Transcript Slide 1

Introduction
“Given the close link between the financial sector
and household and firm balance sheets, a key
question is how these differences in financial
systems affect macroeconomic behaviour. ... Yet
few empirical studies to date have analysed the
effect of different financial structure on business
cycle behaviour -attention has mostly focused on
the role of overall financial development for
growth performance.”
World Economic Outlook, September 2006
Introduction (continued )
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large literature on the impact of finance and
growth, but
few empirical work on the relationship between
finance and volatility, even fewer work on the
effects of capital market
theoretically, developed capital markets, not
only better financial intermediation, help to
smooth out economic fluctuations.
existing studies provide only mixed support of
the hypothesis that higher financial or capital
market development leads to lower volatility
Introduction (continued2)
Theory
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Agency costs and balance sheet effect
[Bernanke and Gertler (1995)]
Information asymmetries
[Greenwald and Stiglitz (1993)]
Unequal access to investment opportunities
[Aghion et al. (1999)]
Limited diversification
[Acemoglu and Zilibotti (1997)]
Theory (continued )
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Maturity mismatch in intermediaries’ portfolios,
non-transferable specific knowledge, and lower
transparency in a bank-based system.
[Rajan and Zingales (2001)]
Breaking up of relationship lending magnifies the
initial shocks [Hann et al. (1999)].
Fire sales of a single troubled bank could cause
asset-price deterioration that precipitates other
banks into crisis [Fecht (2004)].
Empirical
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Lopez and Spiegel (2002) analyse cross-section data
and find that financial development does mitigate
economic fluctuations.
Loayza and Ranciere (2004) shows a positive longrun relationship between financial intermediation
and output growth co-exists with negative short-run
relationship.
Tiryaki (2003) finds that investment volatility
decreases as financial secotor expands, but volatility
of output business cycles is largely irresponsive to
financial development.
Measurement Issues
• Capital Market Development
• Financial Development
• Volatilities
• Output
• Growth Volatility
• Business Cycle Volatility
• Investment Volatility
• Consumption Volatility
Measures of Capital Market
Development
1.
Absolute measure
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identify the level of capital market development
itself without reference to other development in
the financial system
Turnover ratio, Stock value traded ratio, Market
capitalization ratio
2. Relative measure
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gauge the development of capital markets relative
to that of financial intermediaries, particularly the
banking sector
also know in the literature as “Financial
Structure”, indicating whether the financial system
is market-based, or bank-based.
Measures of Capital Market
Development (continued )
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Absolute measures
1. “Turnover ratio” = the value of shares traded on
domestic exchange divided by the total value of
listed shares
2. “Value traded” = the value of trades of domestic
shares on domestic exchange divided by GDP
3. “Market capitalization ratio” = the total stock
market capitalization over GDP
Measures of Capital Market
Development (continued )
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Relative measures [Beck et al. (2001)]
1. Structure-Activity = log(
2.
Structure-Size = log(
stock _ value _ traded / gdp
)
bank _ crdit / gdp
stockmarket _ capitalization / gdp
)
bank _ credit / gdp
3. Structure-Efficiency =
log(
stock _ value _ traded / gdp
)
overhead _ cos t / banking _ system _ assets
4. Structure-Aggregate = First principal component
of the above three indices, but in this paper only
the first two due to data limitation
Measures of Financial Development
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Ideally, a measure of financial development would indicate
the effectiveness which the financial system performs its
functions:
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clearing and settlement, pooling resources, transferring
resources across time and space, managing risk, providing
information, and dealing with incentive problems
[Merton and Bodie (2004)]
No such measures exist. Use proxies, which practically
measure degrees of financial intermediation
1.
Private credit ratio = ratio of domestic credit extended to
the private sector by financial intermediaries to GDP
2.
Liquidity ratio = ratio of liquid liabilities (usually M3) to
GDP
Measures of Volatility
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Output volatility
• Growth volatiliy = s.d. of growth rates of real gdp per capita
• Volatility of business cycle component of output
= s.d. of filtered real gdp per capita
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apply Chistiano-Fitzgerald (CF) band-pass filter
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extract cyclical variations that last 2 to 8 years
Investment volatility
• Investment volatility = s.d. of gross capital formation growth
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Consumption volatility
• Consumption volatility = s.d. of household consumption growth
Methodology
A
reduced-form equation relating volatility,
financial intermediation, and capital market
 it  0  1.FDit  2 .FSit  3.X it  it
σ is a measure of volatility. Depending on the specification, it could be log
of standard deviation (sd.) of growth rate of output (g-vol), investment
(i-vol), or consumption (c-vol), or sd. of CF-filtered log of output (bvol).
FD is a measure of financial development, namely log of private credit ratio
(credit).
FS is a measure of capital market development. An absolute and a relative
measure would be log of turnover ratio (turnover) and financial
structure-aggregate index (struc), respectively.
X is a vector of standard controlled variables
[see e.g. Lopez and Spiegel (2002), Beck et al. (2003)]
Methodology (continued )
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Controlled variables (X) include:
• income level, trade openness ratio, government
consumption over GDP, s.d. of changes in real
effective exchange rate, s.d. of changes in terms of
trade
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Instrumental variables (Z) in IV and Panel IV:
• IV: time trend, legal origin, creditor’s protection
index [La-Porta et al. (1998)]
• Panel IV: time trend, creditor’s protection, human
capital index
Data
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The panel covers annual data of 44 countries from
1975 to 2004. Data sources are International Financial
Statistics (IFS), World Development Indicators (WDI),
Barro-Lee data set [Barro and Lee (2000)], Legal Origin
and Creditor's Protection data set [La-Porta et al.
(1998)], and Financial Structure data set [Levine
(2002)].
The annual data are transformed into six five-year-span
panel data from 1975-2004.
The transformation method is the average, but for
volatilities (such as growth volatility), standard
deviation is used.
12
10
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80
120
160
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Domestic Credit to private sector (%of GDP)
Standard Deviation of Growth rate of GDP per capita
Standard Deviation of Growth rate of GDP per capita
Scatter Diagrams
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100
200
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Stock Market Turnover ratio
400
Robustness check
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Alternative measures of financial and capital market
development are used.
Liquidity ratio (M3/GDP) is used instead of private credit ratio
(private credit/GDP) to measure a degree of financial
development.
Value traded ratio (stock value traded/GDP) and market
capitalization ratio (stock market capitalization/GDP) are used
instead of turnover ratio (stock value traded/stock market
capitalization) as a measure of capital market development.
Major findings do not materially change with alternative
measures.
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Inclusion of the effects of institutional quality and financial
liberalization policy also does not change the result.
Other plausible relevant variables (e.g. standard deviation of
inflation, average inflation rate, and investment ratio) are also
included in the estimation, but have never been significant.
Policy Implication
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The above econometric analysis supports theoretical prediction
that the development of capital markets reduces output,
investment, and consumption volatilities.
Still the question whether the magnitude of the effects is
economically meaningful.
Use a coefficient of log of turnover ratio (turnover) from fixed
effects estimation (FEI) of growth volatility as a benchmark. The
coefficient is -0.16. The inter-quartile range of turnover ratio in
the sample is 49.36. In terms of log difference, it is 1.67.
Therefore, the effect of an inter-quartile improvement in
turnover ratio is -0.27 (-0.16 * 1.67) or a reduction of 27% of
volatility.
The average growth volatility is 2.1%. A decrease of 27% would
mean a decrease of 0.50 percentage point (2.1-2.1*exp(-0.27))
in standard deviation of growth rate.
Conclusion
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This paper investigates the effect of capital market development
on output, investment and consumption volatilities in forty-four
countries using data from 1975 to 2004 period.
The main result is that output, investment and consumption
volatilities are negatively related to measures of capital market
development after controlling for other relevant variables.
However, the absolute magnitude of the effect is quite small.