A Robust Test for OLS Trends in Daily Temperature Data

38 Pages Posted: 18 Jul 2015 Last revised: 19 Aug 2015

Jamal Munshi

Sonoma State University

Date Written: July 15, 2015

Abstract

Trends in time series data estimated with OLS linear regression may be tested with a robust procedure that is less sensitive to influential observations and violations of regression assumptions. The test consists of comparing the average age of data tritiles. If the higher tritiles are newer a rising trend is indicated for the sample period. If the higher tritiles are older a declining trend is indicated. If neither of these conditions is met, no sustained trend in the sample period may be inferred from the data. Daily temperature data from selected USHCN and USCRN stations are used to demonstrate the utility of the proposed methodology.

Keywords: trend analysis, rising temperatures, global warming, climate change, Hurst exponent, robust statistics

Suggested Citation

Munshi, Jamal, A Robust Test for OLS Trends in Daily Temperature Data (July 15, 2015). Available at SSRN: https://ssrn.com/abstract=2631298 or http://dx.doi.org/10.2139/ssrn.2631298

Jamal Munshi (Contact Author)

Sonoma State University ( email )

1801 East Cotati Avenue
Rohnert Park, CA 94928
United States

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