5 Discussion and Concluding Remarks
5.3 Future outlook
Limitations of this study result mainly from having only four years of origination vintages with a sufficient breadth of observations and a limited number of years of performance information. One extension of this study would result from replicating this analysis once data are available over a longer time horizon. This would allow for insights into default timing by borrower and product type as well as the study of borrower behaviour throughout a business cycle at a loan-level. On a technical level – if supplemented with prepayment information – longer-running mortgage default data would allow the study of competing risks models which additionally capture the interdependency of default likelihood with likelihood of prepayment.
As mortgage credit risk is driven equally by loss severities as it is driven by default rates a study on determinants of loss severities would provide a useful complement to
24 Note: Diaz-Serrano (2005) do not include OLTV in the regression analysis due to data limitations.
this study. Such an analysis based on a similarly composed pool of data on defaulted mortgage loans in the UK is underway.
Furthermore, a comparison to other countries would not only benefit the understanding of the UK mortgage risk but also help to develop a comprehensive understanding of risk factors across jurisdictions and market setups. Such a cross-country study would lead to important insights into the dependency between the housing market framework and credit risk and could feed into policy recommendations of governments and financial regulators.
REFERENCES
Ambrose, B, Buttimer, J and Capone, C, 1997. The impact of the delay between default and foreclosure on the mortgage default option. Journal of Money, Credit, and Banking 29, p. 314-325.
Breedon, F and Joyce, M, 1992, House prices, arrears and possessions, Bank of England Quarterly Bulletin, p. 173–79.
Brookes, M, Dicks, M and Pradhan, M, 1994, An empirical model of mortgage arrears and repossessions, Economic Modelling 11, p. 134–44.
Coles, A, 1992, Causes and characteristics of arrears and possessions, Housing Finance. 13, p.10–12.
Demyanyk, Y and Hemert,O, 2009, Understanding the subprime mortgage crisis, Review of Financial Studies, forthcoming.
Diaz-Serrano, L, 2005, Income volatility and residential mortgage delinquency across the EU, Journal of Housing Economics 14, p. 153-177.
Doling, J, Ford, J and Stafford, B (Eds), 1988, The Property Owing Democracy.
Aldershot: Avebury.
Figuera, C, Glen, J and Nellis, J, 2005, A dynamic analysis of mortgage arrears in the UK housing market, Urban Studies 42, 1755-1769.
Ford, J, Kempson, E and Wilson, M, 1995, Mortgage arrears and possessions:
perspectives from borrowers, lenders and the courts, HMSO, London.
Hellebrandt, T., Kawar, S. and Waldron, M., 2009, The economics and estimation of negative equity, Bank of England Quarterly Bulletin Q2.
Jackson, J R and Kaserman, D L, 1980, Default risk on home mortgage loans: a test of competing hypotheses, The Journal of Risk and Insurance, p. 678-90.
Lambrecht, B, Perraudin, W and Satchell, S, 1997, Time to default in the UK mortgage market, Economic Modelling 14, p. 485-99.
May, O and Tudela, M, 2005, When is mortgage indebtedness a financial burden to British households? A dynamic probit approach, Bank of England Working Paper 277.
Mayer, C, J, Pence, K and Shurland, S, 2009, The rise in mortgage defaults, Journal of Economic Perspectives 23, p. 27-50.
Whitley, J, Windram, R and Cox, P, 2004 , An empirical model of household arrears, Bank of England Working Paper no. 214.
Tables and Charts
Table 1: Number of Loans by Transaction Series
Repossession Information
Arrears Information Bluestone 7,767 7,767
Eurosail 16,231
Leek 21,461 11,709
Ludgate 1,447
Mansard 3,271 1,935 Money Partners 10,062
RMAC 12,895 4,957 RMS 13,053
Total 68,509 44,046 A. Number of Loans by Transaction Series
(Non-Conforming)
Arkle 314,874 Arran1 25,316 Gracechurch 72,508 Granite 285,159 Total 697,857
B. Number of Loans by Transaction Series (Prime)
Table 2: List of Transactions in each Transaction Series Transaction Transaction
Series Bluestone041 Bluestone Bluestone061 Bluestone Bluestone071 Bluestone esail061 Eurosail esail063 Eurosail esail071 Eurosail Leek 14 Leek Leek 20 Leek Leek 21 Leek Ludgate061 Ludgate Mansard061 Mansard MPS1 Money Partners MPS2 Money Partners MPS3 Money Partners MPS4 Money Partners
Rmac061 RMAC
Rmac062 RMAC
Rmac063
RMAC RMS21
RMS
RMS22 RMS
Table 3: Number of Loans by Origination Vintage
Number of Loans Prime
Repossession Information
Arrears Information
Arrears Information Missing 2,599 2 - Pre 2000 307 15 48,302 2000-2002 2,595 913 95,811 2003 966 966 59,071 2004 1,656 1,999 88,615 2005 12,503 4,295 120,586 2006 31,710 27,779 188,080 2007 16,173 8,077 97,392 All 68,509 44,046 697,857
Non-Conforming
Table 4: Number of Loans by Year of Repossession Repossession Year Number of Loans % of Total
2004 2 0.07%
2005 92 3.39%
2006 407 15.01%
2007 977 36.03%
2008 1174 43.29%
2009 60 2.21%
Table 5: Average OLTV by Origination Vintage
Non-Conforming Prime
Repossession Information
Arrears Information
Arrears Information
Pre 2000 64.7% 75.5% 61.0%
2000-2002 68.7% 68.2% 62.4%
2003 72.9% 73.0% 62.0%
2004 72.7% 73.1% 64.8%
2005 73.5% 76.2% 70.6%
2006 77.0% 75.3% 70.1%
2007 81.9% 82.5% 69.3%
Table 6: Average DTI by Origination Vintage
Non-Conforming Prime
Repossession Information
Arrears Information
Arrears Information
Pre 2000 30.1% 40.8% 30.0%
2000-2002 33.9% 30.8% 31.3%
2003 33.8% 33.7% 32.9%
2004 35.7% 35.2% 33.6%
2005 35.6% 35.0% 35.6%
2006 35.5% 36.8% 35.8%
2007 36.4% 37.2% 36.0%
Table 7: Distribution of Loan Characteristics
Prime Characteristics
Repossession Information
Arrears Information
Arrears Information
Self Employed 31.3% 39.1% 10.8%
Self Certification 59.8% 61.4%
Fast Track 0.0% 0.0% 16.5%
Interest Only
(owner-occupied) 50.4% 50.3% 26.4%
Interest Only
(BtL) 89.5% 90.8% 0.0%
Remortgage
Loans 59.3% 57.2% 39.2%
Right to Buy 6.6% 18.9% 0.0%
Buy to Let 6.6% 6.5% 0.0%
New Builds 7.1% 6.1% 8.8%
Non-Conforming
Table 8: Adverse Credit Characteristics in Non-Conforming Sector
Repossession Information
Arrears Information
Adverse Credit 26.1% 42.0%
Country Court Judgement
(CCJ) 18.0% 28.7%
Arrears in the last 7-12 months before
origination 7.2% 7.9%
Arrears in the last 0-6 months before
origination 6.0% 5.9%
Bankruptcy or Individual Voluntary Arrangement
(IVA) 1.5% 2.2%
Non-Conforming
Table 9: T-Tests - Repossession Rates by Product and Borrower Characteristics Non-Conforming
Repossession Information
Y N T-Test significance Self Employed 7.3% 3.8% ***
Self Certification 6.1% 4.0% ***
Interest Only
(owner-occupied) 6.5% 4.2% ***
Remortgage Loans 5.6% 4.8% ***
Right to Buy 1.9% 5.5% ***
Buy to Let 5.0% 5.3% NS
New Builds 10.0% 4.9% ***
Adverse Credit 7.1% 4.7% ***
Bankruptcy or Individual Voluntary
Arrangement (IVA) 3.8% 5.3% **
Country Court
Judgement (CCJ) 8.2% 4.6% ***
Arrears in the last 7-12 months before
origination 3.8% 5.3% ***
Arrears in the last 0-6 months before
origination 9.4% 4.9% ***
Table 10: T-Tests – Non-conforming 90ever rates by Product and Borrower Characteristics Non-Conforming
Arrears Information
Y N T-Test significance Self Employed 24.4% 22.0% ***
Self Certification 26.1% 19.4% ***
Interest Only
(owner-occupied) 24.8% 22.4% ***
Remortgage Loans 28.0% 17.6% ***
Right to Buy 26.9% 22.8% ***
Buy to Let 20.8% 23.7% ***
New Builds 20.0% 23.8% ***
Adverse Credit 31.1% 18.1% ***
Bankruptcy or Individual Voluntary
Arrangement (IVA) 18.9% 23.7% ***
Country Court
Judgement (CCJ) 37.3% 18.3% ***
Arrears in the last 7-12 months before
origination 32.2% 21.8% ***
Arrears in the last 0-6 months before
origination 32.0% 22.0% ***
Table 11: T-Tests – Prime 90-ever Rates by Product and Borrower Characteristics Prime Y N T-Test significance
Self Employed 2.8% 2.3% ***
Fast Track 1.9% 2.4% ***
Interest Only
(owner-occupied) 2.9% 2.1% ***
Remortgage Loans 1.4% 1.1% ***
Table 12: Regression Results for 90ever Arrears on Prime Loans
2004 2005 2006 2007 All Vintages
OLTV 0.48%*** 0.23%*** 0.54%*** 0.37%*** 0.66%***
DTI -0.10%*** -0.06%*** -0.11%*** -0.11%***
Fast Track -0.21%*** -0.15%*** -0.32%*** -0.27%*** 0.31%***
Self Employed 0.18%*** 0.14%*** 0.38%*** 0.34%*** 0.34%***
Interest Only 0.42%*** 0.16%*** 0.28%*** 0.14%*** 0.49%***
Pr(arrears)x at mean 1.17% 0.57% 1.58% 1.26% 1.70%
Transaction Dummies Yes Yes Yes Yes Yes
N 88615 120586 188080 97392 697857
R-squared 0.1301 0.1065 0.0826 0.0511 0.0908
The table reports marginal effects from the logistic regression using >3 month arrears in prime sector as a dependent variable (intercept is not reported). The marginal effects for OLTV and DTI measure the effect of a 10% increase in the explanatory variable, while marginal effects for stabilised margin measure the effect of a 1%
increase in the explanatory variable. The categorical variable marginal effect represents the difference in probability of arrears when the categorical variable is 1 and 0. Pr(arrears) states the probability of arrears using the logistic regression parameters where OLTV, DTI are evaluated at their means and categorical variables at zero.
***,**,* represent statistical significance at 1%,5% and 10% levels respectively.
Table 13: Regression Results for 90ever Arrears on Prime Loans: Including Remortgage and Stabilised Margin
OLTV 0.50%*** 0.23%*** 0.18%*** 0.07%***
DTI -0.07%** -0.03%** 0.02%**
Remortgage 0.54%*** 0.28%*** 0.32%*** 0.05%***
Fast Track -0.32%*** -0.31%*** -0.13%***
Self Employed 0.05%* 0.10%*** 0.03%**
Stabilised Margin 0.24%*** 0.26%***
Interest Only 0.23%*** 0.08%*** 0.04%***
Pr(arrears)x at mean 1.09% 0.54% 0.50% 0.21%
Transaction Dummies Yes Yes Yes Yes
N 58187 56479 86057 53417
R-squared 0.0635 0.0655 0.0737 0.0559
2007
2004 2005 2006
The table reports marginal effects from the logistic regression using >3 month arrears in prime sector as a dependent variable (intercept is not reported). The marginal effects for OLTV and DTI measure the effect of a 10% increase in the explanatory variable, while marginal effects for stabilised margin measure the effect of a 1%
increase in the explanatory variable.. The categorical variable marginal effect represents the difference in probability of arrears when the categorical variable is 1 and 0. Pr(arrears) states the probability of arrears using the logistic regression parameters where OLTV, DTI and stabilised margin are evaluated at their means and categorical variables at zero ***,**,* represent statistical significance at 1%,5% and 10% levels respectively.
Table 14: Regression Results for 90ever Arrears on Non-Conforming Loans
2005 2006 2007 All Vintages
OLTV 5.02%*** 4.64%*** 1.21%*** 3.39%***
DTI 0.97%*** 1.08%*** 0.84%***
New Build 7.31%*** 3.81%**
Adverse Credit 13.37%*** 5.48%*** 8.02%*** 7.40%***
Remortgage 5.73%*** 1.82%*** 4.07%*** 2.42%***
Adverse Credit * Remortgage 3.84%*** 1.74%***
Self Certified 2.03%*** -1.62%*** 0.56%***
Adverse Credit * Self Certified 1.50%** 1.76%** 1.96%***
Self Employed 4.54%*** 1.48%*** 1.54%*** 1.20%***
Interest Only 2.4%** 0.9%*** 0.8%** 1.2%***
Pr(arrears)x at mean 23.8% 22.0% 9.1% 15.5%
Transaction Dummies Y Y Y Y
N 2993 19549 7086 30892
R=squared 0.1737 0.2393 0.0651 0.2223
The table reports marginal effects from the logistic regression using >3 month arrears in non-conforming sector as a dependent variable (intercept is not reported). The marginal effects for OLTV and DTI measure the effect of a 10% increase in the explanatory variable. The categorical variable marginal effect represents the difference in probability of arrears when the categorical variable is 1 and 0. Pr(arrears) states the probability of arrears using the logistic regression parameters where OLTV, DTI are evaluated at their means and categorical variables at zero.
***,**,* represent statistical significance at 1%,5% and 10% levels respectively.
Table 15: Regression Results for Repossession on Non-conforming loans
2005 2006 2007 All Vintages
OLTV 3.31%*** 5.17%*** 0.13%*** 5.86%***
DTI 0.53%*** -5.57%***
New Build 3.23%* -3.48%***
Adverse Credit 3.92%*** 5.18%*** 0.97%*** 5.86%***
Remortgage 0.46%*** 0.84%*** 0.25% 2.46%***
RTB 1.28%*** 2.07%*** 2.09%***
BTL 1.05%*** 2.73%*** -0.18%* 0.77%***
Self Certified 0.16% 0.66%*** 0.10%* 0.81%***
Adverse Credit * Self
Certified 0.52%** 1.15%***
Interest Only 0.37%*** 0.86%*** 0.11%** 0.89%***
Pr(Repossession)x at mean 2.29% 5.26% 0.37% 6.00%
Transaction Dummies Y Y Y Y
N 11902 29042 16173 65238
R-squared 0.1644 0.1376 0.11 0.1015
The table reports marginal effects from the logistic regression using repossessions in non-conforming sector as a dependent variable (intercept is not reported). The marginal effects for OLTV and DTI measure the effect of a 10% increase in the explanatory variable. The categorical variable marginal effect represents the difference in probability of repossession/arrears when the categorical variable is 1 and 0. Pr(repossession) states the probability of repossession using the logistic regression parameters where OLTV, DTI are evaluated at their means and dummy variables at zero. ***,**,* represent statistical significance at 1%,5% and 10% levels respectively.
Table 16: Regression Results for Repossession and 90ever Arrears in Non-Conforming: Reduced Sample
Repossession 90ever Repossession
Information
Arrears Information
OLTV 0.52%*** 3.07%***
DTI 0.06%*** 1.61%***
New Build 5.47%***
Adverse Credit 0.29%*** 9.91%***
Self Certified 0.05%* 0.61%
Adverse Credit *
Self Certified 0.12%** 2.22%***
Remortgage 0.11%*** 2.08%***
Interest Only 0.12%*** 3.07%***
Pr(default)x at mean 0.30% 11.64%
Transaction
Dummies Yes Yes
N 21950 21950
R-squared 0.2475 0.2223
The table reports marginal effects from the logistic regression using repossession and 90ever in non-conforming sector as a dependent variable (intercept is not reported). It uses a reduced sample of loans where both repossession and 90ever indicator were available. The marginal effects for OLTV and DTI measure the effect of a 10% increase in the explanatory variable. The categorical variable marginal effect represents the difference in probability of repossession/arrears when the categorical variable is 1 and 0. Pr(defaults) states the probability of repossession/arrears using the logistic regression parameters where OLTV, DTI are evaluated at their means and dummy variables at zero. ***,**,* represent statistical significance at 1%,5% and 10% levels respectively.
Table 17: Regression Results for Repossession and 90ever Arrears in Non-conforming loans:
Debt-Consolidation Test
Repossession 90ever Repossession
Information
Arrears Information
OLTV 2.77%*** 2.51%***
DTI -0.53%*** 0.49%*
Adverse Credit 2.05%*** 4.15%***
New Build 9.64%**
BTL 1.88%***
Self Certified 0.42% 0.85%**
Adverse Credit* Self Certified
1.00%*
Interest Only 0.79%*** 1.50%***
Remortgage 2.01%***
Debt Consolidation 1.23%***
Pr(default)x at mean 10.23% 2.71%
Transaction Dummies Y Y
N 9326 12773
R-squared 0.2575 0.1045
The table reports marginal effects from the logistic regression using repossession and 90ever in non-conforming sector as a dependent variable (intercept is not reported). It uses a reduced sample of loans where debt consolidation information was available. The marginal effects for OLTV and DTI measure the effect of a 10%
increase in the explanatory variable. The categorical variable marginal effect represents the difference in probability of repossession/arrears when the categorical variable is 1 and 0. Pr(defaults) states the probability of repossession/arrears using the logistic regression parameters where OLTV, DTI are evaluated at their means and dummy variables at zero. ***,**,* represent statistical significance at 1%,5% and 10% levels respectively.
Table 18: Kuipers-Score by OLTV band for Prime 2004, 2005, 2006 and 2007 origination vintage models as reported in Table 12
OLTV 2004 2005 2006 2007
0-40 0.013 0.013
40-50 0.015 0.098
50-60 0.031 0.013 0.002 0.245
60-65 0.155 0.011 0.053 0.244
65-70 0.258 0.022 0.041 0.079
70-75 0.173 0.096 0.078 0.147
75-80 0.194 0.170 0.204 0.124
80-85 0.245 0.201 0.177 0.176
85-90 0.176 0.237 0.172 0.177
90-95 0.188 0.131 0.066 0.079
95-98 0.152 0.087 0.035 0.025
Table 19: Kuipers-Score by DTI band for Prime 2004, 2005, 2006 and 2007 origination vintage models as reported in Table 12
DTI 2004 2005 2006 2007
<=20% 0.394 0.344 0.462 0.367
20%-25% 0.425 0.494 0.506 0.457
25%-30% 0.461 0.449 0.406 0.341
30%-35% 0.380 0.404 0.349 0.362
35%-40% 0.400 0.351 0.318 0.237
40%-45% 0.390 0.316 0.292 0.194
>45% 0.380 0.302 0.265 0.203
Table 20: Kuipers-Score by OLTV band for Non-Conforming 90ever 2005, 2006, 2007 and combined origination vintage models as reported in Table 12
OLTV 2004 2005 2006 All
0-40 0.153 0.224 -0.054 0.043
40-50 0.420 0.224 0.100 0.061
50-60 0.386 0.325 0.090 0.059
60-65 0.313 0.305 0.354 0.061
65-70 0.236 0.343 0.208 0.049
70-75 0.481 0.337 0.243 0.046
75-80 0.260 0.374 0.244 0.052
80-85 0.234 0.368 0.218 0.037
85-90 0.275 0.413 0.235 0.029
90-95 0.360 0.351 0.108 0.040
95-98 0.182 0.355 0.195 0.012
Table 21: Kuipers-Score by DTI band for Non-Conforming 90ever 2005, 2006, 2007 and combined origination vintage models as reported in Table 14
DTI 2004 2005 2006 All
<=20% 0.354 0.412 0.022 0.080
20%-25% 0.272 0.387 0.107 0.097
25%-30% 0.286 0.385 0.227 0.100
30%-35% 0.320 0.396 0.284 0.111
35%-40% 0.258 0.395 0.115 0.125
40%-45% 0.346 0.396 0.200 0.143
>45% 0.378 0.332 0.230 0.140
Table 22: Kuipers-Score by OLTV band for Non-Conforming Repossession 2005, 2006, 2007 and combined origination vintage models as reported in Table 15
OLTV 2004 2005 2006 All
Table 23: Kuipers-Score by DTI band for Non-Conforming Repossession 2005, 2006, 2007 and combined origination vintage models as reported in Table 15
DTI 2004 2005 2006 All
Table 24: Cross-Country Comparison of Default Drivers
UK US Portugal Netherlands Greece Germany
OLTV ↑ ↑ ↑ ↑ ↑ ↑
* NA=Data not available or the field was not relevant to the particular country; NS=Variable was not statistically significant at 10% or below; ↑ is where the variable increases the probability of default and ↓ is where the variable decreases the probability of default.
Figure 1: Default Rates by Origination Vintage
% of loans (90ever-Prime /Repossessed Non-Conforming)
0.0%
% of Loans 90ever (Non- conforming)
Non-Conforming Repossession Rate Prime - 90ever Rate
Non-Conforming - 90ever Rate
Figure 2: OLTV Distribution by Origination Vintage - Non-Conforming (Repossession Information)
Figure 3: OLTV Distribution by Origination Vintage - Non-Conforming (Arrears Information)
0.0%
0-40 40-50 50-60 60-65 65-70 70-75 75-80 80-85 85-90 90-95 95-98 OLTV Band
% of loans in vintage
2005 2006 2007
Figure 4: OLTV Distribution by Origination Vintage - Prime
Distribution of OLTVs by Origination Vintage - Prime Loans
0 5 10 15 20 25
0-40 40-50 50-60 60-65 65-70 70-75 75-80 80-85 85-90 90-95 95-98 OLTV Band
% of All Loans in Vintage Pre 2000
2000-2002 2003 2004 2005 2006 2007
Figure 5: Distribution of DTIs by Origination Vintage - Non-Conforming (Repossession Information)
0 5 10 15 20 25
<=20% 20%-25% 25%-30% 30%-35% 35%-40% 40%-45% >45%
DTI Band
% of loans in vintage
2005 2006 2007
Figure 6: Distribution of DTIs by Origination Vintage - Non-Conforming (Arrears Information)
0 5 10 15 20 25
<=20% 20%-25% 25%-30% 30%-35% 35%-40% 40%-45% >45%
DTI Bands
% of loans in vintage
2005 2006 2007
Figure 7: Distribution of DTIs by Origination Vintage - Prime
% of loans in vintage Pre 2000
2000-2002
Figure 8: Repossession Rate by OLTV Band – Non-Conforming (Repossession Information)
0
0-40 40-50 50-60 60-65 65-70 70-75 75-80 80-85 85-90 90-95 OLTV Band
% of Defaulted Loans
2005 2006 2007
Figure 9: 90ever Rate by OLTV Band – Non-Conforming (Arrears Information)
0
0-40 40-50 50-60 60-65 65-70 70-75 75-80 80-85 85-90 90-95 95-98 OLTV Band
% of Loans >=3 months arrears
2005 2006 2007
Figure 10: 90ever Rate by OLTV Band – Prime (Arrears Information)
% of Loans >=3 months Arrears
Pre 2000
Figure 11: Repossession Rate by DTI Band – Non-Conforming (Repossession Information)
0
<=20% 20%-25% 25%-30% 30%-35% 35%-40% 40%-45% >45%
DTI Bands
% of Defaulted Loans
2005 2006 2007
Figure 12: 90ever Rate by DTI Band – Non-Conforming (Arrears Information)
0
<=20% 20%-25% 25%-30% 30%-35% 35%-40% 40%-45% >45%
DTI Band
% of Loans in >=3 month arrears
2005 2006 2007
Figure 13: 90ever Rate by DTI Band – Prime (Arrears Information)
% of loans >=3 month arrears
Pre 2000
Figure 14: Average Pearson Residuals by OLTV Bucket in Prime Model
-0.04
0-40 40-50 50-60 60-65 65-70 70-75 75-80 80-85 85-90 90-95 95-98
OLTV Band
Figure 15: Average Pearson Residuals by DTI Bucket in Prime Model
-0.025
<=20% 20%-25% 25%-30% 30%-35% 35%-40% 40%-45% >45%
DTI Band
Pearson Residuals
2004 2005 2006
Figure 16: Average Pearson Residuals by OLTV Bucket in Non-Conforming 90ever Model
-0.2 -0.15 -0.1 -0.05 0 0.05 0.1 0.15
0-40 40-50 50-60 60-65 65-70 70-75 75-80 80-85 85-90 90-95 95-98
OLTV Bucket
Pearson Residual
2005 2006 2007
Figure 17: Average Pearson Residuals by DTI Bucket in Non-Conforming 90ever Model
-0.06 -0.04 -0.02 0 0.02 0.04 0.06 0.08 0.1 0.12 0.14
<=20% 20%-25% 25%-30% 30%-35% 35%-40% 40%-45% >45%
DTI Band
Pearson Residuals
2006 2007
Figure 18: Average Pearson Residuals by OLTV Bucket in Non-Conforming Repossessions Model
-0.1 -0.05 0 0.05 0.1 0.15 0.2
0-40 40-50 50-60 60-65 65-70 70-75 75-80 80-85 85-90 90-95 95-98
OLTV Band
Residuals 2005
2006 2007
Figure 19: Average Pearson Residuals by DTI Bucket in Non-Conforming Repossessions Model
-0.02 -0.01 0 0.01 0.02 0.03 0.04 0.05
<=20% 20%-25% 25%-30% 30%-35% 35%-40% 40%-45% >45%
DTI Band
Pearson Residuals
2006