Tài liệu The relationship between financial constraint and smes total factor productivity

ERASMUS UNIVERSITY ROTTERDAM INSTITUTE OF SOCIAL STUDIES THE NETHERLANDS UNIVERSITY OF ECONOMICS HO CHI MINH CITY VIETNAM VIETNAM – THE NETHERLANDS PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS THE RELATIONSHIP BETWEEN FINANCIAL CONSTRAINT AND SMEs TOTAL FACTOR PRODUCTIVITY By HỒ BẢO TRÂN MASTER OF ART IN DEVELOPMENT ECONOMICS HO CHI MINH CITY, JANUARY 2016 UNIVERSITY OF ECONOMICS HO CHI MINH CITY VIETNAM ERASMUS UNIVERSITY ROTTERDAM INSTITUTE OF SOCIAL STUDIES THE NETHERLANDS VIETNAM – THE NETHERLANDS PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS THE RELATIONSHIP BETWEEN FINANCIAL CONSTRAINT AND SMEs TOTAL FACTOR PRODUCTIVITY 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 ACKNOWLEDGMENTS I would not be possible to write this master thesis without the support and the encouragement from many people. I would like to express special appreciation to my supervisor, Prof. Dr. Nguyen Trong Hoai, who I have learned a lot from his guidance, useful recommendations and valuable comments. 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 nonfinancial 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. 1 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. 2 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. 3 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 CobbDouglas 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 4 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. 5 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 6 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 7 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. 8 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. 9 2.2.4 Factors impact productivity 2.2.4.1 Firm’s Size Palangkaraya, Stierwald and Yong (2009) used a panel data to study the relationship between productivity, size, and age of Australian firms. They estimated a translog cost function to construct productivity index of firms. The results showed 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. 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. 10