A comparison of direct and iterated multistep AR methods for forecasting macroeconomic time series

DOI10.1016/j.jeconom.2005.07.020zbMath1418.62513OpenAlexW3123760665MaRDI QIDQ291868

Mark W. Watson, Massimiliano Marcellino, James H. Stock

Publication date: 10 June 2016

Published in: Journal of Econometrics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jeconom.2005.07.020

zbMATH Keywords

forecast comparisonsmultistep forecastsVAR forecasts

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Inference from stochastic processes and prediction (62M20) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10)

Related Items

VAR forecasting under misspecification ⋮ Elements of randomized forecasting and its application to daily electrical load prediction in a regional power system ⋮ Predictive density and conditional confidence interval accuracy tests ⋮ Forecasting world trade: Direct versus ``bottom-up approaches ⋮ Bayesian model averaging and exchange rate forecasts ⋮ Forecast Combination and Model Averaging Using Predictive Measures ⋮ Boosting techniques for nonlinear time series models ⋮ Semiparametric modeling of multiple quantiles ⋮ Solving the dynamic traveling salesman problem using a genetic algorithm with trajectory prediction: an application to fish aggregating devices ⋮ Predicting the yield curve using forecast combinations ⋮ Forecasting inflation and GDP growth using heuristic optimisation of information criteria and variable reduction methods ⋮ Real-time factor model forecasting and the effects of instability ⋮ How should parameter estimation be tailored to the objective? ⋮ Track irregularity time series analysis and trend forecasting ⋮ Forecasting in nonlinear univariate time series using penalized splines ⋮ Augmenting the realized-GARCH: the role of signed-jumps, attenuation-biases and long-memory effects ⋮ Density Forecasts in Panel Data Models: A Semiparametric Bayesian Perspective ⋮ Comparison of the finite mixture of ARMA-GARCH, back propagation neural networks and support-vector machines in forecasting financial returns ⋮ Combining VAR and DSGE forecast densities ⋮ Large time-varying parameter VARs ⋮ Clustering nonlinear time series with neural network bootstrap forecast distributions ⋮ Evaluating Direct Multistep Forecasts ⋮ Specific-to-general predictor selection in approximate autoregressions -- Monte Carlo evidence and a large scale performance assessment with real data ⋮ Direct multiperiod forecasting for algorithmic trading ⋮ Multi‐step forecasting in the presence of breaks ⋮ Are disaggregate data useful for factor analysis in forecasting French GDP? ⋮ Dynamic probit models and financial variables in recession forecasting ⋮ The use of encompassing tests for forecast combinations ⋮ Modeling and forecasting (un)reliable realized covariances for more reliable financial decisions ⋮ Bias correction for time series factor models ⋮ Editorial. Annals issue on forecasting -- guest editors' introduction ⋮ Variable selection, estimation and inference for multi-period forecasting problems ⋮ A test for improved multi-step forecasting ⋮ Analysis of telecom service operation behavior with time series ⋮ Keep it simple: on specific-to-general predictor selection for time series forecasting in the short, medium and long run ⋮ Variable selection in regression models using nonstandard optimisation of information criteria ⋮ Combining forecasts based on multiple encompassing tests in a macroeconomic core system ⋮ Model selection for integrated autoregressive processes of infinite order ⋮ Variable selection in panel models with breaks ⋮ Order selection for possibly infinite-order non-stationary time series ⋮ Approximation methods for multiple period Value at Risk and Expected Shortfall prediction ⋮ Modeling tail risks of inflation using unobserved component quantile regressions ⋮ OPTIMAL MULTISTEP VAR FORECAST AVERAGING ⋮ The Multistep Beveridge–Nelson Decomposition ⋮ Forecasting Macroeconomic Variables Using Neural Network Models and Three Automated Model Selection Techniques ⋮ Forecasting Inflation Rates Using Daily Data: A Nonparametric MIDAS Approach

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• VAR forecasting under misspecification
• What does the yield curve tell us about GDP growth?
• Multi-step estimation and forecasting in dynamic models
• Asymptotically efficient autoregressive model selection for multistep prediction
• Robustness of maximum likelihood estimates for multi-step predictions: The exponential smoothing case
• Model selection for multiperiod forecasts
• Forecasting Using Principal Components From a Large Number of Predictors
• MULTISTEP PREDICTION IN AUTOREGRESSIVE PROCESSES
• Asymptotic Inference about Predictive Ability
• Tests of equal forecast accuracy and encompassing for nested models