Tóm tắt luận án: Knowledge spillover, sectoral innovation and firm total factor productivity The case of manufacturing industries in Vietnam.

Knowledge spillover, sectoral innovation and firm total factor productivity The case of manufacturing industries in Vietnam.Knowledge spillover, sectoral innovation and firm total factor productivity The case of manufacturing industries in Vietnam.Knowledge spillover, sectoral innovation and firm total factor productivity The case of manufacturing industries in Vietnam.Knowledge spillover, sectoral innovation and firm total factor productivity The case of manufacturing industries in Vietnam.Knowledge spillover, sectoral innovation and firm total factor productivity The case of manufacturing industries in Vietnam.

MINISTRY OF EDUCATION AND TRAINING UNIVERSITY OF ECONOMICS HO CHI MINH CITY

-NGUYEN THI HOANG OANH

KNOWLEDGE SPILLOVER, SECTORAL INNOVATION AND FIRM TOTAL FACTOR PRODUCTIVITY: THE CASE OF MANUFACTURING INDUSTRIES

1. Dr Pham Khanh Nam

2. Dr Pham Hoang Van

HO CHI MINH CITY, 2021

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Dissertation is completed at:

Người hướng dẫn khoa học:

Academic supervisor 1: Dr Pham Khanh Nam

Academic supervisor 2: Dr Pham Hoang Van

PUBLICATIONS OF RESULTS

Nguyen Thi Hoang Oanh, 2019 Determinants of Firms’ Total Factor

Productivity in Manufacturing Industry in Vietnam: An Approach of

a Cross-Classified Model Journal of Asian Business and Economic Studies (JABES), Volumn 26, Special Issue 01 Available from:

http://jabes.ueh.edu.vn/Home/SearchArticle?volume_id=c8436509- 3f9c-ded2-9119-c243428cc183

Nguyen Thi Hoang Oanh, 2018 Sector Innovation Capacity in

Vietnamese Enterprises: Spillover effects from Research andDevelopment (R&D), Foreign Direct Investment (FDI) and Trade

Asian Conference on Business and Economic Studies (ACBES),

University of Economics Ho Chi Minh City, Ho Chi Minh CityPublishing House of Economics (ISBN: 978-604-922-660-1), pp.265- 284

This study developed the framework of knowledge spillovers

at sector level and investigated these spillover effects of researchand development (R&D), foreign direct investment (FDI) andtrade activities on sectoral innovation by Spatial RegressionModels Besides, the study examined the spillover effects ofsectoral innovation and provincial human resources on firms’TFP with 7,236 enterprises in 38 sectors of Vietnamesemanufacturing industries, located in 62 provinces by Cross-Classified Models By Spatial Regression Models with to 38manufacturing sectors in correspondence to Input/Output tablefrom 2010 to 2014, the intra-industry rather than inter-industryspillover effects were found to be significant; that approved thehypothesis of MAR rather than Jacobs externalities In particular,only R&D and export activities were found to have significantlypositive effects on innovation activities at sector level Incontrast, FDI and import activities seem to have negative impact

on innovation activities In cross-classified models, firms’characteristics in comparison with characteristics of sectors andprovinces may have the highest explanation on the heterogeneity

in firms’ TFP The firm size, capital intensive and exportorientation were found to have stably significantly positiveimpacts on firms’ TFP The sectoral innovation might turn tohave positive impacts on the productivity of firms in that sectorafter one year Besides, the externalities of human resources inprovinces on firms’ productivity were found to be positive

Keywords: Knowledge Spillovers, Sectoral Innovation, TFP, Spatial

Regression Model, Cross-Classified Model

1. INTRODUCTION

1.1.Problem Statement

1.1.1.The importance of the topics in this thesis

It is important to investigate the role of knowledge spillovers

on innovation at sector level As stated by Aghion and Jaravel(2015), “innovations in one firm or one sector often build onknowledge that was created by innovations in another firm orsector” Mehrizi and Ve (2008) argued that sector-level analysisenables the study to link firm level determinants to macro-economic conditions Malerba (2002) also emphasized the role ofsector-level analysis in investigating innovative and productionactivities According to Padoan (1999), adopting a sectoralperspective may investigate the knowledge accumulation anddiffusion In our knowledge, there are few studies on the roles ofchannels of knowledge spillover on sector innovation capacity InVietnam, there are few studies on innovation and most of thesestudies focused on firm level Therefore, the first main objective inthis study is to investigate the role of knowledge spillover onsectoral innovation through three channels including R&D, FDIand trade activities by spatial regression models

It is also important to examine on heterogeneity of firms’ TFP

in considering both firms’ characteristics and spillover effectsfrom sectors and regions TFP is understood as the residual ofoutput that is not contributed by the amount of capital and labor

In Solow model (1956), the residual is a black box representingtechnical change that leads to a sustainable development.Obviously, the

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heterogeneity in firms’ TFP is mainly originated from thedifferences in firms’ characteristics Acemoglu (2009) stated that

“the heterogeneity in TFP are not necessarily due to technology inthe narrow sense For instance, two firms have adopted the sametechnology but make use of these techniques in different wayswith different degrees of efficiency” However, even if thesefirms adopted similar technology, they still have differences inTFP These differences may be originated from the characteristics

of their sectors or their location

It is important to examine to the determinants of firms' TFP bymultileveled factors in a multilevel cross-classified model Thismodel could isolate the impacts of elements at multilevelincluding firm, sectoral, regional or provincial dimensions.However, most of studies on firms’ TFP focused on thedeterminants as firms’ characteristics In Vietnam, studies on TFPare still very limited (CIEM, 2010) although TFP is recentlyperceived as a key role of development quality This study couldmake a contribution as a new approach in investigating TFP inVietnam by applying the multileveled cross-classified model inthe second objective In addition, the study may imply policiesnot only for firms but also for sectors and regions

1.1.2.The gaps and the new aspects in this thesis

There are three new aspects respectively on theoretical framework, methodology and context in this study At theoreticalframework, the knowledge spillover at sector level was developed

by aggregating the stock of knowledge at firm level as in Cohen

and Levinthal (1989) Our model is new when it indicated notonly the intra-industry spillover but also the inter-industryspillover at sector level and investigated the channel ofknowledge spillover from R&D, FDI and trade In addition, thisstudy revealed the spillover effects of sectoral innovation andprovincial human capital on firms’ productivity basing on theideas of intra-industry economies of localization (Marshall,1920), intra-sectoral spillovers (Griliches, 1992) and the role ofhuman capital spillover on productivity (Moretti, 2004).

In regarding to the methodology, the study has two newapproaches Innitially, the study adopted spatial regression model

in investigating sources of knowledge spillovers on sectoralinnovation Then, a Cross-classified model was applied to make

an efficient estimate of the effects on firms’ productivity fromfirm level, sectoral level and provincial level

Besides, knowledge spillover, innovation and productivity,integrated in this study, is a necessary topic in the context ofmanufacturing sector in Vietnam In the context of Vietnam, nostudy investigated the determinants of firms’ TFP at firm, sectorand province level by Cross-classified model Some studies haveconsidered such as FDI transaction (Ni et al., 2015; Vu Hoang

Duong and Le Van Hung, 2017; Khanh Le Phi Ho et al., 2018;

Nguyen, 2017) or agglomeration economies in manufacturingindustries (Francois and Nguyen, 2017; Toshitaka et al.; 2017) orimport competition in the sector (Doan et al., 2016) However,there has been no study applying Cross- classified model.Adopting this model in the case of 63 provinces and 38 sectors in

manufacturing industry makes this study more valuable in the context of Vietnam.

1.2.RESEARCH OBJECTIVES

The first general objective is to investigate channels ofknowledge spillovers on sectoral innovation in manufacturingindustries in Vietnam, the study focuses on the followingresearch questions:

1.1.Is sectoral innovation directly affected by R&Dactivities of that sector in manufacturing industries in Vietnam?

1.2.Is sectoral innovation indirectly affected by R&Dactivities of other sectors in manufacturing industries inVietnam?

1.3.Is sectoral innovation directly affected by transactionswith FDI enterprises in that sector in manufacturing industries inVietnam?

1.4.Is sectoral innovation indirectly affected by transactionswith FDI enterprises in other sectors in manufacturing industries

2.1. How much heterogeneity in firms’ total factorproductivity is explained by firm-level, sector-level andprovince- level determinants?

2.2. Does firms’ size have impact on firms’ TFP inmanufacturing industries in Vietnam?

2.3.Does the capital intensity in firms have impact on theirTFP?

2.4.Is there difference in TFP of exported firms and non- exported firms?

2.5.Is firms’ TFP affected by their sectoral innovation in manufacturing industries in Vietnam?

2.6.Does the human resource in a province have impact on the TFP of firms in that province?

1.3.RESEARCH METHODOLOGY and

RESEARCH SCOPE

In order to investigate three channels of knowledgespillovers on sector innovation capacity, this study applied theSpatial Regression Then the study applied the cross classifiedmodel to examine the heterogeneity in firm productivity fromthree groups of determinants including sector, regional and firmlevel This study made use of the data of Vietnam EnterprisesSurvey (VES) and Vietnam Technology and CompetitivenessSurvey (TCS) in addition to the use of Input Output (I/O) ofVietnam in 2012 Besides, the study also used the annuallysurveyed data on province of General Statistics Office (GSO).The analysis unit in investigating the effect of R&D, FDI andtrade on sectoral innovation is sector The sector unit isaggregated

from data on Vietnamese firms in manufacturing from the year of

2010 to 2014 The relations among sectors are determined basingthe intermediary transaction in the Input Output of Vietnam in

2012 By spatial regression model, the study finds the direct aswell as indirect impact of R&D, FDI and trade on sectoralinnovation

Meanwhile, firm is the analysis unit in investigating theimpacts of characteristics at firm- level, regional and sectorallevel on firms’ total factor productivity (TFP) Firms are also inmanufacturing industries in Vietnam with research period fromthe year of 2011 to 2014 Using TCS and VES data, the studyaccesses the characteristics at the firm level The sectoralcharacteristics in the model is also measured from these data Inaddition, the annual province data on Province Competitive Index(PCI) is also used to determine the human resources at theprovince

1.4. RESEARCH CONTRIBUTION

This study could have contributions on theoreticalperspective as well as policy implication On theoreticalperspective, this study developed the framework and tested thehypothesis of knowledge spillover at sector level The studyapplied a new approach, Spatial Regression Model, to investigatethe knowledge spillovers among sectors Besides, the study tried

to explore the black box of contextual factors on firms’ TFP Inparticular, the study applied the Cross-classified Model toinvestigate the spillover effects of innovation activities at sectorlevel and human resources at province level on firms’ TFP.Determining the core spillover factors on sector innovationcapacity is key information for policymakers to enhance thissector

capacity In addition, the Cross-classified Model also enablespolicymakers to know how important are firm characteristics,sectoral and provincial level attributed to firms’ TFP.

1.5. STRUCTURE OF THIS STUDY

This study consists of five chapters The first chapter is theIntroduction The second chapter is the Literature Review thatcontains the Theoretical framework and Empirical Studies of twogeneral objectives The next chapter, Methodology, shall illustratethe nature of the Spatial Regression Model and the Cross-Classified Model In addition, the chapter also presents the ModelSpecification, Variable measurement and the data The twofollowing chapters is the chapters of Result and Discussion Onechapter provides results and discussions on the SectoralInnovation and Spillover effects The other chapter providesresults and discussions on heterogeneity in TFP of Vietnamesemanufacturing firms The final chapter is the Conclusion andPolicy Implications

transmitted between agents (Romer, 1990) Kaiser (1960) alsostated that knowledge spillovers may be originated from failures

in the protecting knowledge generated in an innovating firm Theamount of this non- appropriable knowledge is called ‘knowledgespillover’ Basing on these ideas, Griliches (1992) proposed thatinvestments in knowledge have a high propensity to spill over forcommercialization by third-party firms which do not pay for thefull cost of accessing and implementing those ideas

2.1.2.Innovation

OECD (2005) made the definition of innovation as follows

“an innovation is the implementation of a new or significantlyimproved product (good or service), or process, a new marketingmethod, or a new organizational method in business practices,workplace organization or external relations.”

Due to the trend of economic development, several studies paymore attention development of organization and marketing termsand base on innovation definition in OECD (2005) This manualcharacterized innovation as the introduction of a new orsignificantly improved product (goods or services); a new orfundamentally improved process, a new marketing method, or anew organization method in terms of business practice,association of work environment

2.1.3.Knowledge production function and the determination

of innovation in this study

This study based on the knowledge production function(KPF), formerly proposed by Pakes and Griliches (1984), to

determining the innovation and its determinants in the model.Pakes and Griliches (1984) illustrated the simplified diagram ofthe knowledge production function as follows:

Figure 0 The framework of knowledge production function

Source: Pakes and Griliches (1984)

In this diagram, K˙ is produced by a knowledge production

function (KPF) which translates past research expenditures, R, and a disturbance term, U, into inventions The disturbance term

reflects the combined effect of other nonformal R&D inputs andthe inherent randomness in the production of inventions

2.1.4.Sectoral Innovation System (SIS) and its determinants

According to Malerba (2002), the founder of sectoralinnovation system, “sectors provide a key level of analysis foreconomists, nosiness scholars, technologists and economichistorians in the examination of innovative and productionactivities” He proposed that a sectoral system includes productsand the set of agents which make market and non-market

interactions for creating, producing and selling those products Asectoral system has a particular knowledge base, technologies,inputs and demand The interactions may emerge among theagents in a sectoral system Agents are known as individuals andorganizations at various levels of aggregation The interactionamong agents may be created through process of communication,exchange, cooperation, competition and command, and theseinteractions are shaped by institutions Therefore, he suggestedthat the sectoral innovation system could be used to explain thecreation, absorption, sharing and utilization of knowledge andinnovation in a sector.

2.1.5.Total Factor Productivity (TFP)

Total Factor Productivity (TFP) identifies the portion ofoutput not explained by traditionally measured inputs of labor andcapital It was widely known that output is a function of the inputsused by a firm and its productivity (Katayama, Lu and Tybout,2009) Basically, the Cobb-Douglas production function is used tomeasure TFP

The choice of measurement methods on TFP in this studybased on the comparison of four principal methods includingFixed effects, Instrumental variables and GMM, the semiparametric estimation algorithm developed by Olley and Pakes(1996) and the semi parametric estimation algorithm developed

by Levinsohn and Petrin (2003)

2.2THEORETICAL FRAMEWORK

2.2.1.Developing model on Knowledge Spillovers at sector-level