Britain’s pre credit-crunch borrowing

Update: Corrected the link to the ONS data.

A lot of commentary regarding Britain’s economy focuses on the huge debts that the government have built up and the effects of the “credit-crunch” and recent recession. When considering this issue, it is worth remembering that Gordon Brown, as chancellor, built up large debts prior to the credit crunch. Using figures taken from a recent bulletin from the Office for National Statistics (see page 15), Britain’s debt going back to 2001 was:

Year Debt (£ billions) Debt (% GDP)
2001 323 30.9
2002 348.1 31.5
2003 380.1 32.4
2004 424 34.5
2005 465.1 36.2
2006 500.9 36.7
2007 634.4 44.2
2008 733.9 51.7
2009 866.2 61.4

Thus we can see that by 2007, the year that Northern Rock ran into trouble, the government had increased the national debt from 30.9% of GDP in 2001, to 44.2% of GDP. This during a period when the economy and tax receipts were both growing.

The government was constantly spending more than it was receiving in taxes from 2002 onwards.

As a result of the credit-crunch and resulting recession, we’ve seen the debt shoot up to 61.4% of GDP since 2007. Had Brown balanced the budget in the years 2002 to 2007, the debt would have been over 13% of GDP lower when trouble hit, and the government would have had more room for maneouvre, probably resulting in a less severe recession as a result.

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Britain’s GDP has fallen by almost 5% since Gordon Brown became PM

Wat Tyler writes:

For the first time ever, Her Majesty has a Prime Minister who has presided over a fall in GDP per capita – and not a small fall either. Since the idiot Brown took over less than three years ago, per capita GDP has fallen by a catastrophic 5%.

Here’s the complete Prime Ministerial record up to end-2009 (per capita GDP at basic prices; ONS data and BOM calcs):

Churchill (1953-55) +7%
Eden (1955-57) +2%
Macmillan (1957-63) +15%
Douglas-Home (1963-64) +4%
Wilson (1964-1970 and 1974-1976) +15%
Heath (1970-74) +12%
Callaghan (1976-1979) +7%
Thatcher (1979-1990) +26%
Major (1990-97) +13%
Blair (1997-2007) +27% (yes, on this measure, he beat Thatcher)
Brown (2007-2009) -5%

Please take a moment to absorb that list. Brown’s record is miles worse that Callaghan’s – despite all those Red Robbo strikes and the Winter of Discontent. And it’s miles worse that Eden’s – widely reckoned to be our worst post-WW2 PM.

Indeed, the damage suffered under Brown has been so extensive, average incomes have now fallen back to their level five years ago – the most dismal five years we’ve seen since the Coronation.

Of course Brown isn’t out of office yet and the final result when he does go may be more favourable to him. However we’ve just experienced the deepest recession of the post WW-II era, and it’s possible it may not be over yet. Also, if the comment about GDP falling back to where it was 5 years ago is correct, it means that the gains made since Labour were re-elected for their third term have been wiped out.

One might complain that in the case of e.g. Thatcher and Major, they both experienced recessions but were in power for a sufficiently long time to see growth return, whilst the current/most recent recession hit Britain not long after Brown became PM and has thus dominated the statistics for his period in office. The problem with this line is that Brown as PM is reaping the consequences of his earlier policies as Brown the Chancellor, i.e. he is primarily responsible for the problems that led to this mess. In the case of the Tories, that was true of the early 1990s recession but the early 1980s recession was an inheritance from the previous Labour government,

An interesting comparison is to look at the GDP with each of the last few recessions and figure out how many years growth were wiped out in each case. Looking at the GDP for each year from 1948 to 2009, courtesy of the ONS, we can see that the 2009 had a lower GDP than 2008, 2007 and 2006. In the previous recession, 1991 was the lowest yearly GDP (though the recession didn’t end until 1992), lower than 1990 and 1989 respectively. In the recession of 79-81, the GDP for 1981 was lower than 1980 and 1979 respectively. In other words the recession has been worse than either of the recessions the last Tory governments had to deal with.

This is reinforced when you look at the %age drop in GDP from the previous high point for each of the recessions. Using the yearly figures, in 2009 the percentage drop was 4.85% (from a high in 2008), for the previous recession it was 1.39% (from a high in 1990) and for 1981 it was 3.38% (from a high in 1979).

Using the quarterly figures, for Q3 2009, the most recent low point, the drop from the previous high (Q1 2008) was 6.03%, where for Q2 1992 (the low point of that recession), the drop was 2.54% from the previous high (Q2 1990). For Q1 1981 the drop was 6.00% from the previous high in Q2 1979. Admittedly, on this measure, that recession is almost as bad as the 2008/9 one in terms of the drop from the previous high, but the 2008/9 recession achieved this drop in a shorter timescale, i.e. it was a sharper recession.

Also, it’s possible the economic woe for the 2008/9 recession isn’t over yet.

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We were misled about the revised growth figures

On Friday, 26th February the BBC (and this misleading ONS press release) were reporting (e.g. this report) that revised figures showed an 0.3% rate of growth in the final quarter of 2009 vs the original 0.1% estimate that quarter, implying things weren’t as bad as had been initially estimated.

What such reports failed to mention (as Edmund Conway reports on his Telegraph blog) was that the ONS revised figures affected earlier quarters of 2009, that the recession was deeper than originally estimated and that we finished 2009 with a lower GDP than was originally estimated!

For example, the current estimate for 2009 Q4 growth, states that the GDP is 3.3% lower for Q4 2009 compared to Q4 2008, where the previous preliminary estimate said it was only 3.2% lower than for Q4 2008.

I.e. according to the new estimates, our economic situation was worse, not better, than the old estimates suggested, yet by focusing on the 0.3% vs 0.1% figure for growth in the final quarter, the BBC and the ONS press release implied that the revisions suggested things had not been as bad as feared.

Background Links:

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On the scope for cutting public spending

Currently, the major political parties in Britain seem to agree that some cuts in public spending are required in order to help bring the soaring, post credit-crunch, budget deficit under control. However they are reluctant to indicate exactly what they will cut and are also reluctant to imply that any major cuts will be made this year (let alone this side of the election which must be held by the summer). The most you tend to get is the mention of a few specific items adding up to at most a few billion (a small percentage of total spending).

This reluctance is understandable. For much of the time since 1997, if a party (usually the Tories) talked about spending cuts, especially if they start attaching figures to the desired levels of cut,  their opponents (usually the government or the Labour party) will ask how many doctors, nurses, teachers, policemen, schools or hospitals will be scrapped, or claiming it will lead to some scary number of them being scrapped, as if any significant cuts in public spending must necessarily hit frontline public services. The political tactic is to suggest to voters that any cuts must entail fewer schools, hospitals, doctors, teachers, etc, and thus those proposing cuts will endanger the services voters care about.

John Redwood, writing in the Telegraph, suggests that actually there may be more scope for cuts that don’t impact public services than debates on this issue usually acknowledge:

The good news is cutting public spending is technically easy when you look at just how much needless and wasteful spending there is.

Anyone saying you can cut without sacking a single nurse, doctor, teacher or uniformed person is usually ridiculed, but it is true.

Out of the 6 million state employees, only around 1 million are these essential front line workers.

Over the last few years public sector efficiency has failed to rise, whilst private sector efficiency regularly rises by 2.5% a year or more.

It is possible to do more for less in the public sector, by applying some of the disciplines of the well run office, shop or factory.

Further support for suggesting there is scope for cutting public spending without touching frontline services can be found in a graph on page 12 of the 2009 Pre-Budget Report. It lists the £676 billion worth of projected public spending for 2009/2010 broken down into the following categories:

  • Social protection £190 billion.
  • Personal social services £29 billion.
  • Health £119 billion.
  • Transport £23 billion.
  • Education £88 billion.
  • Defence £38 billion.
  • Industry, agriculture and employment £21 billion.
  • Housing and environment £30 billion.
  • Public order and safety £36 billion.
  • Debt interest £30 billion.
  • Other £72 billion.

I.e. there is £72 billion worth, over 10% of the total, being spent in addition to the budgets for education, health, industry, the environment, transport, public order and safety, social protection, personal social services, defence, housing and even the payment of  debt interest.

How much of this spending is necessary? Could we not make cuts here without harming front line services? This depends on what the £72 billion is being spent on. The notes in the chart explain: “Other expenditure includes general public services (including international services); recreation, culture, and religion; public service pensions; plus spending yet to be allocated and some accounting adjustments.”

I wonder how much of spending on recreation, culture and religion is really necessary?

What “general public services” are left after you factor the public services covered in the other major categories of spending?

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The credit bubble and the market

Matthew Parris makes an interesting point:

So amid all the doom-mongering and recanting, I have an assertion to make. The market has not failed. The present collapse is evidence that the market is working. Confidence bubbles are an inherent feature of a free market system. Panics — confidence vacuums — are an inherent feature too. The test of the theory of market capitalism is whether the system provides from within itself the means to prick both.

It does. The first — a confidence bubble — has been pricked. We are now sucking ourselves the other way: into a confidence vacuum. In time this too will be pricked. The market will steady.

The bubble that has just burst was based, worldwide, on financial services. Financial services are a product. It is true they are a product critical to the efficient functioning of the market (so is electricity, so is oil) but that just makes them an unusually important product. From time to time products fail in any market. They may fail through force majeure — droughts, floods, pestilence. They may fail due to inherent flaws — airships, Thalidomide, blue asbestos. Or they may fail through ignorance, trickery or the credulity of human beings — Madoff, the property bubble, the repackaging of sub-prime debt.

The present financial crash has been precipitated by product failure of the third kind. Trade in financial instruments too opaque for even those who traded in them to assess them properly, and bonus incentive schemes that acted against the interests of the companies offering them, fuelled a banking bubble that has now burst.

But ask: what pricked it? Did politicians rumble the trade? Did governments, or international forums or symposiums, provide the sharp instrument? Did academic research and expertise expose the dodgy product? Did statutory regulators apply the pin? No, the free market wised up and pricked this bubble. Politicians and finance ministers (if they had had the power) would have tried to keep it inflated. The market puffed itself up, and then, without intervention — despite intervention — the market let itself down. The speed with which this has happened has been awful, but however inconvenient for many or catastrophic for a few, correction is not a failure of the market, but a success.

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The Credit Crunch: What the lenders were doing

From “The Crunch”, by Alex Brummer, pages 42-43:

To get an idea of how all this worked in practice, and to understand why it was built on such shaky foundations, take the fictional example of Mr and Mrs Jerome Smith of downtown Cleveland. They are persuaded by Fast Talking Mortgage Brokers Inc. (FTMB) to buy their shabby clapboard property with a $100,000 mortgage. The interest rate of 10 per cent is being waived for the first two years. In fact, interest has not been forgiven but is being rolled up with the original mortgage, increasing the debt to $120,000. FTMB, having taken an arrangement free from the Smiths, then sells on the mortgage to Grasping Investment Bank (GIB) of New York, which pays the broker a commission for the mortgage. GIB wraps up the Smiths’ loan with dozens of other loans to other Smiths from poor neighbourhoods around the country and renames it Smith Mortgage Obligation (SMO), and then pays its favourite credit rating company, Stamped & Correct, to certify the SMO as good quality debt. The attraction of this SMO is its 10 per cent return at a time when government bonds are getting between 2 and 3 per cent.

But rather than selling SMO directly to clients, GIB takes another route. It creates a new company — a special purpose vehicle called GIB Capital — and this borrows from other banks cheaply and uses the money to buy Smith Mortgage Obligation. GIB then offers shares in GIB Capital, now the proud owner of SMO, to clients, who lap up the shares because of the high return.

Grasping Investment Bank benefits from the process in several ways. It has collected profits and commission on the sale of the SMO and also benefits from leverage (borrowing) because it is using someone else’s money. GIB has also cleverly placed the SMO off its balance sheet in the special purpose vehicle, which it does not have to disclose on its accounts as a liability. It can stretch its capital further and will not have the regulator on its back.

Thus not only are mortgages given to people who are likely to find it difficult to pay them, but they are rated on a dubious basis, responsibility for them is diffused amongst several players, proper accounting of the debt is obscured by creating the special purpose vehicle and extra borrowing from banks is used to facilitate the whole process. It seems to me this process was bound to hide the riskiness of the mortgages from the investors.

Note that SMO in this scenario is an example of a collateralized debt obligation.

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Why do "bubbles" occur in the financial markets?

Virginia Postrel, writing for the Atlantic magazine, discusses experiments some economists have been running that seek to provide insight into the behaviour of financial markets.

The basic idea is simple. You offer the subjects investments which provide 15 regular dividends of $0.24 during the course of the experiment (alternatively you offer a range of possible payments that average $0.24). The subjects then trade those investments with each other. There are 60 rounds of trading, with dividends paid every fourth round.

In theory, no one should pay more than the expected value of the investment at each round of trading, namely the amount of money that is still left on that dividend. At the start, this is $3.60. After the first payment, it falls to $3.36 and so on. This is not what happens. Postrel writes:

Here, finally, is a security with security—no doubt about its true value, no hidden risks, no crazy ups and downs, no bubbles and panics. The trading price should stick close to the expected value.

At least that’s what economists would have thought before Vernon Smith, who won a 2002 Nobel Prize for developing experimental economics, first ran the test in the mid-1980s. But that’s not what happens. Again and again, in experiment after experiment, the trading price runs up way above fundamental value. Then, as the 15th round nears, it crashes. The problem doesn’t seem to be that participants are bored and fooling around. The difference between a good trading performance and a bad one is about $80 for a three-hour session, enough to motivate cash-strapped students to do their best. Besides, Noussair emphasizes, “you don’t just get random noise. You get bubbles and crashes.” Ninety percent of the time.

So much for security.

Why should this be? Postrel suggests:

Experimental bubbles are particularly surprising because in laboratory markets that mimic the production of goods and services, prices rise and fall as economic theory predicts, reaching a neat equilibrium where supply meets demand. But like real-world purchasers of haircuts or refrigerators, buyers in those markets need to know only how much they themselves value the good. If the price is less than the value to you, you buy. If not, you don’t, and vice versa for sellers.

Financial assets, whether in the lab or the real world, are trickier to judge: Can I flip this security to a buyer who will pay more than I think it’s worth?

Why can’t I do the same thing with non-financial goods and services?

My suggestion is as follows. Obviously, for some cases, it is simply not possible (I cannot sell my haircut onto someone else!). In most cases people will buy something in order to use it (rather than to sell it on) and what they will pay for a good limits what anyone else will pay for the good in order to sell it on. In markets where people regularly sell things second hand (books, computers, cars, etc) they do not expect to get the price they got for the new product.

In these cases a used product has less value than an unused product – it may be less shiny, it may have developed some faults, and its lifetime will be shorter than for a new product. The same cannot be said of financial products such as shares or futures. The fact that someone owned a share before I did does not, by itself, devalue the share.

Postrel continues:

In an experimental market, where the value of the security is clearly specified, “worth” shouldn’t vary with taste, cash needs, or risk calculations. Based on future dividends, you know for sure that the security’s current value is, say, $3.12. But—here’s the wrinkle—you don’t know that I’m as savvy as you are. Maybe I’m confused. Even if I’m not, you don’t know whether I know that you know it’s worth $3.12. Besides, as long as a clueless greater fool who might pay $3.50 is out there, we smart people may decide to pay $3.25 in the hope of making a profit. It doesn’t matter that we know the security is worth $3.12. For the price to track the fundamental value, says Noussair, “everybody has to know that everybody knows that everybody is rational.” That’s rarely the case. Rather, “if you put people in asset markets, the first thing they do is not try to figure out the fundamental value. They try to buy low and sell high.” That speculation creates a bubble.

Thus bubbles seem to be an inherent feature of financial markets. Those who profit most buy early and sell midway through the bubble:

In fact, the people who make the most money in these experiments aren’t the ones who stick to fundamentals. They’re the speculators who buy a lot at the beginning and sell midway through, taking advantage of “momentum traders” who jump in when the market is going up, don’t sell until it’s going down, and wind up with the least money at the end. (“I have a lot of relatives and friends who are momentum traders,” comments Noussair.) Bubbles start to pop when the momentum traders run out of money and can no longer push prices up.

Does this mean that no one is to blame for the “credit crunch”?

Well there’s more to this story. After a few repeats of the experiment with the same subjects, you no longer get bubbles. This is not because the participants learn the true value of the dividends though:

But work that Noussair and his co-authors published in the December 2007 American Economic Review suggests that traders don’t reason that way.

In this version of the experiment, participants took part in the 15-round market four times in a row. Before each session, the researchers asked the traders what they thought would happen to prices. The first time, participants didn’t expect a bubble, but in later markets they did. With each successive session, however, they predicted that the bubble would peak later and reach a higher price than it actually did. Expecting the future to look like the past, they traded accordingly, selling earlier and at lower prices than in the previous session, hoping to realize a profit before the bubble burst. Those trades, of course, changed the market pattern. Prices were lower, and they peaked closer to the beginning of the session. By the fourth round, the price stuck close to the security’s fundamental value—not because traders were going for the rational price but because they were trying to avoid getting caught in a bubble.

“Prices converge toward fundamentals ahead of beliefs,” the economists conclude. Traders literally learn from experience, basing their expectations and behavior not on logical inference but on what has happened in the past. After enough rounds, markets work their way toward a stable price.

There is a twist here. The traders end up with behaviour that is optimal for a given environment. Change this environment and their experience may no longer apply. Indeed further experiments confirmed this:

In research published in the June 2008 American Economic Review, Vernon Smith and his collaborators first ran the standard experiment, putting groups through the 15-round market twice. Then the researchers changed three conditions: they mixed up the groups, so participants weren’t trading with familiar faces; they increased the range of possible dividends, replacing four possible outcomes (0, 8, 28, or 60) averaging 24, with five (0, 1, 8, 28, 98) averaging 27; finally, they doubled the amount of cash and halved the number of shares in the market. The participants then completed a third round. These changes were based on previous research showing that more cash and bigger dividend spreads exacerbate bubbles.

Sure enough, under the new conditions, the experienced traders generated a bubble just as big as if they’d never been in the lab. It didn’t last quite as long, however, or involve as much volume. “Participants seem to be tacitly aware that there will be a crash,” the economists write, “and consequently exit from the market (sell) earlier, causing the crash to start earlier.” Even so, the price peaks far above the fundamental value. “Bubbles,” the economists conclude, “are the funny and unpredictable phenomena that happen on the way to the ‘rational’ predicted equilibrium if the environment is held constant long enough.”

One can draw various implications from this. Postrel mentions two:

  • That people should beware markets where lots of cash chases a few good deals. Presumably she has in mind the research showing that increasing the amount of cash increaases the risk of a bubble occurring.
  • That big changes in the financial markets can cause bubbles even with experienced traders since their knowledge is no longer valid.

I’d add that it follows that if state intervention in financial markets causes an increase in the amount cash in those markets, it risks generating a bubble. There is also an increased risk if state interventions (or anything else) nullify the experience the traders in those markets have, or if such interventions encourage large numbers of inexperienced people to enter the markets.

Both Postrel and Charles R. Morris, author of The Trillion Dollar meltdown, point out that the cutting of interest rates by the Federal Reserve frees up more cash to buy financial instruments. Morris blames Greenspan for cutting interest rates and keeping them low during the 2000s, thus causing a flood of cash into the financial markets. The findings reported in Postrel’s article suggest he might have a point.

However interest rate changes are only part of the story. There are other forms of state intervention in the market and there were other factors feeding into the bubble (e.g. trading in new, complex financial instruments came to dominate the markets for example, as Morris shows). I hope to cover these other aspects in later posts.

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Review: The Trillion Dollar Meltdown

A question I have regarding the current financial/economic woes being attributed to the “credit crunch”, is this: Why did the money lenders give out loans on easy terms to people who were likely to default on them? The prime example of this is the so-called ninja loan.

Providing an answer to this question (in terms of the decision making of those managing the loans) is perhaps the most useful aspect of “The Trillion Dollar Meltdown”, by Charles R. Morris, a US centric examination of the credit crunch. By explaining complex financial instruments such as collateralized debt obligations (CDOs) and credit default swaps, Morris illustrates how several factors drove the accumulation of toxic debt:

  • The originators of loans would simply end up selling them on, thus weakening their dependence on the ability of the borrowers to pay the loans back.
  • The subsequent handling of the loans was then split up amongst many different parties, aggravating what Morris describes as the “Agency problem”, the problem of ensuring that an employee, contractor or other party performing a service for you does not act against your interests.
  • There was increasing reliance on complex, mathematical constructs to guide investment decisions. The models the constructs were based on only imperfectly modeled the real world and break down in times of economic stress.

On this basis, it seems to me that the use of difficult to understand models to package loans up into complex financial instruments along with the diffusion of responsibility for managing the loans amongst those trading such instruments may have enabled high levels of risky debt to accumulate.

The originators of loans were incentivised simply to sell as many loans as they could, since they were no longer dependent on the loans being paid off. They’d simply be paid for arranging the loans in the first place.

The people who were subsequently managing the loans, and thus had an interest in ensuring they didn’t buy too much risky debt, were those trading in the financial instruments. The complexity of the instruments (combined with optimistic ratings by the credit rating agencies) obscured the real risks from those people.

This is by no means the full story, since one also has to consider the legal/institutional framework within which this was taking place. For example, there is the role of financial regulators and other forms of government intervention in the financial system to consider as well. There is also the behaviour of the borrowers to consider too.

Morris does address the role of the financial regulators in the US. He blames Alan Greenspan for keeping interest rates low thus enabling a sustained period of cheap credit to develop, and he also blames “free market” ideology and financial deregulation. However here I find him less convincing. My main point is that in many significant respects, the financial system is not a “free market”. For example, the very fact that the Federal Reserve has a monopoly on printing money and sets interest rates shows we’re not talking about a “free market”.

Moreover, Morris himself argues that the financial services sector in the US enjoys “inordinate privileges”, pointing out for example that in a free market, a sector that takes high risks, like the financial sector does, would occasionally endure periods of big losses, as well as enjoying periods of high profits. But while the industry certainly enjoyed the high profits, its losses are often offset by government bailouts (NB: Morris was writing before the recent bailout programmes announced by Western governments).

Morris cites an example where Countrywide was paid $22 billion by the Atlanta Federal Home Loan Bank when they incurred losses that were likely to lead to insolvency. Providing bailouts to loss making companies is most definitely not a “free market” approach. Nor is it a “free market” when a privately run student loan organisation gets subsidies from the state (to take another example Morris criticised). The privileges enjoyed by Freddie Mac and Fannie Mae (the two big mortgage providers in the US) are also incongruous with a “free market” approach, and the role of these privileges in the credit crunch is not examined by Morris.

My point here is not to argue for the “free market” but to suggest that blaming “free market” ideology for failures in a system that enjoys considerable state intervention that goes beyond merely setting the rules of the game is perverse, especially when you simultaneously argue that some of the interventions directly contributed to the failures concerned!

Overall, the book may well prove useful to people wishing to understand the behaviour of the lenders in the credit crunch, but Morris’s attempt to blame it all on “deregulation” and the “free market” going too far is not convincing.

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