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Report NEP-ECM-2021-12-13
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:
- Dimitris Korobilis & Kenichi Shimizu, 2021, "Bayesian Approaches to Shrinkage and Sparse Estimation," Working Papers, Business School - Economics, University of Glasgow, number 2021_19, Nov.
- Greg Lewis & Bora Ozaltun & Georgios Zervas, 2021, "Maximum Likelihood Estimation of Differentiated Products Demand Systems," Papers, arXiv.org, number 2111.12397, Nov.
- Jin Seo Cho & Meng Huang & Halbert White, 2021, "Testing a Constant Mean Function Using Functional Regression," Working papers, Yonsei University, Yonsei Economics Research Institute, number 2021rwp-190, Dec.
- Albert J. Menkveld & Anna Dreber & Felix Holzmeister & Juergen Huber & Magnus Johannesson & Michael Kirchler & Sebastian Neussüs & Michael Razen & Utz Weitzel & Christian T. Brownlees & Javier Gil-Baz, 2021, "Non-standard errors," Economics Working Papers, Department of Economics and Business, Universitat Pompeu Fabra, number 1807, Dec.
- Vishwajit Hegde & Arvind S. Menon & L. A. Prashanth & Krishna Jagannathan, 2021, "Online Estimation and Optimization of Utility-Based Shortfall Risk," Papers, arXiv.org, number 2111.08805, Nov, revised Nov 2023.
- Bin Peng & Liangjun Su & Joakim Westerlund & Yanrong Yang, 2021, "Interactive Effects Panel Data Models with General Factors and Regressors," Papers, arXiv.org, number 2111.11506, Nov.
- Narayanan, Sridhar & Kalyanam, Kirthi, 2021, "Machine Learning, Behavioral Targeting and Regression Discontinuity Designs," Research Papers, Stanford University, Graduate School of Business, number 3992, Oct.
- Michael J. Bohm & Hans-Martin von Gaudecker, 2021, "The Performance of Recent Methods for Estimating Skill Prices in Panel Data," Papers, arXiv.org, number 2111.12459, Nov.
- Evan K. Rose & Yotam Shem-Tov, 2021, "On Recoding Ordered Treatments as Binary Indicators," Papers, arXiv.org, number 2111.12258, Nov, revised Mar 2024.
- Taras Bodnar & Nestor Parolya & Erik Thors'en, 2021, "Is the empirical out-of-sample variance an informative risk measure for the high-dimensional portfolios?," Papers, arXiv.org, number 2111.12532, Nov.
- Chao Zhang & Zihao Zhang & Mihai Cucuringu & Stefan Zohren, 2021, "A Universal End-to-End Approach to Portfolio Optimization via Deep Learning," Papers, arXiv.org, number 2111.09170, Nov.
- Hui Chen & Antoine Didisheim & Simon Scheidegger, 2021, "Deep Structural Estimation:With an Application to Option Pricing," Cahiers de Recherches Economiques du Département d'économie, Université de Lausanne, Faculté des HEC, Département d’économie, number 21.14, Feb.
- Jiarui Chu & Ludovic Tangpi, 2021, "Non-asymptotic estimation of risk measures using stochastic gradient Langevin dynamics," Papers, arXiv.org, number 2111.12248, Nov, revised Feb 2023.
- Heng Z. Chen & Stephen R. Cosslett, 2021, "Semi-nonparametric Estimation of Operational Risk Capital with Extreme Loss Events," Papers, arXiv.org, number 2111.11459, Nov, revised Jul 2022.
- Krishnamurthy, Sanath Kumar & Athey, Susan, 2021, "Optimal Model Selection in Contextual Bandits with Many Classes via Offline Oracles," Research Papers, Stanford University, Graduate School of Business, number 3971, Jun.