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Quarterly GDP statistics facilitate timely economic assessment, but the availability of such data are limited for more than 60 developing economies, including about 20 countries in sub-Saharan Africa as well as more than two-thirds of fragile and conflict-affected states. To address this limited data availablity, this paper proposes a panel approach that utilizes a statistical relationship estimated from countries where data are available, to estimate quarterly GDP statistics for countries that do not publish such statistics by leveraging the indicators readily available for many countries. This framework demonstrates potential, especially when applied for similar country groups, and could provide valuable real-time insights into economic conditions supported by empirical evidence.
Short-term Forecasting for Empirical Economists seeks to close the gap between research and applied short-term forecasting. The authors review some of the key theoretical results and empirical findings in the recent literature on short-term forecasting, and translate these findings into economically meaningful techniques to facilitate their widespread application to compute short-term forecasts in economics, and to monitor the ongoing business cycle developments in real time.
The basic tools for analyzing macroeconomic fluctuations and policies, applied to concrete issues and presented within an integrated New Keynesian framework. This textbook presents the basic tools for analyzing macroeconomic fluctuations and policies and applies them to contemporary issues. It employs a unified New Keynesian framework for understanding business cycles, major crises, and macroeconomic policies, introducing students to the approach most often used in academic macroeconomic analysis and by central banks and international institutions. The book addresses such topics as how recessions and crises spread; what instruments central banks and governments have to stimulate activity when private demand is weak; and what “unconventional” macroeconomic policies might work when conventional monetary policy loses its effectiveness (as has happened in many countries in the aftermath of the Great Recession.). The text introduces the foundations of modern business cycle theory through the notions of aggregate demand and aggregate supply, and then applies the theory to the study of regular business-cycle fluctuations in output, inflation, and employment. It considers conventional monetary and fiscal policies aimed at stabilizing the business cycle, and examines unconventional macroeconomic policies, including forward guidance and quantitative easing, in situations of “liquidity trap”—deep crises in which conventional policies are either ineffective or have very different effects than in normal time. This book is the first to use the New Keynesian framework at the advanced undergraduate level, connecting undergraduate learning not only with the more advanced tools taught at the graduate level but also with the large body of policy-oriented research in academic journals. End-of-chapter problems help students master the materials presented.
After a period of rapid economic growth associated with high commodity prices, the region had entered a phase of lackluster performance. Recent developments, including a new oil price shock, and the outbreak of the Covid-19 epidemic will push the region into recession. Many countries are struggling to contain the spread of the Covid-19 epidemic while avoiding a dramatic decline in economic activity. The report analyzes how to think about this tradeoff. It estimates the potential health costs, assesses the effectiveness of diverse containment strategies, and discusses how large the economic cost could be. The current crisis is unprecedented because it combines a fall in global demand, tighter financial conditions and a major supply shock. The response needs to consider how to socialize the losses, how to prevent a collapse of the financial sector, how to protect jobs and livelihoods, and how to manage and divest the assets that will inevitably end up in the hands of the state.
Greater data availability has been coupled with developments in statistical theory and economic theory to allow more elaborate and complicated models to be entertained. These include factor models, DSGE models, restricted vector autoregressions, and non-linear models.
Inflation is regarded by the many as a menace that damages business and can only make life worse for households. Keeping it low depends critically on ensuring that firms and workers expect it to be low. So expectations of inflation are a key influence on national economic welfare. This collection pulls together a galaxy of world experts (including Roy Batchelor, Richard Curtin and Staffan Linden) on inflation expectations to debate different aspects of the issues involved. The main focus of the volume is on likely inflation developments. A number of factors have led practitioners and academic observers of monetary policy to place increasing emphasis recently on inflation expectations. One is the spread of inflation targeting, invented in New Zealand over 15 years ago, but now encompassing many important economies including Brazil, Canada, Israel and Great Britain. Even more significantly, the European Central Bank, the Bank of Japan and the United States Federal Bank are the leading members of another group of monetary institutions all considering or implementing moves in the same direction. A second is the large reduction in actual inflation that has been observed in most countries over the past decade or so. These considerations underscore the critical – and largely underrecognized - importance of inflation expectations. They emphasize the importance of the issues, and the great need for a volume that offers a clear, systematic treatment of them. This book, under the steely editorship of Peter Sinclair, should prove very important for policy makers and monetary economists alike.
In 2013, the World Bank Group announced two goals that would guide its operations worldwide. First is the eradication of chronic extreme poverty bringing the number of extremely poor people, defined as those living on less than 1.25 purchasing power parity (PPP)†“adjusted dollars a day, to less than 3 percent of the world’s population by 2030.The second is the boosting of shared prosperity, defined as promoting the growth of per capita real income of the poorest 40 percent of the population in each country. In 2015, United Nations member nations agreed in New York to a set of post-2015 Sustainable Development Goals (SDGs), the first and foremost of which is the eradication of extreme poverty everywhere, in all its forms. Both the language and the spirit of the SDG objective reflect the growing acceptance of the idea that poverty is a multidimensional concept that reflects multiple deprivations in various aspects of well-being. That said, there is much less agreement on the best ways in which those deprivations should be measured, and on whether or how information on them should be aggregated. Monitoring Global Poverty: Report of the Commission on Global Poverty advises the World Bank on the measurement and monitoring of global poverty in two areas: What should be the interpretation of the definition of extreme poverty, set in 2015 in PPP-adjusted dollars a day per person? What choices should the Bank make regarding complementary monetary and nonmonetary poverty measures to be tracked and made available to policy makers? The World Bank plays an important role in shaping the global debate on combating poverty, and the indicators and data that the Bank collates and makes available shape opinion and actual policies in client countries, and, to a certain extent, in all countries. How we answer the above questions can therefore have a major influence on the global economy.
Digital technologies are spreading rapidly, but digital dividends--the broader benefits of faster growth, more jobs, and better services--are not. If more than 40 percent of adults in East Africa pay their utility bills using a mobile phone, why can’t others around the world do the same? If 8 million entrepreneurs in China--one third of them women--can use an e-commerce platform to export goods to 120 countries, why can’t entrepreneurs elsewhere achieve the same global reach? And if India can provide unique digital identification to 1 billion people in five years, and thereby reduce corruption by billions of dollars, why can’t other countries replicate its success? Indeed, what’s holding back countries from realizing the profound and transformational effects that digital technologies are supposed to deliver? Two main reasons. First, nearly 60 percent of the world’s population are still offline and can’t participate in the digital economy in any meaningful way. Second, and more important, the benefits of digital technologies can be offset by growing risks. Startups can disrupt incumbents, but not when vested interests and regulatory uncertainty obstruct competition and the entry of new firms. Employment opportunities may be greater, but not when the labor market is polarized. The internet can be a platform for universal empowerment, but not when it becomes a tool for state control and elite capture. The World Development Report 2016 shows that while the digital revolution has forged ahead, its 'analog complements'--the regulations that promote entry and competition, the skills that enable workers to access and then leverage the new economy, and the institutions that are accountable to citizens--have not kept pace. And when these analog complements to digital investments are absent, the development impact can be disappointing. What, then, should countries do? They should formulate digital development strategies that are much broader than current information and communication technology (ICT) strategies. They should create a policy and institutional environment for technology that fosters the greatest benefits. In short, they need to build a strong analog foundation to deliver digital dividends to everyone, everywhere.
Macroeconomic policy decisions in real-time are based the assessment of current and future economic conditions. These assessments are made difficult by the presence of incomplete and noisy data. The problem is more acute for emerging market economies, where most economic data are released infrequently with a (sometimes substantial) lag. This paper evaluates "nowcasts" and forecasts of real GDP growth using five alternative models for ten Latin American countries. The results indicate that the flow of monthly data helps to improve forecast accuracy, and the dynamic factor model consistently produces more accurate nowcasts and forecasts relative to other model specifications, across most of the countries we consider.