Wage Dynamics in Europe Findings from the Wage Dynamics Network (WDN) Frank Smets European Central Bank
WDN Objectives • Two main objectives: – Identify the sources and features of wage and labour cost dynamics that are most relevant for monetary policy; – Clarify the relationship between wages, labour costs and prices, both at the firm and macro-economic level • Inspired by the IPN finding that cross-sector differences in the flexibility of prices was highly negatively correlated with the labour share, suggesting that stickiness in wages and labour costs may be a driving factor behind the slow adjustment of prices. 2
Overview • Institutions and wage structure • Micro facts and macro interpretations – Frequency, timing, indexation and wages of new hires – Downward wage rigidities – Pass-through of wages into prices • Labour markets and the current crisis • Conclusions 3
Wage bargaining institutions: basics Dominant level of bargaining CZ PL EE LT firm 2 CY BG HU UK SK DK BE FI ES DE IT 1 AT FR IE GR LU PT SI higher NL SE 0 0 20 40 60 80 100 Collective bargaining coverage (% workers) Source: EIRO 2006, 2009 4
Wage bargaining institutions: trends • Union density has declined; • But because of widespread extension procedures, the coverage rates have basically remained constant; • There is some trend towards more decentralisation (from sector to firm level). 5
Wage structure across sectors Wage Differentials: Observed 0.5 Observed 0.4 0.3 0.2 0.1 0 -0.1 -0.2 -0.3 -0.4 Sectors(2 digits-nace2) 6
Wage structure across sectors Petroleum and chemical, Wage Differentials: Observed financial and insurance, 0.5 research and development, Observed utilities, are among the 0.4 highest paying industries 0.3 0.2 Finance! 0.1 0 -0.1 -0.2 Clothing, leather and textiles, and retailing are -0.3 among the lowest paying industries -0.4 Sectors(2 digits-nace2) 7
Wage structure across sectors Wage Differentials: Observed vs. Conditioned 0.5 Conditioned 0.4 Observed 0.3 0.2 0.1 0 -0.1 -0.2 -0.3 -0.4 Sectors(2 digits-nace2) 8
Wage structure across sectors TABLE 2.4 Rent sharing and institutions as explanations of wage differentials (1) (2) (3) (4) (5) (6) Levels Change 0.049 *** 0.038 *** 0.074 *** 0.045 *** Rents 0.026* Real gross operating surplus (0.014) (0.011) (0.020) (0.016) (0.015) per worker (GOS) PM competition ‐ 0.347*** ‐ 0.295*** % of small firms in (0.057) (0.076) the industry 0.030 * Bargaining structures % firms with firm ‐ level (0.016) collective agreement *GOS 0.062*** Collective agreement (0.020) coverage* GOS 526 517 423 229 206 260 Observations R 2 0.18 0.24 0.37 0.51 0.60 0.08 Source: Du Caju, Kátay, Lamo, Nicolitsas and Poelhekke (2009). Dependent variable are estimated industry wage differentials after controlling for a large number of observed characteristics as deviations from a measure of aggregate. SES data • Evidence of non-competitive and rent-sharing explanations of wage setting. 9
Overview • Institutions and wage structure • Micro facts and macro interpretations – Frequency, timing, indexation and wages of new hires – Downward wage rigidities – Pass-through of wages into prices • Labour markets and the current crisis • Conclusions 10
Frequency of wage changes • The frequency of wage changes is lower than that of prices: Frequency of price and wage changes % of firms prices 70 wages 60 50 40 30 20 10 0 more frequent once a year less frequent no pattern than once a year than once a year Source: WDN survey • Average duration of wages is about 15 months 11
Frequency of wage changes Table 3.2 –Price and wage rigidity • Wages change (frequency of wage and price changes ) (ordered probit estimates) – less often with high PRICES WAGE Construction -0.369** -0.198** coverage and strong Trade -0.77** 0.108** Market services -0.035 0.12** employment protection; Financial intermediation -0.672** 0.21* 20-49 -0.018 -0.094* – more often with firm 50-199 -0.124** -0.207** >200 -0.168** -0.331** level bargaining and 0.508** Labour cost share 0.054 competitive pressures -0.301** 0.01 indexation. Export (% of sales) -0.139* -0.013 share of white collars 0.167** • Prices change share of high skilled workers 0.087* workforce turnover -0.15** -0.144** share of bonuses on total wage bill 0.01 -0.172** – less often with higher -0.055 collective agreement outside the firm -0.067 collective agreement at the firm level -0.03 -0.112* labour share; coverage of collective agreement 0.055 0.089* EPL 0.104** – And more often with Country dummies yes yes Observations 5340 8993 higher degree of Notes : (*) and (**) denote statistical significance at 5% and 1%, respectively. Source: Druant, Fabiani, Kezdi, Lamo, Martins and competition. Sabbatini (2009). The dependent variable increases with the degree of rigidity. 12
Timing and synchronisation Timing of wage and price changes Percentage of firms that change wages and prices in (a) particular month(s) Note: Germany, Bulgaria and Cyprus not included in the calculation s. Source: Druant, Fabiani, Kezdi, Lamo, Martins and Sabbatini (2009). 13
Indexation of wages to inflation Firm policy of adjusting base wages to inflation: overview Firm-level policy of adjusting base wages to inflation Automatic Informal Past Expected Past Expected Total Total 13.6 3.9 12.9 7.0 36.3 Euro area 16.7 4.1 10.2 5.8 35.7 BE, LU, ES 54.8 11.8 7.9 3.6 78.1 Euro area, no aut. Ind. 6.3 1.9 10.8 6.3 23.9 Non euro area 5.5 3.2 19.8 10.2 38.1 Note: BG, CY and NL not included in the aggregates. Country details in Table 3.3 of the WDN report. – High degree of formal indexation in Belgium, Luxembourg, Cyprus and Spain, consistent with the institutional setting. – In other countries, about one third of the firms have a “policy” that adapts changes in base wages to inflation, mostly to past inflation. 14
Wages of newly hired workers • Most of the variation in hours worked over the business cycle occurs at the extensive margin. ⇒ Wages of new hires are a key determinant of employment. • Micro-evidence for the United States and various European countries suggests that wages of job movers are more pro-cyclical than wages of incumbents: • Survey by Pissarides (2009) suggests an elasticity of about 3; Confirmed by WDN evidence for Portugal. • However, direct survey evidence suggests that firms are reluctant to differentiate wages of newly hired workers and incumbents. 15
Wages of newly hired workers • Around 80 % of firms report that internal factors are the most important factors driving wages of new hires: Percentage of firms reporting each factor 16
Wages of newly hired workers • But external labour market conditions are more important in CEE (36%) than in euro area (15%), mostly reflecting lower coverage. Pseudo R2: 50% 17
Wages of newly hired workers • Main reasons are: – fairness (32/39%) – the fear that such a differentiation may have a negative impact on worker morale and effort (36/35%) • In low-coverage countries, external labour market conditions matter more for firms that – face more competition; – employ more high-skilled workers; – and face a higher turnover. 18
Macro implications • An estimated DSGE model for the euro area (1990:Q2-2008:Q4) with sticky prices and wages, wage indexation and labour market frictions conforms quite well with the micro findings: – The average duration of a wage contract of incumbent workers is estimated to be 4.4 quarters. – Wages of newly hired workers are estimated to be as sticky as those of incumbent workers. – The degree of indexation is estimated to be one third. 19
Macro implications • Together, these features help replicate the relative volatility and persistence in hours worked, real wage and inflation in the euro area quite well Euro area data Benchmark Full wage Flexible wages for new model indexation hires Total hours worked rel. std. dev. 0.721 0.742 0.787 0.637 ser. corr. 0.785 0.837 0.812 0.862 Real wage rel. std. dev. 0.624 0.590 0.542 1.566 ser. corr. 0.826 0.759 0.708 0.728 Inflation rel. std. dev. 0.175 0.192 0.276 0.441 ser. corr. 0.125 0.274 0.395 0.491 Data source: AWM16 database and hours data by Joachim Schroth for the largest 5 economies of the EA. 20
Macro implications • The considerable degree of real wage rigidity leads to a small, but persistent real wage response and a relatively stronger employment response to various shocks. • Example: Tightening of monetary policy output (blue), price deflator (red) 0 -0.5 -1 -1.5 0 2 4 6 8 10 12 14 16 18 20 real hourly wage (blue) & total hours (red) 0.5 0 -0.5 -1 -1.5 0 2 4 6 8 10 12 14 16 18 20 nom. rate 0.25 0.2 0.15 0.1 0.05 0 0 2 4 6 8 10 12 14 16 18 20 21
Macro implications • Confirmed by astructural methodologies: e.g. FAVAR Real GDP and Consumption deflator -3 0.5 x 10 0 -0.5 -1 -1.5 -2 -2.5 RGDP PCD -3 5 10 15 20 Nominal Compensation and Employment -3 0.5 x 10 0 -0.5 -1 -1.5 -2 -2.5 CMP/EMP EMP -3 5 10 15 20 AWM short interest rate 0.3 0.2 0.1 0 -0.1 -0.2 5 10 15 20 22
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