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Report NEP-ECM-2020-11-23
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:
- Martin Bruns & Helmut Luetkepohl, 2020, "An Alternative Bootstrap for Proxy Vector Autoregressions," University of East Anglia School of Economics Working Paper Series, School of Economics, University of East Anglia, Norwich, UK., number 2020-06, Nov.
- Grigory Franguridi & Bulat Gafarov & Kaspar Wuthrich, 2020, "Bias correction for quantile regression estimators," Papers, arXiv.org, number 2011.03073, Nov, revised Feb 2025.
- Hartwig, Benny, 2020, "Robust Inference in Time-Varying Structural VAR Models: The DC-Cholesky Multivariate Stochastic Volatility Model," VfS Annual Conference 2020 (Virtual Conference): Gender Economics, Verein für Socialpolitik / German Economic Association, number 224528.
- Niko Hauzenberger & Michael Pfarrhofer & Luca Rossini, 2020, "Sparse time-varying parameter VECMs with an application to modeling electricity prices," Papers, arXiv.org, number 2011.04577, Nov, revised Apr 2023.
- Mikkel Plagborg-M{o}ller & Christian K. Wolf, 2020, "Instrumental Variable Identification of Dynamic Variance Decompositions," Papers, arXiv.org, number 2011.01380, Nov, revised Jul 2021.
- Alyssa Carlson, 2020, "Relaxing Conditional Independence in an Endogenous Binary Response Model," Working Papers, Department of Economics, University of Missouri, number 2008, Sep.
- Blaise Melly & Rafael Lalive, 2020, "Estimation, Inference, and Interpretation in the Regression Discontinuity Design," Diskussionsschriften, Universitaet Bern, Departement Volkswirtschaft, number dp2016, Nov.
- Jianqing Fan & Ricardo P. Masini & Marcelo C. Medeiros, 2020, "Do We Exploit all Information for Counterfactual Analysis? Benefits of Factor Models and Idiosyncratic Correction," Papers, arXiv.org, number 2011.03996, Nov, revised Jan 2022.
- Kugler, Philipp & Biewen, Martin, 2020, "Two-Stage Least Squares Random Forests with a Replication of Angrist and Evans (1998)," VfS Annual Conference 2020 (Virtual Conference): Gender Economics, Verein für Socialpolitik / German Economic Association, number 224538.
- Brian Quistorff & Gentry Johnson, 2020, "Machine Learning for Experimental Design: Methods for Improved Blocking," Papers, arXiv.org, number 2010.15966, Oct.
- Hiroyuki Kasahara & Yoichi Sugita, 2020, "Nonparametric Identification of Production Function, Total Factor Productivity, and Markup from Revenue Data," CESifo Working Paper Series, CESifo, number 8667.
- Dietmar Pfeifer & Olena Ragulina, 2020, "Adaptive Bernstein Copulas and Risk Management," Papers, arXiv.org, number 2011.00909, Nov, revised Mar 2021.
- Michael Pollmann, 2020, "Causal Inference for Spatial Treatments," Papers, arXiv.org, number 2011.00373, Oct, revised Jan 2023.
- Lingxiao Huang & K. Sudhir & Nisheeth K. Vishnoi, 2020, "Coresets for Regressions with Panel Data," Papers, arXiv.org, number 2011.00981, Nov, revised Nov 2020.
- Uanhoro, James Ohisei, 2020, "Parameterizing structural equation models as Bayesian multilevel regression models: An example with the Global Multidimensional Poverty Index," OSF Preprints, Center for Open Science, number yrd34, Nov, DOI: 10.31219/osf.io/yrd34.
- Vincenzo Candila & Giampiero M. Gallo & Lea Petrella, 2020, "Mixed--frequency quantile regressions to forecast Value--at--Risk and Expected Shortfall," Papers, arXiv.org, number 2011.00552, Nov, revised Mar 2023.