The Role of Financial System in Economic Growth Presented By: Saumil Nihalani

Topics Overview Current Model Suggested New Model Review of Literature Overview of Terms New Model Empirical Analysis Results and Findings Policy Analysis Conclusion Recommendation

Overview 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 Model Developed by Demirguc-Kunt and Levine, 1996; Levine, 2002 and 2003; Beck and Levine, 2002 suggests that: 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 For developing countries: 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: Credit and Stock Market Capitalization positively influence economic growth

Review of Literature 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 Proxy variable : It is an observed variable that is related but not identical to an unobserved explanatory variable in multiple regression analysis 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 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 Fixed effects models: Estimation model for panel data or cluster samples where the error term contains unobserved effect Random effects models : Estimation model where the 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 My intension is to develop the model: 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: Its ability to quantify the relationship between variables

Empirical Analysis Data: Used from 1960 to 1999 Variables used to characterized given country’s financial system: Domestic credit to private non-financial entities (“Credit”) Stock market capitalization Countries have been divided as: Developed and Developing Countries Dominance of Intermediaries or Financial Market Used 1995 GDP Prices ( in U.S. Dollars )

Empirical Analysis I have used Panel data analysis approach to discover connection between financial market and economic growth It is a data set constructed from repeated cross-sections over time It permits more observations to use and allows more freedom The proxy variable for development of financial market is: Stock market capitalization The proxy variable for development of financial intermediaries is: Credit to Private non-financial entities

Empirical Analysis 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 Influence of Credit on GDP: 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 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 Influence of Stock Market on GDP: 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 When the countries are divided according to the type of the respective financial system, financial intermediaries’ dominance, financial market dominance: 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 Even though the findings are not comprehensive, the results do provide clear picture for credit policy implications 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 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 I recommend this model is a good tool for: Policy makers of: Federal government State government Policy makers: To focus on credit view of monetary policy that encourage credit to private non-financial entities, which in turn boost GDP growth

Thank you! For: Your Time Your Interest