Bad Assumptions, Bad Results
One of the most important questions facing decision-makers is: Why are forecasts from so many of today’s sophisticated economic models so often disappointing?
The easy answer is, GIGO.
“GIGO,” as everyone knows and Wikipedia explains, “is an acronym for Garbage In, Garbage Out. It is a fundamental computing and data science principle stating that the quality of an output is strictly determined by the quality of the input. If flawed, biased, or poor-quality data (garbage) is fed into a system, the resulting analysis or output will be equally flawed (garbage), regardless of how advanced the algorithm is.”
So, bad stuff in, bad stuff out.
But the failures of so many forecasting models used by governments as well as those used throughout the business and investing world are about more than bad data.
Sometimes it is bad data.
Far too often, it is ignoring the universal and timeless truth that false assumptions lead to false results.
Which means mistakes can be made whenever assumptions do not match reality.
And there may be no better description of the importance of assumptions matching reality than Mike Tyson’s famous and often-quoted response to a reporter who asked him if he was worried about Evander Holyfield and his fight plan. Tyson's answer was, “Everyone has a plan until they get punched in the mouth.”
Models built on market-based economics are no different. They can look elegant, sophisticated, and convincing until they get punched in the mouth by reality.
Which is why avoiding knowingly false assumptions may be the most important thing investors, businesspeople, policymakers, and publications can do to avoid doing too many stupid things.
DENNIS F. PAULAHA
