Report NEP-ETS-2001-05-02

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.

Other reports in NEP-ETS

The following items were announced in this report:

• Marcelo Cunha Medeiros & Álvaro Veiga & Carlos Eduardo Pedreira, 2000. "Modelling exchange rates: smooth transitions, neural networks, and linear models," Textos para discussão 432, Department of Economics PUC-Rio (Brazil).
• George Hall and John Rust, Yale University, 2001. "Econometric Methods for Endogenously Sampled Time Series: The Case of Commodity Price Speculation in the Steel Market," Computing in Economics and Finance 2001 274, Society for Computational Economics.
• Neil R. Ericsson, 2001. "Forecast uncertainty in economic modeling," International Finance Discussion Papers 697, Board of Governors of the Federal Reserve System (U.S.).
• Michael Binder, Cheng Hsiao, and M. Hashem Pesaran, 2001. "Estimation and Inference in Short Panel Vector Autoregressions with Unit Roots and Cointegration," Computing in Economics and Finance 2001 36, Society for Computational Economics.
• Esben Hoeg, 2001. "Estimation of Diffusions using Wavelet scaling methods," Computing in Economics and Finance 2001 255, Society for Computational Economics.
• Neil R. Ericsson, 2000. "Predictable uncertainty in economic forecasting," International Finance Discussion Papers 695, Board of Governors of the Federal Reserve System (U.S.).
• Hans-Martin Krolzig, 2001. "General--to--Specific Reductions of Vector Autoregressive Processes," Computing in Economics and Finance 2001 164, Society for Computational Economics.
• J. Durbin and S.J. Koopman, 2001. "An efficient and simple simulation smoother for state space time series analysis," Computing in Economics and Finance 2001 52, Society for Computational Economics.
• Romulo Chumacero, 2001. "Testing For Unit Roots Using Economics," Computing in Economics and Finance 2001 2, Society for Computational Economics.