SKILL-BIASED TECHNOLOGICAL CHANGE, INTERNATIONAL TRADE AND THE WAGE STRUCTURE

Transcription

1 SKILL-BIASED TECHNOLOGICAL CHANGE, INTERNATIONAL TRADE AND THE WAGE STRUCTURE New evdence on the determnants of the employment structure from lnked employer-employee panel data for Germany ARND KÖLLING* AND THORSTEN SCHANK* FEBRUARY 2002 Abstract Durng the last two decades, the labour demand structure n Germany and other OECD countres has experenced a decrease n the demand for low sklled and a rse n the demand for hghly sklled employees. The adopton of modern technologes n the producton process as well as the growth of nternatonal trade are often regarded as the man drvng factors behnd ths change. On the other hand, t s often argued that a more flexble wage structure could counteract the fallng demand for the unsklled. Ths study nvestgates these hypothess for West Germany, , usng the LIAB, a unque German lnked employer-employee panel data set, whch combnes nformaton from the German employment statstcs and the IAB establshment panel. Employng a Generalsed Leontef cost functon and controllng for unobserved plant heterogenety, the demand for three dfferent skll types of labour s estmated by the SUR-Method. The results show that the major part of the skll structure s determned by wages, whle we have found only mnor mpacts of a skll-based technologcal change, of nternatonal trade and of short-run effects due to the busness cycle. [182 words] JEL Classfcaton: J23, J31, O33, F16 Keywords: labour demand, substtuton, skll-based technologcal change, labour hoardng, nternatonal trade, lnked employer-employee data * Insttute for Employment Research (IAB), Regensburger Str. 104, D Nuremberg, Germany, / , mal: Arnd.Koellng@ab.de or Thorsten.Schank@ab.de

2 1. Introducton Durng the last two decades, the labour demand structure n Germany and other OECD countres has experenced a decrease n the demand for low sklled and a rse n the demand for hghly sklled employees (see Bellmann et al. 1996, 85pp, Koller & Haas 2001 for Germany and Machn & Van Reenen 1998 for other OECD countres). Snce we do not observe the same development n the supply of labour, consequently the group of unsklled employees faces severe and rsng unemployment problems. Projectons of the German labour force, for example, predcts that ths trend contnues untl the end of the frst decade of the new mllennum (see Wedg, Hofer & Wolff 1999, 58; Schüssler et al. 1999, 57pp). Manly two reasons for ths phenomenon are dscussed. The frst argument follows the noton of a creatve destructon (Schumpeter 1942). Old equpment vanshes, whle modern technology appears. Ths knd of techncal progress s assumed to be skll-based, leadng to an ncrease n the share of hghly sklled employees (Bound & Johnson 1992; Berman, Bound & Grlches 1994). The alternatve argument rests on hgher foregn competton due to the globalsaton of markets. Compettors n low-wage countres damage the poston of less sklled workers n ndustralsed hgh-wage economes (Freeman 1995). Besdes these, captal-skll complementartes and the shft from manufacturng to non-manufacturng ndustres (see Ftzenberger 1999a, 4) and, very recently, organsatonal changes (Bresnahan, Brynjolfsson & Htt 1999) are commonly referred to when explanng shfts n the skll structure of labour demand. It s often argued that the reducton n the demand for the low sklled could be counteracted by lowerng ther wages and that the rgd wage structure n contnental Europe, as opposed to the Unted States and Great Brtan, s at least partly responsble for the hgh unemployment rates of the unsklled. 1, 2 1 Followng ths argument, a lower unemployment rate of the unsklled would obvously be acheved at the expense of a rsng wage nequalty. 1

3 Both explanatons, skll-based technologcal change and ncreased foregn competton, determne long-run effects on the structure of labour demand. However, there are also shfts due to short-run behavour of frms. The change n labour productvty durng a busness cycle s a stylsed fact. Durng a recesson, labour productvty decreases, whle t ncreases durng an economc upswng. One explanaton for ths procyclcal movement s labour hoardng of sklled workers (Hamermesh 1993, 205). The demand for low sklled, on the other hand, s more senstve to a frm s economc condton, because of lower hrng and frng costs of ths group. Therefore, the structure of employment n a frm also depends on short-run effects due to the busness cycle and the share of low sklled employees s assumed to be postvely correlated wth the busness cycle. Ths paper seeks to dentfy the dfferent nfluences on the skll structure wthn a frm, usng the LIAB, a lnked employer-employee panel data set, whch s unque for Germany. Our analyss s based on 880 West German plants for the tme perod from 1994 to 1997 and covers approxmately 350,000 employees per year. It combnes ndvdual data from the offcal employment statstcs of the Federal Employment Servces wth plant data from the IAB- Establshment Panel. The employment statstcs provdes us wth detaled and precse nformaton on personnel characterstcs and the skll decomposton of a plant s workforce and of the (medan) wage of each skll group, whle we observe the economc actvty of a plant (actual and expected output, dfferent types of nvestment, export) and the level of the used technology from the IAB panel. Thus, we are able to estmate the demand for heterogeneous labour based on a rch and new data-set. Furthermore, takng advantage of the longtudnal character of the data, our analyss should produce relable results snce we are able to 2 The German government s currently testng n a few regons the effect of subsdsng the wages of newly hred unsklled employees (for example the SGI Model mplemented n Saarland). Ths reduces frms wage costs, whle employees ncome remans constant. If the beforementoned clam holds, then ths should rse the demand for unsklled employees. 2

4 control for unobserved (tme-nvarant) plant heterogenety, an nherent problem of many emprcal specfcatons. The paper s organsed as follows. Secton 2 revews the theoretcal and emprcal lterature on the structural changes n the frms labour demand. In secton 3, we derve condtonal labour demand functons for three dfferent skll types of labour from a Generalsed Leontef Cost Functon. Secton 4 descrbes the data, whle the emprcal specfcaton s presented n Secton 5. The estmaton results are dscussed n Secton 6. Secton 7 summarses. 2. A bref overvew of prevous studes Followng the semnal artcle by Krueger (1993), the hypothess of a skll-based technologcal change became very popular. The lterature provdes two dfferent explanatons for the ncrease n the share of sklled employees due to techncal progress. The frst assumes a complementary relatonshp between human captal and physcal captal. Ths leads to a hgher demand for the hghly sklled after a frm has mplemented new technologes. Hence, the structure of the workforce shfts towards the sklled/hghly sklled employees. Casell (1999) dstngushes between dfferent knds of technologcal progress. Besdes the skllbased technologcal changes, there are sometmes de-skllng effects of new machnes. In the 1920 s, the use of assembly lnes dd not lead to an ncrease n the requred sklls. In contrast, ndvdual operatons at the workplace were splt nto small peces. Thus, the requred sklls were lowered and more workers were able to work wth ths technology. On the other hand, the use of nformaton technology (IT) and mcroelectroncs snce the 90tes has probably been skll-based snce they requre very specal capabltes and therefore, more human captal. 3

5 The second explanaton for a skll-based technologcal change refers to the dfferent abltes to adapt to a new technology or to an unknown labour envronment (Bartel & Lchtenberg 1987). Because hghly sklled employees are able to learn faster and perform better wth new machnes than the low sklled, t s more attractve for the employer to hre sklled nstead of unqualfed workers. The paper of Krueger (1993) ntated a vast body of lterature on the effects of technologcal changes on the structure of labour demand, whch support the hypothess of a skll-based technologcal change. Emprcal studes for Germany fnd evdence for a skll-based technologcal change (e.g. FtzRoy & Funke 1998, Kaser 2000, Falk & Sem 1999, Falk & Koebel 2000). The work of Lndbeck and Snower (2000) deals wth organsatonal changes that abolsh the taylorstc system of work and also smultaneously shfts the demand for labour n favour of the hghly sklled. These organsatonal changes may be the result of techncal progress, but Legh and Gfford (1999) fnd that the ntroducton of new equpment leads to hgher tranng efforts rather than organsatonal transformatons. Entorf, Gollac & Kramarz (1999) and Entorf & Kramarz (1997) also fnd a demand bas towards hghly sklled labour but the effect reduces after ntroducng unobserved plant heterogenety to the model. Also, t s the experence wth modern technology, not only the use, that s rewarded by the employer. Ftzenberger (1999a, 137pp.) receves dfferentated results, as he dstngushes between several nstruments for modern technologes. Also, he dvdes captal nto two dfferent knds (equpment and plant) and dscrmnates manufacturng from non-manufacturng ndustres. Dependng on the varables used, the nfluence on the skll groups dffer, but an overall trend towards hghly sklled after the ntroducton of new euqpment n the frm s always found. On the other hand, several studes could not confrm a relatonshp between hgher qualfcaton and technologcal progress or fnd other explanatons for the shft n the skll structure. 4

6 Bellmann & Schank (2000) do not fnd complementartes between captal and human captal n Germany. In the paper of DNardo and Pschke (1997), the wage structure changes because of the competton on the product market. If frms whch use modern technology are able to pay hgher wages for sklled employees, then all frms are forced to pay more for these workers, otherwse ther employees would qut. The results of Haskel and Heden (1999) suggest a lower demand for manual workers, f nvestment n computers takes place. Fnally, Robnson and Manacorda (1997) fnd evdence that a great part of the structural changes n the labour force s pctured by the alteratons n the supply of labour. However, skll-based technologcal progress s probably nduced by an ncreased supply of hghly sklled employees (Acemoglu 1998). The alternatve to ths techncal or organsatonal based explanaton of the change n the skll structure s nternatonal trade. Foregn competton leads to hgher productvty pressure on the establshments (Freeman 1995). When frms from low-wage countres appear on the market, wages of less sklled workers must decrease or the share of low sklled n the frm declnes. Machn and Van Reenen (1998) and Berman, Bound and Machn (1998) do not support ths assumpton, but they fnd that skll-based technologcal change takes place not only on the natonal, but also on the nternatonal level. Zera (1998) clams that the adopton of new technologes s proftable for countres wth a hgh productvty. Hence, producers n countres wth a low level of productvty may not fnd t proftable to use new technologes. For Germany, Ftzenberger (1999b) fnds trade as one explanaton for the reducton n the demand of the low sklled, whereas skll bases technologcal change ncreases the demand for hghly and medum sklled workers. The explanatons of a fallng employment share of the unsklled dscussed so far deal wth long-run changes n labour demand, but there s also evdence of shurt-run alteratons. Dfferent adjustment costs or effcency wages lead to dfferences n the adjustment behavour 5

7 for dfferent skll groups durng a busness cycle (cf. Hamermesh 1993, 205; St. Paul 1996, 45pp). The hrng and frng of employees wth hgh replacement cost are expected to take place at a lower rate; and generally, t s assumed that these costs rse wth skll. Therefore, the demand for unsklled employees s awated to fluctuate wth a hgher rate through a busness cycle and ts share n total employment should be larger durng a boom than durng a recesson. Therefore, the proporton of low sklled vares pro-cyclcal whle the proporton of hgh sklled vares counter-cyclcal. Techncal progress or nternatonal trade lead to a drect substtuton of low sklled through hghly sklled employees. Ths process s ndependent of the busness cycle; thus, we should dstngush between both effects n our emprcal nvestgatons. In the next secton, a labour demand model s derved to estmate short-run and long-run effects on the structure of a frm s workforce. 3. A Functonal Framework for Heterogeneous Labour Demand In the followng, we use a cost functon to derve the demand for heterogeneous labour, where the labour nput s stratfed nto three categores (unsklled, medum sklled and hghly sklled employees; see the data descrpton for the actual categorsaton). We assume captal, K, to be a quas-fxed factor of producton. Followng the consderatons n the prevous secton, we assume that modern technologes, IT, the export behavour, EXP, and labour hoardng, LH, nfluence the demand for the dfferent skll groups. Thus, the varable producton cost, C, whch are necessary to produce a certan output level, Y, can be summarsed as: C = C(w 1, w 2, w 3, Y, K, IT, EXP, LH). (1) where w denotes the wage of group : 6

8 We also seek to dentfy short-run effects on the demand for labour n ths study. Therefore, one could argue, that the model has to be specfed as a dynamc labour demand model. There are two reason, why a dynamc formulaton does not ft the needs of the model. Frstly, the assumptons about the costs of adjustment and the producton functon n these models are rather restrctve and questonable (cf. Hamermesh 1993, 232pp.). Secondly, emprcal results for Germany suggest that the adjustment processes for heterogeneous labour s almost completed wthn one year (cf. Köllng 1998, 175pp.). Snce we use yearly data n ths study, employment dynamcs should not affect the results. We choose a Generalsed Leontef cost functon to derve the demand for heterogeneous labour (Dewert 1971). Together wth the Translog specfcaton (Chrstensen, Jorgenson & Lau 1973), the Generalsed Leontef belongs to the most common flexble functonal forms, whch are lnear second-order approxmatons to arbtrary cost functons. They are preferred to the Cobb-Douglas or CES-functons because they do not restrct the substtuton elastctes of the nput factors to be equal to one or to be constant. We select the followng Leontef cost functon: C 2 = Y αj ww j + Y βw + j k γ Z w + u k k, j = 1,...,3, k = 1,...,4; (2) where we have used Z as a column vector consstng of K, IT, EXP and LH, wth Zk defnng the k-th element of ths vector. The condton α = α ensures equal cross partal dervatves j j j j 2 2 ( C / w w = C / w w ). Applyng Shepard s Lemma. e. C / w = N - yelds the condtonal demand functons for the dfferent types of labour: N j 2 = Yα + Y αj + βy + j w k w γ Z k k, j = 1,...3, k = 1,...4. (3) 7

9 The own-wage elastctes of the respectve labour groups are gven by the followng formula:.5.5y α j jwj η N w =. (4).5 N w Snce the cost functon s assumed to be concave, the own wage has a non-postve mpact on the demand for each group 2 C N = w w 0. The cross wage elastctes are gven by:.5.5yα jwj η N w =. (5) j.5 N w Two groups are substtutes, f the dervatve of N wth respect to w j s postve N > 0, j and complements, f ths dervatve s negatve. Fnally, labour demand elas- wj tctes wth respect to output and wth respect to any of the Z-varables can be calculated as: Y ( α + α 2 ) j jwj w + Yβ η N Y =. (6) N and γ Z k k η N Z =. (7) k N 3 By contrast, the dervaton of the mpact of the Z-varables n a Translog system also reles on coeffcents whch occur only n the cost functon. 8

10 We are not only nterested n the mpact of any exogenous varable on the employment levels, but also n the effect of any exogenous varable on the employment shares of each skll group. These can be calculated va the followng expresson: 4 ( N N ) N 1 1 N N j N j N = N N = j 1,...,3; ( ) ( ), = 2 (8) 2 x x j x N x N j x N where N j = N s total employment wthn a plant and x denotes any of the rght-hand 1 = 3 sde varables of our model. Note that ths formula depcts the margnal effect (the mpact of a change n a rght-hand sde varable on the employment share of a partcular skll group), but the extenson to a sem-elastcty or an elastcty s straghtforward. 4. The Matched Employer-Employee Data-Set (LIAB) The use of matched employer-employee data has recently become popular as t allows a more detaled analyss of economc relatonshps. In partcular, varous analyss of the labour market can beneft from the avalablty of employer-employee data. 5 In ths paper, we use the LIAB, whch combnes the employment statstcs of the German Federal Employment servces wth plant level data from the IAB-Establshment Panel. The employment statstcs (cf. Bender, Haas & Klose 2000) cover all employees and tranees subject to socal securty and exclude, among others, a part of the cvl servants ( Beamte ), the self-employed, famly workers, students enrolled n hgher educaton and those n margnal employment. For 1995, the employment statstcs cover nearly 79% of all employed persons n Western Germany and about 86% n Eastern Germany. 4 5 The qualtatve mpact of a varable on the employment share s not drectly obvous from the qualtatve mpact of a varable on the employment levels. A survey of matched employer-employee data sets can be found n Abowd and Kramarz (1999). 9

11 The employment statstcs are collected by the socal nsurance nsttutons for ther purposes accordng to a procedure ntroduced n 1973 and are made avalable to the Federal Employment Servces. Notfcatons are prescrbed at the begnnng and at the end of a person s employment n a plant. In addton an annual report for each employee s compulsory at the end of a year. Msreportng s legally sanctoned. The employment statstcs contan nformaton on an employee s occupaton, the occupatonal status and gross earnngs up to the contrbuton assessment celng and on ndvdual characterstcs lke sex, age, natonalty, martal status, number of chldren and qualfcaton. Each personnel record also contans the establshment dentfer, the ndustry and the sze of the plant. Startng n 1993, the IAB-Establshment Panel (cf. Köllng 2000) s drawn from a stratfed sample of the plants ncluded n the employment statstcs, where the strata are defned over 16 ndustres and 10 plant szes (large plants are oversampled), but the samplng wthn each cell s random. In 1993, the sample started wth 4,265 plants, coverng 0.27% of all plants n West Germany (2 mllon) and 11% of total employment (29 mllon). In 1996, the Eastern German establshment panel started wth 4,313 establshments representng 1.10% of all plants (391 thousand) and 11% of total employment (6 mllon). Altogether, the number of establshments ntervewed ncreased untl the year 2001 up to 15,000, n order to make regonal analyss on the federal state level feasble. The IAB-Establshment Panel s created for the needs of the Federal Labour Servces to provde further and detaled nformaton about the demand sde of the labour market. Therefore, nformaton on the decomposton of the workforce and ts development through tme consttutes a major part of the questonnare. Further questons nclude tranng, workng tme, busness actvtes and establshment polces. Other topcs, for nstance, questons on nnovatons or flexblty of labour, are asked bennally or trennally. In addton, each year 10

12 provdes nformaton on partcular topcs; n 2000, for example, ths has been the lack of sklled employees. The LIAB s created by lnkng the employment statstcs and the IAB-Establshment Panel through a plant dentfer whch s avalable n both data sets. Ths matched employeremployee data-set, whch s unque for Germany, comprses currently the years The Emprcal Specfcaton Based on Equaton (3), we estmate the followng system of employment-output ratos: N Y pt pt w jpt = α + αj + βypt + w γ k j pt k Z Y kpt pt + ε p, j = 1,..., 3; k = 1,... 4; (9) where p denotes plants and t ndexes the year of observaton. In addton, we have dvded Equaton (3) by output, snce t seems reasonable that the error varance of the skll groups s correlated wth the output level (see, for example, Parks 1971). Ths would cause based estmates of the standard errors when estmatng a system of labour nputs themselves. A common problem of earler studes based on cross-sectonal data s unobserved plant heterogenety. To sweep out any unobserved (and tme-nvarant) effects, we apply the wthn transformaton to Equaton (9): 6 N Y pt pt 1 T t N Y pt pt = j k α j Z γ k Y w w kpt pt jpt pt 1 T 1 T t t Z Y kpt pt w w jpt pt + ε + β Y pt 1 - T pt 1 T t ε pt t Y pt +, j = 1,..., 3; k = 1,... 4; (10) 6 Because of ths transformaton, all tme-nvarant varables are swept out. For ths reason, we have not ncluded controls for ndustry classfcaton. 11

13 As can be seen, we subtract from each varable the wthn-plant mean. After addng tme dummes, ths Equaton system s estmated by the Seemngly Unrelated Regresson (SUR) method n STATA V7.0. The SUR method assumes that the error terms between the labour nputs of one plant are correlated, but not those of dfferent plants. For the analyss of ths paper, nformaton from the employment statstcs on wages and on the number of employees n each skll group (unsklled, medum sklled and hghly sklled) has been aggregated at the establshment level. We have combned two varables of the employment statstcs to classfy employees by skll. Workers are categorsed accordng to ther occupatonal status (unsklled, sklled/traned, master craftsmen). Snce the employment statstcs contans only one occupatonal status for salared employees, we have categorsed ths group accordng to ther qualfcaton (wthout apprentceshp and wthout A-levels, wth apprentceshp and/or A-levels, wth a degree from hgher educaton). The nformaton on daly wages s censored at the top, snce there s a contrbuton assessment celng for payments to the socal securty. Therefore, we have carred out twelve Tobt regressons (for each year and for each skll group separately) of the daly wage on a set of other varables from the employment statstcs (natonalty, age, gender, number of chldren, famly status, occupaton and ndustry dummes). 7 We have then used the predcted wages to calculate the medan wage per plant and per skll group. Therewth, we avod a bas n the coeffcents due to censored nformaton on wages and we have also elmnated any potental endogenety of the wages, snce the varables used to predct the wages can be regarded as exogenous. These plant specfc varables (for each skll group the estmated medan wage and the number of employees) are added to the IAB-Establshment Panel, from whch we obtan the 7 For 1997, for example, the regressons are carred out wth ca. 1.0 mllon observatons for the unsklled (6,609 censored), 2.1 mllon observatons for the sklled (187,877 censored) and 0.5 mllon observatons for the hghly sklled (233,241 censored). The regresson ouputs are avalable from the authors upon request. 12

14 other nformaton whch s needed to estmate the system of nput-output ratos gven n the Equaton system (6). We use (yearly) turnover nstead of value added as a proxy for output, snce the data on ntermedate nputs contans mssng values for about one thrd of all plants. Turnover are measured n mllons DM and are deflated by a sectoral prce ndex obtaned from the statstcal offce. Snce the nformaton refers to turnover n the prevous year, we beleve that the problem of endogenety of turnover s mnmsed. The captal stock s approxmated by the sum of nvestment expendture n the last two years and s also measured n mllons DM. Further, we nclude dummy varables whch respectvely ndcate whether a plant has nvested n () property and buldngs, () n producton unts and () n nformaton and communcaton technology. The latter can be regarded as a proxy for the use of new technologes n the plant and, n addton to ths, we use another dummy varable whch s equal to one f uses up-to-date equpment to produce goods or to provde servces. The mportance of nternatonal trade and globalsaton for a plant s measured as the percentage of exports n the turnover of the prevous year. Labour hoardng s approxmated by the expected relatve change of turnover compared to the prevous year. If the value s postve, the share of unsklled s expected to rse. Agrculture, the mnng and energy sector, the bankng and nsurance sector and the publc sector are excluded because ther measure for turnover s not comparable to that of other sectors. We have ncluded only plants wth an (average) employment sze of at least 10, takng account of the fact that small plants have dfferent substtuton possbltes. After the wthn-transformaton, plants wth only one observaton have no mpact on the regresson results and have consequently been dropped from the analyss. Ths leaves us wth a sam- 13

15 ple sze of 2470 observatons and 880 West German plants coverng the tme perod 1994 untl The descrptve statstcs of the varables used are summarsed n Table Estmaton Results Tables 2 and 3 report parameter estmates of constraned seemngly unrelated regresson analyss of Equaton (10), whch was performed separately for manufacturng and for servces. We can already nfer from the parameter estmates that for both subgroups unsklled and medum sklled employees are substtutes and that the unsklled and the hghly sklled are not affected by each other s wage. Whle medum sklled and hghly sklled employees are substtutes n the manufacturng sector, they are complements n the servce sectors. As we have mentoned above, when estmatng a Leontef cost functon, the mpact of a rghthand-sde varable other than wages and output- on the labour demand for group s drectly gven by the respectve coeffcent. In both sectors, captal and medum sklled employees are complements wth smlar quanttatve relatonshps (.e. the pont estmate for servces les n the 95% nterval of the respectve estmate for manufacturng), but the demand for unsklled as well as for hghly sklled employees reman unaffected by a change n the captal stock. The same pattern arses, f a plant ncreases ts export share, whch rses sgnfcantly only the number of medum sklled employees. Wth respect to the dfferent types of nvestment, we observe dstnct mpacts for the two subsamples. Investment n nformaton and technology affects only labour demand n the servce sector, where both the number of unsklled and medum sklled employees n a plant shrnk after the mplementaton of new (or further) nformaton and technology equpment. By contrast, nvestment n producton unts as well as n property and buldngs rses labour demand n manufacturng for all but one skll groups, whereas all estmated parameters for the servce subsample turn out 8 Snce we need two years of the IAB panel to generate our proxy for captal, the regresson sample 14

16 to be nsgnfcant. Upgradng the techncal level of the machnery (such that t becomes upto-date) n the servce sector nfluences the demand for the three skll types n the opposte (albet expected) drecton: the number of unsklled employees falls, whle the number of medum sklled and hghly sklled employees rses. On the other hand, whether or not the techncal level of machnery s up-to-date has no mportance for the labour demand n manufacturng. For both subsamples, we fnd that the expected change n output nfluences the demand for all groups postvely, wth hghly sklled employees beng the least affected. Tables 4 and 5 lst the wage and output elastctes whch have been calculated accordng to Equatons (4)-(6) For both sub-samples, we observe that the own-wage elastcty decreases (n absolute values) wth skll, but the dfferences are statstcally nsgnfcant for manufacturng. By contrast, there s a great varaton n the estmated own wage elastctes for the servce sector. Whle the demand for unsklled workers rses by 27 % f ther wages decrease by 10%, we fnd that the group of the hghly sklled employees s not nfluenced by ther own wage. For each sector, dfferences n the output elastctes between the three skll groups are statstcally not sgnfcant. 11 Except for the medum sklled n the servce sector, all elastctes are statstcally not dfferent from one, mplyng constant returns to scale. does not nclude 1993, although the IAB panel starts n The elastctes have been calculated at the actual sample means (of manufacturng respectvely servces) of N, w and Y. We have used the average resdual of each employment equaton as an estmate for the α, whch s necessary to compute the output elastctes. 10 We wll not dscuss the (sem-)elastctes of the Z-varables, snce ther qualtatve effect s already obvous from the estmated coeffcents reported n Tables 2 and A test on η U nsklled Y =ηmedum Sklled Y delvered for manufacturng the statstc χ (1) = 1.13 ( (pvalue: 0.287) and for servces the statstc χ (1) = 0.01 (p-value: 0.932). A test on 2 2 ηmedum Sklled Y =ηhghly Sklled Y delvered for manufacturng the statstc χ (1) = 1.57 (p-value: 0.21) 2 and for servces the statstc χ (1) = 0.12 (p-value: 0.726). 2 15

17 Tables (6) and (7) report the mpacts on the share of the respectve skll groups, whch have been calculated accordng to Equaton (8). Snce the numbers denote actual changes of the shares (rather than share elastctes), each row sums up to zero. It s evdent, that the skll structure s largely drven by wages. The other varables, whch exhbt sgnfcant mpacts on the skll structure, do manly have the expected sgn. In both subgroups, nvestment n nformaton and technology ncreases the share of the hghly sklled and medum sklled employees at the expense of the unsklled. In the servce sector (only), the same pattern s observed f the techncal standard of the machnery becomes up-to-date. Rsng the captal stock reduces the share of the unsklled n both subgroups. The expected effect of an antcpated change n output.e. a shft towards the share of the unsklled occurs only n the servce sector; though t s very small, f output s expected to double n the current year, for example, then the share of the unsklled ncreases by 0.4%. 7. Summary A decrease n the demand for unsklled employees s a stylsed fact n the economc lterature; and explanatons for ths ongong trend nclude the skll-based technologcal change and the mpact of a rsng nternatonal trade. On the other hand, t s often argued that a less rgd wage structure could reduce unemployment of the unsklled. The emprcal evdence on these hypothess s mxed, often relyng on ncomplete data. Ths study has used the LIAB, a unque, lnked employer-employee data-set for Germany, to nvestgate the determnants of the employment structure wthn a plant. Our analyss has used nformaton of 880 West German plants between 1994 and 1997, whch cover approxmately 350,000 employees per year. Based on a Generalsed Leontef cost functon, we have estmated condtonal labour demand functons for unsklled, medum sklled and hghly sklled employees, where the regressons have been carred out separately for manufacturng and the servce sector. The 16

18 panel structure of the data has allowed to control for unobserved plant heterogenety, a fundamental problem of many studes on ths ssue, whch rely on cross-sectonal data. We have also endogensed the wages, and the rchness of our data-set provded us wth a set of approprate nstruments. We have dentfed a wthn-plant skll-based technologcal change va the mpact of captal, nvestment n nformaton and technology and upgradng of the techncal level of the machnery. Ths effect s stronger n the servce sector, but even there t s relatvely small. The degree of nternatonal trade, whch we have measured as the percentage of exports n total sales, s also found to have only a weak mpact on the skll structure wthn a plant. The major part of the skll structure s determned by the wages and for the servce sector by output. A 5% reducton of the wages of the unsklled, for example, rses the demand for ths group by 2.9 % n manufacturng and by 13.4 % n the servce sector. Ths reassures clams that a less rgd wage structure could reduce unemployment of the unsklled. The own wage elastctes decrease wth skll although the dfferences are not sgnfcant for manufacturng whch confrms earler results for Germany from Ftzroy and Funke (1998). We have found a labour hoardng effect.e. a shft towards the unsklled f output s expected to rse only n the servce sector, but agan the effect of our proxy for labour hoardng s qute small. To conclude, our results show that the major part of the skll structure s determned by wages, whle we have found only mnor mpacts of a skll-based technologcal change, of nternatonal trade and of short-run effects due to the busness cycle. 17

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23 Table 1: Descrptve statstcs of regresson sample Manufacturng Servces Varables Mean Std. Dev. Mean Std. Dev. N u Nm N u h w wm w h Y (mll. DM) K (mll. DM) Export Share Y Expected *100 Y Investment Dummes: IT Producton Unts Property, Buldngs Dummy: Techncal Level of Machnery Up-to-Date a The subscrpts u, m and h denote unsklled, medum sklled and hghly sklled respectvely. 22

24 Table 2: Constraned seemngly unrelated regressons for dfferent skll groups, manufacturng Unsklled Medum sklled Hghly Sklled Y w m w u 1.066*** (2.67) Y w h / w u (-0.18) Y w u / w m 1.066*** (2.67) Y w h / w m 0.260** (2.03) Y w u / w h (-0.18) Y w m w h 0.260** (2.03) 2 Y *** ** *** (-5.61) C (1.53) Export Share (1.45) 0.003*** *100 Y (2.97) Y Expected Investment-Dummes IT (-0.61) Producton Unts 0.614** (2.03) Property, Buldngs 1.947*** Dummy: Techncal Level of Machnery Up-to-Date (3.24) (0.94) (-2.34) 0.526*** (4.51) * (1.78) 0.006*** (2.60) (1.56) 1.605** (2.07) 3.329** (2.16) (-0.77) (-2.63) (1.41) (1.48) 0.001** (2.06) (1.58) (1.13) 0.563* (1.67) (0.06) χ² 83.34*** 70.63*** 34.91*** a Parameters constraned to be the same on: and Y w u / w h ; Y w h / w and m Y w m / w h. b Dependent Varables: Y w m / w and u Y w u / w m ; Y w h / wu N / Y where denotes unsklled (u), medum sklled(m) or hghly sklled (h). c Estmaton of Equaton (9),.e. all varables are dvded by Y and then the wthn-transformaton s appled. d 1955 observatons. Tme dummes addtonally ncluded. */ **/ *** denotes sgnfcance at the 10/ 5/ 1 % level. e 2 Hausman-Test aganst specfcaton wthout wthn-transformaton: χ (33) = , p-value :

25 Table 3: Constraned seemngly unrelated regressons for dfferent skll groups, servces Unsklled Medum sklled Hghly sklled Y w m w u 3.336*** (2.99) Y w h / w u (0.40) Y w u / w m 3.336*** (2.99) Y w h / w m * (-1.77) Y w u / w h (0.40) Y w m w h * (-1.77) 2 Y *** (-1.12) C (0.46) Export Share (0.89) 0.026*** *100 Y (6.66) Y Expected Investment-Dummes IT *** (-4.12) Producton Unts (-0.76) Property, Buldngs Dummy: Techncal Level of Machnery Up-to-Date (1.13) ** (-2.07) (-2.72) 0.750*** (3.70) * (1.76) 0.021*** (7.02) *** (-2.79) (0.23) ( 0.93) 5.451*** (4.51) (-1.62) 0.150*** (2.85) (1.32) 0.002** (2.54) (0.04) (1.33) (0.97) 1.581*** (5.03) χ² 91.85*** *** 58.66*** a 515 observatons. b See Table 1, footnotes a-e. c 2 Hausman-Test aganst specfcaton wthout wthn-transformaton: χ (33) = , p value :

26 Table 4: Employment elastctes for dfferent skll groups, manufacturng Unsklled Medum sklled hghly sklled Elastctes Wages: Unsklled -.572**.378*** Medum sklled.588*** -.500***.397** Hghly Sklled ** -.362** Output 1.262*** 1.608*** 1.091*** Captal ***.006 Export Share *.011 Y Expected.00002***.00004***.00003** *100 Y Sem-Elastctes Investment Dummes: IT Producton Unts.003**.005**.003 Property, Buldngs.008***.011**.009* Dummy: Techncal Level of Machnery: Up-to-Date */ **/ *** denotes sgnfcance on the 10/ 5/ 1 % level. 25

27 Table 5: Employment Elastctes for dfferent skll groups, servces Unsklled Medum sklled Hghly sklled Elastctes Wages: Unsklled *** 1.383***.404 Medum sklled 2.524*** ** * Hghly Sklled * Output * Captal ***.129*** Export Share *.007 Y Expected.0004***.0002***.0001** *100 Y Sem-Elastctes Investment Dummes: IT -.041*** -.014***.0003 Producton Unts Property, Buldngs Dummy: Techncal Level of Machnery: Up-to-Date */ **/ *** denotes sgnfcance on the 10/ 5/ 1 % level **.026***.049*** 26

28 Table 6: Impacts on the the employment share of dfferent skll groups, manufacturng ( N / N j ) X / X Unsklled Medum Hghly sklled sklled Wages: Unsklled -.210**.222*** Medum sklled.209*** -.262***.053* Hghly Sklled * -.041** Output Captal -.007***.008*** -.001*** Export Share *.0001 Y Expected -4.0e e-06 * -4.6e-08 *100 Y ( N / N j ) X Investment Dummes: IT ***.0010***.0002*** Producton Unts * * Property, Buldngs Dummy: Techncal Level of Machnery: Up-to-Date ** Calculated wth paramenters reported n Table (1) and at sample means of the respectve varables. */ **/ *** denotes sgnfcance on the 10/ 5/ 1 % level. 27

29 Table 7: Impacts on the the employment share of dfferent skll groups, servces ( N / N j ) X / X Unsklled Medum Hghly sklled sklled Wages: Unsklled -.922***.870***.052 Medum sklled.853*** -.710** -.143** Hghly Sklled Output Captal -.019* Export Share Y Expected.00004** *** *** *100 Y ( N / N j ) X Investment Dummes: IT ***.0047**.0020*** Producton Unts Property, Buldngs Dummes: Techncal Level Of Machnery Up-to-Date -.012***.012***.003*** Calculated wth paramenters reported n Table (2), at sample means of the respectve varables. */ **/ *** denotes sgnfcance on the 10/ 5/ 1 % level. 28