Report NEP-ECM-2021-12-20

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:

• Hervé Cardot & Antonio Musolesi, 2021. "Zero-inflated regression for unobserved effects panel data models and difference-in-differences estimation," SEEDS Working Papers 1121, SEEDS, Sustainability Environmental Economics and Dynamics Studies, revised Dec 2021.
• Majed Dodin, 2021. "Optimized Inference in Regression Kink Designs," Papers 2111.10713, arXiv.org.
• Yuqian Zhang & Weijie Ji & Jelena Bradic, 2021. "Dynamic treatment effects: high-dimensional inference under model misspecification," Papers 2111.06818, arXiv.org, revised Jan 2025.
• Matthieu Garcin & Maxime L. D. Nicolas, 2021. "Nonparametric estimator of the tail dependence coefficient: balancing bias and variance," Papers 2111.11128, arXiv.org, revised Jul 2023.
• Xiu Xu & Weining Wang & Yongcheol Shin & Chaowen Zheng, 2021. "Dynamic Network Quantile Regression Model," Papers 2111.07633, arXiv.org.
• Taiga Tsubota, 2021. "Identifying Dynamic Discrete Choice Models with Hyperbolic Discounting," Papers 2111.10721, arXiv.org, revised Oct 2024.
• Joshua C. C. Chan & Gary Koop & Xuewen Yu, 2021. "Large Order-Invariant Bayesian VARs with Stochastic Volatility," Papers 2111.07225, arXiv.org.
• Max Cytrynbaum, 2021. "Optimal Stratification of Survey Experiments," Papers 2111.08157, arXiv.org, revised Aug 2023.
• Oscar Engelbrektson, 2021. "Why Synthetic Control estimators are biased and what to do about it: Introducing Relaxed and Penalized Synthetic Controls," Papers 2111.10784, arXiv.org.
• Junhui Cai & Dan Yang & Wu Zhu & Haipeng Shen & Linda Zhao, 2021. "Network regression and supervised centrality estimation," Papers 2111.12921, arXiv.org.
• Riccardo D'Adamo, 2021. "Orthogonal Policy Learning Under Ambiguity," Papers 2111.10904, arXiv.org, revised Dec 2022.
• Blankmeyer, Eric, 2021. "Peer Groups and Bias Detection in Least Squares Regression," MPRA Paper 110866, University Library of Munich, Germany.
• Xingwei Hu, 2021. "Decoding Causality by Fictitious VAR Modeling," Papers 2111.07465, arXiv.org, revised Nov 2021.
• Claudia Shi & Dhanya Sridhar & Vishal Misra & David M. Blei, 2021. "On the Assumptions of Synthetic Control Methods," Papers 2112.05671, arXiv.org, revised Dec 2021.
• Sokol, Andrej, 2021. "Fan charts 2.0: flexible forecast distributions with expert judgement," Working Paper Series 2624, European Central Bank.
• Clements, Adam & Hurn, Stan & Volkov, Vladimir, 2021. "A simple linear alternative to multiplicative error models with an application to trading volume," Working Papers 2021-06, University of Tasmania, Tasmanian School of Business and Economics.
• Myoung-jae Lee & Sanghyeok Lee, 2021. "Difference in Differences and Ratio in Ratios for Limited Dependent Variables," Papers 2111.12948, arXiv.org, revised Aug 2023.
• Christian Bongiorno & Damien Challet & Gr'egoire Loeper, 2021. "Cleaning the covariance matrix of strongly nonstationary systems with time-independent eigenvalues," Papers 2111.13109, arXiv.org, revised Mar 2023.
• Mr. Jorge A Chan-Lau, 2020. "UnFEAR: Unsupervised Feature Extraction Clustering with an Application to Crisis Regimes Classification," IMF Working Papers 2020/262, International Monetary Fund.
• Kenji Hatakenaka & Kosuke Oya, 2021. "Bayesian inference for time varying partial adjustment model with application to intraday price discovery," Discussion Papers in Economics and Business 21-19, Osaka University, Graduate School of Economics.
• Jonathan Roth & Guillaume Saint-Jacques & YinYin Yu, 2021. "An Outcome Test of Discrimination for Ranked Lists," Papers 2111.07889, arXiv.org.
• Luxuan Yang & Ting Gao & Yubin Lu & Jinqiao Duan & Tao Liu, 2021. "Neural network stochastic differential equation models with applications to financial data forecasting," Papers 2111.13164, arXiv.org, revised Nov 2022.