Printed from https://ideas.repec.org/n/nep-ecm/2022-07-11.html
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.Subscribe to this report: email, RSS, or Mastodon, or Bluesky.
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, arXiv.org, number 2205.10198, May, revised Oct 2022.
- Qingliang Fan & Zijian Guo & Ziwei Mei, 2022, "A Heteroskedasticity-Robust Overidentifying Restriction Test with High-Dimensional Covariates," Papers, arXiv.org, number 2205.00171, Apr, revised May 2024.
- Sung Jae Jun & Sokbae Lee, 2022, "Average Adjusted Association: Efficient Estimation with High Dimensional Confounders," Papers, arXiv.org, number 2205.14048, May, revised Apr 2023.
- Philipp Ratz, 2022, "Nonparametric Value-at-Risk via Sieve Estimation," Papers, arXiv.org, number 2205.07101, May.
- Oorschot, Jochem & Segers, Johan & Zhou, Chen, 2022, "Tail inference using extreme U-statistics," LIDAM Discussion Papers ISBA, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA), number 2022014, Mar.
- Ziyu Wang & Yuhao Zhou & Jun Zhu, 2022, "Fast Instrument Learning with Faster Rates," Papers, arXiv.org, number 2205.10772, May, 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, Monash University, Department of Econometrics and Business Statistics, number 6/22.
- Martin Magris & Mostafa Shabani & Alexandros Iosifidis, 2022, "Quasi Black-Box Variational Inference with Natural Gradients for Bayesian Learning," Papers, arXiv.org, number 2205.11568, May, revised Dec 2022.
- Charles F. Manski, 2022, "Inference with Imputed Data: The Allure of Making Stuff Up," Papers, arXiv.org, number 2205.07388, May.
- Clara Bicalho & Adam Bouyamourn & Thad Dunning, 2022, "The Power of Prognosis: Improving Covariate Balance Tests with Outcome Information," Papers, arXiv.org, number 2205.10478, May, revised Oct 2025.
- Nathan Kallus, 2022, "What's the Harm? Sharp Bounds on the Fraction Negatively Affected by Treatment," Papers, arXiv.org, number 2205.10327, May, revised Nov 2022.
- Graham Elliott & Nikolay Kudrin & Kaspar Wuthrich, 2022, "The Power of Tests for Detecting $p$-Hacking," Papers, arXiv.org, number 2205.07950, May, revised Aug 2025.
- Bjoern Schulte-Tillman & Mawuli Segnon & Bernd Wilfling, 2022, "Financial-market volatility prediction with multiplicative Markov-switching MIDAS components," CQE Working Papers, Center for Quantitative Economics (CQE), University of Muenster, number 9922, Jun.
- Onishi, Rikuto & Otsu, Taisuke, 2021, "Sample sensitivity for two-step and continuous updating GMM estimators," LSE Research Online Documents on Economics, London School of Economics and Political Science, LSE Library, number 107522, Jan.
- Matteo Escud'e & Paula Onuchic & Ludvig Sinander & Quitz'e Valenzuela-Stookey, 2022, "Statistical discrimination and statistical informativeness," Papers, arXiv.org, number 2205.07128, May, revised May 2022.
- Mika Meitz & Pentti Saikkonen, 2022, "Subgeometrically ergodic autoregressions with autoregressive conditional heteroskedasticity," Papers, arXiv.org, number 2205.11953, May, revised Apr 2023.