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Comparing the Performance of Home Affordable Modification Program 

(HAMP) Modifications and Non-HAMP Modifications: Early Results 1

EXECUTIVE SUMMARY

I. INTRODUCTION

Since the inception of the Making Home Affordable Program (MHA), more than 1.3 million 

borrowers have had their mortgages permanently modified through MHA’s Home Affordable 

Modification Program (HAMP). This paper analyzes the performance of HAMP modifications to 

better understand the key factors affecting their performance. 

In the first part of this paper, single-variable analysis and program-to-date data for all HAMP 

modifications are used to identify correlations between various HAMP modification 

characteristics and modification performance. 

The most significant factors driving HAMP modification performance are the amount of monthly 

payment reduction relative to the borrower’s pre-modification payment, the length of the 

borrower’s delinquency at time of modification, and, to a slightly lesser extent, credit score at 

time of modification. Post-modification mark-to-market loan-to-value (MTMLTV) ratio appears 

to have some influence on HAMP modification performance for certain segments of the HAMP 

population. Other criteria, such as the borrower’s “back-end” debt-to-income (DTI) ratio2and 

geography have less influence on HAMP modification performance.

In the second part, econometric analysis (regression testing) is used to isolate the key factors 

affecting HAMP modification performance and to compare the performance of loans modified 

through HAMP with other similarly delinquent loans. The innovation in this study comes from 

the merging of HAMP program data with a commercial loan performance database provided by 

CoreLogic,3 which allows HAMP-modified loans to be compared directly with two alternate 

control groups consisting of loans that were modified outside of HAMP and loans that were 

similarly delinquent but never received a modification. The HAMP loans and the two control 

groups were restricted to loans that are part of private label mortgage-backed securities (PLS). 

The regression analysis generated the following results:

Modified PLS loans – both HAMP and non-HAMP – perform significantly better than PLS 

loans receiving no modification.

 

1 This analysis described in this paper was performed by Walter Scott, a Fannie Mae economic researcher working 

for Fannie Mae in its role as program administrator for Making Home Affordable (MHA), a program of the United 

States Department of the Treasury and the Department of Housing and Urban Development. Unless otherwise noted, 

the data points, figures, and tables reflected herein were sourced from Treasury’s MHA system of record.

2

“Back-end” DTI refers to the borrower’s DTI taking into account all of the borrower’s monthly debt obligations, 

not just the obligations under the mortgage loan.

3 CoreLogic’s Loan Performance subprime database provides origination and performance history for approximately 

90 percent of all subprime and Alt-A residential mortgages that were bundled into private label mortgage-backed 

securities and active in the 2010-2011 timeframe.
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Payment reduction and delinquency at the start of the modification are initially the two most 

significant factors driving the performance of both HAMP and non-HAMP modifications. 

However, the significance is found to be time sensitive: the importance of delinquency at 

time of modification decreases as the modification ages, while the importance of payment 

reduction increases. Other factors contributing to performance include post-modification 

MTMLTV, credit score at the time of loan origination, and geography.

HAMP modifications of PLS loans perform better than non-HAMP modifications of PLS 

loans. This is true even when controlling for modification terms, including payment 

reduction. For example, a HAMP modification of a PLS loan with a 10 to 20 percent 

payment reduction performs better than a non-HAMP modification of a similar PLS loan also 

with a 10 to 20 percent payment reduction.

The act of resetting a borrower’s delinquency level was proven to have a major initial impact 

on the borrower’s post-modification performance. This “delinquency reset effect” is also 

time sensitive and diminishes significantly as the modification ages.

While confined to a subset of loans (i.e., PLS loans), these conclusions suggest that borrowers in 

HAMP modifications may be significantly less likely to experience redefault than borrowers 

receiving no modification at all or a modification outside of HAMP. The importance of this issue 

to struggling borrowers, oversight bodies, lawmakers, and other housing policymakers 

underscores the importance of further research on this topic and replication of this analysis on a 

broader set of loan data.

II. SINGLE-VARIABLE ANALYSIS OF FACTORS DRIVING PERFORMANCE 

USING DATA FOR ALL HAMP MODIFICATIONS

As of March 2014, over 945,000 permanent HAMP modifications were performing and in good 

standing within the MHA program. More than 380,000 or 28 percent had been disqualified from 

the program because the borrower missed three consecutive monthly payments on the modified 

loan. Through February 2014, HAMP modifications were experiencing overall redefault rates4of 

5.2 percent, 13.4 percent, 20.3 percent, and 26.1 percent by months 6, 12, 18, and 24, 

respectively. 

The data also indicate that the performance of HAMP modifications has gradually improved over 

time, with more recent vintages of modifications generally performing better than older vintages 

at any given seasoning point. For example, for modifications in effect for one year, 20.5 percent 

of modifications started in the third quarter of 2009 have disqualified, compared to 9.5 percent of 

modifications started in the first quarter of 2013.

In addition, as seen in Figure 1, the data show that the growth rate of redefaults on HAMP 

modifications is declining. Thus, while the cumulative redefault rate for each annual vintage of 

 

4 Unless otherwise noted, this paper defines a redefault as a modification that becomes 90 or more days delinquent 

following modification. 
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modifications grows over time, the redefault rate for each successive three-month period 

generally declines.

Figure 1: HAMP Three-Month Conditional Redefault Rates by Modification Year5

Single-variable analysis of Treasury data collected as part of the HAMP modification process 

helps to shed light on the characteristics that most influence modification performance. The 

results of this analysis are limited by both the inherent limitations of single-variable analysis and

potential unobserved factors not found in the Treasury data. For example, while income level is 

collected as part of the modification process, post-modification fluctuations in levels of income 

are unknown and may have a significant impact on performance. 

Payment Reduction: Most HAMP modifications result in significant mortgage payment 

reductions, with half of the population receiving a monthly payment reduction of approximately 

$500, or over a third of the median monthly payment before modification.6

As seen in Figure 2, single-variable analysis shows that the amount of payment reduction has a 

significant impact on performance. Modifications with larger payment reductions consistently 

outperform those modifications with smaller reductions. This is true across all vintages and 

seasoning points. Over time, the gap in performance among payment reduction cohorts increases 

significantly. For example, 41 percent of HAMP borrowers with modifications that reduce the 

monthly payment by 20 percent or less became 90 or more days delinquent within 24 months of 

modification, compared to only 16 percent of borrowers with a monthly payment reduction of 

greater than 50 percent.

 

5 The three-month redefault rate was calculated as the number of permanent modifications disqualified within the 

three-month period divided by the number of permanent modifications remaining active at month(T – 3) and if still 

active at month T. Permanent modifications remaining active at month(T—3) excludes those permanent 

modifications that have paid off or disqualified by month(T – 3).

6 March 2014 Making Home Affordable Program Performance Report.

2009

2011 2010

2012

2013

0%

1%

2%

3%

4%

5%

6%

6 9 12 15 18 21 24 27 30 33 36 39 42 45 48 3 Month Redefault Rate

Months After Conversion to Permanent Modification
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Figure 2: Performance by Percent Reduction in Monthly Mortgage Payment

Delinquency at Time of Modification: The single-variable analysis also indicates that 

performance of the modification is influenced by the length of delinquency of the loan at the start 

of the modification. Borrowers who were 31 to 90 days delinquent at the start of the HAMP 

modification experienced a 24 percent redefault rate in the subsequent 24 months, compared to a 

rate of 30 percent for borrowers whose delinquency was between 121 and 210 days at trial start.

Figure 3: Performance by Delinquency at Time of Modification

Credit Score: The single-variable analysis also indicates that credit score at the time of 

modification also has a significant impact on performance.

7

For example, borrowers with credit 

 

7 Treasury’s program data contain information on the borrower’s credit score at the time of modification. The data 

show a correlation between degree of delinquency at the time of modification and credit score at the time of 

modification. Borrowers who were more delinquent at the time of modification tended to have lower credit scores, 

0%

10%

20%

30%

40%

50%

60%

70%

12 18 24 30 36 42 48

90+ Day Delinquency Rate

Months After Conversion to Permanent Modification

<= 20%

(20%, 30%]

(30%, 40%]

(40%, 50%]

> 50%

0%

10%

20%

30%

40%

50%

60%

70%

12 18 24 30 36 42 48

90+ Day Delinquency Rate

Months After Conversion to Permanent Modification

<= 30 Days

31 - 90 Days

91 - 120 Days

121 - 210 Days

> 210 Days
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scores below 580 at the time of modification experienced a 33 percent redefault rate in the 

subsequent 24 months, compared to a rate of 11 percent for borrowers whose credit scores were 

above 660.

Figure 4: Cumulative Redefault Rate by Credit Score at Time of Modification

Post-Modification MTMLTV: Single-variable analysis of HAMP data indicates that postmodification MTMLTV has an impact on redefault rates but to a lesser degree than the factors 

discussed above. For example, as seen in Figure 5, the difference in 24-month redefault rates 

between borrowers with an MTMLTV of 80 percent or less and those with an MTMLTV of 

greater than 170 percent is about 9 percentage points. In contrast, borrower outcomes do not vary 

greatly for MTMLTV between 80 and 170 percent.

 

which is logical since delinquency on the mortgage has a significant impact on credit score. Note that Treasury’s 

program data do not include the borrower’s credit score at the time of loan origination, making it impossible to 

analyze the potential impact of this factor on modification performance in the single-variable analysis. 

0%

10%

20%

30%

40%

50%

60%

70%

12 18 24 30 36 42 48

90+ Day Delinquency Rate

Months After Conversion to Permanent Modifiction

< 580

580 - 619

620 - 660

> 660
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Figure 5: Cumulative Redefault Rate by Post-Modification MTMLTV

III. REGRESSION ANALYSIS OF THE EFFECTIVENESS OF HAMP AND NONHAMP MODIFICATIONS FOR PLS LOANS

To gain greater insight into the factors driving modification performance and the effectiveness of 

both HAMP and non-HAMP modifications, this study uses regression analysis to look at three 

populations of similarly delinquent PLS loans: 

Loans modified under HAMP; 

Loans modified outside of HAMP (proprietary modifications); and, 

Loans that were not modified. 

The study population of HAMP loans was derived by matching data from the CoreLogic 

commercial loan performance database for PLS loans against the subset of HAMP modifications 

of PLS. In addition, the loans from this commercial database were restricted to loans that became 

at least 30 days delinquent during the timeframe of the HAMP program. 

The performance of modified loans was measured in terms of the loan’s status after a fixed time 

interval (ranging from six to 36 months) from the date the modification became permanent. The 

loan was considered to have an adverse outcome (redefault) if by the end of a time interval it 

had: a) become 90 or more days delinquent; b) been liquidated at a loss; or c) required an 

additional modification. Loans that became delinquent but were not modified were examined 

over the same time interval. In this control group a loan was considered to have an adverse 

outcome if by the end of the time interval it had: a) become 90 or more days delinquent; b) been 

liquidated; or c) been subsequently modified.

This regression analysis allows for the separation of the true treatment effects of a modification 

from possible selection effects. Modification effectiveness is measured as the selection-biasadjusted average treatment effect on the modified loan (also known as the average treatment 

0%

10%

20%

30%

40%

50%

60%

70%

12 18 24 30 36 42 48

90+ Day Delinquency Rate

Months After Conversion to Permanent Modification

<= 80%

(80%, 100%]

(100%, 120%]

(120%, 150%]

(150%, 170%]

> 170%
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effect on the treated or ATET). This is estimated from an econometric model that simulates 

random assignment of loans to the modification program. The ATET is the average difference 

between a loan’s expected probability of an adverse outcome (defined as becoming 90 or more 

days delinquent) over a fixed period of time depending on whether the loan was modified under 

HAMP, modified outside of HAMP, or not modified at all. For example, if the average loan has 

a 60 percent chance of an adverse outcome without modification but a 40 percent chance when 

modified, then the ATET is 20 percentage points.8

The analysis examined a series of hypotheses about modification effectiveness and the factors 

driving modification performance.

Hypothesis 1: Modifying a loan has a significant effect on borrower performance outcomes, 

even when controlling for borrower and loan characteristics. 

This was strongly confirmed. While selection bias is a significant factor, typically accounting for 

13 to 33 percent of the observed modification effects, there is a substantial modification 

treatment effect. A typical PLS loan receiving a HAMP modification in 2010, for example, had 

its likelihood of redefault reduced by about 40 percentage points, even 36 months after the date 

of modification. 

A breakdown of HAMP and non-HAMP observed effects, selection effects, and treatment effects 

is shown in Figure 6. Note that the selection effects depicted in Figure 6 act in opposite 

directions on the HAMP and non-HAMP populations. The regression analysis predicts that if 

loans had been randomly assigned to modification programs, expected overall HAMP 

performance would be worse, but expected non-HAMP performance would be better. This 

implies that a number of the loans that fell out of the HAMP pipeline but then received 

proprietary modifications during this time period had higher-than-average risk characteristics.

 

8 As with the single-variable analysis, the results may be influenced by variables that are unobservable due to 

limitations in the data set. For example, the commercial database employed by the study does not clearly indicate 

which modifications received principal forgiveness or forbearance, making it difficult to isolate their potential 

effects on modification performance. Similarly, data limitations made it impossible to test the effects of the backend DTI or the borrower’s credit score at the time of modification. Note that unlike the Treasury data used for the 

single-variable analysis, the data used for the regression analysis do include the borrower’s credit score at the time 

of loan origination.
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Figure 6: Breakdown of Estimated Selection and Treatment Effects of 2010 HAMP and 

Non-HAMP Loans

Hypothesis 2: HAMP modifications perform better than non-HAMP modifications, even 

when controlling for borrower and loan characteristics.

This was also confirmed but more strongly for loans receiving a HAMP modification in 2011 

than in 2010. Even when looking only at modifications that reduced borrowers’ payments, 

borrowers receiving a HAMP modification in 2011 have on average a 18 percentage point lower 

redefault rate after 24 months than those receiving non-HAMP modifications. Borrowers 

receiving a HAMP modification in 2010 perform better (7 percentage points lower redefault rate) 

than those receiving non-HAMP modifications through month 36. These differences in 

performance are likely the result of the more generous payment reductions typically offered by 

HAMP modifications versus non-HAMP modifications. Table 1 below compares treatment 

effects of HAMP and non-HAMP modifications across both modification vintages at various 

points in time since modification.

Table 1: Average Treatment Effect on the Treated (Modified) Population, with Sample 

Selection Effects Removed (Numbers Show Percentage Point Decrease in Likelihood of 

Redefault)

0

10

20

30

40

50

60

70

80

90

6 12 18 24 30 36 Rate of 90+ Delinquency or Liquidation

Months after Base Date

2010 HAMP Modifications

0

10

20

30

40

50

60

70

80

90

6 12 18 24 30 36 Rate of 90+ Delinquency or Liquidation

Months after Base Date

2010 Non-HAMP Modifications

Unmodified loans (observed)

Modified loans if not modified

Modified loans selection effect 

removed

Modified loans (observed)

Selection Effect

Treatment Effect

6 12 18 24 30 36

2010 HAMP 56 51 47 44 42 40

2010 Non-HAMP 55 48 43 40 35 33

2011 HAMP 64 60 55 51

2011 Non-HAMP 54 43 37 33

Months Post Modification Modification Vintage
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Hypothesis 3: Controlling for borrower and loan characteristics, payment reduction is the 

most significant factor driving modification performance. 

The results from testing this hypothesis are time-dependent. Initially, the borrower’s level of 

delinquency at the time of modification is the most important factor determining performance, 

with level of payment reduction slightly less important. As time passes, however, payment 

reduction becomes relatively more significant, and by two-or-more years post-modification it 

becomes the most important performance driver.

Figure 7 shows that by 36 months after modification payment reduction is the most important 

factor driving modification performance. 

Figure 7: Relative Impact of Factors on Modification Performance at 36 Months, 2010 

HAMP and Non-HAMP Modifications

Hypothesis 4: HAMP modifications perform better than non-HAMP modifications, even 

when controlling for borrower and loan characteristics and the changes in loan terms. 

This hypothesis was confirmed with qualifications. To assess this hypothesis, the performance of 

a modification with no payment reduction was used as a baseline,9from which the performance 

of a HAMP and non-HAMP modification across different levels of payment reduction could be 

compared. As shown in Figure 8, there appears to be a persistent performance advantage for 

HAMP modifications, independent of the changes in loan terms. At the same time, loans with 

HAMP modifications have shown a stronger response to payment reductions, while non-HAMP 

modifications have had a relatively larger effect for borrowers who were extremely delinquent 

(12 months or more) prior to the modification. 

 

9

For comparison purposes, the analysis assumed a redefault rate of 45 percent at 18 months post-modification.

36.7%

25.5%

10.2%

2.1%

10.5%

2.7%

12.2%

HAMP Performance at 36 months

36.8%

21.3%

12.6%

6.4%

6.8%

2.1% 13.9%

Non-HAMP Performance at 36 months

Payment Reduction

Pre-Mod Delinquency

MTMLTV at Mod

Origination FICO

State / MSA factors

Time Factors (Modification 

Date)

All Other Factors
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Figure 8: Reduction in Redefault Probability 24 Months Post-Modification by Payment 

Reduction Percentage

Hypothesis 5: Modifying a loan has a positive impact on loan performance, even when 

controlling for borrower and loan characteristics and the changes in loan terms. 

Finally, the analysis also sought to test whether a modification has a positive impact even in 

cases where it did not reduce the borrower’s payments or principal balance but simply reset the 

borrower’s delinquency status to “current.” In other words, does the process of bringing a 

delinquent borrower current, by itself, change the borrower’s payment behavior?

This appears to be true primarily in the short term. The act of resetting a delinquent borrower to 

current status has a significant effect on loan performance, but this effect diminishes significantly 

over time and is mostly absent by 36 months after the modification for borrowers that were less 

than or equal to six months delinquent at the time of modification. While still trending 

downward, a residual effect remains 36 months after modification, specifically for the nonHAMP population more than six months delinquent. This is shown graphically in Figures 9 and 

10.

Note that in both Figures 9 and 10 the effect of delinquency at time of modification is initially 

strong but decreases significantly over time. This is shown by the convergence of reduction of 

redefault probability across delinquency buckets over time. This further confirms the results 

from testing Hypothesis 3 (that payment reduction is the most significant factor driving 

modification performance).

0%

5%

10%

15%

20%

25%

30%

35%

40%

5 10 15 20 25 30 35 40 45 50 55 60

% reduction in p(SDQ) in 24 months, from 45% baseline

Payment reduction %

HAMP 2010

HAMP 2011

Non-HAMP 2010

Non-HAMP 2011
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Figure 9: Treatment Effect for 2010 HAMP Modifications by Delinquency at Time of 

Modification 

Figure 10: Treatment Effect for 2010 Non-HAMP Modifications by Delinquency at Time of 

Modification

0

10

20

30

40

50

60

70

6 12 18 24 30 36

Reduction in Redefault Probability (Pctg. Points)

Months Since Modification

18+ mths DLQ

1 2-17 mths DLQ

6-11 mths DLQ

3-5 mths DLQ

2 mths DLQ

1 mth DLQ

-10

0

10

20

30

40

50

60

70

6 12 18 24 30 36

Reduction in Redefault Probability (Pctg. Points)

Months Since Modification

18+ mths DLQ

1 2-17 mths DLQ

6-11 mths DLQ

3-5 mths DLQ

2 mths DLQ

1 mth DLQ
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IV. CONCLUSION

While based on only a few years of performance data, both the single-variable analysis of all 

HAMP program data and the regression analysis on modifications to PLS loans support the 

intuitive proposition that payment reduction and length of delinquency at the time of 

modification are the most critical drivers of modification performance. Other factors, including 

post-modification MTMLTV, the borrower’s credit score at origination, and geography, appear 

to be significant under the regression analysis but less important than payment reduction and 

delinquency status.

The regression analysis – while confined to the PLS population – also supports the proposition 

that HAMP modifications have a better probability of success than similar loans that are either 

not modified or modified outside of HAMP. While the higher success rate of HAMP 

modifications is partly attributable to their greater amount of payment reduction, the analysis 

found that HAMP modifications still perform better even after controlling for modification 

terms, including payment reduction. Additionally, the analysis found that even modifications that 

simply bring a delinquent borrower current may have a positive impact on payment behavior.

This analysis is based on early results, and it will be important to update this research as HAMP 

and non-HAMP modifications build longer performance records. It is also Treasury’s hope that 

this study spurs further research that will seek to apply the regression technique used here on a 

broader population of loans.