Download Topics

The Role of Financial
System in Economic
Growth
Presented By:
Saumil Nihalani
Topics
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Overview
Current Model
Suggested New Model
Review of Literature
Overview of Terms
New Model
Empirical Analysis
Results and Findings
Policy Analysis
Conclusion
Recommendation
Overview
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One of the most important aspects in the field
of Economy and Finance:
 Effects of financial systems on economic
growth
Therefore, to examine the link between:
 Financial markets, financial intermediaries,
and economic growth would be interesting
to study
Existing Model
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Model Developed by Demirguc-Kunt and
Levine, 1996; Levine, 2002 and 2003;
Beck and Levine, 2002 suggests that:
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Financial System does not influence the
economic growth of a country
However, the provision of financial services
plays a significant role in the economic
growth
Suggested New Model
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For developing countries:
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Regardless of the type of dominant
financial system, the Credit View Monetary
Policy ( Credit or Credit Variable) is
significant in explaining the economic
growth
For developed countries:
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Credit and Stock Market Capitalization
positively influence economic growth
Review of Literature
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Goldsmith(1969):
 Relationship between financial development and economic
development
 Suggested that concurrent development of the financial
system and economy
King and Levine (1993):
 To examine statistical significance of the variables ( bank
credit, credits of the central bank..) when regressed towards
GDP growth
Rousseau and Wachtel (1998), Bassanini and Leahy (2001):
 To examine econometric approaches on:
 Co-integration and causality analysis
 Panel data / cross section analysis
Terms
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Proxy variable: It is an observed variable that is related but
not identical to an unobserved explanatory variable in multiple
regression analysis
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Lagged dependent variable: It is an explanatory variable
that is equal to the dependent variable from an earlier time
period. It increases the data requirements, but it provides
simple way to account for historical factors that cause current
differences in the dependent variable that are difficult to
account for in other ways
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Pooled effects models: Estimation model that estimates
with independently pooled cross sections, panel data, or cluster
samples, where the observations are pooled across time as well
as cross sectional units
Terms
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Fixed effects models: Estimation model for panel data or
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Random effects models: Estimation model where the
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cluster samples where the error term contains unobserved
effect
unobserved effect is assumed to be uncorrelated with the
explanatory variables in each time period
F-Test: Method of testing null hypothesis that includes more
than one coefficient
F-Statistic: A statistic used to test multiple hypothesis about the
parameters in a multiple regression model
Durbin-Watson (DW) Statistic: Used to test for first order serial
correlation in the error of a time series regression model under
the classical linear model assumption
The New Model
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My intension is to develop the model:
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To study determinants of GDP
To develop a model to help policy makers
To know how much of the changes in GDP
are explained by the explanatory variables
in the model
Model is useful because:
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Its ability to quantify the relationship
between variables
Empirical Analysis
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Data:
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Variables used to characterized given country’s
financial system:
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Domestic credit to private non-financial entities (“Credit”)
Stock market capitalization
Countries have been divided as:
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Used from 1960 to 1999
Developed and Developing Countries
Dominance of Intermediaries or Financial Market
Used 1995 GDP Prices ( in U.S. Dollars )
Empirical Analysis
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I have used Panel data analysis approach to discover
connection between financial market and economic
growth
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The proxy variable for development of financial
market is:
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It is a data set constructed from repeated cross-sections
over time
It permits more observations to use and allows more
freedom
Stock market capitalization
The proxy variable for development of financial
intermediaries is:
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Credit to Private non-financial entities
Empirical Analysis
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The model is Explained by:
Table 2- Credit as a Proxy for Financial Development: Developed and
Developing Countries; k1 = 1 and k2 = 0
Results and Findings
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Influence of Credit on GDP:
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F-Test result shows that the fixed effects model is more
appropriate than the pooled effects model
Hausman test indicates that the random effects model is
more appropriate than fixed effects model
In the random effects model, the proxy for financial
development is
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Statistically significant in explaining GDP for the developed
countries
Statistically less significant for developing countries
Credit is statistically significant for the entire country sample
Overall, the results indicate that there is direct relation
between credit and GDP growth
Results and Findings
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Influence of Stock Market on GDP:
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Random effects model is observed to be significant
Positive and statistically significant influence of stock market
capitalization on GDP growth
The estimated coefficient is less statistically significant for
developing countries than for the developed countries
See table on following slide…
Table 4 - Stock Market Capitalization as a Proxy for Financial Development: Developed
and Developing; Countries k1 = 0 and k2 = 1
Results and Findings
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When the countries are divided according to the type
of the respective financial system, financial
intermediaries’ dominance, financial market
dominance:
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The stock market capitalization has an ambiguously positive
and statistically significant relation with GDP growth
The result observed to be true for pooled, fixed, and random
effects model
Therefore, the stock market capitalization is significant for
countries where the financial market dominate
This result is opposite where Credit is Proxy variable
Countries with bank-based and intermediate systems, stock
market capitalization has a diminished role in explaining GDP
growth
Table 5 - Stock Market Capitalization as a Proxy for Financial Development:
different Financial Systems k1 = 0 and k2 = 1
Policy Analysis
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Even though the findings are not comprehensive, the
results do provide clear picture for credit policy
implications
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Policy makers should concentrate on ensuring a
sound credit environment, rather than developing
policies that in favor mainly on bank-based or
market-based financial system
Conclusion
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Regardless of type of financial system, the credit
variable is significant in explaining GDP growth
When countries divided based on the dominant
financial systems, stock market capitalization has
positively and statistically significant role with GDP
growth
Both credit and stock market capitalization have a
positive role on GDP growth in developed countries
Credit has statistically significant role on GDP growth
in developing countries
Recommendation
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I recommend this model is a good tool
for:
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Policy makers of:
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Federal government
State government
Policy makers:
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To focus on credit view of monetary policy that
encourage credit to private non-financial
entities, which in turn boost GDP growth
Thank you!
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For:
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Your Time
Your Interest