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

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2 Presentation outline 1.Motivation 2.Existing literature 3.Methodology 4.Data 5.Results and conclusions

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3 1. Context, motivation Policy and scientific contextPolicy 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 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)the retirement behaviour of older individuals (replacement rates, pension, early-retirement schemes, role of health, joint- decision within households) (Mitchell & Fields, 1983) supply side supply side -Not so much the determinants of the labour demand by firms (e.g. labour costs, productivity...) demand side demand side -Despite country-level evidence suggesting that it could matter

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4 1. Context, motivation (cont) Belgium

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5 1. Context, motivation (cont) Belgium

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6 1. Context, motivation (cont) 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 proc glm data=silc.corr; model emplg= rwage rp /solution; run;

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7 1. Context, motivation (cont.) Our main motivation here is to answer two questionsOur main motivation here is to answer two 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

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8 2. Existing literature 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)

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9 2. Existing literature (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)

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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 Grnd & Westergrd-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.

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11 Aubert & Crpont (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 Gbel, 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

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12 3. Methodology Equ.1: productivity log Y it = log L it A + logK it + F it + it where: Y it is the firm value added and L it A a labour quality index -la-Hellerstein L it A = k k L ikt = ref L it + k ( k - ref ) L ikt k being the productivity of type (e.g. age) k workers

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13 Assuming k=0 18-29 k=1 30-49 [ref] k=2 50-65 log Y it y it = A + l i,t + 0 P i0t + 2 P i2t + k it +F it + it with P i2t = L i2t /L i1t 2 = ( 2 1) and 2 = 2 / 1 ;

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14 Equ.2: labour costs ln LC it = ln 1 + ln L it + 0 P i0t + 2 P i2t + it with 2 2 -1= 2 / 1 -1 being the relative labour cost of the considered type of workers Key question 2 = ??? 2 2 = relative productivity of 50-65 2 = relative labour cost of 50-65

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15 Identification challenge y it = A + l i,t + 0 P i0t + 2 P i2t + k it +F it + it it = i + it + it i unobservable (time-invariant) heterogeneity between firms it short-term (asymmetrically) observed productivity shocks, it it random error E( it ) = 0

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

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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 scurit 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)

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18 Information on firms from the (now dominant) service sector, where administrative and intellectual work is predominant Like Aubert & Crpon (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.

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Mean age and value added per employee Denmark Mean age and value added per employee Denmark Belgium June 09 19

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20 5. Results

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21 Estimating age differencials. Calculating the produtivity/labour cost gap 22 22 2 = ( 2 1); 2 = 2 / 1; 2 2 -1= 2 / 1 -1 lnY; Y being value added (productivity) or labour cost

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Testing the significance of the gap (pooled data) 22

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Testing the significance of the gap (by sector) 23

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

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Other robustness checks - Sub-sample of (big) firms properly reporting on part-time work - Sub-samble of (big) firms reporting on human capital attainment of recruits and separating workers + share of blue-collar workers => no major qualitative impact on estimates 25

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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 productivity differential for olders workers,Large productivity differential for olders workers, only partially compensated by lower relative labour costs which could (negatively) affect the labour demand for older workers. 26

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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 27

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28 Other stylised facts

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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 firms age distribution. Resutls on display are obtained using non prarametric estimation methods

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

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References Aubert. P. and B. Crpon (2003). La productivit des salaris gs : une tentative destimation. Economie et Statistique. 368. 95-119. Dostie. B. (2006). Wages. Productivity and Aging. IZA. Discussion Paper No. 2496. Bonn. Germany. Gbel, Ch. and Zwick, Th. (2009), "Age and productivity: evidence from linked employer-employee data," ZEW Discussion Papers 09-020, ZEW - Zentrum fr Europische Wirtschaftsforschung / Center for European Economic Research. Grund and Westergrd-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 31

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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 32