Simulation-based selection of prediction models

Kunst, Robert M.ORCID: (2018) Simulation-based selection of prediction models. ITISE 2018. International Conference on Time Series and Forecasting, 19-21 Sept 2018, Granada. 10 p.

Full text not available from this repository.


We target an assessment of the potential benfits of basing model selection decisions in a forecasting context on simulations that fuse data information and the structure hypothesized by tentative rival models. These procedures can be applied to any empirical forecasting problems. Our main focus is, however, on macro-economic forecasting. Our procedure aims at choosing among a small number of tentative forecast models in the presence of data. From models fitted to the data, pseudo-data are generated. Again, the models are applied to the pseudo-data and their out-of-sample performance is evaluated. The ultimate choice of the forecasting model is based on the relative performance of rival models in predicting 'their own data' and those of the rival model.

Item Type: Conference or Workshop Item (Paper)
Additional Information (public): Proceedings of papers, vol. 1
Keywords: Simulation, forecasting, time series
Research Units: Former Research Units (until 2020) > Macroeconomics and Economic Policy
Related URLs:
Date Deposited: 18 Oct 2018 12:16
Last Modified: 18 Oct 2018 12:16

Actions (login required)

View Item View Item