Houses as ATMs: Mortgage Refinancing and Macroeconomic Uncertainty

• Date: 01 February 2020
• Published date: 01 February 2020
• Author: NIKOLAI ROUSSANOV,MICHAEL MICHAUX,HUI CHEN
• DOI: http://doi.org/10.1111/jofi.12842

THE JOURNAL OF FINANCE •VOL. LXXV, NO. 1 •FEBRUARY 2020

Houses as ATMs: Mortgage Refinancing and

Macroeconomic Uncertainty

HUI CHEN, MICHAEL MICHAUX, and NIKOLAI ROUSSANOV∗

ABSTRACT

Mortgage refinancing activity associated with extraction of home equity contains a

strongly countercyclical component consistent with household demand for liquidity.

We estimate a structural model of liquidity management featuring countercyclical

idiosyncratic labor income uncertainty,long- and short-term mortgages, and realistic

borrowing constraints. We empirically evaluate its predictions for households’ choices

of leverage, liquid assets, and mortgage refinancing using microlevel data. Taking

the observed historical paths of house prices, aggregate income, and interest rates as

given, the model accounts for many salient features in the evolution of balance sheets

and consumption in the cross-section of households over 2001 to 2012.

THE ORIGINS OF THE RECENT financial crisis and the severity of the Great Reces-

sion are often attributed to the increase in consumer indebtedness during the

period of house price run-up in mid-2000s and the subsequent deterioration

of household balance sheets with the sharp decline in house prices (see, e.g.,

Dynan (2012), Mian, Rao, and Sufi (2013)). There is less consensus, however,

about the structural forces driving the borrowing boom and the subsequent

consumption slump.1In particular, the growth of household leverage and con-

sumption expenditures financed with extracted home equity over the house

price boom as documented by Mian and Sufi (2011) are qualitatively consistent

∗Hui Chen is with the Massachusetts Institute of Technology (MIT) and the National Bureau

of Economic Research (NBER). Michael Michaux is unaffiliated (formerly with the University of

Southern California). Nikolai Roussanov is with the Wharton School, University of Pennsylvania

and NBER. We gratefully acknowledge comments and suggestions by Andrew Abel, Rui Albu-

querque, Fernando Alvarez, Nick Bloom, Francisco Buera, John Campbell, Christopher Carroll,

Joao Cocco, Dean Corbae, Morris Davis, John Driscoll, Joao Gomes, Lars Hansen, Erik Hurst, Ur-

ban Jermann, Greg Kaplan, Ralph Koijen, Dirk Krueger,David Laibson, Francis Longstaff, Debbie

Lucas, Hanno Lustig, Rajnish Mehra, Stijn Van Nieuwerburgh, Dimitris Papanikolaou, Jonathan

Parker, Monika Piazzesi, Vincenzo Quadrini, Victor Rios-Rull, Tom Sargent, Martin Schneider,

Antoinette Schoar, Amit Seru, Todd Sinai, Kenneth Singleton (first round editor), Nicholas Soule-

les, Kjetil Storesletten, Harald Uhlig, Luis Viceira, Gianluca Violante, Jessica Wachter, Annette

Vissing-Jorgensen, Pierre-Olivier Weill,Toni Whited, Paul Willen, Randy Wright, Amir Yaron, and

audiences at a number of institutions and conferences. Sangming Oh and Kian Samaee provided

expert research assistance. Roussanov acknowledges support from the Rodney White Center for

Financial Research at the Wharton School. We have read The Journal of Finance’sdisclosure policy

and have no conflicts of interest to disclose.

1Keys et al. (2012) survey the extensive literature on the role of mortgage finance in the housing

boom and bust.

DOI: 10.1111/jofi.12842

C2019 the American Finance Association

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324 The Journal of Finance R

with liquidity-constrained households taking advantage of relaxed housing col-

lateral constraints, but also with consumers’ lack of self-control (e.g., as in

Laibson (1997)), overly optimistic expectations (e.g., Laibson and Mollerstrom

(2010)), and/or lender moral hazard (e.g., Keys et al. (2010)).2

We document that mortgage refinancing activity involving home equity ex-

traction exhibits a strongly countercyclical component that cannot be explained

by fluctuations in interest rates, which suggests that household demand for liq-

uidity is an important driver of borrowing behavior. We further show that a

rational model of home equity–based borrowing by liquidity-constrained house-

holds that matches this key stylized fact can quantitatively account for the em-

pirical patterns in household leverage and consumption over the last decade.

In our model, households face idiosyncratic labor income risk and hous-

ing collateral constraints that resemble key institutional features of the U.S.

mortgage markets. Specifically, households have access to long-term fixed rate

mortgages and short-term home equity lines of credit (HELOC), and they

face two realistic borrowing constraints that restrict the ratios of loan size

to home value (LTV) and loan size to household income (LTI) to be not too high

at the time of new loan origination and refinancing. Additionally, our model

features countercyclical idiosyncratic labor income risk (Meghir and Pistaferri

(2004), Storesletten, Telmer, and Yaron (2004), Guvenen, Ozkan, and Song

(2014)). This property of the labor income process implies that a macroeco-

nomic downturn not only makes more households liquidity constrained, but

also increases their uncertainty about future income.

Our analysis focuses on households’ optimal choices of consumption, lever-

age, precautionary savings in liquid assets and illiquid home equity, as well

as dynamic decisions in debt repayment, mortgage refinancing, home equity

extraction, and default. We abstract from other forms of asset holdings both for

the sake of tractability and because we aim to capture the behavior of an aver-

age household, for which housing wealth dwarfs financial assets by an order of

magnitude.3We follow the partial equilibrium approach of Campbell and Cocco

(2003).4Although much of the existing literature treats mortgage refinancing

and home equity–backed borrowing in isolation, our analysis indicates that an

integrated approach is important for understanding both.5

2Landvoigt (2017) attributes the increase in homeowner leverage to rising uncertainty about

future house prices rather than inflated growth expectations.

3According to our data based on the Survey of Consumer Finances, a median homeowner

household’s home equity is roughly 10 times greater than its liquid asset holdings.

4We abstract from the choice between adjustable and fixed-rate mortgages analyzed by Camp-

bell and Cocco (2003) and Koijen, Van Hemert, and Van Nieuwerburgh (2009). Our approach is

also related to models of consumption smoothing in the presence of transaction costs, for example,

Bertola, Guiso, and Pistaferri (2005), Alvarez, Guiso, and Lippi (2012), and Kaplan and Violante

(2014).

5The wealth and collateral effects of housing on consumption have been studied empirically

(e.g., Caplin, Freeman, and Tracy (1997), Campbell and Cocco (2007), Carroll, Otsuka, and Sla-

calek (2011), Lustig and Van Nieuwerburgh (2010), Case, Quigley, and Shiller (2011), Calomiris,

Longhofer, and Miles (2013)) as well as theoretically (e.g., Campbell and Hercowitz (2005),

Houses as ATMs 325

The decision to refinance trades off the benefits, in the form of lower interest

rates and/or liquidity extraction, against the financial and nonpecuniary costs

of originating a new loan. Because households do not have access to complete

financial markets, the embedded options to default, prepay, or refinance the

mortgage cannot be analyzed using the standard option pricing framework

(see, e.g., Chen, Miao, and Wang (2010)). As first pointed out by Hurst and

Stafford (2004), the ability to convert home equity into liquid assets can lead

to refinancing even if doing so results in an increase in borrowing costs, which

is in sharp contrast to the predictions of traditional models that consider a

reduction in the interest rate the only reason to refinance. Such liquidity-

driven refinancing motives become particularly acute during a recession, when

many households are subject to large negative income shocks.

Fluctuations in household income and house prices also affect the tightness

of households’ borrowing constraints. A rise in house prices relaxes the LTV

constraint, resulting in an increase in cash-outs for high-leverage households.

A rise in household income relaxes the LTI constraint, enabling more low-

income households to access their home equity savings. A looser LTI constraint

can also enable more households to become homeowners or switch to a bigger

house, which would relax the LTV constraint and further increase the amount

of borrowing.6Moreover, the interactions between idiosyncratic labor income

risks and the debt service constraint can cause households to refinance pre-

emptively (before the borrowing constraint binds).7Our model therefore points

to household demand as a key force behind the strong credit expansion during

the 2000 to 2006 house price boom.

Taking the observed historical paths of house prices, aggregate household

income, and interest rates as exogenously given, our baseline model can account

for both the run-up in household leverage from 2000 to 2006 and the sharp

contraction in consumption that followed. In the cross-section, absent any ex

ante heterogeneity, the model generates wide dispersion in the dynamics of

liquid asset holding, household debt, refinancing patterns, and consumption

that are largely consistent with the data.

Specifically, the countercyclical idiosyncratic labor income risks, borrowing

constraints that vary in tightness with house prices and income, and high

costs of default together generate a strong precautionary savings motive, es-

pecially for high-leverage households. As a result, in spite of the buffer pro-

vided by long-term mortgages and HELOCs, households with high boom-time

leverage experience significantly larger consumption declines and debt reduc-

tions during the Great Recession in our model. In other words, deleveraging

need not be “forced” as in the case of short-term mortgages (contrary to the

Fernandez-Villaverde and Krueger (2011), Attanasio, Leicester, and Wakefield (2011), Favilukis,

Ludvigson, and Nieuwerburgh (2017), Midrigan and Philippon (2011)).

6Campbell and Cocco (2015) emphasize the role of the LTI ratio in driving borrower default

decisions. Greenwald (2018) studies the effect of the interactions between the LTV constraint and

debt service constraint on housing demand and house prices in a general equilibrium setting.

7Bolton, Chen, and Wang (2011,2013) study such interactions of financing risks and liquidity

management for firms.