Does It Pay to Be Productive? The Case of Age Groups

Transcription

1 D I S C U S S I O N P A P E R S E R I E S IZA DP No Does I Pay o Be Producve? The Case of Age Groups Alessandra Caald Sephan Kampelmann Franços Rycx Augus 2011 Forschungsnsu zur Zukunf der Arbe Insue for he Sudy of Labor

2 Does I Pay o Be Producve? The Case of Age Groups Alessandra Caald Unversà d Roma La Sapenza and SBS-EM (DULBEA) Sephan Kampelmann Unversé de Llle CLERSE and SBS-EM (DULBEA) Franços Rycx Unversé Lbre de Bruxelles SBS-EM (CEB DULBEA) and IZA Dscusson Paper No Augus 2011 IZA P.O. Box Bonn Germany Phone: Fax: E-mal: za@za.org Any opnons expressed here are hose of he auhor(s) and no hose of IZA. Research publshed n hs seres may nclude vews on polcy bu he nsue self akes no nsuonal polcy posons. The Insue for he Sudy of Labor (IZA) n Bonn s a local and vrual nernaonal research cener and a place of communcaon beween scence polcs and busness. IZA s an ndependen nonprof organzaon suppored by Deusche Pos Foundaon. The cener s assocaed wh he Unversy of Bonn and offers a smulang research envronmen hrough s nernaonal nework workshops and conferences daa servce projec suppor research vss and docoral program. IZA engages n () orgnal and nernaonally compeve research n all felds of labor economcs () developmen of polcy conceps and () dssemnaon of research resuls and conceps o he neresed publc. IZA Dscusson Papers ofen represen prelmnary work and are crculaed o encourage dscusson. Caon of such a paper should accoun for s provsonal characer. A revsed verson may be avalable drecly from he auhor.

3 IZA Dscusson Paper No Augus 2011 ABSTRACT Does I Pay o Be Producve? The Case of Age Groups * Usng longudnal mached employer-employee daa for he perod we nvesgae he relaonshp beween age wage and producvy n he Belgan prvae secor. More precsely we examne how changes n he proporons of young (16-29 years) mddleaged (30-49 years) and older (more han 49 years) workers affec he producvy of frms and es for he presence of producvy-wage gaps. Resuls (robus o varous poenal economerc ssues ncludng unobserved frm heerogeney endogeney and sae dependence) sugges ha workers older han 49 are sgnfcanly less producve han prme age and young workers. In conras he producvy of mddle-age workers s no found o be sgnfcanly dfferen compared o young workers. Fndngs furher ndcae ha average hourly wages whn frms ncrease sgnfcanly and monooncally wh age. Overall hs leads o he concluson ha young workers are pad below her margnal producvy whle older workers appear o be overpad and lends emprcal suppor o heores of deferred compensaon over he lfe-cycle (Lazear 1979). JEL Classfcaon: J14 J24 J31 Keywords: wages producvy agng mached panel daa Correspondng auhor: Franços Rycx SBS-EM (CEB DULBEA) Unversé Lbre de Bruxelles CP 114/02 Avenue F.D. Roosevel 50 B-1050 Brussels Belgum E-mal: frycx@ulb.ac.be * We would lke o hank Sascs Belgum for gvng access o he daa. The usual dsclamer apples.

4 1. Inroducon In European economes he agng of he populaon due o he decrease n brh raes and rsng lfe expecancy represens a dsncve demographc change ha has been documened by nernaonal nsuons (OECD 2006 European Commsson 2007). Ths evoluon s mrrored on he European labour marke where he las hry years have brough a declnng share of young people n he labour force. In many counres he labour marke parcpaon of elderly people has ncreased followng rases n he reremen age. These rends are lkely o perss n he fuure: accordng o projecons he employmen rae of older workers wll ncrease by 19 p.p. from 40% n 2004 for he EU25 o 47% by 2010 and 59% n 2025 (Economc Polcy Commee and European Commsson 2006). Consequenly undersandng he poenal effecs of an agng work force on labour marke performance n general and frm producvy n parcular mgh be crucal n order o help fne-une frms human resource managemen workers' employably and labour marke polces (Borsch-Supan 2010). Wha s more he lnk beween age and producvy s conneced o anoher opcal ssue namely he relaonshp beween age and earnngs. If markes are perfecly compeve hen wages would smply reflec ndvdual producvy. Bu f hs s no he case oher mechansms of wage deermnaon could also play a role. Accordng o he deferred paymen model of Lazear (1979) for example frms creae ncenves for younger workers o curb shrkng and boos job aachmen hrough remuneraon schemes ha rase wages wh age ndependenly of ndvdual producvy. A beer undersandng of he age-wage-producvy nexus s herefore relevan for sound economc polcy and human resource managemen alke. The problem s ha compared o wages measurng producvy and assessng s connecon wh agng s much more complex gven ha we ofen lack a drec measure of producvy dfferences (Auber and Crépon 2003). In fac he lnk beween frm-level producvy and he age srucure has no ye been denfed sasfacorly: exsng research s relavely scarce and conroversal boh heorecally and emprcally. Indeed he mcro daa necessary o sudy he subjec a he frm level has become avalable only recenly. Ths paper provdes one of he frs aemps o evaluae emprcally he relaonshp beween age wage and producvy. More precsely we examne how changes n he proporons of young (16-29 years) mddle-aged (30-49 years) and older (more han 49 years) workers affec he producvy of frms and nvesgae he presence of producvy- 3

5 wage gaps for hese age groups. To do so we use longudnal mached employer-employee daa coverng he Belgan prvae secor over he perod Our daa offers several advanages. Frs he panel provdes accurae nformaon on average producvy and wages whn frms (.e. on he average value added per hour worked and he mean hourly wage) and allows o conrol for a wde range of worker and frm characerscs (such as educaon occupaon gender workng me ype of conrac frm sze frm age and secor). In parcular he daa allows us o compue age varables n erms of hours worked raher han on a per capa bass. Second we are able o address mporan measuremen ssues such as frm-level unobserved heerogeney endogeney of age shares and sae dependence of frm producvy and wages. Hence our daa allows us o ackle varous poenal bases ha are no always accouned for n he exsng leraure. The srucure of he paper s as follows: he nex secon presens a selecve overvew on he exsng leraure; secons 3 and 4 respecvely descrbe our mehodology and daa se; he mpac of dfferen age groups on frm producvy and he comparson beween esmaed age-wage and age-producvy profles s developed n secon 5; he fnal secon concludes. 2. Revew of he leraure In hs secon we presen he srands of he exsng leraure ha are mos relevan for he relaonshp beween age wage and producvy. By and large s far o say ha he opc s sll open o debae snce resuls are relavely scarce and conroversal. From a heorecal pon of vew wo damercally opposed relaonshps beween age and producvy can be envsaged. On he one hand some approaches sugges ha older workers mgh be less producve han younger ones. Indeed he declne n cognve 1 funconng menal and physcal ables (Shepard 1999) ha has been assocaed wh agng may negavely affec performance. Moreover snce older workers are hough o be less healhy han younger counerpars and suffer more frequenly from chronc dseases hey mgh perform less effcenly have hgher raes of abseneesm and herefore lower producvy (Ng and Feldman 2008). Furher f producvy s an ncreasng funcon of nvesmen n new knowledge and a decreasng funcon of human capal deprecaon a he end of he career here wll be a reducon n performance as he posve mpac of recenly acqured human capal wll be ouweghed by ncreasng deprecaon of sklls (Walewsk 1 Cognve ables reflec ner ala numercal capables and verbal reasonng and problem-solvng ables. 4

6 2008). Ths could be parcularly rue n perods of swf echnologcal change n whch acqured sklls deprecae rapdly: n such a conex elderly people are ofen seen as beng less wllng and movaed han younger workers o connuously updae her compeences due o dffculy n processng speed and learnng capables (Skrbekk 2003). In addon o he exen ha echnologcal progress s very fas and deermnes a rapd deprecaon of sklls older workers mgh have an ncenve o rere as soon as possble (Barel and Schermann 1993). Accordng o emprcal research hs appears o be he general percepon ha employers have of older workers (Izn e al. 1994). Employers mgh also be more relucan o nves n ranng for older workers due o he shorer perod of me o benef from on-he-job ranng (Brooke 2003; Prskawez e al. 2006). Fnally young people are hough o be more movaed o exer hgher effor as hey sand o gan relavely more from posve sgnals sen o her employers (Grund and Wesergaard-Nelsen 2005). Conversely older workers mgh nves less effor n erms of hours spen a work or concenraon snce he scope o benef from hgher performance hough promoons and career advancemens s relavely smaller compared o employees n early sages of her careers (Tang and MacLeod 2006). On he oher hand some of he leraure focuses on ceran mplcaons of he human capal model and sresses he posve mpac ha elderly people mgh have on frm producvy (Mncer 1974). Ths second srand of heores suggess ha older workers wll perform beer han younger ones gven ha hey have accumulaed more experence and know-how han younger workers (Czaja and Shar 1998). There s also a hgher probably ha hey have been assgned o a poson n he frm's nernal organzaon ha sus her ndvdual sklls (Jovanovc 1979) and are more lkely o have correcly mached her job preferences wh he employer s requremens (Johnson 1978). Furher as Skrbekk (2003) pons ou n jobs where verbal ables and experence are more mporan han cognve capaces and speedness elderly workers mgh be as producve as younger ones or even more. Fnally echnologcal progress and compulsory ranng mgh have a posve effec f hey nduce agng workers o updae her sklls reman n he job marke and preserve her producvy (Barel and Schermann 1993). As regards emprcal sudes resuls are mxed and dvergng as well. Mos papers relyng on mached employer-employee daa repor a posve bu hump-shaped relaonshp beween age and frm performance. In general srong decreases n producvy are observed 5

7 afer he age of However Hellersen and Neumark (1995) and Hellersen e al. (1999) found ha producvy peaks a 55 years or more. In general sudes nvesgang he ageproducvy relaonshp use workers mean age or shares of workers by age groups as an ndcaor of he age srucure of he workforce whle he mos common measure of frm producvy s frm s value added. Lallemand and Rycx (2009) usng cross secon mached employer-employee daa for he Belgan economy and usng value added per capa o proxy producvy fnd ha young workers are sgnfcanly more producve han older ones. They also assess he dfference beween ICT and non-ict secors and conclude ha he effec of age on producvy s much more pronounced n ICT frms. Tang and MacLeod (2006) usng panel daa o evaluae producvy growh n en Canadan provnces fnd a negave and sgnfcan mpac of he share of older workers (aged 55 and more) on producvy growh (measured by GDP). By conras Berschek and Meyer (2008) analyse a panel of frm level daa for he German manufacurng and servce ndusres measure producvy by sales per workers and fnd ha older workers (aged 49 and more) are no less producve han prme age workers whle younger workers (aged less han 30) would be less producve han prme age workers. In parcular hey fnd ha echnologcal progress proxed by he use of compuer has a posve mpac on older workers producvy. These resuls are n lne wh Göbel and Zwck (2009). Usng panel daa on he German labour marke hey show ha esablshmen producvy ncreases wh he share of workers unl he age group years and decreases only slghly aferwards. A less analysed bu equally unresolved aspec concerns he relaonshp among age wage and producvy. As already menoned whle sandard heory predcs ha wages wll always reflec margnal producvy oher heores clam ha wages can be deermned by facors ndependen from producvy. The deferred paymen model (Lazear 1979) for nsance predcs ha wages wll ncrease wh age n order o recompense workers for her loyaly o he frm. More precsely suggess he exsence of a negave (posve) gap beween wage and margnal producvy for young (older) workers. Tesng for producvy-wage gaps Auber and Crépon (2003) on he bass of daa coverng he French manufacurng servce and commerce secors and quanfyng producvy by value added fnd ha ndvdual producvy grows unl he age of 40 and hen sablzes bu repor no evdence of a producvy-wage gap for elderly people (excep 2 See Andersson e al. (2002) for Sweden Auber and Crépon (2003) for France Dose (2006) for Canada Grund and Wesergaard-Nelsen (2005) for Denmark Haegeland and Klee (1999) for Norway Halwanger e al. (1999) for US Hellersen and Neumark (2004) for US Malmberg e al. (2005) for Sweden Prskawez e al. (2006) for Ausra. 6

8 above 55 years old). Van Ours and Soeldrajer (2010) use a mached worker-frm panel from he Duch manufacurng secor and value added o proxy producvy. Once hey ake no accoun he endogeney of age shares and frm fxed effecs hey fnd ha boh producvy and wage coss ncrease wh age bu canno fnd srong evdence for producvy-wage gaps. Ilmakunnas and Malrana (2005) analyse Fnnsh manufacurng plan daa and specfy dfferen producvy equaons usng value added and sales as proxy for producvy. They fnd an ncreasng producvy-wage gap by age ha hey mpue o srong senory effecs n wage seng. A sgnfcan wage-producvy gap bu of he oppose sgn s found n Cardoso e al. (2010) on he bass of admnsrave longudnal daa on workers and her frms n he manufacurng and servces prvae secor n Porugal and measurng producvy wh oal sales per labour un. They observe ha producvy peaks around he age of 50 and hen remans raher consan whereas wages are que fla afer 29 years old and declne afer 50. Accordng o her esmaes he conrbuon of older workers o frm producvy exceeds her wages. 3. Mehodology The es developed n hs arcle s based on he smulaneous esmaon of a value-added funcon and a wage equaon a he frm-level. The value-added funcon yelds parameer esmaes for he average margnal produc of each workers age group whle he wage equaon esmaes he respecve mpac of each age caegory on he average wage pad by he frm. Gven ha boh equaons are esmaed wh he same se of frms age groups and covaraes he parameers for margnal producs and wages can be compared and conclusons on age producvy-wage gaps can be drawn. Ths echnque was poneered by Hellersen e al. (1999) and refned by Auber and Crépon (2003) van Ours (2009) Göbel and Zwck (2009) van Ours and Soeldrajer (2010) and ohers. Equaon (1) s a funcon lnkng a range of npus of frm o s added value Y. Y F( K QL ) (1) where K represens he frm's capal sock and QL s a qualy of labour erm. The laer allows nroducng a heerogeneous labour force no he value-added funcon. There s an abundan economerc leraure on he esmaon of relaonshps as he one depced n Equaon (1). In an aemp o reflec more accuraely he producon process 7

9 nsde he frm specalss n he feld have proposed specfcaons allowng e.g. for producon neffcences or dfferen elasces of subsuon beween he facors of producon. Snce our focus s no on he producon process self bu raher on he comparson beween producves and wages for a se of workers age groups we use a smple Cobb-Douglas verson of Equaon (1) wh subsuon elasces equal o one and he assumpon of frms operang a he effcency froner. Ths resrcon appears o be unproblemac as prevous frm-level sudes have shown ha producvy coeffcens obaned wh a Cobb-Douglas srucure are robus o oher funconal specfcaons (see for nsance Hellersen and Neumark 2004). Equaon (2) s he basc (Cobb-Douglas) valueadded funcon: log( Y ) log( A ) log( K ) log( QL ) (2) where A s a consan. The parameers α and β are he respecve margnal producves of each npu facor. QL can be wren as: G L j QL L 1 ( j 1) (3) j1 L where L s he oal labour force of he frm and L j /L he proporon of oal labour force n age group j. Subsung Equaon (3) no (2) allows for dfferen margnal producves for each of he G age caegores. If for age group j he parameer θ j s bgger (smaller) han uny hen hs group has a hgher (lower) margnal mpac on producvy han he reference age caegory. If all groups have s equal o one hen Equaon (3) becomes QL = L.e. labour s perfecly homogeneous. As for he wage equaon Auber and Crépon (2003) show ha he average wage of frm can be expressed as: w G w j 1 G j 1 j L L j j w 0 G j 1 w w j 0 L j L w 0 G w j L j 1 1 (4) j w 0 L where w j s he average wage of L j and j = 0 he reference age caegory wh he wage w 0. 8

10 Smlar o he nerpreaon of θ n he producon funcon f he rao w j /w 0 s bgger (smaller) han uny hen he margnal mpac of age group j on he average wage n he frm s hgher (lower) compared o he reference age caegory. Comparng margnal producves and wage dfferenals across age groups bols down o comparng j wh he correspondng w j /w Daa and descrpve sascs Our emprcal analyss s based on a combnaon of wo large daa ses coverng he years The frs carred ou by Sascs Belgum s he Srucure of Earnngs Survey (SES). I covers all frms operang n Belgum ha employ a leas 10 workers and wh economc acves whn secons C o K of he NACE Rev. 1 nomenclaure. 3 The survey conans a wealh of nformaon provded by he managemen of frms boh on he characerscs of he laer (e.g. secor of acvy number of workers level of collecve wage barganng) and on he ndvduals workng here (e.g. age educaon enure gross earnngs pad hours sex occupaon). 4 The SES provdes no fnancal nformaon. Therefore has been merged wh a frm-level survey he Srucure of Busness Survey (SBS). The SBS also conduced by Sascs Belgum provdes nformaon on fnancal varables such as frm-level value added and gross operang surplus (per hour and per worker). The coverage of he SBS dffers from ha of he SES n ha does no cover he whole fnancal secor (NACE J) bu only Oher Fnancal Inermedaon (NACE 652) and 3 I hus covers he followng secors: ) mnng and quarryng (C) ) manufacurng (D) ) elecrcy gas and waer supply (E) v) consrucon (F) v) wholesale and real rade repar of moor vehcles moorcycles and personal and household goods (G) v) hoels and resaurans (H) v) ranspor sorage and communcaon (I) v) fnancal nermedaon (J) and x) real esae renng and busness acves (K). 4 The SES s a srafed sample. The srafcaon crera refer respecvely o he regon (NUTS-groups) he prncpal economc acvy (NACE-groups) and he sze of he frm. The sample sze n each sraum depends on he sze of he frm. Samplng percenages of frms are respecvely equal o and 100 percen when he number of workers s lower han 50 beween 50 and 99 and above 100. Whn a frm samplng percenages of employees also depend on sze. Samplng percenages of employees reach respecvely and 10 percen when he number of workers s lower han 20 beween 20 and 50 beween 50 and 99 beween 100 and 199 and beween 200 and 299. Frms employng 300 workers or more have o repor nformaon for an absolue number of employees. Ths number ranges beween 30 (for frms wh beween 300 and 349 workers) and 200 (for frms wh workers or more). To guaranee ha frms repor nformaon on a represenave sample of her workers hey are asked o follow a specfc procedure. Frs hey have o rank her employees n alphabecal order. Nex Sascs Belgum gves hem a random leer (e.g. he leer O) from whch hey have o sar when reporng nformaon on her employees (followng he alphabecal order of workers names n her ls). If hey reach he leer Z and sll have o provde nformaon on some of her employees hey have o connue from he leer A n her ls. Moreover frms ha employ dfferen caegores of workers namely managers blue- and/or whe-collar workers have o se up a separae alphabecal ls for each of hese caegores and o repor nformaon on a number of workers n hese dfferen groups ha s proporonal o her share n oal frm employmen. For example a frm wh 300 employees (namely 60 managers 180 whecollar workers and 60 blue-collar workers) wll have o repor nformaon on 30 workers (namely 6 managers 18 whe-collar workers and 6 blue-collar workers). For more deals see Demuner (2000). 9

11 Acves Auxlary o Fnancal Inermedaon (NACE 67). The merger of he SES and SBS daases has been carred ou by Sascs Belgum usng frms socal secury numbers. Three flers have been appled o he orgnal daase. The frs derves s raonale from neoclasscal producvy heory whch reles on he assumpon ha prces are economcally meanngful. Ths s why we deleed frms ha are publcly conrolled and/or operang n predomnanly publc secors from our sample. All regressons are herefore appled o prvaely conrolled frms only. 5 Second we have elmnaed frms wh less han 10 observaons he reason for hs beng our use of average values a he frm level. In order o assure ha averages (lke for nsance he proporon of employees n a specfc occupaon) are based on a mnmum number of observaons we flered ou frms ha provded nformaon on less han 10 employees. 6 Ths selecon creron leads o an average number of observaons per frm n each year ha s equal o 35. In addon o applyng hese wo flers he fnal sample on whch our esmaons are based consss only of frms ha are observed n a leas hree consecuve years due o he ncluson of lagged dfferences n our models (see Secon 5.1.). Ths leads o a bas owards bg frms because of he sample desgn of he SES n whch bg frms are more lkely o say n he sample for several consecuve years han small frms (see foonoe 6). Our fnal sample consss of an unbalanced panel of 1735 frms yeldng 5459 frmyear-observaons durng he sx year perod ( ). I s represenave of all medumszed and large frms employng a leas 10 employees whn secons C o K of he NACE Rev. 1 nomenclaure wh he excepon of large pars of he fnancal secor (NACE J) and almos all he elecrcy gas and waer supply ndusry (NACE E). The defnon of earnngs we use n he esmaon correspond o he oal gross wages ncludng prema for overme weekend or ngh work performance bonuses commssons and oher prema. The work hours correspond o he oal remuneraed hours n he reference perod (ncludng pad overme hours). The frm's value added per hour s measured a facor coss and calculaed wh he oal number of hours effecvely worked by he frm's employees. All varables n he SES-SBS are no self-repored by he employees bu provded by he frm's managemen and herefore more precse compared o employee or household surveys. 5 More precsely we elmnae frms for whch publc fnancal conrol exceeds 50%. Ths excluson reduces he sample sze by less han 4%. 6 Ths selecon s unlkely o affec our resuls as leads o a small drop n sample sze. 10

12 [Inser Table 1 here] Table 1 ses ous he means and sandard devaons of seleced varables. We observe ha frms have a mean value added per hour worked of Euros and ha workers mean gross hourly wage sands a Euros. The age srucure of he workforce whn frms s on average composed by: 21% of workers younger han 30 years 63% of prme-aged workers (beween 30 and 49 years) and 16% of older workers (wh a leas 50 years). We also fnd ha 24% of workers are women 54% are blue collar 7 33% have a low level of educaon (.e. lower secondary a mos) 34% work less han 38 hours per week and 96% have an open-ended employmen conrac. Moreover almos 90% of workers n our sample are employed n relavely bg frms (.e. frms wh a leas 100 employees) essenally concenraed n he manufacurng secor (61 percen) hoels and resaurans (13 percen) wholesale and real rade repar of moor vehcles moorcycles and personal and household goods (10 percen) consrucon (10 percen) and real esae renng and busness acves (9 percen). 5. Specfcaon and resuls 5.1. Funconal specfcaons of he model In hs secon we descrbe he hree dfferen specfcaons of he Equaons (2) and (4) ha we esmaed. We herefore move from he general form of he added-value and wage equaons o a se of funconal specfcaons. The model formed by Equaons (5) and (6) s our baselne specfcaon and smlar o he model n Hellersen e al. (1999). The β j n Equaon (5) s he relave margnal mpac of age group j (noe ha β j corresponds o θ j - 1 n Equaon (3)). In Equaon (6) β j s he relave margnal mpac of age share j on he average wage (β j corresponds o w j /w 0-1 n Equaon (4)). The erms μ and μ represen he error erms. 7 Blue-collar occupaons nclude Craf and relaed rades workers Plan and machne operaors and assemblers and Elemenary occupaons. 11

13 12 q q q p p p e e e s s s m m m k k k j j j STANDARDCONTRACT NON WORKDURATION OCCUPATION WOMEN EDUCATION FIRMSIZE I NACE I FIRMAGE I AGEGROUP YEAR I HOURS VALUEADDED ) ( 2) ( ) ( ) ( ) / log( (5) q q q p p p e e e s s s m m m k k k j j j STANDARDCONTRACT NON WORKDURATION OCCUPATION WOMEN EDUCATION FIRMSIZE I NACE I FIRMAGE I AGEGROUP YEAR I HOURS TOTALWAGES ) ( 2) ( ) ( ) ( ) / log( (6) The dependen varable n Equaon (5) s he oal value added by he frm n perod dvded by he oal number of work hours (akng no accoun pad overme hours) ha have been declared for he same perod. The dependen varable n Equaon (6) s frm 's average hourly gross wage (ncludng prema for overme weekend or ngh work performance bonuses commssons and oher prema). I s obaned by dvdng he frm's oal wage bll by he oal number of work hours. Hence he dependen varables n he esmaed equaons are frm averages of added-value and wages on an hourly bass. The man ndependen varables are he shares of hours worked by each age caegory n oal work hours AGEGROUP j. Ths s a beer employmen ndcaor han he number of employees n each age caegory snce akes no accoun age dfferences n workng me. We spl employees of a frm no hree age groups (.e. < ) and consder he share of prme-aged workers as our reference caegory. These age caegores provde a good represenaon of he dfferen sages n he ndvdual lfe cycle. Indeed as noed by Malmberg e al. (2005) one may suppose ha workers younger han 30 years are more

14 healhy moble and movaed ndvduals. The mddle-aged workers mgh () have heaver famly responsbles () be more experenced and () hold mporan managemen responsbles. Workers older han 50 years of age could () have a good knowledge of hemselves (e.g. hey know how o be producve wh a mnmum of effor) () have a beer machng of her ables wh her job preferences () be less movaed o learn and (v) suffer a weakenng of her healh. In addon o he age shares n oal work hours we also ncluded a se of varables conrollng for observable characerscs of he frm and s labour force. Snce he capal sock of frm j s no avalable n he SES-SBS capal s proxed wh a dummy varable for nne economc secors a he one-dg level of he NACE (I m (NACE1) ). Ths s lkely o compensae for he omsson of capal snce he laer ends o be correlaed wh he ype of acvy of he frm. Gven he resuls repored n he emprcal leraure van Ours and Soeldrajer (2010) argue ha he omsson of he exac capal sock does no affec he esmaes of producon funcons on frm-level daa snce he correspondng producvy effecs end o be small (cf. Hellersen e al. 1999; Auber and Crépon 2003; Dose 2006). Addonal dummy conrols are I k (FIRMAGE) ndcang he age of he frm and I s (FIRMSIZE) he frm's sze as measured by he number of employees. We also conrol for he composon of he labour force of frm : EDUCATION e are he proporons of educaonal groups nsde he frm; WOMEN s he share of female workers; OCCUPATION p are he proporons of dfferen occupaonal groups; WORKDURATION q are he shares of par-me and medum-me workers; NON- STANDARDCONTRACT s he proporon of workers wh conracs n whch he employmen erm s no unlmed (for he modales of all conrol varables see Table 1). The esmaed equaons also nclude dummes I (YEAR) for he years of observaon. Esmang Equaons (5) and (6) yelds nsgh no he shape and sgnfcance of age producvy- and wage profles bu does no allow o es drecly wheher he dfference beween he added-value and wage coeffcens for a gven occupaon s sascally sgnfcan. A smple mehod o oban a es for he sgnfcance of producvy-wage gaps has been proposed by van Ours and Soeldrajer (2010). We apply a smlar approach and esmae a model n whch he dfference beween frm 's hourly added-value and average wage s regressed on he same se of explanaory varables as n Equaons (5) and (6). Ths produces age coeffcens ha measure drecly he sze and sgnfcance of each age group producvy-wage gap. We have esmaed Equaons (5) and (6) as well as he producvy-wage gap wh 13

15 wo dfferen mehods. The baselne regresson s a pooled Ordnary Leas Squares (OLS) esmaor wh robus sandard errors (we use a Huber/Whe/sandwch esmae of varance.e. he errors are robus o heeroskedascy and seral correlaon cf. Wooldrdge 2002). Ths esmaor s based on boh he cross-secon varably beween frms and he longudnal varably whn frms over me. Pooled OLS esmaors of value-added models have been crczed for her poenal heerogeney bas (Auber and Crépon 2003; p. 116). Ths bas s due o he fac ha frm producvy depends o a large exen on frm-specfc me-nvaran characerscs ha are no measured n mcro-level surveys. As a consequence he age coeffcens of hese esmaors mgh be based snce unobserved frm characerscs may affec smulaneously he frm's level of added value and s workforce age composon. Ths s referred o as a problem of spurous correlaon and could be caused by facors such as an advanageous locaon frm-specfc asses lke he ownershp of a paen or oher frm dosyncrases. One way o deal wh unobserved me-nvaran heerogeney of frms s o esmae Equaons (5) and (6) as well as he producvy-wage gap n frs dfferences (wh heeroskedascy and seral correlaon robus sandard errors). Frs dfferences do no esmae he level of producvy of frm bu he change n producvy. Tme-nvaran heerogeney s by defnon no lnked o changes n producvy and herefore conrolled for. Snce he frs dfferences esmaor elmnaes frm characerscs ha reman unchanged durng he observaon perod me-nvaran conrol varables are no ncluded n hs specfcaon. In addon o pooled OLS and frs dfferences esmaons we have carred ou a seres of robusness ess o examne wheher our resuls are sensve o: a) he poenal endogeney of he workforce age srucure b) he ncluson of dynamcs n he model and c) he use of a smaller se of conrol varables. The oucome of hese ess (repored n Secon 5.3.) shows ha he man conclusons presened n he nex secon are robus o alernave specfcaons Esmaon resuls We frs esmae equaons (5) and (6) as well as he producvy wage gap by pooled OLS. Resuls regardng he age-producvy profle are presened n he second column of Table 2. They show ha workers younger han 30 are sgnfcanly less producve han prme age and older workers. In conras he producvy of workers older han 49 s no found o dffer sgnfcanly from ha of mddle-aged workers. The regresson coeffcen assocaed o he 14

16 share of young workers s equal o Ths means ha f he fracon of younger workers whn a frm ncreases by one un (.e. one percenage pon) producvy decreases on average by 0.17 percen (.e * 0.01 = = percen). Regresson coeffcens for he shares of young and older workers can hus be roughly nerpreed as elasces beween producvy and fracons of workers by age groups. Ye one should keep n mnd ha a change n one group of (young prme age or older) workers modfes he ncdence of workers n he oher groups (van Ours and Soeldrajer 2010). Turnng o he relaonshp beween age and wage resuls show (see column 3 of Table 2) ha a one percenage pon ncrease n he share of young workers decreases mean hourly wages whn frms on average by 0.32 percen. On he oppose mean hourly wages are found o ncrease on average by 0.11 percen followng a one percenage pon ncrease n he fracon of older workers. Fndngs hus suppor he exsence of a sgnfcan upward slopng age-wage profle. The comparson of esmaes for he age-producvy and age-wage profles suggess ha young workers are pad below her margnal producvy whle workers older han 49 would be overpad. Resuls from he producvy-wage gap regresson (repored n column 4 of Table 2) suppor hs hypohess. Indeed he mpac of he share of young (older) workers on he producvy-wage gap s found o sgnfcanly posve (negave). [Inser Table 2 here] However hese resuls should be nerpreed wh cauon. Indeed hey may suffer from he fac ha me-nvaran unobserved workplace characerscs are no accouned for. Indeed he Breusch and Pagan (1980) Lagrangan mulpler s for he added value and for he wage equaon whch s why we refue he adequaeness of pooled OLS for he esmaon of equaons (5) and (6). We herefore re-esmaed he model as well as he producvy wage gap n frs dfferences. Resuls for he age-wage profle are no very dfferen han hose n he OLS regresson (see column 6 of Table 2). They agan hghlgh ha average hourly wages whn frms ncrease sgnfcanly and monooncally wh mean workers age. Ye he regresson coeffcen assocaed o he share of young workers drops from o whle ha for he fracon of older workers ncreases from 0.11 o Fndngs for he age-producvy profle afer conrollng for frm fxed effecs are que dfferen from hose obaned wh OLS (see column 5 of Table 2). Indeed resuls now show ha workers older han 49 are sgnfcanly less producve han prme age and young workers. Moreover we fnd no evdence anymore for he fac ha young workers would be 15

17 less producve han prme age workers. Overall our resuls lend suppor o he exsence of a mechansm of deferred compensaon over he lfe-cycle (Lazear 1979). Indeed resuls from our producvy-wage gap regresson (see column 7 of Table 2) agan hghlgh he underpaymen of workers younger han 30 and he overpaymen of workers older han Robusness ess An array of ess has been carred ou o assess he robusness of he resuls presened n he prevous secon. The man resuls sand up o a range of alernave specfcaons. Poenal endogeney of age shares A frs ssue o consder s he poenal endogeney of he workforce age srucure. The pon s ha any unobserved producvy shock mgh generae correlaed changes n he workforce age srucure and labour producvy ha are no due o he agng of he workforce per se. For example one mgh expec ha a frm undergong a negave producvy shock would prefer no o hre new ndvduals whch would ncrease he age of he workforce. Hence he correlaon ha we could fnd usng frs dfferences esmaons beween a decrease of frm producvy and he rse of he share of older workers could be purely spurous. A way o address hs smulaney problem s o use nsrumens ha are correlaed wh he problemac explanaory varables and uncorrelaed wh he exogenous shocks (.e. he error erm). To explore he acueness of he smulaney problem n our daa we have esmaed Equaons (5) and (6) as well as he producvy-wage gap n frs dfferences and nsrumened he (dfferenced) age shares wh he one-perod lag of he level of hese shares. In oher words he lagged level of age shares s assumed o be correlaed wh fuure values of he nsrumened varables bu no wh he exogenous shocks. 8 We esmaed he IV frsdfferenced equaons usng he Generalzed Mehod of Momens (GMM) wh a Newey-Wes varance-covarance marx and sandard errors ha are robus o heeroskedascy and seral correlaon. Ths IV approach has been appled o producvy and wage equaons by Auber and Crépon (2003) and s now sandard n he leraure (cf. van Ours 2009; Göbel and 8 We have expermened wh a larger se of nsrumens for nsance by ncludng lags of age shares for -2 and -3. However only he smaller se ncludng one-perod lags passed he es of weak denfcaon. 16

18 Zwck 2009). To examne he relably of our resuls we have compued he usual dagnosc ess for nsrumenal varables. Frs he Klebergen-Paap sasc for underdenfcaon ess wheher he equaon s denfed.e. wheher he excluded nsrumens are all relevan. The null hypohess n hs es s ha he equaon s underdenfed. Second he Klebergen-Paap sasc for weak denfcaon s a Wald F sasc esng wheher he excluded nsrumens are suffcenly correlaed wh he endogenous regressors (he null hypohess beng weak denfcaon). Snce a rejecon rule for hs es has ye o be esablshed we rely on he rule of humb ha weak denfcaon s problemac for F- sascs smaller han 10 (cf. van Ours and Soeldrajer 2010). Fnally we compue an endogeney es wh he null hypohess ha he age shares can acually be reaed as exogenous. The es s based on he dfference of wo Sargan-Hansen sascs: one for he equaon n whch he age shares are reaed as endogenous and one n whch hey are reaed as exogenous. If he null hypohess of hs es canno be rejeced hen nsrumenaon s acually no necessary. The resuls n Appendx 1 ndcae ha under- and weak denfcaon s unproblemac n our case: we rejec he hypohess of under-denfcaon a he one percen level and he Klebergen-Paap sascs for weak denfcaon are above 10. Moreover we canno rejec he hypohess ha age shares can acually be reaed as exogenous: he correspondng p-values are 0.78 (added-value) 0.87 (wage) and 0.74 (producvy-wage gap). Ths means ha nsrumenaon s acually no necessary snce here appears o be no endogeney n he age shares once we conrol for me-nvaran unobserved frm characerscs by akng frs dfferences. The resuls for GMM-IV repored n Appendx 1 should herefore be read wh he dsclamer ha he IV esmaes are less effcen compared o our baselne model n frs dfferences and ha nsrumenaon s acually no necessary n our case. Dynamc specfcaon Anoher problem o consder s he poenal sae dependence of he dependen varable. To do so we esmae a dynamc verson of our models n frs dfferences by ncludng oneperod lag of he dependen varable among he regressors. In oher words we allow he dependen varable o be no only relaed o conemporary npus bu also o be a funcon of s own value n he prevous perod (Arellano and Bond 1991; Göbel and Zwck 2009). The lagged dependen varable s found o be hghly sgnfcan n he hree regressons and he 17

19 goodness of f of our models s mproved (see Appendx 2). Ths beng sad resuls sll confrm conclusons from he sac specfcaon. However he sze of he regresson coeffcens assocaed o he age share varables s somewha reduced. Indeed he dermenal effec of older workers on frm producvy drops from o Moreover mean hourly wages are now found o ncrease (decrease) on average by 0.13 percen followng a one percenage pon ncrease n he fracon of older (younger) workers. Overall hs leads o a (slghly) smaller overpaymen ( underpaymen ) of older (young) workers. More precsely dynamc resuls sugges ha a one percenage pon ncrease n he share of workers younger han 30 (older han 49) ncreases (decreases) he producvy-wage gap whn frms on average by 0.15 percen (0.21 percen). Specfcaon whou worker conrols Our baselne specfcaon conrols for he composon of he frm s labour force n erms of educaonal aanmen gender rao occupaonal shares he exen of medum- and parme work and he proporon of non-sandard work conracs (see secon 5.1.). Ths s he sandard procedure o creae a ceers parbus effec for he age varable. An alernave perspecve on our queson can be obaned by regressng our dependen varables on age shares whou hese conrol varables n he model. In hs case an age group composon n erms of educaon or occupaon s vewed as a consuen elemen of s mpac on producvy wages and producvy-wage gaps nsead of solang he age coeffcens from hese characerscs. We have compued he frs dfferences esmaor (boh sac and dynamc) excludng worker conrols and fnd our conclusons unalered alhough he sze of he regresson coeffcens assocaed o he age share varables are generally bgger n absolue value (see Appendx 3). 6. Concluson Ths paper provdes one of he frs aemps o dsenangle he relaonshp beween age wage and producvy. More precsely we examne how changes n he proporon of young (16-29 years) mddle-aged (30-49 years) and older (more han 49 years) workers affec he producvy of frms and nvesgae he presence of producvy-wage gaps for hese age groups. To do so we use longudnal mached employer-employee daa coverng he Belgan 18

20 prvae secor over he perod Our daa allows o ackle a range of measuremen ssues ha have hampered he exsng leraure on our queson: he panel daa provdes accurae nformaon on average producvy and wages whn frms; conrols for a wde range of worker and frm characerscs; ncludes age varables n erms of hours worked raher han on a per capa bass; and perms o deal wh unobserved frm heerogeney he endogeney of age shares and sae dependence of frm producvy and wages. Resuls based on our preferred specfcaon sugges ha workers older han 49 are sgnfcanly less producve han prme age and young workers. By conras he producvy of mddle-aged workers s no found o be sgnfcanly dfferen from ha of young workers. Fndngs furher ndcae ha average hourly wages whn frms ncrease sgnfcanly and monooncally wh mean workers age. Overall hs leads o he concluson ha young workers are pad below her margnal producvy whle older workers appear o be overpad. These resuls may have mporan polcy mplcaons. The fac ha older workers are found o be less producve han young and prme-age workers suggess ha polces amng o mprove he employmen rae of older people (e.g. abolshng early reremen schemes or lfng he legal reremen age) may be dermenal for frm producvy. Polces encouragng older workers o rean n work or o reurn o work should hus be accompaned by effcen ranng programmes. More effor should also be devoed o he mprovemen of workng condons so as o reduce he mpac of agng on workers physcal and menal healh (and producvy). However consderng our resuls from a lfeme perspecve may lead o somewha dfferen conclusons. The pon s ha workers are found o be underpad when young and overpad when older. As hghlghed by Lazear (1979) hs sequencng of pay may be benefcal o boh employers and employees n nernal labour markes. Indeed s he presen value of career compensaon ha would maer n hese markes. Pu dfferenly he adopon of a deferred compensaon scheme would mprove employees producvy (because smulaes workers effor reduces monorng coss and enables frms o hre and rean he bes employees) and hence allow frms o pay hgher presen value career compensaon han oherwse (Ehrenberg and Smh 2003). Overall hs lfe-cycle perspecve suggess ha he observed under- and overpaymen of respecvely young and older workers n he Belgum prvae secor should no be harmful o employers wh nernal labour markes excep f he presen value of career compensaon exceeds ha of margnal producves. The same should be rue for her 19

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25 Table 1. Descrpve sascs for frms ( ) Varables: Mean Sd. Dev. Added value per hour (2004 Euros) Hourly wage (2004 Euros) Share of workers < 30 years Share of workers beween 30 and 49 years Share of workers > 49 years Share of female workers: Educaon: Lower educaon Lower secondary educaon General upper secondary school Techncal/arsc/professonal upper secondary school Shor hgher educaon Long hgher educaon or unversy Occupaons: Managers Professonals Techncans and assocae professonals Clercal suppor workers Servce and sales workers Craf and relaed rades workers Plan and machne operaors and assemblers Elemenary occupaons Workng me: Par me (< 20 work hours per week) Medum me (20 o 38 hours per week) Full me (> 38 work hours per week) No sandard (.e. non open-ended) employmen conrac Number of employees per frm: < = o o o o > = Frm age: < = 1 year o 4 years o 9 years 0.05 > = 10 years 0.93 Secor (%): Mnng and quarryng (C) 0.01 Manufacurng (D) 0.61 Elecrcy gas and waer supply (E) 0.00 Consrucon (F) 0.10 Wholesale and real rade repar of moor vehcles moorcycles and personal and household goods (G) 0.10 Hoels and resaurans (H) 0.13 Transpor sorage and communcaon (I) 0.07 Fnancal nermedaon (J) 0.01 Real esae renng and busness acves (K) 0.09 Number of observaons 5459 Number of frms

26 Table 2: Esmaon resuls Dependen varable: Value added per hour worked (ln) Share (Age < 30) -0.17*** (0.06) Share (Age > 50) 0.00 (0.07) Pooled OLS Mean wage per hour worked (ln) Value added-wage gap (ln) Value added per hour worked (ln) 0.03 (0.04) -0.12** (0.05) Frs dfferences Mean wage per hour worked (ln) Value addedwage gap (ln) -0.32*** (0.02) 0.15*** (0.06) -0.15*** (0.02) 0.17*** (0.05) 0.11*** -0.11* 0.15*** -0.26*** (0.03) (0.06) (0.02) (0.05) Worker characerscs a Yes Yes Yes Yes Yes Yes Frm characerscs b Yes Yes Yes Dropped Dropped Dropped (Tme nvaran) (Tme nvaran) (Tme nvaran) Year dummes (7) Yes Yes Yes Yes Yes Yes F sasc R squared Number of observaons Number of frms Noes: ***/**/* sgnfcan a he 1 5 and 10% level. Robus sandard errors are repored beween brackes. a Conrol for educaonal and occupaonal composon of he frm s workforce (6 and 8 caegores respecvely) share of female employees workng me (3 caegores) and share of non-sandard work conracs. b Conrol for frm sze (5 dummes) frm vnage age (3 dummes) and ndusry (8 dummes). 25