Economic downturn reshapes forecasting methods, leading to more accurate predictions.
The article explores how to make accurate economic forecasts during a recession by adjusting the prior information used in a statistical model. The researchers found that during an economic downturn, the optimal prior changes in two ways. First, less weight is placed on past economic data compared to more recent information. Second, more uncertainty in a recession requires a wider range of possible values for coefficients in the model. This means that the model may need to be adjusted to account for the increased uncertainty during economic downturns.