## 1estea2022002

## Source details

**Canonical URL:** [1estea2022002](https://www.imf.org/-/media/files/publications/cr/2022/english/1estea2022002.pdf)

## Other formats

- [Markdown version](/-/media/files/publications/cr/2022/english/1estea2022002.pdf.md)
- [Structured JSON version](/-/media/files/publications/cr/2022/english/1estea2022002.pdf.json)

---

### Key findings: magnitude and comparative context
- Year-on-year HICP inflation through June 2022: Estonia 22 percent, Lithuania 20.5 percent, Latvia 19 percent, euro area 8.6 percent (relative to the 2 percent ECB target).
- Between January 2021 and June 2022, average monthly inflation: Estonia 1.3 percent, Lithuania 1.2 percent, Latvia 1.2 percent, euro area around 0.6 percent monthly.
- Estonia’s average monthly inflation rate in 2021–22 was 8-fold higher than its 2011–20 monthly average.
- During 2011–20, Estonia’s inflation averaged less than 0.2 percent per month and 2¼ percent annually.
- Core inflation (ECB preferred measure, excluding energy, food, alcohol, and tobacco) averaged 1.6 percent annually for Estonia in 2011–20; Estonia’s core inflation rose from 0.14 percent per month in 2011–20 to 0.6 percent per month in 2021–22 (through May).
- Core inflation average monthly pace in the first five months of 2022: Estonia 0.9 percent, Latvia 1.1 percent, Lithuania 1.1 percent, euro area 0.4 percent.

### Role of global commodity prices and empirical approach
- Global commodity movements and magnitudes:
  - Fuel price composite index increased almost 5 times over a 2-year period in 2022:Q2 relative to 2020:Q2, and by 2½ times relative to 2019:Q4.
  - International food prices increased by over 60 percent relative to pre-pandemic levels.
  - Natural gas prices increased 10 times in 2022:Q2 relative to 2020:Q2.
- Empirical approach: country-specific time series OLS regressions on monthly data from November 2010 through March 2022, regressing domestic HICPs (or components) on explanatory variables expressed in euros: (i) Brent oil prices; (ii) natural gas prices; and (iii) global food price index, with up to nine lags and seasonal/time dummies.
- Limitations noted: potential omitted variable bias, reverse causality, overfitting concerns, difficulty disentangling passthrough from concurrent demand and supply shocks; mitigants discussed in full analysis.

### Comparative passthrough to headline HICP (2010–22 (March), monthly data)
- Regression fit: adjusted R-squared around 0.6-0.65; commodity price coefficients consistently positive and statistically significant.
- Combined passthrough from oil, gas, and food (Total Size):
  - Estonia: Total Size 0.080 (Oil Size 0.018; Natural gas Size 0.008; Food Size 0.054). Oil Speed 3.0 months; Natural gas Speed 8.0 months; Food Speed 3.9 months.
  - Latvia: Total Size 0.057 (Oil Size 0.026; Natural gas Size 0.006; Food Size 0.025). Oil Speed 0.9 months; Natural gas Speed 9.0 months; Food Speed 4.0 months.
  - Lithuania: Total Size 0.052 (Oil Size 0.022; Natural gas Size 0.004; Food Size 0.026). Oil Speed 0.3 months; Natural gas Speed 5.0 months; Food Speed 5.0 months.
  - Euro-area: Total Size 0.038 (Oil Size 0.014; Natural gas Size 0.005; Food Size 0.019). Oil Speed 0 months; Natural gas Speed 5.0 months; Food Speed 7.0 months.
- Findings: combined passthrough comparable between Estonia and other Baltics, generally higher for the Baltics than for the euro area; Estonia has the highest estimated passthrough from global food prices to general consumer prices.

### Passthrough to components (exact estimates preserved)
- Energy HICP passthrough (Table 2):
  - Estonia: Oil Speed 3.1 months; Oil Size 0.139. Natural gas Speed 1.6 months; Natural gas Size 0.075. Total Size 0.213.
  - Latvia: Oil Speed 1.9 months; Oil Size 0.158. Natural gas Speed 2.2 months; Natural gas Size 0.028. Total Size 0.186.
  - Lithuania: Oil Speed 0.7 months; Oil Size 0.160. Natural gas Speed 2.6 months; Natural gas Size 0.088. Total Size 0.248.
  - Euro-area: Oil Speed 1.2 months; Oil Size 0.214. Natural gas Speed 2.0 months; Natural gas Size 0.017. Total Size 0.231.
  - Additional: Estonia’s energy component share in the HICP rose substantially in 2022 to almost 16 percent; euro area energy weight around 10 percent.
- Food HICP passthrough (Table 3):
  - Estonia: Food Speed 1.3 months; Food Size 0.156. Natural gas Speed 7 months; Natural gas Size 0.024. Total Size 0.180.
  - Latvia: Food Speed 0 months; Food Size 0.052. Natural gas Speed 8 months; Natural gas Size 0.017. Total Size 0.069.
  - Lithuania: Food Speed 3.4 months; Food Size 0.089. Natural gas Speed 7 months; Natural gas Size 0.014. Total Size 0.103.
  - Euro-area: Food Speed 1.4 months; Food Size 0.051. Natural gas Speed 7 months; Natural gas Size 0.006. Total Size 0.057.
  - Additional finding: increases in global natural gas prices have a statistically significant association with rises in domestic food prices for all comparators.
- Passthrough to core inflation:
  - Size of effect significantly smaller for core inflation than for headline for all countries.
  - Estonia’s passthrough coefficient for core inflation estimated to be less than half of that for headline passthrough; Estonia’s passthrough to core inflation is not the highest among the Baltics (it is lower than Lithuania’s).

### Mark-up model, cointegration, and benchmark regression results (selected exact coefficients)
- Mark-up framework embeds passthrough within prices as mark-ups over unit labor costs and imported and fuel prices; cointegration analysis shows a negative and statistically significant ECM.
- Combined passthrough from global commodity prices estimated at 0.08 in the benchmark monthly HICP model; alternative specification: 0.1 when domestic CPI is used instead of the HICP; quarterly model yields similar energy passthrough but not significant food passthrough.
- Selected coefficients and statistics (Table 4):
  - ECM t-1: -0.06*** (t-stat -3.57) monthly HICP; -0.05*** (t-stat -3.25) monthly Dom CPI; -0.26*** (t-stat -7.04) quarterly HICP.
  - △Brent t: 0.008*** (t-stat 3.17) monthly HICP; 0.010*** (t-stat 3.87) monthly Dom CPI; 0.031*** (t-stat 7.51) quarterly HICP.
  - △Brent t-1: 0.009*** (t-stat 3.45) monthly HICP; 0.011*** (t-stat 4.14) monthly Dom CPI; 0.009** (t-stat 2.16) quarterly HICP.
  - △Gas prices t-1: 0.007** (t-stat 2.59) monthly HICP; 0.006** (t-stat 2.41) monthly Dom CPI; 0.012*** (t-stat 3.74) quarterly HICP.
  - △Glob. food prices t-8: 0.040*** (t-stat 3.31) monthly HICP; △Glob. food prices t-7: 0.029** (t-stat 2.54) monthly Dom CPI.
  - Number of observations: 135 (monthly HICP), 135 (monthly Dom CPI), 43 (quarterly HICP).
  - R-squared overall: 0.72 (monthly HICP), 0.71 (monthly Dom CPI), 0.82 (quarterly HICP).
  - R-squared adj.: 0.68, 0.67, 0.78 respectively.
- Interpretation caveats: OLS regressions show correlations; short-term domestic factors proved statistically insignificant in headline HICP regressions though long-term domestic factors operate through unit labor costs.

### Wages, sectoral wage–price dynamics, and domestic drivers
- Headline inflation: regression analysis does not detect a significant relationship between Estonia’s wage growth and headline inflation.
- Core inflation: mixed indications of a positive relationship between wage growth and core inflation; significance not robust across samples and specifications.
- Food inflation and wages (Table 5):
  - Monthly regression: lagged wage growth coefficient 0.064*** (t-stat 5.01); Number of observations 135.
  - Quarterly domestic CPI regression: lagged wage growth coefficient 0.31*** (t-stat 4.09); Number of observations 43.
  - Interpretation: positive and highly significant relationship between lagged wage growth and domestic food price inflation.
- Services inflation and wages (Table 6, monthly 2010(11)–2022(3)):
  - Transportation: lagged wage growth 0.349*** (t-stat 3.11); R-squared overall 0.73; Number of observations 137.
  - Communications: lagged wage growth 0.030** (t-stat 2.67); R-squared overall 0.56.
  - Miscellaneous services: lagged wage growth 0.024** (t-stat 2.55); R-squared overall 0.35.
  - Interpretation: rising wages could trigger increases in services prices (transportation, communications, miscellaneous services).

### Sectoral contributions and composition effects (exact shares and changes)
- Energy HICP increases (December 2020 to May 2022): Estonia 97 percent, Latvia 65 percent, Lithuania 72 percent, euro area 52 percent.
- Energy accounted for over one-half (57 percent) of overall inflation in Estonia over DEC 2020–MAY 2022 (after adjusting for energy weight in the consumer basket).
- Energy’s direct contributions to overall inflation: Latvia and euro area about 50 percent, Lithuania about 40 percent.
- Energy weight in HICP ranged from 10 to 15 percent across these countries; Estonia’s energy component share rose to almost 16 percent in 2022.
- Food price inflation accelerated to 17 percent y/y in Estonia in May 2022; Latvia 19 percent, Lithuania 25 percent.
- Direct contribution of food to Estonia’s overall inflation about 17 percent; Latvia and Lithuania around 25 percent.
- Estonian authorities flagged potential measurement problems of electricity prices that may possibly overstate recent increases.

### Inflation breadth, dynamics, and asymmetries
- Inflation has become increasingly broad-based across the Baltics and the euro area.
- Estonia’s core inflation increased more than four-fold in the recent surge (from 0.14 percent per month to 0.6 percent per month).
- Recursive analysis suggests potential asymmetry: passthrough absolute size appears smaller during episodes when commodity prices are falling.

### Policy implications, challenges, and recommendations
- Overarching goal: prevent entrenchment of elevated inflation while mitigating distributional and growth costs.
- Monetary policy:
  - Rely on forthcoming normalization of the ECB’s monetary policy with a credible strategy to attain the 2 percent euro area-wide target to help steer inflation dynamics in Estonia.
  - Expect a disinflationary push from the reversal of the commodity price surge if it materializes as currently expected by the futures markets; Estonia’s high estimated passthrough may amplify the dampening effect but asymmetry cautioned.
- Fiscal and structural policies:
  - Consider tighter fiscal policies to restrain demand.
  - Structural policies in sectors where greater competitive forces or supply-side measures may moderate price pressures, notably in the energy sector.
  - Well-targeted and efficient measures of social support to the most vulnerable.
- Specific green-transition and carbon-pricing guidance:
  - Adopt a national-level carbon tax in non-ETS sectors as explored with the WB-IMF carbon pricing assessment tool (CPAT) framework.
  - CPAT quantitative findings: introducing a carbon taxation in non-ETS sectors could reduce by up to 18 percent the efforts needed to achieve Estonia’s NDC in 2030.
  - Carbon tax expected to have a positive net welfare effect over time, with climate, transport and air pollution co-benefits outweighing efficiency costs when revenue is recycled into targeted transfers and investments.

### Carbon tax scenarios, fiscal design, and macro outcomes (CPAT-based)
- IMF staff carbon tax scenario (CPAT-based):
  - Policy: Gradual phase-in of a US$75 carbon tax per tCO2e by 2030.
  - Phasing: The carbon tax is gradually phased in from $50 to $75 on non-ETS emissions over 2024-2030.
  - Revenue recycling: 75 and 25 percent of the carbon tax revenue levied is recycled into investment and transfers, respectively (alternative revenue recycling proportions are also analyzed).
  - Multipliers: Growth impacts based on investment and transfer multipliers of 0.9 and 0.5, respectively.
  - Result: Carbon pricing phased in as described supports mitigation goals and, with revenue recycling toward investment and transfers, can produce net positive welfare and favorable GDP growth impacts relative to baseline projections.
- CPAT simulation summary:
  - A gradual phase-in of a $75 per ton carbon tax from 2024 would reduce by about 18 percent the gap between the baseline GHG emissions in 2030 and Estonia’s NDC.
  - A $75 carbon tax per tCO2e phased in over 2024–2030 yields fiscal revenues and welfare benefits (efficiency costs, transport co-benefits, air pollution co-benefits, climate benefits) with a positive net effect as percent of GDP, and distributional effects that can be mitigated by recycling revenues into transfers and investments.

### Building and transport sectors — status, constraints, and policy levers
- GHG and energy facts (exact numeric benchmarks):
  - As of 2020, Estonia GHG emissions reduction was 72 percent relative to 1990 levels.
  - About 32 percent of Estonia’s energy use was derived from renewables (EC, 2022).
  - Transport sector (as of 2019 reporting context): transport emissions rose to double of 1992 level; transport emissions in 2019 reported as 9,199 kt of CO2e in preserved context.
  - Transport sector’s GHG emissions represented about 17 percent of net emissions in 2020; road transport about 98 percent of total transport emissions; of road transport emissions about three quarters from cars and one quarter from buses and trucks.
  - Transport emissions represented 28 percent of all domestically consumed energy as of 2019.
  - Buildings in 2019: contributed to 32 percent of total final consumption of energy and represented around 4 percent of total GHG emissions from the use of energy.
  - Space heating: 71.4 percent of households’ energy consumption.
  - Close to 90 percent of residences in bottom “D” and “E” categories of energy-performance standards.
  - About 9 percent of buildings constructed before 1990 (as of 2014).
  - Between 2000 and 2019, energy consumption in residential buildings increased by about 2.7 percent.
  - Potential energy savings from full renovation: heating consumption down by up to 70 percent; electricity consumption down by up to 20 percent.
  - IEA estimate: implementation of Estonia’s energy strategy could reduce transport energy consumption by up to 40 percent.
  - Estonia’s transport emissions ambition: reduce by 30 percent by 2030 compared to 2005.
  - Environment-related taxation revenue: 8.8 percent of total tax revenue in 2019.
  - KredEx support: up to 40 percent of renovation costs; 50 percent of costs for technical consultants; guarantees covering up to 80 percent of renovation financing.
  - EU Cohesion Policy Fund: finances up to 50 percent of total costs for apartment buildings built before 1993.
  - Required annual residential renovation rate: 2 percent (IEA) vs 0.5 percent actual in 2019.
- Transport policy levers:
  - Car taxation to encourage adoption of more efficient cars, including EVs; investments to expand public transport networks and encourage modal shift (policy plans cited).
  - Estonia does not currently have a carbon-based tax on transport fuels and there is no vehicle registration tax.
  - Public transportation represented about 20 percent of total distance travelled in 2019.
  - Estonia’s share of registered electric and hybrid vehicles is among the lowest in the EU; recommendations include expanding EV subsidies and charging infrastructure (including fast-charging and residential access).
  - Biomethane in public buses promoted through subsidies since 2015; share of biofuels in transport around 6 percent in 2019.
- Building-sector policy levers:
  - Scale up renovation programs to meet a 2 percent annual renovation rate: improve financing terms, expand KredEx support where appropriate, set up ESCOs, public large renovation projects to catalyze private renovations, and train construction-sector workers.
  - Compliance with nearly zero-energy standard (introduced in 2013) will boost efficiency over time if construction-sector skills are upgraded.

### Recommended policy package (concise bullets)
- Combine monetary normalization (ECB) and expected commodity price reversals with active fiscal and structural policies to prevent inflation persistence.
- Use tighter fiscal policy to restrain demand where needed, and structural reforms—especially in the energy sector—to reinforce disinflationary forces.
- Implement well-designed carbon pricing in non-ETS sectors with gradual phase-in (illustrative: $75 per ton from 2024), accompanied by:
  - Targeted transfers to protect low-income households and micro companies.
  - Revenue recycling into investments that accelerate renewable energy, EV charging infrastructure, and building renovations.
- Accelerate vehicle fleet renewal and fuel-efficiency improvements, expand public transport and rail electrification, and promote EV adoption with charging infrastructure investments.
- Strengthen building renovation programs, improve financing, catalyze private-sector renovation demand, and upgrade construction-sector skills to deliver energy savings and emission reductions.

*Source: RECENT DRIVERS OF INFLATION IN ESTONIA: A COMPARATIVE PERSPECTIVE WITH THE BALTICS AND EURO AREA (IMF staff analysis, August 8, 2022).*

### 1. Inflation and Infla tion Expectations in the Baltics and the Euro Area 2021–22_________ 3

### RECENT DRIVERS OF INFLATION IN ESTONIA: A COMPARATIVE PERSPECTIVE WITH THE BALTICS AND EURO AREA

### Key findings: magnitude and comparative context
- Year-on-year HICP inflation through June 2022: Estonia 22 percent, Lithuania 20.5 percent, Latvia 19 percent, euro area 8.6 percent (relative to the 2 percent ECB target).
- Between January 2021 and June 2022, average monthly inflation: Estonia 1.3 percent, Lithuania 1.2 percent, Latvia 1.2 percent, euro area around 0.6 percent monthly.
- Estonia’s average monthly inflation rate in 2021–22 was 8-fold higher than its 2011–20 monthly average.
- During 2011–20, Estonia’s inflation averaged less than 0.2 percent per month and 2¼ percent annually.
- Core inflation (ECB preferred measure, excluding energy, food, alcohol, and tobacco) averaged 1.6 percent annually for Estonia in 2011–20; Estonia’s core inflation rose from 0.14 percent per month in 2011–20 to 0.6 percent per month in 2021–22 (through May).
- Core inflation average monthly pace in the first five months of 2022: Estonia 0.9 percent, Latvia 1.1 percent, Lithuania 1.1 percent, euro area 0.4 percent.

### Role of global commodity prices
- Fuel price composite index (in US dollar terms) increased almost 5 times over a 2-year period in 2022:Q2 relative to 2020:Q2, and by 2½ times relative to 2019:Q4.
- International food prices increased by over 60 percent relative to pre-pandemic levels.
- Natural gas prices increased 10 times in 2022:Q2 relative to 2020:Q2.
- Global rises included metals, cotton, and fertilizers; these feed directly into consumer basket components and spillovers to other prices.
- Small open-economy characteristics and higher food shares, fuel intensities, and pre-existing inflation levels can amplify passthrough from commodity shocks (citing Gelos and Ustyugova (2012) and Rigobon (2010) for context).
- Empirical approach for passthrough: country-specific time series OLS regressions on monthly data from November 2010 through March 2022, regressing domestic HICPs (or components) on explanatory variables expressed in euros: (i) Brent oil prices; (ii) natural gas prices; and (iii) global food price index, with up to nine lags and seasonal/time dummies.

### Sectoral contributions and composition effects
- Energy HICP increases (December 2020 to May 2022): Estonia 97 percent, Latvia 65 percent, Lithuania 72 percent, euro area 52 percent.
- Energy accounted for over one-half (57 percent) of overall inflation in Estonia over DEC 2020–MAY 2022 (after adjusting for energy weight in the consumer basket).
- Energy’s direct contributions to overall inflation: Latvia and euro area about 50 percent, Lithuania about 40 percent.
- Energy weight in HICP ranged from 10 to 15 percent across these countries.
- Food price inflation accelerated to 17 percent y/y in Estonia in May 2022; Latvia 19 percent, Lithuania 25 percent, euro area lower (exact euro area food y/y not reported in source excerpt).
- Direct contribution of food to Estonia’s overall inflation about 17 percent; Latvia and Lithuania around 25 percent.
- In Estonia, energy price increases (including electricity tariff increases) were a major contributor to the difference with comparators; the Bank of Estonia highlighted potential measurement problems of electricity prices that may possibly overstate recent increases.

### Breadth and dynamics of inflation
- Inflation has become increasingly broad-based across the Baltics and euro area.
- Estonia’s inflation variability: higher standard deviation of monthly inflation relative to euro area and other Baltics (figure-based observation).
- Core inflation increased more than four-fold in Estonia during the recent surge (from 0.14 percent per month to 0.6 percent per month).
- During the recent surge, Lithuania’s core inflation peaked at 0.7 percent per month among the Baltics.

### Domestic drivers and interactions with external shocks
- While Estonia’s inflation has been largely driven by external factors (global commodity prices), domestic factors such as wage growth are statistically significant drivers of food and several services components of the CPI (statement of empirical finding; detailed regression estimates are presented later in the source).
- Other domestic and global contributors with substantial inflationary potential include:
  - supply chain disruptions;
  - large fiscal policy support packages implemented during COVID-19;
  - emergence of labor shortages during the COVID-19 crisis;
  - sustained expansionary monetary policy stances in advanced economies.
- The unprecedented size of commodity and general inflation surges requires holistic assessment to gauge potential for sustained inflationary pressures and to inform policy responses.

### Empirical approach and limitations
- Regression specification details: parsimonious general-to-specific modeling, starting with nine lags for all explanatory variables, sequential elimination of statistically insignificant variables at standard pre-set criteria; seasonal dummies and time dummies used as controls.
- Limitations of the global-variable-dominant approach noted: potential omitted variable bias, reverse causality, overfitting concerns, and difficulty disentangling passthrough from concurrent demand and supply shocks; mitigants are discussed in the full analysis.

### Policy implications (summary of discussion points)
- The large size of the inflation surge calls for broad-based policy response to prevent entrenchment of high inflation and associated economic consequences.
- Challenges arise for Baltic policymakers given euro area common monetary policy and the Baltics’ higher exposure to external commodity shocks.
- Better understanding of the episode would help clarify competitiveness and distributional effects relevant for policy design.

*Source: RECENT DRIVERS OF INFLATION IN ESTONIA: A COMPARATIVE PERSPECTIVE WITH THE BALTICS AND EURO AREA (IMF staff analysis, August 8, 2022).*

### 12.      The           gg                ’  global commodity passthrough to the headline

### 12.      The           gg                ’  global commodity passthrough to the headline

### Key empirical findings on passthrough to headline HICP
- Commodity price coefficients are consistently positive and statistically significant; adjusted R-squared of the regressions is around 0.6-0.65.
- Combined passthrough from changes in oil and gas prices:
  - Comparable between Estonia and the other Baltics, but generally higher for the Baltics than for the euro area.
- Estonia has the highest estimated passthrough from global food prices to general consumer prices, consistent with Estonia’s food price inflation being higher than that in the Baltic countries and the euro area over the last decade.
- Recursive analysis suggests potential asymmetry: passthrough absolute size appears smaller during episodes when commodity prices are falling.

### Comparative passthrough to headline HICP (Table 1, 2010–22 (March), monthly data)
- Estonia
  - Oil: Speed 3.0 months; Size 0.018
  - Natural gas: Speed 8.0 months; Size 0.008
  - Food: Speed 3.9 months; Size 0.054
  - Total Size 0.080
- Latvia
  - Oil: Speed 0.9 months; Size 0.026
  - Natural gas: Speed 9.0 months; Size 0.006
  - Food: Speed 4.0 months; Size 0.025
  - Total Size 0.057
- Lithuania
  - Oil: Speed 0.3 months; Size 0.022
  - Natural gas: Speed 5.0 months; Size 0.004
  - Food: Speed 5.0 months; Size 0.026
  - Total Size 0.052
- Euro-area
  - Oil: Speed 0 months; Size 0.014
  - Natural gas: Speed 5.0 months; Size 0.005
  - Food: Speed 7.0 months; Size 0.019
  - Total Size 0.038
- Notes:
  - 1/ Results based on OLS regressions of HICP on global commodity price benchmarks (in Euros).
  - 2/ In months, weighted average based on coefficients.
  - 3/ Sums of statistically significant coefficients at 5 percent.

### Passthrough to energy HICP (Table 2)
- Estonia
  - Oil: Speed 3.1 months; Size 0.139
  - Natural gas: Speed 1.6 months; Size 0.075
  - Total Size 0.213
- Latvia
  - Oil: Speed 1.9 months; Size 0.158
  - Natural gas: Speed 2.2 months; Size 0.028
  - Total Size 0.186
- Lithuania
  - Oil: Speed 0.7 months; Size 0.160
  - Natural gas: Speed 2.6 months; Size 0.088
  - Total Size 0.248
- Euro-area
  - Oil: Speed 1.2 months; Size 0.214
  - Natural gas: Speed 2.0 months; Size 0.017
  - Total Size 0.231
- Notes:
  - 1/ Based on OLS regressions of energy HICP on global energy price benchmarks.
  - 2/ In months, weighted average based on coefficients.
  - 3/ Sums of statistically significant coefficients at 5 percent.
- Additional points:
  - Estonia’s energy component share in the HICP rose substantially in 2022 to almost 16 percent, implying a larger impact of the same increase in domestic energy prices on broader inflation.
  - Energy passthrough in the euro area is relatively high, but the euro area’s lower energy weight (around 10 percent) implies a smaller impact on overall HICP compared with the Baltics.

### Passthrough to food HICP (Table 3, 2010-22 (March), monthly data)
- Estonia
  - Food prices: Speed 1.3 months; Size 0.156
  - Natural gas: Speed 7 months; Size 0.024
  - Total Size 0.180
- Latvia
  - Food prices: Speed 0 months; Size 0.052
  - Natural gas: Speed 8 months; Size 0.017
  - Total Size 0.069
- Lithuania
  - Food prices: Speed 3.4 months; Size 0.089
  - Natural gas: Speed 7 months; Size 0.014
  - Total Size 0.103
- Euro-area
  - Food prices: Speed 1.4 months; Size 0.051
  - Natural gas: Speed 7 months; Size 0.006
  - Total Size 0.057
- Notes:
  - 1/ Based on OLS regressions of food HICP on global commodity price benchmarks.
  - 2/ In months, weighted average based on coefficients.
  - 3/ Sums of statistically significant coefficients at 5 percent.
- Additional finding: For all comparators, increases in global natural gas prices have a statistically significant association with rises in domestic food prices, implying a small spill-over effect from gas to food.

### Passthrough to core inflation
- Estimated passthrough from global commodity prices to core inflation is moderately less significant for Estonia.
- The size of the effect is significantly smaller for core inflation than for headline inflation for all countries; Estonia’s passthrough coefficient for core inflation is estimated to be less than half of that for headline passthrough.
- Estonia’s passthrough to core inflation is not the highest among the Baltics (it is lower than Lithuania’s).

### Mark-up model and comprehensive inflation analysis
- A mark-up model (per De Brouwer and Ericsson (1995) and Ericsson (2009)) was employed to embed global commodity passthrough within a theoretical framework where prices are mark-ups over unit labor costs and imported and fuel prices.
- Cointegration analysis established long-term relationships between inflation, unit labor costs, and import prices; the cointegrating vector enters as a negative and statistically significant lagged error correction term (ECM).
- Key quantitative results (Table 4, benchmark monthly HICP regression model):
  - Combined passthrough from global commodity prices estimated at 0.08.
  - Alternative specification: 0.1 when domestic CPI is used instead of the HICP.
  - Quarterly model: similar coefficients for passthrough from global energy prices but fails to detect statistically significant passthrough for food prices.
- Selected coefficients and statistics from Table 4:
  - ECM t-1: -0.06*** (t-stat -3.57) monthly HICP; -0.05*** (t-stat -3.25) monthly Dom CPI; -0.26*** (t-stat -7.04) quarterly HICP.
  - △Brent t: 0.008*** (t-stat 3.17) monthly HICP; 0.010*** (t-stat 3.87) monthly Dom CPI; 0.031*** (t-stat 7.51) quarterly HICP.
  - △Brent t-1: 0.009*** (t-stat 3.45) monthly HICP; 0.011*** (t-stat 4.14) monthly Dom CPI; 0.009** (t-stat 2.16) quarterly HICP.
  - △Gas prices t-1: 0.007** (t-stat 2.59) monthly HICP; 0.006** (t-stat 2.41) monthly Dom CPI; 0.012*** (t-stat 3.74) quarterly HICP.
  - △Glob. food prices t-7: 0.029** (t-stat 2.54) monthly Dom CPI.
  - △Glob. food prices t-8: 0.040*** (t-stat 3.31) monthly HICP; 0.038*** (t-stat 3.29) monthly Dom CPI.
  - Number of observations: 135 (monthly HICP), 135 (monthly Dom CPI), 43 (quarterly HICP).
  - R-squared overall: 0.72 (monthly HICP), 0.71 (monthly Dom CPI), 0.82 (quarterly HICP).
  - R-squared adj.: 0.68, 0.67, 0.78 respectively.
  - Notes:
    - 1/ WTI price is used instead of Brent price in the quarterly model.
    - Seasonal/time dummies included.
    - *** , **, and * denote significance at 0.01, 0.05, and 0.1 levels respectively.
- Limitations and interpretation:
  - OLS regressions show correlations and do not by themselves test causal relationships unless supplemented by theory or additional tests.
  - Short-term domestic factors (output gap, wage growth, fiscal/monetary variables) proved statistically insignificant in headline HICP regressions, though long-term domestic factors operate through unit labor costs in the cointegrating relationship.
  - Data volatility and small-sample issues (e.g., monthly vs quarterly data availability) limit detection of short-term domestic relationships.

### Assessing the role of wages and wage-price dynamics
- Headline inflation:
  - Regression analysis does not detect a significant relationship between Estonia’s wage growth and headline inflation.
- Core inflation:
  - Some mixed indication of a positive relationship between wage growth and core inflation; relationship can be statistically significant in some samples but results are not robust across samples and specifications.
- Food inflation and wages (Table 5):
  - Regressing domestic food price growth on lagged wage growth and global food/gas prices yields:
    - Monthly: lagged wage growth coefficient 0.064*** (t-stat 5.01)
    - Quarterly domestic CPI: lagged wage growth coefficient 0.31*** (t-stat 4.09)
  - Key controls: growth in global food prices; quarterly specification also includes growth in global gas prices.
  - Number of observations: 135 (monthly), 43 (quarterly).
  - Interpretation: evidence of a positive and highly significant relationship between lagged wage growth and domestic food price inflation.
- Services inflation and wages (Table 6, monthly 2010(11)–2022(3)):
  - Services components with positive relationships to lagged wage growth:
    - Transportation: lagged wage growth 0.349*** (t-stat 3.11); R-squared overall 0.73; Number of observations 137.
    - Communications: lagged wage growth 0.030** (t-stat 2.67); R-squared overall 0.56.
    - Miscellaneous services: lagged wage growth 0.024** (t-stat 2.55); R-squared overall 0.35.
  - Other controls: global commodity prices, lagged dependent variable; seasonal/time dummies included.
  - Interpretation: rising wages could trigger increases in services prices (transportation, communications, miscellaneous services), consistent with the literature that services are less competitively priced and more wage-sensitive.

### Conclusions and policy implications
- Main conclusion:
  - Estonia’s inflation developments have a sizable role of passthrough from global commodity prices; Estonia’s estimated passthrough is broadly comparable to—but generally higher than—that of its Baltic neighbors due to higher food price passthrough. Baltic countries’ passthrough is higher than for the euro area.
- Cautionary notes:
  - Numerical estimates are sensitive to sample selection and specification methods, reflecting short sample sizes, rapid structural change, and data series limitations in small Baltic economies.
  - There may be a large structural break associated with the recent upshift in inflation levels that affects estimates.
- Domestic factors:
  - Conventional domestic factors (output gaps, wages, labor market developments, policy stances) do not show robust statistical association with Estonia’s headline inflation in recent years, but:
    - Long-term links exist between wages and prices via unit labor costs.
    - Short-term links are detected between lagged wage growth and food and several services components.
  - Absence of stronger statistical relationships may reflect data volatility, weaknesses during a period of previously low inflation, and real-time uncertainty over the output gap and monetary policy metrics in a currency union.

*Italicized source attribution: Republic of Estonia — International Monetary Fund (chapter content).*

### 26.      The recent  (and still ongoing) inflation spike has created significant policy challenges.

### 1estea2022002 - 26.      The recent  (and still ongoing) inflation spike has created significant policy challenges.

### Inflation spike: identified challenges
- Risks of reduced economic and investor confidence because of increased economic, real income, and policy uncertainty.
- Disruptions to private and public investment planning, including due to increases in construction costs.
- Adverse impact on income distribution since the high inflation has a particularly deleterious impact on the poor and the most vulnerable.
- Potential damage to the credibility of economic policies and frameworks, particularly if some of the other adverse effects of inflation are not well-contained.

### Policy guidance to prevent entrenchment of elevated inflation
- Implement policies that prevent an entrenching of elevated inflation while mitigating the effect of the increase in the price level in an efficient manner.
- Rely on forthcoming normalization of the ECB’s monetary policy with a credible strategy to attain the 2 percent euro area-wide target to help steer inflation dynamics in Estonia in the right direction.
- Expect a disinflationary push from the reversal of the commodity price surge if it materializes as currently expected by the futures markets; note Estonia’s high estimated passthrough may amplify the dampening effect, but caution is warranted due to the possibility of an asymmetric passthrough.
- Consider additional policy actions to amplify disinflationary forces:
  - Tighter fiscal policies to restrain demand.
  - Structural policies in sectors where greater competitive forces or supply-side measures may moderate price pressures, notably in the energy sector.
  - Well-targeted and efficient measures of social support to the most vulnerable as critical components of the policy package.

### Green transition and carbon taxation — objectives and findings
- The war in Ukraine has reinforced the need to accelerate the green transition and reduce dependence on fossil fuels in the EU.
- Estonia has substantially advanced toward achieving its Green Deal commitments, progress mostly driven by the restructuring of the oil shale industry, but energy security constraints could temporarily jeopardize this progress.
- Progress with GHG reductions in the transport and building sectors has remained modest; review shows room to further incentivize efficiency and promote greener energy sources and sustainability in these sectors.
- The paper explores adopting a national-level carbon tax in non-ETS sectors using the WB-IMF carbon pricing assessment tool (CPAT) framework.
- Key quantified findings from the CPAT analysis:
  - Introducing a carbon taxation in non-ETS sectors could reduce by up to 18 percent the efforts needed to achieve Estonia’s NDC in 2030.
  - A carbon tax will have a positive net welfare effect over time, with climate, transport and air pollution co-benefits outweighing the efficiency costs from introducing a new tax.
  - Revenue from carbon tax, when recycled in terms of targeted transfers and investments, is expected to promote higher and more inclusive growth than otherwise.

### Estonia’s GHG emissions status and targets
- National Determined Contributions (NDC) aim to reduce greenhouse gases by 70 percent by 2030 compared to 1990 levels and achieve climate neutrality by 2050.
- As of 2020, Estonia GHG emissions reduction was 72 percent relative to 1990 levels.
- As of end-2019 (reported): emissions concentrated in the energy sector (59 percent), followed by the transport sector (17 percent), and the agriculture sector (12 percent).
- The Just Transition Fund is expected to further accelerate the transition away from fossil fuels.

### Transport sector: trends and constraints
- Transport GHG emissions have steadily increased over the last 30 years and reached the double of their 1992 level, as of 2019 at 9,199 kt of CO2e (text reports “as of 20 9     9  tons of C  e” — preserved context: transport emissions rose to double of 1992 level).
- Transport sector’s GHG emissions represented about 17 percent of net emissions in 2020.
- In 2020 road transport, about 98 percent of total transport emissions, was the main driver of rising emissions.
  - Of road transport emissions about three quarters was emitted from cars and one quarter from buses and trucks.
- Transport emissions represented 28 percent of all domestically consumed energy as of 2019.
- Drivers and structural facts:
  - The number of vehicles—mostly passenger cars—and kilometers driven increased with rising living standards and income growth.
  - The fuel efficiency of Estonia’s passenger car stock is lower than in most European countries.
  - Emissions of new passenger cars declined by about 25 percent from 2010 to 2020, but the emission efficiency of new passenger cars in CO2/km has been below the EU average.
  - A third of the vehicle stock is 20-year-old or older; Estonia has the second-oldest stock of vehicles in the EU.

### Building sector: trends and constraints
- In 2019, buildings contributed to 32 percent of total final consumption of energy and represented around 4 percent of total GHG emissions from the use of energy.
- Building GHG emissions have been broadly stable since the early 1990s, reflecting limited progress compared to other EU countries.
- Building GHG emissions mostly came from heat and electricity consumption, with electricity accounting for 20 percent of energy consumption.
- Residential buildings represent three quarters of the total building floor area and account for most of the energy demand and GHG emissions of the building sector.
- As of 2018, space heating accounted for the largest share (59 percent) of the building sector’s energy consumption.
- Between 2000 and 2019, energy consumption in residential buildings increased by about 2.7 percent, partly due to the increase in the number dwellings.

### Policy implications and recommended focus areas
- Combine monetary normalization (ECB) and expected commodity price reversals with active fiscal and structural policies to prevent inflation persistence.
- Use tighter fiscal policy and sectoral structural reforms—especially in energy—to reinforce disinflationary forces.
- Implement a well-designed carbon tax in non-ETS sectors, supported by sectoral policies:
  - Carbon tax can reduce NDC effort requirements (up to 18 percent reduction to reach NDC by 2030).
  - Proper revenue recycling (targeted transfers and investments) can deliver net positive welfare effects and more inclusive growth.
- Accelerate policies to improve vehicle fuel efficiency, renew the vehicle fleet, and promote public transport and rail to curb transport emissions.
- Scale up building-sector efficiency measures to reduce the large share of energy consumption from space heating and residential demand.

*Italic source: chapter excerpt from the IMF PDF "1estea2022002 - 26.      The recent  (and still ongoing) inflation spike has created significant policy challenges."*

### 10.      GHG emissions reduction in the building sector has been modest, despite a

### 10. GHG emissions reduction in the building sector has been modest, despite a comparatively moderate reliance on carbon-emitting fuels

### Building-sector emissions and energy-efficiency findings
- GHG emissions in the building sector are driven by space heating (71.4 percent of households’ energy consumption).
- Estonia’s building stock efficiency is among the lowest in Europe with close to 90 percent of residences falling into the bottom “D” and “E” categories of the energy-performance standards.
- Estonia’s energy use for residential space heating in 2019 is comparatively higher than in other EU countries and higher than in Nordic countries, suggesting lower energy efficiency.
- Buildings’ energy inefficiency is mostly attributable to Estonia’s old residential building stock with about 9 percent of buildings constructed before 1990 (as of 2014).
- Government studies suggest that fully renovating buildings would lower heating consumption by up to 70 percent and electricity consumption by up to 20 percent (MEAC, 2020).
- The 2013 building code introduced nearly “zero-energy standard” with which new public and private sector buildings must comply from 2019 and 2021, respectively.

### Transport-sector policies and findings
- National Development Plan for the Energy Sector 2030 and the Transport and Mobility 2021–2035 plan include: (i) car taxation to encourage adoption of more efficient cars, including electric vehicles (EV); and (ii) investments to expand public transport networks and encourage modal shift (MEAC).
- The IEA estimates that the implementation of Estonia’s energy strategy could reduce transport energy consumption by up to 40 percent (IEA).
- Estonia’s Transport and Mobility 2021–2035 Masterplan aims to reduce transport emissions by 30 percent by 2030 compared to 2005, while not exceeding total vehicle fuel consumption levels recorded in 2012.
- Estonia’s environment-related taxation revenue stood at 8.8 percent of total tax revenue in 2019, above the EU average, but this revenue is limited by a narrow base mostly consisting of excise tax on road fuels.
- Estonia does not currently have a carbon-based tax on transport fuels and there is no vehicle registration tax.
- Public transportation represented about 20 percent of total distance travelled in 2019, close to the EU average; the share of public transport use has started to fall from end-2016.
- Policies to promote EV adoption could be expanded; Estonia’s share of registered electric and hybrid vehicles is among the lowest in the EU. Public sector investments in charging infrastructure, including fast-charging stations with focus on residential access, are recommended.
- Estonia has promoted biomethane in public buses through subsidies since 2015 and grants/subsidies since 2018, yet the share of biofuels used in transport stood around 6 percent in 2019.

### Building-sector policies and renovation market
- The government supports energy efficiency through guarantees and subsidies via KredEx:
  - Up to 40 percent of renovation costs of apartment associations and homeowners.
  - 50 percent of the costs related to hiring technical consultants or renovation supervisors.
  - Guarantees covering up to 80 percent of renovation financing for higher-risk buildings.
- EU Cohesion Policy Fund finances up to 50 percent of total costs of apartment buildings built before 1993 (ODYSSEE, 2021).
- Improving long-term credit terms for renovation would mitigate the impact of high upfront renovation costs.
- The IEA estimates that to achieve Estonia’s National Energy Strategy, the annual renovation rate in the residential building stock would need to be 2 percent, which is higher than the 2019 renovation rate (0.5 percent).
- Policy measures to create an active renovation market include:
  - Setting up energy service companies (ESCOs).
  - Public-sector large renovation projects to catalyze private renovations.
  - Training and skills upgrades of construction sector workers to meet higher renovation demand.
- Compliance with the nearly zero-energy standard will boost efficiency over time if construction-sector skills are upgraded.

### Carbon pricing for non-ETS sectors: costs, benefits, and simulations
- Estonia’s existing carbon tax is EUR 2 per ton of eCO2 and applies to CO2 emissions from thermal energy producers except biofuel emissions; it has a comparatively lower rate and coverage among EU countries.
- Several EU countries consider introducing carbon pricing covering non-ETS sectors; Estonia could consider a national carbon pricing scheme for non-ETS sectors.
- Trade-offs: in the near term, carbon pricing could exacerbate high and volatile energy prices created by supply bottlenecks and the war in Ukraine; as pressure on energy prices recedes, national carbon pricing could be considered as part of broader mitigation strategy with protections for low-income households and micro companies.
- CPAT simulation: a gradual phase-in of a $75 per ton carbon tax from 2024 would:
  - Be consistent with the recommended level by the High-Level Commission on Carbon Prices (Stern-Stiglitz 2017).
  - Reduce by about 18 percent the gap between the baseline GHG emissions in 2030 and Estonia’s NDC.
  - Yield a net welfare effect expected to be positive, with climate benefits and transport and air pollution co-benefits outweighing the efficiency costs over the medium to long-term.

### Fiscal revenue, distributional effects, and revenue recycling
- A carbon tax would have a relatively higher impact on energy consumption for low-income households due to the larger share of inelastic energy demand in their expenditure baskets (e.g., heating, transport).
- Distributional burdens could be mitigated through targeted transfers financed through carbon tax revenue.
- Simulations show that recycling carbon tax revenue into transfers and investments would:
  - Mitigate distributional impacts.
  - Support the transition to renewable energy and greater efficiency.
  - Generate higher and more inclusive growth if a higher share of recycled revenue is allocated to investments.
- Fiscal revenue projections (CPAT/IMF staff calculations):
  - Show fiscal revenues from a gradual phase-in of a $75 carbon tax, by fuel and total (Billion of USD; percent of GDP) over 2024–2030, with net total and breakdown by fuel (natural gas, non-road oil, gasoline, diesel, LPG & kerosene).
- Welfare impacts (CPAT/IMF staff calculations):
  - Welfare benefits for a $75 carbon tax per tCO2e by 2030 are composed of efficiency costs, transport co-benefits, air pollution co-benefits, and climate benefits, with a positive net effect as percent of GDP.
  - Distributional chart shows relative mean consumption effect across income deciles in 2030 from the linear phase-in of the $75 carbon tax over 2024–2030.

### Key numerical benchmarks and projections (preserved exactly)
- Space heating: 71.4 percent of households’ energy consumption.
- Close to 90 percent of residences in bottom “D” and “E” categories.
- About 9 percent of buildings constructed before 1990 (as of 2014).
- IEA estimate: reduce transport energy consumption by up to 40 percent.
- Estonia’s transport emissions ambition: reduce by 30 percent by 2030 compared to 2005.
- Environment-related taxation revenue: 8.8 percent of total tax revenue in 2019.
- KredEx support: up to 40 percent of renovation costs; 50 percent of costs for technical consultants; guarantees covering up to 80 percent of renovation financing.
- EU Cohesion Policy Fund: finances up to 50 percent of total costs for apartment buildings built before 1993.
- Required annual residential renovation rate: 2 percent (IEA) vs 0.5 percent actual in 2019.
- Potential energy savings from full renovation: heating consumption down by up to 70 percent; electricity consumption down by up to 20 percent.
- Estonia carbon tax: EUR 2 per ton of eCO2 (applies to thermal energy producers except biofuel emissions).
- Illustrative carbon tax: gradual phase-in of $75 per ton of CO2 equivalent from 2024; reduces the 2030 NDC gap by about 18 percent.

### Policy recommendations (summary)
- Strengthen building renovation programs to achieve an annual renovation rate of 2 percent, including:
  - Improve financing terms and expand KredEx support where appropriate.
  - Promote ESCO markets and public-sector renovation projects to catalyze private demand.
  - Invest in training and skills upgrades in the construction sector to meet renovation needs.
- Consider complementary carbon pricing for non-ETS sectors, with a gradual phase-in (illustrative: $75 per ton from 2024) as part of a broader mitigation strategy, while:
  - Protecting low-income households and micro companies via targeted transfers financed by carbon-tax revenue.
  - Recycling revenues to investments that accelerate renewable energy, charging infrastructure, and renovation markets.
- Expand incentives and infrastructure for electric vehicles:
  - Extend and expand EV subsidy programs.
  - Accelerate investments in charging infrastructure, including fast-charging and residential access.
  - Adopt well-communicated tighter emissions standards with a long-term timetable.
- Further shift mobility towards public transport and electrification:
  - Expand rail services and electrify rail network beyond main lines.
  - Invest in electric buses and charging infrastructure and continue biomethane support where cost-effective.
- Use combined sectoral policies (taxation, subsidies, infrastructure, market development) to maximize co-benefits (transport and air pollution) and minimize distributional burdens.

*Source: IMF staff summary of the chapter "GHG emissions reduction in the building sector has been modest, despite a comparatively moderate reliance on carbon-emitting fuels."*

### 24.      The war  in Ukraine calls for accelerating the green transition. As of 2020, GHG emissions

### The war in Ukraine calls for accelerating the green transition

### GHG emissions and energy mix
- As of 2020, GHG emissions in Estonia were reduced by 72 percent compared to 1990 levels, mostly owing to the restructuring oil-shale sector.
- About 32 percent of Estonia’s energy use was derived from renewables (EC, 2022).
- The war in Ukraine strengthens the case for accelerating the green transition and continuing oil-shale restructuring despite short-term trade-offs between energy security and climate policy.
- Replacing oil shale in electricity production with low- and zero-carbon electricity sources (e.g., wind power, use of biomass) will help achieve GHG mitigation objectives.
- Achieving climate objectives requires accelerating implementation of Estonia’s comprehensive climate policies in line with the REPowerEU plan, especially in the transport and building sectors.

### Transport sector policies
- Policies should further incentivize energy efficiency and sustainability in the transport sector by:
  - Promoting greater vehicle efficiency.
  - Promoting low-carbon transport.
  - Investing in the expansion and electrification of public transport.
- Existing policies and regulations could be complemented by a broader environmental taxation, beyond excise duties, to further incentivize efficiency and the renewal of the road vehicle stock.

### Building sector policies
- Renovations to improve energy efficiency in the building sector should be further incentivized.
- Reducing buildings’ energy demand will require accelerating renovations to increase energy efficiency, which should be supported by an adequate market capacity to provide requisite services.

### Carbon pricing analysis and fiscal design
- A comprehensive and predictable carbon pricing strategy remains critical to achieve emissions targets.
- Calculations based on the IMF-WB CPAT tool demonstrate that adoption of carbon pricing in the building and transport sectors—after high energy prices abate—would help achieve mitigation goals while also generating a net positive welfare effect.
- The revenue generated by carbon pricing could be recycled into targeted transfers to alleviate distributional effects and into green investments to further accelerate the green transition.

### IMF staff carbon tax scenario (CPAT-based)
- Policy: Gradual phase-in of a US$75 carbon tax per tCO2e by 2030.
- Phasing: The carbon tax is gradually phased in from $50 to $75 on non-ETS emissions over 2024-2030.
- Revenue recycling: 75 and 25 percent of the carbon tax revenue levied is recycled into investment and transfers, respectively (alternative revenue recycling proportions are also analyzed).
- Multipliers: The growth impacts are based on investment and transfer multipliers of 0.9 and 0.5, respectively.
- Result: Carbon pricing phased in as described supports mitigation goals and, with revenue recycling toward investment and transfers, can produce net positive welfare and favorable GDP growth impacts relative to baseline projections.

*Source: IMF staff analysis (Carbon Pricing Assessment Tool) and Estonia country section.*

---


_Source: https://www.imf.org/-/media/files/publications/cr/2022/english/1estea2022002.pdf_