Was the title of a talk that Scott Armstrong gave to his fellow Lehigh University Graduating Class of 1959 at their 60th Reunion on June 7. The invited talk addressed the question of whether the alarm over dangerous manmade global warming is a valid scientific claim, and presents findings on the predicitve validity of the methods behind the alarming forecasts from Scott's research with Kesten Green. A copy of the slides for the talk is available from ResearchGate, here.

Econometric election forecasting models contribute to election year commentary around the world. Andreas Graefe, Kesten Green, and Scott Armstrong tested whether applying three relevant conservative forecasting principles from the Golden Rule of Forecasting to modify established election forecasting models would increase the accuracy of out-of-sample forecasts. The short answer is, yes: errors were reduced by up to 43%.

The paper has been published in PLOS One with the long but descriptive title of "Accuracy gains from conservative forecasting: Tests using variations of 19 econometric models to predict 154 elections in 10 countries". It is available, Open Access, here.  

Scott Armstrong presented a commentary on the findings of the M4-Competition at the M4 Conference in New York City on December 10, 2018. The paper, by Scott Armstrong and Kesten Green, concludes that data models should not be used for forecasting, describing six reasons why. The reasons are not new—for example Einhorn pointed out the lack of theoretical support in "Alchemy in the behavioral sciences" in 1972—but they remain true.

The conference paper slides are available from ResearchGate, here.

Accurate predictions and the correct assessment of uncertainty are indispensable for all types of future oriented decisions: from determining appropriate inventory levels and predicting the amount of sales of companies to forecasting revenues and costs and the formulation of a long-term strategy. The purpose of the Makridakis, or M, Competitions has been to provide empirical evidence to guide organizations on how to improve the accuracy of their forecasts and how to assess future uncertainty as realistically as possible.

Scott Armstrong presented a paper with Kesten Green at the International Symposium on Forecasting in Boulder, CO, on 19 June titled "Do Forecasters of Dangerous Manmade Global Warming Follow the Science?". A pdf copy of the slides is available from ResearchGate, here.