Report NEP-ECM-2025-03-17

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:

• Blaise Melly & Martina Pons, 2025. "Minimum Distance Estimation of Quantile Panel Data Models," Papers 2502.18242, arXiv.org.
• Tomohiro Ando & Jushan Bai & Kunpeng Li & Yong Song, 2025. "Bayesian inference for dynamic spatial quantile models with interactive effects," Papers 2503.00772, arXiv.org.
• Javier Viviens, 2025. "Difference-in-Differences and Changes-in-Changes with Sample Selection," Papers 2502.08614, arXiv.org.
• Kosuke Imai & Michael Lingzhi Li, 2025. "Comment on "Generic machine learning inference on heterogeneous treatment effects in randomized experiments."," Papers 2502.06758, arXiv.org.
• Hoffmann, Nathan Isaac, 2023. "Double Robust, Flexible Adjustment Methods for Causal Inference: An Overview and an Evaluation," SocArXiv dzayg_v1, Center for Open Science.
• Claudia Pigini & Alessandro Pionati & Francesco Valentini, 2025. "Grouped fixed effects regularization for binary choice models," Papers 2502.06446, arXiv.org.
• Richard Gerlach & Antonio Naimoli & Giuseppe Storti, 2025. "Using quantile time series and historical simulation to forecast financial risk multiple steps ahead," Papers 2502.20978, arXiv.org, revised Mar 2025.
• Keunwoo Lim & Ting Ye & Fang Han, 2025. "A sliced Wasserstein and diffusion approach to random coefficient models," Papers 2502.04654, arXiv.org.
• Yu Fu & Michael Stanley Smith & Anastasios Panagiotelis, 2025. "Vector Copula Variational Inference and Dependent Block Posterior Approximations," Papers 2503.01072, arXiv.org.
• Yuan Liao & Xinjie Ma & Andreas Neuhierl & Linda Schilling, 2025. "The Uncertainty of Machine Learning Predictions in Asset Pricing," Papers 2503.00549, arXiv.org.
• Angelo Milfont & Alvaro Veiga, 2025. "Structural breaks detection and variable selection in dynamic linear regression via the Iterative Fused LASSO in high dimension," Papers 2502.20816, arXiv.org, revised Apr 2025.
• Yanhao & Wei & Zhenling Jiang, 2025. "Estimating Parameters of Structural Models Using Neural Networks," Papers 2502.04945, arXiv.org.
• Hossein Hassani & Leila Marvian Mashhad & Manuela Royer-Carenzi & Mohammad Reza Yeganegi & Nadejda Komendantova, 2025. "White Noise and Its Misapplications: Impacts on Time Series Model Adequacy and Forecasting," Post-Print hal-04937317, HAL.
• Michael Pfarrhofer & Anna Stelzer, 2025. "Scenario Analysis with Multivariate Bayesian Machine Learning Models," Papers 2502.08440, arXiv.org, revised Mar 2025.
• Yuya Sasaki, 2025. "Uniform Limit Theory for Network Data," Papers 2503.00290, arXiv.org.
• Corral Rodas,Paul Andres & Henderson,Heath Linn & Segovia Juarez,Sandra Carolina, 2023. "Poverty Mapping in the Age of Machine Learning," Policy Research Working Paper Series 10429, The World Bank.
• Xiangdong Liu & Sicheng Fu & Shaopeng Hong, 2025. "Forecasting realized volatility in the stock market: a path-dependent perspective," Papers 2503.00851, arXiv.org.
• Chen Tong & Peter Reinhard Hansen, 2025. "Dynamic Factor Correlation Model," Papers 2503.01080, arXiv.org.
• Carollo, Angela & Putter, Hein & Eilers, Paul H. C. & Gampe, Jutta, 2023. "Event history analysis with two time scales. An application to transitions out of cohabitation," SocArXiv 4ewv3_v1, Center for Open Science.
• Yitong Duan & Weiran Wang & Jian Li, 2025. "FactorGCL: A Hypergraph-Based Factor Model with Temporal Residual Contrastive Learning for Stock Returns Prediction," Papers 2502.05218, arXiv.org.