Tài liệu The financial cycle and macroeconomics: What have we learnt? pdf

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Contents
Introduction 1
1. The financial cycle: core stylised features 2
1.1 Feature 1: it is most parsimoniously described in terms of credit and property
prices 2
1.2 Feature 2: it has a much lower frequency than the traditional business cycle 3
1.3 Feature 3: its peaks are closely associated with financial crises 4
1.4 Feature 4: it helps detect financial distress risks with a good lead in real time 5
1.5 Feature 5: its length and amplitude depend on policy regimes 6
2. The financial cycle: analytical challenges 8
2.1 Essential features that require modelling 8
2.2 How could this be done? 10
2.3 The importance of a monetary economy: an example 12
3. The financial cycle: policy challenges 13
3.1 Dealing with the boom 14
3.2 Dealing with the bust 16
4. Conclusion 23
References 25




1


Introduction
1

Understanding in economics does not proceed cumulatively. We do not necessarily know
more today than we did yesterday, tempting as it may be to believe otherwise. So-called
“lessons” are learnt, forgotten, re-learnt and forgotten again. Concepts rise to prominence
and fall into oblivion before possibly resurrecting. They do so because the economic
environment changes, sometimes slowly but profoundly, at other times suddenly and
violently. But they do so also because the discipline is not immune to fashions and fads. After
all, no walk of life is.
The notion of the financial cycle, and its role in macroeconomics, is no exception. The notion,
or at least that of financial booms followed by busts, actually predates the much more
common and influential one of the business cycle (eg, Zarnowitz (1992), Laidler (1999) and
Besomi (2006)). But for most of the postwar period it fell out of favour. It featured, more or
less prominently, only in the accounts of economists outside the mainstream (eg, Minsky
(1982) and Kindleberger (2000)). Indeed, financial factors in general progressively
disappeared from macroeconomists’ radar screen. Finance came to be seen effectively as a
veil – a factor that, as a first approximation, could be ignored when seeking to understand
business fluctuations (eg, Woodford (2003)). And when included at all, it would at most
enhance the persistence of the impact of economic shocks that buffet the economy, delaying
slightly its natural return to the steady state (eg, Bernanke et al (1999)).
What a difference a few years can make! The financial crisis that engulfed mature economies
in the late 2000s has prompted much soul searching. Economists are now trying hard to
incorporate financial factors into standard macroeconomic models. However, the prevailing,
in fact almost exclusive, strategy is a conservative one. It is to graft additional so-called
financial “frictions” on otherwise fully well behaved equilibrium macroeconomic models, built
on real-business-cycle foundations and augmented with nominal rigidities. The approach is
firmly anchored in the New Keynesian Dynamic Stochastic General Equilibrium (DSGE)
paradigm.
The purpose of this essay is to summarise what we think we have learnt about the financial
cycle over the last ten years or so in order to identify the most promising way forward. It
draws extensively on work carried out at the BIS, because understanding the nexus between
financial and business fluctuations has been a lodestar for the analytical and policy work of
the institution. As a result, the essay provides a very specific and personal perspective on the
issues, just one lens among many: it is not intended to survey the field.
The main thesis is that macroeconomics without the financial cycle is like Hamlet without the
Prince. In the environment that has prevailed for at least three decades now, just as in the
one that prevailed in the pre-WW2 years, it is simply not possible to understand business
fluctuations and their policy challenges without understanding the financial cycle. This calls
for a rethink of modelling strategies. And it calls for significant adjustments to
macroeconomic policies. Some of these adjustments are well under way, others are at an
early stage, yet others are hardly under consideration.

1
This essay is a slightly revised version of the one prepared for a keynote lecture at the Macroeconomic
Modelling Workshop, “Monetary policy after the crisis”, National Bank of Poland, Warsaw, 13-14 September
2012. I would like to thank Carlo Cottarelli, Piti Disyatat, Leonardo Gambacorta, Craig Hakkio, Otmar Issing,
Enisse Kharroubi, Anton Korinek, David Laidler, Robert Pringle, Vlad Sushko, Nikola Tarashev, Kostas
Tsatsaronis, Michael Woodford and Mark Wynne for helpful comments and Magdalena Erdem for excellent
statistical assistance. The views expressed are my own and do not necessarily reflect those of the Bank for
International Settlements.

2



Three themes run through the essay. Think medium term! The financial cycle is much longer
than the traditional business cycle. Think monetary! Modelling the financial cycle correctly,
rather than simply mimicking some of its features superficially, requires recognising fully the
fundamental monetary nature of our economies: the financial system does not just allocate,
but also generates, purchasing power, and has very much a life of its own. Think global! The
global economy, with its financial, product and input markets, is highly integrated.
Understanding economic developments and the challenges they pose calls for a top-down
and holistic perspective – one in which financial cycles interact, at times proceeding in sync,
at others proceeding at different speeds and in different phases across the globe.
The first section defines the financial cycle and highlights its core empirical features. The
second puts forward some conjectures about the elements necessary to model the financial
cycle satisfactorily. The final one explores the policy implications, discussing in turn how to
address the booms and the subsequent busts. The focus in the section is primarily on the
bust, as this is by far the less well explored and still more controversial area.
1. The financial cycle: core stylised features
There is no consensus on the definition of the financial cycle. In what follows, the term will
denote self-reinforcing interactions between perceptions of value and risk, attitudes towards
risk and financing constraints, which translate into booms followed by busts. These
interactions can amplify economic fluctuations and possibly lead to serious financial distress
and economic dislocations. This analytical definition is closely tied to the increasingly popular
concept of the “procyclicality” of the financial system (eg, Borio et al (2001), Danielsson et al
(2004), Kashyap and Stein (2004), Brunnermeier et al (2009), Adrian and Shin (2010)). It is
designed to be the most relevant one for macroeconomics and policymaking: hence the
focus on business fluctuations and financial crises.
The next question is how best to approximate empirically the financial cycle, so defined.
What follows considers, sequentially, the variables that can best capture it, its relationship
with the business cycle, its link with financial crises, its real-time predictive content for
financial distress, and its dependence on policy regimes.
1.1 Feature 1: it is most parsimoniously described in terms of credit and property
prices
Arguably, the most parsimonious description of the financial cycle is in terms of credit and
property prices (Drehmann et al (2012)). These variables tend to co-vary rather closely with
each other, especially at low frequencies, confirming the importance of credit in the financing
of construction and the purchase of property. In addition, the variability in the two series is
dominated by the low-frequency components. By contrast, equity prices can be a distraction.
They co-vary with the other two series far less. And much of their variability concentrates at
comparatively higher frequencies.
It is important to understand what this finding does and does not say. It is no doubt possible
to describe the financial cycle in other ways. At one end of the spectrum, like much of the
extant work, one could exclusively focus on credit – the credit cycle (eg, Aikman et al (2010),
Schularick and Taylor (2009), Jordá et al (2011), Dell’Arriccia et al (2012)). At the other end,
one could combine statistically a variety of financial price and quantity variables, so as to
extract their common components (eg, English et al (2005), Ng (2011), Hatzius et al (2011)).
Examples of the genre are interest rates, volatilities, risk premia, default rates, non-
performing loans, and so on. In between, studies have looked at the behaviour of credit and
asset prices series taken individually, among other variables (eg, Claessens et al (2011a,
2011b)).


3


That said, combining credit and property prices appears to be the most parsimonious way to
capture the core features of the link between the financial cycle, the business cycle and
financial crises (see below). Analytically, this is the smallest set of variables needed to
replicate adequately the mutually reinforcing interaction between financing constraints
(credit) and perceptions of value and risks (property prices). Empirically, there is a growing
literature documenting the information content of credit, as reviewed by Dell’Arricia et al
(2012), and property prices (eg, IMF (2003)) taken individually for business fluctuations and
systemic crises with serious macroeconomic dislocations. But it is the interaction between
these two sets of variables that has the highest information content (see below).
1.2 Feature 2: it has a much lower frequency than the traditional business cycle
The financial cycle has a much lower frequency than the traditional business cycle
(Drehmann et al (2012)). As traditionally measured, the business cycle involves frequencies
from 1 to 8 years: this is the range that statistical filters target when seeking to distinguish the
cyclical from the trend components in GDP. By contrast, the average length of the financial
cycle in a sample of seven industrialised countries since the 1960s has been around
16 years.
Graph 1, taken from Drehmann et al (2012), illustrates this point for the United States. The
blue line traces the financial cycle obtained by combining credit and property prices and
applying a statistical filter that targets frequencies between 8 and 30 years. The red line
measures the business cycle in GDP obtained by applying the corresponding filter for
frequencies up to 8 years, as normally done. Clearly, the financial cycle is much longer and
has a much greater amplitude. The greater length of the financial cycle emerges also if one
measures it based on Burns and Mitchell’s (1946) turning-point approach, as refined by
Harding and Pagan (2006). As the orange (peaks) and green (troughs) bars indicate, the
length is similar to that estimated through statistical filters, and the peaks and troughs are
remarkably close to those obtained with it.
Graph 1
The financial and business cycles in the United States

Orange and green bars indicate peaks and troughs of the financial cycle measured by the combined behaviour

of
the component series (credit, the credit to GDP ratio and house prices) using the turning
-point method.
The blue
line traces the financial cycle measured as
the average of the medium-
term cycle in the component series using
frequency
-based filters. The red line traces the GDP cycle identified by the traditional shorter-
term frequency filter
used to measure the business cycle.

Source: Drehmann et al (2012).


It might be objected that this result partly follows by construction. The filters used target
different frequencies. And Comin and Gertler (2006) have already shown, the importance of
the medium-term component of fluctuations exceeds that of the short-term component also
for GDP.

4



But interpreting the result in this way would be highly misleading (Drehmann et al (2012)).
The business cycle is still identified in the macroeconomic literature with short-term
fluctuations, up to 8 years. Moreover, the relative importance and amplitude of the medium-
term component is considerably larger for the joint behaviour of credit and property prices
than for GDP. And individual phases also differ between both cycles. The contraction phase
of the financial cycle lasts several years, while business cycle recessions generally do not
exceed one year. In fact, as discussed further below, failing to focus on the medium-term
behaviour of the series can have important policy implications.
1.3 Feature 3: its peaks are closely associated with financial crises
Peaks in the financial cycle are closely associated with systemic banking crises (henceforth
“financial crises” for short). In the sample of seven industrialised countries noted above, all
the financial crises with domestic origin (ie, those that do not stem from losses on cross-
border exposures) occur at, or close to, the peak of the financial cycle. And the financial
crises that occur away from peaks in domestic financial cycles reflect losses on exposures to
foreign such cycles. Typical examples are the banking strains in Germany and Switzerland
recently. Conversely, most financial cycle peaks coincide with financial crises. In fact, there
are only three instances post-1985 for which the peak was not close to a crisis, and in all of
them the financial system came under considerable stress (Germany in the early 2000s,
Australia and Norway in 2008/2009).
Graph 2, again taken from Drehmann et al (2012), illustrates this point for the Unites States
and United Kingdom. The black bars denote financial crises, as identified in well known data
bases (Laeven and Valencia (2008 and 2010), Reinhart and Rogoff (2009)) and modified by
the expert judgment of national authorities. One can see that the five crises occur quite close
to the peaks in the financial cycles. In all the cases shown, the crises had a domestic origin.
Graph 2
The financial cycle: frequency and turning-point based methods

United States

United Kingdom



Orange and green bars indicate peaks and troughs of the
financial cycle as measured by the combined
behaviour
of the component series (
credit, the credit to GDP ratio and house prices) using the turning-
point method. The
blue line traces the financial
cycle measured as the average of the medium-term cycle in
the component series
using f
requency based filters. Black vertical lines indicate the starting point fo
r banking crises, which in some
cases (United Kingdom 1976 and United States 2007) are hardly visible as they coincide with a peak in the cycle.

Source: Drehmann et al (2012).

The close association of the financial cycle with financial crises helps explain another
empirical regularity: recessions that coincide with the contraction phase of the financial cycle
are especially severe. On average, GDP drops by around 50% more than otherwise
(Drehmann et al (2012)). This qualitative relationship exists even if financial crises do not


5


break out, as also confirmed by other work, which either considers credit and asset prices
together (Borio and Lowe (2004) or focuses exclusively on credit (eg, Jordá et al (2011)).
2

1.4 Feature 4: it helps detect financial distress risks with a good lead in real time
The close link between the financial cycle and financial crises underlies the fourth empirical
feature: it is possible to measure the build-up of risk of financial crises in real time with fairly
good accuracy. Specifically, the most promising leading indicators of financial crises are
based on simultaneous positive deviations (or “gaps”) of the ratio of (private sector) credit-to-
GDP and asset prices, especially property prices, from historical norms (Borio and
Drehmann (2009), Alessi and Detken (2009)).
3
One can think of the credit gap as a rough
measure of leverage in the economy, providing an indirect indication of the loss absorption
capacity of the system; one can think of the property price gap as a rough measure of the
likelihood and size of the subsequent price reversal, which tests that absorption capacity.
The combination of the two variables provides a much cleaner signal – one with a lower
noise – than either variable considered in isolation.
Graph 3, taken from Borio and Drehmann (2009), illustrates the out-of-sample performance
of the corresponding leading indicator for the United States. Danger zones are shown as
shaded areas. The graph indicates that by the mid-2000s concrete signs of the build-up of
systemic risk were evident, as both the credit gap and property price gap were moving into
the danger zone. And as discussed there, the out-of-sample performance is quite good
across countries.
Graph 3
Estimated gaps for the United States
Credit
-to-GDP gap (percentage points)

Real property price gap (%)
1



The shaded areas refer to the threshold values for the indicators: 2
–6 percentage points for credit-to-
GDP gap;
15
–25% for real property price gap. The estimates for 2008 are based on partial data (up to the third quarter).
1

Weighted average of residential and commercial property prices with weights corresponding to estimates of
their share in overall property wealth. The legend refers to the residential property price component.

Source: Borio and
Drehmann (2009).

2
See also Eichengreen and Mitchener (2004), who find that credit and asset price booms exacerbated the
Great Depression, using similar indicators as Borio and Lowe (2002).
3
If a single variable has to be chosen, then the evidence indicates that credit is the most relevant one; see, eg,
Borio and Lowe (2002), Drehmann et al (2011) and Schularick and Taylor (2009). Drehmann and Juselius
(2012) find that over a one-year horizon, the debt-service ratio provides even more reliable signals. The credit
gap, by contrast, is superior over longer horizons, providing warnings further ahead.

6



In addition, there is growing evidence that the cross-border component of credit tends to
outgrow the purely domestic one during financial booms, especially those that precede
serious financial strains (Borio et al (2011), Avdjiev et al (2012)). This typically holds for the
direct component – in the form of lending granted directly to non-financial borrowers by
banks located abroad
4
– and for the indirect one – resulting from domestic banks’ borrowing
abroad and in turn on-lending to non-financial borrowers.
5
The reasons for this regularity are
not yet fully clear. One may simply be the natural tendency for wholesale funding to gain
ground as credit booms, which is then reflected in rising loan-to-deposit ratios.
6
But, as
discussed further below, no doubt more global forces influencing credit-supply conditions are
also at work (eg, Borio and Disyatat (2011), Shin (2011), Bruno and Shin (2011), CGFS
(2011)).
Graph 4, from Borio et al (2011), illustrates this feature for Thailand, ahead of Asian financial
crisis in the 1990s, and for the United States and United Kingdom, ahead of the recent
financial crisis. It shows the tendency for the direct (continuous blue line) and indirect
(included in the dashed blue lines) components of credit to grow faster than overall domestic
credit (red line) during such episodes. This is true regardless of the overall size of the direct
foreign component relative to the domestic one in the stock of credit (shaded areas).
1.5 Feature 5: its length and amplitude depend on policy regimes
The length and amplitude of the financial cycle are no constants of nature, of course; they
depend on the policy regimes in place.
7
Three factors seem to be especially important: the
financial regime, the monetary regime and the real-economy regime (Borio and Lowe (2002),
Borio (2007)). Financial liberalisation weakens financing constraints, supporting the full self-
reinforcing interplay between perceptions of value and risk, risk attitudes and funding
conditions. A monetary policy regime narrowly focused on controlling near-term inflation
removes the need to tighten policy when financial booms take hold against the backdrop of
low and stable inflation. And major positive supply side developments, such as those
associated with the globalisation of the real side of the economy, provide plenty of fuel for
financial booms: they raise growth potential and hence the scope for credit and asset price
booms while at the same time putting downward pressure on inflation, thereby constraining
the room for monetary policy tightening.


4
Importantly, but rarely appreciated, the commonly used monetary statistics do not capture this component
(Borio et al (2011)).
5
For a detailed description of the stylised facts associated with credit booms combining both macro and micro
data and comparing industrial and emerging market economies, see Mendoza and Terrones (2008); for a
recent survey, Dell’ Arriccia et al (2012).
6
Why this tendency (Borio and Lowe (2004))? Recall that credit and asset price booms reinforce each other, as
collateral values and leverage increase. As a result, credit tends to grow fast alongside asset prices. By
contrast, opposing forces work on the relationship between money (deposits) and asset prices. Increases in
wealth tend to raise the demand for money (wealth effect). However, higher expected returns on risky assets,
such as equity and real estate, as well as a greater appetite for risk, induce a shift away from money towards
riskier assets (substitution effect). This restrains the rise in the demand for money relative to the expansion in
credit. See also Shin (2011) for an emphasis on the role of non-core (wholesale) deposits.
7
This underlines a critical point: the financial cycle as defined in this essay should not be considered a
recurrent, regular feature of the economy, which inevitably unfolds in a specific way (ie, a regular and
stationary process). Rather, it is a tendency for a set of variables to evolve in a specific way responding to the
economic environment and policies within it. The key to this cycle is that the boom sets the basis for, or
causes, the subsequent bust.


7


Graph 4
Credit booms and external credit: selected countries
Thailand in the 1990s

United Kingdom

United States
In billions of US dollars





Thailand in the 1990s

United Kingdom

United States
Year-on-year growth, in per cent





The vertical lines indicate crisis episodes end
-July 1997 for Thailand and end-Q2 2007 and end-
Q3 2008 for the
United States and the United Kingdom. For details on the construction of the various credit components, see
Borio et al (2011).

1
Estimate of credit to the private non-
financial sector granted by banks from offices located outside the
country.

2
Estimate of credit as in footnote (1) plus cross-
border borrowing by banks located in the
country.

3
Estimate as in footnote (2) minus credit to non-residents granted by banks located in the country.
Source: Borio et al (2011).

The empirical evidence is consistent with this analysis. As Graph 1 indicates, the length and
amplitude of the financial cycle has increased markedly since the mid-1980s, a good
approximation for the start of the financial liberalisation phase in mature economies (Borio
and White (2003)).
8
This date is also an approximate proxy for the establishment of monetary
regimes more successful in controlling inflation. And the cycle appears to have become
especially large and prolonged since the 1990s, following the entry of China and other former
communist countries into the global trading system. By contrast, prior to the mid-1980s in,
say, the United States the financial and traditional business cycles are quite similar in length

8
Indeed, the link between financial liberalisation and credit booms is one of the best established regularities in
the literature, drawing in particular on the experience of emerging market economies. It was already evident
following the experience of liberalisation in the Southern Cone countries of Latin America in the 1970s (eg,
Diaz-Alejandro (1985), Baliño (1987)).

8



and amplitude (left-hand panel). In fact, across the seven economies covered in Drehmann
et al (2012), the average length of the financial cycle is 16 years over the whole sample; but
for cycles that peaked after 1998, the average duration is nearly 20 years, compared with 11
for previous ones.
Moreover, it is no coincidence that the only significant financial cycle ending in a financial
crisis pre-1985 took place in the United Kingdom, following a phase of financial liberalisation
in the early 1970s (Competition and Credit Control). That this was also a period of high
inflation indicates that financial liberalisation, by itself, is quite capable of generating sizeable
financial cycles. That said, in those days the rise in inflation and/or the deterioration of the
balance of payments that tended to accompany economic expansions would inevitably
quickly call for a policy tightening, constraining the cycle compared with the policy regimes
that followed.
9

2. The financial cycle: analytical challenges
A systematic modelling of the financial cycle should be capable of accommodating the
stylised facts just described. This raises first-order analytical challenges. What follows
considers three basic features that satisfactory models should be able to replicate and then
makes some conjectures about what strategies could be followed to do this.
2.1 Essential features that require modelling
The first feature is that the financial boom should not just precede the bust but cause it. The
boom sows the seeds of the subsequent bust, as a result of the vulnerabilities that build up
during this phase. This perspective is closer to the prewar prevailing view of business
fluctuations, seen as the result of endogenous forces that perpetuate (irregular) cycles. It is
harder to reconcile with today’s dominant view of business fluctuations, harking back to
Frisch (1933), which sees them as the result of random exogenous shocks transmitted to the
economy by propagation mechanisms inherent in the economic structure (Borio et al
(2001)).
10
And it is especially hard to reconcile with the approaches grafted on the real-
business-cycle tradition, in which in the absence of persistent shocks the economy rapidly
returns to steady state. In this case, much of the persistence in the behaviour of the economy
is driven by the persistence of the shocks themselves (eg, Christiano et al (2005), Smets and
Wouters (2003)). Arguably, since shocks can be regarded as a measure of our ignorance,
rather than of our understanding, this approach leaves much of the behaviour of the
economy unexplained.
The second feature is the presence of debt and capital stock overhangs (disequilibrium
excess stocks). During the financial boom, credit plays a facilitating role, as the weakening of
financing constraints allows expenditures to take place and assets to be purchased. This in
turn leads to misallocation of resources, notably capital but also labour, typically masked by
the veneer of a seemingly robust economy. However, as the boom turns to bust, and asset
prices and cash flows fall, debt becomes a forcing variable, as economic agents cut their

9
In addition, it is no coincidence that financial booms and busts of this kind were quite common during the gold
standard, all the way up to the 1930s. This was the previous time in history in which a liberalised financial
system coincided with a monetary regime that yielded a reasonable degree of price stability over longer
horizon. See Goodhart and De Largy (1999) and Borio and Lowe (2002) for a discussion of these issues and
for evidence.
10
See, in particular, Zarnowitz (1992) for a historical review of the business cycle literature. Of course, unless
one is prepared to endogenise everything and shift to a deterministic world, shocks will inevitably play a role.