The first two criteria require relatively long windows on each side of a turning point and for the full cycle in order to capture changes in interest rates that are not reversed soon afterward; this allows us to identify and study periods of “premature adjustment”, i.e., when a central bank shifts from raising to lowering interest rates (or vice versa) and then needs to reverse course. These longer windows also avoid classifying changes in interest rates that largely reflect market-driven movements as turning points, an issue earlier in the sample when interest rate data is more volatile and policy rates may not be directly set by central banks. In contrast, the third criterion allows for individual phases in a cycle to be short-lived; brief periods of rate hikes or cuts can potentially qualify as an easing or tightening phase—albeit within the longer parameters for a full cycle. This is useful in several cases when a central bank adjusts rates quickly by a large amount, and then does not adjust rates again (such as lowering rates to zero in one meeting in response to a negative shock).

After applying the algorithm, we make several adjustments to the dates identified in order for a month t to qualify as a turning point. These adjustments are mainly to address issues when interest rates are constant for an extended period around the lower bound. First, a month can qualify as the start of an easing (tightening) phase if there is no change in the policy rate but the central bank starts a new QE (QT) program (defined below). Second, if there is not a new balance sheet program, there must be an increase (decrease) in the policy interest rate to qualify as the start of a tightening (easing) phase. Finally, any such increase (decrease) in the policy rate must be meaningful and lasting, defined as |∆it| ≥0.50 percentage point over one month, or at least two rate changes (of any size) occurring over a year, such that the policy rate is at least 30 basis points higher/lower one year after the first rate change.

Appendix 1 provides more information on the details of the criteria used to identify the cycle dates, the application of each of the additional criteria, and the specific countries and dates affected by each of these criteria.

# II.2. Database: Policy Rates and Balance Sheet Programs

To define rate cycles, we focus on the policy interest rate for several reasons. First, policy interest rates are currently the primary tool used by central banks to affect the monetary policy stance. Since our goal is to inform central bank decisions today, this is an obvious measure on which to focus. Employing market-determined measures of interest rates would incorporate fluctuations in rates that are not directly under the control of central banks. Second, data for policy interest rates are widely available over a long period, allowing us to analyze their evolution over the past 55 years (1970-2024) for 24 advanced economies. A long panel is particularly important for our empirical decomposition of the factors driving rate cycles and for the identification of precedents comparable to the ongoing rate cycle.

Finally, we focus on nominal policy rates, instead of attempting to estimate more complex measures of the overall stance of monetary policy.<sup>6</sup> Measuring the overall policy stance would require finding a comparable way to measure the impact of adjusting other policy tools (such as the money supply in certain periods) and modelling variables such as the neutral interest rate (which could be subject to substantial measurement error). Both of these tasks are extremely challenging for an individual country, and even more so for a cross-section of diverse economies

> 6 A series of papers have used alternative approaches to measure the overall stance of monetary policy. For example, Bernanke and Mihov (1998) uses a nested VAR of a range of macroeconomic and financial variables. Woodford (2003) uses deviations from an estimated natural interest rate, and others have considered deviations from certain monetary policy rules, including Taylor (1993) and Orphanides (2003). More recently, Estrella (2022) measures the stance of US monetary policy as movements in a long-term Treasury forward rate relative to that of the federal funds (or shadow) rate.

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