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Report NEP-ECM-2024-11-18
This is the archive for NEP-ECM, a report on new working papers in the area of Econometrics. Sune Karlsson issued this report. It is usually issued weekly.Subscribe to this report: email, RSS, or Mastodon, or Bluesky.
Other reports in NEP-ECM
The following items were announced in this report:
- Zhaonan Qu & Yongchan Kwon, 2024, "Distributionally Robust Instrumental Variables Estimation," Papers, arXiv.org, number 2410.15634, Oct, revised Dec 2024.
- Thomas von Brasch & Arvid Raknerud & Trond C. Vigtel, 2024, "Identifying Demand Elasticity via Heteroscedasticity. A Panel GMM Approach to Estimation and Inference," Discussion Papers, Statistics Norway, Research Department, number 1015, Oct.
- Robert F. Phillips & Benjamin D. Williams, 2024, "A Simple Interactive Fixed Effects Estimator for Short Panels," Papers, arXiv.org, number 2410.12709, Oct.
- Chad Brown, 2024, "Statistical Properties of Deep Neural Networks with Dependent Data," Papers, arXiv.org, number 2410.11113, Oct, revised Jan 2025.
- Ter Steege, Lucas, 2024, "Variational inference for Bayesian panel VAR models," Working Paper Series, European Central Bank, number 2991, Oct.
- Chengwang Liao & Ziwei Mei & Zhentao Shi, 2024, "Nickell Meets Stambaugh: A Tale of Two Biases in Panel Predictive Regressions," Papers, arXiv.org, number 2410.09825, Oct.
- Yannick Hoga, 2024, "Persistence-Robust Break Detection in Predictive Quantile and CoVaR Regressions," Papers, arXiv.org, number 2410.05861, Oct.
- Gawain Heckley & Dennis Petrie, 2024, "Taking an Extra Moment to Consider Treatment Effects on Distributions," Papers, Centre for Health Economics, Monash University, number 2024-18, Oct.
- Kalinke, Florian & Szabo, Zoltan, 2023, "Nyström M-Hilbert-Schmidt independence criterion," LSE Research Online Documents on Economics, London School of Economics and Political Science, LSE Library, number 118251, Aug.
- Qingliang Fan & Ruike Wu & Yanrong Yang, 2024, "Shocks-adaptive Robust Minimum Variance Portfolio for a Large Universe of Assets," Papers, arXiv.org, number 2410.01826, Sep.
- Osman Dou{g}an & Raffaele Mattera & Philipp Otto & Suleyman Tac{s}p{i}nar, 2024, "A Dynamic Spatiotemporal and Network ARCH Model with Common Factors," Papers, arXiv.org, number 2410.16526, Oct.
- Anubha Goel & Puneet Pasricha & Juho Kanniainen, 2024, "Time-Series Foundation AI Model for Value-at-Risk Forecasting," Papers, arXiv.org, number 2410.11773, Oct, revised May 2025.
- Kirill Ponomarev & Vira Semenova, 2024, "On the Lower Confidence Band for the Optimal Welfare in Policy Learning," Papers, arXiv.org, number 2410.07443, Oct, revised Sep 2025.
- Andrew Alden & Carmine Ventre & Blanka Horvath, 2024, "Scalable Signature-Based Distribution Regression via Reference Sets," Papers, arXiv.org, number 2410.09196, Oct.
- Luca Vincenzo Ballestra & Enzo D'Innocenzo & Christian Tezza, 2024, "GARCH option valuation with long-run and short-run volatility components: A novel framework ensuring positive variance," Papers, arXiv.org, number 2410.14513, Oct.
- Robert Fairlie & Daniel Oliver & Glenn Millhauser & Randa Roland & Robert W. Fairlie, 2024, "Estimating Peer Effects among College Students: Evidence from a Field Experiment of One-to-One Pairings in STEM," CESifo Working Paper Series, CESifo, number 11404.
- Pulikandala Nithish Kumar & Nneka Umeorah & Alex Alochukwu, 2024, "Dynamic graph neural networks for enhanced volatility prediction in financial markets," Papers, arXiv.org, number 2410.16858, Oct.