Report NEP-ECM-2022-11-28

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:

• Matteo Barigozzi, 2022. "On Estimation and Inference of Large Approximate Dynamic Factor Models via the Principal Component Analysis," Papers 2211.01921, arXiv.org, revised Jul 2023.
• Yiren Wang & Liangjun Su & Yichong Zhang, 2022. "Low-rank Panel Quantile Regression: Estimation and Inference," Papers 2210.11062, arXiv.org.
• Anish Agarwal & Sarah H. Cen & Devavrat Shah & Christina Lee Yu, 2022. "Network Synthetic Interventions: A Causal Framework for Panel Data Under Network Interference," Papers 2210.11355, arXiv.org, revised Oct 2023.
• Xiaolin Sun, 2022. "Estimation of Heterogeneous Treatment Effects Using a Conditional Moment Based Approach," Papers 2210.15829, arXiv.org, revised Oct 2024.
• Gregory Cox, 2022. "Weak Identification in Low-Dimensional Factor Models with One or Two Factors," Papers 2211.00329, arXiv.org, revised Mar 2024.
• Philipp Ketz, 2022. "Allowing for weak identification when testing GARCH-X type models," Papers 2210.11398, arXiv.org.
• Rub'en Loaiza-Maya & Didier Nibbering, 2022. "Efficient variational approximations for state space models," Papers 2210.11010, arXiv.org, revised Jun 2023.
• Christian Brownlees & Vladislav Morozov, 2022. "Unit Averaging for Heterogeneous Panels," Papers 2210.14205, arXiv.org, revised May 2024.
• Alain-Philippe Fortin & Patrick Gagliardini & Olivier Scaillet, 2022. "Eigenvalue tests for the number of latent factors in short panels," Papers 2210.16042, arXiv.org.
• Riccardo Della Vecchia & Debabrota Basu, 2023. "Online Instrumental Variable Regression: Regret Analysis and Bandit Feedback," Working Papers hal-03831210, HAL.
• Giovanni Ballarin & Petros Dellaportas & Lyudmila Grigoryeva & Marcel Hirt & Sophie van Huellen & Juan-Pablo Ortega, 2022. "Reservoir Computing for Macroeconomic Forecasting with Mixed Frequency Data," Papers 2211.00363, arXiv.org, revised Jan 2024.
• Daniel Borup & Philippe Goulet Coulombe & Erik Christian Montes Schütte & David E. Rapach & Sander Schwenk-Nebbe, 2022. "The Anatomy of Out-of-Sample Forecasting Accuracy," FRB Atlanta Working Paper 2022-16, Federal Reserve Bank of Atlanta.
• Ekaterina Morozova & Vladimir Panov, 2022. "Modelling the Bitcoin prices and the media attention to Bitcoin via the jump-type processes," Papers 2210.13824, arXiv.org.
• David Childers & Jesús Fernández-Villaverde & Jesse Perla & Christopher Rackauckas & Peifan Wu, 2022. "Differentiable State-Space Models and Hamiltonian Monte Carlo Estimation," NBER Working Papers 30573, National Bureau of Economic Research, Inc.
• Hudde, Ansgar & Jacob, Marita, 2022. "There’s More in the Data! Using Month-Specific Information to Estimate Changes Before and After Major Life Events," SocArXiv vueas, Center for Open Science.
• Efrem Castelnuovo & Lorenzo Mori, 2022. "Uncertainty, Skewness and the Business Cycle - Through the MIDAS Lens," CAMA Working Papers 2022-69, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Alessandra Canepa, & Karanasos, Menelaos & Paraskevopoulos, Athanasios & Chini, Emilio Zanetti, 2022. "Forecasting Ination: A GARCH-in-Mean-Level Model with Time Varying Predictability," Department of Economics and Statistics Cognetti de Martiis. Working Papers 202212, University of Turin.
• Aeppli, Clem & Ruedin, Didier, 2022. "How to Measure Agreement, Consensus, and Polarization in Ordinal Data," SocArXiv syzbr, Center for Open Science.
• Richard T. Baillie & Francis X. Diebold & George Kapetanios & Kun Ho Kim, 2022. "A New Test for Market Efficiency and Uncovered Interest Parity," NBER Working Papers 30638, National Bureau of Economic Research, Inc.
• Max Nendel & Alessandro Sgarabottolo, 2022. "A parametric approach to the estimation of convex risk functionals based on Wasserstein distance," Papers 2210.14340, arXiv.org, revised Aug 2024.
• Brodeur, Abel & Cook, Nikolai & Hartley, Jonathan & Heyes, Anthony, 2022. "Do Pre-Registration and Pre-analysis Plans Reduce p-Hacking and Publication Bias?," MetaArXiv uxf39, Center for Open Science.