## Spillovers to Emerging Markets from US Economic News and Monetary Policy

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### Key findings on spillovers and transmission
- US economic news meaningfully affects financial conditions in emerging markets; effects occur immediately within two days of news releases.
- Strongest spillovers:
  - US employment news has the largest and most consistent effects.
  - US economic activity (retail sales, GDP, durable goods orders) and COVID-19 vaccine news have notable effects.
  - US inflation news has smaller effects on US financial conditions and therefore limited immediate spillovers to emerging markets.
- Typical immediate responses to better-than-expected US employment or activity:
  - Lowers credit spreads on US dollar-denominated emerging market government bonds.
  - Increases interest rates on local currency government bonds in emerging markets.
  - Better-than-expected employment news leads emerging market currencies to depreciate against the US dollar.
- Vaccine-news effects:
  - Lowered financial market volatility in the US and lowered credit spreads in emerging markets.
- Transmission channels — evidence summary:
  - Risk channel: most plausible for immediate transmission. Riskier emerging markets see larger credit-spread declines after positive US employment or durable goods orders news; relevant risk dimensions include external risks (external debt, currency volatility) and inflation risk.
  - Trade channel: limited evidence. Emerging market exchange rates react mainly to employment news; depreciation is smaller in EMs with deeper trade ties to the US (effect imprecisely estimated).
  - Portfolio-balance channel: no evidence. Spillovers are not stronger where EM bonds are more substitutable with US Treasuries or where financial ties to the US are deeper.
  - Monetary policy channel: mixed. Retail sales news affects EM short-term yields independently of US monetary policy expectations; employment news effects on long-term EM yields partly transmit via expectations of US monetary policy.

### Sample, measures, and identification
- Sample: 60 emerging markets between January 2000 and May 2020.
- US economic news covered: non-farm payroll employment, initial jobless insurance claims, retail sales, advance estimate for GDP, durable goods orders, core CPI inflation, core PPI inflation.
- Vaccine-news index: covers April 1, 2020 to final Phase III trial results (November 18 for Pfizer-BioNTech and November 30 for Moderna); index uses 57 days with a ±1 news event.
- Surprise construction:
  - Economic surprise = announced value − median prevailing expectation from a market survey.
  - Monetary policy surprise = change in US 2-year Treasury yields in narrow windows around FOMC announcements (5 minutes before to 15 minutes after).
- Core panel specification uses two-day event windows: y_{c,t+1} − y_{c,t−1} = α_c + ζ s_t + u_{c,t+1}, where s_t scaled by its standard deviation and ζ is response to a one-standard deviation surprise.
- Heterogeneity, time-variation, and controls:
  - Country characteristics x_{c,t} included via interactions η s_t x_{c,t}.
  - Time trends and step shifts (t ≥ Nov. 2008, t ≥ 2014) used to identify changes in sensitivity.
  - Extended specification controls for daily change in US 2-year yields r_t to isolate monetary-policy expectation channels.
- Identification: least squares estimation; Driscoll and Kraay (1998) standard errors for panels; Newey and West (1987) for time series.

### Domestic (US) effects of news and monetary policy — representative magnitudes
- One-standard deviation US employment surprise:
  - Appreciates the US dollar by 9.9 basis points against trading-partner currencies over one day.
  - Explains 18 percent of variation in 10-year Treasury yields among news types significant at the 5 percent level.
  - For US yields (selected): 3-month yield 0.9*** (0.34); 2-year term premia 3.8*** (0.68); 10-year expected rate 3.3*** (0.81); Stocks 9.9*** (2.54); VIX -0.7* (0.42).
- Vaccine news:
  - Explains 30 percent of variation in US stock returns and 8 percent of variation in 10-year Treasury yields.
  - Table entry: Vaccine news 10-year exp. rate 1.3** (0.62); Stocks 80.1*** (17.2); VIX -3.4*** (0.99).
- Monetary policy surprises (2-year Treasury instrument):
  - One-standard deviation surprise (5.4-basis points) raises US interest rates at all maturities; coefficient of 5.3 on 2-year Treasury yield matches scaling.
  - Every one-standard deviation tightening appreciates the US dollar by 18.4 basis points and lowers US stock prices by about 33 basis points (equivalently, a 1 percentage point tightening lowers stocks by 6.1 percent).
  - Monetary policy entry: 3-month yield 2.0*** (0.52); 2-year term premia 5.3*** (0.72); 10-year exp. rate 3.2*** (0.64); Stocks 18.4*** (4.49); VIX 1.7** (0.85).
- “Information effects” vs measurement error:
  - Conditional on stock-price reaction, monetary policy effects differ: when stocks move opposite to policy, conditional effects similar to unconditional; when stocks move with policy, effects on some variables differ (e.g., muted dollar/VIX responses).
  - Decomposition ζ = φ(1 − J_t) + λ J_t distinguishes “pure” policy surprises (φ) and announcements that reveal information or have measurement error (λ).

### Effects on emerging markets — average responses and magnitudes (two-day horizon)
- US employment surprises (one-standard deviation = 77,000 jobs):
  - EMBI (credit spreads on dollar-denominated EM bonds): −2.0*** (0.76) basis points.
  - 10-year US Treasury yield increases by 3.3 basis points; EM local-currency 10-year yield increases by 1.3 basis points → EM premium falls by 2 basis points.
  - EM currency depreciates by 4.9 basis points per standard deviation employment surprise.
- US retail sales and durable goods orders:
  - Retail sales: EMBI −2.3*** (0.76) basis points per standard deviation (61 basis points mom growth); raises EM stock prices and increases portfolio inflows (Inflows 25.7*** (8.48)).
  - Durable goods orders: EMBI −1.2 basis points per standard deviation (2.9 percentage points mom growth).
- Vaccine news:
  - EMBI −3.2*** (1.02); 1-year local yield −1.8*** (0.69); Inflows 9.1 (8.69); Stocks 0.7* (0.36).
  - Lowers EM credit spreads, increases capital inflows, and reduces local-currency yields at short and medium maturities.
- Monetary policy surprises (intradaily: one-standard deviation = 5.4-basis points):
  - EMBI +2.4* (1.26) basis points.
  - Local-currency yields rise across maturities: 1-year +2.3** (1.03); 10-year +3.4*** (1.11) basis points.
  - EM stock prices fall 40.9 basis points over two days per one-standard deviation surprise (equivalent to 7.5 percent fall per percentage point tightening).
  - EM currency depreciation: average EM currency depreciates 9.2 basis points per one-standard deviation tightening (equivalent to 1.7 percent per 100 basis point tightening); other reported estimate: 11.6 percent depreciation per percentage point surprise US tightening in an alternative calculation.
- Term premia vs expected rates in EMs:
  - In post-2016 13-country sample, a one-standard deviation (5.4-basis point) surprise increases 5-year EM rates by 5.9*** (1.04) basis points, with about two-thirds (4.2) via term premia and one-third via expected future policy rates in EMs.
- Historical/time variation:
  - Increased sensitivity of EM yields to US monetary policy driven by the global financial crisis and euro area crisis (2008-2013); sensitivity drops in 2014-2020 and is not significantly different from 2000-2008.
- Exchange rate regime:
  - No evidence that flexible exchange rate regimes insulate EMs from US monetary policy surprises in event-study evidence (both de jure and de facto classifications).
- Conditional (“information effects”) spillovers:
  - When US stock prices move opposite to US monetary policy, conditional EM responses are larger and more precise for credit spreads, exchange rates and stock prices.
  - When stocks move in the same direction as policy, EM interest-rate responses are smaller or absent; e.g., a one-standard deviation surprise increases 10-year EM yields by 4.2 basis points if US stocks fall, and by 1.1 basis points if US stocks rise.
  - Tests show low p-values for differences across these conditional responses for many EM financial variables.

### Country-level heterogeneity and channel amplifiers
- Risk channel amplifiers (effects on credit spreads in basis points; Table 5 excerpts):
  - Inflation: Employment -9.82**; Dur. goods orders -11.18*.
  - Exchange rate volatility: Employment -0.20***; Dur. goods orders -0.31**.
  - External debt to GDP: Employment -3.69**.
  - Composite risk rating: Employment -11.10**; Monetary policy 23.70*.
  - Vulnerability index: Employment -5.62**; Dur. goods orders -9.61**; Monetary policy 4.11.
- Trade and financial ties:
  - Trade ties to the US matter modestly for currency responses: Employment exchange rate effect -33.16*.
  - No robust evidence supporting a portfolio balance channel (no stronger spillovers where EM bonds are more substitutable for US Treasuries or with deeper financial ties to the US).

### Robustness checks and data coverage highlights
- Controlling for changes in US Treasury yields:
  - Retail sales effect on 1-year EM yield remains 0.9* (0.53) in alternate specs.
  - Employment effect on 10-year EM yield: 1.3** (0.55) and 0.9 (0.60) across specifications.
- Time-variation tests:
  - Interaction with time trend: Time trend coefficient 0.4** (0.17); Nov. 2008 onwards interaction 6.5** (2.90).
- Exchange-rate insulation tests (Table 8 excerpts):
  - De jure floating: Exch. rate 13.58**.
  - De facto flexibility (LYS): Exch. rate 3.62**.
- Data coverage (selected rows from Table 10 preserved exactly):
  - EMBI spread — Percent per year — 147,983 — 47 — 18.8 — 3.72 — 4.86 — -0.25 — 72.22
  - Yield, 10-year — Percent per year — 68,098 — 23 — 19.6 — 6.95 — 3.01 — 1.13 — 22.42
  - Exchange rate — Log of local currency price of USD — 249,937 — 60 — 19.7 — 3.11 — 2.57 — -3.44 — 10.69
- US news summary (Table 11 selected rows):
  - Employment — Hundreds of thousands of jobs — 223 — 1/7/2000 — 12/7/2018 — -0.16 — 0.77 — -3.28 — 2.08
  - Retail sales — Percentage change mom — 214 — 1/13/2000 — 12/14/2018 — -0.01 — 0.61 — -1.76 — 5.13
  - Monetary policy — Intradaily — Percent per year — 154 — 2/2/2000 — 12/13/2017 — -0.007 — 0.054 — -0.233 — 0.216
  - Vaccine news — Index -1 or 1 — 57 — 1/4/2020 — 12/15/2020 — 0.02 — 1.009 — -1 — 1

### Policy implications and research avenues
- Policy implications:
  - Rising US interest rates need not be adverse for emerging markets if driven by positive US economic news; however, surprise tightenings raise external financing premia through risk channels.
  - Lack of insulation from flexible exchange rates suggests frictions (for example foreign currency trade invoicing) that deserve further exploration.
  - News about US employment appears to preserve uncovered interest parity; positive surprises in US retail sales and GDP lower external financing premia in EMs.
- Suggested future research:
  - Examine persistence of effects beyond one to two days over months or quarters.
  - Explore frictions that limit exchange-rate insulation (trade invoicing in foreign currencies, central bank behavior).
  - Further intraday evidence to better distinguish direct economic-news channels from monetary-policy expectation channels.
  - Deeper analysis of measurement error versus information effects during crisis and stress periods.

*Source: IMF Working Paper — Spillovers to Emerging Markets from US Economic News and Monetary Policy (sections 1–5, analytical approach, domestic effects, effects on emerging markets, concluding remarks, appendix excerpts).*

### 1. INTRODUCTION ........................................................................................................

### 1. INTRODUCTION

### Key findings on spillovers from US economic news and monetary policy
- US economic news meaningfully affects financial conditions in emerging markets.
- Better-than-expected news about US employment or economic activity:
  - Immediately lowers credit spreads on US dollar-denominated bonds issued by emerging market governments.
  - Immediately increases interest rates on local currency government bonds in emerging markets.
  - Better-than-expected employment news leads emerging market currencies to depreciate against the US dollar.
- Positive news about the development of vaccines against the virus that causes COVID-19:
  - Lowered financial markets volatility in the US.
  - Lowered credit spreads in emerging markets.
- News about US inflation has smaller effects on financial conditions in the US and therefore does not immediately spill over to financial conditions in emerging markets.
  - Possible reasons: inflation surprises reflect a mixture of cost-push and demand-pull shocks pulling financial conditions in different directions; US inflation expectations may have been sufficiently anchored so shocks were too transitory to move markets.
- Transmission mechanism evidence:
  - Risk channel is more plausible than trade or portfolio-balance channels for immediate transmission.
    - Riskier emerging markets experience a deeper decline in credit spreads following better-than-expected US employment or durable goods orders.
    - The relevant risk dimensions include external risks (external debt, currency volatility) and inflation risk rather than fiscal risk.
  - Trade channel: limited evidence.
    - Emerging market exchange rates are affected only by news about US employment, not by other US economic activity or inflation news.
    - Better-than-expected US employment news depreciates currencies by less in emerging markets with deeper trade ties to the US, but this effect is imprecisely estimated.
  - Portfolio balance channel: no evidence.
    - No stronger credit-spread reactions in emerging markets with deeper financial ties to the US or whose government bonds move closely with US Treasuries.
- Distinguishing economic-news vs monetary-policy channels:
  - News about US retail sales affects emerging market short-term bond yields independently of effects on future US monetary policy (ruling out a monetary policy channel for retail sales news).
  - For US employment news, it is not possible to statistically distinguish how much of its effect on long-term emerging market bond yields works through expectations of monetary policy.
  - This suggests that prior findings of US interest rate spillovers on employment-release days may reflect employment news rather than monetary policy actions.
- New contributions on US monetary policy spillovers:
  - Increased sensitivity of emerging market bond yields to US monetary policy over time is driven primarily by the period of the global financial crisis and the euro area crisis, implying higher spillovers in financial crises rather than secular trends.
  - Domestic and international effects of US monetary policy depend on whether US stock prices move opposite to, or in the same direction as, monetary policy (consistent with “information effects”); these differential reactions appear in emerging markets’ interest rates, exchange rates, credit spreads, term premia and portfolio flows.
  - Alternative interpretation: reaction of emerging market interest rates may reflect measurement error correlated with economic stress conditions.
  - No evidence that flexible exchange rate regimes insulate emerging markets from US monetary policy surprises in high-frequency event studies.

### Sample and scope
- Sample includes 60 emerging markets, following IMF definitions, between January 2000 and May 2020.
- Study covers eight types of US economic news: non-farm payroll employment, initial jobless insurance claims, retail sales, the advance estimate for GDP, durable goods orders, core CPI inflation and core PPI inflation.
- Vaccine-news measure covers April 1, 2020 to final Phase III trial results (November 18 for Pfizer-BioNTech and November 30 for Moderna); index-based measure uses 57 days where a news event (+1 or -1) was observed.

### 2. ANALYTICAL APPROACH

### Identification of news events and construction of shocks
- US economic-surprise construction:
  - Surprise = announced value − median prevailing expectation from a market survey (Action Economics or Bloomberg the previous Friday).
  - US economic news surprises sourced from Gürkaynak et al. (2020).
- US monetary policy surprises:
  - Constructed as changes in yields on US Treasuries with a 2-year maturity in narrow windows around FOMC announcements.
  - Dataset from the updated dataset behind Gürkaynak et al. (2005).
  - High-frequency window for FOMC announcements: from 5 minutes before each announcement to 15 minutes afterward.
  - Choice of 2-year maturity follows Gertler and Karadi (2015) and Hanson and Stein (2015) to capture forward guidance and asset purchases.
- Vaccine-news index construction:
  - Derived from daily stock returns of Moderna and BioNTech regressed on MSCI US Healthcare Index returns.
  - For each company, daily residual coded as -1 (negative news) or 1 (positive news) if residual falls in bottom or top 10th percentiles of historical distribution, otherwise zero.
  - Overall daily vaccine news index = -1 or 1 if sum of the two companies’ news indices is negative or positive; otherwise zero.
- Event-day sample selection:
  - Regressions estimated only on days when news took place.
  - Event days: FOMC announcement days for monetary policy; release days for each economic indicator, excluding those coinciding with FOMC days.
  - For vaccine index, only 57 days with a ±1 news event are considered.

### Estimation framework
- Core panel specification (two-day event windows to accommodate time zones and trading hours):
  - y_{c,t+1} − y_{c,t−1} = α_c + ζ s_t + u_{c,t+1}
  - Dependent variable y_{c,t} represents various financial indicators on day t in emerging market c, including government bond yields at various maturities, exchange rates, total stock returns, portfolio flows, term premiums and expectations of future short-term monetary policy rates.
  - US economic news and monetary policy surprises s_t are scaled by their standard deviations; ζ is the response to a one-standard deviation increase in the news variable.
- Heterogeneity by country characteristics:
  - Extended model: y_{c,t+1} − y_{c,t−1} = α_c + ζ s_t + γ x_{c,t} + η s_t x_{c,t} + u_{c,t+1}
  - Controls for predetermined characteristics x_{c,t} are included to avoid omitted variable bias in η.
- Time-varying spillovers:
  - Linear trend: y_{c,t+1} − y_{c,t−1} = α_c + ζ s_t + θ τ_t + μ s_t τ_t + u_{c,t+1}, where τ_t denotes years elapsed since 2000.
  - Step shifts: specification with indicator functions for t ≥ Nov. 2008 and t ≥ 2014, and interaction terms with s_t to identify changes in sensitivity after those dates.
- Controlling for US interest-rate movements:
  - Extended model: y_{c,t+1} − y_{c,t−1} = α_c + ζ s_t + β r_t + v_{c,t+1}, where r_t is daily change in US 2-year Treasury yields.
  - Used to examine whether part of US economic news effects transmits through expectations about future US monetary policy.
- Simplified time-series model for US/global financial indicators (one-day event windows):
  - y_t − y_{t−1} = δ + χ s_t + e_{t+1}, where y_t represents US Treasury yields, US expected future policy rates and term premiums, the US dollar nominal effective exchange rate and the US VIX.
- Identification and inference:
  - Models estimated by least squares.
  - Identifying assumption: surprise s_t is uncorrelated with the error term (i.e., surprise captures the unexpected component of announcements and other contemporaneous releases or policy announcements are not correlated with s_t).
  - Standard errors: Driscoll and Kraay (1998) standard errors for panel models to allow for spatial and temporal dependence; Newey and West (1987) standard errors for time-series specifications.
- Decomposition for “information effects” of monetary policy:
  - Decompose ζ or χ into φ(1 − J_t) + λ J_t where J_t = 1 if the sign of the monetary policy surprise agrees with the sign of the change in the S&P500 index in narrow announcement windows, and zero otherwise.
  - φ measures effect of “pure” monetary policy surprises; λ measures effect when monetary policy announcements reveal information about future economic conditions or when measurement error is high (such as during crises).

*Source: IMF Working Paper — Spillovers to Emerging Markets from US Economic News and Monetary Policy (1. INTRODUCTION; 2. ANALYTICAL APPROACH).*

### 3. DOMESTIC EFFECTS OF US NEWS

### 3. DOMESTIC EFFECTS OF US NEWS

### Overview and approach
- Objective: Benchmark domestic effects of US economic news, COVID-19 vaccine news, and US monetary policy on US financial conditions to inform later analysis of spillovers to emerging markets.
- Event-window choice: one-day windows for dependent variables to match two-day windows used for emerging markets and to permit decomposition of yield effects into term premia and expected future short-term interest rate components.

### 3.1 Domestic effects of news about the US economy and vaccines
- General finding: Good news about labour market conditions, retail sales, economic activity (GDP), COVID-19 vaccines, and higher-than-expected inflation all lift US nominal interest rates.
- Yield-curve decomposition:
  - Positive employment news and higher-than-expected CPI inflation lift interest rates mainly by increasing expectations of future monetary policy tightening (expected future short-term interest rates).
  - Positive news about US economic activity (GDP) and higher-than-expected PPI inflation lift interest rates mainly by increasing the term premium embedded in longer-term yields.
  - Jobless claims and retail sales affect both components, with slightly more weight on expected future monetary policy.
- Magnitudes and explanatory power:
  - A one-standard deviation surprise increase in US employment appreciates the US dollar by 9.9 basis points against trading-partner currencies over one day.
  - For 10-year Treasury yields, among news types significant at the 5 percent level:
    - Employment news explains 18 percent of variation.
    - Core PPI inflation explains 3.4 percent of variation.
  - Vaccine news explains 30 percent of the variation in stock returns and 8 percent of the variation in 10-year Treasury yields.
- Stock prices:
  - US stock prices do not respond clearly to labour market, economic activity, or inflation news; they tentatively increase after positive retail sales and durable goods orders (one-standard deviation surprises raise the S&P500 by 19 and 13 basis points, respectively; both significant at the 10 percent level).
  - Vaccine news during the pandemic tended to lift US stock prices without lifting medium-term interest rates (up to 5-year maturity) or expected future short-term interest rates.

### 3.2 Domestic effects of news about US monetary policy
- Monetary policy surprises (using the 2-year Treasury yield as the instrument):
  - Positive monetary policy surprises lift US interest rates at all maturities.
  - The coefficient of 5.3 on the 2-year Treasury yield matches the standard deviation of monetary policy surprises in the chosen scaling.
  - The rise in long-term rates works through expectations of future monetary policy tightenings rather than increases in term premia.
- Exchange rate and stock responses:
  - Every one-standard deviation monetary policy tightening leads the US dollar to appreciate over one day by 18.4 basis points.
  - Equivalently, every 100-basis point monetary policy tightening appreciates the US dollar by 3.4 percent.
  - Every one-standard deviation monetary policy tightening (about 5.4 basis points) leads US stock prices to fall by about 33 basis points over a day.
  - Equivalently, every 1 percentage point tightening leads stock prices to fall by 6.1 percent.
  - Comparable estimate: S&P500 result is similar at 31.9 basis points.

### 3.3 Domestic “information effects” of US monetary policy
- Conditional effects by stock-price reaction:
  - When monetary policy and stock prices move in different directions, effects of US monetary policy are close to unconditional effects.
  - When stocks move in the same direction as monetary policy:
    - US monetary policy has slightly stronger effects on US interest rates (driven more by expected future short-term interest rates than term premia), though increases in sensitivities are not statistically significant.
    - A one-standard deviation (5.4-basis point) surprise increase in the 2-year Treasury yield leads to a 2.9-basis point increase in 10-year yields if stock prices fall, and a 3.9-basis point increase if stock prices rise.
    - These magnitudes are described as equivalent to increases of 57 and 78 basis points, respectively, per percentage point US monetary tightening, after correcting for rounding.
    - When stocks move in the same direction as monetary policy, there is no statistically significant effect on the US dollar or the VIX.
  - Statistical significance: the difference in sensitivities is statistically significant for the US dollar and only marginally significant for the VIX.
- Interpretations:
  - “Information effects” interpretation: the Fed’s announcements reveal information about the economic outlook; positive-information tightenings may raise interest rates and lower the VIX, offsetting the VIX-increasing effect of tightenings.
  - Measurement-error interpretation: monetary policy surprises or stock-price surprises may be poorly measured on some days, with mismeasurement correlated with periods of economic stress; this could make monetary policy appear more effective at influencing interest rates during stress and explains muted dollar/VIX responses when stocks rise with tightenings.
- Robustness and novelty:
  - Results for the 10-year Treasury and stock prices are within one-and-a-half standard deviations of Hoek et al. (2022).
  - Results for 3-month and 2-year yields, term premia, expected future short-term interest rates, the US dollar index and the VIX appear to be new contributions.

### 3.4 US news, risk premia, and volatility
- Equity risk premium on announcement days:
  - The estimated intercept (δ) is highest for monetary policy surprises and implies a 28.6 basis point daily return on US stocks on monetary policy announcement days (standard error 11.8; statistically significant at the 5 percent level).
  - The intercept for jobless claims is 6.9 basis points (standard error 4.1; statistically significant at the 10 percent level).
  - Intercepts are not statistically significant for other macroeconomic news types.
- VIX and risk perceptions:
  - Good news about US employment, retail sales, and vaccines tend to reduce the VIX.
  - Surprise monetary policy tightenings tend to raise the VIX.
  - Every one-standard deviation US monetary policy tightening (a 5.4 basis point increase in 2-year Treasury yields) increases the VIX by 1.7 percent over a day.
  - Intercepts (δ) from equation (6) suggest risk perceptions or risk aversion tend to fall on announcement days:
    - Employment announcement days: intercept -1.8 percent (standard error 0.47; significant at the 1 percent level).
    - Monetary policy announcement days: intercept -2.4 percent (standard error 0.47; significant at the 1 percent level).

*IMF Working Paper — 3. DOMESTIC EFFECTS OF US NEWS*

### 4. EFFECTS OF US NEWS ON EMERGING

### 4. EFFECTS OF US NEWS ON EMERGING MARKETS

### Overview
- Section split: Section 4.1 analyses effects of US economic news; Section 4.2 analyses effects of US monetary policy.
- US employment news has strong spillover effects to emerging markets; US inflation news has limited effects.
- US news affects investor risk perceptions via the VIX, and spillovers vary across emerging markets consistent with a risk channel.
- Rising spillovers over time identified in prior work are linked to the global financial and euro area crisis period.
- No clear evidence that flexible exchange rate regimes insulate emerging economies from US monetary policy surprises.
- US monetary policy spillovers to emerging markets depend on the direction of comovement of US monetary policy with the US stock market.

### 4.1. Effects of US economic news on emerging markets

#### 4.1.1. Effects on the average emerging market
- Employment news
  - Positive US employment surprises lower credit spreads on dollar-denominated emerging market government bonds.
  - Magnitude: a 2-basis point fall in credit spreads over two days for each standard deviation (77,000-job) surprise increase in employment.
  - Positive employment news lifts US interest rates; emerging market credit spreads fall implying emerging market dollar bond yields rise less than one-for-one with US interest rates.
  - Positive employment news also:
    - Lifts yields on long-term local currency government bonds in emerging markets by 1.3 basis points per standard deviation.
    - Depreciates emerging market currencies against the US dollar by 4.9 basis points per standard deviation.
  - Jobless claims do not affect local currency interest rates in the full sample but do in the post-2016 period through the term premium component, suggesting emerging market monetary policy is not expected to offset US news.
  - Emerging market stock prices do not clearly respond to US labour market news.

- Uncovered interest parity consistency
  - On a one-standard deviation US employment surprise: local currency 10-year EM yields increase by 1.3 basis points while 10-year US Treasury yields increase by 3.3 basis points → EM premium falls by 2 basis points.
  - Concurrent EM currency depreciation reduces expected future depreciation, consistent with uncovered interest parity.

- US economic activity (retail sales, GDP, durable goods orders)
  - Positive US retail sales and durable goods orders lower EM credit spreads:
    - Retail sales: 2.3 basis point fall in credit spreads over two days per standard deviation surprise (61 basis points higher month-on-month growth).
    - Durable goods orders: 1.2 basis point fall per standard deviation surprise (2.9 percentage points higher month-on-month growth).
  - Limited effects on local currency government bond yields, except slight effect of retail sales on short-term yields (significant only at the 10 percent level).
  - In post-2016 subsample (13 economies), 5-year yields respond more strongly, with good US news lifting EM interest rates via term premia—suggesting EM monetary policy does not adjust in that period for these countries.
  - Good US retail sales news lifts EM stock prices more than US stock prices:
    - Magnitude: 25.7-basis point increase in EM stock prices over two days per standard deviation surprise in US retail sales.
  - US GDP news:
    - A one-standard deviation (65 basis points higher quarter-on-quarter annualized growth) surprise increase in US GDP leads to portfolio capital flows out of emerging markets by 1.4 basis points of annual GDP over two days.

- Vaccine news
  - Positive vaccine news lowers EM credit spreads, increases capital inflows, and reduces yields on local currency bonds (maturities 1 and 5 years).
  - No clear effect on EM currencies against the US dollar or on EM stock prices.
  - Overall financial conditions in EM ease; capital inflows likely reflect falling risk perceptions (VIX) and lack of short-term US rate reaction.

#### 4.1.2. Transmission channels: risk, trade, portfolio balance, and monetary policy
- Risk channel
  - Evidence that some US economic news effects are stronger for riskier EMs: riskier EMs experience stronger declines in credit spreads after positive US employment or durable goods orders news.
  - Relevant risk measures for employment news include: inflation, exchange rate volatility, external debt, short-term debt relative to reserves, composite risk rating, and a vulnerability index (combining current account deficits, government debt, inflation, credit growth, short-term external debt and international reserves).
  - For durable goods orders, credit growth matters; external debt and risk rating lose significance.
  - Common risk measures across employment and durable goods news: inflation, exchange rate volatility, vulnerability index.
  - Responses of 10-year local currency bond yields do not show a clear relationship to risk as credit spreads do.
  - Conclusion: US economic news transmits internationally at least partly through effects on investors’ risk perceptions or risk aversion.

- Portfolio balance channel
  - Tested substitutability between EM bonds and US Treasuries (correlation of total US dollar returns) and financial links to the US (bilateral asset/liability positions).
  - No evidence that spillovers from US economic news are stronger where EM bonds are more substitutable with US Treasuries or where financial ties to the US are deeper.
  - Conclusion: no support for a portfolio balance channel in transmission of US economic news to EMs.

- Trade channel
  - Positive US employment news depreciations are weaker in EMs with stronger trade ties to the US, suggesting a greater increase in external demand in those countries.
  - Reduction in EM credit spreads is stronger in countries with deeper trade ties to the US (statistically significant at the 5 percent level).
  - However, EMs with more trade with the US do not experience relatively larger increases in interest rates, contradicting a clear trade-driven interest-rate rise.
  - Conclusion: only tentative evidence for a trade channel.

- Monetary policy expectations channel
  - Estimated equation controlling for changes in 2-year Treasury yields to separate direct US news effects from indirect effects via US monetary policy.
  - Findings:
    - Retail sales news: same effect on short-term EM yields whether or not 2-year Treasury yields are held constant → spillover from US retail sales to EM interest rates does not transmit through expectations of US monetary policy.
    - Employment news: effect on long-term EM yields reduces by about one-third and loses statistical significance when controlling for 2-year Treasury yields → some spillover of US employment news transmits through its effects on US monetary policy.
  - Ambiguity remains: amounts attributable to direct vs. indirect effects are unclear due to lack of statistical significance in some specifications; further intraday evidence needed.

### 4.2. Effects of US monetary policy surprises on emerging markets

#### 4.2.1. Effects on the average emerging market
- Context and contributions
  - Use of intraday US monetary policy surprises and daily EM data, large refined sample of EMs, and comprehensive EM financial conditions coverage.
  - Two modest contributions:
    - Increasing sensitivity over time identified by prior work is linked to the global financial and euro area crisis period and ends around 2014.
    - Lack of evidence that flexible exchange rates insulate EMs from US monetary policy surprises.

- Spillovers to EM bond yields and credit spreads
  - A one standard deviation US monetary policy surprise is defined as a 5.4-basis point increase in 2-year Treasury yields in narrow windows around announcement times.
  - Effects:
    - Raises credit spreads on dollar-denominated EM bonds by 2.4 basis points over two days per one standard deviation surprise.
    - Local currency EM government bond yields rise across maturities, from 2.3 basis points at 1-year to 3.3 basis points at 10-year maturity per one standard deviation surprise.
    - The 10-year sensitivity is equivalent to a 61-basis point increase in 10-year EM interest rates for every percentage point tightening in US monetary policy (after correcting for rounding).
  - Historical variation:
    - Sensitivity increased after the global financial crisis; Hoek et al. (2022) find a higher sensitivity of 89 basis points on 2010-2019 sample.
  - Daily US monetary policy surprises produce smaller spillovers:
    - Insignificant effect on credit spreads.
    - A 1-percentage point tightening leads to a 36-basis point rise in EM interest rates (equivalent to coefficient of 2.6 on daily surprises corrected for rounding).
    - This 36-basis point sensitivity is within one standard error of the 29 basis points reported in Albagli et al. (2019).

- Term premia vs. expected future short-term rates
  - Table 4 decomposition (13-country post-2016 sample):
    - One standard deviation (5.4-basis point) surprise US monetary tightening → 2.6-basis point increase in 5-year EM rates in full sample; 5.9-basis point increase in post-2016 13-country sample.
    - In the post-2016 13-country sample, about two-thirds (4.2 out of 5.9) of the effect on 5-year EM rates transmits through term premiums.
    - Remaining one-third transmits through expected future monetary policy rates in EMs, suggesting markets anticipate some fear-of-floating behaviour in the average EM, even since 2016.

- Exchange rates
  - Surprise US monetary tightening leads the US dollar to appreciate trade-weighted; EM currencies depreciate against the US dollar.
  - Average EM currency depreciates 9.2 basis points for every one-standard deviation tightening, equivalent to a 1.7 percent depreciation per 100 basis point tightening.
  - Comparable magnitudes: US trade-weighted dollar appreciation 3.4 percent; similar findings in Bowman et al. (2015) and Hausman and Wongswan (2011).
  - Daily surprises estimate: EM depreciation of 7.5 basis points per standard deviation US monetary tightening.
  - Effect on EM exchange rates is imprecisely estimated; statistically significant only at the 10 percent level.

*IMF Working Paper — 4. EFFECTS OF US NEWS ON EMERGING MARKETS (chapter excerpt)*

### 11.6 percent depreciation of emerging market currencies per percentage point surprise US monetary

### 11.6 percent depreciation of emerging market currencies per percentage point surprise US monetary tightening

### Direct effects on exchange rates, yields, and credit premia
- A surprise US monetary policy tightening is associated with emerging market currency depreciation; one reported estimate is 11.6 percent depreciation of emerging market currencies per percentage point surprise US monetary tightening.
- Both emerging market and US local currency 10-year government bond yields increase by 3.3 basis points in response to a one-standard deviation US monetary policy surprise.
- Emerging market credit spreads on dollar-denominated bonds increase in response to a surprise US monetary policy tightening, indicating rising external premia due to perceptions of higher risk.
- Since emerging market currencies depreciate on the same news, the unchanged premia on 10-year local currency bond yields combined with depreciation reduces expectations of future depreciation.

### Equity market responses
- Emerging market stock prices fall 40.9 basis points over two days for every one-standard deviation (5.4 basis point) surprise US monetary policy tightening.
- This fall is equivalent to a 7.5 percent stock price fall per percentage point tightening.
- The 7.5 percent estimate is within one standard deviation of the 9.6 percent fall reported in Hoek et al. (2022).

### Transmission channels: risk and portfolio balance
- Surprise US monetary policy tightenings raise credit spreads by more in emerging markets with higher composite risk ratings (composite risk rating = International Country Risk Guide rating multiplied by -1 so higher values mean more risk).
- Evidence of stronger US monetary policy effects in riskier emerging markets is found mainly for credit spreads and is driven by the composite risk rating; unreported sub-indices indicate the heterogeneous effect of US employment news is driven by “economic risk”, while the heterogeneous effect of US monetary policy is driven by “political risk”.
- No statistically significant role for credit ratings is found in explaining cross-section spillovers to emerging market credit spreads in the full sample.
- No evidence is found for stronger effects of US monetary policy on credit spreads in emerging markets whose bonds are more substitutable for US Treasuries, or which have stronger financial links to the US (i.e., limited evidence for a portfolio balance channel).

### Time-varying spillovers
- Sensitivity of local currency emerging market 10-year government bond yields to US monetary policy surprises has increased over time using a linear time trend.
- When allowing the trend to vary across episodes, sensitivity increases between the 2000-2008 period and the 2008-2013 period, then the point estimate drops in the 2014-2020 period.
- A Wald test shows the sensitivity in the 2014-2020 period is not significantly different from the sensitivity in the 2000-2008 period, implying the upward linear trend is driven by the 2008-2013 period.
- The increase in sensitivity coincides with the global financial crisis and eurozone debt crisis, suggesting higher spillovers in crisis-related periods rather than a secular trend.

### Role of emerging market currency regime
- Event-study evidence shows the spillover of US monetary policy to emerging markets is no stronger in less flexible exchange rate regimes than in more flexible regimes, for both de facto and de jure classifications.
- Two exchange rate classification systems validate by reflecting larger currency depreciation in emerging markets with less flexible exchange rate regimes.
- The lack of insulation from flexible exchange rates may reflect prevalence of trade invoicing in foreign currencies and possible central bank behavior (e.g., inflation-targeting central banks adjusting policy rates to limit exchange rate volatility).

### Conditional (“information effects”) spillovers related to US stock price movements
- When US stock prices move in the opposite direction to US monetary policy (e.g., stock prices fall with a tightening), the conditional effects on emerging market financial conditions are in the same directions as unconditional effects and are larger (in absolute value) and more precisely estimated, especially for credit spreads, exchange rates and stock prices.
- When US stock prices move in the same direction as US monetary policy (e.g., stock prices rise with a tightening), there is limited evidence that emerging market interest rates respond to US monetary policy surprises:
  - A one standard deviation (5.4-basis point) US monetary policy surprise increases 10-year interest rates in emerging markets by 4.2 basis points if US stock prices fall on the monetary policy announcement, and by 1.1 basis points if US stock prices rise.
  - These magnitudes are equivalent to 77 and 21 basis points per 100-basis point monetary policy tightening, respectively.
  - Restricting to the 17 emerging markets and 2010-2019 sample used in Hoek et al. (2022) yields larger estimates of 136 and 39 (with standard errors of 31.0 and 18.4; statistically significant at the 1 and 5 percent levels).
- No evidence of any reaction of emerging market credit spreads, term premia, expected future policy rates, exchange rates against the US dollar, stock prices or portfolio flows when US stock prices move in the same direction as US monetary policy.
- Low p-values on tests indicate emerging market credit spreads, interest rates, term premia, exchange rates and stock prices respond significantly differently depending on whether US stock prices move opposite to, or the same direction as, US monetary policy.

### Interpretation of conditional findings
- Results can be interpreted as attenuation bias from measurement error related to economic stress, or as “information effects”:
  - Measurement error interpretation: lack of reaction when US stock prices move with policy could reflect attenuation bias.
  - Information effects interpretation: if a US monetary tightening coincides with US stock price rises, that may convey positive information about the economic outlook that lowers risk perceptions and offsets tightening effects—consistent with null responses in many emerging market financial variables.
- The information effects interpretation is harder to reconcile with interest rate responses: if tightening reveals good US news, it should lift emerging market interest rates even more, but clear evidence for this is not found.

*IMF Working Paper excerpt.*

### 5. CONCLUDING REMARKS

### 5. CONCLUDING REMARKS

### Main findings on transmission of US news to emerging markets
- Economic news in the United States, not just monetary policy, affects financial conditions in emerging markets; effects are felt immediately, within two days of the news release.
- News about employment has the strongest effects, followed by news about economic activity and COVID-19 vaccines; news about inflation has limited effects on average.
- Financial conditions in the US and emerging markets respond differently to US monetary policy surprises, depending on the reaction of US stock prices. The paper offers both an “information effects” interpretation and a new interpretation in terms of measurement error correlated with times of economic stress.
- A key transmission channel is international investors’ risk perceptions / risk aversion:
  - US employment, economic activity and monetary policy news influence the VIX.
  - Effects on emerging market interest rates mainly operate through term premia (compensation for the risk of holding longer-term bonds) rather than expectations of future monetary policy.
  - These news types exert stronger effects on the credit spreads of riskier emerging economies.
- Distinction: US monetary policy acts on domestic US interest rates through expected future monetary policy, but on emerging market interest rates through term premia.
- News about the US economy and monetary policy is an important fundamental risk factor in pricing emerging market assets and may have predictable relationships with risk premia.
- Rising US interest rates can have benign implications for emerging markets if driven by good US economic news.
- News about US employment seems to preserve uncovered interest parity.
- Positive surprises in US retail sales and GDP lower external financing premia in emerging markets; surprise US monetary policy tightenings raise external financing premia. Both moves in external premia appear related to risk.
- No significant evidence found for insulation coming from flexible exchange rates, highlighting the importance of frictions (for example foreign currency trade invoicing) to be explored in future work.
- Effects persist over a day for US financial conditions and over two days for emerging markets; further research should examine persistence over several months or quarters.

### Representative quantitative effects (one-standard deviation surprise)
- Selected US effects on US financial conditions (Table 1; coefficient entries and Newey and West (1987) standard errors in parentheses; stars denote significance):
  - Employment: 3-month yield 0.9*** (0.34); 2-year term prem. 3.8*** (0.68); 10-year exp. rate 3.3*** (0.81); Stocks 9.9*** (2.54); VIX -0.7* (0.42).
  - Jobless claims: 3-month yield -0.5** (0.22); 10-year exp. rate -1.1*** (0.24); Stocks -0.7*** (0.17).
  - Retail sales: 3-month yield 0.6*** (0.19); 2-year term prem. 1.6*** (0.41); 10-year exp. rate 1.9*** (0.48); Stocks 1.0*** (0.22); VIX -0.8** (0.41).
  - Vaccine news: 10-year exp. rate 1.3** (0.62); Stocks 80.1*** (17.2); VIX -3.4*** (0.99).
  - Monetary policy: 3-month yield 2.0*** (0.52); 2-year term prem. 5.3*** (0.72); 10-year exp. rate 3.2*** (0.64); Stocks 18.4*** (4.49); VIX 1.7** (0.85).

- US monetary policy effects conditional on US stock response (Table 2; Newey and West (1987) standard errors in parentheses):
  - Given that stocks move in the opposite direction to monetary policy: 3-month yield 1.8*** (0.67); term prem. 5.0*** (0.59); exp. rate 2.9*** (0.85); Stocks 23.7*** (5.74); Daily intradaily Stocks -43.6*** (4.43).
  - Given that stocks move in the same direction as monetary policy: 3-month yield 2.7*** (0.75); term prem. 6.1*** (1.16); exp. rate 3.9*** (0.79); Stocks 4.4 (6.33); Daily intradaily Stocks 35.3*** (11.12).
  - Test of equal coefficients p-values include: VIX 0.02; Stocks (intradaily) < 0.01; Stocks (daily) < 0.01.

- Effects on emerging markets (two-day horizon; Driscoll and Kraay (1998) standard errors in parentheses; Table 3):
  - Employment: EMBI -2.0*** (0.76); 1-year yield 0.6 (0.46); Stocks 4.9** (2.34).
  - Retail sales: EMBI -2.3*** (0.76); 1-year yield 0.9* (0.53); Inflows 25.7*** (8.48).
  - Vaccine news: EMBI -3.2*** (1.02); 1-year yield -1.8*** (0.69); 1-year term prem. -0.9 (0.65); Inflows 9.1 (8.69); Stocks 0.7* (0.36).
  - Intradaily monetary policy: EMBI 2.4* (1.26); 1-year yield 2.3** (1.03); 10-year yield 3.4*** (1.11); Stocks 9.2* (4.87); Term prem. -40.9*** (15.48).

- Effects on 5-year emerging market interest rates and term premia (Table 4; Driscoll and Kraay (1998) standard errors in parentheses):
  - From 2016, 21 EMs: Retail sales term prem. 3.3** (1.51); GDP term prem. 0.9* (0.53); Monetary policy intradaily term prem. 3.1** (1.20); Monetary policy daily term prem. 4.5*** (1.30).
  - From 2016, 13 EMs (term prem. and expected rate decomposition): Monetary policy intradaily term prem. 5.9*** (1.04); Monetary policy daily term prem. 6.5*** (0.96).

### Country-level amplifiers and channels (Table 5)
- Risk channel (effects on credit spreads in basis points):
  - Credit growth: Employment -0.02; Dur. goods orders -0.05*; Monetary policy 0.02.
  - Inflation: Employment -9.82**; Dur. goods orders -11.18*; Monetary policy 1.45.
  - Exchange rate volatility: Employment -0.20***; Dur. goods orders -0.31**; Monetary policy 0.06.
  - External debt to GDP: Employment -3.69**; Dur. goods orders 0.51; Monetary policy -4.74.
  - Short-term external debt to reserves: Employment -1.70*; Dur. goods orders -1.31; Monetary policy 1.14.
  - Composite risk rating: Employment -11.10**; Monetary policy 23.70*.
  - Vulnerability index: Employment -5.62**; Dur. goods orders -9.61**; Monetary policy 4.11.
- Portfolio balance channel and trade channel:
  - Financial ties to the U.S.: Employment 11.35*.
  - Trade ties to the U.S.: Employment exchange rate effect -33.16*.

### Robustness and additional tests
- Controlling for changes in U.S. Treasury yields (Table 6; Driscoll and Kraay (1998) standard errors in parentheses):
  - Retail sales effect on 1-year EM yield: 0.9* (0.53) and 1.0* (0.60) in alternate specifications.
  - Employment effect on 10-year EM yield: 1.3** (0.55) and 0.9 (0.60) in alternate specifications.
  - Interest rate control: -1.1 (10.68) for 1-year; 11.3 (7.89) for 10-year.

- Time variation in monetary policy spillovers (Table 7; Driscoll and Kraay (1998) standard errors):
  - Interaction with time trend: Time trend coefficient 0.4** (0.17).
  - Nov. 2008 onwards interaction: 6.5** (2.90).
  - Chi-squared statistic 2.2; Chi-squared p-value 0.14.

- Exchange rate insulation puzzle (Table 8; Driscoll and Kraay (1998) standard errors):
  - De jure floating: Yield 2.75; Exch. rate 13.58**.
  - Free vs. managed float: Yield 0.77; Exch. rate 7.59.
  - De facto flexibility (LYS): Yield -1.08; Exch. rate 3.62**.

- US monetary policy effects on emerging markets conditional on US stock response (Table 9; Driscoll and Kraay (1998) standard errors):
  - Given stocks move opposite to monetary policy: EMBI 3.7*** (0.63); 1-year yield 3.4*** (0.97); 10-year yield 4.4*** (1.00); Term prem. 13.9*** (2.04); Term prem. (5-year) -57.1*** (6.06).
  - Given stocks move same direction as monetary policy: EMBI -1.0 (0.74); 1-year yield -0.3 (0.72); 10-year yield 1.2 (0.75); Term prem. -3.0 (2.07).
  - Tests of equal coefficients show many p-values < 0.01 for differences.

### Policy implications and avenues for future work
- Policy implication: Rising US interest rates need not be adverse for emerging markets if driven by positive US economic news; however, surprise tightenings raise external financing premia through risk channels.
- The absence of significant insulation from flexible exchange rates suggests the importance of frictions (for example foreign currency trade invoicing); these frictions should be explored in future work.
- Persistence: effects shown over one to two days may matter for agents making longer-horizon decisions; future research should examine persistence over several months or quarters.
- The paper’s estimates can serve as benchmarks for further investigation into the pricing of emerging market assets and the role of US news as a fundamental risk factor.

*Source: IMF Working Paper — "Spillovers to Emerging Markets from US Economic News and Monetary Policy", 5. CONCLUDING REMARKS.*

### REFERENCES

### REFERENCES

### Scholarly citations and working papers
- Extensive bibliography on monetary policy, international spillovers, and asset-price responses, including (but not limited to) works by:
  - Adrian, T., Crump, R.K. and Moench, E. (2013)
  - Ahmed, S., Coulibaly, B., and Zlate, A. (2017)
  - Aizenman, J., Binici, M. and Hutchison, M.M. (2016)
  - Albagli, E., Ceballos, L., Claro, S. and D. Romero (2019)
  - Andersen, T. G., Bollerslev, T., Diebold, F. X., and C. Vega (2003)
  - Bauer, M. D., and C. J. Neely (2014)
  - Bauer, M.D. and Swanson, E.T. (2020)
  - Bluwstein, K. and Canova, F. (2018)
  - Borio, C. and Zhu, H. (2012)
  - Bruno, V. and Shin, H.S. (2015)
  - Calvo, G. A., and C. M. Reinhart (2002)
  - Campbell, J.Y. and Vuolteenaho, T. (2004)
  - Cenesizoglu, T. and Essid, B. (2012)
  - Corsetti, G., Keuster, K., Müller, G.J. and Schmidt, S. (2021)
  - Curcuru, S. E., Kamin, S. B., Li, C., and Rodriguez, M. (2018)
  - Driscoll, J. C., and Kraay, A. C. (1998)
  - Ehrmann, M., and M. Fratzscher (2004)
  - Faust, J., Rogers, J.H., Wang, S.Y.B. and Wright, J.H. (2007)
  - Fleming, M.J. and Remolona, E.M. (1999)
  - Gagnon, J., Raskin, M., Remache, J. and Sack, B. (2018)
  - Gertler, M., and P. Karadi (2015)
  - Gilchrist, S., Yue, V., and E. Zakrajšek (2019)
  - Gopinath, G., Boz, E., Casas, C., Díez, F. J., Gourinchas, P. and M. Plagborg-Møller (2020)
  - Gürkaynak, R.S., Sack, B. and Swanson, E. (2005)
  - Gürkaynak, R. S., Kisacikoğlu, B., and Wright, J. H. (2020)
  - Hanson, S. G., and J. C. Stein
  - Hausman, J., and J. Wongswan (2011)
  - Hess, Patrick J., and Bong-Soo Lee (1999)
  - Hoek, J., Kamin, S. B., and Yoldas, E. (2020)
  - Hoek, J., Kamin, S. and Yoldas, E. (2022)
  - Iacoviello, M., and G. Navarro (2019)
  - Ilzetzki, E., Reinhart, C. M., and Rogoff, K. S. (2019)
  - Kalemli-Özcan, Ṣebnem (2019)
  - Jarociński, M. and Karadi, P. (2020)
  - Levy-Yeyati, E., and Sturzenegger, F. (2003)
  - Miranda-Agrippino, S. and Rey, H. (2020)
  - Nakamura, E. and Steinsson, J. (2018)
  - Neely, C.J. (2015)
  - Pavel S. and M. Wilson (2014)
  - Rigobon, R. and Sack, B. (2008)
  - Rogers, J.H., Scotti, C. and Wright, J.H. (2014)
  - Romer, C.D. and Romer, D.H. (2000)

(References list preserved as in source; specific bibliographic details and journal citations are included above in the original ordering and wording.)

*IMF WORKING PAPERS — Spillovers to Emerging Markets from US Economic News and Monetary Policy*

### APPENDIX

### Data sources and construction — Key points
- US economic news: eight types as used in Gürkaynak, Kısacıkoğlu and Wright (2020):
  - Non-farm payroll employment (monthly)
  - Initial jobless insurance claims (weekly)
  - Retail sales (monthly)
  - Advance estimate for GDP (quarterly)
  - Durable goods orders (monthly)
  - Core CPI inflation (monthly)
  - Core PPI inflation (monthly)
- Sample: 60 emerging markets. Selection process:
  - Start from IMF’s 97 emerging market definitions (neither advanced economies nor low-income developing countries).
  - Drop: offshore financial centres; countries without their own currency; countries undergoing hyperinflation or crises; countries on IMF’s list of fragile states; countries with population less than 1 million; countries with GDP less than US$ 10 billion in 2019.
  - Resulting economies listed explicitly (60 countries).
- Claim: “To the best of our knowledge, this is the largest sample of emerging markets used to study spillovers from US monetary policy news to emerging markets (and the only sample used so far to study spillovers from other types of US economic news to emerging markets).”
- Comparison to prior studies: Hausman and Wongswan (2011), Bowman et al. (2015), Albagli et al. (2019), Hoek et al. (2022), Gilchrist et al. (2019) — noting differing country compositions and counts.

### Financial and macro data sources (emerging markets)
- Nominal, local-currency, emerging market government bond yields:
  - Haver Analytics (primarily official sources if available; otherwise Tullett Prebon; otherwise Reuters).
  - Yield series can be a mixture of yields to maturity and zero-coupon yields.
- Government bond total return indices and EMBI spreads: JP Morgan Markets.
- MSCI total stock return indices and BNP Paribas 5-year EM term premiums: Bloomberg (term premium follows methodology of Adrian et al. (2013)).
- Emerging market exchange rates vs US dollar: IMF’s Global Data Source database if available; otherwise official sources via Haver.
- Daily portfolio flows: Institute of International Finance (aggregate equity and debt flows, as available).

### US financial conditions data definitions
- US Treasury yields: constant maturity spot yields.
- Decomposition of US interest rates into term premia and expected future policy rates: Federal Reserve Bank of New York (methodology of Adrian et al. (2013)).
- US stock prices: Wilshire 5000 total return index and S&P500 stock price index via Haver.
- US dollar index: trade-weighted nominal effective exchange rate from IMF’s Global Data Source.
- VIX: based on the S&P500, calculated by Chicago Board Options Exchange, provided by Haver.

### Heterogeneity measures across emerging markets — data sources
- Private sector credit: World Bank’s Global Financial Development Database.
- Inflation and current account balance: IMF’s World Economic Outlook database.
- External debt to GDP and short-term debt to reserves: World Bank’s World Development Indicators.
- Composite risk rating: International Country Risk Guide.
- Total returns on emerging market bonds: JP Morgan GBI-EM indices.
- Total returns on US Treasuries: JP Morgan broad index.
- Financial ties to the US: averages of bilateral asset claims against the US and liability obligations to the US, in percent of emerging market GDP — sources: IMF’s Coordinated Direct and Portfolio Investment Surveys and BIS’ Locational Banking Statistics (LBS). In LBS, claims and obligations are taken as reported by the US.
- Trade ties to the US: IMF’s Direction of Trade Statistics.
- De jure exchange rate regimes: IMF’s Annual Report on Exchange Arrangements and Exchange Restrictions.
- De facto exchange rate regimes: Ilzetski, Reinhart and Rogoff (2018), and Levy-Yeyati and Sturzenegger (2016), as specified.

### Table 10 — Coverage and variation of emerging market financial condition variables
- Table header: Variable | Units | Obs. | Countries | Years | Mean | Std. dev. | Min. | Max.
- Selected rows preserved exactly:
  - EMBI spread — Percent per year — 147,983 — 47 — 18.8 — 3.72 — 4.86 — -0.25 — 72.22
  - Yield, 3-month — Percent per year — 52,067 — 18 — 19.6 — 5.54 — 3.84 — -0.14 — 64.86
  - Yield, 6-month — Percent per year — 44,389 — 16 — 19.6 — 5.39 — 3.82 — -0.05 — 41.99
  - Yield, 1-year — Percent per year — 53,769 — 20 — 19.6 — 5.87 — 3.58 — -0.04 — 46.00
  - Yield, 2-year — Percent per year — 51,795 — 22 — 19.6 — 6.43 — 4.09 — -0.01 — 28.25
  - Yield, 5-year — Percent per year — 57,742 — 21 — 19.6 — 7.01 — 3.39 — 0.98 — 25.49
  - Yield, 10-year — Percent per year — 68,098 — 23 — 19.6 — 6.95 — 3.01 — 1.13 — 22.42
  - Term premium — Percent per year — 10,165 — 13 — 3.1 — 1.02 — 1.82 — -4.65 — 9.38
  - Expected future policy rate — Percent per year — 9,818 — 13 — 3.1 — 4.96 — 3.67 — 0.28 — 20.84
  - Exchange rate — Log of local currency price of USD — 249,937 — 60 — 19.7 — 3.11 — 2.57 — -3.44 — 10.69
  - Portfolio inflows, total — Percent of annual GDP — 11,581 — 6 — 14.3 — 0.0104 — 0.0643 — -0.5899 — 0.6636
  - Stock price — Log of total return index — 105,454 — 22 — 19.7 — 7.37 — 2.39 — 2.56 — 14.32

### Table 11 — Summary statistics of US news indicators
- Table header: Variable | Units | Obs. | From | To | Mean | Std dev. | Min. | Max.
- Selected rows preserved exactly:
  - Employment — Hundreds of thousands of jobs — 223 — 1/7/2000 — 12/7/2018 — -0.16 — 0.77 — -3.28 — 2.08
  - Jobless claims — Thousands of jobs — 792 — 1/6/2000 — 12/27/2018 — 0.50 — 17.77 — -94.00 — 70.00
  - Retail sales — Percentage change mom — 214 — 1/13/2000 — 12/14/2018 — -0.01 — 0.61 — -1.76 — 5.13
  - GDP — Percentage change qoqar — 62 — 1/28/2000 — 10/26/2018 — -0.09 — 0.65 — -1.68 — 1.80
  - Dur. goods orders — Percentage change mom — 211 — 1/27/2000 — 12/21/2018 — 0.02 — 2.93 — -8.85 — 17.10
  - Inflation — core CPI — Percentage change mom — 213 — 1/14/2000 — 12/12/2018 — -0.008 — 0.091 — -0.300 — 0.246
  - Inflation — core PPI — Percentage change mom — 216 — 1/13/2000 — 12/11/2018 — -0.002 — 0.257 — -0.980 — 1.068
  - Monetary policy — Intradaily — Percent per year — 154 — 2/2/2000 — 12/13/2017 — -0.007 — 0.054 — -0.233 — 0.216
  - Monetary policy — Daily — Percent per year — 176 — 2/2/2000 — 11/5/2020 — -0.007 — 0.071 — -0.260 — 0.270
  - Vaccine news — Index -1 or 1 — 57 — 1/4/2020 — 12/15/2020 — 0.02 — 1.009 — -1 — 1
- Notes: US economic news announcements exclude all monetary policy announcement days. Acronyms: mom = month-on-month; qoqar = quarter-on-quarter annualized.
- Sources: Gürkaynak, Kısacıkoğlu and Wright (2020); Bloomberg, L.P.; Moderna, Inc.; and BioNTech S.E.

### Information effects or measurement error — findings and analysis
- Empirical observation:
  - Jarocinski and Karadi (2020) find that in about one-third of announcements, yields and stock prices move in the same direction (puzzling comovement). The authors of this paper find the same ratio using either 3-month Federal Funds futures or the 2-year Treasury yield.
  - The same ratio prevails in the post-2000 sample period used for the spillover analysis.
- Interpretation and contextual observations:
  - Jarocinski and Karadi (2020) interpret comovement as an information effect: Federal Reserve announcements reveal information about the economic outlook, prompting revisions to expectations and stock valuations.
  - Historical context: four of the six most puzzling dates are associated with the dotcom and financial crises of 2001 and 2008.
  - Bauer and Swanson (2020) note a similar pattern in Nakamura and Steinsson (2018) data, suggesting puzzling comovement may relate to crisis or stress conditions.
  - Contemporary market commentary (e.g., The New York Times) around certain dates (e.g., March 21, 2001) described investor reactions as “disappointed” rather than attributing movements primarily to information effects.
  - Measurement error examples:
    - Disagreement between 1-month and 3-month Federal Funds futures responses on some announcements (sensitivity to choice of interest rate).
    - Surprises in stock prices sensitive to event-window length (examples: November 6, 2002, October 29, 2008).
    - Heterogeneous expectations across investor types (stocks vs bonds) can produce opposing surprise signs (example: March 11, 2008).
    - Earlier-than-expected policy rate cut combined with revised expectations for subsequent cuts can produce appearances of easing/tightening differences (example: January 22, 2008).
    - Rigobon and Sack (2008) emphasize measurement error importance in measuring monetary policy surprises.
  - Crisis conditions amplify measurement error via higher intraday volatility, impaired liquidity, and potential unscheduled policy actions.
- Formal test of measurement error correlation with crisis conditions:
  - Two-step procedure:
    1. Constructed a proxy for measurement error as the perpendicular distance between surprises in 3-month Federal Funds futures and 2-year Treasury yields around FOMC announcements. The distance is measured from an orthogonal (“Deming”) regression line fitted through the two surprise measures.
    2. Regressed this disagreement measure on the average of the VIX over the next 18 months.
  - Result:
    - The coefficient on the VIX is statistically significant at the conventional 5 percent level, with a p-value of 3.5 percent, suggesting a strong relationship between measurement error and economic conditions, especially stress conditions.
  - Regression equation (as presented):
    - disagreement_t = 0.0014 (0.00925) + 0.00102 (0.00048) VIX_t

*IMF WORKING PAPERS — Spillovers to Emerging Markets from US Economic News and Monetary Policy*

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_Source: https://www.imf.org/-/media/files/publications/wp/2023/english/wpiea2023107-print-pdf.pdf_