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 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 Nowcasting GDP and Inflation written by Domenico Giannone and published by . This book was released on 2005 with total page 62 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Nowcasting GDP Growth in a Small Open Economy written by Massimiliano Marcellino and published by . This book was released on 2021 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Forecasting National Activity Using Lots of International Predictors written by Sandra Eickmeier and published by . This book was released on 2016 with total page 60 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Peering Into the Present written by Nikoleta Anesti and published by . This book was released on 2017 with total page 13 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Bank's GDP nowcast represents the Monetary Policy Committee's (MPC's) estimate of economic growth in the current quarter, before official data become available. The nowcast is informed by statistical models, but is ultimately judgemental, reflecting all available information.Users of nowcasts must be aware of the degree of accuracy that can be expected, as this varies across models and time. Models based on survey information tend to be more accurate early in the quarter, whereas high-frequency output data published by the ONS become more useful later.The MPC's Inflation Report nowcasts have been relatively accurate, with a root mean squared error of 0.3 percentage points over the past ten years - lower than a mechanical use of the models could have attained. GDP growth estimates have fallen within 0.1 percentage points of the MPC's expectation about half the time, although much larger surprises have occasionally occurred.
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 Nowcasting GDP written by John W. Galbraith and published by . This book was released on 2013 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Nowcasting GDP Growth Rate written by M. Kuiper 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 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 Data Science for Economics and Finance written by Sergio Consoli and published by Springer Nature. This book was released on 2021 with total page 357 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Gauging the Globe written by Gene Kindberg-Hanlon and published by . This book was released on 2018 with total page 10 pages. Available in PDF, EPUB and Kindle. Book excerpt: Global activity is a key driver of UK GDP and a bellwether of prospects. Nowcasting global GDP growth, or predicting outturns ahead of their release, is therefore a key input into the Monetary Policy Committee's assessment of the UK economic outlook.The Bank uses a suite of models to assess the momentum in the world economy in real time. A wide range of financial market, survey-based and high-frequency output indicators are used to inform the suite.The statistical suite of global nowcasting models tends to provide an accurate assessment of global activity growth, and significantly outperformed a simple model that did not benefit from the use of high-frequency data during the financial crisis.
Download or read book New Monthly Estimation Approach for Nowcasting GDP Growth written by Naoko Hara and published by . This book was released on 2013 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Nowcasting World GDP Growth with High Frequency Data written by Caroline Jardet and published by . This book was released on 2020 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Covid-19 crisis has shown how high-frequency data can help tracking economic turning points in real-time. Our paper investigates whether high-frequency data can also improve the nowcasting performances for world GDP growth on quarterly or annual basis. To this end, we select a large dataset of 151 monthly and 39 weekly series for 17 advanced and emerging countries representing 68% of world GDP. Our approach builds on a Factor-Augmented MIxed DAta Sampling (FA-MIDAS) which allows us to take advantage of our large database and to combine different frequencies. Models that include weekly data significantly outperforms other models relying on monthly or quarterly indicators, both in- and out-of-sample. Breaking down our sample, we show that models with weekly data have similar nowcasting performances relative to other models during “normal” times but strongly outperform them during “crisis” episodes (2008-2009 and 2020). We finally construct a nowcasting model of annual world GDP growth incorporating weekly data which give timely (one every week) and accurate forecasts (close to IMF and OECD projections, but with a 1 to 3 months lead). Policy-wise, this model can provide an alternative “benchmark” projection for world GDP growth during crisis episodes when sudden swings in the economy make the usual “benchmark” projections (from the IMF or the OECD) rapidly outdated.
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 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 Impact of COVID 19 Nowcasting and Big Data to Track Economic Activity in Sub Saharan Africa written by Brandon Buell and published by International Monetary Fund. This book was released on 2021-05 with total page 61 pages. Available in PDF, EPUB and Kindle. Book excerpt: The COVID-19 pandemic underscores the critical need for detailed, timely information on its evolving economic impacts, particularly for Sub-Saharan Africa (SSA) where data availability and lack of generalizable nowcasting methodologies limit efforts for coordinated policy responses. This paper presents a suite of high frequency and granular country-level indicator tools that can be used to nowcast GDP and track changes in economic activity for countries in SSA. We make two main contributions: (1) demonstration of the predictive power of alternative data variables such as Google search trends and mobile payments, and (2) implementation of two types of modelling methodologies, machine learning and parametric factor models, that have flexibility to incorporate mixed-frequency data variables. We present nowcast results for 2019Q4 and 2020Q1 GDP for Kenya, Nigeria, South Africa, Uganda, and Ghana, and argue that our factor model methodology can be generalized to nowcast and forecast GDP for other SSA countries with limited data availability and shorter timeframes.
