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

Author : Mr. Jean-Francois Dauphin

Publisher : International Monetary Fund

Page : 45 pages

File Size : 28,91 MB

Release : 2022-03-11

Category : Business & Economics

ISBN :

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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.





Forecasting National Activity Using Lots of International Predictors

Author : Sandra Eickmeier

Publisher :

Page : 60 pages

File Size : 16,48 MB

Release : 2016

Category :

ISBN :

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Book Description

We look at how large international datasets can improve forecasts of national activity. We use the case of New Zealand, an archetypal small open economy. We apply "data-rich" factor and shrinkage methods to tackle the problem of efficiently handling hundreds of predictor data series from many countries. The methods covered are principal components, targeted predictors, weighted principal components, partial least squares, elastic net and ridge regression. Using these methods, we assess the marginal predictive content of international data for New Zealand GDP growth. We find that exploiting a large number of international predictors can improve forecasts of our target variable, compared to more traditional models based on small datasets. This is in spite of New Zealand survey data capturing a substantial proportion of the predictive information in the international data. The largest forecasting accuracy gains from including international predictors are at longer forecast horizons. The forecasting performance achievable with the data-rich methods differs widely, with shrinkage methods and partial least squares performing best. We also assess the type of international data that contains the most predictive information for New Zealand growth over our sample.



Data Science for Economics and Finance

Author : Sergio Consoli

Publisher : Springer Nature

Page : 357 pages

File Size : 26,21 MB

Release : 2021

Category : Application software

ISBN : 3030668916

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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.



Alternative Economic Indicators

Author : C. James Hueng

Publisher : W.E. Upjohn Institute

Page : 133 pages

File Size : 19,79 MB

Release : 2020-09-08

Category : Business & Economics

ISBN : 0880996765

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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.



Applied Economic Forecasting Using Time Series Methods

Author : Eric Ghysels

Publisher : Oxford University Press

Page : 617 pages

File Size : 44,87 MB

Release : 2018

Category : Business & Economics

ISBN : 0190622016

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Book Description

Economic forecasting is a key ingredient of decision making in the public and private sectors. This book provides the necessary tools to solve real-world forecasting problems using time-series methods. It targets undergraduate and graduate students as well as researchers in public and private institutions interested in applied economic forecasting.



The Oxford Handbook of Economic Forecasting

Author : Michael P. Clements

Publisher : OUP USA

Page : 732 pages

File Size : 28,18 MB

Release : 2011-07-08

Category : Business & Economics

ISBN : 0195398645

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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.



Nowcasting GDP and Inflation

Author : Domenico Giannone

Publisher :

Page : 62 pages

File Size : 18,42 MB

Release : 2005

Category : Economic indicators

ISBN :

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Book Description



Economic Analysis of the Digital Economy

Author : Avi Goldfarb

Publisher : University of Chicago Press

Page : 510 pages

File Size : 30,53 MB

Release : 2015-05-08

Category : Business & Economics

ISBN : 022620684X

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Book Description

There is a small and growing literature that explores the impact of digitization in a variety of contexts, but its economic consequences, surprisingly, remain poorly understood. This volume aims to set the agenda for research in the economics of digitization, with each chapter identifying a promising area of research. "Economics of Digitization "identifies urgent topics with research already underway that warrant further exploration from economists. In addition to the growing importance of digitization itself, digital technologies have some features that suggest that many well-studied economic models may not apply and, indeed, so many aspects of the digital economy throw normal economics in a loop. "Economics of Digitization" will be one of the first to focus on the economic implications of digitization and to bring together leading scholars in the economics of digitization to explore emerging research.



Inflation Expectations

Author : Peter J. N. Sinclair

Publisher : Routledge

Page : 402 pages

File Size : 10,46 MB

Release : 2009-12-16

Category : Business & Economics

ISBN : 1135179778

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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.