Comments on: "Linear models, smooth transition autoregressions and neural networks for forecasting macroeconomic time series: A re-examination"

Article Abstract:

An analysis of methods for forecasting macroeconomic time series proposed by Tomo Terasvirta, Dick van Dijk and Marcelo C. Medeiros in their report " Linear models, smooth transition autoregressions and neural networks for forecasting macroeconomic time series: A re-examination" is presented.

Reports, Terasvirta, Tomo, Dijk, Dick van, Medeiros, Marcelo C.

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Linear models, smooth transition autoregressions, and neural networks for forecasting macroeconomic time series: a re-examination

Article Abstract:

The prediction accuracy of linear autoregressive, smooth transition autoregressive and neural network time series models are analyzed. Forecast combination, nonlinear forecasting, etc. are examined.

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Forecasting aggregates using panels of nonlinear time series

Article Abstract:

The possibility of enhancing the accuracy of forecast of aggregates by regarding panel models for the disaggregate series is explored. Data aggregation, multi-level models, etc. are discussed.

Time-series analysis, Time series analysis

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