## Dynamic Effects of Domestic Retail Fuel Price Shocks on Inflation (excerpt)

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### I. Introduction — context and transmission channels
- Context and motivation
  - Increasing recognition of broader environmental, fiscal, macroeconomic consequences of underpricing energy products.
  - Fuel pricing central to policy debate since 2009 G20 commitments and reaffirmed in 2012 and the 2015 Paris Climate Agreement.
  - Concerns about adverse macroeconomic effects of energy price increases—particularly inflationary impacts on households' real purchasing power—impede reforms.
- Transmission channels from retail fuel price changes to consumer price inflation
  - Direct effect: higher retail gasoline price reduces household purchasing power in proportion to gasoline's share of the consumer basket; may be persistent given short-run inelastic energy demand.
  - Indirect effect: energy used as inputs raises production costs and possibly electricity prices faced by firms—aggregate supply channel important in energy-intensive economies.
  - Interpretation:
    - Direct effect often viewed as akin to an aggregate demand shock.
    - Indirect effect often viewed as an aggregate supply shock.
  - Empirical consensus suggests the direct (demand-like) channel often dominates in practice.

### II. Empirical approach and data
- Estimation strategy
  - Multivariate model variables: retail fuel prices (local currency), nominal effective exchange rate (NEER), consumer price index, short-term interest rate (lending rate).
  - Structural VAR representation and reduced-form described; identification imposes lower-triangular B0^{-1} with fuel prices ordered first.
  - Primary estimation uses local projections (Jordà, 2005) to compute multi-step impulse responses directly; nonlinearities handled via polynomial terms in projections.
  - Identification assumption: retail fuel price changes are predetermined with respect to macro variables.
  - Each local projection includes 12 lags of each endogenous variable, country fixed effects, an intercept, and a binary variable for the 2008–09 great recession.
  - Data transformations: all series in log first-differences except interest rate (first-differenced only).
  - Inference: standard errors clustered at country level, robust to heteroscedasticity and autocorrelation; non-parametric block bootstrap with 2000 replications for hypothesis testing; selected figures use 1000 bootstrap replications for confidence bands.
- Data and sample
  - Monthly domestic retail fuel prices from Kpodar and Abdallah (2017).
  - Sample period: 2000:1 to 2014:6.
  - Sample composition: 110 countries (31 high income countries, 42 emerging countries, 37 low income countries).
  - Unbalanced panel contains around 12600 observations.
  - Retail gasoline price used as primary fuel price variable; retail diesel produces similar results.
  - Restricted sample for non-energy inflation analysis: 77 countries (data on CPI excluding energy and headline CPI available).

### III. Key empirical findings — overall and by income level
- Full sample (accumulated responses to a normalized 1 percent fuel price shock)
  - One month after the shock: around 0.014 percent increase in inflation.
  - Peak response at eight months: around 0.04 percent.
  - Two years after the shock: decays to around 0.025 percent and is statistically insignificant.
  - Interpretation: spillovers to domestic inflation are modest and largely transitory.
- Heterogeneity by income group (peak/representative responses)
  - Low income countries: largest response of around 0.06 percent.
  - Emerging countries: around 0.036 percent.
  - Advanced (high-income) countries: around 0.025 percent.
  - Emerging countries display the most persistent and long‑lasting response among income groups.
- Non-energy inflation vs headline inflation (restricted sample of 77 countries)
  - Effects of fuel price shocks on non-energy inflation are positive and somewhat larger than on headline inflation.
  - Implication: fuel price shocks produce indirect and second-round effects that propagate into non-energy components.

### IV. Role of economic fundamentals in explaining heterogeneity
- Energy intensity
  - Above-median (more energy intensive) peak accumulated inflation response: 0.061 percent.
  - Below-median (less energy intensive) peak accumulated response: 0.027 percent.
  - Peak for more energy intensive group is around 120 percent higher than for less energy intensive group.
- Wage flexibility
  - WEF 2014 centralized collective bargaining indicator used (1 centralized to 7 decentralized); above median = more flexible wages.
  - Peak accumulated inflation response for less flexible wages group: 0.069 percent.
  - Peak for more flexible wages group: 0.037 percent.
  - Peak for less flexible wages group is around 85 percent higher than for more flexible wages group.
  - Persistence: effects last more than two years for less flexible wages group vs around one year for more flexible wages group.
- Monetary policy credibility
  - Arnone et al (2009) Central Bank Autonomy index used; above median = more credible monetary policy.
  - Peak accumulated inflation response for less credible monetary policy group: 0.059 percent.
  - Peak for more credible monetary policy group: half of 0.059 percent.
  - Persistence: effects last about two years for less credible group vs about one year for more credible group.
  - Implication: greater monetary policy credibility helps anchor inflation expectations and limit persistence from fuel price shocks.

### V. Asymmetry and nonlinearity — shock-size experiment design and results
- Shock measurement and experiment design
  - Shock size δ is measured in standard deviation units of the retail fuel price shock (휎
௚௔௦).
  - Shock sizes considered:
    - δ ∈ ± {0.25, 1, 3}
    - Small shocks: δ = 0.25
    - Typical shocks: δ = 1 (one standard deviation)
    - Large shocks: δ = 3
  - The standard deviation of retail fuel price shocks is equal to around 4, 5, and 4.5 percent, for high-income, emerging, and low-income countries in the sample.
  - Impulse responses:
    - Are normalized by δ for comparability.
    - Responses to negative shocks are multiplied by minus one for comparability.
- Two overarching findings
  - Positive and negative fuel price shocks have differential impacts on inflation in both magnitude and persistence; this asymmetry differs across income groups.
  - The degree of asymmetry is at least partly related to the size of the fuel price shocks: asymmetry disappears for small shocks and is amplified for large shocks.

- High-income countries (selected quantitative patterns)
  - For a typical one standard deviation shock:
    - Response of domestic inflation to positive shocks is higher by about 25 percent after one year relative to negative shocks.
    - Response is higher by about 140 percent after two years relative to negative shocks.
    - Persistence: positive shock effects last about two years; negative shock effects last about one year.
  - Large shocks (δ = 3):
    - Large negative shocks produce humped-shaped, very transitory effects lasting about 8 months.
    - Large positive shocks produce sizeable, gradual, and persistent increases in inflation for up to 27 months.
    - The normalized inflationary impact of a large positive shock is around 0.36 percent, 24 months after the shock.
      - This is around 52 percent higher than the impact of a typical one standard deviation positive shock over the same horizon.

- Emerging countries (selected quantitative patterns)
  - For a typical one standard deviation shock:
    - Response to positive shocks is lower by about 15 percent after one year relative to negative shocks.
    - Two years after the shock, effects of positive and negative shocks on domestic inflation are similar.
  - Large shocks (δ = 3):
    - Large negative shocks are humped-shaped, with inflation peaking at around 0.4 percent, 10 months after the shock.
    - Large positive shocks are more gradual, with inflation reaching around 0.4 percent, about 24 months after the shock.

- Low-income countries (selected quantitative patterns)
  - For a typical one standard deviation shock:
    - Response of inflation to positive shocks is higher by about 30 percent after 10 months relative to negative shocks.
  - Large shocks (δ = 3):
    - The inflationary impact of large positive fuel price shocks is more than 400 percent higher than that of negative fuel price shocks of the same magnitude, 18 months after the shock.
    - The normalized inflationary impact of a large positive shock is around 0.44 percent, 18 months after the shock.
      - This is around 30 percent higher than the impact of a typical one standard deviation positive fuel price shock over the same time horizon.

- Possible mechanisms for asymmetry
  - Wage rigidity: downward rigidity of nominal wages—workers resist wage cuts but accept increases—amplifies inflationary effects of positive shocks.
  - Price/markup rigidity: downward rigidity in output prices makes it easier for firms to increase markups than to decrease them.
  - Monetary policy interactions: negative fuel price shocks may allow monetary policy to ease and partially offset disinflationary impacts, while positive shocks can unanchor expectations and induce more persistent inflation.

### VI. Methodological and robustness notes
- Use of local currency fuel price avoids dividing by an endogenous variable.
- Local projection approach is robust to misspecification and to cases where Wold decomposition may not exist.
- Monte Carlo evidence supports the use of flexible projections with polynomial terms to approximate inherent nonlinearities.
- Bootstrap procedures: block bootstrap with 2000 replications for hypothesis testing; figures report 16th and 84th percentile bands (1000 replications in some figure notes).

### VII. Policy implications and conclusion
- Overall conclusions
  - On average, effects of fuel price changes are modest and do not contribute to a sustained impact on inflation.
  - Short- to medium-term effects vary considerably across income groups.
  - Magnitude and persistence of fuel price impacts on domestic inflation depend on energy intensity, wage flexibility, and central bank credibility.
  - Compelling evidence of asymmetry: price increases lead to more pronounced and more persistent inflationary effects than price decreases, especially in high-income and low-income countries.
  - Asymmetry holds for typical shocks, dissipates for small shocks, and is amplified for large shocks.
- Fiscal and coordination implications
  - Policy decisions that increase energy prices (including policies counteracting pollution and environmental damages) should consider the non-linearity in inflation responses.
  - Coordination with the Central Bank is key to avert negative macroeconomic consequences—especially considering the “timing” and the “size” of increases and the cycle of wage negotiations with labor unions—to avoid transforming a transitory supply-side shock into a demand-side shock with wage spiral effects and direct implications on monetary policy.

*Source: IMF staff analysis (wpiea2020093-print-pdf).*

### References  _______________________________________________________________________________________  29

### References

### Figures (listed)
- 1. Monthly Retail Fuel Prices _____________________________________________________________________ 12
- 2. Changes in Retail Fuel Prices and CPI Inflation ________________________________________________ 13
- 3. Dynamic Response of Inflation (accumulated) to a 1 Percent Fuel Price Shock ________________ 14
- 4. Dynamic Response of Inflation (accumulated) to a 1 Percent Fuel Price Shock  
  (Restricted Sample, in Percent) ________________________________________________________________ 14
- 5a. Dynamic Responses of Inflation (accumulated) to a 1 Percent Fuel Price Shock  
  (By Energy Intensity, in Percent) _______________________________________________________________ 17
- 5b. Dynamic Responses of Inflation (accumulated) to a 1 Percent Fuel Price Shock  
  (By Wage Flexibility, in Percent)  _______________________________________________________________  18
- 5c. Dynamic Responses of Inflation (accumulated) to a 1 Percent Fuel Price Shock  
  (By Monetary Policy Credibility, in Percent) ____________________________________________________ 19
- 6. Dynamic (non-linear) Responses of Inflation to Fuel Price Shocks  
  (High-income Countries) ______________________________________________________________________ 22
- 7. Dynamic (non-linear) Responses of Inflation to Fuel Price Shocks 
  (Emerging Countries) __________________________________________________________________________  23
- 8. Dynamic (non-linear) Responses of Inflation to Fuel Price Shocks 
  (Low-Income Countries) _______________________________________________________________________ 24
- 9. Summary of Dynamic Responses of Inflation to Positive and Negative Fuel Price Shocks  
  (High-income Countries, in Percent) ___________________________________________________________  25
- 10. Summary of Dynamic Responses of Inflation to Positive and Negative Fuel Price Shocks 
  (Emerging Countries, in Percent) ______________________________________________________________ 26
- 11. Summary of Dynamic Responses of Inflation to Positive and Negative Fuel Price Shocks  
  (Low-income Countries, in Percent)  ___________________________________________________________  27

### I. INTRODUCTION
- Context and motivation
  - Increasing recognition of broader environmental, fiscal, macroeconomic consequences of underpricing energy products (Clements et al., 2013; Coady, Parry, Sears, and Shang, 2015).
  - Fuel pricing central to policy debate since 2009 G20 commitments and reaffirmed in 2012 and the 2015 Paris Climate Agreement.
  - Concerns about adverse macroeconomic effects of energy price increases—particularly inflationary impacts on households' real purchasing power—impede reforms.

- Transmission channels from retail fuel price changes to consumer price inflation
  - Direct effect: higher retail gasoline price reduces household purchasing power in proportion to gasoline's share of the consumer basket; may be persistent given short-run inelastic energy demand (Labandeira, Labeaga, and López-Otero, 2017).
  - Indirect effect: energy (e.g., diesel, natural gas) used as inputs raises production costs and possibly electricity prices faced by firms—this aggregate supply channel can be important in energy-intensive economies.
  - The direct effect is often viewed as akin to an aggregate demand shock; the indirect effect as an aggregate supply shock.
  - Empirical consensus suggests the direct (demand-like) channel often dominates in practice (Kilian, 2008), though the quantitative importance of the supply channel remains open.

- Amplification mechanisms and policy interactions
  - Less flexible labor markets (centralized wage setting, powerful unions) can cause wage-price spirals that magnify fuel price shock effects.
  - Monetary policy response matters: accommodating transitory supply shocks can let them become permanent via unanchored inflation expectations or wage cycles, potentially necessitating contractionary monetary policy with growth costs.
  - Coordination between monetary and fiscal authorities may be important during energy subsidy reforms (timing, sequencing, size of fuel price increases) with implications for sustainability of reforms (Clements et al., 2013; Davis, 2014; Coady et al., 2015).

### II. LITERATURE REVIEW
- Two main shortcomings in prior work
  1. Focus on international crude oil prices rather than retail domestic fuel prices
     - Crude oil is not consumed directly by consumers and is not directly used as input outside refining; retail fuel prices are more relevant for households and firms (Kilian, 2008).
     - Transmission from global crude prices to retail domestic prices is not one-to-one except where prices are fully liberalized; domestic factors (pricing policies, taxation, exchange rates, country- or region-specific shocks like Hurricane Katrina) materially affect retail fuel prices.
     - Availability of high-frequency retail fuel price data is limited for emerging, developing, and low-income countries, hindering empirical research and increasing uncertainty around reform impacts.
  2. Insufficient attention to non-linearity and asymmetry
     - Effects of shocks may be non-linear: large increases may have different effects than small ones because economic agents adjust behavior only beyond certain magnitudes (Hamilton 1996, 2003).
     - Asymmetry between increases and decreases matters for designing automatic pricing mechanisms and for monetary policy responses—e.g., whether to accommodate supply-side decreases even when secondary effects materialize.
     - Existing studies mostly focused on advanced countries.

- Contribution of the study
  - Uses and updates monthly dataset of domestic retail fuel prices compiled in Kpodar and Abdallah (2017).
  - Focuses on heterogeneity by country-specific factors: income level, energy intensity, labor market flexibility, and central bank credibility.
  - Empirical approach: multivariate model capturing dynamic relations among variables and allowing for non-linearity; shocks to retail domestic fuel prices identified under the common assumption that innovations to domestic fuel price series (measured in local currency units) are predetermined with respect to macroeconomic variables.
  - Sample and scope: monthly data across a broad set of 110 countries over 2010 to 2016—including advanced, emerging, and developing countries.

### Key findings (as reported)
- i. The dynamic response of inflation to a retail domestic fuel price shock is generally modest and transitory.
  - For the full sample, a 1 percent shock to retail fuel prices leads to an increase of about 0.04 percent in the level of consumer prices, one year after the shock, and then decreases thereafter.
  - Responses vary significantly across country groups, with low income countries exhibiting the largest response (around

*Source: wpiea2020093-print-pdf - References*

### 0.06 percent), followed by emerging countries (around 0.036 percent) and advanced

### Dynamic Effects of Domestic Retail Fuel Price Shocks on Inflation (excerpt)

### Empirical approach and data
- Estimation strategy
  - Multivariate model variables: retail fuel prices (local currency), nominal effective exchange rate (NEER), consumer price index, short-term interest rate (lending rate).
  - Structural VAR representation (equation (1a)) and reduced-form (equation (1b)) are described; identification requires imposing restrictions on B0^{-1} (lower-triangular, fuel prices ordered first).
  - Primary estimation uses local projections (Jordà, 2005) to compute multi-step impulse responses directly (equations (2)–(4)); nonlinearities handled via polynomial terms in projections (equation (5)).
  - Identification assumption: retail fuel price changes are predetermined with respect to macro variables (supported by Kilian and Vega (2011) for monthly data).
  - Each local projection includes 12 lags of each endogenous variable, country fixed effects, an intercept, and a binary variable for the 2008–09 great recession.
  - Data transformations: all series in log first-differences except interest rate (first-differenced only).
  - Inference: standard errors clustered at country level, robust to heteroscedasticity and autocorrelation; non-parametric block bootstrap with 2000 replications for hypothesis testing; selected figures use 1000 bootstrap replications for confidence bands.

- Data and sample
  - Monthly domestic retail fuel prices from Kpodar and Abdallah (2017).
  - Sample period: 2000:1 to 2014:6.
  - Sample composition: 110 countries (31 high income countries, 42 emerging countries, 37 low income countries).
  - Unbalanced panel contains around 12600 observations.
  - Retail gasoline price used as primary fuel price variable; retail diesel produces similar results.
  - Restricted sample for non-energy inflation analysis: 77 countries (data on CPI excluding energy and headline CPI available).

### Key empirical findings — overall and by income level
- Full sample (accumulated responses to a normalized 1 percent fuel price shock)
  - One month after the shock: around 0.014 percent increase in inflation.
  - Peak response at eight months: around 0.04 percent.
  - Two years after the shock: decays to around 0.025 percent and is statistically insignificant.
  - Interpretation: spillovers to domestic inflation are modest and largely transitory.

- Heterogeneity by income group (peak/representative responses)
  - Low income countries: largest response of around 0.06 percent.
  - Emerging countries: around 0.036 percent.
  - Advanced (high-income) countries: around 0.025 percent.
  - Emerging countries display the most persistent and long‑lasting response among income groups.

- Non-energy inflation vs headline inflation (restricted sample of 77 countries)
  - Effects of fuel price shocks on non-energy inflation are positive and somewhat larger than on headline inflation.
  - Implication: fuel price shocks produce indirect and second-round effects that propagate into non-energy components.

### Role of economic fundamentals in explaining heterogeneity
- Energy intensity
  - Classification: country above median net inland quantity of energy consumed relative to total real output is "more energy intensive".
  - Peak accumulated inflation response for more energy intensive countries: 0.061 percent.
  - Peak accumulated response for less energy intensive countries: 0.027 percent.
  - Magnitude comparison: peak for more energy intensive group is around 120 percent higher than for less energy intensive group.

- Wage flexibility
  - Classification: WEF 2014 centralized collective bargaining indicator (1 centralized to 7 decentralized); above median = more flexible wages.
  - Peak accumulated inflation response for less flexible wages group: 0.069 percent.
  - Peak for more flexible wages group: 0.037 percent.
  - Magnitude comparison: peak for less flexible wages group is around 85 percent higher than for more flexible wages group.
  - Persistence: effects last more than two years for less flexible wages group vs around one year for more flexible wages group.

- Monetary policy credibility
  - Classification: Arnone et al (2009) Central Bank Autonomy index; above median = more credible monetary policy.
  - Peak accumulated inflation response for less credible monetary policy group: 0.059 percent.
  - Peak for more credible monetary policy group: half of 0.059 percent (i.e., the peak for less credible group is double that of the more credible group).
  - Persistence: effects last about two years for less credible group vs about one year for more credible group.
  - Implication: greater monetary policy credibility (e.g., commitment to low and stable inflation, adoption of inflation targets) helps anchor inflation expectations and limit persistence from fuel price shocks.

### Asymmetry and nonlinearity
- Asymmetric responses
  - Positive domestic fuel price shocks tend to have larger and more persistent impacts on inflation than negative shocks, especially for advanced and low-income countries.
  - Asymmetry is more pronounced for sufficiently large domestic fuel price shocks and essentially vanishes when shocks are small.

- Nonlinear specification
  - Local polynomial projections with polynomial terms allow impulse responses to vary by both sign and size of the fuel price shock and depend on local history (evaluated at the sample mean).
  - Rationale: flexible local projections provide a semi-parametric approximation to potentially asymmetric and nonlinear responses and are robust when VAR assumptions fail.

### Methodological and robustness notes
- Use of local currency fuel price avoids dividing by an endogenous variable.
- Local projection approach is robust to misspecification and to cases where Wold decomposition may not exist.
- Monte Carlo evidence (Jordà, 2005) supports the use of flexible projections with polynomial terms to approximate inherent nonlinearities.
- Bootstrap procedures: block bootstrap with 2000 replications for hypothesis testing; figures report 16th and 84th percentile bands (1000 replications in some figure notes).

*Source: IMF staff analysis (wpiea2020093-print-pdf).*

### section II. In this section, the shock size is now measured in terms of the standard deviation of

### section II. In this section, the shock size is now measured in terms of the standard deviation of

### Shock measurement and experiment design
- Shock size δ is measured in standard deviation units of the retail fuel price shock (휎
௚௔௦).
- Shock sizes considered:
  - δ ∈ ± {0.25, 1, 3}
  - Small shocks: δ = 0.25
  - Typical shocks: δ = 1 (one standard deviation)
  - Large shocks: δ = 3
- The standard deviation of retail fuel price shocks is equal to around 4, 5, and 4.5 percent, for high-income, emerging, and low-income countries in the sample.
- Impulse responses:
  - Are normalized by δ (the shock size in SD terms) for comparability.
  - Responses to negative shocks are multiplied by minus one for comparability.
  - Illustrated in figures 6, 7, and 8; summaries in figures 9, 10, and 11.

### Two overarching findings
- Positive and negative fuel price shocks have differential impacts on inflation in both magnitude and persistence; this asymmetry differs across income groups.
- The degree of asymmetry is at least partly related to the size of the fuel price shocks: asymmetry disappears for small shocks and is amplified for large shocks.

### High-Income Countries
- Main patterns:
  - Positive fuel price shocks lead to inflationary effects that are larger and more persistent than those from negative shocks.
  - For a typical one standard deviation shock:
    - Response of domestic inflation to positive shocks is higher by about 25 percent after one year relative to negative shocks.
    - Response is higher by about 140 percent after two years relative to negative shocks (Figure 6, Panel A).
  - Persistence:
    - Positive shock effects last about two years.
    - Negative shock effects last about one year.
- Size-related behavior:
  - Asymmetry disappears for small shocks (δ = 0.25).
  - Under large shocks (δ = 3):
    - Large negative shocks produce humped-shaped, very transitory effects lasting about 8 months, with quick reversion to pre-shock steady-state.
    - Large positive shocks produce sizeable, gradual, and persistent increases in inflation for up to 27 months.
    - The normalized inflationary impact of a large positive shock is around 0.36 percent, 24 months after the shock (Figure 6, Panel C).
      - This is around 52 percent higher than the impact of a typical one standard deviation positive shock over the same horizon.

### Emerging Countries
- Main patterns:
  - Positive fuel price shocks lead to inflationary effects that are initially smaller—in the short run—than those from negative shocks.
  - In the longer run, positive and negative shocks have similar impacts on domestic inflation.
  - For a typical one standard deviation shock:
    - Response to positive shocks is lower by about 15 percent after one year relative to negative shocks (Figure 7, Panel A).
    - Two years after the shock, effects of positive and negative shocks on domestic inflation are similar.
- Size-related behavior:
  - Asymmetry disappears for small shocks (δ = 0.25).
  - Under large shocks (δ = 3):
    - Large negative shocks are humped-shaped, with inflation peaking at around 0.4 percent, 10 months after the shock (Figure 7c, Panel C).
    - Large positive shocks are more gradual, with inflation reaching around 0.4 percent, about 24 months after the shock.

### Low-Income Countries
- Main patterns:
  - Positive fuel price shocks lead to inflationary effects that are bigger and more persistent than those from negative shocks.
  - For a typical one standard deviation shock:
    - Response of inflation to positive shocks is higher by about 30 percent after 10 months relative to negative shocks (Figure 8, Panel A).
- Size-related behavior:
  - Asymmetry disappears for small shocks (δ = 0.25).
  - Under large shocks (δ = 3):
    - The inflationary impact of large positive fuel price shocks is more than 400 percent higher than that of negative fuel price shocks of the same magnitude, 18 months after the shock (Figure 8, Panel C).
    - The normalized inflationary impact of a large positive shock is around 0.44 percent, 18 months after the shock (Figure 8, Panel C).
      - This is around 30 percent higher than the impact of a typical one standard deviation positive fuel price shock over the same time horizon.

### Possible mechanisms for asymmetry
- Wage rigidity:
  - Workers are potentially more sensitive to inflationary news than disinflationary news, implying downward rigidity of nominal wages (nominal wages flexible upward but sticky downward).
  - Workers refuse wage cuts but demand wage increases when faced with inflationary pressures.
- Price/markup rigidity:
  - Downward rigidity in output prices makes it easier for firms to increase markups than to decrease them.
  - Higher energy prices increase the aggregate price level due to downward sticky wages and prices; falling energy prices do not symmetrically reduce inflation.
- Monetary policy interactions:
  - These micro rigidities imply monetary policy may react asymmetrically.
  - Negative fuel price shocks can create downward pressure on (non-energy) inflation through the expectations channel, allowing monetary policy to ease and partially offset disinflationary impacts—explaining relatively smaller estimated impacts of negative shocks.

### Policy implications and conclusion (summary)
- Overall conclusions:
  - On average, effects of fuel price changes are modest and do not contribute to a sustained impact on inflation.
  - Short- to medium-term effects vary considerably across income groups.
  - Magnitude and persistence of fuel price impacts on domestic inflation depend on energy intensity, wage flexibility, and central bank credibility; wage flexibility and central bank credibility can amplify effects.
  - There is compelling evidence of asymmetry: price increases lead to more pronounced and more persistent inflationary effects than price decreases, especially in high-income and low-income countries.
  - Asymmetry holds for typical shocks, dissipates for small shocks, and is amplified for large shocks.
- Fiscal and coordination implications:
  - Policy decisions that increase energy prices (including policies counteracting pollution and environmental damages) should consider the non-linearity in inflation responses.
  - Coordination with the Central Bank is key to avert negative macroeconomic consequences—especially considering the “timing” and the “size” of increases and the cycle of wage negotiations with labor unions—to avoid transforming a transitory supply-side shock into a demand-side shock with wage spiral effects and direct implications on monetary policy.

*Source: section II and associated figures, wpiea2020093-print-pdf.*

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### Inflation, pass-through, and price dynamics
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- Potter, Simon M., 2000, “Nonlinear Impulse Response Functions,” Journal of Economic Dynamics & Control, Vol. 24, pp. 1425–46.

### Energy subsidies, fiscal risk, and policy implications
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### Econometric methods, identification, and inference
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- Koop, Gary, Hashem Pesaran, and Simon M. Potter, 1996, “Impulse Response Analysis in Nonlinear Multivariate Models,” Journal of Econometrics, Vol. 74, pp. 119–47.
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- Potter, Simon M., 2000, “Nonlinear Impulse Response Functions,” Journal of Economic Dynamics & Control, Vol. 24, pp. 1425–46.
- Stock, James H., and Mark W. Watson, 1999, "Forecasting Inflation," Journal of Monetary Economics, Vol. 44, No. 2, pp. 293–335.
- Kilian, Lutz, and Yun Jung Kim, 2009, "Do Local Projections Solve the Bias Problem in Impulse Response Inference?," Centre for Economic Policy Research (CEPR) Discussion Papers No. 7266.

*Source: wpiea2020093-print-pdf - REFERENCES*

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_Source: https://www.imf.org/-/media/files/publications/wp/2020/english/wpiea2020093-print-pdf.pdf_