## 1. EU-15

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### Overview
- Wages are growing notably faster in the newer EU members (NMS) than in the long-standing EU members (EU-15).
- Average wage increases in NMS reached over 8 percent by mid-2018 from 3 percent in 2014.
- Real product wages (deflated by the GDP deflator) in mid-2018:
  - EU-15: annual rates of growth averaged less than ½ percent.
  - NMS: surged from 3 percent to close to 6 percent.

### Stylized Facts
- EU-15 nominal wage growth and drivers:
  - Average nominal wage growth has remained around 1½ percent since 2011, down from just over 3 percent during 2003–09.
  - GDP deflator (output price) inflation: down 1 percentage point to about 1¼ percent in recent years.
  - Trend labor productivity: down ½ percentage point to 0.6 percent.
  - Real wage growth has remained below trend labor productivity growth; ratio of real wages to trend productivity declined since the global financial crisis and stabilized only in 2017–18.
- NMS nominal and real wage developments:
  - During 2011–15, nominal wage growth of about 3½ percent kept real wages stable relative to productivity.
  - Nominal wage growth picked up rapidly in 2016–17, exceeding 8 percent year over year by mid-2018.
  - With inflation in NMS rising only modestly, real wage gains surged to almost 6 percent year over year by mid-2018.
  - Trend productivity in NMS averaged about 2 percent, much lower than the pre-crisis level.
  - The average ratio of real wages to trend labor productivity was roughly 2½ percent higher than its historical average in 2017.

### Wage Dynamics and Key Drivers
- Model and approach:
  - Uses an error correction model (ECM) linking real product wages to labor productivity in long-run equilibrium.
  - Drivers considered include broader labor market slack beyond unemployment, inflation expectations, and cross-border spillovers from external labor market conditions, migrant flows, and external wage developments.
- Slack measures and spillovers tested:
  - Involuntary part-time employment, hours worked per person, non-employment (NE) index.
  - Foreign measures: GDP-weighted euro area unemployment (fU), euro area wages (fW), German wages separately.
- Nominal wage measurement:
  - Labor compensation per employee hour worked (includes employers’ social security contributions and non-wage benefits).
  - Four-quarter averages and indices with the average for 2000–17 = 100 used for the real wage/trend productivity ratio.

### Labor Market Slack, Unemployment, and Shortages
- Declines in unemployment:
  - NMS: unemployment fell by 6 percentage points on average since 2013, bringing unemployment down to an average of 5.5 percent by mid-2018.
  - Advanced Europe: unemployment fell by 4 percentage points over the comparable period.
- Slack indicators:
  - Broader slack suggests labor markets are not as tight as the rapid fall in unemployment would imply for advanced economies.
  - In NMS slack largely disappeared by about mid-2015, consistent with timing of wage acceleration.
  - Labor shortages exceed pre-crisis peaks in the NMS—especially strong in industry.

### Data, Sample, and Core Modeling Approach
- Sample period: 1995:Q1 to 2017:Q3.
- Country groups:
  - (1) Germany (modeled separately).
  - (2) Panel: Austria, Belgium, France, the Netherlands and Spain.
  - (3) Panel NMS: Czech Republic, Estonia, Hungary, Latvia, Lithuania, Poland, Slovak Republic and Slovenia.
- Key measures and settings:
  - Wage: total labor compensation per employee hour worked.
  - Short-run inflation: HICP.
  - Inflation expectations: one-year-ahead Consensus Forecasts.
  - Structural unemployment (NAIRU): OECD estimates or HP filter; HP filter lambda for trend productivity: 1600.
  - Broad slack indicators: unemployment gap, non-employment (NE) index, hours gap.
  - Migration data from Eurostat (latest update in sample covers data until 2015).

### Econometric Framework and Interpretation
- Long-run specification:
  - Real product wage (RW) regressed on trend productivity (Ptvy_trend), accumulated reform dummy, and foreign real product wage (fRW) where relevant.
  - Reform dummy: equals one for first reform period, increases by one for each subsequent reform and accumulates.
- Short-run dynamics:
  - ECM for nominal wage growth (4–quarter wage growth).
  - Baseline short-run variables: lagged wage growth, lagged inflation, inflation expectations, growth in trend productivity, unemployment gap (level and change), and the fourth lag of ECM term.
  - Lags typically 4 quarters; ECM terms around -0.36 imply about one-third of deviation from long-term equilibrium corrected within a year.

### Long-run Empirical Findings (selected)
- Productivity is primary long-run determinant of real wages across countries.
- Germany:
  - Elasticity of real wages to productivity: 1.027***.
  - Hartz reforms (2003–05) lower equilibrium real wages by 5½ percent.
  - Without controlling for reforms, productivity coefficient biased downward to 0.73.
- Spain:
  - Unemployment benefit reforms reduce real wages by an estimated 4 percent.
- Austria and the Netherlands:
  - German wages have long-term impact with coefficient about 0.2.
  - Employment protection reforms in Austria reduce real wages by 3 percent.
- Belgium:
  - Long-run real wages influenced by German and French wages.
- NMS (selected coefficients from Table 4.2):
  - Czech Republic: log trend productivity coefficient 1.074***.
  - Estonia: 1.187***.
  - Hungary: 0.598***.
  - Latvia: 1.012***.
  - Lithuania: 0.936***.
  - Poland: 0.696***.
  - Slovak Republic: 1.031***.
  - Slovenia: 0.789***.
- Interpretation for NMS:
  - Trend productivity is the key long-run driver; foreign wage movements do not produce lasting deviations from productivity-driven real wage paths.

### Short-run Dynamics, Spillovers, and Migration
- Baseline Phillips-curve results (Euro Area excluding Germany):
  - Productivity growth, inflation, and unemployment gaps (level and changes) are key nominal drivers.
- Broader slack indicators:
  - Non-employment index (NE) and hours gap improve explanatory power and are statistically significant.
- Error-correction:
  - ECM terms around -0.36 and significant.
- External spillovers:
  - Changes in euro area unemployment (lagged two quarters) and euro area wage growth (lagged three quarters) significantly contribute to domestic wage growth.
- Migration effects:
  - Net migration inflow increases weigh on subsequent wage growth; impact modest and temporary.
  - A rise in net migrant inflows by 1 percentage point of the labor force is found to reduce wage growth in the following year by a modest amount (text truncated before exact magnitude in one place).
  - When split into inflows and outflows (column 10), outflows have larger coefficient though difference not statistically significant.
  - In NMS, a rise in inflows by 1 percentage point is found to reduce wage growth in the following year by 0.5 percent.
  - In other euro area countries, a rise in inflows by 1 percentage point is found to reduce wage growth in the following year by 0.4 percent.
  - For Germany, changes in net migration flows do not have a statistically significant impact on wages (column 9).

### Regional Findings — Decomposition and Quantitative Contributions
- Euro Area excluding Germany:
  - Initial slowing in wage rises (average from five-country panel) by 2.3 percentage points in 2010 linked to:
    - lower inflation expectations: 0.8 ppts
    - lower past inflation: 0.5 ppts
    - domestic labor slack: 0.6 ppts
    - wage overhang (error correction): 0.3 ppts
  - Error correction continued to weigh on wages by 0.2 to 0.3 ppts during 2011–15.
  - During 2011–13, inflation expectations and actual inflation recovered, lifting combined contribution by 0.9 ppts.
  - Domestic and external slack weighed more heavily during 2012–14, with a total drag of 0.6 ppts on wage growth in both 2013 and 2014.
  - Contributions from inflation expectations and inflation fell sharply during 2014–15 by 0.9 ppts, with only a slight increase by 2017.
- Newer EU Members:
  - Sharp halt in wage rises in 2009 reflected large negative contributions from rising domestic slack and rising euro area unemployment, plus error correction drag as trend productivity declined.
  - By 2011 declines in domestic slack began to support wages; by 2014 declines in euro area unemployment began to support wages.
  - By 2016–17, low domestic slack began to reinforce wage rises.
  - Diminished domestic slack contributed about 2 percentage points to wage growth in recent years.
  - Combined spillovers from euro area unemployment and euro area wage rises account for about 1½ percentage points of the wage pickup in newer members during 2015–17.
  - Migration outflows may partly account for wage acceleration during 2016–17, but recent migration data are not yet available.
- Germany:
  - Steep initial fall in wage growth by 2.9 percentage points in 2010 linked to:
    - lower inflation expectations: 0.9 ppts
    - domestic labor slack: 0.3 ppts
    - error correction: 1 ppt
  - Recovery in inflation expectations during 2011–13 lifted contribution by 0.8 ppts.
  - Wage growth higher than 3 percent in 2012 led to significant error correction drag during 2012–14, peaking at 0.7 ppts in 2013.
  - Contributions from inflation expectations fell during 2014–15 by 0.4 ppts, with a slight additional decline in 2017.

### Simulation of Spillovers and Scenario Results
- Scenario: hourly wage rates in Germany rise 1 percentage point faster than baseline.
  - Raises euro area wage growth by about 0.4 percentage point given Germany’s weight.
  - The shock spills over into wage growth in both regional panels.
  - Higher German wages spill over through long-run equations for Austria, Belgium, and the Netherlands.
  - Overall, wage growth in the euro area excluding Germany rises about 0.1 percent after one year.
  - Impact on NMS wages slightly larger in near term (about 0.15 percent after one year) but fades to zero over time because long-run real wages in NMS depend only on domestic labor productivity.
  - If higher wages lead to higher inflation, medium-term impact on wages would be higher than these simulations indicate.

### Wage Outlook, Projections, and Assumptions
- With labor market slack continuing to diminish and inflation rising, wage growth is expected to accelerate by end-2021 to:
  - just below 4 percent in Germany,
  - 3.5 percent on average in other Euro area countries,
  - just below 6 percent in new EU members.
- Trend productivity growth assumed to remain at the current level.
- A more optimistic outlook for productivity recovery would imply faster wage growth.
- Risks and uncertainties:
  - Downside: extent to which labor market improvement can continue depends on structural shares of unemployment and under-employment.
  - Sensitivity of wages to fundamentals can vary; greater integration of product and labor markets could make foreign factors more important.

### Key Empirical Findings and Mechanisms (summary)
- Long-run: wage developments in EU15 and NMS are linked to labor productivity.
- Differences in responsiveness:
  - EU15: wages respond relatively slowly to unemployment changes; closely related to inflation and inflation expectations.
  - NMS: wage growth responds more quickly to changes in labor market slack; inflation expectations less important.
- Role of deviations and nominal inertia:
  - Real wages follow productivity in the long run; deviations can persist but are partly corrected via ECM.
  - Example: post-crisis EU15 saw a real wage overhang unwind through low nominal wage growth and subdued inflation.
- Broader slack indicators:
  - Involuntary part-time employment and hours worked per person add information beyond unemployment.
  - Nonemployment index that includes marginally attached workers increases explanatory power for wage developments.

### Selected Econometric Highlights (short-run equations)
- Euro Area excluding Germany (selected coefficients):
  - Trend Labor Productivity, Log, Four Quarter Change (t-4): 0.82***
  - HICP, Log, Four Quarter Change (t-5): 0.31***
  - Expected Inflation, One Year Ahead (t-4): 0.50**
  - Error Correction Term (t-4): -0.36***
- Newer EU Members (selected coefficients):
  - Trend Labor Productivity, Log, Four Quarter Change (t-4): 1.20***
  - Expected Inflation, One Year Ahead (t-4): 0.63***
  - Unemployment Gap (t-4): -0.79***
  - Nonemployment Gap (t-4): -1.27***
  - Error Correction Term (t-4): -0.40***
- Germany (selected coefficients):
  - Trend labor productivity, log, 4 qtr change (t-4): 1.02***
  - Expected inflation, one-year-ahead (t-4): 0.66*
  - Unemployment gap (t-4): -1.30***
  - Involuntary PT employment 4 qtr change (t-1): -1.25***
  - Error correction term (t-4): -0.62***

### Implications for Monitoring and Policy
- Monitor broader labor market slack indicators beyond unemployment: involuntary part-time employment, hours worked per person, and a nonemployment index including marginally attached workers.
- Recognize differing transmission of domestic and foreign slack:
  - In EU15, foreign slack and slow wage growth among competitors contributed to domestic wage moderation.
  - In NMS, domestic labor market recovery is the dominant driver of wage acceleration despite spillovers.
- Account for inflation expectations and nominal wage inertia when assessing persistence of nominal wage trends.
- Faster productivity recovery would raise projected wage growth relative to baseline projections.

*Source: wpiea2019156 - 1. EU-15 (IMF staff calculations drawing on Eurostat, Labor Cost Index, Wages and Salaries).*

### 1. EU-15

### 1. EU-15

### Overview
- Wages are growing notably faster in the newer EU members (NMS) than in the long-standing EU members (EU-15).
- Average wage increases in NMS reached over 8 percent by mid-2018 from 3 percent in 2014.
- Real product wages (deflated by the GDP deflator) in mid-2018:
  - EU-15: annual rates of growth averaged less than ½ percent.
  - NMS: surged from 3 percent to close to 6 percent.

### Stylized Facts
- EU-15 nominal wage growth and related drivers:
  - Average nominal wage growth has remained around 1½ percent since 2011, down from just over 3 percent during 2003–09.
  - GDP deflator (output price) inflation: down 1 percentage point to about 1¼ percent in recent years.
  - Trend labor productivity: down ½ percentage point to 0.6 percent.
  - Real wage growth has remained below trend labor productivity growth, reflected in a declining ratio of real wages to trend productivity since the global financial crisis.
  - The real wage/trend labor productivity ratio stabilized only in 2017–18.
- NMS nominal and real wage developments:
  - During 2011–15, nominal wage growth of about 3½ percent kept real wages stable relative to productivity.
  - Nominal wage growth picked up rapidly in 2016–17, exceeding 8 percent year over year by mid-2018.
  - With inflation in NMS rising only modestly, real wage gains surged to almost 6 percent year over year by mid-2018.
  - Trend productivity in NMS averaged about 2 percent, much lower than the pre-crisis level.
  - The average ratio of real wages to trend labor productivity was roughly 2½ percent higher than its historical average in 2017.

### Wage Dynamics and Key Drivers
- The paper uses an error correction model (ECM) linking real product wages to labor productivity in long-run equilibrium to analyze wage dynamics.
- Considered drivers include:
  - Broader indicators of labor market slack beyond unemployment (e.g., involuntary part-time employment, hours worked per person).
  - Inflation expectations as in a wage Phillips curve.
  - Cross-border spillovers from external labor market conditions, migrant flows, and external wage developments, reflecting significant labor mobility and competition within the EU.

### Labor Market Slack, Unemployment, and Shortages
- Declines in unemployment:
  - NMS: unemployment fell by 6 percentage points on average since 2013, bringing unemployment down to an average of 5.5 percent by mid-2018.
  - Advanced Europe: unemployment fell by 4 percentage points over the comparable period.
- Slack indicators suggest labor markets are not as tight as the rapid fall in unemployment would imply for advanced economies (citing involuntary part-time employment, hours worked per person, etc.).
- In NMS:
  - Slack is estimated to have largely disappeared by about mid-2015, consistent with the timing of the wage acceleration.
  - Labor shortages exceed pre-crisis peaks in the NMS—especially strong in industry—which may help explain the recent acceleration of real wage growth.

### Methodological Note
- Nominal wages are measured as labor compensation (including employers’ social security contributions) per employee hour worked.
- Figures referenced use four-quarter averages and indices with the average for 2000–17 = 100 for the real wage/trend productivity ratio.

*Source: wpiea2019156 - 1. EU-15 (IMF staff calculations drawing on Eurostat, Labor Cost Index, Wages and Salaries).*

### 1. Unemployment - Estimated NAIRU 1/ 2. Labor Shortages: Average for Industry and

### wpiea2019156 - 1. Unemployment - Estimated NAIRU 1/ 2. Labor Shortages: Average for Industry and Services

### Data, sample, and core modeling approach
- Sample period: 1995:Q1 to 2017:Q3.
- Country groups analyzed:
  - (1) Germany (modeled separately).
  - (2) Panel of other Euro Area countries: Austria, Belgium, France, the Netherlands and Spain.
  - (3) Panel of new EU members (NMS): Czech Republic, Estonia, Hungary, Latvia, Lithuania, Poland, Slovak Republic and Slovenia.
- Key wage measure: total labor compensation per employee hour worked (includes employer social security contributions and non-wage benefits).
- Inflation measure for short-run analysis: HICP.
- Inflation expectations proxy: one-year-ahead Consensus Forecasts.
- Structural unemployment (NAIRU): OECD estimates for OECD members; HP filter when OECD estimates are not available. HP filter lambda parameter used to compute trend productivity: 1600.
- Broader slack indicators tested:
  - Unemployment gap (actual unemployment minus NAIRU).
  - Non-employment (NE) index: combines unemployment rate, marginally attached workers, and involuntary part-time employment.
  - Hours gap: difference between actual hours worked per employee and its trend (gap_Hour).
- Foreign spillover measures:
  - GDP-weighted average of euro area unemployment rates (fU).
  - GDP-weighted average of euro area wages (fW).
  - German wages tested separately as a prominent source of spillovers.
- Migration data source: Eurostat (latest update used in sample covers data until 2015).

### Econometric framework
- Long-run specification (real product wages):
  - Real product wage (RW) regressed on trend productivity (Ptvy_trend), accumulated reform dummy, and foreign real product wage (fRW) where relevant.
  - Trend productivity measured with HP filter (lambda = 1600).
  - Reform dummy: equals one for first reform period, increases by one for each subsequent reform and accumulates.
- Short-run dynamics:
  - Error-correction model (ECM) for nominal wage growth, focusing on 4–quarter wage growth (d denotes 4–quarter difference).
  - Baseline short-run explanatory variables: lagged wage growth, lagged inflation, inflation expectations, growth in trend productivity, unemployment gap (level and change), and the fourth lag of the ECM term from the long-run regression.
  - Lags for explanatory variables typically 4 quarters (sometimes 3–5 quarters depending on significance).
- ECM interpretation:
  - Fourth lag of the error correction term included; coefficients on ECM terms around -0.36 (implying on average about one-third of any deviation from long-term equilibrium is corrected in the following year).

### Long-run empirical findings
- Labor productivity is the primary determinant of real wages in the long run across countries.
- Germany:
  - Estimated elasticity of real wages to productivity: close to unity (1.027*** reported in table).
  - Hartz reforms (2003–05) lower equilibrium real wages by 5½ percent.
  - Without controlling for reforms, productivity coefficient biased downward to 0.73 (textual discussion).
- Spain:
  - Unemployment benefit reforms reduce real wages by an estimated 4 percent.
- Austria and the Netherlands:
  - German wages have long-term impact with coefficient about 0.2.
  - In Austria, employment protection reforms are found to reduce real wages by 3 percent.
- Belgium:
  - Long-run real wages influenced by German and French wages (benchmarking practice).
- Newer EU members (selected estimates from Table 4.2):
  - Czech Republic: log trend productivity coefficient 1.074***.
  - Estonia: 1.187***.
  - Hungary: 0.598***.
  - Latvia: 1.012***.
  - Lithuania: 0.936***.
  - Poland: 0.696***.
  - Slovak Republic: 1.031***.
  - Slovenia: 0.789***.
- Interpretation for NMS:
  - Trend productivity is the key long-run driver; foreign wage movements do not produce lasting deviations from productivity-driven real wage paths in the new member states.

### Short-run dynamics and spillovers
- Baseline Phillips-curve style results (Euro Area excluding Germany):
  - Productivity growth, inflation, and unemployment gaps (level and changes) are key nominal drivers of wage growth.
- Broader slack indicators:
  - Incorporating the non-employment index (NE) and hours gap improves explanatory power marginally; both are statistically significant.
- Error-correction results:
  - ECM terms are sizable and significant at around -0.36, indicating partial correction toward long-run equilibrium within a year.
- External spillovers:
  - Changes in euro area unemployment (lagged two quarters) and euro area wage growth (lagged three quarters) are statistically significant contributors to domestic wage growth.
  - Preferred short-run specification uses the non-employment index gap and hours per employee as additional slack measures.
- Migration effects (short-run):
  - Net migration inflow increases weigh on subsequent wage growth, but impact is modest and temporary.
  - A rise in net migrant inflows by 1 percentage point of the labor force (characterized as an exceptionally large shock) is found to reduce wage growth in the following year by a modest amount (text cuts off before exact quantified magnitude).

### Additional methodological and interpretive points
- Robustness:
  - Analytical results are similar when applying an HP filter in all cases for NAIRU estimation.
  - Correlations between real wages (deviations from trend productivity) and unemployment gaps:
    - Initially higher in newer EU members, peaking after six quarters.
    - In EU15 countries correlations start lower and peak after eight quarters (IMF 2018).
- Modeling choices:
  - Germany treated separately as a regional wage leader.
  - Italy excluded from second panel due to unreliable long-term productivity trend (trend labor productivity rose only 1 percent cumulatively since 2002).
- Data caveats:
  - Migration data used only up to 2015, limiting ability to test migration impacts in the most recent sample years.
  - Some country-specific data issues noted (e.g., Hungary: discontinuities in hours worked; Poland: early high real wages relative to productivity and later public-sector wage freeze).

*Source: https://www.imf.org/-/media/files/publications/wp/2019/wpiea2019156.pdf*

### 0.4 percent (column 9).  But in practice, changes in net migration flows are generally small

### wpiea2019156 - 0.4 percent (column 9).  But in practice, changes in net migration flows are generally small

### Migration effects on wage growth
- Changes in net migration flows are generally small relative to the labor force; wage effects are also small and temporary.
- When migration is separated into inflows and outflows (column 10), outflows have a larger coefficient, though the difference is not statistically significant.
- In newer EU members, a rise in inflows by 1 percentage point is found to reduce wage growth in the following year by 0.5 percent.
- In the other euro area countries, a rise in inflows by 1 percentage point is found to reduce wage growth in the following year by 0.4 percent.
- For Germany, changes in net migration flows do not have a statistically significant impact on wages (column 9).

### Newer EU Members: wage dynamics and slack
- Wage Phillips curve baseline:
  - Wage Phillips curves show sizable effects from trend productivity growth, expected inflation, and labor market slack.
  - Lagged inflation is not statistically significant, reducing nominal inertia in wages relative to euro area countries.
- Broader unemployment indicators:
  - Coefficients on labor market slack are notably higher in new member states, indicating greater wage flexibility and aiding adjustment to asymmetric shocks.
- Error correction analysis:
  - Pace of wage convergence to equilibrium is slightly higher, with the coefficient on the error correction term at -0.40.
  - The error correction model with the nonemployment index gap provides a larger increase in explanatory power relative to unemployment.
- External spillovers:
  - Spillovers from foreign labor markets have more significant effects on wage growth in newer member states.
  - Changes in unemployment in the euro area (columns 8 and 9) have substantial and significant impacts on wage growth, with short lags.
  - Growth in euro area wages has a significant impact (column 9), consistent with euro area wages being a starting point for wage bargaining in many newer member states.
- Role of migration and recent wage pickup:
  - Declines in both domestic and foreign slack have contributed to recent wage pick-up in newer members.
  - Migration outflows may partly account for wage acceleration during 2016–17, but migration data for recent years are not yet available.

### Germany: wage dynamics and indicators
- Wage Phillips curve baseline:
  - High responsiveness to the unemployment gap, trend productivity, and inflation expectations.
- Broader unemployment indicators:
  - Growth in involuntary part-time employment is a key indicator of slack (Table 4.5).
  - A nonemployment index is significant but the coefficient on labor productivity growth became negative in that specification.
  - Changes in involuntary part-time employment included separately show a sizable coefficient, possibly reflecting use of changes in employee hours to avoid layoffs.
- Error correction analysis:
  - The error correction term is particularly high (about -0.6) and contributes substantially to explanatory power.
  - The error correction model with changes in involuntary employment is the best baseline model (column 6).
- External spillovers:
  - German wage setting appears anchored on domestic labor market conditions and less sensitive to spillovers than regional panels.
  - German wages are not responsive to changes in euro area unemployment (column 7 in Table 4.5).
  - The estimated coefficient on euro area wage growth has the opposite sign (column 8) from that expected from a spillover.
- Migration:
  - Changes in net migration flows do not have a statistically significant impact on German wages (column 9).

### V. Factors driving wage growth — A. Decomposition (regional findings)
- Euro Area excluding Germany:
  - Initial slowing in wage rises (average from five-country panel) by 2.3 percentage points (ppts) in 2010 is linked to:
    - lower inflation expectations: 0.8 ppts
    - lower past inflation: 0.5 ppts
    - domestic labor slack: 0.6 ppts
    - wage overhang captured by error correction term: 0.3 ppts
  - Error correction continued to weigh on wages by 0.2 to 0.3 ppts during 2011–15.
  - During 2011–13, inflation expectations and actual inflation recovered, lifting combined contribution by 0.9 ppts.
  - Domestic and external slack weighed more heavily during 2012–14, with a total drag of 0.6 ppts on wage growth in both 2013 and 2014.
  - Contributions from inflation expectations and inflation fell sharply during 2014–15 by 0.9 ppts, with only a slight increase by 2017.
- Newer EU Members:
  - Sharp halt in wage rises in 2009 reflected large negative contributions from rising domestic slack and rising euro area unemployment, plus error correction drag as trend productivity declined.
  - By 2011 declines in domestic slack began to support wages; by 2014 declines in euro area unemployment began to support wages.
  - By 2016–17, low domestic slack began to reinforce wage rises.
  - The combination of domestic and external pressures does not fully account for wage acceleration during 2016–17; migration outflows may have contributed, but recent migration data are not yet available.
- Germany:
  - Steep initial fall in wage growth by 2.9 percentage points in 2010 is linked to:
    - lower inflation expectations: 0.9 ppts
    - domestic labor slack: 0.3 ppts
    - error correction: 1 ppt
  - Domestic slack also weighed on wages in 2011 and has not become a source of upward pressure more recently.
  - During 2011–13, recovery in inflation expectations lifted contribution by 0.8 ppts.
  - Wage growth higher than 3 percent in 2012 led to significant error correction drag during 2012–14, peaking at 0.7 ppts in 2013.
  - Contributions from inflation expectations fell during 2014–15 by 0.4 ppts, with a slight additional decline in 2017.

### V. Factors driving wage growth — B. Regional differences and quantitative contributions
- Newer EU members:
  - Wages more responsive to domestic labor slack; coefficients on nonemployment gap and hours gap about two times larger (column 8).
  - Impact of changes in nonemployment much larger than in EU15; wages respond more rapidly to changes in slack.
  - Estimated contribution to wage growth from diminished domestic slack in recent years: about 2 percentage points.
  - Combined spillovers from euro area unemployment and euro area wage rises account for about 1½ percentage points of the wage pickup in newer members during 2015–17.
- Euro area excluding Germany (EU15):
  - Combined spillovers from euro area unemployment and euro area wage rises account for less than ½ percentage point of the wage pickup during 2015–17.
  - Expected and lagged inflation are much more important in wage formation in the EU15:
    - Coefficient on lagged inflation is much more significant.
    - Contribution from expected inflation is more than two times higher in the EU15 than in newer member states.
  - Near-term expected inflation in the euro area remains subdued; contribution of inflation expectations to wage increases declined by 0.5 percentage point during 2016–17 compared with 2012–13.
  - Subdued wage rises can contribute to persistently low inflation.

### V. Factors driving wage growth — C. Simulation of spillovers
- Scenario: hourly wage rates in Germany rise 1 percentage point faster than in a baseline.
  - This would raise euro area wage growth by about 0.4 percentage point given Germany’s weight in the euro area.
  - The shock would spill over into wage growth in both regional panels.
  - Higher German wages would also spill over through long-run equations for Austria, Belgium, and the Netherlands.
  - Overall, wage growth in the euro area excluding Germany rises about 0.1 percent after one year.

*Italic: IMF staff calculations based on Eurostat and Haver Analytics data as presented in the source content.*

### 0.2 percent in the medium term. The

### wpiea2019156 - 0.2 percent in the medium term. The

### Impact on Wages and Channels
- Impact on newer EU member country wages is slightly larger in the near term (about 0.15 percent after one year), but fades to zero over time because in the long run real wages in the newer member states depend only on domestic labor productivity.
- To the extent that higher wages lead to higher inflation, through either domestic demand or cost channels, the medium-term impact on wages would be higher than these simulations indicate.
- Cross-country labor market spillovers through labor market conditions, wage competition and migrant flows influence wage growth:
  - For the EU15, labor market slack in foreign countries and slow wage growth among trade competitors contributed to recent wage moderation.
  - For the newer EU members, spillover effects are significant but not sufficient to outweigh the positive effect on wages from domestic labor market recovery.

### Wage Outlook (projections and assumptions)
- With labor market slack continuing to diminish and inflation rising, wage growth is expected to accelerate by end-2021 to:
  - just below 4 percent in Germany,
  - 3.5 percent on average in other Euro area countries,
  - just below 6 percent in new EU members.
- Trend productivity growth is assumed to remain at the current level.
- A more optimistic outlook for productivity recovery would imply faster wage growth.
- Projections are subject to uncertainties:
  - Downside: extent to which labor market condition can improve further depends on the share of unemployment and under-employment that is structural.
  - Sensitivity of wages to fundamentals can vary over time; with higher integration of product and labor markets, domestic fundamentals may have less effect on wage growth while foreign factors become more important.

### Key Empirical Findings and Mechanisms
- Long-run relationship:
  - Wage developments in the EU15 and newer EU members are both linked to labor productivity in the long run.
- Differences in responsiveness:
  - EU15: wages respond relatively slowly to changes in unemployment and are closely related to inflation and inflation expectations for the coming year. Current nominal wage developments are not unusual; rather, short-term inflation expectations are unusually low owing to prolonged low inflation.
  - Newer EU members: wage growth responds more quickly to changes in labor market slack; inflation and short-term inflation expectations are less important, explaining faster and earlier acceleration in wage growth.
- Role of deviations and nominal inertia:
  - Real wages largely follow labor productivity in the long run, but deviations can develop over time. Error correction models help understand wage moderation, particularly after major shocks in regions with nominal wage inertia (e.g., EU15).
  - Example: during the global financial crisis, nominal wage rises in the EU15 declined little at first even as inflation and productivity fell, resulting in a rise in real wages relative to labor productivity trends; subsequent low nominal wage growth partly reflected unwinding of that real wage overhang.
- Broader indicators of slack:
  - Involuntary part-time employment and hours worked per person contain supplementary information to unemployment on overall slack.
  - A nonemployment index that incorporates involuntary part-time employment along with marginally attached workers increases explanatory power for wage developments relative to unemployment.

### Selected Econometric Highlights (short-run equations)
- Euro Area excluding Germany (selected coefficients):
  - Trend Labor Productivity, Log, Four Quarter Change (t-4): 0.82***
  - HICP, Log, Four Quarter Change (t-5): 0.31***
  - Expected Inflation, One Year Ahead (t-4): 0.50**
  - Error Correction Term (t-4): -0.36***
- Newer EU Members (selected coefficients):
  - Trend Labor Productivity, Log, Four Quarter Change (t-4): 1.20***
  - Expected Inflation, One Year Ahead (t-4): 0.63***
  - Unemployment Gap (t-4): -0.79***
  - Nonemployment Gap (t-4): -1.27***
  - Error Correction Term (t-4): -0.40***
- Germany (selected coefficients):
  - Trend labor productivity, log, 4 qtr change (t-4): 1.02***
  - Expected inflation, one-year-ahead (t-4): 0.66*
  - Unemployment gap (t-4): -1.30***
  - Involuntary PT employment 4 qtr change (t-1): -1.25***
  - Error correction term (t-4): -0.62***

### Implications for Monitoring and Policy
- Monitor broader labor market slack indicators beyond unemployment, including involuntary part-time employment, hours worked per person, and a nonemployment index that includes marginally attached workers.
- Recognize the differing transmission of domestic and foreign slack across regions:
  - In the EU15, foreign slack and slow wage growth among competitors are important contributors to domestic wage moderation.
  - In newer EU members, domestic labor market recovery is the dominant driver of wage acceleration despite spillovers.
- Account for the role of inflation expectations and nominal wage inertia when assessing the persistence of current nominal wage trends.
- Consider that faster productivity recovery would raise projected wage growth relative to baseline projections.

*Source: IMF staff calculations.*

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_Source: https://www.imf.org/-/media/files/publications/wp/2019/wpiea2019156.pdf_