FORECASTING ECONOMIC TIME SERIES

By Frank Schorfheide. Econometric Theory, 2000

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Bayesian forecasting using stochastic search variable selection in a VAR subject to breaks (2010, background): “The negative consequences of ignoring this instability for inference and forecasting has been stressed by, among many others, Clements and Hendry (1998, 1999), Koop and Potter (2001, 2007) and Pesaran, Pettenuzzo and Timmerman (2006).”
A Test for Superior Predictive Ability (2005, background): “Imposing a particular value will (most likely) introduce a “bias,” but if this bias is small, it may be less severe for out-of-sample predictions than the prediction error introduced by estimation error (see, e.g., Clements and Hendry 1998).”
Tourism forecasting: accuracy of alternative econometric models (2003, methodology): “The time models is sensitive to the different methodologies varying parameter (TVP) approach allows for strucused (Clements & Hendry, 1998).”
A Kolmogorov-Smirnov Based Test for Comparing the Predictive Accuracy of Two Sets of Forecasts (2015, background): “1 Note that the Granger and Newbold [16] assumption of forecast errors having zero mean is not essential according to [17].”
Forecasting: theory and practice (2020, methodology): “ic analysis is based mainly on Mean Absolute Error (MAE) and Root Mean Square Error (RMSE). MAE and RMSE are used to provide a relative forecasting evaluation compared to other competitors. Following Clements and Hendry (1998), Kolasa et al. (2012) apply the standard forecast unbiased test to assess”