arXiv 11 Feb 2026 · Econometrics
arXiv:2602.10415 · PDF · DOI · OpenAlex · Extracted main text
This paper rigorously analyzes the properties of the local projection (LP) methodology within a high-dimensional (HD) framework, with a central focus on achieving robust long-horizon inference. We integrate a general dependence structure into h-step ahead forecasting models via a flexible specification of the residual terms. Additionally, we study the corresponding HD covariance matrix estimation, explicitly addressing the complexity arising from the long-horizon setting. Extensive Monte Carlo simulations are conducted to substantiate the derived theoretical findings. In the empirical study, we utilize the proposed HD LP framework to study the impact of business news attention on U.S. industry-level stock volatility.
appendix boundary found by appendix_command · 33% of the source is main text. Read the extracted text to check this.
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 | Montiel Olea, José Luis and Plagborg-Møller, Mikkel (2021) Local projection inference is simpler and more robust than you think | 0.843 | 4 | 3 | 75% |
| 2 | Diebold, Francis X and Yilmaz, Kamil (2009) Measuring financial asset return and volatility spillovers, with application to global equity markets | 0.843 | 3 | 3 | 100% |
| 3 | Diebold, Francis X and Yilmaz, Kamil (2014) On the network topology of variance decompositions: Measuring the connectedness of financial firms | 0.843 | 3 | 3 | 100% |
| 4 | Jordá, Óscar (2005) Estimation and Inference of Impulse Responses by Local Projections | 0.811 | 4 | 2 | 100% |
| 5 | Sílvia Gon calves and Ana María Herrera and Lutz Kilian and Elena Pe… (2024) State-dependent local projections | 0.737 | 3 | 2 | 100% |
| 6 | Jooyoung Cha (2024) Local Projections Inference with High-Dimensional Covariates without Sparsity | 0.737 | 3 | 2 | 100% |
| 7 | Bybee, Leland and Kelly, Bryan and Manela, Asaf and Xiu, Dacheng (2024) Business news and business cycles | 0.644 | 4 | 1 | 100% |
| 8 | Adamek, Robert and Smeekes, Stephan and Wilms, Ines (2024) Local projection inference in high dimensions | 0.644 | 2 | 2 | 100% |
| 9 | Peter J. Bickel and Elizaveta Levina (2008) Covariance Regularization by Thresholding | 0.644 | 2 | 2 | 100% |
| 10 | Atsushi Inoue and Barbara Rossi and Yiru Wang (2024) Local projections in unstable environments | 0.644 | 2 | 2 | 100% |
Showing the top 10 of 39 scored citations.