I’ve been reading Todd Zywicki’s paper An Economic Analysis Of The Consumer Bankruptcy Crisis (1Mb PDF). Zywicki’s approach is to look at aggregate time-series data on a set of suggested causes of rising bankruptcy, suggest that the pattern for these time-series doesn’t match the observed increase in bankruptcy, The main point is, as he says,
Static or declining variables, such as unemployment, divorce, or health care costs, cannot explain a variable that is increasing in value, such as bankruptcy filing rates.
Hence, he says, the ‘traditional model’ of bankruptcy as a “last resort” outcome of financial distress is no longer valid. He therefore falls back on the residual hypothesis of changes in consumer behavior in the form of an increased willingness to resort to bankruptcy, possibly due to the rise of impersonal modes of lending and the decline of moral sanctions. Zywicki doesn’t mention the other obvious residual possibility: an exogenous increase in willingness to lend to high-risk borrowers, but symmetry suggests he ought to.
I don’t think Zywicki’s is the ideal research strategy (see below) but it has the advantage that anyone can play, armed only with Google. So let me point to a variable that has risen in the right way and could reasonably be expected to lead to rising rates of bankruptcy. That variable is the volatility of individual income, or, in simpler terms, the economic risk faced by the average person.
What this means is that the bankruptcy ‘crisis’ is an outcome of the general changes in the US economy over the past 30 years or so. If it weren’t for expanded credit and increased reliance on bankruptcy, the distress caused by growing inequality and income volatility would have been substantially greater. If bankruptcy laws are tightened, distress will increase. To put it simply, bankruptcy is the lesser of two evils.
The link between income volatility and bankruptcy is straightforward. People enter into commitments, and establish consumption habits, when income is high, then run into financial trouble when their income falls.
If income volatility is mostly temporary (income returns to the previous level over a year or two) access to credit helps to smooth consumption. If income volatility is mostly permanent, then the best response is to adjust consumption immediately.
The trouble is, you can’t tell the difference. So people increase their consumption commitments in response to an increase in income that turns out to be temporary or maintain consumption in response to a decline that turns out to be permanent. This is a rational response, but it leads to increased risk of bankruptcy.
The aggregate numbers are consistent with this. Aggregate consumption is more stable than aggregate income.
The obvious place to look for evidence on individual income volatility is the Panel Survey on Income Dynamics. A quick Google (I used “PSID income volatility consumption temporary permanent), confirms the broad outlines of the story above
* individual income volatility has increased fairly steadily since the 1970s, with increases in both temporary and permanent volatility
* income inequality has also increased
* consumption inequality and volatility have not increased nearly as much
* this can be explained by reliance on credit
This paper by Kreuger and Perri (0.5 MB PDF) is useful.
The aggregate trend approach Zywicki and I have used is not the ideal way to address the question. The best thing would be to look at individuals and see what kinds of things predict bankruptcy. There are a couple of ways of doing this.
The best, I think, would be to get access to the models used by credit providers to assess risk. The increase in bankruptcy might be explained by an increase in the proportion of borrowers with high risk characteristics. Alternatively, on Zywicki’s account, there might be an exogenous increase in the default risk for borrowers with given characteristics. I’d expect a bit of both, since the two reinforce each other. Given a big increase in bankruptcy due to increased risk, the moral and legal sanctions against bankruptcy become less effective, which produces a second-round increase.
I don’t suppose credit providers are going to part with their models. So, the next best thing would be to estimate a model of your own using a panel data set like PSID. I’m sure someone has done this, but a quick Google scan didn’t turn them up, and I’m betting that one of my well-informed readers will be able to point me in the right direction.
John Quiggin 
Sorry for nonworking downloads. There’s another link at Todd Zywicki’s homepage
I seem to remember hearing recently that the majority, I think 40%+, of USA bankruptcies were directly related to a healthcare debt.
Francis, IIRC there was an article in the Boston Herald that claimed something like 40% of health cost related bankruptcies had health insurance.
Often marriage is a risk management mechanism. Two incomes are more able to ride the volatile labor market than one. The government subsidies for marriage also add up. Any form of multiple income bonding should probably be encouraged. That includes gay marriage.
The bankrupcy laws in the US are a subsidy to creditors. But companies that market to high risk borrowers should know what is needed to sustain that business. If it is not a profitable business then they should get out of it. Not ask for a helping hand from government.
Unfortunately more and more, the American way is becoming the guarantee of profit from government legislation and the public purse as a source of fund raising. Some of it is quite repulsive. The recent move of a baseball team to Washington DC for instance. I am thankful it is not in VA. What a rort.
I don’t suppose credit providers are going to part with their models
In the USA, there is a thing called a FICO score, which is an industrywide credit score used for some regulatory purposes. Obviously any sane lender will have their own model on top of this, but my understanding is that the FICO model is reasonable (albeit that it tends to score you as risky simply because you’ve had a short credit history, something which there is a whole “near-prime” lending industry set up to game). I can’t get hold of FICO data without paying money but I suspect that a university might and the Federal Reserve certainly could.
What about the decline of savings, was that in the model? Saving money in bank accounts became irrational under the regime of inflation that took off under Whitlam and the habit does not seem to have come back into vogue.
The increase in bankruptcy might be explained by an increase in the proportion of borrowers with high risk characteristics.
New web-based risk/credit markets such as http://www.zopa.com may also increase high-risk borrowers’ access to loaned funds outside the traditional banking system. This is a good thing. The fact that lenders can, at least in principle, choose the level of risk to which they are exposed implies that this may be a better mechanism for accomodating the credit needs of high-risk individuals, compared to the blanket relaxation of risk-tolerance limits by banks and other NFIs. This seems like a great example of letting ‘the market’ decide the correct re-allocation of risk and debt; a welcome complement to the risk-absorption/hedging model that drives the high level of regulation & control required for traditional banks. Will it stop people from going bankrupt? No. But at least lenders can exercise choice over risk-exposure levels for their spare cash (this is peer-to-peer, not corporate, finance). And people experiencing transitional downturns in income (be they recently made redundant or trying to startup experimental ventures) can also exercise more choice over their access to loanable funds.
“The best, I think, would be to get access to the models used by credit providers to assess risk.” Are you expecting this to be a good predictor John? I have my doubts. Banks are pretty rough and ready in their assessment of who they will lend to.
And if they’re expected to be an efficient judge of risks you’d expect them to price risk. But they do so very little. There’s a bit of it with the purchase of lenders’ mortgage insurance, but the interest rate on a loan with an 80% loan to valuation ratio (with a reasonable chance of negative equity in a nasty downturn in a bad suburb) the same as the interest rate on an effectively zero risk mature loan with (say) a 50% loan to valuation ratio.
Nicholas,
In Australia the development of consumer risk models is still in its infancy – most banks here do not use them and certainly do not truly price for risk – that is to say offer different interest rates to borrowers of different riskiness, as your example shows with housing credit. It happens in the larger sized corporate deals, but really nowhere else.
The same is not true in the UK and the US, where banking is much more competitive.
To me, the choice we have is between an effective banking cartel, with APRA making sure that no-one does anything too radical and a more open system where sub-prime lending at high rates is commonplace. Personally, I prefer the latter, but it is a choice we should be looking at.
It makes no sense to price-discriminate on credit quality grounds when making mortgage loans, because the bank’s prospect of getting its money back on a mortgage depends on the collateral as much as the payments. I bet there is quite a lot of price discrimination in credit card rates and unsecured loans; although Australia is a pretty concentrated banking market, it’s really quite competitive and is one of the most innovative banking markets in the world – the “Australian mortgage” with the current account attached to it is just taking of in UK.
Rafe whined “the regime of inflation that took off under Whitlam”
For heaven’s sake that was a) more than 30 years ago and b) ’70s inflation wasn’t confined to Australia. c) the seeds of that inflation had been sewn by the profligrate policies of Menzies, McKewen, Holt, Gorton and McMahon whose combined economic IQ totalled about 3. They laid the foundations for what was to come.
Let me assure you that in parts of Europe and the Americas inflation was far worse in the period ’73 to ’80 than anything you fancy you experienced here.
Francis: “I seem to remember hearing recently that the majority, I think 40%+, of USA bankruptcies were directly related to a healthcare debt.”
Francis, as I understand it, this figure was based on face-to-face interviews. I’d treat it with some skepticism since there’s a natural temptation for people to say “I went broke because I got sick” rather than “I blew all my money on coke” or “I was fired from my job for stealing”.
Program on the emergence of civilization.
“14 species of large animals capable of domesitcation in the history of mankind.
13 from Europe, Asia and northern Africa.
None from the sub-Saharan African continent. ”
Favor.
And disfavor.
They point out Africans’ failed attempts to domesticate the elephant and zebra, the latter being an animal they illustrate that had utmost importance for it’s applicability in transformation from a hunting/gathering to agrarian-based civilization.
The roots of racism are not of this earth.
Austrailia, aboriginals:::No domesticable animals.
The North American continent had none. Now 99% of that population is gone.
AIDS in Africa.
Organizational Heirarchy
Heirarchical order, from top to bottom:
1. MUCK – perhaps have experienced multiple universal contractions (have seen multiple big bangs), creator of the artificial intelligence humans ignorantly refer to as “god”
2. Perhaps some mid-level alien management
3. Mafia (evil) aliens – runs day-to-day operations here and perhaps elsewhere (“On planets where they approved evil.”)
Terrestrial management:
4. Chinese/egyptians – this may be separated into the eastern and western worlds
5. Romans – they answer to the egyptians
6. Mafia – the real-world interface that constantly turns over generationally so as to reinforce the widely-held notion of mortality
7. Jews, corporation, women, politician – Evidence exisits to suggest mafia management over all these groups.
Survival of the favored.
Movies foreshadowing catastrophy
1986 James Bond View to a Kill 1989 San Fransisco Loma Prieta earthquake.
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