Economics and Business

Management

 

Heebner Prediction

 

Author: Paulo Nunes (Economist, Professor and Business Consultant)

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Date Created: 25/05/2011

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Key words:  management,

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Heebner Prediction

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Heebner Prediction Concept

The Seven Prediction Laws Model, developed by Gilbert Heebner, retired economist from Core-States Financial Corp., bases on the premise that is possible to perform rational evaluations when it’s about predictions, and has as goal to evaluate quantitative predictions and develop a cautious and rational prediction philosophy.

Prediction Laws:

Like the model’s name itself indicates, these bases in seven prediction laws, namely:

1. The Story repeats itself; the Story doesn’t repeat: such means that the future isn’t the result of chance, but also doesn’t exactly repeat itself.

2. Sometimes, big accidents (often unpredictable) deflect the economy from its course: despite the exogenous variables being of difficult predictability, some experienced observers can anticipate them.

3. Consensus among the economists’ predictions is more often right than wrong: it’s not wise to automatically be against the consensus.

4. The adherence to a unique economic theory can be dangerous for its prediction conditions: theories can become less valid as the conditions transform.

5. Economic forces work constantly, but in uncertain schedules: there’s a tendency that the predictions have higher probability to be correct as to the cause and effect, than as to its timing.

6. Prevent yourself when something holds back too much from the historic experiment: abnormal behaviors are always important, and should be analyzed attentively.

7. The road is more important than the hotel: the way how the prediction is reached is more important than the prediction itself; the rationality at the base of the prediction is usually elucidative and many times more useful than the prediction itself. 

 

 

Translated from Portuguese by Susana Saraiva, Portuguese-English and English-Portuguese translation specialist. Contact: spams@sapo.pt