Abstract
We estimate wage Phillips curve relationships between sectoral wage growth, unemployment and productivity in a country-industry panel of euro area countries. We find that institutional rigidities – such as labour and product market institutions and regulations – limit the adjustment of euro area wages to unemployment, in both upturns and downturns, particularly in manufacturing and, to a lesser extent, in the construction and service sectors. In addition, there are further limitations in the response of wages to changes in unemployment during economic downturns which suggests that euro area wages are also characterised by significant downward wage rigidities, especially in the manufacturing sector. These results are robust to specifications that account for factors that may affect structural unemployment (such as duration-dependent unemployment effects), as well as changes in the skill composition of employment that may affect the evolution of aggregate wages. The results also hold for panels including or excluding the public sector (where wages may be determined differently to the private sector also due to the effects of fiscal consolidation on public sector wages during the crisis). From a policy perspective, reforms in product and labour markets which reduce wage rigidities can facilitate employment growth and enhance the rebalancing process in the euro area.
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Notes
Macroeconometric studies include (Nunziata 2005), Clar et al. (2007), Camarero et al. (2016) and Knell (2013). Microeconomic analyses of wage curve relationships with a focus on institutional determinants include (Nickell and Quintini 2003), Dickens et al. (2007), Agell and Bennmarker (2007), Holden and Wulfsberg (2008).
Estimates of sector-level unemployment are not available for our sample.
Although some empirical estimates of structural unemployment are available from various institutions, they are not usually suitable for use in the current paper. For example, in many cases, structural unemployment is actually estimated by using wage Philips curve relationships. This would lead to endogeneity problems, if we used them in our wage equation.
Since it can be argued that the natural rate of unemployment exhibits some degree of time variation, in particular during recessions, we estimate a specification in which we approximate it using a measure for long-term unemployment (> 24 months unemployed) as a robustness check (Section 5.2).
To check the robustness of our baseline specification, we employ the Mean Group and Common Correlated Mean Group estimators as alternative. We have also experimented with (System) GMM estimation as alternative but found that our rich dynamic structure as well as our large time dimension pose a severe challenge to these estimators.
For example \(\overline {\beta } =\frac {{\sum }_{i=0}^{4}\beta _{i}}{1-{\sum }_{j=1}^{4}\sigma _{j}}\) yields the aggregate long-run unemployment coefficient.
We use ETCR as a proxy for overall product market regulation as the PMR indicator is available from the OECD only at a 5-year frequency.
Robustness checks in Section 5.3 show that imposing unity on long-run productivity parameters does not qualitatively alter our results.
Although the primary objective of this paper is to understand how structural rigidities interact with the unemployment term, Table 13 in the Appendix reports results from specifications that also add the institutional terms in levels. Overall, the results show that, depending on the specification, institutions have a statistically significant effect with roughly half of these results indicating that institutional terms in levels dominate, whilst the unemployment/institutional interaction terms dominate in the other half of the results. In the few remaining results, multicollinearity may explain why neither of these two institutional terms are statistically significant. Furthermore, multicollinearity may also occur between group-fixed effects and slowly changing institutional indicators which may bias results if institutional terms are included in levels.
This could be a sign that inflation adds an additional dimension to the relationship between labour market reforms and the response of wages to unemployment: as workers care about real wages rather than nominal wages, labour market institutions are designed to protect them predominantly from a reduction in real wages. For a discussion on inflation and real wage rigidity see Babecký (2008) and Rusinova et al. (2015).
We also experimented with a triple interaction between unemployment, institutional terms and our downturn dummy to test whether institutions can explain downward rigidity more generally. If institutions would be responsible for downward wage rigidities then one would expect the coefficient on this triple interaction to be significantly positively signed whilst both the interaction between unemployment and the downturn dummy and the interaction between unemployment and institutional terms would remain significantly positive. However, what we find is a significantly negative coefficient estimate (Table 14 in the Appendix). This could either suggest that institutions, rather than preventing wages to fall during recessions, delay the wage response to a decline in unemployment as the economy recovers. In the light of our results on differential effects during the recent crisis it seems more likely that the negative coefficient estimated stems from the fact that countries with more regulated labour and product markets experienced a deeper recession which ultimately led to a stronger wage adjustment compared to countries with less regulation.
As indicated by the relatively lower parameters for the lagged dependent variable for the construction sector.
For a cross-country analysis on this topic see Rusinova et al. (2015).
See Anderton and Hiebert (2009) for further details.
Differences in productivity measurement across sectors may also explain why wage growth seems to respond less to productivity growth in manufacturing and construction compared to services and the public sector. Compared to manufacturing and construction, productivity is harder to measure for the services sector. For example, in the services sectors it is less clear what constitutes output and when it is produced since the output is not stockable. This applies even more so to public services, making the statistical measurement of productivity in market and public services more difficult or at least inherently different (Djellal and Gallouj 2009). In this sense, our results would then suggest that wages are more responsive to the measure of productivity in services and the public sector which may not be fully comparable to lower coefficients on the measure of productivity for manufacturing and construction. This may also partly explain why aggregate analyses find wage growth to respond more strongly to productivity growth compared to our more disaggregate analysis.
An increase in the share of unskilled employment on the other hand may be associated either with stronger wage dynamics or with stagnation in aggregate wages as low-paid workers enter employment. Hence effects on wage growth may be ambiguous. We therefore set our control variables for compositional effects to zero if annual changes in temporary or youth employment are positive.
Coefficient estimates for changes in temporary and youth employment are found insignificant if institutional terms are excluded. The coefficient on youth employment however turns statistically significant once cross-country differences in labour and product market institutions are accounted for.
Whilst our baseline specification for real wages yields short-run coefficients on productivity of between 0.156 and 0.245 (Table 4), Rusinova et al. (2015) obtain results from a comparable specification of 0.44 to 0.48 which depend on the business cycle, country group and level of inflation. Anderton and Bonthuis (2015) estimate comparable short-run estimates of 0.287 to 0.326. Their long-run estimates of 0.597 to 0.788 are larger than our estimates which lie in the range of 0.236 and 0.342.
References
Agell J, Bennmarker H (2007) Wage incentives and wage rigidity: A representative view from within. Labour Econ 14(3):347–369
Anderton R (2012) MPC Task Force [chairman Robert Anderton], Euro area labour markets and the crisis, European Central Bank Occasional Paper Series (138)
Anderton R (2015) Ad hoc team of the European System of Central Banks [Chairman Robert Anderton; Coordinators/Editors Valerie Jarvis and Bela Szörfi], Comparisons and contrasts of the impact of the crisis on euro area labour markets, European Central Bank Occasional Paper Series (159)
Anderton R, Bonthuis B (2015) Downward wage rigidities in the euro area, University of Nottingham Centre for Globalisation and Economic Policy Research Paper Series 2015/09
Anderton R, Hiebert P (2009) The impact of globalisation on the euro area macroeconomy, University of Nottingham Centre for Globalisation and Economic Policy Research Paper Series 2009/14
Arpaia A, Pichelmann K (2007) Nominal and real wage flexibility in EMU. Int Econ Econ Policy 4(3):299–328
Babecký J (2008) Aggregate wage flexibility in new EU member states. Czech Econ Rev 2(2):123–145
Bayoumi T, Eichengreen B (1993) Shocking aspects of European monetary integration. In: Torres G, Giavazzi F (eds) Adjustment and growth in European Monetary Union. Cambridge University Press, Cambridge, pp 193–229
Blanchard O, Katz LF (1999) New developments in price dynamics – wage dynamics: Reconciling theory and evidence. Amer Econ Rev 89(2):69
Calvo GA (1983) Staggered prices in a utility-maximizing framework. J Monet Econ 12(3):383–398
Camarero M, D’Adamo G, Tamarit C (2016) The role of institutions in explaining wage determination in the eurozone: A panel cointegration approach. Int Labour Rev 155(1):25–56
Campos NF, Macchiarelli C (2016) Core and periphery in the European Monetary Union: Bayoumi and Eichengreen 25 years later. Econ Lett 147:127–130
Clar M, Dreger C, Ramos R (2007) Wage flexibility and labour market institutions: A meta-analysis. Kyklos 60(2):145–163
De Santis R, Cesaroni T (2016) Current account core–periphery dualism in the EMU. World Econ 39(10):1514–1538
Dickens WT, Goette L, Groshen EL, Holden S, Messina Granovsky JS, Schweitzer ME, Turunen J, Ward ME (2007) How wages change: Micro evidence from the international wage flexibility project. J Econ Perspect 21:195–214
Djellal F, Gallouj F (2009) Measuring and improving productivity in services: issues, strategies and challenges. Edward Elgar Publishing, Cheltenham
Galí J (2011) The return of the wage Phillips curve. J Eur Econ Assoc 9 (3):436–461
Holden S, Wulfsberg F (2008) Downward nominal wage rigidity in the OECD. BE J Macroecon 8(1)
Kenen PB (1969) The theory of optimum currency areas: an eclectic view. In: Mundell RA, Swoboda AK (eds) Monetary Problems of the International Economy. University of Chicago Press, Chicago, pp 41–60
Knell M (2013) Nominal and real wage rigidities. In theory and in Europe. J Macroecon 36:89–105
McKinnon RI (1963) Optimum currency areas. Amer Econ Rev 53(4):717–725
Mundell RA (1961) A theory of optimum currency areas. Amer Econ Rev 51 (4):657–665
Nickell S, Quintini G (2003) Nominal wage rigidity and the rate of inflation. Econ J 113(490):762–781
Nunziata L (2005) Institutions and wage determination: a multi-country approach. Oxf Bullet Econ Stat 67(4):435–466
Peng F, Siebert S (2007) Real wage cyclicality in Germany and the UK: new results using panel data, IZA Institute for the Study of Labor Discussion Paper Series 2688
Pesaran MH (2006) Estimation and inference in large heterogeneous panels with a multifactor error structure. Econometrica 74(4):967–1012
Pesaran MH, Smith R (1995) Estimating long-run relationships from dynamic heterogeneous panels. J Econ 68(1):79–113
Rusinova D, Lipatov V, Heinz FF (2015) How flexible are real wages in EU countries? A panel investigation. J Macroecon 43:140–154
Sanz-de Galdeano A, Turunen J (2006) The euro area wage curve. Econ Lett 92(1):93–98
Verdugo G (2015) Real wage cyclicality in the eurozone before and during the Great Recession: Evidence from micro data. European Economic Review, Elsevier
Wortmann M, Stahl M (2016) One size fits some: A reassessment of EMU’s core-periphery framework. J Econ Integr 31(2):377–413
Acknowledgments
We would like to thank participants of the 2016 EEFS Conference and two anonymous referees for their helpful comments and suggestions. All views expressed in this paper are those of the authors and do not necessarily correspond with those of the European Central Bank.
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Anderton, R., Hantzsche, A., Savsek, S. et al. Sectoral Wage Rigidities and Labour and Product Market Institutions in the Euro Area. Open Econ Rev 28, 923–965 (2017). https://doi.org/10.1007/s11079-017-9463-y
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DOI: https://doi.org/10.1007/s11079-017-9463-y