Report NEP-ECM-2022-05-09

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:

• Sid Kankanala & Victoria Zinde-Walsh, 2022. "Kernel-weighted specification testing under general distributions," Papers 2204.01683, arXiv.org, revised May 2023.
• Rub'en Loaiza-Maya & Didier Nibbering, 2022. "Fast variational Bayes methods for multinomial probit models," Papers 2202.12495, arXiv.org, revised Oct 2022.
• Lixiong Li & Marc Henry, 2022. "Finite Sample Inference in Incomplete Models," Papers 2204.00473, arXiv.org, revised Apr 2024.
• Fang, Qin & Guo, Shaojun & Qiao, Xinghao, 2022. "Finite sample theory for high-dimensional functional/scalar time series with applications," LSE Research Online Documents on Economics 114637, London School of Economics and Political Science, LSE Library.
• Martin Huber & Jannis Kueck, 2022. "Testing the identification of causal effects in observational data," Papers 2203.15890, arXiv.org, revised Jun 2023.
• Chen, Cheng & Guo, Shaojun & Qiao, Xinghao, 2022. "Functional linear regression: dependence and error contamination," LSE Research Online Documents on Economics 114636, London School of Economics and Political Science, LSE Library.
• Stefano Bertelli & Gianmarco Vacca & Maria Grazia Zoia, 2022. "Bootstrap Cointegration Tests in ARDL Models," Papers 2204.04939, arXiv.org.
• Karsten Reichold & Carsten Jentsch, 2022. "A Bootstrap-Assisted Self-Normalization Approach to Inference in Cointegrating Regressions," Papers 2204.01373, arXiv.org.
• William C. Horrace & Hyunseok Jung & Yoonseok Lee, 2022. "LASSO for Stochastic Frontier Models with Many Efficient Firms," Center for Policy Research Working Papers 248, Center for Policy Research, Maxwell School, Syracuse University.
• Mauro Bernardi & Daniele Bianchi & Nicolas Bianco, 2022. "Variational inference for large Bayesian vector autoregressions," Papers 2202.12644, arXiv.org, revised Jun 2023.
• Emmet Hall-Hoffarth, 2022. "Causal Discovery of Macroeconomic State-Space Models," Papers 2204.02374, arXiv.org.
• Kun Zhang & Ben Mingbin Feng & Guangwu Liu & Shiyu Wang, 2022. "Sample Recycling for Nested Simulation with Application in Portfolio Risk Measurement," Papers 2203.15929, arXiv.org.
• Manon Costa & Sébastien Gadat, 2021. "Non-asymptotic study of a recursive superquantile estimation algorithm," Post-Print hal-03610477, HAL.
• Rudy Morel & Gaspar Rochette & Roberto Leonarduzzi & Jean-Philippe Bouchaud & St'ephane Mallat, 2022. "Scale Dependencies and Self-Similar Models with Wavelet Scattering Spectra," Papers 2204.10177, arXiv.org, revised Jun 2023.
• Andrew Y. Chen, 2022. "Do t-Statistic Hurdles Need to be Raised?," Papers 2204.10275, arXiv.org, revised Apr 2024.
• Hamdi Raissi, 2022. "On the dependence structure of the trade/no trade sequence of illiquid assets," Papers 2203.08223, arXiv.org.
• Jozef Barunik & Lubos Hanus, 2022. "Learning Probability Distributions in Macroeconomics and Finance," Papers 2204.06848, arXiv.org.
• Julia Nasiadka & Weronika Nitka & Rafa{l} Weron, 2022. "Calibration window selection based on change-point detection for forecasting electricity prices," Papers 2204.00872, arXiv.org.
• Whitehouse, E. J. & Harvey, D. I. & Leybourne, S. J., 2022. "Real-time monitoring of bubbles and crashes," Working Papers 2022007, The University of Sheffield, Department of Economics.
• Yuki Oyama, 2022. "Capturing positive network attributes during the estimation of recursive logit models: A prism-based approach," Papers 2204.01215, arXiv.org, revised Jan 2023.
• Todd E. Clark & Florian Huber & Gary Koop & Massimiliano Marcellino, 2022. "Forecasting US Inflation Using Bayesian Nonparametric Models," Papers 2202.13793, arXiv.org.
• Hai-Anh Dang & Peter Lanjouw, 2022. "Regression-based Imputation for Poverty Measurement in Data Scarce Settings," Working Papers 611, ECINEQ, Society for the Study of Economic Inequality.