A. Introduction

The monetary policy mechanism by which monetary policy is transmitted to the real economy has emerged as the pivotal discussion topic recently because the reality that monetary policy has become the only game can be played by the central bank. However, as the economic situation among countries are dispersed, the empirical investigation resulted from various studies are also, in some cases, contradictionary and confusing. That is why it is a debatable topic in macroeconomics in general and monetary study especially.

However, till to date, there is no consensus among economists about how monetary policy operates. The traditional money channel (or interest rate channel) states that when the central bank reduces its reserves, commercial banks are forced to reduce their demand for deposits due to higher costs of funds. If prices are sticky, in the short run a decrease in real monetary holdings should lead to higher real interest rates. This in turn translates into a contraction of interest-sensitive components of aggregate spending (e.g., consumption and investment) and, therefore, into lower economic growth.

For Indonesia, the understanding and ability of Indonesia Monetary Authority how monetary policy works is necessary mandate of the new Central Bank Act of 1999 especially to help the economic recovery. The understanding how monetary policy works requires enhancements both the capacity and institutional buildings for better monetary policy making process and implementation. As enacted in 1999,the new Central Bank Act provides a clear mandate for Bank Indonesia in conducting its monetary policy to maintain the value of Rupiah both in domestic and international term.

Currently, the main investigation efforts are directed to study on the role played by banking industry in the transmission of monetary policy. The aim is to uncover a credit channel of monetary policy. As the credit channel operates through shifts in loan-supply schedules, uncovering the credit channel in monetary policy means nothing but to looking on the impact of monetary policy instrument to banking industry.

Warjio and Agung (2002) mentioned the reasons why Indonesian monetary authority is eager to study monetary policy channel because the understanding the movements of financial and economic aggregates as result of monetary policy would improve the understanding the link between the financial and the real sectors of the economy. Second, a better understanding of the transmission mechanism would help monetary authorities and analysts to interpret movements in financial aggregates. Finally, more information about the transmission mechanism might lead to a better choice of intermediate monetary targets. As concluded by Aghion, Bacchetta and Banerjetta (2000) the interest rate shock may be necessary to prevent crisis economy from further recession when the responses of such policy by credit supply not so strongly.

In the country experiencing multi crisis, banking, exchange rate and political crises, Indonesian monetary authority worked hard to make the credit channel work. The monetary policy currently is in questionable stage as Indonesia curretly lack of supported institution and condition for succesful monetary policy, such bank capital constraint (CAR), exchange rate instability and firm restructuring process. All these lessen the effectiveness of monetary policy. Under dis-intermediation in the banking industry, indicated by Loan to deposit ratio (LDR) currently at only 34%, the validity of the monetary policy is on attack. The attacks based on the assumption that the work of credit channel depends on the extent to which banks rely on deposit financing and adjust their loan supply schedules following changes in bank reserves as responses to monetary policy action.

The economic crisis that began in the mid-1997 completely changed monetary and banking landscape in Indonesia. After nearly ten years of rapid expansion, Indonesia’s banking system is crippled, with the vast majority of dominant local banks now technically bankrupt without government supports. It then means that when banks strive to survive, no actions will be done to responses the monetary policy action but only responding to prevent from the death.

However, the study is not based on that presumption. We still believe that the roles of monetary variables are still important to influences the bank managers to change their loan or balance sheet position.

B. Theoretical Background

The debate on the monetarty policy via bank lending chanel and balance sheet chanel emerged from the existence of assymentric information problem between lender and borrowers. Bank lending channel focuses on the assumption that bank loan is very important for successful monetary policy. In the monetary policy channel via the “bank lending ”(Bernanke and Blinder,1988), monetary transmission mechanism was delivered by banks upon changing their assets as well as their liabilities.

During a monetary contraction situation, banks will decrease their reserves and reduce their deposits and the the loan. In a monetary expansion, banks increase the loan. If the decrease in deposits is not offset by other funds which are not subject to reserve requirements,or by a decrease in securities,this will result in a decrease in bank loans.If bank loans fall and bank dependent borrowers are dominant in the economy,real investment expenditure will fall. Since bank loans in Indonesia remain the main source of external finance for business enterprises,a disrupting of bank loan supply can reduce the economic activity.

Kim (1999:5-10), using Korean cases, found that bank credit channel is significant after the crisis. The sharp drops in credit supply in line to the eastern asia crisis reduced credit supply provided evidence that constractive monetary policy was responded. There is strong evidence that a substantial excess demand for bank loans becuause of a dramatic decrease in loan supply as impact of banking crisis.

Previously, Kasyap and Stein (1997) found supportive evidences that credit channel is as monetary policy channel. The study was using USA bank panel data during 1976-1993. The study found evidences the impact of monetary policy that affected bank’s propensity to lend, especially among illiquid banks. For Indonesian cases, Agung (1998), using sample data from 1985-1995, proved that a monetary policy was able to influence the bank supply of credit, in particular small banks, not large banks which were able to shield their bank loan supply by finding the cheaper source of funds from overseas. Further investigation using aggregate data during episode of crisis, Warjio and Agung (2002) conclude that monetary policy is still effective to affect bank lending. However different type of bank has different elasticity.

DeBondt (2000) finds evidence for the reaction of bank lending to monetary policy mainly depends on bank size. On the other hand, Favero et al. (1999) do not find such evidence using the same database in a cross-sectional analysis. Worms (2001), Quoted from Kakes and Strum, (2002) – study using the Bundesbank´s bank balance sheet statistics covering all German banks – conclude that we cannot reject the hypothesis that the reaction of a bank’s lending to monetary policy depends on its size, although this effect does not seem to be of macroeconomic importance.

The finding support Kashyap and Stein (1995) that as long as the banks do not face a perfectly elastic demand for their managed liabilities, a bank lending channel will operate. However, some argue that the regulatory action of central banks can also significantly influence bank loan supply. For examples is the regulation on loan classification and capital adequacy ratio (CAR). Interested paper on this issue is the work of Peek and Rosengren (1995), The capital Crunch: Neither a borrower nor lender be, Journal of Credit Money and Banking, 27, p 149-213

De Haan (2001) usig bank level data divides all bank operting in the Netherlands into two classifications base on financial health and market orientation. The results for loan supply suggest that a lending channel is operative in the Netherlands but become less effective for secured bank debt. It means contractive monetary policy does not have any negative effect on secured bank lending.

Altunbas, Fazylop and Molyneux (2002) add more confusions on the role of bank channel in the monetary policy. By using bank specific data for European case, they found that smaller and undercapitalized banks were more responsive to monetary policy. Small banks which have relatively limited access to non-deposit funds such as securities issues or foreign borrowings are expected to be more affected by the monetary shock and to tend to cut their loan supplies immediately following the shock. However, across European countries resulted in inconsistent results and suggest further verification and examinations. Their findings are in line to Ehrmann et al. (2001) that testing for a differential reaction of bank loans to monetary policy across banks for France, Germany, Italy, Spain and the euro-area as a whole and conclude no evidence for a bank lending channel using bank size as the discriminating variable. They also show that the data summarized by BankScope is not necessarily a useful database for exercises of this kind.

These inconsistent results may arise as the impact of the banking industrial strucutre of Europe as mentioned by Lensink and Sterken (2002). Both suggest to view credit market within industrial organisation of banking sector, considering structural factor in the economy, business cycle and institutional factors among nations. However, using individual firm data, Nilsen (1999) concludes the bank lending channel become less important to transfer the effect of monetary policy because small firms still can increase their demand on loan by shifting from investment loan to trade credit.

The importance of banking in the economy especially to the behavior of output that driven by aggregate bank credit will be necessary condition for prompt economic recovery. During the crisis, banks were forced to cut lending, and this resulting “credit crunch” . This is, then believed as the propagation and deepening the crisis. So then restoring the flow of credit should be a priority for policy-makers in the immediate aftermath of banking crises. Bernanke (1983) argued that the contraction in credit inhibited by the banking crisis was instrumental in the propagation of the Great Depression in the U.S. Recent attempt to test for a credit crunch effect in Indonesia was done by Hariadi (2002) and found the evidences of credit crunch during the crisis.

The study on the monetary policy strategy in Indonesia during the banking crisis has been investigated extensively especially by Fane (2000). The strategy was mainly controlling the growth of M0. In sum, achieving a modest target for domestic inflation would not have been very different in practice from setting tight limits on the growth of M0.

Bernanke and Gertler concluded that the effects of an adverse macroecoomic shock may be amplified if it restricts the flow of credit (see, e.g., Bernanke, Gertler, and Gilchrist, 1996). A decline in credit creation capacity could occur because a negative shock worsens firms’ balance sheets and thus their access to credit or because it restricts the ability of banks to supply loans. In a world of asymmetric information, firms with healthier balance sheets can obtain credit on better terms. The firm’s ability to post collateral and provide down payments will reduce the agency costs associated with borrowing. If a negative shock worsens firms’ financial positions, it might impair their access to credit because the assumption that agency risk increases.

Similarly, an adverse shock might reduce bank capital and thus banks’ ability to provide loans. When either firms’ balance sheets deteriorate or banks’ loan supply declines, the reduction in credit forces firms to reduce spending and output.

That is why Bernanke and Gertler believed that the effects of an adverse macroecoomic shock might be amplified if it restricts the flow of credit (see, e.g., Bernanke, Gertler, and Gilchrist, 1996). A decline in credit creation could occur because a negative shock worsens firms’ balance sheets and thus their access to credit or because it restricts the ability of banks to supply loans. In a world of asymmetric information, firms with healthier balance sheets can obtain credit on better terms. Their ability to post collateral and provide down payments reduces the agency costs associated with borrowing.

When a negative shock worsens firms’ financial positions, it might impair their access to credit market. Similarly, an adverse shock might reduce bank capital and thus banks’ ability to provide loans. When either firms’ balance sheets deteriorate or banks’ loan supply declines, the reduction in credit forces firms to reduce spending and output.

Krugman (2001) emphasized the role of deteriorating balance sheets in propagating the Asian crisis. Firms were saddled with short-term foreign currency denominated debt. This debt was largely unhedged against exchange rate risk. Depreciating exchange rates thus multiplied businesses’ liabilities and reduced their retained earnings (equity). Krugman (2001) also stated that, in the case of Indonesia, bank runs and a freezing up of the credit system played an important role. Declines in bank capital and disintermediation reduced the willingness of banks to supply loans. Business borrowers facing a once in a generation crisis lost their credit lifelines and were forced to curtail spending and production.

Djiwandono (2000), the head of the Indonesian Central Bank (BI) in 1997, describes how banking sector problems developed in Indonesia. When spillovers from Thailand’s currency crisis reached Indonesia, BI sought to preserve foreign currency reserves first by widening the exchange rate bands and then by floating the exchange rate. As pressure on the exchange rate continued, BI raised the interest rate on its certificates (Sertifikat Bank Indonesia or SBI’s). The Minister of Finance at the same time directed state enterprises to transfer 3.5 trillion rupiah of bank deposits into SBI certificates. These moves damaged the banking sector. Banks were further harmed in October when IMF demands for the closure of 16 banks led to a bank run. Using the framework of bank lending, Mongid (2004) concluded that the bank lending chanell is valid during the periods of 1992-2002 but become less effective after that.

C. Methodology

C.1 The Framework of The Study.

The point of departure of the study is based on assumption adopted from Luísa Farinha and Carlos Robalo Marques , The Bank Lending Channel Of Monetary Policy: Identification And Estimation Using Portuguese Micro Bank Data, ECB Working Paper 102, December 2001 which states that the monetary policy works by affecting bank assets (loans) and banks’ liabilities (deposits). The key point is that monetary policy besides shifting the supply of deposits also shifting the supply of bank loans. In this context, the crucial response of banks to monetary policy is their lending response and not their role as deposit creators. The two key necessary conditions that must be satisfied for a lending channel to operate are: (a) banks cannot shield their loan portfolios from changes in monetary policy; and (b) borrowers cannot fully insulate their real spending from changes in the availability of bank credit.

The first condition assumes that banks are not able to completely offset the decrease in deposits brought about by monetary policy shocks, by resorting to alternative sources of funds (at least not without incurring in increasing costs). Because of the extra premium that banks have to pay to bring in alternative external funds, banks will make fewer loans after the fall in reserves brought about by monetary policy. Of course, it is expected that banks hedge against changes in monetary policy, by holding securities as a buffer against a reserve outflow. But such buffer is not expected to fully offset the effects of a monetary policy contraction, as buffer stocks are costly for banks (in terms of interest foregone).

The second condition assumes that some spending, which is financed with bank loans, will not occur if banks cut the loans, else the real consequences of the credit channel will be null. In summary, while the traditional theory emphasizes the households’ preferences between money and other liquid assets (bonds) the credit view argues that the banking behavior is also very important to the transmission of monetary policy.

According to Warjio and Agung (2002) there are two necessary conditions for the validity of the bank lending channel; bank loans and securities must be imperfect substitutes for some borrowers, or some borrowers are bank dependent, second the central bank must be able to constrain the supply of bank loans using all available instruments. It seems these conditions are valid in Indonesia Case especially if we refer to Agung (1998).

C.2 Data

The analysis in this study is based on monthly data extracted from the Monthly Statistical Bulletin published by Bank Indonesia and from Asia Recovery Information Center (ARIC) database, Asia Development Bank. The time period under consideration starts with February 1993 and ends with February 2004. This study is based on aggregate data, as detailed data at the individual bank level are not available. This approach is common for a large number of studies on the European countries that face similar data problem. Among others, empirical studies that are dependent on aggregate data such as de Bondt (1999) and Kakes (2000). We will treat all data to fullfil stationarity using Augmented Dickey-Fuller test. When the data is stasionair at the level, no further treatments were conducted. If not the data is then differentiated.

C.3. Variables

Variables employed in this study are discount rate (SBI), Braod Money ( M2), Total banking liability (TLIABI), Foreign Currency Denominated Liability (FLB) Forreign curency denominated assets (FAB), Foreign Gap of banking sector and total liability of banking. The dependent variable is credit growth (CREGR).

Figure 1. Framework of Analysis

Monetary Policy Variables:

Money Supply (M1)

SBI

Control Variable

Total Liability

Foreign Assets

Forex GAP

C.4 Model of Analysis

To estimate the impact of monetary policy and banking system variables to the bank lending, the model of analysis used in this study is linear regression using the credit growth as dependent variable. The model is formulated below:

Cregr = 1 M1 + 2 SBI + 3 FAB + 4 FLB+ 5 Forex Gap + 6 Crisis + ε

Definition:

M1 = Total Narrow Money, Total Central Bank Liability

SBI = SBI Rate of Central Bank

FAB = Total Foreign Asset of banking system

Forex Gap = Total Foreign Liability divided by total foreign denominated Assets.

TLIABI = Total liability of banking system

Cregr = Credit growth = Credit (n) – Credit (n-1) / Credit (n-1) X 100%

Estimation is carried out using Eview Statistical Packard Programme. In the hipotheses testing, we teste on the work of monetary aggregate such as discount rate (SBI) , narrow Money (M1) to influence bank credit growth. We are also to test on the validity of foreign currency gap as determinant of credit growth. The most inportant test is to examine the total libaility in influencing the credit growth.

D. Results

D.1 Decriptive

From table1, we can see some interested points. The mean of foreign exhange gap is more than 1. It means in average total libaility denominated in foreign exchange are higher than foreign asset. The mean value is 1.15 and the standard deviation is 0.49. This figure indicate that Indonesian Banks are vulnerable against the exchange rate movement. However the minimum is only 36% but the maximum gap is almost double of it libaility. Using Jarque-Bera test, the foreign exchnage gap is not normaly distributed.

Table 1 Descriptive Statisitcs

Category	FOREX GAP	NARROWMONEY	SBI INTEREST	TOTAL LIABILITY	FOREIGN ASSET	CREDIT GROWTH
Mean	1.150141	104495.3	17.14692	647744.6	62647.76	0.150436
Median	0.934400	101197.0	13.67000	736776.0	76387.00	1.099400
Maximum	1.969300	224318.0	70.81000	1167894.	187525.0	13.34930
Minimum	0.364300	29051.00	7.450000	185168.0	10681.00	-28.38930
Std. Dev.	0.492703	57565.30	12.57794	337937.7	45057.63	6.235707
Skewness	0.136182	0.384660	2.856364	-0.042070	0.267614	-0.017269
Kurtosis	1.471452	1.832730	10.84526	1.358364	2.014246	11.73639
Jarque-Bera	13.35896	10.83047	521.9329	14.97386	6.972411	422.9721
Probability	0.001256	0.004448	0.000000	0.000560	0.030617	0.000000
Observations	133	133	133	133	133	133

Narrow money is also indicating that the mean and the median is very closed. The mean is IDR 104 trillions and its standard deviation is IDR 57 Trillions. The narrow money grow very fast after the crisis as result of increasing cash holding by society to balance the price increase. The data on narrow money is not normally distributted. SBI, discount rate that mostly used by central bank of Indonesia to influence money in circulation, has mean value 17%. The highest is 70.8% and it was during crisis in 1998 as effort to reduce speculation on US dollar. The stadard deviation is 12.6%. Using Jarque-Bera statitistic , the data is not normally distributed.

The total liability in the banking sector increase from time to time. The mean is IDR 647 trillions and the median is IDR 74 trilion. At the beginning of the observation, the value IDR 185 trillions. The standard deviation is IDR 338 trillions. Using Jarque-Bera statitistic , the data is not normally distributed. The credit rowth, as dependent variable, has mean value 0.15% and the standar deviation is 6.2%. However, the data is not normally distributed.

Credit growth variable has very interesting feature. The mean is 0.15% and median is 1%. The maximum growth rate of credit is 13.3% and lowest growth is negative 28%. The range is 42%. The variability coefficient is very high, 2%. It means the variability is almost 50 time of its means. Similar to other variable, the credit growth is not normally distributed.

D.2 Hypotheses Testing

The first step of the process is to determine the existence of serial corelation. This test is an alternative to the Q-statistics for testing serial correlation. The test belongs to the class of large sample tests known as Lagrange multiplier (LM) tests. As the data for the study is time series data span from 1992 to 2004, the threat of serial correlation is viable. To test the existence of serial correlation we use Breusch-Godfrey Serial Correlation Langgrane Multiplier test. The result is 3.6 for F-statititics and decisively we reject the existence of serial correlation. Unlike the Durbin-Watson statistic for AR(1) errors, the LM test is used to test for because there is not lagged dependent variables. The null hypothesis of the LM test is that there is no serial correlation up to lag order , where is a pre-specified integer. The local alternative is ARMA() errors, where the number of lag terms   = max(). Note that this alternative includes both AR() and MA() error processes, so that the test may have power against a variety of alternative autocorrelation structures. See Godfrey (1988), for further discussion. See table 2

.

Table 2 Correlation Test Using Breusch-Godfrey Serial Correlation LM Test

Breusch-Godfrey Serial Correlation LM Test
F-statistic	3.606351	Probability	0.008138
Obs*R-squared	13.96087	Probability	0.007421

Tabel 3 presents the result generated by Eviews Stattical Package progra. From the table we could see that the ability of the model to explain the variability of credit growth is 27%. It means the model only capable to explain 27% of credit growth in Indonesia during the period of observation. The figure is relatively very low and other varibel are more attributable to credit growth. However, base on Anova (F-test) we found that this model in general can explain the varibility of credit growth. F-ratio is 9.52 and the probability is 1%.

Before data processing, we conduct unit root tests using the Dickey-Fuller (DF) and augmented Dickey-Fuller (ADF) tests. This tests is in Eviews. The Augmented Dickey-Fuller (ADF) Test is the t-statistic for the lagged dependent variable. The null hypothesis of a unit root is rejected against the one-sided alternative if the t-statistic is less than (lies to the left of) the critical value. We found that at level data, the data is not stationary. Then further action was done using first different and we found it was stationary. In the modeling we use first difference.

Tabel 3 Estimation Results Using Eviews

Dependent Variable: CREGR
Method: Least Squares
Date: 08/21/04 Time: 11:48
Sample: 1993:02 2004:02
Included observations: 133
Variable	Coefficient	Std. Error	t-Statistic	Prob.
C	-4.323045	6.167701	-0.700917	0.4846
FOREXGAP	2.713010	3.160710	0.858355	0.3923
NARMONEY	-0.000212	5.88E-05	-3.600769	0.0005
SBI	-0.166116	0.065525	-2.535139	0.0125
TLIABI	5.19E-05	1.10E-05	4.706076	0.0000
FAB	-0.000117	4.30E-05	-2.709540	0.0077
R-squared	0.272610	Mean dependent var		0.150436
Adjusted R-squared	0.243972	S.D. dependent var		6.235707
S.E. of regression	5.421939	Akaike info criterion		6.262847
Sum squared resid	3733.472	Schwarz criterion		6.393239
Log likelihood	-410.4794	F-statistic		9.519350
Durbin-Watson stat	2.354683	Prob(F-statistic)		0.000000

From the table 3 we can explain when foreign gap of increase by 1%, credit growth will increase by 0.2% at positive direction. For varible narrow Money, any increase by 1% will decrease very low ( less than 1 per mile). Discount rate, measured by Bank Indonesia Certificate for one month duration has negative impact as exopected. Any increase in discount rate will decrease the credit growth by 0.16%. As credit is mainly financed by banking liability, any increase in total banking liability will increase credit growth by 0.05%. The increase is very low but in accordance to the theorethical expecatation. Foreign asset of banking has negative sign indicating if the gap increase, credit groth will decrease atlthouh the ealsticity is very low ( less than 1 per mile). In general only narrow money has different result from expecatation.

Foreign Exchange gap is not significant. The t-Statitistic is only 0.85. The null hypotheses that the foreign gap is not statitically significant is accepted. It means for further analysis we should not consider the foreign gap. Regulation concerning the net open position impossed to reduce exchange rate exposure is attributatble to the situation. Limitation that the gap is not allowed to exceed 20% of capital are important feature of the regulation on net open position.

Narrow money as a measure to investigate the ability of monetary policy variable to influesce credit growth end to very confusing result. Narrow money is consisting of central bank liability such as money in circulation and state department account. The coefficient is negative although we expect it is positive. The null hipothese stating that the variable is not significant is rejected. It means the narrow money is mportant to impluece the credit growth. However, as the result is negative future reaseach should be focus on this agregate variable.

Discount rate or SBI has produced result as expected. The coefficeint is negative and statitically significant. It means any increase in discount rate poolicy will hamper the bank credit growth. This result is consitent with previous study that discount rat policy is still very important to manage economic variable. The result also provide another firmed evidence that monetary policy using interest rate is still effective. The finding consistent with Mongid (2004) that found the palussible result on bank credit as monetary policy channel. It suggest that Bank Indonesia use this instrument in carefull way to reduce the fatiquness.

Total liability of the banking, as the source of fund for making credit produce significant result. Total liability of banking system mostly consist of time deposit, saving account and currents account. The interesting feature of this variable is that the number increase from time to time. From perspective of intermediation theory, the result is correct as the sign is positive. It means any increase of bank funds will be transformed into credit. However, the coefficient the coefficient is very low indicating the low sensitivity of the variable. It may provide evidence that banking industry in Indonesia need an structural overhaul to make it more sensible to the deposit change.

Foreign asset bank (FAB), as the variable to capture the size of fund in foreign denominated liability provide signifiicant result. The sign is negative indicating that the increase in foreign currency deposit decrease the number of new credit disbursement. The result is very consistent with prudential measure called Net Open Position (NOP) that prohibited bank to to have foreign exchange exposure more than 20% of its capital. It is also indicating that banks may face dificulty to instantly produce loan in other currency. Theorethically, net open position is not a barrier for the banking firm to produce loan. If matching principle is applicable, meaning the foreign denominated depsoits used to finance foreign denominated loan, Net Ope Position Regulation is netral again loan growth. However , in real life the ability of bank to find borrowers that wiling to borrow in foreign currency is not easy.

Interesting finding of this study is that base money is contracting variable. It mean the ability of central bank to create money may reduce the credit. It is very interesting result because it should have positive impact to credit due to fund availability. The finding should be treated carefully as most of money circulated are in M1 statitistics. Interpretation of the result will end to the conclusion that when money in circulation increase, the credit demand will decrease. However this conclusion is very artificial as the demand drift on currency increase when the festival time happen such as during christmast and Id day.

Figure 2. Residuals plot of the model

Looking a residulas, we can see that the model preformed well in explaining the credit growth during 1993 to 1997 and then 2001 to 2004. During periods associated as crisis time we can see that the credit growth is very volatile indicating that during the crisis, credit growth mostly negative.

However as the result is based on supply side, we can not use the conclusion in very rough that to increase the credit growth, Bank Indonesia should increase the SBI / discount rate at very low level. Or then askeing the banking industry to reduce deposits in foreign currency. The suggestion to collect more public funds is a feasible way to increase the banking intermediation role. As we know that corelation or R-squared is very low, it is very realisitc to look other variable in demand side. It means that we look more on real sector in the economy to increase the credit growth.

E. Conclusion

This study examines whether monetary policy variable and banking sector variable play an important role in the credit growth. The finding suggest that from supply side, the monetary policy using narrow money and discount rate (SBI) are significant to explain the credit growth. It means monetary policy transmission mechanism in Indonesia appear plausible. The finding provides the monetary authority an additional leverage in conducting monetary policy. Restrictive monetary policy stance is found to cause the commercial banks credit growth decrease significantly. From the banking variable perspective, total banking liability is significant and positive mean that the bank function as intermediary are working. Foreign bank asset tend to reduce the credit growth as the result of regulation on net open position limitation.

However as this study are based on supply side, the determinant of banking credit gworh is not answered totally. Low R-squared provide indication that the model is very weak to explain the credit growth. That is necessary for future research to be directed to look at demand side of credit growth.

This study contain a substantial weakness because we do not incorporate bank capital effects. It is generally agreed that bank capital is an important factor in bank asset and liability management and that its importance has likely increased since the implementation of the risk-based capital requirements of the 1988 Basle Accord publicly known as Capita Adequacy Ratio (CAR). The implementation of these regulations has often been blamed for credit crunch. In addition, there is some more general evidence that the cost of loans depends on bank capital. It means higher bank capital lowers the rate charged on loans, even after controlling for borrower characteristics, other bank characteristics and loan contract terms. So bank capital is a significant determinant of loan supply, then it should be incorporated in the model.

When we take into account capital adequacy regulations, the study will allows to address the question what role bank lending plays in the monetary transmission and monetary policy affects the real economy at least in part through a direct effect on the supply of bank loans. A necessary condition for this channel to be operative is that banks change their loan supply in reaction to shocks to their reserves. An important point was presented by Heuvel (2003) that in the presence of capital requirements bank lending plays a special role in the transmission of monetary policy even if banks face a perfect market for some nonreservable liability. The model demonstrates that capital requirements generate a mechanism by which monetary policy shifts the supply of bank loans through its effect on bank capital, rather than reserves.

REFERENCE

Aghion, Ph, Ph. Bacchetta And A. Banerjee (2000), Currrency Crises And Monetary Policy In An Economy With Credit Constraints, CEPR Working Paper, 2000

Agung, J and Rita Morena, (2002), Bank Lending Channel of Monetary Transmission in Indonesia Monetary Transmission in Indonesia, in Perry Warjiyo and Juda Agung, Transmission Mechanisms Of Monetary Policy In Indonesia, Directorate of Economic Research and Monetary Policy, Bank Indonesia

Agung,J.,Bambang Kusmiarso, Bambang Pramono, Erwin G Hutapea, Andry Pasmuko,Nugroho, J Prastowo (2001).Credit Crunch in Indonesia in the Aftermath of the Crisis: Facts, Causes and Policy Implications. Bank Indonesia, Directorate of Economic Research and Monetary Policy.

Agung, Juda (1998) Financial deregulation and bank lending channel of monetary policy in developing countries: The case of Indonesia, Asian Economic Journal ,Vol.12,No.3,273-294.

Azis, Iwan J. “Modeling Crisis Evolution and Counterfactual Policy Simulations: Indonesia 1997-1999.” Asian Development Bank Institute Working Paper 23, 2000.

Altunbas, Y, O. Fazilov and P. Molyneux, (2002), Evidence on Bank Lending Channel In Erope , Jounal of Banking and Fianance, 26, p. 2093-2110

Bernanke, B and Gertler, M., (1995), Inside the black box: credit channel of monetary transmission mechanism, Journal of Economic Perspective , Fall 1995, pp.27-48.

Bernanke, Benjamin S., (1983), “Non-monetary effects of the financial crisis in the propagation of the great depression”, American Economic Review, 73, pp. 257-76.

Bernanke,B. and Blinder,A.S., (1988), Credit, Money and Aggregate Demand, The American Economic Review ,June 1988, pp.257-76.

Cecchetti, S.G., (1995), Distinguishing theories of the monetary transmission mechanism, Fed Res Bank of St Louis Economic Review ,May/June 1995, pp.83-100.

De Bondt , G.J, (2000) financial structure and monetary transmission in Europe: cross country study, Edward Elgar, Cheltelham

Ehrann, M, (2000), firm size and monetary policy transmission, evidence from German business survey data, ECB Working Paper no.21, ECB, Frankfurt

Favero, C.A, Giavassi, F and Flabbi, L, (1999), The transmision mechanism of monetary policy in eurpor: evidence from balancesheet, NBER Working paper.

Fane, George,(2000), Indonesian Monetary Policy During The 1997–98 Crisis: A Monetarist Perspective, BIES, 3 Vol 36 No 3, December

Godfrey, L. G. (1988). Specification Tests in Econometrics, Cambridge University Press.

Hariadi, S, (2002), Peran Saluran Kredit Terhadap Krisis Keuangan di Indonesia, paper presented in Indonesian Economist Symposisum I, 19^th June.

Heuvel Skander J. Van den, (20030, The Bank Capital Channel of Monetary Policy, draft paper, Department of Finance The Wharton School University of Pennsylvania This version: November 2003

Bernanke, Ben, Mark Gertler, and Simon Gilchrist. “The Financial Accelerator and the Flight to Quality.” Review of Economics and Statistics 78 (February 1996), 1-15.

Djiwandono, J. Soedradjad. “Bank Indonesia and the Recent Crisis.” Working paper, University of Indonesia, 2000.

Enoch, Charles, Barbara Baldwin, Olivier Frécaut, and Auto Kovanen, Indonesia: Anatomy of a Banking Crisis, Two Years of Living Dangerously, 1997-99.” IMF Working Paper 01/52, 2001.

Krugman, Paul. “Analytical Afterthoughts on the Asian Crisis.” Working Paper, Princeton University, 1999.

Krugman, Paul. “Balance Sheets, the Transfer Problem, and Financial Crises.” In International Finance and Financial Crises, Essays in Honor of Robert P. lood, Jr. , edited by Isard, P., Razin, A. and Rose, A. Dordrecht, Kluwer, 2001.

Nasution, Anwar. “Economic Recovery from the Crisis in 1997-98.” In Economi Indonesia di Era Politik Baru Ikhsan, edited by Mohammed Ikhsan, Chris Manning, and Hadi Soesastro, Jakarta, Kompas, 2002.

Kim, Hyun E, (1999), Was the credit channel a key monetary transmission following the recent financial crisis in the republic of Korea, Policy Research Working Paper No. 2103, World Bank.

Luísa Farinha And Carlos Robalo Marques , (2001), The bank lending channel of monetary policy: identification and estimation using portuguese micro bank data, ECB Working Paper 102, December

Kakes, J and Strum, JE (2002), Monetary policy and bank lending: evidence from german banking Group, Journal of Banking and Finance, vol. 26, No. 11

Kashsap, Anil K. and J.C Stein and David W. Wilcox, (1993), The monetary policy and credit condition: Evidence from the composition of External Finance, American Economic Review, Vol. 83, No.1 Page 78-98

Kasyap, AK, Stein J.C. ,(1997), The role of banks in monetary policy: survey of implication for the european economic union, Economic Perspective, Fed. Reserved Bank of Chicago 21, 2-19

Kim-Leng Goh, Chin-Sieng Chong and Sook-Lu Yong, (2004), Bank Lending Channel In Monetary Policy Transmission: The Case Of Malaysia, Research Paper, Faculty of Economics & Administration, University of Malaya 50603 Kuala Lumpur MALAYSIA

Lensink, R and Sterken, E,(2002), Monetary transmission and bank competition in the EMU, Journal Banking and fianance 26 p. 2065-2075

Mongid, Abdul , (2003), Bank lending chanell during Indonesian Banking Crisis, Occasional paper for round table discussion,, Bank Indonesia.

Peek, J and Rosengren, Eric (1995), The capital crunch : neither a borrower nor lender be, Journal of credit Money and Banking, 27, p.149-21

3

21