Knowing, When You Do Not Know : Simulating the Poverty and Distributional Impacts of an Economic Crisis

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 This problem is particularly acute when dealing with developing countries where household data is sporadic or out of date. This volume outlines a more comprehensive approach to the problem, showcasing a micro simulation 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 staff s was 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. The volume is organized as follows. Chapter 1 summarizes the methodology underlying the micro simulation model to predict distributional impacts of the crisis, along with several case studies that highlight how the model can be used in different country contexts. Chapters 2 to 4 are written by experts external to the Bank, two of whom participated as discussants at a workshop on the micro simulation work organized in May, 2010 at the World Bank headquarters. Chapter 2 comments on the broader implications and shortcomings of applying the technique described in Chapter 1 and the ability or willingness of governments to respond adequately to its results. Chapter 3 draws parallels between the United States and developing countries to discuss the lessons that can be learned for mitigating the impacts of future crises. Chapter 4 discusses how the micro simulation approach can be sharpened to make it a better tool for distributional analysis moving forward.

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Bibliographic Details
Main Authors: Narayan, Ambar, Sánchez-Páramo, Carolina
Format: Publication biblioteca
Language:English
Published: World Bank 2012-01-12
Subjects:ACCOUNTING, AGGREGATE EMPLOYMENT, AGGREGATE INEQUALITY, AGGREGATE OUTPUT, ANTI-POVERTY, ANTI-POVERTY PROGRAMS, AVERAGE INCOME, BENEFICIARIES, CALORIE INTAKE, CONSTANT POVERTY LINE, COUNTERFACTUAL, CRISES, DATA REQUIREMENTS, DEMOGRAPHIC CHANGES, DEVELOPED COUNTRIES, DEVELOPED WORLD, DEVELOPING COUNTRIES, DEVELOPING WORLD, DEVELOPMENT INSTITUTIONS, DISTRIBUTIONAL EFFECTS, DISTRIBUTIONAL IMPACT, ECONOMIC CONDITIONS, ECONOMIC GROWTH, ELASTICITY, EMPIRICAL EVIDENCE, EMPIRICAL WORK, EMPLOYMENT IMPACTS, EMPLOYMENT STATUS, EXTREME POVERTY, EXTREME POVERTY LINES, FARMERS, FEMALE EMPLOYMENT, FEMALE PARTICIPATION, FINANCIAL CRISIS, FINANCIAL MARKETS, FOOD BASKET, FOOD PRICE, FOOD PRICES, FOOD REQUIREMENTS, GENERAL EQUILIBRIUM, GENERAL EQUILIBRIUM MODELS, GLOBAL MARKETS, GROWTH RATES, HISTORICAL DATA, HOUSEHOLD DATA, HOUSEHOLD HEADS, HOUSEHOLD INCOME, HOUSEHOLD INCOMES, HOUSEHOLD MEMBERS, HOUSEHOLD SURVEY, IMPACT ON POVERTY, INCOME, INCOME DISTRIBUTION, INCOME DISTRIBUTIONS, INCOME GAINS, INCOME GROUPS, INCOME GROWTH, INCOME LEVEL, INCOME LEVELS, INCOME SCALE, INCOME SHOCK, INCOME SHOCKS, INCOME SOURCE, INCOME SOURCES, INCOMES, INDIVIDUAL COUNTRIES, INEQUALITY, INEQUALITY MEASURES, INNOVATIONS, INSURANCE, LABOR FORCE, LABOR FORCE PARTICIPATION, LABOR MARKET, LABOR MARKETS, MACROECONOMIC MISMANAGEMENT, MACROECONOMIC SHOCKS, MIDDLE CLASS, NATIONAL POVERTY, NEW POOR, NOMINAL WAGES, NUTRITION, OCCUPATIONS, OUTPUTS, PARTICIPATION RATES, PER CAPITA INCOME, POLICY CHANGES, POLICY DECISIONS, POLICY DESIGN, POLICY INTERVENTIONS, POLICY MEASURES, POLITICAL ECONOMY, POOR, POOR HOUSEHOLDS, POOR RURAL HOUSEHOLDS, POPULATION GROWTH, POVERTY ESTIMATES, POVERTY GAP, POVERTY HEADCOUNT, POVERTY HEADCOUNT RATE, POVERTY IMPACT, POVERTY IMPACTS, POVERTY INCREASE, POVERTY INDICES, POVERTY LINE, POVERTY LINES, POVERTY PROGRAMS, POVERTY RATE, POVERTY RATES, POVERTY REDUCTION, PRICE CHANGES, PRIVATE TRANSFERS, PRODUCTIVITY, PUBLIC POLICIES, PUBLIC TRANSFERS, REAL OUTPUT, RELATIVE IMPORTANCE, RELATIVE PRICES, RENTS, RURAL, RURAL AREAS, RURAL HOUSEHOLD, RURAL INCOME, SAFETY, SAFETY NET, SAFETY NET PROGRAMS, SAFETY NETS, SIGNIFICANT DIFFERENCES, SOCIAL ASSISTANCE, SOCIAL BENEFITS, SOCIAL POLICY, SOCIAL PROGRAMS, SUSTAINABLE DEVELOPMENT, TARGETING, TRANSFER PROGRAMS, UNEMPLOYED, UNEMPLOYMENT, UNEMPLOYMENT BENEFITS, UNEMPLOYMENT RATE, WAGES, YOUNG WORKERS,
Online Access:http://www-wds.worldbank.org/external/default/main?menuPK=64187510&pagePK=64193027&piPK=64187937&theSitePK=523679&menuPK=64187510&searchMenuPK=64187283&siteName=WDS&entityID=000386194_20120109012250
http://hdl.handle.net/10986/2229
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Summary: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. This volume outlines a more comprehensive approach to the problem, showcasing a micro simulation 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 staff s was 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. The volume is organized as follows. Chapter 1 summarizes the methodology underlying the micro simulation model to predict distributional impacts of the crisis, along with several case studies that highlight how the model can be used in different country contexts. Chapters 2 to 4 are written by experts external to the Bank, two of whom participated as discussants at a workshop on the micro simulation work organized in May, 2010 at the World Bank headquarters. Chapter 2 comments on the broader implications and shortcomings of applying the technique described in Chapter 1 and the ability or willingness of governments to respond adequately to its results. Chapter 3 draws parallels between the United States and developing countries to discuss the lessons that can be learned for mitigating the impacts of future crises. Chapter 4 discusses how the micro simulation approach can be sharpened to make it a better tool for distributional analysis moving forward.