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Report NEP-ECM-2021-06-21
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:
- Sokbae Lee & Yuan Liao & Myung Hwan Seo & Youngki Shin, 2021, "Fast and Robust Online Inference with Stochastic Gradient Descent via Random Scaling," Papers, arXiv.org, number 2106.03156, Jun, revised Oct 2021.
- Taras Bodnar & Nestor Parolya & Erik Thorsen, 2021, "Dynamic Shrinkage Estimation of the High-Dimensional Minimum-Variance Portfolio," Papers, arXiv.org, number 2106.02131, Jun, revised Nov 2021.
- Andreï Kostyrka & Dmitry Igorevich Malakhov,, 2021, "The good, the bad, and the asymmetric: Evidence from a new conditional density model," DEM Discussion Paper Series, Department of Economics at the University of Luxembourg, number 21-09.
- Yu-Chin Hsu & Martin Huber & Ying-Ying Lee & Chu-An Liu, 2021, "Testing Monotonicity of Mean Potential Outcomes in a Continuous Treatment with High-Dimensional Data," Papers, arXiv.org, number 2106.04237, Jun, revised Aug 2022.
- Paul Goldsmith-Pinkham & Peter Hull & Michal Koles'ar, 2021, "Contamination Bias in Linear Regressions," Papers, arXiv.org, number 2106.05024, Jun, revised Jun 2024.
- Vivek F. Farias & Andrew A. Li & Tianyi Peng, 2021, "Learning Treatment Effects in Panels with General Intervention Patterns," Papers, arXiv.org, number 2106.02780, Jun, revised Mar 2023.
- Breen, Richard & Ermisch, John, 2021, "Instrumental Variable Estimation in Demographic Studies: The LATE interpretation of the IV estimator with heterogenous effects," SocArXiv, Center for Open Science, number vx9m7, Jun, DOI: 10.31219/osf.io/vx9m7.
- Christophe Gaillac & Eric Gautier, 2021, "Nonparametric classes for identification in random coefficients models when regressors have limited variation," Working Papers, HAL, number hal-03231392, May.
- Alessandro Casini & Pierre Perron, 2021, "Change-Point Analysis of Time Series with Evolutionary Spectra," Papers, arXiv.org, number 2106.02031, Jun, revised Aug 2024.
- Zhang, Han, 2021, "How Using Machine Learning Classification as a Variable in Regression Leads to Attenuation Bias and What to Do About It," SocArXiv, Center for Open Science, number 453jk, May, DOI: 10.31219/osf.io/453jk.
- Javed, Farrukh & Mazur, Stepan & Thorsén, Erik, 2021, "Tangency portfolio weights under a skew-normal model in small and large dimensions," Working Papers, Örebro University, School of Business, number 2021:13, Jun.
- Knut Are Aastveit & Jamie Cross & Herman K. van Dijk, 2021, "Quantifying time-varying forecast uncertainty and risk for the real price of oil," Tinbergen Institute Discussion Papers, Tinbergen Institute, number 21-053/III, Jun.
- Jason Poulos & Andrea Albanese & Andrea Mercatanti & Fan Li, 2021, "Retrospective causal inference via matrix completion, with an evaluation of the effect of European integration on cross-border employment," Papers, arXiv.org, number 2106.00788, Jun.
- Shosei Sakaguchi, 2021, "Estimation of Optimal Dynamic Treatment Assignment Rules under Policy Constraints," Papers, arXiv.org, number 2106.05031, Jun, revised Aug 2024.
- Victor Chernozhukov & Whitney K. Newey & Rahul Singh, 2021, "A Simple and General Debiased Machine Learning Theorem with Finite Sample Guarantees," Papers, arXiv.org, number 2105.15197, May, revised Oct 2022.
- Andrew Chia, 2021, "Automatically Differentiable Random Coefficient Logistic Demand Estimation," Papers, arXiv.org, number 2106.04636, Jun.
- Eli Ben-Michael & Avi Feller & Jesse Rothstein, 2021, "Synthetic Controls with Staggered Adoption," NBER Working Papers, National Bureau of Economic Research, Inc, number 28886, Jun.
- Schneider, Eric, 2020, "Collider Bias in Economic History Research," CEPR Discussion Papers, C.E.P.R. Discussion Papers, number 14940, Jun.
- Ruijun Bu & Rodrigo Hizmeri & Marwan Izzeldin & Anthony Murphy & Mike G. Tsionas, 2021, "The Contribution of Jump Signs and Activity to Forecasting Stock Price Volatility," Working Papers, University of Liverpool, Department of Economics, number 202109.
- Luisa Corrado & Stefano Grassi & Aldo Paolillo, 2021, "Modelling and Estimating Large Macroeconomic Shocks During the Pandemic," CREATES Research Papers, Department of Economics and Business Economics, Aarhus University, number 2021-08, Jun.