Testing for Relationships between Time Series

Journal of the American Statistical Association, Vol. 71, p. 214, 1976

University of Alberta School of Business Research Paper No. 2013-251

Posted: 28 May 2013 Last revised: 30 May 2013

See all articles by Alice Orcutt Nakamura

Alice Orcutt Nakamura

University of Alberta - School of Business

Masao Nakamura

University of British Columbia (UBC) - Sauder School of Business

Guy Orcutt

Yale University - Department of Economics

Date Written: April 27, 1973

Abstract

The usual procedures for testing the significance of sample correlations between pairs of independently normally distributed series are not appropriate for testing sample correlations between pairs of autocorrelated series. We present sampling evidence supporting our hypothesis that the distributions of sample correlations between pairs of unrelated first-order Markov series conditional on the first lag sample autocorrelations of the series correlated are independent of the population first lag autocorrelations of these series. Based on this evidence, a new test of significance for correlations between autocorrelated series is proposed, which, although treating them as first-order Markov series, does not depend on the generally unknown generating properties of the series.

Suggested Citation

Nakamura, Alice Orcutt and Nakamura, Masao and Orcutt, Guy, Testing for Relationships between Time Series (April 27, 1973). Journal of the American Statistical Association, Vol. 71, p. 214, 1976, University of Alberta School of Business Research Paper No. 2013-251, Available at SSRN: https://ssrn.com/abstract=2270639

Alice Orcutt Nakamura (Contact Author)

University of Alberta - School of Business ( email )

2-32C Business Building
Edmonton, Alberta T6G 2R6
Canada

Masao Nakamura

University of British Columbia (UBC) - Sauder School of Business ( email )

2053 Main Mall
Vancouver, BC V6T 1Z2
Canada
604-822-8434 (Phone)
604-822-8477 (Fax)

Guy Orcutt

Yale University - Department of Economics ( email )

28 Hillhouse Ave
New Haven, CT 06511
United States

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