situations when some of the collected data points may have measurement errors and are therefore submitted to an editing process … form of editing that limits the edit checks to those potential errors that, if indeed in error, are likely to have the …

little persistence of inflation during the 19th century. Using a statistical technique that accounts for these errors, we …

to limiting nonstandard errors in portfolio modeling and emphasize the necessity of robust strategies in low …

accuracy of the underlying assumptions. This paper examines the extent to which assumption errors affect forecast accuracy … ordinary least squares (OLS) techniques systematically underestimate the influence of assumption errors, particularly with … the data. However, the effect of oil price assumption errors on GDP forecast errors remains ambiguous. These results …

This DFG project addressed the research question of how specific decision errors in innovation endeavors occur and … from not pursuing an inherently good project further. Focusing on these distinct decision errors, particularly the latter …

quantile loss function, least absolute errors, and generalized cross-validation criteria to estimate the model parameters. We …

insights and practical applications, offering actionable guidance to investors on limiting nonstandard errors. …