Following the publication of the Golden Rule of Forecasting in late 2015, Scott Armstrong and Kesten Green have made available an Android app to help forecasters to follow the Golden Rule and help forecast users to determine whether a forecast is a product of methods that are consistent with the Golden Rule. To find out more about the free app and to download a copy, clcik on the link on the page of this site.

Kesten Green and Scott Armstrong have created a new website devoted to evidence on the Iron Law of Regulation. The objective of the site is in part to "summarize experimental evidence on the effect of regulations on general welfare". The site is relevant for forecasters who wish to follow the Golden Rule of Forecasting when engaged in forecasting for public policy. The Golden Rule of Forecasting requires that forecasters acquire and use all relevant knowledge about the situation being forecast. You can visit this new resource, and add it to your favorites, at

Running advertisements and other persuasive messages is an expensive business, and the difference between an effective ad and one that isn't can be the difference between success and failure. A new paper by Scott Armstrong, Rui Du, Kesten Green, and Andreas Graefe tests a new method—in the form of the Persuasion Principles Index (PPI) model—for predicting the relative effectiveness of advertisements. In effect, the PPI is a rating of conformity to persuasion principles.

Polly the parrot is back for forecasting the outcome of the U.S. presidential election. In order to calculate the PollyVote forecast, Polly uses the evidence-based principle of combining forecasts to average forecasts within and across different methods, each of which rely on different information. Election forecasting thus provides ideal conditions for demonstrating the benefits of combining. In fact, PollyVote has provided highly accurate U.S. election forecasts since her first appearance in 2004.

The PollyVote currently predicts that the Democrats will gain 51.5% of the national popular two-party vote, compared to 48.5% for the Republicans. Yet, there is still a lot of uncertainty until the candidates are known. You can track the daily updated forecast at

The political leaders and government officials who gathered in Paris have made agreements to implement disruptive and expensive policies on the basis of forecasts of dangerous manmade global warming. The forecasts—which are called scenarios and projections by the U.N. Intergovernmental Panel on Climate Change (IPCC)—are the product of complex computer models involving multitudes of interacting assumptions.

The finding of Kesten Green and Scott Armstrong's recent review that complexity increased forecast errors by 27% on average should have given delegates at the Paris climate policy talks pause for thought: Occam's razor applies to scientific forecasting, too.

At this year's International Symposium on Forecasting, Kesten and Scott presented a review of the IPCC's modeling procedures using a nine-item checklist on conformance with evidence-based guidance on simplicity in forecasting. They found that the IPCC procedures have a "simplicity rating" of 19%. That figure contrasts with a simplicity rating of 93% for the Green, Armstrong and Soon no-change (no-trend) model of long-term global average temperatures.

There is no evidence that climate forecasting is an exception to Occam's razor.