Analysis of the Relationship Between Financial Sector Dynamics, Inflation and Economic Growth

8/9/2019 Analysis of the Relationship Between Financial Sector Dynamics, Inflation and Economic Growth

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ANALYSIS OF THE RELATIONSHIP BETWEEN FINANCIAL SECTORDYNAMICS, INFLATION AND ECONOMIC GROWTH

Josua Pardede

Bank Internasional Indonesia, [email protected]

Abstract - This paper aims to analyze interrelationship

between financial sector, inflation and economic growth in

Indonesia. Vector Error Correction Model (VECM) is

employed in this analysis. Empirical results indicates that, in

long run, there is positive relationship between financialdeepening and economic growth while implied risk premium

has a negative effect on economic growth. Moreover, there is

negative relationship between implied risk premium and

inflation while exchange rate depreciation has a positive

effect on inflation.

Keywords: - Economic growth, financial deepening, inflation,Vector Error Correction Model

I. INTRODUCTION

Financial system possesses a very significant role in supportingthe growth of nation’s economy. This is due to the capability offinancial sector to gather some funds from the bank liabilitiesoutstanding and transfer the fund as a funding resource andinvestment. This will further stimulate investment and accelerateeconomic growth. On the other hand, an efficient financial sectorshould be able to minimize asymmetric information, indicated byhigh transaction cost and information cost occurring in financialmarket (Levine, 1997; Fritzer, 2004 and Kularatne 2002).

The term of financial deepening is commonly used to illustrate arapid development of financial institutions such as banks, capitalmarkets and insurance companies relative to the size andmagnitude of the nation’s economy. This is indicated by

penetration of several financial products and services throughoutall economic sectors to fulfill financial needs. In other words,financial deepening is an increased in provision of financialservice geared to fulfill financial needs in all levels of society,followed by enhancement of market volume. It is expected thatthe increase in financial market volume generated from the

financial sector is able to absorb volatility from each marke participant.

According to several economists, the fundamental of financia

deepening is the development of financial sector that supporteconomic growth through either a supply leading or a demandfollowing (Levine, 1997; Liu, 2003; Lynch, 1996; Kiyotaki anMoore, 2005; Mohan, 2006). An efficiently functioning financiasystem will support and enable productive fund allocation anmitigate the impact of asymmetric information and transactiocosts. The efficient financial system is indicated by prope

portfolio management and risk management which enhancfinancial system resistance towards market shocks.

Worries on the risks and dilemmas due to financial deepeninexist in policy development process in maintaininmacroeconomic stability both directly and indirectly. The direc

impact of financial deepening is related to the vulnerability odomestic economy towards sudden capital outflow. Annegative changes in investors’ risk appetite results in financiainstability, retarding a sustainable economic growth. On thother hand, the indirect impact of financial deepening arisewhen the increasing access to financial sector pushes domestidemands, which are unsupported by the economic capacity. Witregard to this matter, overheating economy will occur due texcessive domestic liquidity, causing inflation expectation whicleads to macroeconomic instability. The latter impact makesense to occur. With pro-cyclical funding characteristics, thloan provision will be less prudent during the booming periodimpacting the financial system. This impact, however, usuall

start to appear in recession. Loose requirement of loan provisiocauses pressures on macroeconomic and financial stability.

Monetary stability, financial system stability and economigrowth are three dimensions that are interrelated. According tthe premise of monetary stability and financial stability mutuallsupportive, the attainment of stabilities in both sectorencourages long-term economic growth. Conversely, economigrowth which is in line with the growth of production capacit


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can improve monetary stability and financial stability. If this process is maintained, sustainable economic growth will beachieved in the long-run.

Figure 1.1 The relationship between monetary stability, financialsystem and economic growth

Several studies discuss basic theories on the relationship between financial sector development and growth such as studies

done by Schumpeter, McKinnon (1973), and Shaw (1973). Themain implication of McKinnon-Shaw research is that therestriction on banking system (such as by imposing the ceilingon bank interest rate, high reserve requirements and credit

program) will retard financial system development which willthen reduce growth rate. Similar conclusion is asserted by recentstudies on endogenous growth theory which summarizes that thelong-term economic development depends on the advancementof the financial sector. Vast empirical studies on the relationship

between financial sector development and economic were done by Levine 1997. Another study was done by King and Levine(1993b), which concludes a strong positive relation betweenfinancial sector development and output rate. Other than that,

King and Levine (1993b) also state that the development offinancial sector can predict future economic growth. This findingfurther confirms that financial sector development influences theeconomic growth.

On the other hand, however, financial sector development potentially elevates the price level (inflation). Furtherobservation indicates that high inflation will disrupt financialinstitution operations and financial market in a country. As anillustration, a high inflation rate will directly related to priceuncertainty, interest rate and currency and in turn will increasecost to mitigate potential risk. Inflation will also promotecurrency devaluation and vulnerability towards speculative

action, such that hedging instrument will become more costly.The impact of high inflation rate will restrain trading process andforeign capital inflow.

Further, the main problem formulated which is the focus of thisresearch is “What are the relationships between financial systemdynamics, inflation and economic growth?” Based on the

problem statement above, the purpose of this research is, first, toanalyze the relationship between financial system, inflation andeconomic growth. Second, to analyze efforts made to improvefinancial system stability to promote economic growth andmaintain price stability.

Hypotheses, proposed conclusion which needs to be tested for itvalidity, of this research are the following: first, there is

positive relation between financial deepening and economigrowth and negative relation between financial system stabilitand economic growth. Second, financial system stability inegatively related to monetary stability (inflation), whilexchange rate depreciation is positively related to inflation. Iorder to further understand the formulated problems and th

purposes of this research, a research framework is constructed afollows:

FIGURE 1.2 Research framework

II. LITERATURE REVIEWS

II.1Financial Deepening

Schumpeter (1911) argues that services provided bintermediaries function of financial system such as mobilizinsavings, evaluating projects, managing risks, monitorin

managers and facilitating transactions play vital role in fosterintechnological innovation and economic growth (Levine, 1993).

In line with Schumpeter, Levine (1995) further divides financiasector into five service categories based on the function ofinancial sector in supporting economic growth. Thdevelopment of financial sector/financial deepening can improvquality and its function in economy in terms of:

1. Providing information about potential investmenopportunities;

2. Monitoring investment and exerting corporatgovernance;

3.

Trading, diversifying and managing risk;4. Mobilizing and pooling of savings;5. Facilitating the exchange of goods and services.

Each of these functions can influence savings rate, investmendecisions and hence influence economic growth.

Evaluating a firm and market condition in order to acquirinformation for future investment plan involves high costHowever, this must be accomplished because capital owner o


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potential investors will not want to invest their money into production activities with limited reliable information. Highinformation cost and transaction cost create less optimalinvestment value (Levine, 2005).

The intermediary function of financial sector reduces cost oftransaction and cost to acquire information about a company andmarket condition, hence lowering the cost to potential investorswhen compared to doing it themselves. Through thedevelopment of effective financial system, financial intermediarycan provide information on the most promising and most

profitable companies to invest in; therefore resource allocationcan be done efficiently which then accelerates the economicgrowth (Levine, 2005).

The financial system’s ability to provide risk diversification canaffect long-run economic growth by altering resource allocationand the savings rate. Capital owner usually dislike risk, while

projects offering high profitability normally have greater riskthan that with low profitability. The ability of financial system todiversify risk can offer higher profit at lower risk to capitalowner to invest in high-risk projects, hence creating positiveimpact on the economic growth (Levine, 2005).

Pooling may also occur through financial intermediaries, whereinvestors (a party who provides funding) entrust their wealth to acertain financial institution that invest in firms (a party whorequires funding). Financial system which is more effective atmobilizing and pooling the savings of individuals can

profoundly affect the economy by increasing savings and capitalaccumulation (Levine, 2005).

According to Mishkin (2004), one of the monetary policytransmission mechanisms is through financial sector creditchannel. Financial sector credit channel is based on the role of

banks in corresponding financial system to anticipateasymmetric information issues occurring in credit market.Asymmetric information issue refers to information gap relatedto fund provision and loan provision, resulting in the inability toefficiently provide credit to the party in needs. The monetary

policy transmission mechanism through financial sector creditchannel is as follows:

Monetary policy increases society’s deposit in financial sector,which increases availability of credit. Borrowers rely on credit

provided by financial sector to finance their business activities;

hence the increase in credits will increase investment andincrease output.

II.2 Financial System Stability

Sutton and Tosovsky (2007) describe financial stability as acondition where financial system is able to: (i) allocate resourceefficiently into productive activities at different times; (ii)

predict and measure financial risks, and (iii) absorb shocks orsudden/dramatic changes in economic conditions. Financialsystem stability includes efficiency and resilience of thefinancial system, which is a complex concept. Stability of the

financial system not only depends on individual financiainstitutions, but also depends on complex interactions betweefinancial institutions, the real sector and the financial market.

The difference between financial stability and monetary stabilitrefers to price stability in general. According to Croket, financiainstability will have a negative impact on the effectiveness omonetary policy (monetary stability) if banks cannot transmtheir monetary policy properly. Theoretically, in a closeeconomy system, monetary policy strongly links to financiastability. This is because in closed economy system, there is lack of externalities that can affect domestic monetary policyTherefore, the effect of monetary policy on domestic financiastability becomes very dominant.

Conversely, in an open economy, the relationship betweemonetary policy and financial stability is more tenuous. This idue to external disruptions in the domestic economy, hencrequiring supporting policies, namely fiscal policy, in order tminimize the loose relationship between monetary policy anfinancial system stability.

II.3 The Relationship between Inflation and Economi

Growth

In recent decades, relationship between inflation and economigrowth has attracted economists, policy makers and central banattentions both in developed and developing countriesSpecifically, the main concern is whether inflation is required foeconomic growth or contrary, whether inflation is dangerous tthe nation's economy. Basically both ideas create intense debatetheoretically and empirically. This issue was first developefrom a controversial idea between structuralists and monetarist

Mundell (1965) and Tobin (1965) predict positive relationshi between inflation rate and capital accumulation rate, which iturn, implies positive relationship towards economic growthThey argue that since money and capital are substitutable, aincrease in the rate of inflation increases capital accumulation bshifting portfolio composition from money to capital anthereby, encouraging the rate of economic growth (Gregorio1996).

Until now, although the relationship between inflation aneconomic growth remains controversial, several empiricastudies show both negative and positive relationship between thtwo macroeconomic variables. Some economists agree that low

and stable inflation stimulate economic growth and vice vers(Mubarik, 2005). A question might arise on how low is thintended inflation rate. The answer clearly depends on the naturand the structure of economy which varies in each countryMacroeconomic experts have adopted econometric technique

by only looking at non-linear effect which concludes that thimpact of inflation on economic growth may be positive up to certain threshold, after which the contribution becomes negativ(Sweidan, 2004). This supports structuralists and monetaristadvanced arguments, by suggesting that low levels of inflatiomay initially be supportive of growth gains, but once theconomy achieves faster growth inflation can be detrimentatowards economic growth.

M bank deposits bank loans I Y↑ → → ↑ → ↑ → ↑


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II.4 The Relationship between Financial Deepening and

Economic Growth

Patrick (1966) identifies two possible causal relationships between financial deepening/financial development andeconomic growth. The first relationship is demand-followingview that postulates demand in every financial service is affected

by economic development; hence the creation of a modernfinancial sector is a response of demand in the economy (saversand investors). In this demand leading relationship, the faster theeconomic grow, the larger is the demand for financialintermediary service, transferring savings from a slow growth toa high growth sector (Kar and Pentecost, 2000:5). The secondrelationship is the supply leading. According to the supplyleading relationship, the existence of financial sector and itsservices will increase investment and economic growth.

Greenword and Jovanovic (1990) argues that there is a two-wayrelationship between financial development and economicgrowth. On the one hand, economic growth stimulates financialdevelopment. This occurs because financial institutionestablishment requires a fixed cost payment. The cost, which is afraction of income, will decrease in growing economy. On theother, by collecting and analyzing information from many

potential investors, financial institutions can undertakeinvestment projects efficiently and, hence, stimulates investmentand economic growth.

Diamond (1984) links financial sector in economic growththrough its role in minimizing monitoring costs emerged fromincentive issues between fund owner and investors. Theincentive matter arises due to asymmetric information occurring

between owners and investors, hence, causing moral hazard andadverse selection. With low monitoring cost, intermediation infinancial sector supports improvement of social welfare.

Recent research on the interaction between financialdevelopment and economic growth by King and Levine (1993)summarizes that financial development determines economicgrowth. Conversely, Arestis and Demetriades (1997), Shan andMorris (2002) and Shan, Sun and Morris (2001) assert that theabove hypothesis only valid in several countries surveyed, hencethere is no general conclusion can be made.

Positive view on the financial system hypothesis whichstimulates economic growth usually focuses on the role offinancial development in mobilizing domestic savings andinvestment through open and liberal financial system, inenhancing productivity through efficient financial marketcreation. Chen (2002) argues that central bank independency ininterest rate policy development and financial intermediation canresult in sustainable economic growth.

II.5 The Relationship between Financial Deepening and

Inflation

Boyd, Levine, and Smith (2000) model variables of bank creditextension to the private sectors, volume of bank liabilitiesoutstanding, stock market capitalization and trading volume (allas ratio to Growth Domestic Product/ GDP) and inflation. Theyfind that at low-to-moderate rate of inflation, any increase in the

rate of inflation markedly reduces volume of bank lending to th private sector, lowers the level of bank liabilities outstandingand significantly decreases level of stock market capitalizatioand trading volume. They also assert that the relationshi

between inflation and financial market development becomeflatter/unclear. This is because the increase in the rate oinflation has a much greater effect on financial development alow inflation rate than at high inflation rate.

To further illustrate, a high level of inflation is related treduction in rate of return of several assets. The high inflatiorate also creates credit restriction, reduction in financia

performance and lowered real sector activities. Why does higlevel of inflation causes reducing in long-term rate of returnThe answer is because high money demand in an econom

promotes inflation. As an example, banks in high inflatioeconomy provides fund or capital reserve in large amounPreviously known, high inflation rate acts like a tax on banreserves. When this tax is paid by the clients, then high inflatiorate reduces deposit interest rate. Further, due to competitio

between bank deposit and other assets, lowering in deposinterest rate will also result in reduction of return on other assetBarnes, Boyd and Smith (1999) and Boyd, Levine and Smit

(2000) highlight that the abovementioned condition is valid in nation’s economy with high rate of inflation, and high rate oinflation is related to low return on short-term asset, governmenobligation and good quality loans.

II.6 Monetary Stability and Financial System Stability

Before looking at the relationship between monetary stabilityfinancial system stability and economic growth, it is essential tagree on definitions related to monetary stability and financiastability. The accepted definition of monetary stability in thcontext of subdued inflation in academics and for the centra

bank is a condition that guarantees the achievement of pric

stability, as defined by low and stable prices (inflation). Pricstability held a very important role in a nation’s econom

because price changes highly influence the process of adjustmenand decision making by economic agents. However, aunderstanding of financial system stability has not yet beeconcluded due to the absence of agreement on a definitionMiskhin (1991) defines financial stability as a condition in whicfinancial sector guarantees efficient allocation of savings aninvestment in sustainable manner and without any significandisturbance. A more commonly used definition in analysis is thamonetary stability is a situation marked by stable asset pricewithout banking crisis, with market interest forces that is easiltransmitted into interest rates. (Issing, 2003).

The definitions given above also generate another question in threlationship between monetary stability and financial systemstability. Are the two mutually supportive or even negativelcorrelated in the sense of trade-off? The conventional viewstates that monetary stability supports financial stability. Thmain proponents of this view regard monetary stability or pricstability as a “sufficient condition” for financial stabilit(Schwartz, 1995). This view assumes that price stability oinflation is one of the main factors behind financial markeinstability. A related idea is that inflation is regarded to increasthe probability of misperceptions concerning future incomattainment and worsens asymmetric information between lender


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and borrowers. In another point of view, a high inflation also promotes large price fluctuations, which create uncertainties in business. This argument is supported by empirical evidenceshowing that financial crisis and banking crisis were generallycaused by sharp increase in price level (Bordo et al, 2000;Calomiris and Gorton, 1991).

This argument is consistent with the idea that banking crisis willtrigger monetary instability In this respect, a twin crises whichinvolves banking system and the exchange rate will result in anunexpected monetary policy (Goldfajn and Gupta, 2002). Inexchange rate crises, a tight monetary policy has the potential tostabilize the exchange rate and the financial sector. However, in

banking crises, the reverse will apply. In situation like this, theselection of monetary policy response will be influenced byseveral factors, such as the extent of currency mismatch indomestic banks and the discretion of central bank policy in

providing liquidity in a crisis situation (Shin, 2005). Thus, withregard to the conventional point of view, generally there is notrade off between monetary stability and financial stability.

The new environment hypothesis, however, states that there is atradeoff between monetary stability and financial stability. Thisis based on the proposition that inflation control by the central

bank can improve market’s positive perception on the economy.Borio et al. (2001) indicates that the combination of asset priceincrease, high economic growth and low inflation can fosteroveroptimistic market on economic performance. This willescalate asset and credit market activities that exceed the

potential production capacity which in turn will promote asset price increase and inflationary pressure.

Issing (2003) studies the trade-off identification based on timehorizon. In this respect, trade-off may occur in short-term, that isduring the period of rapid disinflation (inflation below thetargeted rate). In the ‘new environment', this may bring on

fragility to crises due to reduction of nominal interest rates,which further exacerbates moral hazard in the credit market. Inseveral cases, the very low inflationary can trigger asset price

bubble. The fragility to crises will tend to be short-lived becausethe central bank as monetary authority will raise the nominalinterest rates to settle down inflation as a result of asset priceincrease and prevent long-term inflationary pressure.

Therefore, in the context of central bank’s “forward looking” policy and in relation to price stability, the problem of trade-offwould slowly diminish. From other point of view, regardingthreats arising from financial system instability towards mediumand long-term monetary stability, central bank policy should

consider financial stability in maintaining price stability.Implication of conflicts in short-term may not set aside aconventional policy that price stability supports financial systemstability

III.RESEARCH METHODOLOGY

III.1 Research Variable Identification and Mode

Specification

III.1.1 Research Variables

Research variables used in this research are: economic growt(GROWTH), inflation (INFLATION), credit–to-GDP rati

(FINDEV), interest spread (SPREAD) and exchange ratdepreciation of US dollar to rupiah (XRATE).

The variables are defined as follows:

a) GROWTH represents Indonesian economic growthwhich is nominal GDP at the current price level i

billion rupiahs. The use of nominal NDP as aeconomic growth indicator has been used by King anLevine (1993), Khan and Senhadji (2000), Rousseaand Wachterl (1998) and Aziakpono (2003). The dat

being used is quarterly nominal GDP interpolated tmonthly data using Quadratic-match sum technique

After interpolation, the monthly data is annualized. Thiis obtained from the addition of previous year’ nominaGDP to current GDP. As an example, annualizenominal GDP in April 2010 equals to the addition onominal GDP March 2009 up to nominal GDP Apr2010.

b) Inflation, which is percentage of change in ConsumePrice Index, is a proxy of monetary stability variable.

c) Credit-to-GDP ratio is the ratio between nominal credto nominal GDP. The larger the bank credit extension tthe private sectors, the larger the investment whicmeans that the greater economic growth. Credit growtis therefore proportional to economic growth. Fundin

ratio is an important indicator of financial sector itransferring fund from savers (with excess fund) tinvestors in need. Credit-to-GDP ratio is used as variable in financial development.

d) Interest Spread as proxy Implied Risk Premium is thdifference between interest rate provided by banks aninterest rate set by monetary policy, the 1-month SBrate. The use of interest spread is one of financiasystem stability variables.

e) Exchange rate depreciation is the level of exchange ratdepreciation of US dollar to rupiah. Appreciatio(increase in exchange rate) supports economic growthIn other words, the exchange rate depreciation idirectly related to economic growth. Exchange ratdepreciation is used as external factor variable.

III.1.2 Data

This research utilizes time-series data between 2002:1-2010:1time period. The data are collected from several resources, sucas Indonesian Economic and Financial Statistics (SEKI), BanIndonesia, International Financial Statistics (IFS on-lineInternational Monetary Fund (IMF) and Financial StructurDatabase, World Bank.


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III.1.3 Model Specification

Generally, the VAR model used is as follows:

While the model VECM specification (restricted VAR) is asfollows:

III.2 Bivariate VAR system with order p

VAR with order p of bivariate system or two variables

1

2

t

t

t

y y

y

=

can be defined as

t 1 t 1 p t p t...

− −= + + + + y y y ε

where

1

2

α

α =

is two-dimension vector,11 , 12 ,

21, 22 ,

, 1, 2 , . .. ,i i

i

i i

i p

θ θ

θ θ

= =

is

( )2 2× coefficient matrix and 12

ε

ε

=

t

t

is a white noise

vector. In other words:

1) t has zero mean, [ ]t E = 0

2) t has constant variance,' ,t t

E t = Σ ∀ εε

3) andt sε are not correlated, for t s≠ .

Equationt 1 t 1 p t p t

...− −

= + + + + y y y ε can be written

as follows:

11 , 12 , 111 ,1 12 ,1 11 , 2 12 , 21 1 1 1 2 11

21 , 22 , 221 ,1 22 ,1 21 , 2 22 , 22 2 1 2 2 22

... p p t pt t t t

p p t pt t t t

y y y y

y y y y

θ θ θ θ θ θ ε α

θ θ θ θ θ θ ε α

−− −

−− −

= + + + +

Two-dimension random vectort 1 t t 1

..., , , , ...− +

y y y is a stochastic

process vector. A stochastic process vector is stationary if:

1) [ ]E , t= ∀ t

y µ

2) ( )( )[ ]- -

cov( , ) E ' ( ), t dan 0,1,2,...t t h t t h

h h= − − = Γ ∀ = y

y y y y

III.3 Cointegration Test

Johansen’s cointegration test is based on the VAR(p) model onon-stationary variables. For simpler Johansen test procedureVAR(1) model will be used. Remember that VAR (1) model inoted in matrix notation:

1 1t t t Y Y ε −= Π +

In Johansen’s cointegration test, analysis of variables is not onlfocused on the result of VAR equation system (ImpulsResponse Function and Variance Decomposition are the moscommonly used, as previously discussed), but also considered stepping stone for the next cointegration test, whereby re

parameterization need to be done from VAR(1) model to ModeVector Error Correction (VECM(1)).

The Granger theorem ensures the existence of an error correctiorepresentation in a cointegrated regression. Based on ththeorem, equation VAR(1) can be represented in the form oVECM as follows:

1 1

1 1 2

where:

and

t t t

t t

Y Y

Y Y Y I

ε −

−

∆ = Π +

∆ = − Π = Π −

This VECM (1) form contains information about short-run an

long-run changes stated by parameter and . This Matri

will be further used to determine whether regression systemis cointegrated. This is the core of Johansen test procedure ianalyzing the cointegration relationship between observevariables.

For instance, a component of vector Yt is a first ordeintegration or written as I(1), then Y t-1 is a linear combinatioof variable ∆Y t-1 I(1). In order to estimate all combinatio

possibilities from Yt-1 which results in close correlation wit∆Y t-1, a stationary element, Johansen uses matricharacteristics as follows:

1. If Rank( )=0, then, there is no cointegratio between variables

2. If Rank( )=m (m : the number of variables iVAR model), then all variables are cointegrated

3. If 0 < Rank(

)


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III.4 Innovation Accounting

Basically the test is employed to test the dynamic structure of thesystem variables in the model which have been observed, asreflected by the variables of innovation. In other words, this testis a test of the variables of innovation. This test consists of:

a) The Impulse ResponseThis test is used to observe the effects of a standard deviation

shock to one of the variable of innovation on the currentvalues and the future value of endogenous variables includedin the model.

b) The Cholesky DecompositionThe Cholesky Decomposition commonly known as variancedecomposition provides information about the relativeimportance of each variable in the VAR system according tothe shocks. This test is basically another method to describethe dynamic system contained in VAR by collectingestimates of error variance of a variable or, the differenceamount between the variance before and after the shock.Both shocks are originated from that variable itself and fromother variables.

IV. DATA ANALYSIS

IV.1 Descriptive Analysis

Illustrated below is credit growth and nominal GDP during theobservational period, from 2002 to 2010.

Figure 4.1 Credit growth and economic growth

Figure 4.1 depicts that at the beginning of 2003, the creditgrowth is higher than the economic growth. This situation lastsup to early 2006 where bank lending significantly declined andcredit growth attained its lowest level at the third quarter of2006. This differs from the nominal GDP growth thatexperiences high growth. From the figure above, in general,credit growth and economic growth is positively related althougha lag exists, where the credit growth tends to precede the outputgrowth.

Availability of bank lending is highly influenced by bankliabilities outstanding. Transmission mechanism channel forcredit channel provides the idea that an increase in money supply

will result in an elevation of private sector credit. Furthermoreincrease in investment credit would in turn promote economigrowth.

According to long-term regression equation, credit-to-GDP ratisignificantly influences economic growth. Meanwhile, in shortterm equation, credit-to-GDP ratio variable shows insignificaninfluence. This is in line with findings of Dornbusch, Fischer anStarz which state that investment affects long-term econom(2001:335).

Shown below are the growth of credit-to- nominal GDP ratio anthe growth of nominal GDP between 2002 and 2010.

Figure 4.2 Credit-to-GDP ratio and economic growth

Figure 4.2 above shows that there is a positive relationshi between financial deepening and economic growth. The upwartrend of credit-to-GDP ratio observed between 2002 and 2005, followed by rising economic growth. At the end of 2005 anduring 2006, the credit-to-GDP ratio declined and fun

placement at Bank Indonesia rose. This phenomenon is related tIndonesia’s economic turmoil occurring at that time. In lat2005, government policy in reducing fuel subsidies resulted inegative pressure on the national economy.

In early 2006, amid of unrecovered investment climat perception and economic slow down, credit demand and suppltended to drop and bank operation was more focused in shorterm financing, especially in consumer sector and money marke

placement. Observing obstacles posed by banks, during 2006Bank Indonesia took several steps to give more room to banks i

performing its intermediary role, upholding prudential aspectAll policies developed were placed within an integrated an

systematic framework through January Policy Package (Pakjan2006 and October Policy Package (Pakto) 2006. One importandecision made in strengthening banking structure for economiimprovement is adjustment of definition in Credit ProvisioMaximum Limit (BMPK) setting.

The global economic condition with enduring pressure from thcrisis created several major challenges during 2009. Thchallenges were quite surfaced at the beginning of 2009, as aimpact of global economic crisis which peaked in the fourtquarter of 2008. Uncertainties related with how deep the globacontraction and how quick the global economic recovery witake place, not only increased risk in financial sector, but als


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negatively impacted economic activity in the domestic realsector. The condition created pressure on monetary stability andfinancial system stability on the first quarter of 2009, whileeconomic growth remained in its down trend due to a deepexport contraction of goods and services.

Figure 4.3 Credit growth and economic growth

Figure 4.3 shows the relationship between credit growth andeconomic growth. It is evident that between 2002 and 2005, therise in economic growth was followed by positive credit growth.

While in the post global crisis, between 2008 and 2009, the pressure on output/ the slowing down of economic growth wasfollowed by the reduction in credit volume distributed. Thisindicates that the inherent issue embedded in short term capitalflow is the 'procyclicality', where massive capital inflow occursin economic boom and capital outflow occurring in economicslowdown.

In a rapidly growing economy, capital inflow may cause 'internalimbalances' because capital flow also triggers inflationary

pressures and asset bubbles, and in turn promotes ‘externalimbalance’. This is because the appreciation pressure resultedfrom capital inflow exacerbates the current account. Conversely,

in an economic slowdown, a sudden reversal of capital flows cantrigger depreciation pressure and macroeconomic and financialsystem instability.

Shown below is the movement of lending rate, SBI rate andimplied risk premium (spread) throughout the observation periodfrom 2002 to 2010.

Figure 4.4 Lending rate, 1-month SBI rate and interest spread

Figure 4.4 indicates that the lending rate quickly responses thrise in SBI rate. In situation where SBI rate loosens, the lendinrate shows a lagging response. This condition is clearly seen ithe fourth quarter of 2005 to the first quarter of 2006 and in thfirst quarter of 2009. In the fourth quarter of 2005 to the firsquarter of 2006, Bank Indonesia raised SBI rate to anticipatinflation pressure due to fuel price hikes policy executed iOctober 2005. Interest spread returned to its downtrend due tthe rise in 1-month SBI rate in the second quarter of 2008. Thiis due to Bank Indonesia’s policy in maintaining the weakeninRupiah as a result of global economic crisis. As an impact oglobal crisis, there has been a vast outflow of foreign funds, ithe form of portfolio investment, as an effort to secure theiinvestment. As a result, rupiah rapidly depreciates and BanIndonesia’s responded this situation by raising domestic interesrate to control the weakening rupiah as an impact of globaeconomic crisis.

Figure 4.5 Interest spread and economic growth

It can be seen from graphs shown in Figure 4.5 that the implierisk premium (spread) is negatively related to economic growthBetween the second quarter of 2002 to the beginning of 2005where high interest rate spread was evident, or in other wordsloose BI monetary policy, the economic growth was in itdownward trend. Furthermore, in the fourth quarter of 2005 tthe first quarter of 2006, anticipating the inflation pressure as result of the increase in fuel price on October 2005, Ban

5

10

15

20

25

30

35

40

2003 2004 2005 2006 2007 2008 2009 2010

CREDIT GROWTH GDP GROWTH


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Indonesia raised the BI interest rate. The tight monetary policy isreflected by a lower interest spread.

Figure 4.6 Inflation and interest spread

Figure 4.6 depicts that implied risk premium (spread) shows anegative relation to inflation. From the first quarter of 2003 tothe second quarter in 2005, a tendency of high risk premium wasobserved, or in other words, a loose monetary policy stanceBank Indonesia, followed with low inflation rate. Risk premiumwas low, followed with inclining inflation rate as a consequenceto government policy on raising fuel price due to oil price hikes.

Negative relationship was also noted at the beginning of 2009 upto the end of year 2010, with high risk premium followed withlow inflation rate.

Figure 4.7 Exchange rate depreciation and inflation

The above graph shows a positive relation between exchangerate depreciation and inflation. During the analytical period

between 2002 and 2010, there had been comovements observed between exchange rate depreciation and inflation rate. To bespecific, in the second quarter of 2005 to 2006 and the fourthquarter of 2008 to the third quarter 2009, the movement ofexchange rate tends to precede that of the inflation. In general,there is positive relationship between exchange rate andinflation.

IV.2 VAR Analysis

IV.2.1 Unit Root Test

In this section, stationarity test is conducted on several researcvariables, namely: real GDP growth, inflation, credit-to-GDratio, interest spread and exchange rate. The test employed iAugmented Dickey Fuller (ADF) test.

The model used in ADF test is:

1 1

2

p

t t i t i t

i

Y Y Y µ γ β ε − − +

=

∆ = + + ∆ +∑

From the above mode, a hypothesis can be formulated: Non-stationary data ; stationary data

0

0

H : 1

(Non stationary data)

H : 1

(Stationary data)

p

i

i

p

i

i

φ

φ

=

−

<

∑

∑

Statistical Test:

ˆ 1

= Dickey Fuller

std. error

p

i

i

p

i

i

φ

τ

φ

−

∑

∑

Significance: = 5%α

Decision rule in ADF testing:If the τ statistic value is smaller than the Dickey Fuller criticavalue, then the null hypotesis is rejected, indicating that the timseries data is stationary.

Table 4.1 Unit Root Test

From the unit root testing, the existence of unit roots in thresearch variables indicates that the research data are nonstationary. With regard to the non-stationary originated data, thnext step is to conduct first difference testing. Results suggesthat the first difference data shown to be significant at the 5%significance level. This implies that the research variables arstationary at first difference.


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IV.2.2 Lag Length Determination in VAR

In this section, the AIC and SIC criterion are used in determiningthe optimal lag length in a VAR model.

Determination of optimal lag used by the researcher in order toestimate a short run equation is based on Akaike InformationCriterion (AIC). The criterion of optimal lag information can beseen in Table 4.2 below.

Table 4.2 Optimal lag determination

According to Table 4.2 above, it can be seen that the optimal lag based on AIC is lag 3.

IV.2.3 Cointegration Test

The purpose of cointegration test is to assess similarities ofmovement and relationship stability between variables in a long-run. When a data series contains a unit root and integrated to thesame order, cointegration test can be performed to assess theexistence of cointegration. In this research, the Johansen’sCointegration Test method is employed. An influentialrelationship can be seen from the cointegration that exists

between variables. When a cointegration exists betweenvariables, this implies that influential relationship occursthroughout variables and information is parallelly distributed.

The Johansen’s Cointegration Test indicates that a cointegratingvector exists, or at least a linear independent combination existsfrom the variables contained in the model. The consequence isthat alternative hypothesis which states the presence ofcointegration relationship can be accepted.

Table 4.3 Cointegration Test

Cointegration test result indicates that research variable halong-term relation. It can be concluded that the next step oanalyzing short-run analysis between research variable in longterm can be executed.

In long-term specification model, several restrictions werimposed in a long-term equation parameter. First, in the longrun, there is no relationship between inflation and output. This isupported by the Phillips Curve theory that shows relationship/trade-off between inflation and short-run output. Iother words, in short-run, the economy has to bear the cost anthe inflation if higher economic growth is required. This iclearly shown in the Phillips curve below.


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Figure 4.8 Short-run Phillips Curve

Source: Robert J. Gordon, Macroeconomics, 10th edition, 2006,Addison-Wesley

Secondly, there is no long-term relationship between exchange

rate depreciation and economic growth. Traditional views suchas elasticity approach, absorbance and Keynesian approachargue that exchange rate depreciations have positive effect onoutput. Elasticity approach states that depreciation will boosttrade balance when Marshall Lerner condition is fulfilled.Keynesian approach, where output is assumed to be below

potential output, full employment states that exchange ratedepreciation will positively impact on output and employment.However, the monetary approach argues that exchange ratedepreciations influence real magnitudes especially through theinfluence of real balance in the short-run, but leave all variablesconstant in the long-run (Domac, 1997).

Third, there is no long-run relationship between financialdevelopment and inflation. The increase in bank lending will boost the total amount of money in circulation. According toQuantity Theory of Money, expansion in money supply resultsin inflation. In monetary view, the elevation in total amount ofmoney in circulation encourages the elevation of aggregatedemand and excess demand, leading to increase in price leveland wages, whereby this mechanism only happens in short term.

Table 4.4 Estimation of VECM Long-Run Model

The Likelihood Ratio Test is done to assess the appropriatenesof parameter restrictions in a long-run equation. The value wit2-degree of freedom and is observed. It can be concluded ththe data support parameter restrictions set in the long-ruequation.

IV.2.4 VECM Long-Run Model

In the long-run (with the use of cointegrating vector

interpretation), the following model can be constructed:

Theoretically, the signs located in each variable are logical anrational. From the economic growth equation above, it can bseen that financial deepening FINDEV is positively related teconomic growth GROWTH. This supports the supply leadinhypothesis asserted by Patrick (1996) where financiaintermediaries transfer resources by collecting funds anmobilizing savings to be directed and used for investmen

purpose. This is in line with funding innovation concep proposed Schumpeter (1911).

SPREAD is negatively related to GROWTH. The increase ispread between credit interest rate and interest rate policindicates the increased risk in an economy. This reflects thvulnerability of financial system to shocks. In other wordfinancial system is in an unstable condition, giving pressure toutput.

( )

( )

GROWTH(-1) 26.95074+0.509185 FINDEV -1 3.948655 SPREAD(-1)

[-2.57882] [ 8.00248]

INFLATION -1 13.79273 0.985913 SPREAD(-1) 0.015158 XRAT

= −

= − +

[ ] [ ]

E(-

2.09635 0.33260−


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According to the inflation equation, SPREAD is negativelyrelated to GROWTH. Financial instability shown by increasingrisk in financial system reduces inflation rate. This is relevant inhigh risk situation where market responds by declining

purchasing power, resulting in the reduction of aggregatedemand.

Furthermore, XRATE positively influences INFLATION. Theexchange rate depreciation directly increases money supply, theincreasing in money supply reduces interest rate. The decline ininterest rate promotes investment and aggregate demand. Whilethe excess demand results in elevation of price and wages,thereby, resulting in high inflation rate.

IV.2.5 VECM Short-Run Model

Table 4.5 Estimation of VECM Short-Run Model

From Table 4.5 above, it can be seen that all short-termcorrected coefficients heading towards long-term equilibrium(ECT/Error Correction Term) show negative sign and significantat 99% confidence level. This indicates that the model used isstable enough and is in line with the basic theory. The ECTcoefficient for short-run growth dynamics also shows statisticalsignificance with negative result. The negative sign on ECTcoefficient shows that the VEC model is a backward modelwhere short-run imbalance will be corrected towards long-runimbalance, according to information accommodated within ECTvariables. Besides that, in short-run, economic growth is alsoinfluenced by the growth itself and inflation; while implied risk

premium and inflation are the main contributing factors of shorrun inflation dynamics.

IV.2.6 Impulse Response Function

An impulse response function states the effect of one standardeviation shock to one of the innovations on current time valueand future values of endogenous variables. A shock fromendogenous variable directly influences the variable itself, whic

then influences other endogenous variables through the dynamistructures of VAR and VEC. IRF provides direction anmagnitude of the effect between endogenous variables as demonstrates the influence of one-standard deviatioendogenous variable shock on other endogenous variables anthe variable itself. Therefore, with new information coming upany shock that occur in a variable, will affect the variable itseland other variables in a system. Impulse Response Function oresearch variables for 10 upcoming period is presented below.

Figure 4.9 Impulse Response Function

Responses of economic growth to inflation, financial sectodevelopment, implied risk premium and exchange ratdepreciation shocks.

From Figure 4.9 above, GDP growth’s positive response ievident on a standard deviation shock to credit volume. Th

positive relationship supports the theory stating that increasincredit volume stimulates the real sector economy, which furtheincreases output. On the other hand, GDP growth responsenegatively to a standard deviation shock to spread (implied ris

premium) and exchange rate. The elevation of interest sprea(implied risk premium) reduces investment and creates pressurin economic growth. This occurs permanently up to the 36tmonth.


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Figure 4.10 Impulse Response FunctionResponses of inflation to economic growth, financial sectordevelopment, implied risk premium and exchange rate

depreciation shocks

Figure 4.10 shows the response of inflation towards shocks incredit volume, spread and exchange rate. The increase in creditvolume distributed to banks is responded positively by inflation,with the increased in inflation rate. This occurs as a direct impacton increasing capital resource in real sector, resulting in greatermoney supply in the society. Higher money supply negativelyaffects price level stability (higher inflation rate).

The elevation of interest spread (implied risk premium) is alsonegatively responded by price stability. Increasing risk levelindicated by widening interest spread reduces investment climate

in a country which forces the reduction of real interest rate.Therefore, assuming ceteris paribus, output level declines or inother words, economic recession occurs. In recession, deflationcommonly takes place.

IV.2.7 Variance Decomposition

Table 4.6 Variance Decomposition of Economic Growth

Table 4.6 above shows us that on the first period, the forecasterror variance of GROWTH explained by the GROWTH itself is85%. In 36 months, the forecast error variance explained byGROWTH decreases to 6%. It is evident that economic growthis highly influenced by the implied risk premium and financial

development which describe each forecast error variance ogrowth of 57% and 30%. The exchange rate depreciation aninflation only influences economic growth in short-run. This alsindicates that the data support the restriction imposed in thlong-run equation.

Table 4.7 Variance Decomposition of Inflation

From table 4.7 above, it is observed that on the first period, thforecast error variance of INFLATION explained by thINFLATION itself is reported to be 73%. At the beginning o

period, there has been marked influence from GROWTHvariable of 17.04%, decreasing in 36 months, where GROWTH

only contributes 2% of the forecast error variance fromINFLATION. This is in line with the short-run Phillips Curvtheory which illustrates short-run trade-off between economigrowth and inflation. Up to the 36th month, the forecast errovariance of INFLATION is described by FINDEV, SPREADand XRATE contributing 44%, 25% and 20%, respectively. Thiindicates that in the long-run financial development, implied ris

premium and exchange rate depreciation influence monetarstability (inflation).

V. CONCLUSION AND RECOMMENDATIONS

5.1 Conclusion

This research is conducted to understand the relationshi between financial sector dynamics, inflation and economigrowth in Indonesia. It can be concluded that:

1. A positive relationship is evident between financiadeepening and economic growth, while negativrelationship is observed between financial systemstability and economic growth

a. This is shown by the VECM Model whicillustrates that in a long-run, financiadeepening and financial system stabilitinfluence economic growth.

b.

According to the estimated results of ImpulsResponse, a positive shock of financiadeepening is positively responded by thincreasing economic growth for 36 months. Othe other hand, a positive shock of implied ris

premium (spread), exchange rate depreciatioand inflation are negatively responded by theconomic growth.

2. Negative relationships are evident between financisystem stability and monetary stability (inflation) awell as exchange rate depreciation and inflation

Variance Decomposition of GROWTH

Period S.E. XRATE SPREAD FINDEV GROWTH INFLATION

1 4.675623 1.224627 12.25342 0.65976 85.86219 0

6 10.77995 0.578441 49.0602 0.487891 46.3697 3.503765

12 14.16866 0.137386 66.84135 9.413768 18.79081 4.81669

18 16.69339 0.095708 64.7816 19.24083 10.56299 5.318876

24 18.4802 0.17359 61.08808 25.08083 7.72892 5.928587

30 19.92642 0.279459 58.84812 27.88405 6.578549 6.409827

36 21.25784 0.357925 57.7011 29.21874 5.999509 6.722718

Cholesky Ordering: XRATE SPREAD FINDEV GROWTH INFLATION

Variance Decomposition of INFLATION

Period S.E. XRATE SPREAD FINDEV GROWTH INFLATION

1 0.282013 0.180058 8.867256 1.010217 17.04958 72.89289

6 1.092094 9.970768 36.06197 4.610009 9.809208 39.54804

12 1.74729 10.64549 43.48506 23.87836 3.53918 18.45191

18 2.222245 13.00937 36.525 35.37426 2.501613 12.58976

24 2.588447 15.80549 31.13252 40.33962 2.27741 10.44496

30 2.905923 18.03045 27.92656 42.63289 2.083341 9.326761

36 3.200221 19.5112 25.98069 44.08262 1.910189 8.515301

Cholesky Ordering: XRATE SPREAD FINDEV GROWTH INFLATION


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a. This is shown by the long-run model thatfinancial system stability and exchange ratedepreciation influences inflation rate.

b. According to the estimated results of ImpulseResponse, inflation positively responses a

positive shock of financial deepening, andnegatively responses implied risk premium(spread) and exchange rate depreciation.

3. A positive relationship is observed between economicgrowth and inflation.

According to the estimated results of ImpulseResponse, inflation positively responses a positiveshock in economic growth.

5.2 Recommendations

This research investigates the relationship between financialsector dynamics, inflation and economic activities. In the pasttwo decades, there have been substantial changes in Indonesianfinancial sector. Several deregulations occurring in financialsector markedly impact on macroeconomic condition, especiallyon the economic growth.

Nation’s economy is highly determined by its financialdevelopment because financial sector held a very important rolein performing its intermediary role. Therefore, banking sectorneed to be supported to improve the provision of productiveinvestment credit, while upholding the risk management

principle in its operation. With emerging investment projects,there will be a surge in demand of financial products such aslending. Hence, interactions between monetary sector and realsector need to be encouraged to drive Indonesia’s economy. Inorder to optimize credit distribution to the real sector, there is aneed of solid coordination between Bank Indonesia as monetaryauthority and the government as the fiscal authority, inminimizing asymmetric information that occur in credit market.

Besides, the government is also expected to develop policieswhich creates conducive business environment with regard toseveral economic issues in cost, law enforcement andinfrastructures in order to attract new capital investment.

In relation to the ‘procyclicality’ in Indonesian economy, BankIndonesia is expected to coordinate with the government as afiscal policy authority in supporting ‘countercyclical’macroeconomic policy. This is essential in avoiding potentialrisk if the economy turns to procyclicality. Moreover, monetaryand fiscal policy authority should implement risk managementguidelines in designing policy framework. In other words,macroeconomic policies developed by Bank Indonesia and the

government are expected to consider all potential risks that mayoccur in the nation’s economy, which in turn support financialsystem stability, monetary stability and stimulates sustainableeconomic.


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Documents

Analysis of the Relationship Between Financial Sector Dynamics, Inflation and Economic Growth