Forecasting

Five-Volume Set Auflage
ISBN: 978-1-84860-782-8
Verlag: Sage Publications

Buch, Englisch, 2104 Seiten, Format (B × H): 156 mm x 234 mm, Gewicht: 3941 g

Reihe: SAGE Benchmarks in Social Research Methods

Forecasting has long been a core activity involving most if not all organizations. However, it is only relatively recently that it has become an area of intensive research. The earliest research was based in the core quantitative disciplines of statistics and econometrics. However, prior to 1981 there were relatively few articles whose primary focus was forecasting but with the founding of, first the Journal of Forecasting and then, in 1985, the International Journal of Forecasting, the field rapidly developed its own methodological perspectives. At its heart forecasting is concerned with evaluating alternative approaches to particular forecasting problems. Parts One and Two cover the core methodologies of forecasting. Part Three examines the evaluation of different forecasting methods and how to choose between them. Part Four includes studies that are specific to particular problem areas.

Autoren/Hrsg.

Fildes, Robert A

Allen, Geoff

Fachgebiete

• Sozialwissenschaften Soziologie | Soziale Arbeit Soziale Gruppen/Soziale Themen Sozialprognosen
• Sozialwissenschaften Soziologie | Soziale Arbeit Soziologie Allgemein Empirische Sozialforschung, Statistik
• Wirtschaftswissenschaften Volkswirtschaftslehre Volkswirtschaftslehre Allgemein Wirtschaftsprognose

Inhaltsverzeichnis

VOLUME 1
PART ONE: SMOOTHING PHILOSOPHY
Exponential Smoothing: The State of the Art - Everette Gardner
Exponential Smoothing With an Adaptive Response Rate - D.W. Trigg and A.G. Leach
Forecasting Trends in Time Series - Everette Gardner and Ed McKenzie
Integration with Statistical Approaches
A New Approach to Linear Filtering and Prediction Problems - Rudolf Kalman
Understanding the Kalman Filter - Richard Meinhold and Nozer Singpurwalla
Bayesian Forecasting - P.J. Harrison and C.F. Stevens
A Unified View of Statistical Forecasting Procedures - Andrew Harvey
Estimation and Prediction for a Class of Dynamic Nonlinear Statistical Models - Keith Ord, Anne Koehler and Ralph Snyder
Univariate Analyses of Time Series
Autoregressive Integrated Moving Average Models
Box-Jenkins Seasonal Forecasting: Problems in a Case Study with Discussion - Chris Chatfield and David Prothero
Outliers, Level Shifts, and Variance Changes in Time Series - Ruey Tsay
Unit Root Testing
Distribution of the Estimators for Autoregressive Time Series with a Unit Root - David Dickey and Wayne Fuller
Trends and Random-Walks in Macroeconomic Time Series: Some Evidence and Implications - Charles Nelson and Charles Plosser
Testing the Null Hypothesis of Stationarity against the Alternative of a Unit Root: How Sure Are We that Economic Time Series have a Unit Root? - Denis Kwiatkowski, Peter Phillips, Peter Schmidt and Yongcheol
Efficient Tests for an Autoregressive Unit Root - Graham Elliott, Thomas Rothenberg and James Stock
VOLUME 2
Psychologically-Based Approaches
Formalising Judgment
The Delphi Technique as a Forecasting Tool: Issues and Analysis - Gene Rowe and George Wright
Using Segmentation to Improve Sales Forecasts based on Purchase Intent: Which "Intenders" Actually Buy? - Vicki Morwitz and David Schmittlein
Bootstrapping (Judgmental Meaning)
Clinical Versus Actuarial Judgment - Robyn Dawes, David Faust and Paul Meehl
Heuristics and Biases in Forecasting
Timid Choices and Bold Forecasts: A Cognitive Perspective on Risk-Taking - Daniel Kahneman and Dan Lovallo
Judgment under Uncertainty: Heuristics and Biases - Amos Tversky and Daniel Kahneman
Interaction of Judgmental and Statistical Forecasting Methods: Issues and Analysis - Derek Bunn and George Wright
Improving Judgment
Database Models and Managerial Intuition - 50% Model + 50% Manager - Robert Blattberg and Stephen Hoch
Taking Advice: Accepting Help, Improving Judgment, and Sharing Responsibility - Nigel Harvey and Ilan Fischer
The Accuracy of Combining Judgmental and Statistical Forecasts - Michael Lawrence, Robert Edmundson and Marcus O'Connor
PART TWO: ECONOMETRICS: INTRODUCTION
Commentary on the State of the Art
Econometrics: Alchemy or Science? - David Hendry
Can We Improve the Perceived Quality of Economic Forecasts? - Clive Granger
Vector Autoregressions
Forecasting With Bayesian Vector Autoregressions: Five Years of Experience - Robert Litterman
Cointegration (Merging of TS and Econometrics?)
Spurious Regressions in Econometrics - Clive Granger and Paul Newbold
Econometric Modeling of the Aggregate Time Series Relationship between Consumers' Expenditure and Income in the UK - James Davidson, David Hendry, Frank Srba and Stephen Yeo
Cointegration and Error Correction: Representation, Estimation, and Testing - Robert Engle and Clive Granger
Maximum Likelihood Estimation and Inference on Cointegration - With Applications to the Demand for Money - Soren Johansen and Katarina Juselius
VOLUME THREE
Computer-Intensive Methods
How Effective Are Neural Networks at Forecasting and Prediction? A Review and Evaluation - Monica Adya and Fred Collopy
Some Recent Developments in Nonlinear Time-Series Modeling, Testing, and Forecasting - Jan Degooijer and Kuldeep Kumar
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