Complex Network-Based Global Value Chain Accounting System
From the Perspective of Econophysics
(Sprache: Englisch)
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...
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Klappentext zu „Complex Network-Based Global Value Chain Accounting System “
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.
Inhaltsverzeichnis zu „Complex Network-Based Global Value Chain Accounting System “
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
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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 Robustness Analysis1366.3.2 The Econometric Analysis of Import/Export and GDDI1386.3.3 Statistics on the Global Level1426.3.4 Statistics on the Sectoral Level1436.4 Discussion1466.4.1 Economic Difference between Static Metrics and Dynamic Metrics1466.4.2 Intrinsic Relationship of Dynamic Metrics1476.4.3 Correlation Analysis between Static Metrics and Dynamic Metrics1486.5 Summary150Chapter 7 Industrially Economic Impacts of Trump Administration's Trade Policy toward China1527.1 Bibliometrics on Sino-US Trade War1527.2 Decomposition of GIIC1587.3 Decomposition of GDDI1607.4 Regression Analysis1637.5 Simulation on the Year of 20201657.6 Conclusion167Part IV Competition and Collaboration170Chapter 8 Quantify the Competitive Strength and Weakness of Economies1718.1 Introduction1718.2 Methodology1728.2.1 Bipartite Graph1728.2.2 Resource Allocation Process1738.3 Modeling1768.3.1 Database Selection1768.3.2 Modeling Framework1768.3.3 GIVCNBG Model1788.3.4 GIRCN Model1808.4 Measurement1818.4.1 Sector-Level Indices1818.4.2 Country-Level Indices1838.4.3 Correlation with GDP1858.5 Empirical Analysis: Competitive Strength of TPP-Related Nations1878.5.1 Time-Series Analysis on TPP-Relat ed Nations1888.5.2 Simulation on International Trade Policy1928.6 Summary195Chapter 9 Quantify the Collaborative Opportunity and Threat of Economies2019.1 Introduction2019.2 Methodology2029.3 Modeling2049.3.1 Database Selection2049.3.2 GPCCN Model2079.4 Measurement2119.4.1 Sector-Level Indices2119.4.2 Country-Level Indices2129.4.3 Correlation Analysis between Competitive Strengths and Collaborative Opportunities2159.5 Empirical Analysis: Collaborative Opportunity of BRI-Related Nations2169.5.1 Simulation on Asian Nations2179.5.2 Simulation on European Nations2229.5.3 Simulation on African Nations2269.5.4 Results and Discussions2309.6 Summary231Part V Evolutionary Mechanism233Chapter 10 Extract the Backbone of Global Value Chain23410.1 Introduction23410.2 Formal Problem Setting23510.2.1 Global Threshold23610.2.2 Disparity Filter23610.3 Proposed Algorithms23710.3.1 Searching Paths23810.3.2 Filtering Edges23810.3.3 Mixed Strategy24010.4 Results and Discussions24110.4.1 Preservation of Structural Information24210.4.2 Preservation of Functional Information24410.5 Summary246Chapter 11 Identify the Worldwide Industrial Transfer Pattern24711.1 Introduction24711.1.1 Neoclassical School24811.1.2 Behavioral School24811.1.3 Institutional School24811.2 Methodology24911.2.1 Econometric Model in Industrial Economics24911.2.2 Link Prediction in Complex Networks25011.3 Framework25111.3.1 GISRN Model25111.3.2 Training and Evaluation Metrics25211.3.3 Link Prediction Indices25311.3.4 Accuracy of Prediction Algorithms25611.4 Empirical Analysis I: Evolutionary Characteristics of Globalization25711.4.1 Density of GVC Backbone25711.4.2 Centralization of GVC Backbone25911.4.3 Global Efficiency of GVC Backbone26011.5 Empirical Analysis II: Evolutionary Mechanism of Globalization26111.5.1 Overall Statistics26311.5.2 Industrial Convergence26411.5.3 Mega-Merger Tendency26611.5.4 Industrial Agglomeration26711.5.5 Niche Advantage26711.6 Summary268Chapter 12 Depict the Nested Structure of Production System27012.1 Introduction27112.2 Modeling27212.3 Measurement27412.3.1 Sorting Methods27412.3.2 Nestedness Quantification27512.4 Statistical Analysis27812.4.1 Divergence Analysis27812.4.2 Trend Analysis28012.4.3 Robustness Analysis28212.4.4 Evolutionary Mechanism28412.5 Econometric Analysis28512.5.1 Correlation between Variables28612.5.2 Regression Model29012.6 Empirical Analysis II: Brexit's Impact on European Nations29712.6.1 Brexit29712.6.2 Simulation Setting29812.6.3 Results and Discussions29812.7 Empirical Analysis II: RCEP's Economic Significance to Relevant Nations30112.7.1 RCEP30112.7.2 Simulation Setting30212.7.3 Results and Discussions30212.8 Summary307Part VI Causal Inference309Chapter 13 Connect the Structural Features and Economic Status31013.1 Introduction31013.2 Literature Review31113.3 Econometric Model31213.4 Hypotheses31313.4.1 Hypothesis Formulation31313.4.2 Hypothesis Testing31413.5 Results and Discussions31613.5.1 The Effects of Structural Capital31613.5.2 The Effects of Relational Capital31813.5.3 The Effects of Cognitive Capital31913.6 Summary320Postscript321Appendix323References337
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Autoren-Porträt von Lizhi Xing
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.
Bibliographische Angaben
- Autor: Lizhi Xing
- 2022, 1st ed. 2022, XV, 358 Seiten, 153 farbige Abbildungen, Masse: 15,5 x 23,5 cm, Gebunden, Englisch
- Verlag: Springer, Berlin
- ISBN-10: 9811692637
- ISBN-13: 9789811692635
Sprache:
Englisch
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