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Report NEP-ECM-2024-10-28
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.Subscribe to this report: email, RSS, or Mastodon, or Bluesky.
Other reports in NEP-ECM
The following items were announced in this report:
- Jo~ao Nicolau & Paulo M. M. Rodrigues, 2024, "A simple but powerful tail index regression," Papers, arXiv.org, number 2409.13531, Sep.
- Julius Owusu, 2024, "A Nonparametric Test of Heterogeneous Treatment Effects under Interference," Papers, arXiv.org, number 2410.00733, Oct.
- Eugene Dettaa & Endong Wang, 2024, "Inference in High-Dimensional Linear Projections: Multi-Horizon Granger Causality and Network Connectedness," Papers, arXiv.org, number 2410.04330, Oct.
- Zhe Sun & Yundong Tu, 2024, "Factors in Fashion: Factor Analysis towards the Mode," Papers, arXiv.org, number 2409.19287, Sep.
- Castiel Chen Zhuang, 2024, "A Way to Synthetic Triple Difference," Papers, arXiv.org, number 2409.12353, Sep, revised Sep 2024.
- Francesco Fusari & Joe Marlow & Alessio Volpicella, 2024, "Estimation and Inference of the Forecast Error Variance Decomposition for Set-Identified SVARs," School of Economics Discussion Papers, School of Economics, University of Surrey, number 0424, Sep.
- Niklas Ahlgren & Alexander Back & Timo Terasvirta, 2024, "A new GARCH model with a deterministic time-varying intercept," Papers, arXiv.org, number 2410.03239, Oct, revised Oct 2024.
- Leona Han Chen & Yijie Fei & Jun Yu, 2024, "Multivariate Stochastic Volatility Models based on Generalized Fisher Transformation," Working Papers, University of Macau, Faculty of Business Administration, number 202419, Oct.
- Jin Seo Cho & Peter C.B. Phillips, 2024, "GMM Estimation with Brownian Kernels Applied to Income Inequality Measurement," Working papers, Yonsei University, Yonsei Economics Research Institute, number 2024rwp-232, Oct.
- Yoann Morin, 2024, "Synthetic Difference in Differences for Repeated Cross-Sectional Data," Papers, arXiv.org, number 2409.20199, Sep.
- Roberto Fuentes-Mart'inez & Irene Crimaldi & Armando Rungi, 2024, "Non-linear dependence and Granger causality: A vine copula approach," Papers, arXiv.org, number 2409.15070, Sep, revised May 2025.
- Mathur, Maya B & Shpitser, Ilya & VanderWeele, Tyler J., 2024, "Resurrecting complete-case analysis: A defense," OSF Preprints, Center for Open Science, number f9jvz, Sep, DOI: 10.31219/osf.io/f9jvz.
- Yinhao Wu & Ping He, 2024, "The continuous-time limit of quasi score-driven volatility models," Papers, arXiv.org, number 2409.14734, Sep, revised Jun 2025.
- Lin-Tung Tsai, 2024, "Difference-in-Differences with Multiple Events," Papers, arXiv.org, number 2409.05184, Sep, revised Jan 2025.
- Vedant Vohra, 2024, "Inference for the Marginal Value of Public Funds," Papers, arXiv.org, number 2410.00217, Sep, revised Oct 2025.
- Sukjin Han, 2024, "Mining Causality: AI-Assisted Search for Instrumental Variables," Papers, arXiv.org, number 2409.14202, Sep, revised Jun 2025.
- Ren, Chunhui & Allison, Paul, 2024, "Time-Invariant Variables’ Time-Varying Effects: Misinterpretations of the Fixed-Effects Model in Sociological Research," OSF Preprints, Center for Open Science, number t6ndu, Sep, DOI: 10.31219/osf.io/t6ndu.
- Joshua C. C. Chan & Yaling Qi, 2024, "Large Bayesian Tensor VARs with Stochastic Volatility," Papers, arXiv.org, number 2409.16132, Sep.
- Xiaosai Liao & Xinjue Li & Qingliang Fan, 2024, "Robust Bond Risk Premia Predictability Test in the Quantiles," Papers, arXiv.org, number 2410.03557, Sep.
- Niccolo Lomys & Lorenzo Magnolfi, 2024, "Estimation of Games under No Regret: Structural Econometrics for AI," Working Papers, NET Institute, number 24-05, Sep, revised Nov 2024.
- Tobias Fissler & Yannick Hoga, 2024, "How to Compare Copula Forecasts?," Papers, arXiv.org, number 2410.04165, Oct.
- Luca Margaritella & Ovidijus Stauskas, 2024, "New Tests of Equal Forecast Accuracy for Factor-Augmented Regressions with Weaker Loadings," Papers, arXiv.org, number 2409.20415, Sep, revised Nov 2025.
- Buczak, Philip, 2024, "Mixed-Effects Frequency-Adjusted Borders Ordinal Forest: A Tree Ensemble Method for Ordinal Prediction with Hierarchical Data," OSF Preprints, Center for Open Science, number ny6we, Oct, DOI: 10.31219/osf.io/ny6we.
- Zeda Xu & John Liechty & Sebastian Benthall & Nicholas Skar-Gislinge & Christopher McComb, 2024, "GARCH-Informed Neural Networks for Volatility Prediction in Financial Markets," Papers, arXiv.org, number 2410.00288, Sep.