arXiv 28 Mar 2025 · Econometrics
arXiv:2503.22054 · PDF · DOI · OpenAlex · Extracted main text
tempdisagg is a modern, extensible, and production-ready Python framework for temporal disaggregation of time series data. It transforms low-frequency aggregates into consistent, high-frequency estimates using a wide array of econometric techniques-including Chow-Lin, Denton, Litterman, Fernandez, and uniform interpolation-as well as enhanced variants with automated estimation of key parameters such as the autocorrelation coefficient rho. The package introduces features beyond classical methods, including robust ensemble modeling via non-negative least squares optimization, post-estimation correction of negative values under multiple aggregation rules, and optional regression-based imputation of missing values through a dedicated Retropolarizer module. Architecturally, it follows a modular design inspired by scikit-learn, offering a clean API for validation, modeling, visualization, and result interpretation.
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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 | Sax, C., & Steiner, P (2013) tempdisagg: Methods for Temporal Disaggregation and Interpolation of Time Series | 0.644 | 2 | 2 | 100% |
| 2 | Chow, G. C., & Lin, A. L (1971) Best linear unbiased interpolation, distribution, and extrapolation of time series by related series | 0.405 | 1 | 1 | 100% |
| 3 | Denton, F. T (1971) Adjustment of monthly or quarterly series to annual totals: An approach based on quadratic minimization | 0.405 | 1 | 1 | 100% |
| 4 | Fernández, R. B (1981) A methodological note on the estimation of time series | 0.405 | 1 | 1 | 100% |
| 5 | Litterman, R. B (1983) A random walk, Markov model for the distribution of time series | 0.405 | 1 | 1 | 100% |
| 6 | Quilis, E. M (2018) A generalized version of the Chow–Lin procedure for temporal disaggregation | 0.405 | 1 | 1 | 100% |
Showing the top 6 of 6 scored citations.