This document explores the relationship between financial development and real sector growth in selected countries of the South Asian Association for Regional Cooperation (SAARC) region from 1975 to 2009. It first reviews previous literature on the finance-growth nexus and discusses variables used to measure financial development and real sector growth. The study then presents descriptive statistics and aims to empirically examine whether there is a long-run relationship and causal relationship between financial development and real sector growth in the SAARC countries of Pakistan, India, Nepal and Sri Lanka using cointegration and Granger causality tests.
This study empirically investigates the impact of institutional variables on financial development in 29 African
countries. The Pooled Mean Group estimation method was applied to annual data covering the 2000 to 2014 period.
The results show that in the short run, economic freedom has a positive impact on financial development. In the long
term, democracy has a negatve impact on financial development while corruption and economic freedom positively
affect financial development. This suggests that promoting economic freedom is conducive to financial
development. However, in African countries, democracy is not in favour of financial development.
This study empirically investigates the impact of institutional variables on financial development in 29 African
countries. The Pooled Mean Group estimation method was applied to annual data covering the 2000 to 2014 period.
The results show that in the short run, economic freedom has a positive impact on financial development. In the long
term, democracy has a negatve impact on financial development while corruption and economic freedom positively
affect financial development. This suggests that promoting economic freedom is conducive to financial
development. However, in African countries, democracy is not in favour of financial development.
A STUDY ON THE IMPACT OF TRANSPORT AND POWER INFRASTRUCTURE DEVELOPMENT ON TH...IAEME Publication
UAE as an autonomous country got constituted during the year 1971 by joining
together seven different autonomous and independent emirates. Through meticulous
planning and farsightedness, the country has set a development trend which is unique
in the Arabian Peninsula as well as to the entire world. The wealth and richness of the
country can be mainly attributed to the inflow of petrol income coupled with the
farsightedness and vision of the founding fathers of the nation in deploying the income
towards proper avenues of investment. Ever since its formation, the country has been
giving core attention to the development of infrastructure in the form of
transportation, construction and power generation. Now the country is equipped with
world class infrastructure and is the focal place of attention of other countries of the
world. Since the prime source of revenue is the petrol income, the performance of
UAE economy fluctuates from time to time due to the high volatility in oil prices and
its demand globally. Hence, the country has started laying the foundation for a total
restructuring by focusing on the development of infrastructure and other diversified
portfolios in business so that the primary dependence on petrol could be reduced.
Since 1990’s the country has been investing heavily in building up infrastructure so as
to attract foreign capital for its development. Even though there occurred
uncertainties in petrol income during the last two decades, the country could manage
its GDP growth rate through development in infrastructure and other related
industries. The country has gained appreciable improvement in formation of gross
fixed capital through infrastructure development, which in fact acted as a cushion of
growth during periods of uncertainties caused by fluctuations in petrol price. This
study is an effort to find out the relationship between development of infrastructure
and its impact on the economic development of UAE by considering various elements
in infrastructure such as transportation, power generation and construction. From the
study, it is found that there exists strong relationship between the economic growth of
a country like UAE and its infrastructure development.
This article was aimed to study the environment and the co-movement of China’s economic growth together with
Thailand under economic and macro-finance dimensions by collecting information from academic literatures, global
organization reports, and historical data from opened source database such as World Bank, United Nations,
International Monetary Fund (IMF), and other relatives. The study found that China’s and Thailand’s economic
activities are related particularly in term of trade but the low investment. In fact, services industry has replaced
industrial manufacture to be the influent factor on gross domestic product (GDP) in both two countries. Moreover,
enhancing to promote world- class capital markets and financial system development in China has drawn attraction
from Thailand investors to invest more than a half of Thailand’s direct investment funds in financial firms and
activities in China in 2017. In the conclusion, Thailand’s economic growth is still relied on China’s demand for raw
materials according to goods and products they have exported to China. The suggestion for Thailand is to create their
own technology like China’s development model in order to produce valuable goods and services productivity. And
for both countries, China and Thailand should also have to focus on income distribution through other areas outside
the city under the principal of economic development to improve the welfare of the population.
Extant literature revealed that international trade plays a key role to address the economic phenomena and can help to earn foreign exchange. Despite the accruable benefits from international trade and the countrys huge oil export that account for about 90 of its foreign exchange earnings, Nigerias trade balance and exchange rate remain unfavourable. The persistent rise in Nigerias exchange rate and unfavourable trade balance in recent time warrants an empirical probe. This study therefore examines the effect of exchange rate, domestic income, foreign income, consumption expenditure, money supply and interest rate on trade balance using a secondary time series data covering a period of thirty years from 1991 2020. The study employed a regression technique of the Ordinary Least Square OLS . All data used were secondary data obtained from the statistical bulletin of Central Bank of Nigeria CBN and National Bureau of Statistics NBS annual publications. After determining stationarity of the study variables using the ADF Statistic, it was discovered that the variables were all integrated at level, first and second difference, and found out to be stationary at their first difference. The study also using Johansen Cointegration Test, found that there is a long run relationship between the variables. Hence, the implication of this result is that there is a long run relationship between trade balance and other variables used in the model. From the result of the OLS, it is observed that exchange rate, domestic income, foreign income and money supply have a positive and significant impact on trade balance in Nigeria. The study recommends that the government should fixed or peg on the exchange rate through the central bank. This will enable the government to buy and sell its own currency against the currency to which it is pegged. The government should strive to reduce inflation to make exports more competitive. The government should also enhance supply side policies to increase long term competitiveness. Edokobi, Tonna David | Okpala, Ngozi Eugenia | Okoye, Nonso John "Exchange Rate and Trade Balance Nexus" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-5 , August 2021, URL: https://www.ijtsrd.com/papers/ijtsrd45079.pdf Paper URL: https://www.ijtsrd.com/management/public-sector-management/45079/exchange-rate-and-trade-balance-nexus/edokobi-tonna-david
Monetary Policy and Trade Balance in NigeriaYogeshIJTSRD
Nigeria apex bank Central Bank of Nigeria CBN has continued to battle with the job of reviving the ailing economy and putting it on the path of growth. The economy has witnessed unprecedented job loss, rising poverty level, accelerating inflation, sluggish economic growth and disequilibrium in the balance of trade. The study therefore examine the effect of monetary policy on trade balance in Nigeria. Specifically the study ascertained the extent to which inflation, demand deposit, liquidity ratio, exchange rate and interest rate have influenced trade balance in Nigeria using an econometric regression model of the Ordinary Least Square OLS . From the result of the OLS, it is observed that monetary policy rate, demand deposit, liquidity ratio and exchange rate have a significant positive impact on foreign trade in Nigeria. This means that increases in monetary policy rate, demand deposit, liquidity ratio and exchange rate, will lead to increase in foreign trade in Nigeria. On the other, inflation rate and interest rate has a significant negative impact on foreign trade in Nigeria, meaning that as inflation rate and interest rate increases, will be bring about a decline in foreign trade in Nigeria. Based on the findings of this study, the study recommends that the government should employ a contractionary monetary policy to fight inflation by reducing the money supply in the country through decreased bond price. inflation, demand deposit, liquidity ratio, exchange rate and interest rate have influenced trade balance in Nigeria. The government should intervene in the foreign exchange market in order to build reserves for themselves or provide them to the bank to help stabilize the exchange rate. The government should strive to improve trade performance in the short and long run. They should also reduce government spending and tax capital inflow. Edokobi, Tonna David | Okpala, Ngozi Eugenia | Okoye, Nonso John "Monetary Policy and Trade Balance in Nigeria" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-5 , August 2021, URL: https://www.ijtsrd.com/papers/ijtsrd45080.pdf Paper URL: https://www.ijtsrd.com/management/public-sector-management/45080/monetary-policy-and-trade-balance-in-nigeria/edokobi-tonna-david
This study examined the effect interest rate on economic growth in Nigeria. Augmented Dickey – Fuller (ADF), Bound Test and Autoregressive Distributed Lag (ARDL) were employed to examine the effect of impact of interest rate on economic growth in Nigeria. The unit root test showed gross domestic product was 1(0) while interest rate, investment and gross capital formation were 1(1). The result of the Bound Test indicated long run relationship among the macroeconomic variables employed in the study. The result of the ARDL indicated that interest rate had negative effect on economic growth both in short run and long run. However, in the long run investment and gross capital formation were established to have positive effect on economic growth with gross capital formation being insignificant. It was concluded that interest rate has a macroeconomic tool is not effective in stimulating economic growth in Nigeria. It was recommended that the level of interest rate should be adequately controlled for the purpose of stimulating economic growth without inflationary pressure. Finally, robust macroeconomic policies aimed at ensuring economic stability should be formulated in order to increase capital formation and attract investment in order to promote economic growth.
Impact of Visual Merchandising on Impulsive Buying Behavior of Sri Lankan Mod...YogeshIJTSRD
The focus of the research was to see how different visual marketing approaches affected the impulsive purchase behavior of Sri Lankan modern trade clients. Modern retailers utilize visual merchandising as one of their primary tactics for differentiating their offers and attracting and persuading customers to buy. In store marketing and visual merchandising have attracted a lot of attention recently, and the amount of money spent on visual merchandising has also skyrocketed. As a result, determining the efficiency of the money that is spent on these diverse visual merchandising strategies is critical for all supermarkets. A well structured questionnaire was used to obtain primary data for the study. A total of 392 Sri Lankan modern trade clients were chosen as the sample for the study. The sampling method was snowball sampling, and the data was analyzed using SPSS 25 software. The multiple regression analysis was used to analyze the data. Charts and graphs are used to display the research findings. The studys findings demonstrated that product display and promotional signs have a strong favorable impact on impulsive purchase behavior among Sri Lankan modern trade clients. Based on these findings, businesses may determine which visual merchandising methods are the most effective and devote time and resources to improving them, resulting in increased foot traffic and revenue. K. K. P. D. Kahaduwa | R. M. K. S. Rasanjalee "Impact of Visual Merchandising on Impulsive Buying Behavior of Sri Lankan Modern Trade Customers" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-5 , August 2021, URL: https://www.ijtsrd.com/papers/ijtsrd45046.pdf Paper URL: https://www.ijtsrd.com/management/consumer-behaviour/45046/impact-of-visual-merchandising-on-impulsive-buying-behavior-of-sri-lankan-modern-trade-customers/k-k-p-d-kahaduwa
Second Edition - Jan 2017 - China's Challenge to the World Economic Order - Robbie Van Kampen
Now well into the second decade of the 21st century, the world is witnessing the true extent of China’s economic, political, and growing military reach. This reach and integration into the globalized world has been gradual, incremental, and quiet over the past three decades. In the shadows, China has accelerated significantly in the past 10 years. What does this mean for the established global order? This paper is a road map looking to join the dots on that journey.
Measuring the Dynamics of Financial Deepening and Economic Growth in Nigeria,...iosrjce
The study examined the relationship between financial deepening and economic growth for the
period 1981 to 2013 using empirical evidence from Nigeria. The Engel-Granger two-step cointegration
procedures and Error Correction Model (ECM) were used as the method of estimation. The analyses of
residuals of the OLS regression showed evidence in favour of cointegration between financial deepening and
economic growth. Similarly, estimates from the error correction model provide evidence to show that financial
deepening indicators and GDP series converge to a long-run equilibrium at a reasonably fast rate. The result
points to the fact that the deepening of the financial system can engineer the Nigerian economy to greater
growth.
Measuring the Dynamics of Financial Deepening and Economic Growth in Nigeria,...iosrjce
The study examined the relationship between financial deepening and economic growth for the
period 1981 to 2013 using empirical evidence from Nigeria. The Engel-Granger two-step cointegration
procedures and Error Correction Model (ECM) were used as the method of estimation. The analyses of
residuals of the OLS regression showed evidence in favour of cointegration between financial deepening and
economic growth. Similarly, estimates from the error correction model provide evidence to show that financial
deepening indicators and GDP series converge to a long-run equilibrium at a reasonably fast rate. The result
points to the fact that the deepening of the financial system can engineer the Nigerian economy to greater
growth.
A STUDY ON THE IMPACT OF TRANSPORT AND POWER INFRASTRUCTURE DEVELOPMENT ON TH...IAEME Publication
UAE as an autonomous country got constituted during the year 1971 by joining
together seven different autonomous and independent emirates. Through meticulous
planning and farsightedness, the country has set a development trend which is unique
in the Arabian Peninsula as well as to the entire world. The wealth and richness of the
country can be mainly attributed to the inflow of petrol income coupled with the
farsightedness and vision of the founding fathers of the nation in deploying the income
towards proper avenues of investment. Ever since its formation, the country has been
giving core attention to the development of infrastructure in the form of
transportation, construction and power generation. Now the country is equipped with
world class infrastructure and is the focal place of attention of other countries of the
world. Since the prime source of revenue is the petrol income, the performance of
UAE economy fluctuates from time to time due to the high volatility in oil prices and
its demand globally. Hence, the country has started laying the foundation for a total
restructuring by focusing on the development of infrastructure and other diversified
portfolios in business so that the primary dependence on petrol could be reduced.
Since 1990’s the country has been investing heavily in building up infrastructure so as
to attract foreign capital for its development. Even though there occurred
uncertainties in petrol income during the last two decades, the country could manage
its GDP growth rate through development in infrastructure and other related
industries. The country has gained appreciable improvement in formation of gross
fixed capital through infrastructure development, which in fact acted as a cushion of
growth during periods of uncertainties caused by fluctuations in petrol price. This
study is an effort to find out the relationship between development of infrastructure
and its impact on the economic development of UAE by considering various elements
in infrastructure such as transportation, power generation and construction. From the
study, it is found that there exists strong relationship between the economic growth of
a country like UAE and its infrastructure development.
This article was aimed to study the environment and the co-movement of China’s economic growth together with
Thailand under economic and macro-finance dimensions by collecting information from academic literatures, global
organization reports, and historical data from opened source database such as World Bank, United Nations,
International Monetary Fund (IMF), and other relatives. The study found that China’s and Thailand’s economic
activities are related particularly in term of trade but the low investment. In fact, services industry has replaced
industrial manufacture to be the influent factor on gross domestic product (GDP) in both two countries. Moreover,
enhancing to promote world- class capital markets and financial system development in China has drawn attraction
from Thailand investors to invest more than a half of Thailand’s direct investment funds in financial firms and
activities in China in 2017. In the conclusion, Thailand’s economic growth is still relied on China’s demand for raw
materials according to goods and products they have exported to China. The suggestion for Thailand is to create their
own technology like China’s development model in order to produce valuable goods and services productivity. And
for both countries, China and Thailand should also have to focus on income distribution through other areas outside
the city under the principal of economic development to improve the welfare of the population.
Extant literature revealed that international trade plays a key role to address the economic phenomena and can help to earn foreign exchange. Despite the accruable benefits from international trade and the countrys huge oil export that account for about 90 of its foreign exchange earnings, Nigerias trade balance and exchange rate remain unfavourable. The persistent rise in Nigerias exchange rate and unfavourable trade balance in recent time warrants an empirical probe. This study therefore examines the effect of exchange rate, domestic income, foreign income, consumption expenditure, money supply and interest rate on trade balance using a secondary time series data covering a period of thirty years from 1991 2020. The study employed a regression technique of the Ordinary Least Square OLS . All data used were secondary data obtained from the statistical bulletin of Central Bank of Nigeria CBN and National Bureau of Statistics NBS annual publications. After determining stationarity of the study variables using the ADF Statistic, it was discovered that the variables were all integrated at level, first and second difference, and found out to be stationary at their first difference. The study also using Johansen Cointegration Test, found that there is a long run relationship between the variables. Hence, the implication of this result is that there is a long run relationship between trade balance and other variables used in the model. From the result of the OLS, it is observed that exchange rate, domestic income, foreign income and money supply have a positive and significant impact on trade balance in Nigeria. The study recommends that the government should fixed or peg on the exchange rate through the central bank. This will enable the government to buy and sell its own currency against the currency to which it is pegged. The government should strive to reduce inflation to make exports more competitive. The government should also enhance supply side policies to increase long term competitiveness. Edokobi, Tonna David | Okpala, Ngozi Eugenia | Okoye, Nonso John "Exchange Rate and Trade Balance Nexus" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-5 , August 2021, URL: https://www.ijtsrd.com/papers/ijtsrd45079.pdf Paper URL: https://www.ijtsrd.com/management/public-sector-management/45079/exchange-rate-and-trade-balance-nexus/edokobi-tonna-david
Monetary Policy and Trade Balance in NigeriaYogeshIJTSRD
Nigeria apex bank Central Bank of Nigeria CBN has continued to battle with the job of reviving the ailing economy and putting it on the path of growth. The economy has witnessed unprecedented job loss, rising poverty level, accelerating inflation, sluggish economic growth and disequilibrium in the balance of trade. The study therefore examine the effect of monetary policy on trade balance in Nigeria. Specifically the study ascertained the extent to which inflation, demand deposit, liquidity ratio, exchange rate and interest rate have influenced trade balance in Nigeria using an econometric regression model of the Ordinary Least Square OLS . From the result of the OLS, it is observed that monetary policy rate, demand deposit, liquidity ratio and exchange rate have a significant positive impact on foreign trade in Nigeria. This means that increases in monetary policy rate, demand deposit, liquidity ratio and exchange rate, will lead to increase in foreign trade in Nigeria. On the other, inflation rate and interest rate has a significant negative impact on foreign trade in Nigeria, meaning that as inflation rate and interest rate increases, will be bring about a decline in foreign trade in Nigeria. Based on the findings of this study, the study recommends that the government should employ a contractionary monetary policy to fight inflation by reducing the money supply in the country through decreased bond price. inflation, demand deposit, liquidity ratio, exchange rate and interest rate have influenced trade balance in Nigeria. The government should intervene in the foreign exchange market in order to build reserves for themselves or provide them to the bank to help stabilize the exchange rate. The government should strive to improve trade performance in the short and long run. They should also reduce government spending and tax capital inflow. Edokobi, Tonna David | Okpala, Ngozi Eugenia | Okoye, Nonso John "Monetary Policy and Trade Balance in Nigeria" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-5 , August 2021, URL: https://www.ijtsrd.com/papers/ijtsrd45080.pdf Paper URL: https://www.ijtsrd.com/management/public-sector-management/45080/monetary-policy-and-trade-balance-in-nigeria/edokobi-tonna-david
This study examined the effect interest rate on economic growth in Nigeria. Augmented Dickey – Fuller (ADF), Bound Test and Autoregressive Distributed Lag (ARDL) were employed to examine the effect of impact of interest rate on economic growth in Nigeria. The unit root test showed gross domestic product was 1(0) while interest rate, investment and gross capital formation were 1(1). The result of the Bound Test indicated long run relationship among the macroeconomic variables employed in the study. The result of the ARDL indicated that interest rate had negative effect on economic growth both in short run and long run. However, in the long run investment and gross capital formation were established to have positive effect on economic growth with gross capital formation being insignificant. It was concluded that interest rate has a macroeconomic tool is not effective in stimulating economic growth in Nigeria. It was recommended that the level of interest rate should be adequately controlled for the purpose of stimulating economic growth without inflationary pressure. Finally, robust macroeconomic policies aimed at ensuring economic stability should be formulated in order to increase capital formation and attract investment in order to promote economic growth.
Impact of Visual Merchandising on Impulsive Buying Behavior of Sri Lankan Mod...YogeshIJTSRD
The focus of the research was to see how different visual marketing approaches affected the impulsive purchase behavior of Sri Lankan modern trade clients. Modern retailers utilize visual merchandising as one of their primary tactics for differentiating their offers and attracting and persuading customers to buy. In store marketing and visual merchandising have attracted a lot of attention recently, and the amount of money spent on visual merchandising has also skyrocketed. As a result, determining the efficiency of the money that is spent on these diverse visual merchandising strategies is critical for all supermarkets. A well structured questionnaire was used to obtain primary data for the study. A total of 392 Sri Lankan modern trade clients were chosen as the sample for the study. The sampling method was snowball sampling, and the data was analyzed using SPSS 25 software. The multiple regression analysis was used to analyze the data. Charts and graphs are used to display the research findings. The studys findings demonstrated that product display and promotional signs have a strong favorable impact on impulsive purchase behavior among Sri Lankan modern trade clients. Based on these findings, businesses may determine which visual merchandising methods are the most effective and devote time and resources to improving them, resulting in increased foot traffic and revenue. K. K. P. D. Kahaduwa | R. M. K. S. Rasanjalee "Impact of Visual Merchandising on Impulsive Buying Behavior of Sri Lankan Modern Trade Customers" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-5 , August 2021, URL: https://www.ijtsrd.com/papers/ijtsrd45046.pdf Paper URL: https://www.ijtsrd.com/management/consumer-behaviour/45046/impact-of-visual-merchandising-on-impulsive-buying-behavior-of-sri-lankan-modern-trade-customers/k-k-p-d-kahaduwa
Second Edition - Jan 2017 - China's Challenge to the World Economic Order - Robbie Van Kampen
Now well into the second decade of the 21st century, the world is witnessing the true extent of China’s economic, political, and growing military reach. This reach and integration into the globalized world has been gradual, incremental, and quiet over the past three decades. In the shadows, China has accelerated significantly in the past 10 years. What does this mean for the established global order? This paper is a road map looking to join the dots on that journey.
Measuring the Dynamics of Financial Deepening and Economic Growth in Nigeria,...iosrjce
The study examined the relationship between financial deepening and economic growth for the
period 1981 to 2013 using empirical evidence from Nigeria. The Engel-Granger two-step cointegration
procedures and Error Correction Model (ECM) were used as the method of estimation. The analyses of
residuals of the OLS regression showed evidence in favour of cointegration between financial deepening and
economic growth. Similarly, estimates from the error correction model provide evidence to show that financial
deepening indicators and GDP series converge to a long-run equilibrium at a reasonably fast rate. The result
points to the fact that the deepening of the financial system can engineer the Nigerian economy to greater
growth.
Measuring the Dynamics of Financial Deepening and Economic Growth in Nigeria,...iosrjce
The study examined the relationship between financial deepening and economic growth for the
period 1981 to 2013 using empirical evidence from Nigeria. The Engel-Granger two-step cointegration
procedures and Error Correction Model (ECM) were used as the method of estimation. The analyses of
residuals of the OLS regression showed evidence in favour of cointegration between financial deepening and
economic growth. Similarly, estimates from the error correction model provide evidence to show that financial
deepening indicators and GDP series converge to a long-run equilibrium at a reasonably fast rate. The result
points to the fact that the deepening of the financial system can engineer the Nigerian economy to greater
growth.
Role of Development Finance Institutions in Developing the Nigerian Agricultu...AJHSSR Journal
ABSTRACT : This study investigates the role of development finance institutions (DFIs) in agricultural
sector development in Nigeria. African Development Bank (AfDB), World Bank and International Development
Association (IDA) were the underlying DFIs while agriculture value added formed the basis for measuring
agricultural sector development. Data on the variables were sourced from World Development Indicators (WDI)
and analyzed using error correction mechanism (ECM). The unit root test results indicate that all the variables
are not stationary. However, they become stationary after first differencing and as such they all integrated of
order one. The cointegration test results revealed that the variables have long run relationship. The result
showed that the first and second lag of agriculture value added impacted negatively on its current. One-period
lag of AfDB loan has significant positive relationship with current value of agriculture value added. The result
showed that agriculture value added increased by 0.079 percent due to 1 percent increase in lag of AfDB loan. It
was also found that the lagged values of World Bank and IDA loans exert significant negative impact on
agriculture value added. The Parsimonious ECM revealedthat the model has an adjustment speed of 59.2
percent. Based on the findings, it is recommended that policymakers should prioritize the allocation of AfDB
loans into productive sectors of the economy with particular emphasis on agriculture with a view to driving the
development process in the real sector.
Keywords:Development finance, agriculture sector, Institutions, African Development Bank, World Bank and
value addition
Net External Liabilities and Economic Growth: A Case Study of pakistansanaullah noonari
By using ordinary least square (OLS) method this study is conducted to see the impact of net external liabilities
on economic growth of Pakistan. Other statistical tools like unit root etc were applied to solve the data problem
as we use time series data for the period 1973-2012. The result of the study found that net external liabilities,
education enrolment, export and gross capital formation has positive significance association with GDP while
debt service relation was found insignificance.
Keywords: Net External Liabilities, Gross Domestic product, Debt service
Good governance is essential for economic development as it enhances the effectiveness of economic policies undertaken by the government. The aim of this paper is to study the relationship between governance and economic growth in Africa. Using the World Bank governance indicators we construct a composite index to resume all the indicators in one variable that will be used to measure the impact of governance on growth. The main result of this study is that a change in the governance index of a unit is likely to produce an increase of 1.7% in real GDP. This result seems to be extremely important considering the shortage of financial resources in Africa. Improving governance seems to be the best and the less expensive way the boost economic growth. Thus, African countries need to strengthen their economic efficiency by promoting results-based fiscal management, improving their doing business environment and investing in education to improve the quality of human factor.
Foreign capital flows depends on the prevailing monetary forces as supported by capital flows
theory and the mechanism linking these two variables is that contraction of net domestic assets through an
open market sale of bonds will place upward pressure on domestic interest rates. Higher interest rates attract
foreign funds, generating a capital inflow which relieves the pressure on domestic interest rates. Has this
actually happened? It is against this backdrop that the present study investigated the impact of monetary policy
on international capital inflows in Nigeria for a period of 22 years (1994-2015) using time series data. The
autoregressive distributed lag technique revealed that the short-run and long-run significant determinants of
foreign capital inflows are largely from broad money supply, nominal exchange rate, inflation rate and interest
rates spread except inflation rate that is insignificant in the long-run. This outcome upholds theoretical
prediction. Long-run equilibrium relationship was found between the dependent variable and the regressors.
Further examination of the short run dynamics of the model showed that the speed of adjustment coefficients
ECM (-1) to restore equilibrium have a negative sign and statistically significant at 1% level, ensuring that
long-run equilibrium can be attained and about 89% of the short-run deviation from the equilibrium (long-run)
position is corrected annually to maintain the equilibrium. Since the empirical evidence revealed that monetary
aggregates such as broad money supply, nominal exchange rate, inflation rate and interest rates spread
influence foreign capital inflows, it is therefore recommended that government should continue to pursue
expansionary monetary policy and foreign exchange policies that would ensure competitiveness of the
economy in order to attract the much needed foreign capital inflows that would engender economic growth.
Similar to An exploration of the finance growth nexus-long run and causality evidences from selected countries of saarc region (20)
how to sell pi coins on Bitmart crypto exchangeDOT TECH
Yes. Pi network coins can be exchanged but not on bitmart exchange. Because pi network is still in the enclosed mainnet. The only way pioneers are able to trade pi coins is by reselling the pi coins to pi verified merchants.
A verified merchant is someone who buys pi network coins and resell it to exchanges looking forward to hold till mainnet launch.
I will leave the telegram contact of my personal pi merchant to trade with.
@Pi_vendor_247
Currently pi network is not tradable on binance or any other exchange because we are still in the enclosed mainnet.
Right now the only way to sell pi coins is by trading with a verified merchant.
What is a pi merchant?
A pi merchant is someone verified by pi network team and allowed to barter pi coins for goods and services.
Since pi network is not doing any pre-sale The only way exchanges like binance/huobi or crypto whales can get pi is by buying from miners. And a merchant stands in between the exchanges and the miners.
I will leave the telegram contact of my personal pi merchant. I and my friends has traded more than 6000pi coins successfully
Tele-gram
@Pi_vendor_247
Empowering the Unbanked: The Vital Role of NBFCs in Promoting Financial Inclu...Vighnesh Shashtri
In India, financial inclusion remains a critical challenge, with a significant portion of the population still unbanked. Non-Banking Financial Companies (NBFCs) have emerged as key players in bridging this gap by providing financial services to those often overlooked by traditional banking institutions. This article delves into how NBFCs are fostering financial inclusion and empowering the unbanked.
how to swap pi coins to foreign currency withdrawable.DOT TECH
As of my last update, Pi is still in the testing phase and is not tradable on any exchanges.
However, Pi Network has announced plans to launch its Testnet and Mainnet in the future, which may include listing Pi on exchanges.
The current method for selling pi coins involves exchanging them with a pi vendor who purchases pi coins for investment reasons.
If you want to sell your pi coins, reach out to a pi vendor and sell them to anyone looking to sell pi coins from any country around the globe.
Below is the contact information for my personal pi vendor.
Telegram: @Pi_vendor_247
how to sell pi coins in all Africa Countries.DOT TECH
Yes. You can sell your pi network for other cryptocurrencies like Bitcoin, usdt , Ethereum and other currencies And this is done easily with the help from a pi merchant.
What is a pi merchant ?
Since pi is not launched yet in any exchange. The only way you can sell right now is through merchants.
A verified Pi merchant is someone who buys pi network coins from miners and resell them to investors looking forward to hold massive quantities of pi coins before mainnet launch in 2026.
I will leave the telegram contact of my personal pi merchant to trade with.
@Pi_vendor_247
where can I find a legit pi merchant onlineDOT TECH
Yes. This is very easy what you need is a recommendation from someone who has successfully traded pi coins before with a merchant.
Who is a pi merchant?
A pi merchant is someone who buys pi network coins and resell them to Investors looking forward to hold thousands of pi coins before the open mainnet.
I will leave the telegram contact of my personal pi merchant to trade with
@Pi_vendor_247
What price will pi network be listed on exchangesDOT TECH
The rate at which pi will be listed is practically unknown. But due to speculations surrounding it the predicted rate is tends to be from 30$ — 50$.
So if you are interested in selling your pi network coins at a high rate tho. Or you can't wait till the mainnet launch in 2026. You can easily trade your pi coins with a merchant.
A merchant is someone who buys pi coins from miners and resell them to Investors looking forward to hold massive quantities till mainnet launch.
I will leave the telegram contact of my personal pi vendor to trade with.
@Pi_vendor_247
Financial Assets: Debit vs Equity Securities.pptxWrito-Finance
financial assets represent claim for future benefit or cash. Financial assets are formed by establishing contracts between participants. These financial assets are used for collection of huge amounts of money for business purposes.
Two major Types: Debt Securities and Equity Securities.
Debt Securities are Also known as fixed-income securities or instruments. The type of assets is formed by establishing contracts between investor and issuer of the asset.
• The first type of Debit securities is BONDS. Bonds are issued by corporations and government (both local and national government).
• The second important type of Debit security is NOTES. Apart from similarities associated with notes and bonds, notes have shorter term maturity.
• The 3rd important type of Debit security is TRESURY BILLS. These securities have short-term ranging from three months, six months, and one year. Issuer of such securities are governments.
• Above discussed debit securities are mostly issued by governments and corporations. CERTIFICATE OF DEPOSITS CDs are issued by Banks and Financial Institutions. Risk factor associated with CDs gets reduced when issued by reputable institutions or Banks.
Following are the risk attached with debt securities: Credit risk, interest rate risk and currency risk
There are no fixed maturity dates in such securities, and asset’s value is determined by company’s performance. There are two major types of equity securities: common stock and preferred stock.
Common Stock: These are simple equity securities and bear no complexities which the preferred stock bears. Holders of such securities or instrument have the voting rights when it comes to select the company’s board of director or the business decisions to be made.
Preferred Stock: Preferred stocks are sometime referred to as hybrid securities, because it contains elements of both debit security and equity security. Preferred stock confers ownership rights to security holder that is why it is equity instrument
<a href="https://www.writofinance.com/equity-securities-features-types-risk/" >Equity securities </a> as a whole is used for capital funding for companies. Companies have multiple expenses to cover. Potential growth of company is required in competitive market. So, these securities are used for capital generation, and then uses it for company’s growth.
Concluding remarks
Both are employed in business. Businesses are often established through debit securities, then what is the need for equity securities. Companies have to cover multiple expenses and expansion of business. They can also use equity instruments for repayment of debits. So, there are multiple uses for securities. As an investor, you need tools for analysis. Investment decisions are made by carefully analyzing the market. For better analysis of the stock market, investors often employ financial analysis of companies.
If you are looking for a pi coin investor. Then look no further because I have the right one he is a pi vendor (he buy and resell to whales in China). I met him on a crypto conference and ever since I and my friends have sold more than 10k pi coins to him And he bought all and still want more. I will drop his telegram handle below just send him a message.
@Pi_vendor_247
what is the future of Pi Network currency.DOT TECH
The future of the Pi cryptocurrency is uncertain, and its success will depend on several factors. Pi is a relatively new cryptocurrency that aims to be user-friendly and accessible to a wide audience. Here are a few key considerations for its future:
Message: @Pi_vendor_247 on telegram if u want to sell PI COINS.
1. Mainnet Launch: As of my last knowledge update in January 2022, Pi was still in the testnet phase. Its success will depend on a successful transition to a mainnet, where actual transactions can take place.
2. User Adoption: Pi's success will be closely tied to user adoption. The more users who join the network and actively participate, the stronger the ecosystem can become.
3. Utility and Use Cases: For a cryptocurrency to thrive, it must offer utility and practical use cases. The Pi team has talked about various applications, including peer-to-peer transactions, smart contracts, and more. The development and implementation of these features will be essential.
4. Regulatory Environment: The regulatory environment for cryptocurrencies is evolving globally. How Pi navigates and complies with regulations in various jurisdictions will significantly impact its future.
5. Technology Development: The Pi network must continue to develop and improve its technology, security, and scalability to compete with established cryptocurrencies.
6. Community Engagement: The Pi community plays a critical role in its future. Engaged users can help build trust and grow the network.
7. Monetization and Sustainability: The Pi team's monetization strategy, such as fees, partnerships, or other revenue sources, will affect its long-term sustainability.
It's essential to approach Pi or any new cryptocurrency with caution and conduct due diligence. Cryptocurrency investments involve risks, and potential rewards can be uncertain. The success and future of Pi will depend on the collective efforts of its team, community, and the broader cryptocurrency market dynamics. It's advisable to stay updated on Pi's development and follow any updates from the official Pi Network website or announcements from the team.
Turin Startup Ecosystem 2024 - Ricerca sulle Startup e il Sistema dell'Innov...Quotidiano Piemontese
Turin Startup Ecosystem 2024
Una ricerca de il Club degli Investitori, in collaborazione con ToTeM Torino Tech Map e con il supporto della ESCP Business School e di Growth Capital
how to sell pi coins in South Korea profitably.DOT TECH
Yes. You can sell your pi network coins in South Korea or any other country, by finding a verified pi merchant
What is a verified pi merchant?
Since pi network is not launched yet on any exchange, the only way you can sell pi coins is by selling to a verified pi merchant, and this is because pi network is not launched yet on any exchange and no pre-sale or ico offerings Is done on pi.
Since there is no pre-sale, the only way exchanges can get pi is by buying from miners. So a pi merchant facilitates these transactions by acting as a bridge for both transactions.
How can i find a pi vendor/merchant?
Well for those who haven't traded with a pi merchant or who don't already have one. I will leave the telegram id of my personal pi merchant who i trade pi with.
Tele gram: @Pi_vendor_247
#pi #sell #nigeria #pinetwork #picoins #sellpi #Nigerian #tradepi #pinetworkcoins #sellmypi
The Evolution of Non-Banking Financial Companies (NBFCs) in India: Challenges...beulahfernandes8
Role in Financial System
NBFCs are critical in bridging the financial inclusion gap.
They provide specialized financial services that cater to segments often neglected by traditional banks.
Economic Impact
NBFCs contribute significantly to India's GDP.
They support sectors like micro, small, and medium enterprises (MSMEs), housing finance, and personal loans.
how can I sell pi coins after successfully completing KYCDOT TECH
Pi coins is not launched yet in any exchange 💱 this means it's not swappable, the current pi displaying on coin market cap is the iou version of pi. And you can learn all about that on my previous post.
RIGHT NOW THE ONLY WAY you can sell pi coins is through verified pi merchants. A pi merchant is someone who buys pi coins and resell them to exchanges and crypto whales. Looking forward to hold massive quantities of pi coins before the mainnet launch.
This is because pi network is not doing any pre-sale or ico offerings, the only way to get my coins is from buying from miners. So a merchant facilitates the transactions between the miners and these exchanges holding pi.
I and my friends has sold more than 6000 pi coins successfully with this method. I will be happy to share the contact of my personal pi merchant. The one i trade with, if you have your own merchant you can trade with them. For those who are new.
Message: @Pi_vendor_247 on telegram.
I wouldn't advise you selling all percentage of the pi coins. Leave at least a before so its a win win during open mainnet. Have a nice day pioneers ♥️
#kyc #mainnet #picoins #pi #sellpi #piwallet
#pinetwork
how can I sell pi coins after successfully completing KYC
An exploration of the finance growth nexus-long run and causality evidences from selected countries of saarc region
1. Journal of Economics and Sustainable Development www.iiste.org
ISSN 2222-1700 (Paper) ISSN 2222-2855 (Online)
Vol.4, No.11, 2013
18
An Exploration of the Finance -Growth Nexus: Long Run and
Causality Evidences from Selected Countries of SAARC Region
Abdur Rehman1
and Dr.Ahmed Raza Cheema2
rehmansargodha@yahoo.com , cheemaahmed_raza@yahoo.com
1
Researcher is working with a leading financial institution in Pakistan.
2
Assistant Professor at Department of Economics University of Sargodha, Sargodha, Pakistan.
Abstract
The debate on direction of Granger causality between financial development and real sector growth has been
growing issue since 1980’s. Researchers are fanatical to empirically discern long run and casual relationship for
devising economic policies. This study empirically investigated the finance growth nexus and Causality in the
selected countries of SAARC region (Pakistan, India, Nepal and Sri Lanka) using the yearly data set from 1975-
2009. The study employed the variables of banking sector as a proxy to financial development. Results of
Maddala & Wu and Kao co-integration tests confirm that long run relationship exists between the financial and
real sector variables. Result of Causality shows that it runs from real sector growth to financial sector
development through proxy of Ratio of Liquid Liabilities to GDP per capita, Ratio of Private Credit by Deposit
Money Banks and Financial Institutions to GDP per capita, Ratio of Bank deposits to GDP per capita and Ratio
of commercial bank assets to sum of commercial banks plus central bank assets in the SAARC region.
Keywords:Financial Sector Development, Real Sector Growth, Panel Co-Integration, VECM, Granger Causality,
SAARC region
I-Introduction
Financial development is a process that extends & augments the financial services of banks and other financial
institutions. With the sophistication of technology the role of financial intermediaries has become more
important than before. Every government desires a well established and sophisticated financial sector since a
strong and efficient financial system is a prerequisite of a state. It enables swift transfer of money from one
destination to the other; offer more competitive products thereby increasing the flow of capital within the
economy that results in augmenting real sector growth. Thus a more efficient and robust financial system provide
proficient services that help to boost GDP per capita income.
In pursuit of a developed nation, developing countries join their hands together and establish regional
associations with the objectives to enhance financial and real sector performance. A number of economic
organizations & regions like SAARC, ASEAN, OECD, MENA, OIC, etc. were set up with one of the objective
of economic growth and development. Following the triumphant practices of regional associations, SAARC
organization was established on Dec 08, 1985. The founder members of the organization were India, Pakistan,
Nepal, Sri Lanka, Bhutan and Maldives. Later on Afghanistan joined the regional association in April 2007. The
prime objective of the SAARC region was to accelerate economic and social development. The other objectives
were to improve quality of life, self-reliance and mutual economic assistance.
SAARC countries in the late 1980’s and early 1990’s had implemented reforms to restructure their financial
sector proposed by the international financial institutions and in line with financial steps taken by industry. The
main reforms were based on privatization of government owned financial institution to reduce the state
intervention in financial decisions (Qayyum: 2007, Khan and Khan: 2007, Lawrence & Longjam: 2003, Ghatak:
1997, Gajurel & Pradhan: 2012).
In this context a number of researchers probed the linkage between financial development and economic growth
on the basis of regions, both in time series and cross sectional context. Naceur and Ghazouani (2007), Abu -
Bader and Abu -Qarn (2008) investigated the MENA region, Ramlal and Watson (2005) CARICOM region,
Akinlo and Egbetunde (2010) sub Saharan African region, Shan and Morris (2002), Hassan et al (2011) OECD
countries, Fase and Abma (2003) South East Asia ,Atindehou et al (2005) West African states are few among
others. But a very little work has been found in the literature that traced the finance growth nexus in the SAARC
region. The main economic indicators of SAARC selected countries are given in Table 1.
2. Journal of Economics and Sustainable Development www.iiste.org
ISSN 2222-1700 (Paper) ISSN 2222-2855 (Online)
Vol.4, No.11, 2013
19
Table 1 Real Sector Indicators of Selected Countries of SAARC
Real Sector Indicators
Indicator India Nepal Pakistan Sri Lanka
Population(In Millions) 1214.5 29.9 184.8 20.4
GDP US$(Billion) 1538 15.8 174.9 49.7
GDP/Capita (US$) 1265 562 1050 2435
GDP(PPP) as share of % world total 5.40 0.05 0.63 0.14
Source The World Competitive Report 2011-2012, The World Economic Forum Geneva, data has been
compiled by the Author.
The above data shows main economic indicators of the countries selected for empirical analysis. India is the
most populated country and hence her GDP in $ amounts is higher among other countries. Gross domestic
product per inhabitant is higher in Sri Lanka and that of Nepal is lowest among these countries.
Strengthening the banking sector is pivotal issue in developing and emerging economies as financial sector leads
economic growth through one of banking channel i.e. mobilization of savings (King and Levine, 1993; Rajan
and Zingales, 1998). This study investigates finance growth nexus in selected countries of SAARC region. The
study empirically probed the following research questions.
RQ1: Is there any Long Run relationship between financial development and real sector growth in selected
countries of SAARC Region?
RQ2: Is there any Granger Casual relationship between financial development and real sector growth in
selected countries of SAARC Region?
The rest of the paper is organized as follows; Section-II deals with literature review on finance growth nexus,
Section-III with variables, data sources, Section-IV deals with econometric methodology & economic
framework and last section deals with discussion on outcome of empirical research and conclusion of study.
II-Literature Review
Financial sector plays an important role in the real sector development of a country. A large body of research
investigated the sources of financial development that pave the path for real sector growth. The studies that
traced the finance growth relationship through banking sector proxies, few among others are Demetriades and
Hussein (1996); Arestis and Demetriades, 1997 King and Levine (1993) Beck et al (2000) Christopoulos and
Tsionas (2004); Apergis et al (2007), Ramlal and Watson (2005), Lartey and Farka (2011), Fase and Abma
(2003), Habibullah and Eng (2006) and Acharya et al (2009). The results of empirical research showed that there
exists a positive relationship between financial development and real sector growth. At the same time few
suggested a weak relationship between financial development and economic growth Atindehou et al (2005).
Demetriades and Hussein (1996) probed causal relationship between financial development and economic
growth. The co-integration technique and Maximum likelihood methods were employed on banking sector
variables. The result showed that financial sector was a leading sector in Sri Lanka, Honduras and Spain. In
Venezuela, Guantemala, Thailand, Honduras, Korea, India and Mauritius causality suggested a bi-directional
relationship between financial and real sector growth. The result suggested that financial sector is not a leading
sector in countries i.e. Grace, Turkey, Pakistan, South Africa, El Salvador and Portugal. Furthermore, Korea and
Thailand exhibited a bi-directional causation, reflecting that both real and financial sector contributed in the
growth process.
Ram (1999) investigated the relationship on 95 countries data set for the period from 1960-1989. The result
showed an existence of positive correlation between financial development and real sector growth in 39
countries and negative in remaining 56. The study concluded a weak relationship. Furthermore, result showed
that if liquidity is increased in low and medium income countries growth rate shall also increase.
Shan and Morris (2002) investigated the relationship between indicators of financial development and real sector
growth. The authors used sample of 19 OECD countries along with China & South Korea by taking time series
data from 1985-1998. The results of VAR Model suggested that i) uni-directional causality in Finland and
Portugal from total credit to real sector growth. ii) China, Italy, South Korea and Canada depicted causality from
real sector to credit iii) Bi-directional causation in USA, Japan, Australia and Denmark. Christopoulos and
Tsionas (2004) investigated long run relationship between financial development and economic growth by using
both time series and cross section data over the period from 1970-2000 on ten developing countries. Both cross
section and time series test provided a unique co-integration vector. The uni-directional causality was observed
from financial depth to economic growth. The test inferences provide evidence in favor of existence of long run
relationship between output and financial depth. A causal relationship was found from financial depth to output,
which is uni-directional. Moreover, a short run relationship was observed between output and financial depth.
Arestis et al (2004) probed whether financial structure of a country influence real sector growth or not. The
3. Journal of Economics and Sustainable Development www.iiste.org
ISSN 2222-1700 (Paper) ISSN 2222-2855 (Online)
Vol.4, No.11, 2013
20
result suggests the existence of a long run relationship among the variables. The financial structure explains real
growth process. Ramlal and Watson (2005) examined the relationship on quarterly data for the period 1970-2002
for Barbados, Trinidad & Tobago and Jamaica. The variables used in study were Broad Money divided by GDP,
domestic credit to private sector divided by GDP and Per capita growth in real GDP. The causality inferences
showed a bi -directional causation between financial development and economic growth.
Liu and Hsu (2006) probed the relationship for Japan, Taiwan and Korea on quarterly data set from 1971 to 2001.
Results suggest that financial sector played significant effects on the real sector growth of Taiwan whereas no
role was observed in economic growth of Japan and Korea. Acharya et al (2009) examined the relationship on
panel data set of nine Indian states. The study found that a long run relationship exists between real sector
growth and financial development. The direction of casualty runs from real sector growth to credit. Hassan et al
(2011a) probed the relationship on time series pattern of 68 countries from 1980-2007. The results suggested a
long run linkage between economic growth and financial development in developing countries. OECD countries
with highest values showed the existence of larger financial system. Whereas indicators of credit available to
private sector and availability of liquid liabilities in south Asia and sub Saharan African region showed low
financial depth. Both domestic credit to private sector and domestic credit to banking sector were positively
linked with real sector growth. The Granger results showed bi-directional causality between financial
development and economic growth in all the regions except East Asia and Sub Saharan African, where uni –
directional causality from finance to growth exists.
Fukuda and Dahalan (2011) studied the finance growth nexus on Mexico, India and Indonesia. The study used
proxies of Money supply, private credit by deposit money banks assets to measure financial development.
Furthermore, causal relationship between finance and growth was bi-directional in India, unidirectional in
Indonesia from finance to growth and a complex relationship exists in Mexico as both variables behaved
negatively. Ellahi and Khan (2011) investigated the possible relationship in selected countries of SAARC region.
The study employed Autoregressive distributive lag (ARDL) approach to find the long run relationship. The
results suggest that financial reforms impacts positively in Pakistan, India and Sri Lanka. The one way causality
runs from real sector growth to financial development.
Many authors attempted to trace the relationship through various techniques that empirically probed on different
countries & regions. The literature on finance growth nexus showed that researchers used both time series and
panel data techniques to investigate the linkage. The researcher that based their work on time series techniques
are, Demetriades and Hussein (1996), Rousseau and Wachtel (2000),Rousseau and Xiao(2007) and those who
applied cross section data examination techniques were King and Levine(1993), Levine (1997),Levine et al
(2000),Beck et al (2000),Christopoulos and Tsionas(2004) ,Beck et al (2009),Naceur and Ghazouani(2007),Beck
and Levine (2004),Jamil (2010),Jude (2010),Handa and Khan (2008),Shan and Morris (2002),Cole et al (2008).
However, the general consensus of the researchers is that there exists a long run relationship between financial
and real sector.
III-Proxies of financial development and real sector growth, Data Sources
3.1 Data and its Sources
This study found the relationship between financial development and economic growth on the selected countries
of South Asian Association for Regional co-operation (SAARC). The data on selected variables was obtained for
35 years from 1975-2009 on Pakistan, India, Sri Lanka and Nepal. Since said study combines the Time Period (T)
and Cross Section (N) , it was difficult to find the data for a period of study resultantly study constrained to
analyze on four countries due to unavailability of data for the rest. Following the practices in literature of Luintel
et al (2008), Jamil (2010), data has been obtained from the World Banks Beck et al (2009) Financial Structure
Dataset .Whereas the data on Ratio of GDP to per capita on Current US $ has been obtained from World Bank
development indicators database. Only GDP is taken in the logarithmic form.
3.2 Indicators of financial development and real sector growth
In this study, financial development role is measured by employing banking sector indicators and that of real
sector through GDP per capita (Current US $). This study used indicators that represent financial sector size,
activity, credit distribution and efficiency. These are 1) - Ratio of Liquid Liabilities to GDP per capita (LL),
which captures the absolute size of financial intermediation. This indicator measures the relative size of the
financial sector with that of economy and hence indicator of financial depth of the economy. 2) -Ratio of Private
Credit by Deposit Money Banks and Financial Institutions to GDP per capita (PRVCR) captures the activity of
financial intermediation. It highlights the role of financial intermediaries in credit disbursement within the
economy (it excludes credit extended to central, provisional and local governments and other public sector
entrepreneurs). 3) -Ratio of Commercial Bank Assets to Central Bank Assets plus Commercial Bank Assets
(DMBCBA), this indicator is a symbol of society’s allocation of savings in the banking channels. It separates the
role of monetary authorities with that of commercial banks to channelize the assets for economic growth and
4. Journal of Economics and Sustainable Development www.iiste.org
ISSN 2222-1700 (Paper) ISSN 2222-2855 (Online)
Vol.4, No.11, 2013
21
measures comparative magnitude of in financial sector. 4) -Ratio of Bank Deposits to GDP (BD) shows the
availability of resources with commercial banks for extending loans to private sector and finally 5) - Ratio of
GDP per Capita Income (GDP), used to measure real sector growth. The expected signs of these indicators are
positive with GDP growth as all these variables augment it. The descriptive statistics on yearly data set from
1975-2009 used in this research is given below in table No.2.
Table 2 Descriptive Statistic of Sample
GDP LL PRVCR DMBACBA BD
Mean 5.894625 0.388969 0.222691 0.761462 0.294815
Maximum 7.629059 1.007257 0.653153 0.984048 0.826217
Minimum 4.591338 0.123428 0.037150 0.492064 0.064662
Std. Dev. 0.62549t5 0.137003 0.095323 0.119491 0.121750
Observations 140 140 140 140 140
As far as SAARC region is concerned a little attention has been paid to find the long run relationship and
causality among the variables of financial and real sector growth. Therefore, this paper wants to trace the co-
integration and Granger causality between financial intermediaries and real sector growth variables in the
selected countries of SAARC region.
IV-Econometric Methodology and Framework
Study is based on Panel data technique to find the relationship between economic growth and financial
development. This study estimated relationship by using the following model.
( )E S G f F S D=
Where, ESG = Economic Sector Growth & FSD = Financial Sector Development.
Equation can be written as
,( , , , )it it it it itGDP f PRVCR LL BD DMBCBA=
Where
itGDP =Gross Domestic Product per Capita
PRVCR it =Ratio of Private Credit by Deposit Money Bank and Other Financial Institutions to GDP per Capita
LL it = Ratio of Liquid Liabilities to GDP per Capita
BD it = Ratio of Bank Deposits to GDP per Capita
DMBCBA it = Ratio of Commercial Bank Assets to sum of Deposit Money Bank Assets plus Central Bank
Assets
The economic relationship can be expressed in the form of econometric equation as
0 1 2 3 4it it it it it itGDP PRVCR LL BD DMBCBA eβ β β β β= + + + + +
In the above Model 1...4i = & 1...35t = i.e. i is cross sections i.e. India (IND), Nepal (NPL), Pakistan
(PAK) and Sri Lanka (LKA) and the time period (t) is from 1975-2009.
The objective of study is to find the Casual long run relationship between variables of economic growth and
financial intermediation .It revolve around three steps i.e., First, stationarity of the variables checked with
various Panel unit root methods namely Im, Pesaran & Shin (2003), ADF Fisher Chi Square, Phillips-Perron
Fisher Test (1999).Second, as variables are stationary at first difference, study tested for co-integration using
Maddala and Wu (1999) Johansen methodology of Fisher type and Kao (1999) approach. Third, Granger
causality test applied through Vector Error Correction Model (VECM) to find the direction of causation between
financial development and economic growth.
4.1 Panel Unit Root
It is a standard practice in literature to check stationarity of time series data to be investigated. The literature
suggests that panel based unit root tests have higher power than that of time series, see Breitung (2000), Levin,
Lin and Chu (2002), Im, Pesaran and Shin(2003),Baltagi(2005),and Wang (2009) . Granger and Newbold (1974),
Stock and Watson (1988) found that estimation with non-stationary data provides spurious regression and
produce usual test statistic as unreliable and unauthenticated. No economic meaning among the variables can be
concluded in the presence of Unit root. Further the Mean, variance and co-variance of non-stationary series are
time variant thus provide ambiguous results. Dickey et al (1991) found that trended series creates problems for
econometric interpretations that conclude spurious relationship among variables and provides inconsistent results
on regression of one variable on another. Granger (1986) suggested that non-stationary series can be made
stationary if differenced properly and such procedure is known as Order of Integration.
5. Journal of Economics and Sustainable Development www.iiste.org
ISSN 2222-1700 (Paper) ISSN 2222-2855 (Online)
Vol.4, No.11, 2013
22
Study employed Panel unit root tests proposed by 1) -Im, Pesaran & Shin W -stat 2) -Maddala and Wu ADF
Fisher Chi Square Test and 3) - Maddala and Wu Phillips-Perron Fisher Chi Square Test. These tests are known
as first generation panel unit root tests and are based on cross sectional independence assumption (Hurlin and
Mignon 2006). The Null Hypothesis in ADF Fisher Chi Square, PP Fisher Chi square and Im, Pesaran & Shin
test is of No unit root against alternative that some cross sections without unit root .These tests are based on
individual unit root process that allow for different auto regressive coefficient in the series. Study employed
above tests on individual intercept, individual intercept & trend.
4.1.1 Im, Pesaran and Shin W statistic
IPS test is named after the contribution of Im, Pesaran and Shin (2003). This test is based on the assumption of
Null Hypothesis that series contains a unit root for all countries with alternative that a fraction of panel series is
stationary i.e. it allows heterogeneous co-efficient. The said test assumes balanced panel and have following
specific equation
∑
1
,1,
ip
j
itjtiijtiiiit yyy
=
− +∆++=∆ εβρα Where i = 1. . .N and t = 1. . .T
The said test allows separate non-stationary test for each cross section unit. It is also based on the Augmented
Dickey-Fuller test averaged on cross sections of panel. In IPS test “t” is nothing than average of individual cross
sections ADF t statistic. The specific equation is as follows
∑ )βp(t
N
1
=t
N
1=i
iiiTNT
In IPS test, study shall reject the null hypothesis when t –bar is smaller than critical value from lower tail of a
standard normal distribution. If t-bar is significant then study concludes to reject null hypothesis or panel data is
stationary. Otherwise, if t-bar is not significant then conclude to accept null hypothesis or panel data has unit
root.
4.1.2 ADF Fisher Chi Square and PP Fisher Chi Square
Maddala and Wu (1999) type ADF Fisher Chi-square panel unit root test and Fisher PP Chi-square panel unit
root tests are based on the R.A Fisher (1932) type tests. The assumption behind the test is cross sectional
independence and has the following specific equation
P λ = -2
1
log
N
e
i=
∑ pi , Where
pi = panel unit root Fisher Type test
N = all cross-section N
-2
1
log
N
e
i=
∑ pi = χ2 distribution with d.f 2N
The said test is based on Chi Square (χ2) distribution with 2N degree of freedom. The test is based on
Augmented Dickey Fuller test. Benerjee (1999) found that said test is attractive due to choice of lag length and
sample size.
4.2 Panel Co-integration
Granger (1988), Dickey et al (1991), Wang (2009) states that if there exists a stationary linear combination
between the variables, a non-stationary series I (1) have a co-integration relationship i.e. one or more linear
combinations are in stochastic process, if individually not. The said relationship is called long run equilibrium
relationship among variables.
4.2.1 Maddala and Wu Co-integration Test
Maddala and Wu (1999) developed panel co-integration test by using Fisher’s approach. This test is also known
as combined Johansen test for panel co-integration. Like Panel unit root tests, this technique also gives the
advantage of both time series (T) and cross sectional dimensions (N). It uses Fisher results to propose an
alternative approach for co-integration to obtain test statistic for complete set of panel observations after
combining the panel data from individual cross sections. It is based on the rank of matrix that determines the
existence of number of co-integrating vectors. The specific equation form of Maddala and Wu test is as
∆Yi, t = Πiyi, t−1 + Tk ∆Yi, t−k + ui, t
Maddala and Wu (1999) Johansen's co-integration test results are based on p-values. Johansen (1988) proposed
two types of approaches in non-stationary time series to find co-integration relationship i.e. Fisher Likelihood
Ratio trace statistic and Fisher maximum eigenvalue statistics. The specific form of equation for trace statistic is
given below
6. Journal of Economics and Sustainable Development www.iiste.org
ISSN 2222-1700 (Paper) ISSN 2222-2855 (Online)
Vol.4, No.11, 2013
23
∑+
−−=
n
r
itrace Tr
1
)ˆ1ln()( λλ
In the above trace statistics T represents sample size and ˆ
iλ estimates characteristic root. The equation for
maximum eigenvalue is given as under.
)ˆ1ln()1,( 1max +−−=+ rTrr λλ
In Maddala and Wu type Johansen Fisher test, the Null and alternative hypothesis in trace statics are as under
0 1: ( ) (at most r integrated vector) and : ( ) (at least r+1 integrated vector)H rank r H rank rπ π≤ >
If test rejects Null hypothesis i.e. 0H it means that there exists at least r+1 long term integrated relationship
among the variables.
Whereas the specific form of Null and alternative hypothesis in maximum eigenvalue is as
0 1: ( ) (at most r integrated vector) and : ( ) (at least r+1 integrated vector)H rank r H rank rπ π≤ >
In above maximum eigenvalue statistics, if test statistic accepts 0H it means there exists r co-integrating vectors
among variables. The hypothesis of said test statistic is that it do not have any co-integrated relationship that is r
= 0. If accepted, then test has added the number of co-integrating variables till can’t reject 0H that means
variables have r cointegrated vector. In the panel data set Fisher type Johansen test has following specific form,
which measures existence of long run relationship between the economic growth and financial development
variables .The said test uses the chi-square statistic to access the co-integrating vectors in the panel data. The test
statistic uses p-values
CT = -2
1
log
N
i=
∑ πi 0H =No Co-integration
4.3 Kao Co-Integration Test
Kao (1999) used both DF and ADF test for co-integration in panel. This test is similar to the standard approach
adopted in the Engle Granger two step procedures. Test start with panel regression model as set out in following
equation
it i it itY X uα β= + +
Where Y and X is presumed to be non-stationary and i=1,….., N and t=1,…., T
1
ˆit it itu eu v−= +
Where itu = (Yi t - Xi t ß^
i t - Zi t γ^
) are the residuals from estimating equation. The hypotheses in Kao test are
as H0: ρ = 1 null hypothesis of no co-integration between X and Y
And H1: ρ < 1 Y and X are co-integrated.
Both Dickey Fuller -Type test statistics (DF) and Augmented Dickey Fuller (ADF) test statistics are used in Kao
test to investigate co-integration in panel. Kao propose four specific Dickey Fuller (DF) type test statistic and
one Augmented Dickey Fuller (ADF) type test statistic.
4.4 Granger Causality Tests
Co-integration tests of Maddala and Wu and Kao are able to indicate the existence of long run relationship
among the variables only. The results of Co-integration establishes that a long run relationship exists but do not
tell about the direction of causality. Direction of causality has specific importance in economic literature;
therefore, it is necessary to find the direction of causality for finance growth nexus in selected countries of
SAARC region.
Granger (1988) states that if two variables say 1tX and 2tX are co-integrated and each is stationary at first
difference i.e. I (1) individually, then either 1tX Granger Causes 2tX or 2tX Granger causes 1tX .To find the
direction of Causality for a panel based data Vector Error Correction Model (VECM) was employed using the
Wald test. The VECM regresses the changes in both endogenous variables and exogenous variables on lagged
deviations. VECM approach serves two basic purposes besides indicating direction of causality i.e. Short run
causality and long run causality. If Granger causality exists then it tells about interdependence of variables of
economic growth on financial development and vice versa. The Granger causality represents three types of
relationships i.e.bi-directional or two way causality, uni -directional or one way causality and no causality. The
specific form of the model is given as
7. Journal of Economics and Sustainable Development www.iiste.org
ISSN 2222-1700 (Paper) ISSN 2222-2855 (Online)
Vol.4, No.11, 2013
24
1 1 1 1 2
1 1
1 3 1 4 1 5
1 1 1
1 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . (1 )
m m
i t j i p i t p i p i t p
p p
m m m
i p i t p i t p i t p
p p p
i i t i i t
i t
G D P G D P L L
P R V C R B D D M B C B A
u E C T e
L L
π π π
π
− −
= =
− − −
= = =
−
= + ∆ + ∆ +
∆ + ∆ + ∆ +
+
∑ ∑
∑ ∑ ∑
2 2 1 2 2
1 1
2 3 2 4 2 5
1 1 1
2 2
3
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ( 2 )
m m
j i p i t p i p i t p
p p
m m m
i p i t p i t p i t p
p p p
i i t i i t
i t j
L L G D P
P R V C R B D D M B C B A
u E C T e
P R V C
π π π
π
π
− −
= =
− − −
= = =
−
= + ∆ + ∆ +
∆ + ∆ + ∆ +
+
=
∑ ∑
∑ ∑ ∑
3 1 3 2
1 1
3 3 3 4 3 5
1 1 1
3 3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ( 3 )
m m
i p i t p i p i t p
p p
m m m
i p i t p i t p i t p
p p p
i i t i i t
P R V C L L
G D P B D D M B C B A
u E C T e
π π
π
− −
= =
− − −
= = =
−
+ ∆ + ∆ +
∆ + ∆ + ∆ +
+
∑ ∑
∑ ∑ ∑
4 4 1 4 2
1 1
4 3 4 4 4 5
1 1 1
4 4 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ( 4 )
m m
i t j i p i t p i p i t p
p p
m m m
i p i t p i t p i t p
p p p
i i t i i t
B D B D L L
P R V C R G D P D M B C B A
u E C T e
D M B C B
π π π
π
− −
= =
− − −
= = =
−
= + ∆ + ∆ +
∆ + ∆ + ∆ +
+
∑ ∑
∑ ∑ ∑
5 5 1 5 2
1 1
5 3 5 4 5 5
1 1 1
5 5 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ( 5 )
m m
i t j i p i t p i p i t p
p p
m m m
i p i t p i t p i t p
p p p
i i t i i t
A D M B C B A L L
P R V C R B D G D P
u E C T e
π π π
π
− −
= =
− − −
= = =
−
= + ∆ + ∆ +
∆ + ∆ + ∆ +
+
∑ ∑
∑ ∑ ∑
Where, represents lag operator and Ρ stands for lag length in the above VECM frame work. The above frame
work allows for causality direction. ECT shows error correction term. The Error Correction Term (ECT) co-
efficient i.e. 1iu .. 6iu , quantify tendency of each variable to return towards equilibrium position.
V-Empirical Results and Discussions
In this section the results obtained on finance growth nexus are discussed. At first step, in order to check
stationary or non stationary of variables this study employed three panel Integration tests under the Null
Hypothesis that series contain a unit root. Therefore, a rejection of Null hypothesis means that series does not
have a unit root and is interpreted as evidence of stationary data. In unit root tests, lag order for determining the
unit root process was based on automatic lag selection criteria i.e. Schawz Information Criteria (SIC) whereas
Kernel method was based on Bartlett and Bandwidth selection was based to Newey-west method.
5.1 Results of Panel Unit Root Tests
This paper employed panel unit root tests of Im, Pesaran and Shin (2003), Maddala & Wu (1999) for both Fisher
type using ADF and PP test .The results are given hereunder
8. Journal of Economics and Sustainable Development www.iiste.org
ISSN 2222-1700 (Paper) ISSN 2222-2855 (Online)
Vol.4, No.11, 2013
25
Table 3 Panel Unit Root Tests
Variable
IPS Fischer-ADF Fischer-PP
Intercept
Only
Intercept
+Trend
Intercept
Only
Intercept
+Trend
Intercept
Only
Intercept
+Trend
LGDP
3.81055
(0.9999)
0.66801
(0.7479)
1.02575
(0.9981)
5.82907
(0.6664)
1.67029
(0.9895)
6.40848
(0.6016)
D(LGDP)
-9.44145***
(0.0000)
-8.88527***
(0.0000)
82.0179***
(0.0000)
71.1632***
(0.0000)
82.3167***
(0.0000)
71.6208***
(0.0000)
LL
5.85656
(1.0000)
4.41582
(1.0000)
8.34791
(0.4002)
16.4224**
(0.0367)
3.62057
(0.8896)
3.25982
(0.9170)
D(LL)
-3.31762***
(0.0005)
-1.49697*
(0.0672)
50.2467***
(0.0000)
28.5663***
(0.0004)
63.7977***
(0.0000)
127.941***
(0.0000)
PRVCR
3.08422
(0.9990)
1.67236
(0.9528)
5.94553
(0.6533)
8.64040
(0.3735)
2.12690
(0.9769)
2.66768
(0.9535)
D(PRVCR)
-1.43896*
(0.0757)
-0.41527
(0.3390)
29.2178***
(0.0003)
21.3379***
(0.0063)
25.7203***
(0.0012)
18.2272**
(0.0196)
DMBCBA
1.98763
(0.9766)
-0.76648
(0.2217)
1.72943
(0.9982)
11.9394
(0.1539)
1.85307
(0.9852)
7.89184
(0.4441)
D(DMBCBA)
-8.57410***
(0.000)
-7.97239***
(0.000)
73.3226***
(0.0000)
62.6574***
(0.0000)
78.4666***
(0.0000)
88.5860***
(0.0000)
BD
4.16866
(1.0000)
6.11223
(1.0000)
3.32625
(0.9122)
11.3906
(0.1805)
2.38337
(0.9669)
2.09608
(0.9779)
D(BD)
-2.61896**
(0.0044)
-3.45664***
(0.0003)
41.8616***
(0.0000)
34.1647***
(0.0000)
52.7951***
(0.0000)
47.0435***
(0.0000)
Order of
Integration
I(1) I(1) I(1) I(1) I(1) I(1)
***, ** and * denote significance at 1%, 5% and 10% significance level, respectively. P-values are reported in
squared brackets. GDP is ratio of GDP to per captia income, LL is ratio of Liquid Liabilities to GDP per captia,
PRVCR is ratio of Private credit by deposit money bank and other financial institutions to GDP per captia, BD is
ratio of Bank Deposits to GDP per captia, and DMBCBA is the ratio of Deposit Money Bank Assets to Deposit
Money Bank Assets plus Central Bank Assets
Table 3 depicts the results of IPS panel unit tests of Im et al (2003), Maddala and Wu type test of ADF Fisher
and PP-Fischer (1999). The results show that variables employed are non-stationary at level except LL in ADF –
Fischer test at intercept & trend. Therefore, study repeated the panel unit root tests on first difference in
accordance with the guidelines of Granger (1974).The results of unit root employed on first difference unfolds
that all variables are in non-stochastic trend at first difference. Therefore, study concluded that data series is in
I (1) process.
Thus results of Panel unit root tests confirms that variables are non stationary at Level and stationary at First
difference, therefore, the next step is to find the Panel co-integration tests. The first step is to find the appropriate
lag length as Co-integration test of Maddala and Wu is sensitive to it. Lag order by various criteria are given
below in Table 4.
Table 4 VAR Lag Order Selection Criteria
Lag Log L LR FPE AIC SC HQ
0 744.3129 NA 1.78e-11 -10.56161 -10.45655 -10.51892
1 1700.938 1831.254 2.96e-17 -23.87055 -23.24019 -23.61439
2 1773.905 134.4666 1.49e-17 -24.55578 -23.40013* -24.08616*
3 1805.078 55.22155* 1.37e-17* -24.64397* -22.96303 -23.96089
4 1826.772 36.88056 1.45e-17 -24.59675 -22.39052 -23.70020
5 1846.433 32.01925 1.58e-17 -24.52048 -21.78895 -23.41047
6 1862.892 25.62826 1.81e-17 -24.39846 -21.14164 -23.07498
7 1884.632 32.29998 1.94e-17 -24.35189 -20.56978 -22.81495
8 1893.265 12.20974 2.52e-17 -24.11808 -19.81067 -22.36768
* indicates lag order selected by the criterion and LR: sequential modified LR test statistic (each test at 5% level),
FPE: Final prediction error, AIC: Akaike information criterion, SC: Schwarz information criterion, HQ: Hannan-
Quinn information criterion
After finding the lag order the next step is to employee Maddala and Wu technique of Fisher type Johansen
methodology and Kao test to find the co-integration in the Panel structure, detail of which are given hereunder.
9. Journal of Economics and Sustainable Development www.iiste.org
ISSN 2222-1700 (Paper) ISSN 2222-2855 (Online)
Vol.4, No.11, 2013
26
5.2 Results of Co-integration
Granger (1988) suggested that if there exists a stationary linear combination between the variables, a non-
stationary series I (1) have a co-integration relationship i.e. one or more linear combinations are in stochastic
process, if individually not. Therefore, study performed panel co-integration test on variables of interest are in I
(1) process. The results of panel co-integration are discussed in detail in the following table.
Table 5 Co-Integration Results
Hypothesis
Fischer Trace
Statistics
Probability
Fischer
Max Eigen Value
Statistics
Probability
None 102.1*** (0.0000) 53.03*** (0.0000)
At Most 1 57.99*** (0.0000) 42.67*** (0.0000)
At Most 2 23.56** (0.0027) 21.89** (0.0051)
At Most 3 9.488 ( 0.3028) 8.915 (0.3495)
At Most 4 10.09 (0.2584) 10.09 (0.2584)
Kao Co-Integration Test
Kao Test t-Statistics -3.058006** (0.0011)
Notes: probabilities are computed using the asymptotic Chi-square distribution (Maddala and Wu) and t-Statistic
(Kao test); p-values are shown immediately to the right of the relevant test statistic; ***, **, * indicate that the
null hypothesis is rejected at 1, 5, and 10 percent, respectively.
The results highlighted in Table 5 are obtained from Maddala & Wu panel co-integration test (1999) and Kao
test (1999). The study employed five variables that capture financial development and real sector growth.
Therefore, there are chances of existence of at most four co-integrating relationships among the variables.
Results of both Likelihood ratio trace statistics and maximum eigenvalue statistics are given against hypothesis
of none, at most one, at most two, at most three, and at most four co-integration relationships. Both these
statistics determines the co-integrating vectors in the non-stationary panels. The null hypothesis is of No co-
integration in the panel dataset against the alternative that there exists a co-integration in the series. Lag order
has been found by various criteria, the majority of which gives a lag order of 3.But this study has taken the lag
order as 2 from Schwarz information criterion to save the loss of degree of freedom. The Likelihood ratio trace
statistic is 102.1 at 0r = i.e. for none co-integrating relationship, 57.99 at 1r = i.e. for at most one, 23.56 at
2r = for at most two, 9.488 at 3r = for at most three, and 10.09 at 4r = for at most four in the Likelihood
trace statistic. The results of at most none, at most one and at most two co-integration trace statistics are
significant at 1% level of significance. These results of trace statistic suggest that there exist at least two co-
integrating vectors that establish a long run relationship among the variables of financial development and real
sector growth in selected countries of SAARC region.
The results of maximum eigenvalue shows that test statistic is 53.03 at 0r = for none co-integrating
relationship, 42.67 at 1r = for at most one, 21.89 at 2r = for at most two, 8.915 at 3r = for at most
three,10.09 and at 4r = for at most four in the maximum eigenvalue statistics. The results at none, at most one
and at most two are significant at 1% level of significance. This test also suggests that there exists a long run
relationship among variables and found two co-integrating vectors.
Both the results of Maddala and Wu test of co-integration i.e. likelihood trace statistic and eigenvalue statistic
are statistically significant. This shows that there exists a co-integration relationship among the variables of
financial intermediaries and economic sector growth. Thus, it is concluded that GDP per capita, liquid liabilities
to GDP per capita, Private credit by deposit money bank and other financial institutions to GDP per capita, Bank
deposits to GDP per capita and central bank assets as ratio of central bank assets plus domestic money bank
assets have a co-integrating relationship. Therefore, financial development and real sector growth can led the
economic growth in the long run, which is a positive and encouraging sign for the SAARC region.
Kao test statistics (1999) is employed as an alternative test to confirm the robustness of results. The results based
on Kao ADF tests statistic also suggests that there exists a long run relationship as the “t” statistic value rejects
the Null hypothesis of No co-integration at 1% level of significance. Both the panel co-integration tests of
Maddala and Wu (1999) and Kao (1999) confirms that there exists a long run relationship between the variables
of financial intermediaries and economic growth These variables can jointly pave the long run growth in the real
sector of India, Nepal, Pakistan and Sri Lankan. These results are consistent with the findings of Christopoulos
and Tsionas (2004) Cavenaile et al (2011) Levine and Zervos (1998) Iyare and Moore (2011) Akinlo and
Egelunde (2010) Rahamn (2004) Arestis et al (2004) Acharya et al (2009).Rehman and Cheema (2013).
5.3 Results of Granger Causality
The section 5.2 empirically proved that a long run relationship exists among the variables .Granger concluded
10. Journal of Economics and Sustainable Development www.iiste.org
ISSN 2222-1700 (Paper) ISSN 2222-2855 (Online)
Vol.4, No.11, 2013
27
that if there is a co-integration relationship then there must be causality, therefore, it is necessary to find the
direction of causation among the finance growth indicators. The table no. 6 shows results of Vector Error
Correction (VEC) Granger Causality /Block Wald test.
Table 6 Granger Causality-Wald Test
LGDP LL PRVCR DMBCBA BD
LGDP
2.014446
(0.3652)
0.019158
(0.9905)
3.334568
(0.1888)
1.774359
(0.4118)
LL
6.408479**
(0.0406)
0.004355
(0.9978)
2.754358
(0.2523)
3.029743
(0.2198)
PRVCR
5.269098*
(0.0718)
0.593018
(0.7434)
3.925268
(0.1405)
1.750531
(0.4168)
DMBCBA
13.16978**
(0.0014)
1.164253
(0.5587)
7.575196**
(0.0227)
1.173810
(0.5560)
BD
6.490143**
(0.0390)
1.758121
(0.4152)
0.031735
(0.9843)
2.608585
(0.2714)
Notes:-Reported estimates are asymptotic Wald statistics. P-values is in parentheses ( ) showing level of
significance at 10%, 5% and 01% by *, ** and *** respectively.
The result shows the causality among the variables of economic growth and financial development in the
selected countries of SAARC region. The Granger causality result shows a uni -directional relationship from real
sector development to liquid liabilities. The result demonstrates that GDP Granger cause to Liquid liabilities at 5%
level of significance .It means that growth in GDP per capita play a significant role in the real sector of selected
countries of SAARC region as it augment liquid liabilities which is a symbol of financial deepening. These
results are consistent with the findings of Handa and Khan (2008) for Sri Lanka and Abu- Bader and Abu- Qarn
(2008) for Israel who found that causality runs from GDP per capita to liquid liabilities in these countries.
Results are inconsistent with Jamil (2010) for developed countries, Abu- Bader and Abu- Qarn (2008) for
Algeria, Egypt, Morcco and Syria and Perera and Paudel (2009) for Sri Lanka. Furthermore, these results are
also inconsistent with Jamil (2010) as well as with Handa and Khan (2008) for Pakistan that liquid liabilities do
not have casual relationship with real sector growth.
The results of Granger causality showed that uni-directional causality exists between PRVCR and GDP in the
Panel of SAARC countries. This causality runs from GDP to PRVCR at 10% level of significance .Results are
consistent with the findings of Handa and Khan (2008) who found unidirectional causality from GDP to PRVCR
in Sri Lanka , Shan and Morris (2002) found One way from economic growth to credit in Canada, China, Italy &
Korea, Hassan et al (2011) , who found causality from growth to credit in Sub Sahara Africa and Algeria, Egypt
and Morocco and with Rehman and Cheema (2013) who found one- way causality from growth to credit in
Pakistan. Whereas these results are inconsistent with the findings of Handa and Khan (2008) for Pakistan, Shan
and Morris (2002) for France, Greece, Ireland, Netherland, New Zeeland, Norway, Spain, Sweden, Switzerland
and United Kingdom as no causality found. These results are also not consistent with the findings of Jamil (2010)
who found bi-directional relationship between PRVCR and GDP in the panel of 76 countries. The same results
also hold for developed countries where uni directional causality found in the sample of developing countries.
Handa and Khan (2008) found bi-directional causality from GDP to PRVCR in India. Shan and Morris (2002)
found two ways Causality in Australia, Denmark, Japan and USA, and One way from credit to economic Growth
in Finland and Portugal. Hassan et al (2011), found uni-directional causality from PRVCR to growth in Sub
Sahara Africa and Latin Asia, South Asia and Pacific regions Abu Badar and Abu Qarn (2008) found one way
casualty from PRVCR to growth in Algeria, Egypt and Morocco. Atindehou et al (2005) found uni-directional
causality from PRVCR to growth in Mauritania and Sierra Leone
Findings of Granger causality result shows that uni-directional causality exists between real sector growth and
DMBCBA. The results are consistent with Ang and Mekibbin (2007), Zang and Kim( 2007). These results are
inconsistent with Bailliu (2000) who found yuni-directional from Assets to real sector growth, Jamil (2010) who
found bi-directional causality with complete panel and uni-directional from assets to growth with the developed
countries
The results of Granger causality through Vector Error Correction (VEC) Granger Causality /Block Wald tests
runs from real sector to financial development through the variables of liquid Liabilities, DMBCBA and Banking
sector deposits. It means that uni-directional causality runs from growth to finance in the SAARC region. With
the increase in the GDP per capita in these countries the financial deepening and banking sector deposits shall
increase. The role of commercial sector shall also enhance with real sector growth in the region.
5.4 Conclusion and policy Implications.
This study probed the possible long run as well as Granger casual relationship between financial development
and economic growth in the selected countries of SAARC region. It examined finance growth linkage in India,
11. Journal of Economics and Sustainable Development www.iiste.org
ISSN 2222-1700 (Paper) ISSN 2222-2855 (Online)
Vol.4, No.11, 2013
28
Nepal, Pakistan and Sri Lanka covering 35 yearly observations from 1975 to 2009. Empirical results based on
Co-integration tests of Maddala & Wu and Kao t-statistics confirmed that long run finance-growth relationship
exists in the SAARC region. One way causality was found that run from economic growth to financial
development. The study concluded that the financial reforms that were started in late 1980’s and early 1990’s in
SAARC countries were successful in achieving the targets. The policy implication is that these countries should
devise the policies that promote economic growth in the region.
REFERENCES
Abu- Bader, S. and Abu- Qarn, A.S. (2008). “Financial Development and Economic Growth: Evidences From
Six MENA Countries” Review of Development Economics, 12(4):803-81.
Acharya, D. Amanullah, S. and Joy, S. (2009). “Financial Development and Economic Growth In Indian States:
An Examination” International Research Journal of Finance and Economics, 24.
Akinlo A E. and Egbetunde T (2010). “Financial Development and Economic Growth: The Experience of 10
Sub-Saharan African Countries Revisited” The Review of Finance and Banking, 02(01):017-028.
Al-Yousif, Y. K. 2002. “Financial Development And Economic Growth Another Look At The Evidence From
Developing Countries” Review of Financial Economics, 11:131-150.
Ang, J. B. and McKibbin, W. J. (2007) ,Financial liberal- ization, financial sector development and growth:
evidence from Malaysia, Journal of Development Economics, 84, 215–33.
Apergis, N. Filippidis, L. and Economidou, C (2007). “Financial Deepening and Economic Growth Linkages:
A Panel Data Analysis” Review of World Economics, 143(1):179-198.
Arestis P, Luintel, A.D. and Luintel, K.B. (2004). “Does Financial Structure Matter” Working paper No.399,
The Levy Economics Institute of Bard College.
Arestis, P. and Demetriades, P.O (1997) “Financial Development and Economic Growth: Assessing the evidence”
Economic Journal 107,783-799.
Aretsis, P.Demetriades, P.O. and Luintel, K.B. (2001). “Financial Development and Economic Growth: The
Role of Stock Markets “Journal of Money Credit and Banking, 33(1):16-41.
Atindehou, R.B. Gueyie, J.P. and Amenounve, E.K. (2005). “Financial Intermediation and Economic Growth:
Evidences from Western Africa” Journal of Applied Financial Economics, 15:777-790.
Bagehot, Walter. Lombard Street (1924) “A Description of the Money Market”, London: John Murray, 1873.
Reprinted (with introduction by Hartley Withers) London: William Clowes and Sons.
Bailliu, J. N.( 2000) Private capital flows, financial development, and economic growth in developing countries,
Bank of Canada Working Paper No. 2000- 15, Ontario, Canada.
Beck, T. Demirguc-Kunt, A. and Levine, R. (1999). “A New Database on Financial development and Structure”.
The World Bank development Research Group July 1999, WP No.2146.
Beck, T. Demirguc-Kunt, A. and Levine, R. (1999). “A New Database on Financial development and Structure”.
Financial Sector Discussion Paper No. 02 The World Bank development Research Group September 1999.
Beck, T. Demirguc-Kunt, A. and Levine, R. (2009). “Financial Institutions and Markets across Countries and
Over Time. Data and Analysis”, policy research working paper 4943, The World Bank Development
Research Group Financial and Private sector team May 2009.
Beck, T. Levine, R. (2004). “Stock Markets, Banks, and Growth: Panel Evidence” Journal of Banking &
Finance, 28:423-432.
Beck, T. Levine, R. Loayza, N. (2000). “Finance and the Sources of Growth” Journal of Financial Economics,
58:261-300.
Bekaert, G.Harvey, C.R. Lundblad, C.( 2005). “Does Financial Linearization Spur Growth?” Journal of
Financial economics, 77:3-55.
Bencivenga, V.R. and Smith, B.D. (1991). “Financial Intermediation and Endogenous Growth”, Review of
Economic studies, 58:195-209.
Benhabib, J. and Spiegel, M.M. (2000). “The Role of Financial Development in Growth and Investment”Journal
of Economic Growth, 5(4):341-360
Blander, R.D. and Dhaene, G. (2004). “Unit root tests for panel data with AR (1) errors and fixed T”.
Cavenaile, L.Gengenbach, C. and Palm, F. (2011). “Stock Markets, Banks and Long Run Economic Growth: A
Panel Co-integration-Based Analysis” A Working Paper CREPP - Centre de recherche en Economie
Publique et de la Population CREPP WP No 2011/02.
Chakraborty, I. and Ghosh, S.( 2011). “The Relationship Between Financial Development and Economic Growth
and The Asian Financial Crisis: An FMOLS Analysis” Int J Eco. Res, 2(3):88-101.
Christopoulos, D. K. and Tsionas, E. G. (2004). “Financial Development and Economic Growth: Evidence from
Panel Unit Root and Co-Integration Tests”. Journal of development economics, 73:55-74.
Cole, R. A., Moshirian, F. Wu, Q. (2008). “Bank Stock Return and Economic Growth” Journal of Banking and
12. Journal of Economics and Sustainable Development www.iiste.org
ISSN 2222-1700 (Paper) ISSN 2222-2855 (Online)
Vol.4, No.11, 2013
29
finance, 32:995-1007.
Dawson, P.J (2003) “Financial Development and Growth in Economies in Transition” Applied Economics
Letters 10 833-836
Demetriades, P. O. and Hussein, K.A. (1996). “Does Financial Development Cause Economic Growth? Time
Series Evidences From 16 Countries” Journal of Development Economics , 51:387-411.
Demirguc-Kunt, A .and Levine, R. (2008). “Finance and Economic Opportunity” The World Bank Policy
Research Working Paper No.4468.
Demirguc-Kunt, A. and Levine, R. (2004). “Financial Structure and Economic Growth –A Cross Country
Comparisons of Banks, Markets and Development” Cambridge MA, MIT Press USA 17-23.
Demirguc-Kunt, A. and Levine, R. (2008). “Finance, Financial Sector Policies and Long Run Growth”. The
International Bank for Reconstruction and Development, the World Bank Working Paper No.11.
Dickey, D.A and Fuller, W, A. (1981), “Likelihood Ratio Statistics for Autoregressive Time Series with A Unit
Root” Ecnometrica 49(4)1057-1072.
Dickey, D.A., Janes, D.W. and Thrornton, D.L. (1999). “A Premier on Co-Integration with an Application to
Money and Income” Federal Reserve Bank of St.Louis Review, 73(02):58-78.
Dritsaki, C. and Bargiota, M.D, (2005). “The Casual Relationship Between Stock Credit Market And Economic
Development: An Empirical Evidences for Greece”, Economic Change and Restructuring, 38:113-127.
Edirisuriya, P. (2007). "Effects of Financial Sector Reforms in Sri Lanka: Evidence from the Banking Sector",
Asia Pacific Journal of Finance and Banking Research 1(1): 45-64.
Ellahi, N. and Khan, M.A.( 2011). “Testing Finance Growth Nexus: An Auto Regressive Distributed Lag
(ARDL) Methodology Approach For Selected SAARC Countries” South Asian Journal of Management, 18
(02):76-91.
Engle, R.F and Granger, W.J. (1987), “Co-Integration and Error Correction: Representations, Estimation and
Testing”. Ecnometrica 55(2), 251-276.
Fase, M.M.G. and Abma, R.C.N (2003). “Financial Environment and Economic Growth in Selected Asian
Countries” Journal of Asian Economies, 14:11-21
Financial Sector Assessment (2005) “A Handbook- Indicators of Financial Structure Development and
Soundness”, International Bank for Restructuring and development/World Bank and International Monetary
Fund USA. 15-33.
Fry, M. (1997) Emancipating the Banking System and Developing Markets for Government Debt. London,
Routledge, Bank of England, Centre for Central Banking Studies, pp. 37-49.
Fukuda, T. and Dahalan, J. (2011). “Finance- Growth- Crisis Nexus In Emerging Economies: Evidences From
India, Indonesia and Mexico” International Business and Economic Research Journal, 10 (12):59-78.
Gajurel, D.P and Pradhan, R.S, (2012)“Concentration and Competition in Nepalese Banking” Journal of
Business, Economics & Finance Vol.1 (1)
Gajurel, D.P and Pradhan, R.S(2012) “Concentration and Competition in Nepalese banking” Journal of Business,
Economics & Finance 1 (1):2012.
Ghatak, S.(1997): “Financial Liberalization: The Case of Sri Lanka” Empirical Economics 22(1):1997, 117-129.
Goldsmith, R.W. (1969), “Financial Structure and Development”, New Haven, CT: Yale University Press.
Graff, M. (2003). “Financial Development and Economic Growth in Corporatist and Liberal Market Economies”
Emerging Market Finance and Trade, 39 (2): 47-69.
Granger, C.W.J. and Newbold, P. (1974). “Spurious Regression in Econometrics” Journal of Econometrics,
2:111-120.
Grley, J.G and Shaw, E.S ( 1995) “Financial Aspects of Economic Development”, The American Economic
Review, 45:4pp515-538
Habibullah, M.S.and Eng, Yoke-Kee. (2006). “Does Financial Development Cause Economic Growth? A Panel
Data Dynamic Analysis for the Asian Developing Countries”, Journal of the Asia Pacific Economy
11(4):377-393.
Handa, J. and Khan, S.R. (2008). “Financial Development and Economic Growth: A Symbiotic Relationship”
Applied Financial Economics, 18:1033-1049.
Hassan, M. K.,Sanchez, B., Yu, J.S. ( 2011). “Financial Development and Economic Growth: New Evidences
from Panel Data” The Quarterly Review of Economics and Finance, 51:88-104.
Hassan, M.K., Sanchez, B., Yu. J.S (2011). “Financial Development and Economic Growth in the Organization
of Islamic Conference Countries” JKAU: Islamic Econ, 24(1):145-172.
Im, S.O. Pesaran, M.H. and Shin, Y. (2003), “Testing for Unit Roots in Heterogeneous Panels” Journal of
Ecnometrics, 115:53-74.
Iyare, S. and Moore, W.( 2011) “Financial Sector Development and Growth In Small Open Economies” Applied
Economics, 43:10, 1289-1297.
13. Journal of Economics and Sustainable Development www.iiste.org
ISSN 2222-1700 (Paper) ISSN 2222-2855 (Online)
Vol.4, No.11, 2013
30
Jamil, M. (2010). “Impact of Financial Markets Development and Stock Market Volatility on Economic Growth:
A Dynamic Panel Data Analysis”
Johansen, S. (1998), “Statistical Analysis of Co-integration Vectors”, Journal of Economic Dynamics and
Control, 12:231-254.
Jude, E.C.,( 2010). “Financial Development and Growth: A Panel Smooth Regression Approach” Journal of
Economic Development, 35(1).
Kao (1999) “Spurious Regression and Residual based tests for co-integration in panel data” Journal of
Econometrics 90:1-44.
Kao, C., (1999), “Spurious Regression and Residual-Based Tests for Co-integration in Panel Data”, Journal of
Econometrics 90, 1–44.
Kar, M. and E. Pentecost (2000) “Financial Development and Economic Growth in Turkey: Further Evidence on
the Causality Issue.” CIFER working paper 00/27Loughborough University
Khan, M.A and Khan, S (2007): “Financial Sector Restructuring in Pakistan” Institute of Development
Economics Pakistan MPRA paper No.4141
King, R. G. and Levine, R. (1993). “Finance and Growth: Schumpeter Might be Right” The Quarterly Journal of
Economics, 108(3):717-737.
Lartey, E.K.K. and Farka, M. (2011). “Financial Development, Crisis and Growth” Applied Economic Letters,
711-714.
Lawrence, P. and Longjam, I.’(2003), “Financial Liberalization in India: Measuring Relative Progress”, Keele
Economics Research Paper No. 2003/8, Kele University.
Levine, R. (1997). “Financial Development and Economic Growth: Views and Agenda” Journal of Economic
literature, 35 (2):688-726.
Levine, R. and Zervos, S.( 1998). “Stock Markets, Banks and Economic Growth”The American Economic
Review, 88(3):537-558.
Levine, R., Loayza, N. and Beck, T .(2000). “Financial Intermediation And Growth: Causality and Causes”
Journal of Monetary Economics, 46(01): 31-77.
Liu, W-C.and Hsu, C-M. (2006). “The Role of Financial Development in Economic Growth: The Experience Of
Taiwan, Korea And Japan” Journal of Asian Economics, 17: 667-690
Lucas, R.E.,( 1988) “On the Mechanics of Economic Development” Journal of Monetary Economics 22 (1988)
3-42. North-Holland
Luintel B. and Khan M. (1999). A Quantitative Reassessment of the Finance‐Growth Nexus: Evidence from a
Multivariate VAR. Journal of Development Economics; V.60, pp. 381‐405.
Luintel, K.B. Khan, M., Arestis, P., and Theodoridis, K. (2008). “Financial Structure and Economic Growth”
Journal of Development Economics 86:181-200.
Maddala, G.S. (1999). “On The Use of Panel Data Methods with Cross-Country Data”, Annales deconomics et
de statistique, 55(56):429-449.
Maddala, G.S. and Wu, S.( 1999). “A Comparative Study Of Unit Root Tests With Panel Data and A New
Simple Test”, Oxford Bulletin of Economics and Statistics , Special Issue (1999) 0305-9049.
Naceur, S.B, Ghazouani, S.( 2007). “Stock Markets, Banks, and Economic Growth: Empirical Evidence from the
MENA Region” Research in International Business and Finance, 21:297–315.
Patrick, H.T.(1966), "Financial Development and Economic Growth in Underdeveloped Countries" Economic
Development and Cultural Change vol. 14, no. 2
Pedroni, P., (2004), “Panel Cointegration: Asymptotic and Finite Sample Properties of Pooled Time Series Tests
with an Application to the PPP Hypothesis”, Econometric Theory 20, 597–625.
Perera, N. and Paudel.R.C. (2009). “Financial Development and Economic Growth in Sri Lanka” Journal of
Applied Econometrics and international Development, 9(1):157-164.
Rahman, M.H. (2004). “Financial Development –Economic Growth Nexus: A Study of Bangladesh”. The
Bangladesh Development Studies 3-4
Rajan, R.G. and Zingales, L. (1998). “Financial dependence and Growth” The American Economic Review,
88(3):559-586.
Ram, R. (1999). “Financial Development and Economic Growth: Additional Evidences” Journal of development
studies, 35(4):164-174.
Ramlal, V., Watson, P. K. (2005) “Financial Development and Economic Growth in the CARICOM Sub Region”
37th Annual Monetary Studies Conference Bahamas.
Rehman and Cheema (2013), “Financial development and real sector growth in Pakistan” Interdisciplinary
journal of contemporary research in business May 2013 Volume 5, No 1
Rousseau, P.L, Xiao, S. (2007). “Banks, Stock Markets, and China's ‘Great Leap Forward” Emerging Markets
Review 8:206–217.
14. Journal of Economics and Sustainable Development www.iiste.org
ISSN 2222-1700 (Paper) ISSN 2222-2855 (Online)
Vol.4, No.11, 2013
31
Rousseau, P.L. and Wachtel, P. (2000). “Equity Markets and Growth: Cross- Country Evidence on Timing and
Outcomes, 1980-1995” Journal of Banking & Finance, 24:1933-1957.
Schumpeter J (1911) “The Theory of Economic Development: An Inquiry into Profits, Capital, Credit, Interest
and Business Cycle”, Cambridge Mass: Harvard University Press
Seelanatha, L., Wickremasinghe, G.B(2009),“Financial Reforms in Sri Lanka and Their Influence on the
Banking Industry Banks and Bank Systems”, 4(4), 2009.
Shan, J. and Morris, A. (2002). “Does Financial Development ‘Lead’ Economic Growth?” International Review
of Applied Economics, 16(2):153-168.
Shaw, E.S. (1973) “Financial Deepening in Economic Development” New York: Oxford University Press
Stock, J., and Watson, M. (1991). A probability model of the coincident economic indicators. In Kajal Lahiri and
Geoffrey Moore, editors, Leading Economic Indicators, New Approaches and Forecasting Records.
Cambridge University Press, Cambridge
Zhang, H. and Kim, Y. C. (2007) Does financial development precede growth? Robinson and Lucas might be
right, Applied Economics Letters, 14, 15–9.
15. This academic article was published by The International Institute for Science,
Technology and Education (IISTE). The IISTE is a pioneer in the Open Access
Publishing service based in the U.S. and Europe. The aim of the institute is
Accelerating Global Knowledge Sharing.
More information about the publisher can be found in the IISTE’s homepage:
http://www.iiste.org
CALL FOR PAPERS
The IISTE is currently hosting more than 30 peer-reviewed academic journals and
collaborating with academic institutions around the world. There’s no deadline for
submission. Prospective authors of IISTE journals can find the submission
instruction on the following page: http://www.iiste.org/Journals/
The IISTE editorial team promises to the review and publish all the qualified
submissions in a fast manner. All the journals articles are available online to the
readers all over the world without financial, legal, or technical barriers other than
those inseparable from gaining access to the internet itself. Printed version of the
journals is also available upon request of readers and authors.
IISTE Knowledge Sharing Partners
EBSCO, Index Copernicus, Ulrich's Periodicals Directory, JournalTOCS, PKP Open
Archives Harvester, Bielefeld Academic Search Engine, Elektronische
Zeitschriftenbibliothek EZB, Open J-Gate, OCLC WorldCat, Universe Digtial
Library , NewJour, Google Scholar