Disclosure Regulation on Mortgage Securitization and

Subprime Loan Performance

Lantian Liang Harold H. Zhang Feng Zhao Xiaofei Zhao∗

October 2, 2014

Abstract

Regulation AB (Reg AB) enacted in 2006 mandates disclosure by originators of 20%or more of the pool assets on information regarding the size and composition of theoriginator’s origination portfolio as well as information material to an analysis of theperformance of the pool assets such as the originators credit-granting or underwritingcriteria. Using data on the non-agency mortgage backed security (MBS) market, wefind that after Reg AB a higher fraction of mortgage deals consists of loans fromlow-stake originators just below the disclosure threshold. Deals with these low-stakeoriginators have significantly larger losses than those without and this is only so fordeals issued after Reg AB. In particular, deals with originators who change from high-stake to low-stake have larger losses. Analysis on loan level data provides furtherevidence that securitized loans show worse performance when their originators increasetheir participation of deals as a low-stake originator after Reg AB. Overall, our evidencesuggests that mortgage securitizers circumvent the disclosure requirement in Reg ABand this has adverse impact on mortgage performance.

Keywords: Regulation AB; Disclosure Threshold; MBS Performance

∗Naveen Jindal School of Management, University of Texas at Dallas, 800 West Campbell Road, Richard-son, Texas, 75080, email: lantian.liang@utdallas.edu, harold.zhang@utdallas.edu, feng.zhao@utdallas.edu,xiaofei.zhao@utdallas.edu

1. Introduction

Regulation reform on disclosure in the private-label MBS market remains a virtually un-

explored area in the aftermath of the 2007-2008 subprime mortgage crisis. To meet the

insatiable demand from global investors reaching for higher yields, the entire supply chain

of mortgage securitization increasingly expanded lending to riskier borrowers. Compelled

by the rapid growth of loan securitization market and the lack of explicit regulations direct-

ed towards the distinguishing features of this market, Securities and Exchange Commission

introduced Regulation AB (Reg AB). While Reg AB became effective in January 2006, no

study has devoted to examining its effects on loan securitization market. Our investigation

represents the first attempt to evaluate how Reg AB affected the structure of securitization

and securitized loan performance.

In this study, we focus on the effect of disclosure regulation under Reg AB on the resi-

dential mortgage securitization market. Existing studies attribute the financial crisis to the

sharp increase in mortgage loan defaults.1 Securitized residential mortgages accounted for

a large fraction of new issuance of securitized loans in the period leading to the financial

crisis.2 We collect detailed deal and loan level data on securitized mortgages which facili-

tate an in-depth investigation and allows quantitative assessment on the regulation effects.

Specifically, we examine the effect of disclosure threshold on loan originators under Reg AB,

the structural change of the MBS issuance and the associated impact on the performance of

securitized mortgages.

To identify the effect on securitized mortgages, we resort to cross sectional variation in

deal strucuture and loan originators with different reactions to the regulation. Specifically, we

focus on its effect on loan originators because Reg AB sets different disclosure requirements

1See, Mian and Sufi (2009), Nadauld and Sherlund (2009), Keys, Mukherjee, Seru, and Vig (2010), Keys,Seru, and Vig (2012), Purnanandam (2011), among others.

2According to former International Monetary Fund chief economist Simon Johnson, the “total volume ofprivate mortgage-backed securities (excluding those issued by Ginnie Mae, Fannie Mae and Freddie Mac)grew from $11 billion in 1984 to over $200 billion in 1994 to close to $3 trillion in 2007.”

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on loan originators based on the percentage of loans included in a mortgage deal by each

originator. Reg AB Item 1110 requires identification of any originator or group of affiliated

originators that originated, or is expected to originate, 10% or more of the pool assets;

and requires disclosure of information regarding the size and composition of the originator’s

origination portfolio as well as information material to an analysis of the performance of

the pool assets, such as the originator’s credit-granting or underwriting criteria for the asset

types being securitized, if the originator originated or is expected to originate 20% or more

of the pool assets.

We collect information on loan originators from mortgage deal prospectuses of privately

securitized residential mortgages between 2003 and 2007 from Bloomberg. For each mortgage

deal, its prospectus provides information on the composition of loans originated by different

originators. To link individual loans to a particular originator in a deal, we utilize First

American Corelogic LoanPerformance database. Corelogic data provides the name of the

original lender for each loan. We collect identity and affiliation information for the original

lender of each loan to determine if the original lender is one of the mortgage deal originators

or is affiliated with one of these deal originators. Using this information, we assign individual

loans to the originators listed in the prospectus supplements, which we use to perform loan

level analysis on the impact on loan performance of deal structure change due to Reg AB.

Our investigation demonstrates several significant effects of the regulatory disclosure

mandate on certain loan originators and the performance of securitized mortgages. First,

we find that the number of financial institutions originated less than 20% of loans in each

mortgage deal (referred to as low-stake originators hereafter) increased significantly post Reg

AB. In particular, the percentage of deals having low-stake originators more than doubled

after Reg AB relative to before Reg AB. This unintended consequence of Reg AB has a

significant effect on performance of securitized mortgages. Deals with low-stake originators

have significantly larger cumulative net losses than those without and this is only so for

deals issued after Reg AB, but not before Reg AB. In particular, deals with originators who

2

change from high-stake to low-stake have larger cumulative net losses. Analysis on loan level

data provides further evidence that securitized loans show worse performance when their

originators increase their participation of deals as low-stake originators after Reg AB. This

result also suggests that the strategic use of the regulatory threshold is unlikely due to the

motive of avoiding SEC compliance costs, rather, it is more likely driven by the intention of

avoiding scrutiny and potentially withholding some adverse information on riskier loans.

Our paper contributes to two strands of research. First, it offers the first empirical inves-

tigation on the effect of changes in regulations on mortgage securitization on the practices

of financial institutions participated in this market and their consequences on loan perfor-

mance. Second, it sheds light on the effect of mandatory disclosure on financial institutions

and the performance of securitized loans issued by these financial institutions. While early

studies argue that firms disclose bad news to avoid lawsuits in the future (Skinner (1994)),

more recent evidence suggests that firms disclosing more also have more frequent litigation

(Skinner (1997)). Kothari, Shu, and Wysocki (2009) argue that firms withhold bad news up

to certain threshold and provide evidence using different magnitude of stock market reaction

to negative and positive news.

The rest of the paper is organized as follows. Section 2 describes the most relevant

item on originator information disclosure under Reg AB. Section 3 describes data and pro-

vides summary statistics. Section 4 presents and discusses our empirical findings at deal

level. Section 5 provides loan level evidence on the impact of low-stake originators on loan

performance. Finally, section 6 concludes.

2. Regulation AB

Securities and Exchange Commission defined asset-backed securities (ABS) as securities that

are backed by a discrete pool of self-liquidating financial assets. ABS market experienced

a rapid growth in the last two decades. One source estimates that annual issuance of U.S.

3

public non-agency ABS grew from $46.8 billion in 1990 to $416 billion in 2003.3 Another

source estimates that new issuance for 2003 was at $800 billion.4 Prior to the introduction

of Reg AB, there have been few SEC initiatives directly related to ABS. In this section, we

describe the most relevant item of Reg AB on originator information disclosure for mortgage

securitization and discuss the implications for mortgage deal structure and securitized loan

performance.

Asset-backed securitization is a financing technique in which financial assets are pooled

and converted into instruments that may be offered and sold more freely in the capital mar-

kets. In a basic securitization structure, a financial institution known as sponsor constructs

a pool of financial assets, such as mortgage loans, self-originated or acquired directly or

through an affiliate. Securities backed by the pool of financial assets are then sold to in-

vestors by investment banks known as underwriters. Payment on the asset-backed securities

depends primarily on the cash flows generated by the assets in the underlying pool and other

rights designed to assure timely payment such as guarantees known as credit enhancements.

Asset-backed securities and ABS issuers differ from corporate securities and operating

companies in that “there is generally no business or management to describe in offering these

securities. Instead, information about the transaction structure and the quality of the asset

pool and servicing is often what is most important to investors.”5 According to SEC, prior

to Reg AB, many of the SEC existing disclosure and reporting requirements, which were

designed primarily for corporate issuers, did not elicit the information that is relevant for

most asset-backed securities transactions. Reg AB which became effective in January 2006

thus represents a comprehensive treatment of asset-backed securities under the Securities Act

and the Exchange Act. It consolidates and codifies SECs positions and industry practice

which it has done through no-action letters and the filing review process over time leading

to Reg AB.

3See Bank One Capital Markets, Inc., 2004 Structured Debt Yearbook.4See Asset Securitization Report (pub. by Thomson Media Inc).5See Securities and Exchange Commission Asset-Backed Securities Proposed rule Release NOS. 33-8419;

34-49644.

4

Reg AB covers four primary regulatory areas: Securities Act registration; disclosure;

communications during the offering process; and ongoing reporting under the Exchange

Act.6 The new rules on disclosure represent the most dramatic changes on the ABS markets.

Prior to Reg AB, there was no disclosure items specifically tailored to asset-backed securities.

While eliminating unnecessary boilerplate and de-emphasizing unnecessary legal recitations

of terms, Reg AB requires that issuers disclose information material to an asset-backed

securities transaction, such as the background, experience, performance, and roles of various

transaction parties, including the sponsor, the servicing entity and the trustee. It also

requires, for the first time, that certain statistical information on a static pool basis be

provided if material to the transaction to aid in an investors analysis of current and prior

performance.

Specifically on loan originators, Reg AB Item 1110 requires identification of any originator

or group of affiliated originators that originated, or is expected to originate, 10% or more

of the pool assets; and requires disclosure of information regarding the size and composition

of the originator’s origination portfolio as well as information material to an analysis of

the performance of the pool assets, such as the originator’s credit-granting or underwriting

criteria for the asset types being securitized, if the originator originated or is expected to

originate 20% or more of the pool assets. Thus, loan originators of 20% or more of the

collateral pool represents an important disclosure threshold which did not exist prior to Reg

AB. Our empirical investigation on the effect of Reg AB on securitized loan performance

will focus on the change in loan originators in the disclosure threshold and associated cross

sectional variations in loan performance of these originators.

Prior to Reg AB, the SEC positions on the ABS issuance was done through no-action

letters. These positions and industry practice are consolidated and codified under Reg AB.

Therefore, in the post-Reg AB period, riskier loans in a deal from certain originators may

be used strategically to keep their fraction in the deal below the threshold in order to

6See Securities and Exchange Commission Regulation AB Final Rule 33-8518.http://www.sec.gov/rules/final/33-8518.pdf.

5

avoid mandatory information disclosure. As a consequence, we expect the number of deals

involving below threshold low-stake originators (20 percent under Reg AB) to increase in

mortgage deals after Reg AB. This gives us the following testable hypothesis.

Hypothesis 1: All else equal, the likelihood of a deal involving low-stake originators is

higher after Reg AB than before Reg AB.

There are two main motives on the use of low-stake originators. The first is to achieve

lower SEC compliance costs. Apparently, Reg AB imposes higher compliance costs on issuers

of mortgage deals consisting of loans from originators with stakes over 20% in a deal. If

possible, ABS issuers may use loans from low-stake originators to minimize SEC compliance

costs. However, the presence of low-stake originators should have no impact on deal or

loan performance under this motive. The second possible motive is to avoid disclosure of

information on riskier loans which constitute a low-stake in a deal. In pre-Reg AB period, a

deal does not need to limit an originator’s loans to under 20% of the deal to avoid information

disclosure because of no disclosure threshold requirement. After Reg AB, if ABS issuers take

in riskier loans and also avoid scrutiny, it is much more likely to limit these loans to under

the 20% threshold in the deal to avoid scrutiny by investors and regulators. In other words,

if avoiding information disclosure is the main motive, we would expect the performance to

be worse for deals with the increased presence of more low-stake originators, after Reg AB.

Hypothesis 2: All else equal, the increased presence of low-stake originators should be

associated with worse performance of securitized mortgages after Reg AB than before Reg

AB.

3. Data description and summary statistics

Our data comes primarily from two sources: Bloomberg and First American Corelogic Loan-

Performance. We collect information on deal characteristics from Bloomberg which provides

information on mortgage originator(s) and underwriter(s) extracted from deal prospectuses.

6

Our sample consists of privately securitized mortgage deals that were issued between 2003

and 2007, a period immediately preceding the financial crisis. Each deal in our database

has detailed information on deal characteristics at issuance. In the meantime, our loan lev-

el data consists of information on privately securitized mortgages constructed by Corelogic

LoanPerformance. It provides information on loan origination date, the mortgage loan pool,

the identity of the securitizer, the MBS where the loan is placed, and detailed information

on borrower and loan characteristics. We also construct variables from various sources on

regional housing and economic conditions at the time of loan origination.

Bloomberg reports the identities of originators and the percentage of loans that each of

them originates for the deal. Not every deal provides origination information, thus we focus

on a sample of 2,248 deals for which origination information is available for our investigation.

From the detailed origination information, we identify deals that have originators that con-

tributed 10-20% or below 20% of the collateral pool. Considering the disclosure requirements

of Reg AB, we use 10-20 percent as the main measure of a low-stake originator and use below

20 percent as an alternative measure. We also calculate the aggregate percentage of loans

originated by these low-stake originators for each deal. In our sample period, 18% (22% if we

use below 20% as the criterion) of the deals have low-stake originators. The unconditional

mean of the aggregate percentage of low-stake loans for a deal is 4.8% to 5.6%. The highest

aggregate low-stake origination percentage is 100%. In other words, in the extreme case,

a deal could consist of loans entirely from low-stake originators. For deals with originators

contributing 10-20% loans in a deal, the percent of loans from these originators are on aver-

age 25.8%. For deals with originators contributing less than 20% collateral pool, the percent

of loans from these originators are on average 24.5%.

Our deal level performance measure is the cumulative net loss rate measured as the sum

of all losses of principal suffered until December 2010 divided by the total original balance

of all mortgages. We utilize an extensive list of deal characteristics as control variables.

These include deal original collateral balance, an indicator for high reputation following

7

Griffin, Lowery, and Saretto (2014), the number of tranches, average share of loans that

are low or no documentation in the collateral, average FICO score, weighted average loan-

to-value (LTV) ratio, percentage of adjustable rate mortgages in the deal, an indicator for

negative amortization, percentage of purchase loans, percentage of loans for single family

house, percentage of loans for owner-occupied house, and percentage of second lien loans.

Bloomberg provides information on mortgage originator(s) collected from the deal prospec-

tus supplements, but not on individual loans. To assign individual loans to a particular

originator in a deal with multiple originators, we use Corelogic LoanPerformance database

that provides the name of the original lender for each loan, where it can be a direct lender

or a mortgage broker/correspondent. We collect identity and affiliation information for the

original lender of each loan to determine if the original lender is one of the mortgage deal

originators or is affiliated with one of these deal originators. When such a link can be made,

we can assign individual loans to the originators listed in the prospectus supplements. When

the original lenders cannot be linked to any of the originators as is often the case with the

loans acquired by the originators, we set originator information for these loans as missing

and exclude them in our loan level analysis. Definitions for all variables at both deal and

loan levels are described in the Appendix.

Since changes in house prices have an impact on mortgage performance, we include

additional control variables in our analysis. For deal level analysis, we calculate the house

prices change for the representative geographic area using the housing price index for the

corresponding state reported by the Federal Housing Finance Agency (FHFA). Specifically,

we compute weighted-average house price change associated with a deal from the quarter

that the deal was issued to the last quarter of 2010. We also compute pre-deal housing price

appreciation over the four quarters preceding the issuing quarter. For loan level data, we

compute housing price appreciation over the 24 months after origination using the housing

price index for the borrowers metropolitan statistical area (MSA) reported by the Office

of Federal Housing Enterprise Oversight (OFHEO). We also compute the change in the

8

state-level unemployment rate over the 24 months after origination using data reported by

the Bureau of Economic Analysis and collect the median household income in 1999 for

the borrowers zip code as reported by the U.S. Census Bureau in 2000. Additionally, we

include credit spread and 10-year Treasury yield as macro control variables. We begin our

investigation with deal level analysis. Table 1 reports summary statistics for deal level

variables.

Table 1 about here

Table 2 reports the correlation coefficients on the main variables of interest at deal level.

The cumulative net loss is significantly positively correlated with the presence of low-stake

originators and the aggregate percentage of loans originated by low-stake originators in these

deals. The results are very similar for both measures of low-stake originators: percentage

of loans in a deal within 10-20% or percentage of loans in a deal below 20%. Consistent

with our intuition on higher risk associated with worse performance, deal cumulative net

loss is positively correlated with original collateral asset value, the average loan-to-value

ratio, percentage of adjustable rate mortgages, the presence of negative amortization loans,

percentage of purchase loans, and percentage of loans with second lien. It is also negatively

correlated with the average FICO score and the percentage of single family home loans.

Table 2 about here

4. The change in origination structure and its impact

on deal performance

We start our empirical analysis by examining the impact of Reg AB on the use of low-stake

originators. We then focus on investigating the impact of this origination structure change

on the performance of securitized mortgages at the deal level.

9

4.1. The change in origination structure under Reg AB

We define low-stake originators as those who contributed an amount to the total collateral

mortgage pool in an MBS deal that is less than the threshold necessitating mandatory

disclosure by SEC under Reg AB. Specifically, to test our hypothesis on the impact of Reg

AB, we define low-stake originators as those who contributed between 10 and 20 percent

to a mortgage pool. As a robustness check, we also use an alternative low-stake originator

definition as those with less than 20 percent loans in the underlying collateral pool. There

is an empirical issue related to the below 10 percent disclosure, especially in the post 2006

period because according to Reg AB, there is no requirement on the disclosure of identity for

these originators. Therefore, the disclosure of below 10 percent is voluntary and we do not

observe all below 10 percent originators.7 This may lead to a measurement error on whether

a deal has and who are the below 10 percent originators and the total percentage of loans

originated by this type of originators. Consequently, we focus primarily on the low-stake

originators contributed 10-20% of the collateral pool.

To visualize the change in origination structure, we plot the number and percentage

of deals with low-stake originators in our sample period in Figure 1. The top panels of

Figure 1 present the plots for deals with originators contributing 10-20 percent of a collateral

pool before and after Reg AB. Both the number and the percentage of deals with low-stake

originators show similar pattern sourrounding Reg AB. Specifically, the number of deals with

low-stake originators experienced a sharp increase from 121 in the pre-Reg AB regime (before

2006) to 303 in the post-Reg AB regime (after 2006). In percentage terms, the increase is

more than doubled from around 11% before Reg AB to 27% after Reg AB. Moreover, from

the bottom panels of Figure 1, it is clear that the percentage of low-stake deals is relatively

stable in the pre-Reg AB period and the sharp jump occurred right after Reg AB became

effective and remained high.

7Though not directly related, Lee and Mason (2012) show that affiliation matters for the loan-levelselective disclosure of originators.

10

Figure 1 about here

The increase in the use of low-stake originators pre- and post-Reg AB is statistically

significant. In Table 3, we use logistic regressions to evaluate this change by controlling for

other factors that may affect the deal structure. In column (1), the dependent variable is a

dummy variable which takes a value of one if a deal has at least one 10-20 percent originator

and takes a value of zero otherwise. The result shows a very significant increase in probability

(more than tripled) that a deal would involve at least one 10-20 percent originator in the

post Reg AB period (e1.32 = 3.74). We find similar result in column (2) when we use the

alternative dependent variable to capture the presence of at least one low-stake originator

contributing less than 20 percent to the collateral pool.

Table 3 about here

To demonstrate the change in origination structure around the 20% threshold, we examine

the difference in the percentage of mortgage deals with originators contributing loan fractions

just below 20%, say [10,20)%, [15,20)%, and [18,20)%, and the percentage of mortgage deals

with originators contributing loan fractions just above 20%, say [20,30]%, [20,25]%, and

[20,22]%, respectively, before and after Reg AB. Figure 2 shows the difference between the

percentage of mortgage deals in respective brackets. We observe a jump up after Reg AB

in 2006 and remained high for 2007. This pattern is robust for all comparison brackets:

before Reg AB, the difference between the brackets around the 20% threshold is negative

or marginally positive; after Reg AB, this difference becomes positive in all comparison

brackets, indicating increases in deals in the brackets just below 20% than just above 20%.

Considering that the loan pools before Reg AB may be different from that after Reg AB, we

apply a difference-in-difference test to the differentials in the percentages of deals with just

below 20% originators and just above 20% originators. We observe a differential of 6.6% for

[10,20)% versus [20,30]%, 5.8% for [15,20)% versus [20,25]%, and 2.8% for [18,20)% versus

[20,22]%, respectively. Our test results show that the increase in the percentage of deals with

11

just below 20% originators relative to that with just above 20% originators is statistically

significant at 1% test level for all three comparison brackets.

Figure 2 about here

Next, we evaluate the increase in the use of low-stake originators quantitatively, control-

ling for the other factors that may affect the structure as well as the lead underwriter fixed

effect. Table 4 reports the results for OLS (panel A) and ordered logit (panel B) regression

analysis. Clearly, there is a significant increase in the fraction of mortgage deals that involves

originators changing from contributing just above the threshold 20% of the total collateral

pool to just below the threshold after Reg AB. Our OLS estimation shows that controlling

for deal characteristics, issuer reputation, and macroeconomic variables, the fraction of deals

with originator contributions from just above the threshold of 20% to just below the thresh-

old increased by 15% from [20,30]% to [10,20)%, 8% from [20,25]% to [15,20)%, and 3%

from [20,22]% to [18,20)%, respectively, from before Reg AB to after Reg AB. Given that

the average fractions of deals with low-stake originators in [10,20)%, [15,20)%, and [18,20)%

brackets are 11%, 5.7%, and 2.1%, respectively, before Reg AB, our estimates show that the

percentage of deals with low-stake originators just below the threshold increased by 136% for

[10,20)%, 140% for [15,20)%, and 142% for [18,20)%, respectively, under Reg AB. Qualita-

tively similar results are also observed using ordered logit regression analysis. For instance,

the log-odds ratio of mortgage deals with originators reducing their contributions from just

above the threshold to just below the threshold is higher by 92% for [20,30]% to [10,20)%,

65% for [20,25]% to [15,20)%, and 54% for [22,22]% to [18,20)%, respectively, after Reg AB.

Table 4 about here

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4.2. The impact of origination structure change on deal perfor-

mance

Now that we have documented a significant increase in the low-stake originators just below

the 20% threshold in MBS deals after Reg AB, we seek to understand whether this origination

structure change has any impact on mortgage performance. Due to lack of regulation specific

to MBS disclosure in pre-2006 period, if MBS issuers engage in riskier loans and attempt to

avoid disclosing adverse information, they did not have to limit riskier loans from a particular

originator to the 20% threshold. After Reg AB, due to the required information disclosure

regulation on originators with 20% or more loans in a deal, if MBS issuers take in riskier loans

and attempt to avoid disclosure on the originators of these riskier loans, they are much more

likely to strategically use the statutory 20% threshold to achieve the objective. Therefore,

for deals issued after Reg AB, we would expect deals with increases in low-stake originators

to have worse performance if the low-stake position is used strategically to avoid adverse

information disclosure about the origination process and loan quality. On the other hand,

we would expect the presence of low-stake originators to have no impact on deal performance

if it were primarily driven by the motive of reducing SEC compliance costs.

To test our hypothesis, we regress deal cumulative net loss on variables that capture

the presence of low-stake originators and their interactions with a post Reg AB dummy

variable. The inclusion of the interaction term allows us to assess if the change in low-stake

originators in mortgage deals has an incremental effect post-Reg AB than pre-Reg AB. We

use two measures for the presence of low-stake originators in our regression analysis: (1) a

dummy variable representing the presence of at least one low-stake originator in a mortgage

deal; and (2) a continuous variable that captures the aggregate percentage of loans originated

by the low-stake originators in a deal. We do so for low-stake originators contributing 10-20

percent of a collateral pool and for low-stake originators contributing less than 20 percent

collateral pool, respectively.

13

The results are reported in Table 5. Columns (1) to (4) present the findings for the

low-stake originators contributing 10-20 percent of a collateral pool. It is quite clear that

prior to Reg AB, the disclosure threshold does not have any significant impact on deal

performance. However, after Reg AB, deals with low-stake originators have significantly

worse performance. Specifically, the estimate in column (2) indicates that the presence of

at least one 10-20 percent low-stake originator corresponds to 1.83 percentage points higher

deal cumulative net loss. This represents 27% of the average cumulative net loss in our

full sample period (1.83/6.74). When using the aggregate percentage of loans originated by

10-20 percent originators as the measure of low-stake originator involvement, our estimate

shows that a one standard deviation increase in this aggregate percentage of low-stake loans

leads to a 0.8% increase in the cumulative net loss which represents 12% average cumulative

net loss for our full sample (0.8/6.74). Our results are robust if we define the low-stake

originators using less than 20 percent collateral pool contribution in a deal (see columns (5)

to (8)).

Table 5 about here

To provide further evidence that the effect on mortgage deal cumulative net loss associat-

ed with the presence of low-stake originators pre- and post-Reg AB is due to the regulatory

disclosure threshold, we conduct regression analysis including both the presence of origina-

tors contributing 10-20% collateral pool and originators contributing 20-30% collateral pool,

a bracket just above the threshold. Table 6 reports the results of our analysis. For both

measures of the low-stake originators (the dummy variable representing the presence and

the continuous variable representing the percentage of collateral loan pool), we find that

originators contributing 20-30% collateral pool had no significant effect on deal cumulative

net loss. On the other hand, low-stake originators contributing 10-20% collateral pool are

associated with significantly larger deal cumulative net loss. More important, the larger

deal cumulative net loss is concentrated in deals with the presence of low-stake originators

contributing 10-20% post-Reg AB. This finding highlights the effect on deal performance of

14

loan originators who contributed 10-20% collateral pool post-Reg AB, an amount just below

the disclosure threshold.

Table 6 about here

4.3. Deal performance and strategic use of the threshold

Next, we investigate the impact of the strategic use of the 20 percent threshold on mortgage

deal performance. For this analysis, we introduce a dummy variable “Strategic Originator

10-20% orig. increase” to represent the increase in the number of 10-20% originators in each

deal pre- and post-Reg AB. Specifically, for each originator, we compute the change in the

percentage of deals for which the originator contributed a low stake (10-20%) in a collateral

pool before and after Reg AB. For each deal, we define the dummy variable which takes a

value of one if there are originators experienced an increase in the number of deals for which

these originators contributed a low-stake in a collateral pool pre- and post-Reg AB, and takes

a value of zero otherwise. Similarly, we define a dummy variable “Strategic Originator below

20% orig. increase.” As an alternative, we also use “Strategic Originator (High 10-20% orig.

increase)” to represent a dummy variable which takes a value of one if there are originators

experienced larger than the average increase in low-stake originators and takes a value of

zero otherwise. Similarly, we define a dummy variable “Strategic Originator (High below

20% orig. increase).” For our sample of 149 originators, the average increase in low-stake

originators is 2.0% for the 10-20% loan contribution group and 6.4% for below 20% loan

contribution group post Reg AB.

Table 7 reports the results of our analysis. Our estimate shows that deals with increased

strategic originators in 10-20% origination contribution group are associated with 0.7% higher

cumulative net loss than deals with no strategic originators (column (1)). Similar result is

found when we use the dummy variable “Strategic Originator below 20% orig. increase”

(column (2)). When using the alternative measure “Strategic Originator (High 10-20% orig.

increase),” we find that deals with more than average increase in strategic originators in

15

10-20% origination fraction group are associated with 1.1% higher cumulative net loss than

other deals (column (3)). Similar effect is found for “Strategic Originator (High below 20%

orig. increase)” (column (4)). Consistent with our intuition, we observe a larger impact

on the cumulative net loss on deals with originators shown larger than average increase in

low-stake originators.

Table 7 about here

4.4. The impact of origination structure change on deal yields and

credit enhancement

One question is whether the higher cumulative net loss of mortgage deals that experienced

increases in low-stake originators is reflected in deal initial yield spreads and credit enhance-

ment. This is relevant for assessing the cost to investors of the disclosure threshold under

Reg AB. For credit enhancement, we focus on subordination which is measured as the per-

centage of the face value of trust securities not rated AAA by Moodys or Standard & Poors

at deal close. For deal yields, we use the initial average yield spread of all securities issued

by the trust of mortgage deals. This is the difference between the average yield of all secu-

rities issued by the trust weighted by the face value of the securities and the yield on the

10-year Treasury bond. The former is calculated using the standards of the Bond Market

Association and reported by Bloomberg.

Table 8 reports the results of our regression analysis. Panel A shows that the presence of

low-stake originators has no effect on deal yield spread. The deal structure change associated

with the 20% threshold under Reg AB does not change the result. This is true for both

low-stake originators contributing 10-20% collateral pool (column (1)) and contributing less

than 20%collateral pool (column (2)). However, the presence of low-stake originators has a

significant impact on credit enhancement measured by mortgage deal subordination. Under

both measures of low-stake originators, their presence is associated with a higher average

16

subordination before Reg AB and a lower suboridination post Reg AB (columns (3) and

(4)). This shows a sharp contrast on the impact of the presence of low-stake originators

on subordination with respect to Reg AB. Combining the findings on deal yield spreads

and subordination, we have evidence suggesting that investors may have not impounded the

increase in low-stake originator risk due to the 20% disclosure threshold under Reg AB in

yields and credit enhancement.

Table 8 about here

Panel B reports results of analysis on whether the strategic use of the 20% threshold

under Reg AB is reflected in deal yields and credit enhancement. For both measures of the

strategic use of the threshold under Reg AB, we find no evidence that the increase in the

strategic use of the threshold in deals with larger than average increase in the number of

deals with low-stake originators contributing 10-20% or below 20% collateral pool is reflected

in deal yield spreads or subordination.

Overall, our results on Reg AB have two very important implications. First, the 20%

disclosure threshold was used strategically after Reg AB. Second, this strategic use is likely

driven by avoiding scrutiny and potentially withholding some adverse information on riskier

loans. The policy implication is that although alleviating certain compliance costs may be

beneficial for certain ABS issuers, a cost (of larger magnitude) may be transferred to the

investors. Therefore, it may be beneficial to further tighten the regulation of ABS market

by not leaving so much room for certain non-disclosures.

5. The change in origination structure and its impact

on loan performance

We now turn to investigating the impact of origination structure change on mortgage perfor-

mance at loan level. We first directly compare the loans originated by the strategic originators

17

with those originated by others and then examine how the performance difference is related

to strategic originators increasing their number of mortgage deals with 10-20% stakes.

We recognize that loans from originators with different stakes in a deal may have different

quality. To control for this, we introduce the variable loan origination percentage (“Origpct”)

as follows. For each loan i in mortgage deal j, we compute the percentage of loans in deal j

originated by the same originator that originated loan i and assign this percentage to all loans

originated by the same originator in deal j. Following the definition of a strategic originator in

Table 7, we compute the change in the percentage of deals for which an originator contributed

10-20% collateral pool before and post Reg AB (“Origchg”).

Using loan origination percentage we can further divide loans by their originators’ stake

size when these loans were placed in mortgage deals. Merging the deal level originator

information with loan level data and excluding missing observations, we have more than

three and a half million loans in 1,603 deals. The average loan origination percentage is

86%, suggesting that majority loans were originated by originators with stake size larger

than the threshold. In the meantime, three percent of all loans belong to the 10-20% stake

group. The average of the variable “Origchg” is 4.1% with a standard deviation 11.3% for

all loans, slightly different from those at deal level. Following the standard practice, we use

securitized loan delinquency, defined as 60 days or more past due within 24 months of loan

origination, as loan performance measure in our loan level analysis.

In Table 9, we report the summary statistics for the loan level variables for the whole

sample and subsamples of loans from 10-20% and 20-30% stake groups, respectively. We

use loans from 20-30% stake group for comparison due to their vicinity in stake size. We

observe that the sample averages for these variables are close between the whole sample and

subsamples, and even closer between the two subsamples.

Table 9 about here

We take two steps in our loan level analysis. In the first step, we examine whether

strategic originators have worse performing loans than others. Since the strategic originators

18

are more likely to increase the 10-20% stake deals after Reg AB, we expect that loans from

the originators with larger increases in 10-20% stake deals are riskier than loans by other

originators. This suggests that loan delinquency will increase in the variable “Origchg.”

In the second step, we investigate whether loans in the 10-20% stake deals by strategic

originators are worse than loans by other originators. We use loans in the 20-30% stake

deals as a control group because of their close proximity to the 10-20% stake deals. If MBS

issuers strategically place riskier loans in the 10-20% deals, we expect the variable “Origchg”

has a larger positive effect on delinquency for loans in the 10-20% deals than those in the

20-30% deals. We conduct this analysis separately for pre and post Reg AB subsamples of

loans because we expect the strategic use of the 10-20% deals occurs post Reg AB but not

before Reg AB.

Table 10 reports the marginal effects from probit regression for the whole sample with

Origpct (column (1)), the whole sample with both Origpct and Origchg (column (2)), the

subsample of loans with the stake size 10-20% (column (3)), and the subsample of loans with

the stake size 20-30% (column (4)). Our estimation shows that for the full sample the loans

from larger stake sizes have lower delinquency. This finding makes it necessary to control

for the stake size in our subsequent analysis. As expected, for the strategic originators the

variable “Origchg” is positively assoicated with delinquency, controlling for the stake size

and various loan level controls. The economic magnitude is significant in that loans from

an originator who increased the fraction of low-stake deals by 10% are 0.5% more likely to

be delinquent. For the subsample of loans from 10-20% stake deals we observe the same

effect for “Origchg” that the low-stake loans from strategic originators are worse than the

low-stake loans from other originators. On the other hand, we find the difference for loans

from 20-30% stake deals between strategic originators and others has the opposite sign, a

striking contrast around the 20% threshhold.

Table 10 about here

Next we explicitly test whether the strategic originators utilize 10-20% stake deals dif-

19

ferently from their closest 20-30% stake deals post-Reg AB versus pre-Reg AB. Table 11

presents the results of a probit regression on loans from 10-30% stake size for the pre-Reg

AB subsample (2003-2005) and the post-Reg AB subsample (2006-2007). Our estimation for

the pre-Reg AB subsample loans shows that the variable “Origchg” is positively associated

with loan delinquency, yet statistically insignificant for the pre-Reg AB period. However,

the effect on the loans from the 10-20% stake deals is actually weaker than on those from 20-

30% stake deals. This suggests no strategic use of the 10-20% stakes pre-Reg AB, a finding

support our intuition.

In contrast, our estimation for the post-Reg AB subsample shows that the effect of

“Origchg” is much stronger for loans from 10-20% stake deals than those from 20-30% stake

deals. This indicates that the strategic use of low stakes concentrates in the 10-20% deals.

We note that “Origchg” is negatively associated with delinquency for loans from 20-30%

stakes. This is consistent with the explanation that the strategic originators shift riskier

loans into the 10-20% stakes from 20-30% stakes. The sharp contrast in loan delinquency

rate pre- and post-Reg AB illustrates the strategic originator’s use of 10-20% stakes for

riskier loans. This lends support to our finding on the impact of strategic originators on the

deal cumulative net loss documented above.

Table 11 about here

6. Conclusion

How to design and implement effective regulation has received widespread attention following

the 2007-2008 subprime mortgage crisis. Very little is known about the impact on the non-

agency MBS market of the regulation on ABS, Reg AB, implemented during the height

of the housing boom right before the crisis. Even less is known about the effects of these

regulations on the market participants and resulting economic impact. In this paper we fill

in the void on these issues.

20

One of the most important aspects of Reg AB is the disclosure requirement on the part

of the mortgage originators. Specifically those originators who contribute more than 20%

of the loans in the collateral pool are required to provide detailed financial information

material to the investor analysis of the collateral assets. The purpose of this requirement

is to encourage transparency and therefore accountability. Using the mortgage deals before

and after Reg AB, we find that certain originators circumvent this requirement by staying

below the 20% threshold. Furthermore, it is exactly these originators that contributed to

the worse performance of the MBS deals. Our loan level analysis provides support evidence

on the findings of deal analysis. This suggests that the beneficial effect of the 20% disclosure

threshold requirement has been somewhat mitigated and its effectiveness curtailed.

Overall, our study on how these regulations change the market participants behavior and

the ensuing economic impact can shed light on future research and policy-making regarding

the asset-backed securities markets. There are other aspects of these regulations that could

potentially change these markets and we leave those topics for future research.

21

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Keys, Benjamin J., Tanmoy Mukherjee, Amit Seru, and Vikrant Vig, 2010, Did securitization

lead to lax screening? evidence from subprime loans, The Quarterly Journal of Economics

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securitization: Evidence from prime and subprime mortgage markets, Review of Financial

Studies 25, 2071–2108.

Kothari, S. P., Susan Shu, and Peter D. Wysocki, 2009, Do managers withhold bad news?,

Journal of Accounting Research 47, 241–276.

Lee, Hong, and Joseph R Mason, 2012, Selective disclosure of originators in mortgage secu-

ritizations, Working Paper.

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from the U.S. mortgage default crisis, The Quarterly Journal of Economics 124, 1449–

1496.

Nadauld, Taylor D, and Shane M Sherlund, 2009, The role of the securitization process in

the expansion of subprime credit (Divisions of Research & Statistics and Monetary Affairs,

Federal Reserve Board).

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crisis, Review of Financial Studies 24, 1881–1915.

22

Skinner, Douglas J, 1994, Why firms voluntarily disclose bad news, Journal of accounting

research pp. 38–60.

Skinner, Douglas J., 1997, Earnings disclosures and stockholder lawsuits, Journal of Ac-

counting and Economics 23, 249–282.

23

Appendix: Variable definitionsDeal and macro variables:

• Cumulative net loss: Historical percentages of cumulative loss on the underlying loans comprising the

entire collateral that backs the deal

• Has originator 10-20% (d): Equals 1 if a deal has (an) originator(s) originate(s) percentage of loans

between 10

• Has originators < 20% (d): Equals 1 if a deal has (an) originator(s) originate(s) loans below 20%; 0

otherwise

• Total percentage of origination 10-20%: Total percentage of originations that are between 10% and

20%

• Total percentage of origination below 20%: Total percentage of originations that are below 20%

• Original collateral balance (in Billions): The original balance of the underlying loans comprising the

entire collateral

• High reputation: Equals 1 if the deal has an underwriter IPO reputation score greater than or equal

to 8 (from Professor Jay Ritter’s website); 0 otherwise

• No. of tranches: Number of securities in a deal

• Low documentation: Dummy variable indicating underlying loans with limited, as distinguished from

full, documentation

• FICO: Weighted average original credit score of the underlying loans

• LTV: Original loan to value percentage of the loan

• Adjustable rate mortgage: The percentage of the adjustable rate mortgage loans

• Negative amortization: Equals 1 if the deal consists of mortgages with negative amortization features;

0 otherwise

• Purchase loans: The percentage of the Loan Purpose (the reason for the loan) for Purchase

• Single family: The percentage of Single Family Mortgaged Properties, the type of properties against

which the loans were written

• Owner occupied: The percentage of the Occupancy (the purpose of the property) for Owner Occupied

• Second lien: The percentage of the loans comprising the collateral that are second lien

• House prices change: We compute the average house price changes from issue quarter to the last

quarter of 2010 using the state level Federal Housing Finance Agency’s (FHFA) seasonally adjusted

quarterly house price index. The weighted average for each deal is taken over the top five states by

their mortgage balances assuming the remaining 45 states have equal representation

• House prices run-up: We use the same data and method as in “House prices change to calculate the

weighted average price change associated with a deal during the four quarters preceding the quarter

the deal was closed

• Credit spread: The spread between BBA and AAA corporate bond yields in issue month

24

• 10 Year Treasury: 10 year treasure yield in issuing month

Loan level variables:

• Delinquency: Equals 1 if the loan payment is 60-day past due within the 24 months of origination

and 0 otherwise

• FICO: Fair, Isaac and Company (FICO) credit score at origination standardized with sample mean

and variance

• Full DOc: Dummy variable equal to one if the borrower has complete documentation on income and

assets

• CLTV: Combined loan to value ratio for the first lien loan at origination. The ratio includes a second

lien when it exists. The LTV ratio is in decimal (e.g., a 20% down payment = 0.80 LTV ratio).

• Investor: Dummy variable equal to one if the borrower does not owner-occupy the property

• DTI: Back-end debt-to-income ratio, defined as the total monthly mortgage payment to monthly

gross income at origination, in percent. The back-end DTI differs from the front-end DTI in that

the back-end DTI includes mortgage insurance, homeowners insurance, property tax, and any other

continuing home ownership expenses

• Miss DTI: Dummy variable equal to one if DTI is missing. Demyanyk and Van Hemert (2011) interpret

a Miss DTI as a negative signal about borrower quality

• Cash-Out: Dummy variable equal to one if the purpose of the loan is for a cash-out refinance where

the balance of the loan is increased to raise cash. As noted by Pennington-Cross and Chomsisengphet

(2007), the most common reasons for a cash-out refinance are to consolidate debt and to improve

property

• PrePayPen: Dummy variable equal to one when the loan has a prepayment penalty and/or is an

option ARM or negative amortization loan. These loan features make refinancing less likely in default

• Initial Rate: The initial mortgage interest rate, in percent

• Margin: Margin (in percent) for an adjustable-rate or hybrid loan over an interest rate index, appli-

cable after the first interest rate reset. For example, a 2/28 hybrid adjustable-rate loan has a low

(teaser) fixed rate for the first two years, followed by a variable rate based on 6-month LIBOR plus

a Margin that is fixed for the life of the loan

• Rate Reset: Time period (in months) before the interest rate in an adjustable-rate loan starts to

adjust. Hybrid adjustable rate loans have initial fixed interest rates of 24 or 36 months, while pure

adjustable rate loans have shorter first interest rate reset periods

• Loan Amt.: Size of the loan at origination, in dollars

• ARM: Dummy variable equal to one if the loan is an adjustable rate mortgage and the first interest

rate reset period is less than or equal to one year from the date of origination

• Balloon: Dummy variable equal to one for a fixed rate or adjustable rate loan where the payments

are lower over the life of the loan leaving a Balloon payment at maturity. For example, a fixed rate

mortgage that amortizes over 40 years, but matures in 30 years, leaving a Balloon payment after 30

years

25

• Hybrid2: Dummy variable equal to one for an adjustable rate loan with the initial monthly payment

fixed for the first two years. This is typically referred to as a 2/28 hybrid ARM, with the interest

rate over the remaining 28 years of the loan equal to the value of an interest rate index (i.e., 6-month

LIBOR) measured at the time of adjustment, plus a Margin that is fixed for the life of the loan. The

initial fixed rate is called a “teaser” interest rate because it is lower than what a borrower would pay

for a 30-year fixed rate mortgage

• Hybrid3: Dummy variable equal to one for a 3/27 hybrid ARM (i.e., the initial interest rate is fixed

for 3 years)

• Int. Only: Dummy variable equal to one if the loan has an interest only feature. For example, a

30-year fixed rate or adjustable rate loan may permit the borrower to only pay interest for the first

sixty months of the loan, but then must make payments in order to repay the loan in the final 25

years

• Local Income: Zip Code level median income in 1999 from the U.S. Census Bureau 2000

• Unemployment: State-level change in the unemployment rate from loan origination to 24 months

thereafter, reported by the Bureau of Economic Analysis

• Price Appr.: MSA-level house price index appreciation (in decimal) from loan origination to 24 months

thereafter, reported by the office of Federal Housing Enterprise Oversight (OFHEO)

26

Table 1: Summary statisticsThis table presents the summary statistics on the variables defined in the Appendix. The

statistics reported include Mean, St. Dev. (standard deviation), the kth percentile (Pk for

k = 5, 25, 50, 75, 95) of each variable. We use (d) to denote that the variable is a dummy

variable. We also use (%) if the variable is in percentage term.

Variable Mean St. Dev. P5 P25 P50 P75 P95

Cumulative net loss 6.74 7.79 0.02 0.74 3.33 10.58 23.13Has originators 10-20%(d) 0.18 0.38 0 0 0 0 1Has originators < 20%(d) 0.22 0.42 0 0 0 0 1Total % of orig. 10%-20% 4.77 12.92 0 0 0 0 30.62Total % of orig. <20% 5.64 14.11 0 0 0 0 34.16Original Face 0.8 0.52 0.23 0.42 0.68 1.01 1.8High reputation (d) 0.78 0.42 0 1 1 1 1No. of tranche 21.14 11.24 10 15 18 24 43Low Documentation (d) 0.57 0.49 0 0 1 1 1FICO 698.41 46.14 611 672.5 715 735 746LTV 73.17 5.66 63 70 74 76 81Adjustable rate mortgage (%) 58.1 40.25 0 0 59.07 100 100Negative amortization (d) 0.07 0.25 0 0 0 0 1Purchase loans (%) 43.76 14.4 18.19 36.12 43.18 53.21 67.7Single family (%) 68.39 11.23 54.63 62.42 68.46 73.39 88.97Owner occupied (%) 87.45 9.11 70.64 85.1 87.58 93.62 97.3Second lien (%) 0.5 1.66 0 0 0 0 3.94House prices change -23.34 10.78 -38.07 -30.67 -25.6 -17.17 -1.85House prices run-up 7.68 5.18 -1.98 3.24 9.14 11.6 14.02Credit spread 0.89 0.12 0.68 0.82 0.9 0.94 1.1310 Year Treasury 4.47 0.36 3.9 4.2 4.5 4.72 5.1

27

Table

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28

Table 3: Determinants of origination structureThis table presents the results of analyzing the determinants of origination structure. All the

variables are defined in the Appendix. Has originators 10-20% (d) and Has originators <20%

(d) are regressed on other explanatory variables using logit regressions. The t-statistics based on

standard errors clustered by issue semester are reported in the parentheses below each coefficient

estimate. Statistical significance levels of 1%, 5%, and 10% are indicated with ***, **, and *

respectively.

Has originators 10-20%(d) Has originators < 20%(d)

Post Reg AB 1.32*** 1.20***(5.99) (4.16)

Original collateral balance -0.49** -0.41**(-2.28) (-2.18)

High reputation (d) -0.29 -0.09(-0.82) (-0.29)

No. of tranches -0.00 0.00(-0.03) (0.43)

Low documentation (d) -0.52*** -0.48***(-4.70) (-3.62)

FICO -0.00 -0.00(-1.20) (-0.78)

LTV -0.01 -0.00(-0.40) (-0.32)

Adjustable rate mortgage (%) -0.00 -0.00(-1.51) (-0.86)

Negative amortization (d) -0.86*** -0.98***(-3.18) (-4.09)

Purchase loans (%) -0.00 -0.01(-0.47) (-1.31)

Single family (%) -0.01** -0.02***(-2.41) (-3.33)

Owner occupied (%) -0.02*** -0.02***(-2.67) (-3.19)

Second lien (%) -0.09*** -0.09***(-2.88) (-3.10)

House prices run-up 0.03** -0.00(2.28) (-0.28)

Credit spread 0.91* 0.06(1.89) (0.12)

10 Year Treasury 0.06 -0.05(0.23) (-0.16)

Lead-underwriter FE Yes YesPseudo R2 0.128 0.130Observations 2248 2248

29

Table 4: Difference in origination structure in brackets below and above 20%This table presents the results of analyzing the difference between percentage of deals with

originators in the bracket right below 20% and percentage of deals with originators in the

bracket right above 20%. For each deal, we create a dummy variable to represent the existence

of originators in a bracket right below 20% and another dummy variable presenting the existence

of originators in a bracket right above 20%. The difference between these two dummy variables is

denoted as diffA20B where [A,20) is the bracket right below 20% and [20,B) is the bracket right

above 20%. The combinations of {A,B} in our analysis include {10,30}, {15,25}, and {18,22}.Panel A reports the results of regressing this difference on Post Reg AB dummy variable and

other control variables using OLS regressions. Panel B reports the corresponding results using

ordered logistic regressions. The control variables are the same as in Table 3. The t-statistics

based on standard errors clustered by issue semester are reported in the parentheses below each

coefficient estimate. Statistical significance levels of 1%, 5%, and 10% are indicated with ***,

**, and * respectively.

Panel A: OLS regressions

diff102030 diff102030 diff152025 diff152025 diff182022 diff182022(1) (2) (3) (4) (5) (6)

Post Reg AB 0.08*** 0.15*** 0.05*** 0.08*** 0.03*** 0.03**(4.55) (5.02) (4.69) (4.01) (4.06) (2.98)

Control variables No Yes No Yes No YesLead-underwriter FE Yes Yes Yes Yes Yes YesAdjusted R2 0.012 0.018 0.007 0.008 0.007 0.007Observations 2248 2248 2248 2248 2248 2248

Panel B: Ordered logit regressions

diff102030 diff102030 diff152025 diff152025 diff182022 diff182022(1) (2) (3) (4) (5) (6)

Post Reg AB 0.48*** 0.92*** 0.47*** 0.65*** 0.47*** 0.54***(3.73) (5.18) (4.03) (3.32) (4.46) (3.25)

Control variables No Yes No Yes No YesLead-underwriter FE Yes Yes Yes Yes Yes YesPseudo R2 0.0209 0.0315 0.0191 0.0279 0.0271 0.0386Observations 2248 2248 2248 2248 2248 2248

30

Table

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(2)

(3)

(4)

(5)

(6)

(7)

(8)

Has

orig

inat

ors

10-2

0%(d

)0.9

5**

-0.2

6(2

.87)

(-0.6

4)

Pos

tR

egA

B×

Has

orig

inat

ors

10-2

0%

(d)

1.8

3**

(2.7

7)

Tot

al%

ofor

igin

ator

sor

ig.

10-2

0%0.0

2*

-0.0

1(2

.17)

(-0.7

9)

Pos

tR

egA

B×

Tot

al%

ofor

igin

ator

sori

g.

10-2

0%

0.0

6***

(3.6

6)

Has

orig

inat

ors<

20%

(d)

0.8

6**

-0.2

6(2

.86)

(-0.8

6)

Pos

tR

egA

B×

Has

orig

inat

ors<

20%

(d)

1.7

6***

(3.5

1)

Tot

al%

ofor

igin

ator

sor

ig.<

20%

0.0

2*

-0.0

1(2

.02)

(-0.8

3)

Pos

tR

egA

B×

Tot

al%

ofor

igin

ator

sori

g.<

20%

0.0

6***

(3.8

2)

Dea

lch

arac

teri

stic

sco

ntr

olY

esY

esY

esY

esY

esY

esY

esY

esL

ead

-un

der

wri

ter

and

issu

ese

mes

ter

FE

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Ad

just

edR

20.7

39

0.7

41

0.7

39

0.7

41

0.7

39

0.7

41

0.7

39

0.7

41

Ob

serv

atio

ns

2,0

91

2,0

91

2,0

91

2,0

91

2,0

91

2,0

91

2,0

91

2,0

91

31

Table 6: Origination brackets [10,20), [20,30), and cumulative net lossThis table reports the results of analyzing the impact of [20,30) originators on deal performance,

compared to the impact of [10,20) originators. All the variables are defined in the Appendix. The

t-statistics based on standard errors clustered by issue semester are reported in the parentheses

below each coefficient estimate. Statistical significance levels of 1%, 5%, and 10% are indicated

with ***, **, and * respectively.

(1) (2) (3) (4)

Has originators 10-20%(d) 0.90** -0.16(2.99) (-0.43)

Post Reg AB × Has originators 10-20% 1.57**(2.70)

Has originators 20-30%(d) 0.19 -0.44(0.53) (-1.37)

Post Reg AB × Has originators 20-30% 1.02(1.55)

Total % of originators orig. 10-20% 0.02* -0.01(2.24) (-0.79)

Post Reg AB × Total % of originators orig. 10-20% 0.06***(3.57)

Total % of originators orig. 20-30% 0.00 -0.01(0.51) (-1.12)

Post Reg AB × Total % of originators orig. 20-30% 0.03(1.82)

Control variables Yes Yes Yes YesLead-underwriter and issue semester FE Yes Yes Yes YesAdjusted R2 0.739 0.741 0.739 0.742Observations 2091 2091 2091 2091

32

Table 7: Origination structure and cumulative net loss, cross-sectional analysisWe identify originators who increase the use of low-stake (10-20% or below 20%) loans from pre-

Reg AB to post-Reg AB and analyze these originators’ deal performance compared to others.

For each deal, we define the dummy variable Strategic Originator (10-20% orig. increase) which

takes a value of one if there are originators experienced an increase in the number of deals for

which these originators contributed a low-stake (10-20%) in a collateral pool pre- and post-Reg

AB, and takes a value of zero otherwise. We also define a dummy variable Strategic Originator

(High 10-20% orig. increase) if an originator’s increasing use of low-stake loans is above the

average increase of all originators. Similarly defined dummy variables are based on below 20%

threshold. All the other variables are defined in the Appendix. The t-statistics based on standard

errors clustered by issue semester are reported in the parentheses below each coefficient estimate.

Statistical significance levels of 1%, 5%, and 10% are indicated with ***, **, and * respectively.

(1) (2) (3) (4)Strategic Originator (10-20% orig. increase) (d) 0.67**

(2.77)Strategic Originator (below 20% orig. increase) (d) 0.55*

(2.11)Strategic Originator (High 10-20% orig. increase) (d) 1.05***

(3.80)Strategic Originator (High below 20% orig. increase) (d) 0.86***

(4.01)Control variables Yes Yes Yes YesLead-underwriter and issue semester FE Yes Yes Yes YesAdjusted R2 0.736 0.736 0.738 0.737Observations 2028 2028 2028 2028

33

Table 8: Origination structure change, yields and credit enhancementThis table reports the results of analyzing the impact of low-stake originators on deal initial

yields and credit enhancement. For deal yields, we use the initial average yield spread of all

securities issued by the trust of mortgage deals. This is the difference between the average yield

of all securities issued by the trust weighted by the face value of the securities and the yield

on the 10-year Treasury bond. For credit enhancement, we focus on subordination which is

measured as the percentage of the face value of trust securities not rated AAA by Moody’s or

Standard & Poors at deal close. The Strategic Originator variables are defined in Table 7. All the

other variables are defined in the Appendix. The t-statistics based on standard errors clustered

by issue semester are reported in the parentheses below each coefficient estimate. Statistical

significance levels of 1%, 5%, and 10% are indicated with ***, **, and * respectively.

Panel A: Origination structure change, initial yield and subordination

Initial yield Subordination(1) (2) (3) (4)

Has originators 10-20%(d) 0.09 1.22***(0.70) (4.36)

Post Reg AB × Has originators 10-20% 0.03 -1.63***(0.19) (-4.00)

Has originators < 20%(d) -0.01 1.03***(-0.07) (4.11)

Post Reg AB × Has originators < 20% 0.1 -1.45***(0.76) (-4.09)

Control variables Yes Yes Yes YesLead-underwriter and issue semester FE Yes Yes Yes YesAdjusted R2 0.615 0.614 0.821 0.821Observations 2,248 2,248 2,153 2,153

Panel B: Strategic use of origination structure, initial yield and subordination

Initial yield Subordination(1) (2) (3) (4)

Strategic Originator (High 10-20% orig. increase) (d) 0.05 -0.63(1.02) (-1.81)

Strategic Originator (High below 20% orig. increase) (d) 0.03 -0.31(0.64) (-0.99)

Control variables Yes Yes Yes YesLead-underwriter and issue semester FE Yes Yes Yes YesAdjusted R2 0.615 0.615 0.834 0.833Observations 2,157 2,157 2,063 2,063

34

Table 9: Summary statistics for loansThis table reports the mean values for the loan-level variables. We report these numbers for all

loans for which we can identify the originators at the deal level, as well as for the loans whose

originators contributed loans to deals in the brackets of [10,20)% and [20,30)%.

Originator’s share in a dealVariables All loans [10,20)% [20,30)%Delinquency 0.23 0.25 0.23FICO 638 654 645Full Doc 0.59 0.50 0.52CLTV 81.70 82.20 81.40Investor 0.08 0.10 0.10DTI 39.21 38.48 38.55Miss DTI 0.18 0.15 0.15Cash-Out 0.12 0.13 0.12PrePayPen 0.64 0.58 0.62Initial Rate 7.10 7.05 6.93Margin 5.19 4.70 4.97Rate Reset 27.77 34.36 33.83Loan Amt. 232,299 257,756 248,703ARM 0.07 0.06 0.07Balloon 0.08 0.07 0.03Hybrid2 0.45 0.35 0.39Hybrid3 0.15 0.29 0.27Int. Only 0.17 0.30 0.22Local Income 47,772 48,485 48,252Unemployment 0.10 0.26 0.16Price Appr. 0.09 0.08 0.09

35

Table 10: Impact of origination structure on individual loansThis table reports the results of analyzing the impact of low-stake originators on individual loan

performance. We regress the loan Delinquency status on origination change variable and other

loan-level variables using probit regressions. Origchg is defined as the change from pre-Reg AB

to post-Reg AB in the fraction of 10-20% deals for each originator (same for all loans from the

same originator). For each deal, Origpct is defined as the share of the originator (same for all

loans in the same deal and from the same originator). All the other variables are defined in

the Appendix. The standard errors clustered by issue semester are reported in the parentheses

below each coefficient estimate. Statistical significance levels of 1%, 5%, and 10% are indicated

with ***, **, and * respectively.

All loans All loans [10,20)% loans [20,30)% loans

Origchg .05429*** .04644** -.02211(.01557) (.01915) (.02667)

Origpct -.00034*** -.00031*** -.00045 .00038(4.9e-05) (5.0e-05) (.00147) (.00153)

FICO -.09315*** -.09324*** -.10421*** -.10203***(.00201) (.00198) (.0045) (.00413)

Full Doc -.05918*** -.05916*** -.0651*** -.06162***(.00171) (.0017) (.00658) (.0048)

CLTV .06071*** .0607*** .07354*** .06615***(.00355) (.00354) (.00456) (.00497)

Investor .05032*** .05022*** .03664*** .05519***(.004) (.00393) (.00985) (.00852)

DTI .02001*** .02033*** .0214*** .02064***(.00122) (.00119) (.00418) (.0042)

Miss DTI .03301*** .03305*** .05612*** .07221***(.00518) (.0051) (.0149) (.01807)

Cash-Out .00071 .00046 -.00769* .00215(.00183) (.00181) (.00461) (.00554)

PrePayPen .04821*** .04807*** .06099*** .0532***(.00186) (.00185) (.00449) (.00488)

Initial Rate .03285*** .03282*** .03*** .02516***(.00251) (.00249) (.00718) (.00686)

Margin .02643*** .02598*** .03086*** .02003***(.00233) (.00225) (.00618) (.00664)

Rate Reset -.01603*** -.01562*** -.00569 -.01676***(.00242) (.00238) (.00555) (.00476)

Loan Amt. .01711*** .01744*** .01999*** .01933***(.0013) (.00128) (.00357) (.0042)

ARM .02469** .02277** .00396 .02724(.01039) (.01036) (.02694) (.02929)

Balloon .0327*** .03355*** .00922 .03326(.00566) (.00553) (.01722) (.02071)

Hybrid2 .00483 .00545 -.00708 .03018*(.00573) (.00557) (.01506) (.01627)

Hybrid3 .00245 .00199 -.01457 .0331*(.0062) (.00614) (.01591) (.01863)

Int. Only .01694*** .01671*** .01258 .01138(.00266) (.00265) (.00883) (.00884)

Local Income -.01763*** -.01748*** -.01973*** -.01882***(.00066) (.00066) (.00261) (.00204)

Unemployment -.17262*** -.17263*** -.22798*** -.15577***(.0071) (.0071) (.01803) (.02972)

Price Appr. -.19053*** -.19021*** -.20274*** -.19701***(.00339) (.00336) (.01037) (.00894)

Deal and issue semester FE Yes Yes Yes YesPseudo-R2 0.240 0.240 0.290 0.239N 3531107 3531107 99108 150317

36

Table 11: Individual loan performance in the brackets of [10,20) and [20,30)This table reports the results of analyzing the impact of low-stake originators on individual loan

performance in pre- and post-Reg AB periods. Origchg and Origpct are defined in Table 10. For

each deal, Has 10-20 is a dummy variable that equals 1 if the originator has a share of 10-20%

(same for all loans in the same deal and from the same originator) and 0 otherwise. All the

other variables are defined in the Appendix. The standard errors clustered by issue semester

are reported in the parentheses below each coefficient estimate. Statistical significance levels of

1%, 5%, and 10% are indicated with ***, **, and * respectively.

Pre-Reg AB Post-Reg AB[10,30)% loans [10,30)% loans

Origchg × Has 10-20 -.01711 .27893***(.03024) (.08056)

Origchg .03409 -.24171***(.02219) (.06662)

Has 10-20 .02201** -.02095(.0103) (.03023)

Origpct .00077 -.0017(.00084) (.00218)

FICO -.05691*** -.1381***(.00329) (.00666)

Full Doc -.02603*** -.12518***(.00226) (.00866)

CLTV .02113*** .10819***(.00319) (.0063)

Investor .02003*** .05851***(.00635) (.01214)

DTI .01399*** .04486***(.00234) (.00657)

Miss DTI .03107*** .13275***(.01194) (.02217)

Cash-Out -.01356*** .01299*(.00249) (.00745)

PrePayPen .02684*** .0902***(.003) (.00875)

Initial Rate .01013** -.0103(.00437) (.01055)

Margin .01811*** .0486***(.00488) (.00971)

Rate Reset -.01574*** -.02522**(.00385) (.01012)

Loan Amt. .01643*** .0557***(.00353) (.00526)

ARM -.04382*** -.03712(.00882) (.04502)

Balloon -.0149 .0608**(.01198) (.02801)

Hybrid2 .00516 .01296(.01203) (.02659)

Hybrid3 .00593 .02093(.01412) (.03037)

Int. Only -.01003** .05252***(.00434) (.01604)

Local Income -.00937*** -.04666***(.00142) (.00279)

Unemployment .0583*** -.38403***(.01318) (.0142)

Price Appr. -.12623*** -.18802***(.00485) (.01473)

Deal and issue semester FE Yes YesPseudo-R2 0.313 0.326N 139316 109181

37

Figure 1: Distribution of Origination Structure before and after Reg AB

The bar plots in this figure represent the difference between number (and percentage) of deals

with originators in the [10,20)% and number (and percentage) of deals without originators in

this range. The top panel compares the corresponding measures pre Reg AB (pre 2006) with

post Reg AB (post 2006). The bottom panel plots these measures on an annual basis from 2003

to 2007.

121

1000

303

824

Pre 2006 Post 2006

Has Orig 10-20% No Orig 10-20%

10.8

89.2

26.9

73.1

Pre 2006 Post 2006

Has Orig 10-20% No Orig 10-20%

29

168

35

330

57

502

188

450

115

374

2003 2004 2005 2006 2007

Has Orig 10-20% No Orig 10-20%

14.7

85.3

9.6

90.4

10.2

89.8

29.5

70.5

23.5

76.5

2003 2004 2005 2006 2007

Has Orig 10-20% No Orig 10-20%

38

Figure 2: Difference in percent of deals in brackets right below and above 20%

The bar plots in this figure represent the difference between percentage of deals with originators

in the bracket right below 20% and percentage of deals with originators in the bracket right

above 20%. Panel A compares [10,20) with [20,30). Panel B compares [15,20) with [20,25).

Panel C compares [18,20) with [20,22).

Panel A: Percent of deals with [10,20) originators minus Percent of deals with [20,30) originators

2003 2004 2005 2006 20070

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.08

0.09

0.1

Panel B: Percent of deals with [15,20) originators minus Percent of deals with [20,25) originators

2003 2004 2005 2006 2007−0.01

0

0.01

0.02

0.03

0.04

0.05

0.06

0.07

Panel C: Percent of deals with [18,20) originators minus Percent of deals with [20,22) originators

2003 2004 2005 2006 2007−0.02

−0.015

−0.01

−0.005

0

0.005

0.01

0.015

0.02

39