Download or read book Nowcasting GDP A Scalable Approach Using DFM Machine Learning and Novel Data Applied to European Economies written by Mr. Jean-Francois Dauphin and published by International Monetary Fund. This book was released on 2022-03-11 with total page 45 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Nowcasting GDP written by and published by . This book was released on with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Seeing in the Dark written by Mr.Andrew Tiffin and published by International Monetary Fund. This book was released on 2016-03-08 with total page 20 pages. Available in PDF, EPUB and Kindle. Book excerpt: Macroeconomic analysis in Lebanon presents a distinct challenge. For example, long delays in the publication of GDP data mean that our analysis often relies on proxy variables, and resembles an extended version of the “nowcasting” challenge familiar to many central banks. Addressing this problem—and mindful of the pitfalls of extracting information from a large number of correlated proxies—we explore some recent techniques from the machine learning literature. We focus on two popular techniques (Elastic Net regression and Random Forests) and provide an estimation procedure that is intuitively familiar and well suited to the challenging features of Lebanon’s data.
Download or read book Computational Statistical Methodologies and Modeling for Artificial Intelligence written by Priyanka Harjule and published by CRC Press. This book was released on 2023-03-31 with total page 389 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Download or read book GDPNow written by Patrick Higgins and published by . This book was released on 2014 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Seeing in the Dark written by Andre Tiffin and published by . This book was released on with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Nowcasting and Forecasting GDP in Emerging Markets Using Global Financial and Macroeconomic Diffusion Indexes written by Oguzhan Cepni and published by . This book was released on 2018 with total page 33 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this paper, we contribute to the nascent literature on nowcasting and forecasting GDP in emerging market economies using big data methods. This is done by analyzing the usefulness of various dimension reduction, machine learning and shrinkage methods including sparse principal component analysis (SPCA), the elastic net, the least absolute shrinkage operator, and least angle regression when constructing predictions using latent global macroeconomic and financial factors (diffusion indexes) in a dynamic factor model (DFM). We also utilize a judgmental dimension reduction method called the Bloomberg Relevance Index (BBG), which is an index that assigns a measure of importance to each variable in a dataset depending on the variable's usage by market participants. In our empirical analysis, we show that DFMs, when specified using dimension reduction methods (particularly BBG and SPCA), yield superior predictions, relative to benchmark linear econometric or simple DFMs. Moreover, global financial and macroeconomic (business cycle) diffusion indexes constructed using targeted predictors are found to be important in four of the five emerging market economies (including Brazil, Mexico, South Africa, and Turkey) that we study. These findings point to the importance of spillover effects across emerging market economies, and underscore the importance of parsimoniously characterizing such linkages when utilizing high dimensional global datasets.
Download or read book Nowcasting GDP Using Machine Learning Methods written by Dennis Kant and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book When are Google Data Useful to Nowcast GDP written by Laurent Ferrara and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Nowcasting GDP Using Machine Learning Algorithms written by Adam Richardson and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Machine Learning Use in GDP Nowcasting written by and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Nowcasting New Zealand GDP Using Machine Learning Algorithms written by Adam Richardson and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Nowcasting Real GDP Growth written by Evžen Kočenda and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: We analyze the performance of a broad range of nowcasting and short-term forecasting models for a representative set of twelve old and six new member countries of the European Union (EU) that are characterized by substantial differences in aggregate output variability. In our analysis, we generate ex-post out-of-sample nowcasts and forecasts based on hard and soft indicators that come from a comparable set of identical data. We show that nowcasting works well for the new EU countries because, although that variability in their GDP growth data is larger than that of the old EU economies, the economic significance of nowcasting is on average somewhat larger.
Download or read book Nowcasting GDP Using Machine Learning Algorithms written by Adam Richardson (Economist) and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Completing the Market Generating Shadow CDS Spreads by Machine Learning written by Nan Hu and published by International Monetary Fund. This book was released on 2019-12-27 with total page 37 pages. Available in PDF, EPUB and Kindle. Book excerpt: We compared the predictive performance of a series of machine learning and traditional methods for monthly CDS spreads, using firms’ accounting-based, market-based and macroeconomics variables for a time period of 2006 to 2016. We find that ensemble machine learning methods (Bagging, Gradient Boosting and Random Forest) strongly outperform other estimators, and Bagging particularly stands out in terms of accuracy. Traditional credit risk models using OLS techniques have the lowest out-of-sample prediction accuracy. The results suggest that the non-linear machine learning methods, especially the ensemble methods, add considerable value to existent credit risk prediction accuracy and enable CDS shadow pricing for companies missing those securities.
Download or read book Machine Learning and Causality The Impact of Financial Crises on Growth written by Mr.Andrew J Tiffin and published by International Monetary Fund. This book was released on 2019-11-01 with total page 30 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine learning tools are well known for their success in prediction. But prediction is not causation, and causal discovery is at the core of most questions concerning economic policy. Recently, however, the literature has focused more on issues of causality. This paper gently introduces some leading work in this area, using a concrete example—assessing the impact of a hypothetical banking crisis on a country’s growth. By enabling consideration of a rich set of potential nonlinearities, and by allowing individually-tailored policy assessments, machine learning can provide an invaluable complement to the skill set of economists within the Fund and beyond.
Download or read book Lasso Regressions and Forecasting Models in Applied Stress Testing written by Mr.Jorge A. Chan-Lau and published by International Monetary Fund. This book was released on 2017-05-05 with total page 34 pages. Available in PDF, EPUB and Kindle. Book excerpt: Model selection and forecasting in stress tests can be facilitated using machine learning techniques. These techniques have proved robust in other fields for dealing with the curse of dimensionality, a situation often encountered in applied stress testing. Lasso regressions, in particular, are well suited for building forecasting models when the number of potential covariates is large, and the number of observations is small or roughly equal to the number of covariates. This paper presents a conceptual overview of lasso regressions, explains how they fit in applied stress tests, describes its advantages over other model selection methods, and illustrates their application by constructing forecasting models of sectoral probabilities of default in an advanced emerging market economy.
