OBSOLESCENCE OF THE 30-YEAR MORTGAGE MODEL

Salvatore R. Gulino

138 Main St Essex Ma, 01929

sg@mbsadvisorsinc.com

Abstract

We examine the relationship between the macroeconomics of real-estate and the

negative impact of the 30-year mortgage model on the economy as it relates to

elevated Housing Cost To Income (HCTI) ratios. The average borrower’s housing

expense has risen to approximately 50% of an American’s average net income. As

a consequence, it is not uncommon for homeowners to find themselves financially

ill-equipped to handle moderate economic contractions. Our research suggests

having a thorough understanding of how these intricate economic components

work together will provide an enhanced comprehension of the present, and future

health of our financial system.

Key Words: Systemic Risk, Optimized Fixed Income Model, Macro/Micro Economics, Credit Default Risk, Underwater MortgagesJEL Codes: C53, D00, G01, G02, G21, N00.

**This article and research received no outside funding. It was solely supported by the author. I am grateful to Eric P. Pasini whose edits have improved this paper.

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I. Introduction

Economists and governments at large view the real-estate market as one of the key

components which affects a capitalistic society’s economy (Bluhm, Overbeck and Wagner,

2010). By being aware of the different stages of real estate cycles, and how it affects the

expansion and contraction of our economy, we are better equipped to deal with the ever changing

state of the economy (Alexander and Moloney, 2011). We examine the conceptualization of the

real-estate market cycles as being a clock with different progressive stages of economic time,

which can be advanced, slowed down, or to some degree reversed. Our research suggests this as

being a key element in controlling economic contractions. (Allen and Barth, 2012). If we can

recognize which direction our real-estate cycle is currently heading, we may be able to alter its

trajectory to our economy’s advantage. Is it really possible to manage economic time, which

could conceivably lead to the end of real-estate bubbles? If so, could the proper management of

real-estate cycles be used to facilitate a positive stabilizing impact on the economy? This paper

investigates the driving forces we believe could lead to the answers to these, and other questions

economist and policy makers alike have been pondering for many years.

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II. THE EFFECTS OF HCTI PARADOX ON AFFORDABLE HOUSING INITIATIVES

FDR’s affordable housing initiative was responsible for the rapid expansion of home

ownership throughout the United States (Allen and Barth, 2012). This was accomplished in part

through the creation of The Federal National Mortgage Association, which provided affordable

low down payment mortgages extended over a 30-year period of time. Over the past several

decades the United States has continued to implement economic policies to encourage home

ownership through affordable low downpayment mortgage programs (Bluhm, Overbeck and

Wagner, 2010).

The Housing Cost to Income (HCTI) index consists of the average cost of a single

family home divided by median income. According to the 1940 U.S. Census Bureau, the median

price of a single family home in the U.S. was approximately $2,938 (Aalbers, 2012). The median

yearly wage was $1,730. The HCTI ratio was just over 2:1. The HCTI ratios were 3 - 4:1

throughout the 1950s - 1960s. By the 1970s, HCTI ratios increased to over 5:1 (U.S Census

Table I). Figure I denotes the housing appreciation trend in light blue has accelerated at a higher

rate of speed during the past 40 years (Shiller, [2005]). Housing values on average have doubled

at the end of a housing boom, out pacing increases in median income by 50% (see Figure II, U.S

Census, [1969-2008]). The disproportionate rate of speed between a borrower’s housing expense

and their income appreciation since the 1970s, has led to the median housing expense to rise to

approximately 50% of an average homeowners net income. In an effort to keep the economy

growing at a moderate pace the Federal Reserve’s policy is to keep inflation at a rate of 2% per

year. Over the past four decades they're efforts have led to an average inflation rate of 3% per

year. When compounded, a 3% inflation rate over 10 years, approaches 40%. The combination of

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a homeowners housing expense being approximately 50% of their average income, along with a

40% inflation rate increase over ten years, has fostered generations of financially strapped

borrowers with mortgage payments that exceed their ability to pay within several years of buying

their homes. (Wiedemer and Baker, [2013]). Over the past 40 years the rationale behind the

policy of stimulating the economy through the increase in homeownership is being undermined

by the 30-Year amortization model (Allen, [2013]). The central issue at hand is the amount of

equity the 30-Year mortgage model is capable of generating within a ten-year period has proven

to be insufficient for our modern-day economy (Jones, [2013]). There is an increase in

probability of borrower default rates when mortgages become higher than the value of a

borrower’s home during economic contractions. The frequency of economic contractions, which

has led to an escalation of mortgage defaults is approximately once in every ten years (see Figure

I, Shiller, [2005]).

Figure I: Shiller Real Home Price Index

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Figure II: Median Income VS New Home Appreciation

The drive to stimulate the economy through homeownership, which enable borrowers to

over extend themselves beyond their ability to pay, resulting in a negative impact on the

economy is known as The HCTI Paradox. Figure III shows the decrease of home values of

Shillers 20-City Index leading to 2008. A faster Principal Reduction Amortization Model

(PRAM) would prevent a HCTI Paradox caused by underwater mortgages by enabling borrowers

to build enough equity to refinance into lower interest rates or the option of selling a home they

can no longer afford during economic contractions (see Figure IV).

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During Each Housing BoomEach Decade

Figure III: Case-Shiller 20-City Home Price IndexFigure III: PRAM VS 30-Year

Figure IV PRAM VS 30-Year Mortgage Model Principal Reduction Comparison

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$0

$52.50

$105.00

$157.50

$210.00

2005 2007 2008 2009 2010 2012 2013 2014

$0$20,000$40,000$60,000$80,000

$100,000$120,000$140,000$160,000$180,000$200,000

1 2 3 4 5 6 7 8 9 10 11 12

12-Year Comparison at a 6% Interest Rate

Prin

cipa

l Bal

ance

Number Of Years

PRAM 30 Year Conv

III. The Essentials of A Modern-day Mortgage Amortization Model

Contrary to popular belief among some financial analysts, the mortgage crisis of 2008

may have occurred with or without the existence of subprime mortgages. According to the U.S.

Census Bureau, subprime mortgages at their peak rose to just over 20% of all home mortgages

originated, of which 35% defaulted. Subprime mortgage defaults accounted for approximately

7% of mortgages originated at their peak. The cumulative defaults of conventional mortgages

from vintage pools of 2007 were over 13%, surpassing subprime default rates (see Figure V,

Fannie Mae 2013). The credit characteristics of Fannie Mae and Freddie Mac mortgage pools

originated between the years 2001-2007 were virtually the same, however, default rates from

vintage pools prior to 2004 were approximately 1.5% (Fannie Mae, [2013]).

The crisis began when the housing default rates were approaching 6%, leading to the conclusion,

a severe housing bubble would have occurred with or without the influence of subprime

mortgages (see Figure V, Fannie Mae), [2013]. Nearly 100% of the three million mortgages

originated prior to 2008 still underwater in 2013 would have been sufficiently de-leveraged

under PRAM (Macdonald, [2012], see Fig IV). The data in Figure III and IV confirms, most of

the anchoring principles of the 30-Year mortgage have been lost due to its inability to reduce

mortgage balances quick enough to keep up with our modern-day economy.

The 30-Year mortgage model has proven to be incapable of offsetting the historically low

increase in wages to keep up with the past appreciation in housing and inflation rates (Wolfson,

[2013]) A new amortization model that is mutually beneficial to lenders, borrowers, and bond

investors in today’s economy is essential (Jones, [2013]). A modern-day mortgage amortization

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model should offer the capability and flexibility to sustain the following factors (Wolfson,

[2013]):

1. Entice borrowers to stay in their mortgages for a longer period of time (Alexander and

Moloney, [2011]).

2. A rapid Principal Reduction Amortization Mortgage (PRAM) model should be used to

quickly and effectively de-leverage the current banking system while providing more

equity to borrowers in a shorter period of time.

3. It should decrease the weighted average risk of bonds attributable to the first ten years

of a borrower’s mortgage (Wiedemer and Baker, [2013]).

Figure V: Cumulative Default Rates of Single-Family by Origination Year

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Figure VI: PRAM VS 30 - Year Model’s Equity and Lender Recapitalization Rates.

IV. Advantages of Software Based PRAM Models

Since the late 1970s borrowers no-longer keep their mortgages till full term. Most

borrowers either sell, or refinance their mortgage within 10 years (Bluhm, Overbeck and Wagner,

2010). PRAM’s 20- Year model reduces the accrued interest to capital risk ratio’s for lenders and

MBS investors from, 3:1 under a 30-Year model to 2-1, nullifying the HCTI paradox created by

the 30-Year model currently inhibiting the economic stimulus goals of the Federal Reserve.

Under PRAM borrowers will have the ability to obtain 50% more equity in several years,

virtually eliminating the issue of homeowners being unable to fulfill their mortgage obligations

by enabling them to have enough equity to qualify for a lower rate refinance or the option of

selling their home during economic contractions. (Allen, [2013]) Figure IV leads us to conclude

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the net effects of the PRAM model could virtually eliminate foreclosures created by underwater

mortgages (Wiedemer and Baker, [2013]).

Software based PRAM models yields and Weighted Risk Averages (WRA) can be easily

modified and optimized by a lender to their own specifications. The PRAM model is capable of

being programmed to slow down or rapidly increase the reduction of the principal balance of a

mortgage. PRAM’s ability to rapidly reduce the total sum of a mortgage balance during the first

10 years leads to a dramatic reduction in principal and accrued interest, reducing the term of a

mortgage from 30 to 20 years. The result of which, enables borrowers to gain twice the amount

of equity within the first 10 years, while simultaneously reducing a lender’s risk in half

compared to the 30-Year mortgage (see Figure VI). Moreover, the innate tax advantages of

revenue streams comprised of mostly principal during the first 10 years, while PRAM software

keeps track of all the deferred interest being accrued and compounded, enables lenders and MBS

investors to receive nearly 40% higher tax-free revenue streams, creating approximately 1% in

additional yields annually. PRAM’s software based amortization models can be programed to

reduce principal at approximately the same pace as the 15-Year mortgage. Thus PRAM would

receive the same 1% discount in interest rate over the 30-year mortgage as does the 15-Year

mortgage. You will notice in Figure VII PRAM example, despite having a lower rate, it’s

monthly payment is $31 higher. There is a $64 difference in payment between a 5% and 6%

interest rate. Oppose to lowering PRAM’s monthly payment by $95, PRAM applies the $95

difference toward lowering the principal balance of the mortgage each month. The result of

making an extra $95 payment toward the principal balance each month for over 120 months

combined with a 1% lower rate, with monthly payments that are composed of more principal,

leads to shorter mortgage terms from 30 to 20 years, resulting in a $25,414 increase in equity

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within 10 years. It is mathematically impossible to use the current 70 year old conventional 15,

20 or 30-Year mortgage formula to duplicate the same results as the PRAM model.

PRAM’s monthly payment is only $31 more, however, borrowers would receive $25,414

in additional equity in ten years, double the amount it would receive compared to the 30-Year

mortgage. PRAM will cost the borrower $372 dollars a year, $3720 more over 10 years, for the

borrower to make over $25,000 more equity. Borrowers would receive over 680% return on their

investment per year with zero risk. All the borrower has to do is make their mortgage payments.

Figure VII: PRAM VS 30-Year Outline.

V. PRAM’s Influence on Bond Ratings

Under the MBS system, the highest yields are paid to the riskiest tranches of bonds,

which are tied to the first ten years of a mortgage term (Green, [2013]). Borrowers sell or

refinance their homes within 10 years of obtaining their mortgage. As a consequence of this

trend, bond investors as a whole are resigned to invest large sums of capital, 30-Years worth of

capital, for only 10 years of accrued interest, into the riskiest tranches of the bond pool. These

revenue streams are all too often dependent on borrowers that have a high balance mortgage with

HCTI ratio approaching 6:1 (Wolfson, [2013]). Figure VIII reviews the mindset of most bond

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investors, the higher the risk, the more yield an investor will expect to make from their

investment (Allen, [2013]). Due to PRAM’s ability to rapidly reduce principal 50% faster than

the 30-Year model, it will produce approximately 50% more AA/Aa - AAA/Aaa rated tranches

within the first ten years compared to the 30-Year based model (Alexander and Moloney,

[2011]). This translates into a greater weighted average increase in yields within the PRAM

based bond pools. (Stone and Zissu, [2012]).

Figure VIII Bond Risk VS Return (Splettstoesser, 2009).

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If PRAM were to add 50% more AAA rated bonds during the first ten years than the 30-

Year mortgage model, most of the tranches that were below AAA would receive a credit

enhancement as well (Macdonald, [2012]). PRAM based MBS tranches attributed to the first ten

years will have higher yields due to their lower weighted risk averages. Figure IX is a typical

commercial pool made up of, in part, AAA and BBB rated bonds (Stone and Zissu), [2012]. If

PRAM were to enhance just 30% of the entire pool, the gain between AAA and BBB rated bonds

would be an additional 1.72% in yield. 30% of $2 billion pool is $600 million. Under the PRAM

model, the yearly revenue increase in the pool based on a gain of 1.72% of a $600 million

pool would be an additional $10,320,000 per annum in yield with half the total weighted average

risk [Alexander and Moloney, [2011]). Naturally, similar results can be achieved with all fixed

income investment vehicles, including GSE and non-GSE residential mortgage pools.

Should PRAM inject 50% more AAA rated mortgages within the first ten years, a majority of the

classes below AAA would receive a rating upgrade as well (Allen, [2013]).

Figure IX Summery of Certificates

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IV. Conclusion

It is apparent that most, if not all tranches rated below AAA would receive an increase in

yield through the use of the PRAM model, which will have an overall positive effect on

mortgage rates (Johnson, [2013]). As Figure I should confirm, the mortgage meltdown of the

70s, 80s, 90s, and yet again in 2008, is a habitual reminder to the financial industry of the

inherent risks associated with the inability of the 30-Year amortization model to sufficiently de-

leverage mortgage pools within the first ten years (Alexander and Moloney),[2011]. A 30-Year

amortization model as demonstrated in Figure VI takes nearly 12 years to reduce the LTV to

80%. In contrast, the PRAM model would take approximately five years. As of 2013

approximately three million mortgages were underwater in the U.S resulting in mass

foreclosures. (Blinder, Alan.S., [2013]). If all the mortgage pools originated in 2005-2007 were

based on the PRAM mortgage model, nearly 100% of the three million mortgages still

underwater in 2013 would have been sufficiently de-leveraged. Most of the consequences

manifested by the mass foreclosures that followed may have been avoided (see Figure VII).

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!

Table I: HCTI Affect on Interrelated Economic Indices Percentage Change Between The Years of

1965-2013

!

!

_____________________________________________________

* Bold and italicized figures indicate real-estate boom years

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