Main characteristics of Japanese Official Development Assistance (ODA) flows
At the end of the 1990s, the Japanese government distributed annually more than US$10 billion as foreign aid directly or indirectly to developing countries. Japan’s ODA can be divided into the following four groups: 1) Bilateral Grants, 2) Technical Co-operation, 3) Multilateral Aid, and 4) Bilateral Loans. In 2001, Bilateral Grants made up 19.3 percent of Japan’s total ODA budget; Technical Co-operation constituted 29.7 percent; Multilateral Aid and Bilateral Loans accounted for 24.7 percent and 26.3 percent, respectively. There have been criticisms that Japanese ODA loans have been provided mainly for economic infrastructure projects only. In response to these criticisms, the Japanese government claims to have made efforts to channel these loans into various social sectors, such as agricultural projects or rural development.
The Role of Non-governmental Organisations (NGOs) in Japan’s Foreign Aid Policy
The reinforcement of the Non-governmental organisations’ role in Japan’s ODA program is a challenging task. However, if this objective is achieved, at least three advantages could ensue. Firstly, Japanese NGOs would be able to independently carry out the small-scale aid projects that directly address the needs of local communities in aid recipient countries. These grassroots aid projects could complement the government-supervised large-scale aid projects. Secondly, the Japanese government could utilize NGOs’ staff as an alternative source of information. Finally, effective co-operation between NGOs and the government could help enhancing the transparency of Japan’s foreign aid policy. Under the current system, bureaucrats dominate the policymaking process so that it is difficult for outsiders to access the information on Japan’s ODA program.
Complexity, Network-Decisions And Alternative Risk Premia: Some New Theories Of Structural Change And Portfolio Decisions.
Structural Change is the basis for many decisions such as government fiscal and monetary policies, government interventions, corporate-expenditure decisions, corporate strategic decisions, portfolio management decisions in finance; household allocation decisions, etc.. Structural change in industries and national economies is increasingly more difficult to detect partly because of the growth and dominance of Complex Systems and “Networks” in modern industries and economies – such Networks and Complex Systems include GVCs (global value chains), retail store networks; franchising networks; internet networks; services networks; credit-chains in industries; online social networks; etc.. The relationship between Complexity and Structural Change is well established in the physics, applied math and economic dynamics literatures. Traditional definitions and modeling of structural change have erroneously focused on changes in labor, technological progress, market share, and or capital – which are grossly inadequate in the new economy and post- global financial crisis (as confirmed by changes in the global retailing and housing industries and other industries). Also the modeling of structural change seems to be constrained by the availability of data, and often omits the relationship between structural change on one hand, and globalization, financial stability and international financial contagion. This article: i) introduces the Operations Strategy Model of structural change, explains how it differs from the Lewis Model of Structural Change; and explains the often omitted relationship between operations strategy (of companies and government agencies) and structural change; ii) introduces other new Complexity-based models/theories of Structural Change in industries; iii) reviews the relationships among Operations Research, Complexity and Structural Change; iv) explains the symbiotic relationship between structural change on one hand, and economic growth, financial stability, financial contagion and globalization; v) discusses the significant gap between academic research and practice and explains some issues and factors that should be considered in the development and testing of structural change models; vi) explains how alternative risk premia can be generated from new models of Structural Change.