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

Dissertation is completed at:

Người hướng dẫn khoa học:

Academic supervisor 1: Dr Pham Khanh Nam

Academic supervisor 2: Dr Pham Hoang Van

……… Time: Date This dissertation could be accessed at the following library:

http://jabes.ueh.edu.vn/Home/SearchArticle?volume_id=c8436509-Nguyen Thi Hoang Oanh, 2018 Sector Innovation Capacity in Vietnamese Enterprises: Spillover effects from Research and Development (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 City Publishing House of Economics (ISBN: 978-604-922-660-1), pp 265-284

Abstract

This study developed the framework of knowledge spillovers

at sector level and investigated these spillover effects of research and development (R&D), foreign direct investment (FDI) and trade activities on sectoral innovation by Spatial Regression Models Besides, the study examined the spillover effects of sectoral innovation and provincial human resources on firms’ TFP with 7,236 enterprises in 38 sectors of Vietnamese manufacturing industries, located in 62 provinces by Cross-Classified Models

By Spatial Regression Models with to 38 manufacturing sectors

in correspondence to Input/Output table from 2010 to 2014, the intra-industry rather than inter-industry spillover effects were found to be significant; that approved the hypothesis of MAR rather than Jacobs externalities In particular, only R&D and export activities were found to have significantly positive effects

on innovation activities at sector level In contrast, FDI and import activities seem to have negative impact on innovation activities In cross-classified models, firms’ characteristics in comparison with characteristics of sectors and provinces may have the highest explanation on the heterogeneity in firms’ TFP The firm size, capital intensive and export orientation were found

to have stably significantly positive impacts on firms’ TFP The sectoral innovation might turn to have positive impacts on the productivity of firms in that sector after one year Besides, the externalities of human resources in provinces 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 on knowledge that was created by innovations in another firm or sector” Mehrizi and Ve (2008) argued that sector-level analysis enables the study

to link firm level determinants to macro-economic conditions Malerba (2002) also emphasized the role of sector-level analysis in investigating innovative and production activities According to Padoan (1999), adopting a sectoral perspective may investigate the knowledge accumulation and diffusion In our knowledge, there are few studies on the roles of channels of knowledge spillover on sector innovation capacity In Vietnam, there are few studies on innovation and most of these studies focused on firm level Therefore, the first main objective in this study is to investigate the role of knowledge spillover on sectoral innovation through three channels including R&D, FDI and trade activities by spatial regression models

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

in considering both firms’ characteristics and spillover effects from sectors and regions TFP is understood as the residual of output that

is not contributed by the amount of capital and labor In Solow model (1956), the residual is a black box representing technical change that leads to a sustainable development Obviously, the

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

“the heterogeneity in TFP are not necessarily due to technology in the narrow sense For instance, two firms have adopted the same technology but make use of these techniques in different ways with different degrees of efficiency” However, even if these firms adopted similar technology, they still have differences in TFP 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 by multileveled factors in a multilevel cross-classified model This model could isolate the impacts of elements at multilevel including firm, sectoral, regional or provincial dimensions However, most

of studies on firms’ TFP focused on the determinants as firms’ characteristics In Vietnam, studies on TFP are still very limited (CIEM, 2010) although TFP is recently perceived as a key role of development quality This study could make a contribution as a new approach in investigating TFP in Vietnam by applying the multileveled cross-classified model in the second objective In addition, the study may imply policies not 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 frame work, methodology and context in this study At theoretical framework, 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 not only the intra-industry spillover but also the inter-industry spillover at sector level and investigated the channel of knowledge spillover from R&D, FDI and trade In addition, this study revealed the spillover effects of sectoral innovation and provincial human capital on firms’ productivity basing on the ideas of intra-industry economies of localization (Marshall, 1920), intra-sectoral spillovers (Griliches, 1992) and the role of human capital spillover

Besides, knowledge spillover, innovation and productivity, integrated in this study, is a necessary topic in the context of manufacturing sector in Vietnam In the context of Vietnam, no study investigated the determinants of firms’ TFP at firm, sector and province level by Cross-classified model Some studies have considered 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 manufacturing industries (Francois and Nguyen, 2017; Toshitaka et al.; 2017) or import 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 of knowledge spillovers on sectoral innovation in manufacturing industries in Vietnam, the study focuses on the following research questions:

1.1 Is sectoral innovation directly affected by R&D activities

of that sector in manufacturing industries in Vietnam?

1.2 Is sectoral innovation indirectly affected by R&D activities of other sectors in manufacturing industries in Vietnam? 1.3 Is sectoral innovation directly affected by transactions with FDI enterprises in that sector in manufacturing industries in Vietnam?

1.4 Is sectoral innovation indirectly affected by transactions with FDI enterprises in other sectors in manufacturing industries

in Vietnam?

1.5 Is sectoral innovation directly affected by trade activities

in that sector in manufacturing industries in Vietnam?

1.6 Is sectoral innovation indirectly affected by trade activities in other sectors in manufacturing industries in Vietnam? The second objective of this study is to investigate the impacts

of characteristics at firm- level, regional and sectoral level on firms’ total factor productivity (TFP) with the following research questions:

2.1 How much heterogeneity in firms’ total factor productivity is explained by firm-level, sector-level and province-level determinants?

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

2.3 Does the capital intensity in firms have impact on their TFP?

2.4 Is there difference in TFP of exported firms and exported firms?

non-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 knowledge spillovers

on sector innovation capacity, this study applied the Spatial Regression Then the study applied the cross classified model to examine the heterogeneity in firm productivity from three groups

of determinants including sector, regional and firm level This study made use of the data of Vietnam Enterprises Survey (VES) and Vietnam Technology and Competitiveness Survey (TCS) in addition to the use of Input Output (I/O) of Vietnam in 2012 Besides, the study also used the annually surveyed data on province

of General Statistics Office (GSO)

The analysis unit in investigating the effect of R&D, FDI and trade on sectoral innovation is sector The sector unit is aggregated

from data on Vietnamese firms in manufacturing from the year of

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

2012 By spatial regression model, the study finds the direct as well

as indirect impact of R&D, FDI and trade on sectoral innovation Meanwhile, firm is the analysis unit in investigating the impacts of characteristics at firm- level, regional and sectoral level

on firms’ total factor productivity (TFP) Firms are also in manufacturing industries in Vietnam with research period from the year of 2011 to 2014 Using TCS and VES data, the study accesses the characteristics at the firm level The sectoral characteristics in the model is also measured from these data In addition, the annual province data on Province Competitive Index (PCI) is also used to determine the human resources at the province

1.4 RESEARCH CONTRIBUTION

This study could have contributions on theoretical perspective

as well as policy implication On theoretical perspective, this study developed the framework and tested the hypothesis of knowledge spillover at sector level The study applied a new approach, Spatial Regression Model, to investigate the knowledge spillovers among sectors Besides, the study tried to explore the black box of contextual factors on firms’ TFP In particular, the study applied the Cross-classified Model to investigate the spillover effects of innovation activities at sector level and human resources at province level on firms’ TFP

Determining the core spillover factors on sector innovation capacity is key information for policymakers to enhance this sector

capacity In addition, the Cross-classified Model also enables policymakers 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 the Introduction The second chapter is the Literature Review that contains the Theoretical framework and Empirical Studies of two general objectives The next chapter, Methodology, shall illustrate the nature of the Spatial Regression Model and the Cross-Classified Model In addition, the chapter also presents the Model Specification, Variable measurement and the data The two following chapters is the chapters of Result and Discussion One chapter provides results and discussions on the Sectoral Innovation and Spillover effects The other chapter provides results and discussions on heterogeneity in TFP of Vietnamese manufacturing firms The final chapter is the Conclusion and Policy Implications

to another The concept of this spillover is originated from the public good nature of knowledge which is non-rival and non-excludable (Arrow, 1962) Depending on types of knowledge, the knowledge spillovers could be voluntarily or involuntarily

transmitted between agents (Romer, 1990) Kaiser (1960) also stated that knowledge spillovers may be originated from failures in the protecting knowledge generated in an innovating firm The amount of this non- appropriable knowledge is called ‘knowledge spillover’ Basing on these ideas, Griliches (1992) proposed that investments in knowledge have a high propensity to spill over for commercialization by third-party firms which do not pay for the full 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 significantly improved product (good or service), or process, a new marketing method, or a new organizational method in business practices, workplace organization or external relations.”

Due to the trend of economic development, several studies pay more attention development of organization and marketing terms and base on innovation definition in OECD (2005) This manual characterized innovation as the introduction of a new or significantly improved product (goods or services); a new or fundamentally improved process, a new marketing method, or a new 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 of the knowledge production function as follows:

Figure 0 The framework of knowledge production function

Source: Pakes and Griliches (1984)

In this diagram, 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 and the inherent randomness in the production of inventions

2.1.4 Sectoral Innovation System (SIS) and its determinants

According to Malerba (2002), the founder of sectoral innovation system, “sectors provide a key level of analysis for economists, nosiness scholars, technologists and economic historians in the examination of innovative and production activities” He proposed that a sectoral system includes products and the set of agents which make market and non-market

interactions for creating, producing and selling those products A sectoral system has a particular knowledge base, technologies, inputs and demand The interactions may emerge among the agents

in a sectoral system Agents are known as individuals and organizations at various levels of aggregation The interaction among agents may be created through process of communication, exchange, cooperation, competition and command, and these interactions are shaped by institutions Therefore, he suggested that the sectoral innovation system could be used to explain the creation, absorption, sharing and utilization of knowledge and innovation in a sector

2.1.5 Total Factor Productivity (TFP)

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

The choice of measurement methods on TFP in this study based on the comparison of four principal methods including Fixed effects, Instrumental variables and GMM, the semi parametric estimation algorithm developed by Olley and Pakes (1996) and the semi parametric estimation algorithm developed by Levinsohn and Petrin (2003)

2.2 THEORETICAL FRAMEWORK

2.2.1 Developing model on Knowledge Spillovers at sector-level