Interpolation and Shock Persistence of Prewar U.S. Macroeconomic Time Series: A Reconsideration

Daniel Levy () and Hashem Dezhbakhsh

No 2022-02, Working Papers from Bar-Ilan University, Department of Economics

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)
Pages: 26 pages
Date: 2022-03
New Economics Papers: this item is included in nep-his, nep-mac and nep-ore
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Related works:
Journal Article: Interpolation and shock persistence of prewar U.S. macroeconomic time series: A reconsideration (2022)
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)
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