Author : Michael P. Clements
Publisher : OUP USA
Page : 732 pages
File Size : 22,6 MB
Release : 2011-07-08
Category : Business & Economics
ISBN : 0195398645
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.
Author : Eric Ghysels
Publisher : Oxford University Press
Page : 617 pages
File Size : 26,79 MB
Release : 2018
Category : Business & Economics
ISBN : 0190622016
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.
Author : Vladimir Kuzin
Publisher :
Page : 0 pages
File Size : 40,23 MB
Release : 2009
Category :
ISBN : 9783865585097
Author : Graham Elliott
Publisher : Newnes
Page : 719 pages
File Size : 32,45 MB
Release : 2013-08-23
Category : Business & Economics
ISBN : 0444536841
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 : John Geweke
Publisher : Oxford University Press
Page : 576 pages
File Size : 39,89 MB
Release : 2011-09-29
Category : Business & Economics
ISBN : 0191618268
Bayesian econometric methods have enjoyed an increase in popularity in recent years. Econometricians, empirical economists, and policymakers are increasingly making use of Bayesian methods. This handbook is a single source for researchers and policymakers wanting to learn about Bayesian methods in specialized fields, and for graduate students seeking to make the final step from textbook learning to the research frontier. It contains contributions by leading Bayesians on the latest developments in their specific fields of expertise. The volume provides broad coverage of the application of Bayesian econometrics in the major fields of economics and related disciplines, including macroeconomics, microeconomics, finance, and marketing. It reviews the state of the art in Bayesian econometric methodology, with chapters on posterior simulation and Markov chain Monte Carlo methods, Bayesian nonparametric techniques, and the specialized tools used by Bayesian time series econometricians such as state space models and particle filtering. It also includes chapters on Bayesian principles and methodology.
Author : Mr.Jaromir Benes
Publisher : International Monetary Fund
Page : 37 pages
File Size : 44,21 MB
Release : 2010-03-01
Category : Business & Economics
ISBN : 1451963629
This paper outlines a simple approach for incorporating extraneous predictions into structural models. The method allows the forecaster to combine predictions derived from any source in a way that is consistent with the underlying structure of the model. The method is flexible enough that predictions can be up-weighted or down-weighted on a case-by-case basis. We illustrate the approach using a small quarterly structural and real-time data for the United States.
Author : Maximo Camacho
Publisher :
Page : 74 pages
File Size : 18,60 MB
Release : 2013-11-01
Category : Business & Economics
ISBN : 9781601987426
Short-term Forecasting for Empirical Economists seeks to close the gap between research and applied short-term forecasting. The authors review some of the key theoretical results and empirical findings in the recent literature on short-term forecasting, and translate these findings into economically meaningful techniques to facilitate their widespread application to compute short-term forecasts in economics, and to monitor the ongoing business cycle developments in real time.
Author : Thomas B. Fomby
Publisher : Emerald Group Publishing Limited
Page : 0 pages
File Size : 46,63 MB
Release : 2013-12-18
Category : Business & Economics
ISBN : 9781781907528
Advances in Econometrics publishes original scholarly econometric papers with the intention of expanding the use of developed and emerging econometric techniques by disseminating ideas on the theory and practice of econometrics, throughout the empirical economic, business and social science literature.
Author : Edward P. Herbst
Publisher : Princeton University Press
Page : 295 pages
File Size : 19,10 MB
Release : 2015-12-29
Category : Business & Economics
ISBN : 0691161089
Dynamic stochastic general equilibrium (DSGE) models have become one of the workhorses of modern macroeconomics and are extensively used for academic research as well as forecasting and policy analysis at central banks. This book introduces readers to state-of-the-art computational techniques used in the Bayesian analysis of DSGE models. The book covers Markov chain Monte Carlo techniques for linearized DSGE models, novel sequential Monte Carlo methods that can be used for parameter inference, and the estimation of nonlinear DSGE models based on particle filter approximations of the likelihood function. The theoretical foundations of the algorithms are discussed in depth, and detailed empirical applications and numerical illustrations are provided. The book also gives invaluable advice on how to tailor these algorithms to specific applications and assess the accuracy and reliability of the computations. Bayesian Estimation of DSGE Models is essential reading for graduate students, academic researchers, and practitioners at policy institutions.
Author : Claudia Foroni
Publisher :
Page : 0 pages
File Size : 23,98 MB
Release : 2011
Category :
ISBN : 9783865587817
