Memo to the Board of Governors of the Federal Reserve System,  December 14, 2000. 5 The first instance was the May 2001 Bluebook. 6 Thomas Laubach and John C. Williams. Measuring the Natural Rate of Interest. Board of Governors of the Federal Reserve System, Finance and Economics Discussion  Paper Number 2001-56. November 2001. 7 Thomas Laubach and John C. Williams. "Measuring the Natural Rate of Interest," Review of Economics and Statistics 85, no.4 (November 2003): 1063-70. 8 Thomas Laubach and John C. Williams, "Measuring the Natural Rate of Interest Redux," Business Economics 51, no. 2 (April 2016): pp. 57-67. 9 Kathryn Holston, Thomas Laubach, and John C. Williams, "Measuring the Natural Rate of Interest: International Trends and Determinants," Journal of International  Economics 108 (May 2017): S59-S75. 10 These issues are discussed in detail in "Adapting the Laubach and Williams and Holston, Laubach, and Williams Models to the COVID-19 Pandemic," and "Measuring the  Natural Rate of Interest After COVID-19," by Kathryn Holston, Thomas Laubach, and John C. Williams. 11 Federal Reserve Bank of New York, Measuring the Natural Rate of Interest. 12 Oxford COVID-19 Government Response Tracker, Blavatnik School of Government, University of Oxford. 13 Note that we no longer produce HLW estimates for the United Kingdom because the model does not provide a good fit for the data. The estimates for the UK were highly  imprecise even before the pandemic and the subsequent data has exacerbated this problem. 14 Thomas Laubach and John C. Williams.
I should note that this is described in detail in the paper, "Measuring the Natural Rate of Interest After COVID-19," that was posted this morning on the New York Fed's r-star web page. First, we incorporated an additional persistent supply shock related to the effects of the pandemic that directly reduce the economy's potential. We measure this shock using the Oxford COVID-19 Government Response Stringency Index for each economy.12 This index aggregates measures of government containment and shutdown policies. Because the index is no longer being produced, we assume that in each case, it declines smoothly to zero over 2023-24. Second, we use a statistical procedure that accounts for outliers in the model's estimation. Specifically, from the second quarter of 2020 to the fourth quarter of 2022, we estimate a time-varying process for the variance of the shocks hitting the economy. This procedure places a lower weight on periods when there are very large outliers. Our results show that outliers are particularly large in 2020, as seen in Figure 2. By comparison, the estimated magnitude of outliers is relatively modest in 2021 and 2022. Starting in 2023, we assume that the distribution of shocks is no longer affected by the pandemic. Letting the Data Speak  Estimation of the modified model reveals three key findings. First, the modified estimation procedure yields results that are overall quite similar to those from the original model during the pre-pandemic period. Second, the current estimates of r-star are similar to those estimated directly before the pandemic.