Understanding Economic Forecasts

Understanding Economic Forecasts
Author: David F. Hendry
Publisher: MIT Press
Total Pages: 236
Release: 2003
Genre: Business & Economics
ISBN: 9780262582421

How to interpret and evaluate economic forecasts and the uncertainties inherent in them.

Economic Forecasting

Economic Forecasting
Author: Ken Holden
Publisher: Cambridge University Press
Total Pages: 222
Release: 1991-04-04
Genre: Business & Economics
ISBN: 9780521356121

This book provides an introduction to the methods employed in forecasting the future state of the economy. It is the only text currently available which provides a comprehensive coverage of methods and applications in this fast-growing area. Part I outlines the available techniques, including those used in business forecasting and econometric forecasting. Part II considers the most important applications of forecasting.

Applied Economic Forecasting Using Time Series Methods

Applied Economic Forecasting Using Time Series Methods
Author: Eric Ghysels
Publisher: Oxford University Press
Total Pages: 617
Release: 2018
Genre: 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.

Handbook of Economic Forecasting

Handbook of Economic Forecasting
Author: Graham Elliott
Publisher: Elsevier
Total Pages: 667
Release: 2013-08-23
Genre: Business & Economics
ISBN: 0444627405

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

Econometric Forecasting and High-frequency Data Analysis

Econometric Forecasting and High-frequency Data Analysis
Author: Roberto S. Mariano
Publisher: World Scientific
Total Pages: 200
Release: 2008
Genre: Business & Economics
ISBN: 9812778969

This important book consists of surveys of high-frequency financial data analysis and econometric forecasting, written by pioneers in these areas including Nobel laureate Lawrence Klein. Some of the chapters were presented as tutorials to an audience in the Econometric Forecasting and High-Frequency Data Analysis Workshop at the Institute for Mathematical Science, National University of Singapore in May 2006. They will be of interest to researchers working in macroeconometrics as well as financial econometrics. Moreover, readers will find these chapters useful as a guide to the literature as well as suggestions for future research. Sample Chapter(s). Foreword (32 KB). Chapter 1: Forecast Uncertainty, Its Representation and Evaluation* (97 KB). Contents: Forecasting Uncertainty, Its Representation and Evaluation (K F Wallis); The University of Pennsylvania Models for High-Frequency Macroeconomic Modeling (L R Klein & S Ozmucur); Forecasting Seasonal Time Series (P H Franses); Car and Affine Processes (C Gourieroux); Multivariate Time Series Analysis and Forecasting (M Deistler). Readership: Professionals and researchers in econometric forecasting and financial data analysis.

Forecasting: principles and practice

Forecasting: principles and practice
Author: Rob J Hyndman
Publisher: OTexts
Total Pages: 380
Release: 2018-05-08
Genre: Business & Economics
ISBN: 0987507117

Forecasting is required in many situations. Stocking an inventory may require forecasts of demand months in advance. Telecommunication routing requires traffic forecasts a few minutes ahead. Whatever the circumstances or time horizons involved, forecasting is an important aid in effective and efficient planning. This textbook provides a comprehensive introduction to forecasting methods and presents enough information about each method for readers to use them sensibly.

Applied Econometrics with R

Applied Econometrics with R
Author: Christian Kleiber
Publisher: Springer Science & Business Media
Total Pages: 229
Release: 2008-12-10
Genre: Business & Economics
ISBN: 0387773185

R is a language and environment for data analysis and graphics. It may be considered an implementation of S, an award-winning language initially - veloped at Bell Laboratories since the late 1970s. The R project was initiated by Robert Gentleman and Ross Ihaka at the University of Auckland, New Zealand, in the early 1990s, and has been developed by an international team since mid-1997. Historically, econometricians have favored other computing environments, some of which have fallen by the wayside, and also a variety of packages with canned routines. We believe that R has great potential in econometrics, both for research and for teaching. There are at least three reasons for this: (1) R is mostly platform independent and runs on Microsoft Windows, the Mac family of operating systems, and various ?avors of Unix/Linux, and also on some more exotic platforms. (2) R is free software that can be downloaded and installed at no cost from a family of mirror sites around the globe, the Comprehensive R Archive Network (CRAN); hence students can easily install it on their own machines. (3) R is open-source software, so that the full source code is available and can be inspected to understand what it really does, learn from it, and modify and extend it. We also like to think that platform independence and the open-source philosophy make R an ideal environment for reproducible econometric research.

The Oxford Handbook of Economic Forecasting

The Oxford Handbook of Economic Forecasting
Author: Michael P. Clements
Publisher: OUP USA
Total Pages: 732
Release: 2011-07-08
Genre: 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.

Forecasting Economic Time Series

Forecasting Economic Time Series
Author: Michael Clements
Publisher: Cambridge University Press
Total Pages: 402
Release: 1998-10-08
Genre: Business & Economics
ISBN: 9780521634809

This book provides a formal analysis of the models, procedures, and measures of economic forecasting with a view to improving forecasting practice. David Hendry and Michael Clements base the analyses on assumptions pertinent to the economies to be forecast, viz. a non-constant, evolving economic system, and econometric models whose form and structure are unknown a priori. The authors find that conclusions which can be established formally for constant-parameter stationary processes and correctly-specified models often do not hold when unrealistic assumptions are relaxed. Despite the difficulty of proceeding formally when models are mis-specified in unknown ways for non-stationary processes that are subject to structural breaks, Hendry and Clements show that significant insights can be gleaned. For example, a formal taxonomy of forecasting errors can be developed, the role of causal information clarified, intercept corrections re-established as a method for achieving robustness against forms of structural change, and measures of forecast accuracy re-interpreted.