Report NEP-ETS-2026-06-15

This is the archive for NEP-ETS, a report on new working papers in the area of Econometric Time Series. Yong Yin issued this report. It is usually issued weekly.

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Other reports in NEP-ETS

The following items were announced in this report:

• Todd E. Clark & Florian Huber & Gary Koop, 2026, "A Nonparametric Approach to Augmenting a Bayesian VAR with Nonlinear Factors," Working Papers, Federal Reserve Bank of Cleveland, number 26-14, Jun, DOI: 10.26509/frbc-wp-202614.
• Kpante Emmanuel Gnandi & Fredy Pokou & Jules Sadefo Kamdem, 2026, "Nonlinear and Heavy-Tailed Predictability in Transition-Energy Financial Markets," Papers, arXiv.org, number 2605.26890, May.
• Silvia Goncalves & Ana Maria Herrera & Lutz Kilian & Elena Peavento & Iones Kelanemer Holban, 2026, "Semiparametric Local Projections," Papers, arXiv.org, number 2606.13519, Jun.
• Yuxin Tao & Feiyu Jiang & Xiaofeng Shao, 2026, "Generalized Spectral Testing with Sample Splitting," Papers, arXiv.org, number 2605.29315, May.
• Vicente Esteve & Nicola Rubino, 2026, "Testing public debt sustainability with time-varying volatility: the case of Italy, 1861-2024," Working Papers, Department of Applied Economics II, Universidad de Valencia, number 2610, May.
• Joel M. David & Raffaella Giacomini & Xiyu Jiao & Weining Wang, 2026, "Causal State-Dependent Local Projections," Bristol Economics Discussion Papers, School of Economics, University of Bristol, UK, number 26/829, 01.
• Zhiruo Zhang & Firmin Doko Tchatoka & Qazi Haque, 2026, "Adaptive Bayesian Shrinkage of High-Dimensional Panel VARs," CAMA Working Papers, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University, number 2026-40, Jun.
• Jiaze Sun & Kelvin J. L. Koa & Ruiyang Ni & Yize Liu & Haonan Chen & Ke-Wei Huang, 2026, "FinStressTS: A Parametric Synthetic Benchmark for Time-Series Forecasting in Finance," Papers, arXiv.org, number 2606.03184, Jun.
• Pinjaman, Saizal, 2026, "A Simple Note on Augmented Autoregressive Distributed Lag Model (A-ARDL)," EconStor Preprints, ZBW - Leibniz Information Centre for Economics, number 341087, DOI: 10.6084/m9.figshare.32304789.
• Ajay Kumar Verma & Jul Jon Ramirez General & Yvan Landry Ndzonde Fonkou, 2026, "Deep Learning Forecasting of the U.S. Aggregate Bond Index," Papers, arXiv.org, number 2605.27977, May.