Tibor Szendrei, Arnab Bhattacharjee
arXiv 22 Aug 2024 · Econometrics
arXiv:2408.12286 · PDF · DOI · OpenAlex · Extracted main text
Growth-at-Risk has recently become a key measure of macroeconomic tail-risk, which has seen it be researched extensively. Surprisingly, the same cannot be said for Inflation-at-Risk where both tails, deflation and high inflation, are of key concern to policymakers, which has seen comparatively much less research. This paper will tackle this gap and provide estimates for Inflation-at-Risk. The key insight of the paper is that inflation is best characterised by a combination of two types of nonlinearities: quantile variation, and conditioning on the momentum of inflation.
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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 | Lopez-Salido, D. and F. Loria (2022) Inflation at risk | 1.000 | 7 | 4 | 100% |
| 2 | Adrian, T., N. Boyarchenko, and D. Giannone (2019) Vulnerable growth | 1.000 | 7 | 3 | 100% |
| 3 | Banerjee, R. N., J. Contreras, A. Mehrotra, and F. Zampolli (2020) Inflation at risk in advanced and emerging market economies | 1.000 | 5 | 3 | 100% |
| 4 | De Grauwe, P (2011) Animal spirits and monetary policy | 1.000 | 5 | 3 | 100% |
| 5 | McMillen, D. P (2015) Conditionally parametric quantile regression for spatial data: An analysis of land values in early nineteenth century chicago | 0.874 | 6 | 2 | 100% |
| 6 | Szendrei, T., A. Bhattacharjee, and M. E. Schaffer (2024) Fused LASSO as non-crossing quantile regression self | 0.874 | 6 | 2 | 100% |
| 7 | Bondell, H. D., B. J. Reich, and H. Wang (2010) Noncrossing quantile regression curve estimation | 0.644 | 4 | 1 | 100% |
| 8 | Koenker, R. and G. Bassett (1978) Regression quantiles | 0.644 | 2 | 2 | 100% |
| 9 | Kohns, D. and T. Szendrei (2023) Horseshoe prior Bayesian quantile regression | 0.644 | 2 | 2 | 100% |
| 10 | Wolters, M. H. and P. Tillmann (2015) The changing dynamics of us inflation persistence: A quantile regression approach | 0.644 | 2 | 2 | 100% |
Showing the top 10 of 54 scored citations.