Projections and forecasts in Australia: The context
Despite the considerable expansion of demographic projection activity in Australia over the past two decades, comparatively little of this work has found its way into the academic literature. This issue of the Journal attempts to address this deficiency by bringing together six distinctive contributions on various aspects of demographic projections and forecasting. The present introductory paper describes the context of this work and provides an overview of the papers which follow.
Population Forecasts for South Pacific Nations using Autoregressive Models 1985 — 2000
SummaryThis paper uses an autoregressive statistical model to forecast population for Fiji, Western Samoa, Tonga, Solomon Islands, and Vanuatu and compares these forecasts with those obtained from other methods. The growth rate of population is predicted to continue to fall in Fiji and Tonga, rise a little for Western Samoa, and rise considerably in Vanuatu and the Solomon Islands. The implications of the forecasts for recent government development plans are also discussed.
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.