22Buletin Ekonomi Moneter dan Perbankan, Volume 19, Nomor 1, Juli 2016

I. INTRODUCTION

Our preliminary investigation indicates that the response of deposit interest rate and lending rate towards monetary policy in Indonesia has been asymmetric. The response of deposit rate has been relatively proportional and timely, whereas the response of lending rate has been lagging and relatively rigid. This could be an indication of uncompetitive market (Cottarelli dan Kourelis, 1994; Borio and Fritz, 1995). Moreover, responses towards monetary policy among group of banks with different assets are heterogenous. Therefore, it indicates that some behavior related to individual market power and interaction among banks affect the industry response.

Those problems, which related to competition behavior in banking industry, are likely to affect the monetary policy transmission, particularly through interest rate channel and lending channel. Further, competition is also a relevant factor to increase efficiency (Hafidz dan Astuti, 2013) and to determine interest rates (Muljawan et. al. 2014).

Previous literatures conduct empirical estimates on this issue by applying widely-used competition indicators such as Lerner Index (Amidu and Wolfe, 2013), Hirchman-Herfindahl Index (Adams and Amel, 2011), Panzar and Rosse H-Statistic (Gunji et. al, 2007; Oliviero et. al., 2011) and Boone Indicator (van Leuvensteijn, 2013). This method, particularly by using Lerner, Boone Indicator or H-Statistic can indicate “conduct and performance” effect, whereas HHI only capture market structure effect. However, those approaches are generally explains competition on the whole industry, and does not capture asymmetrical interactions among individual banks.

Ariefianto (2009) suggest estimating specification that derived from Monti-Klein model that allows possible indication of leader-follower or Cournot interactions. This model is originally based on Cournot interactions (see Klein, 1971; Frexias and Rochet, 2008). In addition, Toolsema- Veldman and Schoonbeek (1999) had derived a Stackleberg version of this model. However, Ariefianto (2009) estimates are based on arbitrary choice of samples.

This research will examine competition in banking industry using industrial organization approach, also by improving methods to determine sample selection. Further, this research will model interest rate setting on a bank towards monetary policy using game theory and analyze the implications on monetary policy transmissions. Particularly, this research tries to answer three questions; first, how is the competition behavior on Indonesian banking industry? Second, if the leader(s) exist, how the followers will respond to leader’s decisions? Third, how does the bank competition indirectly affect monetary policy transmissions?

This research is aim to contribute a more interactive indication about competition behavior on banking industry. In addition, this research potentially indicates a recommendation to increase the effectiveness of monetary policy transmission. We limit the analysis on the case of Indonesia.

Competition and Leader-Follower Interactions: Panel Estimates on Indonesian Banking

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II. THEORY

Bank competition is essential to be discussed. Competition between banks tends to raise efficiency (Hafidz and Astuti, 2013). Empirically, the degree of competition is one of determining factors of interest rate (Muljawan et. al. 2014). Moreover, a more concentrated banking industry has more rigid interest rate movement (Hannan and Berger, 1991; Neumark and Sharpe, 1992). However, Adams and Amel, (2011) said that the relationship between banking competition and monetary policy response are ambiguous.

Previous empirical studies conduct estimates on this issue by applying a widely-used competition indicators such as Lerner Index (Amidu and Wolfe, 2013), Hirchman-Herfindahl Index (Adams and Amel, 2011) and Panzar and Rosse H-Statistic (Gunji et. al, 2007; Oliviero et. al., 2011). This method, particularly by using Lerner or H-Statistic can indicate “conduct and performance” effect, whereas HHI only capture market structure effect. However, those approaches generally provide insights on the industry as a whole, and cannot capture asymmetrical interactions among individual banks.

Ariefianto (2009) suggest estimating specification that derived from Monti-Klein model that allows possible indication of leader-follower relationship or Cournot interactions. This model is originally based on Cournot interactions (see Klein, 1971; Frexias and Rochet, 2008). In addition, Toolsema-Veldman and Schoonbeek (1999) had derived a Stackleberg version of this model.

We recall a form of Monti-Klein model, by noting the following assumptions:

1.Two bank products, deposit and credit, are homogenous. Bank 1 and bank 2 have linier function of deposit and credit demand:

rL = α - βL ; L= L1 + L2	(1)
rD = a + bD ; D = D1 + D2	(2)

2.Banks using deposit and credit quantities as strategic instrument

3.Linier cost function:

C1	(L1, D1) = γL,1L1	+ γD,1D1	(3)
C2	(L2, D2) = γL,2L2	+ γD,2D2	(4)

4.Interbank money market rate (r) is exogenous variable as it affected by monetary policy of Bank Indonesia.

24Buletin Ekonomi Moneter dan Perbankan, Volume 19, Nomor 1, Juli 2016

5. Profit function of bank:

�i = rLLi - rDDi - r(Li - Di) - Ci(Li, Di)

(5)

Combining equations (1) to (5) above, obtained maximization utility function of bank:

(6)

First partial differentiation of (6) to lending and credit variable derives equation (7) and

(8) as follows:

Li =	α - r - γL,i	-		1			LP -	1	L-i		(7)
	2β			2				2
Di =	r - a + γD,i		-		1		DP -		1	D-i	(8)
									2
	2b			2

Equation (7) and (8) show that the quantity of credit (deposit) of a bank is affected inversely by that the quantity of credit (deposit) of the leader and those of other competitor.

III. METHODOLOGY

3.1. Empirical Specification

For the first analysis, we use a general specification that allows leader-follower (i.e. Stackleberg) relationship, the possibility of Cournot competition and other form of Competition, as in Ariefianto (2009).

From (7) and (8), we have basic understanding that one bank’s lending (deposit) depends on its leader and other bank’s lending (deposit). Combining (7) and (8) with macroeconomics and

banking variables, where , the general specification can be represent as follows:

Xit = α + β1Xpt + β2X-i,t + ΣkγkYkt + ΣmμmZmit + uit

(9)

Xit is the amount of loan (deposit) of a particular bank i at t, Xpt is the amount of loan (deposit) supplied by the leader, X-i,t is the amount of loan (deposit) supplied by the rest of followers, Ykt is the kth panel-invariant factor, zmit is the mth panel-variant factor, and uit is the stochastic error. α is a constant.

Competition and Leader-Follower Interactions: Panel Estimates on Indonesian Banking

25

The possible key hypotheses on Equation (9) are as follows: 1. If β1 < 0 and β2 < 0, it indicates that the leader and other competitor are significant to affect bank’s quantity of credit/ deposit; 2. If β1 < 0 and β2 = 0, then the market is indicated to be consistent to leaderfollower relationship (i.e. Stackleberg competition). 3. If β2 < 0, β1 = 0, then the market is indicated to be consistent with Cournot model, or it can be inferred that there is no leader exist. 4. If β1 > 0 and/or β2 > 0 , it may indicate other form of competition that is not usually predicted.

Control variables, the “panel variant” or “panel invariant” factors consists of macroeconomic variables (GDP, inflation, exchange rates, and benchmark interest rates), specific internal bank variables (non-performing loans, capital adequacy ratio, etc), and industry variables (HHI). This list of control variables are partly based on Claessens and Laeven (2004) and Angellini dan Certorelli (2003). Further details of these variables are reported on the appendix.

We use two approaches to estimate Equation (9), namely: 1. the standard panel fixed effect methodology to absorb time-invariant unobserved heterogeneity (by replacing a with αi ); 2. dynamic panel data as in Arellano-Bond (1991) to minimize the risks of endogeneity (by replacing α with Xit-1).

3.2. Grouping of Observations

Observations consist of monthly data of 119 banks listed in Indonesia. The main data source are Bank Indonesia and CEIC. Observations are grouped based on an identification of whether banks compete on a relevant market, where the products across banks have a high degree of interchangeability. This step is crucial as competition is the central issue in this paper. To facilitate this matter, on estimations on credit market we use degree of similarity on credit across economic sectors between each bank and the leader candidate, using the following formula:

	K
Xi =	Σ			xik	-	xIk			(10)
				Σk xik		Σk xIk
	k

xik is bank i’s lending on sector k, and xIk is bank leader’s lending on the corresponding sector. This formula was modified and inversed from trade complementary index (Michaely, 1996), which is used generally in international trade analysis. The leader candidates are Bank A, Bank B, Bank C, Bank D, and Bank E.

Similarly, for estimations on deposits, we use degree of similarity on deposit spatially (i.e. individual bank’s deposit distribution across provinces) between each bank and its leader candidate, using following representation:

	Competition and Leader-Follower Interactions: Panel Estimates on Indonesian Banking								27
				Table 2.
			Dynamic Panel Estimation for Credit
		Group A	Group B	Group C		Group D	Group E	Full Sample
VARIABLES
Leader Credit		-0.0638**	-0.0585***	-0.0447**		-0.134**	-0.0247**		-0.208*
		(0.0263)	(0.0184)	(0.0197)		(0.0680)	(0.0108)		(0.121)
Follower Credit		-0.0084	-0.122**	-0.167***		-0.0834	-0.0422		0.163
		(0.0414)	(0.0521)	(0.0419)		(0.0942)	(0.0541)		(0.138)
CONTROL
VARIABLES
1. Macroeconomics			GDP, inflation rate, inter-bank rate, exchange rate
2. Structural			HHI, credit diversification , credit to PDB ratio
3. Internal bank			NPL, CAR, BOPO
Constant		0.983***	0.997***	0.992***		0.983***	0.970***	0.965***
		(0.00495)	(0.00595)	(0.0102)		(0.00611)	(0.0105)	(0.00647)
Observations		913	945	945		832	840		3,521
Number of bank		27	27	27		26	24		105
Sargan test prob		0.331	0.278	0.212		0.267	0.514		0.898
Arellano-Bond
AR(2) prob		0.967	0.762	0.393		0.105	0.413		0.110
Dependent variable: Log(Credit)		(…) = Robust standard errors

Significance level: *** p<0.01, ** p<0.05, * p<0.1

Dynamic panel data for credit indicates a leader-follower relationship for all groups estimated, and also consistent for full-sample estimates, that contain all banks in the industry.

Bank C and Bank B groups follows Stackleberg and Cournot competition model simultaneously. The highest response to the leader’s decision is indicated on the group of banks with Bank D as the leader. GDP have positive impact with short term elasticity 0.14 – 0.30. Interbank money market rate and NPL variables are negative, tends to be inelastic. The lag dependent parameters are estimated below unity, thus indicate dynamic stability.

4.2. Deposit Market

The fixed effect panel data regression shows that a leader-follower relationship occurs in all groups of observations, except for the groups of observations with Bank C and Bank A as the leader, respectively. Cournot competition model applies for all groups, except for the group of banks with Bank A as the leader. The highest follower response to the leader’s decision occurs on the group of banks with Bank D as the leader. GDP have positive impact to quantity of deposit with elasticity that close to unity, especially in groups of banks with Bank C, Bank A, and Bank D the leader, respectively. Non-performing loan (NPL) has a negative impact to bank’s deposit amount.

Competition and Leader-Follower Interactions: Panel Estimates on Indonesian Banking

29

on follower’s deposit. GDP have positive impact to deposit variables. Herfindahl–Hirschman Index (HHI) has negative impact with small effect. Lag dependent coefficients below 1 indicates dynamic stability of the model.

V. CONCLUSIONS

The estimation results suggest a leader and follower relationship among banks on most of the grouped observations, although with some variations in magnitude. Generally, competition between followers is insignificant on credit market, but is significant on deposit market. Leader and follower competition result can be viewed on Table 3 below. Control variables, such as: GDP, inflation rate, interbank rate, exchange rate, HHI, credit diversification, credit to PDB ratio, and operational bank ratios are generally show consistent parameters as expected. All-sample estimates also suggesting similar results, and hence confirming the robustness of selected- sample regressions. For estimates using dynamic panel regressions, all estimations fulfill dynamic stability and well represent the data variations. Moreover, the estimations met the exogeneity assumptions for instrumental variables.

Table 5.

Group Summary

	Panel Data		Lending	Deposit
Fixed Effect		Competition	Stackleberg,	Stackleberg and Cournot,
			Except Group C	Except Group C and Group A
Arellano-Bond		Highest Response	Group B	Group D
		Competition	Stackleberg with Cournot	Stackleberg and Cournot
			for Group C and Group B
		Highest Response	Group D and Group B	Group D
Arellano-Bond		Competition	Stackleberg	Stackleberg and Cournot
				simultaneously

Although our results indicate that leader-follower relationship is generally hold on both credit and deposit market, either in separate groups or full sample, this paper still put restrictive assumptions on the leaders’ behavior. The interactive responses between leaders have yet to be analyzed without any prior restrictions. The suggestion for further research is to improve the empirical specification. For instance, to use credit/deposit similarities as a weight matrix that attached to the leader-follower coefficients to allow multiple leaders at once as well as to allow heterogeneous response towards each leader’s decisions.

30Buletin Ekonomi Moneter dan Perbankan, Volume 19, Nomor 1, Juli 2016

References

Adams, Robert M. and Dean F. Amel (2011). Market structure and the pass-through of the federal funds rate. Journal of Banking & Finance, 35: 1087–1096.

Amidu, Mohammed and Simon Wolfe (2013). The effect of banking market structure on the lending channel: Evidence from emerging markets. Review of Financial Economics, 22: 146–157

Angelini, Paolo dan Nicola Cetorelli (2003). The Effects of Regulatory Reform on

Competition in the Banking Industry, Journal of Money, Credit and Banking, Vol. 35,

No. 5: 663-684

Arellano, M., and S. Bond. (1991). Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations. Review of Economic Studies, 58: 277–97.

Ariefianto, M.D. (2009). Perilaku Persaingan Industri Perbankan Di Indonesia Pasca Krisis, Analisa Dengan Pendekatan Teori Oligopoli Dan Ekonometrika Panel Data 2002-2008, PhD Dissertation, University of Indonesia.

Borio, C. and Fritz, W. (1995). The response of short-term bank lending rates to policy rates: a cross-country perspective, BIS Working Paper No. 27. 5

Claessens, Stijn and Luc Laeven (2004). What Drives Bank Competition? Some International Evidence, Journal of Money, Credit and Banking, 36 (3): 563-583.

Cottarelli, C. and Kourelis, A. (1994). Financial structure, bank lending rates and the transmission of monetary policy, IMF Staff Paper, 42: 670–700.

Freixas X. and J.-C. Rochet (2008). The microeconomics of banking, Boston: The MIT Press, 2nd edition.

Gunji , Hiroshi, Kazuki Miura and Yuan Yuan (2009). Bank competition and monetary policy, Japan and the World Economy, 21: 105–115

Klein, Michael A. (1971). A Theory of the Banking Firm. Journal of Money, Credit and Banking, 3(2): 205-218.

Olivero, María Pía, Yuan Li, and Bang Nam Jeon (2011). Competition in banking and the lending channel: Evidence from bank-level data in Asia and Latin America, Journal of Banking & Finance 35, 560–571

Roodman, D. (2009). How to do xtabond2: An introduction to difference and system GMM in Stata. The Stata Journal, 9 (1): 86–136.

Competition and Leader-Follower Interactions: Panel Estimates on Indonesian Banking

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Toolsema-Veldman, L. & Schoonbeek, L. (1999). Bank behavior and the interbank rate in an oligopolistic market. Working paper, University of Groningen, SOM research school.

Van Leuvensteijn, Michiel (2013). Impact of bank competition on the interest rate passthrough in the Euro area, Applied Economics, 45: 1359–1380

32Buletin Ekonomi Moneter dan Perbankan, Volume 19, Nomor 1, Juli 2016

Appendix

Table 1.

List and Notes of Dataset

Variables	Source	Notes
Main Variables
Credit	Bank Indonesia	Total credit of individual bank data
Deposit	Bank Indonesia	Total deposit of individual bank data
Credit/deposit of the leader	Bank Indonesia	5 banks as candidate (Bank A, B, C, D, E)
Credit/deposit of the followers	Bank Indonesia, authors’	Industry data – data on a particular bank observed
	calculation.
Macroeconomics
GDP	CEIC	Nominal, interpolated to monthly using quadratic
		match sum
Inflasi	CEIC	Year-on-year terms
Interest rate	CEIC, Bank Indonesia	Interbank call money
Exchange rates	CEIC
Industry
HHI	Bank Indonesia, authors’	Using credit/deposit approach
	calculation.
Credit to GDP ratio	Authors’ calculation	As a proxy to indicate the industry
Internal Bank		significance on the economy
NPL	Bank Indonesia
CAR	Bank Indonesia	Share of credit with quality 3 to 5
BOPO	Bank Indonesia
Credit to asset ratio	Bank Indonesia,	Operational cost / revenues
	authors’ calculation	As a proxy to indicate business diversification

	Competition and Leader-Follower Interactions: Panel Estimates on Indonesian Banking						33
			Table 2.
		Fixed Effect Estimates on Credit Market
		Group A	Group B	Group C	Group D	Group E
VARIABLES
Kredit leader		-0.0189**	-0.0557**	-0.0107	-0.0175*	-0.0292*
		(0.00799)	(0.0232)	(0.0307)	(0.00923)	(0.0148)
Kredit follower		0.0961	0.0209	-0.110	0.215		0.375
		(0.204)	(0.168)	(0.253)	(0.285)	(0.345)
Variabel kontrol
1. Makroekonomi
PDB		1.041***	1.124***	1.185***	0.908***	0.933***
		(0.236)	(0.208)	(0.230)	(0.280)	(0.199)
Inflasi		-0.000251	-0.00365	-0.000910	0.000500	0.000488
		(0.00135)	(0.00298)	(0.00200)	(0.00164)	(0.00417)
Suku bunga PUAB		-0.00530	-0.00556	-0.0127*	-0.0116	-0.00582
		(0.00556)	(0.0113)	(0.00652)	(0.00935)	(0.0231)
Real Exchange Rate		-0.182*	-0.355***	-0.214***	-0.211	-0.250**
		(0.0836)	(0.0730)	(0.0575)	(0.131)	(0.105)
2. Struktural
HHI		-0.000474	0.000980	0.00102**	-8.79e-05	-0.00108
		(0.000411)	(0.000663)	(0.000437)	(0.000573)	(0.000646)
Diversifikasi		-0.199***	-0.238***	-0.125***	-0.148***	-0.0771
		(0.0459)	(0.0688)	(0.0324)	(0.0454)	(0.0813)
Rasio kredit/PDB		0.0694***	0.0685***	0.107***	0.0661***		0.144*
		(0.0180)	(0.0209)	(0.0190)	(0.0150)	(0.0695)
3. Internal bank
NPL		-0.0197**	-0.0288***	-0.00764	-0.0280***	-0.0248**
		(0.00648)	(0.00416)	(0.00826)	(0.00151)	(0.00956)
CAR		-9.92e-05***	0.000721	-0.00197	-0.00249	-0.00345
		(1.31e-05)	(0.00162)	(0.00362)	(0.00376)	(0.00669)
BOPO		1.91e-05	0.000229	0.000250**	0.000244	-0.000663
		(0.000271)	(0.000165)	(9.83e-05)	(0.000200)	(0.000514)
Constant		-4.483***	-3.435*	-4.104***	-3.940***		-5.745
		(1.107)	(1.795)	(1.236)	(1.196)	(4.673)
Observations		420	525	525	525		525
R-squared		0.902	0.862	0.914	0.900		0.720
Number of bank		12	15	15	15		15

34Buletin Ekonomi Moneter dan Perbankan, Volume 19, Nomor 1, Juli 2016

Table 3.

Dynamic Panel Estimates on Credit Market

	Group A	Group B	Group C	Group D	Group E	Full Sample
Variabel
Kredit leader	-0.0638**	-0.0585***	-0.0447**	-0.134**	-0.0247**	-0.609*
	(0.0263)	(0.0184)	(0.0197)	(0.0680)	(0.0108)	(0.314)
Kredit follower	0.00843	-0.122**	-0.167***	-0.0834	-0.0422	0.642*
	(0.0414)	(0.0521)	(0.0419)	(0.0942)	(0.0541)	(0.365)
Variabel kontrol
1. Makroekonomi
PDB	0.131**	0.205***	0.305***	0.189***	0.144**	0.0970
	(0.0545)	(0.0632)	(0.0545)	(0.0487)	(0.0731)	(0.0847)
Inflasi	0.00279*	0.000804	0.00250***	-0.000652	0.00178	-0.000783
	(0.00148)	(0.000889)	(0.000825)	(0.000915)	(0.00163)	(0.00165)
Suku bunga PUAB	-0.0157**	-0.0155***	-0.0236***	-0.0176***	-0.0178**	-0.0109*
	(0.00643)	(0.00449)	(0.00513)	(0.00474)	(0.00759)	(0.00640)
Exchange Rate	-0.111	-0.142***	-0.251***	-0.0198	-0.115	0.0374
	(0.0698)	(0.0492)	(0.0541)	(0.0486)	(0.0812)	(0.0473)
2. Struktural
HHI	-0.000484*	0.00055***	-5.84e-06	0.00075***	-0.000501	0.00104**
	(0.000280)	(0.000202)	(0.000188)	(0.000211)	(0.000321)	(0.000522)
Rasio kredit/PDB	0.00409*	0.000956	0.00460	0.00719***	0.00609	0.00516**
	(0.00241)	(0.00156)	(0.00402)	(0.00222)	(0.00457)	(0.00248)
Diversifikasi	-0.0131	0.00464	-8.21e-05	0.0120***	0.0174***	-0.00155
	(0.0111)	(0.00459)	(0.00584)	(0.00380)	(0.00496)	(0.00350)
3. Internal bank
BOPO	-0.000100	5.70e-05	-0.000195	-0.000186	5.03e-05	-2.89e-05
	(0.000197)	(0.000125)	(0.000152)	(0.000155)	(0.000154)	(0.000102)
NPL	-0.00170	-0.00558***	-0.0064***	-0.0070***	-0.00219	0.00305
	(0.00128)	(0.00157)	(0.00208)	(0.00139)	(0.00379)	(0.00643)
CAR	-0.0007***	0.00113**	0.000980	-6.58e-05	-0.000149	-0.00086***
	(0.000243)	(0.000526)	(0.000717)	(8.72e-05)	(0.000722)	(0.000310)
Lag dependen	0.983***	0.997***	0.992***	0.983***	0.970***	0.986***
	(0.00495)	(0.00595)	(0.0102)	(0.00611)	(0.0105)	(0.00939)
Observations	913	945	945	832	840	3,319
Number of bank	27	27	27	26	24	105

	Competition and Leader-Follower Interactions: Panel Estimates on Indonesian Banking						35
			Table 4.
		Fixed Effect Estimates on Deposit Market
		Group A	Group B	Group C	Group D	Group E
VARIABLES
DPK leader		-0.106	-0.122**	-0.0968	-0.359**	-0.166**
		(0.138)	(0.0421)	(0.103)	(0.127)	(0.0639)
DPK follower		-0.607	-0.887**	-0.831*	-1.893***	-0.974*
		(0.426)	(0.316)	(0.390)	(0.562)	(0.461)
Variabel kontrol
1. Makroekonomi
PDB		0.222	1.078***	1.575***	1.580**	2.199***
		(0.336)	(0.301)	(0.429)	(0.628)	(0.523)
Inflasi		-0.0365***	-0.00629**	-0.0103	-0.0170***	-0.0121*
		(0.0107)	(0.00277)	(0.00690)	(0.00314)	(0.00569)
Suku bunga PUAB		0.179**	0.0574***	0.0312	0.128***	-0.00557
		(0.0788)	(0.0140)	(0.0207)	(0.0154)	(0.0331)
Exchange Rate		0.0575	-0.489**	-0.749***	-0.491**	-0.855*
		(0.235)	(0.158)	(0.228)	(0.204)	(0.443)
2. Struktural
HHI		-0.00513**	-0.00624***	-0.00669***	-0.00620***	-0.0150***
		(0.00166)	(0.00118)	(0.00170)	(0.00127)	(0.00437)
Diversifikasi		0.124***	0.215***	0.0191	0.0762***	0.0228***
		(0.0307)	(0.0443)	(0.0610)	(0.0216)	(0.00370)
Rasio kredit/PDB		0.164***	0.121***	0.105***	0.165***		0.418
		(0.0395)	(0.0273)	(0.0331)	(0.0367)	(0.270)
3. Internal bank
NPL		-0.000784	0.00186	-0.0185	0.0156	0.00430
		(0.0246)	(0.0141)	(0.0172)	(0.0154)	(0.0314)
CAR		0.00509***	-0.0159***	-0.0187***	-0.000991	-0.0111**
		(0.000583)	(0.00454)	(0.00414)	(0.000869)	(0.00386)
BOPO		0.000440	4.76e-05	0.000648	0.000629	-4.96e-05
		(0.000889)	(0.000387)	(0.000605)	(0.000538)	(0.000194)
Constant		17.76**	14.50***	8.653***	23.26***		4.441
		(6.755)	(3.571)	(2.630)	(3.152)	(7.023)
Observations		391	408	408	380		403
R-squared		0.430	0.558	0.493	0.526		0.271
Number of bank		12	12	12	12		14

36Buletin Ekonomi Moneter dan Perbankan, Volume 19, Nomor 1, Juli 2016

Table 5.

Dynamic Panel Estimates on Deposit Market

	Group A	Group B	Group C	Group D	Group E	Full Sample
VARIABLES
DPK leader	-0.466***	-0.269***	-0.185***	-0.298***	-0.209***	-0.471***
	(0.0541)	(0.0419)	(0.0455)	(0.0711)	(0.0402)	(0.128)
DPK follower	-0.231***	-0.165*	-0.370***	-0.256***	-0.777***	-0.339***
	(0.0860)	(0.0851)	(0.116)	(0.0900)	(0.170)	(0.0582)
Variabel kontrol
1. Makroekonomi
PDB	0.857***	0.394***	0.643***	0.652***	0.903***	0.776***
	(0.0963)	(0.114)	(0.153)	(0.156)	(0.188)	(0.218)
Inflasi	0.00259	0.00409*	0.00252	0.00539**	-0.00336	-0.00392
	(0.00269)	(0.00240)	(0.00231)	(0.00262)	(0.00609)	(0.00315)
Suku bunga PUAB	0.0161**	0.0328***	0.0149*	-0.0178	0.0602**	0.0380**
	(0.00799)	(0.0110)	(0.00837)	(0.0109)	(0.0236)	(0.0190)
Exchange Rate	-0.0597	0.419***	-0.0256	-0.205*	0.351*	0.240
	(0.0856)	(0.123)	(0.0966)	(0.119)	(0.196)	(0.169)
2. Struktural
HHI	-0.00352***	-0.00266***	-0.00206***	-0.000923	-0.00369***	-0.000771
	(0.000461)	(0.000462)	(0.000495)	(0.000591)	(0.00118)	(0.00114)
Rasio kredit/PDB	0.00301	0.00318	0.00245	0.00505	0.0763**	0.00844
	(0.00209)	(0.00253)	(0.00234)	(0.00532)	(0.0344)	(0.00541)
Diversifikasi	-0.0137***	-0.00451	0.00949*	0.0133	-0.00125	-0.00322**
	(0.00519)	(0.00768)	(0.00516)	(0.0124)	(0.00194)	(0.00154)
3. Internal bank
BOPO	0.000596	0.000765**	0.000229	0.000398	0.000542*	0.00101*
	(0.000379)	(0.000366)	(0.000344)	(0.000506)	(0.000327)	(0.000590)
NPL	-0.00265	-0.00428***	-0.00225	-0.00583	-0.0161	0.0109
	(0.00261)	(0.00158)	(0.00150)	(0.00532)	(0.0129)	(0.00853)
CAR	0.000204	0.000230	-0.000343	-0.000152	-0.000823	0.00778***
	(0.000298)	(0.000292)	(0.000355)	(0.000396)	(0.00117)	(0.000680)
Lag dependen	0.989***	0.991***	0.992***	0.999***	0.937***	0.988***
	(0.00834)	(0.00797)	(0.00968)	(0.0122)	(0.0250)	(0.0171)
Observations	798	822	774	846	754	3,212
Number of bank	25	25	25	25	26	106