Yunyun Wang, Tatsushi Oka, Dan Zhu
arXiv 19 Mar 2024 · Econometrics · 2 citations (OpenAlex)
arXiv:2403.12456 · PDF · DOI · OpenAlex · Extracted main text
Macro variables frequently display time-varying distributions, driven by the dynamic and evolving characteristics of economic, social, and environmental factors that consistently reshape the fundamental patterns and relationships governing these variables. To better understand the distributional dynamics beyond the central tendency, this paper introduces a novel semi-parametric approach for constructing time-varying conditional distributions, relying on the recent advances in distributional regression. We present an efficient precision-based Markov Chain Monte Carlo algorithm that simultaneously estimates all model parameters while explicitly enforcing the monotonicity condition on the conditional distribution function. Our model is applied to construct the forecasting distribution of inflation for the U.S., conditional on a set of macroeconomic and financial indicators. The risks of future inflation deviating excessively high or low from the desired range are carefully evaluated. Moreover, we provide a thorough discussion about the interplay between inflation and unemployment rates during the Global Financial Crisis, COVID, and the third quarter of 2023.
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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 | Kilian, Lutz and Manganelli, Simone (2007) Quantifying the risk of deflation | 0.928 | 4 | 4 | 100% |
| 2 | Korobilis, Dimitris and Landau, Bettina and Musso, Alberto and Phell… (2021) The time-varying evolution of inflation risks | 0.928 | 4 | 4 | 100% |
| 3 | Lopez-Salido, David and Loria, Francesca (2024) Inflation at risk | 0.928 | 4 | 3 | 100% |
| 4 | Primiceri, Giorgio E (2005) Time varying structural vector autoregressions and monetary policy | 0.843 | 3 | 3 | 100% |
| 5 | Barnichon, Regis and Mesters, Geert (2020) Identifying modern macro equations with old shocks | 0.737 | 3 | 2 | 100% |
| 6 | Blanchard, Olivier (2016) The Phillips curve: Back to the '60s? | 0.737 | 3 | 2 | 100% |
| 7 | Del Negro, Marco and Lenza, Michele and Primiceri, Giorgio E and Tam… (2020) What's up with the Phillips Curve? | 0.737 | 3 | 2 | 100% |
| 8 | Inoue, Atsushi and Rossi, Barbara and Wang, Yiru (2025) Has the Phillips curve flattened? self | 0.737 | 3 | 2 | 100% |
| 9 | Forbes, Kristin and Gagnon, Joseph and Collins, Christopher G (2021) Low Inflation Bends the Phillips Curve around the World | 0.644 | 2 | 2 | 100% |
| 10 | Harding, Martín and Lindé, Jesper and Trabandt, Mathias (2023) Understanding post‐COVID inflation dynamics | 0.644 | 2 | 2 | 100% |
Showing the top 10 of 54 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
|---|---|---|---|---|
| 1 | International vulnerability of inflation | 0.405 | 1 | 1 |