The Changing Demand for Skills: Evidence from the Transition

Transcription

1 DISCUSSION PAPER SERIES IZA DP No The Changng Demand for Sklls: Evdence from he Transon Smon Commander Janos Kollo March 2004 Forschungsnsu zur Zukunf der Arbe Insue for he Sudy of Labor

2 The Changng Demand for Sklls: Evdence from he Transon Smon Commander London Busness School, EBRD and IZA Bonn Janos Kollo Insue of Economcs, Budapes and IZA Bonn Dscusson Paper No March 2004 IZA P.O. Box Bonn Germany Phone: Fax: Emal: Any opnons expressed here are hose of he auhor(s) and no hose of he nsue. Research dssemnaed by IZA 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 company suppored by Deusche Pos World Ne. The cener s assocaed wh he Unversy of Bonn and offers a smulang research envronmen hrough s research neworks, research suppor, and vsors and docoral programs. 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 on he IZA webse ( or drecly from he auhor.

3 IZA Dscusson Paper No March 2004 ABSTRACT The Changng Demand for Sklls: Evdence from he Transon Transon has nvolved major job desrucon and creaon. Ths paper examnes he skll conen of hese changes usng a dealed hree counry frm survey. I shows ha ranson has exered a srong bas agans unsklled labour who have los employmen dsproporonaely. Moreover, job creaon n new frms ends o be based agans workers wh low educaonal aanmens and sklls. The skll conen of blue collar work has also shfed upwards. Alhough here s varaon across he sampled counres, hese appear o be common feaures. They wll have major longer run mplcaons for he level and srucure of employmen and for nequaly hrough he dsrbuon of earnngs. JEL Classfcaon: J21, J23, J63, P31 Keywords: job reallocaon, human capal, ranson, Hungary, Romana, Russa Correspondng auhor: Smon Commander London Busness School Sussex Place Regens Park London NW1 4SA Uned Kngdom Emal: scommander@london.edu Thanks o Karnn Tnn for excellen research asssance and o Mark Schankerman for suggesng some useful changes from an earler draf, as well as o oher semnar parcpans a LBS, EBRD and an IZA/WDI Workshop n Cosa Rca n 2003.

4 1. Inroducon I s wdely beleved ha he planned economes enered ranson rch n human capal relave o marke economes a comparable ncome levels. Ths has been arbued o subsanal publc spendng on educaon, n urn assocaed wh hgh enrolmen raes 1. Ths posve nherance was, however, qualfed by he fac ha whle he share of educaed workers n he labour force was relavely hgh, here was sgnfcan varaon n he qualy of educaon. Moreover, many of he sklls mpared - n parcular hrough vocaonal ranng were hghly process or frm specfc. In some cases, hs led o low adapably of workers; a poenally major lmaon once frms sared o be resrucured and when job mobly became a more mporan consderaon. In addon, he wage dsrbuon was severely compressed. Ths had obvous movaonal consequences and was undoubedly one of he facors ensurng ha he producvy of workers was generally low. Transon nvolved a rude shock o hese arrangemens. Jobs have been desroyed as frms have faled. Varaon n he rae of job desrucon across counres has been large. In he advanced reformers of Cenral Europe, subsanal job desrucon came quckly. The combnaon of resource reallocaon and resrucurng has also led o major job creaon, bu employmen raos have been sablzed a levels below he European average. By conras, where reforms have proceeded more slowly as n Russa and much of he CIS - reducons n workng hours, wage arrears and a burgeonng nformal secor have resuled. Furher and rrespecve of he pace of reform here s evdence of a severe fall n educaon spendng and n he qualy of educaonal servces. Alhough here s now a body of work ha has looked a he employmen flows from conracng o emergng secors usng enerprse level daa 2, job and worker reallocaon has mosly been analysed wh he assumpon of homogeneous labour. There has been lle hard evdence concernng he skll conen of job losses and gans 3. Ths paper begns o recfy hs defcency. The sklls dmenson of ranson s crcal n a number of regards. Gven he nherance, a reasonable pror mgh be ha he ranson counres, relavely rch n sklls, would have generaed jobs conngen on he overall pace of reform ha were skll rch. The skll composon of he labour force should affec he ypes of jobs ha frms wsh o creae a hck marke n sklled workers should lead o sklled jobs beng posed as frms seek o mach more effcenly human sklls o physcal capal. However, hs pror has been 1 For example, Flanagan (1997); Newell (2001) 2 See, Konngs e al 1996, Blsen and Konngs 1998, Lehmann and Wadsworh 2000, Brown and Earle 2001

5 o some exen undermned by recen sudes of leracy and oher basc sklls. For example, n hree ou of he four ranson counres nvolved n he OECD Leracy Survey, profcency scores fell below he OECD average. One conjecure mgh be ha he dffuson of human capal nensve echnologes has been consraned by he low adapably of workers and he defcences of adul ranng. 4 Furhermore, ranson has proceeded alongsde a major shf n he relave demand for skll ypes n he marke economes. Par of hs appears arbuable o he dffuson of ICT echnology. There appears o be a robus lnk beween ICT and nvesmen n human capal and he sklls of he labour force 5. The balance of evdence from he OECD pons o some subsuon effecs as lower sklled workers ge dsplaced by machnes, bu he sze of he ne employmen effec also depends on he degree o whch ICT adopon rases he demand for sklled labour 6. Ceranly, gven he nal condons of relavely low levels of ICT adopon alongsde relavely sklled workforces, we mgh have expeced he ranson counres o have acceleraed adopon raes wh mplcaons for relave labour demand. In hs conex, our paper akes a dealed look a he ways n whch jobs have been desroyed and creaed and he relave skll conen of such jobs across frms, secors and counres. I s based on a survey of frms ha was mplemened n 2000 n hree ranson economes, Hungary, Romana and Russa. Counry selecon was guded by he wsh o capure hree dsnc busness envronmens. EBRD progress n ranson ndcaors show ha Hungary has proceeded furher across all aspecs of reform han Romana whch, n urn, has proceeded furher han Russa 7. These counres can be seen o characerse dfferen sages of ranson, hence allowng some sense of he varaon condonal on overall progress n reform. The survey allowed denfcaon of sklls by educaonal aanmen as well as by dscree skll caegores. The paper denfes several key forces ha have been a work. Even a he end of he 1990s ranson has connued o reveal a srong bas agans unsklled labour assocaed wh he closure or resrucurng of sae and prvased frms. Unsklled labour has los employmen dsproporonaely. Furher, job creaon n new prvae manufacurng and servce secor frms has been unambguously based agans low skll workers. In addon, he 3 An excepon s Jurajda and Terrell Case sudy evdence of low adapably s provded n World Bank (1996) whch analyses he Tungsram plan acqured by General Elecrc. For a more general, analycal consderaon of he adapably ssue, see Aghon and Commander (2000). 5 See, ner ala, Auor e al (1998); Chennells and Van Reenen (1999); Bresnahan e al (2001). 6 See, for example, Falk (2001). 2

6 skll conen of blue collar work appears o have changed. However, he relave nfluence of hese facors has vared subsanally across he hree counres covered n hs paper. Ths varaon n large measure reflecs he dfferen sages of reform ha hese counres have aaned. The paper s organsed as follows. Secon 2 nroduces he daase. Secon 3 looks a ne changes o jobs, and relaes hem o changes n relave wages. Secon 4 looks a wha he fuure s lkely o hold, gven he presence or absence of perceved labour hoardng and shorages of parcular sklls. Secon 5 provdes esmaes of he wage elasces of demand and Secon 6 concludes. 2. Daa descrpon The analyss n he paper s based on a daase colleced by he EBRD desgned o allow a more quanave and dealed look a he changng srucure of sklls and work. A survey of 921 frms n he hree counres - Hungary, Romana and Russa was mplemened n md For each counry, he sample was srafed boh by employmen sze and secor. Farms and rural frms were excluded from he sample. Samplng occurred over a wde regonal base. In Russa, frms were nervewed n 25 oblass or regons; n Romana n 8 regons and n Hungary n 6 dsrcs. For he majory of he quanave quesons, he reference perod covered 1997 o 2000 hereby yeldng a maxmum of four daa pons. Whle, he daase s relavely small, has properes ha are generally absen n he larger daases commonly used o analyse labour marke behavour. These nclude nformaon on ownershp, he age of he frm and capal sock, as well as very dealed breakdowns of he skll feaures of he labour force over me. Some smple descrpve sascs are provded n Table 1 whch show ha n all hree counres he bulk of nervewed frms were n manufacurng and had over 50 employees. Large frms wh over 250 employees accouned for over a hrd of he sample and were more populous n Romana and Russa han n Hungary. Whle mos frms were esablshed pre-1990, a sgnfcan mnory of frms n Romana and Hungary were esablshed afer he sar of ranson. Sklls were measured n wo ways n he survey. Frs, frms were asked o classfy her jobs on he bass of skll conen usng four occupaonal grades: () unsklled and semsklled blue collar, () sklled blue collar, () whe collar and, (v) manageral. Second, hey were asked o provde he composon of each occupaonal group on he bass of workers 7 For he laes measures, see EBRD (2003). 3

7 educaonal backgrounds agan usng four caegores. These were, (a) prmary school, (b) vocaonal ranng school (provdng no cerfcae requred for enry o hgher educaon), (c) secondary school and (d) college or unversy 8. Whle s common o assume ha educaon s a decen proxy for sklls, s clear from hs daase ha changes of he educaonal mx whn skll grades consue a key componen of resrucurng. There s also an mporan qualfcaon o be made. There have been - and are - salen dfferences n he educaonal and job classfcaon sysems operang n he hree counres. For example, prmary school has en grades n Russa bu only egh grades n Hungary and Romana snce Vocaonal educaon n Hungary has generally been for hree years and been whou cerfcaon. In Romana was parly provded n he prmary schools. By conras, n Russa, here have been wo ypes of vocaonal ranng, one for lower level sklls of wo years; he oher of four years for junor professonals. Boh have been cerfed. Gven hese dfferences we analyse he daa a a counry level and pay close aenon o he local conex when drawng conclusons. Fnally, Russan frms repored wages only by skll grades. As a resul, skll-specfc changes n Russa are analysed separaely. In he paper we also classfy frms by wheher hey have desroyed or creaed jobs or by ne changes whn broad secors dsngushed by ype of acvy (manufacurng versus erary) 9. Wh respec o he laer, we dsngush beween an old secor comprsng saeowned or prvased domesc frms, whch were esablshed under socalsm and have equpmen nhered from ha perod 10. The new secor consss of frms esablshed afer 1990 or ownng new equpmen (.e pos-1990 vnage) or majory foregn-owned enerprses rrespecve of her dae of esablshmen and age of her equpmen 11. Table 1 shows ha here s some varaon across counres. In Hungary he share of new frms n manufacurng s above 60 percen as agans under 29 percen n Russa. However, mos erary secor frms n Russa are new and overall he share of new frms n oal sampled frms ranges beween percen. Dsaggregang n erms of ownershp, nearly hree quarers of he sae frms were old as agans 57 percen of frms ha were prvased by A mes, hese are abbrevaed o BCU, BCS, WC and MAN for he sklls caegores and o PRIM, VOC, SEC and HIGH for he educaonal levels. 9 An obvous queson arses concernng he mpac of break-ups, mergers, and le changes ha may nflae raes of job desrucon and creaon. In our survey, over 90 percen of he frms n he sample were operang connuously beween 1997 and Frms were asked o ell he average age of he equpmen hey use o produce her leadng produc or provde her mos mporan servces. Equpmen was classfed as old n case average age exceeded 10 years. 11 For old-secor frms a and b and c apples. For new-secor frms d or e or e holds. 4

8 3.1. Job creaon and job desrucon: some aggregaes Pror o dscussng our fndngs, we need o sgnal a possble source of measuremen error. When usng sandard frm regsers, he break-ups, mergers and le changes accompanyng ranson end o nflae raes of job desrucon and creaon. Ths rsk exss, alhough o a much lesser exen, n our survey. Over 90 percen of frms n he sample were operang connuously beween However, among he frms classfed as de novo here were sx large ules reporng 1998 as her dae of esablshmen and no employmen n Ths s obvously no credble and o avod measuremen error we used he reference perod for Romana hroughou hs paper 12. Before urnng o analyss of skll-specfc changes, a bref overvew of job reallocaon raes based on changes n he aggregae employmen of frms s presened n Table 2 and compared wh earler esmaes for he hree counres 13. Wha emerges s ha no only are here sgnfcan dfferences n annual creaon and desrucon raes beween bu also wh respec o earler observaons. Thus, job creaon raes n all counres are hgher a he end of he 1990s han earler n he ranson, whle job desrucon raes have moved n dfferen drecons. In Romana our survey pcks up far hgher desrucon raes relave o 1993/94, whle n Hungary and Russa desrucon raes have declned. Ths reflecs dfferen sages of ranson n he case of Romana and Hungary whle n he Russan case he sharp fall n desrucon n 1999/2000 reflecs he srong growh n oupu followng he 1998 devaluaon as well as he generally slow pace of reallocaon. These dfferences are refleced n he ne changes, wh Romana experencng a parcularly sharp declne n oal employmen. Table 2 also ndcaes ha as mgh be expeced ha here are large dfferences n creaon, desrucon and ne raes for dfferen ownershp ypes. Job creaon raes n Hungary and Romana were sgnfcanly hgher n new prvae frms, whle n Russa hs was he case for boh new prvae and prvased wh new equpmen. Job desrucon raes were larges n all counres for sae owned and prvased frms wh old equpmen. In all counres here were negave ne raes for sae frms bu here was large, cross-counry varaon. In Hungary 12 In an earler verson of hs paper, he frms n queson were classfed as de novo. Ths dd no sgnfcanly affec he resuls. Commander and Kollo (2001). An alernave approach would be o exclude hem from he sample. 13 The raes are defned as he sum of ne changes n expandng (conracng) frms over he mean sock of jobs n all frms. The jobs creaed n (genune) new frms are ncluded. 5

9 and Romana only new prvae frms experenced posve ne job growh, whle n Russa hs was also rue for prvased frms wh new equpmen Changes by sklls and educaon How have dfferen skll caegores been affeced? Table 3 shows he ne relave change of employmen beween n he hree counres. Wha emerges s ha whle aggregae employmen changed very lle n Hungary and Russa and fell by over 1/10 n Romana, here was a clear paern n he dsrbuon of skll changes. In parcular, here s an unambguous declne n unsklled employmen across all counres wh mos of ha concenraed among workers wh low educaonal aanmens. Ths was parcularly marked n Romana where here was a declne of beween 16-20% for workers wh prmary or vocaonal educaon. By conras, Table 3 also shows ha here has been a growh n employmen for more educaed workers. There s also evdence of a shf owards more educaed labour whn each occupaonal grade, ncludng among unsklled blue collar jobs. Alhough hese whn-group shfs have been sgnfcan, he combned effec on he occupaonal composon has been rval. In erms of he skll caegores, s noable ha job desrucon has fallen mosly on blue collar workers manly he unsklled, alhough he balance beween sklled and unsklled has vared across counry. For Russa, whle we fnd ha here was a sgnfcan declne n unsklled blue collar employmen and a lesser declne for whe collar jobs, employmen of boh sklled blue collar workers and managers rose. Dsaggregang n erms of broad secors as well as old and new secors, Table 4 ndcaes ha n Hungary, old manufacurng desroyed all ypes of jobs excep hose of relavely hghly educaed manual workers and whe collar workers. Mos of he ne loss was concenraed among workers wh low educaonal aanmens. The erary secor s conrbuon o employmen change was generally modes bu almos always posve. New manufacurng added per cen o he sock of blue collar jobs held by relavely hghly educaed workers, bu reduced he employmen of low educaed blue collars by around 2-3 per cen. In Romana across-he-board job desrucon by old manufacurng frms has occurred wh a furher bas agans low-educaed workers whn each occupaonal group. New manufacurng ended o desroy jobs for low-educaed workers and was generally unable o replace he jobs los n sae-owned or old prvased ndusral enerprses. The 14 We lack nformaon on frms ha closed, so he he desrucon raes presened n he paper wll be underesmaes 6

10 erary secor was more successful n mgang he mpac of ndusral declne on low-skll blue collar employmen bu he ne oucome was noneheless negave everywhere n he lower segmens of he labour marke. Russa looks a b dfferen. There s no srong dfference beween old and new secors n eher manufacurng or he erary secor. In boh pars of manufacurng here s some weak evdence of job desrucon beng concenraed on low skll-educaon jobs and no clear paern for he erary secor. We now ry o explan he varaon n he ne raes of change n employmen observed n he frm-skll-educaon cells. We regress he ne measure on dummes for skll, secor, sze and branch, weghng he observaons by employmen and cluserng for frms. In oher words, we adjus he sandard errors under he assumpon ha he ne raes are ndependen beween, bu no whn, frms. Despe her smplfed naure, hese esmaons summarsed n Table 5 - provde a crsp summary of he changes. In he case of Hungary and Romana old manufacurng frms prncpally cu unsklled-low educaon jobs, whle creang jobs for relavely well educaed workers, ncludng among unsklled blue collar posons. Relave o old manufacurng, employmen n new manufacurng grew sgnfcanly bu here was relavely lle dfference beween manufacurng and erary secors. In Romana he gap beween he secors was larger. By conras, n Russa, he resuls renforce he fndng ha employmen change was only loosely correlaed wh sklls and neher he manufacurng-servces dvde nor he new / old dsncon have affeced s varaon. Small frms have, however, grown faser and here s some evdence ha her labour demand was sgnfcanly based oward hghly educaed whe collars as well as sklled blue collar workers wh vocaonal ranng. In shor, hese esmaons emphasse he fac ha changes of employmen have dffered beween neracons of skll grades and educaon, whle also emphassng he mporance of he new / old dsncon n he more reformed counres. As mgh be expeced job growh hroughou has been concenraed n boh he new secor and n servces. However, here has been sgnfcan varaon across counry boh n erms of he magnudes of he changes as also her dsrbuons. Ths suggess ha he demand for sklls s shaped by facors ha have come ogeher somewha dfferenly across he hree counres under examnaon. Ths brngs us o he ssue of he role of whn and nra-frm effecs. Table 6 provdes hree measures; (1) overall: he sum of ne changes/ sock, (2) frm-specfc: he sum of frmspecfc ne changes / sock and, (3) nra-frm: he sum of skll-specfc, nra-frm changes / 7

11 sock. These are calculaed as follows. The frm-specfc change of employmen (n) of a gven educaonal group s defned as - n F = n 0 (N 1 /N 0 ) n 0, where N sands for oal employmen n he frm. Ths s he change ha would have occurred n case of skll-neural expanson or conracon. Inra-frm, skll-specfc change s defned as n I = n n F. Frm-specfc changes were removed from he daa. The overall or ne measure s he sum of ne changes/sock. Wha Table 6 demonsraes very clearly s ha workers wh low educaon are a far hgher rsk of job loss no only because her frms are lkely o conrac bu because nra-frm demand has also been based agans hem. For boh Romana and Russa all groups would have los n he case of skll-neural changes of employmen bu skll-specfc changes mananed a srong relave demand for hghly educaed workers. However, n Hungary growng demand for hghly educaed workers was fully explaned by he skll-neural expanson of frms employng hgh sklled workers. Fnally, s worh emphassng he fac ha alhough job creaon appears o be based oward workers wh more educaon, s also he case ha educaed workers have connued o lose her jobs n manufacurng; esmony o he proraced lengh of he shake-ou occurrng amongs frms nhered from he prevous sysem. 4. Explanng changes n relave wages and employmen Tha here have been changes n relave wages and employmen s clear. The challenge s undersand wheher hey have been drven by supply or demand sde facors. Alhough hs s hard o answer wh such lmed observaons on me, we sar by smply relang changes n relave wages o employmen and hen mplemen he procedure employed by Kaz and Murphy (1992) o ry and dsenangle supply and demand sde shfs. Relang he change n relave wage o he change n employmen 15, we fnd ha n he Hungaran case he wo ndcaors moved ogeher. The relave wages of blue collars wh prmary educaon fell parallel wh her declnng share n employmen. By conras, all groups wh secondary or hgher educaon (apar from managers wh a secondary school background) mproved her relave poson n erms of boh employmen and wages. The groups where rsng employmen levels were assocaed wh fallng relave wages, and vce 15 The rao of a skll group s share n job creaon o s share n job desrucon (o remove he effec of aggregae employmen) s used as he measure of relave employmen change. The relave wage of skll group,j a me s defned as: r j = (w ref /W )exp(b j ), where he b-s are esmaed wh cross-secon wage regressons. Conrols for regon, secor and frm sze were ncluded o capure compensang dfferenals. 8

12 versa, all had vocaonal schoolng. For Romana, he pcure s less clear. However, only n he case of four groups - comprsng 29 per cen of he populaon - dd wages and employmen move n he oppose drecon. Blue collar workers mosly los, whle whecollar, hghly educaed labour ganed n erms of relave employmen and wages 16. Kaz and Murphy (1992) provde a useful way of ryng o explan changes n relave wages. Ther framework has K ypes of labour npus. Facor demands can be expressed as; X = D( W, Z ), where X = K 1 vecor of labour npus employed n he marke a me, W = K 1 marke prces for hese npus a me. Z = m 1 vecor of demand shf varables a me. Ths can be wren n erms of dfferenals as: dx = D dw + D w z dz Assumng a concave aggregae producon funcon, he on facor demands, D w wll be negave semdefne, mplyng K K marx of cross prce effecs dw '( dx D z dz ) = dw ' D dw w 0 In oher words, changes n facor supples ne of demand shfs and changes n wages wll negavely covary. We sar by lookng a wheher he daa are conssen wh sable facor demand, wh changes n relave wages beng drven by facors, such as educaonal aanmen raes. In hs case, wages wll generaed by relave supply changes wh facor demand sable. dw ' dx 0 To do hs, we use nformaon from he survey. For K, we have 16 groups: 4 occupaon groups (manageral, whe collar, sklled blue collar, unsklled blue collar) * 4 educaon groups (hgher, vocaonal, secondary and prmary). Relave wages were calculaed as follows; w k = ( esmaed wage of group k a year )/( wage ndex a ) relave wage of group a : av. full-me employmen of group 1 over me av wage of group 1 ' av. full-me employmen over me wage ndex a = M M av wage of group K av. full-me employmen of group k over me av. full-me employmen over me The wage ndex a me beng he smple average of esmaed wages of groups 1..K n year. 16 Resuls avalable on reques 9

13 The supply of group a me ; x = ( employmen of group a )( av. relave wage of group over me) Ths hen allows esng for fxed facor demand for a number of me perods; [ln w ln w ]'[ln x ln x ] Table 7 gves he nner producs are repored for boh counres. τ τ As can be seen, he bulk of he numbers are posve n he case of Hungary all are posve Ths suggess ha supply shfs canno be he sole explanaory facor. We now urn o look a he possble role of demand shfs beween and whn secors. For hs exercse, we have daa on; 4 educaon groups: hgher, vocaonal, secondary, prmary; 4 occupaon groups: manageral, whe collar, sklled blue collar, unsklled blue collar and, 12 ndusry groups: (new/old)*(manufacurng/erary)*(small/medum/large sze) Relave wages ha are used o wegh employmen are calculaed as above. The demand shf measure s: = d D x k jk x j X k x x x where he base perod s he average of The overall (ndusry-occupaon) demand shf ndex s k j k j d X k, where j ndexes all ndusryoccupaon cells. Ths can be decomposed no; a beween ndusry demand shf ndex b X k, where j ndexes ndusry groups and a whn ndusry demand shf ndex X = X X. w k d k b k Indces are repored n form of ln( 1+ X ) k Table 8 repors he resul of hese exercses where beween and whn decomposon are done for each par of years, as well as for he longer perod from In he Hungaran case, wha emerges s here s lle evdence of srong dfferenal beween effecs. For he whn decomposons, he low educaon caegores end o be negavely sgned whle hgh educaon appears o experence a posve shf. Lookng a he longer perod he overall effec for boh hgher and vocaonal educaon s posve, parcularly n he former nsance. In he Romanan example, he sgn on he annual beween columns are mosly negavely sgned. The whn columns ndcae a posve bu small - number for hose wh hgher educaon. The overall effec s negave for all skll caegores. However, n he case of he longer reference perod, he overall effec for hgher educaed workers s srongly posve, drven mosly by whn effecs. 10

14 These resuls sugges ha shfs n he skll composon were mosly demand drven n Hungary bu more ambguous n Romana. However, for he laer here s some evdence over he hree year perod ha here was as srong posve shf n favour of workers wh hgher educaon. Fnally, urnng o Russa, he daa show a 21 per cen decrease n employmen of unsklled blue collars, and 6 per cen fall n whe collar jobs, whle he number of sklled blue collars and managers ncreased by 7 and 3 per cen, respecvely. A shf from unsklled o sklled manual workers could be observed n new-ype frms, whle he old secor shed mosly whe collars. Regressons smlar o hose presened for Hungary and Romana could no denfy sgnfcan dfferences beween secors or branches, and poned o hgher han average raes of growh n groups wh vocaonal and hgher educaon (where hese varables were avalable). The daa on wage changes see Table 9 - sugges no sgnfcan dfference beween workers of creang and desroyng frms, n he case of sklled labour. However, he relave wages of unsklled blue collars fell subsanally, by 12 percenage pons, and he declne was drven by wage cus n conracng and sagnang enerprses. 5. Can demography explan he changes? In prncple, a major shf owards more educaed labour could have happened whou any shf n he demand for sklls hrough demographc change. Rerng workers would have been replaced by beer educaed school leavers. In hs case, ncreased levels of sklls would have been largely assocaed wh replacemens on an nra-frm, nra-occupaonal bass. Usng he survey evdence, we are able o gve an upper-bound esmae for such subsuon beween low and hgh-educaed workers, by dsenanglng cases when job creaon for he laer group was assocaed wh desrucon of low-sklled employmen 17. Denong frms wh, skll grades wh j, he hgh and low-educaed groups wh H and L, and he number of jobs creaed or desroyed wh dl, subsuon can be defned as: s j = 0 f dl H j < 0 (no creaon => s j = 0) dl H j f 0 < dl H j < dl L j (less creaon han desrucon => s j = creaon) dl L j f dl H j > dl L j (more creaon han desrucon => s j = desrucon) 17 The esmae s upper-bound because he jobs creaed and desroyed may have been locaed n dfferen deparmens. 11

15 S j = Sum (s j )/ Sum (dl H j) s.. dl H j>0 gvng an upper-bound esmae of nra-frm, nraoccupaon subsuon as a proporon of job creaon. Analogous o S j we can defne a replacemen rao (R j ) o look a how many jobs los by low-educaed workers were flled by applcans wh more educaon whn he same enerprse (r j ). Summng r j by frms gves an esmae of whn-frm replacemen as a proporon of oal jobs los. Esmaes of S j and R j are presened n Table 10. Low educaon comprses prmary school n he case of unsklled blue collars; he prmary or vocaonal level n he case of sklled blue collars; and prmary, vocaonal, or secondary background n he case of whe collars. The daa sugges ha only 2-16 per cen of oal desrucon was replaced by jobs creaed for more educaed workers whn he same enerprse (wh he excepon of sklled blue collars n Russa). 18 Takng job creaon for relavely hgh-educaed employees onehundred, he share of subsuon appears o be somewha hgher, fallng o a range beween 15 and 35 per cen. We can clearly observe a bas agans he low-educaed n desrucon, and preference for he beer educaed n creaon. Recallng ha he esmaes of S j and R j are based upwards, hese magnudes may pon o a weak role for demographc change. 6. Lookng forward: evdence on labour hoardng & shorages The prevous secons have drawn aenon o he sgnfcan changes n he skll composon ha have occurred. However, hese changes mgh only reflec emporary adjusmens. Gven ha we can only look a perssence n eher job creaon or desrucon raes, hs may no be an adequaely long perod o esablsh wheher such adjusmens have been emporary 19. Perssence n job desrucon has been very hgh, ypcally n excess of 90 per cen. Perssence n job creaon has also been hgh, bu wh greaer varaon across skll caegores. Ths suggess ha much of he adjusmen has no been emporary n naure. Furher, such adjusmens obvously depend on how far frms beleve her employmen levels are relave o desred or equlbrum levels. Frms n he survey were asked how her acual level of employmen compared wh he desred level gven her exsng capal sock, echnology and oupu. The answers were gven for he four skll groups usng a caegorcal scale and he fndngs are summarsed n Table The share of frms reporng hgher han 18 In he Russan case he calculaons exclude he unsklled caegory for lack of daa on her educaonal composon. 19 The perssence rae for job creaon s measured by how many jobs creaed beween year and +1 survve unl year +2 wh he desrucon rae defned analogously. Resuls avalable on reques. 20 Redundances could be n he followng ranges; beween 5-10%, 11-20% and over 20%; shorages beween 5-10% and over 10%. 12

16 desred levels ranged beween 3-9 per cen n Hungary, 7-13 per cen n Romana, and 5-10 per cen n Russa. Usng he mean of a gven skll caegory and replacng over 20 per cen wh 25 per cen as a lower bound and 40 per cen as he upper bound, we can roughly esmae he magnude of excess employmen n erms of workers. The lower and upper esmaes fall farly close o each oher wh even he laer ndcang neglgble raos of beween 0.3 o 3.7 per cen. In Hungary, he excess workforce was evenly dsrbued across secors. In Romana, 76 per cen was concenraed n hose old-secor frms whch were downszng beween 1998 and 2000 suggesng ha despe he huge employmen losses of old frms her process of adjusmen had no ye been compleed. By conras, n Russa 68 per cen was employed n old-secor frms whch had no downszng before 2000 ndcang he very lmed mpac of reforms. Alogeher, 98 per cen of he redundan Russan workforce was employed n he old secor, as opposed o 82 per cen n Romana, and only 36 per cen n Hungary. The proporon of frms reporng lower han desred levels was somewha hgher, parcularly n he case of sklled blue collars (17 per cen n Romana 36 per cen n Hungary and Russa). The esmae of he number of workers s however low: 4-5 per cen n he case of sklled blue collars and below 2.5 per cen n oher caegores 21. From hese daa, a pcure of furher downward adjusmens o employmen emerges for Romana despe very hgh raes of job desrucon n he old secor durng Smlarly, n Russa a relavely large proporon of frms n old manufacurng repored excess unsklled workers. The locus of job desrucon wll lkely reman n he old secor n hese counres. Whle he cross-counry dfferenals are ellng, he lesson from hese fgures s ha frms acual employmen levels are nfrequenly, and only margnally, hgher han her desred level n Cenral Europe. The fac ha Russan frms despe relavely low ne adjusmens o employmen repored low labour hoardng appears perverse. I lkely reflecs he general absence of resrucurng even ndeed a lack of undersandng of wha resrucurng may enal n erms of relave job losses and he curous mx of adjusmen measures aken by many old frms; namely wage and hours adjusmen. 21 Of course, frms reporng shorages may no be able o fnance a desred level of employmen. By conras, hgher han desred levels mply an acual cos. Ths suggess ha he nformaon on excess employmen s lkely o be more robus han ha on shorages. 13

17 7. Wage elasces - Cross secon esmaes If frms are ndeed a or close o her opmum, we can esmae her demand for sklls usng a smple sac model derved from he ranslog cos funcon. Denong oupu wh Y, facor quanes and facor prces wh X and p, he mnmum cos (C*) funcon s: C = 1 ( 2)ln * v + v y Y + v p p p j y p Y remander + j j ln ln + 0 ln ln γ γ ln ln + 2 Applyng Shephard s lemma, and neglecng he remander we can derve a sysem of opmal cos share equaons 22 : ( 3) ln C * / ln p = p X / p X = s = v + γ ln p + γ lny s... γ j = γ j j and γ = γ j = γ = 0 Y j y The own-prce elasces (ε ) and he cross-prce elasces (σ j ) can be compued usng he esmaed parameers and observed cos shares: ε = ( γ + s s ) / s 2 σ = ( γ + s s ) / s j j j We lack daa on capal coss, so ha we have o esmae (3) by dsngushng hree ypes of labour - unsklled blue collar, sklled blue collar, and whe collars ncludng managers - resrcng he analyss o frms reporng her ne sales revenues. 23 Furher loss of observaons comes from he excluson of frms employng only one or wo ypes of labour. Ths means ha we can esmae he equaons for 180 Hungaran, 242 Romanan, and 148 Russan frms respecvely. 24 The esmaons were repeaed for 133, 144 and 98 manufacurng frms, respecvely. Table 12 shows ha he own-wage elasces are correcly sgned (wh he excepon of Russan whe collars), and decrease as we move from unsklled labourers o more sklled groups. The esmaes for whe collars and sklled blue collars are 22 For he dervaon, see Hamermesh (1993). 23 We also lack nformaon on socal secury conrbuons bu hese, beng lnear n wages, do no affec he cos shares once capal cos s excluded. 24 Though he dependen varables are he same n all equaons, an OLS esmaor would sll be neffcen because of he resrcons. Therefore Zellner s Seemngly Unrelaed Regressons procedure was used. 14

18 lowes n Russa, slghlz hgher n Romana, and much hgher n Hungary 25. The demand for unsklled blue collars seems o be hghly responsve o wages n all counres. Wh one excepon, unsklled blue collar workers and oher groups appear o be eher prce-subsues or nearly ndependen. Fnally, we can pu hese esmaes ogeher wh hose for repored dsequlbra. The expecaon s ha posve resduals from he skll share equaons (ndcang hgher han desred or opmal levels of employmen) would be posvely correlaed wh repored excess employmen. Conversely, negave resduals would be expeced o rase he probably of complans of shorages. Unvarae logs wh a dummy for repored excess labour on he lef hand and he esmaon resdual on he rgh hand found ha he lnkages beween repored and esmaed excess employmen were ndeed posve, alhough no always sgnfcan. When repored shorages were regressed on he resdual we go negave and/or nsgnfcan coeffcens n all cases bar one Conclusons Ths paper has broken new ground n lookng a changes o he skll dsrbuon n hree ranson counres. Wha emerges s nformave. There has been large scale job desrucon n old manufacurng frms ha had survved he frs seven years of ranson whou eher modernsng her equpmen and/or fndng foregn nvesors. These enerprses desroyed jobs on a massve scale n Romana and, somewha less dramacally, n Hungary. In Russa, he rae of job desrucon has been noably lower: a funcon of he far slower pace of reform and pressure o resrucure. In Cenral and Easern Europe, he dfference beween old and new manufacurng n erms of her respecve demand for sklls has been n degree raher han ype. Changes n he skll profle of new manufacurng were acheved hrough a mx of job creaon and desrucon whle n old manufacurng selecon n downszng appears as key. Toal employmen n new manufacurng grew a a modes rae of jus under 4 percen n boh Hungary and Romana. The hghes raes of growh were wh jobs for hghly educaed whe collars, as well as for blue collars wh 'above sandard' levels of educaon. A he same me, new manufacurng creaed hardly any for eher unsklled or sklled blue collar workers as well as whe collar workers wh lmed 25 Keres and Köllõ (2002) usng anoher daa base whch ncluded capal coss - esmaed an own-prce elascy of 1.8 for workers wh prmary and vocaonal educaon, and 1.0 and 0.6 for wo groups of sklled labour n These values are conssen wh our fndngs. 26 These resuls are avalable reques 15

19 educaon. Whle changes n he skll composon have been n smlar drecon, he magnudes have been raher dfferen. In Hungary he growh of a dynamc new manufacurng secor resuled n replacng around 85 percen of he jobs los n he old secor. Ths rao was much lower n Romana a only 57 percen. The servces secor has had a raher dfferen mpac on he demand for sklls. In Romana, a counry where he servces secor was parcularly resrced under plannng, s subsequen growh has largely nvolved creang jobs for blue collar workers. In Hungary, where he gap-fllng growh of servces was exhaused by he md 1990s, relave demand grew subsanally for only wo caegores: blue collar workers wh secondary educaon and hghly educaed whe collars. For Russa, he overall pcure s que comparable o he oher wo counres n one respec. Unsklled blue collar employmen has been desroyed a a hgh rae whle employmen of oher skll caegores has evolved more favourably. The man concluson from our daa concerns overszed, old manufacurng frms cung ancllary low-sklled jobs and unproducve whe-collar posons. The dfferences beween frms underakng successful sraegc resrucurng and ohers have no been as clearly ransmed o he labour marke as n Hungary or Romana, no leas because of he recourse o wage arrears, reducons n workng hours, emporary leaves and oher paral adjusmen measures. Turnng o he demand for sklls, he shf owards hghly educaed whe collar workers s a marked feaure n all hree counres. An equally unambguous shf can be observed from less o more educaed blue collar workers or, from unsklled o sklled manual workers n Russa. Indeed, he hghes growh raes can be observed for unsklled blue collar workers wh hgher han prmary educaon and sklled blue collar workers wh secondary educaon. The presence of educaon-specfc wage dfferenals whn blue collar skll grades - combned wh he fas-growng employmen of educaed manual workers and frm's complans of sklled blue collar shorages - lead us o conclude ha he skll conen of blue collar work has been changng subsanally. Ths ransformaon seems o be a leas as mporan as he ncreased bas oward employmen of more hghly educaed workers. The change n he demand for sklls emergng from he analyss of our survey has some mporan mplcaons. Workers wh lmed educaon have los her jobs dsproporonaely and her relave wages have also been fallng. Alhough he elmnaon of he labour hoardng of low sklled workers appears o have been nearly compleed n Hungary and Romana, bu less so n Russa, new frms and secors have also, n he ne, desroyed 16

20 raher han creaed low-skll jobs. We have also observed clear shfs from he employmen of relavely low o hgh-educaed labour whn he blue collar caegory. Our resuls also show ha he demand for low-sklled labour has been hghly responsve o wages. However, f wages fall n response o job desrucon her proxmy o benefs may reduce supply whle f he mnmum wage s ncreased o avod ncenve problems as n Hungary - demand may fall furher. In sum, we have found evdence of common changes ha herald a bleak fuure for he employmen prospecs of hose wh low sklls or educaon. Whle ncenve problems may be a serous par of he unemploymen problem n hs segmen of he labour marke, our paper suggess ha demand-sde developmens may be equally mporan. Ye, sadly, crosscounry evdence on he evoluon of educaonal spendng snce he sar of ranson shows ha mos counres have experenced subsanal declnes n educaon spendng wh assocaed falls n he qualy of educaonal servces. Such falls have been sharpes n he CIS and, n parcular, n he poorer counres of ha regon 27. The conclusons of hs paper sugges ha asde from rasng he share of resources devoed o educaon, here s a need o change he conen of educaon. In parcular, he reform of vocaonal ranng and cerfcaon and he relaonshp wh oher educaonal sreams remans a prory. Whou such naves, he longer run mplcaons for employmen and nequaly may be hghly adverse. References Aghon, Phlppe and S. Commander (1999), On he dynamcs of nequaly n he ranson, Economcs of Transon, 7, 2, Auor, Davd, L. Kaz and A.B. Krueger (1998), Compung Inequaly: Have Compuers changed he Labour Marke?, Quarerly Journal of Economcs, 113, 4, Blsen, V. and J. Konngs (1998): Job creaon, job desrucon and growh of newly esablshed, prvased, and sae-owned enerprses n ranson economes: Survey evdence from Bulgara, Hungary, and Romana, Journal of Comparave Economcs, Sepember. Boer, To (2001): Transon wh labour supply, WDI Bresnahan, Tmohy, E. Brynjolfsson and L. H (2001), Informaon Technology, Workplace Organsaon and he Demand for Sklled Labour, Quarerly Journal of Economcs, forhcomng 27 See UNICEF (2001) 17

21 Brown, Davd and J. Earle (2001): Gross job flows n Russan ndusry before and afer he reforms: Has desrucon become more creave?, IZA DP No 351 Chennells, Lucy and J. Van Reenen, (1999), Has Technology Hur Less Sklled Workers? Insue for Fscal Sudes Workng Paper, 99-27, London Commander, Smon, J. McHale and R. Yemsov (1995), Russa, n Smon Commander and Fabrzo Corcell (edors), Unemploymen, Resrucurng and he Labour Marke n Easern Europe and Russa, Washngon DC Commander, Smon, A. Tolsopaenko and R. Yemsov (1999), Channels of Redsrbuon: Inequaly and Povery n he Russan Transon, Economcs of Transon, 7, 2, Davs, Seven J., and J. Halwanger (1992): Gross job creaon, gross job desrucon, and employmen reallocaon, Quarerly Journal of Economcs, 107, 3, European Bank for Reconsrucon and Developmen, (2000 and 2001), Transon Repor, London European Commsson (2000): Employmen n Europe Recen rends and prospecs, Luxembourg, 2001 Falk, Marn (2001), Dffuson of Informaon Technology, Inerne Use and he Demand for Heerogeneous Labour, ZEW Dscusson Paper No.01-48, Mannhem Flanagan, Rober (1995), Labour marke responses o a change n economc sysem, Proceedngs of he World bank Annual Bank Conference on Developmen Economcs, 1994, Washngon DC Jurajda and Terrell.b.a. Keres, G and J. Kollo (2001a), Economc ransformaon and he reurn o human capal: he case of Hungary, , Paper presened a he conference Undersandng Skll Obsolescence -Theorecal Innovaons and Emprcal Applcaons, May 10-12, Maasrch. Keres, G and J. Kollo (2001b), Demand for Unsklled, Young-Sklled, and Older Sklled Workers - Evdence on Large Hungaran Frms, Insue of Economcs, Budapes Konngs, J, H. Lehmann and M. Schaffer, 1996, Job Creaon and Job Desrucon n a Transon Economy: Ownershp, Frm Sze and Gross Flows n Polsh Manufacurng, , Labour Economcs, 3, 3, Lehmann, H and J. Wadsworh, (2000), Tenures ha shook he world: Worker Turnover n Russa, Poland and Bran, Journal of Comparave Economcs, 28,

22 Munch, Danel, J. Svejnar and K. Terrell, (1999), Reurns o human capal under he communs wage grd, Journal of Comparave Economcs, 27, Newell, Andrew, (2001), The Dsrbuon of Wages n Transon Counres, IZA Dscusson Paper 267, Bonn, March Sascs Canada (2000): Leracy n he nformaon age, OECD and Mnsry of Indusry, Canada OECD (1998): Technology, Producvy and Job creaon, Pars UNICEF, (2001) Transmonee Daabase, Florence World Bank, (1996), World Developmen Repor: From Plan o Marke, Washngon DC 19

23 Table 1: Sample characerscs Hungary Romana Russa Number of frms Employees (2000) 68, , ,633 Medan sze of frms Number of manufacurng frms Oher secors ( erary ) Small frms (<50 employees) Medum-szed frms ( employees) Large frms (>= 250 employees) Esablshed n or afer Majory foregn-owned (>50 per cen) Average age of equpmen < 10 years Share of new frms n manufacurng Share of new frms n erary secor a) Old = domesc and esablshed before 1990 and equpmen older han 10 years b) New = majory foregn or esablshed afer 1989 or equpmen younger han 10 years Table 2: Job reallocaon raes (all frms) Creaon Desrucon Reallocaon Ne change Excess reall. Hungary Blsen-Konngs (1997) Romana Blsen-Konngs (1997) Russa Brown-Earle (2001) average

24 Table 3: The ne relave change of employmen (Ne change as a percenage of he md-perod sock: 1997/2000 for Hungary and Russa; 1998/2000 for Romana) Educaon: prmary vocaonal secondary hgher oal Hungary unsklled blue collar sklled blue collar whe collar Manager Toal Romana unsklled blue collar sklled blue collar whe collar Manager Toal Russa unsklled blue collar sklled blue collar whe collar Manager Toal Noe: Cells wh a md-perod sock of employmen lower han 100 suppressed. The ypcal educaonal level(s) conanng a leas 60% of he workers of he gven skll group are shaded. 21

25 Table 4: The conrbuon of secors o change of employmen whn he mos mporan skll groups (Ne change n he secor/base-perod sock of jobs n all secors, by skll) Manufacurng Terary Hungary old new old new Unsklled b.c. prmary vocaonal secondary Sklled blue col. prmary vocaonal secondary Whe collar. vocaonal secondary hgher Manager. secondary hgher Manufacurng Terary Romana old new old new Unsklled b. c. prmary vocaonal secondary Sklled blue col. prmary vocaonal secondary Whe collar. vocaonal secondary hgher Manager. secondary hgher

26 Table 5: Varaons n he ne raes Dependen varable: ne raes n frm-sklleducaon cells Hungary Romana Coeffcen Coeffcen Unsklled blue collar prmary 0 0 vocaonal secondary hgher Sklled blue collar prmary vocaonal secondary hgher Whe collar prmary vocaonal secondary hgher Manager prmary vocaonal secondary hgher Manufac - new Terary - old Terary new Sze< Sze > Consan N of obs F Prob ar Cases are unweghed *) Sandard errors adjused for cluserng by frms. 23

27 Table 6: Ne raes by educaon Hungary Romana Russa overall frmspecfc nrafrm Overall frmspecfc Inrafrm overall frmspecfc nrafrm Prmary Vocaonl Secondy Hgher Table 7: Inner Producs of Changes n Relave Wages Hungary Romana Table 8:Changes n Demand for Labour: Beween and whn effecs Be w- een 199 Be w- een 199 Be w- een 200 W h-n Hungary W W h-n h-n Ove r-all Ove r-all Ove r-all Be w- een 200 W h-n Ove r-all /97 9/98 0/99 8/97 9/98 0/99 8/97 9/98 0/99 0/97 0/97 0/97 Hgh Voc Sec Pr Be w- een 199 8/97 Be w- een 199 9/98 Be w- een 200 0/99 W h-n W h-n Romana W h-n Ove r-all Ove r-all Ove r-all Be w- een 200 0/97 W h-n Ove r-all 199 8/ / / / / / / /97 Hgh Voc Sec Pr