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Long-Run Covariability

Author(s): Mueller, Ulrich K.; Watson, Mark W.

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Abstract: We develop inference methods about long‐run comovement of two time series. The parameters of interest are defined in terms of population second moments of low‐frequency transformations (“low‐pass” filtered versions) of the data. We numerically determine confidence sets that control coverage over a wide range of potential bivariate persistence patterns, which include arbitrary linear combinations of I(0), I(1), near unit roots, and fractionally integrated processes. In an application to U.S. economic data, we quantify the long‐run covariability of a variety of series, such as those giving rise to balanced growth, nominal exchange rates and relative nominal prices, the unemployment rate and inflation, money growth and inflation, earnings and stock prices, etc.
Publication Date: May-2018
Citation: Mueller, Ulrich K, Watson, Mark W. (2018). Long-Run Covariability. ECONOMETRICA, 86 (3), 775 - 804. doi:10.3982/ECTA15047
DOI: doi:10.3982/ECTA15047
10.3982/ECTA15047
ISSN: 0012-9682
EISSN: 1468-0262
Pages: 775 - 804
Type of Material: Journal Article
Journal/Proceeding Title: ECONOMETRICA
Version: Final published version. Article is made available in OAR by the publisher's permission or policy.



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