Deus ex Machina? A Framework for Macro Forecasting with Machine Learning
Deus ex Machina? A Framework for Macro Forecasting with Machine Learning

Author: Marijn A. Bolhuis

Publisher: International Monetary Fund

Published: 2020-02-28

Total Pages: 25

ISBN-13: 1513531727

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We develop a framework to nowcast (and forecast) economic variables with machine learning techniques. We explain how machine learning methods can address common shortcomings of traditional OLS-based models and use several machine learning models to predict real output growth with lower forecast errors than traditional models. By combining multiple machine learning models into ensembles, we lower forecast errors even further. We also identify measures of variable importance to help improve the transparency of machine learning-based forecasts. Applying the framework to Turkey reduces forecast errors by at least 30 percent relative to traditional models. The framework also better predicts economic volatility, suggesting that machine learning techniques could be an important part of the macro forecasting toolkit of many countries.

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

Published: 2022-03-11

Total Pages: 45

ISBN-13:

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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.

Computational Statistical Methodologies and Modeling for Artificial Intelligence
Computational Statistical Methodologies and Modeling for Artificial Intelligence

Author: Priyanka Harjule

Publisher: CRC Press

Published: 2023-03-31

Total Pages: 389

ISBN-13: 1000831078

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This book covers computational statistics-based approaches for Artificial Intelligence. The aim of this book is to provide comprehensive coverage of the fundamentals through the applications of the different kinds of mathematical modelling and statistical techniques and describing their applications in different Artificial Intelligence systems. The primary users of this book will include researchers, academicians, postgraduate students, and specialists in the areas of data science, mathematical modelling, and Artificial Intelligence. It will also serve as a valuable resource for many others in the fields of electrical, computer, and optical engineering. The key features of this book are: Presents development of several real-world problem applications and experimental research in the field of computational statistics and mathematical modelling for Artificial Intelligence Examines the evolution of fundamental research into industrialized research and the transformation of applied investigation into real-time applications Examines the applications involving analytical and statistical solutions, and provides foundational and advanced concepts for beginners and industry professionals Provides a dynamic perspective to the concept of computational statistics for analysis of data and applications in intelligent systems with an objective of ensuring sustainability issues for ease of different stakeholders in various fields Integrates recent methodologies and challenges by employing mathematical modeling and statistical techniques for Artificial Intelligence

Powering the Digital Economy: Opportunities and Risks of Artificial Intelligence in Finance
Powering the Digital Economy: Opportunities and Risks of Artificial Intelligence in Finance

Author: El Bachir Boukherouaa

Publisher: International Monetary Fund

Published: 2021-10-22

Total Pages: 35

ISBN-13: 1589063953

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This paper discusses the impact of the rapid adoption of artificial intelligence (AI) and machine learning (ML) in the financial sector. It highlights the benefits these technologies bring in terms of financial deepening and efficiency, while raising concerns about its potential in widening the digital divide between advanced and developing economies. The paper advances the discussion on the impact of this technology by distilling and categorizing the unique risks that it could pose to the integrity and stability of the financial system, policy challenges, and potential regulatory approaches. The evolving nature of this technology and its application in finance means that the full extent of its strengths and weaknesses is yet to be fully understood. Given the risk of unexpected pitfalls, countries will need to strengthen prudential oversight.

Impacts of Generative AI on Creativity in Higher Education
Impacts of Generative AI on Creativity in Higher Education

Author: Fields, Ziska

Publisher: IGI Global

Published: 2024-08-27

Total Pages: 564

ISBN-13:

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Many educators in the realm of higher education face the critical challenge of fostering creativity in students using traditional teaching methods. In today's rapidly evolving world, these methods have become inadequate to nurture the innovative thinking demanded by modern society. Impacts of Generative AI on Creativity in Higher Education reveals a solution in the integration of generative AI into higher education. To revolutionize how we nurture and harness student creativity, the book explores the intersection of creativity, generative AI, and higher education with a fresh perspective and practical guidance for educators and institutions. It delves into the fundamental concepts of generative AI and its potential applications, providing educators with the tools to create more engaging and innovative learning environments.

The Coding Manual for Qualitative Researchers
The Coding Manual for Qualitative Researchers

Author: Johnny Saldana

Publisher: SAGE

Published: 2009-02-19

Total Pages: 282

ISBN-13: 1446200124

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The Coding Manual for Qualitative Researchers is unique in providing, in one volume, an in-depth guide to each of the multiple approaches available for coding qualitative data. In total, 29 different approaches to coding are covered, ranging in complexity from beginner to advanced level and covering the full range of types of qualitative data from interview transcripts to field notes. For each approach profiled, Johnny Saldaña discusses the method’s origins in the professional literature, a description of the method, recommendations for practical applications, and a clearly illustrated example.

Minding the Future
Minding the Future

Author: Barry Dainton

Publisher: Springer Nature

Published: 2021-08-31

Total Pages: 287

ISBN-13: 3030642690

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Bringing together literary scholars, computer scientists, ethicists, philosophers of mind, and scholars from affiliated disciplines, this collection of essays offers important and timely insights into the pasts, presents, and, above all, possible futures of Artificial Intelligence. This book covers topics such as ethics and morality, identity and selfhood, and broader issues about AI, addressing questions about the individual, social, and existential impacts of such technologies. Through the works of science fiction authors such as Isaac Asimov, Stanislaw Lem, Ann Leckie, Iain M. Banks, and Martha Wells, alongside key visual productions such as Ex Machina, Westworld, and Her, contributions illustrate how science fiction might inform potential futures as well as acting as a springboard to bring disciplinary knowledge to bear on significant developments of Artificial Intelligence. Addressing a broad, interdisciplinary audience, both expert and non-expert readers gain an in-depth understanding of the wide range of pressing issues to which Artificial Intelligence gives rise, and the ways in which science fiction narratives have been used to represent them. Using science fiction in this manner enables readers to see how even fictional worlds and imagined futures have very real impacts on how we understand these technologies. As such, readers are introduced to theoretical positions on Artificial Intelligence through fictional works as well as encouraged to reflect on the diverse aspects of Artificial Intelligence through its many philosophical, social, legal, scientific, and cultural ramifications.

Learning to Industrialize
Learning to Industrialize

Author: Kenichi Ohno

Publisher: Routledge

Published: 2014-04-03

Total Pages: 369

ISBN-13: 1136198849

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This book proposes a new, pragmatic way of approaching economic development which features policy learning based on a comparison of international best policy practices. While the important role of government in promoting private sector development is being recognized, policy discussion often remains general without details as to what exactly to do and how to avoid common pitfalls. This book fills the gap by showing concrete policy contents, procedures, and organizations adopted in high-performing East Asian economies. Natural resources and foreign aid and investment can take a country to a certain income level, but growth stalls when given advantages are exhausted. Economies will be caught in middle income traps if growth impetus is not internally generated. Meanwhile, countries that have soared to high income introduced mindset, policies, and institutions that encouraged, or even forced, accumulation of human capital – skills, technology, and knowledge. How this can be done systematically is the main topic of policy learning. However, government should not randomly adopt what Singapore or Taiwan did in the past. A continued march to prosperity is possible only when policy makers acquire capability to formulate policy suitable for local context after studying a number of international experiences. Developing countries wanting to adopt effective industrial strategies but not knowing where to start will benefit greatly by the ideas and hands-on examples presented by the author. Students of development economics will find a new methodological perspective which can supplement the ongoing industrial policy debate. The book also gives an excellent account of national pride and pragmatism exhibited by officials in East Asia who produced remarkable economic growth, as well as serious effort by an African country to emulate this miracle. The Open Access version of this book, available at http://www.taylorfrancis.com/doi/view/10.4324/9780203085530 has been made available under a Creative Commons Attribution-Non Commercial-No Derivatives 4.0 license.