Author : Mr.Troy Matheson
Publisher : International Monetary Fund
Page : 24 pages
File Size : 40,18 MB
Release : 2011-02-01
Category : Business & Economics
ISBN : 1455218995
We develop monthly indicators for tracking growth in 32 advanced and emerging-market economies. We test the historical performance of our indicators and find that they do a good job at describing the business cycle. In a recursive out-of-sample forecasting exercise, we find that the indicators generally produce good GDP growth forecasts relative to a range of time series models.
Author : Mr.Michael Stanger
Publisher : International Monetary Fund
Page : 25 pages
File Size : 38,62 MB
Release : 2020-01-17
Category : Business & Economics
ISBN : 1513525859
Monthly economic indicators support policy analysis of current economic developments and forecasting. This paper presents an overview of the data and statistical requirements to develop those indicators taking into account resource constraints that LIC typically face. We review statistical procedures for developing these indicators under the System of National Accounts and propose a general procedure to derive a monthly composite indicator of economic growth in low income economies.
Author : Graham Elliott
Publisher : Elsevier
Page : 1386 pages
File Size : 49,11 MB
Release : 2013-10-24
Category : Business & Economics
ISBN : 0444627413
The highly prized ability to make financial plans with some certainty about the future comes from the core fields of economics. In recent years the availability of more data, analytical tools of greater precision, and ex post studies of business decisions have increased demand for information about economic forecasting. Volumes 2A and 2B, which follows Nobel laureate Clive Granger's Volume 1 (2006), concentrate on two major subjects. Volume 2A covers innovations in methodologies, specifically macroforecasting and forecasting financial variables. Volume 2B investigates commercial applications, with sections on forecasters' objectives and methodologies. Experts provide surveys of a large range of literature scattered across applied and theoretical statistics journals as well as econometrics and empirical economics journals. The Handbook of Economic Forecasting Volumes 2A and 2B provide a unique compilation of chapters giving a coherent overview of forecasting theory and applications in one place and with up-to-date accounts of all major conceptual issues. - Focuses on innovation in economic forecasting via industry applications - Presents coherent summaries of subjects in economic forecasting that stretch from methodologies to applications - Makes details about economic forecasting accessible to scholars in fields outside economics
Author : Karl Heinrich Oppenländer
Publisher :
Page : 314 pages
File Size : 14,71 MB
Release : 1997
Category : Business & Economics
ISBN : 9781859724361
The pressure to produce explanations and forecasts and the economic dichotomies which insist on appearing, lead to a desire to deal with the description, analysis and forecast of the phenomenon of business cycles using economic indicators. This text provides an introduction to business cycles and their theoretical and historical basis. It also includes work on early indicator research and provides examples of business cycle indicators.
Author : Mr.Maxym Kryshko
Publisher : International Monetary Fund
Page : 51 pages
File Size : 27,91 MB
Release : 2011-09-01
Category : Business & Economics
ISBN : 1463903499
Dynamic factor models and dynamic stochastic general equilibrium (DSGE) models are widely used for empirical research in macroeconomics. The empirical factor literature argues that the co-movement of large panels of macroeconomic and financial data can be captured by relatively few common unobserved factors. Similarly, the dynamics in DSGE models are often governed by a handful of state variables and exogenous processes such as preference and/or technology shocks. Boivin and Giannoni(2006) combine a DSGE and a factor model into a data-rich DSGE model, in which DSGE states are factors and factor dynamics are subject to DSGE model implied restrictions. We compare a data-richDSGE model with a standard New Keynesian core to an empirical dynamic factor model by estimating both on a rich panel of U.S. macroeconomic and financial data compiled by Stock and Watson (2008).We find that the spaces spanned by the empirical factors and by the data-rich DSGE model states are very close. This proximity allows us to propagate monetary policy and technology innovations in an otherwise non-structural dynamic factor model to obtain predictions for many more series than just a handful of traditional macro variables, including measures of real activity, price indices, labor market indicators, interest rate spreads, money and credit stocks, and exchange rates.
Author :
Publisher :
Page : 32 pages
File Size : 36,44 MB
Release : 1984
Category : Dollar, American
ISBN :
Author : Mr.Ashvin Ahuja
Publisher : International Monetary Fund
Page : 28 pages
File Size : 12,40 MB
Release : 2017-06-01
Category : Business & Economics
ISBN : 1484302567
Assessing country risk is a core component of surveillance at the IMF. It is conducted through a comprehensive architecture, covering both bilateral and multilateral dimensions. This note describes some of the approaches used internally by Fund staff to examine a wide array of systemic risks across advanced, emerging, and low-income economies. It provides a high-level view of the theory and methodologies employed, with an on-line companion guide providing more technical details of implementation. The guide will be updated as Fund staff’s methodologies for assessing country risk continue to evolve with experience and feedback. While the results of these approaches are not published by the IMF for market sensitivity reasons, they inform risk assessments featured in bilateral surveillance as well as in the IMF’s flagship publications on global surveillance.
Author : Karim Barhoumi
Publisher : International Monetary Fund
Page : 14 pages
File Size : 18,9 MB
Release : 2015-01-26
Category : Business & Economics
ISBN : 149830754X
This paper develops a new monthly World Trade Leading Indicator (WTLI) that relies on nonparametric and parametric approaches. Compared to the CPB World Trade Monitor’s benchmark indicator for global trade the WTLI captures turning points in global trade with an average lead between 2 and 3 months. We also show that this cyclical indicator is able to track the annual growth rate in global trade, suggesting that the recent slowdown is due in part to certain cyclical factors. This new tool can provide policy makers with valuable foresight into the future direction of economic activity by tracking world trade more efficiently.
Author : Giorgio Gomel
Publisher : Springer Science & Business Media
Page : 284 pages
File Size : 49,17 MB
Release : 2012-07-31
Category : Business & Economics
ISBN : 3642286380
This book takes readers on a unique journey across some of the most debated implications of the rise of the Chinese economy on the global scene. From the analysis, suggestions emerge on how to improve statistical tools to measure performance and to obtain more precise macroeconomic forecasts. Moreover, it confirms the suspicion that a governance model of firms that does not sufficiently encourage market competition may have significant costs in terms of efficiency for the Chinese production system. The analysis of demographic factors and of household savings gives further support to calls for a serious reform effort, particularly of the pension and health care systems, to utilize households’ savings more efficiently and equitably. Finally the analyses of Chinese and global trade underscore the need for a less superficial consideration of the implications of the Chinese presence in global markets.
Author : Sergio Consoli
Publisher : Springer Nature
Page : 357 pages
File Size : 19,73 MB
Release : 2021
Category : Application software
ISBN : 3030668916
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.
