The relationship between financial constraint and SMEs total factor productivity

DECLARATION This is to certify that this thesis entitled “The relationship between financial constraint and SMEs total factor productivity”, which is submitted by me in fulfillment of th

By

HỒ BẢO TRÂN

MASTER OF ART IN DEVELOPMENT ECONOMICS

HO CHI MINH CITY, JANUARY 2016

By Hồ Bảo Trân

A Thesis Submitted in Partial Fulfillment of the Requirements for the Degree of

Master of Art in

Development Economics

Academic Supervisor Prof Dr Nguyễn Trọng Hoài

Ho Chi Minh City, January 2016

DECLARATION

This is to certify that this thesis entitled “The relationship between financial constraint and SMEs total factor productivity”, which is submitted by me in fulfillment of the requirements for the degree of Master of Art in Development Economic to the Vietnam – The Netherlands Programme

The thesis constitutes only my original work and due supervision and acknowledgement have been made in the text to all materials used.”

Hồ Bảo Trân

I would like to acknowledge all the lecturers at the Vietnam – Netherlands Programme for their knowledge of all the courses, during the time I studied at the programmme In particular, I am grateful to Dr Tran Tien Khai, Dr Pham Khanh Nam, and Dr Truong Dang Thuy for their valuable comments and suggestions for

my concept note, thesis research design as well as in the thesis writing process

Next, I would like express my thank you to all my friends at VNP They have spent time learning and sharing memorable moments with me

Finally, I dedicate my thesis to my parents and my sister, who always love, take care and support me

ABBREVIATIONS

CIEM: Central Institute for economic management GSO: General Statistic Office of Vietnam

R&D: Research and development

SMEs: Small and medium enterprises

TFP : Total factor productivity

UK: The United Kingdom

ABSTRACT

Using panel data from Vietnamese Small and Medium Enterprises Survey from 2004 to 2010, this study aims to examine the relationship between financial constraint and firm total factor productivity of small and medium enterprises (SMEs) in Vietnam To achieve this objective, this study measures the total factor productivity of the SMEs Then, this study identifies the relationship between financial constraint and total factor productivity of SMEs Levinson-Petrin approach

is used in order to calculate the total factor productivity of firm in the first step In the second step, an estimation model is built to examine the linkage between financial constraint and firm total factor productivity The research finds that there

is relationship between financial constraint and firm productivity For example, the relationship between firm leverage and total factor productivity of firm is positive

It means that access to large external finance can help a firm ease the degree of credit constraints, thereby increasing its capacity and survival in the market.Secondly, liquidity ratio does not have significant impact on firm productivity in Vietnam Thirdly, firm size and firm age have positive relationship with firm productivity In other word, firms with larger size and older will have higher productivity Finally, firms join in export activities are found to get higher productivity than the others

TABLE OF CONTENTS

Chapter 1: INTRODUCTION 1

1.1 Problem statement: 1

1.2 Research objective: 2

1.4 Research questions: 3

1.5 Scope of the study: 3

1.6 The structure of the study: 3

Chapter 2: LITERATURE REVIEW 4

2.1 Productivity: Concepts and measurements 4

2.2 Financial constraint and firm productivity 5

2.2.1 Financial constraint definition 5

2.2.3 Financial constraint and firm’s productivity 6

2.2.4 Factors impact productivity 10

2.2.5 Conceptual framework 12

CHAPTER 3: RESEARCH METHODOLOGY AND DATA 14

3.1 An overview of SMES in Vietnam 14

3.2 Model specification 18

3.3 Research hypotheses and concept measurements 20

3.3.1 Research hypotheses: 20

3.3.2 Measurement of variables 20

3.4 Data collection 21

3.5 Estimation methodology 22

CHAPTER 4: EMPIRICAL RESULT 24

4.1 Total factor productivity of SMES 24

4.1.1 Data descriptions 24

4.1.2 Total factor productivity of SMEs in Vietnam 25

4.2 The relationship between financial development and total factor productivity 26

4.2.1 Data description 26

4.2.2 Regression result 29

Chapter 5: CONCLUSION 32

5.1 Main finding: 32

5.2 Policy implications 33

5.3 Limitations and further research 34

REFERENCES 35

APPENDIX 39

LIST OF TABLES

Table 3.1: Definition of SMEs in Vietnam 14

Table 3.2: Concepts and measurements of variables in the study 21

Table 4.1: Descriptive statistic of production factor variables 24

Table 4.2: Levinsohn-Petrin Estimation of Production Technology 26

Table 4.3: Summary of Statistics 26

Table 4.4: The correlation matrix of Structural variables 28

Table 4.5.1: Regression result 29

Table 4.5.2: Regression result 30

LIST OF FIGURES

Figure 2.1 Conceptual framework 12

Figure 3.1: Number of Small, Medium and Large Enterprises by Size of Capital resources 16

Figure 3.2: Number of Large, Medium and Small Enterprises by Size of Employees 17

Figure 4.1: A Fitted Plot of Total Factor Productivity versus Financial Indicators 27

Chapter 1: INTRODUCTION

1.1 Problem statement:

The importance of financial development in raising productivity and promoting economic growth has been discussed in many reports (e.g., Goldsmith 1969; McKinnon 1973; Greenwood and Jovanovic 1990; Bencivenga and Smith 1991) The financial system pressure handicaps financial development and results in misallocation of resources, then reduce productivity and economic growth As the financial systems develop well, overall economic productivity will be improved through the efficient reallocation of resources At firm level, financial development

of a firm allows a firm to appropriate new business opportunities, conduct investment and research activities, make a defense against financial and non-financial shocks and achieve higher productivity More importantly, firm productivity is an essential indicator in transforming financial market development

to economic growth at macro level

Financial constraints are prevalent problems that firms have to face in most developing countries, where finance resources are inadequate and financial institutions are underdeveloped According to the investment climate surveys of the World Bank, including more than 26,000 firms in 53 developing countries, Hallward-Driemeier and Smith (2005) found that the cost and access to external finance was regarded as one of the top 5 problems that firms faced The operation of financial market and the availability of credit influence the performance of firms It prevents firms from funding all desired investments Levine (2005), Beck et al (2005) point out that financial constraints, including low liquid and limited access to financial resources, make the growth prospect of firms worse Using a large panel data of firms in 47 developing countries, Ayyari et al (2007) indicated that external finance increased innovation significantly Similarly, Gatti and Love (2008) found that access to credit had a positive effect on TFP in Bulgaria

In Vietnam, manufacturing firms play an important role in the decade of economic growth In 2014, there are nearly 70,000 businesses closed There are many reasons such as long loss profit, management capacity, operating restrictions and lack of funds business… In which, financial market development offers a crucial impetus for enhancing firm competitiveness and catalyzing industrialization

As mentioned above, financial constraints are a prevailing problem facing firms in developing countries where capital is scarce and financial institutions are underdeveloped The research of Minjia Chen (2010), Badia et al (2008) suggested that financial constraints have significant effect on productivity in China and Estonia

In Vietnam, the scientific research using a panel data to find out the link between financial constraints and total factor productivity of Vietnam’s manufacturing sector is limited This study will present the evidence of this linkage using the panel data for manufacturing firms from 2004 to 2010

1.2 Research objective:

The study aims to examine the linkage between financial constraint and firm productivity of SMEs in Vietnam Therefore, it has three main objectives, which can be stated as following:

 To estimate the total factor productivity of SMEs in Vietnam

 To find the relationship between financial constraint and total factor productivity of SMEs in Vietnam

 To give policy implication for improving firm productivity through financial constraint

1.4 Research questions:

The main research question this study aims to answer is:

1 Is there any relationship between financial constraint and productivity of SMEs in Vietnam?

2 What are the policy implications to improve the productivity of SMEs?

1.5 Scope of the study:

The study will examine the link between financial constraint and total factor productivity of SMEs in Vietnam using the panel data of 2004, 2006, 2008, 2010

1.6 The structure of the study:

This study contains 5 main chapters, which are constructed by following: Chapter 2 reviews the literature as well as empirical study about the relationship between financial constraint and firm productivity It begins with the definition of productivity and its measurement Then, the linkage between financial constraint and firm productivity at firm level is discussed Chapter 3 presents the methodology and data This chapter provides an overview about SMEs in Vietnam, conceptual framework and model specification Chapter 4 provides the empirical result Finally, chapter 5 concludes the main finding, limitation and further researches

Chapter 2: LITERATURE REVIEW

This chapter will review the literature about the relationship between financial constraint and total factor productivity Initially, the concept of total factor productivity is introduced Then, the empirical studies of the impact of financial constraint and other factors on total factor productivity are examined Finally, the conceptual framework is presented

2.1 Productivity: Concepts and measurements

Productivity is normally defined as a ratio of the output volume to the input volume In other words, it measures how much of output is acquired from a given level of inputs

Productivity = Quantity of outputs produced/ Quantity of inputs consumed Productivity measurement efforts to point out improvements in using the capital resources, that is, to motivate and evaluate efforts to produce more outputs with fewer inputs while maintaining quality

Total Factor Productivity (TFP) is the fraction of output, which not explained

by the amount of inputs used in production process Thus, its level is defined by the efficiency of inputs used in production process

Total Factor Productivity (TFP) is normally defined as the contribution of

‘third factor” input other than capital and labour input The third factor is normally refer to factors including the improvement of technology and knowledge, innovation, superior management technique, as well as workers education, skills and experience

Total factor productivity cannot be measured directly Instead, it is a residual which accounts for effects on total output not caused by inputs In the Cobb-Douglas production function, total factor productivity is captured by the variable A

Consider the simple Cobb-Douglas function:

Y = ALα Kβ , α + β = 1

Y is total aggregate output

L is an index of aggregate labour input

K is an index of aggregate capital input

A is an index of aggregate of technology or called total factor productivity

α and β are the output elasticities of labor and capital, respectively

The TFP index is calculated by diving both sides of production function by LαKβ

TFP = A = Y/Lα Kβ

2.2 Financial constraint and firm productivity

2.2.1 Financial constraint definition

“Financial constraints” means that obstacles prevent firms from funding profitable investment projects This barrier can come from credit constraints, dependence on bank loans, incapability to issue equity, or illiquidity assets

Financial constraints caused by information asymmetries and agency problems have been well demonstrated by literature to affect firm’s activities, including fixed investment, inventories, employment, and wages (e.g Benito and Hernando, 2007; Nickell and Nicolitsas, 1999) Firms facing financial constraints have difficulties in raising external finance Due to the pecking order of financing costs (Myers and Majluf, 1984) financially constrained firms have to mainly rely on their own internal finance and pay premium to obtain debt and, less likely, equity finance Therefore, they cannot choose their optimal capital structure and consequently cannot make optimal decisions on other real activities Financially constrained firms may have to forego profitable investment opportunities when they are short of funds This certainly distorts the efficient allocation of resources and reduces firm’s efficiency and productivity Further, if firms want to improve productivity by carrying out research and development activities, without a supportive financial system, they will find it extremely difficult to finance the highly risky research and development projects due to the classical concerns of external lenders

2.2.3 Financial constraint and firm’s productivity

Nickell and Nicolitsas (1999) used a panel data of UK’s firms to analyze the impact of increasing financial pressure, which is measured by borrowing ratio, on firm’s productivity, as well as employment and wage rises It found that financial pressure has a positive but small effect on productivity In their approach, TFP is measured by the logarithm of the output to capital and the model is estimated by using production function with financial variables Their results are consistent with the bankruptcy theory When financial pressure increases, bankruptcy risks intensify Firms’ managers and employees have strong motivation to reduce bankruptcy risks in order to keep their jobs Therefore, it is believed that they will increase their efforts to enhance productivity

Gatti and Love (2008) used data from a cross section of Bulgarian firms to estimate the impact of access to credit on productivity First, they estimate TFP in cross section of Bulgarian firms and then construct models to identify financial effects on firms’ productivity The explanatory are mainly dummies to indicate firm size, industry types, ownerships and other firm characteristic variables Their result suggests that access to credit to be strongly and positive associated with firms’ productivity

Badia and Slootmaekers (2008) gave evidence on the relationship between

financial constraints and firm’s productivity in case of Estonia Their estimation

methods combine two steps, a production function with financial variables and a process with an estimation TFP variables first and a model to estimate TFP second Their result shows that young and highly indebted firms tend to be more financially constrained A large number of firms show some degree of financial constraints, with firms in the primary sector are the most constrained However, financial constraints do not decrease firms’ productivity in most of sectors excepting R&D sector The negative impacts of financial constraints on productivity are remarkably large for R&D firms Their results are consistent with the argument that financial

development can enhance firms’ innovation, through which influence firms’ productivity The impact can be transmitted to growth at the firm level first and at aggregate level finally

At micro level financial development can affect productivity by improving firm innovation and then productivity Beck et al (2005) suggested that firm with high liquidity is expected to be resilient to financial and non-financial shocks Similarly, entrance to large external finance can help a company reduce the level of credit constraints, therefore increase their ability and existence in the market (Aghion et al 2007; Levine 2005)

In this study, I will use two variables including leverage and liquidity as proxies

of financial constraints

2.2.3.1 Leverage

The first proxy is Leverage, the ratio of debt to total assets, which denotes two opposite effects On the one hand, high debt implies that firms had access to external finance in the past, which may be a signal that the firms do not face with financial constraint However, it does not certainly mean that firms can obtain as much finance as it would like to or receive the loan as much as the optimal value

On the other hand, leverage can have negative impact on investment expenditure through (1) a liquidity effect (according to Lang et al., 1996) and (2) firms can face bigger barriers in accessing external sources of capital because of high leverage Nucci, Pozzolo and Schvardi (2005) used a dataset for panel of Italian firms in order to study the relationship between firms’ capital structure and TFP They argued that firms undertaking innovative activities hold a large share of immaterial and thus, more innovative firms tends to have a different capital structures from less innovative ones Ultimately, differences in propensity to innovate are likely to convert into different TFP levels They built a TFP model on firms’ leverage, immaterial assets ratio and other control variables such as firms’ size, firms’ cash flow, long-run bank debt ratio, liquid assets ratio, time dummy, and geography

dummy The results suggested that the negative relationship between firms’ leverage and productivity is non-linear and it depended on some firm-specific characteristics In particular, they found that the negative relationship is stronger for firms, which have a lower share of short-term debt and lower liquidity

Ghosh (2009) utilized data on high-tech Indian firms to study the association between leverage and productivity The results showed that firms with low leverage tend to have higher productivity, on average Lower leverage may infer higher accumulation of immaterial assets, for example knowledge capital, and result in higher TFP

Nunes, Sequeira and Serrasqueiro (2007) used a large sample of firms in Portunal to examine the link between leverage and labour productivity, and find the relationship is non-linear They used quantile regressions to estimate labor productivity on firms’ leverage, tangibility, size, growth and ownership They showed that leverage of Portuguese firms tended to negative affect labour productivity for the majority of firms with relatively lower productivity but to positive affect this variables for firms with relative higher productivity

Pushner (1995) studied the relationship between leverage and firm’s TFP in Japan, and find the relationship is strong negative On one hand, a positive relationship between leverage and firms’ productivity can be supported by bankruptcy theory mentioned above A high degree of leverage increases bankruptcy risks and hence stimulates managers as well as employees to increase their efforts to improve productivity On the other hand, a negative relationship can come from an agency problem Banks usually issue loan collateralized R&D activities positively related with productivity, but negatively related to leverage because of its negative relationship with collateral Therefore, leverage has negative relationship with productivity perhaps through the linkage of research and development The findings above point that the effect of leverage on productivity may depend on the dominant impact of leverage and other firm characteristics

Consequently, policies in order to increase borrowing may not help to improve productivity

Hypothesis 1: Leverage has a significant and negative relationship with firm

productivity

2.2.3.2 Liquidity

According to Keynes ((1930), p.67), one asset is considered as more liquid than another “if it is more certainly realizable at short notice without loss” Liquid asset can be converted into cash quickly and at a low cost Keeping liquid assets can result in high opportunity cost to firms, but firms have more liquid asset can be seen

as less risky to lenders Theories imply that the more liquid assets increase firms’ capacity to raise cash on short notice Myers and Rajan (1998) argued that the liquidity of assets can open up various business strategies, which may be disadvantageous to lenders’ benefits, and hence excessive liquid assets may reduce the reliability of firms to their lenders As a result, excessive liquidity can reduce the ability of firms in raising external finance However, liquidity is still an aspect that the lenders will consider when they make lending decisions

Firms with high share of liquid assets may be more able to implement activities for enhancing productivity than firms with low share of liquid assets and depend less on their floating cash flow for these activities This is acceptable that liquid firms can quickly liquidize some of their assets in case they need extra funds for activities to improve productivity Illiquid firms may not be able to do the same and, thus, more depend on their current cash flow for productivity enhancing activities In fact, Nucci, Pozzolo and Schivardi (2005) discovered that low liquidity Italian firms suffer stronger negative effects from leverage than high liquidity firms

Hypothesis 2: Liquidity will have positive influence on firm productivity

2.2.4 Factors impact productivity

Castany, López-Bazo, and Moreno (2005) studied the differences in TFP across firm size in Spanish manufacturing sector They showed that some factors including innovative activities, using of skill labor has promoted productivity, especially, firm size plays an important role in explaining differences in productivity between firms Firm size affects research and development activities and employees’ qualification, which impact on productivity, and thus firm size relate to firm productivity Firm’s size is also used to control for the effect of economies of scale on firm’s productivity (Balk, 2001)

2.2.4.2 Firm’s Age

Several empirical studies about the relationship between firm age and firm productivity pointed out that productivity was not constant over lifetime of firm Taymaz (2002) stated that new firms awaked to their actual productivity after observing their performance in the industry If their performance is ineffective, they either grow or exit New firms, which survive, attaint higher productivity than existing firms The results also suggested that productivity growth rates have negative correlation with age and size of firms

Similarly, Power (1998) studied the linkage between productivity and age of firms in the manufacturing sector of the U.S in the period from 1972 to 1988 and found that the productivity growth rates are negative correlated with firms age at a specific time in the lifetime of firms

In contrast, Celikkol (2003) showed that the oldest firms within a given industry performed higher productivity growth rate than the average rates This study focused on the food and kindred products industry in the U.S and found that older firms achieved higher productivity growth rate than younger firms

Huyghebaert & Van de Gucht (2007) indicated that the access to external finance is often limited for young companies Even if they can obtain external financing, they have to pay expensive costs for it Consequently, the chances for young firms to develop are often restricted

Palangkaraya, Stierwald and Yong (2009) used a panel data to study the relationship between productivity, size, and age of Australian firms The results show that firms’ size and firms’ age relate to firms productivity In particular, larger firms are on average more productive, but older firms are less productive

2.2.4.3 Export status

Firms’ export status is included to capture the role of exporting on firms’ productivity In the economics literature, exporters are often recognized to be more productive than non-exporters This finding is cited as a reason for export promotion in many developing countries There are two theories to explain for the positive link between firm’s export status and its productivity One is self-selection: only productive firms have ability to take part in export activities and compete in international markets (Bernard and Jensen, 1999) The other is “learning by doing”: engaging in export market allows firms to achieve new knowledge, and access to new technology which contribute to enhance their productivity (Van Biesebroeck (2005), Clerides et al., 1998; Evenson and Westphal, 1995) In this model, I use export status dummy XMit to identify the effect of export market on productivity It takes value of 1 if the firms take part in export/ import market and 0 otherwise

2.2.5 Conceptual framework

Figure 2.1 Conceptual framework

The relationship between financial constraints and firm productivity will be examined in two steps:

(1) TFP measurement: productivity is proxy by total factor productivity (TFP) It captures the growth, which could not be explained by changes in production inputs, thus it can serve as a traditional proxy of productivity improvement

It is measured by Levinson and Petrin (2003) method

(2) Relationship between financial constraint and TFP: the total factor productivity index will be regressed again by financial variables and control variables Financial constraint variables are mentioned in this study including leverage and liquidity At micro level finance can affect productivity by

Total Factor Productivity

improving firm innovation and then productivity (Nickell and Nicolitsas, 1999; Beck et al, 2005; Ghosh, 2009; Pushner, 1995; Nucci, Pozzolo and Schivardi, 2005)

This step will also employ control variables, which have impact on firm productivity, such as: firm size (Palangkaraya, Stierwald and Yong, 2009; Castany, López-Bazo, and Moreno, 2005; Balk, 2001), firm age (Taymaz, 2002; Celikkol, 2003; Power, 1998; Palangkaraya, Stierwald and Yong, 2009) and export status (Bernard and Jensen, 1999; Van Biesebroeck, 2005; Clerides et al., 1998; Evenson and Westphal, 1995)

CHAPTER 3: RESEARCH METHODOLOGY AND DATA

Firstly, this chapter will present an overview of SMEs in Vietnam Then, the model specification, and variables measurement will be constructed based on the literature Finally, the using data and estimation methodology will be mention at the end of this chapter

3.1 An overview of SMES in Vietnam

Every country has its own definition of small and medium-sized enterprise Basically, the definition include aspects such as number of employees, invested capital, size of annual turnover, and total assets However, the most common used indexes are number of employees and total invested capital In Vietnam, the definition of SMEs is defined by the government through the Decree number 90/2001/ND-CP in November 2001, and updated by 56/2009/ND-CP in June 2009 According to the degree 56, a firm is defined as a SME when it has equal or less than 300 persons or maximum total capital is 100 billion The definition of SMEs is defined more clearly in table 1 below:

Table 3.1: Definition of SMEs in Vietnam

Number

of employees

I Agriculture,

forestry and fishery ≤10 ≤ VND 20 billion 10-200 VND 20-100 billion 200-300

II Industry and

construction ≤10 ≤ VND 20 billion 10-200 VND 20-100 billion 200-300 III Trade and

services ≤10 ≤ VND 10 billion 10-50 VND 10-50 billion 50-100

Source: Government's Decree No 56/2009/ND-CP

In recent year, promotion of small and medium enterprises (SMEs) has been given more attention Many laws such as company law, enterprises law, home investment

law, civil law, and commercial law have been passed to create favorable environment for the development of small and medium enterprises Since 2005-

2006, when enterprises law has been effective and Vietnam has become the member

of World Trade Organization (WTO), the number of enterprises has been increasing significantly

Small and medium enterprises have played an important role in Vietnam’s economy

by contributing into GDP, creating job, raising fund for business and solving social problems According to survey in 2011, SMEs has accounted for 97.6 percent of total numbers of enterprises The number of small and medium enterprises has increased significantly from 2006 to 2011 From figure 3.1, we can see that along with the increasing trend in the number of total enterprises, the total number of SMEs in 2011 had grown by 2.64 times compared with that in 2006; average increased 21.4 percent per year