There is a growing debate on the relative merits of universal and targeted social assistance transfers in achieving income redistribution objectives. While the benefits of targeting are clear, i.e., a larger poverty impact for a given transfer budget or lower fiscal cost for a given poverty impact, in practice targeting also comes with various costs, including incentive, administrative, social and political costs. The appropriate balance between targeted and universal transfers will therefore depend on how countries decide to trade-off these costs and benefits as well as on the potential for redistribution through taxes. This paper discusses the trade-offs that arise in different country contexts and the potential for strengthening fiscal redistribution in advanced and developing countries, including through expanding transfer coverage and progressive tax financing.
Fiscal policy is a key tool for achieving distributional objectives in advanced economies. This paper embeds the discussion of fiscal redistribution within the standard social welfare framework, which lends itself to a transparent and practical evaluation of the extent and determinants of fiscal redistribution. Differences in fiscal redistribution are decomposed into differences in the magnitude of transfers (fiscal effort) and in the progressivity of transfers (fiscal progressivity). Fiscal progressivity is further decomposed into differences in the distribution of transfers across income groups (targeting performance) and in the social welfare returns to targeting due to varying initial levels of income inequality (targeting returns). This decomposition provides a clear distinction between the concepts of progressivity and targeting, and clarifies the relationship between them. For illustrative purposes, the framework is applied to data for 28 EU countries to determine the factors explaining differences in their fiscal redistribution and to discuss patterns in fiscal redistribution highlighted in the literature.
This paper discusses the definition and modelling of a universal basic income (UBI). After clarifying the debate about what a UBI is and presenting the arguments in favor and against, an analytical approach for its assessment is proposed. The adoption of a UBI as a policy tool is discussed with regard to the policy objectives (shaped by social preferences) it is designed to achieve. Key design dimensions to be considered include: coverage, generosity of the program, overall progressivity of the policy, and its financing.
Addressing the poverty and distributional impacts of carbon pricing reforms is critical for the success of ambitious actions in the fight against climate change. This paper uses a simple framework to systematically review the channels through which carbon pricing can potentially affect poverty and inequality. It finds that the channels differ in important ways along several dimensions. The paper also identifies several key gaps in the current literature and discusses some considerations on how policy designs could take into account the attributes of the channels in mitigating the impacts of carbon pricing reforms on households.
This paper explores how fiscal policy can affect medium- to long-term growth. It identifies the main channels through which fiscal policy can influence growth and distills practical lessons for policymakers. The particular mix of policy measures, however, will depend on country-specific conditions, capacities, and preferences. The paper draws on the Fund’s extensive technical assistance on fiscal reforms as well as several analytical studies, including a novel approach for country studies, a statistical analysis of growth accelerations following fiscal reforms, and simulations of an endogenous growth model.
Many studies predict massive job losses and real wage decline as a result of the ongoing widespread automation of production, a trend that may be further aggravated by the COVID-19 crisis. Yet automation is also expected to raise productivity and output. How can we share the gains from automation more widely, for the benefit of all? And what are the attendant equity-efficiency trade-offs? We analyze this issue by considering the effects of fiscal policies that seek to redistribute the gains from automation and address income inequality. We use a dynamic general equilibrium model with monopolistic competition, including a novel specification linking corporate power to automation. While fiscal policy cannot eliminate the classic equity-efficiency trade-offs, it can help improve them, reducing inequality at small or no loss of output. This is particularly so when policy takes advantage of novel, less distortive transmission channels of fiscal policy created by the empirically observed link between corporate market power and automation.
Targeting is a commonly used, but much debated, policy tool within global social assistance practice. Revisiting Targeting in Social Assistance: A New Look at Old Dilemmas examines the well-known dilemmas in light of the growing body of experience, new implementation capacities, and the potential to bring new data and data science to bear. The book begins by considering why or whether or how narrowly or broadly to target different parts of social assistance and updates the global empirics around the outcomes and costs of targeting. It illustrates the choices that must be made in moving from an abstract vision to implementable definitions and procedures, and in deciding how the choices should be informed by values, empirics, and context. The importance of delivery systems and processes to distributional outcomes are emphasized, and many facets with room for improvement are discussed. The book also explores the choices between targeting methods and how differences in purposes and contexts shape those. The know-how with respect to the data and inference used by the different household-specific targeting methods is summarized and comprehensively updated, including a focus on “big data†? and machine learning. A primer on measurement issues is included. Key findings include the following: · Targeting selected categories, families, or individuals plays a valuable role within the framework of universal social protection. · Measuring the accuracy and cost of targeting can be done in many ways, and judicious choices require a range of metrics. · Weighing the relatively low costs of targeting against the potential gains is important. · Implementing inclusive delivery systems is critical for reducing errors of exclusion and inclusion. · Selecting and customizing the appropriate targeting method depends on purpose and context; there is no method preferred in all circumstances. · Leveraging advances in technology—ICT, big data, artificial intelligence, machine learning—can improve targeting accuracy, but they are not a panacea; better data matters more than sophistication in inference. · Targeting social protection should be a dynamic process.
In the Middle East and North Africa (MENA) countries price subsidies are common, especially on food and fuels. However, these are neither well targeted nor cost effective as a social protection tool, often benefiting mainly the better off instead of the poor and vulnerable. This paper explores the challenges of replacing generalized price subsidies with more equitable social safety net instruments, including the short-term inflationary effects, and describes the features of successful subsidy reforms.
Examining the increasingly relevant topic of public sector efficiency, this dynamic Handbook investigates the context of constrained fiscal space and public funding sources using cross-country datasets in areas including China, India and sub-Saharan Africa and OECD economies.
