L13.5 Forecast Revisions | Summary and Q&A
TL;DR
The law of iterated expectations states that the expected value of a revised forecast, given new information, is equal to the original forecast on average.
Key Insights
- 👶 The law of iterated expectations explains how to update forecasts based on new information.
- 💁 Revised forecasts are calculated using the expected value of the variable given the specific available information.
- 😘 On average, the revised forecast will not be higher or lower than the original forecast.
- 🥺 Real-life forecasts may be influenced by biases and hidden factors, leading to more frequent upward revisions of forecasts.
Transcript
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Questions & Answers
Q: What is the law of iterated expectations?
The law of iterated expectations states that the expected value of a revised forecast, given new information, is equal to the original forecast on average. It helps with understanding how to update forecasts based on new data.
Q: How does the law of iterated expectations apply to forecasting sales?
In the context of forecasting sales, the initial forecast at the beginning of the year is based on expected values. When new information, such as the value of another variable, becomes available, the revised forecast is calculated using the expected value of sales given that specific information.
Q: Does the law of iterated expectations imply that forecasts will not change?
No, the law does not imply that forecasts will not change. It simply states that, on average, the revised forecast will not be higher or lower than the original forecast. Individual forecasts may still vary based on the specific information available.
Q: How does the law of iterated expectations relate to real-life forecasts?
The law of iterated expectations does not contradict real-life experiences where forecasts are often revised upwards. In real life, forecasts may not be calculated as honest expected values but can be influenced by biases and hidden factors.
Summary & Key Takeaways
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The law of iterated expectations explains how to revise a forecast based on new information.
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Forecasts are made using expected values, but when new information is obtained, the revised forecast should be the expected value of the variable given the specific information.
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The law states that, on average, the revised forecast will not be higher or lower than the original forecast, but it could vary in individual cases.