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Does Financial Development Cause Economic

Growth? A Panel Data Dynamic Analysis for the Asian

Developing CountriesMuzafar Shah Habibullah

a& Yoke-Kee Eng

b

aDepartment of Economics, Universiti Putra Malaysia, Selangor, Malaysia

bFaculty of Accountancy and Management, Universiti Tunku Abdul Rahman, Kajang,

Selangor, Malaysia

Available online: 27 Jun 2007

To cite this article: Muzafar Shah Habibullah & Yoke-Kee Eng (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

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Journal of the Asia Pacific Economy

Vol. 11, No. 4, 377393, November 2006

Does Financial Development CauseEconomic Growth? A Panel DataDynamic Analysis for the AsianDeveloping Countries

MUZAFAR SHAH HABIBULLAH & YOKE-KEE ENGDepartment of Economics, Universiti Putra Malaysia, Selangor, MalaysiaFaculty of Accountancy and Management, Universiti Tunku Abdul Rahman, Kajang, Selangor,

Malaysia

ABSTRACT This paper examines the causal relationship between financial development andeconomic growth of the Asian developing countries from a panel data perspective and uses thesystemGMM techniquedeveloped by Arellano& Bover (1995)and Blundell & Bond (1998)andconducts causality testing analysis. The panel data sets involve 13 Asian developing countries:Bangladesh, India, Indonesia, South Korea, Lao PDR, Malaysia, Myanmar, Nepal, Pakistan,Philippine, Singapore, Sri Lanka and Thailand for the period 19901998. The result of ourstudy is in agreement with other causality studies by Calderon & Liu (2003), Fase & Abma(2003), and Christopoulos & Tsionas (2004) that financial development promotes growth, thus

supporting the old Schumpeterian hypothesis and Patricks supply-leading hypothesis.

KEY WORDS: Finance-growth nexus, demand-following, supply-leading, Asian countries

JEL CLASSIFICATIONS: O11, O16, O53

Introduction

Capital formation has been widely accepted as a prerequisite for economic growth

(Lewis, 1955; Nurkse, 1962). Nevertheless, in the fragmented and distorted financial

system of the developing economies, capital is hard to come by. In the 1960s and

early 1970s, the developing countries had been described as financially repressed

economies (McKinnon, 1973; Shaw, 1973). Pervasive government intervention in

controlling interest rates and the allocation of credit tends to distort financial marketsand, as a result, lead to fragmentation of financial markets and financial disinterme-

diation. McKinnon recommends the liberalization of the interest rates to attain their

Correspondence Address: Muzafar Shah Habibullah, Department of Economics, Faculty of Economics

and Management, Universiti Putra Malaysia, 43400 Serdang, Selangor, Malaysia. E-mail: muzafar@

econ.upm.edu.my

ISSN 13547860 Print/14699648 Online/06/04037717 C 2006 Taylor & Francis

DOI: 10.1080/13547860600923585


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378 M. S. Habibullah & Y.-K. Eng

true equilibrium level and by determining credit allocation on the basis of viabil-

ity and productivity of projects. The recommendations made by McKinnon are well

taken by majority of the developing countries of Latin America, Africa and Asia.

Many of these developing countries attempted to increase the role of market forces

in the determination of interest rates, the allocation of credit and the overall scale of

financial intermediation in the late 1970s and the 1980s. However, the results of the

process of financial liberalization in many developing countries have varied from a

disastrous one to a successful transition to a more efficient and market-oriented finan-

cial system. While the Southern Cone region of Latin America-Argentina, Chile and

Uruguay experienced bank panics and collapses as a result of financial liberalization

(Diaz-Alejandro, 1985), the other countries in this region in particular, Colombia,

Brazil and Mexico have abandoned financial liberalization programs (Fry, 1989).Nonetheless, financial liberalization in a number of Asian countries has helped

make financial systems more efficient and has enhanced the effectiveness and flex-

ibility of monetary policies.1 In the early 1960s, the financial system of almost all

countries in Asia were characterized by one or more of a range of restrictive financial

measures, including interest rate regulations, selective credit allocation controls, ex-

plicit and implicit taxes on financial institutions, government ownership of financial

institutions, segmentation and international capital controls, among others. However,

such features have either become less distinct or completely removed as deregulation,

market-orientation and internationalization of banking and finance have proceeded at

a rapid pace since the early 1980s.

Asia, South Korea, Taiwan and the countries of the ASEAN region have benefited

greatly from the financial liberalization exercises.2 For instance, the development of

monetization and the financial deepening3 in selected Asian countries are shown in

Table 1. The degree of monetization in the Asian countries has been significant over

the195694 periods. Theuse of money (M1), relativeto GNP(gross national product),

has stabilized in most of the Asian countries, and declined in Myanmar, Singapore,

Sri Lanka, and Thailand. However, increasing use of broad money (M2) is evident

in all the Asian countries, as shown by the consistent rise in the countries M2/M1

and M2/GNP ratios during the periods, reflecting the movement towards higher level

of monetized economy. During the deregulation period of 198694, Thailand regis-

tered the highest M2/M1 ratio of 7.46, followed by Korea (4.00), Singapore (3.75),

Malaysia (3.61), Philippines (3.38) and Indonesia (3.34). Other Asian countries show

a ratio of less than 3.00. During the same period, other indicators of monetization, the

holdings of money percapita andtotal bank deposits percapita, suggest that Singapore

and Taiwan have significantly higher levels of monetization relative to those in theremaining eight Asian countries.

Table 1 also presents the relationship between total assets of the financial system

and national income, which measure the stage of financial intermediation in a country.

More interestingly, thedominance of thebanking system (comprising only the Central

Bank andcommercial banks)in allthe Asian financial systemwas particularlymarked,


4/18

Does Financial Development Cause Economic Growth? 379

Ta

ble1.Selectedmeasuresofmonetization

andfinancialdeepeninginselectedAsia

ncountries,196694

Indonesia

Malay

sia

Myanmar

Nepal

Philippines

Financialindicators

1966751976851986941966751976

85198694196675197685198694196675

197685198694196675197685198694

M1/GNP

0.08

0.11

0.12

0.18

0.20

0.23

0.23

0.21

0.21

0.09

0.12

0.14

0.10

0.08

0.08

M2/GNP

0.11

0.19

0.40

0.37

0.57

0.81

0.25

0.27

0.30

0.12

0.24

0.32

0.21

0.23

0.27

M2/M1

1.33

1.73

3.34

2.02

2.91

3.61

1.11

1.29

1.44

1.36

2.00

2.35

1.98

2.74

3.38

Currency/M1

0.60

0.45

0.41

0.50

0.47

0.41

0.83

0.91

0.91

0.69

0.64

0.69

0.52

0.53

0.67

M2percapita(US$)

12

82

239

180

924

1985

22

44

175

10

31

55

54

127

205

Percapitatotalbank

8

61

211

145

803

1668

6

14

58

4

21

40

59

148

180

deposits(US$)

Totalfinancialassets/GNP

0.29

0.48

0.86

0.65

1.19

2.17

0.51

1.44

1.84

0.19

0.39

0.54

0.58

0.94

0.99

Assets/GNP:

CentralBank

0.15

0.22

0.26

0.17

0.23

0.40

0.39

0.34

0.45

0.12

0.18

0.24

0.16

0.29

0.41

Commercialbanks

0.14

0.26

0.60

0.40

0.72

1.23

0.13

1.10

1.39

0.07

0.21

0.30

0.34

0.54

0.49

Totalbankingsystem

0.29

0.48

0.86

0.57

0.95

1.63

0.51

1.44

1.84

0.19

0.38

0.54

0.50

0.82

0.90

1971

94

1971

94

1971

94

1971

94

1971

94

Incomeelasticityofnet

issues:

Financialsystem,ofwhich;

1.24

1.53

1.15

1.38

1.20

CentralBank

1.05

1.46

0.89

1.20

1.25

Commercialbanks

1.37

1.50

1.76

1.62

1.23

Totalbankingsystem

1.24

1.47

1.15

1.37

1.22

Singapore

SouthK

orea

SriLanka

Taiwan

Thailand

Financialindicators

1966751976851986941966751976

85198694196675197685198694197075

197685198694196675197685198694

M1/GNP

0.27

0.25

0.24

0.11

0.11

0.10

0.17

0.14

0.13

0.18

0.27

1.47

0.14

0.10

0.09

M2/GNP

0.61

0.66

0.89

0.29

0.34

0.39

0.25

0.29

0.31

0.44

0.74

1.47

0.30

0.43

0.70

M2/M1

2.29

2.63

3.75

2.59

3.28

4.00

1.51

2.18

2.40

2.46

2.70

3.16

2.24

4.34

7.46

Currency/M1

0.44

0.51

0.46

0.45

0.46

0.41

0.53

0.50

0.54

0.34

0.27

0.18

0.62

0.67

0.69

M2percapita(US$)

829

4243

12503

94

556

2276

44

77

146

316

1759

12449

69

278

1116

Percapitatotalbank

744

4249

12889

82

578

2524

28

62

113

244

1290

9617

53

250

1062

deposits(US$)

Totalfinancialassets/GNP

0.97

1.90

2.63

0.64

1.05

1.45

0.54

0.74

0.72

1.09

1.55

2.59

0.58

0.89

1.36

Assets/GNP:

CentralBank

0.07

0.38

0.54

0.16

0.20

0.24

0.24

0.30

0.25

0.32

0.35

0.63

0.21

0.20

0.23

Commercialbanks

0.86

1.42

1.97

0.38

0.66

0.70

0.24

0.37

0.44

0.63

0.96

1.55

0.31

0.52

0.86

Totalbankingsystem

0.92

1.80

2.50

0.53

0.86

0.93

0.48

0.67

0.69

0.94

1.31

2.18

0.52

0.72

1.09

1971

94

1971

94

1971

94

1971

94

1971

94

Incomeelasticityofnet

issues:

Financialsystem,ofwhich;

1.41

1.26

1.11

1.39

1.38

CentralBank

2.50

1.04

1.04

1.24

1.06

Commercialbanks

1.31

1.20

1.23

1.45

1.46

Totalbankingsystem

1.41

1.16

1.14

1.37

1.34

Sources:Habibullah

(1999b),andHabibullah&Smith(1997).


5/18


ranging from 0.54 for Nepal to 2.50 for Singapore. The income elasticity of assets of

financial institutions to national income is just as revealing. As indicated in Table 1,

the income elasticity of financial assets during the deregulation era was way above

unity for all the Asian countries. The income elasticity of financial assets in Malaysia,

which was 1.53 during the period 197194, is one of the highest among the Asian

countries.

The success of increasing the role of the financial sector in enhancing growth in

the Asian developing countries has received positive response from the World Bank.

The World Bank (1989, p. 11) reports that, in East Asia the newly industrialized

economies and several others have pursued sound macroeconomic policies and main-

tained the competitiveness of the exports. They have generally adapted well to the

shocks of the 1970s and early 1980s. The populous economies of South Asia havealso achieved good results. Their success has more to do with macroeconomic stabil-

ity, prudent fiscal and external borrowing policies and rural modernization than with

internationally competitive trade policies.

Furthermore, a comprehensive study by theWorld Bank (1989) on those developing

countries that have embarked on financial liberalization programs supports the con-

tention that financial liberalization matters for economic growth. The World Bank

(1989, p. 30) reports that, faster growth, more investment and greater financial depth

all come partly from higher saving. In its own right, however, greater financial depth

also contributes to growth by improving the productivity of investment. Investment

productivity is significantly higher in the faster growing countries, which also have

deeper financial systems. This suggests a link between financial development and

growth.

As a matter of fact, the role of financial sector has been well recognized in the de-

velopment literature. The seminal work of Patrick (1966) has resulted in widespread

investigations into the role of the financial sector as an engine for economic growth.

Patrick points out two possible relationships between financial development and eco-

nomic growth. First, as the economy grows,it generatesdemand for financial services,

which he calls a demand-following phenomenon. According to this view, the lack

of financial institutions in developing countries is an indication of lack of demand

for their services. Second, the establishment and the widespread expansion of finan-

cial institutions in an economy may actively promote development, which Patrick

called supply-leading phenomenon. This latter view, which has been dubbed the

financial-led growth hypothesis, has been popular among governments in several

developing countries as a means to promoting development.

Moreover, there are two views in which the financial system can be manipulatedfor enhancing economic growth. The Struturalist School recommends an expansion

in the structure of the financial system, such as an increase in the number of financial

institutions. This school also encourages an increase in the array of financial instru-

ments made available to the public (Goldsmith, 1969; Patrick, 1966). Neo-liberals

on the other hand, advocate the liberalization of the financial system, by which they


6/18


mean the relaxation of controls imposed on the financial systems by the monetary

authorities (McKinnon, 1973; Shaw, 1973). Neo-liberals believe that administratively

determined (as opposed to market-determined) low rates of interest may not encour-

age savings. Without savings there cannot really be any investment. Thus, according

to this school, the freeing of interest rates is the key to capital formation and growth.

Goldsmith (1969), McKinnon (1973), Shaw (1973), Fry (1988) and more recently

King & Levine (1993a, 1993b) are among others who have provided evidence that

financial development is a prerequisite for economic growth.

The objective of this paper is to provide further evidence on the financial-led

growth hypothesis proposed by Patrick using the dynamic panel data analysis pop-

ularized by Arellano & Bond (1991). Since long series of data are scarce for the

developing countries, by using the panel data approach, it is possible to analyze theissue of financial-led growth using pooled cross-sectional and time-series data. To

explore the causal relationship between financial deepening and economic growth,

we use the Generalized Method of Moments (GMM) panel estimates proposed by

Arellano & Bover (1995) and Blundell & Bond (1998) to extract consistent and effi-

cient estimates on the role of financial development on economic growth in the Asian

developing countries. The selected Asian countries included in the present study are

Bangladesh, India, Indonesia, South Korea, Lao PDR, Malaysia, Myanmar, Nepal,

Pakistan, Philippine, Singapore, Sri Lanka and Thailand.

This paper is organized as follows. The next section briefly reviews the theoretical

and empirical aspect on the role of financial development on economic growth. The

section after discusses on the method of estimation, and the discussions of the empir-

ical results are presented in the subsequent section. Lastly, our concluding remarks

are given in the final section.

A Review of Related Literature

Theoretical considerations

The importance of the saving and investment process in economic development arises

partly because capital goods depreciate over time, a significant flow of saving must

be generated and transferred into productive investment just to maintain a nations

capital stock and preserve existing living standards. For living standards to rise, a

healthy flow of saving and investment must be sustained. As a general proposition,

the greater the proportion of current output saved and invested, the more rapid the rate

of economic growth. In a modern society, as a result of specialization and division oflabor, the process of investment is separated from the savings process. Thus, it is the

function of the financial institutions to provide the mechanism to channel funds from

the savers to the investors. By reducing the asymmetry of information for borrowers

and lenders, the allocation of funds to the most productive sectors can be made,

thereby increasing economic efficiency and social welfare.


7/18


The role of the financial sector as the engine of growth or supply-leading one

in enhancing growth goes far back to the work of Schumpeter (1934). Schumpeter

argues that financial sector leads economic growth by acting as a provider of fund

for productive investments and therefore could lead to accelerating economic growth.

The theoretical work linking the financial sector to economic growth was provided in

later years, among others by Pagano (1993), Greenwood & Jovanovic (1990), Levine

(1991), Bencivenaga & Smith (1991) and Saint-Paul (1992).

Pagano (1993) provides a simple endogenous growth model called the AK model

to look at the impact of financial development on economic growth. To illustrate

how financial development affects growth, we draw heavily from Pagano (1993) by

assuming the following aggregate production function

Yt = AtKt (1)

where output is a linear function of the aggregate capital stock. This production

function can be seen as a reduced form as a result (a) as in Romer (1989), that a firm

in a competitive economy with external economies faces a technology with constant

returns to scale but productivity is an increasing function of the aggregate capital stock

Kt; and (b) as in Lucas (1988), assuming Kt be a composite of physical and human

capital, then the two types of capital are reproducible with identical technologies.

Assuming in themodelthat there is no population growthand theeconomy produces

only one good which can be consumed or invested, if it is invested, and given the rate

of depreciation per period as , then the gross investment equals

It = Kt+1 (1 )Kt (2)

The role of financial institutions is to transfer savings into investment. In the process,

they absorb resources so that a dollar saved by savers will generate less than a dollars

worth of investment. Assume as the fraction of each dollar saved that is available

for investment, while the remainder (1-) is retained by the financial institutions as a

reward for the services rendered.

In a closed economy, the capital market equilibrium requires that gross saving Stequals gross investment It. The following equation ensure equilibrium in the capital

market

St = It (3)

Next we derive the growth rate at time t + 1 from equation (1) as

gt+1 = (Yt+1/Yt) 1 = (Kt+1/Kt) 1 (4)


8/18


Rewriting equation (2) as Kt = It + (1 )Kt+1 and substituting into equation (4)

we have

gt+1 = (It + Kt Kt Kt)/Kt = (It/Kt) (5)

Rewriting equation (1) as Kt = Yt/A and, together with equation (3), substituting

into equation (5) and dropping the time indices, we have the steady-state growth rate

as

g = A(I/Y) = As (6)

where s denotes the gross savings rate ( S/Y). Equation (6) reveals that there aretwo ways in which the development of the financial sector might affect economic

growth. First, banking sectors that operate in a more competitive environment, are

likely to become more efficient in the process of transferring saving into investment,

and as a result can be raised. As rises in equation (6), it also increases the growth

rate g. Second, to their best interest, financial institutions can allocate funds to those

projects where the marginal product of capital is highest. In this model, banks increase

the productivity of capital, A, thereby promoting growth. Thus, savings channeled

through financial institutions are allocated more efficiently, and the higher productivity

of capital results in higher growth.

Other theoretical work by Greenwood & Jovanovic (1990), Levine (1991),

Bencivenaga & Smith (1991) and Saint-Paul (1992) indicate that efficient financial

markets improve the quality of investments and promote economic growth. Ben-

civenga & Smith (1991) contend that banks as liquidity providers permit risk-averse

households to hold interest-bearing deposits and the funds obtained are then chan-

neled to productive investment. By eliminating self-financed capital investment by

firms, banks also prevent the unnecessary liquidation of such investment by firms

who find that they need liquidity. In other words, financial intermediaries permit an

economy to reduce the fraction of its savings held in the form of unproductive liquid

assets, and to prevent misallocations of invested capital due to liquidity needs. This

suggests that financial intermediaries may naturally tend to alter the composition of

savings in a way that is favorable to capital accumulation, and if the composition

of savings affects real growth rates, financial intermediaries will tend to promote

growth.

Levine (1991) demonstrates that stock markets help individuals manage liquidity

and productivity risk and, as a result, stock markets accelerate growth. According toLevine, in the absence of financial markets, firm-specific productivity shocks may

discourage risk-averse investors from investing in firms. However, the stock markets

allow individuals to invest in a large number of firms and diversify against idiosyn-

cratic firm shocks. This raises the fraction of resources allocated to firms, expedites

human capital accumulation and promotes economic growth. In other words, Levine


9/18


concurs that growth only occurs if society invests and maintains a sufficient amount

of capital in firms that augment human capital and technology in the process of pro-

duction. The more resources allocated to firms, the more rapid will be economic

growth.

Saint-Paul (1992) relates the relationship between the financial sector and eco-

nomic growth by emphasizing the complementarity role between financial markets

and technology. According to Saint-Paul, if financial markets are underdeveloped,

then individuals will choose poorly productive, but flexible technologies. Given

these technologies, producers do not experience much risk, and hence there is lit-

tle incentive to develop financial markets. On the other hand, if financial markets

are developed, technology will be more specialized and risky, thereby resulting

in a positive impact on productivity. Financial markets, therefore, contribute togrowth by facilitating a greater division of labor. Thus, an economy that possesses

highly developed financial markets, that allow the spreading of risk through finan-

cial diversification among the economic agents, will be able to achieve a higher

level of development than an economy in which the financial markets are not very

developed.

The theoretical argument by Bencivenga& Smith (1991), Levine (1991), and Saint-

Paul (1992) support the proponents of the supply-leading hypothesis proposed by

Schumpeter (1934)and Patrick (1966). However,Robinson (1953) has questionedthis

one-way causality, arguing that finance follows rather than leads economic growth.

This line of argument is sharedby Greenwood& Jovanovic (1990), Blackburn& Hung

(1998), and Harrison et al. (1999) who demonstrate two-way causal relationships

between financial development and economic growth.

According to Greenwood & Jovanovic (1990) economic growth fosters invest-

ment in organizational capital, which in turn promotes further growth. In this respect,

financial intermediaries collect and analyze information and provide this valuable

information to allow investors resources to flow to their most profitable use. Apart

from this, intermediaries also play the traditional role of pooling risks across large

numbers of investors. Thus, by investing through financial intermediaries, individuals

obtain both a higher and a safer return. The development of financial superstructure,

since it allows a higher return to be earned on capital investment, in turn feeds back on

economic growth and income level. Greenwood & Jovanovic conclude that economic

growth provides the avenue to develop financial structure, while developed financial

structures stimulate higher economic growth since investment could be more effi-

ciently undertaken.

On the other hand, Harrison etal. (1999), and Blackburn & Hung (1998) argue thatfinancial intermediation encourages economic growth because it reduces the cost of

project appraisal. As the number of projects increases in a growing economy, more

banks enter the markets as banks activity and profit increases. This entry reduces the

average distance between banks and borrowers, promotes regional specialization and

reduces the cost of intermediation.


10/18


Some empirical evidence

Goldsmith (1969), McKinnon (1973), Shaw (1973), Fry (1988), Jung (1986), Gupta

(1984) and King & Levine (1993a, 1993b) are among those who have provided evi-

dence that financial development is a prerequisite for economic growth. Nevertheless,

other researchers are skeptical with respect to the financial-led growth hypothesis.

Dornbusch & Reynoso (1989) have questioned the conclusions of previous influen-

tial studies and argue that the evidence in support of the financial-led growth paradigm

is episodic and a vast exaggeration.

Despite the skepticism, the testing of the nexus between finance and growth has

flourished. Demetriades & Hussein (1996), Arestis & Demetriades (1996), Murinde &

Eng (1994) and Thornton (1994, 1996) are among the few studies that have tested thefinancial-led hypothesis on several Asian countries. Using annual data from 1965 to

1992, Demetriades & Hussein found that among the Asian countriescoveredunder the

study; only in the case of Sri Lanka did the evidence support the financial-led growth

hypothesis. For Pakistan, their result indicates that economic growth causes financial

development. Further, Demetriades & Husseins study suggests that bidirectional

causal relationships are evident for India, South Korea and Thailand. In another

related study, Arestis & Demetriades further support the evidencethat the relationships

between financial development and economic growth for India and South Korea are

bidirectional.

Murinde & Eng (1994) test the financial-led hypothesis on Singapore using quar-

terly data for the period 1979:1 to 1990:4. Using an array of financial indicators, they

found that the results strongly support the financial-led hypothesis for Singapore.

On the other hand, Thornton provides some empirical evidence on the supply-leading

hypothesis in several Asian countries. Using annual data as far back as 1950s to 1990,

Thornton (1994) found that the financial-led hypothesis was supported by monetary

data of Nepal, the Philippines and Thailand. The demand-following hypothesis was

supported by Myanmar and Korea monetary data. However, a bidirectional relation-

ship between the monetization variable and economic growth is evident for Malaysia.

For India and Sri Lanka, the results suggest that there is no causal relationship be-

tween economic growth and the financial indicator. In another study, Thornton (1996)

found that the Philippines, Malaysia, Nepal and Thailand support the financial-led

hypothesis, while demand-following are supported by Myanmar and Korea.

On a sample of six Asian countries, Luintel & Khan (1999) examine the long-run

causality between financial development and economic growth employing the mul-

tivariate VAR framework. They found bi-directional causality between financial de-velopment and economic growth in all six countries, namely; India, Korea, Malaysia,

Philippines, Sri Lanka and Thailand. In another study on Asian economies, Al-

Yousif (2002) found that Philippines and Korea support the financial-led hypothesis;

Sri Lankaand Pakistan support the demand-following hypothesis, while Malaysia and

Singapore show a two-way causal effect between financial development and growth,


11/18


but the result for Thailand suggests finance is irrelevant for growth. Habibullahs

(1999a) study on seven Asian developing countries suggests that only the Philippines

support the financial-led growth hypothesis. The cases of demand-following growth

hypothesis are supported by Malaysia, Myanmar, and Nepal. On the other hand, a

bi-directional causality between growth and finance are evident for Indonesia, Sri

Lanka and Thailand.4

Further evidence on the financial-led hypothesis is documented by Fase & Abma

(2003). Using pooled data on Bangladesh, India, Malaysia, Pakistan, Philippines,

Singapore, South Korea, Sri Lanka, and Thailand, Fase & Abma conclude that fi-

nancial development matters for economic growth and that causality runs from the

level of financial intermediation and sophistication to growth. The supply-leading

hypothesis is also supported by more recent studies by Calderon & Liu (2003) on109 developing and developed countries, and Christopoulos & Tsionas (2004) on 10

developing countries. Both studies conclude that the supply-leading hypothesis is the

dominant force behind the relationship between finance and the sources of growth; in

particular, financial depth contributes more to the causal relationship in developing

countries.

Methodology

Our task is to determine the causal direction between the two variables in question.

Doesfinancialdevelopment lead economic growth or otherwise? Do the monetary data

in the Asian developing countries support the supply-leading or demand-following

growth hypothesis? There are at least three reasons for conducting a causality test:

(a) to ensure that there is causal relationship between the two variables and to avoid

spurious regressions, (b) ordinary least squares will yield inconsistent estimates of

the parameters if two-way causal relationships are detected, and (c) for policy making

purposes,it is importantfor understanding whether theimpact is short-run or long-run.

Since the influential work of Granger & Newbold (1974) and Engle & Granger

(1987), on the treatment of integrated time series data, many studies have been con-

ducted employing the cointegration methodology in orderto avoid the spurious regres-

sion problems, particularly in causality testing. The cointegration approach provides

a way in which the long-run information of the integrated series in levels is conserved

into equationsthat comprise stationarycomponents (called the errorcorrectionmodel)

that give valid statistical inferences. The majority of the studies reviewed earlier em-

ployed this method. However, in the present study, we are using a sample of 13 Asian

developing countries with nine years of annual observations for the period 1990 to1998. To circumvent the problem of the short time period we apply a newly developed

GMM technique for panel data to conduct the causality test.

To illustrate, we assumethe endogenous variables aregenerated by a time stationary

VAR(m) process in a panel data context (see Holtz-Eakin et al., 1988, 1989). The set

of endogenous variables includes the growth of output per capita (y) measured by real


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GDP per capita, and the financial development indicator (x) measured using the ratio

of domestic credit to GDP, observed for N countries over T periods. The following

equations are ready for estimation, with growth of output per capita as the dependent

variable in equation (7) while the financial development indicator is the dependent

variable in equation (8), as follows

yt = 0 +

m

i =1

iyti +

m

i =1

ixti + i + it i = 1, . . . , N; t = 1, . . . ,T

(7)

xt = 0 +

m

i =1

iyti +

m

i =1

ixti + i + it i = 1, . . . , N; t = 1, . . . ,T

(8)

where i and t denote countries and time respectively. For example, the test of whether

x causes y is simply a test of the joint hypothesis that1 =2 = =m are all equal

to zero. If this null hypothesis is accepted, then it means that x does not cause y. To

account for the individual effects, the intercept is often allowed to vary with each unit

in a panel analysis, which is represented asi and i in the above equations. The error

terms it and it are assumed to be independently distributed across countries with

zero mean, but may be heteroskedastic across time and countries. Arellano & Bond

(1991) point out that they can be either serially uncorrelated or moving average.

Although including lagged dependent variables in the panel enables the examina-

tion of the dynamics between the variables in study, Nickell (1981) shows that this

leads to biased estimation, especially when N is much larger than T, like in this study.To overcome this problem, the standard procedure is to eliminate the individual ef-

fects by a first difference transformation (Anderson & Hsiao, 1981). Indicating with

the first difference operator, equation (7) and (8) become equation (9) and (10)

respectively as follow

yt =

m

i =1

iyti +

m

i=1

ixti + it i = 1, . . . , N; t = 2, . . . ,T (9)

xt =

m

i =1

iyti +

m

i =1

ixti + it i = 1, . . . , N; t = 2, . . . ,T (10)

Focusing on the growth of output per capita (equation (7)), if the errors are serially

uncorrelated, they will be moving average of order onein equation (9).In general, if theerrorsare moving average of order kin themodelat levels,they will be moving average

of order k+ 1 in the model in first differences. Therefore, the errors in equation (9)

are correlated with some of the explanatory variables, and consistent estimation of the

parameters requires some instrumental variables method as suggested by Anderson

& Hsiao (1981).


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However, the instrumental variable estimator as proposed by Anderson & Hsiao

(1981) does not necessarily yield efficient estimates, since it does not make use of

all the available moment conditions and also does not account for the differenced

structure of the new error terms. In this study, therefore, we employ the GMM-

System estimator proposed in Arellano & Bover (1995) and Blundell & Bond (1998).

This estimator combines in a system the transformed equations (3) and (4) and the

level equations (1) and (2), and estimates the parameters by exploiting two sets of

GMM-style instruments: one for the differenced equations and one for the level

equations.5 Thus, the system consists of the stacked regressions in differences and

levels, with the moment conditions E[yisit] =E[xisit] = 0 for s < t, i = 1, . . . , N

applied to the first part of the system, the regressions in differences, and the moment

conditions E[yit1(i + it)] =E[xit1(i + it)] = 0 i = 1, . . . , Napplied to thesecond part, the regressions in levels. Given that lagged levels are used as instruments

in difference regressions, only the most recent difference is used as an instrument in

the level regressions. Using Monte Carlo experiments, Blundell & Bond (1998) show

that the GMM-System estimator reduces the potential biases in finite samples and

asymptotic imprecision associated with the difference estimator. The key reason for

this improvement is the inclusion of the regression in level, which does not eliminate

cross-country variation or intensify the strength of measurement error.

The consistency of the GMM estimator depends both on the validity of the assump-

tion that the error term, , does not exhibit serial correlation and on the validity of

the instruments. To check the correct specification of instruments we perform a set

of tests: the m2 test for second-order serial correlation of the differenced residuals,

and the Sargan-Hansen test of over-identifying restrictions. Full details on these tests

and the estimation procedure may be found in Arellano & Bond (1991, 1998), and

Arellano & Bover (1995).

Results and Discussions

Apart from avoiding the problem of a short span of time series data for a causality

type study for several countries, a GMM panel data analysis has several advantages

over cross-sectional or time-series in the following ways: (a) working with a panel, we

gain degrees of freedom by adding the variability of the time series dimensions; (b)

in a panel context, we are able to control for unobserved country-specific effects and

thereby reduce biases in the estimated coefficients; (c) the panel estimator controls

for the potential endogeneity of all explanatory variables by using lagged values

of the explanatory variables as valid instruments (see Levine et al., 2000); (d) thesmall number of time-series observations should be of no concern given that all the

asymptotic properties of the GMM estimator rely on the size of the cross-sectional

dimension of the panel (Becketal., 2000); and (e) when the number of cross-sectional

units is much larger than the number of time-series periods, the non-stationarity

problem commonly seen in time-series data can be reduced (Holtz-Eakin etal., 1988).


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Results of the causality test between financial developments (measured using the

ratio of domestic credit to GDP) and economic growth (real GDP per capita) for the

period 1990 to 1998 for 13 Asian developing economies6 is presented in Table 2.

The results reported are the one-step estimator, for which inferences based on the

Table 2. GMM estimates of panel causality tests for the Asian countries

Dependent variable Growth Finance

Constant 0.1048 0.2082(1.4607) (2.5047)

Growth (-1) 0.75405 0.5406(2.0510) (2.4806)

Growth (-2) 0.5976 0.1564(1.4829) (1.3777)

Growth (-3) 0.79463 0.1705(1.3176) (0.7893)

Finance (-1) 0.0828 0.5491(0.7756) (1.6132)

Finance (-2) 0.50935 0.5735(2.1179) (1.4255)

Finance (-3) 0.206 1.0752(0.8796) (2.1643)

m2 0.497 1.519(p-value) (0.620) (0.129)Sargan-Hansen [d.f] 1.8924 [32] 5.8436 [32](p-value) (0.999) (0.999)Sargan Difference [d.f] 0.0764 [8] 0.0238 [8](p-value) (0.9999) (0.9999)Hausman-Arellano 1.40059 2.7159(p-value) (0.496) (0.257)Causality 8.3171 5.7759Wald test (0.040) (0.123)

Instrumental variables: All lagged y and x All lagged yand xdated t-4 and earlier dated t-4 and earlier

Differenced equation xt 3and yt 3 xt 3and yt 3Level equation

Notes:

1) t-statistics are in parenthesis. Standard errors and test statistic are asymptotically robustto heteroskedasticity.2) Time dummies were included in all equations.

3) m2 is test for first- and second-order serial correlation in the first-differenced residuals,asymptotically distributed as N (0,1) under the null of no serial correlation.4) Sargan-Hansen test is a test of over-identifying restriction.5) Sargan-Hansen Difference is a nested test for the additional instruments variables of thelevel equation.6) Hausman-Arellano test is a Hausman type test for the absence of mean independence,and more generally, for the instruments set for the equation in levels.Asterisk () denote statistically significant at the 5 percent level.


15/18


asymptotic variance matrix has been found to be more reliable than the two-step

estimator.7 In this study, we choose a lag length of three years as suggested by

the Holtz-Eakin et al. (1988) that the lag length should be less than one-third of

the total time period to avoid the over-identification problem as a result of incorrect

estimates of the covariance matrix. Using three lags structure, after differentiation,

five observations per individual unit are available.8 As to the specification tests: the

Sargan-Hansen test of over-identifying restrictions accepts the validity of instruments.

Moreover, both the Sargan-Hansen and Arellanos version of the Hausman test do

not reject the validity of the addition moment condition used in the levels equations,

suggesting that the unobservable country specific effect is uncorrelated with the dif-

ferences of the regressors. On the other hand, the m2 test of serial correlation in the

first differences residuals is consistent with the maintained assumption of no serialcorrelation in the residual terms. According to all these tests, therefore, the choice of

instruments seems to be correct.

To infer causality between financial development and economic growth, the Wald

test is used to test the null hypothesis that the estimated coefficients, sayi , in equation

(1) are all zero. Focusing on the output equation as presented in column two of Table 2,

the null hypothesis that supply-leading has no role in the Asian economies can be

rejected at the 5 percent level of significance. Focusing on the coefficients of the

indicator of financial development, we observe that the coefficients of the lagged

financial development indicators are statistically insignificantly different from zero

except one. The coefficient of the second lagged of the financial development indicator,

on the other hand, is highly significant and has the expected positive sign. This

result suggests that financial development has a causal positive impact of economic

growth in the Asian developing countries. On the other hand, focusing on the financial

development indicator equation as presented in column 3 in Table 2, the insignificance

of the Wald test suggests that the demand-following growth hypothesis canbe rejected

at the 5 percent level.

Conclusion

This paper examines the causal relationship between financial development and eco-

nomic growth from panel data perspectives using the GMM technique developed

by Arellano & Bover (1995) and Blundell & Bond (1998) by conducting causal-

ity testing analysis. The panel data sets involve 13 Asian developing countries:

Bangladesh, India, Indonesia, South Korea, Lao PDR, Malaysia, Myanmar, Nepal,

Pakistan, Philippine, Singapore, Sri Lanka and Thailand for the period 19901998.As pointed out earlier, the study on the direction of causality between financial

development and economic growth is important because it has different policy im-

plications on economic strategy to enhance growth, particularly, in the developing

nations. The present study supports the belief that there is a strong link between the

financial sector and economic growth as found by King & Levine (1993a, 1993b).


16/18


Our study supports the contention made by Calderon & Liu (2003) that financial

depth contributes more to the causal relationships in developing countries. Our result

suggests that the supply-leading growth hypothesis indicates that financial intermedi-

ation promotes economic growth in the nine Asian developing nations for the period

19901998. It implies that thepolicy of liberalization andfinancialreforms adapted by

these Asian countries has shown to improve economic growth. Our study is in agree-

ment with other causality studies by Calderon & Liu (2003), Fase & Abma (2003),

and Christopoulos & Tsionas (2004) that financial development promotes growth,

thus, supporting the old Schumpeterian hypothesis and Patricks supply-leading

hypothesis.

Acknowledgment

We thank theeditor of this journal andan anonymous referee forhelpful comments and

suggestions on theearlier draft of thepaper. Allremaining errorsare sole responsibility

of the authors.

Notes

1. See Habibullah (1999b) for further discussion and description on financial liberalization in ten Asian

developing countries.

2. The Association of South East Asian Nations (ASEAN) was founded in 1967 with the signing of the

ASEANDeclaration. At thetime of writing, theASEAN membercountriesincludedBrunei, Cambodia,

Indonesia, Lao PDR, Malaysia, Myanmar, Philippines, Singapore, Thailand and Vietnam.3. Shaw (1973) defines financial deepening as the phenomenon in which the financial sector grows at a

rate faster than the real sector of an economy. On the other hand, the process of monetization refers to

the size as well as the composition of the stock of money (money supply) in an economy. Chandavarkar

(1977) notes that the difference between monetization and financial intermediation is that the latter

refers to the process of mediation through institutions and instruments between primary savers and

lenders and ultimate borrowers and is measured by the financial interrelations ratio. Thus, it connotes

financial deepening rather than widening (enlargement of the money exchange economy), which is the

phenomenon expressed in the term monetization.

4. In thisstudy,Habibullah(1999a) hasproposed the useof thedivisiamonetary aggregatesas an alternative

proxy for the financial development indicator. In general, the proposed divisia monetary aggregates do

well in explaining the role of finance on economic growth in those Asian countries under study.

5. Arellano & Bond (1991) propose the two-step GMM estimator. In the first-step, the error terms are

assumed to be independent and homoskedastic across countries and over time. In the second-step, the

residualsobtained in thefirst-step areused to construct a consistent estimate of the variancecovariance

matrix, then to relax the assumptions of independence and homoskedasticity.6. All data were compiled from the various issues of the International Financial Statistics published by

the International Monetary Fund.

7. If the residuals are not only serially uncorrelated but also homoskedastic, the first-step estimate is

asymptotically equivalent to the two-step estimator.

8. Longerlag structures would reducetoo much thetime dimension of thedata, and theresultingestimates

would be unreliable as warned by Holtz-Eakin et al. (1988, 1989).


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