Contents:Preface1. IntroductionMasahisa Fujita, Satoru Kumagai and Koji NishikimiPART I: BASIC VIEWPOINTS ON EAST ASIAN ECONOMIC INTEGRATION2. Regional Integration in East Asia: Perspectives of Spatial and Neoclassical EconomicsMasahisa Fujita and Nobuaki Hamaguchi3. Specialization and Agglomeration Forces of Economic IntegrationKoji NishikimiPART II: GENERAL VIEWS ON EAST ASIAN ECONOMIC INTEGRATION4. Industrial Clustering and MNE Management in East Asia: Recent Progress and Prospects for Asian Triangle Akifumi Kuchiki5. Evolution of Institutions and Policies for Economic Integration in East Asia: History and ProspectsYoshihiro Otsuji and Kunihiro Shinoda6. Economic Integration in Asia: European RespectivesAnthony J. Venables, Alan Winters and Linda YuehPART III: CASE STUDIES OF EAST ASIAN ECONOMIC INTEGRATION7. Structure and Determinants of Intra-Regional Trade in East AsiaSatoru Kumagai8. Location Choices of Korean MNEs in East Asia: Escaping the NutcrackerHo Yeon Kim9. Location Choices of Japanese MNEs in East AsiaToshitaka Gokan10. Economic Opening and Industrial Agglomeration in ChinaZao Chen, Yu Lin and Ming Lu11. The Home Market Effect in ASEAN Countries Ikumo IsonoIndex

Economic integration in East Asia : perspectives from spatial and neoclassical economics

Interactions between elements, which are usually represented by networks, have to delineate potentially unequal relationships in terms of their relative importance or direction. The intrinsic unequal relationships of such kind, however, are opaque or hidden in numerous real systems.For instance, when a node in a network with limited interaction capacity spends its capacity to its neighboring nodes, the allocation of the total amount of interactions to them can be vastly diverse. Even if such potentially heterogeneous interactions epitomized by weighted networks are observable, as a result of the aforementioned ego-centric allocation of interactions, the relative importance or dependency between two interacting nodes can only be implicitly accessible. In this work, we precisely pinpoint such relative dependency by proposing the framework to discover hidden dependent relations extracted from weighted networks. For a given weighted network, we provide a systematic criterion to select the most essential interactions for individual nodes based on the concept of information entropy. The criterion is symbolized by assigning the effective number of neighbors or the effective out-degree to each node, and the resultant directed subnetwork decodes the hidden dependent relations by leaving only the most essential directed interactions. We apply our methodology to two time-stamped empirical network data, namely the international trade relations between nations in the world trade web (WTW) and the network of people in the historical record of Korea, Annals of the Joseon Dynasty (AJD). Based on the data analysis, we discover that the properties of mutual dependency encoded in the two systems are vastly different.

Uncovering Hidden Dependency in Weighted Networks via Information Entropy

Dynamical properties of the transcriptional regulatory network of {\it Escherichia coli} and {\it Saccharomyces cerevisiae} are studied within the framework of random Boolean functions. The dynamical response of these networks to a single point mutation is characterized by the number of mutated elements as a function of time and the distribution of the relaxation time to a new stationary state, which turn out to be different in both networks. Comparison with the behavior of randomized networks reveals relevant structural characteristics other than the mean connectivity, namely the organization of circuits and the functional form of the in-degree distribution. The abundance of single-element circuits in {\it E. coli} and the power-law in-degree distribution of {\it S. cerevisiae} shift their dynamics towards marginal stability overcoming the restrictions imposed by their mean connectivities, which is argued to be related to the simultaneous presence of robustness and adaptivity in living organisms.

Comparative study of the transcriptional regulatory networks of E. coli and yeast: Structural characteristics leading to marginal dynamic stability

Uncovering hidden dependency in weighted networks via information entropy

The distributions of trade values and relationships among countries and product categories reflect how countries select their trade partners and design export portfolios. Here we consider the exporter-importer network and the exporter-product network with links weighted by the logarithm of the corresponding export values each year from 1962 to 2018, and study how the weights of the outgoing links from each country are distributed. Such local logarithmic export distributions by destinations and products are found to follow approximately the Gaussian distribution across exporters and time, implying random assignment of export values on a logarithmic scale. However, a nonzero skewness is identified, changing from positive to negative as exporters have more partner importers and more product categories in their portfolios. Seeking the origin, we analyze how local exports depend on the out-degree of the exporter and the in-degrees of destinations or products and formulate their quantitative and measurable relation incorporating randomness, which uncovers the fundamental nature of the export strategies of individual countries.

Skewness of local logarithmic exports.

We generalize an algorithm used widely in the configuration model such that power-law degree sequences with the degree exponent λ and the number of links per node K controllable independently may be generated. It yields the degree distribution in a different form from that of the static model or under random removal of links while sharing the same λ and K. With this generalized power-law degree distribution, the critical point K_{c} for the appearance of the giant component remains zero not only for λ≤3 but also for 3<λ<λ_{l}≃3.81. This is contrasted with K_{c}=0 only for λ≤3 in the static model and under random link removal. The critical exponents and the cluster-size distribution for λ<λ_{l} are also different from known results. By analyzing the moments and the generating function of the degree distribution and comparison with those of other models, we show that the asymptotic behavior and the degree exponent may not be the only properties of the degree distribution relevant to the critical phenomena but that its whole functional form can be relevant. These results can be useful in designing and assessing the structure and robustness of networked systems.

Giant component in a configuration-model power-law graph with a variable number of links.

Different shares of distinct commodity sectors in production, trade, and consumption illustrate how resources and capital are allocated and invested. Economic progress has been claimed to change the share distribution in a universal manner as exemplified by the Engel’s law for the household expenditure and the shift from primary to manufacturing and service sector in the three sector model. Searching for large-scale quantitative evidence of such correlation, we analyze the gross-domestic product (GDP) and international trade data based on the standard international trade classification (SITC) in the period 1962 to 2000. Three categories, among ten in the SITC, are found to have their export shares significantly correlated with the GDP over countries and time; The machinery category has positive and food and crude materials have negative correlations. The export shares of commodity categories of a country are related to its GDP by a power-law with the exponents characterizing the GDP-elasticity of their export shares. The distance between two countries in terms of their export portfolios is measured to identify several clusters of countries sharing similar portfolios in 1962 and 2000. We show that the countries whose GDP is increased significantly in the period are likely to transit to the clusters displaying large share of the machinery category.

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Engel's law in the commodity composition of exports.

The relationship between Korea and Latin American and the Caribbean has come a long way. As the two economies embraced trade with one another in the early 1990s, their connection went from being irrelevant to being a wealth machine. Bilateral trade grew at an impressive annual rate of 11.5%reaching a record high in 2021. The trade boom was followed by US$26 billion in investments by Korean firms in the region since 2000. Despite this meteoric rise, lingering trade barriers remain, and new challenges are emerging from a string of disruptive shocks to the global economyprotectionist backlashes; growing and interrelated sanitary, food, energy, and climate crises; and a fast-moving “digital transformation.” This monograph argues that, despite the challenges, both economies have a set of policies, institutions, and comparative advantages that, if reinforced and leveraged by trade and cooperation, can turn these shocks into bilateral and global opportunities for inclusive and sustainable growth.

Latin America and Korea: Partners for Sustainable Trade and Investment

The Joint Report on Multilateral Development Banks Climate Finance is an annual collaborative effort to publish multilateral development bank climate finance figures, together with a clear explanation of the methodologies for tracking this finance. This joint report, alongside the banks publication of climate finance statistics in their respective corporate media, is intended to track progress in relation to their climate finance targets such as those announced at COP21 and the greater ambition pledged for the post-2020 period.

Sung-Gook Choi

Papers

Giant component in a configuration-model power-law graph with a variable number of links.

Engel's law in the commodity composition of exports.

Skewness of local logarithmic exports.

Latin America and Korea: Partners for Sustainable Trade and Investment

2021 MDB Joint Report