1 Loan Loss Provisions Policy - Emerging vs. Developed Economies MSc student: Irina Gabriela...

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Loan Loss Provisions Policy -Emerging vs. Developed Economies

MSc student: Irina Gabriela BidivenciuSupervisor: Professor Moisa Altar, PhD

Bucharest, July 2007

The Academy of Economic StudiesDoctoral School of Finance and Banking

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CONTENTS

1. Introduction2. Literature review3. The model4. Estimation Results

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

5. Conclusions

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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.

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.

Bank Management

Profitability

Safety

Risk and/or Capitalvs. Return

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2. Literature review

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.

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3. The Model3.1. 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: Bankscope EUROSTAT BNR

tA

LLP

1t

t

A

LLP

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3.2. The Model Hypothesis of Prudent Loan Loss

Provisioning Behavior. Data filters

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%

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3.3. The Model Description

Testing the hypothesis of imprudent behavior and verifying the nature of the relationship between banks’ provisions and earnings:

(1)

The speed of adjustment of the dependent lagged variable is depicted through:

(2)

ititititit

TGDPLA

EBP

A

LLP

4321

it

ittitiit

LA

EBP

A

LLP

A

LLP

A

LLP2

2,2

1,1 1

ititit TGDP 43

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3.4. Correlation matrix

Developed Economies Income smoothing Imprudent behavior Anti-business cyclical behavior

Emerging Economies No Income smoothing Imprudent behavior No anti-business cyclical behavior

LLP_D_ASSETS

EBP_D_ASSETS LOAN_GROWTH

GDP_PERCAPIT

A_GROWTH

LLP_D_ASSETS

1 0.88684 -0.09170 -0.18222

EBP_D_ASSETS

0.88684 1 -0.01670 -0.10325

LOAN_GROWTH

-0.09170 -0.01670 1 -0.00044

GDP_PERCAPITA

_GROWTH

-0.18222 -0.10325 -0.00044 1

LLP_D_ASSETS

EBP_D_ASSETS LOAN_GROWTH

D_GDP_PERCAPITA_GROWTH

LLP_D_ASSETS

1 -0.66704 -0.02542 0.03251

EBP_D_ASSETS

-0.66704 1 0.07737 -0.10628

LOAN_GROWTH

-0.02542 0.07737 1 0.09348

D_GDP_PERCAPIT

A_GROWTH

0.03251 -0.10628 0.09348 1

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4. The Estimations Results 4.1. Generalized Least Squares

Developed Economies Emerging EconomiesDependent 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 Coefficient Std. Error t-Statistic Prob. C 0.013783 0.006481 2.126585 0.0370

EBP/D_ASSETS(-1) 0.347296 0.045008 7.716235 0.0000 LOAN_GROWTH -0.022664 0.015219 -1.489246 0.1409

GDP_PERCAPITA_GROWTH -0.540963 0.404254 -1.338175 0.1852 Effects Specification Cross-section random S.D. / Rho 0.000000 0.0000

Idiosyncratic random S.D. / Rho 0.030701 1.0000 Weighted Statistics R-squared 0.800741 Mean dependent var 0.023889

Adjusted R-squared 0.792201 S.D. dependent var 0.070316 S.E. of regression 0.032054 Sum squared resid 0.071921 F-statistic 93.76722 Durbin-Watson stat 2.172780 Prob(F-statistic) 0.000000

Unweighted Statistics R-squared 0.800741 Mean dependent var 0.023889

Sum squared resid 0.071921 Durbin-Watson stat 2.172780

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)


EBP/D_ASSETS(-1) -0.107385 0.025489 -4.212948 0.0001 LOAN_GROWTH 0.046035 0.090796 0.507019 0.6136

D_GDP_PERCAPITA_GROWTH -0.551364 0.591945 -0.931445 0.3545 Effects Specification Cross-section random S.D. / Rho 0.029479 0.0110





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4.1. Generalized Least Squares (contd.)

Running the GLS estimates the results are different amongst the developed and emerging economies

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.

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4.1. Generalized Least Squares (contd.)

Testing the stationarity Levin, Lin & Chu

Testing the robustness of the estimations Hausman Test (endogeneity test)

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

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4.1. Generalized Least Squares – negative earnings dummy (contd.)

Emerging Economies Hausman test - robustnessGLS – 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: 16:15 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)


EBP/D_ASSETS(-1) -0.104695 0.027977 -3.742235 0.0003 NEG_DUMMY_D_EBP_A -0.644021 0.036267 -17.75794 0.0000

LOAN_GROWTH -0.031850 0.060637 -0.525260 0.6009 D_GDP_PERCAPITA_GROWTH -0.539775 0.551575 -0.978608 0.3308

Effects Specification Cross-section random S.D. / Rho 0.000000 0.0000





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)


EBP/D_ASSETS(-1) -0.139670 0.026428 -5.284894 0.0000 NEG_DUMMY_D_EBP_A -0.612618 0.022481 -27.25060 0.0000

LOAN_GROWTH 0.059751 0.079401 0.752526 0.4549 D_GDP_PERCAPITA_GROWTH -0.316756 0.616077 -0.514150 0.6092

RES_EBP_DUMMY 0.033749 0.040453 0.834277 0.4077 Effects Specification Cross-section random S.D. / Rho 0.000000 0.0000





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4.2. Generalized Method of Moments

Developed Economies Emerging EconomiesDependent 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) -0.164017 0.038027 -4.313210 0.0002

LLP(-2)/D_ASSETS(-3) -0.159180 0.037886 -4.201548 0.0002 EBP/D_ASSETS(-1) 0.348678 0.010832 32.18844 0.0000

LOAN_GROWTH -0.020737 0.021382 -0.969796 0.3402 GDP_PERCAPITA_GROWTH -0.493335 0.211695 -2.330407 0.0269

Effects Specification Cross-section fixed (first differences) R-squared 0.642670 Mean dependent var -0.012323

Adjusted R-squared 0.593383 S.D. dependent var 0.054695 S.E. of regression 0.034877 Sum squared resid 0.035276 J-statistic 5.052150 Instrument rank 10.00000

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)


LLP(-2)/D_ASSETS(-3) -0.039891 0.071376 -0.558889 0.5816 EBP/D_ASSETS(-1) -0.125916 0.010823 -11.63448 0.0000

LOAN_GROWTH 0.488898 0.205357 2.380724 0.0259 D_GDP_PERCAPITA_GROWTH 0.256842 1.375091 0.186782 0.8535

Effects Specification Cross-section fixed (first differences) R-squared 0.774711 Mean dependent var 0.066084


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4.2. Generalized Method of Moments (contd.)

Running the GMM estimates the results are different amongst the developed and emerging economies

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.

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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/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)


LLP(-2)/D_ASSETS(-3) -0.028256 0.070218 -0.402398 0.6913 EBP/D_ASSETS(-1) -0.123587 0.010413 -11.86895 0.0000

LOAN_GROWTH 0.446715 0.207351 2.154395 0.0424 D_GDP_PERCAPITA_GROWTH 0.284347 1.370150 0.207530 0.8375

NEG_DUMMY_D_EBP_A -0.233926 0.246244 -0.949979 0.3524 Effects Specification Cross-section fixed (first differences) R-squared 0.787484 Mean dependent var 0.066084


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)

Variable Coefficient Std. Error t-Statistic Prob. LLP(-1)/ASSETS(-2) 0.024249 0.226920 0.106862 0.9159

LLP(-2)/ASSETS(-3) -0.384981 0.075946 -5.069163 0.0001 EBP/D_ASSETS(-1) 0.000621 0.000390 1.593604 0.1260

LOAN_GROWTH -0.004175 0.004604 -0.906836 0.3748 D_GDP_PERCAPITA_GROWTH 0.055208 0.077733 0.710233 0.4854

NEG_DUMMY_D_EBP_A 0.017577 0.003438 5.112044 0.0000 RES_GMM_DIN_DUMMY -0.000547 0.000503 -1.088171 0.2889

Effects Specification Cross-section fixed (first differences) R-squared 0.679877 Mean dependent var -0.000997


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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. Prudent behavior of the bank management regarding provisioning;2. 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;

3. No income smoothing

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4.3. A Commercial Bank / monthly data (contd.)

OLS estimates GMM estimatesDependent 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)

Coefficient Std. Error t-Statistic Prob. C(1) -0.003491 0.009338 -0.373850 0.7145

C(2) -0.099483 0.151676 -0.655892 0.5233 C(3) -0.519590 0.250340 -2.075538 0.0583 C(4) -0.166315 0.210285 -0.790903 0.4432 C(5) 0.637116 0.757107 0.841514 0.4153 C(6) 0.456431 0.180139 2.533773 0.0249

R-squared -0.797006 Mean dependent var -0.052750

Adjusted R-squared -1.488163 S.D. dependent var 0.161136 S.E. of regression 0.254175 Sum squared resid 0.839865 Durbin-Watson stat 0.926324 J-statistic 0.223881

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

Coefficient Std. Error t-Statistic Prob. C(1) -0.033746 0.031349 -1.076467 0.2912

C(2) 0.093451 0.124459 0.750860 0.4592 C(3) 0.654870 0.658454 0.994557 0.3288 C(4) -0.003258 0.251260 -0.012966 0.9897

R-squared 0.135684 Mean dependent var -0.022210

Adjusted R-squared 0.039648 S.D. dependent var 0.134822 S.E. of regression 0.132122 Akaike info criterion -1.090267 Sum squared resid 0.471319 Schwarz criterion -0.905236 Log likelihood 20.89913 Durbin-Watson stat 1.476980

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Loan Loss Provisions, Loan Portfolio, EBIT

0,00

200,00

400,00

600,00

800,00

1.000,00

1.200,00

1.400,00

1.600,00

Date

Lo

an

s,

Lo

an

Lo

ss P

rovis

ion

s

-15,00

-10,00

-5,00

0,00

5,00

10,00

15,00

20,00

25,00

30,00

35,00

EB

IT Loans

LLP

EBIT

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Developed Economies – Loans

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Developed Economies – Loan Loss Provisions

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Emerging Economies – Loans

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Emerging Economies – Loan Loss Provisions

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5. Conclusions

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;

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5. Conclusions (contd.)

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.

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References

Basel Committee on Banking Supervision (2006), “Sound credit risk assessment and valuation for loans”, Bank for International Settlements

Cavallo, M and Majnoni, G (2001), “Do Banks Provision for Bad Loans in Good Times, Empirical Evidence and Policy Implications”, World Bank Research Working Paper No. 2619

Crouhy, M., Galai, D. and Mark R. (2006), “The Essentials of Risk Management”, The McGraw-Hill Companies, Inc, New York

Cossin, D. and Pirotte H. (2001), “Advanced Credit Risk Analyses – Financial Approaches and Mathematical Models to Assets, Price and Manage Credit Risk”, John Wiley & Sons, Inc, New York

Epstein, B. J. and Mirza A.A. (2002), “IAS 2002 Interpretation and Application of International Accounting Standards”, John Wiley & Sons, Inc, New York

Fernández de Lis, S. F., Pagés, J. M., Saurina, J., (2000), “Credit growth, problem loans and the credit risk provisioning in Spain”, Banco de España – Servicio de Estudios, Documento de Trabajo No. 0018

Fisher, S., (2003), “Implications of the Basel II for Emerging Market Countries”, The William Taylor Memorial Lectures No. 7, Group of trinity, Washington, DC

Hansen, B.E. and West, K.D. (2002), “Generalized Method of Moments and Macroeconomics”, Journal of Business & Economic Statistics

Laeven, L and Majnoni, G (2002), “Loan Loss Provisioning and the Economic Slowdowns: Too Much, Too Late?”, Conference Series, Federal Reserve Bank of Boston

Levine, A and Lin, C-F (1992), “Unit Root Tests in Panel Data: Asymptotic and Finite-sample Properties”, University of California, San Diego, Department of Economics, Discussion Paper 92-23

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References (contd.)

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 loan loss provision regulatory regimes”, Banco de España, Documento de Trabajo No. 0614

Pynnonen, S. (2007), “A Short Introduction to the Generalized Method of Moments Estimation”, 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

Yaffee, R., (2003), “A primer for Panel Data Analysis”, Connect Information Technology at New York University, Information Technology Services

Wooldridge, J. M., (2001), “Econometric Analysis of Cross Section and Panel Data”, The MIT Press, Cambridge, Massachusetts, London, New England

**** Credit Policy (2007), Raiffeisen Bank **** Annual Reports (2004, 2005, 2006), Raiffeisen Bank EUROSTAT, General and regional statistics, Economy and finance indicators BANKSCOPE, Bureau Van Duk National Bank of Romania, Annual Reports and Monthly Bulletins National Bank of Romania, Regulation No. 5 (2002)

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