Knowing When You Do Not Know

"Economists have long sought to predict how macroeconomic shocks will affect individual welfare. Macroeconomic data and forecasts are easily available when crises strike. But policy action requires not only understanding the magnitude of a macro shock, but also identifying which households or individuals are being hurt by (or benefit from) the crisis. Moreover, in many cases, impacts on the ground might be already occurring as macro developments become known, while micro level evidence is still unavailable because of paucity of data. Because of these reasons, a comprehensive real-time understanding of how the aggregate changes will translate to impacts at the micro level remains elusive. This problem is particularly acute when dealing with developing countries where household data is sporadic or out of date. A popular solution is to extrapolate the welfare impact of a shock from the historical response of income or consumption poverty to changes in output, by estimating an 'elasticity' of poverty to growth. Although this method provides an estimate for the aggregate poverty impact of a macro shock, it has limited value for analysts and policymakers alike. Aggregate numbers are useful to capture the attention of policymakers and the international community, but in the absence of any information on who is affected and to what extent, provide little guidance on what actions need to be taken. To take one example, most targeted anti-poverty programs focus on the existing poor. But when a crisis occurs, any efforts to expand or retool existing programs would require finding out who is likely to become poor and how much more deprivation is likely to occur among the existing poor as a result of the shock. Moreover, the specific characteristics of an output shock, whether it is caused, for example, by a natural disaster, a reduction of external demand, or internal macroeconomic mismanagement, may lead to very different impacts along the income scale that demand different policy responses. This volume outlines a more comprehensive approach to the problem, showcasing a microsimulation model, developed in response to demand from World Bank staff working in countries and country governments in the wake of the global financial crisis of 2008-09. During the growing catastrophe in a few industrialized countries, there was rising concern about how the crisis would affect the developing world and how to respond to it through public policies. World Bank staffs were scrambling to help countries design such policies; this in turn required information on which groups of the population sectors, and regions the crisis would likely affect and to what extent.