Overview

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.

Full Product Details

Author:   Lizhi Xing
Publisher:   Springer Verlag, Singapore
Imprint:   Springer Verlag, Singapore
Edition:   1st ed. 2022
Weight:   0.729kg
ISBN:  

9789811692635

ISBN 10:   9811692637
Pages:   358
Publication Date:   09 February 2022
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   Manufactured on demand  
We will order this item for you from a manufactured on demand supplier.

Table of Contents

Preface 1Part I Background 3Chapter 1 Fundamental Issues in This Book 41.1 Concept of Econophysics 41.2 Purpose of Book 41.3 Literature Review 51.3.1 Industrial Complex Network 61.3.2 Global Value Chain 71.3.3 Input-Output Network 81.4 Data Structure 101.4.1 Advantage of IO Table 101.4.2 Available ICIO Database 101.4.3 Hierarchy of Economies 141.4.4 Classification of Industrial Sectors 241.5 ICIO Network Model 241.6 Summary 30Part II Topological Structure 32Chapter 2 Recognize the Trade Roles of Industrial Sectors 332.1 Introduction 332.2 Definition 342.2.1 Trade Types on the GVC 342.2.2 Decomposition of Trade Roles 362.3 Measurement 382.3.1 Statistical Inference on TBPs 382.3.2 Measurment of Dependency 402.4 Empirical Analysis: Economies' Two Sorts of Dependence on Foreign Trade 412.4.1 Statistics on All Economies 422.4.2 Significance of Dual Circulation 432.4.3 Economic Meanings of Network-Based Dependency 452.5 Summary 47Chapter 3 Probe the Industrial Linkages Reasonably and Effectively 483.1 Introduction 483.2 Methodology 493.2.1 Path Issue in Similarity-Weight Network 493.2.2 Revised Floyd-Warshall Algorithm 503.2.3 Theoretical Basis of SRPL in GIVCN Model 523.2.4 Computation of SRPL in Consideration of Self-Loops 553.3 Empirical Analysis: Fragments of GVC 573.3.1 Single-Tuple Motif 573.3.2 Double-Tuple Motif 583.3.3 Triple-Tuple Motif 603.4 Summary 65Chapter 4 Find the Vital Industrial Sectors and IO Relations 664.1 Introduction 664.2 Measurement 674.2.1 Average/Maximum Strongest Relevance Degree 674.2.2 Betweenness Centrality of Node 684.2.3 Betweenness Centrality of Edge 704.2.4 Closeness Centrality of Node 714.3 Connectedness/Compactness of NVC 734.4 Pivotability of Industrial Sectors 774.4.1 Overall Statistics 774.4.2 Cross-National Analysis 784.4.3 Robustness Analysis 814.5 Pivotability of IO Relations 824.5.1 Heterogeneity of Pivotability 824.5.2 Domestic Pivotability 864.5.3 International Pivotability 874.5.4 Global Pivotability 894.6 Coordinates of Industrial Sectors 914.6.1 Overall Statistics 914.6.2 Time-Series Analysis 954.6.3 Cross-Country Analysis 994.6.4 Cross-Sector Analysis 1044.7 Comparison with Similar Studies 1084.8 Summary 108Part III Markov Process 111Chapter 5 Measure the Global Impact of Industrial Sectors 1125.1 Introduction 1125.2 Methodology 1125.2.1 Features of Value Stream in Economic System 1125.2.2 Industrial Impact on the GVC 1135.2.3 Structural Holes Theory in Dynamic Network 1145.3 Measurement 1155.3.1 Random Walk Centrality 1165.3.2 Global Industrial Impact Coefficient 1175.4 Empirical Analysis: Macroeconomic Trend Forecast 1175.4.1 Comparative Analysis with Classic IO Theory 1175.4.2 Robustness Analysis 1205.4.3 Statistics on Major Economies 1255.4.4 Geographical Distribution of GIIC 1295.4.5 Correlation Analysis with GDP 1315.5 Summary 132Chapter 6 Measure the Impact of Final Demands on the Global Production System 1346.1 Introduction 1346.2 Measurement 1346.2.1 Counting First Passage Betweenness 1346.2.2 Global Demand Dependence Index 1366.3 Empirical Analysis: Macroeconomic Trend Forecast 1366.3.1 Robustness Analysis 1366.3.2 The Econometric Analysis of Import/Export and GDDI 1386.3.3 Statistics on the Global Level 1426.3.4 Statistics on the Sectoral Level 1436.4 Discussion 1466.4.1 Economic Difference between Static Metrics and Dynamic Metrics 1466.4.2 Intrinsic Relationship of Dynamic Metrics 1476.4.3 Correlation Analysis between Static Metrics and Dynamic Metrics 1486.5 Summary 150Chapter 7 Industrially Economic Impacts of Trump Administration's Trade Policy toward China 1527.1 Bibliometrics on Sino-US Trade War 1527.2 Decomposition of GIIC 1587.3 Decomposition of GDDI 1607.4 Regression Analysis 1637.5 Simulation on the Year of 2020 1657.6 Conclusion 167Part IV Competition and Collaboration 170Chapter 8 Quantify the Competitive Strength and Weakness of Economies 1718.1 Introduction 1718.2 Methodology 1728.2.1 Bipartite Graph 1728.2.2 Resource Allocation Process 1738.3 Modeling 1768.3.1 Database Selection 1768.3.2 Modeling Framework 1768.3.3 GIVCNBG Model 1788.3.4 GIRCN Model 1808.4 Measurement 1818.4.1 Sector-Level Indices 1818.4.2 Country-Level Indices 1838.4.3 Correlation with GDP 1858.5 Empirical Analysis: Competitive Strength of TPP-Related Nations 1878.5.1 Time-Series Analysis on TPP-Relat ed Nations 1888.5.2 Simulation on International Trade Policy 1928.6 Summary 195Chapter 9 Quantify the Collaborative Opportunity and Threat of Economies 2019.1 Introduction 2019.2 Methodology 2029.3 Modeling 2049.3.1 Database Selection 2049.3.2 GPCCN Model 2079.4 Measurement 2119.4.1 Sector-Level Indices 2119.4.2 Country-Level Indices 2129.4.3 Correlation Analysis between Competitive Strengths and Collaborative Opportunities 2159.5 Empirical Analysis: Collaborative Opportunity of BRI-Related Nations 2169.5.1 Simulation on Asian Nations 2179.5.2 Simulation on European Nations 2229.5.3 Simulation on African Nations 2269.5.4 Results and Discussions 2309.6 Summary 231Part V Evolutionary Mechanism 233Chapter 10 Extract the Backbone of Global Value Chain 23410.1 Introduction 23410.2 Formal Problem Setting 23510.2.1 Global Threshold 23610.2.2 Disparity Filter 23610.3 Proposed Algorithms 23710.3.1 Searching Paths 23810.3.2 Filtering Edges 23810.3.3 Mixed Strategy 24010.4 Results and Discussions 24110.4.1 Preservation of Structural Information 24210.4.2 Preservation of Functional Information 24410.5 Summary 246Chapter 11 Identify the Worldwide Industrial Transfer Pattern 24711.1 Introduction 24711.1.1 Neoclassical School 24811.1.2 Behavioral School 24811.1.3 Institutional School 24811.2 Methodology 24911.2.1 Econometric Model in Industrial Economics 24911.2.2 Link Prediction in Complex Networks 25011.3 Framework 25111.3.1 GISRN Model 25111.3.2 Training and Evaluation Metrics 25211.3.3 Link Prediction Indices 25311.3.4 Accuracy of Prediction Algorithms 25611.4 Empirical Analysis I: Evolutionary Characteristics of Globalization 25711.4.1 Density of GVC Backbone 25711.4.2 Centralization of GVC Backbone 25911.4.3 Global Efficiency of GVC Backbone 26011.5 Empirical Analysis II: Evolutionary Mechanism of Globalization 26111.5.1 Overall Statistics 26311.5.2 Industrial Convergence 26411.5.3 Mega-Merger Tendency 26611.5.4 Industrial Agglomeration 26711.5.5 Niche Advantage 26711.6 Summary 268Chapter 12 Depict the Nested Structure of Production System 27012.1 Introduction 27112.2 Modeling 27212.3 Measurement 27412.3.1 Sorting Methods 27412.3.2 Nestedness Quantification 27512.4 Statistical Analysis 27812.4.1 Divergence Analysis 27812.4.2 Trend Analysis 28012.4.3 Robustness Analysis 28212.4.4 Evolutionary Mechanism 28412.5 Econometric Analysis 28512.5.1 Correlation between Variables 28612.5.2 Regression Model 29012.6 Empirical Analysis II: Brexit's Impact on European Nations 29712.6.1 Brexit 29712.6.2 Simulation Setting 29812.6.3 Results and Discussions 29812.7 Empirical Analysis II: RCEP's Economic Significance to Relevant Nations 30112.7.1 RCEP 30112.7.2 Simulation Setting 30212.7.3 Results and Discussions 30212.8 Summary 307Part VI Causal Inference 309Chapter 13 Connect the Structural Features and Economic Status 31013.1 Introduction 31013.2 Literature Review 31113.3 Econometric Model 31213.4 Hypotheses 31313.4.1 Hypothesis Formulation 31313.4.2 Hypothesis Testing 31413.5 Results and Discussions 31613.5.1 The Effects of Structural Capital 31613.5.2 The Effects of Relational Capital 31813.5.3 The Effects of Cognitive Capital 31913.6 Summary 320Postscript 321Appendix 323References 337

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Author Information

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

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