Chapter 11 INTERNATIONAL PRODUCTIVITY COMPARISONS AT THE INDUSTRY LEVEL Introducton by Hans Gersbach Alfred Weber-Insttut, Unverstät Hedelberg 1 As more and more ndustres experence the globalsaton of busness actvtes, measurng productvty performance has become an area of concern for companes and polcy makers n Europe, the Unted States and Japan. Ths paper provdes a non-techncal synthess of the productvty measurement methods used n a seres of comparatve ndustry studes. Such studes try to reach beyond standard aggregaton levels for productvty measurement. Snce most sectors at the two-dgt or three-dgt aggregaton level contan a varety of ndustres, whch can dffer n captal ntensty and technology used, productvty comparsons at the ndustry level have to take place at the fourdgt level. At ths level, the possbltes to have comparable output across countres are hgher and drect physcal productvty measurement can become feasble. However, the need to have consstent output and nput data and, f necessary, an ndustry-talored currency converson, s greater than at hgher aggregaton levels. The methodology we use to measure productvty at the ndustry level reles on two basc pllars. 2 Frst, we need a detaled value-added chan comparson across countres that yelds output and nput data. Second, we use an ndustry purchasng power party (ndustry PPP) concept to convert output values nto a common currency. The ndustry PPP s an mplct by-product f we can obtan a physcal productvty measure, or s derved and used explctly f value added or gross output s used as a productvty measurement. The data used n productvty comparsons s a combnaton of publcly avalable statstcal data and data from consultng actvtes. In ths chapter we provde a bref non-techncal overvew of the possbltes and dffcultes of measurement of productvty. We also gve a short summary of ndustry productvty results whch llustrate that productvty has converged n a few, but not n all, ndustres across countres. Moreover, we llustrate how GDP per capta dfferences can be traced back to productvty dfferences at the ndustry level. However, snce varatons n comparatve productvty dfferences are large, there s no possblty to nfer productve dfferences at the ndustry level from aggregate data. 293
Physcal productvty measurement Productvty s measured by computng the rato of output to nput. For example, average labour productvty s defned as the rato of the output produced n a country or an ndustry to the number of hours worked to produce that output. Dffcultes n measurng productvty arse both on the output and nput sdes. To overcome these dffcultes, a detaled value-added chan comparson s necessary. Wth respect to output, three basc measurement approaches can be appled: physcal unts, value added and gross output. The necessary value-added chan comparson obvously dffers wth the output concept used. Physcal productvty measurement n the servce sector Physcal output s an attractve measure, but t s not always feasble due to product varety as well as dfferences n qualty. In a number of cases, especally n the servce sector, physcal productvty s a promsng alternatve to value added or gross output comparsons. Physcal productvty needs a detaled comparson of the value-added chans n all the ndustres compared whch leads to a functonal productvty measurement. In ths approach t s assumed that an ndustry conssts of separate functonal actvtes whch each produce a relatvely homogeneous output. However, snce no meanngful revenue shares are avalable for the separate actvtes, the preferable Dvsa output ndex cannot be constructed and employment shares have to be used as weghts. To obtan such homogenous output measures, a seres of adjustments s requred n order to elmnate heterogenetes n the servces provded (see e.g. Baly, 1993; Gordon, 1993). Physcal productvty measures can be appled n a number of ndustres, such as telecommuncatons, the arlne ndustry or retal bankng. In the telecommuncaton ndustry for example, labour productvty smply conssts of a weghted average of access lne productvty and call (mnutes) productvty. Physcal productvty measurement n manufacturng ndustres Physcal productvty measurement s also possble n manufacturng ndustres although the requred degree of dsaggregaton usually ncreases. Even an ndustry such as steel requres a breakdown nto specfc product categores before physcal productvty measures become meanngful. Hence, such comparsons cannot usually be performed at the ndustry level, but rather at a company or product category level. Such productvty comparsons for specfc product categores n an ndustry can also help to calculate mplct ndustry PPPs as dscussed n the next secton. Productvty measurement wth value added or gross output Value-added chan comparsons and output and nput measurement An alternatve approach to physcal output s to use value added. Value added measures how much addtonal value s created n the market-place. Value added per unt of labour s a commonly used measure of productvty at the aggregate level (e.g. van Ark and Plat, 1993; van Ark, 1996; Baumol, Blackman and Wolff, 1989; Dollar and Wolff, 1993; Barro, 1991; O Mahony, 1992, Summers and Heston, 1991). Value added s defned as factory-gate gross output less purchased materals, packagng, contract work and energy. In many cases, one can use the value added 294
defnton from the Producton Census of Manufacturers whch also accounts for nventory changes. To obtan consstent data of value added across countres, some adjustments are requred, such as accountng for auxlary unts, adjustng for dfferences n reportng unts, etc. (for more detals, see Gersbach and van Ark, 1994). The advantage of usng value added s that t accounts for dfferences n vertcal ntegraton across countres. Furthermore, t accommodates qualty dfferences between products, as prce premums for qualty are translated nto hgher value added. However, the value-added concept suffers from a dfferent treatment of nputs such as materal and energy. Usng the value-added concept from the Producton Census also yelds the total number of employees. Usng the same source for output and nput data s one of the major advantages of the Census. Total labour nput has to be adjusted for dfferences n the number of hours worked by each employee. However, before value added and correspondng hours worked can be used for productvty comparsons, a detaled value-added chan comparson of ndustres s necessary. Although the defntons of the ndustres n Germany, Japan and the Unted States are n some respects smlar, there are stll mportant dfferences across these countres concernng the manufacturng actvtes takng place wthn each ndustry. 3 These dfferences relate to: the mx of fnshed goods on the one hand, and parts and components on the other; the range of fnshed goods; treatment of ndustral and non-ndustral servces, and the coverage of dstrbuton and other non-manufacturng actvtes. The frst two ponts are easy to solve and take nto account; examples can be found n Gersbach and van Ark (1994). We wll dscuss the complexty of the last ssue. In order to base comparsons on the same value-added defnton across countres, purchased ndustral and non-ndustral servces could not be excluded from value added. In partcular, the amount of non-ndustral servces can dffer substantally across ndustres and also for smlar ndustres across countres. In the manufacturng ndustres studed, purchased non-ndustral servces accounted for between 12 and 40 per cent of value added. The most mportant components of nonndustral servces are expenses on communcatons and advertsng, transportaton and warehousng. The hghest percentage shares were for non-durable consumer goods ndustres (e.g. for soap and detergents), where advertsng plays a key role. The queston now arses as to whether these dfferences n the relatve amount of purchased nonndustral servces across countres create bases n the productvty measures. The frst potental bas s that an ndustry n one country outsources more servces whle the correspondng ndustry n the other country does more n-house. For example, the latter ndustry may tself perform certan downstream actvtes such as transportaton and dstrbuton. Although the overall amount of servces used n the value chan s not affected by dfferences n outsourcng across countres, these dfferences between countres may ntroduce a bas n the productvty measurement of a sngle component n the chan. 295
The necessary adjustment n ths case can affect output, ndustry PPPs and employment measurement. Consder, for example, the beer ndustry: the dstrbuton systems for beer n the three countres are dfferent. In the Unted States, manufacturers sell to dstrbutors who n turn serve retalers. However, n Germany and Japan, between 50 to 70 per cent of output s delvered drectly to restaurants and shops, resultng n smaller and more complex shpments and requrng more manpower n the sales force. Snce we used physcal productvty, an estmate for the number of employees engaged n delvery of fnshed goods was removed from the analyss: these numbers were estmated at 10 per cent n the Unted States, 14 per cent n Japan and 21 per cent n Germany. If productvty was measured n terms of value added, value added and ndustry PPPs have to be taken at the factory gate ether ncludng or excludng dstrbuton expenses n both countres. A second bas may occur f one ndustry purchases more servces than the correspondng ndustry n the other country rrespectve of the dfferent degree of outsourcng. For example, the advertsng ntensty n a gven ndustry may be hgher n one country than n another, or servces may smply be more expensve. The mpact of ths second source of bas on the productvty measures depends on the queston of whether or not these servces prmarly reflect qualty dfferences n otherwse homogenous goods, for example, better consumer nformaton or more convenent delvery. An error s ntroduced when dfferences n purchased servces are due to dfferences n the effcency of usng these servces or when servces are relatvely more expensve n one country than n another for reasons other than greater consumer beneft. The productvty of the ndustry that uses more of the purchased nonndustral servces s overstated compared to the other country. For aggregate manufacturng, evdence to show that the amount of non-ndustral servces dffers substantally across countres s rather weak. For the Unted States, purchased servces accounted for 25.6 per cent of ntermedate nputs n manufacturng n 1987. The correspondng percentages were 23.8 per cent for Japan and 25.9 per cent for Germany (van Ark, 1993). It should be emphaszed that, n the case of Germany, Census estmates are based on nformaton for legal unts (enterprses) and not on an actvty bass as n the nput-output tables. Accordng to the German Census, the share of servce nputs n total ntermedate nputs s 18.6 per cent. Germany s generally known for ts relatvely small share of outsourcng of servce actvtes (e.g. Ochel and Schreyer, 1988). The dscusson on the use of value added shows the potental ptfalls snce one can not account drectly for the effcency of all the nputs used. Moreover, as mentoned n the followng secton, the need for double deflaton can dwarf the results. If nput prces are substantally dstorted, the use of value added can lead to substantal mstakes. Hence, the thrd approach, that whch has to be appled for the food ndustry, s to use shpment values requrng that one look at the same part of the producton chan across countres. Our prmary focus s on labour productvty snce labour s the prmary factor n value added. A dfferent measure of productvty s total factor productvty (also called multfactor productvty). Ths s computed as the rato of output to an ndex of both captal and labour nputs rather than smply labour. Its advantage s that t explctly ncorporates the contrbuton of captal to the producton of output, where captal s the stock of machnery and structures. Total factor productvty requres that an ndustry PPP s also needed to translate captal nto a common currency makng t necessary to estmate the mx and nternatonal prce comparsons of machnery and structure expendtures. 296
In our cross-country comparsons, we do not adjust for dfferences n the mx of labour nput as s done, for nstance, n the BLS multfactor productvty seres usng changng weght ndces (see Dean, 1996). Internatonal comparablty of labour skll data s dffcult to acheve and these data are treated n cross-country comparsons as explanatory factors. Industry PPPs The most mportant complcaton arses from the fact that value added or gross output s not denomnated n the same currency across countres. As a result, ths approach requres a mechansm allowng value added to be converted to a common currency. We use the ndustry PPP concept. The use of ndustry PPPs s motvated n a smlar way to the unt value ratos of the ndustry-oforgn approach, and exstng unt value ratos can be used n several ndustres as a startng pont. An ndustry PPP represents the number of unts of dfferent currences requred to purchase an equvalent amount of ndustral output. Hence, product prces of ndustres have to be measured at the factory gate. For ndustres that produce only one homogenous good, the ndustry PPP s smply the relatonshp of the unt prces at the factory gate. Suppose the factory-gate prce of a unt n the Unted States was US$1, whle the prce of the same unt n Germany was DM 2. The ndustry PPP would be DM 2/US$1. Usng the ndustry PPP leads to the same result as the drect physcal performance measures f there s only one homogenous product. The ndustry PPP-method can, however, handle more general cases where drect physcal performance measures are mpossble. The calculaton of ndustry PPPs requres comparable products or servces produced by the operatons of a gven ndustry n all three countres, e.g. a tonne of steel of a certan type. The prce of the standard tem n DM n relaton to the prce n dollars yelds a prce rato for the Unted States- Germany comparson. The ndustry PPP s then defned as a blateral Fsher ndex, by calculatng a weghted average of the prce comparsons. Specfcally, the ndustry PPP for the Germany-Unted States comparson s gven as follows: Industry PPP s U GU / = = 1 s = 1 G p y U p y U U G and U denote the two countres, Germany and Unted States. p G, p U are the factory prces of good n the two countres. y U s the quantty of good produced n the Unted States. Hence, the ndustry PPP s derved by usng the US quantty weghts. Smlarly, one can derve an ndustry PPP at quantty weghts for Germany: Industry PPP s G GU / = = 1 s = 1 G p x U p x G G The fnal ndustry PPP used for the productvty comparson s the geometrc average of both prce ndces: 297
G Industry PPP = IndustryPPP GU IndustryPPP U GU / / GU / In the ndustry studes of the McKnsey Global Insttute (1992, 1993), ndustry PPPs were calculated and modfed for nne manufacturng case ndustres. Fve methods were consdered to arrve at ndustry PPPs, whch wll be dealt wth subsequently: New ndustry PPPs were obtaned from surveys specfcally carred out for the studes. Exstng product UVRs based on Census nformaton were adjusted for dfferences n terms of product mx and product qualty across countres: adjustment of exstng UVRs for dfferences n product mx; adjustment of exstng UVRs for dfferences n product qualty; reshufflng product matches on the bass of ndustry expert nformaton; Indrect methods were used to obtan proxy PPPs, for example by usng company estmates on cost and proft or by adjustng ICP expendture PPPs for dstrbuton margns and taxes. PPPs were adjusted for prce dfferentals of ntermedate nputs. Implct PPPs were obtaned usng physcal productvty comparson. The choce of method depends manly on data avalablty and qualty. In most cases at least two dfferent avenues were taken. In the followng we gve some specfc examples. Example: mx adjustments to the exstng UVR n the automotve sector Product mx was defned accordng to the European market segmentaton, whch classfes cars accordng to sze and basc features. Ths standard s normally used only n European countres, but t does provde a world-wde yardstck aganst whch cars from other countres can be classfed. After classfyng cars n Japan and the Unted States accordng to the standard market segmentaton, and applyng producton value weghts from standard automotve statstcs to each of the market segments, the approprate mx adjustment was obtaned. The adjustment for mx showed that n 1987 Japanese cars were on average 37 per cent lghter than US cars. By 1990, ths adjustment was smaller (29 per cent), reflectng the shft of Japanese producers toward larger luxury cars. A smlar but smaller adjustment n the same drecton was made for the Germany/US comparson (11 per cent). Example: adjustment of exstng UVRs for dfferences n product qualty In the ndustry studes, the qualty concept appled was related to the valuaton of the product by users, nsofar as t could be connected to characterstcs of the product tself or the producton process. PPPs were adjusted for qualty dfferences where these were recognsed by consumers n such a way that they were wllng to pay a prce premum, and where these qualty dfferences were the result of dfferences n the products and producton process, rather than dfferences n taste across countres (see Trplett, 1996, for a dscusson). The remanng notons of qualty were treated as dfferences n consumer preferences, whch may explan the dfferences n productvty but whch are not used to adjust the productvty measure tself. Moreover, qualty premums were only measured n markets where two products under consderaton are sold wth equal access. Otherwse qualty premums and prce markups are not dstngushable. 298
There are substantal dfferences n relablty, functonalty and basc qualty among the cars produced n the three countres wthn each ndvdual market segment. The qualty dfference s defned as the prce dfferental whch a consumer wth unrestrcted access to foregn products would be wllng to pay for a car of the same category, based on hs/her percepton of qualty dfferences such as relablty and functonalty, etc. In the Japan/Unted States comparson, the qualty adjustment on the bass of ths procedure was 12 per cent, whch was the prce premum whch Amercan consumers wth ready access to all models were wllng to pay for a Japanese car over a smlar US model n 1987. By 1990, ths prce premum had been reduced to 8 per cent. In Germany, consumers valued the qualty of German-made cars almost equal to that of Japanese cars,.e. they commanded a 10 per cent qualty premum over US cars n 1987. Ths qualty premum had shrunk to about 5 per cent n 1990. Ths procedure reles on a market valuaton to reveal the value of product attrbutes to consumers, and can only be used when products are close substtutes, markets are compettve and customers have unrestrcted access to the entre product range. Example: Dffcultes n qualty adjustments What, however, f tastes dffer? If dfferent buyng patterns at the same relatve prces exst across countres, measured qualty prema can go n opposte drectons n dfferent countres. In such cases productvty comparsons are dstorted by dfferences n consumer tastes whch can make t almost mpossble to account for qualty dfferences. Typcal examples can be found n consumer goods ndustres such as food and beverages. Probably the most famous example s beer: many observers beleve that German beer tastes better than US beer. The usual argument nvoked to extol the qualty of German beer s that Amercan consumers wllngly pay more than twce the prce of a regular Amercan beer to sample German beers. However, the prce of mported beer n the Unted States reflects marketng decsons to sell mports to small segments of the publc that place the hgheest value on the dfferent taste and, above all, the mage of foregn beers. Ths market segment exsts n Germany, where foregn beers also fetch hgher prces. A further complcaton n qualty adjustment arses when output and nput dffer n qualty. For nstance, the productvty of automotve assembly operatons depends on the qualty of parts (defects, ease of assembly, etc.). Smultaneous qualty dfferences at the output and nput levels requres estmatng two separate (or nterrelated) qualty prema n order to correctly measure ndustry productvty (see Trplett, 1996 for a detaled dscusson). Example: Adjustng ICP PPPs n food processng An ndrect method s to make use of exstng expendture ICP PPPs from the Internatonal Comparsons Project (ICP). In order to derve ndustry PPPs from fnal expendture PPPs, certan adjustments are requred. Fnal expendture PPPs reflect prce ratos at the retal level and need to be adjusted for dfferences n relatve dstrbuton margns and dfferences n sales and value-added taxes. In addton, one needs to check the mpact of ncluded mport prces and excluded export prces n expendture PPPs. In food processng, ICP expendture PPPs were adjusted to factory-gate prces by makng the followng adjustments: frst, we used Fsher blateral prce ndces; second, dstrbuton margns of wholesalers and retalers were derved for the three countres on the bass of propretary nformaton; thrd, where necessary, food product prces were adjusted for dfferences n taxes on sales and value added. These appeared to have approxmately the same effect n Japan as n the Unted States, but there was a sgnfcant dfference n Germany. Adjustng for the hgher taxes n Germany brought the DM/US$ PPP down slghtly. These adjustments were made for ndvdual ndustres n processed foods (for example, meat, dary, etc.). An aggregate PPP was obtaned by 299
weghtng the ndustry PPPs by the value of shpments taken from the Census. The overall ndustry PPPs amounted to DM 2.07/US$ and Yen 252/US$. Results n the manufacturng sector Industry PPPs for the nne manufacturng ndustres are shown n Table 1. Table 1 reveals that there are wde varatons among ndustry PPPs. Compared to the average nomnal exchange rate n 1990 (Germany/Unted States: DM 1.62 /US$; Japan/Unted States: Yen 145/US$), the ndustry PPPs for Germany are generally above the exchange rate reflectng the commonly held vew that the German currency was overvalued aganst the dollar at that tme. The Japanese ndustry PPPs are dstrbuted around the exchange rate, wth beer and food processng showng very hgh prce levels. Table 1. Industry PPPs n 1990, blateral Fsher ndex Case studes Industry PPPs Germany/Unted States Japan/Unted States Auto cars 2.24 114 Auto parts 2.24 120 Metal-workng 2.18 138 Steel 1.90 170 Computer 2.06 154 Consumer electroncs 2.97 115 Detergents 2.02 188 Beer 2.23 210 Food 2.06 241 Source: Baly and Gersbach (1995), taken from McKnsey Global Insttute (1993). Second, value added per hour worked were calculated for each ndustry and translated nto dollars usng the ndustry PPPs. The results are gven n Table 2. Lookng frst at the German-US comparsons, labour productvty n 1990 was vrtually dentcal for metal-workng and steel. Table 2 also reveals that productvty n Germany s lower than productvty n the Unted States n sx of the ndustres. In addton Table 2 shows that productvty n operatons located n Japan s substantally ahead of productvty n Germany n fve ndustres. Turnng to the Unted States-Japan comparson, the wde varatons n productvty relatve to the Unted States are strkng. In food processng, for example, operatons n Japan account for only one-thrd of the US level of output per hour. Japanese operatons have hgher productvty n fve of the nne case studes. However, the relatvely small gaps n automotve assembly and parts show that recently US ndustres have caught up wth the hgh productvty of Japanese ndustres. Table 2. Labour productvty of case studes n 1990 Value added at ndustry PPP per hour worked (Unted States = 100) Industres Relatve productvty Germany Japan Unted States Auto cars 66 116 100 Auto parts 76 124 100 Metal-workng 101 119 100 Steel 100 145 100 Computers 89 95 100 Consumer electroncs 62 115 100 Detergents 88 94 100 Beer 44 69 100 Food 76 33 100 Source: Baly and Gersbach (1995). 300
The productvty pcture n 1990 shows that German manufacturng ndustres were laggng n terms of productvty (see also van Ark, 1996). Over recent years, there are sgns of a recovery and a slow catchng-up. The relatonshp between aggregate and ndustry productvty levels Productvty s the rato of the output of goods and servces to the nput of resources used to produce them. At the natonal level, aggregate productvty s an mportant ndcator of economc strength; for any level of employment, the hgher productvty, the hgher the populaton s materal lvng standards. Hence many studes try to measure productvty at the natonal or sector level, usng purchasng power partes for the whole economy (e.g. Baumol, Blackman, and Wolff, 1989; Dollar and Wolff, 1993). Naturally, snce many polces affect specfc parts of the economy dfferently, t s nterestng, and necessary, to decompose aggregate GDP per capta dfferences across countres nto dfferences across smaller and smaller parts of economes. Bascally, GDP per capta dfferences can be decomposed n sx steps. Frst, the number of people employed as a fracton of the total populaton may be dfferent across countres. Second, annual workng hours per employed person may vary. Thrd, dfferences n output per hour worked may occur snce ether the non-market sectors (government, educaton, health care, etc.), or the market sector, or both, exhbt dfferent labour productvty across countres. Fourth, wthn the market sector, labour productvty dfferences can arse due to dfferent performances of sectors (servce, manufacturng, etc.). Ffth, dfferences n the productvty of sectors can be caused by productvty dfferences at the ndustry level. Sxth, countres can have the same labour productvty at the ndustry level, but have dfferent levels of aggregate productvty because one country's employment mx s shfted towards hgh-productvty 4 ndustres or sectors the so-called mx effect. Usng the 1990 PPP benchmark, the Unted States had the hghest GDP per capta n 1990 wth Germany, Japan and France 14 to 19 per cent lower, and the Unted Kngdom about 25 per cent lower than the Unted States (Table 3). The man conclusons that can be drawn from a decomposton of these dfferences are the followng: Table 3. GDP per capta, 1990 US dollars (US = 100) Country par 1990 301 1990 US =100 US$ (US = 21 450) France 17 450 81 Germany 18 550 86 Japan 17 490 82 Unted Kngdom 15 750 73 Source: OECD Natonal Accounts (1992). Frst, f we move to GDP per person employed, the Unted States stays ahead, however France's productvty level s slghtly lower. The dfference between the Unted States and Germany amounts to 14 percentage ponts, whle Japan and the Unted Kngdom are more than 20 per cent lower than the US level. Second, movng to dfferences n GDP per hours worked: usng the 1990 PPP benchmark would place France and Germany 10 and 6 percentage ponts ahead of the Unted States, whle the productvty of the Unted Kngdom and Japan s 19 and 33 per cent lower than the US level.
Thrd, when the non-market components (government, health care, educaton) are removed from value added and employment, the estmated relatve productvtes compared wth the Unted States are lower for the market sectors than for the overall economes (Table 4). To calculate the productvty of the market sector a new blateral Fsher PPP for ths sector has to be derved, buldng up from the exstng blateral prce comparsons of basc headngs. Table 4. Labour productvty n market economes, 1988 Value added at PPP per FTE and per hour worked (US = 100) Country par 1988 Value added per FTE 1988 Value added per hour worked France-Unted States 84 98 Germany-Unted States 83 95 Japan-Unted States 61 52 Unted Kngdom-Unted States 72 77 Source: Own calculatons usng OECD ISDB and BLS, BEA, Eurostat. Based on blateral Fsher PPPs. Fourth, nternatonal productvty dfferences n the market sector are n most cases translated nto dfferences n the productvty of sectors 5. The drecton of the gaps s consstent wth the dfferences at the aggregate level, at least compared to the productvty leader, the Unted States For nstance, France, Germany, the Unted Kngdom and Japan show lower aggregate productvty n manufacturng and servces than the Unted States (Tables 5 and 6). 6 However, the productvty dfferences at the sector and ndustry levels for France and Germany would suggest a lower aggregate productvty for the market sector than actually measured. Table 5. Labour productvty of manufacturng, selected years 1970-93 Value added at ndustry PPP per hour worked (US = 100) Country par 1970 1975 1980 1985 1990 1993 France-Unted States 73 79 90 90 91 88 Germany-Unted States 76 84 92 88 83 80 Japan-Unted States 43 52 64 68 76 74 Unted Kngdom-Unted States 51 53 52 58 66 70 Source: van Ark (1995); Gersbach and van Ark (1994). Updated from 1990 usng nformaton from the US Bureau of Labor Statstcs. Table 6. Labour productvty n servces US = 100 Telecom Retal bankng Country Arlnes General merchandse Restaurants 1989 1 1989 2 1989 retalng 1987 1987 France 1 72 56 69 104 Germany 72 50 68 96 92 Japan 66 44 Unted Kngdom 72 38 64 82 1. Average productvty of the European arlne ndustry. 2. Total factor productvty. Source: Baly (1993); McKnsey Global Insttute (1992). Ffth, the varablty of productvty dfferences at the ndustry level s substantally hgher than any dfferences at the aggregate or sector levels. As llustrated by our examples, the order of magntude of labour productvty dfferences can reach 40-50 percentage ponts (Tables 2 and 6). Moreover, at the ndustry level, labour productvty for Japanese manufacturng ndustres s n some cases hgher than that for the Unted States. In contrast, France, the Unted Kngdom and Germany exhbt almost no leadershp n productvty at the ndustry level. 302
Hence, naton-specfc factors appear to be domnant n explanng productvty dfferences. However, for Japan, ndustry-specfc factors n the manufacturng sector are more mportant n the understandng of comparatve performance. However, the relatvely small sample of ndustres does not allow sgnfcant conclusons to be drawn on the relatonshp of country- and ndustry-specfc factors. Furthermore, large varatons of relatve labour productvty n ndustres show that aggregate productvty gves a very ncomplete pcture of the technologcal and productvty characterstcs across countres. Fnally, mx dfferences do not play a very large role for large countres: they can explan only 12 percentage ponts of aggregate dfferences. Thus, aggregate labour productvty dfferences have to be explaned manly by productvty dfferences at the ndustry level. For Germany, however, the mx effect can help to reconcle relatve hgh productvty for the market economy and lower productvty at dsaggregated levels. NOTES 1. Ths chapter draws from a seres of McKnsey Global Insttute ndustry studes, and s based on research at the unverstes of Basel and Hedelberg. 2. For overvews on productvty measurement at the more aggregate level, see van Ark (1996) and Kuroda, Motohash and Kazushge (1996). 3. The dfferences between the countres are to some extent caused by the fact that the basc statstcal unt n the German Kostenstrukturerhebung s the legal unt compared to the local unt n the Japanese and US Censuses. As a result the coverage of actvtes n a German ndustry s more dverse than n Japan and the Unted States. 4. Hgh productvty means that value added per hour worked s hgher than average. 5. There s no unque language for decomposng the data on an economy. We apply the followng scheme: total economy, market economy (excludng government, educaton, etc.), sectors (e.g. manufacturng), branches (e.g. basc metals), and ndustres (usually a collecton of four-dgt SIC codes, e.g steel). 6. For manufacturng, both approaches: employng unt value ratos (UVRs); or usng expendture purchasng power partes (EPPPs) yeld drectonally the same results (van Ark, 1995; Hooper, 1996). 303
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