Distribution of Export Price Risk in a Developing Country
We address the issue of social distribution of an aggregate risk (on agricultural export price), from a macroeconomic perspective. Individual incomes in representative social groups are computed as a function of export prices, which are assumed to be stochastic, using an applied general equilibrium model of an archetype developing economy. The statistical properties of the resulting distribution of individual incomes are then examined. We consider a mapping of different policies on agricultural prices (stabilization or complete pass-through), monetary rules (accommodating or not) and exchange rate regimes (fixed versus flexible).
Crisis and the Poor: Socially Responsible Macroeconomics
Macroeconomic crises not only affect the current living standards of the poor, but their ability to grow out of poverty. This paper presents evidence on the impact of economic crisis on poverty and inequality in Latin America. Crises not only result in higher poverty rates but also may cause irreversible damage to the human capital of the poor. In light of this evidence, the author concludes that crisis avoidance and a pro-poor response to crisis should be a major component of a poverty reduction strategy. As a result, the paper analyses the role of exchange rate policy, capital controls and countercyclical fiscal policy in generating or avoiding crisis. Responses to macroeconomic crisis are assessed by considering the effects of different policy combinations, the use of safety nets and the composition of fiscal adjustment to protect the income of the poor in the face of macroeconomic adjustment. The main lesson is that socially responsible macroeconomic policy can protect the poor during times of crisis and simultaneously contribute to lower chronic poverty.
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.