Report NEP-ECM-2018-05-28

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.

Other reports in NEP-ECM

The following items were announced in this report:

• Fela ÖZBEY, 2018. "Evaluation Estimation Performances of Liu Type and Two-Parameter Ridge Estimators Using Monte Carlo Experiments," Proceedings of International Academic Conferences 7508770, International Institute of Social and Economic Sciences.
• Laura Liu, 2018. "Density Forecasts in Panel Data Models: A Semiparametric Bayesian Perspective," Papers 1805.04178, arXiv.org, revised Oct 2021.
• Audrone Virbickaite & Hedibert F. Lopes & Maria Concepción Ausín & Pedro Galeano, 2018. "Particle Learning for Bayesian Semi-Parametric Stochastic Volatility Model," DEA Working Papers 88, Universitat de les Illes Balears, Departament d'Economía Aplicada.
• Ryo Kato & Takahiro Hoshino, 2018. "Semiparametric Bayes Instrumental Variable Estimation with Many Weak Instruments," Discussion Paper Series DP2018-14, Research Institute for Economics & Business Administration, Kobe University.
• Cassim, Lucius, 2018. "Non-parametric Estimation of GARCH (2, 2) Volatility model: A new Algorithm," MPRA Paper 86861, University Library of Munich, Germany.
• Michael Zimmert, 2018. "The Finite Sample Performance of Treatment Effects Estimators based on the Lasso," Papers 1805.05067, arXiv.org.
• Schweikert, Karsten, 2018. "Testing for cointegration with threshold adjustment in the presence of structural breaks," Hohenheim Discussion Papers in Business, Economics and Social Sciences 07-2018, University of Hohenheim, Faculty of Business, Economics and Social Sciences.
• Farzad Sabzikar & Qiying Wang & Peter C.B. Phillips, 2018. "Asymptotic Theory for Near Integrated Process Driven by Tempered Linear Process," Cowles Foundation Discussion Papers 2131, Cowles Foundation for Research in Economics, Yale University.
• Viet Anh Nguyen & Daniel Kuhn & Peyman Mohajerin Esfahani, 2018. "Distributionally Robust Inverse Covariance Estimation: The Wasserstein Shrinkage Estimator," Papers 1805.07194, arXiv.org.
• Baumeister, Christiane & Hamilton, James, 2018. "Inference in Structural Vector Autoregressions When the Identifying Assumptions are Not Fully Believed: Re-evaluating the Role," CEPR Discussion Papers 12911, C.E.P.R. Discussion Papers.
• Jörg Schwiebert, 2018. "A Bivariate Fractional Probit Model," Working Paper Series in Economics 381, University of Lüneburg, Institute of Economics.
• Jason Poulos & Shuxi Zeng, 2017. "RNN-based counterfactual prediction, with an application to homestead policy and public schooling," Papers 1712.03553, arXiv.org, revised May 2021.
• Adams Vallejos & Ignacio Ormazabal & Felix A. Borotto & Hernan F. Astudillo, 2018. "A new $\kappa$-deformed parametric model for the size distribution of wealth," Papers 1805.06929, arXiv.org.
• Lettau, Martin & Pelger, Markus, 2018. "Estimating Latent Asset-Pricing Factors," CEPR Discussion Papers 12926, C.E.P.R. Discussion Papers.
• Shota Gugushvili & Frank van der Meulen & Moritz Schauer & Peter Spreij, 2018. "Nonparametric Bayesian volatility learning under microstructure noise," Papers 1805.05606, arXiv.org, revised Mar 2024.
• Becker, Janis & Leschinski, Christian, 2018. "Estimating the Volatility of Asset Pricing Factors," Hannover Economic Papers (HEP) dp-631, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.