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---

### Introduction — key observations
- Labor market improvements in Europe since 2013:
  - Strong job growth and unemployment falling to lower-than-pre-crisis levels in most economies.
- Nominal wage growth:
  - In the European Union (EU)’s newer member states (NMS), nominal wage growth averaged nearly 8 percent since the first quarter of 2017.
  - In other European countries (EU15+3), nominal wage growth reached 2 percent.
- Inflation:
  - Core inflation remained, on average, below 2 percent in both NMS and EU15+3.
- Productivity-adjusted wage growth versus inflation:
  - In NMS, productivity-adjusted wage growth has exceeded inflation by about 3 percentage points on average since early 2017.
  - In EU15+3, the gap between productivity-adjusted wage growth and inflation is about 0.4 percentage point.
- Labor costs and productivity:
  - Compensation costs have outpaced improvements in labor productivity, especially in NMS.
  - Labor costs constitute almost 50 percent of business expenses in NMS and 53 percent in EU15+3 countries.
- Minimum wages and wage dynamics in NMS:
  - Minimum wages in NMS rose, on average, by 46 percent between 2015Q1 and 2019Q1.
  - Over the same time period, average wages rose by 33 percent.
- Group definitions and coverage:
  - NMS: Bulgaria, Croatia, the Czech Republic, Estonia, Hungary, Lithuania, Latvia, Poland, Romania, the Slovak Republic, and Slovenia.
  - EU15: Austria, Belgium, Denmark, Finland, France, Germany, Greece, Ireland, Italy, Luxembourg, the Netherlands, Portugal, Spain, Sweden, and the United Kingdom.
  - EU15+3 adds Israel, Norway, and Switzerland to the long-standing group.
- Data and measurement notes:
  - Quarterly seasonally adjusted data; real wage growth measured as nominal wage growth minus the GDP deflator growth.

### Empirical approach and model specification
- Models and identification:
  - Panel Vector Autoregression (PVAR) for unconditional (average) passthrough.
  - Interacted PVAR (IPVAR) for state-dependent passthrough by interacting with country characteristics.
  - Cholesky ordering (lag length L = 4): import price inflation, nominal wage growth adjusted for trend productivity, core consumer price inflation, unemployment gap.
- Key variables and transformations:
  - Baseline wage measure: total compensation per employee (national accounts).
  - Stationarity: year-over-year growth rates of wages, core CPI, and import prices.
  - Wage growth adjusted for trend productivity: trend estimated via HP filter of year-over-year growth of labor productivity.
  - HP smoothing parameter for NAIRU where OECD NAIRU not available: 1600.
- Conditioning variables (IPVAR):
  - Anchoring of inflation expectations (deviation of long-term professional forecasts from central bank target, transformed so higher numbers imply better anchoring).
  - Corporate profitability (profit share), product market regulation (PMR), labor share, relative price of investment goods (Penn World Table 9.1).
  - Continuous interacting variables evaluated at 25th and 75th percentiles; dummies evaluated for the two regimes (pre/post crisis or low/high inflation).
- Data frequency:
  - Main endogenous variables: quarterly; conditioning variables: annual interpolated to quarterly.

### Main findings: dynamic passthrough and magnitudes
- Timing and dynamics:
  - A positive wage growth shock has a small initial impact on core inflation, builds up, peaks around 6 quarters, and then dissipates.
- Magnitudes (exact estimates preserved):
  - A 1 percentage point exogenous increase in wages leads to:
    - 1.1 percentage point higher inflation in the newer EU member states (NMS) after three years.
    - 1 percentage point higher inflation in other European countries (EU15+3) after three years.
  - The passthrough from wages to prices at the end of 3 years is about one-third (slightly higher for NMS).
- Evolution over time:
  - The passthrough of labor costs into core inflation weakened in the last decade.
  - The passthrough ratio declined to less than 20 percent in the post-2008 period.
  - For NMS, the passthrough ratio in the post-2008 period is estimated to be only one-half of its pre-2008 value.
- Aggregate impulse-response evidence (selected exact figures):
  - In a low inflation environment (core inflation below country average), a 1 percentage point wage increase raises inflation by a cumulative 0.3 percent over three years, with an estimated passthrough ratio of about 11 percent.
  - In a high inflation environment (inflation above country average), the cumulative impact is significantly higher, with the passthrough ratio of about a third.
  - Anchoring examples:
    - At the 75th percentile of the anchoring measure, a 1 percentage point wage increase raises inflation by a cumulative 0.9 percentage point over three years.
    - At the 25th percentile (weakly anchored expectations), the cumulative impact increases to 1.4 percentage point.

### State-dependent factors shaping passthrough
- Passthrough is weaker when:
  - Inflation is subdued and inflation expectations are better anchored.
  - Aggregate corporate profitability is higher.
  - Sectors are more exposed to competition (domestic or foreign).
  - Firms have access to cheaper intermediate inputs or investment goods.
- Mechanisms discussed:
  - Delays in transmission of wages to prices (possible imminent pickup).
  - Structural changes in firms’ pricing behavior under low expected inflation.
  - Competitive pressures limiting pass-through.
  - Profitability buffers allowing firms to absorb higher wage costs without raising prices.
- Quantitative example on profitability:
  - A 1 percentage point increase in labor costs leads to a cumulative increase in inflation of only 0.7 percentage point over three years when evaluated at the 75th percentile of corporate profitability.

### Sectoral evidence: foreign competition and wage-to-price passthrough
- Sectoral empirical strategy:
  - 55 sectors across 32 European countries (WIOD 2016 release, annual 2000-14).
  - Regression specification: y_{s,c,t} = α · w_{s,c,t} + δ · w_{s,c,t} · m_{s,c,t} + μ · m_{s,c,t} + β · y_{s,c,t−1} + γ_{s,c} + γ_{s,t} + γ_{c,t} + ε_{s,c,t−1}.
  - Fixed effects: sector-country, sector-year, country-year; standard errors clustered at country-sector level.
- Key sectoral findings:
  - Interaction coefficient δ (wage growth × import penetration) is negative and statistically significant across alternative measures of external competitive pressures.
  - Higher foreign competition attenuates passthrough of wage growth to producer prices.
  - Robustness: pattern holds when restricting to 19 manufacturing sectors.
- Box 1 (eight NMS, alternative data and econometric approach):
  - Overall: A 1 percentage point increase in unit labor costs is found to increase producer prices by 0.9 percentage point within three years (sectoral estimate, eight NMS, 1995–2016).
  - Country variation: three-year cumulative increase about 0.5 percentage point in Poland and Hungary, and 1.3 percentage point in Latvia.
  - Table 1 coefficients on Wage growth: 0.164***, 0.217***, 0.258***, 0.192***, 0.295***, 0.319*** (standard errors: (0.035), (0.030), (0.030), (0.042), (0.049), (0.042)).
  - Interaction coefficients (Wage growth * Foreign Competition): -0.013, -0.029, -0.071, -0.031***, -0.053***, -0.092* (standard errors: (0.007), (0.017), (0.041), (0.011), (0.020), (0.054)).
  - Observations reported: 21,240; 21,240; 21,240; 7,385; 7,385; 7,385. R-squared: 0.339; 0.338; 0.338; 0.401; 0.401; 0.391.
- Sectoral heterogeneity:
  - Services: stronger transmission of wage increases to sectoral prices than manufacturing.
    - Average cumulative response: manufacturing 0.7 percentage point; services close to 1 percentage point.
  - Transmission stronger when the economy-wide output gap is positive; muted under excess supply.
  - Services firms with greater domestic market power (high Lerner index) tend to fully pass higher wage costs to consumers; firms with lower market power limit price increases to two-thirds of wage hikes.
  - In manufacturing, evidence on domestic market power is less clear-cut.
- Global value chains and imports:
  - Higher imports-to-output shares and higher GVC participation reduce passthrough.

### Product market competition (domestic) and market power
- Product market regulation (PMR) results:
  - More vigorous domestic competition mutes passthrough of wage growth to inflation.
  - Passthrough is marginally higher at the 75th percentile of a country’s PMR score (higher regulatory barriers) than at the 25th percentile.
- Lerner index:
  - Average Lerner index in the sample: 0.17 in Manufacturing sectors, and 0.29 in Services.
  - Higher Lerner index (greater market power) in services associated with stronger passthrough.

### Corporate profitability, labor-share effects, and input prices
- Corporate profit shares:
  - At end-2018: corporate profits = 47 percent of gross value added in NMS and 40 percent in EU15+3 countries.
  - Since the beginning of 2017: corporate profits declined each year by about 1 percent of gross value added in NMS and 0.3 percent in other European countries.
  - Contrast: corporate profits account for only a third of gross value added in the United States.
- Labor share:
  - Lower labor share implies wage developments matter less for inflation; IPVAR regressions confirm cumulative impact of wage increases on inflation is lower in a low labor share regime.
- Access to cheaper inputs:
  - Decline in relative prices of machinery and equipment since the 1990s has allowed firms to pay higher wages without raising prices.
  - Passthrough is lower in countries that experienced a larger decline in the price of investment goods.
  - Figure 10 panels: impact of wage growth on core inflation significantly higher at the 75th percentile of the relative price of machinery and equipment than at the 25th percentile.
- Other supporting factors for profits while wages rise: access to cheaper intermediate inputs, lower taxation or financing costs, adoption of new technologies.

### Policy-relevant implications and recommendations
- Aggregate conclusion:
  - The cumulative impact of a 1 percentage point increase in wages is 1.1 percentage point higher inflation in European countries at the end of three years.
  - Overall passthrough ratio (accounting for wage response to their own increases) is about one third.
  - Passthrough from wage growth to core inflation has been only two-thirds as strong in the decade since the global financial crisis compared to pre-crisis period.
- Factors likely to keep passthrough subdued going forward:
  - Subdued inflation and inflation expectations in many European economies.
  - Healthy corporate profitability (though declining in NMS since 2017).
  - Firms’ access to cheaper inputs (e.g., investment goods).
  - High reported competitive pressures: more than two-thirds of firms report increased competitive pressures compared to the pre-crisis era (Wage Dynamics Network Survey).
- Policy recommendations:
  - Findings support the need for monetary policy in many European countries to remain accommodative for longer to guard against a downshift in inflation expectations.
  - Caution: prolonged accommodative financial conditions may encourage greater risk taking; policy makers should remain vigilant against buildup of financial vulnerabilities and other undesirable side effects.
- Practical considerations for policymakers:
  - Strengthen inflation-anchoring mechanisms to lower sensitivity of inflation to wage growth.
  - Account for sector-specific exposure to competition when assessing inflationary risks from wage developments.
  - Monitor corporate profitability, labor shares, and relative input prices as buffers that can mute wage-to-price passthrough.

### Data sources, coverage, and methodological notes
- Main data coverage for quarterly indicators: 1995:Q1 – 2019:Q1.
- Key data sources:
  - Wages, labor productivity, core inflation, services inflation, non-energy industrial goods inflation, unemployment gap, profit share, labor share: Eurostat; Haver Analytics.
  - Inflation expectation anchor: Bems et al. (2018).
  - Product market regulation: OECD PMR Database (1998, 2003, 2008, 2013).
  - Relative price of investment: Penn World Table 9.1 (annual 1995-2017).
  - Sectoral data: OECD STAN; WIOD where relevant.
- Empirical methodology for sectoral analysis:
  - Heterogeneous panel ARDL with Mean-Group (MG) estimator (also considered PMG); ARDL(1,1) error-correction representation; Hausmann tests mostly favored MG.
  - Lerner index estimated using Roeger (1995)’s dual Solow residual approach; user cost of capital approximation uses depreciation rate of 10 percent.
- Selected empirical statistics preserved exactly:
  - HP smoothing parameter for NAIRU where OECD NAIRU not available: 1600.
  - Depreciation rate used in user cost of capital approximation: 10 percent.
  - Average Lerner index: 0.17 in Manufacturing sectors, and 0.29 in Services.
  - Scatter regression in Annex Figure 1: fitted line y = 0.7062x + 0.7925 and R²  = 0.7641 (Minimum versus Average Wage Growth, cumulative percent change; 2015Q1-2019Q1).

*Source: wpiea2019280-print-pdf — IMF staff calculations and cited data sources as listed in the document.*

### REFERENCES .............................................................................................................

### REFERENCES

### Figures and Box Inventory
- BOX
  - 1. Sectoral Dimension of the Link between Wage Growth to Inflation .................................... 28
- FIGURES
  - 1. Wage Growth, Productivity and Inflation ............................................................................... 5
  - 2. Evolution of Growth in Labor Costs ....................................................................................... 6
  - 3. Response of Core Inflation to a Wage Shock ........................................................................ 13
  - 4. Response of Core Inflation to a Wage Shock Before and After the Great Financial Crisis ..   14
  - 5. Inflation Expectations and Anchoring ................................................................................... 16
  - 6. Competitive Pressures for Europe ......................................................................................... 18
  - 7. The Role of Foreign Competition .......................................................................................... 19
  - 8. The Role of Domestic Competition ....................................................................................... 23
  - 9. The Role of Corporate Profitability ....................................................................................... 24
  - 10. The Role of Other Costs ...................................................................................................... 26
  - 11. Factors Pointing to Low Wage-Inflation Passthrough Ratio ............................................... 27
- TABLE
  - 1. Sectoral Evidence on the Effect of Wage Growth on Producer Prices: The Role of Foreign Competition ............................................................................................................................... 22

### Introduction — Key findings and observations
- Labor market improvements in Europe since 2013:
  - Strong job growth and unemployment falling to lower-than-pre-crisis levels in most economies.
- Nominal wage growth patterns:
  - In the European Union (EU)’s newer member states (NMS), nominal wage growth averaged nearly 8 percent since the first quarter of 2017, with sizable gains in compensation across all sectors of the economy.
  - In other European countries (EU15+3), nominal wage growth reached 2 percent.
- Inflation:
  - Core inflation remained, on average, below 2 percent in both NMS and EU15+3.
- Productivity-adjusted wage growth versus inflation:
  - In NMS, productivity-adjusted wage growth has exceeded inflation by about 3 percentage points on average since early 2017.
  - In EU15+3, the gap between productivity-adjusted wage growth and inflation is about 0.4 percentage point.
- Labor costs and productivity:
  - Compensation costs have outpaced improvements in labor productivity, especially in NMS.
  - Labor costs constitute almost 50 percent of business expenses in NMS and 53 percent in EU15+3 countries.
- Minimum wages and wage dynamics in NMS:
  - Minimum wages in NMS rose, on average, by 46 percent between 2015Q1 and 2019Q1.
  - Over the same time period, average wages rose by 33 percent.
  - Significant increases in minimum wages in the newer EU member states accompanied and likely contributed to the strong aggregate wage growth.
- Coverage and group definitions:
  - NMS (newer EU members) include Bulgaria, Croatia, the Czech Republic, Estonia, Hungary, Lithuania, Latvia, Poland, Romania, the Slovak Republic, and Slovenia.
  - Long-standing EU members (EU15) include countries that joined the EU before May 1, 2004: Austria, Belgium, Denmark, Finland, France, Germany, Greece, Ireland, Italy, Luxembourg, the Netherlands, Portugal, Spain, Sweden, and the United Kingdom.
  - Cyprus, Ireland, Luxembourg, and Malta are not included in the analysis because their GDP data distort labor productivity numbers.
  - Israel, Norway, and Switzerland are added to the long-standing group, forming the acronym EU15+3.
- Data and measurement notes:
  - Quarterly seasonally adjusted data are used and weighted by purchasing-power-parity GDP to aggregate across the two country groups.
  - Real wage growth is measured as nominal wage growth minus the GDP deflator growth.

*Source: wpiea2019280-print-pdf (REFERENCES section) — IMF staff calculations and cited data sources as listed in the document.*

### 6. EU15+3:  Core Inflation

### 6. EU15+3:  Core Inflation

### Key questions and scope
- Research questions:
  - How large is the passthrough of labor costs to inflation in Europe, and how long does it take for wage growth to feed into prices?
  - Has the extent of passthrough changed over time, specifically in the aftermath of the global financial crisis?
  - What factors influence the extent of passthrough (e.g., prevailing inflationary environment, exposure to foreign and domestic competition, corporate profitability, access to cheaper intermediate inputs)?
- Sample and period:
  - 27 European countries over 1995Q1-2019Q1.
  - Country groups: 16 advanced economies (EU15+3) and 11 newer EU member states (NMS).

### Empirical approach and model specification
- Models:
  - Panel Vector Autoregression (PVAR) to obtain unconditional (average) passthrough.
  - Interacted Panel Vector Autoregression (IPVAR) to obtain conditional (state-dependent) passthrough by interacting with country characteristics.
- Variables and ordering (Cholesky identification; lag length L = 4):
  - Import price inflation (most exogenous), nominal wage growth adjusted for trend productivity, core consumer price inflation, unemployment gap (least exogenous).
  - Models include import price inflation, nominal wage growth adjusted for trend productivity, core price inflation, and an unemployment gap, with this causal ordering.
- IPVAR specifics:
  - Coefficients allowed to evolve deterministically with a time-varying country characteristic ffff (equation (3)).
  - Conditioning variables include anchoring of inflation expectations, corporate profitability, product market regulation (PMR), labor share, and the relative price of investment goods.
  - For continuous interacting variables, responses reported at the 25th and 75th percentiles; for dummies (pre/post crisis or low/high inflation), impulse responses reported for the two regimes.
- Identification assumption: timing assumptions implicit in the Cholesky ordering hold irrespective of the level of the interacting variable.
- Data frequency and transformations:
  - Main endogenous variables compiled at quarterly frequency (Eurostat and others); conditioning variables at annual frequency interpolated to quarterly.
  - Baseline wage measure: total compensation per employee (national accounts).
  - Stationarity transformation: year-over-year growth rates of wages, core CPI, and import prices.
  - Wage growth adjusted for trend productivity (trend estimated via HP filter of year-over-year growth of labor productivity).
  - HP smoothing parameter for NAIRU where OECD NAIRU not available: 1600.
  - Anchoring measure: deviation of long-term professional forecasts from central bank target (transformed so higher numbers imply better anchoring).
  - Product market regulation: OECD PMR indicators.
  - Relative price of investment: Penn World Table 9.1.
  - Labor and profit shares: Eurostat and Haver Analytics.

### Main findings: dynamic passthrough and magnitudes
- Timing and dynamic pattern:
  - A positive wage growth shock has a small initial impact on core inflation, builds up, peaks around 6 quarters, and then dissipates.
- Magnitudes (selected exact estimates from the analysis):
  - A 1 percentage point exogenous increase in wages leads to:
    - 1.1 percentage point higher inflation in the newer EU member states (NMS) after three years.
    - 1 percentage point higher inflation in other European countries (EU15+3) after three years.
  - The passthrough from wages to prices at the end of 3 years is about one-third (with a slightly higher estimate for the NMS).
- Evolution over time:
  - The passthrough of labor costs into core inflation weakened in the last decade.
  - The passthrough ratio declined to less than 20 percent in the post-2008 period (Figure 4, panel 2).
  - For the newer EU member states, the passthrough ratio in the post-2008 period is estimated to be only one-half of its pre-2008 value.
- Robustness and comparisons:
  - Estimated passthroughs are similar to findings in Bobeica, Ciccarelli and Vansteenkiste (2019) and Bundesbank (2019).
  - Results corroborate findings for the United States and several CESEE countries reported in other recent literature.

### Factors shaping the passthrough (state-dependent results)
- Passthrough is weaker when:
  - Inflation is subdued and inflation expectations are better anchored.
  - Aggregate corporate profitability is higher (including when profitability is supported by access to cheaper inputs, such as investment goods).
  - Sectors are more exposed to competition (domestic or foreign), reducing the ability of firms to pass cost increases to consumers.
- Interpretation and mechanisms discussed in the paper:
  - Delays in transmission of wage developments to prices (possible imminent pickup).
  - Structural changes in firms’ pricing behavior given low expected inflation.
  - Increased competition domestically or from abroad limiting pass-through.
  - Firms’ profitability providing buffers to absorb higher wage costs without raising prices.

### Policy-relevant implications
- Given subdued inflation expectations, strong competitive pressures, and comfortable profit margins in Europe, the results imply:
  - The recent increase in wage growth is unlikely to meaningfully spur inflation in the near term.
- Understanding which of the proposed mechanisms dominates (expectations, competition, profitability buffers, etc.) is important for assessing the inflation outlook and appropriate policy response.

*Source: IMF staff analysis from the PDF chapter "6. EU15+3:  Core Inflation" (wpiea2019280-print-pdf).*

### 1. EU15+3: Impulse Response of Core Inflation  to A  Wage Shock

### 1. EU15+3: Impulse Response of Core Inflation to A Wage Shock

### Impulse-response evidence (aggregate)
- Charts compare impulse responses of core inflation to a wage shock across EU15+3 and NMS and before vs post 2008.
- Cumulative three-year impacts:
  - In a low inflation environment (core inflation below country average), a 1 percentage point wage increase raises inflation by a cumulative 0.3 percent over three years, with an estimated passthrough ratio of about 11 percent.
  - In a high inflation environment (inflation above country average), the cumulative impact is significantly higher, with the passthrough ratio of about a third.
- When evaluated at different degrees of inflation-expectations anchoring:
  - At the 75th percentile of the anchoring measure, a 1 percentage point wage increase raises inflation by a cumulative 0.9 percentage point over three years.
  - At the 25th percentile (weakly anchored expectations), the cumulative impact increases to 1.4 percentage point.
- Authors note a smaller and statistically insignificant decline in the passthrough ratio among the EU15+3 sample, consistent with other studies (footnote: Ciccarelli and Vansteenkiste (2019) do not detect significant changes in passthrough in four largest euro area economies).

### Role of inflation and inflation expectations
- Mechanism proposed:
  - Persistent low inflation and better-anchored inflation expectations reduce firms’ incentives to pass labor-cost increases onto prices because cost increases are perceived as transitory.
  - Conversely, higher inflation and unanchored expectations lead firms to perceive cost increases as more persistent, strengthening the wage-inflation link.
- Empirical findings:
  - IPVAR framework uncovers a tight relationship between prevailing inflation rate and passthrough: impact of labor cost increases on prices is lower and slower in below-average inflation periods.
  - Using Bems et al. (2019) anchoring index (deviation of long-term professional forecasts from central bank target): long-term inflation expectations are generally well-anchored in Europe, with two-year expectations somewhat higher in NMS.
  - Improved anchoring in NMS during the 2000s may explain a decline in passthrough over time in those countries; in contrast, degree of anchoring remained relatively unchanged in the four largest euro area countries and inflation expectations have drifted below target.
- Quantitative examples (preserved exactly):
  - "A 1 percentage point wage increase raises inflation by a cumulative 0.3 percent over three years, with an estimated passthrough ratio of about 11 percent."
  - "A 1 percentage point wage increase raises inflation by a cumulative 0.9 percentage point over the period of three years when the impulse response is evaluated at the 75th percentile... This impact increases by about a half—to 1.4 percentage point—when inflation expectations are weakly anchored (i.e. ... 25th percentile)."

### Role of competition (domestic and foreign)
- Survey evidence:
  - More than two-thirds of firms report increased competitive pressures compared to the pre-crisis era (Wage Dynamics Network Survey, third wave, 2014-15).
- Trade exposure:
  - Imports have continued to rise as a share of output despite slower global trade growth.
  - Import penetration by sector (final imports to sectoral gross value added):
    - Manufacturing: around 60 percent.
    - Services: less than 5 percent.
- Implication: higher exposure to foreign competition reduces firms’ ability/willingness to pass wage-cost increases into prices.

### Sectoral evidence and empirical strategy
- Objective: test whether wage-price passthrough is weaker in sectors with greater foreign competition using 55 sectors across 32 European countries (WIOD 2016 release, annual 2000-14).
- Key variables:
  - Producer price growth: growth in the value added deflator of sector s, country c, year t (log difference).
  - Productivity-adjusted wage growth: growth in labor compensation per person engaged less growth in real value added per person engaged.
  - Import penetration measures: ratio of final imports to sectoral gross output; alternatives include log ratio and a dummy for above-median penetration.
- Panel regression specification (preserved notation and equation structure):
  - y_{s,c,t} = α · w_{s,c,t} + δ · w_{s,c,t} · m_{s,c,t} + μ · m_{s,c,t} + β · y_{s,c,t−1} + γ_{s,c} + γ_{s,t} + γ_{c,t} + ε_{s,c,t−1}
  - Where γ_{s,c} are sector-country fixed effects, γ_{c,t} are country-year fixed effects, γ_{s,t} are sector-year fixed effects.
- Identification and controls:
  - Country-year fixed effects capture country-specific time-varying shocks (inflation expectations, slack, commodity shocks).
  - Country-sector fixed effects capture time-invariant sectoral differences within countries.
  - Sector-year fixed effects capture common sectoral shocks across countries.
  - Standard errors clustered at the country-sector level.

### Empirical findings (sectoral)
- Interaction results:
  - The interaction coefficient δ (wage growth × import penetration) is negative and statistically significant across specifications using three alternative measures of external competitive pressures (final-imports-to-gross-output ratio; log ratio; above-median dummy).
  - Interpretation: higher foreign competition attenuates the passthrough of wage growth to producer prices.
- Robustness:
  - Pattern holds when restricting analysis to the 19 manufacturing sectors in the WIOD.
- Direct association:
  - Higher exposure to foreign competition is directly associated with lower growth in producer prices, consistent with other studies (Lian et al. (2019)).

### Conceptual and policy implications (drawn from analysis)
- Low inflation and well-anchored expectations reduce wage-to-inflation passthrough, implying that monetary credibility and anchored expectations can dampen inflationary effects of wage growth.
- Increased domestic and foreign competition, particularly import penetration in manufacturing, reduces firms’ pass-through of labor-cost increases to prices.
- Sectoral heterogeneity matters: services (low import penetration) show larger passthrough from wages to prices than non-energy industrial goods (high import penetration).
- For policymakers:
  - Strengthening inflation-anchoring mechanisms can lower sensitivity of inflation to wage growth.
  - Consider sector-specific exposure to competition when assessing inflationary risks from wage developments.

*Italic: Source — wpiea2019280-print-pdf, "1. EU15+3: Impulse Response of Core Inflation to A Wage Shock"*

### Box 1, which focuses on eight of the newer EU member states, uses an alternative sectoral data

### Box 1, which focuses on eight of the newer EU member states, uses an alternative sectoral data source and a different econometric approach, presents further corroborating evidence on the importance of exposure to foreign competitive pressures in shaping the passthrough of wage growth into producer prices.

### Sectoral evidence: foreign competition and wage-to-price passthrough
- Overall finding: A 1 percentage point increase in unit labor costs is found to increase producer prices by 0.9 percentage point within three years (sectoral estimate, eight NMS, 1995–2016).
  - Country variation: three-year cumulative increase is about 0.5 percentage point in Poland and Hungary, and 1.3 percentage point in Latvia.
- Exposure to foreign competition weakens the passthrough of wage growth to producer prices:
  - Table 1 (sectoral regressions; dependent variable: growth in sectoral value added deflators):
    - Coefficients on Wage growth: 0.164***, 0.217***, 0.258***, 0.192***, 0.295***, 0.319***
      - Standard errors (in parentheses): (0.035), (0.030), (0.030), (0.042), (0.049), (0.042)
    - Coefficients on Wage growth * Foreign Competition: -0.013, -0.029, -0.071, -0.031***, -0.053***, -0.092*
      - Standard errors: (0.007), (0.017), (0.041), (0.011), (0.020), (0.054)
    - Coefficients on Foreign Competition: -0.010***, -0.016**, -0.006, -0.020***, -0.012, -0.026*
      - Standard errors: (0.003), (0.008), (0.005), (0.007), (0.008), (0.016)
    - Lagged growth in producer prices: -0.079***, -0.078***, -0.078***, -0.076*, -0.078*, -0.075*
      - Standard errors: (0.025), (0.025), (0.025), (0.044), (0.044), (0.045)
    - Constants: -0.018, 0.025***, 0.026***, -0.034*, 0.020***, 0.036***
      - Standard errors: (0.012), (0.002), (0.003), (0.018), (0.004), (0.014)
    - Observations: 21,240; 21,240; 21,240; 7,385; 7,385; 7,385
    - R-squared: 0.339; 0.338; 0.338; 0.401; 0.401; 0.391
  - Note on measures: In columns (1) and (4), foreign competition = ratio of sectoral final imports to gross output; columns (2) and (5) use log of the ratio; columns (3) and (6) use a dummy if sectoral import penetration is above sample median.
- Box Figure 1 (three-year cumulative responses):
  - Services sector shows stronger transmission of wage increases to sectoral prices than manufacturing:
    - Average cumulative response: manufacturing 0.7 percentage point; services close to 1 percentage point.
  - Transmission is stronger when the economy-wide output gap is positive; muted in excess supply.
  - Firms in services with greater domestic market power (high Lerner index) tend to fully pass higher wage costs to consumers; firms with lower market power limit price increases to two-thirds of wage hikes.
  - In manufacturing the evidence on domestic market power is less clear-cut.
- Foreign trade and GVCs:
  - Higher imports-to-output shares and higher GVC participation reduce passthrough.

### Product market competition (domestic competition)
- More vigorous domestic product market competition mutes passthrough of wage growth to inflation.
  - Evidence: IPVAR regressions using OECD product market regulation (PMR) indicator suggest more vibrant competition and fewer barriers to entry reduce consumer price sensitivity to wage increases.
  - Passthrough is marginally higher when evaluated at the 75th percentile of a country’s PMR score (higher regulatory barriers) than at the 25th percentile.
  - Box 1 (sectoral analysis) finds fiercer domestic competition, captured by the Lerner index, weakens the link between wage growth and producer prices in services.

### Corporate profitability and labor-share effects
- Economy-wide corporate profit shares:
  - At end-2018: corporate profits = 47 percent of gross value added in NMS and 40 percent in EU15+3 countries.
  - Since the beginning of 2017: corporate profits declined each year by about 1 percent of gross value added in NMS and 0.3 percent in other European countries.
  - In contrast, corporate profits account for only a third of gross value added in the United States (noted for contrast).
- Impact on passthrough:
  - Higher corporate profit shares are associated with smaller passthrough from wage growth to consumer price inflation.
    - Example estimate: a 1 percentage point increase in labor costs leads to a cumulative increase in inflation of only 0.7 percentage point over three years when evaluated at the 75th percentile of corporate profitability.
    - When corporate profits are at the 25th percentile, the impact of wage growth on inflation is significantly higher.
  - Lower labor share (compensation of employees as percent of GVA) implies wage developments matter less for inflation.
  - IPVAR regressions confirm cumulative impact of wage increases on inflation is lower in a low labor share regime than in a high labor share regime.

### Access to cheaper inputs and other cost factors
- Decline in relative prices of machinery and equipment since the 1990s has allowed firms to pay higher wages without raising prices.
  - Sources attribute decline to faster productivity growth in capital goods sectors and deeper trade integration.
- Passthrough is lower in countries that experienced a larger decline in the price of investment goods:
  - Figure 10 panels show the impact of wage growth on core inflation is significantly higher at the 75th percentile of the relative price of machinery and equipment than at the 25th percentile.
- Other factors that can support corporate profits even as wages rise: access to cheaper intermediate inputs, lower taxation or financing costs, adoption of new technologies that reduce labor demand.

### Conclusion and policy implications
- Historical aggregate result: The cumulative impact of a 1 percentage point increase in wages is 1.1 percentage point higher inflation in European countries at the end of three years.
- Overall passthrough ratio (accounting for wage response to their own increases) is about one third.
- Passthrough from wage growth to core inflation has been only two-thirds as strong in the decade since the global financial crisis compared to pre-crisis period.
- Factors likely to keep passthrough subdued going forward:
  - Subdued inflation and inflation expectations in many European economies.
  - Healthy corporate profitability (though declining in NMS since 2017).
  - Firms’ access to cheaper inputs (e.g., investment goods).
  - High reported competitive pressures: more than two-thirds of firms report increased competitive pressures compared to pre-crisis era (Wage Dynamics Network Survey).
- Policy recommendation:
  - Findings support the need for monetary policy in many European countries to remain accommodative for longer to guard against a downshift in inflation expectations.
  - Cautionary note: prolonged accommodative financial conditions may encourage greater risk taking; policy makers should remain vigilant against buildup of financial vulnerabilities and other undesirable side effects.

*Source: WIOD, Johnson and Noguera (2017), OECD STAN, IMF staff calculations, and IMF working paper materials as presented in the supplied content.*

### Annex Table 1. Sources of Information

### Annex Table 1. Sources of Information (wpiea2019280-print-pdf)

### Data sources and frequency
- Wages: Compensation of employees/total employees; quarterly; 1995:Q1 – 2019:Q1; Source: Eurostat; Haver Analytics.
- Relative import prices: Import price deflator/GDP deflator; quarterly; 1995:Q1 – 2019:Q1; Source: Eurostat; Haver Analytics.
- Labor productivity: Real gross value added/total employment; quarterly; 1995:Q1 – 2019:Q1; Source: Eurostat; Haver Analytics.
- Inflation expectation anchor: Deviation of long-term inflation forecasts produced by professional analysts from the central bank's target; annual; Source: Bems et al. (2018).
- Core inflation: CPI excl. energy and unprocessed food; quarterly; 1995:Q1 – 2019:Q1; Source: Eurostat; Haver Analytics.
- Services inflation: CPI excl. goods; quarterly; 1995:Q1 – 2019:Q1; Source: Eurostat; Haver Analytics.
- Non-energy industrial goods inflation: CPI for goods excl. food, alcohol, tobacco, and energy; quarterly; 1995:Q1 – 2019:Q1; Source: Eurostat; Haver Analytics.
- Unemployment gap: Unemployment rate – NAIRU (or trend unemployment rate); quarterly; 1995:Q1 – 2019:Q1 and annual (NAIRU) 1995 - 2019; Source: Eurostat; Haver Analytics; OECD.
- Profit share: NFCs gross operating surplus/NFCs gross value added; quarterly; 1995:Q1 – 2019:Q1; Source: Eurostat; Haver Analytics.
- Labor share of income: Compensation of employees/gross value added; quarterly; 1995:Q1 – 2019:Q1; Source: Eurostat; Haver Analytics.
- Product market regulation: PMR index; annual; 1998, 2003, 2008, and 2013; Source: OECD PMR Database.
- Relative price of investment: Machinery and equipment price deflator/consumption deflator; annual; 1995-2017; Source: Penn World Table 9.1.

### Annex figures (themes and data coverage)
- Annex Figure 2: Average Nominal Wage Growth by Sector (Year-over-year percent change) — sectoral series for NMS and EU15+3 across subperiods 2010-15, 2015-16, 2017-19.
- Annex Figure 1: NMS: Minimum and Average Wages — panels showing cumulative percent change and scatter for 2015Q1-2019Q1 with fitted line y = 0.7062x + 0.7925 and R²  = 0.7641.
- Annex Figure 3: NMS: Before and After the Great Financial Crisis.
- Annex Figure 4: NMS: Inflation Expectations and Anchoring — panels include Cumulative IRF (Percentage points) and Passthrough Metric (Three-year cumulative; percent) by periods and inflation regimes; comparisons for Before 2008 vs Post 2008, High vs Low inflation regime, Poorly anchored vs Better anchored inflation expectations.
- Annex Figure 5: NMS: The Role of Corporate Profitability — covers 20 economies: 6 NMSs and 14 EU15+3 countries; panels show Cumulative IRF (Percentage points) and Passthrough Metric (Three-year cumulative; percent) by labor share of income (High labor share vs Low labor share).

### Empirical methodology (summary)
- Model: Heterogeneous panel ARDL (autoregressive distributed lag) specification estimated primarily with the Mean-Group (MG) estimator; also considered Pooled Mean Group (PMG).
- Purpose: Estimate disaggregated relationships between productivity-adjusted sectoral wages and producer prices, robust to bi-directional feedback, heterogeneous dynamics, and sectoral heterogeneity.
- Error-correction representation: ARDL(1,1) formulation with speed of wage adjustment parameter 휑휑_i and long-run relationship parameters 휃_0i, 휃_1i.
- Response measurement: Cumulative responses charted to include both long-term (error-correction) and short-term components (including current period price change).
- Estimator choice: MG yields consistent averages across cross-section allowing heterogeneous long-run and short-run relationships and error variances; PMG imposes homogeneous long-run elasticities but allows heterogeneous adjustment. Hausmann tests mostly favored MG in this application.

### Data construction and key variable definitions
- Sectoral data source: OECD STAN (Structural Analysis) database for Industrial Analysis; classification based on ISIC Rev.4; average non-overlapping coverage ~70 sectors (22 manufacturing, 40 services). WIOD sectoral data included where relevant.
- Producer price: Constructed as the output-based price index; for Baltic states, output volume proxied by real value-added due to data limitations.
- Productivity-adjusted wage: Based on labor costs/compensation of employees (wages and salaries plus supplements such as social security contributions, private pensions, health insurance, life insurance); results robust to using wages and salaries only.
- Output gap: From IMF WEO Database.
- Lerner index (sectoral market power): Estimated using Roeger (1995)’s dual Solow residual approach; Lerner index defined as (P – MC)/P or 1/|E| with values between zero and one (higher = greater market power).
  - Estimation details: Nominal Solow residual ∆y_i and change in output-capital ratio ∆x_i computed from STAN variables; user cost of capital f_i = ln(R_i) approximated with R_i = P_i (i - π + δ), where P_i is country-specific fixed capital formation deflator, i - π is long-term interest rate less 5-year ahead inflation, and δ is depreciation rate of 10 percent.
  - Sectoral markups estimated via OLS regression ∆y_i = β ∆x_i + γ Out_of_sample ∆x_i + ε_i, where β is time-invariant structural component and second term captures cyclical component.
- Coverage limitation: STAN-based sectoral richness comes at cost of limited coverage of newer EU member states; modified producer price measures constructed for Czech Republic, Hungary, Poland, Slovak Republic, Slovenia, Estonia, Lithuania, Latvia.

### Key empirical statistics reported
- Sample coverage for many quarterly indicators: 1995:Q1 – 2019:Q1.
- PMR index years: 1998, 2003, 2008, and 2013.
- Relative price of investment coverage: annual 1995-2017.
- Depreciation rate used in user cost of capital approximation: 10 percent.
- Average Lerner index in the sample: 0.17 in Manufacturing sectors, and 0.29 in Services.
- Scatter regression in Annex Figure 1: fitted line y = 0.7062x + 0.7925 and R²  = 0.7641 (Minimum versus Average Wage Growth, cumulative percent change; 2015Q1-2019Q1).

*Sources: Annex content of wpiea2019280-print-pdf (tables, figures, data descriptions, methodology, and references).*

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_Source: https://www.imf.org/-/media/files/publications/wp/2019/wpiea2019280-print-pdf.pdf_