Report NEP-ECM-2024-04-01
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.
Other reports in NEP-ECM
The following items were announced in this report:
- Daniele Ballinari, 2024. "Calibrating doubly-robust estimators with unbalanced treatment assignment," Papers 2403.01585, arXiv.org, revised Jun 2024.
- Alberto Abadie & Anish Agarwal & Raaz Dwivedi & Abhin Shah, 2024. "Doubly Robust Inference in Causal Latent Factor Models," Papers 2402.11652, arXiv.org, revised Oct 2024.
- Ruixuan Liu & Zhengfei Yu, 2024. "Quasi-Bayesian Estimation and Inference with Control Functions," Papers 2402.17374, arXiv.org.
- Sukjin Han & Adam McCloskey, 2024. "Inference for Interval-Identified Parameters Selected from an Estimated Set," Papers 2403.00422, arXiv.org.
- Tom Boot & Didier Nibbering, 2024. "Inference on LATEs with covariates," Papers 2402.12607, arXiv.org, revised Nov 2024.
- Yuya Sasaki & Jing Tao & Yulong Wang, 2024. "High-Dimensional Tail Index Regression: with An Application to Text Analyses of Viral Posts in Social Media," Papers 2403.01318, arXiv.org, revised Oct 2024.
- Sung Hoon Choi & Donggyu Kim, 2024. "Matrix-based Prediction Approach for Intraday Instantaneous Volatility Vector," Papers 2403.02591, arXiv.org, revised Dec 2024.
- Philipp Aschersleben & Julian Granna & Thomas Kneib & Stefan Lang & Nikolaus Umlauf & Winfried Steiner, 2024. "Modeling multiplicative interaction effects in Gaussian structured additive regression models," Working Papers 2024-01, Faculty of Economics and Statistics, Universität Innsbruck.
- Giovanni Angelini & Luca Fanelli & Luca Neri, 2024. "Invalid proxies and volatility changes," Working Papers wp1193, Dipartimento Scienze Economiche, Universita' di Bologna.
- Yiyan Huang & Cheuk Hang Leung & Siyi Wang & Yijun Li & Qi Wu, 2024. "Unveiling the Potential of Robustness in Selecting Conditional Average Treatment Effect Estimators," Papers 2402.18392, arXiv.org, revised Oct 2024.
- Santiago Pereda-Fern'andez, 2024. "Fast Algorithms for Quantile Regression with Selection," Papers 2402.16693, arXiv.org.
- Mohamed Doukali & Xiaojun Song & Abderrahim Taamouti, 2022. "Value-at Risk under Measurement Error," Working Papers 202209, University of Liverpool, Department of Economics.
- Sukjin Han & Hiroaki Kaido, 2024. "Set-Valued Control Functions," Papers 2403.00347, arXiv.org, revised Mar 2024.
- Man Chon Iao & Yatheesan J. Selvakumar, 2024. "Estimating HANK with Micro Data," Papers 2402.11379, arXiv.org.
- Kettlewell, Nathan & Walker, Matthew J. & Yoo, Hong Il, 2024. "Alternative Models of Preference Heterogeneity for Elicited Choice Probabilities," IZA Discussion Papers 16821, Institute of Labor Economics (IZA).
- Grant Hillier & Kees Jan van Garderen & Noud van Giersbergen, 2024. "Improved Tests for Mediation," Papers 2403.02144, arXiv.org.
- Victor Chernozhukov & Christian Hansen & Nathan Kallus & Martin Spindler & Vasilis Syrgkanis, 2024. "Applied Causal Inference Powered by ML and AI," Papers 2403.02467, arXiv.org.
- Johannes Carow, 2024. "A critical assessment of the two-way fixed-effects model for firm-level dependent variables," Working Papers 2405, Gutenberg School of Management and Economics, Johannes Gutenberg-Universität Mainz.
- Sina Akbari & Negar Kiyavash, 2024. "Non-linear Triple Changes Estimator for Targeted Policies," Papers 2402.12583, arXiv.org.
- Andrii Babii & Marine Carrasco & Idriss Tsafack, 2024. "Functional Partial Least-Squares: Optimal Rates and Adaptation," Papers 2402.11134, arXiv.org.
- Yuchen Hu & Henry Zhu & Emma Brunskill & Stefan Wager, 2024. "Minimax-Regret Sample Selection in Randomized Experiments," Papers 2403.01386, arXiv.org, revised Jun 2024.
- Richard Schnorrenberger & Aishameriane Schmidt & Guilherme Valle Moura, 2024. "Harnessing Machine Learning for Real-Time Inflation Nowcasting," Working Papers 806, DNB.
- Pengfei Zhao & Haoren Zhu & Wilfred Siu Hung NG & Dik Lun Lee, 2024. "From GARCH to Neural Network for Volatility Forecast," Papers 2402.06642, arXiv.org.