Technology Adopion Coss and Produciviy Growh: The Transiion o Informaion Technology By James Bessen* 10/01 Absrac: Using wo panels of U.S. manufacuring indusries, his paper esimaes capial adjusmen coss from 1961 o 1996. I find ha from 1974-83 adjusmen coss rose sharply hey more han doubled from abou 3% of oupu o around 7%. Moreover, his increase is specifically associaed wih a shif o invesmen in informaion echnology. Bu such large adopion coss imply ha he Solow residual mismeasures produciviy growh: adopion coss are resource coss represening an unmeasured invesmen. I find ha when his invesmen is included, produciviy grew abou 0.4% per annum faser han official measures during he 70 s and early 80 s, reducing he size of he produciviy slowdown. Indeed, esimaed produciviy growh raes were roughly he same from 1974-88 as from 1949-73. Thus echnology ransiions criically affec produciviy growh measuremen. Keywords: Technological change, produciviy, adjusmen cos, informaion echnology JEL codes: O30, O47, E22 James Bessen Research on Innovaion jbessen@researchoninnovaion.org *Thanks o Diego Comin, Bob Hun, Boyan Jovanovic and several referees for helpful commens. Thanks o Randy Becker, Bill Gullickson, Shelby Herman and Seve Rosenhal for daa and informaion abou daa.
1 Technology Adopion Coss and Produciviy Growh - Bessen 9/01 I. Inroducion The lieraure on echnology adopion is filled wih examples of abrup echnology ransiions. For example, U.S. railroads shifed from using mainly seam locomoives o mainly diesel locomoives in a decade [Mansfield, 1968, p. 175]. The sandard echnology adopion curve ( diffusion curve) is S-shaped very rapid adopion afer a long, slow iniial period. Moreover, wih general purpose echnologies [Helpman, 1998], many differen indusries may adop new echnologies a once. For example, many indusries adoped elecriciy-based echnologies during he 1920 s and 30 s and many adoped elecronics-based echnologies during he 1970 s and 80 s. Such Schumpeerian echnology ransiions pose a problem for produciviy measuremen because such new echnologies are usually new goods, ha is, hey are no perfec subsiues for earlier echnologies. Specifically, whole new echnologies may incur large adopion coss because hey involve learning new skills, implemening new forms of organizaion, and developing complemenary invesmens. Indeed, reviewing he recen lieraure on he impac of compuers, Brynjolfsson and Hi [2000] find ha complemenary organizaional invesmens may be much larger han he invesmen in compuer equipmen iself. Also, informaion echnology, in paricular, ofen involves cusomizaion and cusom-sofware, some of which remains unmeasured in official saisics. Because such complemenary invesmens appear in official produciviy saisics only as resource coss wihou he corresponding conribuion o invesmen (and hence oupu), produciviy may be mismeasured. This paper esimaes hese adopion coss in he U.S. manufacuring secor from 1961-96 and i calculaes revised produciviy growh esimaes based on hese. Using wo panels of indusry daa (one using 4-digi SIC indusries, he oher 2-digi), I obain wo main empirical resuls. Firs, I find ha capial adjusmen coss rose sharply during he period from 1974-83, a he same ime as invesmen sharply shifed oward informaion echnology (IT). Second, I find ha his rise in coss is specifically associaed wih his change in echnology. In oher words, hese are coss of adoping new echnology. Applying adjusmen cos esimaes from each panel o BLS produciviy measures for he manufacuring secor, I obain esimaes of produciviy growh from 1974-83 of 0.91% and 0.94%, compared o an official esimae of 0.52%. For 1974-88 he esimaes are 1.42% and 1.53%, compared o 1.13%. These growh raes compare favorably o he official growh measures from 1949-73 of 1.52%, suggesing ha any produciviy slowdown was brief a mos.
2 Technology Adopion Coss and Produciviy Growh - Bessen 9/01 Implicaions and relaionship o he lieraure Several sudies have presened models where adopion coss accoun for he produciviy slowdown of he 70 s, including Hornsein and Krusell [1996], Greenwood and Yorukoglu [1997] and Greenwood and Jovanovic [1998]. In hese models, adopion coss are assumed o increase wih he rae of embodied echnical change. Several auhors, including Gor and Wall [1998], Greenwood e al [1997], Hercowiz [1998], and Hulen [1992], have also considered he effec of embodied echnical change on produciviy measuremen during he 70 s and 80 s. Many of hese sudies infer a rae of embodied echnical change from he slow drif beween official price deflaors for producer s durable equipmen and Gordon s [1990] alernaive esimaes. Bu Gordon s qualiy-adjused price deflaors are unlikely o capure he full value of adopion coss, which are complemenary invesmens. 1 And he resuling esimaes are qualiaively quie differen. Gordon s drif grows seadily a abou 3% a year during he poswar period. My esimaes of adopion coss surge sharply in he 70 s (see Figure 3 below). Several oher sudies have used calibraed models o explore adopion coss (or organizaional coss), including Rober Hall [2000] and Michael T. Kiley [1999, 2000]. Again, he paern emerging from my direc esimaes is generally differen. The magniude of his acceleraion is imporan no only because i affecs he calculaion of produciviy growh. Several of hese models also relae he rise in adopion coss in he 70 s o changes in wages, he skill premium and sock prices. For insance, Greenwood and Yorukoglu speculae ha he growh rae of embodied echnical change acceleraed 2% per annum during he 70 s. From his, heir model implies a roughly 1.5% increase in learning coss as a share of GDP and a subsanial increase in wage inequaliy. Ye my esimaes sugges ha adopion coss increased by 4% of GDP in he 70 s. The implied effec on wage inequaliy, sock prices and oher variables should also be correspondingly larger. Anoher lieraure has aemped o assess he impac of IT on produciviy, including Bernd and Morrison [1995], Chun [2001], Jorgenson and Siroh [1999, 2000], Oliner and Sichel [1994, 2000] and Whelan [2000]. This lieraure suggess ha he reurns o IT invesmen were low or non-exisen during he 70 s and early 80 s and have increased since hen. This is consisen 1 Mos of he componens of Gordon s index are consruced using he mached model mehod. Some componens use hedonic regressions. Under cerain condiions, hedonic deflaors may parially reflec adopion coss (see below), bu his only capures a porion of he adopion cos and i only applies o a small porion of oal invesmen.
3 Technology Adopion Coss and Produciviy Growh - Bessen 9/01 wih my resuls for convenionally measured produciviy. Specifically, omission of adopion coss ends o undersae he effec of IT on produciviy growh during he 70 s. Skepicism abou he role of IT On he oher hand, he idea ha IT adopion coss may be relaed o he produciviy slowdown has generaed some skepicism for several reasons: 1. IT invesmen is posiively associaed wih produciviy growh. Comin [2000] finds ha indusries ha inves in IT a a higher level (relaive o invesmen in oher goods) end o have higher produciviy growh. Bu in my model, adopion coss are associaed wih he ransiion o new echnology. Tha is, measured produciviy growh is relaed o he rae of change in invesmen, no he level of invesmen. An indusry ha invess heavily in IT oday may have high produciviy growh, bu i may also have incurred adopion coss a some poin in he pas when, perhaps, i made iniial heavy invesmens in IT. 2. A second reason for skepicism is ha IT equipmen and sofware only have a small facor share, abou a 3% share of cos even in 1999. This raises he quesion wheher such a small facor can affec produciviy much. For insance, Oliner and Sichel [1994] argue ha compuers were unlikely o exer much effec on produciviy during he 80 s because hey had a small cos share. Bu his view implicily assumes ha informaion echnology eners he producion process wihou affecing oher inpus, as some sor of surgical subsiuion. Bu much evidence suggess, insead, ha compuers hemselves represen only a small par of he oal change enabled by informaion echnology. There is much evidence ha IT is associaed wih deep, complemenary organizaional change [Brynjolfsson and Hi, 2000, Black and Lynch, 2001]. Moreover, he new echnology is inroduced in informaion sysems, applicaions ha involve compuers, bu also many oher invesmens. For example, in newspapers, compuers replaced ypewriers in he newsroom. Bu his permied complemenary ransiions from ho meal ype o phooype and from leerpress prining o offse prining. And hese changes ofen required enire new prining plans. Thus compuers (or IT equipmen) comprised only a small par of he oal invesmen in new echnology, albei he criical enabling invesmen. Boh he adopion coss and he subsequen produciviy gains were a funcion of he enire invesmen, no jus he invesmen in compuers per se. Below I measure he adopion coss of oal invesmen, bu I also find an associaion beween hese coss and IT spending.
4 Technology Adopion Coss and Produciviy Growh - Bessen 9/01 3. A final reason for skepicism is he apparen recen reversal of he Solow paradox. Alhough during he 70 s and 80 s compuers were found everywhere bu in he produciviy saisics, he las several years have had rapid growh in real IT spending accompanied by srong produciviy growh. If he produciviy slowdown resuled from adopion coss, hen why don hose same adopion coss cause a slowdown now? Bu he relaionship beween adopion coss and IT spending has likely changed beween 1999 and 1979. The regression analysis below provides some evidence ha he IT surge of he lae 90 s did no have he same effec on capial qualiy as earlier spending. In fac, he saisical relaionship beween invesmen and produciviy growh of he previous hree decades appears o change during he 90 s. This effec is no surprising for a leas wo reasons. Firs, adopion coss for IT are likely a funcion of he number of compuers (or compuer erminals), no he power of hose compuers. The cos of learning a new 1,000 MHz PC sysem is no likely o be 40 imes greaer han he cos of learning a 25 MHz PC sysem in 1985. In fac, he learning cos on he new sysem may well be less because he greaer compuer power suppors beer sofware. Alhough he 70 s saw rapid growh in he number of compuers and compuer erminals, mos of he IT surge in he lae 90 s, on he oher hand, arose from greaer compuing power per compuer and more sofware per compuer. Figure 1 chars he real share of IT invesmen in oal invesmen; his surged in he lae 90 s. The char also shows he share of nominal invesmen spen on IT hardware. This rose sharply from 1974 o 1983 bu has remained more or less fla since hen. Now alhough he cos of compuing power has dropped sharply since he mid-80 s, he cos of personal compuers has fallen only slighly [Bernd and Rappapor, 2000]. This means, roughly, ha he number of compuers purchased relaive o oal invesmen has no changed much since he mid-80 s. Hence his surge in compuing power migh no increase adopion coss. Furhermore, par of he surge in he lae 90 s consiss of greaer sofware spending. Bu his migh well be associaed wih reduced adopion coss. Beer sofware is user-friendly and easier o learn. Also, some porion of adopion coss consiss of cusomizaion and programming performed by non-programmers. 2 Greaer sofware spending may represen a parial subsiuion of purchased sofware for his aciviy. 2 The conribuion of programming personnel is capured as sofware in he mos recen official saisics [Parker and Grimm, 2000], bu he aciviy of non-programmers is no. Hisorically, few personnel using compuers in he early years had compuer-specific job iles, and oday much cusomizaion and programming aciviy is sill performed by oher occupaions, e.g., economiss who are SAS programmers.
5 Technology Adopion Coss and Produciviy Growh - Bessen 9/01 More generally, much of his discussion has been framed as an examinaion of wheher he simulaneous surge in produciviy and IT invesmen represens a New Economy or jus a emporary supply shock. The resuls here sugges a somewha differen picure: we are now well ino he hird decade of boh srong produciviy growh and srong IT invesmen. The nex secion exends he Solow accouning framework o include adjusmen coss. Then in Secion III, I use his framework o obain esimaes. Secion IV applies hese esimaes o he problem of accouning for produciviy growh and Secion V concludes. II. Adopion Coss and Technology Transiions Adjusmen Coss Adjusmen coss represen a diversion of oupu o producing a complemen of invesmen in capial goods. A ime (1) ( ) c Y Y = 1 * where Y is acual oupu, Y* is poenial oupu, and c is he percenage rae of adjusmen coss, a funcion of invesmen. The absolue magniude of he adjusmen cos is * Y c. The poenial oupu can be wrien using a convenional producion funcion (2) ),, ( * M L K F A Y = where A represens produciviy, K is capial, L is labor and M is maerials and energy. I assume consan reurns o scale and compeiive markes in L and M. Taking logs, differeniaing and approximaing assuming ha c << 1 (so ha ( ) c c 1 ln ), (3) M F F M L F F L d c d K M L A Y β α = π β α π + β + α + 1,, ˆ ˆ ˆ ˆ ˆ where ^ designaes a growh rae and capial is assigned a residual oupu share. The measured Solow residual is hen (in coninuous ime) (4) d d c A K M L Y Z = π β α ˆ ˆ ~ ˆ ~ ˆ ~ ˆ ˆ where α ~ and β ~ are esimaes of he labor and maerials elasiciies, respecively. In discree ime,
6 Technology Adopion Coss and Produciviy Growh - Bessen 9/01 hese esimaes are usually calculaed as he average oupu share (average of he beginning and ending period), providing a Tornqvis index of produciviy growh. Equaion (4) shows ha he Solow residual growh, Ẑ, will be a biased esimaor of rue produciviy growh if c changes over ime. In normal circumsances where life proceeds smoohly along a balanced growh pah, c migh plausibly change lile. However, when firms make radical shifs in echnology, hey may incur subsanial new coss adoping ha echnology, biasing sandard produciviy measures. Forunaely, equaion (4) provides boh a means o esimae c and, wih esimaes in hand, a means o adjus produciviy measures. Economeric Specificaion Consider firs he esimaion of adjusmen coss. To do his, I assign a funcional form o c. In general, adjusmen coss can be described as a funcion of he invesmen rae and echnology, c c( I K, T ) =, where I is invesmen and T is some measure of echnology. I will defer reamen of T unil he nex secion, leaving jus he invesmen relaionship o be specified. Afer some experimenaion, I chose (5) c I = γ K 1 1 and several relaed forms. Then in discree ime, for he ih indusry a ime (4) becomes I i (6) Zˆ, 1 i = a + µ i γ + εi K i, 1 where a represens overall produciviy growh capured as a year dummy, µ represens an indusry fixed effec, is he firs difference operaor and ε is a sochasic error erm. Noe ha he fixed effecs capure fixed indusry differences in he rae of produciviy growh, such as differences ha migh arise from differences in R&D spending. This equaion is similar o one used by Lichenberg [1988] in a sudy of plan level adjusmen coss. My approach differs from his in several ways. I use a non-parameric measure of produciviy growh as he dependen variable and I scale adjusmen coss by he capial sock. Because I am comparing indusries composed of differen numbers of plans, i is necessary o scale invesmen by some measure of he capial sock. Like Lichenberg, I use gross raher han
7 Technology Adopion Coss and Produciviy Growh - Bessen 9/01 ne invesmen. Lichenberg, however, does go furher and apporions his resuls beween replacemen invesmen and expansion invesmen. Also, Lichenberg uses curren period invesmen while I use lagged invesmen. As Lichenberg noes, simulaneiy problems bias esimaes of γ downward when curren period invesmen is used. By using lagged invesmen, I avoid his simulaneiy issue, alhough I poenially undersae he oal adjusmen cos because I miss curren period adjusmen coss. On he oher hand, if produciviy growh is serially correlaed and he change in invesmen rae is correlaed wih produciviy growh, las year s simulaneiy may also bias my esimaes of γ. In general hese correlaions are no large: serial correlaion of produciviy growh is -.02 and +.14 for he NBER-CES and BLS samples (described below), respecively. The corresponding correlaions beween he change in invesmen rae and concurren produciviy growh are.11 and.04. So i is possible ha he BLS esimaes obained using (6) may be biased oward zero. Performing a maximum likelihood AR1 esimaion (no shown) generaed similar coefficiens and smaller sandard errors. For he NBER-CES daa, i is possible ha some effec oher han adjusmen cos migh cause he sligh negaive correlaion, oversaing esimaes of γ. Tess of Granger causaliy (no shown) find ha changes in he invesmen rae Granger-cause produciviy growh in boh daa samples. Thus serial correlaion issues do no appear o have much influence on he esimaes obained using (6). Noe also, ha I assign a linear funcional form o adjusmen coss. This conrass wih much of he macroeconomic lieraure ha assumes ha adjusmen coss are convex. My aim (like Lichenberg s) is o assess he magniude of adjusmen cos, no he curvaure, so a linear form should be a reasonable firs-order approximaion o quadraic forms. In any case, experimens using quadraic specificaions fi he daa raher poorly and hese specificaions were rejeced in favor of linear forms. The linear specificaion does no capure fixed coss of adjusmen eiher. However, episodes of zero invesmen occur in less han 0.1% of he sample. So fixed coss would be incurred in virually all of my daa, bu he linear specificaion simply does no capure his effec. In oher words, his specificaion will undersae oal adjusmen coss if fixed coss occur. Noe, also, ha exernal adjusmen coss are no capured. The (undiscouned) average adjusmen cos rae can be calculaed using (5) and (1) as
8 Technology Adopion Coss and Produciviy Growh - Bessen 9/01 (7) φ c Y * I = γ Y K * 1. This represens he adjusmen cos incurred by one dollar of invesmen. Given he linear specificaion, i also equals he marginal adjusmen cos. Measuring Produciviy Growh (8) Equaion (4) can be re-arranged d c A ˆ = Z ˆ +, d indicaing ha rue produciviy growh may be obained by adding dc d o he measured Solow residual. This equaion has a sraighforward inuiive explanaion. The adjusmen cos represens a complemenary invesmen ha is no included in measured invesmen. Bu his unmeasured invesmen is a componen of oupu. Tha is, Y* is he measure of rue oupu, which is larger han Y by he amoun of invesmen, faser by dc d. * c Y. Then, using equaion (1), Y ˆ * = Y ˆ + d c d, or oupu grows I use equaion (8) as a simple, basic means o correc measured produciviy growh for adjusmen cos changes. This assumes ha all oher inpus and oupus are measured correcly. This migh no be he case, however, when adopion coss are large. There are wo possible, offseing effecs: adopion coss may disor price deflaors for capial goods and adopion coss may imply unmeasured capial socks (human and/or physical capial). Firs, adopion coss influence he pricing of capial goods in ways ha may no be capured by price deflaors. Consider wo vinages of a capial good, v = {0,1 }, wih efficiencies of q v, adjusmen cos raes φ v, and prices p v. Then if hese wo models are offered a he same ime, i mus be rue ha he coss of efficiency unis are equivalen, (9) p (1 + φ q 0 0 1 (1 1) 0 ) = p + φ q 1, or p p 1 0 = q q 1 0 1 + φ 1 + φ 0 1. Noe ha relaive prices are no longer deermined solely by relaive efficiencies, bu relaive adjusmen coss also come ino play.
9 Technology Adopion Coss and Produciviy Growh - Bessen 9/01 This means ha qualiy adjusmens used o consruc invesmen deflaors will no properly capure qualiy differences in he presence of adjusmen coss. This is because boh he mached model mehod of deflaor consrucion and hedonic mehods assume ha efficiency prices will be equal for wo models sold a he same ime, or p 0 q0 = p1 q1. The mached model mehod compares closely similar models a wo poins in ime and hen assumes ha oher models sold a he same ime have he same efficiency prices. The hedonic mehod performs a crosssecional regression of he prices of differen models agains heir characerisics again assuming efficiency prices are equal across models a any one ime. 3 Clearly, in he presence of adjusmen coss ha may vary from model o model, his assumpion will no be rue. In paricular, if φ 1 > φ 0, hen invesmen in model 1 will be undersaed relaive o invesmen in model 0. Noe ha his is a measuremen problem wih qualiy-adjused price deflaors and since rue q is unobserved, (9) canno be used o infer values of φ. Now, he correcion in (8) akes care of his measuremen problem for capial goods ha are boh produced and consumed wihin he manufacuring secor for example, he unmeasured invesmen in vinage 1 above equals he associaed increase in adjusmen coss. However, he manufacuring secor also produces capial goods ha are consumed in oher secors. If qualiy is mis-measured, hen his porion of oupu is undersaed and a furher adjusmen needs o be made. If he value of capial goods is undersaed because of rising adjusmen coss, hen an addiional posiive correcion o manufacuring produciviy growh is needed. On he oher hand, he exisence of unmeasured invesmen suggess ha physical capial socks or human capial socks or boh may also be mis-measured. Here much depends on he assumpions made abou he naure of his invesmen, is depreciaion rae, facor shares and wheher he ransiion o new vinages acceleraes obsolescence of old capial. If acceleraing adopion coss make capial socks grow faser han measured, a negaive adjusmen would have o be made o (8). Thus he wo possible measuremen issues associaed wih rising adopion coss have opposie effecs on produciviy growh esimaes. I experimened wih a variey of assumpions regarding hese wo measuremen issues, and found ypically: a.) boh effecs are subsanially smaller han he direc effec of adjusmen coss shown in (8), and, b.) he increased growh in 3 In addiion, he adjusmen rae will be an omied independen variable, causing hedonic coefficiens o be undersaed. If adjusmen coss are correlaed wih qualiy, hen his bias will be reduced, bu he basic measuremen problem discussed in he ex remains.
10 Technology Adopion Coss and Produciviy Growh - Bessen 9/01 oupu ended o be slighly larger han he increased growh in capial socks. Neverheless, because his approach involves some speculaion, in his paper I simply use equaion (8) o calculae produciviy growh. The reader should inerpre he resuls as a baseline or saring poin. Furher research is necessary o evaluae he significance of possible measuremen problems. Finally, noe ha he role adjusmen coss play above is counerpar o anoher wellrecognized role hey play in produciviy growh accouning. Adjusmen coss are commonly used o explain he effec of capaciy uilizaion on produciviy measuremen. Capaciy may no be fully uilized because quasi-fixed facors of producion, such as capial, adjus only slowly o economic shocks. Assuming ha firms opimize dynamically, a firm faced wih a posiive (negaive) demand shock may no inves (disinves) o he opimal long-run level because invesmen incurs adjusmen coss. 4 Bu clearly, his can only be par of he sory. If he anicipaion of adjusmen coss prevens firms from fully adjusing capaciy, hen when firms finally do inves, hey mus incur hose adjusmen coss. And his affecs he measuremen of produciviy growh. III. Empirical Resuls Daa and Variables To esimae adjusmen coss, I use a comprehensive, deailed panel of manufacuring indusries ha provides significan cross-secions and ime series: he NBER-CES Manufacuring Indusry Daabase [Barelsman and Gray, 1996] from 1958 o 1996, which includes 459 indusries a he 4-digi SIC code level (1987 SIC codes). I exclude asbesos producs, SIC 3292, an indusry ha essenially disappeared in recen years due o legal resricions. I also use a smaller panel derived from he April, 2001 release of he BLS mulifacor produciviy daabase. 5 This panel includes 19 2-digi SIC indusries (I exclude obacco), however, i also includes annual measures of IT invesmen and socks, permiing invesigaion of he relaionship beween IT and adopion coss. The variables used are described in he Appendix. However, wo deserve furher discussion. Firs, I experimened wih several differen specificaions for he adjusmen cos. As 4 See Dixi and Pindyck [1994] for an overview. See Bernd and Fuss [1986] for he specifics of correcing for capaciy uilizaion in produciviy growh accouning. 5 Thanks o Seve Rosenhal and Bill Gullickson for providing requesed daa.
11 Technology Adopion Coss and Produciviy Growh - Bessen 9/01 noed above, he invesmen measure needs o be scaled by a measure of indusry size and I experimened wih differen scaling measures, including real oupu, oal capial sock and srucures sock. I obained he bes fi using invesmen divided by he sock of srucures. This may occur because srucures may be measured wih less error han equipmen. The resuls below, however, are based using invesmen divided by he oal capial sock. The adjusmen cos esimaes are slighly lower, bu he qualiaive picure is quie similar. Second, he capial socks in he NBER-CES daabase were developed from indusry level invesmen daa using a perpeual invenory mehod. 6 The specific mehodology was developed a he Federal Reserve Board [Mohr and Gilber, 1996] and uses BEA deflaors (including he hedonic deflaor for compuers), sochasic reiremens, and bea decay of service efficiency. These socks, like he BLS socks, do no use he BEA depreciaion raes ha incorporae obsolescence along wih physical depreciaion. To make sure his assumpion was no criical, I developed a corresponding series of capial socks using he curren BEA mehods [Kaz and Herman, 1997, Fraumeni, 1997]. The adjusmen cos esimaes changed only slighly. I also derived esimaes using he BLS daa (Table 4 below). BLS esimaes of producive capial sock weigh deailed asse ypes differenly (he NBER-CES daa effecively only have 2 asse classes). The adjusmen cos esimaes obained from he BLS daa a he 2-digi level are reasonably close o he esimaes from NBER-CES daa a he 4-digi level. Overall Measures Table 1 presens several variaions on equaion (6). The firs wo columns show he regression wih and wihou indusry fixed effecs. 7 Indusry fixed effecs conrol for heerogeneiy in indusry-specific facors ha migh influence he average rae of produciviy growh. For insance, indusries wih high R&D spending migh experience faser produciviy growh. If R&D were also correlaed wih invesmen, his migh bias he esimaes of adjusmen coss. As shown here does no appear o be much bias; fixed effecs are used in all subsequen regressions. Columns 3 and 4 explore differen lags in he invesmen erm. The adjusmen coss appear o diminish over ime as would be expeced. However, invesmen seems o incur 6 These daa only incorporae price deflaors for compuers from 1972 on. However, compuers represen only a iny fracion of capial in 1972, and even less for earlier years, so his should cause no significan bias. 7 Durbin Wason ess do no indicae a problem wih serial correlaion.
12 Technology Adopion Coss and Produciviy Growh - Bessen 9/01 saisically significan coss for up o wo years, so I use adjusmen erms wih boh one and wo year lags (Column 5). Following Bernd and Fuss [1986], I conrol for capaciy uilizaion effecs by assigning capial a residual share of oupu in he calculaion of he Solow residual. However, his approach migh no fully accoun for uilizaion effecs if labor or maerials do no adjus insananeously. Capaciy uilizaion migh also effec esimaes if reurns o scale are no consan. In Column 6, I also include several measures ha may capure capaciy uilizaion. These do no appear o affec he esimaes of adjusmen coss. To esimae he adjusmen cos rae, φ, I use sample means and replace poenial oupu wih las year s acual oupu, γ Y 1 K 1. These esimaes are shown in he boom row. For a single lagged value (Column 2), I find 17 of adjusmen cos for each dollar of invesmen. By comparison, Lichenberg, using plan level daa also derived from he Census of Manufacures and Annual Survey of Manufacures, finds adjusmen coss of 21 for replacemen invesmen and 35 for expansion invesmen. Since he gross invesmen measure I use is he sum of replacemen invesmen and expansion invesmen in Lichenberg s sudy, my esimae based on indusry aggregaes is slighly lower han his. However, Lichenberg uses only a single, curren year of invesmen. 8 When I include invesmen wih a wo-year lag, adjusmen coss rise o 41 per dollar of invesmen. This is somewha higher han Lichenberg s esimaes, however, considering he differences in mehod and daa, hese resuls are broadly consisen. Incorrecly measured capial socks migh bias he esimaes of adjusmen cos. In paricular, if he service efficiency of capial declines more rapidly han accouned for in he consrucion of he capial sock, a spurious negaive correlaion migh arise, leading o biased esimaes. Noe ha he capial sock in he NBER-CES daabase uses a bea decay model of service efficiency. This ends o decay less rapidly during he firs few years afer new capial is insalled. BEA capial socks, largely based on geomeric depreciaion, end o decline more rapidly han bea decay during he early years of use. To examine he robusness of he esimaes, I consruced a corresponding se of invesmen raes and capial socks for each 4-digi indusry using BEA mehods and BEA depreciaion. Regressions using hese alernaive socks did no generae maerially differen esimaes of adjusmen coss (resuls no shown). 8 Lichenberg failed o obain significan resuls using lagged invesmen in his specificaion. However, given he noisiness of plan level daa, his is no surprising.
13 Technology Adopion Coss and Produciviy Growh - Bessen 9/01 Time Trends Table 2 presens he regression performed over differen inervals. Table 2a shows 3 longer inervals and Table 2b shows each of hese furher divided ino wo shorer inervals. Figure 2 displays he adjusmen coss from Table 2b. A sharp and dramaic paern emerges. Adjusmen coss more han doubled from he early 60 s o he lae 70 s and early 80 s. This is a raher large difference. Afer 1988 he sandard errors grow large and he coefficiens lose significance. This change could arise from increased errors in measuring capial and invesmen. For insance, he NBER-CES daa does no include spending on unbundled sofware which looms large in he new BEA and BLS accouns [Parker and Grimm, 2000]. Or i may mean ha he new informaion sysems used in differen indusries have very disparae effecs on adjusmen coss. To explore he ime paern of adjusmen coss more precisely, I also esimaed a nonlinear model assuming ha he coefficiens increased linearly from 1974 o a erminal year. Afer some experimenaion, he bes fi was achieved wih 1986 as he erminal year. Then he following equaion was esimaed using non-linear leas squares from 1961 hrough 1988: Zˆ =.007 (.001) Ii,.101 +.018T (.019) (.004) Ki 1, 1 Ii,.087 +.012T (.018) (.004 ) Ki, 2 2 (10) T 0, 1973 13 < 1974 1973 < < 1986 < 1987 wih sandard errors in parenheses below he coefficiens ( R 2 =. 011 ). To esimae c for each year, I use sample means for lagged values of I and K. This gives he average value of c for individual indusries. Since he aggregae oupu of he manufacuring secor is less han he sum of oupus of he indusries (because some indusries produce inermediaes), I muliply his figure imes he sum of indusry oupu divided by secor oupu (from he BLS). This yields a value of c for he enire secor, expressing adjusmen coss as a percen of aggregae oupu. The annual values are shown in Figure 3. Afer a small, emporary rise in he 60 s, c increases from 2.4% in 1973 o 6.5% in 1983 and 7.1% in 1986. Thus adjusmen coss as a percen of oupu rose over 4%. The overall paern is exacly wha one would expec if many indusries experienced echnology ransiions during he 70 s and early 80 s. As more indusries swiched o new
14 Technology Adopion Coss and Produciviy Growh - Bessen 9/01 echnologies hey would experience rising adopion coss during his period. Once mos firms had made he ransiion, subsequen capial vinages based on he new echnologies would no incur such large increases in adopion coss and migh even experience decreases in hese coss. Of course, many oher condiions changed during he 70 s as well, so his is no he only possible explanaion. An imporan quesion is wheher he rise in adjusmen coss is echnologyspecific or no. For example, informaion echnology or new energy efficien echnology could incur specific learning coss. On he oher hand, oher sors of changes migh increase adjusmen coss for all ypes of invesmens, giving rise o non-echnology-specific increases in adjusmen coss. This migh be he case if, say, he educaional qualiy of he workforce fell, making learning more cosly. This migh also be he case if governmen regulaion made he insallaion of new equipmen more cosly. Given he large size of he addiional adjusmen coss, i is difficul o idenify a plausible non-echnology-specific explanaion. The labor force acually became more highly educaed during he 70 s. And alhough governmen polluion conrols may have increased he insallaion coss of many ypes of equipmen, i is hard o see how such increases could accoun for 4% of oupu. Moreover, mos of his increase would be in he cos of he equipmen iself, no in adjusmen coss. The 70 s also saw an increase in R&D spending and rising energy coss. Boh of hese facors are likely o give rise o echnology-specific adjusmen coss R&D generaes new echnology ha may have adopion coss; shifs o energy efficien equipmen may incur echnology-specific adapaion coss. To explore hese facors furher, Table 3 repeas he regressions for differen indusry groups from 1970 83. Column 1 repeas he overall regression, and Columns 2 and 3 show he sample segregaed ino high ech and low ech indusries. I idenified 137 high ech indusries which had high employmen of scieniss and engineers relaive o oal employmen [Hadlock e al, 1991]. As can be seen, he high ech indusries had somewha higher adjusmen coss, alhough he difference in coefficiens is no quie significan a he 1% level. Columns 4 and 5 segregae he sample ino high- and low-energy-using indusries based on he raio of energy consumpion o oupu in 1970. Here, oo, here is a modes, and no saisically significan, difference in favor of energy-inensive indusries. Thus neiher R&D nor a swich o energy efficien equipmen appears o explain he sharp rise in adjusmen coss, alhough hey may conribue marginally.
15 Technology Adopion Coss and Produciviy Growh - Bessen 9/01 IT and Adjusmen Coss I remains o explore he rise in IT spending as a possible cause of he rise in adjusmen coss. To do his, I use he BLS panel, which includes IT invesmen. Firs, i is necessary o check ha his panel has adjusmen paerns similar o hose in he NBER-CES daa, despie he reduced variaion in he cross-secional dimension. Column 1 of Table 4 performs a basic adjusmen cos regression using a single lagged invesmen rae. Adding an addiional lag did no generae a significan coefficien. For he single lag, he coefficien is highly significan and corresponds o an adjusmen cos of 57 per dollar of invesmen, somewha higher han he 41 in Table 1, bu reasonably similar given he differences in daa and capial measures. Column 2 ess wheher adjusmen coss rose sharply in he BLS panel from 1974-83. I add a variable ha is zero ouside of his inerval and equals he change in he invesmen rae during his inerval. The coefficien should reflec he incremen in adjusmen coss during his period. Alhough he coefficien is only significan a he 5% level, i is roughly he righ magniude and reflecs a large increase in adjusmen coss. Combined, he coefficiens imply an adjusmen cos of 94 from 1974-83 and of 41 before and afer his inerval. Again, hese figures are somewha higher han in Table 2a, bu reasonably similar. Thus he basic paern observed in he much larger NBER-CES daabase also appears here. To es for a link beween IT spending and adjusmen coss, I modify he specificaion of adjusmen coss in (5) o include a proxy for informaion echnology. The basic inuiion is ha a higher share of IT in invesmen or in he capial sock migh incur higher adjusmen coss. Two simple specificaions are (11) c = I γ K 1 1 + δ I I IT and c = I γ K 1 1 + K δ K IT 1 1 where IT I and IT K are real IT invesmen and sock, respecively. The capial share in second specificaion may be hough of as a proxy for relaive invesmen flows over several years. Wih hese specificaions, any increase in IT-inensiy incurs a emporary reducion in measured produciviy growh. Columns 3 and 4 use he firs of hese specificaions, wihou and wih ime dummies. Afer some experimenaion, I found ha he regression fi bes wih zero lag in he IT erm, and so his is wha I presen in hese regressions, despie he possible aenuaion of he coefficien because of simulaneiy issues. The IT coefficien is highly significan in Column 3, bu when ime dummies
16 Technology Adopion Coss and Produciviy Growh - Bessen 9/01 are added, he significance disappears. The independen variaion in he cross-secional dimension of IT invesmen may simply be insufficien o offse he simulaneiy losses. Column 5 uses he sock specificaion. This is less volaile and can be used well wih a lag. Here he resuls wih ime dummies are highly significan and wih a large coefficien for IT share of capial. Thus here does appear o be a srong link beween he IT share and a loss of produciviy. Bu does his accoun for he rise in adjusmen coss measured in Table 2? Using (7) applied o he specificaion in Column 5 a mean sample values, I calculaed he mean adjusmen cos per dollar of invesmen for he inervals in Table 2a. From 1961-73 he calculaed mean adjusmen cos is 37, from 1974-83 i is 72, and from 1984-96 i is $1.68. Esimaes for he firs wo inervals mach raher closely. Increased IT spending does seem o accoun for he sharp increase in adjusmen coss in he 70 s and early 80 s. However, afer 1984, he esimaes diverge. Recall, however, ha he esimaes for he las inerval in Table 2a have large sandard errors and are no saisically significan, possibly because he NBER-CES daa may no fully capure IT invesmen. So his divergence is no necessarily a odds wih a link beween adjusmen coss and IT. To es wheher he linear specificaion of IT share in Column 5 migh cause adjusmen cos esimaes in he 90 s o be oversaed, I added a quadraic erm in Column 6. These esimaes do sugges a sligh concaviy, bu he coefficiens are no significan and even hen, he esimaed concaviy is relaively sligh. Finally, I use he esimaes in Column 5 o calculae annual values of c using sample means. These are also shown in Figure 3 for 1961 hrough 1988. As can be seen, hese esimaes are quie similar o he esimaes obained using NBER-CES deailed indusry daa, alhough hey end o run slighly higher. Thus he wo esimaes generae a consisen paern of adjusmen coss, one based on IT and oal invesmen, he oher jus using invesmen daa. Based on his evidence, I conclude ha he sharp rise in adjusmen coss during he 70 s and early 80 s can be primarily aribued o increased IT invesmen. Greaer R&D and a ransiion o energy efficien equipmen may have also conribued o a lesser degree. In oher words, adjusmen coss rose because of echnology adopion coss.
17 Technology Adopion Coss and Produciviy Growh - Bessen 9/01 IV. Implicaions for Produciviy Growh Measuremen Adjusmens o BLS Esimaes for Manufacuring The annual esimaes of c displayed in Figure 3 can be used o adjus esimaes of manufacuring secor produciviy growh using equaion (8). The firs row of Table 5 displays he annualized produciviy esimaes from he BLS April 2001 release broken ino four periods. As can be seen, hese measures exhibi he well-known produciviy slowdown. Produciviy growh during 1974-88 fell o 1.13% per annum compared o 1.52% during 1949-73. 9 Using shorer inervals, growh fell o 0.52% from 1974-83 compared o 1.84% from 1961-73. The following wo rows show he average annual growh in c and he adjused produciviy growh esimaes using he NBER-CES esimaes from (11). The las wo rows show comparable esimaes using BLS daa wih he specificaion in Column 5 of Table 4. The adjusmens have a subsanial impac. A produciviy slowdown sill appears comparing he shorer inervals, bu comparison of he longer inervals suggess eiher no slowdown or, a mos, a very small produciviy slowdown. As noed above, hese produciviy growh esimaes ignore possible measuremen problems associaed wih adopion coss. Neverheless, hese resuls demonsrae ha adopion coss during echnology ransiions can easily inroduce very large errors ino sandard produciviy calculaions. And he inerpreaion of echnical change during he 70 s lies in he balance. V. Conclusion Moses Abramowiz [1956] called he Solow residual a some sor of measure of ignorance. I is, perhaps, comforing o assume ha our ignorance grows only gradually and ha he rae of echnological change remains more or less consan. Bu evidence from hisory and evidence on he diffusion of innovaions sugges ha echnologies frequenly exhibi dramaic, Schumpeerian ransiions. This paper finds evidence of jus such a ransiion during he 1970 s: he cos of insalling and implemening new capial more han doubled. And I find evidence linking his increase o a greaer share of invesmen in IT. Such a dramaic change suggess ha firms experienced large adopion coss when swiching o new echnologies. This concurs wih case sudy evidence. 9 A business cycle rough (NBER) occurred during 1949 and a peak in 1973. In 1974 he economy was in recession, bu he official rough was reached in 1975.
18 Technology Adopion Coss and Produciviy Growh - Bessen 9/01 Bu a rapid increase in adopion coss implies ha he Solow residual does no accuraely measure produciviy growh. Calculaions based on esimaed adopion coss demonsrae ha produciviy growh may have subsanially exceeded he Solow residual during he 70 s, shrinking he measure of he produciviy slowdown. In oher words, much of he apparen produciviy slowdown may be an arifac of measuremen error. Our ignorance may, in fac, increase sharply during periods of echnological ransiion. This is imporan because, from a longer hisorical perspecive, echnology ransiions may no be infrequen. The shif o an increasing share of invesmen going o informaion echnology is, in fac, par of a longer secular rend he share of invesmen going o equipmen has increased overall (wih occasional inerrupions) since he nineeenh cenury. Some of his increase can be readily idenified wih new echnologies, e.g., he growh in spending on elecrical devices and elecric ransmission equipmen during he middle of he las cenury. From his perspecive, he 60 s when measured produciviy was high, bu also when he equipmen share of invesmen did no increase may have been a emporary respie from he echnology ransiions implied by his rend. Raher han a normal period, his era may have benefied from improvemens o exising echnologies wihou he coss of adoping many new echnologies. The rise in adopion coss during a echnology ransiion affecs more han produciviy growh. Oher researchers have argued ha adopion coss may also relae o changes in wage inequaliy, wage skill premia, he relaive employmen of skilled workers, and sock prices [Hornsein and Krusell, 1996, Greenwood and Yorukoglu, 1997, and Greenwood and Jovanovic, 1998]. The resuls here emphasize he imporance of hese connecions.
19 Technology Adopion Coss and Produciviy Growh - Bessen 9/01 Appendix. Definiions of Variables used in he NBER-CES Esimaions L M K Y I / K α β π Labor calculaed as annual producion hours imes he raio of oal payroll o producion wages. This includes nonproducion labor in efficiency unis. Deflaed maerials and energy. Real ne capial sock based on FRB mehods. Socks of individual asse ypes are calculaed using sochasic service lives and bea decay of efficiency. Depreciaion does no include obsolescence. Socks of differen asse ypes are added one-for-one o compose aggregae sock. Real oupu calculaed as deflaed shipmens plus invenory change. Invesmen rae calculaed as deflaed gross invesmen divided by ne real plan. Labor share of oupu calculaed as oal payroll divided by nominal shipmens plus invenory change. This quaniy is hen muliplied by he raio of employee compensaion o wages and salaries found in he NIPA ables for he corresponding 2-digi SIC indusry and year. Maerials share calculaed as nominal cos of maerials and energy divided by nominal shipmens plus invenory change. Capial share of oupu calculaed as 1 - α - β (assumes consan reurns o scale) References Abramoviz, Moses. 1956. Resource and Oupu Trends in he Unied Saes Since 1870, American Economic Review, v. 46, p. 5-23. Barelsman, Eric J. and Wayne Gray. 1996. The NBER Manufacuring Produciviy Daabase, NBER Technical Working Paper, No. 205. Bernd, Erns and Melvyn Fuss. 1986. Produciviy Measuremen wih Adjusmens for Variaions in Capaciy Uilizaion and Oher Forms of Temporary Equilibrium, Journal of Economerics 33, p. 7 29.
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