Report NEP-ECM-2021-09-06

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:

• Wenjie Wang & Yichong Zhang, 2021. "Wild Bootstrap for Instrumental Variables Regressions with Weak and Few Clusters," Papers 2108.13707, arXiv.org, revised Jan 2024.
• Kirill Borusyak & Xavier Jaravel & Jann Spiess, 2021. "Revisiting Event Study Designs: Robust and Efficient Estimation," Papers 2108.12419, arXiv.org, revised Jan 2024.
• James G. MacKinnon, 2021. "Fast cluster bootstrap methods for linear regression models," Working Paper 1465, Economics Department, Queen's University.
• Raffaella Giacomini & Toru Kitagawa & Matthew Read, 2021. "Robust Bayesian Analysis for Econometrics," Working Paper Series WP-2021-11, Federal Reserve Bank of Chicago.
• Honda, Toshio & 本田, 敏雄 & Lin, Chien-Tong, 2022. "Forward variable selection for ultra-high dimensional quantile regression models," Discussion Papers 2021-02, Graduate School of Economics, Hitotsubashi University.
• Stéphane Girard & Gilles Claude Stupfler & Antoine Usseglio-Carleve, 2021. "Extreme Conditional Expectile Estimation in Heavy-Tailed Heteroscedastic Regression Models," Post-Print hal-03306230, HAL.
• Hao Dong & Taisuke Otsu & Luke Taylor, 2021. "Bandwidth Selection for Nonparametric Regression with Errors-in-Variables," Departmental Working Papers 2104, Southern Methodist University, Department of Economics.
• François Gardes, 2021. "Biases on variances estimated on large data-sets," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-03325118, HAL.
• Juergen Deppner & Marcelo Cajias & Wolfgang Schäfers, 2021. "Accounting for Spatial Autocorrelation in Algorithm-Driven Hedonic Models: A Spatial Cross-Validation Approach," ERES eres2021_51, European Real Estate Society (ERES).
• Jin Li & Ye Luo & Xiaowei Zhang, 2021. "Dynamic Selection in Algorithmic Decision-making," Papers 2108.12547, arXiv.org, revised Sep 2023.
• Liu, Dungang & Li, Shaobo & Yu, Yan & Moustaki, Irini, 2020. "Assessing partial association between ordinal variables: quantification, visualization, and hypothesis testing," LSE Research Online Documents on Economics 105558, London School of Economics and Political Science, LSE Library.
• Rice, Gregory & Wirjanto, Tony & Zhao, Yuqian, 2021. "Exploring volatility of crude oil intra-day return curves: a functional GARCH-X Model," MPRA Paper 109231, University Library of Munich, Germany.
• Gordon John Anderson & Teng Wah Leo, 2021. "On Extending Stochastic Dominance Comparisons to Ordinal Variables and Generalising Hammond Dominance," Working Papers tecipa-705, University of Toronto, Department of Economics.
• Nguyen, Hoang & Javed, Farrukh, 2021. "Dynamic relationship between Stock and Bond returns: A GAS MIDAS copula approach," Working Papers 2021:15, Örebro University, School of Business.
• Lang, Megan & Qiu, Wenfeng, 2021. "Cherry Picking," MetaArXiv as9zd, Center for Open Science.
• Mani Bayani, 2021. "Robust PCA Synthetic Control," Papers 2108.12542, arXiv.org, revised Oct 2021.
• Andres, Antonio Rodriguez & Otero, Abraham & Amavilah, Voxi Heinrich, 2021. "Evaluation of technology clubs by clustering: A cautionary note," MPRA Paper 109138, University Library of Munich, Germany.
• Marcelo Cajias & Willwersch Jonas & Lorenz Felix & Franz Fuerst, 2021. "Peeking inside the Black Box: Interpretable Machine Learning and Hedonic Rental Estimation," ERES eres2021_104, European Real Estate Society (ERES).
• Lisa Crosato & Caterina Liberati & Marco Repetto, 2021. "Look Who's Talking: Interpretable Machine Learning for Assessing Italian SMEs Credit Default," Papers 2108.13914, arXiv.org, revised Sep 2021.