The internationalization of industry supply chains and. the location of innovation activities

Transcription

1 The nternatonalzaton of ndustry supply chans and the locaton of nnovaton actvtes Bran J. Ffarek, Francsco Veloso, Clff I. Davdson Carnege Mellon Unversty, Engneerng and Publc Polcy ABSTRACT Current polcy dscussons on offshorng mostly focus on ts mpact on lower sklled manufacturng and servces jobs, assumng that hgher-value-added jobs and, especally, nnovaton actvtes are not affected by offshorng. Contrary to ths vew, we suggest that nnovaton actvty wll also move abroad as a result of offshorng. Yet, the movement of nnovaton actvtes abroad wll be condtoned by the nature of knowledge, causng some nnovaton actvtes to reman n the US whle drvng other actvtes away. To explore ths dea we analyze the quantty of and knowledge utlzed by nnovaton actvtes over tme n rare-earth catalyst and magnet technologes, showng how knowledge spllovers among dfferent segments of an ndustry value chan can play a role n the movement of nnovaton outsde the US. We then develop an nnovaton model to gan further nsght nto the characterstcs of nnovaton actvtes that reman n the US. Keywords: Internatonalzaton, rare earth elements, nnovaton, knowledge spllovers, offshorng

2 1 INTRODUCTION After a hgh-grade depost was found n Calforna n the early 1950s, the US quckly became a domnant producer of rare earth elements (atomc numbers 21, 39, 57-71). Ths lead to US developments n large-scale separaton technques for these elements and, subsequently, to sgnfcant nvestment n researchng potental uses for the elements. Ths resulted n the development of mportant and dverse technology based applcatons throughout the 1970s and 1980s, ncludng ceramcs, catalysts, magnets and phosphors. However, over the past 20 years, the supply chans of rare earth based applcatons have been offshored from the US to Asa. Today over 85% of rare earth materals orgnates n Chna. Most research to date on vertcal specalzaton, nternatonalzaton, and offshorng suggests ths ndustry evoluton should not negatvely mpact the ablty and nvolvement of the US n nnovaton actvtes. The global supply and producton networks should result n lower costs for ndvdual frms, leadng to expanded markets, lower prces for consumers, ncreased resources for R&D actvtes and the creaton of new busness opportuntes for exstng and new frms (Aron and Sngh, 2005, Farrell, 2005, Branstetter, 2006). Other researchers also suggest that smlar benefts for frms and natonal economes arse as frms access local knowledge and learn about complementary technologes not readly accessble at home locatons (Dunnng, 1995, Florda, 1997, Zander, 2002). However, many ndustry representatves have voced concerns wth the ablty of the US to mantan leadershp n rare earth technology based applcatons. In fact, US patentng actvty n rare earth based technologes has been declnng snce 1990, the date when most of the manufacturng shfted to Asa (Ffarek et al., 2007). Yet, ths trend s not unform. For example, 2

3 the US has contnued to be a strong leader n nnovaton n catalyst applcatons of rare earths, whle nnovaton n rare earth magnet technology applcatons has moved away from the US. These ntal fndngs may call nto queston our understandng of the mpacts of nternatonalzaton and offshorng n a regon and the common polcy approaches to address these trends. Researchers, corporate executves and polcy makers typcally assert that offshorng benefts natonal home economes as long as dsplaced workers are absorbed nto other postons where they wll be able to generate greater value to the economy (Feenstra, 1998, Jaffee, 2004). Therefore polces typcally focus on movng frms and ndvdual workers hurt by nternatonalzaton nto more value added actvtes by provdng generous severance packages, job-retranng programs and contnung-educaton grants to upgrade worker sklls. The noton behnd these programs s that a naton whose jobs are beng dsplaced by offshorng ought to specalze n hgher-value-added work, whch combned wth productvty gans from offshorng, leads to the mprovement of a naton s welfare. Innovaton actvtes n partcular are those thought to be further away from beng affected by offshorng and, n fact, consdered to be a desred goal n terms of alternatve occupatons to those beng dsplaced. Yet, ndustry evoluton and observed geographc relocaton of R&D n the rare earths ndustry away from the US suggests there s a more mportant queston not currently beng properly addressed: Under what condtons can technology sectors offshore low-skll supply chan operatons such as raw materal producton or manufacturng, whle effectvely mantanng hgher-skll R&D busness functons n the home regon? Although nternatonal supply chans, ncludng offshorng, are assocated wth the development of frm-level capabltes to coordnate geographcally dspersed networks of tasks and producton actvtes (Levy, 2005), many hgher-value-added nnovaton actvtes depend on 3

4 complex nteractons among dfferent value chan segments that requre face-to-face contact (Leamer and Storper, 2005). These crtcal nteractons can be dsrupted by geographc dstances between busness unts. As a result, t s possble that, as manufacturng and servce postons move overseas, these nteractons are jeopardzed, leadng busness managers to relocate engneerng work and R&D so that t can be more geographcally algned wth producton and thus away from the home envronment. Ths s consstent wth a loomng concern voced by some academcs and the greater publc that nnovaton wll also be offshored, ultmately affectng the ablty of home economes to mantan ther economc growth and leadershp (Horvt, 2004, Hra and Hra, 2005). Thus, answerng the queston above entals a crtcal understandng of the condtons under whch R&D actvtes are lkely to follow the relocaton of producton and servce postons or, on the contrary, they are ndependent of the locaton of other segments of the value chan. Ths paper explores the changng nature of knowledge used for nnovaton actvtes followng the nternatonalzaton of supply chan actvtes amng n partcular to understand the drvers that keep nnovaton actvtes n the home regon, despte supply chan nternatonalzaton. To address ths ssue, the research uses two technology sectors that are part of the rare earth ndustry, catalysts and magnets, to dentfy crtcal factors that nfluence the locaton of nnovaton actvtes followng the offshorng of low technology operatons n the rare earth ndustry supply chan. The analyss draws from frm-level unstructured ntervews that dentfy crtcal drvers, nputs, and nteractons n the nnovaton processes of these technologes. It also uses detaled nformaton from a subset of over 75,000 patent applcatons over the perod from that document the generaton and regonal locaton of techncal knowledge n rare earth elements and ther applcatons. The data s used to examne the 4

5 geographc locaton of nnovaton actvtes and the changng nature of knowledge utlzed by these actvtes n dfferent locatons. Results suggest that, as expected, knowledge exchange among dfferent actors n ndustral supply chans nfluence the locaton of nnovaton actvtes. Yet, they also show that demand and the polcy envronment play a crtcal role n ths process. Innovaton n catalyst technologes s hghly drven by natonal and drect customer envronmental polcy and strategy, whch has enabled a strong contnued leadershp of the US n nnovaton actvtes. Magnet technology reles on sgnfcantly on suppler, producer and customer nteractons and assocated knowledge spllovers, contrbutng to movement of nnovaton away from the US. The conclusons of ths paper reflect the need to reframe the dscusson on approprate responses to nternatonalzaton and offshorng. The polcy dscusson needs to shft from focusng on movng up the value added chan of actvtes to crtcally understand what characterstcs and comparatve advantages wthn regons drve nnovaton actvtes to reman localzed despte the emergence of nternatonal supply chans. In the future, f we hope to mantan a healthy rate of nnovaton n the US, t wll be crtcal for polces to help move frms and workers nto actvtes where the nteractons between local busness, nsttutons, and the technology envronment matters. The paper s organzed as follows. Frst, we dscuss the background of the rare earth ndustry, the technology applcatons of rare earth materals, the nternatonalzaton of the rare earth supply chan, and nnovaton trends wthn rare earth technologes. We then develop the theoretcal background of nnovaton actvtes and the nternatonalzaton of supply chans. In the subsequent secton, we ntroduce our patent data and regresson analyses. We then present the results and dscuss ther mplcatons. Next we develop an nnovaton model to gan further 5

6 nsght nto the changng nature of knowledge utlzed for nnovaton actvtes n dfferent technologes and locatons. Fnally, we draw conclusons from ths analyss and suggest future work. 2 BACKGROUND OF RARE EARTHS 2.1 Producton and supply chan of rare earth raw materals The rare earth elements are a relatvely abundant naturally occurrng group of ffteen elements. Rare earths exhbt very smlar chemcal and physcal characterstcs, varyng only slghtly n ther electronc confguratons and onc rad. Consequently, they were orgnally very dffcult and costly to separate. Pror to 1950, rare earths were not commercally produced n sgnfcant quanttes and mostly sold as naturally occurrng mxtures of the ndvdual elements, such as mschmetal. In the early 1950s, the US quckly became a domnant producer of rare earth raw materals after a hgh-grade bastnaeste depost was found n Mountan Pass, CA. Early development was supported largely by the sudden demand for the rare earth element, Europum, created by the commercalzaton of color televson. By 1965, the sngle depost n Mountan Pass had become the most sgnfcant source of raw and processed rare earths n the world wth reserves of 13 mllon metrc tons. Other sgnfcant raw materal sources ncluded monazte extracted from Australa, Inda and Brazl but large scale separaton and processng operatons remaned lmted to the US and France. For example, the French frm Rhone-Poulenc (now Rhoda Rare Earths) purchased raw materals mostly from Australa and operated separaton facltes n France and the US. The rare earth ndustry s unque n that there are only a few rare earths processors but the markets for ther products are characterzed by very large number of dverse, technologcally advanced and mostly 6

7 small consumers. Molycorp, Inc. of the US s the only fully ntegrated mne-to-metals rare earth producer. By 1982, the US, Australa, Inda and Brazl accounted for over 95% of world output, wth the US bastnaeste depost supplyng over 50% of world output. However, Australa, Inda, and Brazl contnued to export raw rare earth materals to the US and France for further processng. At ths tme new markets for hgh-qualty, separated rare earths oxdes and metals were begnnng to develop, ensurng a growng market for rare earths n terms of value. Ths prompted Molycorp and Rhone-Poulenc to expand ther separaton and processng facltes. Throughout the 1980s, Chna sgnfcantly ncreased ther producton of rare earth raw materals for sale n the nternatonal market. Between 1980 and 1987, Chnese producton ncreased from 8% to 31% of the world total followng chaotc and unplanned development. The ncreasng market share ganed by low prced Chnese rare earths n the late 1980s mpacted processors elsewhere, especally n the US. For example, n 1988, Research Chemcals, the largest US producer of rare earth metals, were taken over by Rhone-Poulenc. In 1990, Ronson Metals Corporaton, mschmetal manufacturers for 75 years, ceased operatons and put all of ther assets up for sale. In the late 1980s, the changng pattern of rare earth consumpton away from mxed compounds towards hgh-purty, separated rare earths sgnfcantly affected the structure of the rare earth ndustry. New nternatonal entrants n rare earth processng emerged to meet the hgher demand for separated materals, ncludng smaller processors n Japan, as well as Trebacher Chemsche Werke, Th. Goldschmdt, Rare Earth Products Ltd. and AS Megon n Europe. However, rare earth processng remaned domnated by Molycorp, Inc. n the US and Rhone Poulenc, whch contnued to mantan processng facltes n France and the US. 7

8 In 1990 the structure of the Chnese rare earth ndustry and producton and export levels were reorganzed by the central government. Afterwards, rare earth producers n Chna also sgnfcantly ncreased ther producton of hgh purty separated rare earths, movng from less than 10% to 50% of producton by Concurrently wth these changes, the mpacts elsewhere n the rare earth ndustry were even more sgnfcant. In 1993, Dowa Rare Earths Company was forced to close ther rare earths plant n Japan because Chna began producng hgh qualty materal at 60% of ther market prce. In 1994, Nppon Rare Earths, a jont venture between Sumtomo Metal Mnng Company of Japan and Rhone Poulenc of France based n Japan, dscontnued operatons. Mtsubsh of Japan also closed ther subsdary company, Asan Rare Earths based n Malaysa and Mtsu Mnng and Smeltng n Japan suspended ther long term supply contracts. Meanwhle, producton of rare earth raw materals from Australa declned as a consequence of growng supples of rare earth ores from Chna and restrants concernng dsposal of the radoactve wastes assocated wth monazte extracton, wth the prce of monazte peakng n Ths n combnaton wth ncreased producton n Chna prompted Rhone- Poulenc and W.R. Grace and Company of the US, two of the major rare earth processors once heavly dependent on Australan ores, to begn purchasng rare earth chlordes from Chna. Snce the 1990s, Chna has contnued to ncrease ts domnance n the producton of rare earth raw materals (Fgure 1) and processed rare earths (Table 1). At the same tme, producton operatons elsewhere suffered economc and envronmental setbacks. Throughout the 1990s many Japanese companes transferred technology assets to Chna to secure rare earth supples, effectvely adng Chna s move nto the ntegrated producton of rare earth products. In March 1998, Molycorp, Inc. suspended producton at ts Mountan Pass rare earth processng plant due to envronmental concerns over ts wastewater ppelne. In 1999, Rhoda Rare Earths 8

9 consoldated extracton and separaton operatons to processng facltes n France and Chna. As a result of ths move ther US rare earths separaton facltes were closed, wth much of the equpment beng transferred to Rhoda s jont venture wth a Chnese rare earth frm. Today, Chna alone produces about 95% of the world s supply of rare earths, roughly 95,000 mt (USGS, 2005), and nearly 75% of the world s supply of separated rare earths Global Producton of Rare Earth Oxdes Producton, kt Total Other Chna 10 USA Monazte-placer era Mountan Pass era Chnese era? Separated REs % of Processed RE Fgure 1 Global producton of rare earth oxdes, Table 1 The growth of the Chnese rare earth ndustry (t REO contaned) Average Yearly Producton % 18% 32% 53% 80% Separated REs Exported 255 3,400 14,000 19,000 45,000 Proporton of Separated REs n Exports Total Processed RE Exported 6% 23% 35% 45% 70% 4,300 14,800 40,000 42,200 64,300 9

10 2.2 Rare earth technology nnovaton The trends n the locaton of rare earth nnovaton actvtes are captured usng USPTO patents and shown n Fgure 2. The nnovaton actvtes captured by the patent data nclude nnovatons n the producton and separaton of rare earths as well as technology applcatons for whch rare earths are a necessary component. The natures of the majorty of the patents are of the latter. The fgure focuses on nnovaton n the US precsely because t was orgnally the domnant regon and therefore t had the potental to see greater adverse effects from the nternatonalzaton actvtes. Usng these patent trends, Ffarek et al. (2007) fnd that US leadershp n rare earth technology nnovaton has been erodng snce No. of Patents Applcaton year US NonUS Fgure 2 Rare earth technology nnovaton trends, : US vs. Non-US frst nventor home locaton. Fgure 2 shows the rate of US patentng actvty n rare earth based technologes has been declnng snce Yet, ths trend s not unform. For example, Fgure 3 shows that the US has contnued to be a strong leader n nnovaton n catalyst applcatons of rare earths, whle nnovaton n magnet technology applcatons has moved away from the US. The exstence of sgnfcant dfferences n response to a strong supply chan nternatonalzaton make t an 10

11 excellent case to explore what mght be crtcal drvers that lead R&D actvtes to stay n a regon or to follow the supply chan and producton relocaton. Intervews wth ndustry leaders and a revew of crtcal ndustry reports (Roskll, 2001) help formulate a prelmnary hypothess, leadng to a model and emprcal test. In fact, accounts suggest that R&D actvtes n rare earth catalyst technology are drven by natonal and customer envronmental polces and strateges. Ths has fueled a strong contnued leadershp of the US n nnovaton actvtes throughout our study tme perod, despte the nternatonalzaton of the rare earth supply chan. On the contrary, rare earth magnet technology reles heavly on suppler, producer and customer nteractons and assocated knowledge spllovers among the supply chan, contrbutng to the movement of nnovaton away from the US. Ths contrast and especally the potental role of spllovers lead to the nterest n systematc examnaton of the relatonshp between knowledge spllovers and the locaton of nnovaton actvtes. Thus, n the subsequent secton we begn by examnng the theory behnd the role of knowledge spllovers n the locaton of nnovaton actvtes. Rare Earth Permanent Magnets Rare Earth Catalysts No. of Patents No. of Patents US NonUS US NonUS Fgure 3 Rare earth magnet and catalyst technology nnovaton trends,

12 3 THEORETICAL BACKGROUND: Knowledge spllovers and the locaton of nnovaton actvtes Exstng lterature suggests that successful nnovaton happens through a delcate balance wthn a system that ncludes clents, supplers, R&D unts, and the fnancal system (Lundvall, 1992, Edqust, 1997, Mlls et al., 2004, Chapman and Corso, 2005). A smlar vew s defended by the lterature on nnovaton clusters (Porter, 1990, Porter, 1998) whch focuses on the mportance of geographc proxmty between the organzatons of a system for nnovaton. Ths s also supported by an emergng perspectve that looks at a frm as part of an ndustral ecology (Rcart et al., 2004) and dentfes the mportance of dversty wthn a geographc locaton for nnovaton. The underlyng concept for these lteratures s the mportance of knowledge transfers wthn supply chans and locatons for nnovaton. Knowledge spllovers are generated when nvestments n knowledge creaton by one party also beneft other partes wthout them necessarly havng to pay as much for the knowledge. Exstng work has generally concluded that knowledge spllovers are geographcally localzed (Jaffe et al., 1993, Audretsch and Feldman, 1996, Almeda and Kogut, 1999, Branstetter, 2006). The common argument for the geographc localzaton of knowledge spllovers comes from the noton that knowledge transfer requres effectve communcaton of codfed as well as tact elements. Whle codfed knowledge can easly be transferred across dstances, the transfer of tact knowledge typcally requres drect face-to-face nteractons between ndvduals (Zander and Kogut, 1995, Hansen, 2002). Ths aspect has been explored n partcular by measurng the mportance and dffuson of knowledge spllovers n patent ctatons n the US (Jaffe et al., 1993). 12

13 The mportance of geographc localzaton n knowledge spllovers has remaned a consstent perspectve despte sgnfcant levels of nternatonalzaton over the past 20 years. The pattern of multnatonal corporate foregn nvestment n R&D over ths tme perod reflects ths consstency albet n a dchotomous way. Early foregn drect nvestment was orented towards explotng exstng capabltes n new foregn markets. As a result, R&D was kept localzed n the home regon, wth some lmted remote nvestment to support foregn manufacturng facltes (Vernon, 1966, Caves, 1971, Hymer, 1976, Rugman, 1981). Later, when R&D nvestment abroad began to emerge wth a stronger presence, t was seen as a tool to access foregn scentfc knowledge and technologcal capabltes consdered to be relevant for the frm (Florda, 1997, Kuemmerle, 1999, Serapo et al., 2000). In both contexts, the geographc localzaton of knowledge spllovers requres local nvolvement to access knowledge and socal networks that facltate the transfer of external knowledge to the frm. Further studes have found that multnatonals consder potental knowledge spllovers opportuntes when makng R&D nvestment n foregn subsdares (Fenberg and Gupta, 2004) and when locatng foregn manufacturng operatons (Chung and Alcacer, 2002). In a more recent paper, Macher and Mowery (2004) go further to suggest that when knowledge spllovers or other capabltes among segments of the value chan matter for nnovaton, nnovaton actvtes are lkely to follow the nternatonalzaton of supply chan actvtes. On the other hand, f nnovaton s not mpacted by these spllovers, the locaton of segments of the ndustry value chan should have lttle nfluence on the locaton of nnovaton actvtes. Yet, ths dea has not been drectly addressed n the lterature. Ths research tres to advance our understandng of ths noton by analyzng the locaton of nnovaton actvtes n two technology segments that are expected to have dfferent relance 13

14 on knowledge spllovers. In the second secton we descrbed the movement of the rare earth element supply chan away from the US and the subsequent changes n the locatons of rare earth technology nnovaton. Whle overall the locaton of nnovaton actvtes s movng away from the US, some nnovaton actvtes reman n the US and others do not. Our emprcal analyss ams to examne the nature of knowledge utlzed by patentng actvty n rare earth catalyst and magnet technology patents. 4 Emprcal Analyss Ths study uses patents ssued by the Unted States Patent and Trademark Offce (USPTO) as a proxy for nnovatve actvty n rare earth catalysts and magnets. There s a substantal pror body of lterature argung that patents are a useful measure of nnovatve actvty (Basberg, 1987, Acs et al., 2002). Although there are well documented lmtatons to the use of patent data, n partcular the fact that not all nnovatons are patented, Grlches (1990) as well as Patel and Pavtt (1995) have documented that patents are a reasonable proxy for nnovaton especally n hgh technology ndustres. Archbug and Panta (1996) clam that patent data can provde estmates of nnovatve actvty at the frm, ndustry, and country levels, whle Pavtt (1985) concludes that patents provde a consstent pcture of sectoral patterns of nnovatve actvtes. Whle many studes support the use of patents as a measure of nnovaton output, patent ctatons are also one of the most traceable records to understand crtcal knowledge flows (Jaffe et al., 1993, Almeda, 1996, Mowery et al., 1996, Stuart and Podolny, 1996). Ctatons are ncluded n patent applcatons by the nventor and the patent examner to help delmt the patent grant by dentfyng pror art of relevance to the focal patent. If one consders a gven patent, backward ctatons lsted n the patent can be used to ndcate the locatons and tmng of pror 14

15 nnovaton actvtes that have generated knowledge useful for generatng the gven patent. Therefore, one can use ctatons to look at whether the nature of knowledge utlzed for knowledge generaton n rare earth catalyst and magnet technology s changng over tme. These clams make patent studes a useful measure for nnovaton wthn a system boundary, pror knowledge utlzed for the generaton of new knowledge and a good metrc to address the research questons hghlghted above. For ths study, two regresson models at the patent level are developed to statstcally determne f there s a sgnfcant change n the propensty for rare earth magnet and rare earth catalyst nnovaton actvtes n the US to utlze prevously generated local knowledge versus knowledge generated by smlar nnovaton actvtes abroad followng the nternatonalzaton of the rare earth supply chan and producton actvtes. 4.1 Data development In ths emprcal analyss we use USPTO patentng actvty n rare earth magnet and rare earth catalyst technologes over the tme perod We utlze patent classfcatons provded by the USPTO to buld the relevant patent datasets for rare earth magnet and catalyst technologes. Ths s accomplshed by locatng several patents that perfectly ft nto each technology. Followng the backward and forward ctatons of each patent and the ctatons of these ctatons, we comple an extensve lst of patent classes that may correspond to each technology [more detal on ths avalable from the authors upon request]. From ths classfcaton lst for each technology, 8 patent classes and 17 patent classes shown n table 3 were chosen to represent rare earth magnet and catalyst technology, respectvely. The fnal patent datasets were then compled usng a keyword search wthn the prevously chosen relevant patent classes. The keyword search was necessary because, for example, n the descrpton of patent class 148/101 15

16 we see that a process for generatng a ferrte permanent magnet materal would qualfy. However, we are only nterested n process technology for manufacturng rare earth permanent magnet materals. Smlarly, n the descrpton of patent class 502/320 we see that a catalyst composton consstng of alumnum would qualfy. For ths class we are only nterested n catalyst compostons consstng of scandum or yttrum. The keyword search returned patents that contaned rare earth keywords also shown n Table 2 anywhere wthn the patent document. After removng patents assgned to ndvdual nventors, the fnal combned dataset ncluded 1879 patents of whch 637 are rare earth magnet patents and 1242 are rare earth catalyst patents. Table 2 Keywords and USPTO classfcatons used to develop patent dataset Rare Earth Elements Rare Earth Magnet Rare Earth Catalyst Rare Earth 148/ /304 Lanthande 148/ /303 Lanthanum, La 148/ /302 Cerum, Ce 148/ /314 Praseodymum, Pr 148/ /320 Neodymum, Nd 148/ /322 Promethum, Pm 148/ /323 Samarum, Sm 148/ /327 Europum, Eu 502/332 Gadolnum, Gd 502/341 Terbum, Tb 502/346 Dysprosum, Dy 502/348 Holmum, Ho 502/351 Erbum, Er 502/354 Thulum, Tm 502/355 Ytterbum, Yb 502/65 Scandum, Sc 502/73 Yttrum, Y Lutetum, Lu 16

17 The analyss uses four peces of nformaton found n patent applcatons: (1) locaton nformaton measured by frst nventor home locaton to dentfy the locaton of nnovaton actvtes, (2) patent applcaton year, (3) complete patent classfcaton lst to dentfy technology classes, and (4) patent ctatons to dentfy knowledge used by the gven patent. The analyss then uses three peces of nformaton found n patents lsted as ctatons of patent applcatons: (1) patent number s used to dentfy wthn technology and outsde knowledge (e.g., f the patent number lsted as a ctaton for a magnet patent s ncluded n the set of dentfed magnet patents, then t s dentfed as wthn technology knowledge), (2) locaton nformaton measured by frst nventor home locaton to dentfy the locaton of the nnovaton actvty that generated the cted patent, and (3) applcaton year used to dentfy f the cted patent was appled for wthn seven years pror to the applcaton of the ctng patent. We lmt ctatons to those appled for seven years pror to the applcaton of the ctng patent for two reasons. Frst, snce our patent dataset covers the years 1975 to 2002, ctatons for a patent appled for n 1978 would have only three pror years of patents from whch to draw. However, a patent appled for n 1995 would have 20 pror years of patents from whch to draw. Therefore by lmtng the ctaton lag to seven years, all patents ncluded n the ctaton dataset have an equal number of years from whch to draw ctatons. Second, we are emprcally nterpretng ctatons as a measure of the knowledge base whch has been expanded by the knowledge contaned wthn the patent as well as the transfer of tact knowledge or n other words a knowledge spllover among dfferent sets of nnovaton actvtes. We assume that ctatons to patents appled for more than seven years pror represent codfed knowledge. Usng the patent nformaton explaned above we measure 10 varables for our two datasets of rare earth magnet and rare earth catalyst patent applcatons between 1982 and

18 For each patent we measure the locaton of the frst nventor s home at the country level and the patent applcaton year. We use ths nformaton to generate two dummy varables. Frst, a varable denotes whether the patent s locaton s n the US or outsde of the US (US). Second, a varable denotes f the patent s applcaton year was before or after 1990 (d), whch corresponds to the begnnng of Chnese domnance n the producton of rare-earth materals. Ths subsequently led to the nternatonalzaton of the rare earth supply chan begnnng wth raw materals, movng to raw materal processng and the producton of rare earth technology applcatons. For the remanng patent level varables, we frst develop a procedure to dentfy the complete techncal classfcaton lst of knowledge developed and utlzed by a gven patent. The techncal classfcatons are based on USPTO patent classfcatons. The techncal classfcaton lst begns as the complete lst of classfcatons assgned by the USPTO to the gven patent. Then we examne the complete classfcaton lst of a patent cted by the gven patent. If the classfcaton lst of the cted patent contans zero classfcatons n common wth the techncal classfcaton lst, then the techncal classfcaton lst for our patent s augmented wth the man USPTO classfcaton of the cted patent. If the classfcaton lst of the cted patent contans at least one common element, then no addtonal classfcatons are ncluded n the techncal classfcaton lst. The complete techncal classfcaton lst s determned by examnng each patent cted by the gven patent. We then use the techncal classfcaton lst to categorze the ctatons made to prevous patents nto four categores. The frst category s pror knowledge ncluded n our patent datasets representng rare earth catalyst or magnet technology, also classfed by the USPTO wth a matchng classfcaton wth at least one element of the techncal classfcaton lst generated for 18

19 the gven patent and also generated by an nnovaton actvty located n the US. Ths category s called US wthn technology class knowledge (C uw ). If the gven patent s also generated by an nnovaton actvty located n the US ths category represents local techncal knowledge spllovers. For a technology where knowledge spllovers matter for nnovaton actvtes, we would expect ths category to receve the most ctatons by the gven patent. The second category of knowledge s NonUS wthn technology class knowledge (C nw ) whch s smlar to C uw knowledge except that t was generated by nnovaton actvtes located outsde of the US. If we agan consder that the gven patent s generated by an nnovaton actvty n the US, then ths category represents techncal knowledge generated by nnovaton actvtes located outsde of the US. As suggested by other researchers, as an ndustry nternatonalzes and frms gan access to knowledge outsde of ther home regon as well as develop decentralzed R&D networks, we would expect the second category of knowledge to receve an ncreasng amount of ctatons by the gven patent. If knowledge spllovers matter for a technology, we would also expect the second category of knowledge to reman less mportant than local knowledge measured by the frst category of knowledge. The thrd and fourth categores of knowledge are US outsde knowledge (C uo ) and NonUS outsde knowledge (C no ). These categores of knowledge whle havng at least one classfcaton element n common wth the complete techncal classfcaton lst for the gven patent are not ncluded n the patent datasets representng rare earth catalyst or magnet technology. We measure these categores because prevous researchers have found that techncal knowledge s often used for more than one technology applcaton. All ctatons to patents n any of the four categores appled for more than 7 years pror to the ctng patent s applcaton year 19

20 are dscounted from the data to avod ctaton truncaton ssues and ctaton of codfed knowledge. The techncal classfcaton lst representng the technology class of the patent s then employed on the entre USPTO patent database to measure the number of avalable patents for ctaton n each of the four categores relevant for our estmaton: US wthn technology patents (k uw ), the number of NonUS wthn technology patents (k nw ), the number of US outsde technology patents (k uo ), and the number of NonUS outsde technology patents (k no ). The USPTO patent contans knowledge that s avalable for our patent to have used f the followng two condtons are satsfed (1) f the applcaton year of the USTPO patent occurs less than seven years pror to the applcaton year of our patent and (2) the complete lst of classfcatons assgned to the USPTO patent contans at least one common classfcaton wth the complete techncal classfcaton lst generated for our patent. Gven the USPTO patent s found to be avalable for our patent to cte, we assgn the patent to one of our four categores k uw, k nw, k uo, or k no. If the USPTO patent s contaned n our rare earth magnet or rare earth catalyst dataset then t s assgned as an avalable wthn technology class patent (k uw or k nw ). Otherwse, the USPTO patent s assgned as an avalable outsde technology patent (k uo or k no ). If the USPTO patent s from the US then t s assgned as an avalable US patent (k uw or k uo ). Otherwse, the USPTO patent s assgned as an avalable NonUS patent (k nw or k no ). The above data drectly measured and counted usng the rare earth magnet and rare earth catalyst data are then combned to form three addtonal varables. Frst, for each patent we calculate the percent of knowledge utlzed by the gven patent that was prevously generated by nnovaton actvtes located n the US (perus) usng Equaton We then calculate the 20

21 percent of knowledge utlzed that was prevously generated by nnovaton actvtes wthn the same technology class (perwthn) usng Equaton 2. Fnally, we calculate the percent of patents avalable for ctaton that orgnate from local nnovaton actvtes (perus_aval) or n other words were prevously generated by nnovaton actvtes n the same country usng Equaton 3. perus uw uo = (1) C perwthn perus uw C + C uw nw + C + C C + C nw uo + C + C + C uo no uw nw = (2) aval C uw k + k nw + k + k + C uo no uw uo _ = (3) k + k no The descrptve statstcs for the data are shown frst for rare earth catalysts and second for rare earth magnets n Table 3. The correlaton statstcs are shown n Table 4. In the next secton, we descrbe the regressons employed to analyze the nature of knowledge utlzed by nnovaton actvtes n the US and abroad followng the nternatonalzaton of supply chan and producton actvtes for rare earth catalyst and magnet technologes. The regresson s performed at the patent level. 21

22 Table 3 Descrptve statstcs Rare earth Catalyst Rare earth Magnet Varable Descrpton Mean SD Count Mn Max C lw Local wthn technology ctatons C gw Global wthn technology ctatons C lo Local outsde ctatons C go Global outsde ctatons k lw Avalable local wthn technology patents k gw Avalable global wthn technology patents k lo Avalable local outsde patents k go Avalable global outsde patents US 0-1 locaton dummy varable d 0-1 tme perod dummy varable perlocal_aval Percent local patents avalable perlocal Percent local ctatons made perwthn Percent wthn technology ctatons made C lw Local wthn technology ctatons C gw Global wthn technology ctatons C lo Local outsde ctatons C go Global outsde ctatons k lw Avalable local wthn technology patents k gw Avalable global wthn technology patents k lo Avalable local outsde patents k go Avalable global outsde patents US 0-1 locaton dummy varable d 0-1 tme perod dummy varable perlocal_aval Percent local patents avalable perlocal Percent local ctatons made perwthn Percent wthn technology ctatons made

23 Table 4 Correlaton statstcs Rare earth Catalyst 1. C lw 2. C gw C lo C go k lw k gw k lo k go US d perlocal_aval perlocal perwthn Rare earth Magnet 1. C lw 2. C gw C lo C go k lw k gw k lo k go US d perlocal_aval perlocal perwthn Regresson Analyss Dependent varable The dependent varable n the frst regresson analyss s the percent of US ctatons (perus) made by patent. The regresson analyss s conducted separately for rare earth catalyst and magnet technologes. In both rare earth catalyst and magnets, we see from Fgure 3 that the percentage of nnovaton actvtes conducted n the US s decreasng over tme, albet decreasng sgnfcantly more for rare earth magnet technology. Therefore, f knowledge spllovers are mportant for technology development n ether technology, we would expect perus to have a decreasng trend over tme. However, f a decreasng trend s found for the dependent varable, t may also suggest that for US nnovaton actvtes knowledge spllovers are becomng less 23

24 mportant as a global knowledge network develops perhaps drven by the nternatonalzaton of supply chan actvtes and offshorng decsons by US frms. If an ncreasng trend s found for the dependent varable, t suggests the locaton of nnovaton actvtes s drven by somethng other than knowledge spllovers because both nnovaton actvtes located n the US and abroad are ncreasngly dependent on knowledge generated by pror US nnovaton actvtes. Snce the dependent varable s a percentage that takes the values of 0 and 1 as well as percentages between 0 and 1, we perform the standard logt transformaton whch s gven by L perus ln (4) ( perus ) = 1 perus To drectly nterpret the coeffcents of our regressons, we wll need to transform the results back nto the orgnal percentage metrc. However, before performng the transformaton we employ the followng equatons to substtute for 0 and 100 percent data ponts whch present problems for the logt transformaton (Equaton 4) and must be adjusted away from the extreme values (Neter et al., 1983). 1 f perus = 0 2n perus = (5) 2n 1 f perus = 1 2n where n = C uw, + C nw, + C uo, + C no, Model and crtcal varables The purpose of the regresson s to statstcally determne f there s a sgnfcant change n the propensty for rare earth magnet and rare earth catalyst nnovaton actvtes n the US to utlze prevously generated local knowledge versus smlar nnovaton actvtes abroad. To perform ths evaluaton, two ndependent varables are of crtcal mportance. The frst s a

25 varable (US) that s employed to measure the overall propensty dfference for prevously generated local knowledge to be utlzed by nnovaton actvtes n the US and abroad. If knowledge spllovers are sgnfcant for the development of rare earth catalyst or magnet technology, we would expect the coeffcent for US to be postve and sgnfcant ndcatng that nnovaton actvtes n the US utlze a hgher percentage of knowledge prevously generated n the US than abroad. Conversely, a postve and sgnfcant coeffcent also ndcates that nnovaton actvtes outsde of the US use a lower percentage of knowledge generated by nnovaton actvtes n the US or n other words outsde of the country of the frst nventor lsted on the patent. A second 0-1 varable (d) s utlzed to capture sgnfcant changes n the propensty trends before and after 1990, whch corresponds to sgnfcant nternatonalzaton of the rare earth supply chan and the begnnng of Chnese domnance n the producton of rare-earth materals. If a postve and sgnfcant coeffcent s found for d, then pror knowledge generated by nnovaton actvtes located n the US are more mportant for the development of new knowledge wthn the US and abroad. We also employ one crtcal control varable (perus_aval) that controls for the percent of patents avalable for ctaton that were generated by prevous nnovaton actvtes located n the US. The general dea beng that f a patent randomly makes ctatons to avalable patents, then we would expect the percent of US ctatons wll be equal to the percent of US patents avalable for ctaton. Ths varable also controls for changes n nnovaton trends over tme. By employng ths control varable, we are able to examne the dfferences n the nature of knowledge beng utlzed for nnovaton actvtes despte the changng shares of patents beng generated by a partcular locaton. 25

26 A lnear regresson model s used to estmate the mpact of the ndependent varables on the propensty for a successfully appled patent to utlze knowledge prevously generated by US nnovaton actvtes. In Model 1 we test for a sgnfcant change n the propensty for nnovaton actvtes to utlze US knowledge after 1990 n both the US and abroad. Model 1a s specfed n the followng form: perus ln = α + βus + λd + ϕperlocal _ aval 1 perus (6) To more closely examne the change n the US, we conduct a second run (Model 1b) that solates the change n propensty for US nnovaton actvtes to utlze US knowledge by ncludng the nteracton (US*d). Ths nteracton term s crtcal to determne f any trend n the percent of US knowledge utlzed by nnovaton actvtes s drven by the mportance of knowledge spllovers or by the decreasng percentage of nnovaton actvtes conducted n the US. Model 1b s specfed n the followng form: perus ln = α + βus + λd + γ + 1 perus ( US * d ) ϕperus _ aval (7) 5 Emprcal Results and dscusson 5.1 Regresson results Table 5 shows the regresson results at the patent level for rare earth catalyst and magnet technologes. The frst mportant outcome n Model 1a for both technologes s the coeffcent for US for both rare earth catalysts and magnets s postve and sgnfcant (0.9, p < and 0.6, p < for catalysts and magnets, respectvely). Ths result ndcates that nnovaton actvtes 26

27 undertaken wthn the US utlze sgnfcantly more knowledge from US nnovaton actvtes than those performed outsde of the US. Ths may suggest that knowledge spllovers play an mportant role n technology development for catalysts and magnets. Ths result remans consstent n Model 1b where we separate out the effect for US nnovaton actvtes after 1990 further suggestng that knowledge spllovers may play an mportant role n these technologes. Table 5 Regresson results at patent level by technology, rare earth magnet and catalyst Dependent Varable: ln(perus/(1-perus)) Logstc transform of percent US ctatons Rare earth Catalyst Rare earth Magnet Model 1a 1b 1a 1b US 0.90*** 0.87*** 0.60*** 0.28** 0-1 dummy locaton (0.06) (0.10) (0.09) (0.14) d 0.26*** 0.24** ** 0-1 dummy tme perod (0.08) (0.10) (0.10) (0.12) US*d ** US after 1990 (0.13) (0.19) perlocal_aval 4.26*** 4.28*** 2.85*** 2.67*** Random ctaton control (0.32) (0.32) (0.54) (0.54) Intercept -2.71*** -2.71*** -1.73*** -1.52*** (0.20) (0.20) (0.24) (0.25) Adj R Observatons Standard errors n parentheses ** p 0.05 *** p The next mportant results deal wth the coeffcent for the tme perod dummy varable (d). In Model 1a and 1b for rare earth catalysts, we fnd the coeffcent to be postve and sgnfcant (0.26, p < and 0.24, p < 0.001, respectvely). Ths ndcates that despte the nternatonalzaton of the rare earth supply chan after 1990 the percent of knowledge generated by US nnovaton actvtes and subsequently used for nnovaton actvtes wthn the US and abroad has ncreased. Ths then suggests that knowledge spllovers may not play an mportant role n catalyst technology development because NonUS. The coeffcent for the nteracton term 27

28 (US*d) also confrms ths result because t s nsgnfcant. Therefore, ths further suggests there s another drver for key catalyst nnovaton actvtes to be located n the US. In contrast, Model 1a for rare earth magnets we fnd an nsgnfcant coeffcent for d suggestng that after 1990 there s no change n the percent of knowledge generated by prevous US nnovaton actvtes to be used for magnet technology development despte the nternatonalzaton of the rare earth supply chan and producton as well as the decrease n the percentage of nnovaton actvtes located wthn the US. Ths result suggests two possble realtes. Frst, despte the nternatonalzaton of the rare earth supply chan and producton actvtes, rare earth magnet nnovaton actvtes outsde of the US contnue to rely on prevous knowledge generated by nnovaton actvtes n the US. Second, wth the nternatonalzaton of the rare earth supply chan and producton actvtes, rare earth magnet nnovaton actvtes n the outsde US now rely more on prevous knowledge generated outsde of the US, whle nnovaton actvtes the reman n the US now rely even more on prevous nnovaton actvtes also conducted n the US. The former realty suggests the globalzaton of knowledge used for nnovaton actvtes for rare earth magnet technology, whle the latter suggests the localzaton of nnovaton actvtes and the mportance of knowledge spllovers. The coeffcent of d and the nteracton term (US*d) n Model 1b for rare earth magnet technology (-0.35, p < 0.01 and 0.57, p < 0.01, respectvely) suggests the localzaton of knowledge utlzed for rare earth magnet nnovaton actvtes and the ncreasng mportance of knowledge spllovers. Innovaton actvtes outsde of the US after 1990 rely less on knowledge generated by US nnovaton actvtes and nnovaton actvtes n the US rely more on pror US nnovaton actvtes. 28

29 Overall, the regresson results suggest that locatons and technologes respond dfferently to the nternatonalzaton of relevant supply chan and producton actvtes. Furthermore, for technologes where knowledge spllovers are crtcal for subsequent nnovaton actvtes, the nternatonalzaton of supply and producton actvtes are lkely to drve nnovaton actvtes away from the home regon. However, our regresson analyss does not allow us to dstngush between the followng scenaros. If we consder that a share of nnovaton actvtes n the US are generated by frms only developng technology for a local market utlzng local knowledge and the rest of the nnovaton actvtes generated by frms developng technology for global markets utlzng local and global knowledge. In the frst scenaro, the propensty for nnovaton actvtes n the US to utlze pror knowledge generated n the US could ncrease f the frms focused on a local technology market begn to use proportonately more US knowledge whle the share of nnovaton actvtes for local and global markets remans the same. In the second scenaro, the share of nnovaton actvtes performed for local markets could ncrease possbly suggestng that frms developng technology for global markets have relocated outsde of the home regon. To evaluate these scenaros, we develop an nnovaton model n the next secton. In all of our regressons, the control for random percent of US patents avalable for ctaton (perus_aval) s statstcally sgnfcant (p < 0.001). Ths suggests our method of measurng the number, locaton and technology class of pror nnovaton actvtes producng knowledge applcable to an nnovaton actvty s sgnfcantly correlated wth the actual number of ctatons n each ctaton category made by a patent. Therefore, we utlze the number of avalable patents n each ctaton category wthn our model. 29

30 5.2 Modelng knowledge spllovers and the locaton of nnovaton actvtes We consder an nnovaton n a gven technology class c (e.g. rare earth magnets) whch has taken place n one locaton. The nnovaton can be generated by a specfc R&D project, by a project manager, or by a product lne worker. For every nnovaton there s a set of pror knowledge generated by other nnovatons that contrbutes to nnovaton s development. To be able to explore the role of spllovers, the set of pror knowledge wll be organzed n 4 broad categores assocated to prevous nnovaton actvtes conducted by frms wthn the same man ndustry, frms outsde of ths ndustry, unverstes, and nsttutons such as natonal laboratores and government organzatons. The frst category s pror knowledge n technology class c also generated n locaton l, whch s called local wthn class knowledge (C lw ). For an nnovaton actvty located n the US, ths category s analogous to US wthn technology class knowledge (C uw ) used n the regresson analyses. Also, snce our regresson analyses are only concerned wth two locatons (US and NonUS), for an nnovaton actvty located outsde the US the category C lw s analogous to NonUS wthn technology class knowledge (C nw ). The second set of knowledge s global wthn class knowledge (C gw ) whch s defned as pror knowledge n technology class c generated outsde of locaton l. The thrd and fourth sets of knowledge are local outsde knowledge (C lo ) and global outsde knowledge (C go ). These sets of knowledge are outsde of the technology class c of nnovaton. Accordng to the regresson analyses for US nnovatons the percent of local or US ctatons s sgnfcantly correlated wth the percent of local or US patents prevously generated. Therefore, we use ths to suggest that the quantty of knowledge n each of the four categores, C lw, C gw, C lo, and C go, utlzed by nnovaton s a functon of the quantty of prevously generated knowledge avalable n each of the matchng four categores: local wthn class 30