Co-authors: Dora Xia and Hongyi Chen
Evaluating the stance of monetary policy for the open economies of East Asia requires a different approach than that developed for the US. In recent years, the discussion has centered around the concept of the neutral real interest rate, or r*. A commonly used definition of r* is the interest rate that prevails when economic slack is zero and inflation is stable. Observers then ask, by comparing r* with the existing policy rate, whether current monetary conditions are too accommodative or too restrictive.
The neutral rate of interest is inherently unobservable as it is a hypothetical concept. Consequently, it must be inferred through estimation. The semi-structural models designed to estimate r* for the US do not adequately capture the macroeconomic dynamics of East Asian economies. In particular, exchange rates and capital flows play a more significant role in East Asia, with spillovers from the US factoring in. Moreover, since the Great Financial Crisis of 2008-09, central banks have expanded their purview beyond the business cycle to give more attention to financial stability.
Our study for the Bank for International Settlements (BIS Working Paper No. 1285) provides new estimates of r* for China, Korea, and Japan. Rather than taking the common approach of estimating a semi-structural model, we apply band spectrum regression analysis which detects sensitivity in parameter estimates to the different periodicities that characterize business and financial cycles. This allows us to differentiate r* and the stance of monetary policy by type of cycle, recognizing that these cycles move over different time horizons. In particular, monetary policy is known to act with long and variable lags, while financial shocks can erupt quickly but impose long lasting economic effects. Further, productivity and demographic factors are seen to be slow moving forces.
We focus on four broad factors that influence r*: an economic factor; a financial factor; a monetary factor; and a structural factor. The economic factor summarizes aggregate demand and supply conditions that influence monetary policy. The financial factor captures the variety of signals that let the central bank know whether financial stability is under threat. The monetary factor pertains to variables that are directly or indirectly influenced by central bank policy decisions. The structural factor encompasses such economic forces as productivity and demography. Finally, we incorporate the impact of the US on all three Asian countries, and the impact of China on Korea and Japan.
The main results are presented in Figure 1 and Table 1 below. Figure 1 plots estimates of the monetary policy stance with respect to both the business cycle and the financial cycle. If the central bank policy rate is too low relative to r*, the monetary policy stance indicator is positive meaning policy is too loose. The reverse holds with a negative policy stance indicator meaning policy is too tight. The darkly shaded areas of the graphs indicate periods of recession.
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Figure 1. Monetary Policy Stances: Business Cycle and Financial Cycle Perspectives |
We highlight a few findings. First, the graphs show a prevalence of relatively loose monetary policy being sustained in the Asian countries. For the US, overly loose policy is mainly associated with stress conditions, including the 2001 dot-com bubble, the GFC, and the pandemic. Second, for both Korea and China, the monetary policy stance as measured over the financial cycle is consistently tighter than over the business cycle. One interpretation of this might be that for these countries longer-term financial stability considerations weighed more heavily on policy makers than shorter-run business cycle considerations focused on inflation. Further for Korea and China, monetary policy gradually becomes closer to neutral after 2017. Earlier loosening associated with the GFC is especially visible for these two countries at both business and financial cycle frequencies. Finally, for China specifically, a brief but sharp loosening is apparent in 2015 around the time of the stock market collapse and surprise devaluation of the renminbi (Burdekin and Siklos, 2025).
Table 1 presents band spectrum regression results for the case in which the US neutral rate is included for all three Asian countries and China's neutral rate is included for the other two. Several results are worth highlighting. First, all estimated signs are consistent with theoretical expectations. Second, the impact of the US neutral rate is statistically significant for both business and financial cycles in Japan and Korea, although only for the financial cycle in China. China's neutral rate is significant only for the business cycles of Japan and Korea. Third, the financial factor, often ignored in studies of r*, has a significant bearing on neutral rates for both business and financial cycles in the US and China as well as for the business cycle in Japan and the financial cycle in Korea. For the US, the quantitative magnitudes are notably high.
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Table 1. Band Spectrum Regression Estimates Standard errors are in parentheses. F-stat (p) is the test of the joint statistical significance of the explanatory variables with respect to the p value. */**/*** indicate significance at 1/5/10% levels. |
Our principal contribution is to demonstrate that movement of neutral rates is sensitive to whether the business cycle or the financial cycle serves as the reference. The two cycles operate at different time horizons, the business cycle with a period generally of two to eight years, the financial cycle with a much longer period of 10 to 20 years. Another important contribution is to show that spillovers from the US and China are economically and statistically significant. Specifically, neutral rates in Japan and Korea are influenced by neutral rates in both the US and China. While the US neutral rate also influences China’s, the impact is considerably smaller than its effect for Japan and Korea.
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Co-author Dora Xia is a Principal Economist at the Bank for International Settlements.
Co-author Hongyi Chen is a Senior Adviser at the Hong Kong Institute for Monetary and Financial Research.