This book aims to theoretically and empirically enrich the GVC accounting framework with statistical physics and complex network theory from the perspective of econophysics, thus adding up to the existing theories. Besides, it also aims at capturing the essences of network models such as topological complexity, hierarchy, transmissibility, interaction, and causality and reflecting the objective interrelations among economies or between economies and economic systems on the GVC, so as to reveal the inherent evolution of the cross-regional and even global economic systems.

Auteur
Lizhi Xing, Ph. D. in management, is Associate Researcher in College of Economics and Management, Beijing University of Technology. His work adopts Inter-Country InputOutput (ICIO), also called Multi-Region InputOutput (MRIO), data to build weighted and directed complex network models, which are the basis of measurement, simulation, and prediction on the international trade.

Contenu
Preface1Part I Background3Chapter 1 Fundamental Issues in This Book41.1 Concept of Econophysics41.2 Purpose of Book41.3 Literature Review51.3.1 Industrial Complex Network61.3.2 Global Value Chain71.3.3 Input-Output Network81.4 Data Structure101.4.1 Advantage of IO Table101.4.2 Available ICIO Database101.4.3 Hierarchy of Economies141.4.4 Classification of Industrial Sectors241.5 ICIO Network Model241.6 Summary30Part II Topological Structure32Chapter 2 Recognize the Trade Roles of Industrial Sectors332.1 Introduction332.2 Definition342.2.1 Trade Types on the GVC342.2.2 Decomposition of Trade Roles362.3 Measurement382.3.1 Statistical Inference on TBPs382.3.2 Measurment of Dependency402.4 Empirical Analysis: Economies' Two Sorts of Dependence on Foreign Trade412.4.1 Statistics on All Economies422.4.2 Significance of Dual Circulation432.4.3 Economic Meanings of Network-Based Dependency452.5 Summary47Chapter 3 Probe the Industrial Linkages Reasonably and Effectively483.1 Introduction483.2 Methodology493.2.1 Path Issue in Similarity-Weight Network493.2.2 Revised Floyd-Warshall Algorithm503.2.3 Theoretical Basis of SRPL in GIVCN Model523.2.4 Computation of SRPL in Consideration of Self-Loops553.3 Empirical Analysis: Fragments of GVC573.3.1 Single-Tuple Motif573.3.2 Double-Tuple Motif583.3.3 Triple-Tuple Motif603.4 Summary65Chapter 4 Find the Vital Industrial Sectors and IO Relations664.1 Introduction664.2 Measurement674.2.1 Average/Maximum Strongest Relevance Degree674.2.2 Betweenness Centrality of Node684.2.3 Betweenness Centrality of Edge704.2.4 Closeness Centrality of Node714.3 Connectedness/Compactness of NVC734.4 Pivotability of Industrial Sectors774.4.1 Overall Statistics774.4.2 Cross-National Analysis784.4.3 Robustness Analysis814.5 Pivotability of IO Relations824.5.1 Heterogeneity of Pivotability824.5.2 Domestic Pivotability864.5.3 International Pivotability874.5.4 Global Pivotability894.6 Coordinates of Industrial Sectors914.6.1 Overall Statistics914.6.2 Time-Series Analysis954.6.3 Cross-Country Analysis994.6.4 Cross-Sector Analysis1044.7 Comparison with Similar Studies1084.8 Summary108Part III Markov Process111Chapter 5 Measure the Global Impact of Industrial Sectors1125.1 Introduction1125.2 Methodology1125.2.1 Features of Value Stream in Economic System1125.2.2 Industrial Impact on the GVC1135.2.3 Structural Holes Theory in Dynamic Network1145.3 Measurement1155.3.1 Random Walk Centrality1165.3.2 Global Industrial Impact Coefficient1175.4 Empirical Analysis: Macroeconomic Trend Forecast1175.4.1 Comparative Analysis with Classic IO Theory1175.4.2 Robustness Analysis1205.4.3 Statistics on Major Economies1255.4.4 Geographical Distribution of GIIC1295.4.5 Correlation Analysis with GDP1315.5 Summary132Chapter 6 Measure the Impact of Final Demands on the Global Production System1346.1 Introduction1346.2 Measurement1346.2.1 Counting First Passage Betweenness1346.2.2 Global Demand Dependence Index1366.3 Empirical Analysis: Macroeconomic Trend Forecast1366.3.1 Ro...