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

Hashem Dezhbakhsh and Daniel Levy ()

EconStor Open Access Articles and Book Chapters, 2022, vol. 213

Abstract: The U.S. prewar output series exhibit smaller shock-persistence than postwar-series. Some studies suggest that 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 Time Series; Periodic Nonstationarity; Stationary Time Series; Prewar US Time Series; Prewar vs Postwar Business Cycles (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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https://www.econstor.eu/bitstream/10419/251467/1/Dezhbakhsh-and-Levy-WP-2022.pdf (application/pdf)

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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