Strategic Irish Mortgage Arrears: The Smoking Gun

shouldnt the PPR and NPPR dummies give opposite signs to each other?

As an addendum to the above – if people are “strategically” choosing to not pay their mortgages on underwater/high-LTV properties, it’s because the banks have made it clear that there are no repercussions for this.

No one is being repossessed. No one is being bankrupted.

Either mortgages are recourse or they’re not.

If they are no longer recourse, then banks need to reprice their interest rates to reflect this new reality.

People have always gone into arrears – it was up to the bank to have systems in place (to alert themselves internally and to externally let the borrower know they were on the bank’s radar) to monitor, manage and control this situation.

Seeing a lot more people then previously with high and low-LTV not making repayments should be seen as something serious broken in the banking system.

Just as tellingly, with over 50% of SME loans in arrears, you have another sign that something is very broken in the Irish banks.

Worryingly – you also have a glimpse of more holes appearing in books of the zombie banks – and now they have the “Cyprus” option…

There are many solutions readily available to the residents of Priory Hall who have had to endure undescribable torture due to inaction of: Banks, Architects, Local Authorities, Builders and Politicians.
The death of a young father with two small children campaigning for justice in this inner circle of hell not of his making is a call for a solution.
It really is not very difficult. There are many good properties available at Northern Cross. I just walked the site…again. All that has to happen is that people get a key. They move in and turn the lights on.
A sleight of hand in the Dail could make it happen.
Failing this, people could just quite simply move into those properties which are habitable.
Is there any person in Ireland or a court of law who would evict a person under these circumstances?
It’s just a thought…

David Duffy said that strategic arrears for AIB were around 2% at the recent Dail Finance committee. Gregory Connor has been an inexplicable, shameless, cheer leader for spreading rumour after rumour figures on the level of “strategic defaults”. Why did PTSB not turn up with their sob story in the Dail 2 weeks ago?

Mr. O’Connor you are wasting a god awful amount of time mining an anonymous data set. You want to tank them for the anonymous data set so do I because I don’t believe in anonymous data sets. This is a state entity and they should not be leaking any data sets to anyone the whole lot should be out there in the open published for all and sundry to analyse. Basically, I just want one figure, how many mortgages that PTSB have out of their total mortgage book are “strategic” defaulters. No mumbo jumbo no funny stuff professor? Oh and it might help to get a clear definition of “strategic defaulters”. The definition is the goal post that keeps being moved around.

Alan Dukes tells us the banks have not got a clue about what the losses on their residential loan books are going to be buy you can dice and slice into that loan book to tell us what the “strategic defaulters” are? Now if we know what the motivation of the strategic defaulters are please Sir pray tell what is your motivation, your obsession if you will, with “strategic defaulters”?

@Gregory Connor,

Thanks for this.

Looking at fig. 1 (and I may be reading it wrong), why does it peak before the end? This would seem to imply that a huge number of mortgages with an LTV of 2.8 are defaulting but that this declines pretty steadily thereafter. Should it not continue to rise if LTV is the major factor in driving arrears?

Thank you for your time.

one thing we need to be clear on : Guiso et al DO NOT LOOK AT STRATEGIC DEFAULT.
“To identify the proportion of strategic defaults, we employ two questions. The first asks, “How many people do you know who have defaulted on their house mortgage?” Those who know at least one such person are then asked, “Of the people you know who have defaulted on their mortgage, how many do you think walked away even if they could afford to pay the monthly mortgage?” By taking a ratio of the two, we obtain an estimate of the percentage of actual defaults that are considered “strategic” by the defaulters’ acquaintances. ”
This is, I content, at best a most imperfect fuzzy and eminently caveatable measure. We dont even have that here.

@Gregory,

Thanks for the reply. Very interesting stuff.

We’ve handed over billions to bankers who we know now were clearly gaming the system – all the while they kept their jobs and earned millions.

And yet we’re still, even now five years on, worried about some punter getting one over with a “strategic default.”

It would be like inspecting people’s shoes as they boarded life boats on the Titanic – “no hard soles people, you might scratch the side of the ship.”

Any attempt to measure ‘strategic’ defaults is to be welcomed, because undoubtedly there are strategic defaults. A few points.

The word delinquent, while used in the US for late payments of all kinds, carries a much more pejorative meaning, currently and historically, in Ireland and the UK, where its meaning generally denotes repeated criminal offending.

The data would appear to suggest that even where ‘just’ 30% of net income is used to service the mortgage, up to 25% default where the loan/value ratio is high. This on first reflection is a very high figure. However what does it mean for different groups of income earner.

Monthly net income Mortgage
10,000 3000
6000 1800
4000 1200
3000 900
2000 600
1500 450
1000 300

So, who is likely to be a strategic defaulter? It is abundantly clear that those > 4000 net monthly income should, prima facie, be able to afford the mortgage and still live. The same cannot be said at all for the person whose net income is 2000 or lower.
Absolute net income is a ‘must know’ figure in relation to the evaluation of true strategic default percentages.

The next point I would make about the data, is that unless one separates BTL from OO, then the data will lack any effectiveness form a policy point of view. Although lumped together, in a very bad error of judgement, in the Blackrock / PCAR exercise, they are entirely different from the point of view of society and it is society that is paying the cost of the crisis.
They may all be PDH mortgages to the banks, but that is a bank definition. We need separation of these completely different mortgages when viewed by the individual or society.

Jim Stafford, the leading insolvency expert, in addition to his remarks on professional versus paye housing requirements, mentioned a case on of his on radio the same evening.
The person owed €40 million, his assets were ..pause..in his wife name and he worked for his sons.
Strategic default?
Make no mistake about to which income sector the vast bulk of bank write-off will go. Many have already gone there.

The mortgage cirsis shows how a society’s poltiical, legal and financial institutions can struggle to function when there is a widespread problem of bad debt. Ireland’s prior laws around bankruptcy and reposession were quickly acknowledged to be inadequate, but our politicians have done little to improve them despite several attempts. Our courts are laboring under a heavy case load and could face a deluge if the banks actually went after every delinquent mortgage. However our banks have shown little enthusiasm for ths task, even though they have been handed several billion from the government expressly for the purpose.

Under these circumstances who can doubt that the percentage of strategic defaulters is greater than normal. But the roots of the crsis are not in strategic default, but in institutional stress and failure in the face of widespread over -indebtedness.

The processes of building up debt, and then removng bad debt through default and restructuring, are not symmetric. One is easy and pleasant, the other difficult and painful. The mantra “Debt doesn’t matter, because one man’s debt is another man’s asset”, which implies symmetry, is false.

Prof Eamon Walsh gave a balanced response to the Oireachtas hearings in an RTÉ Morning Ireland interview:

http://www.rte.ie/news/player/2013/0905/20433399-did-we-learn-anything-from-the-finance-committees-questioning-of-banks/

What is striking about this issue and so many more that are highlighted in the OECD survey of Ireland, is the staggering level of managerial incompetence in Irish institutions when it comes to process.

People run from hard decisions and for people like Richard Bruton running a permanent publicity campaign, it must seem a lot more exciting than trying to sort out the apprenticeship shambles; the innovation shambles and the banjaxed job activation programmes.

In the case of the mortgage and SME debt crisis, the Central Bank appears to operate by target when it should be in charge and shaming ministers to update laws that are hindering resolution of the mess.

Eamon Walsh said some banker had said a customer with money on deposit was not paying a mortgage with the bank.

That may be an isolated case but do not doubt that the system is shambolic.

There is nobody in charge.

@ BeeCeeTee

Based on information compiled by the National Consumer Law Center (NCLC), at least 10 states can be generally classified as non-recourse for residential mortgages: Alaska, Arizona, California, Hawaii, Minnesota, Montana, North Dakota, Oklahoma, Oregon, and Washington. Recent legislation also makes Nevada non-recourse in most cases for residential purchasers for mortgages obtained on or after October 1, 2009.

http://www.cga.ct.gov/2010/rpt/2010-R-0327.htm

This is senior hurling. When a crisis overtakes the ability of an industry to self manage, it becomes political. Fukushima.

This bank is regulated by the Financial Authority. Maybe it wasn’t.
Your home is at risk if you do not keep up repayments. Maybe it isn’t.

That old economics stalwart, the rational agent- what would he do ?
And who is going to pay for it? And what does Joe Duffy’s woman in Clontarf make of it all ?

And all the time the house prices fall.

The crude assumption here is that there is a clear distinction between can’t pay/won’t pay. The only people who genuinely can’t pay are those who do not have the money. But most would also include those who don’t have the money left after paying for “necessities”. What about those who don’t have the money left after paying for Sky, the second holiday, the second family car etc. Paying the mortgage takes its place in priority for the discretionary spend. It is entirely to be expected that that priority would fall down the list as the payments are perceived to be more and more money into a black hole. Gregory seems to define strategic default as anybody who has not pared their expenditure back to the bare necessities. For me truly wicked strategic defaulting is when the money is actually diverted into savings and I don’t think there is evidence here that this is happening to any great degree.

Also I think skeptic’s observation that LTV may be a proxy to completely different risk factors such as belonging to an era of reckless lending or pertaining to loans of recent vintage greatly undermines the inference that the statistics are mainly explained by strategic default.

I won’t pretend to understand the probit/logit stuff, maybe I have to go to Limerick for that.

@seafoid

Joe Duffy’s ‘woman in Clontarf’ is delighted to tell you that your reference to house prices still falling does not apply to Clontarf!!

@ Gregory Connor

After a crash course on probits I am struggling with your figures. As I understand it the probit beta for LTV is .3983. So if LTV goes from 1.5 to 2 that would be a shift of .1995 sigmas but that can never give rise to as big a shift in probabilities as 19.92% unless you mean this is the percentage shift in the probabilities e.g. from 10% to 11.992%. What am I missing?

It is not clear that there’s enough information in the dataset to clear the mist on strategic defaults . Any chance of age, location, original salary, current salary, year of purchase , fall in property value, value of savings with banks ?

The banks have all the data and it seems they are releasing it selectively.

@ WGU

I can’t see how you formed that view from my post. I merely said I wouldn’t condemn those who bought overpriced property in an attempt to create a pension fund for themselves and then, as a consequence of personal circumstances, decided to prioritise the rental for necessary living expenses. Good luck to them while the banks dither on repossessing. No tenant is discommoded: he/she enjoys the use of the property while paying a monthly rent and he/she is not to know who the ultimate owner is of the property. If you choose to call these people “thiefs” and “deadbeats” so be it. All I’m saying is I don’t condemn them. As Mrs Slocombe used to say (‘Are You Being Served’): “I am unanimous in this”.

@ Gregory Connor

Thanks for that clarification. I have put te probit parameters into excel and looked at a few of the marginal distributions. By and large the model directionally is in accord with our intuition but I think if we stray far from the median the linear nature of the model lacks credibility. For example, setting PPR=1, NONPPR=0,LTV=1, APPNETS = .2 and examining the marginal distribution of NETS we get a Pr(def) = 33% when NETS = 0 and Pr(def) = 54% when NETS = 1. It seems that some transformation of NETS to a variable ranging from -inf at NETS=0 to +inf at NETS = 1 would be more credible.

I realise it is easy to knock any model so being more constructive I looked at the LTV marginal distribution with NETS = .2. This constituency could perhaps be characterised as those who could pay their mortgage of they made a reasonable effort and I also think any inferences about them are less susceptible to skeptic01 syndrome.

This graph clearly demonstrates that the probability of default increases significantly with LTV with the 50% Pr(def) occuring at 1.85. At this value the people in the survey are most likely to make the decision to switch from making the effort to pay their mortgage to throwing in the towel – that seems reasonably credible.

As mentioned before I hesitate to use the pejorative term “strategic default”. Better to say that the more your property drops into negative equity the less sacrifices you are prepared to make to pay down your mortgage. True strategic default is when with little or no sacrifice you can pay your mortgage but have decided not to do so, possibly saving to make a moonlight flit out of the country.

I love the definition there BW2. Its useful and sensible. Far more so than characterising those in arrears as squatters.

@ Gregory Connor

I am indeed confused by the unexplained. You describe your blue line as the “local-average empirical default”. I took “empirical” to man the actual observed default in that locale, which I was surprised should be so high in the locality of negligible LTVs. Am I misinterpreting the meaning of the word “empirical”?

@ Gregory Connor

It seems one should try and subjectively come up with potentially better fits than linear. For example, it would seem reasonable to posit that for LTVs below .9 the LTV is not factor. This might suggest a better variable is -inf up to LTV=.9 and log(LTV-.9) for LTV>.9. Similarly we might try log(NETS/(1-NETS)). The test of success would be whether you increase significantly the max log likelihood.

Very interesting discussion. Maith sibh

Samuel Karlin was supposed to have said “The purpose of models is not to fit the data but to sharpen the questions”.

I wonder what the influence of the individual bank is on the level of defaults. Which bank has the biggest share of the post 2005 business, the stuff most likely to be in trouble, as a % of total mortgage book ?

ILPM grew very aggressively pre 2008 and they probably weren’t expecting prices to fall…In 2009 they told investors that arrears would peak in 2010 with unemployment .. as if..

Interesting discussion of some of the background to all this here: http://www.rte.ie/radio/utils/radioplayer/rteradioweb.html#!rii=9%3A20437775%3A172%3A14-09-2013%3A

though towards the end George Lee tells Colm MacCarthey that ‘Paul has texted in’ and that the text says that Colm invented austerity. I would have thought that Paul Sommerville would be ok with austerity.

hmm – less than signs came through in my post, but greater than signs did not. I was trying to say that if LTV is greater than 100 you should default if the face of a hit to cash flow, and with LTV less than 100 you shouldn’t. And a measured LTV of 110 means thaere is a small, but non-zero, chance that true LTV is less than 100.

@an duanaire

Minor point: Colm McCarthy did ‘not’ invent austerity.

Austerity was invented/created by the 2002-2007 admin steeped in the ‘efficent markets hypothesis’ (sic) ideology of the Progressive Democrats in bed with a reckless Fianna Fail cabinet – the inventors were Michael McDowell, Mary Harney, Charles McCreevey, a silent Brian Cowen, and Bertrand Ahern.

… hence this thread on the misery of thousands.

@all
Keep up the good work.

@Gregory Connor

Whatever the ‘cutting-edge’ nature of the econometric techniques the plausibility of the findings depends on the underlying quality, and limitations, of the data set.

That said, the move to some empirics in the Irish context is welcome.

@GC
Terrific stuff,less negative equity about over here…less SD..
If they just fix the NE problem…oh hold on.
http://www.tradingfloor.com/posts/worst-us-housing-markets-playing-catch-1380468609

@GC
Table 1 seems to have arrears of sub 40% for the sample but figure 1 shows the arrears rate as around 40% and up for most loan to value ratios, including those in positive equity. How much data is each group that Table 1 based on?

If you ignore all <30%, then the picture isn’t as clear. The significance of the 2 binomial models does show that LTV is significant but an R squared of .06 seems quite low to me.

I’d be very interested in a model which adds variable rate and tracker rate dummy variables to the models as I think this could be a big driver of the affordability ratio.

You say that there is no relationship between arrears and LTV, as arrears is based purely on cashflows. However while a morgage holder is in arrears, the LTV is increasing driven by the increase in the principle loan amount for the arrears. Looking at the Q2 central bank data, 20% of Total arrears are over 2 years in arrears and 20% between 1 and 2 years. This probably wasn’t as much of a problem in the US data.

I also wonder if the dataset contains some informative censoring, as more sustainable solutions – eg. term extention – would be offered to those who have low LTV ratios by PTSB. Are restructured morgages in the data? How?

It is good to see analysis of the massive problem that is morgage arrears in this country – be it strategic or otherwise.

so, the next logical step would be, to draw 2- or 3-sigma confidence bands around the curve in figure 1.
What program do you use?

Thanks to the posting of the financial statement by brian woods snr, it looks feasible to me, to analyze for the income remaining for consumption, divided by family size (the SOEP / DIW counts 1st adult 1.0, all others 0.5, and children 0.3 – 0.5 as “effective consumption weight”, not their phrase!)

My expectation is, that this goes a long way to explain non-strategic defaulters, expecially those with LTV ratios< 1.0, which would then also help understanding at higher ratios.

@ BW II: I had a good chuckle at that! Nice to be ‘confused’!

@ francis: I’m the scientist – my namesake BW II is, I believe, an Actuary. So he will be good at the math stuff.

My ‘stuff’ is fossil energy sources and their relationship to various aspects of economic activity.

Oooops,

I am very sorry, and I like you both : – )
Sometimes I am digging around in fossils like Wilhelm Röpke 1932 “crisis and cycles” myself : – )

first bavaria prognosis 57 % of the seats for the black block CSU, the greenies are cratering and already a big mouth

time CSU SPD GRÜNE FDP LINKE FW PIRATEN Sonstige
18:00 49 21 8.5 3 2 8.5 2.0 6.0 projection
18:23 49 20.9 8.3 3 2.1 8.4 8.3 first counts

D o D,

special greetings just for you : – )

a French sex criminal murders his stupid Swiss hippo therapeut, and German police arrests him in Poland. Schengen works : – )

just without some funny islands.

http://www.badische-zeitung.de/schweiz/deutsche-polizei-verhaftet-schweizer-moerder-in-polen–75245698.html

@seafóid

“The banks have all the data and it seems they are releasing it selectively.”

That would be an accurate statement.

Blame the borrowers. Blame the borrowers. Blame the borrowers.

Sorry, just to clarify my point I am aware that you have measures of income both at time of mortgage and current time. But loan servicing ability is also a function of other expenditures. For example, a correlation between number of dependent children and LTV could explain your results. I am not suggesting that explanation in particular but it would certainly be neccesary to argue why the error term is unproblematic in this model before using the marginal effects as indices of “delinquency”.

@ GC: You are not achieving any positive result with this ‘research. If the input data is as iffy as you suggest, then you should have by-passed it. Pandora’s Box?

Stepping back from the salient fact – that lots of folk are not servicing their debts (inc. mortgages) on time, there is/are causal factors for this situation. What is/are those causal factor/s?

The first (and obvious one) that comes to mind is inability to pay; these folk are basically insolvent – their income/s is/are less than their expenses. So the first matter that has to be resolved is that of incomes – both total and nett. I doubt that any SFS form filling will achieve this. Maybe a mandatory Declaration of Income to the Revenue – with a pretty sharp ‘or else’ clause would, but again one has to wonder mightedly. Folk can be quite economical with the facts when it comes to ‘statements of income’.

LTV ratios (Irish ones) are a quite hopeless metric. They have more in the way of a sentimental value as opposed to a quantitative value; a value that is appropriate for estimating a reliable statistic. You do know about that Meaningless Mean?

No amount of statistical jiggery-pokery analysis will ‘straighten out’ bent or fraudulent input data. Its not the formulae – its the critter that selects the raw data and whether or not that raw data was sampled in a statistically robust manner. ???

If I had proffered this analysis to one of my tutors, I fancy I might have got a flea in my ear and at best been instructed to re-do my analysis – using verifiable data – of a statistically reliable sort!

Gregory
Two issues arise
a) availability and b) use of data. What data are available to you? Thats one q. Then there are lots of techniques to engage in variable dimension reduction. three that come to mind are PC analysis, some form of stepwise regression, or a quasi Hendry type General to Specific approach. you have 30k obs. Degrees of freedom are not a problem
In fact, this is really not the way to go imho. What would be useful would (variable dimensionality aside) be a nested LOGIT analysis from a universe of originated loans to see the determinants of full, stressed and partial (default) repayment. This dataset is censored in all sorts of ways and again we have no definition of strategic default.

@BL,it’s starting to be reminiscent of Clinton,asking for a definition off sex,are you still in denial ?
I think Gregory has done fantastic work,not for one minute am I pretending to understand all the “tech” parts,but I do understand strategic default,it ain’t that difficult a concept to grasp.

@BL it’s little old Ireland,at what “number” do you think policy will be impacted?
Assuming there is any SD the logical next step is to review the policy options,too much stick is useless bit carrot may work much better.
Motivate them to pay,see link above to “forgive and forget” or pretty much any decent research stateside on “fixing” SD.

@BL doing nothing is extremely damaging to society,the situation is out of control.
Brian if a massive humongous SD number overwhelms the court systems,then there truly is only one workable option left….shock horror debt write offs.link above.
“Many options, little will. Many policy options are available to fix America’s dysfunctional housing and mortgage markets. But the political will to deploy them is scarce. Small wonder: None is a panacea, most reward ‘bad’ behavior, some involve government funds, and none will satisfy all parties. Yet all are better than doing nothing, and a combination of carrots and sticks could create incentives for good behavior and real results.”

@brianwoodsII given the geographical pattern of house price reductions, are you confident that there is no reason for NE to be related to demographic factors?

I always like to be the 100th posting, at time of writing I am in line

@ LD

Okaaay, still much more likely that increased NE is causal rather than a mere proxy to other factors. As a life assurance man we constantly come up across this conundrum – is a statistical risk factor causal or merely coincidental. The most controversial is treating gender as a rating factor. All statistical analyses point to gender being a mortality risk factor and yet the EU banned its use from last December.

@Gregory Connor

A number of questions arise from your dataset.

The numbers the PTSB gave you:
Did they segregate the BTL from the PPR?
Did they indicate where on person had multiple mortgages in arrears?
Did they show individual per-property arrears or simply show the LTV-to-arrears total?

One person with a hundred BTLs in default with high-LTV is not counted as a hundred high-LTV in arrears, I assume?

Also, having people fill out a SFS and selecting the data from this is a skewed pre-determined group – but not representative of the whole – of the arrears catagory, no? Those in arrears, but paying, with High-LTVs will not appear (if they haven’t sought or been asked to do a SFS yet) but those in arrears and not paying with high-LTVs will, no?

@Gregory Connor

One other point on US research on “strategic” default – I would assume that the research was done in a situation where the banking system hadn’t implode.

Do you think that comparing default rates in a system where the banking system continued as normal to default rates where the banking system imploded may be slightly misleading?

@ Prof L

“I seem to be the designated referee” on the evidence that would seem to me a self designation.

Let’s get real here. All our intuition suggests that there would be a reduced willingness to pay off your mortgage the deeper you fall into NE. Anybody want to state categorically that they wouldn’t feel that way?

The work done by GC on his dataset confirm this intuition beyond any reasonable doubt and also puts some plausible quantifiers on the effect. The cig industry still argues that cigs are good for you and the NRA are convinced that the availability of guns reduces gun crime. I hope this debate has been helpful to GC in anticipating the many possible criticisms that he will face. Most of the criticisms fall into the possible space but it seems to me much more plausible to accept that increasing NE is a prime causal factor in default (I decline to use the qualifier “strategic” for reasons explained earlier).

@ JG ty

We have drifted here. There is a vast literature (see some below) on the determinants of defaults. In many of these LTV is important. There is much less, due to nobody knowing what it is, on “strategic defaults”
Here are some papers with extracts from the abstracts that suggest useful additional variables. If Greg and Tom have these then im sure they will include them. If they dont, then the paper can only be indicative of the importance of a set of bank selected variables.
Below are papers, with extracts from the abstract. Their words not mine.

Carranza 2013
We show that home prices and debt balances are the main determinants of mortgage default.

Quercia 2012
even within moderate- and low-income segments, lower or very low income is associated with higher default and lower prepayment probabilities. In addition, depending on how low the borrower’s income is, classic determinants of loan termination such as credit scores, the amount of equity in the home and local labor market conditions can have different impacts on default and prepayment probabilities

Sarmiento 2012
This article shows that the rise in unemployment played a very significant factor in the rise of mortgage delinquencies during the Great Recession. Estimation results, moreover, show that changes in the Unemployment Rate (UR; from loan origination) as opposed to the level of the UR explain mortgage default.
Crook 2012
declines in credit quality for consumer and for real estate loans, but support for the reduced stigma explanation was restricted to real estate loans

yang 2011
mong the different volatility components, omitting the cross-sectional dispersion of individual home prices would produce the largest bias in assessing home-price-based mortgage default risk

Kau 2011
he paper demonstrates that MSA-level frailty, together with other risk factors, has significant effects on the probability of mortgage terminations risks.

Pennington-Cross 2010
Default probabilities increase dramatically when payment shocks are mixed with low or no equity in the home

Seslen 2010
using a novel measure, based on changes in net operating incomes and property values at the metropolitan statistical area-property-type-year level. Employing a semi-parametric competing risks model for a variety of specifications, we find that the probability of default is extremely low even at very high levels of stress, although the coefficient estimates of greatest interest are very statistically significant.

An 2010
he optimal choice between these two termination events may depend on unobserved propensities related to change in income, job location, or family size, and substantial inertial forces including search costs, neighborhood change and attachment to an area.

Daglish 2009
However, default probabilities are highly sensitive to changes in interest rates and house prices.

Hagwouth 2008
We find that while credit standards were important in determining the probability of an early default, changes in the economy-especially a sharp reversal in house price appreciation-after 2004 were the more critical factor in the increases in default rates that we observe. An important additional result is that in spite of our rich set of covariates, much of the increase remains unexplained, even in retrospect.

Carranza, J.E., Estrada, D.
Identifying the determinants of mortgage default in Colombia between 1997 and 2004
(2013) Annals of Finance, 9 (3), pp. 501-518.

Sarmiento, C.
The role of the economic environment on mortgage defaults during the Great Recession
(2012) Applied Financial Economics, 22 (3), pp. 243-250.

Crook, J., Banasik, J.
Forecasting and explaining aggregate consumer credit delinquency behaviour
(2012) International Journal of Forecasting, 28 (1), pp. 145-160. .

Kau, J.B., Keenan, D.C., Li, X.
An Analysis of Mortgage Termination Risks: A Shared Frailty Approach with MSA-Level Random Effects
(2011) Journal of Real Estate Finance and Economics, 42 (1), pp. 51-67.

Yang, T.T., Lin, C.-C., Cho, M.
Collateral Risk in Residential Mortgage Defaults
(2011) Journal of Real Estate Finance and Economics, 42 (2), pp. 115-142.

Pennington-Cross, A., Ho, G.
The termination of subprime hybrid and fixed-rate mortgages
(2010) Real Estate Economics, 38 (3), pp. 399-426.

Seslen, T., Wheaton, W.C.
Contemporaneous loan stress and termination risk in the cmbs pool: How «ruthless» is default
(2010) Real Estate Economics, 38 (2), pp. 225-255.

Daglish, T.
What motivates a subprime borrower to default?
(2009) Journal of Banking and Finance, 33 (4), pp. 681-693.

Haughwout, A., Peach, R., Tracy, J.
Juvenile delinquent mortgages: Bad credit or bad economy?
(2008) Journal of Urban Economics, 64 (2), pp. 246-257.

Deng, Y., Pavlov, A.D., Yang, L.
Spatial heterogeneity in mortgage terminations by refinance, sale and default
(2005) Real Estate Economics, 33 (4), pp. 739-764.

Last post on this : From
Luigi Guiso, Paolo Sodini, Chapter 21 – Household Finance: An Emerging Field, In: George M. Constantinides, Milton Harris and Rene M. Stulz, Editor(s), Handbook of the Economics of Finance, Elsevier, 2013, Volume 2, Part B, Pages 1397-1532, ISSN 1574-0102, ISBN 9780444594068,

“Overall, the theoretical literature emphasizes that negative equity positions do not automatically trigger default. Other monetary and non-monetary costs, such as relocation and social stigma, may play an important role implying that default may not occur unless equity becomes substantially negative.69 In addition to the option value to delay, default varies in the cross section of households along several dimensions such as mortgage type, leverage ratio, income to loan ratio and income risk.”
followed by their summation of evidence
” Consistently with the models sketched in the previous section, various monetary and non-monetary costs seem to play an important role. Elul et al. (2010) find that, for a given home equity position, default is more likely for households short of liquidity. Guiso, Sapienza, and Zingales (in press) find that default is significantly lower among borrowers that are less likely to become unemployed and have longer tenure—a measure of the attachment to the current location. They are also able to study the moral and social determinants of the attitudes towards strategic default. 82% of respondents believe that it is morally wrong to engage in strategic default, despite the fact that, at least in non-recourse states, insolvency carries no legal consequence.71 Everything else equal, households who think that it is immoral to default strategically are 9.9 percentage points less likely to declare strategic default. In addition, as suggested by the literature on personal bankruptcy (Fay et al., 2002 and Gross and Souleles, 2002a), the decision to default strategically might be driven by other emotional considerations (White, 2010). It has been argued that individuals are more likely to inflict a loss on others when they have suffered a loss themselves, especially if they consider their loss to be unfair (e.g. Fowler, Johnson, and Smirnov, 2004). Indeed, Guiso, Sapienza, and Zingales (in press) find that individuals who feel anger for the economic situation during the Great Recession are more willing to express their willingness to default. Similarly, households who trust banks less, or who know somebody that defaulted strategically, are more likely to declare their intention to do so. This negative externality may be an important amplification mechanism that parallels the effect studied by Campbell, Giglio, and Pathak (2011), who argue that foreclosures impact negatively the prices of nearby houses, presumably because of induced vandalism or neighborhood deterioration”

I note that is Prof L’s last post, I was wondering about his day job.

Unusually, though he is difficult to follow at times, I seem to be somewhat aligned to him on this. He, like me but unlike others, appears to accept that NE is a causal factor in D but feels the jury is out as to whether that proves SD.

The US seems quite a different culture esp in non-recourse States. There it appears SDers come out openly and tell their bank they can stuff their mortgage, so called jingle mail. Here SDers do not come out. They disguise themselves as wholesome Ders.

The term “strategic” is a characterisation of the motivation for the default and different observers will have different criteria for making that characterisation. Personally, I do not classify a default as strategic unless the borrower can clearly afford to pay, e.g. where his circumstances have not deteriorated, but decides deliberately not to do so. GC seems to be less “sympathetic” and characterises anybody who would have made more effort not to default if it were not for the NE as a SDer.

bit euro work on this topic regarding ‘motivation’
cheat sheet and the paper…..
“We find that solvent borrowers are more likely to default
strategically when stricter disclosure creates common knowledge about bank weakness. Borrowers are also less likely to repay in the presence of higher uncertainty regarding other borrowers’ financial health, regardless of disclosure rules”
http://www.voxeu.org/article/strategic-default-and-borrower-runs
http://www.dnb.nl/en/binaries/working%20paper%20312_tcm47-257144.pdf

@ GC

That’s a bit of a sore brainer for someone with an inadequate Wiki education on these matters. Trying to get my head around the NONPPR aspect. Am I correct in this interpretation: let’s say I am modelling NONPPRLTV of 1. Do I have a contribution to sigma of .718 due to LTV and -0.161 due to NONPPRLTV i.e. a net contribution to sigma of .557?

@ GC

My read of some of this probit stuff is as follows:

Your original 5 parameter probit predicts accurately whether a person would default or not on (geometric) average 52.1% of the times

The enhanced 14 para probit increases this average to 52.6%

A crude model which says everyone has the same 40% chance of defaut would be right on average 51% of times.

It’s not clear to me that the probit model significantly increases the predictive power of default for this sample.

@Gregory

A few things:

Your results are obviously more credible having included these controls.

Minor point but interaction terms in probits are tricky. Would be good, as sense check, to run a linear probability model (LPM)

STATA’s “dprobit” command gives simple marginal effects at the mean of the independent variables.

Your model controls for income. I think the tenor of a lot of the comments here is whether, even with this, that LTV is showing strategic default in the abscence of information about outgoings including other types of debt the people are servicing, dependent children and so on. I can hear your point that these complicate the model and also the argument they should be uncorrelated with LTV. But you must concede that you are effectively saying that the LTV variable is not picking up any unobserved heterogeneity in ability to pay. None of the comments above have really got under the skin of that point other than to dismiss it. Brian Woods II point that we should just use correlations instead of a correctly controlled statistical model is wrong and will lead to potentially overestimating the extent of strategic default.

There is a lot of research to show that one thing that drives behaviour is perception that you are in line with social norms. A result that widely travels claiming large amounts of strategic default could itself contribute to higher degrees of strategic default. Even if we accept a causal coefficient on LTV, the pseudo R-squared is small indicating a vast amount of heterogeneity that is basically the many social, cultural and unobserved financial determinants of default.

Anyway, this has been an interesting post possibly near an end!

@JG, As you say,”Shure it’s only a billion”….. But the Special Liquidator’s US “smash and grab” raid has gone seriously awry! Even sidelined Linklaters for the world’s biggest lawyers in Skadden – Linklaters must have been making a total *&^$!! of it to date. There will be a galaxy of lawyers (That’s what they call a big group of them believe it or not) collecting in Delaware on Friday afternoon. See you in Court 6 in Wilmington tomorrow, John?

Beta is also an input – a Table showing the dependence of Pseudo R^2 on Beta and Median Pr(Y=1) is the output.

@Gregory just to repeat the point made to Brian. I would never argue to suppress valid results. The question I would ask though in highly volatile situations where a result might cause a feedback effect is at what stage do you feel confident enough in a set of results to put forward a claim that could influence the situation. I think this has been a useful post and hopefully in the spirit of testing a result in a seminar before being willing to claim that it is true or at least not obviously explained by things a reasonable reviewer could point to. I have also hoped there would be more interactions like this on the blog even if they might be very boring for some of the readers.