countries at different points in time (such as the money supply or exchange rate). Closely related, we do not take into account changes in monetary policy tools or frameworks over time. Finally, we focus on a sample of 24 advanced economies (including the euro area), but do not consider emerging and developing economies, many of which would likely have very different rate cycles.

# II. Rate Cycles: Methodology, Data, and Dates

This section adapts the methodology used in the extensive literature on business cycles to identify cycles in policy interest rates. We also incorporate information on central banks’ balance sheet programs—large-scale asset purchases (QE, quantitative easing) when short-term policy rates had reached the lower bound, and subsequent asset sales (QT, quantitative tightening). This section begins by introducing the methodology and then describes the data on policy interest rates and asset purchase programs used to identify the rate cycles. It concludes with the resulting dates for easing and tightening phases used in the remainder of the paper.

# II.1. Dating Methodology

Our goal is to identify the turning points of rate cycles using a methodology that links to the longstanding literature on business cycles and can be applied consistently over a long period and across countries. Because of the substantial volatility in interest rates early in our sample period and differences in monetary policy frameworks across countries and time, we cannot use an off-theshelf approach, rely on country-specific analyses, or employ simple rules of thumb as is sometimes done for business cycles (such as the two quarters of negative GDP growth popularly used as a shorthand to identify recessions).

Instead, we modify the BBQ algorithm proposed by Bry and Boschan (1971) and then developed in Harding and Pagan (2002).<sup>5</sup> This algorithm evaluates increases and decreases in a series to locate local maxima and minima over specified windows. If an adjacent local peak and trough of policy interest rates meets the censoring criteria set in the algorithm, they define the start of the two phases (easing and tightening) that together constitute a cycle. More specifically, the algorithm identifies a local maxima in the monthly series for interest rates it at time t if the interest rate increases and does not immediately fall back per the following criteria: Similarly, a local minima occurs in month t if: A local maxima is the peak of the interest rate series and can be the start of an easing phase (if it meets the requirements above), while a local minima is the trough of the interest rate series and can be the start of a tightening phase. A full “rate cycle” comprises an easing and a tightening phase, just as a business cycle comprises an expansion and contraction phase. For these local maxima and minima to qualify as the start of an easing or tightening phase, respectively, we set three parameters: (i) a window of at least 18 months on each side of a local maxima and minima; (ii) a window of at least 36 months for a full cycle (including both tightening and easing phases); and (iii) a window of at least 7 months for any individual phase of a cycle (either a tightening or easing phase).

> 5 The BBQ algorithm was first proposed by Bry and Boschan (1971), building on the work of Burns and Mitchell (1946) that lays the foundation for identifying US business cycles. See Claessens, Kose, and Terrones (2009, 2012) for details and applications to identifying business and financial cycles.

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