## CHAPTER 2 THE GREAT TIGHTENING: INSIGHTS FROM THE RECENT INFLATION EPISODE

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---

### Overview of the recent inflation episode
- Pandemic and demand-supply dynamics:
  - COVID-19 triggered shutdowns and supply-chain disruptions; recovery with restrictions produced a surge in consumer demand for goods while supply ramps lagged.
  - Fiscal stimulus magnitudes cited:
    - Fiscal stimulus amounted to an average of about 12 percent of GDP in advanced economies and to an average of 4 percent of GDP in emerging markets.
    - Quantitative easing policies amounted to about 20 percent of GDP in several advanced economies.
  - The war in Ukraine produced a global food and energy crisis; by mid-2022 global inflation had tripled relative to its prepandemic level.
- Inflation peaks and surprises:
  - Annual inflation peaked in 2022 at about 8 percent in the median advanced economy and emerging market and extended beyond that in the median low-income country before receding over 2023.
  - Forecast errors in 2022: median forecast error reached 2.5 percentage points for advanced economies, 1.1 percentage points for emerging markets, and 1.5 percentage points for low-income countries.
  - Disinflation in 2023–24 progressed faster than expected, with negative forecast errors for 2024 in forecasts made in 2023.
- Sectoral patterns:
  - Demand rotated toward goods amid lockdowns, producing earlier and higher goods inflation than services; reopening shifted demand toward services over time.
  - Energy and food were central drivers of headline inflation increases and subsequent decreases; energy-dependent sectors surged in 2021 and peaked in 2022, with plateauing by end-2023.
  - Historical peak pass-through from a 1 percentage point increase in energy prices into CPI inflation:
    - about 0.06 percentage point in advanced economies;
    - about 0.17 percentage point in emerging market and developing economies.

### The policy response: “The Great Tightening”
- Characterization:
  - A global tightening cycle tested monetary policy frameworks as central banks calibrated timing and pace amid sectoral shocks and relative price shifts.
  - Central banks did not start rate hikes synchronously; some countries (for example, Brazil and Chile) moved earlier than others.
- Focus:
  - The chapter centers mainly on policy interest rates through conventional demand channels, complementary to analyses of communications, balance sheet policies, price-suppressing measures, and liquidity measures.
- Cross-country monetary patterns and sample details:
  - Monetary tightening analysis uses a sample comprising 16 AEs and 65 EMDEs.
  - Real rates in panel analysis are constructed as nominal rates minus one-year-ahead inflation expectations.
  - Economic conditions at liftoff are reported as the deviation of the central bank’s targeted inflation rate from the central bank target in the quarter of first tightening.

### Empirical findings — Phillips curves, wages, and transmission
- Price versus wage Phillips curves:
  - Price Phillips curves steepened and shifted upward: inflation accelerated faster when unemployment declined and disinflation occurred with fewer job losses than expected.
  - Wage Phillips curves did not steepen substantially; wages were less responsive though they shifted upward with short-term inflation expectations.
- Drivers of inflation across countries and over time:
  - Energy shocks and other headline shocks played an outsized role early; these headline shocks passed through to broader inflation.
  - Import prices accounted for a sizable part of pass-through in emerging markets.
  - Long-term inflation expectations remained broadly anchored and did not directly contribute to inflation dynamics.
- United States specifics:
  - Initially driven by energy price shocks and other sector-specific shocks; since mid-2022 the main driver of US inflation has been a tight labor market.
  - By the first quarter of 2024, labor market tightness was contributing 2.5 percentage points to US CPI inflation, partly offset by a modest deflation in energy costs.
- Transmission of monetary policy tightening:
  - Empirical assessment uses a vector autoregression model with time-varying coefficients and a standardized monetary policy tightening shock across selected countries during tightening cycles since the 1990s.
  - Estimates suggest peak effects on consumer prices vary by country; no systematic and statistically significant difference is detected in the magnitude of responses when post-2022 price responses are compared with the average transmission observed during tightening cycles in the 1990s through 2019.
  - Caveat: moderate changes in specific transmission channels or country-specific dynamics cannot be ruled out.

### Model-based framework and mechanisms
- Global Dynamic Network Model features:
  - Rich input-output linkages across sectors and countries; allows relative demand for each sector to change.
  - Two-country setup (United States and rest of world) to assess synchronized global tightening.
  - Occasionally binding supply constraints as limits on maximum employment of firms that can bind in extreme cases, producing sectoral bottlenecks and propagating input-price effects.
  - Allows aggregate and sectoral shocks, including monetary policy shocks, aggregate demand shocks, and many sectoral demand and supply shifts.
- Mechanism for steepening and shifting Phillips curves:
  - When supply constraints are rare, the aggregate Phillips curve is close to linear.
  - As more sectors hit supply constraints, firms cannot expand employment/output and prices rise in constrained sectors; aggregating across sectors yields a nonlinear (steepened) aggregate Phillips curve.
  - Relative demand shocks can shift the aggregate Phillips curve upward when high-demand sectors bind while weak-demand sectors do not.
- Calibration and quantified model findings:
  - Supply bottlenecks contributed 2–3 percentage points to US inflation during 2020–22 and then contributed negatively after 2023.
  - Supply constraints were an important persistent drag on real GDP during the period examined.
  - Supply bottlenecks tend to raise prices persistently in the short run but produce one-off rather than persistent increases in inflation; inflation impacts are smaller than GDP effects.
  - Turning off agriculture and raw energy shocks lowers inflation—especially around the start of the war in Ukraine—while making a smaller difference for GDP.

### Model counterfactuals and policy experiments
- Tightening three quarters earlier (counterfactual):
  - Lowers peak inflation by about 2 percentage points relative to the data.
  - Results in a 0.8 percentage point reduction in real GDP for 2022.
  - With capacity constraints estimated from the data, tighter policy is more potent in lowering inflation and has lower output cost compared with the case where constraints are assumed away.
- Role of global synchronization:
  - If the rest of the world delays tightening three quarters while US rates remain as observed, domestic disinflation slows and sectoral spillovers raise inflation in agriculture, mining, and energy more than in other sectors.
  - Sectors with highly flexible prices (agriculture, mining, energy) generate waves of price increases in manufacturing and services via input-output linkages.
- Comparison of four monetary policy rules in a milder hypothetical scenario:
  1. Targeting stickiest-price sectors (information technology and telecommunications; finance and insurance; professional, scientific, and technical; education, health, and government services; and arts, entertainment, and recreation).
     - Delivers relatively fast disinflation.
  2. Inflation forecast targeting (stabilize four-quarter moving average of future CPI inflation).
     - Ends up “running the economy hot” by responding to medium-term inflation (which is lower than inflation on impact), leading to a surge in inflation and inflation expectations; despite higher nominal rates, yields lower real rates and requires a prolonged medium-term reduction in real GDP to bring inflation to target.
  3. Average inflation targeting (target average of preceding four quarters of inflation).
     - Produces inflation and GDP responses most similar to targeting stickiest-price sectors; delayed response implies a more gradual return of inflation to target and real GDP remains below steady state in the medium term for longer.
  4. Sectoral Taylor rule targeting equally CPI inflation and sectoral inflation in agriculture, mining, and energy.
     - Tightens markedly more on impact because food and energy prices are flexible and supply constrained; overreacts to transitory inflation delivering a sharp recession, followed by rapid policy-rate reductions and subsequent surges in inflation and GDP as shocks dissipate.

### Policy implications and recommendations
- Diagnostic priority:
  - Prioritize diagnosing drivers of inflation—particularly prevalence and sectoral distribution of supply bottlenecks and their interaction with demand—despite real-time challenges.
- Policy rules and targeting:
  - When supply bottlenecks are widespread and interact with demand (steep aggregate Phillips curve), stronger monetary responses can be warranted because disinflation via tightening is less costly in output terms (favorable sacrifice ratio).
  - When constraints are confined to commodity sectors, conventional rules focusing on core or stickiest prices are more appropriate to avoid unnecessary recession risk.
  - Include well-defined escape clauses in policy frameworks to tackle inflationary pressures when aggregate Phillips curves steepen; forward guidance should internalize those escape clauses and allow front-loading of tightening.
- Complementarity with other tools:
  - Central bank communications, balance sheet policies, price-suppressing measures, and liquidity measures remain important complements to policy interest rates and can affect inflation dynamics and transmission.
  - Non-monetary tools used during the episode (survey of 174 countries, March–July 2022) included energy and consumption subsidies, import tax reductions, export restrictions, price and wage controls, government-led negotiations, and taxes on inflation; these tools have trade-offs such as fiscal cost, misalignment with climate goals, poor targeting, black-market risks, and international spillovers.
- Data and modeling investments:
  - Develop models capturing sectoral linkages and heterogeneity and collect more granular sectoral data to map sectoral networks and refine models.
  - Use high-frequency sectoral indicators of supply constraints and demand pressures (including upstream and downstream supply-chain disruptions and sectoral labor-market indicators) to support real-time policymaking.
- International considerations:
  - Synchronized global tightening can be more effective than country-by-country tightening by lowering tradable goods prices, especially commodities.
  - Advanced-economy QT strengthens currencies (through higher term premiums) more than conventional tightening (through short-term policy rate), increasing pressure on emerging market and developing economies and worsening inflation-output trade-offs for economies with fixed exchange rates.

### Central bank balance sheet policies and QT evidence
- Balance sheet expansions during 2020–22:
  - Central bank balance sheets grew by more than 20 percent of GDP in Japan, the United Kingdom, and the euro area; about 18 percent of GDP in the United States.
- Evidence on quantitative tightening (QT) effects:
  - A one-standard-deviation QT shock had a small, possibly slightly negative, effect on short-term rates while raising term premiums by about 12 basis points.
  - Active QT tended to have a stronger impact on long-term rates than passive QT in the recent episode.
  - The cumulative impact of QT announcements since 2021 has equaled at most two or three rate hikes in some countries.
- Potential risks and caveats:
  - QT could have stronger effects if conducted more rapidly or on a larger scale, especially once reserves become scarce.
  - Financial stability risks could increase (for example, higher liquidity dependence of banks and sudden deposit withdrawals).
  - External validity of estimates remains an open empirical question given limited experience beginning in 2021.

*Italic: Source: Chapter 2, “THE GREAT TIGHTENING: INSIGHTS FROM THE RECENT INFLATION EPISODE,” World Economic Outlook (October 2024), International Monetary Fund.*

### Introduction

### ch2 - Introduction

### Overview of the recent inflation episode
- The past three years featured an extraordinary set of inflationary events beginning with the COVID-19 pandemic, which triggered economic shutdowns and supply-chain disruptions. As recovery progressed with restrictions still in place, consumer demand for goods surged while producers struggled to ramp up supply, producing price pressures in the goods sector and later in services.
- The unprecedented fiscal and monetary stimulus deployed by advanced economies and some emerging markets initially increased savings; over time a drawdown of those savings boosted demand, widening supply-demand imbalances and spurring inflation as capacity remained constrained.
- The war in Ukraine produced a global food and energy crisis that exacerbated inflationary pressures. By mid-2022, global inflation had tripled relative to its prepandemic level.
- Fiscal and monetary policy magnitudes cited:
  - Fiscal stimulus amounted to an average of about 12 percent of GDP in advanced economies and to an average of 4 percent of GDP in emerging markets.
  - Quantitative easing policies amounted to about 20 percent of GDP in several advanced economies.

### The policy response: “The Great Tightening”
- These inflationary pressures prompted a global tightening cycle—the “Great Tightening”—testing monetary policy frameworks as central banks calibrated timing and pace under sectoral shocks and relative price shifts.
- Central banks did not start rate hikes synchronously; some countries (for example, Brazil and Chile) moved earlier than others depending on country-specific circumstances and timing of shocks.
- The chapter focuses mainly on the role of policy interest rates through conventional demand channels, complementary to other work on communications, balance sheet policies, price-suppressing measures, and liquidity measures.

### Chapter objectives and structure
- Objectives:
  - Disentangle contributions of shocks and policy responses to the inflation surge and subsequent disinflation.
  - Draw lessons for monetary policymakers as geopolitical tensions and extreme weather events may trigger further sectoral shocks.
- Structure:
  - Stylized facts from raw data and empirical Phillips curves.
  - Documentation of monetary policy response and transmission across countries and time.
  - Development of a new multisector network model to construct counterfactual scenarios assessing sectoral capacity constraints, global tightening, and other fundamentals; comparison of alternative simple policy rules under different scenarios.

### What happened? Dissecting inflation dynamics
- Peak and surprise:
  - Starting in late 2020, inflation rose to levels not seen since the 1970s.
  - Annual inflation peaked in 2022 at about 8 percent in the median advanced economy and emerging market and extended beyond that in the median low-income country before receding over 2023.
  - Forecast errors: median forecast error in 2022 reached 2.5 percentage points for advanced economies, 1.1 percentage points for emerging markets, and 1.5 percentage points for low-income countries. Disinflation in 2023–24 progressed faster than expected, with negative forecast errors for 2024 in forecasts made in 2023.
- Expectations and wages:
  - Long-term inflation expectations remained broadly stable; short-term expectations and nominal wages rose, but real wage growth remained contained in most economies and wage-price spirals did not occur.
- Sectoral shifts and dispersion:
  - Large sectoral shifts in demand and supply produced pronounced changes in relative prices and a spike in cross-sectoral inflation dispersion.
  - Demand rotated toward goods amid lockdowns and supply-chain disruptions, causing goods inflation to surge earlier and higher than services. When economies reopened, demand shifted toward services and sectoral drivers changed over time.
- Role of energy and food:
  - The war in Ukraine put substantial pressure on noncore components of headline inflation—particularly food and energy—driving much of both the increase and the subsequent decrease in overall inflation.
  - Energy-dependent sectors experienced inflation surges in 2021 and peaked in 2022; by end-2023, inflation was plateauing in energy-dependent sectors while less energy-dependent industries were primary drivers of overall inflation thereafter.
- Energy price pass-through magnitudes and evidence:
  - Historical peak pass-through from a 1 percentage point increase in energy prices into CPI inflation at the country level was about 0.06 percentage point in advanced economies and 0.17 percentage point in emerging market and developing economies.
  - The pass-through from energy prices into CPI inflation did not strengthen materially across a wide range of countries during this episode.
  - Countries with lower energy price inflation—notably Asian emerging market and developing economies—had lower overall CPI inflation, suggesting an important role for energy prices.

### Empirical findings and Phillips curves
- Price versus wage Phillips curves:
  - Price Phillips curves steepened: the relationship between economic slack and inflation shifted upward and steepened, meaning inflation accelerated faster than expected when unemployment declined and disinflation occurred with fewer job losses than expected.
  - Wage Phillips curves did not steepen: wages did not spike in the same way as prices did.
- Supply bottlenecks and demand interaction:
  - Interaction of supply bottlenecks with demand pressures can rationalize the steepening of price Phillips curves. Declines in capacity in high-demand sectors (for example, durable goods early in the pandemic; transportation during reopening) significantly contributed to inflationary pressures.
- Transmission and sectoral heterogeneity:
  - Energy shocks spread through sectoral networks according to sectoral price flexibility and energy dependence, with stronger pass-through in more energy-dependent sectors and in sectors with more flexible prices.
  - Flexible-price sectors (energy, vehicles, household equipment, restaurants, hotels, recreation) led early inflation dynamics; more rigid-price sectors (clothing, communications, health) became primary drivers by end-2023.

### Model-based insights and counterfactuals
- Multisector network model:
  - A new multisector network model was developed to evaluate counterfactual scenarios and quantify the importance of sectoral capacity constraints, the global nature of monetary tightening, and other fundamentals in driving both the inflation surge and the ensuing disinflation.
- Key model-driven insights:
  - When the Phillips curve is steep for an economy overall, the benefits of monetary tightening are amplified—counteracting demand-driven inflation in the presence of prevalent supply bottlenecks presents a favorable sacrifice ratio.
  - Tightening on a global scale can be more effective than tightening by individual countries because it can lower the price of tradable goods, especially commodities.
  - If supply constraints are confined to the commodity sector, conventional policy rules targeting measures of core inflation remain appropriate. Strong reactions to flexible commodity prices can bring down inflation fast but risk a recession later; targeting sticky prices yields more gradual disinflation with a smoother output path.

### Policy implications and recommendations
- Diagnostic priority:
  - Diagnosing the drivers of inflation—particularly the prevalence and sectoral distribution of supply bottlenecks and their interaction with demand—is vital, though challenging in real time.
- Policy rules and targeting:
  - Policy should account for sectoral heterogeneity: when supply bottlenecks are widespread and interact with demand, stronger monetary responses can be warranted given steep price Phillips curves; when constraints are confined to commodity sectors, conventional rules focusing on core inflation are more appropriate to avoid unnecessary recession risk.
- Complementarity with other tools:
  - While the chapter centers on policy interest rates, other instruments (central bank communications, balance sheet policies, price-suppressing measures, liquidity measures) remain important and may affect inflation dynamics and transmission.

*Italic: Source: Chapter 2, “THE GREAT TIGHTENING: INSIGHTS FROM THE RECENT INFLATION EPISODE,” World Economic Outlook (October 2024), International Monetary Fund.*

### 1. Drivers of US PCE Inflation

### 1. Drivers of US PCE Inflation

### Shifting and steepening of the Phillips curve
- Prior to 2020, the Phillips curve was relatively flat, implying a weak trade-off between output and inflation.
- During the pandemic the empirical Phillips curve notably steepened and shifted upward, particularly in advanced economies and more for goods than for services.
- Implications of the steeper slope:
  - A given decrease in economic slack was associated with a larger increase in inflation.
  - A given increase in economic slack was associated with a larger decline in inflation.
- Country-level estimation details and sample:
  - Linear fits use a sample of 29 advanced economies and 15 emerging markets during the period from the first quarter of 2010 to the first quarter of 2024.
  - The first two quarters of 2020 are excluded in the reported estimates.
  - The unemployment gap is estimated using a univariate Hodrick-Prescott filter.
- Wage Phillips curve:
  - The empirical wage Phillips curve did not steepen much in either advanced economies or emerging markets, but shifted upward as short-term inflation expectations increased.
  - Wages were less responsive, indicating recent inflation dynamics likely did not reflect solely excessive tightness in the labor market.

### Pass-through of commodity and headline shocks
- A richer estimated Phillips curve allows a correlational decomposition of inflation drivers (methodology similar to Ball, Leigh, and Mishra (2022) and Dao and others (2024)).
- Across countries since mid-2022:
  - Tight labor markets play a moderate role in explaining inflation dynamics (with the possible exception of the United States during the later period).
  - Energy shocks and other headline shocks played an outsized role early in the episode and were subsequently passed on to broader inflation.
  - Import prices accounted for a sizable part of the pass-through in emerging markets.
  - Long-term inflation expectations remained anchored and did not directly contribute to inflation dynamics.
- United States specifics:
  - Initially driven by energy price shocks and other sector-specific shocks (supply disruptions and shortages).
  - These headline shocks passed through into broader inflation in 2021 and early 2022.
  - Since mid-2022 the main driver of US inflation has been a tight labor market.
  - By the first quarter of 2024, labor market tightness was contributing 2.5 percentage points to US CPI inflation, partly offset by a modest deflation in energy costs.
- Other advanced economies and emerging markets:
  - Other advanced economies (particularly in Europe) were initially driven by large energy price shocks; energy pass-through alone contributed more than 2.5 percentage points to CPI inflation at its peak.
  - For emerging markets, import price pass-through (including exchange rate effects) was a significant driver; import prices in local currency were used for the decomposition.

### Monetary policy reaction and tightening
- Global patterns:
  - Central banks initially adopted expansionary monetary policies during the pandemic, then transitioned to tightening as broader inflationary pressures emerged.
  - Timing and pace of tightening varied across countries depending on shock impacts, lockdown timing, initial conditions, and institutional features.
- Sample and measurement:
  - Monetary tightening analysis uses a sample comprising 16 AEs and 65 EMDEs.
  - In panel 1 (Figure 2.8), real rates are constructed as nominal rates minus one-year-ahead inflation expectations.
- Cross-country variation:
  - Commodity price increases after the war in Ukraine produced terms-of-trade improvements for exporters and deteriorations for importers, affecting policy responses.
  - Central banks with a history of low and stable inflation could “look through” transitory supply shocks for longer; others faced limited room to maneuver.
  - Some emerging market and developing economies (for example, Brazil, Chile, and Mexico) started rate hikes earlier than others; Asia exhibited a more tempered response; the United States adjusted relatively later.
- Economic conditions at liftoff:
  - Panel 2 of Figure 2.8 reports economic conditions at the first interest rate hike during the current tightening cycle for a set of countries; inflation is reported as deviation of the central bank’s targeted inflation rate from the central bank target in the quarter of first tightening.

### Policy responses compared with the 1970s
- Definition used for inflation episodes:
  - An inflation episode is defined as a period with an increase in inflation of more than 2 percentage points in a year.
  - Episodes are grouped as “resolved” or “unresolved”; an episode is considered resolved if inflation declines in the neighborhood of 1 percentage point of its pre-episode level within a five-year window.
- Observations comparing post-2020 episodes with 1970s episodes:
  - Post-2020 inflation episodes have been more pronounced and persistent compared with the resolved episodes of the 1970s, with inflationary pressures building sharply during episodes and continuing to rise in the subsequent year.
  - Nominal interest rate hikes during resolved episodes of the 1970s were larger, with real rates swiftly transitioning to contractionary territory.
  - Post-2020 episodes involved milder nominal rate adjustment and a more prolonged expansionary policy stance, indicated by sustained negative real interest rates.
  - During unresolved 1970s episodes, the median policy stance remained consistently expansionary, with more prolonged and more negative real interest rates than observed after 2020.
- Overall: the recent episode lies between the resolved and unresolved episodes of the 1970s in terms of inflation dynamics and the speed of the policy response.
- Inflation expectations anchoring:
  - Proxying the degree of inflation expectations anchoring using past inflation volatility indicates inflation expectations were more strongly anchored post-2020 than in the 1970s (limited direct inflation expectations data for the 1970s).

### Transmission of monetary policy tightening: continuities and changes
- Competing forces affecting transmission:
  - Weaker transmission factors: increased popularity of fixed-rate mortgages reducing sensitivity of household payments to rising interest rates; excess household savings buffering consumption.
  - Potentially stronger transmission factors: synchronized global tightening weakening exchange-rate channel but strengthening channels through world commodity prices; a steeper Phillips curve implying a smaller effect on output but stronger disinflationary impact.
- Empirical assessment:
  - The chapter measures overall transmission using a vector autoregression model with time-varying coefficients, focusing on a standardized monetary policy tightening shock across selected countries during tightening cycles since the 1990s.
  - Estimates suggest peak effects on consumer prices vary by country, but no systematic and statistically significant difference is detected in the magnitude of responses when post-2022 price responses are compared with the average transmission observed during tightening cycles in the 1990s through 2019.
  - This conclusion holds when comparing the full path of impulse responses over time, not just peak effects.
- Caveats:
  - The methodology is designed to detect significant changes in overall transmission using available data; it does not rule out moderate changes in specific transmission channels or country-specific dynamics.

*Source: ch2 - 1. Drivers of US PCE Inflation (chapter extract) — IMF staff calculations and figures as presented in the source PDF.*

### CHAPTER 2 THE GREAT TIGHTENING: INSIGHTS FROM THE RECENT INFLATION EPISODE

### CHAPTER 2 THE GREAT TIGHTENING: INSIGHTS FROM THE RECENT INFLATION EPISODE

### Model-Based Framework: Global Dynamic Network Model
- Features:
  - Rich input-output linkages across sectors and countries to trace transmission of sectoral price pressures to core inflation, allowing relative demand for each sector to change.
  - Two-country setup (United States and rest of world) to assess synchronized global tightening.
  - Occasionally binding supply constraints as limits on maximum employment of firms that can bind in extreme cases (lockdowns, demand surges), producing sectoral bottlenecks and propagating input-price effects to other sectors.
  - Allows aggregate and sectoral shocks, including monetary policy shocks, aggregate demand shocks, and a rich set of sectoral demand and supply shifts.

### Widespread Bottlenecks and the Steepening/Shifting Phillips Curve
- Mechanism:
  - When supply constraints are rare, aggregate Phillips curve is close to linear.
  - As more sectors hit supply constraints, firms cannot expand employment/output and prices rise in constrained sectors; aggregating across sectors yields a nonlinear (steepened) aggregate Phillips curve.
- Model illustrations (Figure 2.11 context):
  - Steepening: contractionary monetary policy + low demand → sectors below labor constraints; as policy becomes more expansionary, more sectors bind and the Phillips curve steepens (blue line vs red line without bottlenecks).
  - Shifting: adding relative demand shocks causes high-demand sectors to bind and face upward price pressures, while weak-demand sectors produce less; combination yields an upward shift in the aggregate Phillips curve.
- Note: The model’s capacity to both steepen and shift the Phillips curve allows empirical data to determine the relative importance of each channel.

### Role of Constraints and Commodity-Specific Shocks (Model Quantified to Data)
- Calibration: Two-region model (US and rest of world) fitted to match sectoral dispersion in inflation and output.
- Key quantified findings:
  - Supply constraints were an important persistent drag on real GDP during the period examined (Figure 2.12, panel 4).
  - Supply bottlenecks contributed 2–3 percentage points to US inflation during 2020–22 and then contributed negatively after 2023 (Figure 2.12, panel 3).
  - Supply bottlenecks tend to raise prices persistently, producing one-off rather than persistent increases in inflation; hence inflation impacts are smaller than GDP effects.
- Commodity-sector counterfactuals:
  - Turning off shocks specific to agriculture and raw energy lowers inflation, especially around the start of the war in Ukraine when supply constraints in these sectors were tightest (Figure 2.12, panels 5 and 6).
  - Turning off commodity-specific shocks makes a smaller difference for GDP.
  - Caveat: turning off agriculture and raw energy shocks does not freeze their prices because aggregate demand shocks and constraints in other sectors can still move these prices.

### Policy Experiments: Counterfactuals and Hypothetical Scenario

- Counterfactual scenarios (tightening three quarters earlier):
  - Tightening earlier lowers peak inflation by about 2 percentage points relative to the data (Figure 2.13, panel 1).
  - Tightening earlier results in a 0.8 percentage point reduction in real GDP for 2022 (Figure 2.13, panel 2).
  - Comparison with and without bottlenecks:
    - With capacity constraints estimated from the data (solid red lines), tighter policy is more potent in lowering inflation and has lower output cost compared with the case where constraints are assumed away (dashed red lines).
    - Reason: constraints steepen the Phillips curve, making expansionary policies more inflationary but disinflation via tightening less output-costly.
- Role of global synchronization:
  - If the rest of the world delays tightening (ROW delays tightening three quarters) while US rates remain as observed, domestic disinflation slows and sectoral spillovers raise inflation in agriculture, mining, and energy more than other sectors (Figure 2.14).
  - Sectors with highly flexible prices (agriculture, mining, energy) generate waves of price increases in manufacturing and services via input-output linkages.
- Hypothetical milder scenario (positive aggregate demand shock + negative capacity shocks in agriculture, mining, energy):
  - Four monetary policy rules compared (Figure 2.15):
    1. Targeting inflation in sectors with the stickiest prices (stickiest-price sectors defined as information technology and telecommunications; finance and insurance; professional, scientific, and technical; education, health, and government services; and arts, entertainment, and recreation).
    2. “Inflation forecast targeting” (stabilize four-quarter moving average of future CPI inflation).
    3. “Average inflation targeting” (target average of preceding four quarters of inflation).
    4. Sectoral Taylor rule targeting equally CPI inflation and sectoral inflation in agriculture, mining, and energy.
  - Comparative outcomes:
    - Targeting stickiest-price sectors:
      - Delivers relatively fast disinflation.
    - Inflation forecast targeting:
      - Ends up “running the economy hot” by responding to medium-term inflation (which is lower than inflation on impact), leading to a surge in inflation and inflation expectations.
      - Despite higher nominal rates, this rule yields lower real rates than the other rules, causing higher initial output but requiring a prolonged medium-term reduction in real GDP to bring inflation to target.
    - Policy rule with higher weight on food and energy:
      - Tightens markedly more on impact because food and energy prices are more flexible and sensitive to the demand shock and are supply constrained.
      - Overreacts to transitory inflation, delivering a sharp recession.
      - As shocks dissipate, food and energy prices fall faster than overall CPI, prompting a rapid fall in policy rates and a subsequent surge in inflation and GDP.
      - Short-term relative prices closer to flexible-price benchmark, but longer-term relative price movements become more persistent, distorting resource allocation for longer.
    - Average inflation targeting:
      - Produces inflation and GDP responses most similar to targeting stickiest-price sectors.
      - Delayed response implies a more gradual return of inflation to target and real GDP remains below steady state in the medium term for longer.

### Summary and Policy Implications
- The recent inflationary episode was characterized by prominent sectoral shifts amid policy stimulus and capacity constraints.
- Supply bottlenecks and sectoral shocks (notably in agriculture and raw energy) materially affected inflation dynamics and real GDP.
- Policy lessons from model experiments:
  - Earlier monetary tightening can materially lower peak inflation (about 2 percentage points in the counterfactual) but entails output costs (about 0.8 percentage point reduction in real GDP for 2022 in the counterfactual).
  - Presence of supply bottlenecks steepens the Phillips curve and can make disinflation via monetary tightening less costly in terms of output than in a no-bottlenecks world.
  - Lack of global coordination in tightening (delays by the rest of the world) can slow domestic disinflation and propagate sectoral inflation through input-output linkages.
  - Monetary policy rules that over-weight flexible, commodity-sensitive sectors (food and energy) risk overreacting to transitory shocks and producing sharp recessions and volatile follow-on dynamics.
  - Targeting stickiest-price sectors or using average inflation targeting performs relatively well in the modeled mild scenario; inflation forecast targeting may run the economy hot and produce larger medium-term output costs.

*Source: IMF staff calculations and analysis from CHAPTER 2 THE GREAT TIGHTENING: INSIGHTS FROM THE RECENT INFLATION EPISODE (October 2024).*

### 1. Interest Rates2. Inflation

### 1. Interest Rates2. Inflation

### Sectoral dynamics and Phillips curves — empirical findings and model insights
- Statistical decompositions attribute an important role to price pressures arising from individual sectors and their spillovers to core inflation.
- The relationship between inflation and economic slack shifted and steepened during the recent episode.
- A newly developed structural multisector model can account for:
  - Transmission of sector-specific price pressures to the rest of the economy.
  - The shifting and steepening of Phillips curves via a mechanism running through binding supply constraints combined with demand shocks.
- Sectoral supply constraints tend to have large but short-lived effects on inflation as they start to bind.
- Steeper Phillips curves result from the interaction of binding sectoral supply constraints with demand shocks.
- Distinction between aggregate and sectoral Phillips curve steepening:
  - New lesson: When supply bottlenecks are prevalent and combined with strong demand, the aggregate Phillips curve steepens. Policy tightening in that case is effective at easing demand pressures and bringing down inflation quickly with limited output costs (the sacrifice ratio is low). Monitoring whether key sectors bump against supply bottlenecks in an overheated economy is crucial.
  - Old lesson: When supply bottlenecks are confined to specific sectors, standard rules focusing on inflation in sectors with the stickiest prices remain appropriate. Sectoral Phillips curves steepen in constrained sectors, but effects may not spread widely enough to steepen the aggregate Phillips curve; monetary tightening can sharply reduce flexible commodity prices but at the expense of lower output and eventual inflation undershoot.
  - Policy synthesis: Include well-defined escape clauses in policy frameworks to tackle inflationary pressures when aggregate Phillips curves steepen; forward guidance should internalize those escape clauses and allow front-loading of tightening.

### Policy implications for central banks, data, and modeling
- Central banks should differentiate between immediate/transitory effects of sectoral constraints and more persistent impacts when combined with demand pressures.
- Investing in improved models and data collection is recommended:
  - Develop models that capture sectoral linkages and heterogeneity (as exemplified by the chapter’s model).
  - Collect more granular sectoral data to map sectoral networks and refine models; quantify how much and how fast sectoral price pressures propagate depending on centrality/criticality and price stickiness.
  - Use high-frequency sectoral indicators of supply constraints and demand pressures (including upstream and downstream supply-chain disruptions and sectoral labor-market indicators) to support real-time policymaking.
- Consider the distribution of risks when weighing benefits of “running the economy hot,” and prevent inflation from drifting too far from target for an extended period, especially when inflation expectations are less anchored and policy credibility is weaker.
- Open economies can benefit from positive spillovers of other central banks’ policy tightening through lower tradable goods prices; synchronized tightening mutes the exchange rate channel relative to the tradable goods channel.
- Better understanding of inflation expectations formation across horizons and agents would help inform policymaking.

### Central bank balance sheet policies — QE, QT, and effects
- Since the global financial crisis, central banks expanded toolkits with balance sheet policies at the ELB; central bank balance sheets grew during 2020–22 by:
  - more than 20 percent of GDP in Japan, the United Kingdom, and the euro area;
  - about 18 percent of GDP in the United States.
- Quantitative tightening (QT) differs from quantitative easing (QE):
  - QE is typically used when short-term policy rates are constrained by the ELB; QT has been used alongside policy tightening.
  - If QT and rate hikes are partly substitutable, greater QT can be partly offset by slower policy-rate tightening, muting QT’s effects.
  - QT may occur against a steeper Phillips curve.
- Evidence on QT effects so far:
  - A one-standard-deviation QT shock had a small, possibly slightly negative, effect on short-term rates while raising term premiums by about 12 basis points.
  - Active QT tended to have a stronger impact on long-term rates than passive QT in the recent episode.
  - The cumulative impact of QT announcements since 2021 has equaled at most two or three rate hikes in some countries, thus contributing moderately to a tighter policy stance.
- Potential for larger QT effects:
  - QT could have stronger effects if conducted more rapidly or on a larger scale, especially once reserves become scarce.
  - Financial stability risks could increase (for example, higher liquidity dependence of banks and sudden deposit withdrawals).
  - Advanced-economy QT strengthens their currencies (through higher term premiums) more than conventional tightening (through the short-term policy rate), increasing pressure on emerging market and developing economies; this worsens inflation-output trade-offs in economies with fixed exchange rates that must raise rates sharply to maintain pegs.
- Conclusion: QT has so far had modest effects and largely worked in the background rather than as an explicit tightening tool; external validity of estimates remains an open empirical question given limited experience beginning in 2021.

### Inflation stabilization policies beyond monetary policy — tools, rationale, and limitations
- Countries frequently used non-monetary tools during the pandemic and postpandemic recovery. Survey and data context:
  - Based on surveys of 174 countries conducted from March to July 2022.
- Energy and consumption subsidies:
  - Widely used to maintain lower prices, especially for energy; many governments subsidized fuel and electricity and reduced value-added taxes, sales taxes, and excises on essential goods.
  - Subsidies absorb cost increases and can limit pass-through to prices; energy subsidies played a significant role in stabilizing inflation in the euro area in the recent episode.
  - Limitations: substantial fiscal costs, misalignment with climate goals, poor targeting of the vulnerable, distortion of relative prices, overconsumption of subsidized goods, and potential to fuel further price rises.
- Import tax reductions and export restrictions:
  - Used to stabilize domestic prices, especially in emerging markets and low-income countries.
  - Import tax cuts lower imported goods prices and increase domestic supply; export restrictions ease domestic inflationary pressures.
  - Limitations: fiscal costs, and both policies induce adverse international spillovers by reducing global supply or increasing global demand, which can contribute to further price increases.
- Price and wage controls:
  - Historically used (including in the 1960s and 1970s) and applied again since the pandemic, particularly on essential food items in emerging markets and low-income countries.
  - Can be justified in contexts of monopsony or monopoly power.
  - Limitations: can lead to black markets, shortages, and prevent relative price adjustment.
- Other policies:
  - Government-led negotiations to coordinate wage and price setting can help manage wage-price spirals and anchor expectations but may distort relative prices.
  - Tax on inflation policies (taxes proportional to a firm’s increase in prices) can provide firms incentives to moderate price increases and offer stabilization gains under certain conditions, but practical implementation needs clarification.
- Overall conclusion: Monetary policy remains the primary tool for managing demand-driven inflation. Alternative tools are useful when monetary policy is limited (for example, during cost-push shocks or under an exchange rate peg) but require careful assessment of effectiveness and trade-offs to minimize adverse side effects.

*Source: IMF staff calculations, World Economic Outlook: Policy Pivot, Rising Threats, Chapter 2.*

### Box 2.2 (continued)

### ch2 - Box 2.2 (continued)

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*World Economic Outlook: Policy Pivot, Rising Threats — Box 2.2 (continued), Chapter 2*

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_Source: https://www.imf.org/-/media/files/publications/weo/2024/october/english/ch2.pdf_