Handbook of economic forecasting

Medientyp: E-Book

Titel: Handbook of economic forecasting / ed. by Graham Elliott
1

Enthält: Front cover; Title page; Copyright page; Introduction to the Series; Contents of the Handbook; Table of contents; Part 1: FORECASTING METHODOLOGY; 1 Bayesian Forecasting; Abstract; Keywords; Introduction; Bayesian inference and forecasting: A primer; Models for observables; An example: Vector autoregressions; An example: Stochastic volatility; The forecasting vector of interest; Model completion with prior distributions; The role of the prior; Prior predictive distributions; Hierarchical priors and shrinkage; Latent variables; Model combination and evaluation; Models and probability
A model is as good as its predictionsPosterior predictive distributions; Forecasting; Loss functions and the subjective decision maker; Probability forecasting and remote clients; Forecasts from a combination of models; Conditional forecasting; Posterior simulation methods; Simulation methods before 1990; Direct sampling; Acceptance sampling; Importance sampling; Markov chain Monte Carlo; The Gibbs sampler; The Metropolis-Hastings algorithm; Metropolis within Gibbs; The full Monte; Predictive distributions and point forecasts; Model combination and the revision of assumptions
'Twas not always so easy: A historical perspectiveIn the beginning, there was diffuseness, conjugacy, and analytic work; The dynamic linear model; The Minnesota revolution; After Minnesota: Subsequent developments; Some Bayesian forecasting models; Autoregressive leading indicator models; Stationary linear models; The stationary AR(p) model; The stationary ARMA(p,q) model; Fractional integration; Cointegration and error correction; Stochastic volatility; Practical experience with Bayesian forecasts; National BVAR forecasts: The Federal Reserve Bank of Minneapolis
Regional BVAR forecasts: economic conditions in IowaReferences; 2 Forecasting and Decision Theory; Abstract; Keywords; Preface; History of the field; Introduction; The Cambridge papers; Forecasting versus statistical hypothesis testing and estimation; Forecasting with decision-based loss functions; Background; Framework and basic analysis; Decision problems, forecasts and decision-based loss functions; Derivatives of decision-based loss functions; Inessential transformations of a decision problem; Recovery of decision problems from loss functions; Recovery from point-forecast loss functions
Implications of squared-error lossAre squared-error loss functions appropriate as ""local approximations""?; Implications of error-based loss; Location-dependent loss functions; Distribution-forecast and distribution-realization loss functions; References; 3 Forecast Evaluation; Abstract; Keywords; Introduction; A brief history; A small number of nonnested models, Part I; A small number of nonnested models, Part II; A small number of nonnested models, Part III; A small number of models, nested: MSPE; A small number of models, nested, Part II; Summary on small number of models
Large number of models
Bayesian ForecastingForecasting and Decision Theory -- Forecast Evaluation -- Forecast Combinations -- Predictive Density Evaluation -- Forecasting with VARMA Models -- Forecasting with Unobserved Components Time Series Models -- Forecasting economic variables with nonlinear models -- Approximate Nonlinear Forecasting Methods -- Forecasting with Many Predictors -- Forecasting with Trending Data -- Forecasting with Breaks -- Forecasting Seasonal Time Series -- Survey Expectations -- Volatility and Correlation Forecasting -- Leading Indicators -- Forecasting with Real-Time Macroeconomic Data -- Forecasting in Marketing.

Beteiligte: Elliott, Graham [Sonstige Person, Familie und Körperschaft]; Granger, C. W. J. [Sonstige Person, Familie und Körperschaft]; Timmermann, Allan [Sonstige Person, Familie und Körperschaft]

Erschienen: Amsterdam; Heidelberg [u.a]: Elsevier North Holland, 2006
2007

Umfang: Online-Ressource

Sprache: Englisch

ISBN: 9780444513953

RVK-Notation: QN 200 : Konjunkturschwankungen. Konjunkturprognosen
QH 237 : Zeitreihenanalyse. Anwendungen stochastischer Prozesse, stochastische Prozesse, stochastische Differentialgleichungen

Schlagwörter: Wirtschaft > Prognose > Prognoseverfahren > Ökonometrie > Theorie

Entstehung:

Anmerkungen: Includes bibliographical references and indexes. - Print version record

Beschreibung: Research on forecasting methods has made important progress over recent years and these developments are brought together in the Handbook of Economic Forecasting. The handbook covers developments in how forecasts are constructed based on multivariate time-series models, dynamic factor models, nonlinear models and combination methods. The handbook also includes chapters on forecast evaluation, including evaluation of point forecasts and probability forecasts and contains chapters on survey forecasts and volatility forecasts. Areas of applications of forecasts covered in the handbook include eco

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