Download This PDF is a selection from a published volume from... of Economic Research Volume Title: NBER International Seminar on Macroeconomics 2012

This PDF is a selection from a published volume from the National Bureau
of Economic Research
Volume Title: NBER International Seminar on Macroeconomics 2012
Volume Author/Editor: Francesco Giavazzi and Kenneth D. West,
organizers
Volume Publisher: University of Chicago Press
Volume ISBN: 978-0-226-05313-4 cloth; 978-0-226-05327-1 paper;
0-226-05327-X paper
Volume URL: http://www.nber.org/books/giav12-1
Conference Date: June 15-16, 2012
Publication Date: August 2013
Chapter Title: Comment on "Global House Price Fluctuations:
Synchronization and Determinants"
Chapter Author(s): Kirstin Hubrich
Chapter URL: http://www.nber.org/chapters/c12772
Chapter pages in book: (p. 167 - 173)
Comment
Kirstin Hubrich, Research Department, European Central Bank
I.
Introduction
The housing boom preceding the recent financial crisis has led to a renewed interest in the role of the housing market developments. In particular, the large fluctuations in house prices in the United States, but
also in other countries, motivate a number of recent studies. An early,
leading theoretical paper is Iacoviello (2005), who shows the importance of collateral effects for consumption responses to house prices.
Recent empirical contributions that study the housing market include
Claessens, Kose, and Terrones (2012), Feroli et al. (2012), Moench and
Ng (2011), and Stock and Watson (2009), among others.
This paper addresses two important issues: First, it investigates how
synchronized housing cycles are across countries. Second, it analyzes
the main shocks driving movements in global house prices.
The authors use a broad range of different measures of synchronization of house prices to address the first question. They find a high degree
of synchronization of house prices on a global level, also documented
by the authors, finding that 20 to 35% (depending on the period) of the
variation in house prices is explained by a global house price factor.
To address the second question, the authors identify and investigate
the global shocks driving house prices, including interest rate shocks,
monetary policy, productivity, credit, and uncertainty shocks. They find
that interest rate shocks identified based on a recursive identification
scheme do have a significant negative effect on house prices, but global
monetary policy shocks (identified by sign restrictions) do not have
a sizable impact. The latter analysis is carried out in a FAVAR model
framework in which the authors analyze global shocks that explain
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168
Hubrich
house price developments. The authors also find no significant influence of productivity and credit shocks, but an important impact of an
uncertainty shock. The paper provides interesting new insights in the
extent of synchronization of global house price developments and their
determination. It also outlines interesting avenues of further research.
There are three issues for further research that are worth mentioning
in this discussion, but that I will not discuss in detail: First, for further
research it would be desirable to examine the relative importance of
the different shocks affecting house prices considered in this paper in
one large nesting model. As the authors state, that gives rise to methodological challenges. It might be worthwhile to address these challenges
in extensions of the FAVAR framework in future research. Second,
it will be of interest to investigate what is behind the heterogeneous
impact of shocks across countries and the structural and institutional
factors driving those differences, as the authors note in their conclusion. Third, it should be noted that the authors base their conclusion
regarding the role of monetary policy in driving house prices on the
unexpected interest rates and monetary policy shocks identified in their
analysis. The role of systematic monetary policy changes might also be
of relevance in this context and constitutes an interesting direction for
further research.
In my comment I will in particular focus on further future avenues
of research that address some caveats of the present analysis and discuss some related literature. In particular, I will highlight the role of
episodic time variation and nonlinearities investigating house price developments.
II.
Globalization, Great Moderation, and Episodic Time Variation
in House Prices
The sample period covered in the paper is 1971:1 to 2011:3. To account
for possible time variation in how shocks affect house price developments, the authors’ investigation splits the sample into two subperiods: 1971:1 to 1984:4 and 1985:1 to 2011:3, where the former period is
referred to as preglobalization and the latter as globalization period.
The globalization period covers what is usually referred to as the Great
Moderation, but it also includes the recent crisis period. Therefore, the
authors have also carried out some robustness analysis by excluding
the recent crisis period and concluding the sample in 2007:2. This is
an important part of the analysis since the transmission of shocks for
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Comment
169
the crisis period might have been quantitatively and qualitatively very
different, thereby covering some other transmission mechanism during the time before the crisis. The exclusion of the recent crisis does not
change their main results.
Related literature has also shed light on the time variation in the relations between house prices and other macro and financial variables.
For instance, Muellbauer and Murphy (1997) provide evidence for
shifts in house prices due to real wealth effects, among others, for an
early sample period. Hubrich et al. (2013) investigate the response of
house prices to shocks in a time-varying parameter vector autoregressive model. They find that the response of house prices to real shocks
is stronger in times of house price peaks, but still small overall. This
confirms for one of the shocks the results from the linear model of the
authors (although their real shock is based on a different identification
scheme). This is important, since an impulse response from a linear
model might hide very different impacts in some periods.
III.
Uncertainty, House Prices, and the Macroeconomy: A Role
for Nonlinearities
An important issue are potential nonlinearities in the relation between
house prices and other financial and macroeconomic variables. Nonlinearities might be expected in the relation between house prices, credit,
and the real economy, as the authors mention, but also in connection
with uncertainty. Periods of high uncertainty in stock prices as reflected
in the VIX that the authors use to measure uncertainty, are more generally associated with periods of high financial stress. This can be seen in
figure 1, that depicts the financial stress indicator that was used at the
Federal Reserve Board during the recent financial crisis, together with
the Volatility Index (VIX). Financial stress indices (FSI) generally are
built based on volatilities and risk spreads of bond and equity markets,
like the one presented here, and sometimes also include indicators from
the banking sector. The idea is to capture potential instabilities in a wide
range of financial markets. The VIX, measuring stock market volatility,
is often used as a global measure of uncertainty (see, e.g., Bloom 2009).
As can be seen, the FSI and the VIX have a broadly related dynamic
pattern. Even though the FSI often indicates a somewhat higher level of
financial stress and deviates in some periods from the VIX, both indices
exhibit peaks in periods of pronounced financial stress.
One main and noteworthy finding of the present paper is the impor-
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170
Hubrich
Fig. 1. Financial stress indicator and VIX
Sources: Federal Reserve Board; see also Hubrich and Tetlow (2012).
tance of the “uncertainty shock” for global house price developments.
The authors of this paper proceed their investigation within a linear
model framework while acknowledging that nonlinearities might play
a role. Indeed, they point to the development of models that allow for
nonlinear feedback effects between policy choices and the interaction
between the real economy, housing sector, and financial markets as one
important avenue of future research. Also, they indicate the relevance
of studying certain episodes in times of pronounced cycles in credit and
housing markets that is related to the issue of nonlinearities mentioned.
In the remainder of my discussion, I will emphasize the importance of
taking into account nonlinearities and provide some empirical evidence
for nonlinearities in a related context.
In particular, in the context of examining the influence of an uncertainty shock, its relation to house prices, and the interaction with GDP
growth, inflation, and interest rates, nonlinearities might be important.
The impact of an uncertainty shock might be quite different in episodes
of high uncertainty in comparison to normal times. As argued in Hubrich and Tetlow (2012), the reason that nonlinearities might be expected in the relation between the financial sector and the real economy
is that in episodes of high financial stress a more pronounced feedback
between the financial sector and the real side of the economy might
arise. Borrowers’ balance sheet deterioration might lead to a change in
agents’ attitudes toward risk. Increased risk aversion and uncertainty
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Comment
171
impedes borrower–lender relationships inducing credit rationing, and
amplification effects in high financial stress episodes are caused by leverage and feedback effects from asset prices. The evidence of nonlinearities presented in Hubrich and Tetlow (2012) also has implications
for the developments of house prices. Borrowers’ balance sheet deterioration will affect the net worth of the borrower that is eligible as
collateral. Credit rationing also affects the ability of the borrower to
raise money for house purchases. Prior to the recent crisis, an increase
in uncertainty also meant higher demand for relatively safer assets like
housing.
Two sources of nonlinearities might be relevant in the context of the
interaction between the macroeconomy and house prices: there could
be nonlinearities in the shocks (i.e., the volatility of the shocks might be
very different in some periods than in others), or nonlinearities in the
transmission of those shocks through the economy. One way to address
both modeling nonlinear feedback effects and the episodic nature of
shock transmission in certain phases of the cycle, or associated with
higher uncertainty in stock prices or financial markets in general, is to
estimate a Markov-switching vector autoregressive model.
In a study that investigates more broadly the relation between financial instability and macroeconomic dynamics, Hubrich and Tetlow
(2012) analyze the interaction of financial stress with output growth, inflation, and monetary policy. They estimate a Markov-switching model
with recently developed Bayesian estimation techniques and investigate the question whether it is only the shocks that have changed in episodes of high financial stress, or also the transmission of shocks through
the economy. Hubrich and Tetlow (2012) provide evidence that financial
stress transmits differently to the real economy in high stress than in
normal, more tranquil times. They find evidence that the transmission
of shocks changes in high financial stress episodes, and not only the
volatility of the shocks. Figure 2 presents impulse response functions
from one of the models investigated in the work underlying Hubrich
and Tetlow (2012) to illustrate their findings. The impulse responses are
conditional on the regime that was in place at the time of the shock to
persist. The figure shows that the effect of financial stress on the real
economy is much larger and much more protracted in episodes of high
stress than in normal times. They also investigate via counterfactuals
how the economy would have developed in certain periods of interest if the economy would have remained in normal times rather than
switching to a high stress regime. Their analysis provides evidence of
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172
Hubrich
Fig. 2.
Impulse response of output growth to positive financial stress shock
an economically plausible different reaction of the real economy, monetary policy, and inflation in high stress episodes.
As explained earlier, this evidence of nonlinearities in the broader
context of financial instability and macroeconomic dynamics is of relevance for conclusions for the transmission of shocks to house prices
via the collateral channel and credit constraints. Further research along
those lines promises to provide interesting insights.
IV.
Conclusion
Overall, the paper offers a large set of interesting new empirical insights on the synchronization and determinants of global house price
fluctuations, an area of research highly relevant in light of the recent
crisis. A lot can still be learned on how national policies, regulations,
and institutional frameworks influence synchronization and differences
in house prices across countries that is beyond the scope of this paper.
In this comment I have highlighted that investigating nonlinearities in
feedback effects between the housing sector, the financial sector, and the
macroeconomy is an important line of further research.
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Comment
173
Endnote
The views expressed in this comment are those of the author and do not necessarily
reflect those of the European Central Bank. The author can be contacted at kirstin.hubrich
@ecb.int. For acknowledgments, sources of research support, and disclosure of the author’s material financial relationships, if any, please see http: // www.nber.org / chapters
/ c12772.ack.
References
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