Download Loan Loss Provisions Policy - Emerging vs. Developed Economies

The Academy of Economic Studies
Doctoral School of Finance and Banking
Loan Loss Provisions Policy Emerging vs. Developed Economies
MSc student: Irina Gabriela Bidivenciu
Supervisor: Professor Moisa Altar, PhD
1
Bucharest, July 2007
CONTENTS
1.
2.
3.
4.
Introduction
Literature review
The model
Estimation Results



5.
2
Estimations of the Loan Loss Provisions Model using GLS
Estimations of the Loan Loss Provisions Model using GMM
Estimations of the Loan Loss Provisions Model within a commercial
bank
Conclusions
1. Introduction
The modern economies are different
from those in the past in their ability
to identify the risk, to measure it, to
appreciate its consequences and in
taking action accordingly.
Bank
Management
Safety
The loan loss provisions are a
“device” that can correct the
negative effects of the loan portfolio
problems within the bank sector.
The level of the loan loss provisions
must be designed to cover the
expected losses during the
economic cycle.
3
Risk and/or Capital
vs. Return
Profitability
2. Literature review






4
The Basel Committee (1988)  new method for evaluating the capital assets correlation based on a simplified weights system algorithm and a
minimum capital adequacy ratio of 8%.
Basel II (2004) International Convergence of Capital Measurement and
Capital Standards: all the credit institutions are required to have a policy in
relation to credit risk, arrears and provisioning management.
Pérez, D., Salas-Fumás, V., Saurina, J., (2006)  the banks must protect
their capital from expected or unexpected losses through loan loss provisions
and not to wait until the negative events occurred without affecting the
transparency using the statistical provisions.
Laeven, L. and Majnoni, G., (2002)  banks on average postpone
provisioning when faced with cyclical upturns and favorable income conditions
until negative conditions set in (income smoothing practices).
Cavallo M. and Majnoni G., (2001)  the fiscal authority may affect relevant
business decisions for banks and financial institutions.
Fernández de Lis, S., Pagés, J. M. and Saurina J., (2000)  introduction of
statistical provisions in Spain. In good times the banks have to set aside
provisions that might be depleted in bad times when the excesses of the last
upturn appear in the form of impaired assets.
3. The Model
3.1. The Model Variables





Total Assets (A)
Loan Loss Provisions (LLP)
Profits Before Tax and Provisions (EBP)
Loan Growth in real terms (∆L)
Real Growth in GDP per capita (∆GDP) or Real Growth of
Industrial Output Index (∆IOI)
Note: The values of the loan loss provisions at time t correspond to the
values of the assets at time t-1.
Data Source:


5

Bankscope
EUROSTAT
BNR
 LLP 


 A t

LLPt
At 1
3.2. The Model Hypothesis of Prudent Loan Loss
Provisioning Behavior. Data filters



6
The coefficient on earnings before tax and provisions is
negative;
The coefficient on loan growth is negative;
The coefficient on real growth rate of GDP per capita / the
real growth of the Industrial Output Index is negative.
The bank/year observations that exhibit one of the following features
were excluded:
o
Ratio of loan loss provisions over lagged total assets > 90% or
<10 %;
o
Earnings before provisions over lagged total assets > 12%
o
Loan growth rate in real terms > 56%
o
Loan decreasing rate in real terms > 50%
3.3. The Model Description
Testing the hypothesis of imprudent behavior and verifying the
nature of the relationship between banks’ provisions and
earnings:
 LLP 
 EBP 

    1 
   2 Lit  3GDPit   4Tt  i   it
 A 
 A it
(1)
The speed of adjustment of the dependent lagged variable is
depicted through:
 LLP 
 LLP 
 LLP 
 EBP 
  1

     1
  2

   2 Lit 
 A  it
 A  i ,t 1
 A  i ,t  2
 A  it
  3GDPit   4Tt   i   it
7
(2)
3.4. Correlation matrix
Developed Economies
Emerging Economies
Income smoothing
 Imprudent behavior
 Anti-business cyclical behavior

No Income smoothing
 Imprudent behavior
 No anti-business cyclical behavior

LLP_D_ASSETS EBP_D_ASSETS LOAN_GROWTH
8
GDP_PERCAPIT
A_GROWTH
LLP_D_ASSETS EBP_D_ASSETS LOAN_GROWTH
D_GDP_PERCA
PITA_GROWTH
LLP_D_ASSETS
1
0.88684
-0.09170
-0.18222
LLP_D_ASSETS
1
-0.66704
-0.02542
0.03251
EBP_D_ASSETS
0.88684
1
-0.01670
-0.10325
EBP_D_ASSETS
-0.66704
1
0.07737
-0.10628
LOAN_GROWTH
-0.09170
-0.01670
1
-0.00044
LOAN_GROWTH
-0.02542
0.07737
1
0.09348
GDP_PERCAPITA
_GROWTH
-0.18222
-0.10325
-0.00044
1
D_GDP_PERCAPIT
A_GROWTH
0.03251
-0.10628
0.09348
1
4. The Estimations Results
4.1. Generalized Least Squares
Developed Economies
Emerging Economies
Dependent Variable: LLP/D_ASSETS(-1)
Method: Panel EGLS (Cross-section random effects)
Date: 06/17/07 Time: 15:27
Sample (adjusted): 1999 2006
Cross-sections included: 10
Total panel (unbalanced) observations: 74
Swamy and Arora estimator of component variances
White period standard errors & covariance (d.f. corrected)
Variable
Dependent Variable: LLP/D_ASSETS(-1)
Method: Panel EGLS (Cross-section random effects)
Date: 06/11/07 Time: 21:32
Sample (adjusted): 1999 2006
Cross-sections included: 11
Total panel (unbalanced) observations: 83
Swamy and Arora estimator of component variances
White period standard errors & covariance (no d.f. correction)
Coefficient
Std. Error
t-Statistic
Prob.
C
0.013783
EBP/D_ASSETS(-1)
0.347296
LOAN_GROWTH
-0.022664
GDP_PERCAPITA_GROWTH -0.540963
0.006481
0.045008
0.015219
0.404254
2.126585
7.716235
-1.489246
-1.338175
0.0370
0.0000
0.1409
0.1852
Variable
Coefficient
Std. Error
t-Statistic
Prob.
C
0.075376
EBP/D_ASSETS(-1)
-0.107385
LOAN_GROWTH
0.046035
D_GDP_PERCAPITA_GROWTH -0.551364
0.036149
0.025489
0.090796
0.591945
2.085172
-4.212948
0.507019
-0.931445
0.0403
0.0001
0.6136
0.3545
0.029479
0.279551
0.0110
0.9890
Effects Specification
Cross-section random S.D. / Rho
Idiosyncratic random S.D. / Rho
Effects Specification
0.000000
0.030701
0.0000
1.0000
Cross-section random S.D. / Rho
Idiosyncratic random S.D. / Rho
Weighted Statistics
R-squared
Adjusted R-squared
S.E. of regression
F-statistic
Prob(F-statistic)
0.800741
0.792201
0.032054
93.76722
0.000000
Mean dependent var
S.D. dependent var
Sum squared resid
Durbin-Watson stat
Weighted Statistics
0.023889
0.070316
0.071921
2.172780
R-squared
Adjusted R-squared
S.E. of regression
F-statistic
Prob(F-statistic)
Unweighted Statistics
9
R-squared
Sum squared resid
0.800741
0.071921
Mean dependent var
Durbin-Watson stat
0.445932
0.424892
0.276082
21.19395
0.000000
Mean dependent var
S.D. dependent var
Sum squared resid
Durbin-Watson stat
0.081290
0.364052
6.021484
1.652518
Unweighted Statistics
0.023889
2.172780
R-squared
Sum squared resid
0.447363
6.075083
Mean dependent var
Durbin-Watson stat
0.084784
1.637939
4.1. Generalized Least Squares (contd.)
Running the GLS estimates  the results are different amongst
the developed and emerging economies
10

The banks within developed countries smooth the income while within
the emerging countries this is not a common practice;

The loan loss provisions follow the loan portfolio growth only within the
emerging economies;

The loan loss provisions policies are correlated with the economic
cycle.
4.1. Generalized Least Squares (contd.)
Testing the stationarity  Levin, Lin & Chu
Testing the robustness of the estimations  Hausman Test (endogeneity
test)
11

Developed Countries: the fixed effects results do not differ
significantly from the random effects results

Emerging Countries: when running an auxiliary regression the
resid term takes value of 0.001
4.1. Generalized Least Squares – negative earnings
dummy (contd.)
Emerging Economies  Hausman test - robustness
GLS – negative earnings dummy
GLS – negative earnings dummy + resid
Dependent Variable: LLP/D_ASSETS(-1)
Method: Panel EGLS (Cross-section random effects)
Date: 06/12/07 Time: 16:45
Sample (adjusted): 2001 2006
Cross-sections included: 11
Total panel (unbalanced) observations: 61
Swamy and Arora estimator of component variances
White cross-section standard errors & covariance (d.f. corrected)
Dependent Variable: LLP/D_ASSETS(-1)
Method: Panel EGLS (Cross-section random effects)
Date: 06/12/07 Time: 16:15
Sample (adjusted): 1999 2006
Cross-sections included: 11
Total panel (unbalanced) observations: 83
Swamy and Arora estimator of component variances
White period standard errors & covariance (d.f. corrected)
Variable
Coefficient
Std. Error
t-Statistic
Prob.
C
EBP/D_ASSETS(-1)
NEG_DUMMY_D_EBP_A
LOAN_GROWTH
D_GDP_PERCAPITA_GROWTH
0.096448
-0.104695
-0.644021
-0.031850
-0.539775
0.027049
0.027977
0.036267
0.060637
0.551575
3.565629
-3.742235
-17.75794
-0.525260
-0.978608
0.0006
0.0003
0.0000
0.6009
0.3308
0.000000
0.268180
0.0000
1.0000
Variable
Coefficient
Std. Error
t-Statistic
C
0.083750
EBP/D_ASSETS(-1)
-0.139670
NEG_DUMMY_D_EBP_A
-0.612618
LOAN_GROWTH
0.059751
D_GDP_PERCAPITA_GROWTH -0.316756
RES_EBP_DUMMY
0.033749
0.008122
0.026428
0.022481
0.079401
0.616077
0.040453
10.31162
-5.284894
-27.25060
0.752526
-0.514150
0.834277
0.0000
0.0000
0.0000
0.4549
0.6092
0.4077
0.000000
0.282011
0.0000
1.0000
Effects Specification
Cross-section random S.D. / Rho
Idiosyncratic random S.D. / Rho
Effects Specification
Cross-section random S.D. / Rho
Idiosyncratic random S.D. / Rho
Weighted Statistics
R-squared
Adjusted R-squared
S.E. of regression
F-statistic
Prob(F-statistic)
0.503078
0.477595
0.264638
19.74155
0.000000
Mean dependent var
S.D. dependent var
Sum squared resid
Durbin-Watson stat
Weighted Statistics
0.084784
0.366142
5.462612
1.629710
R-squared
Adjusted R-squared
S.E. of regression
F-statistic
Prob(F-statistic)
0.573359
0.534574
0.277595
14.78281
0.000000
0.084784
1.629710
R-squared
Sum squared resid
0.573359
4.238258
Unweighted Statistics
12
R-squared
Sum squared resid
0.503078
5.462612
Prob.
Mean dependent var
Durbin-Watson stat
Mean dependent var
S.D. dependent var
Sum squared resid
Durbin-Watson stat
0.091951
0.406899
4.238258
1.459464
Unweighted Statistics
Mean dependent var
Durbin-Watson stat
0.091951
1.459464
4.2. Generalized Method of Moments
Developed Economies
Emerging Economies
Dependent Variable: LLP/D_ASSETS(-1)
Method: Panel Generalized Method of Moments
Transformation: First Differences
Date: 06/13/07 Time: 17:51
Sample (adjusted): 2004 2006
Cross-sections included: 11
Total panel (unbalanced) observations: 28
White period instrument weighting matrix
White period standard errors & covariance (d.f. corrected)
Instrument list: @DYN(LLP(0)/D_ASSETS(-1),-2) LLP(-3)/D_ASSETS(
-4) LLP(-4)/D_ASSETS(-5)
Dependent Variable: LLP/D_ASSETS(-1)
Method: Panel Generalized Method of Moments
Transformation: First Differences
Date: 06/17/07 Time: 15:28
Sample (adjusted): 2003 2006
Cross-sections included: 10
Total panel (unbalanced) observations: 34
White period instrument weighting matrix
White period standard errors & covariance (d.f. corrected)
Instrument list: @DYN(LLP-D_ASSETS(-1),-2) LLP(-3)/D_ASSETS(-4)
Variable
Coefficient
Std. Error
t-Statistic
Prob.
LLP(-1)/D_ASSETS(-2)
LLP(-2)/D_ASSETS(-3)
EBP/D_ASSETS(-1)
LOAN_GROWTH
GDP_PERCAPITA_GROWTH
-0.164017
-0.159180
0.348678
-0.020737
-0.493335
0.038027
0.037886
0.010832
0.021382
0.211695
-4.313210
-4.201548
32.18844
-0.969796
-2.330407
0.0002
0.0002
0.0000
0.3402
0.0269
Variable
Coefficient
Std. Error
t-Statistic
Prob.
LLP(-1)/D_ASSETS(-2)
-0.082073
LLP(-2)/D_ASSETS(-3)
-0.039891
EBP/D_ASSETS(-1)
-0.125916
LOAN_GROWTH
0.488898
D_GDP_PERCAPITA_GROWTH 0.256842
0.077156
0.071376
0.010823
0.205357
1.375091
-1.063730
-0.558889
-11.63448
2.380724
0.186782
0.2985
0.5816
0.0000
0.0259
0.8535
Effects Specification
Effects Specification
Cross-section fixed (first differences)
13
R-squared
Adjusted R-squared
S.E. of regression
J-statistic
0.642670
0.593383
0.034877
5.052150
Cross-section fixed (first differences)
Mean dependent var
S.D. dependent var
Sum squared resid
Instrument rank
-0.012323
0.054695
0.035276
10.00000
R-squared
Adjusted R-squared
S.E. of regression
J-statistic
0.774711
0.735530
0.413950
5.642289
Mean dependent var
S.D. dependent var
Sum squared resid
Instrument rank
0.066084
0.804932
3.941154
11.00000
4.2. Generalized Method of Moments (contd.)
Running the GMM estimates  the results are different amongst the
developed and emerging economies
14

All the banks considered are slow in adjusting their provisions over a
certain number of years as suggest the slow decrease of the lagged
dependent variable coefficient.

The banks within the developed countries smooth their earnings while
within the emerging countries this is not a common practice.

The banks within the developed countries have an imprudent
behaviour regarding provisioning while the others are showed to be
prudent in their polices;

The loan loss provisions polices follow the economic cycle only within
the banks from Western Europe.
4.2. Generalized Method of Moments – negative
earnings dummy (contd.)
Emerging Economies  Hausman test - robustness
GMM – negative earnings dummy
GMM – negative earnings dummy + resid
Dependent Variable: LLP/ASSETS(-1)
Method: Panel Generalized Method of Moments
Transformation: First Differences
Date: 06/12/07 Time: 21:44
Sample (adjusted): 2004 2006
Cross-sections included: 11
Total panel (unbalanced) observations: 28
White period instrument weighting matrix
White period standard errors & covariance (d.f. corrected)
Instrument list: @DYN(LLP(0)/ASSETS(-1),-2) LLP(-3)/D_ASSETS(-4)
LLP(-4)/D_ASSETS(-5)
Dependent Variable: LLP/D_ASSETS(-1)
Method: Panel Generalized Method of Moments
Transformation: First Differences
Date: 06/12/07 Time: 21:12
Sample (adjusted): 2004 2006
Cross-sections included: 11
Total panel (unbalanced) observations: 28
White period instrument weighting matrix
White period standard errors & covariance (d.f. corrected)
Instrument list: @DYN(LLP(0)/D_ASSETS(-1),-2) LLP(-3)/D_ASSETS(
-4) LLP(-4)/D_ASSETS(-5)
Variable
Coefficient
Std. Error
t-Statistic
Prob.
LLP(-1)/D_ASSETS(-2)
LLP(-2)/D_ASSETS(-3)
EBP/D_ASSETS(-1)
LOAN_GROWTH
D_GDP_PERCAPITA_GROWTH
NEG_DUMMY_D_EBP_A
-0.096623
-0.028256
-0.123587
0.446715
0.284347
-0.233926
0.072205
0.070218
0.010413
0.207351
1.370150
0.246244
-1.338171
-0.402398
-11.86895
2.154395
0.207530
-0.949979
0.1945
0.6913
0.0000
0.0424
0.8375
0.3524
Variable
Coefficient
Std. Error
t-Statistic
Prob.
LLP(-1)/ASSETS(-2)
0.024249
LLP(-2)/ASSETS(-3)
-0.384981
EBP/D_ASSETS(-1)
0.000621
LOAN_GROWTH
-0.004175
D_GDP_PERCAPITA_GROWTH 0.055208
NEG_DUMMY_D_EBP_A
0.017577
RES_GMM_DIN_DUMMY
-0.000547
0.226920
0.075946
0.000390
0.004604
0.077733
0.003438
0.000503
0.106862
-5.069163
1.593604
-0.906836
0.710233
5.112044
-1.088171
0.9159
0.0001
0.1260
0.3748
0.4854
0.0000
0.2889
Effects Specification
Effects Specification
Cross-section fixed (first differences)
15
R-squared
Adjusted R-squared
S.E. of regression
J-statistic
0.787484
0.739185
0.411080
7.349217
Cross-section fixed (first differences)
Mean dependent var
S.D. dependent var
Sum squared resid
Instrument rank
0.066084
0.804932
3.717702
11.00000
R-squared
Adjusted R-squared
S.E. of regression
J-statistic
0.679877
0.588414
0.004406
6.572038
Mean dependent var
S.D. dependent var
Sum squared resid
Instrument rank
-0.000997
0.006867
0.000408
11.00000
4.3. A Commercial Bank / monthly data

Similar model for a commercial Romanian bank  the bank behavior
between 1st of June 2004 and 31st of March 2007

Test the stationarity  Augmented Dickey Fuller

The estimates results:
1.
2.
3.
16
Prudent behavior of the bank management regarding provisioning;
The relation with the economic cycle: Industrial Output Index the
overall portfolio exposure with the industrial sector represents
about 25 percent of the total loan portfolio exposure;
No income smoothing
4.3. A Commercial Bank / monthly data (contd.)
OLS estimates
GMM estimates
Dependent Variable: LLP/ASSETS(-1)
Method: Least Squares
Date: 07/02/07 Time: 22:14
Sample (adjusted): 2004M08 2007M02
Included observations: 31 after adjustments
White Heteroskedasticity-Consistent Standard Errors & Covariance
LLP/ASSETS(-1)=C(1)+C(2)*EBP/ASSETS(-1)+C(3)
*LOAN_GROWTH+C(4)*IOI_GROWTH
C(1)
C(2)
C(3)
C(4)
R-squared
Adjusted R-squared
S.E. of regression
Sum squared resid
Log likelihood
17
Coefficient
Std. Error
t-Statistic
Prob.
-0.033746
0.093451
0.654870
-0.003258
0.031349
0.124459
0.658454
0.251260
-1.076467
0.750860
0.994557
-0.012966
0.2912
0.4592
0.3288
0.9897
0.135684
0.039648
0.132122
0.471319
20.89913
Mean dependent var
S.D. dependent var
Akaike info criterion
Schwarz criterion
Durbin-Watson stat
-0.022210
0.134822
-1.090267
-0.905236
1.476980
Dependent Variable: LLP/ASSETS(-1)
Method: Generalized Method of Moments
Date: 06/16/07 Time: 18:53
Sample (adjusted): 2005M08 2007M02
Included observations: 19 after adjustments
Kernel: Bartlett, Bandwidth: Fixed (2), No prewhitening
Simultaneous weighting matrix & coefficient iteration
Convergence achieved after: 144 weight matrices, 145 total coef
iterations
LLP(0)/ASSETS(-1)=C(1)+C(2)*LLP(-1)/ASSETS(-2)+C(3)*LLP(-2)
/ASSETS(-3)+C(4)*EBP/ASSETS(-1)+C(5)*LOAN_GROWTH
+C(6)*IOI_GROWTH
Instrument list: LLP(-3)/ASSETS(-4) LLP(-4)/ASSETS(-5) LLP(-5)
/ASSETS(-6) LLP(-6)/ASSETS(-7) LLP(-7)/ASSETS(-8) LLP(-7)
/ASSETS(-8) LLP(-8)/ASSETS(-9) LLP(-9)/ASSETS(-10) LLP(
-10)/ASSETS(-11) LLP(-11)/ASSETS(-12) LLP(-12)/ASSETS(
-13)
C(1)
C(2)
C(3)
C(4)
C(5)
C(6)
R-squared
Adjusted R-squared
S.E. of regression
Durbin-Watson stat
Coefficient
Std. Error
t-Statistic
Prob.
-0.003491
-0.099483
-0.519590
-0.166315
0.637116
0.456431
0.009338
0.151676
0.250340
0.210285
0.757107
0.180139
-0.373850
-0.655892
-2.075538
-0.790903
0.841514
2.533773
0.7145
0.5233
0.0583
0.4432
0.4153
0.0249
-0.797006
-1.488163
0.254175
0.926324
Mean dependent var
S.D. dependent var
Sum squared resid
J-statistic
-0.052750
0.161136
0.839865
0.223881
18
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7
Loans, Loan Loss Provisions
1.600,00
800,00
10,00
600,00
5,00
0,00
400,00
-5,00
200,00
-10,00
0,00
-15,00
Date
EBIT
Loan Loss Provisions, Loan Portfolio, EBIT
35,00
1.400,00
30,00
25,00
1.200,00
20,00
1.000,00
15,00
Loans
LLP
EBIT
Developed Economies – Loans
19
Developed Economies – Loan Loss Provisions
20
Emerging Economies – Loans
21
Emerging Economies – Loan Loss Provisions
22
5. Conclusions
23

The banks within the developed countries provision less during high
GDP growth, suggesting an undesirable anti-business cyclical
behavior. On the contrary, the banks behavior from the emerging
countries does not follow the economical cycle. The reason of this
behavior is related with the economy development and the boom of
the bank sector within all those countries;

The banks from developed countries smooth their income through the
loan loss provisioning policies. This might result in lower earnings
quality since net income does not representatively portray the
economic performance of the business entity for the period. The banks
from the emerging countries do not smooth their income;
5. Conclusions (contd.)
24

The amounts allocated to the loan loss provisions in the emerging
countries follow the growth of the loan portfolio showing a prudent
behavior of the banks’ managers accordingly with the new fiscal and
prudential requirements;

Credit risk is a normal part of banking. However, where the amount of
risk is excessive or where this is not properly monitored and controlled,
it can produce a significant threat to the credit institution and its
earnings.
References










25
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References (contd.)
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26
Mazararu, E, (2005), “The New Basel Accord”, The Corporate Development Sector, Raiffeisen
Bank
Pérez, D., Salas-Fumás V., Saurina, J., (2006), “Earnings and capital management in alternative
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University of Vaasa, Department of Mathematics and Statistics, Finland
Keller G. and Warrack B. (2001), “Statistics for Management and Economics”, Fifth Edition,
Duxbury Thomson Learning
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