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Report NEP-ETS-2020-02-17
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:
- Franses, Ph.H.B.F., 2019, "Estimating persistence for irregularly spaced historical data," Econometric Institute Research Papers, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute, number EI2020-03, Sep.
- Katsuya Ito & Kei Nakagawa, 2020, "NAPLES;Mining the lead-lag Relationship from Non-synchronous and High-frequency Data," Papers, arXiv.org, number 2002.00724, Feb.
- Mahmut Gunay, 2020, "Nowcasting Turkish GDP with MIDAS: Role of Functional Form of the Lag Polynomial," Working Papers, Research and Monetary Policy Department, Central Bank of the Republic of Turkey, number 2002.
- Mohitosh Kejriwal & Xuewen Yu, 2019, "Generalized Forecasr Averaging in Autoregressions with a Near Unit Root," Purdue University Economics Working Papers, Purdue University, Department of Economics, number 1318, Dec.
- Ruijun Bu & Kaddour Hadri & Dennis Kristensen, 2018, "Diffusion Copulas: Identification and Estimation," Working Papers, University of Liverpool, Department of Economics, number 20184, Jul.
- Yao Rao & Brendan McCabe, 2018, "Structural Change and the Problem of Phantom Break Locations," Working Papers, University of Liverpool, Department of Economics, number 20185, Nov.
- Christian Pinshi, 2020, "Rethinking error correction model in macroeconometric analysis : A relevant review," Working Papers, HAL, number hal-02454971, Jan.
- Amit Tewari, 2020, "Forecasting NIFTY 50 benchmark Index using Seasonal ARIMA time series models," Papers, arXiv.org, number 2001.08979, Jan.
- Blazejowski, Marcin & Kwiatkowski, Jacek, 2020, "Bayesian Model Averaging for Autoregressive Distributed Lag (BMA_ADL) in gretl," MPRA Paper, University Library of Munich, Germany, number 98387, Jan.