MULTISTEP PREDICTION IN AUTOREGRESSIVE PROCESSES

By Ching-Kang Ing. Econometric Theory, 2003

133 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/1d277ec4cc19efc4149d0bbe284623b9170ba919

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Citations in the corpus

Direct multi-step estimation and forecasting (2006, unknown): “More recently Ing (2003) has analysed the estimation of stationary AR(p) processes via a misspecified AR(k) model, and, contrary to Bhansali (1996), did not assume independence between the estimation sample and the realizations to forecast.”
Multi-Period Forecasts of Volatility: Direct, Iterated, and Mixed-Data Approaches (2009, background): “Because model uncertainty might lead to severe forecasting biases, the theoretical papers on the subject seem to favor direct over iterated multi-period forecasts (Bhanzali (1999), Ing (2003), and Chevillon and Hendry (2005)).”
ACCUMULATED PREDICTION ERRORS, INFORMATION CRITERIA AND OPTIMAL FORECASTING FOR AUTOREGRESSIVE TIME SERIES (2007, background): “When Pn is independent of n, Ing and Wei ([14], Corollary 1) obtained an asymptotic expression for qn(k̂n,Pn)−σ 2, where k̂n,Pn , defined in (1.10), is the minimizer of ICPn(k), with 1 ≤ k ≤ Kn and Kn satisfying (K.4).”
Adaptive Estimation of Autoregressive Models with Time-Varying Variances (2008, unknown): “Thus (23) converges to zero by letting T →∞ then M →∞.”
Approximately Normal Tests for Equal Predictive Accuracy in Nested Models (2007, unknown): “See Ing (2003) and Marcellino et al. (2004) for theoretical and empirical comparison of direct and iterated methods.”
FORECAST EVALUATION (background): “See Ing (2003) and Marcellino, Stock and Watson (2004) for theoretical and empirical comparison of direct and iterated methods.”
A Comparison of Direct and Iterated Multistep Ar Methods for Forecasting Macroeconomic Time Series (2006, background): “…are correctly specified, in the sense of estimating the best linear predictor, the theoretical literature tends to conclude that the robustness of the direct forecast to model misspecification makes it a more attractive procedure than the bias-prone iterated forecast (Bhansali, 1999; Ing, 2003).”