Report NEP-ECM-2024-07-15

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:

• James G. MacKinnon & Morten {O}rregaard Nielsen & Matthew D. Webb, 2024. "Jackknife inference with two-way clustering," Papers 2406.08880, arXiv.org.
• Kensuke Sakamoto, 2024. "Dyadic Regression with Sample Selection," Papers 2405.17787, arXiv.org, revised Jul 2024.
• Pedro Picchetti & Cristine C. X. Pinto & Stephanie T. Shinoki, 2024. "Difference-in-Discontinuities: Estimation, Inference and Validity Tests," Papers 2405.18531, arXiv.org.
• Federico A. Bugni & Mengsi Gao & Filip Obradovic & Amilcar Velez, 2024. "Identification and Inference on Treatment Effects under Covariate-Adaptive Randomization and Imperfect Compliance," Papers 2406.08419, arXiv.org, revised Jun 2024.
• Bin Peng & Liangjun Su & Yayi Yan, 2024. "A Robust Residual-Based Test for Structural Changes in Factor Models," Papers 2406.00941, arXiv.org.
• Tadao Hoshino & Takahide Yanagi, 2024. "Estimating Dyadic Treatment Effects with Unknown Confounders," Papers 2405.16547, arXiv.org.
• Francq, Christian & Zakoian, Jean-Michel, 2024. "Finite moments testing in a general class of nonlinear time series models," MPRA Paper 121193, University Library of Munich, Germany.
• Duarte Gonc{c}alves & Bruno A. Furtado, 2024. "Statistical Mechanism Design: Robust Pricing, Estimation, and Inference," Papers 2405.17178, arXiv.org.
• Chang, Jinyuan & Chen, Cheng & Qiao, Xinghao & Yao, Qiwei, 2023. "An autocovariance-based learning framework for high-dimensional functional time series," LSE Research Online Documents on Economics 117910, London School of Economics and Political Science, LSE Library.
• Sho Miyaji, 2024. "Two-way fixed effects instrumental variable regressions in staggered DID-IV designs," Papers 2405.16467, arXiv.org.
• Andrea Bucci, 2024. "A sequential test procedure for the choice of the number of regimes in multivariate nonlinear models," Papers 2406.02152, arXiv.org.
• James G. MacKinnon & Morten {O}rregaard Nielsen & Matthew D. Webb, 2024. "Cluster-robust jackknife and bootstrap inference for binary response models," Papers 2406.00650, arXiv.org.
• Bijan Mazaheri & Chandler Squires & Caroline Uhler, 2024. "Synthetic Potential Outcomes and Causal Mixture Identifiability," Papers 2405.19225, arXiv.org, revised Oct 2024.
• Johannes Hoelzemann & Ryan Webb & Erhao Xie, 2024. "Non-Parametric Identification and Testing of Quantal Response Equilibrium," Staff Working Papers 24-24, Bank of Canada.
• David Kohns & Noa Kallioinen & Yann McLatchie & Aki Vehtari, 2024. "The ARR2 prior: flexible predictive prior definition for Bayesian auto-regressions," Papers 2405.19920, arXiv.org, revised May 2024.
• Demian Pouzo & Zacharias Psaradakis & Martín Sola, 2024. "On the Robustness of Mixture Models in the Presence of Hidden Markov Regimes with Covariate-Dependent Transition Probabilities," Department of Economics Working Papers 2024_04, Universidad Torcuato Di Tella.
• Jin Seo Cho, 2024. "Estimating and Inferring the Nonlinear Autoregressive Distributed Lag Model by Ordinary Least Squares," Working papers 2024rwp-227, Yonsei University, Yonsei Economics Research Institute.
• Aristide Houndetoungan, 2024. "Count Data Models with Heterogeneous Peer Effects under Rational Expectations," Papers 2405.17290, arXiv.org.
• Xuxing Chen & Abhishek Roy & Yifan Hu & Krishnakumar Balasubramanian, 2024. "Stochastic Optimization Algorithms for Instrumental Variable Regression with Streaming Data," Papers 2405.19463, arXiv.org.
• Alessandra Amendola & Vincenzo Candila & Antonio Naimoli & Giuseppe Storti, 2024. "Adaptive combinations of tail-risk forecasts," Papers 2406.06235, arXiv.org.
• Ruoxuan Xiong & Alex Chin & Sean J. Taylor, 2024. "Data-Driven Switchback Experiments: Theoretical Tradeoffs and Empirical Bayes Designs," Papers 2406.06768, arXiv.org.
• Jay Lu & Yao Luo & Kota Saito & Yi Xin, 2024. "Did Harold Zuercher Have Time-Separable Preferences?," Papers 2406.07809, arXiv.org.
• Joshua Nielsen & Didier Sornette & Maziar Raissi, 2024. "Deep LPPLS: Forecasting of temporal critical points in natural, engineering and financial systems," Swiss Finance Institute Research Paper Series 24-33, Swiss Finance Institute.
• Enrico Wegner & Lenard Lieb & Stephan Smeekes & Ines Wilms, 2024. "Transmission Channel Analysis in Dynamic Models," Papers 2405.18987, arXiv.org, revised Jul 2024.
• Ippei Fujiwara & Adrian Pagan, 2024. "Re-Examining What We Can Learn About Counterfactual Results from Time Series Regression," CAMA Working Papers 2024-44, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• LeRoy, Stephen F, 2024. "Reconsidering Causation," University of California at Santa Barbara, Economics Working Paper Series qt12q3t2vd, Department of Economics, UC Santa Barbara.
• Dongwoo Kim & Young Jun Lee, 2024. "Semi-nonparametric models of multidimensional matching: an optimal transport approach," Papers 2405.18089, arXiv.org.
• Milen Arro-Cannarsa & Dr. Rolf Scheufele, 2024. "Nowcasting GDP: what are the gains from machine learning algorithms?," Working Papers 2024-06, Swiss National Bank.
• Pötscher, Benedikt M., 2024. "Comments on B. Hansen's Reply to "A Comment on: `A Modern Gauss-Markov Theorem'", and Some Related Discussion," MPRA Paper 121144, University Library of Munich, Germany.
• Askitas, Nikos, 2024. "A Hands-on Machine Learning Primer for Social Scientists: Math, Algorithms and Code," IZA Discussion Papers 17014, Institute of Labor Economics (IZA).