Predictability of Aggregated Time Series

Stephen Snudden

LCERPA Working Papers from Laurier Centre for Economic Research and Policy Analysis

Abstract: Macroeconomic series are often aggregated from higher-frequency data. We show that this seemingly innocent feature has far-reaching consequences for the predictability of such series. First, the series are predictable by construction. Second, conventional tests of predictability are less informative about the data-generating process than frequently assumed. Third, a simple improvement to the conventional test leads to a sizeable correction, making it necessary to re-evaluate existing forecasting approaches. Fourth, forecasting models should be estimated with end-of-period observations even when the goal is to forecast the aggregated series. We highlight the relevance of these insights for forecasts of several macroeconomic variables.

Keywords: Forecasting and Prediction Methods; Interest Rates; Exchange Rates; Asset Prices; Oil Prices; Commodity Prices (search for similar items in EconPapers)
JEL-codes: C1 C53 E47 F37 G17 Q47 (search for similar items in EconPapers)
Pages: 25
Date: 2021
New Economics Papers: this item is included in nep-ecm, nep-ene, nep-ets, nep-for, nep-isf and nep-mac
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Persistent link: https://EconPapers.repec.org/RePEc:wlu:lcerpa:bm0127

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