arXiv 7 Jul 2026 · Econometrics
arXiv:2607.05882 · PDF · DOI · OpenAlex · Extracted main text
Macroeconomic forecasts refer to outcomes that are first released and then revised. A 90 percent interval for the first GDP release, a six-month value, or a latest-value benchmark is not the same uncertainty statement. We ask how revision risk evolves through the release cycle and what can be reported in real time when later-outcome errors are scarce. We decompose later-outcome MSE into preliminary forecast risk, revision risk, and their covariance. In SPF data, first-release to roughly 180-day revisions account for 8.3 percent of later-outcome MSE across real-activity targets, versus 3.6 percent across inflation targets. We show that later-outcome uncertainty is partially identified: released histories give early-error and revision marginals, but not their dependence. This yields a sharp Frechet-Makarov set and motivates direct late calibration, dependence-robust transport, and signed or revision-model transport. Out-of-sample results support method choice rather than a universal transport rule: coverage and stability determine when transport gains are usable.
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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 | Clements, Michael P (2017) Assessing Macroeconomic Uncertainty in Real Time When Data Are Subject to Revision | 0.737 | 3 | 3 | 67% |
| 2 | Clements, Michael P. and Galvão, Ana Beatriz (2013) Real-Time Forecasting of Inflation and Output Growth with Autoregressive Models in the Presence of Data Revisions | 0.737 | 3 | 3 | 67% |
| 3 | Clements, Michael P. and Galvão, Ana Beatriz (2023) Density Forecasting with Bayesian Vector Autoregressive Models under Macroeconomic Data Uncertainty | 0.737 | 3 | 3 | 67% |
| 4 | Chernozhukov, Victor and Hong, Han and Tamer, Elie (2007) Estimation and Confidence Regions for Parameter Sets in Econometric Models | 0.644 | 2 | 2 | 100% |
| 5 | Frank, Maurice J. and Nelsen, Roger B. and Schweizer, Berthold (1987) Best-Possible Bounds for the Distribution of a Sum–-a Problem of Kolmogorov | 0.644 | 2 | 2 | 100% |
| 6 | Imbens, Guido W. and Manski, Charles F (2004) Confidence Intervals for Partially Identified Parameters | 0.644 | 2 | 2 | 100% |
| 7 | Makarov, G. D (1982) Estimates for the Distribution Function of a Sum of Two Random Variables when the Marginal Distributions are Fixed | 0.644 | 2 | 2 | 100% |
| 8 | Manski, Charles F (2003) Partial Identification of Probability Distributions | 0.644 | 2 | 2 | 100% |
| 9 | Molinari, Francesca (2020) Microeconometrics with Partial Identification | 0.644 | 2 | 2 | 100% |
| 10 | Aruoba, S. Bora gan (2008) Data Revisions Are Not Well Behaved | 0.405 | 1 | 1 | 100% |
Showing the top 10 of 37 scored citations.