Printed from https://ideas.repec.org/n/nep-ets/2020-03-23.html
Report NEP-ETS-2020-03-23
This is the archive for NEP-ETS, a report on new working papers in the area of Econometric Time Series. Yong Yin issued this report. It is usually issued weekly.Subscribe to this report: email, RSS, or Mastodon, or Bluesky.
Other reports in NEP-ETS
The following items were announced in this report:
- Oksana Bashchenko & Alexis Marchal, 2020, "Deep Learning, Jumps, and Volatility Bursts," Swiss Finance Institute Research Paper Series, Swiss Finance Institute, number 20-10, Mar.
- Kung-Sik Chan & Simone Giannerini & Greta Goracci & Howell Tong, 2020, "Testing for threshold regulation in presence of measurement error with an application to the PPP hypothesis," Papers, arXiv.org, number 2002.09968, Feb, revised Nov 2021.
- Andree,Bo Pieter Johannes & Spencer,Phoebe Girouard & Azari,Sardar & Chamorro,Andres & Wang,Dieter & Dogo,Harun, 2019, "Pollution and Expenditures in a Penalized Vector Spatial Autoregressive Time Series Model with Data-Driven Networks," Policy Research Working Paper Series, The World Bank, number 8757, Feb.
- Firmin Doko Tchatoka & Qazi Haque, 2020, "On bootstrapping tests of equal forecast accuracy for nested models," School of Economics and Public Policy Working Papers, University of Adelaide, School of Economics and Public Policy, number 2020-03, Feb.
- Michael W. McCracken & Serena Ng, 2020, "FRED-QD: A Quarterly Database for Macroeconomic Research," Working Papers, Federal Reserve Bank of St. Louis, number 2020-005, Mar, DOI: 10.20955/wp.2020.005.
- Jarek Duda, 2020, "Adaptive exponential power distribution with moving estimator for nonstationary time series," Papers, arXiv.org, number 2003.02149, Mar, revised Mar 2020.
- Manav Kaushik & A K Giri, 2020, "Forecasting Foreign Exchange Rate: A Multivariate Comparative Analysis between Traditional Econometric, Contemporary Machine Learning & Deep Learning Techniques," Papers, arXiv.org, number 2002.10247, Feb.
- Savi Virolainen, 2020, "A mixture autoregressive model based on Gaussian and Student's $t$-distributions," Papers, arXiv.org, number 2003.05221, Mar, revised May 2020.
- Michael D. Cai & Marco Del Negro & Edward P. Herbst & Ethan Matlin & Reca Sarfati & Frank Schorfheide, 2020, "Online Estimation of DSGE Models," NBER Working Papers, National Bureau of Economic Research, Inc, number 26826, Mar.
- Sven Otto & Jorg Breitung, 2020, "Backward CUSUM for Testing and Monitoring Structural Change with an Application to COVID-19 Pandemic Data," Papers, arXiv.org, number 2003.02682, Mar, revised Mar 2022.
- Yoshimasa Uematsu & Takashi Yamagata, 2019, "Estimation of Weak Factor Models," ISER Discussion Paper, Institute of Social and Economic Research, The University of Osaka, number 1053r, Apr, revised Mar 2020.
- Florian Huber & Gary Koop & Michael Pfarrhofer, 2020, "Bayesian Inference in High-Dimensional Time-varying Parameter Models using Integrated Rotated Gaussian Approximations," Papers, arXiv.org, number 2002.10274, Feb.