Report NEP-ECM-2022-07-11

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:

• Kuanhao Jiang & Rajarshi Mukherjee & Subhabrata Sen & Pragya Sur, 2022. "A New Central Limit Theorem for the Augmented IPW Estimator: Variance Inflation, Cross-Fit Covariance and Beyond," Papers 2205.10198, arXiv.org, revised Oct 2022.
• Qingliang Fan & Zijian Guo & Ziwei Mei, 2022. "A Heteroskedasticity-Robust Overidentifying Restriction Test with High-Dimensional Covariates," Papers 2205.00171, arXiv.org, revised May 2024.
• Sung Jae Jun & Sokbae Lee, 2022. "Average Adjusted Association: Efficient Estimation with High Dimensional Confounders," Papers 2205.14048, arXiv.org, revised Apr 2023.
• Philipp Ratz, 2022. "Nonparametric Value-at-Risk via Sieve Estimation," Papers 2205.07101, arXiv.org.
• Oorschot, Jochem & Segers, Johan & Zhou, Chen, 2022. "Tail inference using extreme U-statistics," LIDAM Discussion Papers ISBA 2022014, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
• Ziyu Wang & Yuhao Zhou & Jun Zhu, 2022. "Fast Instrument Learning with Faster Rates," Papers 2205.10772, arXiv.org, revised Oct 2022.
• Ryan Zischke & Gael M. Martin & David T. Frazier & Donald S. Poskitt, 2022. "The Impact of Sampling Variability on Estimated Combinations of Distributional Forecasts," Monash Econometrics and Business Statistics Working Papers 6/22, Monash University, Department of Econometrics and Business Statistics.
• Martin Magris & Mostafa Shabani & Alexandros Iosifidis, 2022. "Quasi Black-Box Variational Inference with Natural Gradients for Bayesian Learning," Papers 2205.11568, arXiv.org, revised Dec 2022.
• Charles F. Manski, 2022. "Inference with Imputed Data: The Allure of Making Stuff Up," Papers 2205.07388, arXiv.org.
• Clara Bicalho & Adam Bouyamourn & Thad Dunning, 2022. "Conditional Balance Tests: Increasing Sensitivity and Specificity With Prognostic Covariates," Papers 2205.10478, arXiv.org.
• Nathan Kallus, 2022. "What's the Harm? Sharp Bounds on the Fraction Negatively Affected by Treatment," Papers 2205.10327, arXiv.org, revised Nov 2022.
• Graham Elliott & Nikolay Kudrin & Kaspar Wuthrich, 2022. "The Power of Tests for Detecting $p$-Hacking," Papers 2205.07950, arXiv.org, revised Apr 2024.
• Bjoern Schulte-Tillman & Mawuli Segnon & Bernd Wilfling, 2022. "Financial-market volatility prediction with multiplicative Markov-switching MIDAS components," CQE Working Papers 9922, Center for Quantitative Economics (CQE), University of Muenster.
• Onishi, Rikuto & Otsu, Taisuke, 2021. "Sample sensitivity for two-step and continuous updating GMM estimators," LSE Research Online Documents on Economics 107522, London School of Economics and Political Science, LSE Library.
• Matteo Escud'e & Paula Onuchic & Ludvig Sinander & Quitz'e Valenzuela-Stookey, 2022. "Statistical discrimination and statistical informativeness," Papers 2205.07128, arXiv.org, revised May 2022.
• Mika Meitz & Pentti Saikkonen, 2022. "Subgeometrically ergodic autoregressions with autoregressive conditional heteroskedasticity," Papers 2205.11953, arXiv.org, revised Apr 2023.