Merging models and experts

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Abstract

It is argued that for specific forecast settings there must exist an optimally-sized model with forecasts that only need occasional adjustments by experts. The argument is built on recent evidence on the interaction between models and experts. A consequence of this is that the future research agenda should involve more interaction between researchers in model-based forecasting and those who are engaged in judgemental forecasting research.

Section snippets

Propositions

In this section I put forward four propositions, of which some are perhaps obvious, given the abundant evidence in the literature, while one or two propositions may seem surprising and lead to discussion. Some of the propositions are based on my consulting experience for the Netherlands Bureau of Economic Policy Analysis (CPB) and for the pharmaceutical company Organon. The CPB uses a many-equations model that covers the full economy in order to produce point forecasts for quarterly

Research agenda

To summarize, the above propositions clearly indicate that the interaction between a model and an expert is a very important one. It is doubtful whether macroeconomic or sales forecasts can be based either on experts' opinions only or on model output only, so the interaction is important, as it can be observed in everyday practice. Apparently, there can be something like an optimal interaction between the two. This means that modellers need to know more about what experts do with their

Acknowledgements

Many thanks are due to an anonymous Associate Editor for helpful suggestions.

References (10)

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