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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.Subscribe to this report: email, RSS, or Mastodon, or Bluesky.
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, arXiv.org, number 2204.01683, Apr, revised May 2023.
- Rub'en Loaiza-Maya & Didier Nibbering, 2022, "Fast variational Bayes methods for multinomial probit models," Papers, arXiv.org, number 2202.12495, Feb, revised Oct 2022.
- Lixiong Li & Marc Henry, 2022, "Finite Sample Inference in Incomplete Models," Papers, arXiv.org, number 2204.00473, Apr, revised Oct 2025.
- 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, London School of Economics and Political Science, LSE Library, number 114637, Jan.
- Martin Huber & Jannis Kueck, 2022, "Testing the identification of causal effects in observational data," Papers, arXiv.org, number 2203.15890, Mar, revised Jun 2023.
- Chen, Cheng & Guo, Shaojun & Qiao, Xinghao, 2022, "Functional linear regression: dependence and error contamination," LSE Research Online Documents on Economics, London School of Economics and Political Science, LSE Library, number 114636, Jan.
- Stefano Bertelli & Gianmarco Vacca & Maria Grazia Zoia, 2022, "Bootstrap Cointegration Tests in ARDL Models," Papers, arXiv.org, number 2204.04939, Apr.
- Karsten Reichold & Carsten Jentsch, 2022, "A Bootstrap-Assisted Self-Normalization Approach to Inference in Cointegrating Regressions," Papers, arXiv.org, number 2204.01373, Apr.
- William C. Horrace & Hyunseok Jung & Yoonseok Lee, 2022, "LASSO for Stochastic Frontier Models with Many Efficient Firms," Center for Policy Research Working Papers, Center for Policy Research, Maxwell School, Syracuse University, number 248, Mar.
- Mauro Bernardi & Daniele Bianchi & Nicolas Bianco, 2022, "Variational inference for large Bayesian vector autoregressions," Papers, arXiv.org, number 2202.12644, Feb, revised Jun 2023.
- Emmet Hall-Hoffarth, 2022, "Causal Discovery of Macroeconomic State-Space Models," Papers, arXiv.org, number 2204.02374, Apr.
- Kun Zhang & Ben Mingbin Feng & Guangwu Liu & Shiyu Wang, 2022, "Sample Recycling for Nested Simulation with Application in Portfolio Risk Measurement," Papers, arXiv.org, number 2203.15929, Mar.
- Item repec:hal:journl:hal-03610477 is not listed on IDEAS anymore
- Rudy Morel & Gaspar Rochette & Roberto Leonarduzzi & Jean-Philippe Bouchaud & St'ephane Mallat, 2022, "Scale Dependencies and Self-Similar Models with Wavelet Scattering Spectra," Papers, arXiv.org, number 2204.10177, Apr, revised Jun 2023.
- Andrew Y. Chen, 2022, "Do t-Statistic Hurdles Need to be Raised?," Papers, arXiv.org, number 2204.10275, Apr, revised Apr 2024.
- Hamdi Raissi, 2022, "On the dependence structure of the trade/no trade sequence of illiquid assets," Papers, arXiv.org, number 2203.08223, Feb.
- Jozef Barunik & Lubos Hanus, 2022, "Learning Probability Distributions in Macroeconomics and Finance," Papers, arXiv.org, number 2204.06848, Apr.
- Julia Nasiadka & Weronika Nitka & Rafa{l} Weron, 2022, "Calibration window selection based on change-point detection for forecasting electricity prices," Papers, arXiv.org, number 2204.00872, Apr.
- Whitehouse, E. J. & Harvey, D. I. & Leybourne, S. J., 2022, "Real-time monitoring of bubbles and crashes," Working Papers, The University of Sheffield, Department of Economics, number 2022007, Apr.
- Yuki Oyama, 2022, "Capturing positive network attributes during the estimation of recursive logit models: A prism-based approach," Papers, arXiv.org, number 2204.01215, Apr, revised Jan 2023.
- Todd E. Clark & Florian Huber & Gary Koop & Massimiliano Marcellino, 2022, "Forecasting US Inflation Using Bayesian Nonparametric Models," Papers, arXiv.org, number 2202.13793, Feb.
- Hai-Anh Dang & Peter Lanjouw, 2022, "Regression-based Imputation for Poverty Measurement in Data Scarce Settings," Working Papers, ECINEQ, Society for the Study of Economic Inequality, number 611, Apr.