Interpolation and shock persistence of prewar U.S. macroeconomic time series: A reconsideration

Hashem Dezhbakhsh, Daniel Levy

Research output: Contribution to journalArticlepeer-review

Abstract

The U.S. prewar output series exhibit smaller shock-persistence than postwar-series. Some studies suggest this may be due to linear interpolation used to generate missing prewar data. Monte Carlo simulations that support this view generate large standard-errors, making such inference imprecise. We assess analytically the effect of linear interpolation on a nonstationary process. We find that interpolation indeed reduces shock-persistence, but the interpolated series can still exhibit greater shock-persistence than a pure random walk. Moreover, linear interpolation makes the series periodically nonstationary, with parameters of the data generating process and the length of the interpolation time-segments affecting shock-persistence in conflicting ways.

Original languageEnglish
Article number110386
JournalEconomics Letters
Volume213
DOIs
StatePublished - Apr 2022

Bibliographical note

Publisher Copyright:
© 2022 Elsevier B.V.

Keywords

  • Linear interpolation
  • Nonstationary series
  • Periodic nonstationarity
  • Prewar US time series
  • Random walk
  • Shock-persistence
  • Stationary series

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