  This study presents a statistical approach for identifying transitions
between climate states, referred to as breakpoints, using well-established
econometric tools. We analyse a 67.1 million year record of the oxygen isotope
ratio delta-O-18 derived from benthic foraminifera. The dataset is presented in
Westerhold et al. (2020), where the authors use recurrence analysis to identify
six climate states. We consider several model specifications. Fixing the number
of breakpoints to five, the resulting breakpoint estimates closely align with
those identified by Westerhold et al. (2020) across various data binning
frequencies and model specifications. Treating the number of breakpoints as a
parameter to be estimated results in statistical justification for more than
five breakpoints in the time series. Our approach offers the advantage of
constructing confidence intervals for the breakpoints, and it allows testing
for the number of breakpoints present in the time series.
