The impact of loans to small and medium enterprises the case study of vietnam

LIST OF FIGURE Figure 2.1 Illustration of the impact of loan to SMEs………5 Figure 2.2 Optimal coordination of production factors when loan increases…….…6 Figure 3.1 Impact of loans to SMEs

UNIVERSITY OF ECONOMICS ERASMUS UNVERSITY ROTTERDAM

HO CHI MINH CITY INSTITUTE OF SOCIAL STUDIES

VIETNAM – NETHERLANDS PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS

THE IMPACT OF LOANS TO

SMALL AND MEDIUM ENTERPRISES:

THE CASE STUDY OF VIET NAM

By

BUI THI HONG CHINH

MASTER OF ARTS IN DEVELOPMENT ECONOMICS

Ho Chi Minh City, January 2018

UNIVERSITY OF ECONOMICS ERASMUS UNVERSITY ROTTERDAM

HO CHI MINH CITY INSTITUTE OF SOCIAL STUDIES

VIETNAM – NETHERLANDS PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS

ACKNOWLEDGEMENT

This process of writing a thesis is a collaborative experience involving the support and helps from many people I want to express my gratitude to those who give me the tremendous support to complete this thesis

First of all, I would like to thank gratefully to my supervisor Dr Nguyen Thi Thuy Linh I cannot finish my thesis if do not get the support and the advice from her

Beside that, I want to thank to Dr Pham Khanh Nam who give me many useful and important advice that help me very much through the time I do the thesis

Moreover, I want to thank Dr Truong Dang Thuy who helps me answer questions when I need it

And I want to thank the professors and the teacher staff of Viet Nam – erlands Program that gave many supports to me to have the knowledge, to solve the difficult problems in my studying process

Neth-Last, I want to thank my closet friends and my family

ABBREVIATIONS

SME Small and Medium Enterprise

RD Regression Discontinuity Design

PSM Propensity Score Matching Method

DD Difference in difference

VIF Variance inflation factor

IV Instrumental variable

HET Heteroscedasticity

SOE State Owned Enterprise

OECD Organization for Economic Co-operation and Development

DNNN State enterprises

NHNN State Bank

NHTM Commercial Bank

ABSTRACT

After a period of growth and affected by the crisis, Vietnam's economy has creased Hundreds of thousands of small and medium-sized enterprises went bank-rupt and shut down Loan is a solution for business to expand scale, increase sales and profits, but it can create jobs, increase salaries to improve social welfare or not?

de-To verify that argument, the author uses the PSM method and combines with DD on the SME data set from 2009 to 2013 to more accurately assess the impact of the loans

The results show that loans do not have the effect of improving employee comes, as well as creating more jobs In addition, the loans from informal sources with low cost do not help enterprises to expand their operations because of the small scale Loans from official sources are large scale, but the high costs overwhelm profits Moreover, the impact of formal loans also causes businesses to reduce their jobs The topic also shows other factors such as export, type of ownership, scale, production technique, entrepreneurial qualification that affects to employment and wage

in-TABLE OF CONTENTS

ACKNOWLEDGEMENT III ABBREVIATIONS IV ABSTRACT V

CHAPTER 1: INTRODUCTION 1

1.1 PROBLEM STATEMENT 1

1.2.1 Research objectives 2

1.2.2 Main research question 3

CHAPTER 2: LITERATURE REVIEW 4

2.1 REVIEW OF THEORY 4

2.1.1 Definition of small and medium enterprises and types of credits 4

2.1.2 The impact of loans to employee from producer theory 4

2.1.3 Factors affecting the operation of the business 8

2.2 REVIEW OF EMPIRICAL STUDIES 10

2.2.1 Impact of loan to SMEs in Viet Nam 10

2.2.2 Previous researches 12

2.3 SUMMARY 13

CHAPTER 3: RESEARCH METHODOLOGY 14

3.1 ANALYTICAL FRAMEWORK 14

3.2 ECONOMETRICS MODELS 15

3.2.1 Impact assessment methodology 15

3.2.2 Research proposal and select model 18

3.2.3 Dependent variables 21

3.2.4 Independent variables 21

3.3 DATA 24

CHAPTER 4: RESEARCH RESULTS 25

4.1 OVERVIEW OF THE RESEARCH TOPIC 25

4.2 DESCRIPTIVE STATISTICS 28

4.3 REGRESSION RESULTS 30

4.3.1 OLS regression results 30

4.3.2 PSM combined with DD results 32

4.3.3 Verification of model stability 41

4.4 DICUSSIONS 42

CHAPTER 5: CONCLUSIONS AND POLICY IMPLICATIONS 47

5.1 CONCLUSIONS 47

5.2 POLICY IMPLICATIONS 48

5.3 LIMITS OF THE STUDY 49

REFERENCES 50

APPENDICES 55

APPENDICES 1: DIVIDE THE SIZE OF THE BUSINESS 55

APPENDICES 2 INFLATION AND PRICE INDEX VND (1994=1) 56

APPENDICES 3 INFLATION AND PRICE INDEX VND (1994=1) (CONT) 56

APPENDICES 4 IMPACT ASSESSMENT BY MATHEMATICAL METHOD 57

APPENDICES 5 GROUPS WERE DEVIDED BY PSM METHOD 58

APPENDICES 6 REGRESSION DISCONTINUITY DESIGN - RD 59

APPENDICES 7 INSTRUMENTAL VARIABLE - IV 60

APPENDICES 8 DEFINITION OF SOME VARIABLES 61

APPENDICES 9 DESCRIPTIVE STATISTICS 62

APPENDICES 10 ANALYSIS OF CORRELATION BETWEEN QUANTITATIVE VARIABLES 64

LIST OF TABLE

TABLE 3.1 DESCRIPTION AND MEASUREMENT VARIABLES 22

TABLE 4.1 DATA STATISTICS 25

TABLE 4.2 STATISTICS DESCRIBE THE PARTICIPANTS AND THE CONTROL GROUPS BEFORE THE LOAN 28

TABLE 4.3 IMPACT OF LOAN TO SMALL AND MEDIUM ENTERPRISES- BASIC MODEL 31

TABLE 4.4 REGRESSION MODEL OF THE LOANS TO SME 32

TABLE 4.5 TREND POINT OF GENERAL SUPPORT AREA 34

TABLE 4.6 IMPACT OF LOANS TO SME ON THE LABOUR COSTS 35

TABLE 4.7 IMPACT OF LOANS TO SME ON THE NUMBER OF EMPLOYEES 37

TABLE 4.8 IMPACT OF EACH TYPE TO SME ON THE LABOUR COSTS 38

TABLE 4.9 IMPACT OF EACH TYPE TO SME ON THE NUMBER OF EMPLOYEES 40

TABLE 4.10 INVESTMENT AND LABOUR 42

TABLE 4.11 THE SCALE OF THE MOST IMPORTANT LOAN 43

LIST OF FIGURE

Figure 2.1 Illustration of the impact of loan to SMEs………5

Figure 2.2 Optimal coordination of production factors when loan increases…….…6

Figure 3.1 Impact of loans to SMEs when enterprises participate and do not join in loans……….…….15

Figure 3.2 Impact assessment by DD method……… … 18

Figure 3.3 Illustrate the general support area and the observation area discarded with PSM……… ……19

Figure 4.1 The supply of formal credit……….…26

Figure 4.2 The supply of informal credit……….27

Figure 4.3 The biggest difficulties prevent the development of SMEs………44

The giant state-owned corporations enjoy too many privileges but inefficient erations were restructured, foreign investment (FDI) has not restored as expected economy, cooperative economy is slow and efficiency is not much At this time, the SME is the most emphasis The SMEs bankrupt, dissolute too much to be explained

op-by the macro-economy, made SMEs difficult to search their market, difficult to cess to loans (VCCI, 2015) The dissolution of a series of enterprises affects the so-cial security issues such as GDP, consumption, unemployment, price indexes be-cause Vietnam has a large stock of human resources, of which SMEs account for

ac-96, 4% of the total number of enterprises in the country (ADB, 2014) By the end of

2013, Viet Nam had a total of 359,794 SMEs, accounting for 5.1 million workers, accounting for 46.8% of the nation's labor force (ADB, 2014) Vietnam needs more and more sustainable SMEs in a competitive environment To do that, the State needs appropriate support measures, first of all to exist, then to expand, thereby cre-

ating jobs and increasing laborers' incomes and solve the macroeconomics of the country

According to many economists, loan is very important problem, even the ing factor to support SMEs (ADB, 2014, Tran Hoang Ngan, 2015) Referring to SMEs, the first thing to mention is difficult access to credit and the need to remove barriers to accessing credit (Tran Dinh Thien et al., 2015) Many economists have traditionally believed that loan is the key to help SMEs better function The policies promulgated by the State such as the establishment of the SME Development Fund, the application of the ceiling lending interest rate, the expectation of SME devel-opment to increase incomes, create jobs for employees

lead-In fact, there is little research to quantify the impact of loans to SMEs by iment Moreover, the performance evaluation of SMEs does not clearly distinguish between growth and development The growth of SMEs is measured by the increase

exper-in revenue and profit The development of SMEs exper-involves equitable growth and tribution of results in a relatively fair way, which helps business owners and work-ers achieved benefit On the other hand, the development of SMEs is reflected in an increase in the wage index and employment This topic explores the impact of loan

dis-on the costs that an enterprise invests in employees and the impact dis-on their wages and employment from formal or informal loans; after that, provide appropriate poli-

cy recommendations for small and medium enterprises That is why the study titled

"Impact of loans to employee in small and medium enterprises" in order to clarify the issue: loan to employee in SMEs is the solution to social security, isn't it? On the other hand, the topic seeks the impact of loan on development through the wage index, employment at the enterprise micro level

1.2 Research objectives

1.2.1 Research objectives

This study determines the relationship between loans and number of employees, wages in small and medium enterprises From that, research offers the policy impli-cations to improve the activity of business

1.2.2 Main research question

Does the loan to SMEs impact on the labour costs?

Does the loan to SMEs impact on the number of employees?

Does the each type of credit to small and medium enterprises impact on the labour costs and the number of employees?

1.4 Structure of the thesis

This thesis consists of five main chapters Chapter one is introduction Chapter two

is literature review, including review of theory and review of empirical studies that related to the impact of loan to employee in SMEs Chapter three is research meth-odology; in this chapter will be present about analytical framework and the method-ology, variable measure, descriptive statistics to dataset Chapter four is research results, including overview of the research topic, descriptive statistics, results and dicussions Chapter five is conclusions and policy implications in addition that is limits of the study

CHAPTER 2: LITERATURE REVIEW

2.1 Review of theory

Chapter 2 presents theories concerning the impact of loan capital on labor in small and medium enterprises In Section 2.1 is Review of theory, which includes definitions and the impact of the factors seen from the manufacturer's theory Sec-tion 2.2 is a review of empirical studies, including Loans to SMEs in Viet Nam and other relevant studies Section 2.4 is summary of chapter 2

2.1.1 Definition of small and medium enterprises and types of credits

There are many ways to classify enterprise with the criteria related to the ber of full-time, part-time and non-permanent employees, World Bank definite about the scales of enterprises such as: microenterprises scale from 1 to 9 employ-ees; small businesses with 10 to 49 employees; medium-sized businesses with 50 to

num-299 employees; large enterprises with 300 employees or more In Viet Nam, there is distinction by industry Decree 90/2001/ND-CP and 56/2009/ND-CP said that small businesses from 10 to 200 employees, medium businesses with 200 to 300 employ-ees in all industries except trade and services (Appendice 1)

Capital (K) is understood as the inputs for production serves as machinery, equipment, land , or financial capital It is mobilized from various sources Ac-cording to this approach, capital and loan are understood to be identical

Formal credit is the credit that is provided by financial intermediaries who have the function of lending, mobilizing and lending in a clear and transparent manner

Informal credit is a credit that is provided by financial intermediaries who do not have the function of lending It exists mainly in the form of private loans with high interest rates and asymmetric information

2.1.2 The impact of loans to employee from producer theory

Loans do not directly develop businesses This financial source will be allocated through investment in inputs such as workshop, equipment, machinery, technology,

human resources, then expand production and business activity to increase sales, profitability and scale expansion (Nguyen Kim Anh et al, 2011) When businesses

invest resources, they will hire more labours, pay more wages (Figure 2.1)

Source: Nguyen Kim Anh et al (2011)

According to producer theory, enterprises operate on the principle of minimizing production costs When loans increased, that is described as follows:

Suppose the production function of enterprise is Q = f (K, L) with the output Q

Q is dependent on the inputs (capital K, labor L and other factors) The underlying assumption to producer theory is the minimum cost of inputs, denoted C The next

important assumption is the marginal productivity of capital (MPK= f

+ Many opportunities to invest

+ Increase Ability to invest + Increase investment by using better technology

+ Create opportunities to expand the small businesses

+ Diversification of economic activities + Enhance profitability from investment

+ Increase in income for workers + Increase Employment + Increase re-sources

Min C (K, L) = r*K + w*L (2.1) When output Q0 is unchanged:

Optimizing the amount of capital and labor input of business, K and L to mize (2.1) with constraints (2.2) Lagrange multiplier method is applied to solve the problem, Lagrange equations:

mini-Z = f (K, L) + λ (w*L + r*K - C) (2.3) Partial of Z to the variables K, L and λ is zero:



 , switch side r and w, to score (2.4): (2.5), we have:

K L

MP r

Figure 2.2 The optimal coordination of production factors when loan increases

Source: Simulation Pindyck, Robert S and Daniel L Rubinfeld (2013), Graph 7.8, page 253

With C0 initial resources, business rearchs maximize productivity at output Q0

with input K0 and L0

In the short term, the business is difficult to minimize costs because of the edness of capital elements So, when the capital increases, resources will be Credit + C0, production increases into Q1 credit, hiring more workers at L1

fix-In the long term, businesses will adjust both the K and L, so that the marginal cost per unit of production increased from the addition of one labour equals margin-

al cost per unit of production increased from the addition of one unit of capital From equation (2.7):

So, in the long term, the business can invest more capital at K2 and labour at L2, but the best situation: minimize the cost with optimal output is Q2credit

Theoretically, businesses will use the loan to expand their production by more investing in the number of employees; and with fixed wage, the cost of labour is higher From the theory above, the subject will focus on two hypotheses:

H1.1: Loans have a positive impact on the labour costs in SMEs

H1.2: Loans have a positive impact on the number of employees in SMEs

H2.1 Formal and informal credit have a positive impact on the labour costs in SMEs

H2.2 Formal and informal credit have a positive impact on the number of ees in SMEs

employ-2.1.3 Factors affecting the operation of the business

The subject of the study is the impact of loan to small and medium enterprise in Viet Nam, in other words, the causal relationship of the loan to the salary and em-ployment of SMEs based on the producer theory Businesses that take the initiative

to loan may be different from a business that does not actively loan to expand duction Without a loan, businesses will use capital more efficiently, but using more labour The number of employees and salaries are influenced by many other factors, and loan is just one of many factors The study identifies a number of factors that influence wages and employment, loan firms that have the potential to bias the im-pact of loans:

pro-Labour productivity: The economist said that the business want to increase ries for employees, they must increase labour productivity If labour productivity does not increase, but wages rise That will cause capital deficits because produc-tion costs increase

sala-Property: It is one of the most visible information about the business Business credit is limited by lack of collateral (Gertler and Gilchrist, 1991)

Years of business: In Vietnam, the age of a business influences the viability and development of that business (Hansen et al., 2009) Bentolila et al (2013) conclud-

ed that age affects labour in the enterprise Because businesses connect to many sources, including financial institutions Therefore, the ability to loan is easy than newly established enterprises

Ownership form: each type of business, salary policy and recruitment will be different Type of enterprise affecting the participation of preferential interest rate package (Dinh Tuan Minh et al., 2010) Foreign ownership influences the efficiency

as well as the ability of SMEs to join the international production network (Harvie, 2010)

Characteristics group of the industry: Each industry produces different products,

so the combination of capital and labor is different (Bentolila et al, 2013) The plex careers require skilled labor, and are highly paid High profit industries are more accessible to financial sources Different technological levels approach differ-ent credit guarantees (Oh, Inha, et al, 2009)

com-Market Size: The ups and downs of the macro economy affect the size of the business Enterprises operating in the export sector are more likely to have access to credit than in the domestic market (Dinh Tuan Minh et al., 2010)

Characterized group by size: Large firms that approach banks or formal cial institutions are easier than small businesses (Harvie, 2010) In Asia, companies depend on banks are mainly large companies (Claessens et al, 2000) Medium-sized firms have access to a much higher interest rate subsidy package than microenter-prises (Signore, 2015) Enterprise size is one of the factors affecting the business performance of Vietnamese enterprises (Ari Kokko and Fredrik Sjoholm, 2004; Hansen et al, 2009)

finan-Financial capacity: It is also considered by many economists to be characterized

by its size (Ramanathan, 2002).In a market economy, financial capacity is not only from own capital but also from loan sources So besides finance, loans also affect the employee in the business

Regional characteristics: Input and output markets for enterprises are as near as possible, the more accessible the business is, the less time and expense for the busi-ness Urban enterprises in the South have significantly higher investment probabili-ties than those in the North and rural enterprises (CIEM, 2014), but urban enterpris-

es are less likely to survive than rural (Hansen et al, 2009)

When studying SME, it is difficult to identify microenterprises with the teristics of a household (Hulme, 2000) Therefore, the characteristic of the business owner (sometimes also the household head) has an important role in all household business activities

charac-2.2 Review of empirical studies

2.2.1 Impact of loan to SMEs in Viet Nam

With market failures affect the operation of SMEs, the State needs to intervene

to help SMEs develop sustainably, create jobs for workers, increase wages and crease social welfare The reasons which for the State intervene in supporting SMEs were summarized by the World Bank in 2004:

in-Incomplete information: Information asymmetry makes the market failure and financial institution problems, hindering the development of SMEs The solu-tion is to improve institutions, improve financial markets, and provide direct financ-ing from government for SMEs to promote growth and development

Positive External: SME loan will help to improve competitiveness and preneurship The growth of SMEs makes the economy change about effectiveness and productivity, and increases in social welfare from the increased benefits of competition

entre-Poverty Reduction Tool: The rise of SMEs helps to promote employment more than the growth of large enterprises because of the more labor-intensive SMEs Therefore, the policies support SMEs to be linked to social welfare

The State of Viet Nam has many documents to support SMEs in financial opment The first legal document is Decree 90/2001/ND-CP, replacing Decree 56/2009/ND-CP After that, the Government established the SME Development Fund (Decision No 601/QD - TTg) in 2013 with a chartered capital of 2,000 VND billion Circular 13/2015/TT-BKHDT promulgates the list of priority areas for sup-port and criteria for selection of priority beneficiaries of the SME Development Fund In 2016, SME will receive a preferential interest rate of 5.5% for short-term loans and 7% for medium- and long-term loans, but the fund is not enough to sup-ply the needs of enterprises (Nguyen Xuan Thanh, 2016) That’s right! In total sys-tem, credit debt for SMEs is more than 977 trillion dong (State Bank, 2015) Ac-cording to the Ministry of Finance, credit debt of SMEs in the economy over the years about 25%

devel-State-owned commercial banks, foreign banks, joint ventures provide finance for SMEs at a moderate level The other funds come from donor organizations (World Bank, 2007) SOEs also loans, that makes the budget to SMEs less (Pham Chi Lan, 2016) Economic stimulus package in 2009 combined with the financial institution restructuring event in 2012 makes credit growth in 2009 and 2010 higher than 30% In this stimulus package, credit guarantees for SMEs accounted for about 29% (Dinh Tuan Minh et al, 2010; Tran Hoang Nhi, 2009)

In fact, SMEs have low official loaning rates They must satisfy many criteria, regulation, collateral assets, credit history from commercial banks (Phan Thi Linh, 2015) Therefore, businesses not only loan from commercial banks but also loan from other informal sources In Vietnam, informal loans are the main source of credit for SMEs, accounting for about 80 percent, and official loans account for 30 percent Small businesses mainly loan from non-bank sources such as internal funds

(savings, retained earnings, family networks) and the informal sector (money ing) (OECD, 2006)

lend-2.2.2 Previous researches

In terms of business, Wang (2013) uses panel data by collecting the dataset from

2010 to 2011 to look at the impact of microfinance on next year's performance, cluding net profit growth and revenue growth Data coverage was collected in Tai-zhou, Zhejiang Province, China His research shows that microfinance has played

in-an importin-ant role in the growth of revenue in-and profitability of SMEs But the tation of the article is the short time data, so it is impossible to study the impact of microfinance on the growth of employment and wages

limi-In terms of employees, Berger (1989) and Petersen (1994) argues that finance for SMEs tends to stabilize incomes rather than to increase, in other words,

micro-to maintain business activity and not create jobs Two other studies use random sampling on the effectiveness of corporate grants for similar results Micro-enterprise research, De Mel, McKenzie and Woodruff (2008b) conducted in Sri Lanka and McKenzie and Woodruff (2008) conducted in Mexico Random selected

a microenterprise group in each country that was funded from 100 USD to 200 USD The authors find evidence from grants that increase income for businesses, whether financed by cash or equipment, the same material gives the same results The results also show that one-time donors do not raise poor people's income be-cause the role of business owners is no longer important On the other hand, grants

do not increase the income of self-employed women

In Italy, Europe, Adorno V and Dg (2007) assessed the impact of subsidy policy under Law No 488/1992 by nonparametric method and compared it with the con-ventional parameter method (DD), data from 1996 to 2000 Research used continu-ous variables The results show that the impact of the policy was positive, statisti-cally significant This means that companies that receive lower subsidies are 12 percent to 9 percent lower, the number of employees is 25 percent to 11 percent,

and fixed assets fall 25 percent and opposite The more capital is subsidized, the more policy is effective, and then the reduced marginal effectiveness Therefore, additional subsidies are not highly effective

In addition, Signore and Pierfederico Asdrubali (2015) combined PSM and DD methodology to assess the impact of credit on SMEs in the Middle East Dataset collected from 2005 to 2012 Research shows that the youngest and smallest SME groups were the most beneficiary And the loan increased labor by 17.3% in the first five years In the sixth year, sales increased 19.6% However, SMEs limited in allo-cating resources when they creased in short term loans, effectively being solved in the medium term

With 9890 businesses from PCI survey, in where 3225 businesses received a 4% interest rate subsidy In Viet Nam, Dinh Tuan Minh et al (2010) studied the effect

of interest rate support policy on enterprises' operations The results showed that interest rate subsidy package had had a positive impact on labor change, but very little, only few workers Enterprises used this capital to expand short-term produc-tion by hiring more labor than investing in machinery and equipment for long-term production The support was suitable for medium enterprises and mining compa-nies Limitations were cross-data, so the author used two multiple regression meth-ods and PSM only evaluates the impact at the time of the survey

2.3 Summary

The impact of loan to small and medium enterprises has many different results Basing on the assumption that people are rational at the marginal point, firms will use the loan to invest in the resources which they use the most profitable For de-veloped and developing countries, or in the short and long run, the marginal utility

of the plant, equipment and labour are different They occur the different impact of loan to employee Enterprises can use loans to invest in labour or invest in equip-ment, workshops, technology to expand production It is even possible to use loans

to invest in other resources not for production

CHAPTER 3: RESEARCH METHODOLOGY

This section presents quantitative methods for assessing the impact of loan capital and the proposed model Section 3.1 says about analytical framework Section 3.2 presents the proposed model, including two models for the two implementation steps, the variables used for the model Section 3.3 describes the data used for the model

- LABOUR COST

Loan

(formal and

informal)

- The impact of loans

- Age of business owner

- The sex of business owner

…

- Qualification of business owner

3.2 Econometrics models

3.2.1 Impact assessment methodology

The study estimates the impact of loan to employee The nature of the impact

as-sessment is to see the difference in output after intervention, relative to output in the

absence of intervention

Figure 3.1 Impact of loans on SMEs when enterprises participate and do not

join in loans

In practice, it is not possible to observe the case of no intervention Therefore, it

is necessary to create a group that is close to the participant group, called the control

group and not affected by the program

Since the selection variable is not random, it leads to error in sampling, with

un-observable characteristics affecting output and un-observable characteristics affecting

the outcome or eligibility of the loan Therefore, the objective of the impact

assess-ment will be to eliminate the impact of sample selection or to find the appropriate

method for treatment Common methods in impact assessment studies:

Source: Acevedo and Tan (2011) Figure 1.1, Page 3

Time

3.2.1.1 Random sampling, multivariate regression model estimation

By using multivariate regression analysis, the policy variable is one of the factors influencing the output The regression models commonly used are:

Y = a1 + a2X2i + a3X3i + +akXki + ak+1Tki+1 + ui (3.1)

With a1 is the root coordinates,, the average value of Y when the

a2X2i = a3X3i = = akXki = 0

ai is the individual regression coefficients

ui is estimated residuals, with expectation 0 and finite variance

Ti is a policy variable, usually using as a binary variable, the value is 1 if the ithobservation has participated in the program The value is 0 if the ith observation does not participate in the program Policy variables can be continuous treatment

Y is the dependent variable That is the output which the research wants to know how the outcome have been affected when participating to loan

Xi (i=2…k) is ith independent variable That is the observable characteristics of the business

Regression to control the differentiation of these observations affect output, so coefficients ak+1 is impact of joining to loan This method is often used in terms of data at a time The above regression can not show the impact of policy involvement not related to the different characteristics that affect the dependent variable This method strongly assumes the form of regression and may be endogenous So applying linear regression will often be inaccurate in estimating the impact of the policy

3.2.1.2 Propensity Score Matching Method (PSM)

PSM is the method used to evaluate the impact of a trend point Assuming that after controlling the difference of observations, the result of participating groups is the same of the control group in the absence of intervention First, regression of the

probability model to calculate the Pi probability of the ith enterprise participating in the loan Khandker (2010) and Rubin (1983) prove that the comparison on P (X) is also approximated on X under certain assumptions The equation is as follows:

ed - TOT, written in the form of mathematics as follows:

regres-3.2.1.3 Difference in Difference Method (DD)

The difference in difference method compares the impact and control groups based

on differences in the results for each observation period Original survey on both non-participants and participants, then investigated both groups after the impact of loan From there, we calculated the difference between the median results which observed in the intervention and control groups before and after the program im-pact This method has a parallel assumption: If no policy is involved then the results

of the two groups are equal

The picture below (Figure 3.2) means (Y3 – Y2) = (Y1 – Y0) Equation DD = (Y4 –

Y0) - (Y2 – Y1), so by the parallel assumption, the result of the policy effect DD = (Y4 – Y3)

Figure 3.2: Impact assessment by DD method

The advantage of DD is that it eliminates sampling errors and lowers costs But if before the intervention, the trend of the two groups was different, the sam-pling error may not be constant over time as assumed by the DD

3.2.2 Research proposal and select model

The topic combines PSM with DD method to more accurately compare trol and participation units This combination can calculate the effect of observed and unobserved traits under the condition that the parallel hypothesis exists For general data, the on-line linear equation DD calculates the median difference in the outputs between participants i and non-join j belonging to the general support area:

Before intervention After intervention

Source: Ruiz and Love (2012) Figure 4, page 23

Intervention Output

First, we will prepare the regression of a probability function that calculates the ability of participants of each enterprise based on pre-programmed features Then remove observations that are not in the general support area (Figure 3.3) This step removes the second kind of deviation from the observable characteristics of the business

Figure 3.3: Illustrates the general support area and the observation area

dis-carded with PSM

The next step, regression based on table data by DD method combines POOL-OLS over time, to calculate the effect of the program This step removes the first type of error caused by the unobserved characteristics of the business At this stage, the proposed econometric model is:

Yit = β0 + β1Time + β2Treat + β3Treat*Time + β4Zit + εit (3.6)

Yit is the output (the income, the number of employees ) of enterprise ith at time T

Density Business participates

Source: Khandker et al (2010), Figure 4.1, page 59

The area of ing observations Trend Point

remov-Treat=1 : Businesses participate to loan

Treat=0 : Businesses depend the control groups

Time=0 : Pre-program time is the end of 2008 in the research paper

Time=1 : Post-program time is the end of 2012 in the research paper

Treat*Time : Interactive variables of Treat and Time dummy variables

Zit are control variables, bearing the characteristics of the business

The OSL regression will result in the following:

 : The difference between the two groups is created by the impact of the loan

Here, Time is dummy variable, using to impact assessment of begin and end gram between control group and participating group It receives the value “1” if the time of survey was in 2012, and thevalue is “0” if time of survey is 2008

pro-3.2.3 Dependent variables

LNWAGE: natural loragit (1 + wageit) with wageit is the total average cost (thousand) which ith enterprises in t year to expend for employee (including salaries, bonuses, allowances, labor outsourcing ) And other labor costs (social insurance, training, hiring .) This cost is the real cost, in other words is already eliminated inflation over the years, the base year is 1994 The price index of the year based on information about the inflation of financial announcements, as well as combined calculated from CIEM (Appendices 2, Appendices 3) In addition, businesses that

do not pay wages (self-employed, self-employed, etc) should contain a value of 0 Plus 1 to ensure mathematically but do not make distortions to cost Using the logarit of the dependent variable to explain the economic significance as a percentage

lnLABOR: natural logarit of the total number of employees in the enterprise including permanent employees and seasonal workers Regardless of regular workers were full-time and part-time (as individuals working under 20 hours a week, or only 5 to 20 days a month) or get paid and unpaid (form self-employed) are not excluded Calculate the time taken at the end of the business year, summarized in the accounting of economic accounts

3.2.4 Independent variables

The study uses DD combination PSM, so some features may be used for both steps But in each step you can use a number of separate variables to increase the fit for each model

A number of studies have used the observed characteristics of enterprises to ate the ability to receive financial loans Dinh Tuan Minh et al (2010) showed char-acteristics of type of ownership Target market is decisive for participating in the interest rate support program X Wang (2013) points out that product innovation, as well as managerial attitudes and competencies, labor productivity, past credit histo-

evalu-ry, retention rates on image revenue affects the ability to receive microfinance The

World Bank (2007) argues that in Vietnam land ownership certificates have stricted SMEs access to credit Inha Oh et al (2009), some characteristics affected the ability to receive credit increases to a point then decreases such as turnover, age, enterprise size There are also other characteristics that affect fixed assets, labor productivity, R & D, ownership, and occupation

re-Some studies use enterprise observational characteristics to control labor effects: Bentolila et al, (2013) use size control variables (assets), age of enterprise, age of enterprise squared, provincial, sector, short-term bank debt, long-term bank debt

Pham and Lensink (2008) use household characteristics such as gender, marriage, ethnicity, education level.The following independent variables will be defined (Appendix 8) and put into use in the model to explain the dependent variable But in the process of regression, there are added or drawn variables as appropriate

Table 3.1 Description and measurement variable

+/-

Time Time variables

Dummy variable: the value is 1 if the time of survey was in 2012, recognized the value to

Dummy variable: the value is 1 if join to row of the official long-term loan before program and the value is 0 if not

bor-Dummy variable: the value is 1 if they ticipate in the official short-term loan pro-gram funds and the value is 0 if not

par-+

AGE Years of operations Years of operations since business was +/-

founded

MICRO Enterprises Scale1 Dummy variable: the value is 1 if

microen-terprises and the value is 0 if other - LNASSET corporate finance

Dummy variable: the value is 1 if the hold enterprise, the value is 0 if other - EXPORT Market Dummy variable: the value is 1 if the export,

OWN-LAND Land ownership

Dummy variable: the value is 1 if the land use rights, the value is 0 if there is no land use rights

+

HAND Production tool

Dummy variable: the value is 1 if only hand tools, the value is 0 if other -

HAge entrepreneurs age Measured in years, since business owners

Edu Academic level Dummy variable: the value is 1 if the high

school graduation, if the value is 0 if not +

lnNSLD Labour productivity Natural logarithm of output divided by the

Province Including 10 dummies representing 10

3.3 Data

Surveys conducted around August, from 2009 to 2013 Direct interviews in 2013 of about 2,461 non-state SMEs, operating in the processing sector (CIEM 2010, 2012 and 2014) Of these, a further 1,988 respondents were interviewed in 2011 The

2011 survey was similar to 2449 enterprises that had 1999 repeat from the 2009 survey It was conducted in 10 provinces and cities, including Ha Hai Phong, Ho Chi Minh City, Ha Tay2, Phu Tho, Nghe An, Quang Nam, Khanh Hoa, Lam Dong and Long An The sample in 10 provinces was selected based on two data sources from the General Statistics Office of Vietnam (GSO) Survey data includes both formal and informal household enterprises

The study focused on the surveyed enterprises in all three surveys, to conduct the study on the data table In addition, any business that actually engages in real credit

is considered to have a loan This step eliminates the "yes" to the question "does the business have a loan?" But the fact that it can’t be borrowed is not affected by the impact of the loan

Also due to some changes in the questions, there are some unobservable traits from

2009 to 2013, which is unfortunately a limitation of the data and accessibility of the author's data To apply the PSM and DD combination, the subject will select the pre-programmed features taken from the 2009 trend-scoring regression Credit pro-grams (policy variables) are businesses that are borrowing from August 2009 to August 2011 Therefore, when applying the DD method of pre-programmed eco-nomic account is the end of 2008, the economic account after the program is the end

of 2012

2 Ha Tay was incorporated into Hanoi in early 2009 However, in Ha Tay the data is still considered as a

CHAPTER 4: RESEARCH RESULTS

This section presents estimated results Section 4.1 is overview of the research

top-ic Section 4.2 shows descriptive statistics Section 4.3 the research offers sion results and Section 4.4 is the dicussion about causing of the effects of the loan

regres-4.1 Overview of the research topic

The topic uses dataset of CIEM from 2009 to 2013 with many statistic number which concerns to loans, labour, employment, investment, the problem of business The aim of paper is to seek the impact of loan to SMEs about employment and wages and analyze a few the other impacts

Table 4.1 Data Statistics

Unit: Business

08/2007-08/2009

08/2011

08/2009- 08/2013

08/2011-% Loans from formal creditors in total debt 46,02% 46,57% 40,92%

% Loans from non-debt formally in total debt 53,98% 53,43% 59,08%

% Qualified College, University 20,64% 24,05% 25,86%

Source: Author of calculations from SME 2009, 2011, 2013

For the proportion of credit sources: In the debt structure over time, the source

of loans from informal organizations increased from 53% to 59% Data differed from the OECD (2006) that informal loans typically about 70% - 80% of the SME debt structure in Vietnam This can be explained that SMEs have easily access to loans from formal sector

Leadership characteristics: the average age of business owners does not change much, about 45 - 46 years old Sample survey had trends with the owner of female (male drop from 65% to 59%) Educational attainment also changed in the sample, high school graduation from 59% to 70%, and college-level qualifications also in-creased from 20% to 25% Data was most of the Kinh-owned enterprise, fluctuate around 93% and little changed

Regional Characteristics: There has been a gradual improvement in tion over the years

transporta-Figure 4.1: The supply of formal credit

Data of enterprises about the source of formal credits interviewed, the majority

of commercial banks, accounting for 62% - 69% of the supply over the period While Enterprise Support Fund has limited credit facilities for manufacturing enter-

Social policy bank

Foreign bank

Private

equi-ty bank

State mercial Bank

com-prises, accounting for only 1.2% to 4.4% Private bank also provided loans ranging

from 11% to 17% The Social Policy Bank has tended to reduce its role in the

for-mal credit supply structure for enterprises, from 11% to 8% There is no significant

change in the structure of official capital supply

Figure 4.2: The supply of informal credit

When interviewed about sources of informal credits, most of them were from

relatives, relatives, who accounted for 60% - 67% of the supply This is followed by

other private sources, which are private credit institutions from 27% to 20%

Enter-prises also borrow from other enterEnter-prises with the proportion from 4% - 10% Other

Relatives, friends

Private