Feras A. Saad, Todd B. Walker
arXiv 28 Sep 2026 · Econometrics
arXiv:2609.36280 · PDF · Extracted main text
Seasonal adjustment is fundamental to economic analysis, but uncertain because seasonal components are inherently latent. This article introduces a probabilistic model discovery method that decomposes a time series into seasonal and nonseasonal components. The method returns a posterior distribution over the structure and parameters of a seasonal component. In simulation studies, the method can improve point forecasts, interval predictions, and recovery of seasonal components relative to X-13ARIMA-SEATS. In a study of eight U.S. macroeconomic series during the COVID-19 recession, the method surfaces significant ex-ante uncertainty about current seasonal adjustments in real time, well before many X-13 revisions reach their eventual peaks.
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The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | U.S. Census Bureau (2025) X-13ARIMA-SEATS Reference Manual | 1.000 | 5 | 3 | 100% |
| 2 | Saad, Feras A. and Patton, Brian J. and Hoffmann, Matthew D. and Sau… (2023) Sequential Monte Carlo Learning for Time Series Structure Discovery self | 0.874 | 5 | 2 | 100% |
| 3 | Rasmussen, Carl E. and Williams, Christopher K. I (2006) Gaussian Processes for Machine Learning | 0.737 | 4 | 3 | 50% |
| 4 | Box, George E. P. and Jenkins, Gwilym M (1976) Time Series Analysis: Forecasting and Control | 0.737 | 3 | 2 | 100% |
| 5 | Clive W. J. Granger (1978) Seasonality: Causation, Interpretation, and Implications | 0.644 | 2 | 2 | 100% |
| 6 | MacKay, David J. C (1998) Introduction to Gaussian Processes | 0.511 | 2 | 2 | 50% |
| 7 | Brown, Robert G (1963) Smoothing, Forecasting and Prediction of Discrete Time Series | 0.511 | 2 | 1 | 100% |
| 8 | Findley, David F. and Lytras, Demetra P. and McElroy, Tucker S Detecting Seasonality in Seasonally Adjusted Monthly Time Series | 0.511 | 2 | 1 | 100% |
| 9 | U.S. Bureau of Labor Statistics The Employment Situation–-July 2025 | 0.405 | 1 | 1 | 100% |
| 10 | U.S. Bureau of Labor Statistics (2026) Seasonal Adjustment Methodology for National Labor Force Statistics | 0.405 | 1 | 1 | 100% |
Showing the top 10 of 35 scored citations.