What goes into a forecast question? This article outlines the key elements of a forecast question and walks you through an example question, so you can examine and learn from each component. It also discusses the different types of questions (e.g., binary and multiple choice) that forecasters are likely to see on a forecasting platform.
It’s important to review all critical elements of a forecast question before beginning your own research. There are four key elements that we discuss here: the question itself, possible answers, background information, and question time frame. In the next section, we will show an example forecast question and explain individual components in further detail.
Definitions of any ambiguous terms.
Background information to familiarize forecasters with the topic and provide them with starting points for their research.
Resolution criteria to state the conditions by which the outcome will be judged.
Sources which will be relied upon for the final resolution.
Question starting and closing dates: The question start date is the date the question was launched and gives forecasters a sense of how long the question has been on the site. The question closing date is the last possible date that forecasts will be accepted on a question before it resolves. A question might be resolved prior to its closing date if the event in question occurs earlier.
Breaking down a specific question’s components often reveals much about the topic and answer options, even before beginning your own research. In the example below, we’ve underlined key components of a forecast question and outlined our takeaways from each part.
Blue: The first term (e.g., who, what, when, where, why) of a forecast question can tell you about the possible answers before you even look at the options. For example, “Will” here likely indicates that you are looking for a yes/no binary resolution.
Red: This is the “subject” of the question, pointing to whose actions are in focus.
Green: This is the objective and verifiable metric you are analyzing.
Purple: This is specifying context related to the objective metric you are analyzing. This information tells you how to limit your research, and, in this case, why these regulatory actions could matter.
Yellow: The time frame tells you how to limit your research and forecast accordingly.
Pink circles: Pay special attention to the background information and resolution criteria found under “See more details” and the question closing date to know how often you should review and update your forecast, and when the question will inevitably resolve.
Black circle: If you have doubts or questions about any component of the forecast question, submit a New Clarification request found under the settings gear icon.
It’s also helpful to know about the types of forecast questions and answer styles on a Cultivate-run forecasting site – you may have already noticed there are several! See descriptions and examples of the types used most often below:
Our question development teams work to design each forecast question so that
every element is intentional and aligns with the needs of the stakeholder or
decision-maker. However, don’t hesitate to reach out for a clarification if
there is any doubt about any particular component. Thanks for forecasting with