Forecasting Confidence Intervals: Sensitivity Respecting Panel-Data Point-Value Replacement Protocols

Abstract

In the practice of Time Series [TS] forecasting there are very often situations where it is prudent to modify certain “outlier” values in the TS-Panel. A simple modification protocol is to replace selected TS-points by the Average of their adjacent Near-Neighbor-points [ANN]. Thus, a research question, not previously addressed and thus of interest, is: Are ANN-TS modifications balanced—50% of the time provoking OLS-forecasting variation, thus reducing the predicative acuity of the 95% Confidence Intervals; and, by symmetry, 50% of the time smoothing resulting in more predicative resolution. Research Plan To address this question, we: (i) collected accounting information to be forecasted from firms on the Bloomberg™ terminals for Income Statement and Balance Sheet sensitive variables, (ii) formed three ANN-modifications, and (iii) computed 95% Confidence Intervals using the firm-Panel and the three modified Panels. Results Regarding the research question, surprisingly the ANN-replacement protocols were not balanced. In fact, about 2/3 of the time the ANN was smoothing in nature, and thus about 1/3 of the time the ANN-protocol provoked OLS-variation. We discuss the important implication of this result for forecasting in the economic context.