House Prices, Borrowing Constraints, and Monetary Policy in the Business Cycle

TLDR: This paper developed a general equilibrium model with sticky prices, credit constraints, nominal loans and asset prices, and found that monetary policy should not target asset prices as a means of reducing output and inflation volatility.

Abstract: I develop a general equilibrium model with sticky prices, credit constraints, nominal loans and asset prices. Changes in asset prices modify agents’ borrowing capacity through collateral value; changes in nominal prices affect real repayments through debt deflation. Monetary policy shocks move asset and nominal prices in the same direction, and are amplified and propagated over time. The “financial accelerator” is not constant across shocks: nominal debt stabilises supply shocks, making the economy less volatile when the central bank controls the interest rate. I discuss the role of equity, debt indexation and household and firm leverage in the propagation mechanism. Finally, I find that monetary policy should not target asset prices as a means of reducing output and inflation volatility.

Figures

Figure A.4: Frequency Of Times The Borrowing Constraint Binds As A Function Of The LoanTo-Value m, For Different Values Of The Other Parameters.

FIGURE 3: RESPONSE OF AGGREGATE CONSUMPTION TO A HOUSE PRICE SHOCK VARIOUS VALUES OF m AND m”

FIGURE 7: POLICY FRONTIERS: NOMINAL VERSUS INDEXED DEBT

Table 2: Estimated parameters and their standard errors in the extended model

Figure A.1: Simulated Variables, Baseline Case

FIGURE 2: TOTAL OUTPUT LOSS IN RESPONSE TO A MONETARY SHOCK IN THE BASIC MODEL. COMPARISON BETWEEN ALTERNATIVE MODELS

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House Prices, Borro wing Constraints and M onetary P olicy in
th e B u s in e ss C y c le
Ma tteo Iacoviello
∗
Boston College
Decem ber 6, 2004
Abstract
I develop and estimate a monetary business cycle model with nominal loans and collateral constraints
tied to housing values. Demand shocks move together housing and nominal prices, and are amplified
and propagated over time. The financial accelerator is not uniform: nominal debt dampens supply
shocks, stabilizing the economy under interest rate control. Structural estimation supports two key
model features: collateral effects dramatically improve the response of aggregate demand to house prices
shoc ks; nominal debt improves the sluggish response of output to inflation surprises. Finally, policy
evaluation considers the role of house prices and debt indexation in affecting monetary policy trade-offs.
(JEL E31, E32, E44, E52, R21)
∗
Departmen t of Economics, Boston College, Chestnut Hill, MA 02467, USA (email: iacoviel@bc.edu).
I am deeply indebted to my Ph.D. advisor at the London Sch ool of Economics, Nobuhiro Kiyotaki,
for his continuous help and invaluable advice. I thank Fabio Canova, Raffaella Giacomini, Christopher
House, Peter Ireland, Raoul Minetti, François Ortalo-Magné, Marina Pavan, Christopher Pissarides,
Fabio Schiantarelli, two anonymous referees and seminar participants at the Bank of England, Boston
College, the European Central Bank, the Ente Luigi Einaudi, the Federal Reserve Bank of New York,
the Federal Reserve Bank of St.Louis, the London School of Economics, the NBER Monetary Economics
Meeting and Northeastern University for their helpful comments on various versions of this work. Viktors
Stebunovs provided superb research assistance.

The population is not distributed bet ween debtors and creditors randomly. Debtors have
borrowed for good reasons, most of which indicate a high marginal propensity to spend
from wealth or from current income or from any other liquid resources they can command.
Typically their indebtedness is rationed by lenders [...]. Business borrowers typically have a
strong propensity to hold physical capital [...]. Their desired portfolios contain more capital
than their net worth [...]. Household debtors are frequently young families acquiring homes
and furnishings before they earn incomes to pay for them outright; given the difficulty of
borrowing against future wages, they are liquidity-constrained and have a high marginal
propensity to consume.
James Tobin, Asset Accumulation and Economic Activity, 1980 p.10.
A long tradition in economics, starting with Irving Fisher’s (1933) debt-deflation explanation of the
Great Depression, considers financial factors as key elements of business cycles. In this view, deteriorating
credit market conditions, like growing debt burdens and falling asset prices, are not just passive reflections
of a declining economy, but are themselves a major factor depressing economic activit y.
Although this “credit view” has a long history, most of theoretical work on this subject has been
partial equilibrium in nature until the late 1980s, when Ben Bernanke and Mark Gertler (1989) formalized
these ideas in a general equilibrium framework. Following their work, various authors have presented
dynamic models in which financing frictions on the firm side may amplify or propagate output fluctuations
in response to aggregate disturbances: examples include the real models of Nobuhiro Kiyotaki and John
Moore (1997) and Charles Carlstrom and Timothy Fuerst (1997), and the sticky-price model of Bernanke,
Gertler and Simon Gilchrist (1999). Empirically, various studies have shown that firms’ investment
decisions are sensitive to various measures of firms’ net worth (see Glenn Hubbard, 1998, for a review).
At the same time, evidence of financing constraints at the household level has been widely documented by
Stephen Zeldes (1989), Tullio Jappelli and Marco Pagano (1989), John Campbell and Gregory Mankiw
(1989) and Christopher Carroll and Wendy Dunn (1997).
While these studies have highlighted the importance of financial factors for macroeconomic fluctua-
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tions, to date there has been no systematic evaluation of the exten t to whic h a general equilibrium model
with financial frictions can explain the aggregate time-series evidence on the one hand, and be used for
monetary policy analysis on the other. This is the perspective adopted here. From the modeling point of
view, my starting point is a variant of the Bernanke, Gertler and Gilchrist (1999) new-Keynesian setup
in which endogenous variations in the balance sheet of the firms generate a “financial accelerator” by
enhancing the amplitude of business cycles. To this framework, I add two main features: (1) collateral
constrain ts tied to real estate values for firms, as in Kiyotaki and Moore (1997), and for a subset of the
households; (2) nominal debt. The reason for housing
1
collateral is practical and substantial: practi-
cal because, empirically, a large proportion of borrowing is secured b y real estate; substantial because,
although housing markets seem to play a role in business fluctuations,
2
the channels by which they
affect the economy are far from being understood. The reason for ha ving nominal debt comes from the
widespread observation that, in low inflation countries, almost all debt contracts are in nominal terms,
even if they appear hard to justify on welfare-theoretic grounds: understanding their implications for
macroeconomic outcomes is therefore a crucial task.
In addition, I ask whether the model is able to explain both key business cycle facts and the interaction
bet ween asset prices and economic activity. To this end, I estimate the key structural parameters by
minimizing the distance between the impulse responses implied b y the model and those generated by
an unrestricted Vector Autoregression. The estimates are both economically plausible and statistically
significant. They also provide support for the two main features of the model (collateral constraints and
nominal debt). In the concluding part of the paper, therefore, I use the estimated model for quantitative
policy analysis.
The model transmission mec hanism works as follows. Consider, for sake of argument, a positive
demand shock. When demand rises, consumer and asset prices increase: the rise in asset prices increases
the borrowing capacity of the debtors, allowing them to spend and in vest more. The rise in consumer
prices reduces the real value of their outstanding debt obligations, positively affecting their net worth.
Given that borrowers have a higher propensity to spend than lenders, the net effect on demand is
positive, and acts as a powerful amplification mechanism. However, while it amplifies the demand
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shocks, consumer price inflation dampens the shocks that induce a negative correlation between output
and inflation: for instance, adverse supply shoc ks are beneficial to borrowers’ net worth if obligations
are held in nominal terms. Hence, unlike the previous papers, the financial accelerator really depends on
where the shocks come from: the model features an accelerator of demand shocks, and a “decelerator”
of supply shocks.
The transmission mechanism described above is at the root of the model success in explaining two
salient features of the data. First, collateral effects on the firm and the household side allow matching
the positive response of spending to a house price shock.
3
Second, nominal debt can replicate the hump-
shaped dynamics of spending to an inflation shock.
4
Suc h improvement s in the model ability to reflect
short-run dynamic properties are especially important, given that several studies (e.g. Jordi Galí, 2004,
and Peter Ireland, 2004b) have stressed the role of non-tec h nology and non-monetary disturbances for
understanding business fluctuations.
Finally, I address and answer two important policy questions. First, I find that allowing the monetary
authority to respond to asset prices yields negligible gains in terms of output and inflation stabilization.
Second, I find that nominal (vis-à-vis indexed) debt yields an improved output-inflation variance trade-
off for the central bank: this happens because the sources of trade-offs in the model do not get amplified,
since such shocks, ceteris paribus, transfer resources from lenders to borrowers during a downturn.
The plan of the paper is as follows. The next section presents some VAR evidence on house prices and
the business cycle. Section II presents the basic model. Section III extends the basic model by including
a constrained household sector and by allowing for variable capital. Section IV estimates the structural
parameters of the model. Section V analyses its dynamics. Section VI looks at house prices and debt
indexation for the formulation of systematic monetary policy. Concluding remarks are in Section VII.
I. VAR evidence on house prices and the business cycle
Figure 1 presents impulse responses (with 95 percent bootstrapped confidence bands) from a VAR with
detrended real GDP (Y ), change in the log of GDP deflator (π) , detrended real house prices (q),and
Fed Funds rate (R) from 1974Q1 to 2003Q2.
5
I use this VAR to document the key relationships in the
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data, and, later in the paper, to choose the parameters of the extended model in a way to match the
VAR impulse resp onses.
Here and in the rest of the paper, the variables are expressed in percentages and in quarterly rates.
The shocks are orthogonalized in the order R, π, q and Y . The ordering did not affect the results
substan tially: as I will show below, such an ordering also renders the VAR and the model more directly
comparable. The results suggest that a model of the interaction between house prices and the business
cycle has to deliver:
1) A negative response of nominal prices, real house prices and GDP to tight money (Figure 1, first
row);
2) A significant negative response of real house prices and a negative but small response of output to
a positiv e inflation disturbance (second row);
3) A positive comovemen t of asset prices and output in response to asset price shocks (third row) and
to output shocks (fourth row). Taken together, the two rows highlight a two-way interaction between
house prices and output.
In the rest of this paper, I develop and estimate a model that is consisten t with these facts and that
can be used for policy analysis. I start with a basic model, which conveys the intuition.
II. The basic model
Consider a discrete time, infinite horizon economy, populated by entrepr e neurs and patient households,
infinitely lived and of measure one. The term “patient” captures the assumption that households have
lower discount rates than firms and distinguishes this group from the impatient households of the ex-
tended model (next section). Entrepreneurs produce a homogeneous good, hiring household labor and
combining it with collateralizable real estate. Households consume, work, demand real estate and money.
In addition, there are retailers and a central bank. Retailers are the source of nominal rigidity. The central
bank adjusts money supply and transfers to support an interest rate rule.
In order to have effects on economic activity from shifts in asset holdings, I allow housing investment
by both sectors. However, I assume that real estate is fixed in the aggregate, which guarantees a variable
5

Frequently asked questions

Q1. What are the contributions in "House prices, borrowing constraints and monetary policy in the business cycle" ?

I thank Fabio Canova, Raffaella Giacomini, Christopher House, Peter Ireland, Raoul Minetti, François Ortalo-Magné, Marina Pavan, Christopher Pissarides, Fabio Schiantarelli, two anonymous referees and seminar participants at the Bank of England, Boston College, the European Central Bank, the Ente Luigi Einaudi, the Federal Reserve Bank of New York, the Federal Reserve Bank of St. Louis, the London School of Economics, the NBER Monetary Economics Meeting and Northeastern University for their helpful comments on various versions of this work. Although this “ credit view ” has a long history, most of theoretical work on this subject has been partial equilibrium in nature until the late 1980s, when Ben Bernanke and Mark Gertler ( 1989 ) formalized these ideas in a general equilibrium framework. 

Q2. What have the authors stated for future works in "House prices, borrowing constraints and monetary policy in the business cycle" ?

Assessing this is an important task for future research. 

Q3. What is the effect of deflation on the economy?

Debt deflation plays a role too: as obligations are not indexed, deflation raises the cost of debt service, further depressing entrepreneurial consumption and investment. 

Q4. What is the effect of sticky prices on the real rate?

With sticky prices, monetary actions affect the real rate, and its increase works by discouraging current consumption and hence output. 

Q5. What are the first-order conditions for anoptimum?

The first-order conditions for anoptimum are the consumption Euler equation, real estate demand and labor demand:1 ct = Etµ γRtπt+1ct+1¶ + λtRt(7)1 ct qt = Etµ γct+1µ νYt+1 Xt+1ht + qt+1¶ + λtmπt+1qt+1 ¶ (8) w0t = (1− ν)Yt/ (XtLt) . 

Q6. What is the effect of the negative correlation between inflation and output?

the negative correlation between inflation and output induced by an inflation shock acts as a built-in stabilizer for the economy. 

Q7. How does Samwick (1998) calculate the underlying distribution of discount factors?

Samwick (1998) uses wealth holdings at different ages to infer the underlying distribution of discount factors: for about 70 percent of the households, he finds mean discount factors of about 0.99; for about 25 percent of households, he estimates discount factors below 0.95. 

Q8. How many percent of the entrepreneurial asset share is a steady state value?

I set the elasticity of output to real estate ν to 0.03 (with j = 0.1, this yields a steady state value of h, the entrepreneurial asset share, of 20 percent). 

Q9. What is the reason why the estimate of the autocorrelation in the technology shock is low?

the estimate of the autocorrelation in the technology shock is low (ρA = 0.03) and less precisely estimated: one explanation might be the detrending method used in the VAR, which takes away the low-frequency component of GDP. 

Q10. What is the optimum consumption Euler equation for the household?

In fact, the steady state consumption Euler equation for the household implies, with zero inflation, that R = 1/β, the household time preference rate. 

Q11. What is the effect of the fall in house prices?

The effect is reinforced through the fall in house prices, which leads to lower borrowing and lower entrepreneurial housing investment. 

Q12. What is the obvious explanation for the lack of features in the model?

Perhaps the simplest explanation for this finding is that the model lacks features such as expectational delays, inertial adjustment of prices or habit persistence that elsewhere authors have shown can help replicating the delayed responses of macroeconomic variables to various shocks (see e.g. Julio Rotemberg and Michael Woodford, 1997, Galí and Gertler, 1999, Fuhrer, 2000). 

Q13. What is the difference between indexed and nominal debt?

say, a favorable technology shock: for a given drop in prices, output rises less with nominal debt than with indexed debt because of the negative deflation effect; however, output gap rises more with nominal debt than with indexed debt because, while in both cases downward price stickiness prevents aggregate demand from rising enough to meet the higher supply, debt-deflation implies that demand rises even less if debt is not indexed. 

Q14. What did the first attempt to estimate the capital adjustment cost of the housing stock mean?

Preliminary attempts to estimate these parameters (using the methods described in Section IV.C) led to estimates of the capital adjustment cost ψ around 2 and pushed the housing adjustment cost parameters φe and φh towards zero. 

Q15. What is the output drop in the solid line?

The solid line illustrates the case when both collateral and debt deflation effects are shut off, so that only the interest rate channel works (see Appendix B for the technical details): output falls by 3.33 percent. 

Q16. What is the effect of the drop in output in the model?

The drop in output is immediate in the model, while is delayed in the data, although the total output sacrifice is in line with the VAR estimate. 

Q17. What is the definition of a discrete time, infinite horizon economy?

Consider a discrete time, infinite horizon economy, populated by entrepreneurs and patient households, infinitely lived and of measure one.