Report NEP-ECM-2024-01-01

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:

• Bo Zhang & Jiti Gao & Guangming Pan & Yanrong Yang, 2023. "Eigen-Analysis for High-Dimensional Time Series Clustering," Monash Econometrics and Business Statistics Working Papers 22/23, Monash University, Department of Econometrics and Business Statistics.
• Timo Dimitriadis & Yannick Hoga, 2023. "Regressions under Adverse Conditions," Papers 2311.13327, arXiv.org, revised Jul 2024.
• Hong, Y. & Linton, O. B. & McCabe, B. & Sun, J. & Wang, S., 2023. "Kolmogorov-Smirnov Type Testing for Structural Breaks: A New Adjusted-Range Based Self-Normalization Approach," Cambridge Working Papers in Economics 2367, Faculty of Economics, University of Cambridge.
• Dmitry Arkhangelsky & David Hirshberg, 2023. "Large-Sample Properties of the Synthetic Control Method under Selection on Unobservables," Papers 2311.13575, arXiv.org, revised Dec 2023.
• Hajivassiliou, Vassilis & Savignac, Frédérique, 2024. "Simultaneously incomplete and incoherent (SII) dynamic LDV models: with an application to financing constraints and firms’ decision to innovate," LSE Research Online Documents on Economics 119379, London School of Economics and Political Science, LSE Library.
• Guglielmo Maria Caporale & Luis Alberiko Gil-Alana, 2023. "Exponential Time Trends in a Fractional Integration Model," CESifo Working Paper Series 10774, CESifo.
• Sid Kankanala, 2023. "Quasi-Bayes in Latent Variable Models," Papers 2311.06831, arXiv.org, revised Jan 2025.
• Chaya Weerasinghe & Ruben Loaiza-Maya & Gael M. Martin & David T. Frazier, 2023. "ABC-based Forecasting in State Space Models," Monash Econometrics and Business Statistics Working Papers 12/23, Monash University, Department of Econometrics and Business Statistics.
• James J. Heckman & Rodrigo Pinto, 2023. "Econometric Causality: The Central Role of Thought Experiments," Working Papers 2023-029, Human Capital and Economic Opportunity Working Group.
• Elias Tsakas, 2023. "Belief identification by proxy," Papers 2311.13394, arXiv.org.
• Nikhil Agarwal & Pearl Z. Li & Paulo J. Somaini, 2023. "Identification using Revealed Preferences in Linearly Separable Models," NBER Working Papers 31868, National Bureau of Economic Research, Inc.
• Kan, Raymond & Lassance, Nathan & Wang, Xiaolu, 2023. "The distribution of sample mean-variance portfolio weights," LIDAM Discussion Papers LFIN 2023006, Université catholique de Louvain, Louvain Finance (LFIN).
• Eli Ben-Michael & Avi Feller & Liyang Sun, 2023. "Using multiple outcomes to improve the synthetic control method," CeMMAP working papers 24/23, Institute for Fiscal Studies.
• Finn Christensen, 2023. "Comparative Statics for Difference-in-Differences," Working Papers 2023-08, Towson University, Department of Economics, revised Nov 2023.
• Seth M. Freedman & Alex Hollingsworth & Kosali I. Simon & Coady Wing & Madeline Yozwiak, 2023. "Designing Difference in Difference Studies With Staggered Treatment Adoption: Key Concepts and Practical Guidelines," NBER Working Papers 31842, National Bureau of Economic Research, Inc.
• David S. Lee & Justin McCrary & Marcelo J. Moreira & Jack R. Porter & Luther Yap, 2023. "What to do when you can't use '1.96' Confidence Intervals for IV," NBER Working Papers 31893, National Bureau of Economic Research, Inc.
• Stéphane Crépey & Noufel Frikha & Azar Louzi & Gilles Pagès, 2023. "Asymptotic Error Analysis of Multilevel Stochastic Approximations for the Value-at-Risk and Expected Shortfall," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-04304985, HAL.
• Alexandre Bonnet R. Costa & Pedro Cavalcanti G. Ferreira & Wagner Piazza Gaglianone & Osmani Teixeira C. Guillén & João Victor Issler & Artur Brasil Fialho Rodrigues, 2023. "Predicting Recessions in (almost) Real Time in a Big-data Setting," Working Papers Series 587, Central Bank of Brazil, Research Department.