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

Hashem Dezhbakhsh and Daniel Levy ()

Economics Letters, 2022, vol. 213, issue C

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.

Keywords: Linear interpolation; Random walk; Shock-persistence; Nonstationary series; Periodic nonstationarity; Stationary series; Prewar US time series (search for similar items in EconPapers)
JEL-codes: C01 C02 E01 E30 N10 (search for similar items in EconPapers)
Date: 2022
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Related works:
Journal Article: Interpolation and shock persistence of prewar U.S. macroeconomic time series: A reconsideration (2022)
Working Paper: Interpolation and Shock Persistence of Prewar U.S. Macroeconomic Time Series: A Reconsideration (2022)
Working Paper: Interpolation and Shock Persistence of Prewar U.S. Macroeconomic Time Series: A Reconsideration (2022)
Working Paper: Interpolation and shock persistence of prewar U.S. macroeconomic time series: A reconsideration (2022)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecolet:v:213:y:2022:i:c:s0165176522000623

DOI: 10.1016/j.econlet.2022.110386

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