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Report NEP-ECM-2020-11-02
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:
- Anine E. Bolko & Kim Christensen & Mikko S. Pakkanen & Bezirgen Veliyev, 2020, "Roughness in spot variance? A GMM approach for estimation of fractional log-normal stochastic volatility models using realized measures," CREATES Research Papers, Department of Economics and Business Economics, Aarhus University, number 2020-12, Oct.
- Don S. Poskitt, 2020, "On GMM Inference: Partial Identification, Identification Strength, and Non-Standard," Monash Econometrics and Business Statistics Working Papers, Monash University, Department of Econometrics and Business Statistics, number 40/20.
- Jad Beyhum & Eric Gautier, 2020, "Factor and factor loading augmented estimators for panel regression," Working Papers, HAL, number hal-02957008, Nov.
- Francisco Blasques & Christian Francq & SĂ©bastien Laurent, 2020, "A New Class of Robust Observation-Driven Models," Tinbergen Institute Discussion Papers, Tinbergen Institute, number 20-073/III, Oct.
- Marco Bee, 2020, "On discriminating between lognormal and Pareto tail: A mixture-based approach," DEM Working Papers, Department of Economics and Management, number 2020/9.
- Herwartz, Helmut & Rohloff, Hannes & Wang, Shu, 2020, "Proxy SVAR identification of monetary policy shocks: MonteCarlo evidence and insights for the US," University of Göttingen Working Papers in Economics, University of Goettingen, Department of Economics, number 404.
- Ruben Hipp, 2020, "On Causal Networks of Financial Firms: Structural Identification via Non-parametric Heteroskedasticity," Staff Working Papers, Bank of Canada, number 20-42, Oct, DOI: 10.34989/swp-2020-42.
- Masahiro Kato & Kenshi Abe & Kaito Ariu & Shota Yasui, 2020, "A Practical Guide of Off-Policy Evaluation for Bandit Problems," Papers, arXiv.org, number 2010.12470, Oct.
- Xing Yan & Weizhong Zhang & Lin Ma & Wei Liu & Qi Wu, 2020, "Parsimonious Quantile Regression of Financial Asset Tail Dynamics via Sequential Learning," Papers, arXiv.org, number 2010.08263, Oct.
- Andrii Babii & Xi Chen & Eric Ghysels & Rohit Kumar, 2020, "Binary Choice under Asymmetric Loss in a Data-Rich Environment: Theory and an Application to Algorithmic Fairness," Papers, arXiv.org, number 2010.08463, Oct, revised Nov 2025.
- Iv'an Fern'andez-Val & Hugo Freeman & Martin Weidner, 2020, "Low-Rank Approximations of Nonseparable Panel Models," Papers, arXiv.org, number 2010.12439, Oct, revised Mar 2021.
- Mengheng Li & Bowen Fu, 2020, "US Shocks and the Uncovered Interest Rate Parity," CAMA Working Papers, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University, number 2020-87, Oct.
- Andrew C. Harvey, 2020, "Time series models for epidemics: leading indicators, control groups and policy assessment," National Institute of Economic and Social Research (NIESR) Discussion Papers, National Institute of Economic and Social Research, number 517, Oct.
- Item repec:wrk:wrkemf:36 is not listed on IDEAS anymore
- Nosratabadi, Saeed & Mosavi, Amir & Duan, Puhong & Ghamisi, Pedram & Filip, Ferdinand & Band, Shahab S. & Reuter, Uwe & Gama, Joao & Gandomi, Amir H., 2020, "Data science in economics: comprehensive review of advanced machine learning and deep learning methods," LawRxiv, Center for Open Science, number kczj5, Oct, DOI: 10.31219/osf.io/kczj5.