Data Science for Economics and Finance


Book Description

This open access book covers the use of data science, including advanced machine learning, big data analytics, Semantic Web technologies, natural language processing, social media analysis, time series analysis, among others, for applications in economics and finance. In addition, it shows some successful applications of advanced data science solutions used to extract new knowledge from data in order to improve economic forecasting models. The book starts with an introduction on the use of data science technologies in economics and finance and is followed by thirteen chapters showing success stories of the application of specific data science methodologies, touching on particular topics related to novel big data sources and technologies for economic analysis (e.g. social media and news); big data models leveraging on supervised/unsupervised (deep) machine learning; natural language processing to build economic and financial indicators; and forecasting and nowcasting of economic variables through time series analysis. This book is relevant to all stakeholders involved in digital and data-intensive research in economics and finance, helping them to understand the main opportunities and challenges, become familiar with the latest methodological findings, and learn how to use and evaluate the performances of novel tools and frameworks. It primarily targets data scientists and business analysts exploiting data science technologies, and it will also be a useful resource to research students in disciplines and courses related to these topics. Overall, readers will learn modern and effective data science solutions to create tangible innovations for economic and financial applications.




The Oxford Handbook of Economic Forecasting


Book Description

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.




Handbook on Constructing Composite Indicators: Methodology and User Guide


Book Description

A guide for constructing and using composite indicators for policy makers, academics, the media and other interested parties. In particular, this handbook is concerned with indicators which compare and rank country performance.




Short-Term Forecasting for Empirical Economists


Book Description

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 Economy in the Time of Covid-19


Book Description

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.




Nowcasting GDP - A Scalable Approach Using DFM, Machine Learning and Novel Data, Applied to European Economies


Book Description

This paper describes recent work to strengthen nowcasting capacity at the IMF’s European department. It motivates and compiles datasets of standard and nontraditional variables, such as Google search and air quality. It applies standard dynamic factor models (DFMs) and several machine learning (ML) algorithms to nowcast GDP growth across a heterogenous group of European economies during normal and crisis times. Most of our methods significantly outperform the AR(1) benchmark model. Our DFMs tend to perform better during normal times while many of the ML methods we used performed strongly at identifying turning points. Our approach is easily applicable to other countries, subject to data availability.




Poverty and Shared Prosperity 2020


Book Description

This edition of the biennial Poverty and Shared Prosperity report brings sobering news. The COVID-19 (coronavirus) pandemic and its associated economic crisis, compounded by the effects of armed conflict and climate change, are reversing hard-won gains in poverty reduction and shared prosperity. The fight to end poverty has suffered its worst setback in decades after more than 20 years of progress. The goal of ending extreme poverty by 2030, already at risk before the pandemic, is now beyond reach in the absence of swift, significant, and sustained action, and the objective of advancing shared prosperity—raising the incomes of the poorest 40 percent in each country—will be much more difficult. Poverty and Shared Prosperity 2020: Reversals of Fortune presents new estimates of COVID-19's impacts on global poverty and shared prosperity. Harnessing fresh data from frontline surveys and economic simulations, it shows that pandemic-related job losses and deprivation worldwide are hitting already poor and vulnerable people hard, while also shifting the profile of global poverty to include millions of 'new poor.' Original analysis included in the report shows that the new poor are more urban, better educated, and less likely to work in agriculture than those living in extreme poverty before COVID-19. It also gives new estimates of the impact of conflict and climate change, and how they overlap. These results are important for targeting policies to safeguard lives and livelihoods. It shows how some countries are acting to reverse the crisis, protect those most vulnerable, and promote a resilient recovery. These findings call for urgent action. If the global response fails the world's poorest and most vulnerable people now, the losses they have experienced to date will be minimal compared with what lies ahead. Success over the long term will require much more than stopping COVID-19. As efforts to curb the disease and its economic fallout intensify, the interrupted development agenda in low- and middle-income countries must be put back on track. Recovering from today's reversals of fortune requires tackling the economic crisis unleashed by COVID-19 with a commitment proportional to the crisis itself. In doing so, countries can also plant the seeds for dealing with the long-term development challenges of promoting inclusive growth, capital accumulation, and risk prevention—particularly the risks of conflict and climate change.




Inflation Expectations


Book Description

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.




Alternative Economic Indicators


Book Description

Policymakers and business practitioners are eager to gain access to reliable information on the state of the economy for timely decision making. More so now than ever. Traditional economic indicators have been criticized for delayed reporting, out-of-date methodology, and neglecting some aspects of the economy. Recent advances in economic theory, econometrics, and information technology have fueled research in building broader, more accurate, and higher-frequency economic indicators. This volume contains contributions from a group of prominent economists who address alternative economic indicators, including indicators in the financial market, indicators for business cycles, and indicators of economic uncertainty.




Panel Nowcasting for Countries Whose Quarterly GDPs are Unavailable


Book Description

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.