How do Fed policy rate changes affect emerging market yields?
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A large existing literature examines how central-bank transmission mechanisms affect output, inflation and financial conditions in domestic and foreign countries. Emerging Market (EM) crises, from Mexico in the 1980s to more recent episodes in Argentina and Turkey, have often followed external shocks interacting with domestic vulnerabilities.
The Fed policy rate and the US dollar are particularly important drivers of capital flows, exchange rates and foreign direct investment into EMs. Countries with more developed local markets and active central banks monitoring macroprudential risks are less affected than those where such features are absent. Despite regionalisation, geo-economic fragmentation and loss of hegemony, the US Fed policy remains the most watched global economic policy for EM investors. In addition, the Fed’s policy rate affects developed markets through interlinkages with trade and across financial markets.
The 2013 “taper tantrum”, triggered by Fed Chair Ben Bernanke’s indication that the Fed could slow its quantitative easing (QE) bond purchases, exemplifies this sensitivity: US Treasury yields rose sharply, EM currencies depreciated against the dollar, and EM bonds incurred sizeable losses as capital flows responded to changing US–EM rate differentials.
This research paper documents how the spread between 10-year versus 2-year yields in emerging market countries changes following Fed policy rate changes. To study transmission effects from the Fed to EM countries, we focus on Fed policy rate changes over 2015–2024 and their effects on EM yield curves. EM yield curves are basic inputs for portfolios that comprise EM assets—both bonds and equities. Our sample period spans sub-periods covering QE, quantitative tightening (QT), Covid, 2021-22 inflation shock, and the Russia-Ukraine war. The period is useful for analysing EM sovereign yield curve behaviour across vastly different global macroeconomic conditions with different sub regimes. Figure 1 depicts the policy rate changes over the full sample period.
Figure 1: Fed policy rate changes in basis points (bps)
December 2015-December 2024
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Note: QT (Fed balance-sheet reduction) was under way for the 18 decisions from 13 December 2017 to 31 July 2019 and from 15 June 2022 to 18 December 2024. QE (Fed asset purchases) accompanied the 100 bps emergency cut on 16 March 2020, in response to the Covid pandemic. The remaining nine decisions were taken when the Fed balance sheet was neither being expanded through QE nor reduced through QT.
We document differential sensitivity across countries. On average, Brazil’s yield curve (represented by 2s-10s spread) moved the most and China’s the least in response to Fed policy rate changes (see later for further discussion). Hikes were followed by modest flattening and cuts by steepening mainly during the emergency rate cut in March 2020; and the differences are consistent with countries’ savings, external debt and reserves. These results are descriptive reporting of the responses of EM spreads and should not be viewed as causal effects.
This blog summarises the main results of a longer, more detailed paper, which will be made available on request.
We studied both periods of QE and QT. QE involves the central bank creating bank reserves to purchase securities on the open market, increasing the money supply and therefore stimulating growth. QT is the opposite: central banks sell securities on the open market or let them mature without reinvesting the proceeds, reducing the money supply and restricting growth. QT was used between 2017-2019 as the US economy appeared to be stable and healthy enough to sustain a reduction in the Fed’s balance sheet. However, bank reserves dropped too low in late 2019, contributing to stress in the repo market. The onset of the Covid pandemic in early 2020 then triggered a panic in financial markets amidst fears that the global economy would grind to a halt. This prompted the Fed to launch another aggressive QE programme, doubling its balance sheet to a peak of nearly $9 trillion.
As inflation started rising sharply in 2021, the Fed slowed down their asset purchases, before transitioning into QT alongside aggressive tightening of monetary policy. Inflationary pressures were then further intensified by Russia’s invasion of Ukraine in February 2022, particularly through higher energy and agricultural prices. Against this backdrop, the Fed delivered four successive 75 bps rate increases in 2022, helping push policy rates to 5.5% by July 2023, their highest level in decades. The levels of the Fed policy rate corresponding to the changes in Figure 1 are shown in Figure 2.
Figure 2. Evolution of the Fed policy rate, 2005-2024
Why does US monetary policy matter for EM yield curves?
The monetary policy of advanced economies such as the US can affect EMs through several channels including capital flows, asset prices and the interest setting behaviour of the central bank (Mohanty, 2014). International spill overs from monetary policy (Takáts and Vela, 2014) can be characterised in terms of the effects on (i) exchange rate (ii) policy rate (iii) long term policy rates (iv) portfolio flows and (v) international bank lending. It is worth emphasising that there are interactions across these five affected variables. For open economies, the transmission channel operates through policy rates, as EM central banks may respond directly to actual or expected changes in advanced economy policy rates. Another channel of transmission is through the exchange rate where a fall in the foreign policy rate leads to an appreciation of the domestic currency. Asset purchases by major central banks also have a similar effect.
In the 1970s and 1980s, when EM financial markets were less developed and largely reliant on capital from advanced countries such as the US, it was accepted that Fed policy rates were a major driver or catalyst of policy rate changes in the emerging markets. A common view during those periods was that “when the US and its markets sneezed, the EM countries caught a cold.” Our central finding from this study is that when the US “sneezes” (by changing Fed policy rates), there are effects on EM yield spreads, but not all EM economies generate a uniform response across their sovereign yield curves.
Monetary policy and effects on the domestic interest rates and asset returns
Even in developed economies, there are asymmetric effects of central bank policy rate hikes versus cuts. Typically, central banks are tasked with controlling inflation through interest rate hikes which affect financial bank borrowing costs. Banks pass on the increased costs to consumers via higher interest rates on credit cards, mortgages, loans, and corporate borrowing. Financial markets also influence the transmission mechanism as rate changes impact stock and bond prices, creating a wealth effect via the portfolio.
Dimson-Marsh-Staunton’s US data (UBS Global Investment Returns Yearbook 2025, Chapter 3) found that from 1914 to 2024, US rates were rising 46% of the time and falling 54%; in the UK, from 1930, rates were rising 32% of the time and falling 68%. In the US, annualised real equity and bond returns were 3.2% and −0.3%, respectively, during rate-rise (tightening) periods, compared with 9.5% and 3.4% during rate-cut (easing) periods. The corresponding UK figures were 1.1% and 0.1% during tightening periods versus 8.5% and 2.9% during easing periods. Risk premia and Sharpe ratios were generally higher during easing cycles; inflation was higher during tightening cycles in both countries.
For investments, what matters to global investors are the domestic interest rates less US interest rates. The remainder of the paper describes the event-study design, presents full-sample results, and concludes with investor implications on asset allocation and portfolio construction.
Data and methodology
Using an event-study framework, we document the response of 2-year versus 10-year government bond yield spreads across twelve EM economies: China, India, Indonesia, Malaysia, Thailand, South Africa, Turkey, Czech Republic, Hungary, Poland, Mexico and Brazil. The responses are over the 21 calendar days following the announcement date of each Fed policy rate change between 16 December 2015 and 18 December 2024. During the sample period, there were 28 changes in the Fed’s policy rate, 20 rate hikes and eight rate cuts. Empirically, we attempted to answer the following: how do emerging market yield spreads respond to changes in the Fed policy rate? We also want to examine if the effects from US rates to EM yield spreads are similar in direction and magnitude across our selected EM countries. Figure 3 illustrates our event window.
Figure 3: Illustration of 21-day window using Brazilian response to 14 June 2017 Fed hike.
We analyse 2-year and 10-year sovereign yields, using the difference between the 10-year yield less the 2-year yield as a measure of the yield spread. In the US, an inverted 10-year versus 2-year yield curve (negative yield spread) has historically been associated with recession risk and changing policy rate expectations. While a negative spread in EMs may similarly indicate weaker economic conditions, its interpretation is less uniform because of differences in market structure, inflation dynamics, policy credibility and term premia. Focusing on the slope also allows us to distinguish changes in curve shape from parallel shifts in yields. For Hungary and Malaysia, where 2-year yields are unavailable, we use the 10-year yield versus the 3-year yield, which provides a comparable measure of spread or curve steepness. To maintain comparability, we exclude data with fewer than 11 observations in the 21 calendar days following a Fed policy rate change. For the emergency 50 bps Fed cut on 3 March 2020, the event window is limited to a total of 11 calendar days because it preceded a 100 bps emergency cut on 16 March 2020, caused by Covid.
For each Fed decision, day 0 is the date of the Fed announcement, and we observe each country’s daily 2s-10s spread from day 0 to day 21 (trading days only). Table 1 reports the average of these daily spreads: this describes the level of each country’s yield curve slope after Fed decisions, but it is not a direct measure of how the slope responded. Table 2 and the rankings discussed below instead use the change in the spread, defined as the spread on the last trading day of the window (day 21, or the nearest earlier trading day) minus the spread on day 0.
For consistency across all countries, we take day 0 to be the date of the Fed announcement. FOMC decisions are announced at 2pm US Eastern Time, after markets in Asia and other eastern time zones have closed, so for those countries the day 0 spread is a pre-announcement observation; if markets were anticipating the Fed decision, some of this pre-announcement effect may be captured on day 0. For Mexico and Brazil, the day 0 close follows the announcement. We do not adjust for these differences in local market timing.
As with any event study, the results should be interpreted cautiously, as country-specific factors such as domestic policy decisions and other events within the event window, as well as structural factors (such as savings, debt to exports, reserves to imports and openness of trade) may also affect the observed spread changes. These factors have been found important in the studies of EM sovereign debt crises and currency crises. The 21-day window captures short-run, post-decision adjustment while accommodating differing local market calendars. The analysis is descriptive and based on cross-country comparisons, examining realised Fed policy rate changes rather than high-frequency monetary policy surprises. Data are sourced from Bloomberg.
Results
The results show substantial heterogeneity in the responsiveness of EM sovereign yield curves to Fed policy rate changes. Notably, heterogeneity is also present among countries within the same region, reflecting inter-country differences in their political and economic backdrop. As mentioned in our 3D macroscope blog, we recommend assessing countries holistically based on their demographics, economics, and investments. We present summary statistics of spreads in Table 1. These 2s-10s spreads are averaged over 21-calendar day periods following a Fed policy rate change and then averaged across the Fed decisions for which spread data are available for each EM country. Table 1 shows wide differences in the level and volatility of yield curve slopes across the 12 countries.
Table 1. Summary statistics of 2s-10s spreads following Fed policy rate changes (bps)
Table 2 shows, for each country, the average change in its 2s-10s spread over the event window across all Fed decisions of the same size. The change is measured between the first and last trading days of the window, with green indicating steepening (spread widening) and red flattening (spread narrowing).
Some policy change rate buckets contain fewer observations and therefore caution is needed in interpreting a small sample size for material effects.
Table 2: Average change in 2s-10s spread, grouped by size of Fed policy rate change (bps)
Blank cells denote lack of available data. Each cell is the average change in spread across all Fed decisions of that size in Figure 1 for which data are available for that country. For example, the -25 bps column averages up to five 25 bps cuts (31 July, 18 September and 30 October 2019; 7 November and 18 December 2024), while the -100 column reflects a single event, the emergency cut of 16 March 2020. Turkey is not shown because spread data are available for too few Fed decisions.
Following the Fed policy rate hikes, the EMs often exhibit a modest flattening tendency in their respective yield curves. An interpretation is that tighter global financial conditions and increased currency pressures push shorter-term yields up, but the extent of the flattening remains dependent on country-specific term premia and risk dynamics. Institutional and market characteristics influence the magnitude of responses as well as their directionality.
In contrast, Fed policy rate cuts tended to steepen yield curves. For example, after 50 bps cuts, ten of eleven countries steepened on average, and after the 100 bps emergency cut due to Covid, Malaysia, Thailand and Mexico steepened sharply whilst Hungary and Poland flattened. Neither hikes nor cuts produced a uniform response. Across individual episodes, 53% of country responses to Fed hikes flattened, and cuts were followed by steepening, mainly arising from the March 2020 emergency rate cut. Excluding this event, cut responses were evenly split between flattening and steepening. The dispersion of responses across countries was similar for hikes and cuts, suggesting that domestic conditions shape each country’s curve regardless of the direction of Fed monetary policy.
Country-specific macro factors
The country-specific factors in this section are illustrative; they exemplify differences between countries and are potential explanations of why EM yield curves respond differently to the same Fed policy rate change. For parsimony, we present four of the most important emerging markets in our study, by GDP (Brazil, China, India and Mexico); the same indicators can be computed for all 12 countries, and data are available on request. We compute five different macroeconomic indicators of the countries between 2015-2024. External Debt-to-Exports, Openness of Trade (defined by the sum of imports and exports divided by GDP), Consumption-to-GDP, Reserves-to-Imports and Savings Ratio.
The four economies differ markedly in their external financing positions. Brazil carries the heaviest burden, with total external debt averaging 197% of annual exports, compared with 116% for Mexico, 98% for India and 71% for China. This reflects a large external debt stock set against a relatively narrow export base. The averages, however, mask a significant improvement. Between 2015 and 2024, exports grew faster than external debt in Brazil, Mexico and India, and Brazil’s ratio fell from 234% to 154%. China was the exception: its debt outpaced exports and the ratio rose from 56% to 63%.
Reserve buffers are strongest in China and Brazil, at around 15.5 and 15.3 months of import cover respectively, with China’s being built through a persistent current account surplus. Both buffers eroded as imports grew while reserves stagnated. India exhibited the largest increase in reserves (+82%), but due to a faster growth in imports, holds a lower import cover of around 9.3 months. Mexico holds the thinnest buffer at 4.4 months, consistent with its free-floating exchange rate regime.
Trade openness is highest by a wide margin in Mexico (78% of GDP), reflecting deep integration into North American supply chains, with the bulk of its exports destined for the United States. India (43%), China (37%) and Brazil (31%) are large economies driven by domestic demand, and Brazil’s exports are generally concentrated in commodities.
Consumption and savings show a clear divide between Latin America and Asia. Consumption averaged 83% and 80% of GDP in Brazil and Mexico, against 70% in India and 56% in China. Gross savings mirror this, ranging from 44% in China to 14% in Brazil.
Taken together, these measures suggest distinct channels of vulnerability to US monetary policy. Brazil combines low domestic savings and high external debt with a large but declining reserve buffer, which points to exposure through the cost of external financing. Mexico’s vulnerability stems primarily from its trade dependence on the United States and modest reserves. China is the most insulated, with high savings, low external debt relative to exports and the largest reserves. India operates around the middle of the four countries examined.
Spread changes per 1 bps of Fed policy rate change
For each Fed decision, we measure the change in each country’s 2s-10s spread between the first and last trading days of the event window, and divide it by the absolute size of the Fed move, so that the sign indicates steepening (positive) or flattening (negative). To compare responsiveness between countries, we take the average of the absolute values of these normalised changes and then rank the 12 emerging markets by the averages in each episode. EM data are not always available for the full event window, so where observations were missing, we have used the shorter window available to us and adjusted for the gaps in data. Results should be interpreted with caution where data are less readily available.
Of the countries with at least 16 episodes observed, Brazil’s 2s-10s spread moved the most on average, by 0.87 bps per 1 bp of Fed change, and Brazil ranked in the top three in 16 of 26 episodes, including all three cuts in 2024. Hungary (0.70 bps), Indonesia (0.66 bps) and Mexico (0.60 bps) followed. Brazil’s sensitivity is consistent with its macroeconomic profile: the lowest savings rate and the highest external debt relative to exports. Mexico’s curve more often flattened than steepened (16 of 28 episodes), consistent with Fed tightening feeding through the short end as Banxico raised rates in step.
Hungary was the most responsive market during the 2022–23 hikes (0.83 bps). China (0.14 bps), Malaysia (0.22 bps) and India (0.31 bps) were consistently the least responsive. China ranked in the top three in only one of 16 episodes. These markets combine high domestic savings and large reserves, with China and India also restricting capital flows, which limits the pass-through of Fed policy. Turkey shows the largest average move (1.51 bps) but from only five episodes, and South Africa (0.34 bps) from seven, so we refrain from drawing conclusions for these two countries.
Macro investment implications
The analysis suggests that EM sovereign yield curves should not be treated uniformly in response to Fed policy. Differences in spread responses may point to relative-value opportunities for fixed-income investors and may also transmit to other domestic credit markets, including high-yield and corporate bonds. Investors should therefore look beyond headline yield levels and assess each country’s linkages to US financial conditions, domestic policy credibility and economic structure. Treating EM as a single macro trade risks overstating correlations, concentrations and country-level differences. Portfolio construction exercises should incorporate careful analysis of domestic macroeconomic conditions and their interaction with US monetary policy.
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Despite greater geopolitical fragmentation, the US dollar and the Fed policy rate continue to remain dominant anchors of global financial conditions. Understanding their history and role remains important for asset managers, pension funds, sovereign wealth funds, hedge funds, insurers and foundations. Currently, EMs are more resilient than they were in the 1990s. This reflects their progress in strengthening domestic institutions, deepening local-currency bond markets and expanding their domestic investor base. Yet, some external vulnerabilities remain, and EMs are still exposed to global shocks. Our research documents evidence of interest rate changes in emerging markets following Fed policy rate changes over an interestingly relevant period of monetary history that includes QE, QT, Covid, the 2021–22 inflation shock, and the Russia-Ukraine war. EM sovereign bond yields, and their spreads, remain sensitive to changes in US monetary policy, although the transmission effects vary considerably across countries. Our results also contribute towards construction of portfolios that include EM equities and bonds, by demonstrating the changing asset dynamics (EM interest rate yields and spreads) in response to Fed policy.
Acknowledgements
We thank Zuhair Mohammed and Hishendhra Ravindra for their insightful comments, along with Ellie Glossop for her excellent assistance with charts throughout the paper.
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- Dimson, E., Marsh, P. and Staunton, M. (2025), UBS Global Investment Returns Yearbook 2025, Chapter 3.
- Mohanty, M.S. (2014), “The transmission of unconventional monetary policy to the emerging markets: an overview”, BIS Papers No 78, pp 1–24.
- Takáts, E. and Vela, A. (2014), “International monetary policy transmission”, BIS Papers No 78, pp 25–44.
