## IMF WORKING PAPERS High Inflation in the Baltics — Executive Summary

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---

### Key findings on inflation drivers
- Headline inflation surged in 2022 to 17.2 percent in Latvia, 19.4 percent in Estonia, and 18.9 percent in Lithuania; the overall euro area average for the same period was 8.4 percent.
- Inflation in the Baltics is largely driven by global factors, with substantial contributions from energy and food prices.
- The average weights in CPI baskets are 16.4 for energy and 29.3 for food in the Baltics, versus 10.2 for energy and 20 for food in the euro area average.
- In 2022, energy accounted for about 8.5 percent of overall inflation in the Baltics on average, compared to 4.1 percent in the euro area.
- In 2022, the food price component in the HICP accounted for about 5.5 percent on average in the Baltics, compared to 1.9 percent in the euro area.
- Latvia has the higher share of energy and food in its consumer price index basket among the three Baltic countries.
- Much of the rise in inflation can be linked to the large increase in energy and food prices and to the Baltics’ small size and high economic openness, which expose them to external developments.

### Monetary policy, fiscal policy, and policy effectiveness
- As part of the euro area, monetary policy is set by the European Central Bank (ECB) for the area as a whole and is, effectively, exogenous to region-specific Baltic macroeconomic factors.
- Over the past few years, including the period before COVID-19, the cyclical position of the Baltic countries was more advanced than the euro area average; the stance of the ECB, while appropriate for the euro area as a whole, was too loose for Estonia, Latvia, and Lithuania specifically.
- Given the limited scope for country-specific monetary policy, fiscal policy is the main macroeconomic stabilization tool available to the Baltics.
- Empirical results show that, through its impact on domestic demand, fiscal policy has a statistically significant impact on inflation rates across the three Baltic countries.
- The effectiveness of fiscal policy is nevertheless constrained by the high openness of these economies.

### Risks to competitiveness and wage-productivity dynamics
- High and persistent inflation risks inducing high nominal and real wage growth in non-tradables and above-productivity wage growth in the exporting sector, which would erode competitiveness and growth if sustained.
- To date, persistent wage growth pressures significantly above the euro area have not materialized into a loss of competitiveness, but a more persistent shock could lead to larger and persistent second-round effects, affecting inflation expectations and wage negotiations.
- Tight labor markets across the Baltics exacerbate risks of wage pressures.
- During recent years, inflation expectations remained anchored in the Baltics, resulting in significant negative real wage growth while inflation was elevated.

### Data (coverage and measurement)
- Sample: quarterly data from the first quarter of 2000 to the last quarter of 2022.
- Sources: World Economic Outlook (WEO) database and Eurostat.
- Domestic variables: real GDP growth, inflation, nominal wage growth, and economic slack (domestic economic slack is measured by the unemployment gap — deviation from the Hodrick-Prescott —HP— filtered unemployment rate).
- Global variables: oil prices, global food prices, world real GDP growth, and the real effective exchange rate (REER).
- Measurement conventions:
  - All variables other than the real effective exchange rate are expressed as year-on-year growth rates in percentage points.
  - The real effective exchange rate is included in logs. An increase in the real effective exchange rate corresponds to a real appreciation of the domestic currency.
- Note on energy price indicator: the oil price is used as an indicator of energy price shocks. There is a very high positive correlation (about 0.9 between 2019-2023) between oil prices and electricity prices.

### Empirical methodology
- SVAR framework:
  - Structural form: A0 y_t = μ + A1 y_{t-1} + … + Aρ y_{t-ρ} + ε_t
  - Endogenous variables: oil price growth, inflation, food price growth, domestic real GDP growth, domestic economic slack, nominal wage growth, the real effective exchange rate, world real GDP growth.
  - Identification: sign restrictions and zero restrictions to identify five structural shocks: global (supply) shocks (oil and food prices); global (demand) shock (world real GDP growth); domestic (demand) shock (real GDP growth); domestic (supply) shock (domestic CPI).
  - Analysis focuses on the global supply shock to oil prices and the domestic demand shock to real GDP growth.
- Fiscal-analysis VAR:
  - Quarterly VAR with sign restrictions (Uhlig 2005) and the baseline including four lags (lag selection by AIC).
  - Endogenous variables for fiscal analysis: real GDP growth (log difference of real GDP), effective interest rates (Wu-Xia shadow rate), change in inflation (difference in core or headline inflation), growth of the primary balance as percentage of (potential) GDP.
  - Identification assumptions: a contractionary fiscal policy (increase in the primary balance) lowers GDP growth and decreases inflation; a positive aggregate demand shock raises inflation.

### Key empirical results — global and domestic shocks
- Global (oil) shocks:
  - A 5 percentage point increase in oil prices increases inflation in the Baltics by around 0.3–0.4 percentage points (significantly above the euro area, 0.1 percentage points).
  - The oil price shock leads to a 0.7–0.8 percentage point contraction in output in the Baltics (0.5 percentage points in the euro area).
  - The oil price shock leads to a 1 percentage point decline in nominal wage growth in Lithuania after the third quarter (impact on wage growth is not statistically significant in Estonia and Latvia).
  - In the euro area, the oil price shock leads to a decline in nominal wage growth (marginally significant).
- Domestic (real GDP) shocks:
  - A one standard deviation shock to domestic real GDP—around 0.7–0.8 percentage points of growth in the Baltics and 0.6 percentage points in the euro area—increases inflation by around 0.3–0.4 percentage points in the Baltics, well above the 0.1 percentage point impact in the euro area.
  - The increase in output raises wage growth in Estonia by around 1 percentage point and leads to a transitory rise in euro area wage growth (impact is statistically insignificant for Latvia and Lithuania).
- Variance decomposition (inflation):
  - Global factors (oil price growth, food price growth, and world real GDP growth) explain about 37 percent of the variance of inflation.
  - Domestic factors (domestic real GDP growth and domestic prices) account for about 25 percent of the variance of inflation.
- Robustness:
  - Robustness checks on a shorter sample for the post GFC period (2011-2020) show similar results.

### Impact of fiscal policy on inflation (empirical findings)
- A positive one-standard deviation shock to the primary balance corresponds to a tightening of fiscal policy of 2.4, 3.2 and 2.9 percentage points of (potential GDP) for Estonia, Lithuania, and Latvia respectively.
- A fiscal tightening has an immediate negative impact on both headline and core inflation rates:
  - The impact on headline inflation is about twice that on core inflation: 0.4-0.7percentage points for headline and 0.2 to 0.4 percentage points for core.
  - The disinflationary effect is driven by the impact of fiscal policy on domestic demand through a negative and significant impact on GDP two quarters after the shock in Lithuania and Latvia (the impact on Estonia is not statistically significant).
- Per 1 percentage point increase in the primary balance as a percentage of potential GDP:
  - Linked reductions in headline inflation by 0.5 to 1.4 percentage points and in core inflation by 0.6 to 1.5 percentage points.
- Impulse response magnitudes and elasticities (selected reported entries):
  - Estonia (Core): At t=0 -0.68*; Peak -0.68*; Long Term -0.01; Elasticity -1.41
  - Estonia (Headline): At t=0 -0.36*; Peak -0.36*; Long Term 0.01; Elasticity -1.52
  - Latvia (Core): At t=0 -0.62*; Peak -0.62*; Long Term -0.02*; Elasticity -0.83
  - Latvia (Headline): At t=0 -0.19*; Peak -0.19*; Long Term 0.01; Elasticity -0.54
  - Lithuania (Core): At t=0 -0.41*; Peak -0.41*; Long Term -0.01; Elasticity -0.48
  - Lithuania (Headline): At t=0 -0.29*; Peak -0.29*; Long Term 0.00; Elasticity -0.71
- Duration and dynamics:
  - The impulse response of headline inflation to a primary balance shock becomes statistically insignificant after 7 to 8 quarters in Estonia and Latvia, while this disinflationary effect only lasts 2 quarters in Lithuania.
  - The impact on core inflation is short-lived in all three countries, lasting only 1-2 quarters.
  - Overall, fiscal policy shocks have no long-term impact on inflation rates as the impulse responses in headline inflation rates are not statistically different from zero after 8 quarters (2 quarters for core inflation).
  - The shadow interest rate (Krippner) decreases by about 0.3 percentage points in the few quarters following the fiscal contraction, with the decrease slowly fading away.

### Wage–productivity nexus (manufacturing/tradeable sector)
- Data and measurement:
  - Quarterly data from 2000Q1 to 2022Q4 from Eurostat, OECD, and the IMF WEO.
  - Real wage = compensation per thousand employees (or wages and salaries) deflated by HICP or GDP deflator.
  - Labor productivity = real value added per hours worked.
  - Methods: cointegration and error-correction models (Engle-Granger two-step).
- Long-run co-movement:
  - There is a robust long-run (cointegration) relationship between real wages and labor productivity in manufacturing for all three Baltic countries over 2000Q1-2022Q4.
  - Estimated long-run coefficients (narrative):
    - Estonia: coefficient below one; reported as 0.87.
    - Lithuania: coefficient below one; reported as 0.72.
    - Latvia: coefficient above one in a statistically significant way with an estimated lower bound of 1.2.
- ADF test results (2000Q1-2022Q4) for wage measures (selected reported values):
  - Wage measured as compensation of employees, without crisis dummy:
    - Lithuania ** -2.16
    - Latvia ** -2.30
    - Estonia *** -2.85
  - Wage measured as wages and salaries, without crisis dummy:
    - Lithuania * -1.86
    - Latvia *** -3.06
    - Estonia *** -3.07
  - Critical values (ADF): 1% -2.60; 5% -1.95; 10% -1.61
- Short-run error-correction dynamics:
  - Short-run deviations from the long-term wage–productivity relationship have tended to be self-correcting for Estonia and Lithuania.
  - Speed of reversion to long-term equilibrium:
    - Estonia: about 3 quarters.
    - Lithuania: about 6 quarters.
  - Latvia: short-run dynamics are more inconclusive; parameters of short-run models are not (all) significant, indicating a more muted short-term reversion and the possibility that short-term deviations may be permanent.
- Reported LR coefficient estimates (selected reported entries):
  - LTU 0.72 (narrative); reported table values include 0.63*** / 0.75*** / 0.82*** / 0.71***.
  - LVA 1.28 (narrative lower bound 1.2); reported table values include 0.63*** / 1.27*** / 0.83*** / 1.1***.
  - EST 0.87 (narrative); reported table values include 0.63*** / 0.9*** / 0.64*** / 0.78***.

### Labor market flexibility and institutional factors
- Estonia’s faster wage adjustment to productivity is associated with a relatively more flexible labor market, notably the ease to dismiss regular workers (EPL indicator) and early reforms (2009-2010).
- Lithuania progressed with key labor market reforms in 2017-18.
- Latvia appears to have the least flexible labor market, with EPLs among the most stringent in Europe and limited recent progress with reforms (over 2014-2019).
- Wages in the Baltics are mostly determined at the firm-level rather than industry-level; collective bargaining coverage is low.
- Employer perceived labor market shortages (EC survey) tend to be lower than the EU average during downturns and higher in boom periods.

### Conclusions and policy implications
- Inflation in the Baltics is mainly driven by global factors, but domestic demand matters as well, implying fiscal policy can play a role in containing inflation.
- Being part of the euro zone, the Baltic countries lack monetary autonomy and depend on the ECB’s monetary policy stance for the euro area; the ECB’s contractionary stance came late and not strong enough for Baltic-specific circumstances, though the 2022 tightening helped reduce inflationary pressures.
- Fiscal policy is the main domestic macroeconomic stabilization tool left to address inflationary pressures in the Baltics.
- Fiscal policy stance recommendation (empirical basis):
  - Given the balance of risks and the impact of fiscal policy on inflation through domestic demand, a tighter fiscal stance would actively contribute to lower inflation in the current context.
  - Structural policies such as setting moderate minimum and public sector wages can help mitigate the risk of higher wage growth because of their role as references in private sector wage negotiations and their influence on inflation expectations.
- Competitiveness and wage risks:
  - Persistently higher inflation than in the euro area, above what would be justified by productivity gains, could make inflation expectations adjust upwards and perpetuate price and wage increases.
  - If past patterns hold:
    - Estonia and Lithuania can temporarily absorb wages above productivity without a long-term impact on competitiveness (short-term deviations are self-correcting).
    - Latvia has significantly less capacity to absorb such deviations because wage growth has on average outpaced productivity and short-term deviations show less evidence of self-correction.
  - Lower labor market flexibility in Latvia raises greater risks to competitiveness and convergence relative to Estonia and Lithuania.
- Policy priorities:
  - Fiscal policy should be the primary macro-stabilization tool in the Baltics given the constraints on country-specific monetary policy.
  - Policymakers should guard competitiveness by limiting sustained wage growth that outpaces productivity, particularly in the tradable sector.
  - Monitoring and addressing labor market rigidities—especially in Latvia—can reduce the persistence of wage-productivity deviations and help preserve competitiveness.
  - Continued attention to anchoring inflation expectations is critical to avoid persistent second-round effects and to limit real wage erosion for low-income earners.
  - Given the outsized role of energy and food in Baltic CPI baskets, policies that mitigate pass-through from commodity-price shocks (including targeted social measures to protect vulnerable households) are important in managing distributional consequences.

*IMF WORKING PAPERS High Inflation in the Baltics — Executive Summary.*

### Executive Summary ......................................................................................................

### Executive Summary

### Key findings on inflation drivers
- Headline inflation surged in 2022 to 17.2 percent in Latvia, 19.4 percent in Estonia, and 18.9 percent in Lithuania; the overall euro area average for the same period was 8.4 percent.
- Inflation in the Baltics is largely driven by global factors, with substantial contributions from energy and food prices.
- The average weights in CPI baskets are 16.4 for energy and 29.3 for food in the Baltics, versus 10.2 for energy and 20 for food in the euro area average.
- In 2022, energy accounted for about 8.5 percent of overall inflation in the Baltics on average, compared to 4.1 percent in the euro area.
- In 2022, the food price component in the HICP accounted for about 5.5 percent on average in the Baltics, compared to 1.9 percent in the euro area.
- Latvia has the higher share of energy and food in its consumer price index basket among the three Baltic countries.
- Much of the rise in inflation can be linked to the large increase in energy and food prices and to the Baltics’ small size and high economic openness, which expose them to external developments.

### Monetary policy, fiscal policy, and policy effectiveness
- As part of the euro area, monetary policy is set by the European Central Bank (ECB) for the area as a whole and is, effectively, exogenous to region-specific Baltic macroeconomic factors.
- Over the past few years, including the period before COVID-19, the cyclical position of the Baltic countries was more advanced than the euro area average; the stance of the ECB, while appropriate for the euro area as a whole, was too loose for Estonia, Latvia, and Lithuania specifically.
- Given the limited scope for country-specific monetary policy, fiscal policy is the main macroeconomic stabilization tool available to the Baltics.
- Empirical results show that, through its impact on domestic demand, fiscal policy has a statistically significant impact on inflation rates across the three Baltic countries.
- The effectiveness of fiscal policy is nevertheless constrained by the high openness of these economies.

### Risks to competitiveness and wage-productivity dynamics
- High and persistent inflation risks inducing high nominal and real wage growth in non-tradables and above-productivity wage growth in the exporting sector, which would erode competitiveness and growth if sustained.
- To date, persistent wage growth pressures significantly above the euro area have not materialized into a loss of competitiveness, but a more persistent shock could lead to larger and persistent second-round effects, affecting inflation expectations and wage negotiations.
- Tight labor markets across the Baltics exacerbate risks of wage pressures.
- During recent years, inflation expectations remained anchored in the Baltics, resulting in significant negative real wage growth while inflation was elevated.

### Empirical evidence on the wage-productivity nexus (tradeable/manufacturing sector)
- Productivity growth has been closely linked to wage growth in the Baltics over 2000-22.
- Lithuania’s productivity in the manufacturing sector was above wage growth on average over 2000-22.
- Latvia’s productivity was slightly below wage growth on average over 2000-22.
- Estonia’s productivity was similar to wage growth on average over 2000-22.
- There is robust evidence of a long-run (cointegration) relationship between (real) wages in the tradeable (manufacturing) sector and productivity in the Baltics.
- Statistical evidence of a short-run relationship—underpinning a reversion to the long-run relationship—was conclusive only for Lithuania and Estonia.
  - Implication: short-term deviations of wages from productivity are self-correcting in Estonia and Lithuania (at a faster rate in Estonia), but in Latvia these deviations may prove more persistent, highlighting a greater risk to competitiveness and convergence.
- These outcomes are correlated with the degree of labor market flexibility; Latvia is the least flexible of the three.

### Policy implications and priorities
- Fiscal policy should be the primary macro-stabilization tool in the Baltics given the constraints on country-specific monetary policy.
- Policymakers should guard competitiveness by limiting sustained wage growth that outpaces productivity, particularly in the tradable sector.
- Monitoring and addressing labor market rigidities—especially in Latvia—can reduce the persistence of wage-productivity deviations and help preserve competitiveness.
- Continued attention to anchoring inflation expectations is critical to avoid persistent second-round effects and to limit real wage erosion for low-income earners.
- Given the outsized role of energy and food in Baltic CPI baskets, policies that mitigate pass-through from commodity-price shocks (including targeted social measures to protect vulnerable households) are important in managing distributional consequences.

*IMF WORKING PAPERS High Inflation in the Baltics — Executive Summary.*

### 1.    Data

### 1. Data

### Data coverage and variables
- Sample: quarterly data from the first quarter of 2000 to the last quarter of 2022.
- Sources: World Economic Outlook (WEO) database and Eurostat.
- Domestic variables: real GDP growth, inflation, nominal wage growth, and economic slack (domestic economic slack is measured by the unemployment gap — deviation from the Hodrick-Prescott —HP— filtered unemployment rate).
- Global variables: oil prices, global food prices, world real GDP growth, and the real effective exchange rate (REER).
- Measurement conventions:
  - All variables other than the real effective exchange rate are expressed as year-on-year growth rates in percentage points.
  - The real effective exchange rate is included in logs. An increase in the real effective exchange rate corresponds to a real appreciation of the domestic currency.
- Note on energy price indicator: the oil price is used as an indicator of energy price shocks. There is a very high positive correlation (about 0.9 between 2019-2023) between oil prices and electricity prices.

---

### 2. Empirical Methodology

### SVAR framework for inflation dynamics
- Model form (structural representation):
  - A0 y_t = μ + A1 y_{t-1} + … + Aρ y_{t-ρ} + ε_t
  - y_t is an n*1 vector of endogenous variables; A0,…,Aρ are coefficient matrices; ε_t is a vector of structural shocks.
- Endogenous variables in y_t include:
  - oil price growth, inflation, food price growth, domestic real GDP growth, domestic economic slack, nominal wage growth, the real effective exchange rate, world real GDP growth.
- Identification:
  - Sign restrictions and zero restrictions imposed to identify supply and demand factors, broadly following Corsetti et al. (2014) and Finc and Tillman (2022).
  - Five structural shocks identified: global (supply) shocks (oil and food prices); global (demand) shock (world real GDP growth); domestic (demand) shock (real GDP growth); domestic (supply) shock (domestic CPI).
  - Analysis focuses on the global supply shock to oil prices and the domestic demand shock to real GDP growth.

---

### 3. Empirical Results

### Key impulse-response findings
- Global (oil) shocks:
  - A 5 percentage point increase in oil prices increases inflation in the Baltics by around 0.3–0.4 percentage points (significantly above the euro area, 0.1 percentage points).
  - The oil price shock leads to a 0.7–0.8 percentage point contraction in output in the Baltics (0.5 percentage points in the euro area).
  - The oil price shock leads to a 1 percentage point decline in nominal wage growth in Lithuania after the third quarter (impact on wage growth is not statistically significant in Estonia and Latvia).
  - In the euro area, the oil price shock leads to a decline in nominal wage growth (marginally significant).
- Domestic (real GDP) shocks:
  - A one standard deviation shock to domestic real GDP—around 0.7–0.8 percentage points of growth in the Baltics and 0.6 percentage points in the euro area—increases inflation by around 0.3–0.4 percentage points in the Baltics, well above the 0.1 percentage point impact in the euro area.
  - The increase in output raises wage growth in Estonia by around 1 percentage point and leads to a transitory rise in euro area wage growth (impact is statistically insignificant for Latvia and Lithuania).

### Variance decomposition (inflation)
- Global factors (oil price growth, food price growth, and world real GDP growth) explain about 37 percent of the variance of inflation.
- Domestic factors (domestic real GDP growth and domestic prices) account for about 25 percent of the variance of inflation.
- Charted shares by country indicate higher importance of global supply and demand for Estonia, Latvia, and Lithuania relative to the euro area.

### Robustness
- Robustness checks on a shorter sample for the post GFC period (2011-2020) show similar results.

---

### C. The Impact of Fiscal Policy on Inflation

### Data for fiscal analysis
- Quarterly data and sample periods:
  - Latvia and Lithuania: 1999Q1 to 2022Q3.
  - Estonia: 2002Q1 to 2022Q3.
- Endogenous variables: real GDP growth (log difference of real GDP), effective interest rates (Wu-Xia shadow rate), change in inflation (difference in core or headline inflation), growth of the primary balance as percentage of (potential) GDP.
- Lag selection: based on the AIC information criteria, with the baseline model including four lags. Results are consistent across various lag structures.

### Empirical methodology for fiscal shocks
- Vector autoregression (VAR) with sign restrictions to identify fiscal shocks (Uhlig 2005), using the standard VAR model from Nguyen et al. (2023).
- Identification assumptions (contemporaneous sign restrictions only):
  - A contractionary fiscal policy (an increase in the primary balance) is assumed to lower GDP growth and decrease inflation.
  - A positive aggregate demand shock (higher GDP growth) is associated with higher inflation.
- Sign restrictions apply to contemporaneous effects with no size restrictions.

*Source: IMF staff calculations, IMF Working Papers excerpt.*

### 3.    Empirical Results

### 3.    Empirical Results

### Impact of a Fiscal (Primary Balance) Shock on Inflation
- A positive one-standard deviation shock to the primary balance corresponds to a tightening of fiscal policy of 2.4, 3.2 and 2.9 percentage points of (potential GDP) for Estonia, Lithuania, and Latvia respectively.
- A fiscal tightening has an immediate negative impact on both headline and core inflation rates:
  - The impact on headline inflation is about twice that on core inflation: 0.4-0.7percentage points for headline and 0.2 to 0.4 percentage points for core.
  - The disinflationary effect is driven by the impact of fiscal policy on domestic demand through a negative and significant impact on GDP two quarters after the shock in Lithuania and Latvia (the impact on Estonia is not statistically significant).
- Table 4 (impact expressed per 1 percentage point increase in the primary balance as a percentage of potential GDP):
  - A 1 percentage point increase in the primary balance is linked to a reduction in headline inflation by 0.5 to 1.4 percentage points and in core inflation by 0.6 to 1.5 percentage points.
- Impulse response magnitudes and elasticities (Table 4, Core and Headline):
  - Estonia (Core): -0.68* (At t=0), -0.68* (Peak), -0.01 (Long Term), Elasticity -1.41
  - Estonia (Headline): -0.36* (At t=0), -0.36* (Peak), 0.01 (Long Term), Elasticity -1.52
  - Latvia (Core): -0.62* (At t=0), -0.62* (Peak), -0.02* (Long Term), Elasticity -0.83
  - Latvia (Headline): -0.19* (At t=0), -0.19* (Peak), 0.01 (Long Term), Elasticity -0.54
  - Lithuania (Core): -0.41* (At t=0), -0.41* (Peak), -0.01 (Long Term), Elasticity -0.48
  - Lithuania (Headline): -0.29* (At t=0), -0.29* (Peak), 0.00 (Long Term), Elasticity -0.71
  - (Table labels: At t=0; Peak 1/; Long Term; Elasticity; Core / Headline)

### Duration and Dynamics of the Fiscal Shock Effects
- The impact on inflation gradually dissipates over the following quarters:
  - The impulse response of headline inflation to a primary balance shock becomes statistically insignificant after 7 to 8 quarters in Estonia and Latvia, while this disinflationary effect only lasts 2 quarters in Lithuania.
  - The impact on core inflation is short-lived in all three countries, lasting only 1-2 quarters.
  - Overall, fiscal policy shocks have no long-term impact on inflation rates as the impulse responses in headline inflation rates are not statistically different from zero after 8 quarters (2 quarters for core inflation).
- Real economy and monetary responses:
  - As expected, the tightening in fiscal policy has a significant negative impact on growth.
  - The shadow interest rate (Krippner) decreases by about 0.3 percentage points in the few quarters following the fiscal contraction, with the decrease slowly fading away.

### Global vs Domestic Drivers of Inflation
- Global factors account for a larger share of the variation in inflation than domestic shocks:
  - About 37 percent of the variance of inflation is explained by global factors (demand and supply).
  - Domestic factors (demand and supply) explain about 25 percent of the variance of inflation.
- Global supply shocks to oil prices have an instantaneous positive and significant effect on consumer price inflation in all the Baltic countries.
  - Global supply shocks do not have an immediate significant impact on wage growth in the Baltics except for Lithuania, which records a significant increase in wage growth after the third quarter following an oil price shock.
- A domestic demand shock (domestic real GDP) increases inflation in the Baltics (above the increase in the euro area) and seems to have an impact on wage growth in Estonia and the euro area.

### Wage–Productivity Nexus (Tradeable/Manufacturing Sector)
- Data and methods:
  - Quarterly data from 2000Q1 to 2022Q4 from Eurostat, OECD, and the IMF WEO.
  - Real wage = compensation per thousand employees (or wages and salaries) deflated by HICP or GDP deflator.
  - Labor productivity = real value added per hours worked.
  - Analysis focuses on the manufacturing sector; cointegration and error-correction models (Engle-Granger two-step).
- Long-run co-movement and estimated long-run slopes:
  - There is a robust long-run (cointegration) relationship between real wages and labor productivity in manufacturing for all three Baltic countries over 2000Q1-2022Q4.
  - Estimated LR coefficients (models with and without crisis dummy):
    - Estonia: coefficient below one; estimated value reported as 0.87 in narrative.
    - Lithuania: coefficient below one; estimated value reported as 0.72 in narrative.
    - Latvia: coefficient above one in a statistically significant way with an estimated lower bound of 1.2.
- Augmented Dickey–Fuller (ADF) test results (Period: 2000Q1-2022Q4):
  - Wage measured as compensation of employees, without crisis dummy:
    - Lithuania ** -2.16
    - Latvia ** -2.30
    - Estonia *** -2.85
  - Wage measured as compensation of employees, with crisis dummy:
    - Lithuania ** -2.20
    - Latvia -2.29
    - Estonia *** -2.89
  - Wage measured as wages and salaries, without crisis dummy:
    - Lithuania * -1.86
    - Latvia *** -3.06
    - Estonia *** -3.07
  - Wage measured as wages and salaries, with crisis dummy:
    - Lithuania ** -2.08
    - Latvia *** -3.08
    - Estonia *** -3.41
  - Critical values (ADF): 1% -2.60; 5% -1.95; 10% -1.61
- Short-run error-correction dynamics:
  - The ECM suggests short-run deviations from the long-term wage–productivity relationship have tended to be self-correcting for Estonia and Lithuania.
  - Speed of reversion to long-term equilibrium:
    - Estonia: about 3 quarters.
    - Lithuania: about 6 quarters.
  - Latvia: short-run dynamics are more inconclusive; parameters of SR models are not (all) significant, indicating a more muted short-term reversion and the possibility that short-term deviations may be permanent.
- Estimated LR relationship coefficients (selected reported estimates):
  - Reported coefficient estimates in model summaries:
    - LTU 0.72 (narrative), 0.63*** / 0.75*** / 0.82*** / 0.71*** (various table entries)
    - LVA 1.28 (narrative lower bound 1.2), 0.63*** / 1.27*** / 0.83*** / 1.1*** (various table entries)
    - EST 0.87 (narrative), 0.63*** / 0.9*** / 0.64*** / 0.78*** (various table entries)
  - (Table 6 presents multiple model specifications with and without crisis dummy and two wage measures; significance indicated with ***/**/* where shown.)

### Labor Market Flexibility and Implications for Wage Dynamics
- Cross-country differences mirror labor market flexibility:
  - Estonia’s faster wage adjustment to productivity is associated with a relatively more flexible labor market, notably the ease to dismiss regular workers (EPL indicator) and early reforms (2009-2010).
  - Lithuania progressed with key labor market reforms in 2017-18.
  - Latvia appears to have the least flexible labor market, with EPLs among the most stringent in Europe and limited recent progress with reforms (over 2014-2019).
- Institutional and structural features:
  - Wages in the Baltics are mostly determined at the firm-level rather than industry-level; collective bargaining coverage is low.
  - Employer perceived labor market shortages (EC survey) tend to be lower than the EU average during downturns and higher in boom periods.
  - Current labor market tightness is unprecedented since the GFC and could add to wage pressures.

### Conclusions and Policy Implications (from Empirical Results)
- Inflation drivers and policy roles:
  - Inflation in the Baltics is mainly driven by global factors, but domestic demand matters as well, implying fiscal policy can play a role in containing inflation.
  - Being part of the euro zone, the Baltic countries lack monetary autonomy and depend on the ECB’s monetary policy stance for the euro area; the ECB’s contractionary stance came late and not strong enough for Baltic-specific circumstances, though the 2022 tightening helped reduce inflationary pressures.
  - Fiscal policy is the main domestic macroeconomic stabilization tool left to address inflationary pressures in the Baltics.
- Fiscal policy stance recommendation (empirical basis):
  - Given the balance of risks and the impact of fiscal policy on inflation through domestic demand, a tighter fiscal stance would actively contribute to lower inflation in the current context.
  - Structural policies such as setting moderate minimum and public sector wages can help mitigate the risk of higher wage growth because of their role as references in private sector wage negotiations and their influence on inflation expectations.
- Competitiveness and wage risks:
  - Persistently higher inflation than in the euro area, above what would be justified by productivity gains, could make inflation expectations adjust upwards and perpetuate price and wage increases.
  - If past patterns hold:
    - Estonia and Lithuania can temporarily absorb wages above productivity without a long-term impact on competitiveness (short-term deviations are self-correcting).
    - Latvia has significantly less capacity to absorb such deviations because wage growth has on average outpaced productivity and short-term deviations show less evidence of self-correction.
  - Lower labor market flexibility in Latvia raises greater risks to competitiveness and convergence relative to Estonia and Lithuania.

*IMF Working Paper — "High Inflation in the Baltics", Section 3. Empirical Results*

### References

### References

### Studies on inflation dynamics and global influences
- Auer, Raphael, Claudio E. V. Borio, and Andrew J. Filardo (2017). “The Globalisation of Inflation: The Growing Importance of Global Value Chains,” BIS Working Paper No. 602 (Basel: Bank for International Settlements).  
- Auer, Raphael, Andrei A. Levchenko, and Phil   lip   Sauré (2019). “International Inflation Spillovers through Input Linkages,” Review of Economics and Statistics, Vo. 101, pp. 507–521. 
- Bems, Rudolf, Francesca Caselli, Francesco Grigoli, Bertrand Gruss, Weicheng Lian (2018). “Is Inflation Domestic or Global? Evidence from Emerging Markets,” IMF Working Paper No. 241. 
- Ciccarelli, Matteo and Benoît Mojon (2010). “Global Inflation”, The Review of Economics and Statistics, Vol. 92. 
- Finck, David and Peter Tillmann (2022). “The Role of Global and Domestic Shocks for Inflation Dynamics: Evidence from Asia,” Oxford Bulletin of Economics and Statistics. 
- Klein, Nir (2012). “Real Wage, Labor Productivity, and Employment Trends in South Africa: A Close Look,” IMF Working Paper No. 12/92 (Washington, DC: International Monetary Fund). 
- Mikolajun, Irena and David Lodge (2016). “Advanced economy inflation: the role of global factors” 
- Forbes, Kristin J., “Inflation Dynamics: Dead, Dormant, or Determined Abroad?” Brookings Papers on Economic Activity, Fall 2019. 
- Bobeica, Elena and Marek Jarocinski (2019). “Missing Disinflation and Missing Inflation: A VAR Perspective”, International Journal of Central Banking.

### Regional and country-specific analyses (Baltics, Europe, Western Balkans, Asia)
- Benkovskis, Konstantins, Dmitry Kulikov, Daina Paula, and Laura Ruud (2009). “Inflation in the Baltic Countries”, Kroon and Economy. 
- Chen, Q., and G. Everaert (2015). “It Takes Two to Tango: Wages and Productivity in Lithuania,” IMF Selected Issues Paper No. 15/139(Washington, DC: International Monetary Fund). 
- Conti, Antonio M., Stefano Neri, Andrea Nobili (2017). “Low inflation and monetary policy in the euro area”, ECB Working Paper No. 2005. 
- Masso, Jaan and Raul Eamets (2004). "Labour Market Flexibility and Employment Protection Regulation in the Baltic States”, (No. 1147). IZA Discussion Papers. 
- Masso, Jaan and Karsten Staehr (2005). “Inflation dynamics and nominal adjustment in the Baltic States” 
- Gohar, Minasyan,  Ezgi Ozturk, Magali Pinat, Mengxue Wang, and Zeju Zhu (2023). “Inflation Dynamics in the Western Balkans”, IMF Working Paper No. 49. 
- Finck, David and Peter Tillmann (2022). “The Role of Global and Domestic Shocks for Inflation Dynamics: Evidence from Asia,” Oxford Bulletin of Economics and Statistics. 
- Kamber, Güneş, Madhusudan Mohanty, and James Morley (2020). “Have the driving forces of inflation changed in advanced and emerging market economies?”, BIS Working Papers No. 896. 

### Theoretical frameworks and fiscal-monetary interactions
- Afonso, Antonio, Jose Alves, and Raquel Balhote (2019). “Interactions Between Monetary and Fiscal Policies," Journal of Applied Economics, Vol. 22, pp. 132–151. 
- Catao, Luis A.V., and Macro E. Terrones (2005). “Fiscal Deficits and Inflation,” Journal of Monetary Economics, Vol. 52, pp.  529–554. 
- Sargent, Thomas J., and Neil    Wallace (1981). "Some Unpleasant Monetarist Arithmetic," Federal Reserve Bank of Minneapolis Quarterly Review, Vol. 5, pp. 1–17. 
- Sims, Christopher A. (1994). "A Simple Model for Study of the Determination of the Price Level and the Interaction of Monetary and Fiscal Policy,” Economic Theory, Vol. 4, pp. 381–399. 
- Reichlin, Lucrezia, Giovanni Ricco, and Matthieu Tarbe (2022). "Monetary-F iscal Crosswinds in the European Monetary Union," European Economic Review, 104328. 
- Fischer, Stanley, Ratna Sahay, and Carlos A. Végh (2002). "Modern Hyper-and High Inflations," Journal of Economic Literature, Vol. 40, pp. 837–880. 
- Sims, Christopher A. (1994). "A Simple Model for Study of the Determination of the Price Level and the Interaction of Monetary and Fiscal Policy,” Economic Theory, Vol. 4, pp. 381–399. 
- Friedman, Milton (1963). Inflation: Causes and Consequences. (  Asia Publishing House). 

### Commodity prices, productivity, and sectoral studies
- Gelos, Gaston and Yulia Ustyugova (2012). “Inflation Responses to Commodity Price Shocks – How and Why Do Countries Differ?”, IMF Working Paper 12/225. 
- Berka, Martin, Michael B. Devereux, and Charles Engel (2018). « Real Exchange Rates and Sectoral Productivity in the Eurozone,” American Economic Review, 108(6), 1543-1581. 
- Corsetti, Giancarlo, Luca Dedola, and Sylvain Leduc (2014). ‘The International Dimension of Productivity and Demand Shocks in the U. S. Economy’, Journal of the European Economic Association, Vol. 12, pp. 153–176. 
- Nguyen, Tai Dang (2019). “Impact of Government Spending on Inflation in Asian Emerging Economies: Evidence from India, China, and Indonesia," Singapore Economic Review, Vol. 64, pp. 1171–1200. 

### IMF and international reports cited
- International Monetary Fund (2022). “Europe Regional Economic Outlook: The Fog of War Clouds the European Outlook,” October 2022. 
- International Monetary Fund (2023). “World Economic Outlook: A Rocky Recovery,” April 2023. 
- Binici, Mahir, Samuele Centorrino, Serhan Cevik and Gyowon Gwon (2022). “Here Comes the Change: The Role of Global and Domestic Factors in Post-Pandemic Inflation in Europe,” IMF Working Paper No. 241. 

*High Inflation in the Baltics: Disentangling Inflation Dynamics and Its Impact on Competitiveness Working Paper No. WP/2024/061*

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_Source: https://www.imf.org/-/media/files/publications/wp/2024/english/wpiea2024061-print-pdf.pdf_