Forecast evaluation with shared data sets

Article Abstract:

Data sharing is common practice in forecasting experiments using which the forecasters often analyze the same data set using a host of different models and sets of explanatory variables. This practice introduces statistical dependencies across forecasting studies that can severely distort statistical inference and helps the forecasters to merge empirical evidence and draw inference by comparing the previously accumulated results.

Economic forecasting

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Statistically significant forecasting improvements: how much out-of-sample data is likely necessary?

Article Abstract:

Out-of-sample forecasting is known to be a rigorous check of the statistical adequacy of a model. Testing the out-of-sample forecasting superiority of one model over another needs a priority partitioning of the data into a model specification or estimation period and a model comparison or evaluation period.

Time-series analysis, Time series analysis

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Multi-period forecasting using different models for different horizons: an application to U.S. economic time series data

Article Abstract:

The author improves on economic forecasting by carefully selecting a model for each of many time periods rather than using a single model for the entire series.

Economic indicators

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