arXiv 25 Jul 2023 · Econometrics · publishedJournal of Econometrics (2024) · 22 citations (OpenAlex)
arXiv:2307.13364 · PDF · DOI · OpenAlex · Extracted main text
We propose a novel bootstrap test of a dense model, namely factor regression, against a sparse plus dense alternative augmenting model with sparse idiosyncratic components. The asymptotic properties of the test are established under time series dependence and polynomial tails. We outline a data-driven rule to select the tuning parameter and prove its theoretical validity. In simulation experiments, our procedure exhibits high power against sparse alternatives and low power against dense deviations from the null. Moreover, we apply our test to various datasets in macroeconomics and finance and often reject the null. This suggests the presence of sparsity -- on top of a dense model -- in commonly studied economic applications. The R package FAS implements our approach.
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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 | Fan, Masini \ Medeiros (2023) `Bridging factor and sparse models', The Annals of Statistics 51(4), 1692–1717 | 1.000 | 18 | 3 | 100% |
| 2 | Fan, Lou \ Yu (2024) `Are latent factor regression and sparse regression adequate?', Journal of the American Statistical Association 119(546), 1076–1… | 1.000 | 9 | 3 | 100% |
| 3 | Bai \ Ng (2006) `Confidence intervals for diffusion index forecasts and inference for factor-augmented regressions', Econometrica 74(4), 1133–1150 | 0.956 | 8 | 3 | 88% |
| 4 | Lederer \ Vogt (2021) `Estimating the Lasso's effective noise.', Journal of Machine Learning Research 22, 276–1 | 0.935 | 11 | 5 | 82% |
| 5 | Ahn \ Horenstein (2013) `Eigenvalue ratio test for the number of factors', Econometrica 81(3), 1203–1227 | 0.928 | 4 | 4 | 100% |
| 6 | Kolesár, Müller \ Roelsgaard (2023) `The fragility of sparsity', arXiv preprint arXiv:2311.02299 | 0.874 | 5 | 2 | 100% |
| 7 | Stock \ Watson (2002) `Forecasting using principal components from a large number of predictors', Journal of the American Statistical Association 97(4… | 0.822 | 6 | 2 | 83% |
| 8 | Giannone, Lenza \ Primiceri (2021) `Economic predictions with big data: The illusion of sparsity', Econometrica 89(5), 2409–2437 | 0.737 | 3 | 2 | 100% |
| gonccalves2014bootstrapping | unmatched citation key gonccalves2014bootstrapping | 0.737 | 3 | 2 | 100% |
| 10 | Bai \ Ng (2002) `Determining the number of factors in approximate factor models', Econometrica 70(1), 191–221 | 0.644 | 2 | 2 | 100% |
Showing the top 10 of 48 scored citations. 1 of these could not be matched to a bibliography entry, so only the citation key is shown.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
|---|---|---|---|---|
| 1 | The Fragility of Sparsity | 0.405 | 1 | 1 |