Macro determinants on non performing loans of commercial banks in vietnam

According to Louzis 2010, macroeconomic variables, especially the real GDP growth rate, unemployment rate have strong effects on the level of NPLs.. Nkusu 2011 determined the negative im

MINISTRY OF EDUCATION AND TRAINING THE STATE BANK OF VIETNAM

BANKING UNIVERSITY OF HO CHI MINH CITY

TRAN NGOC LOAN

MACRO DETERMINANTS ON NON-PERFORMING LOANS IN VIETNAM

UNDERGRADUATE THESIS MAJOR: FINANCE – BANKING

CODE: 7340201

HO CHI MINH CITY – 2018

MINISTRY OF EDUCATION AND TRAINING THE STATE BANK OF VIETNAM

BANKING UNIVERSITY OF HO CHI MINH CITY

TRAN NGOC LOAN

MACRO DETERMINANTS ON NON-PERFORMING LOANS IN VIETNAM

UNDERGRADUATE THESIS MAJOR: FINANCE – BANKING

CODE: 7340201

SUPERVISOR: MS NGUYEN THI MY HANH

HO CHI MINH CITY – 2018

ABSTRACT

The global economic history has witnessed many financial crises have stemmed from inefficient banking industry Hence, the banking sector can be seen as the most vital determinants of development and stability of the economy In recent years, the non-performing loan (NPL) problem of commercial banks in Vietnam has become increasingly serious, raising concerns about uncertainty surrounding the banking sector

in particular and the economy in general Many studies have found that NPLs are determined by internal (or bank-specific) factors and external (or macroeconomic) factors The research is carried out to investigate the macroeconomic determinants on NPLs of commercial banks in Vietnam from 2011 to 2016 Based on previous studies, this research is going to collect the potential external factors such as real GDP growth rate, inflation, unemployment and real interest rate Dynamic panel data estimation is employed to serve the purpose of this research Dataset includes 17 commercial banks during the period of 6 years from 2011 to 2016 The outcome reveals that unemployment rate, GDP and real interest rate have significant influences on NPLs while inflation rate and NPL in the previous year are found to be not relevant in the case of Vietnam

ACKNOWLEDGEMENT

First of all, I would like to express my very appreciation to my supervisor Ms Nguyen Thi My Hanh for her sincere comments, for her patient guidance and useful critiques of this work Also, I would like to thank all the members of staff at High quality department of Banking University, Ho Chi Minh City Without their assistance, this thesis would not be completed

In addition, I am very grateful to my family and friends for giving the biggest support and strength in difficult moments

AUTHOR’S DECLARATION

I hereby confirm that this thesis entitled: “Macro determinants on performing loans in Vietnam”, is my own work, and none of this work has been published before submission

non-Regards,

Tran Ngoc Loan

THESIS SUPERVISOR’S DECLARATION OF APPROVAL

I hereby confirm that I have supervised the undergraduate thesis of Ms Tran Ngoc Loan entitled: “Macro determinants on non-performing loans in Vietnam”

The above mentioned thesis is completed and can be submitted for public defense

Sincerely,

Ms Nguyen Thi My Hanh

TABLES OF CONTENTS

ABSTRACT i

ACKNOWLEDGEMENT ii

AUTHOR’S DECLARATION iii

THESIS SUPERVISOR’S DECLARATION OF APPROVAL iv

TABLES OF CONTENTS v

LIST OF ABBREVIATIONS viii

LIST OF TABLES ix

LIST OF FIGURE x

CHAPTER 1: INTRODUCTION 1

1.1 Banking sector in Vietnam 1

1.2 Background of the study 3

1.3 Research objectives 5

1.4 Research questions 5

1.5 Research subjects and scope 5

1.6 Research method 5

1.7 Significance of the study 6

1.8 Structure of the study 7

1.9 Conclusion 8

CHAPTER 2: LITERATURE REVIEW 9

2.1 Introduction 9

2.2 Theoretical Framework 9

2.2.1 Business cycle theory 9

2.2.2 Financial accelerator theory 10

2.2.3 Monetary policy transmission mechanism theory 10

2.2.4 Debt deflation theory 11

2.2.5 Inflation and loan default 12

2.3 Macro determinants of non-performing loans 13

2.3.1 Non-performing loans 13

2.3.2 GDP growth rate 17

2.3.3 Inflation 18

2.3.4 Unemployment Rate 19

2.3.5 Real interest rate 20

2.4 Empirical Review 20

2.5 Conclusion 28

CHAPTER 3: RESEARCH METHOD 29

3.1 Introduction 29

3.2 Research questions and hypotheses 29

3.2.1 Research questions 29

3.2.2 Research hypotheses 29

3.3 Model specification 31

3.4 Research method 32

3.5 Data collection 33

3.6 Conclusion 35

CHAPTER 4: FINDINGS AND DISCUSSION 36

4.1 Introduction 36

4.2 Overview of non-performing loans in Vietnam 36

4.3 Descriptive statistics 40

4.4 Estimation results 41

4.5 Tests of specification for panel data 43

4.6 Discussion 44

4.7 Conclusion 47

CHAPTER 5: CONCLUSION 49

5.1 Introduction 49

5.2 Conclusion 49

5.3 Policy implications 50

5.4 Limitations of the study 51

5.5 Suggestions for future research 51

REFERENCES 53

APPENDIX 1: LIST OF COMMERCIAL BANKS USED IN MODEL 57

APPENDIX 2: RESULTS OF MODEL FROM STATA 13 58

APPENDIX 3: MACRO VARIABLES USED IN MODEL 59

LIST OF ABBREVIATIONS

NFSC National Financial Supervision Commission

TTP Trans Pacific Strategic Economic Partnership

LIST OF TABLES

Table 2.1 Classification of debts under quantitative method 14

Table 2.2 Summary of literature review 27

Table 3.1 Summary of Variables under Study 33

Table 4.1 Summary of Descriptive Statistics 40

Table 4.2 Summary of Estimation Result 42

Table 4.3 Hansen & Arellano-Bond test 44

Table 4.4 Summary of findings 45

LIST OF FIGURE

Figure 4.1 Non-performing loan ratio of banking system from 2011 to 2016 37 Figure 4.2 Commercial Banks selling bad debts to VAMC in 2014 38

CHAPTER 1: INTRODUCTION

1.1 Banking sector in Vietnam

It can be denied that banking industry plays a vital role in the financial system

as well as the economy of any country Banks operates as intermediation function in that they collect money from those who have excess and lend it to others who need it for their investment Leading credit to borrowers is one mean by which banks contribute to the growth of a country Advancing credit facilities is a vital role of banking sector Besides, commercial banks also act as a channel to carry out the State Bank‟s monetary policy and the government‟s policies

Based on global economic history, most of economic crises such as Asian financial crisis in 1997 or global financial crisis in 2008 were consequence of poor and failed financial system Financial crisis in 1997 started from Thailand then spread to neighboring countries as a result of economic bubble and inefficient banking industry The global financial crisis in 2008 resulted from the collapse of Lehman Brother (1985 – 2008) in the United States (U.S) was an obvious evidence for the risk of a poor financial regulation Therefore, the banking sector can be seen as the most vital determinants of the development and stability of the economy

The good performance of banking sector will boost the growth of economy especially developing countries whiles its failures will put the whole economy in a potential crisis

In Vietnam, there are two tiers in banking sector The first one is the State Bank

of Vietnam (SBV) which is the main financial regulatory agency The second one consists of commercial banks, financial companies, credit co-operatives, people‟s credit funds and insurances companies The main activity driving banking system is commercial banks Vietnam‟s banking system has 46 commercial banks concluded: 4

state-owed banks; 31 stock commercial banks; 9 foreign banks and 2 venture banks.1

joint-Since established, banking system has changed in operations as well as policies

In the early of 2000s, it marked a great effort of Vietnam to open up its economy to the world such as the Bilateral Trade Agreement between Vietnam and the U.S in 2001 and Vietnam‟s successful participation in the World Trade Agreement (WTO) in 2007

In 2008, SBV for the first time allowed 100% foreign-owned bank to operate in Vietnam Before that, only branch offices of foreign banks or joint-venture banks are allowed in Vietnam In recent years, Vietnam‟s banking industry has shown a huge potential for foreign investment In particularly, the government put effort to reform banking system SBV suggested that merge and acquisition of loss making and incompetent banks would be necessary to improve efficiency within the industry By forcing incompetent banks to merge and acquire, SBV has increased exploitation of economies of scale and reduced burden on regulators The International Monetary Fund, the World Bank and other international financial organizations were assisting Vietnam in the implementation of financial reforms to help ensure stability and promote the effectiveness of the banking system in Vietnam In addition, trade agreements stimulating foreign ownership and investment is also a positive sign Vietnam has taken part in Trans Pacific Strategic Economic Partnership (TTP) and Free Trade Agreement with different countries Moreover, restructuring is to standardize banking system which will be compatible and accessible to other countries

Vietnam‟s banking sector began 2015 on a positive note, with Moody‟s having upgraded the financial system from “negative” to stable in mid-December According

to the credit-rating agency, the improvement reflected the “increased stability in the

1

operating environment for the banks, as well as in Vietnam‟s macroeconomic situation, and a reduction in liquidity stress in system”

1.2 Background of the study

In recent years, non-performing loans (NPLs) have been a great concern of Vietnam‟s economy in general and banking sector in particular According to financial experts, NPLs can be seen as “a clot of blood” clogging the economy The high rate of NPLs did not allow the growth of bank credit of Vietnam and this led to indirect impacts on implementation of the macroeconomic indicators Many countries have experienced having a large amount of NPLs in the banking system, which impacts their economic health

The period from 2011 to 2015 is considered as one of the most difficulties and challenges period of banking sector In the beginning of 2011, Vietnamese banking system faced a lot of problems which led to the chaotic and uncontrollable situation High lending interest rate (18 – 21%/year) made production difficult The volatility of exchange rate, gold price caused market instability In addition, liquidity stress frequently occurred Activities of commercial banks was risky and vulnerable Besides, small credit institutions affected negatively on the market

In Vietnam, the banking sector is struggling with NPLs which have negative impacts on their performances as well as the country‟s economic growth In 2011, NPL ratio was reported at 3.07% but this figure did not reflect the real level of NPLs In reality, NPL ratio reached over 10%, and even up to 17.43% The high levels of NPL also affected macroeconomic situation Inflation rate in 2012 jumped to double digits, causing negative real interest rate In 2014, the NPLs of Vietnamese banking system was 2.02%, ranked the fourth highest in ASEAN countries (higher than Singapore, Malaysia, and Cambodia) (Hao Thi Kim Do, Lam Khanh Chu & Phuong Minh Nguyen, 2017) However, this indicator did not reflect real NPL ratio In February

2014, Moody estimated that NPLs in the banking system was at least 15% of its total asset, more than three times SBV‟s official ratio of 4.7% at that moment Gene Fang, Moody‟s vice-president, said “Capital remains inadequate to absorb the extent of potential losses stemming from pervasive weaknesses in asset quality” At the same time, the agency kept “negative outlook” on Vietnam‟s banking system Although NPLs resolutions by government has made positive progress, outstanding and potential NPLs volume remain high, imposing risk on financial institutions‟ safety and efficiency (World Bank, 2017) It is suggested that the major concerns and challenges

in managing NPLs stem from global and domestic economic slumps such as commodity cycle downturns, delay in project implementation or banks‟ recognition of stressed assets and the inability to exit these

Many studies have shown that NPLs are determined by macroeconomic and banking specific factors According to Louzis (2010), macroeconomic variables, especially the real GDP growth rate, unemployment rate have strong effects on the level of NPLs Nkusu (2011) determined the negative impact of GDP on NPL ratio and positive influences of unemployment rate, inflation and real interest rate on NPLs.Then, the studies of Ahlem Salma Messai and Fathi Jouini (2013) and Prasana (2014) found the significant inverse relationship between growth rate in GDP and NPLs In addition, Prasana (2014) also showed the positive impact of inflation on NPLs The study of Nguyen Thi Hong Vinh (2015) gave the same result However, there are some studies showed different results of the relationship between macroeconomic factors and the level of NPLs

Because of the increasing NPLs in Vietnam, the author chooses the thesis topic

“Macro determinants on non-performing loans in Vietnam” The study will examine the effects of macroeconomic factors on NPL during the difficult period of Vietnam‟s

banking system 2011 – 2016 and suggest some recommendations for bank managers and policy makers

1.3 Research objectives

The main objective of this study is to determine whether macroeconomic factors influence on NPLs in Vietnam In particular, the study will find out how the four macroeconomic factors, i.e GDP growth, inflation, unemployment and real interest rate affect NPLs of Vietnamese commercial banks

1.4 Research questions

The fundamental question which the study attempt to answer is as follows:

To what extents do macroeconomic factors influence on NPLs in Vietnam?

1.5 Research subjects and scope

The main research subject in the study is non-performing loans in Vietnam This study will investigate NPLs in Vietnam from 2011 to 2016

1.6 Research method

Dynamic panel data approach is used to investigate the relationship between macroeconomic factors and NPLs in the Vietnamese banking system Although previous studies have shown that regression model like Ordinary Least Square (OLS) method, Fixed Effects Model (FEM) and Random Effects Model (REM) are used However, OLS estimation does not reflect the specific cross units Moreover, there are some problems such as heteroscedasticity, autocorrelation in model and OLS approach

is therefore not appropriate in this case As a result, the author will also use dynamic panel data with Generalized Moments of Method (GMM) to analyze data In addition, the author also checks the usual specification tests such as Hansen test and Arellano-Bond test

Data: The macroeconomic data are taken from the websites of the General Statistical Office (GSO), International Monetary Fund (IMF) and World Bank The data relating to NPLs are obtained and calculated from Vietnamese commercial banks‟ financial statements

1.7 Significance of the study

The banking system always has specific risks which can not be avoided According to Janvisloo (2013), the quality of loan could be one of the factors which limit the banks‟ loan supply and affect investment spending Due to the fact that banks play an important role in regulating of monetary policy, their performance is also influenced by economic conditions and fiscal policies In other words, macroeconomic variables impact on commercial banks‟ loan quality directly Financial crises in economic history are obvious evidences for the relationship between performance of banking system and macroeconomic environment Every country has different economic conditions as well as banking system Therefore, it is necessary to examine the potential macro determinants of NPLs in Vietnamese commercial banks These determinants include real GDP growth rate, inflation rate, unemployment rate and real interest rate

This study is important for banks and governments because it will inform about the effect of macroeconomic factors on NPLs The findings will enable managers and investors of financial institutions make decisions on reducing risks In addition, the State Bank can implement appropriate policies based on the economic changes in order

to ensure the stability and performance of banking sector Besides, the government plays a crucial role in regulating the economy Based on the results of this study, the government can implement appropriate policies and solutions for macroeconomic environment in order to ensure the development of the country as well as mitigate potential financial crisis in the future

1.8 Structure of the study

This section presents the structure of this study which includes five chapters as follows:

 Chapter 1 – Introduction

In this chapter, the research shows an overview of banking sector in Vietnam; rational of study; research objective; research subject and scope, research method and research significance

 Chapter 2 – Literature Review

This chapter provides a theoretical framework that explains how macroeconomic factors affect NPLs

 Chapter 3 – Research method

In this chapter, some hypotheses are proposed, and then a model is built up to describe how macroeconomic factors such as GDP, inflation, unemployment and interest rate affect NPL Next, it explains why GMM estimation is used and how data is collected

 Chapter 4 – Findings and Discussion

This chapter gives an overview of non-performing loan in Vietnam and discussing about findings

 Chapter 5 – Conclusions

This chapter sums up the main findings of the study Besides, the author discusses limitations of this study and suggests some new directions for future research

1.9 Conclusion

By revisiting the situation of commercial banks in Vietnam, this chapter reflects how non-performing loans impact on banking sector Therefore, it is crucial to examine the macroeconomic determinants of NPLs in Vietnam Also, this chapter gives an overview of the study so that readers can easily pick out the most information at a glance

CHAPTER 2: LITERATURE REVIEW

2.1 Introduction

This chapter mentions theories which related to non-performing loans as well as gives the concept of non-performing loans The author also presents definitions of explanatory variables used in this study By revisiting empirical literature, it is basic for author explains the knowledge gap and building hypotheses in the next chapter

2.2 Theoretical Framework

2.2.1 Business cycle theory

The relationship between loan quality and macroeconomic variables has been widely debated within the framework of business cycles by linking the boom and depression of business cycles with financial vulnerability and stability of the banking sector Modigliani and Miller (1967) developed the theory of economic cycle and consumption model It was said that in the period of economic growth, enterprises and individuals will be easier in payment of loans from commercial banks because of better investment opportunity and business prospect In contrast, when economic condition slows, agents will face more difficulties in business and use of loans, thereby making negative effects on repayment Supporting the same idea, Mileris (2014) stated that most of bank crisis theories are based on changes in economic fundamentals, and regard banking crises as a natural consequence of business cycles He developed the statistical model to predict the increase of doubtful and NPLs in the commercial banks when the stages of business cycle change

GDP growth is considered as an important macroeconomic determinant of the banks performance as well as a tool used to control business cycle fluctuations As the effect of economic changes mentioned above, it is expected the negative correlation between GDP growth and NPLs GDP growth can significantly influence the

borrowers‟ ability to repay loans as evidences suggest that higher GDP growth reduces NPLs ratio (Salas and Saurina (2002); Quagliarllo (2007); Khemraj and Pasha (2009))

2.2.2 Financial accelerator theory

The financial accelerator theory developed by Bernanke and Gertle (1995) explained that a small economic shock can have a large effect on lending and borrowing activities It relies on the interplay between economic agents‟ net worth and external finance premium which arises due to asymmetric information between lenders and borrowers Economic agents‟ net worth is defined as the sum of liquid assets collateral value of illiquid assets less outstanding obligations, external financial premium is defined as the difference between of the cost of funds raised externally and opportunity cost internal to the firm (Bernanke, Gertler and Gilchrist, 1999)

The theory argues that the less amount of borrowers‟ wealth contributed to the project, the more interest their interests will diverge from the interests of the supplier of external funds Borrowers were more wager to undertake riskier projects which have a high profitability of large return than those offering low returns From borrowers‟ perspectives, these projects are preferred since the firms‟ losses in the case when the projects‟ returns are low and limited to zero by legal regulation From lenders‟ perspectives, these projects are unfavorable since they bear all, or most of, the cost in the case of low project returns The theory indicates that because of economic shocks, the borrowers may not have the ability to borrow and are likely to avoid repayment of their loans

2.2.3 Monetary policy transmission mechanism theory

Monetary policy comprises the rules and actions adopted by the State Bank to achieve its objectives Monetary policy transmission mechanism changes macroeconomic factors (such as interest rate, inflation, exchange rate, unemployment, and etc.) which can affect the ability of borrowers to pay loans so it leads to the effects

on NPLs Miskin (2010) described monetary policy transmission mechanism was a process by which policy actions translated attainment and sustenance of policy objectives In more detail, the change in interest rate (or money supply) affects prices and productions in the economy The change in monetary leads to the changes in economic indicators such as interest rate, asset prices, expenditure, exchange rate and credit ability of commercial bank and then to price, production and unemployment According to traditional transmission mechanism, expansionary monetary policy reduces nominal interest The impact of monetary policy on macroeconomic indicators through traditional transmission mechanism was agreed by many experts Moreover, other indicators such as production, income and cash flow also influence on expenditure and consumption (Blinder and Maccini, 1991; Chirinko, 1993; Boldin, 1993)

According to Bernanke and Gertler (1995), channels of monetary do not operate independently but together the changes in monetary policies Therefore, it is vital to assess the impact of channels in monetary on credit growth in banking system Transmission channels of monetary policy such as interest channel, credit channel, asset price channel influence on the selection of antagonistic, moral hazard, investment activities and consumptions of borrowers, repayment ability as well as loan quality

2.2.4 Debt deflation theory

This theory was developed by Iriving Fisher following the Wall Stress Crash of

1929 and the ensuing Great Depression Deflation occurs when prices are falling in contrast to inflation which describes the rise in prices (Fisher, 1933)

Fisher‟s analysis is based on two fundamental principals, over-indebtedness and deflation This theory suggests that when the debt bubble burst the following chain of consequences in nine links: At first, agents seek to reduce indebtedness by „liquidating‟

debt, leading to (1) distress selling and (2) contraction of deposit because people

withdrawn money to pay debts These consequences caused (3) a fall in the level of

prices and (4) fall in the net worth of business, precipitating bankruptcies and (5) fall in profits Because of reduction in profits, business have to (6) reduce production, trade and employment of labor These losses, bankruptcies and unemployment lead to (7) Pessimism and loss of confidence, which in turn lead to (8) the demand of hoarding money The above eight changes cause (9) complicated disturbances in the rates of interest In particular, the nominal interest rate falls while the real interest rate rise

The complicated disturbances described above can be assumed as both external and internal forces (macro and micro factors) influencing state of over-indebtedness existing between debtors and creditors or both which can be compound to loan defaults

2.2.5 Inflation and loan default

Inflation is considered as a factor contributing to the performance of the banking sector According to Brownbridge (1998), the fluctuation of inflation would have had two important consequences for the loan quality Firstly, from the firms‟ perspective, high inflation increases the volatility of business profits because of its unpredictability nature Consequently, it entails a high degree of variability in the rates of increase of the prices of goods and services which make up the overall price index Therefore, the probability for firms making losses rises, as does the probability that they will earn windfall profits This decreases the ability of the firms to honour its debt obligations which leads to increase NPLs Secondly, high inflation makes banks have more difficulties in loan appraisal In more details, from consumers‟ perspective, the viability of potential borrowers depends upon unpredictable development in the overall rate of inflation, its individual components, exchange rates and interest rates The uncertainty in the behaviours of these variables puts enormous pressure on bank loan

offers Moreover, asset prices are also likely to be highly volatile under such conditions Hence, the future real value of loan security is also very uncertain

The higher inflation causes the increase of loan default It is explained by Brenda Midecha Imbuga (2014) that when the rate of inflation increases, the bank must cushion themselves from loss of value of their cash assets by seeking higher returns from loans Similarly, depositors expect higher returns on their deposits to retain the real value of their cash assets The expectation of depositors and lenders to cover the premium of inflation leads to rise of interest rate This raises the cost of loans and higher costs raise the risk of default Therefore, inflation and loan default have a positive correlation

2.3 Macro determinants of non-performing loans

In Vietnam, Decision No 493/2005/QD-NHNN of April 22, 2005 issued the regulation on the debts, provisioning and use of provisions against credit in the banking activity of credit institutions In Article 2, term 6, it was stated that “NPLs are debts, which have been classified as those in Groups 3, 4 and 5 stipulated in Article 6 or

Article 7 of this Regulation The ratio of NPLs to the total outstanding debt is used to assess the credit quality of credit institutions” Based on this Decision, Debts in Group

3 are debts which are overdue for a period of 90 to 180 days

The table 2.1 below shows classification of debt under quantitative method according to Circular No 02/2013/TT-NHNN dated 21/03/2013

Table 2.1 Classification of debts under quantitative method

Group 1(Current) Undue debts which, according to the Bank‟s

assessment, could be fully recovered, both principal and interest, when they fall due;

Debt which are overdue for less than 10 days and according to the Bank‟s assessment, both overdue principal and interest could be fully recovered in accordance with the remaining repayment schedule Group 2 (Special mentioned) Debts which are overdue from 10 days to 90 days;

First-time rescheduled debts which, according to the Bank‟s assessment, both principal and interest could

be fully recovered within the rescheduled term

Group 3 (Sub-standard) Debts which are overdue from 91 days to 180 days;

First-time restructured debts, except for the first time rescheduled debts which are classified in Group 2;

Debt of which interest was waived or reduced because customer was not able to fully repay interest in accordance with the repayment schedule;

Type of debts Definition

Debts which are recovered under inspections conclusions

Group 4 (Doubtful) Debts which are overdue from 181 days to 360

days;

First-time restructured debts which are overdue for less than 90 days within the restructured term; Second-time restructured debts;

Debts which must be recovered under inspection conclusions but fail to be repaid although recovery term was overdue for less than 60 days; … Group 5 (Bad) Debts which are overdue for more than 360 days;

First-time restructured debts which are overdue for more than 90 days within the restructured term; Second-time restructured debts which are overdue within the restructured term;

Debts which are restructured for the third times or more;

Frozen debts and debts which are awaiting resolution;

Debts which must be recovered under section conclusions but fail to be repaid although recovery term was overdue for more than 60 days;…

Source: Circular No 02/2013/TT-NHNN dated 21/03/2013

In general, the 90-day criterion is commonly – but not universally used in most

of banking systems in many countries A debt can be seen as a NPL based on two main factors: 90-day overdue and the ability of repayment

2.3.1.2 The impacts of non-performing loans on commercial banks

Banking sector has plays important role in economy of a country As a credit intermediation, it is a “bridge” between supply and demand monetary Therefore, the fluctuation of banking industry has some certain impacts on the whole banking system

as well as the development of economy In particularly, loan default affects commercial banks and economy

According to Rozina & Jewel (2017), banking system is dependent on liquidity, profitability and performance of the banks There are many researches investigating the linkage of NPLs and banks‟ financial performance (Karim and partners (2010); Kolapo and partners (2012); Klein (2013))

Berger & DeYoung (1997) stated that NPLs decreases cost efficiency The main profit of commercial banks gained from lending It is suggested that the increase of problem loans cause banks to increase spending on monitoring, working out, and/or selling off these loans Moreover, NPL ratio also effects bank capital, suggesting that decreases in bank capital ratios generally precede increases in NPLs for banks To sum

up, high level of NPL reduces banks capital because they can not recover NPLs and increasing cost to solve the problem loans Hence, the profit of commercial banks becomes lower

When NPL situation occurs frequently and continuously without solving precisely, it is said that commercial banks lost credibility in credit business Public may lose confidence from banks which leads to be a risk in banking system and economic growth

Non-performing loan is considered as one of determinants of liquidity risk (Muriithi, 2010) The higher loans growth had higher level of NPLs which exposed them to liquidity risk Liquidity problems if unchecked may adversely affect banks‟ profitability, capital and under extreme circumstances, it may cause the collapse of banks‟ solvent In addition, a bank having liquidity problems may experience difficulties in meeting demands of depositors

2.3.1.3 The impacts of non-performing loans on the economy

The ineffective NPLs solutions lead to higher NPLs ratio in balance sheet of banks which means commercial banks can not do lending transactions as well as companies and enterprises limit capital sources to conduct production and business activities If this situation lasts for a long period, it has a negative impact on economic development in the next years

Banking sector plays an important role in the economy of a country Therefore, the changes of banking system have an impact on economic growth In the financial history in the world, it is witnessed that a lot of banking collapse is one of reasons of financial crisis High non-performing loan ratio in commercial banks is the factor of banking collapse Evidences from banking crisis in the past demonstrate how influence

of NPLs on economic development

2.3.2 GDP growth rate

Gross Domestic Production (GDP) can be defined as the measurement of the total market value of the goods or services produced by the economy of a particular country as well as total income earned by the people living at that company

There are two types of GDP:

 Nominal GDP: refers to the aggregate market value of the economic output produced in a year with in the boundaries of the country In a

simple way, nominal GDP is GDP without the effect of inflation Nominal GDP is used when comparing different quarters of output within the same year

 Real GDP: refers to the value of economic output produced in a given period, adjusted according to the changes in the general price level It means GDP adjusted for inflation Real GDP is used in comparison in two or more financial years The growth of real GDP is a better indicator

of economic growth compared to nominal GDP

The growth of GDP implies that economy is performing well with the increase

of income of the people The rising income of borrowers indicates the ability to pay off loans

2.3.3 Inflation

Inflation is defined as a sustained increase in the general level of prices for goods and services in a country, and is measured as annual percentage change Under conditions of inflation, the prices of things rise overtime

There is no single theory for the cause of inflation that is universally agreed upon by economists and academics, but there are a few hypotheses that are commonly held:

 Demand-pull inflation: the increase of the demand for goods and services leads to bid up the prices

 Cost-push inflation: When the cost of production goes up, the companies need to increase prices to maintain their profit margins The cost of products can include wages, taxes or materials

 Monetary inflation: the oversupply of money in economy causes inflation The prices are determined by their supply and demand The oversupply leads to the downward trend of prices

There are several different measures of inflation in the world In general, all measures seek to show the annual change in living costs However, different measures

of inflation five different inflation figures There are two common measures of inflation, such as:

 Consumer Price Index (CPI) – a measure of price changes in consumer goods and services such as gasoline, food, clothing and automobiles The CPI measures price change from the perspective of the purchaser

 Producer Price Indexes (PPI) - A family of indexes that measure the average change over time in selling prices by domestic producers of goods and services PPIs measure price change from the perspective of the seller

2.3.4 Unemployment Rate

The unemployment rate is the share of the labor force that is jobless, expressed

as a percentage It is a lagging indicator, meaning that it generally rises or falls in the wake of changing economic conditions, rather than anticipating them When the economy is in poor shape and jobs are scarce, the unemployment rate can be expected

to rise When the economy is growing at a healthy rate and jobs are relatively plentiful,

it can be expected to fall

The unemployment rate is calculated by the number of unemployed people is divided by the number of people in the labor force, which consists of all employed and unemployed people The ratio is expressed as a percentage

In Vietnam, the definition of unemployed peopled is determined according to international standard include three elements: peopled age at least 15years old who have no jobs even a-hour of working, willing to work and seeking job

2.3.5 Real interest rate

A real interest rate is an interest rate that has been adjusted to remove the effect

of inflation to reflect the real cost of funds to the borrowers and real yield to lenders or

to investors The real interest rate of an investment is calculated as the amount of nominal interest rate subtracting inflation rate

Real interest rate is considered one of crucial tools in regulating monetary policy In the case of Vietnam, high level of real interest rate when the profit rate of investment activities remains at low level does not stimulate investment activities, especially in private sector Consequently, reduction in economic growth presses more burdens in stimulating the growth of capital in investment public sector which is ineffective because of deficit budget and public debt Real interest rate is frequently high in short term which encourages depositors while the demand of mobilizing capital

in mid and long term in banking system is high This leads to the unbalance between mobilization and lending in Vietnam banking industry

Therefore, high interest rate makes business activities of commercial banks face

to more difficulties and risk

2.4 Empirical Review

Existing studies investigated that NPLs were not affected by not only specific factors but also macroeconomic determinants Several studies from many countries found GDP growth rate as a significant variable explaining NPLs as follows:

bank-Salas and Saurina (2002) examined the loan losses of Spanish commercial and savings bank during the period 1985-1997, taking into account both macroeconomic

and individual bank level variables They found the negative association between NPL and real GDP growth

Fofack (2005) conducted the research the causes of NPLs in Sub-Saharan Africa between 1993 and 2002 The correlation and causality analysis focuses on a number of macroeconomic and microeconomic (banking-sector) variables The macroeconomic variables consisted of GDP per capital, inflation, real interest rates, changes in the real exchange rate, interest rate spread and broad money supply (M2) He found that the GDP per capital was one of the most significant macroeconomic variables This indicator has a negative sign The falling of GDP per capital had a tendency to increase the scope of default of loans In contrast, this study showed a positive relationship between real interest rate and NPL On the other hand, inflation does not a significantly explaining variable of NPLs

Quagliariello (2007) carried out his study to find the relationship between NPLs and business cycle He collected data of 207 Italian intermediaries from 1985 and 2002 then estimated both static and dynamic model The result showed that the change in economy impacted on loan losses In more detail, in the long run, GDP growth made new NPLs ratio decrease

Khemraj and Pasha (2009) studied the determinants of NPLs in the Guyanese banking sector This study analyzed the sensitivity of NPLs to macroeconomic and bank specific sector They estimated by using a fixed effect model on data of the period from 1994 to 2004 The macroeconomic variables concluded annual inflation rate, real effective exchange rate and annual growth in real GDP The findings from this study showed that GDP growth was inversely related to NPL Also, the finding indicated a significant positive association between the real interest rate variable and NPLs Otherwise, they also suggested a mixed relationship between inflation and NPLs In

more details, the variable had a negative impact on NPLs at time t but a positive

influence at time t-1 It was stated that the inflation variables were not statistically

significant in their regression model

Louzis (2010) examined the determinants of NPLs both macroeconomic and bank-specific variables in the Greek banking sector It utilized a panel data set comprising the 9 largest Greek banks from 2003 to 2009 on a quarterly basis The analysis was conducted in a disaggregated manner by classifying the banks‟ total loan portfolios into three main categories including mortgages, business and consumer loans The aim of dividing three types of loans was to detect possible similarities or differences in the determinants of each kind of portfolio Dynamic panel data methods estimated a strongly negative effect of the real GDP and positive effect of unemployment rate on the level of NPL

The research of Nkusu (2011) analyzed the link between NPLs and macroeconomic performance in advanced economies using two complementary approaches: panel regressions and a panel vector autoregressive (PVAR) model The sample covered annual data from 1998 to 2009 for a sample of 26 advanced economies 2

The list of macro variables included GDP growth, unemployment, change in house price index, change in the equity price index, inflation, the nominal effective exchange rate, policy rate of interest and credit to the private sector The findings indicated the adverse responses of GDP growth and NPLs In contrast, the positive effect of inflation, unemployment rate and policy interest rate on NPLs were confirmed in this study

The study of Mileris (2012) reported the macroeconomic determinants of loan portfolio credit risk in banks The data set of 22 EU countries for the period between

2

Australia (AUS), Austria (AUT), Belgium (BEL), Canada (CAN), Czech Republic (CZE), Denmark (DEN), Finland (FIN), France (FRA), Germany (GER), Greece (GRE), Iceland (ICL), Israel (ISR), Italy (ITA), Japan (JPN), Korea (KOR), Luxembourg (LUX), the Netherlands (NET), New Zealand (NZL), Norway (NOR), Portugal (POR), Singapore (SGP), Spain (SPA), Sweden (SWE), Switzerland (SWI), the United Kingdom (UK),

2007 and 2011 was analyzed by applying the logistic regression, factor analysis and probit methods From the result, inflation rate had a positive relationship with NPLs

Inekwe and Murumba (2013) evaluated the relationship between real GDP and NPLs in Nigeria banking industry from 1995 to 2009 The study made use of 15-year time series data on real GDP and NPLs and analyzing by using the Pearson Moment Correlation Coefficient (r) Like other countries, this paper showed a significant relationship between real GDP and NPLs However, the direction of relationship was contrary to other studies, which means an increase in real GDPs is accompanied by increase in NPLs in Nigeria in period of 15 years The author explained the findings due to the fact that credit facilities obtained from the banks were not properly utilized

in productive activities or it may be due to customers operating in a harsh economic environment

Ahlem Selma Messai and Fathi Jouni (2013) detected the determinants of NPLs for a sample of 85 banks in three countries (Italy, Greece and Spain) in the period from

2004 to 2008 Like existing literature, the results showed that GDP growth had a negative impact on NPLs On the other hand, it also confirmed a significant positive correlation between unemployment rate as well as real interest rate and the level of NPLs

Warue (2013) conducted a research to investigate the link between NPLs and bank-specific and macroeconomic factors in commercial banks in Kenya from 1995 to

2009 There were 7 macroeconomic variables included: real GDP, GDP per capital, lending interest rate, inflation, government expenditure, exports and imports, exchange rate The effects of macroeconomic variables on NPLs levels were tested by utilizing pooled and fixed effects panel analysis In both approaches, real GDP was found negatively and significantly related to NPLs performance in local banks and government banks However, the foreign banks in Kenya were not responsive to

changes in real GDP Otherwise, the linkage between inflation and NPLs was different

In more details, existing literatures showed the positive effect of inflation on NPLs while this study implied the negative impact of inflation on NPLs in government banks Local and foreign banks were not responsive to changes in inflation

Fawad and Taquadus (2013) investigated the explanatory power of macroeconomic variables as determinants of NPLs from 1990 to 2000 There were nine macroeconomic variables including GDP growth, unemployment rate, real interest rate, inflation, real effective exchange rate, consumer price index, exports, industrial production and foreign direct investment The findings confirmed the negative influences of GDP growth rate, inflation and real interest rate On the other hand, the impact of unemployment rate on NPLs was insignificant

Mwangi (2014) examined the effect of interest rates on NPL in commercial bank in Kenya The data set concluded 43 licensed commercial bank from 2009 to

2013 By analyzing from multiple linear regression with OLS method, explanatory variables such as real interest rate, interest rate spread, cost income ratio, total assets and capital adequacy were estimated While existing studies found a significant, positive relationship between NPLs and real interest rate, the outcome established significant, negative impact of real interest rate on the level of NPL

Prasanna (2014) investigated the determinants, especially macroeconomic factors of NPLs, in Indian Banking system Panel dataset of 31 Indian between 2000 and 2012 was estimated by using the random effects GLS model The result found GDP growth rate was the most influencing variables in determining level of non-performing assets Higher growth rates of economy reduced NPLs significantly In addition, the authors also found the significant positive impact of inflation and interest rate on the level of NPLs Rate of unemployment was found to have positive impact but was not significant hence it can not explain the changes in NPL in this case