Report NEP-ECM-2021-04-19

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:

• Shalini Sharma & Víctor Elvira & Emilie Chouzenoux & Angshul Majumdar, 2021. "Recurrent Dictionary Learning for State-Space Models with an Application in Stock Forecasting," Post-Print hal-03184841, HAL.
• Harvey, A., 2021. "Score-driven time series models," Cambridge Working Papers in Economics 2133, Faculty of Economics, University of Cambridge.
• Giovannini, Massimo & Pfeiffer, Philipp & Ratto, Marco, 2021. "Efficient and robust inference of models with occasionally binding constraints," JRC Working Papers in Economics and Finance 2021-03, Joint Research Centre, European Commission.
• Simar, Léopold & Wilson, Paul, 2021. "Nonparametric, Stochastic Frontier Models with Multiple Inputs and Outputs," LIDAM Discussion Papers ISBA 2021003, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
• Denis Chetverikov & Jesper Riis-Vestergaard S{o}rensen, 2021. "Selecting Penalty Parameters of High-Dimensional M-Estimators using Bootstrapping after Cross-Validation," Papers 2104.04716, arXiv.org, revised Nov 2024.
• Dieppe, Alistair & Francis, Neville & Kindberg-Hanlon, Gene, 2021. "The identification of dominant macroeconomic drivers: coping with confounding shocks," Working Paper Series 2534, European Central Bank.
• Christopher Dobronyi & Jiaying Gu & Kyoo il Kim, 2021. "Identification of Dynamic Panel Logit Models with Fixed Effects," Papers 2104.04590, arXiv.org, revised Apr 2021.
• Simon Freyaldenhoven, 2021. "Factor Models with Local Factors—Determining the Number of Relevant Factors," Working Papers 21-15, Federal Reserve Bank of Philadelphia.
• Geminiani, Elena & Marra, Giampiero & Moustaki, Irini, 2021. "Single and multiple-group penalized factor analysis: a trust-region algorithm approach with integrated automatic multiple tuning parameter selection," LSE Research Online Documents on Economics 108873, London School of Economics and Political Science, LSE Library.
• Xiao, Jiaqi & Juodis, Arturas & Karavias, Yiannis & Sarafidis, Vasilis, 2021. "Improved Tests for Granger Non-Causality in Panel Data," MPRA Paper 107180, University Library of Munich, Germany.
• Gorodnichenko, Yuriy & Lee, Byoungchan, 2020. "Forecast Error Variance Decompositions with Local Projections," Department of Economics, Working Paper Series qt8w31z6qx, Department of Economics, Institute for Business and Economic Research, UC Berkeley.
• Christian M. Dahl & Emil N. S{o}rensen, 2021. "Time Series (re)sampling using Generative Adversarial Networks," Papers 2102.00208, arXiv.org.
• Alfred Galichon & Bernard Salani'e, 2021. "The Econometrics and Some Properties of Separable Matching Models," Papers 2102.02564, arXiv.org.
• Gareth Liu-Evans, 2021. "Improving the Estimation and Predictions of Small Time Series Models," Working Papers 202106, University of Liverpool, Department of Economics.
• Andrea Giuseppe Di Iura & Giulia Terenzi, 2021. "A Bayesian analysis of gain-loss asymmetry," Papers 2104.06044, arXiv.org.
• Alfred Galichon, 2021. "A survey of some recent applications of optimal transport methods to econometrics," Papers 2102.01716, arXiv.org.
• Christopher Turansick, 2021. "Identification in the Random Utility Model," Papers 2102.05570, arXiv.org, revised May 2022.