Tibor Szendrei, Arnab Bhattacharjee, Mark E. Schaffer
arXiv 20 Mar 2024 · Econometrics · 1 citations (OpenAlex)
arXiv:2403.14036 · PDF · DOI · OpenAlex · Extracted main text
Growth-at-Risk is vital for empirical macroeconomics but is often suspect to quantile crossing due to data limitations. While existing literature addresses this through post-processing of the fitted quantiles, these methods do not correct the estimated coefficients. We advocate for imposing non-crossing constraints during estimation and demonstrate their equivalence to fused LASSO with quantile-specific shrinkage parameters. By re-examining Growth-at-Risk through an interquantile shrinkage lens, we achieve improved left-tail forecasts and better identification of variables that drive quantile variation. We show that these improvements have ramifications for policy tools such as Expected Shortfall and Quantile Local Projections.
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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 | Adrian, T., N. Boyarchenko, and D. Giannone (2019) Vulnerable growth | 1.000 | 15 | 5 | 100% |
| 2 | Chernozhukov, V., I. Fernández-Val, and A. Galichon (2010) Quantile and probability curves without crossing | 1.000 | 6 | 4 | 100% |
| 3 | Szendrei, T. and K. Varga (2023) Revisiting vulnerable growth in the euro area: Identifying the role of financial conditions in the distribution self | 1.000 | 5 | 3 | 100% |
| 4 | Bondell, H. D., B. J. Reich, and H. Wang (2010) Noncrossing quantile regression curve estimation | 0.988 | 28 | 6 | 96% |
| 5 | Koenker, R. and G. Bassett (1978) Regression quantiles | 0.941 | 6 | 3 | 83% |
| 6 | Jiang, L., H. J. Wang, and H. D. Bondell (2013) Interquantile shrinkage in regression models | 0.928 | 5 | 4 | 80% |
| 7 | Carriero, A., T. E. Clark, and M. Marcellino (2025) Specification choices in quantile regression for empirical macroeconomics | 0.874 | 8 | 2 | 100% |
| 8 | Ruzicka, J (2021) Quantile local projections: Identification, smooth estimation, and inference | 0.874 | 6 | 2 | 100% |
| 9 | Koenker, R (2005) Quantile regression | 0.811 | 4 | 2 | 100% |
| 10 | Jiang, L., H. D. Bondell, and H. J. Wang (2014) Interquantile shrinkage and variable selection in quantile regression | 0.737 | 3 | 3 | 67% |
Showing the top 10 of 44 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
|---|---|---|---|---|
| 1 | MIDAS-QR with 2-Dimensional Structure | 0.874 | 9 | 2 |
| 2 | Momentum Informed Inflation-at-Risk | 0.874 | 6 | 2 |
| 3 | Joint Quantile Shrinkage: A State-Space Approach toward Non-Crossing Bayesian Quantile Models | 0.737 | 3 | 2 |
| 4 | A Roof Over Risk: A House Price-at-Risk Framework for Hungary | 0.405 | 1 | 1 |