Abstract

This paper aims at studying the determinants of inward Foreign Direct Investment (FDI) varying with sectors, by considering particularly multinational corporation (MNC)’s location strategies and local technology resources in host industries. Using data from China’s National Bureau of Statistics and National Development and Reform Commission, we empirically analyze the main determinants of industrial inward FDI, across 20 manufacturing sectors (2-digit) in China, over the period 2001-2008, and we are particularly interested in 9 high-technology (HT) and medium-high-technology (MHT) industries. The random effect panel estimations reveal that when industrial technological intensity is controlled, host technology resources are significantly positive determinants for newly inward FDI. The dynamic econometrical approach by System Generalized Method of Moment (GMM) estimations for HT and MHT industries obtain interesting results, which show evident impacts on MNC’s strategic behaviors, brought about by geographic agglomeration (or industrial concentration) effects and local protection (that we will call “new oligopolistic reactions”). Besides, FDI in HT and MHT industries are both market and export seeking. High productivity, large economies of scale, and abundant technology resources attract newly FDI in these industries. This study has two contributions: firstly, it covers the deficiency that many researches on FDI in China only focus on aggregate flow without distinguishing host sector’s characteristics; secondly, it provide the local government some useful suggestions on regional development and industrial policies, especially in technology industries.

Highlights

  • multinational corporation (MNC)’ Foreign Direct Investment (FDI) location strategies are caused by various reasons

  • This paper aims at studying the determinants of inward Foreign Direct Investment (FDI) varying with sectors, by considering multinational corporation (MNC)’s location strategies and local technology resources in host industries

  • Using data from China’s National Bureau of Statistics and National Development and Reform Commission, we empirically analyze the main determinants of industrial inward FDI, across 20 manufacturing sectors (2-digit) in China, over the period 2001-2008, and we are interested in 9 high-technology (HT) and medium-high-technology (MHT) industries

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Summary

Introduction

MNCs’ FDI location strategies are caused by various reasons. During the 1970s, FDI were mainly “NorthNorth” flows which concentrated in Triad regions (US, Europe and Japan) [1]. Instance, China’s international specialization index in high technology industry is close to Germany since 2007, ranking the third place in the world By this way, analyses on determinants of “New North-South” FDI trends need new researches. [17] uses three agglomeration variables which considered both home country agglomeration effects and host industrial specialization, by studying 3902 manufacturing FDI locations in France. [23] employs Total Factor Productivity (TFP) as a proxy of technical efficiency of factor usage and number of people employed in R & D in each industry for measuring labor quality, when analyzing determinants of FDI in manufacturing sectors in Czech Republic Another group of studies prefer to use labor’s education level as a measurement of technology resources [7,24,25]. Our study introduces theoretical background of determinants on industrial FDI, based on industry performance in host country; secondly, it gives the descriptions of variables and hypothesis; thirdly, econometric methods and results are presented; fourthly, it discusses the main findings and gives suggestions on regional development and industrial policies; the final section draws conclusions and outlines perspectives for future research

Theoretical Determinants of Industrial FDI
Host Assets Exploiting
Host Industry Competitiveness of Export and Market Size
Description of Variables and Hypothesis
Independent Variables
Econometric Specifications and Results
Panel Model
Dynamic Panel Model
I1 E1 E2
Discussions and Implications
Findings
Conclusion and Perspectives
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