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 ass...