How Resilient Were Emerging Market Economies Through the 2022-23 U.S. Monetary Tightening Cycle

July 02, 2026

How Resilient Were Emerging Market Economies Through the 2022-23 U.S. Monetary Tightening Cycle?

Shaghil Ahmed, Ozge Akinci, and Albert Queralto¹

1. Introduction

The cross-border spillover effects of shifts in U.S. monetary policy have long been a focus of academics and policymakers alike. A common finding in the literature is that changes in the stance of U.S. monetary policy have sizable effects on economic activity and financial markets in emerging market economies (EMEs). Previous research has shown that the spillovers of U.S. monetary policy to EMEs depend both on the context in which the monetary policy changes are occurring - that is, what shocks are prompting the U.S. policy shift - and the vulnerabilities of the EMEs themselves. (See, for example, Hoek, Kamin, and Yoldas (2022) and Ahmed, Akinci, and Queralto (2024)).

In this note, we analyze one specific aspect these spillovers: how less-vulnerable and more-vulnerable emerging market economies fared through the most recent U.S. monetary policy tightening cycle of 2022-23 relative to the predictions a full-fledged model that is calibrated to capture empirically relevant features of a wide range of EMEs. This tightening cycle has been unprecedented in both magnitude and speed, with a cumulative rise in the federal funds rate not seen in the previous 30 years (Figure 1, left panel). The right panel of the figure shows that market expectations of the federal funds rate path shifted upwards by 4 percentage points between late 2021 and late 2023, with the bulk of the moves occurring in 2022. Given the history of large spillovers to EMEs, it is important to know how resilient these economies have been to this recent aggressive U.S. tightening and the accompanying rise in market expectations of the U.S. policy rate (Figure 1, right panel).

We find that the relatively more vulnerable EMEs fared better in both financial market and growth outcomes through the recent U.S. monetary policy tightening cycle than would be expected from our model, while the relatively less vulnerable fared a bit better than the model predictions for financial outcomes but substantially worse for growth outcomes.

2. Overview of the Model

Our baseline framework is a two-country New Keynesian model consisting of a home country (a small EME) and the foreign economy (the United States). Here we present only a brief overview of our model - full details can be found in Ahmed, Akinci, and Queralto (2024).

In addition to standard trade linkages, the model features financial linkages between these two countries: EME financial intermediaries can borrow from the foreign economy (in dollars) as well as from domestic households (in local currency). The model allows for key EME vulnerabilities that have been emphasized in the literature, including deviations from uncovered interest parity and currency mismatches, modeled as in Akinci and Queralto (2023); dollar invoicing of EME exports, as highlighted in Gopinath et al. (2018); and a backward-looking component of EME long-term inflation expectations. The model also includes a set of nominal and real rigidities that help generate empirically realistic effects of monetary policy shocks.

Two of the sources of EME vulnerability play a particularly important role in our analysis. The first is the presence of foreign currency-denominated debt in firms' balance sheets, which lead to adverse financial consequences from domestic currency depreciation that, in principle, can more than offset the positive effects through net exports of such depreciation. The second is the imperfect anchoring of inflation expectations - a property typical of EMEs with histories of high-inflation episodes and earlier absence of inflation targeting frameworks. In the model, we incorporate this feature by postulating that firms rely on past inflation surprises to guide their price setting decisions rather than being entirely forward-looking as in the case of well-anchored long-term inflation expectations. This is a simple way to capture the idea that in some EMEs the central banks' inflation targets may lack full credibility.

3. Two Polar Cases: Fully Growth-Driven vs. Fully Monetary-Driven Tightening

The context in which U.S. monetary tightening is occurring is important in studying its spillover effects. The spillovers are relatively more benign if the U.S. tightening reflects a "growth" shock arising from stronger aggregate demand that raises both growth and inflation than if it represents a "monetary" shock occurring in response to more direct inflation shocks or reflecting a hawkish shift in policy (see, for example, Hoek, Kamin, and Yoldas (2022)). This feature reflects that U.S. aggregate demand shocks would have direct positive spillovers to other countries that would offset some of the adverse effects from higher U.S. interest rates.

Thus, in studying the effects of the recent U.S. tightening, it would be important to know to what extent it was driven by growth shocks versus monetary shocks. For illustrative purposes, we begin with two polar cases: one in which throughout this episode, the U.S. tightening is assumed to be fully growth-driven, and another in which it is assumed to be fully monetary-driven. Specifically, for the growth-driven polar case, we feed into our model innovations to U.S. aggregate demand that replicate the upward movements in market expectations of the federal funds rate depicted in the right panel of Figure 1. Similarly, for the monetary-driven polar case, we search for the sequence of shocks to the monetary policy rule that allows the model to match the same upward movements over time in market expectations of the federal funds rate. We view these polar cases as useful bounds to gauge the range of possible spillover effects.

The blue and red lines in Figure 2 show the predicted effects from the model on the GDP of less vulnerable (left) and more vulnerable (right) EMEs for the polar cases of only growth shocks and only monetary shocks, respectively. (We will return to the green line later.) For the less vulnerable economies, the model sees the 2022 tightening as having only mild adverse effects, even when it is assumed to be entirely monetary driven, and beneficial effects on net if it assumed to be entirely growth driven. But for the more vulnerable EMEs, the model sees the recent tightening as having negative effects on activity even if it were driven entirely by growth shocks, and very adverse effects (a GDP hit of 6 percent) if it were completely monetary driven.

These are illustrative polar cases, of course, and it is most likely some combination of growth and monetary shocks that drove the U.S. tightening. Below we discuss one way to identify what that combination might have been.

4. More Realistic Case: Model-Inferred Mix of Growth and Monetary Shocks

We use the model to infer a specific mix of positive growth and adverse monetary shocks driving the U.S. tightening, assuming that these two shocks were the only shocks driving the dynamics of the fed funds rate and U.S. GDP. Here we use the feature that these two shocks would drive U.S. GDP in opposite directions. Using a measure of the shift in market participants' expectations of U.S. growth, along with the shifts in the expected path of the fed funds rate shown earlier, we can infer from the model the specific combination of growth and monetary shocks over time that drove the tightening.

Figure 3 charts the evolution of a survey-based measures of U.S. quarterly real GDP growth expectations of financial analysts, obtained from the Blue Chip Economic Indicators. It shows progressive mark-downs to expected growth through almost all of 2022 that occurred while expectations of the federal funds rate (shown earlier) were being revised up. This suggests that over this period monetary shocks dominated, even though starting in December 2022, growth expectations started to be revised upwards. We can see this more clearly by going back to figure 2; the dashed green line shows the predictions for the effects on GDP of the inferred combination of growth and monetary shocks identified. It shows the predictions to be somewhat closer to those discussed earlier under the assumption that the shocks were only monetary (the red line) than under the assumption that they were only growth shocks (the blue line). All this is consistent with the idea that the evolution of the survey-based expectations of U.S. growth and of the federal funds rate path suggests that the 2022-23 U.S. tightening was driven more by adverse monetary shocks than by positive growth shocks, although both played a role.

5. Predicted vs. Realized Effects on Financial Markets and Real Activity

Next, we turn to the question of how the actual evolution of financial variables and real activity in less and more vulnerable economies over this tightening period compares with the model's predictions for the inferred combination of growth and monetary shocks.

EMEs are divided into less-vulnerable and more-vulnerable groups based on a methodology that computes a cross-country vulnerability index presented in Ahmed, Coulibaly, and Zlate (2017). This vulnerability index summarizes the relative strength of different EMEs macroeconomic fundamentals based on six variables: current balance as a share of GDP, foreign exchange reserves as a share of GDP, short-term external debt as a share of foreign exchange reserves, gross government debt-to-GDP ratio, average annual inflation over the past three years, and a 5 year run-up in bank credit to the private sector-to-GDP ratio. The less vulnerable group comprises countries with a vulnerability index below the median, and the more vulnerable group comprises those with an above-median vulnerability index.

Figure 4 shows the evolution of EME corporate borrowing spreads (top row) and EME nominal exchange rates (bottom row) for less and more vulnerable EMEs (left and right columns, respectively). Using the same convention as earlier, the blue lines show the model's predictions when the U.S. tightening is completely growth-driven while the red lines show the case when it is completely monetary-driven. The dashed green lines show the predictions of the model from the model-inferred combination of growth and monetary shocks. The model-implied paths are constructed by assuming that absent shocks, spreads and exchange rates would have remained constant at their 2021:Q4 levels. The actual data are shown by the solid black lines.

For the less vulnerable EMEs, the behavior of exchange rates (bottom left panel) was close to the model's predictions of significant depreciations. In these same economies, the level of corporate spreads was lower than suggested by the identified combination of shocks and close to the path implied by assuming growth shocks only. In contrast, the degree of financial stress since early 2022 in the more vulnerable economies was considerably less than the model's prediction under the growth-monetary shock combination and close to what only growth shocks would have implied.

Turning to real activity, the message is roughly the same when looking at the behavior of real GDP levels, depicted in Figure 5. Here the predicted outcomes are generated by assuming that absent shocks GDP paths of EMEs would have followed the path indicated by private sector forecasts as of 2021:Q4, shown by the dashed-dotted lines. Again, as can be seen from the right panel, the more vulnerable EMEs displayed remarkable resilience, with GDP levels considerably higher than the model-implied path from the growth-monetary combination. As seen in the left panel, the less vulnerable EMEs, on the other hand, saw GDP outcomes well below those predicted from the growth-monetary shock combination and very close to those implied by assuming only monetary-driven tightening.

All in all, for financial markets, our evidence suggests that both less vulnerable and more vulnerable EMEs fared better overall than our model would suggest, and the more vulnerable economies especially so. For activity, more vulnerable economies did considerably better than the model predicts, while the less vulnerable economies did substantially worse. One possible interpretation of the divergence in outcomes is that developments outside of the United States, such as movements in global commodity prices and China's growth prospects, are also important for EME economic activity and financial conditions and these factors may have affected more-vulnerable and less-vulnerable EMEs in different ways. An alternative interpretation is that the more vulnerable EMEs may have improved their monetary and other policy frameworks in ways that are not showing up, at least not yet, in the variables used in the vulnerability index.

References

Ahmed Shaghil, Ozge Akinci, and Albert Queralto, "U.S. monetary policy spillovers to emerging markets: Both policy drivers and vulnerabilities matter," International Finance Discussion Papers 1321r1. Washington: Board of Governors of the Federal Reserve System.

Ahmed, Shaghil, Brahima Coulibaly, and Andrei Zlate, "International financial spillovers to emerging market economies: How important are economic fundamentals?" Journal of International Money and Finance, 2017, 76, 133-152.

Akinci, Ozge and Albert Queralto, "Exchange rate dynamics and monetary spillovers with imperfect financial markets," The Review of Financial Studies, 10 2023, 37 (2), 309-355.

Gopinath, Gita, Emine Boz, Camila Casas, Federico Diez, Pierre-Olivier Gourinchas, and Mikkel Plagborg-Moller, "Dominant Currency Paradigm," NBER Working Paper, 2018, (22943).

Hoek, Jasper, Steve Kamin, and Emre Yoldas, "Are higher U.S. interest rates always bad news for emerging markets?" Journal of International Economics, 2022, 137, 103585