Download financial liberalization

financial liberalization
Abstract
Financial liberalization has led to financial deepening and higher growth in several
countries. However, it has also led to a greater incidence of financial crises. Here, we
review the empirical evidence on these dual effects of financial liberalization across
different groups of countries. We then present a conceptual framework that explains
why there is a trade-off between growth and incidence of crisis, and helps account
for the cross-country difference in the effects of financial liberalization.
Keywords
bail-out guarantees; banking crises; boom–bust cycles; capital account liberalization;
contract enforceability; credit growth; currency crises; economic growth; equity
market liberalization; financial liberalization; financial openness; foreign direct
investment; India; insolvency risk; international flows; investment; investment
subsidies; lending booms; portfolio flows; probit models; prudential regulation;
skewness; Thailand; tradable and non-tradable Sectors; trade liberalization
JEL classifications
F3; F4
Article
Financial liberalization (FL) refers to the deregulation of domestic financial markets
and the liberalization of the capital account. The effects of FL have been a matter of
some debate. In one view, it strengthens financial development and contributes to
higher long-run growth. In another view, it induces excessive risk-taking, increases
macroeconomic volatility and leads to more frequent crises. This article brings
together these two opposing views.
The data reveals that FL leads to more rapid economic growth in middle-income
countries (MICs), but does not have the same effect in low-income countries (LICs). In
MICs this process is not smooth, however: It takes place through booms and busts.
Indeed, MICs that have experienced occasional financial crises have grown faster, on
average, than non-liberalized countries with stable credit conditions. In LICs liberalization
does not lead to higher growth because their financial systems are not sufficiently
developed so as to permit significant increases in leverage and financial flows.
The contrasting experiences of Thailand and India illustrate these dual effects.
Thailand, a liberalized economy, has experienced lending booms and crises, while India, a
non-liberalized economy, has followed a slow but safe growth path (see Figure 1). In India
GDP per capita grew by only 99 per cent between 1980 and 2002, whereas Thailand’s
GDP per capita grew by 148 per cent, despite a major crisis. As will be shown below in a
set of data analyses, this trade-off exists more generally across MICs.
1
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Romain Rancière and Aaron Tornell and Frank Westermann
From The New Palgrave Dictionary of Economics, Second Edition, 2008
Edited by Steven N. Durlauf and Lawrence E. Blume
Real credit
14
12
Real per capita GDP
2.8
India
Thailand
10
India
Thailand
2.4
2.0
8
4
1.6
1.2
2
0
80 82 84 86 88 90 92 94 96 98 00 02
0.8
80 82 84 86 88 90 92 94 96 98 00 02
Figure 1 Safe vs. risky growth path: a comparison of India and Thailand,
1980–2002. Note: The values for 1980 are normalized to 1. Sources: International
Financial Statistics (IMF) and Word Bank Development Indicators.
Asymmetric financial opportunities across sectors are key to understanding the
effects of FL. In particular, in MICs contract enforceability problems affect the
tradable (T) and non-tradable (N) sectors differently. Many T-sector firms are able to
overcome these problems and gain access to international capital markets, whereas
most N-sector firms are financially constrained and depend on domestic banks for
their financing. Trade liberalization promotes faster productivity growth in the Tsector, but is of little direct help to the N-sector. By allowing banks to borrow on
international capital markets, FL leads to an increase in investment by financially
constrained firms, most of which are in the N-sector. However, while FL increases
investment, it also increases borrowers’ incentives to take on insolvency risk because
there are implicit and explicit bail-out guarantees that cover lenders against systemic
defaults. This is why greater leverage and growth is associated with aggregate
financial fragility and occasional crises.
In the rest of this article we describe the ways in which FL has been measured
and the empirical estimates of its effects on growth and crises. We then present a
conceptual framework and a review of the policy issues. In a nutshell, any evaluation
of FL must weigh its benefits against its costs. Focusing exclusively on the growth
effects of liberalization during good times would miss the link between FL and
crises. Focusing only on volatility and crises could lead to an excessive cautiousness
about the risks of FL. The case for FL requires that its growth and welfare benefits
outweigh the costs associated with more frequent financial crises.
Measuring financial liberalization
There are three classes of FL indices. First, there are de jure indices based on official
dates of policy reforms. An example is the index based on the IMF Annual Report on
Exchange Arrangements and Exchange Restrictions (Grilli and Milesi-Ferretti, 1995).
This class of indices permits a comparison of the periods before and after liberalization.
A drawback, however, is that legislated changes take time to translate into liberalization
on the ground. Liberalization may even fail to materialize altogether when wellfunctioning domestic financial markets are absent. Bekaert, Harvey and Lundblad
(BHL, 2005) overcome this problem by constructing a de jure indicator of equity market
liberalization that records the date after which foreign investors are able to invest in
domestic securities. A second class of indices uses de facto measures of financial
openness, like the capital flows–GDP ratio used by Edison et al. (2004). The drawback
is that these measures are contaminated by cyclical fluctuations and thus are imprecise
indicators for dating FL. Lastly, de facto indices identify structural breaks in the trend of
2
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6
capital inflows (Tornell, Westermann and Martinez TWM, 2003). These indices
combine the advantages of the two previous classes as they provide more precise FL
dates based on actual, rather than merely legislated, policy reforms.
BHL (2005) find that equity market liberalization leads to an increase of one
percentage point in average real per-capita GDP growth. Rancière, Tornell and
Westermann (RTW, 2005) find that capital account liberalization leads to a similar
gain in growth. To illustrate the link between FL and growth we add liberalization
dummies to a standard growth regression:
Δyit ¼ λyi;ini þ γXit þ ϕ1 TLit þ ϕ2 FLit þ εjt ;
ð1Þ
where Δyit is the average growth rate of GDP per capita; yi,ini is the initial level of
GDP per capita; Xit is a vector of control variables that includes initial human
capital, the average population growth rate, and life expectancy; and TLit and FLit are
the trade and financial liberalization dummies of TWM (2003), respectively. For
each country and each variable, we construct ten-year averages starting with the
period 1980–9 and rolling forward to the period 1990–9. Thus each country has up
to ten data points in the time-series dimension. The liberalization dummies take
values in the interval [0,1], depending on the proportion of liberalized years in a
given window. We estimate the panel regressions using generalized least squares.
The FL dummy enters significantly at the five percent level in all regressions.
Regression 1-1 of Table 1 shows that following FL growth in real GDP per-capita
increases by 1.5 percentage points per year, after controlling for the standard
variables. Trade liberalization increases growth by 0.8 percent per year (column 1-2).
When both liberalization dummies are included (column 1–3), both enter
significantly. This suggests that trade and financial liberalization have independent
effects and jointly contribute to higher long-run growth.
Table 1 Regressions explaining growth in GDP per capita, 1980–99a
Independent variablea
Mean of real credit
growth rate
Standard deviation of
real credit growth rate
Negative skewness of real
credit growth rate
Financial liberalization
Trade liberalization
Summary statistics:
Adjusted R2
No. of observations
1–1
1–2
1.530c
(0.191)
0.793c
(0.152)
1–3
1.443c
(0.221)
0.776c
(0.196)
1–4
1–5b
1–6
1–7b
0.154c
(0.009)
–0.030c
(0.003)
0.266c
(0.021)
0.170c
(0.012)
–0.029c
(0.007)
0.174c
(0.069)
0.110c
(0.009)
–0.019c
(0.004)
0.135c
(0.031)
1.811c
(0.163)
0.895c
(0.198)
0.093c
(0.007)
–0.014c
(0.003)
–0.095c
(0.053)
1.894c
(0.122)
0.838c
(0.155)
0.848
0.897
0.807
0.629
0.667
0.731
0.752
409
430
408
424
269
408
253
Notes: aThe estimated equations are eqs. (1) and (2) in the text; the dependent variable is the average
annual growth rate of real GDP per capita. Control variables include initial per capita income,
secondary schooling, population growth, and life expectancy. Standard errors are reported in
parentheses and are adjusted for heteroskedasticity according to Newey and West (1987).
b
This regression includes the group of middle-income countries only.
c
Significance at the 5% level. The equation is estimated in an overlapping panel regression by GLS
with data as ten-year averages starting with 1980–9 and rolling forward to 1990–9.
Source: Authors’ regressions.
3
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Financial liberalization and growth
5
3.93
4
3.10
2.98
3
2.92
2.17
2
1.96
0.91
1
1.89
1.71
1.40
0.90
0.47
0.21
0.72
0.22
0.02
0.01
0.00
0
-0.24
-0.33
-0.48
-1
2.09
1.86
1.79
1.69
-0.81
-0.89
-0.99
-1.12
-1.32
-1.31
-1.10
-1.36 -1.33
-1.72
-2
-2.17
-2.20
-2.54
-3
-2.60
-2.81
-3.25
open
closed
-4
-4.37
TUR
VEN
TUN
SPA
THA
PRT
SOU
POL
PER
PHL
PAK
MYS
MOR
LKA
MEX
KOR
ISR
JOR
IRL
IND
IDN
GRC
COL
EGY
CHL
CHN
BRA
BGD
ARG
-5
Figure 2 Liberalization and annual percent growth. Note: The country episodes are
constructed using windows of different length for each country. Country episodes
that are shorter than five years are excluded. Averaging over these periods, we
estimate a simple growth regression by OLS in which real per capita growth is the
dependent variable and which only includes the respective initial income and
population growth. The figure plots the residuals from this regression, from 1980 to
1999. Sources: Population growth for Portugal: International Financial Statistics
(IMF). All other series: World Bank Development Indicators.
Several studies find mixed evidence on the link between financial openness and
growth. This can be attributed either to the indicators of openness used or to the
sample considered. First, some studies include low-income countries that do not have
functioning financial markets. In these countries we do not expect the financial
deepening mechanism to work. One might also expect the growth effect of FL to be
smaller in high-income than in middle-income countries as the latter face more
severe borrowing constraints. Hence, sample heterogeneity can create a bias against
finding a linear growth effect of FL. Klein (2005) finds that FL contributes to growth
among MICs but not among poor or rich countries. Second, some studies test the
effect of changes in the capital flows–GDP ratio on growth. However, because this
index does not identify a specific liberalization date, it is not appropriate for
comparing the behaviour of macroeconomic variables before and after liberalization.
Furthermore, these measures tend to exhibit year-to-year fluctuations that do not
reflect actual changes in the degree financial openness.
4
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Figure 2 illustrates the link between FL and growth for individual MICs. For
each country, we plot growth residuals before and after FL. Growth residuals are
obtained by regressing real per capita growth on initial income per capita and
population growth. Figure 2 shows clearly that for almost all countries growth has
been higher in the financially liberalized period.
FL is typically followed by boom–bust cycles. During the boom, bank credit expands
very rapidly and excessive credit risk is undertaken. As a result, the economy becomes
financially fragile and prone to crisis. Although the likelihood that a lending boom
will crash in a given year is low, many booms do eventually end in a crisis. During
such a crisis, new credit falls abruptly and recuperates only gradually.
The incidence of crises can be measured by analysing countries’ financial
histories and by codifying the occurrence of banking crises, currency crises, and
sudden stops in capital inflows. Kaminsky and Reinhart (1999) use such a crisis
index in a probit model to test whether banking and currency crises are crises are
more likely to occur after FL.
RTW (2005) use a more parsimonious indicator of financial fragility: the negative
skewness of credit growth. Negative skewness is a de facto indicator that captures the
existence of infrequent, sharp and abrupt falls in credit growth. Since credit growth is
relatively smooth during boom periods, and crises happen only occasionally, in
financially fragile countries the distribution of credit growth rates is characterized by
negative outliers in a long enough sample. These outliers correspond to the abrupt falls
in credit growth that occur during the crisis or ‘bust’ stage of the boom–bust cycle.
The advantages of this skewness measure, relative to other more complex indicators of
crises, are that it is objective and comparable across countries.
In the literature variance is the typical measure of volatility. Variance, however,
is not a good instrument to identify growth-enhancing credit risk because high
variance reflects not only the presence of boom–bust cycles but also the presence of
high-frequency shocks.
Table 2 partitions country-years into two groups: liberalized and non-liberalized.
The table shows that, across MICs, the financial deepening induced by FL has not
been a smooth process but has been characterized by booms and occasional busts.
We can see that FL leads to an increase in the mean of credit growth of four
percentage points (from 3.8 percent to 7.8 percent) and a fall in the skewness of
credit growth from near zero to –1.09, and has only a negligible effect on the
variance of credit growth. Notice that, across high-income countries, credit growth
exhibits near-zero skewness, and both the mean and the variance are smaller than
across MICs. This difference reflects the absence of severe credit market
imperfections in high-income countries.
Table 2 Moments of credit growth before and after financial liberalization
Moment
MICs
Mean
Standard deviation
Skewness
HICs
Mean
Standard deviation
Skewness
Liberalized country-years
0.078
0.151
–1.086
0.025
0.045
0.497
Non-liberalized country-years
0.038
0.170
0.165
...
...
...
Note: The sample is partitioned into two country-year groups: liberalized and non-liberalized. Before
the standard deviation and skewness are calculated, the means are removed from the series and data
errors for Belgium, New Zealand and the United Kingdom are corrected for. The total sample ranges
from 1980 to 1999.
Source: Authors’ calculations.
5
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Financial liberalization and crises
Growth and crises
Δyit ¼ λyi;ini þ γXit þ β 1 μΔB;it þ β 2 σΔB;it þ β 3 SΔB;it þ ϕ1 TLit þ ϕ2 FLit þ εjt ; ð2Þ
where Δyit, yi,ini, Xit, TLit, and FLit are defined as in eq. (1), and μΔB,it, σΔB,it, and
SΔB,it are the mean, standard deviation, and skewness of the real credit growth rate,
respectively. We estimate eq. (2) using the same type of overlapping panel data
regression as for eq. (1). Columns 1-4 through 1-7 of Table 1 report the estimation
results. Consistent with the literature, we find that, after controlling for the standard
variables, the mean growth rate of credit has a positive effect on long-run GDP
growth, and the variance of credit growth has a negative effect. Both variables enter
significantly at the five percent level in all regressions.
The first key point is that the financial deepening that accompanies rapid GDP
growth is not smooth but, rather, takes place via booms and busts. Columns 1-4 and
1-5 show that negative skewness – a bumpier growth path – is on average associated
with faster GDP growth across countries with functioning financial markets. This
estimate is significant at the five percent level.
To interpret the estimate of 0.27 for skewness, consider India, which has nearzero skewness, and Thailand, which has a skewness of about minus 2. A point
estimate of 0.27 implies that an increase in the bumpiness index of 2 (from zero to
minus 2) increases the average long-run GDP growth rate by 0.54 of a percentage
point a year. Is this estimate economically meaningful? To address this question, note
that, after controlling for the standard variables, Thailand grows about two percentage
points faster per year than India. Thus, about a quarter of this growth differential can
be attributed to credit risk taking, as measured by the skewness of credit growth.
The second key point is that the association between skewness and growth does
not imply that crises are good for growth. Crises are costly. They are the price that
has to be paid in order to attain faster growth in the presence of credit market
imperfections. To see this, consider column 1-6. When the FL dummy is included,
bumpiness enters with a negative sign (and is significant at the five percent level). In
the MIC set, given that there is FL, the lower the incidence of crises the better. We
can see the same pattern when we include high-income countries in column 1-7.
Clearly, liberalization without fragility is best, but the data suggest that this
combination is not available to MICs. Instead, the existence of contract enforceability
problems implies that liberalization leads to higher growth because it eases financial
constraints but, as a by-product, also induces financial fragility. However, because
crises occur relatively rarely, FL has a positive net effect on long-run growth.
A unified approach
An alternative approach to understand the contrasting effects of FL is to combine the
linear growth regression with a crisis probit model. In this way one can decompose
the net effect of FL into a direct pro-growth effect and an indirect anti-growth effect,
via a higher propensity to crises. Using this approach, RTW (2006) find that the
direct effect of FL on growth is 1.2 percentage points and the indirect effect is minus
0.25 percentage points. In order to understand this result, one should keep in mind
that even in financially liberalized countries crises are rare events. Therefore, even if
6
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To close the circle we show that countries with a greater incidence of crises countries
have grown faster than those with smooth credit paths. We do so by adding three
moments of real credit growth to growth regression (1)
crises have large output consequences, their estimated growth effect remains modest.
In contrast, since FL is likely to improve access to external finance, it has a firstorder impact on growth.
To analyze FL and the subsequent boom–bust cycles, consider an economy with two
sectors: non-tradables (N) and tradables (T). Alternatively, one can think of ‘neweconomy’ and ‘traditional’ sectors, respectively. The key is that each sector uses as
input the other sector’s output.
This economy is subject to severe contract enforceability problems that generate
financing constraints. While T-firms can overcome such constraints and finance
themselves in bond and equity markets, most N-firms are financially constrained and
bank-dependent. Since N-goods serve as intermediate inputs for both sectors, the
N-sector constrains the long-run growth of the T-sector and that of GDP: there is a
bottleneck.
In such an economy, FL increases GDP growth by increasing the investment of
financially constrained firms. However, the easing of financial constraints is
associated with the undertaking of insolvency risk because FL not only lifts
restrictions that preclude risk taking but also is associated with explicit and implicit
systemic bail-out guarantees that cover creditors against systemic crises.
It is a stylized fact that, if a critical mass of borrowers is on the brink of
bankruptcy, authorities will implement policies to ensure that creditors get repaid (at
least in part) and thus avoid an economic meltdown. These bail-out policies may
come in the form of an easing of monetary policy in response to a financial crash,
the defence of an exchange rate peg in the presence of liabilities denominated in
foreign currency, or the recapitalization of the financial sector.
Because domestic banks have been the prime beneficiaries of these guarantees,
investors use domestic banks to channel resources to firms that cannot pledge
international collateral. Thus liberalization results in biased capital inflows. T-firms
and large N-firms are the recipients of foreign direct investment (FDI) and portfolio
flows, whereas most of the inflows to the N-sector are intermediated through
domestic banks, which enjoy bail-out guarantees. Insolvency risk often takes the
form of maturity mismatch or risky debt denomination (currency mismatch).
Taking on insolvency risk reduces expected debt repayments because authorities
will cover part of the debt obligation in the event of a systemic crisis. Thus the
guarantee allows financially constrained firms to borrow more than they could
otherwise. This increase in borrowing and investment is accompanied by an increase
in insolvency risk. When many firms take on insolvency risk, aggregate financial
fragility arises together with increased N-sector investment and growth. Faster Nsector growth then helps the T-sector grow faster because N-sector goods are used in
T-sector production. Therefore, the T-sector will enjoy more abundant and cheaper
inputs than otherwise. As a result, as long as a crisis does not occur, growth in a
liberalized economy is faster than in a non-liberalized one.
Of course, financial fragility implies that a self-fulfilling crisis may occur. And
during crises GDP growth falls. Crises must be rare, however, in order to occur in
equilibrium – otherwise agents would not find it profitable to take on credit risk in
the first place. Thus, average long-run growth is greater along a risky path than
along a safe one even if there are large crisis costs. This is why FL leads both to
higher long-run growth and to a greater incidence of crises. Schneider and Tornell
7
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Conceptual framework
Economic policy
Several observers have suggested that partial liberalization is the optimal policy to
reap the growth benefits of openness without having to suffer from volatility and
crises. They suggest the implementation of trade liberalization but not of FL, or the
restriction of capital flows to FDI, the least volatile form of capital flows. These
recommendations seem impractical. First, an open trade regime is usually sustained
by an open financial regime because exporters and importers need access to
international financial markets. Since capital is fungible, it is difficult to insulate the
financial flows associated with trade transactions. The data indicates that trade
liberalization has typically been followed by FL. As Figure 3 shows, by 1999 72
percent of countries that had liberalized trade had also liberalized financial flows,
bringing the share of MICs that were financially liberalized to 69 percent, from 25
percent in 1980.
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
Trade liberalization
1980
1982
1984
1986
1988
1990
1992
Financial liberalization
1994
1996
1998
Figure 3 Share of MICs that liberalized trade and financial flows, 1980–99. Note:
The figure shows the share of countries that have liberalized relative to the total
number of MICs in our sample. Source: Tornell, Westermann and Martinez (2003).
8
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(2004) and RTW (2003) formalize the intuitive argument we described using a
general equilibrium model with rational agents.
This discussion of the mechanism through which FL affects the growth of MICs
also explains why FL does little to improve the growth of LICs. LICs often do not
have functioning financial markets and thus lack the infrastructure that allows the
financial system to direct international funds to profitable firms. MICs, by contrast,
have enough financial infrastructure to allocate funds reasonably well, even though
contract enforceability problems prevent them from doing so as efficiently as highincome countries (HICs). Because of the imperfections in their financial systems, the
price of fast growth in MICs is financial fragility. The contrasting experiences of
Thailand and India during the period 1980–2002 illustrate this trade-off clearly. As
we discussed earlier, Thailand experienced booms and busts while India did not.
While Thailand experienced spectacular growth, India’s growth was dismal.
Recently, India has opened its economy to both trade and finance. Not surprisingly,
India is currently experiencing a lending boom. It will be interesting to analyse the
evolution of the Indian economy around 2015.
See Also
•
•
•
•
banking crises
currency crises
foreign direct investment
international capital flows
Bibliography
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growth? Journal of Financial Economics 77, 3–55.
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©Palgrave Macmillan. The New Palgrave Dictionary of Economics. www.dictionaryofeconomics.com. You may not copy or distribute without permission. Licensee: Palgrave Macmillan.
Second, FDI does not obviate the need for risky international bank flows. FDI
goes mostly to financial institutions and large firms, which are mostly T-firms. Thus,
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investment and generate bottlenecks that would limit long-run growth. Bank flows
are hardly to be recommended, but for most firms it might be that or nothing.
Clearly, allowing risky capital flows does not mean that anything goes. Appropriate
prudential regulation must also be in place.
In an environment with asymmetric financial opportunities authorities may be
tempted to make direct investment subsidies to constrained sectors. The historical
evidence indicates that such centrally planned policies typically fail. We now know
that either authorities do not possess the appropriate information or crony capitalism
and rampant corruption take over. A second-best policy is to liberalize financial
markets and allow banks to be the means through which resources are channelled to
financially constrained firms. Here, it is important to make a distinction between
‘systemic’ and ‘unconditional’ bail-out guarantees. The former are granted only if a
critical mass of agents default. The latter are granted on an idiosyncratic basis
whenever there is an individual default. We have argued that, if authorities can
commit to grant only systemic guarantees, and if prudential regulation works
efficiently, then FL will induce higher long-run growth in a credit-constrained
economy. In contrast, if guarantees are granted on an unconditional basis or there is a
lax regulatory framework, the monitoring and disciplinary role of banks in the
lending process will be negated. In this case, FL will simply lead to overinvestment
and corruption.
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of FL countries have to be exposed for ever to the risk of crises. The amelioration of
contract enforceability problems, through a better legal system and other institutional
reforms, is a fundamental source of higher growth and lower volatility in the longrun. However, it often takes time for these reforms to be achieved. In the meantime,
countries with functioning financial markets can be made better off by liberalizing
and experiencing a rapid but risky growth path, rather than remaining closed and
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