Making big decisions in life is sometimes require courage, particularly if it will affect our life in long term (e.g. Choosing education, career). It may be different than short term, daily decisions, which outcome will cointegrate in the long term. If errors exist, we can simply hope that it will back to normal tomorrow, and offset today's bad experience. If dynamic forecasting is too risky, we can simply use static projections, by updating the data and reestimate the model frequently.
In econometrics, short term forecasting is often fit well by simple autoregressive models, that only require historical data of variable projected. But for long term, advanced theory and more complex methods are often required. we also have to use many exogenous and instrumental variables, together with assumptions and scenarios. Therefore, it require much more information.
So what it has to be in the real life? To choose a career, we have to collect large scale of historical information about story of others, including exogenous variables such as particular individual characteristics, and control variables such as social acceptance and support. We have to make assumptions or scenarios to set values of exogenous shocks. Indeed, once assumptions are flawed or scenario we choose is misleading, we will face unexpected future. Nevertheless, information between sets of choices are often unbalanced.
Suppose there are two long term choices, let's consider them equivalent to long maturity assets that have very high transaction costs. One has sufficient number of observations and known exogenous data, while the other has not, but shows higher return in that small number of observations. Which asset should we choose?