The effect of credit growth on credit quality evidences of commercial banks in dong nai province

UNIVERSITY OF ECONOMICS
HO CHI MINH CITY
VIETNAM

ERAMUS UNIVERSITY ROTTERDAM
INSTITUTE OF SOCIAL STUDIES
THE NETHERLANDS

VIETNAM – THE NETHERLANDS
PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS

THE EFFECT OF CREDIT GROWTH ON CREDIT QUALITY:
EVIDENCE FROM THE COMMERCIAL BANKS IN DONG NAI
A thesis submitted in partial fulfilment of the requirements for the degree of

MASTER OF ARTS IN DEVELOPMENT ECONOMICS

By

TRINH HOANG VIET

Academic Supervisor

Dr. VO HONG DUC

HO CHI MINH CITY, December 2015


DECLARATION
I hereby declare that the thesis “THE EFFECT
CREDIT QUALITY: EVIDENCE

FROM

OF

CREDIT GROWTH

THE COMMERCIAL BANKS

IN

ON

DONG NAI”,

which is submitted to Vietnam – Netherlands Programme, is my original research
work. All of the contents which are not from my own work are cited carefully and
clearly in this thesis.
I certified that the contents of this thesis have not been and are not being
submitted for any other degrees.
This thesis was done under the supervision and guidance of Dr. Vo Hong Duc,
Economic Regulation Authority, Western Australia and the Edith Cowan
University, Australia. Any other contributions to this thesis are presented in the
ACKNOWLEDGEMENT section.
Signature

Trinh Hoang Viet
Ho Chi Minh City, 1st November 2015
In my capacity as the supervisor of this thesis, I certified that the statements
above are true to the best of my knowledge.

Signature

Dr. Vo Hong Duc
Date: ....................................
i


ACKNOWLEDGEMENT
I would like to express my great appreciation to VNP Lecturer Team for their
dedication in teaching, which brought to me useful knowledge and experiences in
my academic career.
I would like to express my deep gratitude to Dr. Vo Hong Duc, my research
supervisors, for his patient guidance and useful critiques of this research work.
I would like to offer my special thanks to Mr. Pham Quoc Bao and Mr. Pham
Thanh Huu for facilitating me to collect necessary data during my internship in The
State Bank of Viet Nam, Dong Nai Branch.
I wish to acknowledge the contributions of all VNP students in Class 20,
especially Mr. Vo Van Hung and Mr. Nguyen Son Kien, for sharing learning
experiences and valuable academic materials.
I would also like to extend my thanks to all VNP Staffs for their enthusiasm of
assisting my study over the last two years.
Finally, I would not forget to send my deepest thank to my parents who
always encourage me to keep up with my study objectives.

ii


ABSTRACT
This research is conducted to examine and quantify the effect of credit growth
on credit quality for the commercial banks in Dong Nai. In relation to this possible

effect, theoretical framework of the so–called “three shifts” in the credit market is
likely to explain that credit growth might have positive or negative effect on credit
quality. These three shifts are generally known as: (i) a supply shift (an expansion in
bank loan supply by lowering credit standards), (ii) a demand shift (an increase in
loan demand to optimize business activities) and (iii) productivity shift (a positive
change in macroeconomic conditions). In addition, empirical evidence confirms that
rapid credit growth of commercial banks could lead to a deterioration or
improvement of credit quality. The macroeconomic context for banking industry
indicates that the decline in credit quality after a period of growth might be a
reflection of (1) negative changes in the macroeconomic determinants which have a
bad influence on the business activities of borrowers; and (2) information
externality which makes banks hardly gain efficiency in evaluating their customers.
This study utilizes the data of 29 commercial banks operating in Dong Nai
province for the period from 2009Q3 to 2014Q4. The econometric technique of
Difference GMM for dynamic panel data model is adopted in order to examine the
effect of credit growth on credit quality in the context of the commercial banks in
Dong Nai. This study finds empirical evidence to confirm that credit growth causes
the decrease in credit quality after three quarters to one year. In addition, this effect
of credit growth in the long run is found in this study.
These findings obtained from this study reflects that: (i) commercial banks in
Dong Nai might have lowered their credit standards to increase their lending to
business customers and individuals; (ii) the conditions of local economy in Dong
Nai might have not been really favorable for business activities during the research
period; (iii) and the information externality in the loan market might have distorted
the accuracy of customers evaluation in relation to their financial capacity.
iii


Keywords: credit growth, credit quality, commercial bank, difference GMM,
dynamic model, non–performing loan.

iv


TABLE OF CONTENTS
DECLARATION .............................................................................................................. i
ACKNOWLEDGEMENT ..................................................................................................ii
ABSTRACT ................................................................................................................. iii
TABLE OF CONTENTS .................................................................................................. v
LIST OF TABLES ........................................................................................................vii
LIST OF FIGURES ..................................................................................................... viii
CHAPTER 1 INTRODUCTION ...................................................................................... 1
1.1 PROBLEM STATEMENT ..................................................................................... 1
1.2 RESEARCH OBJECTIVE AND QUESTION ............................................................ 2
1.3 RESEARCH SCOPE AND METHODOLOGY .......................................................... 2
1.4 THESIS STRUCTURE ......................................................................................... 3
CHAPTER 2 LITERATURE REVIEW ........................................................................... 4
2.1 THE MACROECONOMIC CONTEXT FOR BANKING ............................................. 4
2.1.1

Main Characteristics of Banks ..............................................................4

2.1.2

Shock and Vulnerability of Banking System..........................................6

2.1.3

The Effect of Macroeconomic Determinants.........................................6

2.1.4

Credit Growth and Vulnerability of Banking System ............................7

2.2 CREDIT GROWTH AND CREDIT QUALITY THROUGH DIFFERENT SHIFTS ........... 9
2.3 CONTROL FACTORS FOR CREDIT QUALITY .................................................... 17
2.4 PREVIOUS EMPIRICAL STUDIES ...................................................................... 20
2.5 THE CONCEPTUAL FRAMEWORK.................................................................... 26
CHAPTER 3 METHODOLOGY AND DATA ................................................................ 27
3.1 MEASURING CREDIT QUALITY ...................................................................... 27
3.2 DATA COLLECTION METHOD ........................................................................ 29
3.3 ECONOMETRIC METHODOLOGY ..................................................................... 30
3.3.1

Dynamic Panel Data Estimator ..........................................................31

3.3.2

Econometric Problems ........................................................................31
v


3.3.3

Estimating The Long–run Coefficients ................................................33

3.3.4

Econometric Specification...................................................................35

3.3.5

Hypothesis testing ...............................................................................35

CHAPTER 4 RESULT AND DISCUSSION .................................................................... 38
CHAPTER 5 CONCLUSIONS ...................................................................................... 46
REFERENCES ............................................................................................................. 49

vi


LIST OF TABLES
TABLE 2.1

Change in credit standard, credit growth and credit quality ............... 16

TABLE 2.2

Summarization of the literature ........................................................... 25

TABLE 3.1

Necessary items and their account type .............................................. 29

TABLE 3.2

The expected signs of variables used in the research .......................... 30

TABLE 3.3

The calculation of variables ................................................................ 30

TABLE 3.4

Hypotheses need testing ...................................................................... 37

TABLE 4.1

Descriptive statistics ............................................................................ 39

TABLE 4.2

Estimation result .................................................................................. 41

vii


LIST OF FIGURES
FIGURE 2.1 The macroeconomic context for banking .............................................. 8
FIGURE 2.2 Supply shift ......................................................................................... 10
FIGURE 2.3 Demand shift ....................................................................................... 13
FIGURE 2.4 Productivity shift ................................................................................. 15
FIGURE 2.5 Different shifts in the macroeconomic context for banking ............... 16
FIGURE 2.6 The effect of credit growth on credit quality ...................................... 26
FIGURE 4.1 Deposit growth rate and deposit interest rate ...................................... 39

viii


CHAPTER 1

INTRODUCTION
1.1 PROBLEM STATEMENT
Commercial bank is one of the most important financial intermediaries in the
economy. Their main functions are mobilizing and lending money to allocate
financial resources for households, firms and other economic entities. The typical
problem of banks is that when borrowers could not use well the money they had
borrowed, a credit risk arose. One of the main causes is that banks lower their credit
standards to attract more borrowers. Although it might be a good opportunity to
boost credit growth in the present time, banks will face a higher probability to deal
with non–performing loans (NPLs) in the future. However, if loans expansion is due
to an increase in the demand, this growth will not essentially lead to bad loans.
Therefore, credit growth may be a reflection of credit quality under some
circumstances.
When the economy is in the stage of recession, it is certain to affect negatively
on the financial market especially the banking system. The general picture is that
commercial banks attempt to boost credit growth for profit objective whereas
households and firms who borrow money from banks have to face with difficulties
in business activities. This leads to a consequence that credit growth may reduce
credit quality. The problem is whether the profit target of commercial banks by
boosting credit growth would be efficient or it just increases the NPLs which bring
no profits or even losses.
The determination of the effect of credit growth on credit quality is getting
more and more important for not only commercial banks but also central bank and
policy makers. For commercial banks, it may help them to consider the appropriate
time of loosening or tightening credit standards and the decision to expand or limit
lending activities. For central bank, it will help to control the loans growth of
1

commercial banks. This is to prevent potential banking crisis when the credit quality
is too low. In some cases, understanding the true influence of credit growth on
credit quality could help to recognize the real state of the economy in order to apply
macroeconomic policies more efficiently.
In a report of The State Bank of Vietnam, Dong Nai branch (2015), the current
debit balance of total loans is about 100 billion VND. This source of capital is
mainly concentrated on prior fields and industries of Dong Nai province. The
overdue loans are kept at a safe ratio of 2.32 percent. However, the business
activities of firms still meet many difficulties when commercial banks apply new
standards of classifying debts. Besides, commercial banks are detected of infringing
credit regulations such as appraising credit documents carelessly; misevaluating
customer financial capacity and collaterals; and not supervising capital usage
closely. Under these conditions above, commercial banks in Dong Nai might have
to face a high chance of potential credit risk while lending activities is more and
more expanded.
1.2 RESEARCH OBJECTIVE AND QUESTION
This research is to investigate the influence of banks’ credit growth on their
credit quality under the control of some characteristics of banks. To achieve the
research objective, this study attempts to answer the following question:
Does a positive change in the commercial banks’ credit growth lead to a
negative change in banks’ credit quality in the case of Dong Nai banking system?
1.3 RESEARCH SCOPE AND METHODOLOGY
The research is carried out in the scope of credit growth and credit quality of
29 commercial banks in Dong Nai province, Vietnam. The data is collected in the
period from 2009Q3 to 2014Q1.

2


The main methodology of this study is quantitative analysis. Due to the

availability of panel data, the limitations of common estimation methods and the
objective of capturing the changes of banks’ credit growth and credit quality, this
research applies the method of Difference GMM for the dynamic panel data model.
Besides, the dynamic model could be used to generate long–run coefficients which
reflect the equilibrium of the effects of credit growth.
1.4 THESIS STRUCTURE
This thesis includes five chapters. Chapter 1 introduces the background and
motivation of the research on the effect of credit growth on credit quality. Chapter 2
reviews related theories, previous empirical studies and builds a conceptual
framework for the research. Chapter 3 presents the data collection method and
quantitative techniques for producing necessary results. Chapter 4 shows the results
and discussions. Chapter 5 summarizes main research findings, brings out policy
implications, raises some limitations and suggests further studies.

3


CHAPTER 2

LITERATURE REVIEW
This chapter introduces the two main theories related to the effect of credit
growth on and credit quality. First, the macroeconomic context for banking is to
explain how this effect could occur. Second, the so–called three shifts are to explain
the detail channels in which credit growth could affect credit quality in the credit
market. This chapter also presents some theories about the effect of some bank
characteristics on credit quality as control factors. Besides, some related previous
empirical studies and the conceptual framework for this research are also presented.
2.1 THE MACROECONOMIC CONTEXT FOR BANKING
2.1.1 Main Characteristics of Banks
As the role of a financial intermediary, banks have a large contribution on the

entire economy in the aspect of finance or anything relating to money. Banking
itself is an industry in the economy. Therefore, banks have their own characteristics
which are unique and different from other industries. In order to analyze banking
system under the impact of the macroeconomic context, this research is firstly to
introduce the three main bank characteristics which have close relationship to credit
growth and credit quality.
Banks have extremely high leverage (1). Banks mostly use other people’s
money for their portfolio. Similarly, banks primarily mobilize capital for lending
activities. According to Gavin and Hausmann (1996), bank leverage has two
implications. First, bank operations are very sensitive to the volatility of the
macroeconomic determinants due to very thin capital. They may become insolvent
after small negative changes of the economy. Second, high leverage may bring to a
problem relating to the benefit of bank shareholders and debt–holders. Bank

4


managers often generate risky portfolio to bring the highest benefit for shareholders
while debt–holders is limited in their capital recovery in case of insolvency.
Banks are easy to become illiquid (2). First, the term of deposit liabilities tend
to be higher than the term of loan assets. Borrowers – for example, firms and
households need a long time to finance their business activities while the depositors
have right to withdraw money at any time. In case of time deposits, the depositors
are still allowed to withdraw money as long as they accept low or no interest rate.
Second, if banks attempt to manage the term of their loans, the borrowers still have
longer time in paying the debts. There is a temporary solution in which borrowers
could roll over their loans by borrowing the new to service the old ones in the same
bank. This action is not always allowed or even illegal, so it affects strongly and
negatively on profitability of the borrowers, which causes a decrease in credit
quality. This characteristic raises a problem that banks have to plan for their

additional reserves. These reserves are used to reduce the illiquidity which may
occur under the influence of adverse macroeconomic shocks.
Banks cannot evaluate exactly their borrowers in the expansionary phase of
the economy (3). Gavin and Hausmann (1996) indicated that “good times are bad
times for learning” about the truth of financial capacity of the borrowers. The
advantages of the economy may be one of the reasons of lending booms. The
borrowers could easily borrow money from a bank to service the debts in another
bank. Therefore, most of the borrowers appear in good state with banks although
their financial capacity may be different. In this case, banks have difficulty in
determining which loans may potentially become NPLs.
These characteristics above are to imply that the decision of boosting credit
growth should be considered carefully especially in the disadvantageous conditions
of macroeconomic environment. Banks have very high probability in the decline of
credit quality, which is the source of illiquidity as well as banking crisis.

5


2.1.2 Shock and Vulnerability of Banking System
The action of using mobilized money for lending requires a necessary
condition in which the growth rate of deposit liabilities is higher than the deposit
interest rate. However, if this condition does not hold, in principle, banks still have
a solution for this problem by calling their borrowers for paying their mature debts.
Actually, banks have limitations to do so because it depends too much on the ability
of the borrowers. Consequently, there would be a net resources transfer from
banking system to depositors in the form of withdrawal and interest. The large
amount of this net resources transfer will create a shock in the banking system. And
if this amount is large enough, the banking system would collapse, which create the
vulnerability (Gavin and Hausmann, 1996).
2.1.3 The Effect of Macroeconomic Determinants

The shock from large change in the net resources transfer may originate from
the changes of the economy. When there is a negative economic surprise from one
or some macroeconomic determinants, there would be two cases: (i) the borrowers
cannot service their debts due to the reduced efficiency in their business activities;
(ii) banks are limited to investing activities especially lending and become illiquid
due to the decline in deposit demand or increase in withdrawal. Both cases lead to
banking crisis in the form of insolvency. In the first case, credit quality decreases
and banks are not able to recover enough principal and interest to finance their
deposit liabilities. In the second case, banks hardly meet the demand of
withdrawals. These consequences may lead to potential financial vulnerability in the
future. However, if banks can boost their mobilizing activities, they would have a
source of liquidity for withdrawal demand of depositors. Besides, banks would have
more time to deal with their NPLs.

6


2.1.4 Credit Growth and Vulnerability of Banking System
As discussed above, the macroeconomic determinants do not have direct and
complete effect on the banking system. Their affect is mainly on the business
environment and the depositors’ behaviors. The core question is the reason why
banking system becomes too fragile to suffer from the negative changes of the
economy. It is easy to understand that borrowers’ business activities are strongly
influenced by these changes. If banks have very close relationship with their
borrowers, absolutely, they are also influenced. Rapid credit growth would be a
typical proxy for this close relationship. The more banks expand their loans, the
more they rely on their borrowers.
Boosting credit growth is closely related to the third characteristic of banks.
Once they recognized the good appearance in the ability of their borrowers, they are
willing to lend more. This creates a link between credit growth and the vulnerability

of the banking system. However, credit growth should be considered as a signal of
economic development than a cause of vulnerability. The next question is in what
circumstances credit growth performs its negative aspects. The answer would be
concerned about information problems.
Gavin and Hausmann (1996) believed that “…it is very difficult for bankers to
obtain information about the creditworthiness of borrowers” (p. 14). First, due to the
economic expansion, the borrowers can perform well on their capital and gain
positive cash flow. This would be an advantage opportunity to offer loans not only
for the existing customers but also new borrowers. Banks would have very limited
information about their new borrowers. Thus, the probability of misevaluating them
may be quite high, which causes potential decline in credit quality in the future.
Second, the plenty of loans supply during the economic expansion helps the
borrowers to approach more lenders. As stated above, banks offer the loans and the
borrowers use these loans as a source of paying debts in other banks. These loans
accidentally and adversely impact on other banks’ information, which create an
7


information externality in the credit market. This type of externality also leads to
credit misevaluation and potentially low credit quality.
Figure 2.1 summarizes the macroeconomic context for banking. The scope of
this research concentrates on the “lending” and “paying debts” direction in this
figure. The negative relationship of credit growth and credit quality might reflect
two situations. Firstly, the adverse shocks from macroeconomic determinants would
make business activities become inefficient, which obstructs the ability of paying
debts. Secondly, the good signals in the expansionary phase of the economy might
create information externalities for banks to evaluate their customers.
FIGURE 2.1 The macroeconomic context for banking
Depositors
Mobilizing

Principals
Lending interests

Long term

Paying debts

Flexible term

Banking system

Evaluating
customers

Withdrawals
Deposit interests

Information externality

Lending

Business activities

Borrowers

Macroeconomic effects

Source: Author’s summarization

8

Macroeconomic
determinants


2.2 CREDIT GROWTH AND CREDIT QUALITY THROUGH DIFFERENT SHIFTS
Theoretically, the nature of credit growth may not relate to its quality. It
means credit growth might not directly have any influence on the change in credit
quality. However, the amount of loans which banks decide to lend would depend
greatly on the performance of themselves and their customers. For instance, banks
underestimate the risk of their borrowers and are willing to lend more. Therefore,
the relationship of credit growth and credit quality might exist.
One of the earliest studies on the theoretical link between credit growth and
credit quality is present by Clair (1992). This link comes from banks lowering their
credit standards to attract more borrowers. This action may lead to low credit
quality in the future. Besides, when banks boost credit growth but they do not have
any appropriate strategies to administrate their borrowers’ loans usage. Credit
quality would decline.
Clair (1992) also indicated that credit growth may positively correlate to credit
quality during the recovery or expansion phases of the economy or the structural
changes in the financial markets – for example, reducing barriers between banks
and borrowers to expand credit growth and reduce credit risk through
diversification.
Keeton (1999) had developed a theory about different shifts to investigate the
effect of credit growth on credit quality. This study explained both negative and
positive relationship between credit growth and credit quality.
This relationship is firstly explained by a supply shift in the loan market. In
this research, supply shift means banks have decision on the willingness to lend
more and there are two ways for them to carry out. The first is to reduce the lending

rate of new loans and the second is to lower the credit standards of these loans. To
make lending become easier, banks would overestimate the value of collaterals of
the loans, accept to lend customers with low financial capacity or go through
9


projects of which cash–flow statement is not appraised carefully. These actions
lower the credit standards and put banks into a high chance of lending to the
borrowers with low credit– worthiness. The loans to these borrowers become low
quality credit.
Under the assumptions that banks reduce the lending rate as well as lower the
credit standards of customers, the occurrence of supply shift which boost credit
growth will tend to result in the low credit quality.
FIGURE 2.2 Supply shift
r e ሺzሻ

D

S1
S2

r1e

r1e

r2e

r2e

S1

D

S2
z2

z1

L1

L2

r e Expected rate of return from loans
z Measure of credit standards
L Total amount of loans
S Supply of loans from banks
D Demand of loans from the borrowers
Figure 2.2 presents how the supply shift has effect on total amount of lending
and the level of credit standards. In the left–hand side, the expected rate of return of
banks is a function of credit standards. This figure assumes that the credit–standard
could be measured in number z on the horizontal axis. The high value of z shows
that the borrowers are in good state of servicing debts, for example, they have high
value on their collaterals or their investment project is safe. Banks’ lending decision
10


is made basing on the expected rate of return from loans which is measured on the
vertical axis. This expected rate of return depends on both lending rate and debt
servicing capacity. Good borrowers would bring high expected rate of return for
banks and it might be the same as the lending rate. If there are any signs of not good

borrowers, the banks’ expected rate of return would be less than the lending rate.
From the side of credit standard, with each value of z, banks could derive a
maximum expected rate of return. This is reflected by the curve r e ሺzሻ. For a point
of any value of z, when the lending rate increases, the banks’ expected rate of return
will increase. However, the increase in the lending rate could not always raise the
expected rate of return, there would be a limit. For example, when the lending rate
increases, good borrowers still have enough financial capacity in their project to
repay for debts. If the lending rate increases more and more, the borrowers tend to
invest in riskier project with the expectation of higher return for repayment. These
borrowers might become inferior and banks’ expected rate of return could not
increase any more. Thus, the curve r e ሺzሻ in the left–hand diagram shows the
maximum expected rate of return. This curve is upward sloping because banks
expect to earn more return from the borrowers with better credit standards by
offering them high lending rate.
The curve r e ሺzሻ could also be analyzed from the side of expected rate return.
For any given value of r e , there would be a minimum credit standard level of the
borrowers. For example, at the equilibrium point in the loan market, banks will
expect for r1e . It is certain that banks could not give any credit to any borrowers with
lower than z1 because the expected rate of return will be less than r1e no matter how
high the lending rate is. All borrowers from z1 and higher could receive loan and
would be charged a lending rate which is high enough for bank to receive r1e . The
minimum level of credit standards would be a threshold for banks to decide whether
they lend or not. The higher the expected rate of return banks desire, the higher
threshold of credit standards they set to their customers.
11


The right–hand side of Figure 2.2 describes the loan market which determines
the banks’ expected rate of return. Banks are willing to lend more if their expected
rate of return from loans increases. Thus, the supply curve is upward sloping. For

the demand curve, it is downward sloping due to two reasons. Firstly, banks could
charge lending rate basing on their expected rate of returns. Higher lending rate may
bring higher return. However, the borrowers have to suffer high cost of capital and
they will borrow less. Secondly, the negative slope of the demand curve could be
explained through the left–hand diagram. When the expected rate of return of banks
increase, the threshold level of credit standard would be higher, then the number of
borrower who meets the credit standards would reduce.
The loan market is in the equilibrium when the bank loan supply equals to the
loan demand. Before the supply shift, the supply curve is S1S1. At the equilibrium,
banks’ expected rate of return is r1e and the total amount of loans is L1.
Let assume that banks desire to expand the total amount of loans which causes
the supply shift. To do this, banks have to firstly reduce their credit standards for
attracting more borrowers. On the right–hand diagram, the supple curve will shift to
the right from S1S1 to S2S2. The total lending would increase from L1 to L2. Then the
expected rate of return would decrease from r1e to r2e . It means banks do not require
such high rate of return. Therefore, they not only charge lower lending rate for good
borrowers but also reduce the credit standards threshold to approach more
borrowers. This decline in the credit standards is presented by the movement down
along the curve r e ሺzሻ. Once the credit standard declines, banks have to suffer more
borrowers with low capacity of servicing debts, which causes NPLs or low credit
quality. The whole progress could be describes in brief as follow:
𝐂𝐫𝐞𝐝𝐢𝐭 𝐬𝐭𝐚𝐧𝐝𝐚𝐫𝐝𝐬 ↓ → 𝐂𝐫𝐞𝐝𝐢𝐭 𝐠𝐫𝐨𝐰𝐭𝐡 ↑ → 𝐂𝐫𝐞𝐝𝐢𝐭 𝐪𝐮𝐚𝐥𝐢𝐭𝐲 ↓
HYPOTHESIS A: Credit growth might negatively associate with credit quality

12


Keeton (1999) also supposed that the expansion in lending which occurs not
by a supply shift may have positive effect on credit quality. There would be two
reasons. First, the source of loan expansion is caused by positive shift of the

borrowers’ demand. This positive demand shift may come from – for example, the
decision to change the capital structure of firms or projects in order to improve the
cash–flow. In this case, the borrowers’ repayment capacity might become better,
which improved the credit quality. Second, the source of loan expansion is still from
the positive demand shift but this shift come from the productivity of borrowers. It
could be called productivity shift. The case of productivity shift reflects favorable
conditions in the borrowers’ business activities, which boost credit growth first and
credit quality afterward.
For demand shift, under the consumption that increase in the borrowers’ loans
demand does not related to their goodness in financial capacity – for example,
requiring loans from banks to avoid high interest rate in the capital market or
restructuring capital to reach optimal leverage ratio, the demand shift which boost
credit growth will lead to high credit quality.
FIGURE 2.3 Demand shift
D2

r e ሺzሻ

S

D1
r2e

r2e

r1e

r1e

D2

S
z1

z2

D1
L1

L2

When banks face with the increase in loans demand, they will charge higher
lending rate and give more strict credit standards. However, this is still a good
13


choice for the borrowers to achieve their objectives of – for example, restructuring
capital. Therefore, the demand shift also raises the credit standards.
As can be seen in the right–hand diagram of Figure 2.3, the increase in the
loans demand shifts the curve D1D1 to the right, D2D2. The total amount of loans
increases from L1 to L2 and the expected rate of return raises from r1e to r2e .
However, this change does not have any influence on the curve r e ሺzሻ in the left–
hand diagram. Thus, the increase in expected rate of return also tightens the
minimum credit standards from z1 to z2. In other words, when the loans demands
increases, bank will expect more return by raising both lending rate and the
minimum credit standards. This action helps banks to avoid some bad borrowers
and the credit quality would be improved.
In a demand shift, banks do not often realize demand shift, they still keep the
lending rate and the threshold level of credit standards unchanged. There would be
more and more borrowers who meet the credit standards desire to borrow money.
Then, they realize the growth in demand and start to raise lending rate and tighten

credit standards. Lastly, the credit quality increases. Therefore, the process would
be as follow:
𝐂𝐫𝐞𝐝𝐢𝐭 𝐠𝐫𝐨𝐰𝐭𝐡 ↑ → 𝐂𝐫𝐞𝐝𝐢𝐭 𝐬𝐭𝐚𝐧𝐝𝐚𝐫𝐝𝐬 ↑ → 𝐂𝐫𝐞𝐝𝐢𝐭 𝐪𝐮𝐚𝐥𝐢𝐭𝐲 ↑
For productivity shift under the consumption that the increase in loans demand
comes from the favorable conditions in business activities of the borrowers.
Although the credit standards may decline in this case, boosting credit growth could
result in high credit quality.
When the productivity shift occurs – for example, firms have some
improvements in their technology, the input costs reduce or the economy is in good
condition, the borrowers will need more credit to operate their business or invest in
new projects. In this case, banks might believe that most borrowers would have
good opportunities in business and obtain more cash inflows to service debts. Thus,
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their attitude to credit standards may change negatively and riskily. It means banks
would expect higher rate of return than at the same level of credit standards or they
are willing to loosen the credit standards in order to earn the same expected rate of
return. Therefore, the curve r e ሺzሻ shifts to the left, which can be seen on the left–
hand diagram of Figure 2.4. On the one hand, this shift of the curve r e ሺzሻ could
attract more borrowers due to the decline in credit standards and on the other hand,
the productivity shift also increase the loans demand to meet the requirements of
business activities. This would bring a significant positive shift in loans demand. In
the right–hand side of Figure 2.4, total amount of loans will grow dramatically from
L1 from L2 and banks’ expected rate of return increase from r1e to r2e . Although
banks loosen their credit standards to accept more bad borrowers, these borrowers
are not certain to be really bad because they still experience benefits from
productivity shift. As a result, the credit quality is still improved. However, there
would be a possibility that banks still safely keep the curve r e ሺzሻ unchanged like
the demand shift case.

FIGURE 2.4 Productivity shift
r2e ሺzሻ

D2
r1e ሺzሻ

S

D1
r2e

r2e

r1e

r1e

D2
S
z2

D1
L1

z1

L2

As discussed above, productivity shift make banks loosen credit standards and
make borrowers demand large amount of loans. The question of whether the change

of credit standards or credit growth happens first would depend on who could

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realize the productivity shift first. Anyway, credit quality is improved lastly. The
process would be as follow:
𝐂𝐫𝐞𝐝𝐢𝐭 𝐠𝐫𝐨𝐰𝐭𝐡 ↑ ሺ𝐂𝐫𝐞𝐝𝐢𝐭 𝐬𝐭𝐚𝐧𝐝𝐚𝐫𝐝𝐬 ↓ 𝐨𝐫 ↑ሻ → 𝐂𝐫𝐞𝐝𝐢𝐭 𝐪𝐮𝐚𝐥𝐢𝐭𝐲 ↑
HYPOTHESIS B: Credit growth might positively associate with credit quality
TABLE 2.1
Type of shift

Change in credit standard, credit growth and credit quality
Order of change

H.A: Credit growth might negatively associate with credit quality
Supply shift

Credit standards ↓

Credit growth ↑

Credit quality ↓

H.B: Credit growth might positively associate with credit quality
Demand shift

Credit growth ↑

Standards ↑

Credit quality ↑

Productivity shift Credit growth ↑ ሺCredit standards ↓ or ↑ሻ Credit quality ↑

Table 2.1 summarizes the relationship between credit growth and credit
quality with the appearance of level of credit standards. Besides, the order of change
of different shifts is to confirm that a change in credit growth in the past may lead to
a change in credit quality in the future. This effect is not contemporaneous.
Figure 2.5 shows the position of different shifts in the macroeconomic context
for banking and they do not exist simultaneously. First, banks lower their credit
standard in evaluating customers to make a supply shift. Second, the demand of
capital from borrowers for improving their business activities would create a
demand shift. Finally, the advantages from macroeconomic determinants would
generate a productivity shift for business activities.

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