”, then the chip supply in circulation around the tables is equal to the casino’s dollar reserves. Of course, there might be a few cases of chips in the croupier’s office and even a chip-pressing machine in the basement, but these chips are not yet in circulation. They are just waiting to be handed over to the next patron who walks in the door with a full wallet. Under this regime, every gambler can be completely certain that they will be able to redeem their winnings at the end of the night.

While your thousand dollar stake might seem like a lot, there are a few high-rollers who frequent the place who like to play with much larger sums. Rather than producing chips with very high denominations, this casino has introduced convenient “smart chip cards”. High rollers can pay the cashier as much money as they like and the cashier will add it to the virtual chip balance on their smart cards. At every gaming table, the croupier has a card reader which can be used to debit the balance on the card in return for actual chips. This means that the total chip supply in circulation is the sum of actual chips and virtual chip balances on the smart cards. But still, this chip supply is matched by money in the cashier’s safe.

Now suppose you are a trusted regular at the casino and one night you turn up short of cash. No problem, the casino is happy to advance you your thousand dollars in return for a quickly scribbled IOU with your signature. Your credit is good. You take your $1,000-worth of chips and walk to the Blackjack table. But now something has changed. The total chip supply in the casino is $1,000 higher than the money in the cashier’s safe. In theory this could be a problem. You could immediately lose the $1,000 in chips and walk out. Then if everyone in the casino wanted to redeem their chips, there would not be enough money to go around. But, it isn’t likely to be a problem in practice. The casino operates 24 hours a day and so there are always far more than $1,000 in chips in circulation. On top of that, the house takes a decent cut on the tables, so it would not take very long for the casino to win back over $1,000-worth of chips and then $1,000 can be held back from the profits that the cashier regularly sends up to the manager’s office. In fact, the credit seems so safe, the casino decides to offer credit more widely. While they are at it, they introduce a few other innovations, like offering lucky door prizes in chips, which also adds to the supply of chips in circulation without a corresponding increase in money in the cashier’s safe.

These loans that the casino has introduced give it the ability to “create” an additional supply of chips. But not all lending creates new chips. If instead of borrowing from the house, you had offered your IOU to a high-rolling friend you would still get your $1,000 in chips for the evening, but you got them from your friend so the chip supply does not change.

The new lending arrangements are working well, but the system is limited by the fact that the cashier does not know all of the patrons very well, and is naturally being very cautious about who to lend chips to. To manage this bottleneck, the casino decides to allow senior croupiers to provide loans to gamblers they know well as long as they take responsibility for the credit-worthiness of the borrower. So now getting credit is simply a matter of providing an IOU to the senior croupier who knows you best and he or she will charge up your smart chip card. If you need actual chips, that is not a problem either as the senior croupier has a stash under the table borrowed from the cashier. Of course, the croupier is taking a bit of a risk providing you with this advance since the house expects him or her to make good any amounts you do not repay. So to make it worth their while, you give the croupier a few chips for their trouble each time you need an advance. This works so well that the cashier no longer offers loans directly to anyone other than the senior croupiers.

As successful as the new arrangements are, the casino does have to be very careful about putting strict limits on the number of chips that the senior croupiers can create through lending. Otherwise, the day may come when there are simply too many chips and not enough money in the safe and a successful gambler may walk up to the cashier to cash in their chips only to find that the cashier does not have enough money in the safe. Word will spread and everyone will want their money back, but the casino will be unable to oblige. It would be bankrupt. So while there may be no limit to the number of chips that the casino could physically manufacture (and of course it has complete control of smart chip card balances), there is a constraint on the number it can put into circulation. This constraint is a direct consequence of the fact that chips are redeemable for cash.

The analogy to the real economy should be clear here. The cashier operates like a central bank and government treasury combined. The senior croupiers are the banks. Chips are money and smart chip card balances correspond to bank account balances. In the same way that senior croupier lending effectively creates new chips, so bank lending adds to the money supply in an economy. But what is the analogy to the money in the cashier’s safe? While central banks around the world do maintain reserves of gold and foreign currencies (think of all the US dollars that the central bank of China has), for many countries the analogy breaks down in one important respect.

The casino made a commitment to redeem your chips for cash. Some central banks do make similar commitments. In the days of the gold standard, central banks in Australia, the US, the UK and elsewhere would exchange currency for gold. Of course there were times, as in war, when this convertibility was suspended, but in those days having something backing money was seen as just as important as having money backing chips in a casino. The gold standard system was abandoned after the second world war and instead, under the Bretton Woods system, domestic currencies could be exchanged at the central bank for a fixed number of US dollars. This system collapsed in turn in the 1970s. Today, some countries such as China do maintain currencies pegged to the US dollar (or some other currency) and so still make a commitment of convertibility. However, most countries have adopted so-called “fiat” money. The word fiat is Latin for “let it be” and fiat money does not derive its value from any form of backing. It is declared to be money, and so it is. Many people still assume that Australian dollars are in fact backed by something, but if you tried to take a $10 note to the Reserve Bank of Australia, you would be lucky to get two $5 notes in return. You could certainly not be assured of getting any particular amount of gold or US dollars.

Some people find the entire concept of fiat money deeply disturbing and pine for a return to the “real” money days of the gold standard. But fiat money is in fact an extremely powerful innovation. In the casino analogy, the cashier must always be careful about how many chips are put into circulation to avoid the crisis of being unable to convert chips back to cash. However, in a country with fiat money, the central bank makes no convertibility commitments, so this risk simply does not exist. It has monopoly power in the creation of currency. So, the government simply cannot run out of money. There may be very good reasons for a government to curb its spending. For example, it may not want to add too much to demand in the economy because it is concerned about inflation. But running out of money is not one of those reasons, whatever the president of the United States may think.

I will leave it there for now, as this post is long enough already. But, stay tuned for more on the macroeconomic implications of a modern fiat money system.

Which countries work the hardest?

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Last week over dinner with friends, a debate arose as to whether Australians worked harder than Americans or not. The case for the affirmative argued that many Australians were very successful overseas and indeed Australians working abroad were highly sought after by employers. The case for the negative drew on experiences working with large US firms which exhibited far more aggressive, high-pressure work-practices than Australian firms.

Since we had more wine than data, the argument did not last very long and we instead moved on to the question of whether China now more closely resembles a fascist regime than a communist one (this debate was quickly mired in definitional issues and became rather animated). Reflecting later on the first discussion, I decided to dig up some data on hours worked and attempt to determine a winner for the debate. According to the OECD, Australia and the United States drew very close in 1979 when workers in both countries put in an average of 35 hours per week. But apart from that, over the last forty years US workers have fairly consistently worked an average of 1 to 1.5 hours more each week than Australian workers.

Total Hours Worked per head of Workforce (1950-2008)

And what of the rest of the world? Among the countries covered in the 2008 OECD data, Korea* was by far the most industrious country. Employed Koreans laboured an average of 44.5 hours each week. From there, hours worked fell quickly to Greece on 40.8 hours and then down to the Czech Republic on 38.3 hours. Australia and the United States are in a tightly packed group, ranging from Iceland in seventh place overall on 34.8 hours per week down to Australia in 16th place on 33.1 hours per week. The United States is towards the top of this group, working an average of 34.5 hours and sitting in ninth place overall. The Hanseatic League is not what it once was as Germany, Norway and the Netherlands are clustered at the bottom of the league table, all putting in around 27 hours of work each week.

National Ranking of Hours Worked in 2008*

One shortcoming of these figures is that they do not give an indication of the total effort contributed to each country. This is because the averages are calculated per head of the workforce and ignores children, the unemployed, the sick and the retired. It is conceivable that in countries with fewer workers, those workers may have to work harder to support everyone else. Indeed, recalibrating the numbers based on total hours worked per head of the total population does change the rankings somewhat. Korea still puts in a good showing, but surrenders first place to Luxembourg. Australia climbs a few places to 11th place and in the process pulls one place ahead of the United States, reflecting in part the higher unemployment rate in the United States. Coming in last place is France, which puts in an average of only 13.5 hours of labour per capita.

Two Measures of Hours Worked in 2008*

But is this data enough to resolve the debate? Unfortunately not. There are too many things that this kind of broad data does not capture. For instance, underemployment is a significant concern in many countries, including Australia and the United States. If there are many people not working as many hours as they would like to, actual hours worked may not be a good indication of the relative industriousness of different countries. Segmentation is another problem. Before our dinner-table debate moved on to China, speculation arose about possible differences in work patterns in US firms based in large cities on the East and West coasts compared to workplaces around the rest of the country. Again, aggregate statistics cannot capture any such differences.

So next time this particular group of friends meets, I will have some data to bring to the table, but not enough to carry the argument.

* Only 2007 data is available for Korea. All other data is for 2008.

Deceptive Charts #2

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Last month I wrote about the dangers of secondary axes, but even charts with a single axis can be deceiving. I have been reflecting on this after reading Jon Peltier’s critique of Microsoft’s “professional” charting tutorials earlier this week. One of the charts Peltier takes issue with is a column chart which has the value axis starting at 100 rather than zero. He writes:

This is a major chart fail. The value axis on a column or bar chart should always include zero. Always. If you want to expand the scale to help resolve the values, then a column chart is not the right chart type.

In today’s Silicon Alley Insider chart of the day I saw exactly the same chart fail. The chart, which I have reproduced below, shows the ranking of various magazines and newspapers by the wealth of their readers (the data is taken from a report by B to B Media Business).

Median Income of Readers – Silicon Alley Version

This chart may do a good job of highlighting the Wall Street Journal leading position, thereby supporting Silicon Alley’s headline “The Journal Has The Richest Readership Among Print Pubs”. But it also gives a distorted impression of just how solid the Journal’s lead is. Starting the income axis at zero, shown in the chart below, gives a rather different impression. The Wall Street Journal still sits at the top, but the variation across the titles is much less significant than the original chart suggested.

Median Income of Readers – Zero-based Version

Nevertheless, precisely because it displays less variation in the data, the zero-based chart does seem less useful and it is harder to read the values. Commenting on Peltier’s post and musing on my posterous Extras blog, I wondered whether starting axes with zero should be considered an inviolable rule of charting. One of the gurus of data visualisation is William S. Cleveland. In his book “The Elements of Graphing Data” he gives this advice: “Do not insist that zero always be included on a scale showing magnitude”. He goes on to make this argument:

For graphical communication in science and technology assume the viewer will look at the tick mark labels and understand them. Were we not able to make this assumption, graphical communication would be far less useful. If zero can be included on a scale without wasting undue space, then it is reasonable to include it, but never at the expense of resolution.

At first glance this would seem to get the Silicon Alley Insider out of chart jail. But the story does not end there. Cleveland’s book focuses on scientific charts, particularly line and scatterplots (also known as X-Y plots) and there is scarcely a bar or column chart to be found. Furthermore, in his paper “Graphical Methods for Data Presentation: Full Scale Breaks, Dot Charts, and Multibased Logging” (The American Statistician, November 1984), he makes the following observations:

The bar of a bar chart has two aspects that can be used to visually decode quantitative information—size (length and area) and the relative position of the end of the bar along the common scale. The changing sizes of the bars is an important and imposing visual factor; thus it is important that size encode something meaningful. The sizes of bars encode the magnitudes of deviations from the baseline. If the deviations have no important interpretation, the changing sizes are wasted energy and even have the potential to mislead (Schmid 1983).

Cleveland’s solution to showing data variation without having bar lengths deceive was to invent a new type of chart: the “dot plot”. Dot plots, which I have used here on the Stubborn Mule to illustrate statistics on asylum-seekers and universities, use position alone to encode the data. This means that it is much safer to drop zero from the axis. Although rather tricky to produce using Microsoft Excel (I use the R package), they are a good substitute for bar and column charts. This BeyeNetwork article goes into more detail about dot plots, including the use of multi-panel plots, which I will look at in a future post.

So, here is a dot plot version of the newspaper and magazine rankings by reader income.

Median Income of Readers – Dot Plot Version

Now you know to be vigilant against the deceptive use of axis scales.

Mahalo 3.0: my new mechanical Turk

Hot and Dry Days Ahead for Australia

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Earlier this month, the Australian Bureau of Meteorology released the October figure for the Southern Oscillation Index (SOI). It showed a precipitous plunge of almost 20 points down to -14.6. Just how significant a drop this is can be seen in the chart below, which shows the distribution of monthly changes in the SOI going back to 1876 (-14.6 is at the lower 5% quantile, which means that a fall as big as this, or bigger, has only occurred 5% of the time).

Distribution of SOI changes (Jan 1876-Oct 2009)

But what exactly is the SOI and what is the significance of this decline in the index? The index is the standardised anomaly of the monthly average difference in sea-level air pressure between Tahiti and Darwin. “Standardised anomaly” means that the index measures the deviation of this pressure difference from the long-term average and is scaled by the standard deviation of the pressure difference and then multiplied by 10. The significance of the index lies in its relationship to the El Niño weather phenomenon. According to the Bureau of Meteorology:

Sustained negative values of the SOI often indicate El Niño episodes. These negative values are usually accompanied by sustained warming of the central and eastern tropical Pacific Ocean, a decrease in the strength of the Pacific Trade Winds, and a reduction in rainfall over eastern and northern Australia. The most recent strong El Niño was in 1997/98, although its effect on Australia was rather limited. Severe droughts resulted from the weak to moderate El Niño events of 2002/03 and 2006/07.

The chart below gives a historical perspective of the SOI over the last ten years. To get a better sense of the trends in the index, I have overlaid two different types of curve smoothing: a lowess (“locally-weighted scatterplot smoothing”) curve and a spline curve. The two give very similar results and make the 2002/03 and 2006/07 SOI downturns clearly visible. The timing of these downturns suggest that the corresponding droughts follow with something of a lag.

Southern Oscillation Index (Jan 2000-Oct 2009)

Over the last couple of years, the SOI has been solidly in positive territory and, again with a lag, there has followed an improvement in drought conditions. Indeed, New South Wales recently replaced the tight water restrictions which had been in place for a number of years with the less onerous “Water Wise” rules. Unfortunately, this change may turn out to have been premature. If the downward trend in the index seen over the last few months persists, Australia may face a return to severe drought conditions.

For anyone who is interested in how these charts were created, here is the R code. It is also available from the Stubborn Mule files section.

UPDATE: at the request of singingfish, here is a chart showing the full recorded history of the SOI back to 1876. The blue line is a spline smoothed curve.

Southern Oscillation Index (1876-2009)

Melbourne Cup by Numbers

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I don’t know anything about horses. Ever since I was bitten by one at the Easter Show as a small child, they have ranked very low on my animal preference list: only just above geese. Still, at this time of year almost everyone in Australia gets caught up in some way with the Melbourne Cup, the race that stops the nation. As usual, I expect that my involvement will only stretch as far as participating in the $2 sweep at the office, thereby avoiding the need to actually make any kind of ignorance-based horse selection.

But, with a mule as this blog’s mascot, you would think that I could do better than that, so I have thrown my charting skills at the history of previous winners in as slap-dash a manner as I can to see where playing the historical odds would get me.

I thought I would start with colour because, even as a racing-form novice, I suspect that should have no bearing on the result and so it seems like a safe place to start. Based on the winners going back to 1861, here is the distribution of winning colours.

Cup Winners by Colour (1861-2008)

This suggests that bay-coloured horses have an edge (or maybe it is just a common colour for a horse). What about the “sex” of horse (please do not ask me what all of these terms mean, but apparently “horse” is a sex)?

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The Kindle in Australia

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Earlier this week, Amazon began shipping the international version of the “Kindle” electronic book reader for US$279. The first generation of the Kindle was released almost two years ago in the US, so it has been a long time coming. But, with the announcement this week of the competing Barnes & Noble “Nook“, it looks as though the era of the e-book reader is well and truly upon us.

The Kindle has a monochrome “electronic paper” screen rather than the pervasive LCD screens found on laptops, iPhones and BlackBerries. Also known as e-paper or e-ink, the electronic paper screen comes a lot closer to replicating the appearance of traditional printed paper. There is no back-light and in fact displaying a page draws no power, it is only changing the display that will draw on the battery. As a result, the battery life of electronic paper devices is much longer than other devices. Amazon claims that, with the wireless connection turned off, you can read on the Kindle for up to two weeks before draining the battery. This also means that the Kindle can display an image on the screen when it is powered off, which is somewhat disconcerting at first. Although the contrast is not quite as high as print (the background is not quite white and the text is a little grey), reading on the Kindle is very comfortable. Better still, the quality does not degrade in strong sunlight as is often the case for LCD screens (although they are getting better all the time). So reading the Kindle outside is just as easy as it is in bed (although you will still need a bedside light).

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Petrol Price Update

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Another five months on since my last petrol price update and oil prices have continued to rise, but so has the value of the Australian dollar. So while crude oil prices in US dollars are up around 75% since their lows in February, they are only up 29% in Australian dollar terms.

West Texas Intermediate Oil Prices

The Australian dollar has been rising steadily for the last six months, pushed along by the Reserve Bank of Australia which has started raising their target cash rate. Higher interest rates in Australia make it more attractive for offshore investors to buy Australian securities and they have to buy Australian dollars to do so. Australian investors holding foreign assets may do the same.

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I have a love/hate relationship with psychometric testing

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A while ago, I had a bit of a rant in the post I Hate Personality Tests. Responding in this guest post, Maria Skarveli (who knows far more about psychology than I do) ponders personality testing phobia.

As a psychology student belonging to the faculty of health and behavioural sciences which also harbours biology, medical science and physiology, I was constantly hassled by my friends that were studying law, commerce and engineering and forever asking me “Can you read my mind?” or worse “Are you trying to analyse me?” as if I was Professor Xavier and I could distinguish mutants from humans. Of course I had to keep a straight face and stop myself from saying, “You’re an idiot, there you have it analysis complete” I just rolled my eyes and went with the flow. But deep down I was insulted. It was bad enough psychology had been branded as a “soft science”, which is apparently less intellectually stimulating than the “hard sciences” such as biology, physics and chemistry. But now the general view from all faculties was that psychology is akin to the paranormal, dare I say astrology!

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