Report NEP-ECM-2023-02-13

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:

• Luo, Yu & Graham, Daniel J. & McCoy, Emma J., 2023. "Semiparametric Bayesian doubly robust causal estimation," LSE Research Online Documents on Economics 117944, London School of Economics and Political Science, LSE Library.
• Nicholas Brown & Jeffrey Wooldridge, 2023. "More Efficient Estimation of Multiplicative Panel Data Models in the Presence of Serial Correlation," Working Paper 1497, Economics Department, Queen's University.
• Zongwu Cai & Hongwei Mei & Rui Wang, 2023. "A Model Specification Test for Nonlinear Stochastic Diffusions with Delay," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202301, University of Kansas, Department of Economics, revised Jan 2023.
• Nicholas Brown & Kyle Butts & Joakim Westerlund, 2023. "Difference-in-Differences via Common Correlated Effects," Working Paper 1496, Economics Department, Queen's University.
• Markus Pelger & Jiacheng Zou, 2022. "Inference for Large Panel Data with Many Covariates," Papers 2301.00292, arXiv.org, revised Mar 2023.
• Luther Yap, 2023. "Asymptotic Theory for Two-Way Clustering," Papers 2301.03805, arXiv.org, revised Jun 2024.
• Haowen Bao & Zongwu Cai & Yuying Sun & Shouyang Wang, 2023. "Penalized Model Averaging for High Dimensional Quantile Regressions," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202302, University of Kansas, Department of Economics, revised Jan 2023.
• Apoorva Lal & Wenjing Zheng & Simon Ejdemyr, 2023. "A Framework for Generalization and Transportation of Causal Estimates Under Covariate Shift," Papers 2301.04776, arXiv.org.
• Denis Chetverikov & Elena Manresa, 2022. "Spectral and post-spectral estimators for grouped panel data models," Papers 2212.13324, arXiv.org, revised Dec 2022.
• Tadao Hoshino & Takahide Yanagi, 2023. "Randomization Test for the Specification of Interference Structure," Papers 2301.05580, arXiv.org, revised Dec 2023.
• Mate Kormos & Robert P. Lieli & Martin Huber, 2023. "Interacting Treatments with Endogenous Takeup," Papers 2301.04876, arXiv.org, revised Dec 2024.
• Zhang, Junyi & Dassios, Angelos, 2023. "Truncated Poisson-Dirichlet approximation for Dirichlet process hierarchical models," LSE Research Online Documents on Economics 117690, London School of Economics and Political Science, LSE Library.
• Watanabe, Toshiaki & Nakajima, Jouchi, 2023. "High-frequency realized stochastic volatility model," Discussion paper series HIAS-E-127, Hitotsubashi Institute for Advanced Study, Hitotsubashi University.
• Yi-Ting Chen & Chu-An Liu, 2021. "Model Averaging for Asymptotically Optimal Combined Forecasts," IEAS Working Paper : academic research 21-A002, Institute of Economics, Academia Sinica, Taipei, Taiwan.
• Sebastiano Michele Zema & Francesco Cordoni, 2023. "A non-Normal framework for price discovery: The independent component based information shares measure," LEM Papers Series 2023/03, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
• Crespo, Marelys & Gadat, Sébastien & Gendre, Xavier, 2023. "Stochastic Langevin Monte Carlo for (weakly) log-concave posterior distributions," TSE Working Papers 23-1398, Toulouse School of Economics (TSE).
• André de Palma & Karim Kilani, 2022. "Best, worst, and Best&worst choice probabilities for logit and reverse logit models," Working Papers hal-03913928, HAL.
• Maria Nareklishvili & Nicholas Polson & Vadim Sokolov, 2022. "Feature Selection for Personalized Policy Analysis," Papers 2301.00251, arXiv.org, revised Jul 2023.
• Michael Greenacre, 2023. "The chi-square standardization, combined with Box-Cox transformation, is a valid alternative to transforming to logratios in compositional data analysis," Economics Working Papers 1857, Department of Economics and Business, Universitat Pompeu Fabra.
• Farmer, J. Doyne & Dyer, Joel & Cannon, Patrick & Schmon, Sebastian, 2022. "Calibrating Agent-based Models to Microdata with Graph Neural Networks," INET Oxford Working Papers 2022-30, Institute for New Economic Thinking at the Oxford Martin School, University of Oxford.