Outsoursing and total factor productivity evidence from vietnamese small and medium sized enterprises

ABBREVIATIONS SMEs : Small and Medium-sized Enterprises R&D : Research and Development GDP : Gross Domestic Product ROE : Return on equity OECD : Organization for Economic Co-operation a

UNIVERSITY OF ECONOMICS ERASMUS UNIVERSITY ROTTERDAM

HO CHI MINH CITY INSTITUTE OF SOCIAL STUDIES

VIETNAM THE NETHERLANDS

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

OUTSOURCING AND TOTAL FACTOR

PRODUCTIVITY: EVIDENCE FROM

VIETNAMESE SMALL AND MEDIUM-SIZED

ENTERPRISES

BY

PHAM THI HOA TIEN

MASTER OF ARTS IN DEVELOPMENT ECONOMICS

HO CHI MINH CITY, December 2017

UNIVERSITY OF ECONOMICS INSTITUTE OF SOCIAL STUDIES

HO CHI MINH CITY THE HAGUE

VIETNAM THE NETHERLANDS

VIETNAM - NETHERLANDS PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS

OUTSOURCING AND TOTAL FACTOR

PRODUCTIVITY: EVIDENCE FROM

VIETNAMESE SMALL AND MEDIUM-SIZED

ENTERPRISES

A thesis submitted in partial fulfilment of the requirements for the degree of

MASTER OF ARTS IN DEVELOPMENT ECONOMICS

By

PHAM THI HOA TIEN

Academic Supervisor:

PHAM THI BICH NGOC

HO CHI MINH CITY, December 2017

DECLARATION This is to certify that this thesis titled “Outsourcing and total factor productivity: evidence from Vietnamese Small and Medium-sized Enterprises”, which is submitted in fulfillment of

the requirements for the degree of Master of Arts in Development Economics to the Vietnam Netherlands Program (VNP) The thesis constitutes only my original work and due supervision and acknowledgement have been made in the text to all material used

Finally, I would like to thank my family and friends, who always unconditionally supported me in not only the thesis writing but also my whole life

Pham Thi Hoa Tien

Ho Chi Minh City, December 2017

ABBREVIATIONS

SMEs : Small and Medium-sized Enterprises

R&D : Research and Development

GDP : Gross Domestic Product

ROE : Return on equity

OECD : Organization for Economic Co-operation and Development

ILSSA : Labor Studies and Social Affairs

MOLISA : Ministry of Labor, Invalids and Social Affairs

SSE : Stockholm School of Economics

GSO : General Statistic Office

TFP : Total Factor Productivity

TCT : Transaction Cost Theory

RBV : Resource-Based View

RDT : Resource Dependency Theory

GMM : Generalized Method of Moment

2SLS : Two Stages Least Square

CDM : Crépon, Duguet and Mairesse

FEM : Fixed Effects Model

REM : Random Effects Model

ABSTRACT

This study aims to examine the impacts of outsourcing activities on firms total factor productivity of 4,549 Vietnamese enterprises by using a panel dataset of Small and Medium-sized Enterprises during the period from 2005 to 2013 It is supposed to contribute to existing empirical, literature by employing the complementarity and substitutability test to investigate the effect of outsourcing on firms’ total factor productivity The total factor productivity in this study is calculated based on Levinsohn Petrin method Furthermore, the Fixed Effects with Driscoll Kraay standard error model, which has the advantage of correcting the problem

of autocorrelation and heteroskedasticity is applying to get the better result of outsourcing and firms’ total factor productivity relationship estimation The finding proves a significant positive nexus between outsourcing and firms’ total factor productivity and confirms that firms spend more on outsourcing will get higher total factor productivity index These results are supported by a majority of empirical papers about relationship of outsourcing and total factor productivity and outsourcing’s theories From the findings, this study will give some discussion as well as some policy recommendations for firms to enhance their productivity

Key words: Vietnamese SMEs, Total factor productivity, Driscoll Kraay

TABLE OF CONTENT

ACKNOWLEDGEMENT i

ABSTRACT iv

TABLE OF CONTENT v

LIST OF TABLES viii

LIST OF FIGURES ix

CHAPTER 1 INTRODUCTION 1

1.1 Research problems 1

1.2 Research objectives and questions 3

1.2.1 Research objectives 3

1.2.2 Research questions 3

1.3 Data and methodology 3

1.4 Thesis structure 4

CHAPTER 2 LITERATURE REVIEW 6

2.1 Outsourcing 6

2.1.1 Definition of outsourcing 6

2.1.2 Theoretical background for outsourcing 7

2.1.2.1 Transaction Cost theory 7

2.1.2.2 Resource dependency theory 8

2.1.2.3 Resource-based view theory 9

2.2 Total factor productivity 10

2.2.1 Definition 10

2.2.2 Measurement of total factor productivity 10

2.3 Empirical studies- outsourcing and TFP 13

2.4 Conceptual framework 14

CHAPTER 3 DATA AND RESEARCH METHODOLOGY 16

3.1 Data source 16

3.2 Research model 16

3.2.1 Dependent variable 18

3.2.2 Independent variables 18

3.2.2.1 Explanatory variables 18

3.2.2.2 Control variables 19

3.3 Methodological approach 25

3.4 Econometric approach 26

3.4.1 Method for step 1 26

3.4.1.1 Levinsohn Petrin 26

3.4.2 Method for step 2 and step 3 27

3.4.2.1 Ordinary least square 27

3.4.2.2 Fixed effects model 28

3.4.2.3 Fixed effects model with Driscoll Kraay standard error 28

CHAPTER 4 EMPIRICAL RESULTS 30

4.1 Summary statistics and analysis 30

4.1.1 Data summary 30

4.1.2 Summary statistics 33

4.1.3 Model specification and diagnostic testing 35

4.2.1 Step 1: Calculate total factor productivity at the firm level 36

4.2.2 Step 2: The difference between firms with and without outsourcing 37

4.2.3 Step 3: The relationship between outsourcing expenditure and firms’ TFP 39

CHAPTER 5 CONCLUSION AND DISCUSSIONS 41

5.1 Main findings 41

5.2 Discussion and suggested policies 42

5.3 Limitation and potential future research 44

REFERENCE 46

APPENDIX 52

LIST OF TABLES

Table 3.1 Number observations in dataset 2005-2013 16

Table 3.2 Variables description 23

Table 4.1 Observations by type of firms Error! Bookmark not defined. Table 4.2 Observations by type of firms in the period 2005-2013 31

Table 4.3 Firms types with and without outsourcing 31

Table 4.4 Firms sizes in the period 2005-2013 32

Table 4.5 Descriptive statistics of TFP and other variables 33

Table 4.6: Firms sizes with and without outsourcing 34

Table 4.7 Correlation between variables 35

Table 4.8: Comparision of OLS, Fixed Effect and LP estimation 36

Table 4.9 : Regression results of different TFP between outsourcing firms and none outsourcing firms 38

Table 4.10: Regression results of TFP within outsourcing firms 39

v

LIST OF FIGURES

Figure 2-1 Conceptual Framework 15

Figure 3-1 Empirical study stages 25

Figure 4-1 Firm sizes with and without outsourcing 34

Figure 4-2 The trend of average total factor productivity from 2005-2013 37

CHAPTER 1 INTRODUCTION 1.1 Research problems

Outsourcing or the act of contracting out internal activities to foreign suppliers, has rapidly become a critical approach in the modern economy, especially for manufacturing firms Despite being a widely used concept, outsourcing might originate from the late 1970s to early 1980s as a mean to search for external resources to maximize the firm’s profit (Corbett, 2004) While outsourcing allows the companies to focus on their strength in maintaining and developing core competencies, it also mitigates the expertise shortage in the less well-developed part of company in which that want to outsource (López, 2014)

Through the decades, outsourcing delivers many benefits for business actors such as reducing cost, improving productivity, enhancing efficiency and concentrating on the core business operation which lead to lower resource cost and higher quality products (Gilley & Rasheed, 2000) These advantages of outsourcing were demonstrated through many empirical studies For example, outsource information technology helped reducing operational cost (Loh

& Venkatraman, 1995); outsourcing non-core activities would develop service organizations’ capability and flexibility to adapt to the rapidly changing economic environment (Lankford & Parsa, 1999; Sia, Koh, & Tan, 2008)

Despite many positive aspects, outsourcing also poses serious risks to the firms (Weidenbaum, 2005) For instance, the unbalance between the actual demands from outsourcing users and outsourcing contractor’s products, the high product’s price or the leakage of core competency could potentially affect the firm (Lutchen, 2004) This could be explained by the inflated information on the vendor’s capability on which they could offer, the misunderstanding in product’s requirement between the employers and partners, or the lack of control on the subcontract Or in another word, the positive impact of outsourcing could be bounded by their threat (Antonietti, Ferrante, & Leoncini, 2016) While firm’s technology might be stolen by their outsourcing vendor due to the lack of controlling in legal systems (Weidenbaum, 2005)

In fact, a variety of multinational companies include Apple, Boeing, Nike, Mattel, Calvin Klein, Kodak are practicing outsourcing successfully (see Quinn and Hilmer (1994); Doh (2005); and other) For some identical samples, it is worth mentioning Nike, which is not only a famous footwear company also a successful firm by applying outsourcing Since they outsource all their core products to the third party, Nike increased 20 percent in growth rate and earned 31 percent return on equity (ROE) for its shareholder (Quinn & Hilmer, 1994) Another outstanding case of using outsourcing efficiently is the cooperation between IBM and Kodak Eastman in 1989 This pushed Kodak to become a favorite brand in the photography industry (Dickson, 2011) Implementing outsourcing successfully in the multinational company is undeniable (Doh, 2005; Landefeld & Mataloni, 2004) However, the effect of outsourcing on small and medium-sized enterprises (SMEs) remains unclear This raises the question: how do the small and medium enterprises apply outsourcing to maximize efficiency and profits?

From an empirical perspective, outsourcing is studied too broadly Previous studies focused on the internal factors that impacts on outsourcing decisions, which are connected to agency cost theory, resource dependency theory, transaction cost theory (Michael & Michael, 2011) Other researchers measured the impact of outsourcing on productivity However, most

of the measurement collected information at the industry level and from input-output tables, rather than firm-level data (López, 2014).Therefore, the number of research studies about the impact of outsourcing on productivity at firm level is limited Particularly, for the case of Vietnam and Organization for Economic Co-operation and Development (OECD) economies where SMEs contribute over 40% and 55% to overall Gross Domestic Product (GDP), respectively Besides, there is lack of research about the outsourcing effect on firm’s productivity in the context of SMEs in Vietnam

Therefore, the shortage of outsourcing studies on the firm’s total factor productivity for the case of Vietnam opens a new line for enquiry Insights gained from studying outsourcing

in small and medium enterprises provide promising prospects for benefiting Vietnam’s overall economy in which SMEs are dominant This study is expected to give a closer look at the Vietnamese SMEs’ total factor productivity using the Petrin et al (2004) approach Besides

that, this study also investigates how outsourcing impact SMEs’ total factor productivity Moreover, the impact of outsourcing on firms’ productivity is analyzed under the effect of other fundamental factors such as labor force, capital, technology, innovation, and other

Therefore, this study aims to contribute to the existing literature by adding some perspectives to empirical evidence to fully understanding the impact of outsourcing and other factors on SMEs’ total factor productivity The result may help the policymakers in deciding appropriate agenda for supporting outsourcing to obtain the target productivity

1.2 Research objectives and questions

1.2.1 Research objectives

The primary purpose of this study is to investigate the effect of outsourcing on firms total factor productivity in the case of Vietnamese small and medium-sized enterprises during the period of 2005 to 2013

1.2.2 Research questions

These following questions will be answered to deal with this objective:

(1) Do firms with outsourcing activities have higher total factor productivity?

(2) For Vietnamese SMEs with outsourcing activities, does expenditure outsourcing positively effect on total factor productivity?

1.3 Data and methodology

This study employs the data from Small and Medium Enterprises (SMEs) of Vietnam (2005-2013) These surveys are conducted every two years by the collaboration of educational organizations and government agencies: Stockholm School of Economics (SSE), Department

of Economics- the University of Copenhagen, the Institution of Labor Studies and Social Affairs (ILSSA) in the Ministry of Labor, Invalids and Social Affairs (MOLISA) Ten Vietnamese provinces or cities are included in the survey project: four cities or provinces in the North (Ha Noi, Ha Tay, Hai Phong, Phu Tho); four provinces in the central (Khanh Hoa, Nghe An, Lam Dong, Quang Nam) and two cities or provinces in the south (Long An, Ho Chi

repeated from the previous survey For firms who do not respond or not in operation, data is replaced, these numbers account for 20% data Thus, data is considered represented for the Vietnamese SMEs population In addition, data used in this study ends in 2013 because the dataset of the 2015 year was not published at the time this study was completed

After unbalanced panel data is obtained, firms total factor productivity will be calculated depend on the basic production function model Cobb Douglass This study employs Petrin et al (2004) method to solve the problem of endogeneity in error term The results of TFP for each firm will be used as dependent variables to run the regression with the outsourcing variables and control variables in the Ordinary Least Squares (OLS) model, Fixed effects (FE) model, Fixed effects (FE) with Discroll and Kraay standard error to analyse their relationship as well as their interactions The results of the fixed effects with Discroll and Kraay standard error estimation is taken as the key results In the meantime, OLS model is also used as a comparison result according to previous studies

1.4 Thesis structure

This study consists of five chapters

Chapter 1: Introduction

This section provides the research motivation and overall information about this study

Chapter 2: Literature review

This chapter presents the literature review, which covers theoretical background and empirical review

Chapter 3: Research methodology

This chapter offers research methodology, which describes the empirical model and estimation method

Chapter 4: Research results

This chapter presents the statistic description, regression result, and statistical analysis

Chapter 5: Conclusions and discussion

This chapter summarizes the conclusion, the implication, the limitation, and the further

research

CHAPTER 2 LITERATURE REVIEW

In this chapter, the literature framework of this study consists of four main points The first part provides some definitions and theoretical background of outsourcing The definition and measurement of total factor productivity will be introduced in the second part The third part will present some empirical studies about the relationship between outsourcing and total factor productivity The final part contains the conceptual framework of the study

Outsourcing is not simply a procurement decision, outsourcing is presented as a

“decision to reject the internalization of activity” according to Gilley and Rasheed (2000) Outsourcing was classified in two ways: abstention and substitution First, in the abstention outsourcing, outsourcing raised when goods or services were purchased from outside firm;

however, those were not produced internally in the previous The abstention-based outsourcing was considered as a type of outsourcing and distinguished from purchasing activity due to good or service outsourced only was internalized within the managerial and financial capabilities of the firm in the past Second, in the substitution outsourcing, the former internal activities were substituted by the external resource from purchasing This kind of outsourcing was recognized as vertical disintegration, which eliminated the participation of firm in production stages In general, both types of outsourcing imitated the decision of company on rejecting the internalization, and the outsourcing could be separated with a typical transaction by the capacity of a firm to implement outsourced activities by itself

In this research, we employ the concept of Penc (2002)which was developed by Matejun (2010) to apply to small and medium-sized enterprises; outsourcing is defined as contracting out their activities to external partner due to its shortages of resources however still focus on their strategies and core competencies

2.1.2 Theoretical background for outsourcing

There were three fundamental theories that dominate outsourcing research: transaction cost theory (TCT), resource-based view (RBV), and resource dependency theory (RDT) These theories are elaborated to answer why firms need to terminate in-house to transfer to outside services (Gerbl, McIvor, & Humphreys, 2009) These theories were one of the most influential ones in nexus with outsourcing However, a significant limitation of TCT, RDT, and RBV is that these theories were mainly based on economic rationale (McIvor, 2009) The existent of theories help to explain the reason: why do firms terminate in-house operations in favor of outside services?

2.1.2.1 Transaction Cost theory

Transaction cost theory was a primary outsourcing theory, which was initiated by Coase (1937) and developed by Williamson (1979) This theory specified the conditions, which influenced the decision of an organization to manage itself internally (within its boundaries) or externally (i.e., outsourcing) (Gerbl et al., 2009)

Transaction cost according to Gurbaxani and Whang (1991) was the cost of "using a market” containing operational costs (search cost, selection cost, bargaining cost) and contractual costs (writing, monitoring and enforcing a contract, coordinating cost All activities of firms were based on the balance between transaction cost and production economics; however, the decision of firms for “make-or-buy” was decided based on economizing of transaction costs (Williamson, 1985) Besides, transaction costs were affected

by three factors: conditional asset specificity supporting the transaction, the level and kind of uncertainty rounding the transaction and the frequency of transaction In which, asset specificity was seen as critical to transaction since it had a substantial impact on the selection

of governance structures (Riordan & Williamson, 1985; Williamson, 1989)

There were two main behavioral assumptions were studied for this theory: bounded rationality (the experience of uncertainty from various sources in transacting, complex contracts were necessary to one degree or another Williamson (1989)) and opportunism (for the economic actors tend to self-interest-seeking, which created the environment for developing guile Since it took a high cost to refine complex contracts, which are necessarily incomplete, thus opportunism added uncertain behavior to contractual relationships to set the stage for ex-post performance problems Therefore, when combined bounded rationality with opportunism, the organization would experience the complicated problems with uncertain complexity With two behavioral assumptions, the problem of organization was dealing with economizing organizational transaction on bounded rationality while protecting them against the hazards of opportunism (Williamson, 1985)

Consequently, transaction cost theory advised business actors to keep processes that were highly specific in-house, as the market transaction costs for communication and agreement were too high to make outsourcing a viable alternative (Gerbl et al., 2009)

2.1.2.2 Resource dependency theory

The assumption about resource dependency theory is firms seek the opportunities to enhance their power (Pfeffer & Salancik, 1978; Ulrich & Barney, 1984) Therefore, before the lack of resources firm could get the needed resources, they had to try to set up the relationship

with powerful firms As a result, firms changed their structure and strategies to purchase the external resources (Ulrich & Barney, 1984) Resource dependency theory was also a useful way to examine the relationship between outsourcing decision of firm and their abilities to utilize resources from outside environment (Yuchtman & Seashore, 1967)

Resource dependency theory revealed that to gain advantage from outsourcing, the economic actors should adjust their strategy to have strong processes and outsource from the weaker vendor (Teng et al., 1995) Therefore, firms could access the balancing power through resource accessibilities, potential supplier number, switching supplier’s cost (Teng et al., 1995)

2.1.2.3 Resource-based view theory

The third fundamental outsourcing theory was the resource-based view, this theory supplemented for transaction cost theory and resource dependency theory by emphasizing the firm’s resource accumulation (Penrose, 1959; Wernerfelt, 1984) Firms got the sustained competitive advantage from external resources, which was value, imperfectly imitable, non-substitutable in competing for firm resources (Arnold, 2000; Barney, 1991) Outsourcing helped to solve the problem of constraint by maintaining current resources and enhance strategic affordances (Grant, 1991; Teng et al., 1995) In this case, the resource-based view theory demonstrated that the competitive advantage of firm come from owning the “difficult-to-replicate” resources such as having loyal customers, good reputation, and competent employees (Lovallo & Mendonca, 2007) The competitive advantages of firm come from core competency, its marginal impact did not underline sustainable competitive advantage, which made it appropriate for outsourcing (Arnold, 2000; McIvor, 2009) In this way, the resource-based view theory related to internal strategy’s activities which pertained to competitors versus external arrangement (McIvor, 2009)

2.2 Total factor productivity

2.2.1 Definition

Productivity was merely defined as the efficiency of production or how much output could be created from given set of input through production process (Syverson, 2011) Thus, productivity was the ratio of output and input Productivity was also a typical indicator to measure the economic performance of a firm, an industry, or whole country

There were two main groups classified to measure productivity: single factor productivity (is calculated as the proportion of output per particular input), multifactor productivity or total factor productivity (measure the variation of output acquired from a given set of inputs) (Hulten, 2001) The weakness of single factor productivity measurement was only reflecting partial productivity for labor capacity or capital Besides that, total factor productivity measurement was seen as a better way to measure the productivity when could take into account contribution of more than an input (Van Beveren, 2012) Therefore, this study employs total factor productivity to measure firms’ productivity

2.2.2 Measurement of total factor productivity

Multifactor productivity or total factor productivity was regularly estimated via using production function in many previous studies such as: the relation of foreign direct investment and domestic firms productivity (Smarzynska Javorcik, 2004), the effect of R&D on firm’s productivity (Hall, Lotti, & Mairesse, 2009), the impact of information technology on firm’s productivity (Chun, Kim, & Lee, 2015)

To estimate these relationships, previous studies usually employed primary production function, which was Cobb-Douglas production function regression

From the production function above, many econometric methods could be applied In order to obtain robust and consistent coefficients, we must solve the problem of error terms The results from Fixed Effects estimator and OLS estimator would be both consistent and efficient if only the error term is independently and identically distributed Since, we still face the problem

of input endogeneity in a production function Hence, we also use the methodology described in Levinsohn and Petrin (2003) and Petrin et al (2004) which uses intermediate inputs as a proxy

to control for unobservable productivity shocks (LP hereafter)

The LP method was more developed than the Olley and Pakes (1992) which used investment as a proxy for productivity shocks for two reasons: (1) the investment proxy might not smoothly respond to the productivity shock, violating the consistency condition, and (2) using intermediate input proxies avoided truncating all the zero investment firms

Consider the following Cobb-Douglas production function model:

𝑦𝑡 = 𝛼 + 𝛽1 𝑘𝑡+ 𝛽2 𝑙𝑡+ 𝛽3 𝑚𝑡+ 𝜔𝑡+ 𝜀𝑡Where ωt denotes productivity, a state variable which could impact the choices of inputs;

and ε t stand for an error term that was uncorrelated with input choices Both ω t and ε t were

unobserved Firms’ decision in inputs could give rise to simultaneity bias The positive

correlation between ω t and inputs used in period t will yield inconsistent results

Olley and Pakes (1992) developed an estimator that uses investment as a proxy for these unobservable shocks The LP method highlighted that intermediates might respond

more smoothly to productivity shocks Accordingly, demand for the intermediate inputs m t is

assumed to depend on capital stock k t and state variable ω t

m t = m t (k t , ω t )

Since the demand function was monotonically increasing in ωt (Levinsohn & Petrin,

2003), we have the inversion of the intermediate demand function:

ω t = ω t (k t , m t )

Assumed that productivity is governed by a first-order Markov process:

ω t = E[ω t |ω t −1] + ξ t

Where ξt denotes productivity innovation term

If we use revenues as the dependent variable in the model, then the production function

is given as:

𝑦𝑡 = 𝛽𝑙 𝑙𝑡+ 𝜑𝑡(𝑘𝑡, 𝑚𝑡) + 𝜀𝑡

Where now: φ t (k t , m t ) = α + β t k t + β m m t + ω t (k t , m t )

The function φ t can be estimated with a third-order polynomial approximation in m t and

k t, and thus this first stage of the estimation yields the estimation 𝛽̂ of β𝑙 l

The coefficients on capital and intermediate inputs are obtained in the second stage For

any candidate values β k * and β m *, we estimate 𝜔̂ by using: 𝑙

𝜔̂ = 𝜑𝑡 ̂ − 𝛽𝑡 𝑘∗𝑘𝑡− 𝛽𝑚∗𝑚𝑡Then the residual of the production function is computed as:

𝜀𝑙̂ = 𝑦+ 𝜉𝑡 𝑡− 𝛽̂ 𝑙𝑙 𝑡− 𝛽𝑘∗𝑘𝑡− 𝛽𝑚∗ 𝑚𝑡− 𝐸[𝜔𝑡̂ ] |𝜔𝑡−1where a consistent approximation of the expected value of ωit is given as:

𝜔̂ = 𝛾𝑡 0+ 𝛾1𝜔𝑡−1+ 𝛾2𝜔𝑡−12 + 𝛾3𝜔𝑡−13 + 𝜇𝑡

The residual must interact with at least two instruments to identify both β k and β m The estimations 𝛽̂ of β𝑘 k and 𝛽̂ of β𝑚 m are found as the solution by minimizing the sample residual of

the production function for β k * and β m * The LP method applies the GMM estimator using lag

values of inputs as instruments A bootstrapping procedure is also used to construct the standard errors for 𝛽̂ , 𝛽𝑙 ̂, and 𝛽𝑘 ̂ 𝑚

TFP is then measured as the difference between the actual and predicted output

tfp  y  k l  m

2.3 Empirical studies- outsourcing and TFP

The nexus of outsourcing and firm’s productivity was studied in many previous studies Nevertheless, the conclusion of this relation did not come to a consensus On one hand, outsourcing might affect positively on firm’s productivity, which could be measured through some indicators On another hand, some research proved negative effect due to

outsourcing

How does outsourcing affect firm’s productivity? The most significant researches found outsourcing have a positive effect on total factor productivity These positive effect of outsourcing on firms’ TFP are usually explained by the benefit of outsourcing contribute to enterprise Outsourcing helps firm improve their financial performance (by immediately improving cost) and non-financial performance to help firm concentrate on developing core competencies For example, López (2014) in Spanish with a sample of 1,728 Spanish manufacturing range from 1990 to 1999, its result revealed that outsourcing intensity for manufacturing firm has positive effect on total factor productivity The explanation is that outsourcing help firms to decline manufacturing costs and equipment investment in plant, which lead to improvement of TFP In addition, in the research of Lin and Ma (2012) outsourcing was defined as two types: services and material purchased from external This study used GMM to analyze the impact of outsourcing on firm’s productivity found that there was a positive relationship between material outsourcing and productivity The study of Crinò (2008) revealed that service offshoring has a significant and largely positive impact on productivity in the home countries, based on the panel data of twenty industries (both manufacturing and services) for nine Western European countries from1990 to 2004 This result is explained that outsourcing could reduced investment in manufacturing capacity, lowers fixed costs, which leads to improve firm’s productivity By using outside suppliers for products or services, an outsourcer is able to take advantage of emerging technology without investing significant amounts of capital in that technology Thus, Amiti and Wei (2006) found

a significant positive effect of international services outsourcing and smaller positive effect of material international outsourcing on labor productivity when employed US data at industrial

was positively related to both total factor productivity and labor productivity by utilized the data of three manufacturing industries in the United Kingdom in the period 1980-1992 The reason is outsourcing can switch suppliers as new, more cost effective technologies become available instead of committing a specific type of technology By this way, outsourcing allows for quick response to changes in the environment to over the constrain of flexibility in the long run Ten Raa and Wolff (2001) found that total factor productivity growth in manufacturing industries was positively related to change in outsourcing, using US manufacturing industry data

However, there are some cases the effect of outsourcing on productivity is negative in some aspect The major reasons for negative effect is outsourcing could lead to loss of long-run research and development (R&D) competitiveness The reliance of firms on outsourcing is declining innovation by the outsourcer, because outsourcing often used as a substitute for innovation As a result, firms that outsource are likely to lose touch with new technological breakthroughs that offer opportunities for product and process innovations For example, Winkler (2010) used data of German manufacturing industries in the period 1995-2006; found that the effects of a share of intermediate material either from domestic suppliers or from abroad were small and even negative while purchased services from abroad had a positive and significant impact on labor productivity In addition, as suppliers gain knowledge of the product being manufactured, they may use that knowledge to begin marketing the product on their own For instance, Falk (2012) found different results: material outsourcing had positive effect while services outsourcing had negative effect on firm’s productivity by using OLS method Moreover, Daveri and Jona-Lasinio (2008) used data for 21 manufacturing industry sectors in Italy between 1995 and 2003 found that imported intermediate materials had a significantly positive impact on overall productivity growth, while purchased services had a negative impact on productivity

2.4 Conceptual framework

Regarding empirical background and literature reviews in previous chapters, a majority research reveals that outsourcing could have positive impact on firm total factor productivity

(Antonietti et al., 2016; Antonioli, Mazzanti, Montresor, & Pini, 2015; Falk, 2012; Lin & Ma, 2012; López, 2014) This research proves the hypothesis of positive outsourcing – firms total factor productivity relationship in case of Vietnamese SMEs for some reasons Firstly, outsourcing could help firm to improve their financial performace and their productivity by imediately reducing production cost, material cost, fixed cost and so on Secondly, outsourcing also offer firms to overcome the constraint of felexibility to take advantage of technology, which lead to the improvement of productivity Finally, outsourcing contribute to improve firms‘ TFP

by transfering the low value added activities to third parties, which could help firm to concentrate on developing their core competencies

In this study, the outsourcing effect is reviewed in ter m of two components: (i) whether firms outsource or not, (ii) share of outsourcing in total firm’s expenditure The conceptual framework will be summarized as follow:

TFP

Figure 2-1 Conceptual Framework

CHAPTER 3 DATA AND RESEARCH METHODOLOGY

3.1 Data source

This study employs the data from Small and Medium Enterprises (SMEs) of Vietnam

in period 2005-2013 These surveys are conducted every two years by the collaboration of Educational organizations and government agencies: Stockholm School of Economics (SSE), Department of Economics- the University of Copenhagen, the Institution of Labor Studies and Social Affairs (ILSSA) in the Ministry of Labor, Invalids and Social Affairs (MOLISA) Ten provinces/cities of Vietnam are implemented the survey project: four cities/provinces in the North (Ha Noi, Ha Tay, Hai Phong, Phu Tho); four provinces in the central (Khanh Hoa, Nghe

An, Lam Dong, Quang Nam) and two cities/provinces in the south (Long An, Ho Chi Minh)

The raw data was cleaned up and deleted outlier to get the final dataset which has the total number of observations represented for 97% of total number of SMEs after five-round survey; hence final dataset collected can be illustrative for the entire dataset

Table 3.1 Number observations in dataset 2005-2013

Year No of obs.in data Total obs.in raw data %

establishes the relationship between the dependent variable – total factor productivity, explanatory variable: the ratio of outsourcing expenditure with total cost (shared outsourcing expenditure), dummy outsourcing and control variables: age of firm, firm size (total asset), firm capital structure and innovation

Therefore, the below models would be estimated:

Model 1- firms’ total factor productivity calculation

In this model, the firms’ TFP is measured as the difference between the actual and predicted output according to Levinsohn and Petrin (2003) approach is presented as follow:

K it : is average value of physical capital of firm i at year t

L it : is total labor of firm i at year t

M it : is average value of intermediate input of firm i at year t

Model 2- The impact of outsourcing on firms’ total factor productivity

firm_age it : is age of firm i is calculated at year t

firm_size it : is proxied as logarithm total asset of firm i at year t

capital_structure it : is ratio of debt over total asset of firm i at year t

dummy_innovation it : total innovation expenditure of firm i at year t

dummy_outsourcing it : is having outsourcing activities of firm i at year t

outsourcing_exp_intensity it : ratio of total outsourcing expenditure and total

expenditure of firm i at year t

3.2.1 Dependent variable

This study investigates the relationship between the outsourcing activities and firm total factor productivity Therefore, the dependent variable will be firm total factor productivity However, the firm total factor productivity variable is not available in the dataset Hence, this variable is calculated based on Levinsohn-Petrin method as explained in above This indicator is widely applied in previous studies such as Van Beveren (2012); Görg, Hanley, and Strobl (2008)

3.2.2 Independent variables

3.2.2.1 Explanatory variables

The primary explanatory variable of this study is outsourcing variable, which is adopted from the Vietnamese Small and Medium-sized Enterprises Survey The definition and measurement of outsourcing are generally employed in a variety of empirical studies (Daveri and Jona-Lasinio (2008); (Girma & Görg, 2004); Keiko and Kiyoyasu (2010); (López, 2014; Ten Raa & Wolff, 2001)) In almost all studies, outsourcing variable is employed under as dummy type or proxied as the ratio of total expenditure for material or services from outside over Since outsourcing expenditure is available information in Vietnam Small and Medium-sized Enterprises survey, and there is no study that analyzes the relation of outsourcing and total factor productivity for the case of SMEs in Vietnam using same data In this way, this research might be the first to utilize directly outsourcing information in the Vietnamese SMEs dataset to investigate the impact of outsourcing on firm total factor productivity In term of the structure of questionnaires in SMEs survey, the data offers information about the outsourcing exercises of each firm (subcontract) Particularly, data information indicating whether the firm subcontracts production and information about subcontracted expenditures This information allows this study to define the ratio of subcontracted purchases over total expenditure (which

is employed as a proxy for the outsourcing variable) This ratio is used to identify the impact

of outsourcing on firm TFP following López (2014) In addition, this study employs dummy variable of outsourcing to compare the TFP between firms with outsourcing and firms without outsourcing

3.2.2.2 Control variables

Besides the outsourcing effect, there are other components of firm’s characteristic that may also influence firm total factor productivity regarding previous theoretical and empirical literature such as firm age, firm size, capital structure, innovation, etc (see Cucculelli, Mannarino, Pupo, and Ricotta (2014), Kim (2006); Tovar, Ramos-Real, and De Almeida (2011); De Kok, Fris, and Brouwer (2006); Huergo and Jaumandreu (2004); Dhawan (2001)) These elements will be control variables and controlled heterogeneity problem in the empirical model at a firm level All the control variables in this study will be presented as followed:

Firm size

One of critical firm characteristic aspect is firm size, which is considered to have an important nexus with firm total factor productivity Thus, firm size is used as a mandatory control variables in many previous researches about firm total factor productivity In addition, major previous studies suggest the positive relation between firm size and firm total factor

productivity For example, Tovar et al (2011) analyzed the impact of firm size on Brazilian

firm’s productivity by employing a dataset of seventeenth electricity distributor in Brazil for the period 1998-2005 This study employed Stochastic Frontier Analysis to determine total factor productivity, which contained three elements: (i) technical change, (ii) scale efficiency change and (iii) technical efficiency change It is discussed that productivity difference can be explained by firm size differential through scale efficiency change and technical change Due

to positive impact of firm size on total factor productivity, small electricity distribution firms are suggested to be merged to get higher productivity The positive relation of firm size and its productivity was also reinforced by Margaritis and Psillaki (2010), Cucculelli et al (2014) In contrast, Dhawan (2001) find a negative nexus of firm size and total factor productivity This research found that small firms are more productive than large firms for the case of US firms from1970 to 1989 Firm size in this study is measured by taking logarithm of total assets

according to previous studies Moreover, another reason of using the logarithm form is minimizing the heteroscedasticity effect of large figure number

Firm age

Along with firm size, another essential control variable for firm total factor productivity in many studies is firm age For example, Cucculelli et al (2014) employed dataset of manufacturing enterprise in Italy and applied the two-stage least square method to define the origin of firm total factor productivity In the first stage, the method of Levinsohn and Petrin (2003) was used to calculated firm total factor productivity In the second stage, total factor productivity from the first stage is using as a dependent variable to run the regression with other independent variables (such as family-managed status, firm size, financial leverage, ownership concentration, firm age) in order to determine the nexus of these elements with firm total factor productivity It proved that non-family-owned firms gain more productivity than family-owned firms Moreover, this research found the positive effect of firm age on firm productivity for the case of family-owned firms; however, there was no relation between firm age and its total factor productivity for case of non-family Huergo and Jaumandreu (2004) revealed that in the beginning operation stage, firm productivity grew quickly at five percent, then this speed would continuously decrease to equal average productivity at two percent during eight years, this is the result for the case of over 2,300 Spanish manufacturing firms in period 1990 - 1998 In this study, the total number of operational year of a firm or firm age is calculated by taking the conducting survey year minus its established year (Saeidi et al., 2015)

Capital structure

In empirical literature, firm’s financial leverage or capital structure was a crucial control variable The relation of firm capital structure and total factor productivity was well analyzed not only in empirical studies but also in theories In one hand, agency cost theory proposed that debt negatively influent on firm productivity According to Jensen and Meckling (1976), the agency theory also assumed to have conflicts among owners and hired managers due to their differential self-interest, which caused for the agency cost of equity The default risk of paying high-interest rate was a kind of agency cost that firm would face Therefore,

Myers (1977) demonstrated that firms had lower debt ratio would execute more effective than those had higher debt ratio Furthermore, Kim (2006) found the negative relation between debt ratio and firm total factor productivity by analyzing Korean manufacturing firms data They also found the debt ratio impact negatively on productivity within Chaebols firms (which was managed by a family member, had liability dependent, and diversity of business activities) In another hand, companies were suggested to pay out their free cash flow to investors to avoid using its improper by managers follow free cash flow theory (Jensen, 1986) Thus, higher financial leverage forced firms to make more money to facilitate their liability as well as avoid misusing free cash flow Firms debt impact positively on firm’s productivity in this case Margaritis and Psillaki (2010) found that capital structure of firm correlated positively with its efficient, this impact was stronger for chemical and textile firms when analyzed a dataset comprises three main France industries: chemicals, computers, and textiles They offered the two-stage method to determine this nexus In the first stage, their study implied an analysis of data envelopment and distance function method to calculate firm’s efficiency In the second stage, taking firm efficiency result as a dependent variable to run OLS regression with independent variables (financial leverage, asset structure, growth opportunities, firm size, ownership status, profitability) to estimate the relation between firm’s financial leverage and its efficiency In many previous studies, financial leverage was typically defined as the ratio of total debt (or total equity) to total assets (Wu & Shen, 2013) In this study, capital structure or financial leverage equal total debt divided by total assets

Innovation

In term of innovation effect, there are many empirical studies investigate the impact of innovation on firm total factor productivity such as : Belderbos et al (2004);Parisi et al (2006);Santos et al (2014) Crépon et al (1998) found that innovative inputs create innovative outputs, and then innovative output influenced on the performance of enterprises Belderbos et

al (2004) analyzed the effect of innovation factors on firm performance by using a dataset of

2056 Netherland manufacturing enterprises They revealed that both R& D collaboration factor and intensity of innovation variable influent positively on firm’s productivity growth The result of Parisi et al (2006) proved that innovative product and process have a massive

impact on firm total factor productivity However, there were some researches demonstrate that innovation factors do not affect firm productivity Besides, Santos et al (2014) proved that firm productivity could not be explained by innovation efforts from the investment Atuahene-Gima and Ko (2001) also explained the unimportant effect of innovation factors on firm’s productivity via uncertainly innovative characteristic Since this study does not focus on the relationship between innovation and productivity, the innovation is only mentioned as a control variable to strengthen the accuracy of the regression Therefore, this study employs dummy variable for innovation which was applied in many studies such as (Crépon et al., 1998); Hall et al (2009) In this situation, innovation variable equals one if the firm spends money on innovation activities during the surveyed year and equal zero if contrast

All the variables are used in this study will be summarized as followed: