Report NEP-ECM-2021-02-08

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.

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Other reports in NEP-ECM

The following items were announced in this report:

• Shi, Chengchun & Song, Rui & Lu, Wenbin & Li, Runzi, 2020. "Statistical inference for high-dimensional models via recursive online-score estimation," LSE Research Online Documents on Economics 103043, London School of Economics and Political Science, LSE Library.
• Paulo M.M. Rodrigues & Marina Balboa, 2021. "Multivariate Fractional Integration Tests allowing for Conditional Heteroskedasticity with an Application to Return Volatility and Trading Volume," Working Papers w202102, Banco de Portugal, Economics and Research Department.
• Andre Lucas & Anne Opschoor & Luca Rossini, 2021. "Tail Heterogeneity for Dynamic Covariance Matrices: the F-Riesz Distribution," Tinbergen Institute Discussion Papers 21-010/III, Tinbergen Institute, revised 11 Jul 2023.
• Wang, Wenjie, 2020. "On Bootstrap Validity for the Test of Overidentifying Restrictions with Many Instruments and Heteroskedasticity," MPRA Paper 104858, University Library of Munich, Germany.
• Siem Jan Koopman & Julia Schaumburg & Quint Wiersma, 2021. "Joint Modelling and Estimation of Global and Local Cross-Sectional Dependence in Large Panels," Tinbergen Institute Discussion Papers 21-008/III, Tinbergen Institute.
• Pincheira, Pablo & Hardy, Nicolás & Muñoz, Felipe, 2021. ""Go wild for a while!": A new asymptotically Normal test for forecast evaluation in nested models," MPRA Paper 105368, University Library of Munich, Germany.
• Minji Bang & Wayne Yuan Gao & Andrew Postlewaite & Holger Sieg, 2021. "Using Monotonicity Restrictions to Identify Models with Partially Latent Covariates," Papers 2101.05847, arXiv.org, revised Jun 2022.
• Palumbo, D., 2021. "Testing and Modelling Time Series with Time Varying Tails," Cambridge Working Papers in Economics 2111, Faculty of Economics, University of Cambridge.
• Nicolas Debarsy & Cem Ertur, 2019. "Interaction matrix selection in spatial econometrics with an application to growth theory," Post-Print halshs-01278545, HAL.
• Florian Eckert & Philipp Kronenberg & Heiner Mikosch & Stefan Neuwirth, 2020. "Tracking Economic Activity With Alternative High-Frequency Data," KOF Working papers 20-488, KOF Swiss Economic Institute, ETH Zurich.
• Edvard Bakhitov & Amandeep Singh, 2021. "Causal Gradient Boosting: Boosted Instrumental Variable Regression," Papers 2101.06078, arXiv.org.
• Arthur Lewbel & Susanne M. Schennach & Linqi Zhang, 2020. "Identification of a Triangular Two Equation System Without Instruments," Boston College Working Papers in Economics 1022, Boston College Department of Economics, revised 15 Dec 2022.
• Tam'as Krisztin & Philipp Piribauer, 2021. "A Bayesian approach for estimation of weight matrices in spatial autoregressive models," Papers 2101.11938, arXiv.org, revised Aug 2022.
• Pablo Montero-Manso & Rob J Hyndman, 2020. "Principles and Algorithms for Forecasting Groups of Time Series: Locality and Globality," Monash Econometrics and Business Statistics Working Papers 45/20, Monash University, Department of Econometrics and Business Statistics.
• Daouia, Abdelaati & Gijbels, Irene & Stupfler, Gilles, 2021. "Extremile Regression," TSE Working Papers 21-1176, Toulouse School of Economics (TSE).
• Pincheira, Pablo & Hardy, Nicolas, 2020. "The Mean Squared Prediction Error Paradox: A summary," MPRA Paper 105020, University Library of Munich, Germany.