Working on the Train? The Role of Technical Progress and Trade in Explaining Wage Differentials in Italian Firms

Transcription

1 CENTRO STUDI LUCA D AGLIANO DEVELOPMENT STUDIES WORKING PAPERS Workng on the Tran? The Role of Techncal Progress and Trade n Explanng Wage Dfferentals n Italan Frms Paolo Manasse* Luca Stanca** *Unversty of Bologna, Italy **Unversty of Mlan-Bcocca, Italy

2 Workng on the Tran? The Role of Techncal Progress and Trade n Explanng Wage Dfferentals n Italan Frms Paolo Manasse, Luca Stanca December 3, 2003 Abstract Ths paper presents frm-level evdence on the dynamcs of the relatve demand for non-manual workers n Italan manufacturng durng the 1990s. The analyss provdes a number of nterestng results. Frst, wthn-frm skll upgradng s the man determnant of the ncrease n the non-manual wage bll share. By contrast, demand changes assocated to trade have shfted employment away from skll-ntensve frms. Second, whle the relatve number of hours worked by sklled workers wthn frms has rsen, the hourly wage premum has fallen. Thrd, wthn-frm skll upgradng s strongly and sgnfcantly related to nvestment n computers and R&D, suggestng skll-based techncal progress as the man explanaton for the ncrease n the relatve demand for non-manual workers. Fnally, the paper shows that falng to dsaggregate annual wages nto the number of hours worked and hourly wages, leads to underestmate the skll-bas of techncal progress. We thank ISTAT for kndly provdng the data for ths study. We are ndebted to Slva Prna for excellent research assstance. Gorgo Basev and Paolo Epfan provded useful comments. Correspondng author. Department of Economcs, Unversty of Bologna, Strada Maggore 45, 40100, Bologna, Italy. Telephone: # E-mal: manasse@spbo.unbo.t Unversty of Mlan-Bcocca. Pazza dell Ateneo Nuovo 1, Mlano, Italy. Telephone: # E-mal: luca.stanca@unmb.t 1

3 JEL Classfcaton: F1, F16, J31, O3 Keywords: wage dfferentals, skll bas, techncal progress, globalzaton. 1 Introducton Once upon a tme, before the era of portable computers and cellular phones, commuters on the Mlan-Rome tran route broadly fell nto two categores: frst class travellers, manly busness people and academcs, usually spendng ther tme readng the fnancal and general press, or takng naps (the latter); economy class travellers, manly famles, young people and toursts, often nvolved n anmated conversatons wth fellow travellers, typcally about soccer or poltcs. Nowadays, frst-class travellers can be seen slently hunched over ther laptops, or heard nosly talkng busness over ther cellular phones. Most second-class travellers stll chat ther way to ther destnaton, although now over cellular phones, and some watch DVD s on ther lap-tops. Academcs, now travellng n economy class, ether read newspapers or work on ther laptops (or take naps). 1 Ths anecdotal evdence suggests three workng hypotheses: 1. techncal progress n Italy, as n many other countres, has been skll-based, that s, t has rased the relatve productvty of more educated workers (frst-class travellers presumably make a more productve use of personal computers) as well as the relatve number of hours worked by sklled workers (frst class travellers now work nstead of relaxng); 2. relatve wages n Italy have not (fully) adjusted to the change n relatve productvty and hours (as a consequence, academcs no longer can afford to travel and take naps n frst class); 3. possbly as a result, frms have consderably rased the proporton of non-manual workers n employment. Ths paper explores these conjectures by nvestgatng the dynamcs of manual and non-manual employment and wages n Italan manufacturng durng the 1990s. We present frm-level evdence on the sources and determnants of the ncrease n the demand for non-manual workers, based on a new data set, prevously unavalable for research, that covers a large panel of manufacturng frms between 1989 and The analyss provdes a number of results supportng these conjectures. 1 We are grateful to Gorgo Basev for ths example. 2

4 Frst, Italan frms have substtuted unsklled for sklled workers at a rate comparable to those experenced n other ndustralzed countres (wth hghtech frms playng a leadng role n ths process): wthn-frm skll upgradng s the man determnant of the shft n relatve labor demand n the nnetes. By contrast, demand changes assocated to trade have moved employment away from skll-ntensve frms, contrbutng to moderate the change n relatve factor prces: between-frm employment shfts have reduced the relatve demand for sklls. Thus the evdence supports the dea of an Italan anomaly, n that trade lowers wage nequalty (cf Manasse et al. (2003)). Second, and most mportant, we add a second anomaly for the Italan case: the relatve stablty of wage dfferentals wthn frms hdes an mportant composton effect. At frm level the relatve number of hours worked by sklled workers has rsen, due to sklled based techncal change, whereas relatve wages have not adjusted. As a result, non-manual hourly wages have fallen n relatve terms. Thrd, wthn-frm skll upgradng, measured by changes n both relatve employment and number of hours, s strongly and sgnfcantly related to nvestment n computers and R&D. Fnally, we show that the conventonal approach that measures annual, rather than hourly relatve wages, produces a downward bas n the estmate of the skll-bas of techncal progress. The reason s that changes n relatve hours worked are ncorrectly attrbuted to changes n factor prces rather than quanttes. When properly measured, techncal progress s estmated to rase the relatve productvty of non-manual workers by roughly half a percentage pont per year. The paper s structured as follows. Secton 2 brefly dscusses the theoretcal background of the analyss and relates the present work to the lterature. Secton 3 provdes a descrpton of the data set and presents some stylzed facts of relatve wage and employment dynamcs n Italy n the last decade. In secton 4 we present a decomposton of the aggregate changes n the relatve wage bll, employment and wages, nto ther respectve wthn-frm and between-frm components. Secton 5 takes a closer look at the behavor of wages, and shows the mplcatons of dsaggregatng annual wages nto the number of hours worked and hourly wages. In secton 6 we present evdence from frm-level regressons to provde an nterpretaton of the observed wage and employment dynamcs, and secton 7 focuses on the bas of skll-based techncal change. Secton 8 concludes wth a dscusson of the man results. 3

5 2 Technology, trade and wages In the last two decades labor markets n OECD countres have wtnessed a sgnfcant change n the structure of employment and wages for sklled and unsklled workers. Snce the early 1980s, both the share of non-manual employment and the wage dfferental between manual and non-manual workers have grown consderably n the US and the UK. 2 In contnental Europe, wage dfferentals have been stable, and most of the adjustment has taken place on the quantty sde, wth rsng non-manual workers employment rates and manual workers unemployment rates. 3 The conventonal wsdom for Europe s that the lack of adjustment n relatve wages s due to more rgd labor market nsttutons (mnmum wages, hrng and frng costs, centralzed barganng and unon power, etc.), wth unemployment rates adjustng to the fallng demand for unsklled workers. A large body of lterature has attempted to provde an nterpretaton of these developments, 4 wth most studes concentratng on the determnants of the relatve demand for sklled labor. 5 In partcular, trade ntegraton and technologcal change have been consdered the man factors behnd the rse n the demand for sklled workers. 6 The technology vew argues that techncal progress has been skll-based: new producton practces assocated to the ntroducton of computers have ncreased the relatve productvty of sklled workers. Ths has led to hgher relatve demand, and n turn to hgher employment shares and wage prema for sklled workers. Emprcally, skll-based techncal change s consstent wth ncreased employment shares of sklled labor wthn ndvdual sectors (or frms/plants, dependng on the 2 See e.g. Katz and Murphy (1992)), Bound and Johnson (1992), Lawrence and Slaughter (1993), Berman, Bound, and Grlches (1994)) for the Unted States, and Haskel (1998), Haskel and Slaughter (2001b)) for the Unted Kngdom. 3 See e.g. Freeman and Katz (1996), OECD (1997), Berman, Bound and Machn (1998), Machn and Van Reenen (1998), Card, Kramarz, and Lemeux (1998). 4 For recent surveys of ths lterature see Haskel (2000) and Slaughter (1999). 5 Katz and Murphy (1992) argue that lower relatve supply of sklls could account only for a small part of the observed changes n relatve wages n the Unted States between 1963 and See also Topel (1997) for an analyss of the supply-sde determnants of wage nequalty. 6 Other explanatons often proposed are outsourcng (see e.g. Haskel (1996), Feenstra and Hanson (1999)), and changes n nsttutonal factors such as the declne of the nfluence of unons, collectve barganng, and lower mnmum wages (see e.g. Goslng and Machn (1993) and Fortn and Lemeux (1997)). 4

6 level of aggregaton and the specfc way new technologes are adopted). The trade vew ponts to Stolper-Samuelson effects of ncreased exposure to nternatonal trade. 7 Accordng to advocates of ths explanaton, competton from developng countres has lowered the relatve prce of unsklledntensve goods. As resources have shfted to sectors producng more proftable skll-ntensve products, the relatve demand for manual workers has fallen. Ths argument thus blames the growth of trade n goods, servces and factors n the past three decades (.e. globalzaton ). Emprcally, the trade vew s consstent wth employment n developed countres movng from skll-unntensve towards skll-ntensve sectors (frms/plants). The broad consensus emergng from the early emprcal lterature, generally based on studes of ndustry data, s that, whle nternatonal trade accounts for no more than 15-20% of the rse n wage dfferentals, the rest can be explaned by skll-based techncal progress (see e.g. Bound and Johnson (1992) and Berman et al. (1994) for the Unted States, but also Berman et al. (1998) and Machn and Van Reenen (1998) for an nternatonal perspectve). 8 Ths concluson s supported by two man fndngs. Frst, most of the aggregate skll upgradng s due to changes wthn ndustres, whereas the reallocaton of employment between ndustres plays a smaller role. Second, wthn-ndustry skll upgradng s sgnfcantly related to a number of ndcators of technologcal change. Ths explanaton has been recently challenged, both emprcally and theoretcally. At the emprcal level, a number of studes based on frm-level or plant-level data reach conclusons sgnfcantly dfferent from those obtaned on the bass of ndustry data. 9 Bernard and Jensen (1997), for example, fnd that wthn-ndustry ncreases n the demand for sklled labor can be largely attrbuted to shfts n employment between plants of the same ndustry (see also Bernard and Jensen (1995)), wth exportng plants playng a major role. 10 Earler studes, t s argued, have gnored mportant dynamcs occur- 7 See Rchardson (1995), Wood (1995) and Slaughter (1998) for recent surveys on the effects of trade on wage dynamcs. 8 A smlar concluson has been reached usng both prce (e.g. Leamer (1996), Feenstra and Hanson (1996)) and volume (e.g., Borjas, Freeman and Katz (1997)) data to capture the effect of trade on the labor market. 9 Most plant- and frm-level analyses am at assessng the lnks between exportng actvty and productvty (see e.g. Bernard and Jensen (1999) and Bernard et al. (2000)) or the exstence of learnng effects assocated wth the exports status of frms (see e.g. Clardes, Lauch and Tybout (1998)). 10 For a theoretcal explanaton of ths evdence see Manasse and Turrn (2001). 5

7 rng at the level of ndvdual frms and establshments, and thus have largely underestmated the role of demand and trade. At the theoretcal level, trade theorsts have argued that what matters for factor prces (n a two-sector two-factor Heckscher-Ohln economy) s the sector bas of techncal progress, rather than ts factor bas (see e.g. Leamer (1994, 1998)). 11 There are relatvely few studes on the Italan case. Most of the exstng evdence for Italy s based on ndustry-level data. Bella and Qunter (2000) analyze a panel of manufacturng ndustres, and argue that trade competton has had a small mpact on employment changes, whereas technologcal progress has played a major role. Fan et al. (1999) reach smlar conclusons on the lmted role of trade for labor market dynamcs, usng a panel of fourteen manufacturng sectors between 1985 and Among frm-level studes, Dell Arnga and Lucfora (1994) look at a cross secton of metal-mechancal frms to dscuss the role of trade unons n affectng wage dfferentals. 12 Casavola et al. (1996) consder a large panel of frms between 1986 and 1990, fndng that technologcal change explans most of the ncrease n relatve sklled employment. More recently, Manasse et al. (2001) analyze a panel of metal-mechancal frms observed from 1992 to 1995 and fnd that skll-based techncal change s the man determnant of skll upgradng. 13 The study also fnds that trade has dampened the effects of technology on wage dfferentals, as employment has shfted towards unsklled-ntensve frms (see also Fan et al. (1999)). Ths anomaly s due to the fact that Italy manly trades wth more advanced European partners, and frms are specalzed n relatvely low tech goods. The present study on one hand confrms these results for the entre manufacturng sector, and for a much longer tme horzon ( ). On the other, the new data set enables us to separate hours worked and from the number of employees of each category, 11 Krugman (1995), however, shows that ths crtcsm rests on the assumpton of local techncal change affectng a small open economy. See Haskel (2000) for an nterpretaton of ths debate, and Haskel and Slaughter (2001a) for emprcal evdence on the role of sector bas for the dynamcs of wage dfferentals. 12 Erckson and Ichno (1995) and Dell Arnga and Lucfora (2000) dscuss the role of labor market nsttutons n explanng a compressed wage structure n Italy. Ferragna and Qunter (1998) examne the relatonshp between export actvty, productvty and performance. See also Qunter and Rosat (1995) for an nvestgaton of nter-ndustry wage dfferentals. 13 In partcular, technology has contrbuted to rase wage nequalty wthn the category of sklled workers (.e. makng managers better and clerks worse off) rather than between manual and non-manual workers. 6

8 and thus to dstngush the relatve prce of an hour of work from the relatve earnngs. The paper adds another anomaly to the Italan case: despte workng more hours, the earnngs of non manual workers wthn frms have faled to adjust, so that relatve hourly wages have actually fallen. The possble explanatons for ths rgdty are dscussed n the concludng secton. Aganst ths background, our paper contrbutes to the lterature n several respects: data, methodology and, we thnk, results. As to the frst aspect, we explot a new and much more comprehensve data set for Italy, fllng an mportant gap for assessng the role of technology and trade for ths country; as to methodology, we provde a general and consstent approach to frm-level between/wthn decompostons; moreover, we show how prevous estmates of the role of techncal progress may contan a bas of the bas, due to the fact that changes n relatve hours are reflected n changes n factor prces rather than quanttes. 3 The data Our analyss s based on frm-level data for the Italan manufacturng sector. The data set s drawn from the Statstcal Informaton System on Enterprses (SISSIEI), a network of databases developed by the Italan Statstcal Insttute (ISTAT, Central Drectorate of Statstcs on Insttutons and Enterprses), that combnes statstcal nformaton from four man sources: the System of Accounts of Frms (SCI) and the Survey on Technologcal Innovaton of Industral Enterprses (INN), both collected on a yearly bass; the monthly statstcs on Foregn Trade Flows (COE), and the Archves of Actve Frms (ASIA, SIRIO, NAI). 14 Our sample conssts of a balanced panel of 8441 manufacturng frms wth annual observatons from 1989 to 1995, coverng about 22 per cent of total manufacturng. The sample ncludes all the frms wth at least 20 employees who responded contnuously to the ISTAT surveys between 1989 and The data set provdes nformaton on the ncome statement (sales, out- 14 See Sorce and Fazo (1999) and Corsn, D Francescantono and Monducc (1998) for a more detaled descrpton of the constructon of the data set. 15 Note that the System of Accounts of Frms, the man component of SISSIEI, s based on a survey whch s conducted by ISTAT on all Italan frms wth at least 20 employees and on a representatve random sample for frms wth less than 20 employees (see Corsn et al. (1998)). 7

9 put, costs and outlays, value added, labor costs, captal deprecaton and allowances, nterests on debts, taxes, profts, etc.), the balance sheet (real assets, fnancal assets and labltes, fnancal and commercal credts and debts, etc.), frms employment and wages, fxed captal formaton, R&D and exports. Data on employment and wages are avalable separately for manual workers (tranees and producton workers) and non-manual workers (clerks and executves). 16 The majorty of frms n the sample (63%) falls nto the category of medum frms (between 25 and 100 employees), whle 23% are large (more than 100 employees) and the remanng 14% are small (below 25 employees). As for the geographc dstrbuton, 80% of the frms n the sample are located n Northern Italy, 15.5% n Central Italy and the remanng 4.5% n the South. 17 Table 1 provdes a prelmnary descrpton of the data, reportng sample and (approprately defned) sub-sample averages for a number of wage and employment ndcators. Column 1 shows the share of non-manual workers n the wage bll ( W Bn ), whle columns 2 and 3 dsplay ts components: the rato W B of the wage rate of non-manual workers over the average wage ( Wn, henceforth W skll premum ), and the share of non-manual workers n employment ( E n E, henceforth skll ntensty ). In the perod , on average, the share of non-manual workers n the wage bll was 43.3 per cent, the skll premum per cent, and skll ntensty 31.8 per cent. Table 1 also reports, n columns 4 and 5, the average annual wage rate of non-manual and average workers (W n = 68.2 and W = 50.2 mllons Italan lra, respectvely), and, n columns 6 and 7, the average number of non-manual and total employees n the sample (E n = 43.3 and E = 136 thousands, respectvely). Between 1989 and 1995 the share of non-manual workers n the wage bll rose by 3.5 percentage ponts (0.58 per cent a year, on average). Ths rse reflects a sgnfcant ncrease n skll ntensty (2.4 per cent), wth a relatvely modest 0.8 per cent rse n the skll premum. Hence, relatve wages n our sample conform to the stcky pattern found n other studes for earler perods (e.g. Erckson, Ichno (1995)). The rse n skll-ntensty, n turn, reflected an absolute ncrease of average non-manual employment (from Wages nclude salares, socal contrbutons pad by the frm, and contrbutons pad by the frm to the severance-payment fund (TFR). 17 The three geographc areas are defned as follows. North: Pemonte, Valle D Aosta, Lombarda, Alto Adge, Veneto, Frul Veneza Gula, Lgura, Emla Romagna. Center: Toscana, Umbra, Lazo, Marche, Abruzzo, Molse. South: Campana, Baslcata, Pugla, Calabra, Scla, Sardegna. 8

10 to 43.4 thousands) despte the contracton of total employment from to thousands (note that ths mples that manual employment fell by 6.4 thousand unts n our sample of frms). The followng blocks n Table 1 document the sgnfcant heterogenety of frms n the sample. Groupng frms accordng to ther sze, larger frms pay substantally hgher wages than small and medum frms. Skll prema are hghest n medum-sze frms (134.7 per cent) and lowest n small frms (128.5 per cent), whle the wage bll share and skll ntensty are ncreasng n sze. Consderng a classfcaton based on the geographc dstrbuton, frms located n the South are on average smaller (119.5 employees) and pay substantally lower wages than those n the rest of the country. Also, they appear to pay hgher skll prema (140.2%) than those n the rest of the country, although they are characterzed by lower wage bll shares (36%) and skll ntensty (25.7%). Next, we consder two further classfcatons, accordng to ther export actvty and computer ntensty. Hgh-export ( low-export ) frms are defned as those whose share of exports n total sales s above (below) the medan. 18 Smlarly, hgh-technology ( low-technology ) frms are defned as those whose share of computer stock over total captal stock s above (below) the medan. 19 Hgh- and low-export frms pay smlar wages and have smlar wage bll shares and skll ntensty (despte the former beng larger). Technology-ntensve frms (henceforth hgh-tech ) employ a substantally hgher proporton of sklled workers (35.4% aganst 27.2%). Despte payng hgher salares for both types of workers, the wage dfferentals are surprsngly lower n hgh-techs. The share of sklled workers n the wage bll s about 10 percentage ponts hgher for hgh-tech than for low-tech frms. Table 2 groups hgh/low-tech frms and hgh/low-export frms by sze, snce some of the features prevously observed may be smply due to dfferences n scale. The fgures suggest that the features of hgh-tech frms do not depend on ther sze: hgh-tech frms are more skll-ntensve, pay lower prema, and have hgher non-manual wage bll share than low-tech frms n all sze groups. On the other hand, the smlartes between hgh- and lowexporters n the total sample turn out to be a fallacy of composton: small and medum hgh-exporters are more skll ntensve and pay lower skll prema than low-exporters of the same sze, whle the converse s true for large 18 Due to data lmtatons, the rato of exports to total sales s only avalable for Thus ths classfcaton s based on frms nputs, rather than on ther output. 9

11 hgh-exporters. 4 Frm-Level Decompostons In ths secton we present frm-level decompostons n order to provde an nterpretaton of the aggregate annual wage and employment changes descrbed above. We decompose the change n the relatve wage bll nto the respectve contrbutons of employment skll-ntensty and wage skll-premum. Each of these s further dsaggregated nto a between and a wthn component. The former reflects reallocatons of employment and wages that occur between dfferent frms; the latter dentfes changes n the employment and wage structure that occur wthn ndvdual frms. We depart here from the lterature n an mportant aspect: nstead of focusng on the decompostons for the relatve wage bll and employment ntensty taken n solaton (see e.g. Berman et al., (1994), Bernard and Jensen (1997), Berman et al. (1998), Machn and Van Reenen (1998)) we proceed by nestng the wage bll wth employment and wage decompostons. Unlke the standard approach, our methodology allows us to dentfy the respectve contrbutons of annual wages and employment to the change n the wage bll share. Moreover, our approach provdes drect nformaton on the changes of relatve wages (see also Manasse et al., 2001). Let the frms n the sample be ndexed by superscrpt = 1,..., I, and denote manual and non-manual workers wth subscrpts m and n, respectvely (so that E n and W n denote non-manual employment and annual wage n frm ). Frm employs E = E n + E m workers. Total employment s E = E, and total non-manual employment s E n = E n. The average wage at the frm s defned as W = W ne n+w me m En +E m frm s defned as Wn = W ne n P W ne n P E n = W B E and the non-manual wage at the P W E P E = W B E = W B En n. Fnally, let W = and En denote the (sample-wde) average and non-manual W n = = W Bn E n mean wage, respectvely. The change n the share of non-manual workers n the wage bll can be decomposed as follows: ( W B I ( n W W B ) = n W ) En = E I ( ) ( ) ( ) ( ) W n E n E + n W n W E E W =1 10 W tot Etot (1)

12 where denotes tme dfference and the upper bar denotes an average over tme. The frst term n the square brackets n (1) s the sum of changes n wage prema, weghted by the tme-averaged share of non-manuals n employment (Wtot). The second term s the sum of changes n skll ntenstes, weghted by the correspondng tme-averaged wage prema (Etot). Consder frst the employment component (Etot). Ths may rse for two reasons: ether ndvdual frms have, on average, become more skll-ntensve (wthn effect), or employment has shfted towards frms that are relatvely ntensve of sklled workers (between effect). Smlarly, for the wage component, hgher wage prema may be due ether to the fact that ndvdual frms have, on average, pad hgher skll prema (wthn effect), or to the fact that wages have grown more rapdly n frms payng relatvely hgher prema (between effect). In order to dsentangle these dfferent sources, we decompose the two terms n equaton (1) nto ther respectve between and wthn components. The (weghted) employment component can be wrtten as follows: I ( E n E Etot ) ( ) W n W = I [ ] ( ) W PnS + S Pn n Ewt Ebet W where Pn = E n s the proporton of sklled workers n frm s employment, E and S = E s the share of frm n total employment. The frst term n E square brackets represents the change n the non-manual employment share that can be attrbuted to changes n frms factor proportons, Pn, keepng constant ther relatve sze, S. Ths reflects shfts n factor ntensty wthn frms (henceforth denoted wth Ewt): f postve, t suggests that on average frms have substtuted unsklled wth sklled workers. The second term gves the part of the total change that can be attrbuted to the change n frms employment share or relatve sze, S, keepng each frm s factor proportons constant. Ths reflects movements of employment between frms (and s denoted by Ebet): f postve, t suggests that employment has shfted, on average, towards skll-ntensve frms. Smlarly, the (weghted) wage component can be dsaggregated as follows: I ( W n W W tot ) ( ) E n E = [ ] ( ) E DnR + R Dn n W wt W bet E 11 (2) (3)

13 where Dn = W n s the wage dfferental pad by frm, and R = W s the W W relatve wage pad by frm as a rato of the average (sample-wde) wage rate. The frst term n square brackets s the part that can be attrbuted to changes n frms wage dfferentals, Dn, keepng constant ther relatve wages, R. Ths s the wage-wthn component (Wwt): f postve, t suggests that on average frms have rased skll prema. The second term accounts for the changes n frms relatve wage rates, keepng ther wage prema constant. Ths s the between component (Wbet): t s postve f, on average, wages have rsen faster n frms that pay hgher prema. Summng up, wthn-frm movements presumably reflect factor-specfc shocks, such as changes n the relatve factor productvty and/or wage prema, due to skll-based techncal progress. Between movements presumably reflect frm and sector-specfc shocks, such as changes n domestc and foregn demand affectng market shares and/or average wage rates. 20 Table 3 presents the results of the decompostons n equatons (1-3): the average annual change of the share of non manual workers n the wage bll (WBtot), and the contrbutons of the change n skll ntensty (Etot) and the change n the skll premum (Wtot), splt further nto ther respectve between and wthn contrbutons (Ebet, Ewt, Wbet, Wwt). The frst row dsplays the results for the overall sample of frms. 21 Between 1989 and 1995 the share of non manual workers n the wage bll rses by 0.58 per cent a year on average. Ths s largely accounted for by the skll ntensty component (Etot = 0.51 per cent), wth a smaller contrbuton of the wage premum component (W tot = 0.07 per cent). Interestngly, the rse n the proporton of sklled workers n employment s due to substantal wthn-frm substtuton of unsklled wth sklled labor (Ewt = 0.63 per cent a year), whereas the between component s negatve (Ebet = 0.12 per cent), partally offsettng the effect of the wthn component. Ths means that, on average, employment has moved towards unsklledntensve frms, thus moderatng the rse n the proporton of sklled workers n employment. 22 Lookng at the wage components, most of the (small) total change can be attrbuted to the between effect (W bet = 0.06 per cent): on 20 Clearly, demand and trade may ndrectly affect wthn-frm changes through ther mpact on factor prces (see below). 21 Note that the lower number of observatons (compared to table 1) s due to the presence of frms employng only manual workers. 22 Ths result confrms the fndngs n Manasse et al. (2001) for the metal-mechancal sector. See also Fan et al. (1999) for smlar results based on ndustry data for Italy. 12

14 average wages have rsen faster n frms payng hgher skll prema. Rows 2 and 3 of table 3 dvde the sample nto two four-year subperods ( and ). The results ndcate that, for both relatve employment and wages, changes were much larger n the frst sub-perod: the share of non-manual workers n the wage bll rose at an average annual rate of 1 per cent between 1989 and 1992, as opposed to just 0.17 per cent between 1992 and It s nterestng to observe that ths deceleraton s largely explaned by the employment component. In partcular, the relatve expanson of employment n unsklled-ntensve frms (the negatve Ebet) occurs only n the second sub-perod, , a perod of boomng manufacturng exports, partcularly for low-skll frms, spurred by a rapdly deprecatng real exchange rate (see Manasse et al. (2002)). In the same perod skll-upgradng (the postve Ewt component) also slows down. The next blocks n table 3 show the contrbutons of ndvdual subsamples of frms to the overall decomposton. Lookng at the classfcaton of frms by ther computer-ntensty, two nterestng features appear from the table. Frst, hgh-tech frms account for a large share of the wthn-frm rse n skll ntensty (Ewt about 0.40 per cent as opposed to 0.24 per cent for low-tech frms). Ths fndng s consstent wth the hypothess that new technologes (computers) and sklls are complement, so that techncal change has ndeed been sklled-based. Second, hgh-tech frms also entrely account for the negatve employment between component, Ebet. Thus hgh-tech frms, the most actve n rasng ther skll ntensty, have lost market shares durng ths perod. Lookng at the classfcaton of frms by ther export actvty, we observe an mportant result: hgh-export frms account entrely for the negatve employment between component. The last two fndngs suggest that the Italan specalzaton pattern n nternatonal trade s shftng employment towards unsklled-ntensve goods and away from computer-ntensve frms. 23 Notce also that, when we classfy frms jontly for computer-ntensty and export-actvty, skll-upgradng (Ewt) occurs equally for all hgh-tech frms (rrespectve of beng hgh or low exporters), whereas the loss of employment share (Ebet) s more evdent among hgh-tech exporters. 23 It should be noted that the negatve employment between component s largely attrbutable to large frms (-0.13 per cent). Wthn these frms, hgh-exporters are ndeed less skll ntensve than low-exporters (relatve sklled employment s 33.5 and 36.4, respectvely). 13

15 5 Hours and hourly wages In ths secton we examne our workng on the tran conjecture that techncal progress affects the relatve number of hours worked by non manual workers. The pont here s that consderng annual rather than hourly wages, that s lumpng together the number of hours wth the hourly wage rate, as generally done n the lterature, s potentally msleadng. When hours change, ths erroneously shows up n factor prces (annual wages) rather than n factor quanttes (total hours employed). Thus the prevous decompostons may be msleadng, and the estmated skll-bas of techncal progress may be based (see below). We obtan the average number of hours worked per employee n frm (h ) by dvdng the number of hours worked n frm (H ) by the number of ts employees (E ): h = H. The hourly average wage at the frm s then defned E as the rato between the annual wage rate and the average number of hours per employee: ω = W. Average non-manual hours (h h n) and hourly wage rates (ω n) at frm are calculated smlarly. Table 4 shows sample and sub-sample means across frms for average worker s and non-manual worker s hours (h and h n, respectvely), hourly wage rates (ω and ω n ), and the correspondng hourly skll ntensty ( hn ) h and wage premum ( ωn ). In the entre sample, non manual employees work ω longer hours per year ( vs ), and earn hgher hourly wages than average workers (39.6 vs thousand lre per hour, correspondng to Euro and 15.6 respectvely). The average hourly skll premum and hourly ntensty are thus and per cent, respectvely. Lookng back at Table 1, we see that n the total wage premum of (frst row, second column), only (Table 4) s the actual prce dfferental, the rest smply reflectng dfferences n hours. Lookng at changes between 1989 and 1995, the hourly wage premum rses by 1.2 percentage ponts, whle hourly skll ntensty rses untl 1993 and then falls back to just below the ntal level. Comparng ths wth the change n relatve annual wages ( Wn ), Table W 1 second column, we see that the modest rse n relatve annual wages s (more than) entrely due to the rse n the hourly premum ( ω n ω ). The hourly wage premum s smaller n hgh-tech and hgh-export frms, whle hourly skll ntensty s relatvely more unform across frms. Proceedng as before, we am at separatng the (between) changes resultng from compostonal effects from those occurrng at frm level (wthn). Thus we calculate between/wthn decompostons for the three components 14

16 of the relatve wage bll (see the Appendx for detals), employment (E), hours worked (H) and hourly wages (HW ): ( W B n ) = (Ewt + Ebet) + (Hwt + Hbet) + (HW wt + HW bet) (4) W B The results, presented n Table 5, are revealng, partcularly when compared wth those reported n Table 3. The apparent stablty of annual wage prema wthn frms (W wt = 0.01 n table 3), hdes the offsettng contrbutons of hours and hourly wages: relatve non-manual hours have rsen at the annual rate of Hwt = 0.19, whle, gven the lack of adjustment n salares, the hourly premum (HW wt) has fallen at the same rate. Gven that the relatve prce of an hour of sklled labor has actually declned, frms have substtuted manual wth non-manual workers not only n terms of employment levels (on the extensve margn), at the annual rate of Ewt = 0.63, but also n terms of hours (on the ntensve margn), at the annual rate of Hwt = The latter phenomenon s smply obscured when the standard defnton of annual wages s used. Wthn frms, relatve non-manual hours have therefore rsen approxmately at the annual rate of = 0.82 whch s about one thrd above the estmate n Table 3. We now turn to the nterpretaton of these decompostons. 6 Interpretng the decompostons So far we have nterpreted the wthn and between components as reflectng technology and demand shocks, respectvely. Ths nterpretaton, however, s not warranted: wthn-frm changes may also be due to demand shocks. Suppose, for example, that the domestc relatve prce of unsklled-ntensve ( tradtonal ) goods rses, due to a change n preferences or to trade lberalzaton. 24 As new frms enter the tradtonal sector, the share of unsklled workers n employment rses (between effect). The resultng excess demand for unsklled workers lowers the wage premum, and nduces frms to substtute manual wth non-manual workers (a postve employment wthn effect). In ths case, a demand shock (between frms) ndrectly causes a (wthn-frm) change n factor proportons. Attrbutng the latter to technology would be ncorrect, and t would result n overestmatng the role of technology (and underestmatng that of demand or trade). 24 We thank Paolo Epfan for rasng ths pont. 15

17 In ths secton we therefore examne whether t s correct to nterpret wthn and between components as reflectng technology and demand, respectvely. We regress the between and wthn frm-level changes n wages (both annual and hourly), employment and hours, on varables that proxy for frm-level demand and technology. If our assumed nterpretaton s correct, wthn-frm changes should be sgnfcantly related to technology but not to demand varables, whle the converse should be true for between changes. We use the rate of growth of total sales as an ndcator of the change n demand for a frm s output, and consder two alternatve ndcators of technologcal change at frm-level: the rato of nvestment n computers over total nvestment, and the rato of research and development expendtures over total sales. 25 All regressons nclude sze, regon, and ndustry dummes to allow for dfferent frm and ndustry characterstcs. The general specfcaton s therefore: C d = α + β 1 ls + β 2 ICI + β 3 RDS + j γ j DUM j (5) where C d ndcates frm s contrbuton to the overall change n the relatve wage bll, employment and (annual and hourly) wage ( C = W B, E, W, HW, H), and the subscrpt d = bet, wt denotes between and wthn components, respectvely; ls s the growth rate of total sales, ICI s the rato of the frm s nvestment n computers over total nvestment, RDS s the rato of Research and Development expendtures over total sales, and DU M represents a set of ndustry, sze and geographc dummes. The results of OLS estmaton of equaton (5) are presented n table The growth rate of sales has a postve and hghly sgnfcant coeffcent n all between regressons (wth the excepton of the hourly wage equaton): demand shocks are postvely related to between-frm changes n both employment and annual wages, but not to wthn changes (wth the excepton of hours, Hwt, and hourly wages, HW wt). Lookng at the technology ndcators, the computer share of nvestment ICI s postve and sgnfcant n the wage bll and employment wthn equatons, whle negatve but never sgnfcant n the between equatons. The research and development ndcator 25 The R&D varable also contans expendtures for patents, concessons, and copyrghts. 26 The lower number of observatons (from 8203 n the decompostons to 7377 n the regressons) s largely due to data lmtatons on the technology ndcators: only 8005 and 7830 observatons, respectvely, are avalable for the computer ntensty and research and development ndcators. 16

18 RDS s postve, although not sgnfcant, n the wage bll and employment wthn equatons. Interestngly, t s postve and strongly sgnfcant n the equaton for the wthn frm relatve number of hours, Hwt. The results for hourly wages are less clear-cut: the wthn component s sgnfcantly related to both the growth of sales (postvely) and the R&D ndcator (negatvely); the between component s not sgnfcantly affected by ether demand or technology ndcators. 27 Overall, the evdence suggests that between-frm changes for all the ndcators examned are postvely and sgnfcantly related to changes n demand. In addton, there s a postve and sgnfcant relatonshp between techncal change, as measured by nvestment n computers and R&D ntensty, and wthn-frm skll upgradng both on the extensve margn (number of employees) and the ntensve margn (number of hours worked per employee). 7 The (based) bas of techncal change In the prevous sectons we found that the man determnant of the rse of non-manual employment and wage bll shares s frms substtutng nonmanual for manual workers. In ths secton, we use a cost functon framework to measure the effect of techncal change on the relatve productvty of nonmanual workers (the so called skll-bas of techncal change). We fnd a postve and sgnfcant skll-bas. Also, we show that defnng relatve wages n terms of annual, rather than hourly, salares, produces a downward bas n the estmates of the skll-bas as well as of the elastcty of factor substtuton. In order to solate the effect of techncal progress on factor shares, one needs to control for changes n factor prces and captal ntensty: the rse n the share of sklled workers wthn frms may be smply due to a fall n ther relatve factor prces or to captal deepenng when sklls and captal are complement. We defne techncal progress as a reducton n unt cost (an nward shft of the unt-soquant) at constant factor prces and captal ntensty (see Bnswanger, 1974). Techncal progress s neutral f, despte lower unt costs, frms on average do not change factor proportons, at gven factor prces and captal ntensty. However, f they ncrease on average the proporton of sklled workers n employment (when they pck a new tangency 27 In order to address the possble endogenety of the proxes for demand and technology, we also estmated the equatons by nstrumental varables, usng the ntal levels of the regressors as nstruments, and obtaned qualtatvely smlarly results. 17

19 pont on an lower socost lne of the same slope), then techncal progress rases the relatve productvty of non-manual workers and s defned skll-based. Emprcally, we mplement ths approach followng Berman et al. (1994). An equaton for the wage bll share can be derved from a translog cost functon wth quas-fxed factors of producton (Brown and Chrstensen (1981)). Assume that frms choose varable factors, manual and non manual labor, n order to mnmze costs, subject to an output constrant. Producton requres (manual and non-manual) labor and captal, whch s fxed n the short run. The cost functon has the translog functonal form, and returns to scale are constant. Under these assumptons the change n the share of non-manuals n the wage bll share can be wrtten as follows: ( W B n W B ) = α + β ln( w n ) + γ ln( K wm Y ) + ε (6) where K and Y represent captal and value added, respectvely (the actual specfcaton also ncludes a set of ndustry, sze and geographc dummes, as n (5)). Note that the ntercept α measures the average bas n techncal change, and the resdual ε provdes an estmate of the frm-specfc bas. If the slope coeffcent β s postve (negatve) a change n the relatve prce of non-manual labor rases (lowers) ts cost share, mplyng that the elastcty of substtuton between nputs s below (above) unty (σ = β+s n(1 s n ) s n(1 s n), where s n = W B n ). A postve (negatve) estmate for γ mples that captal W B s complement (substtute) to non-manual labor, snce t rases (lowers) ts wage bll share at constant factor prces. In the followng we present results obtaned estmatng the above equaton usng ether annual or hourly wages (w = W, ω) as factor prce. Table 7 reports OLS estmaton results usng annual wages. We estmate equaton (6) n ts basc verson, and subsequently add, ether ndvdually or jontly, the two ndcators of technologcal change descrbed above (computers as a share of total nvestment and R&D over sales). Startng from the basc specfcaton, we see that the constant s postve and sgnfcant: the ncrease n the relatve productvty of non manual workers (the average bas of techncal progress) occurs at an annual rate of 0.48 and thus rases the wage bll share of sklled workers by almost half of a percentage pont per year. The change n relatve wages has a postve and statstcally sgnfcant coeffcent, mplyng an elastcty of substtuton between labor nputs of σ = The coeffcent of the captal-value added rato s also postve 18

20 and sgnfcant, ndcatng complementarty between captal and sklled labor. Captal deepenng has thus contrbuted to skll upgradng. When we add to the basc model technology ndcators ndvdually (equatons 2-3) or jontly (equaton 4), both the computer share of total nvestment and R&D expendtures as a fracton of sales have postve and hghly statstcally sgnfcant coeffcents. The estmate of the average skll bas falls slghtly (to 0.44) when explct proxes of techncal progress are ncluded n the equaton, whle the estmated elastcty of substtuton s robust across dfferent specfcatons. 28 Next we re-estmate the prevous equaton wth hourly wages on the rght hand sde, and obtan the results shown n Table 8. Compared wth those n Table 7, the parameters for captal deepenng and the computer share n nvestment are vrtually unchanged, whle the estmates for the rato of R&D expendtures over sales are almost double n sze. Usng hourly wages has two more mportant consequences: the estmated average skll-bas rses consstently n all specfcatons, respectvely from α n the range ( ) to α n the range ( ). Smlarly, the estmated elastcty of substtuton rses from σ = 0.49 to σ = The reason for the larger estmated skll bas s the followng: techncal progress rases, as we saw, the relatve number of non-manual hours, but when wages are ncorrectly measured (on an annual, rather than hourly bass), ths effect s attrbuted to hgher relatve factor prces, rather than to the bas. As for the larger elastcty of substtuton, note that n the second specfcaton ths elastcty effectvely measures the change n total hours (employment plus average hours) nduced by a change n relatve factor prces, so that the estmated elastcty must also be larger. If techncal nnovaton and sklled hours are complement, estmates of the skllbas and of the elastcty of substtuton based on annual wages (e.g. Berman et al., 1994, Berman et al., 1998) are therefore lkely to underestmate the skll-bas of techncal change. Summng up, our estmates suggest that skll-based technologcal change has rased the relatve productvty of non manual workers at an annual rate of roughly half of a percentage pont, and thus was the key determnant of the ncrease n the demand for non-manual workers n Italan manufacturng durng the 1990s. We also found that n order to assess the role of techncal progress on wage nequalty and skll upgradng, t s mportant to dsaggre- 28 The results are also robusts to the use of begnnng-of-perod levels for the technology ndcators. 19

21 gate annual wages nto the number of hours worked and ther hourly prce. The current practce n the lterature fals to do so, and therefore erroneously attrbutes changes n hours to factor prces rather than quanttes. Ths produces a downward bas n the estmated skll-bas of techncal progress. 8 Dscusson and conclusons Ths paper has presented frm-level evdence on the dynamcs of wage prema and relatve employment and hours n Italan manufacturng n the nnetes. We have exploted a new data set, prevously unavalable for research, that covers a balanced panel of 8441 manufacturng frms between 1989 and The analyss has reached a number of nterestng results on the effects of technology and trade on employment and wages n Italan manufacturng frms. Frst, Italan frms have substtuted unsklled for sklled workers at a rate comparable to those experenced n other ndustralzed countres, wth hghtech frms playng a leadng role n ths process (wthn-frm skll upgradng s the man determnant of the shft n relatve labor demand n the nnetes). Ths s a new, and somewhat unexpected, result, gven that most studes on European economes fnd sgnfcant effects of techncal progress at sector level only after 1995 (e.g. Daver, 2000). By contrast, demand changes assocated to trade have moved manufacturng employment away from skll-ntensve frms, contrbutng to moderate the change n relatve factor prces (between-frm employment shfts have reduced the relatve demand for sklls). Ths anomaly s consstent wth the fndng n Manasse et al. (2002), obtaned from a much smaller sample of (metalmechancal) frms and a shorter tme horzon. The anomaly s probably due to the specalzaton pattern of Italan trade. Durng the nnetes frms have become ncreasngly specalzed n unsklled-ntensve tradtonal goods (such as shoes, textles, furnture etc., see Charlone, 2001), and have been ncreasngly exportng to more technology abundant European countres. Second, the relatve stablty of wage dfferentals wthn frms hdes a second anomaly: when composton effects are taken care of, the relatve number of hours worked by sklled workers has rsen whereas relatve hourly wages have fallen. The narrowng of hourly skll prema n the face of techncal progress may come unexpected, partcularly to readers unfamlar wth the features of the Italan labor market. Yet t s well known the Italan 20

22 centralzed system of wage barganng systematcally fals to talor wages to frms and workers productvty, wth unons actng as a powerful nstrument of wage equalzaton. For example, salares n the South are equalzed to salares n the North, despte large productvty gaps, and ths s generally regarded as an explanaton of a rate of unemployment whch s four tmes larger n the South than n the North. In addton, possbly as a result of ths compresson n relatve hourly wages, Italy has been exportng college graduates and sklled workers ( the bran dran ) at a rate that has no comparson n Europe (see Becker, Ichno and Per (2002)). Thrd, wthn-frm skll upgradng, measured by changes n both relatve employment and number of hours, s strongly and sgnfcantly related to nvestment n computers and R&D. Ths suggests that the skll bas of techncal change has been a key determnant of the ncrease n the relatve demand for non-manual workers n Italan manufacturng n the last decade. Fnally, the paper makes an mportant methodologcal pont: n order to assess the role of techncal progress on wage nequalty and skll upgradng, t s essental to dsaggregate hours worked from ther prce. Falng to do so, and attrbutng hours to factor prces rather than quanttes, bases downward the estmates of the skll bas whenever techncal progress and hours are complement. Properly measured, techncal progress s found to rase the relatve productvty of non-manual worker by half a percentage pont every year. Whether these results extend beyond the manufacturng sector s one of the questons to be nvestgated n further research. Fnally, notce that our fndng that total relatve hours have rsen (wthn frms) whle hourly relatve wages have fallen, suggests that labor supply effects can no longer be ruled out as a possble explanaton of the Italan case. In order to assess the role of factors such as ageng labor force, female partcpaton, mmgraton, educaton, changes n preferences away from lesure and so on, data on ndvdual workers should be merged wth frms data: another mportant project for further research. 21

23 9 Appendx Ths appendx provdes some detals on the dervaton of the contrbutons of employment, hours worked and hourly wages to the wage bll presented n secton 5: = = = [ I I I ( ) W Bn = W B ( E n E ( E n E I ) ( ) W n + W ) ( ) W n W ( ω n ω ( ) ( E n W n E W Ewt ( h n h ) ( ω n ω ) ( E n Hwt ( E n E ( W n W ) Wn W ) ( ) ] E n = E ( ) ( ) ( + h n ω n E n h ω E ) ( ) ( ) h n E n h E ) ( ) E ) ( ω n ω ) ( h nh ) ( E n HW wt E ) + ( + E E h h ( + ) ( W n W ) ( ω n ω Hbet ) ( h n Ebet ω ω h HW bet ) + + ) ( E n E ) ( E n E = ) + ) The frst, second and thrd lne above correspond to the frst, second and thrd term of equaton (4) n the text. 22