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Ageing Workforce, Productivity and Labour costs of Belgian Firms

Ageing Workforce, Productivity and Labour costs of Belgian Firms . Vandenberghe, Vincent (IRES- UCL) Waltenberg , Fabio ( CEDE, Universidade Federal Fluminense) ZEW seminar, Mannheim June 15, 2010. U niversité C atholique de L ouvain. Presentation outline. Motivation Existing literature

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Ageing Workforce, Productivity and Labour costs of Belgian Firms

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  1. Ageing Workforce, Productivity and Labour costs of Belgian Firms Vandenberghe, Vincent (IRES- UCL) Waltenberg, Fabio (CEDE, Universidade Federal Fluminense) ZEW seminar, Mannheim June 15, 2010 Université Catholique de Louvain

  2. Presentation outline Motivation Existing literature Methodology Data Results and conclusions

  3. 1. Context, motivation Policy and scientific context - Ageing population, political initiatives to increase older empl. rates but (very) low employment in some EU countries (e.g. Belgium, France, Luxembourg) - Existing literature looks mainly at… the consequences of an ageing population, in terms of welfare cost or growth (Gruber and Wise, 2004) the retirement behaviour of older individuals (replacement rates, pension, early-retirement schemes, role of health, joint-decision within households…) (Mitchell & Fields, 1983) <=> supply side Not so much the determinants of the labour demand by firms (e.g. labour costs, productivity...) <=> demand side Despite country-level evidence suggesting that it could matter

  4. 1. Context, motivation (cont) Belgium

  5. 1. Context, motivation (cont) Belgium

  6. 1. Context, motivation (cont) proc glm data=silc.corr; model emplg= rwage rp /solution; run; Standard Parameter Estimate Error t Value Pr > |t| Intercept 0.20 0.16800741 1.23 0.2312 rwage -.58 0.17990096 -3.26 0.0038 rp 0.17 0.22314542 0.76 0.4560

  7. 1. Context, motivation (cont.) Our main motivation hereis to answertwo questions Do ageing workforces negatively affect productivity performance of firms? [growth/ GDP] Are employers willing to (re)employ older workers? [Employment rate] => Key assumption: a sizeable negative productivity- vs. labour costs gap is likely to adversely affect the labour demand for older workers

  8. 2. Existingliterature on age, productivity (and labour costs) Individual-level data “Individual job performance is found to decrease from around 50 years of age, which contrasts with life-long increases in wages. Productivity reductions at older ages are particularly strong for work tasks where problem solving, learning and speed are needed, while in jobs where experience and verbal abilities are important, older individuals’ maintain a relatively high productivity level.” (Skirbekk, 2004: SURVEY)

  9. 2. Existingliterature (cont.) Country-level data “(…) large macro-data panel (…) explores the impact of the age composition of the labour force on levels and growth rates of output per worker as well as on total factor productivity (TFP). The results point to an inversely U-shaped relationship between the share of workers in different age groups (...) the impact of projected ageing of the labour force on productivity and per-capita growth could be really substantial in some cases” (Werding, 2007)

  10. Firm-level data*** Hellerstein et al. (1999) [USA]: wages and productivity tend to grow with age, but no significant gap. Malmberg, Lindh, & Halvarsson (2006) [Sweden]: an accumulation of high shares of older adults in Swedish manufacturing plants does not seem to have a negative effect on plant-level productivity Gründ & Westergård-Nielsen (2008) [DK]: find that mean age (and age dispersion) in Danish firms are inversely u-shaped related to firm productivity Skirbekk, (2008)[International survey]: The most common finding from these studies is a hump-shaped relation between job performance and age. Of the 14 studies considered, 11 find a productivity decline in the 50s relative to the 30s and 40s, two have inconsistent results, while one finds that productivity peaks among the oldest workers.

  11. Aubert & Crépont (2003),Economie & Statistiques [France], productivity rises with age until around the age of 40, before stabilizing, a path which is very similar to those of wages. A wage-productivity gap is observed only for workers aged more than 55 Dostie (2006), IZA [Canada] obtains concave (inversely U-shaped) age-productivity profiles. Significant wage-productivity gap occurs with educated males aged 55 + Ilmakunnas & Mliranta(2007) [Finland]. Older workers separations are correlated with higher productivity, lower cost=> higher profits Göbel, Ch. and Zwick, Th. (2009) [Germany] find that productivity increases with the share of employees until the age of 50-55 and only decreases slightly afterwards van Ours, J.C & Stoeldraijer, L. (2010),[Netherlands] find little evidence of an age related pay-productivity gap

  12. 3. Methodology Equ.1: productivity log Yit = α log LitA +ß logKit +γ Fit + it where:Yitis the firm’ value added andLitA a “labour quality index” à-la-Hellerstein LitA = ∑k λkLikt = µref Lit + ∑k (µk - µref) Likt µk being the productivity of type (e.g. age) k workers

  13. Assuming k=0  18-29 k=1  30-49 [ref] k=2  50-65 log Yit ≡ yit = A+ αli,t+ η0 Pi0t + η2Pi2t+ß kit +γFit +  it with Pi2t= Li2t/Li1t η2= α (λ2– 1)and λ2= µ2/µ1;

  14. Equ.2: labour costs lnLCit = ln π1 + ln Lit + 0Pi0t + 2Pi2t + it with2≡ Φ2-1= π2/ π1 -1 π being the relative labour cost of the considered type of workers Key question λ2= ??? Φ2 λ2= relative productivity of 50-65 Φ2= relative labour cost of 50-65

  15. Identification challenge yit = A+ αli,t+ η0 Pi0t + η2 Pi2t+ß kit +γFit +  it it=δi+ ωit+ εit δiunobservable (time-invariant)heterogeneity between firms ωitshort-term (asymmetrically) observed productivity shocks, ωit εitrandom error E(εit) = 0

  16. Production/productivity (cont.) We report the results of several estimations methods: OLS, first-difference, within (fixed-effect), System GMM à-la Blundell-Bond Our preferred approach = proxying the short-term productivity shocks ωit using with demand for intermediate inputs (Levinshon & Petrin, 2003) intit =I(ωit , kit) [5] Assuming this function can be inverted the residual  itbecomes δii +ωit(intit) + εit [6] with ωit(intit) that can be approximated by a polynomial expansion in int.

  17. 4. Our Data Employers-employees matched data ~10.000 firms with 20+ workers (BELFIRST- BNB) using firm identifiers, we are able to inject information from banque Carrefour de la sécurité sociale on the age of (all) workers employed by these firms: ~1.200.000 workers …..we do not need to assign workers to firms using matching methods like in Hellerstein et al. (1999) Data aggregated at firm level Long Panel 1998-2006 (9 years)

  18. Information on firms from the (now dominant) service sector, where administrative and intellectual work is predominant Like Aubert & Crépon (2003) and Dostie (2006), we have a measure of firms’ productivity (the net valued added), which is measured independently from firms’ wage cost Contrary to Dostie (2006), we do have a measure of firms’ capital stock, such that no imputation method is required.

  19. Meanage and value added per employeeDenmarkBelgium

  20. 5. Results

  21. Estimating age differencials. Calculating the produtivity/labour cost gap lnY; Y being value added (productivity) or labour cost η2 2 21 η2= α (λ2– 1);λ2= µ2/µ1; 2≡ Φ2-1= π2/ π1 -1

  22. Testing the significance of the gap (pooled data)

  23. Testing the significance of the gap (by sector)

  24. Testing the significance of the gap (firm-size)

  25. Otherrobustnesschecks - Sub-sample of (big) firms properly reporting on part-time work - Sub-samble of (big) firmsreporting on human capital attainment of recruits and separatingworkers + share of blue-collarworkers => no major qualitative impact on estimates

  26. Conclusion An increase of 10 percentage points in the share of older workers (>50) in a firm depresses its added value by 3.2% (preferred model & cross-model average) Large productivitydifferential for oldersworkers, only partially compensated by lower relative labour costs …which could (negatively) affect the labour demand for older workers.

  27. Conclusion (cont.) The dominant service sector does not seem to offer working conditions that mitigate the negative relationship between age and productivity Older workers in smaller firms display a larger productivity gap, and their productivity is less aligned on labour costs. Small firms might be less inclined to employ them

  28. Other stylised facts

  29. Other stylised facts (cont.) Profitablity of firms located in Belgium and workforce age (intervalles de confiance au seuil de 2,5% confidence interval). Year1998-2006 Source: Belfirst & Carrefour Note: Profits : value added/labour cost, centered using year and NACE4 fixed effects. Age data correspond to the 75th percentile of the firm’s age distribution. Resutls on display are obtained using non prarametric estimation methods

  30. Relative levels of productivity and age (100=age average) Wage 1 Wage 2 100 Productivity Firm 1 Firm 2 Age/seniority 1 Age/seniority 2 Productivity/labour cost gaps and employment contract à-la-Lazear Mandatory departure from firm 1 B A

  31. References Aubert. P. and B. Crépon (2003). “La productivité des salariés âgés : une tentative d’estimation”. Economie et Statistique. 368. 95-119. Dostie. B. (2006). Wages. Productivity and Aging. IZA. Discussion Paper No. 2496. Bonn. Germany. Göbel, Ch. and Zwick, Th. (2009), "Age and productivity: evidence from linked employer-employee data," ZEW Discussion Papers 09-020, ZEW - Zentrum für Europäische Wirtschaftsforschung / Center for European Economic Research. Grund and Westergård-Nielsen (2008). International Journal of Manpower. Vol. 29(5). pp. 410-422 Hellerstein. J.K. and Neumark. D. (1995). ‘Are Earning Profiles Steeper than Productivity Profiles: Evidence from Israeli Firm-Level Data’. The Journal of Human Resources. vol. 30. 1. pp. 89-112. Ilmakunnas, P. and M. Maliranta, (2007), Ageing, Labour Turnovers and Firm Performance, ETLA DP, No 102, The Research Institute of the Finnish Economy, Helsinki

  32. References (cont.) • Levinsohn. J. and A. Petrin (2003). Estimating production functions using inputs to control for unobservables. Review of Economic Studies. 70 (2). 317-341 • Malmberg. B. Lindh. T & Halvarsson. M., (2005). Productivity consequences of workforce ageing -Stagnation or a Horndal effect?. Arbetsrapport No 2005:17. Institute for Futures Studies. Stockholm. • Skirbekk, V. (2004), Age and individual productivity: a literature survey, In: Feichtinger, G. (Editor): Vienna yearbook of population research 2004. Vienna: Austrian Academy of Sciences Press, pp. 133-153. • Skirbekk, V. (2008), Age and productivity capacity: Descriptions, causes and policy options, Ageing Horizons, 8, pp. 4-12. • van Ours, J.C & Stoeldraijer, L. (2010), Age, Wage and Productivity, IZA Discussion Papers 4765, Institute for the Study of Labor (IZA), Bonn. • Werding, M. (2007). "Ageing, Productivity and Economic Growth: A Macro-level Analysis," PIE/CIS Discussion Paper 338, Center for Intergenerational Studies, Institute of Economic Research, Hitotsubashi University

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