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Estimation and Inference of Linear Trend Slope Ratios With an Application to Global Temperature Data
Author(s) -
Vogelsang Timothy J.,
Nawaz Nasreen
Publication year - 2017
Publication title -
journal of time series analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.576
H-Index - 54
eISSN - 1467-9892
pISSN - 0143-9782
DOI - 10.1111/jtsa.12209
Subject(s) - estimator , inference , statistics , mathematics , econometrics , statistical inference , series (stratigraphy) , statistical hypothesis testing , computer science , geology , paleontology , artificial intelligence
We examine estimation and inference of the ratio of linear trend slopes between two time series. Our methodological results are motivated by recent empirical climate papers that estimate and test hypotheses about the relative warming rate in the lower‐troposphere relative to surface warming, i.e. the amplification ratio. We analyze statistical properties of several estimators and test statistics that allow serial correlation. Relative merits of the estimators and test statistics depend on the magnitude of the trend slopes relative to the noise in the data. We make specific recommendations for practitioners. We revisit the empirical findings of Klotzbach et al . (2009, 2010) and obtain similar results using our recommended approach.