Our statistical procedure extracts appropriate time trends from real interest rates even with short samples and high volatility. Equilibrium interest rate estimates from the seminal Laubach-Williams model (Laubach and Williams 2003) are very imprecise even for advanced economies. This is both due to a weak relationship between the output gap and the real interest rate gap and due to a weak relationship between inflation and the output gap. If these relationships are very weak, their model is unobservable and the equilibrium interest rate cannot be uniquely identified (Hamilton _et al._ 2016, Fiorentini _et al._ 2018). Those cases are already common for advanced economies, but the identification challenges are even more severe for EMDEs. First, many of them report only annual data, which makes it even harder to find a strong relationship between these variables and, second, EMDEs are more likely to have structural breaks in their data. Fiorentini _et al_ . (2018) show that if the interest rate gap is assumed to be stationary, the Laubach-Williams model can identify the equilibrium interest rate even when the relationships between the output gap, the interest rate gap, and inflation are weak. They also show that from this assumption it follows directly that the equilibrium real interest rate can be estimated with a univariate local level specification model that decomposes the ex-ante real interest rate into its permanent and transitory component. Instead of ARCH, we use a stochastic volatility model to allow for time-varying variance of the interest rate gap and estimate it with Bayesian methods, which is more suitable for EMDEs.

Our study contributes, first and foremost, to the large literature on estimating equilibrium interest rates. The equilibrium rate of interest is a theoretical concept and cannot be observed. The most prominent methodology to estimate it, based on a semi-structural model of Laubach and Williams (2003), provides only very imprecise estimates and even minor modifications of the model or the estimation strategy can result in very different estimates of equilibrium interest rates.<sup>3</sup> In addition, it is not suited for the estimation of equilibrium real rates in EMDEs due to its data requirements and the need for a strong relationship between the variables included in the model. Recent advances have concentrated on the following areas: first, estimation procedures have been extended and improved for the United States;<sup>4</sup> second, they have been applied to more advanced economies;<sup>5</sup> and, third, equilibrium interest rates for some advanced economies have been constructed for much longer time periods.<sup>6</sup> We contribute to this literature by offering an estimation method that allows to extend the estimation of equilibrium rates to many more countries, which to the best of our knowledge is yet missing.<sup>7</sup> Second, we add to the literature on the global interest rate. Current estimates of the global interest rate are mostly based on small sets of countries: King and Low (2014) present a “world” real interest rate based on data from the G7 countries and Del Negro _et al._ (2019) interpret the common trend of a VAR model estimated for the same seven economies as the “global” interest rate. While these countries constitute a large share of the world economy, they still provide only a limited understanding of the global interest rate. Wynne and Zhang (2018) add the BRICS countries to their estimation of a global

> 3 Among others, this is shown in Clark and Kozicki (2005), Kiley (2015), Lewis and Vazquez-Grande (2017), Brand _et al_ . (2018), and Beyer and Wieland (2019).

> 4 Examples include Holston _et al_ . (2017), Del Negro _et al_ . (2017), Christensen and Rudebusch (2017), and Krustev (2019).

> 5 Examples include Mendes (2014), Fujita and Fujiwara (2016), Belke and Klose (2017), Hledik and Vlcek (2018), and Beyer and Wieland (2019).

> 6 Examples include Hamilton _et al._ (2016), Fiorentini _et al._ (2018), and Schmelzing (2020).

> 7 The only exceptions are Klose (2020) and Wynne and Zhang (2018), who estimate equilibrium rates for the BRIC countries with the Laubach-Williams model. This is only possible because these countries have good quarterly data, which is not the case for most other EMDEs.

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