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Bootstrapping time-dependent stationary processes

Author

Listed:
  • Kit Baum

    (Boston College)

  • Jesus Otero

    (Universidad del Rosario)

Abstract

We present the community-contributed blockboot command to bootstrap time-dependent stationary processes using four schemes that preserve the processes' dependence structure by resampling blocks of observations. These schemes include the nonoverlapping block bootstrap of Carlstein (1986, Annals of Statistics, 14: 1171–1179); the moving block bootstrap of Kunsch (1989, Annals of Statistics, 17: 1217–1241) and Liu and Singh (1992, Exploring the Limits of Bootstrap, ed. LePage and Billard: Wiley); the circular block bootstrap of Politis and Romano (1992, Exploring the Limits of Bootstrap); and the stationary block bootstrap of Politis and Romano (1994, Journal of the American Statistical Association, 89: 1303–1313). An illustration of these four block bootstrap schemes for time-series data in the context of computing the size of unit-root tests extends and updates the findings of Schwert, ”Tests for Unit Roots: A Monte Carlo Investigation“ (1989, Journal of Business and Economic Statistics, 7: 147–159). We find that the results are most sensitive to the choice of block length, which can be specified in the command or computed automatically.

Suggested Citation

  • Kit Baum & Jesus Otero, 2026. "Bootstrapping time-dependent stationary processes," UK Stata Conference 2026 02, Stata Users Group.
    • Handle: RePEc:boc:lsug26:02
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    File URL: http://repec.org/lsug2026/Baum_blockboot_UK26.pdf
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