Unit Roots, Change, and Decision Bounds

Robert Kunst ()

No 58, Economics Series from Institute for Advanced Studies

Abstract: The problem of optimal decision among unit roots, trend stationarity, and trend stationarity with structural breaks is considered. Each class is represented by a hierarchically random process whose parameters are distributed in a non-informative way. The prior frequency for all three processes is the same. Observed trajectories are classified by two information condenser statistics zeta1 and zeta2. zeta1 is the traditional Dickey-Fuller t-test statistic that allows for a linear trend. zeta2 is a heuristic statistic that condenses information on structural breaks. Two loss functions are considered for determining decision contours within the (zeta1, zeta2) space. Whereas quadratic discrete loss expresses the interest of a researcher attempting to find out the true model, prediction error loss expresses the interest of a forecaster who sees models as intermediate aims. For both loss functions and the empirically relevant sample sizes of T=50, 100, 150, 200, optimal decision contours are established by means of Monte Carlo simulation.

Keywords: Time series; Integrated processes; Structural breaks; Loss; function (search for similar items in EconPapers)
JEL-codes: C22 C44 (search for similar items in EconPapers)
Pages: 37 pages
Date: 1998-09
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https://irihs.ihs.ac.at/id/eprint/1096 First version, 1998 (application/pdf)

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Working Paper: Unit Roots, Change, and Decision Bounds (1998)
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