Report NEP-ECM-2021-02-15

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.

Subscribe to this report: email, RSS, or Mastodon, or Bluesky.

Other reports in NEP-ECM

The following items were announced in this report:

• Umberto Triacca & Olivier Damette & Alessandro Giovannelli, 2020. "A Test of Sufficient Condition for Infinite-step Granger Noncausality in Infinite Order Vector Autoregressive Process," CEIS Research Paper 496, Tor Vergata University, CEIS, revised 18 Jun 2020.
• Denis Kojevnikov, 2021. "The Bootstrap for Network Dependent Processes," Papers 2101.12312, arXiv.org.
• Lea Bottmer & Guido Imbens & Jann Spiess & Merrill Warnick, 2021. "A Design-Based Perspective on Synthetic Control Methods," Papers 2101.09398, arXiv.org, revised Jul 2023.
• Dan M. Kluger & Art B. Owen, 2021. "Kernel regression analysis of tie-breaker designs," Papers 2101.09605, arXiv.org, revised Jan 2023.
• Aknouche, Abdelhakim & Dimitrakopoulos, Stefanos, 2020. "On an integer-valued stochastic intensity model for time series of counts," MPRA Paper 105406, University Library of Munich, Germany.
• Ines Wilms & Jacob Bien, 2021. "Tree-based Node Aggregation in Sparse Graphical Models," Papers 2101.12503, arXiv.org.
• Christoph Breunig & Xiaohong Chen, 2021. "Simple Adaptive Estimation of Quadratic Functionals in Nonparametric IV Models," Papers 2101.12282, arXiv.org, revised Feb 2022.
• Chen, Yunxiao & Moustaki, Irini & Zhang, H, 2020. "A note on likelihood ratio tests for models with latent variables," LSE Research Online Documents on Economics 107490, London School of Economics and Political Science, LSE Library.
• Max-Sebastian Dov`i, 2021. "Inference on the New Keynesian Phillips Curve with Very Many Instrumental Variables," Papers 2101.09543, arXiv.org, revised Mar 2021.
• Abhimanyu Gupta & Xi Qu, 2021. "Consistent specification testing under spatial dependence," Papers 2101.10255, arXiv.org, revised Aug 2022.
• Georges Sfeir & Filipe Rodrigues & Maya Abou-Zeid, 2021. "Gaussian Process Latent Class Choice Models," Papers 2101.12252, arXiv.org.
• Youssef M. Aboutaleb & Mazen Danaf & Yifei Xie & Moshe Ben-Akiva, 2021. "Discrete Choice Analysis with Machine Learning Capabilities," Papers 2101.10261, arXiv.org.
• Takaaki Koike & Shogo Kato & Marius Hofert, 2021. "Measuring non-exchangeable tail dependence using tail copulas," Papers 2101.12262, arXiv.org, revised Feb 2023.
• Matthew J. Colbrook & Zdravko I. Botev & Karsten Kuritz & Shev MacNamara, 2020. "Kernel Density Estimation with Linked Boundary Conditions," Research Paper Series 414, Quantitative Finance Research Centre, University of Technology, Sydney.
• Smith, Leonard A. & Du, Hailiang & Higgins, Sarah, 2020. "Designing multi-model applications with surrogate forecast systems," LSE Research Online Documents on Economics 103275, London School of Economics and Political Science, LSE Library.
• Tommaso Proietti & Alessandro Giovannelli, 2020. "Nowcasting Monthly GDP with Big Data: a Model Averaging Approach," CEIS Research Paper 482, Tor Vergata University, CEIS, revised 12 May 2020.
• Xiaodong Wang & Fushing Hsieh, 2021. "Unraveling S&P500 stock volatility and networks -- An encoding-and-decoding approach," Papers 2101.09395, arXiv.org, revised Oct 2021.
• Tommaso Proietti, 2020. "Peaks, Gaps, and Time Reversibility of Economic Time Series," CEIS Research Paper 492, Tor Vergata University, CEIS, revised 17 Jun 2020.
• Item repec:hal:wpaper:hal-01943883 is not listed on IDEAS anymore

• Carol Alexander & Michael Coulon & Yang Han & Xiaochun Meng, 2021. "Evaluating the Discrimination Ability of Proper Multivariate Scoring Rules," Papers 2101.12693, arXiv.org.