Estimating the number of unit roots: A multiple decision approach

Arbeitspapier

The problem of detecting unit roots in univariate and multivariate time series data is treated as a problem of multiple decisions instead of a testing problem, as is otherwise common in the econometric and statistical literature. Four examples for such multiple decision designs are considered: first- and second-order integrated univariate processes; conintegration in a bivariate model; seasonal integration for semester data; seasonal integration for quarterly data. In all cases, restrictedly optimum decision rules are found for finite samples based on Monte Carlo simulation.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: Reihe Ökonomie / Economics Series ; No. 16

Classification and Topics

• Classification: Wirtschaft ; Single Equation Models; Single Variables: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes ; Multiple or Simultaneous Equation Models: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models ; Econometric and Statistical Methods: Special Topics: Other
• Subject: multiple decision ; unit roots ; autoregressive processes

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Kunst, Robert M.
• Event: Veröffentlichung
• (who): Institute for Advanced Studies (IHS)
• (where): Vienna
• (when): 1995

Further information

• Handle: http://hdl.handle.net/10419/68658
• Last update: 10.03.2025, 11:44 AM CET