The Need and Criteria for the Sectoral Programming of Australian Aid to Papua New Guinea
The challenges posed by high balance of payments deficits that manifest as high saving-investment gaps in Papua New Guinea (PNG) are analysed. Foreign aid can play play a pivotal role to fill these balance of payments or savings-investment gaps. Australia as the largest donor of foreign aid to PNG is concerned about the need for the effective disbursement or programming aid. In this paper we demonstrate that using sectoral (bunch-criteria) based on the semi-input-output model provides a better framework for evaluating the effective performance of aid than programming aid to projects.
Quantification of Sectoral Development Prospects in Papua New Guinea Using Tinbergen and Rasmussen Criteria
The paper critically reviews the development strategy that is embodied in the "eight aims" of the national plan enuciated for the development of post-independent economy of Papua New Guniea (PNG). An algebraic exposition of the semi-input-output criterion is the applied to identify the attractiveness of tradable sectors that qualify for further grooming on the basis of their comparative advantage in trade. The semi-input criterion is also applied for project appraisal and its mechanics are demonstrated using the palm oil project as a case study. The key sectors of the PNG economy using dominant linkage and spread effects are identified as potential candidates for development in the framework of the semi-input-output methodology.
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.