But forecasters often resist considering these…
““But forecasters often resist considering these out-of-sample problems. When we expand our sample to include events further apart from us in time and space, it often means that we will encounter cases in which the relationships we are studying did not hold up as well as we are accustomed to. The model will seem to be less powerful. It will look less impressive in a PowerPoint presentation (or a journal article or a blog post). We will be forced to acknowledge that we know less about the world than we thought we did. Our personal and professional incentives almost always discourage us from doing this.””
About This Quote
This interpretation was drafted with AI assistance. It is one reading of the quote, not the author's own explanation.
Models often fail when applied beyond their original context, revealing hidden uncertainties and the need for humility.
In simple terms: Models break outside familiar data, showing limits.
Key Takeaway
Acknowledge model limits.
Themes
uncertainty
modeling
humility
Mood
cautious
analytical
Type
analytical
pragmatic
When to use this quote
- policy making
- forecasting
Key Concepts
statistical inference
risk assessment
Questions to Reflect On
- When should you trust a model?
- How can you incorporate uncertainty into decisions?
A Different Perspective
Overemphasis on models can ignore qualitative insights.