Knowledge Production Function in South Korea: An Empirical Analysis

Transcription

1 Knowledge Producon Funcon n Souh Korea: An Emprcal Analyss Dong-Jn Chung, Sangsup Cho, and Jung Mann Lee Absrac In hs paper we esmae knowledge producon funcon for 15 Souh Korean ndusry secors usng panel daa. To accommodae he nfluence of ner-secoral neracons on he creaon of knowledge, we esmaed parameers for relaed knowledge producon funcons usng he Dynamc Seemngly Unrelaed Regresson (DSUR) model proposed by Mark e al. (2005). We found he elascy of knowledge producon wh respec o he sze of research saff o be 0.25 and ha wh respec o he exsng sock of knowledge o be The fac ha he elascy of new knowledge creaon wh regard o he exsng knowledge sock s below 1 n Souh Korea corroboraes he vew ha he rae of long-erm growh of s economy s chefly deermned by elasces relaed o producon funcons of goods and servces and he rae of populaon growh, and ha s governmen, o ensure a connued growh for he Korean economy, mus shf he focus of R&D polces from he curren drec nervenon-cenered model o one conssng of ndrec measures, namely supporng knowledge managemen and dffuson and he creaon of a knowledge sharng sysem. Keywords Knowledge-based economc growh, knowledge producon funcon, conegraed coeffcen, DSUR, R&D polcy. I. INTRODUCTION N mos recen endogenous models of economc growh, I macro producon funcons nclude knowledge sock or R&D sock. In he growh model proposed by Wezman (1998), for example, he creaon of new knowledge s effeced hrough dscovery of new combnaons of exsng knowledge, and hs connuous creaon of knowledge drves he connued expanson of he economy. In a smlar ven, Jones (2005) argued ha knowledge, by vrue of s beng a non-compeve wealh, plays a capal role n he growh of an economy. Meanwhle, Caballero and Jaffe (1993), n her dscusson of he mporance of R&D n he producon of knowledge, gves an n-deph reamen o he srucural aspecs of knowledge accumulaon. Wezman (1996, 1998) pcured he creaon of knowledge as a form of economy of scale realzed from he exsng sock of knowledge, whle Jones (1995, 2002) and Korum (1997) proposed growh models based on an assumed phenomenon of dmnshng reurns o scale. For Olsson (2000), knowledge Dong-Jn Chung s wh he Insuon for Informaon Technology Advancemen, 58-4 Hwaam-Dong, Yuseon-Gu, Daejeon, Souh Korea. Sangsup Cho s wh 120-1, Anseo-dong, Cheonan, Chungnam, S. Korea. (correspondng auhor: ; e-mal: choss@offce.hoseo.ac.kr ). Jung Mann Lee s wh he Insuon for Informaon Technology Advancemen, 58-4 Hwaam-Dong, Yuseon-Gu, Daejeon, Souh Korea. producon funcons are a knd of concave funcons wh regard o knowledge opporunes. Exsng knowledge opporunes, he conends, even f hey connue o be used o produce new knowledge, may ulmaely dsappear compleely, becomng an empy se. Hence, n knowledge-based growh models, he ssue s less he role of knowledge accumulaon n economc growh han he economc conrbuon of he knowledge producon funcon. The esmaon of he magnude of he parameers of knowledge producon funcons has as s sarng pon wo muually conradcory vews on he prospecs for long-erm economc growh whn endogenous growh heores. The underlyng assumpon of he endogenous models of economc growh developed by Romer (1990), Grossman e al. (1991) and Aghon e al. (1992), for nsance, s ha he conrbuon of he exsng sock of knowledge, as reusable elemens, o he creaon of new knowledge, keeps he scale of knowledge producon consan. Endogenous growh models of hs knd suppose he exsence of a scale effec, whereby s he sze of R&D work force engaged n he producon of knowledge ha ulmaely deermnes he rae of economc growh. Jones (1995) and Korum (1997), on he oher hand, propose weaker endogenous growh models, under whch he producon of knowledge s subjec o dmnshng reurns o scale wh regard o he aggregae sock of knowledge. Under hs premse, he rae of ncrease n he sze of R&D work force deermnes he rae of economc growh. In oher words, he growh apprecaes no scale effec and s chefly deermned by he rae of long-erm populaon growh. Alhough here s lle doub as o he mporance of knowledge producon funcons whn growh heores, aemps o emprcally measure hem have been hus far few. Ths sae of affars has o do, on he one hand, wh he nsuffcency of avalable daa, and wh he absence of an adequae measuremen mehod, on he oher. In hs sudy, we esmae knowledge producon funcons for 15 Souh Korean ndusry secors usng secoral panel daa from a perod from 1982 o In acknowledgemen of he fac ha he creaon of knowledge n an ndusry secor benefs from he exsng sock of knowledge n oher secors, we esmae he parameers of knowledge producon funcons usng he DSUR (Dynamc Seemngly Unrelaed Regresson) model proposed by Mark e al. (2005). 1 1 The mporance of ner-secor neracons s acknowledged n mos sudes on he spllover of R&D, ncludng by Grlches (1998). 80

2 Varables relaed o knowledge producon funcons esmaed n hs sudy are he number of paens regsered, ha of research workers and he surrogae varable for he sze of knowledge sock, whch s he cumulave number of paens regsered snce Treang hese economc varables quanavely requres a measuremen echnque capable of conrollng nonsaonary panel daa. Kao e al. (2000) demonsraed ha, when a conegraon relaonshp can be esablshed n nonsaonary panel daa, whch s he case of he daa n hs sudy, he conegraed coeffcen can be esmaed usng one of he followng hree mehods: OLS wh bas-correcon, FM-OLS (Fully Modfed OLS) and DOLS (Dynamc OLS). However, hs mehod proposed by Kao e al. ends o resul n a low effcency of parameer esmaes, when here exs conemporaneous correlaons beween cross-seconal uns of analyss. To sdesep hs analycal ssue, one can eher resor o he SURE mehod proposed by Zeller (1962) based on he radonal panel esmaon mehodology or he echnque proposed by Hsao (1986), whch consss n elmnang correlaons exsng beween he uns of analyss by addng or subracng he mean value of cross-seconal uns o or from he daa. More recenly, Mark e al. (2005) came up wh a sgnfcanly more effcen esmaor han exsng mehods for compung conegraed coeffcens: DSUR. In hs sudy, we chose he DSUR esmaor developed by Mark e al. (2005) for he esmaon of knowledge producon funcons for Souh Korean ndusres. The prmary conrbuons of hs sudy are as follows: Frs, by esmang knowledge producon funcons, a holy debaed concep ha s a cenral componen of economc growh heores, usng comparavely long-erm daa spannng a wde range of Souh Korean ndusry secors, we offer a bass for selecng economc growh heores ha are bes adaped o he local knowledge economy envronmen. Second, he objecve and opmal esmaes of knowledge producon funcons provded by hs sudy can asss polcymakng n R&D and forecasng of relaed polcy effecs. The res of hs paper s organzed as follows: n Chaper 2, we descrbe n deal he mporance of knowledge producon funcon by presenng he economc sgnfcance of he parameers of knowledge producon funcon whn growh heores from recen years, and brefly presen he measuremen mehods requred o esmae he knowledge producon funcons ha are relevan o hs sudy. In Chaper 3, we presen he daa used n he esmaon and he resuls of he esmaon. Fnally, n Chaper 4, we summarze he fndngs of hs sudy and presen mplcaons for R&D polces, ncludng polcy prores mos lkely o ensure connued economc growh. II. ESTIMATION METHODOLOGY A. Theorecal Background In Jones (1995, 2005) R&D-based growh model, knowledge producon funcons and relaed parameers are assgned he followng roles n a counry s economc growh. For he sake of smplcy, le us say ha he growh of a naonal economy s deermned by s volume of labor and aggregae sock of knowledge. In oher words, Y = A (1) σ L Y Here, le us assume ha σ > 0. Labor, one of he facors of producon, s dsngushed no ha for he producon of goods and ha for he producon of knowledge, accordng o he followng srucures of deermnaon: n L = L0e (2) L = L + L (3) Y A any gven pon n me, knowledge oupu, anoher facor of producon, s deermned n he followng manner: λ A A A & = νl A (4) Here, ν > 0 and A & corresponds o he newly-produced knowledge addng o he exsng sock. φ s he parameers of he knowledge producon funcon, he crucal elemens n knowledge-based growh models. When a knowledge producon funcon s conceved as n equaon (4), he rae of ncrease n knowledge oupu can be deermned n wo dfferen ways, dependng on he magnude of φ. If φ < 1, he rae of knowledge producon ncrease wll be deermned as n he followng: 2 λn = 1 φ φ g A (5) In equaon (5) he rae of knowledge producon growh s proporonae o ha of populaon growh. Accordngly, he level of a counry s economc producon or s level of producon per capa s dependen on he populaon sze of ha economy. However, when φ = 1, he knowledge producon funcon n equaon (4) may be gven a smplfed expresson as below: A = νl A (6) Equaon (6) shows ha he producon of knowledge grows n funcon of λ, exponen of he sze of R&D work force. Hence, economc growh of a counry s deermned by s sze of populaon. In oher words, growh raes n counres wh larger populaons are hgher han n counres wh smaller populaons [scale effec]. λ A 2 See Jones (2005), pp for seps leadng o equaon (4). 81

3 The parameer wh a decsve effec on growh, whch s also he mos mporan elemen n Jone s R&D-based growh model, whch assumes he sze of φ s less han one, correspondng o he conrbuon of he exsng sock of knowledge o he creaon of new knowledge. Romer (1990), Grossman e al. (1991) and Aghon e al. (1992) developed her endogenous growh models on he assumpon ha φ = 1. Jones (1995) and Korum s (1997) models, on he oher hand, assume ha φ < 1, whch explans he more modes rae of growh under hese models. Furhermore, he dfferen szes of φ call for dfferen polcy measures. If he parameer esmae of he knowledge producon funcon n a secor s φ = 1, hs warrans aggressve polcy measures o encourage R&D, beng an ndcaon ha economc growh may be acceleraed hrough new creaon of knowledge. Ifφ < 1, hs means ha economc growh s raher deermned by elasces relaed o producon funcons of goods and servces and long-erm rae of populaon growh, hus makng aggressve governmen polcy n he R&D secor less pernen [see Jones, 2005, p.1093]. In hs sudy, we calculae he aggregae sock of knowledge usng per-secor paen regsraon daa for 15 Souh Korean ndusry secors. Then, we compue he parameers of knowledge producon funcon by esmang equaon (4) usng he measuremen mehod descrbed n he mmedaely followng secon of hs paper, and derve mplcaons for R&D polces from he resuls of hs esmaon. One hng ha mus no be overlooked n he esmaon of knowledge producon funcons for mulple ndusry secors s he ner-secor ransmsson of knowledge. In oher words he creaon of new knowledge n any gven secor benefs from knowledge spllover from oher secors, boh drecly and ndrecly. Hence, for greaer accuracy, one mus acknowledge muual nfluence beween dfferen ndusry secors, raher han supposng he creaon of new knowledge as an auonomous nra-secor process, and he esmaon mehod mus ake no accoun he economc effec of he knowledge spllover. III. METHODOLOGY The mehod used n hs sudy o esmae he parameers of knowledge producon funcons s he DSUR (Dynamc Seemngly Unrelaed Regresson) esmaor proposed by Mark, e al. (2005). DSUR esmaors resorng o smulaneous equaons are wdely consdered more effcen han conegraed vecor esmaors for panel daa, when he resduals of funcons are correlaed. A conegraed vecor esmaor for panel daa proposed by Moon (1999) s que smlar o DSUR. However, DOLS-based SUR s known o be more effcen, when dealng wh small samples, han he laer SUR esmaor based on DOLS [Kao e al. 2000]. 3 3 Wh large samples, he wo esmaors yeld dencal resuls. As hs sudy supposes he exsence of an nerlnkage beween he 15 ndusry secors suded, concernng he process of knowledge producon, s bes o esmae relaed conegraed coeffcens usng a sysem equaon. DSUR s an opmal choce, because he samples used n hs sudy mach n erms of he number of secors analyzed and years of me seres daa.e. balanced daa. We were able o confrm ha Mark e al. s DSUR esmaor was subsanally more effcen han smple DOLS, when each sample has a dfferen coeffcen, and he resduals of esmaon equaon are correlaed. 4 We se up a knowledge producon funcon as n he followng and esmae relaed parameers usng he DSUR esmaor: p = α + λ l + φ k + u (7) All lower-case symbols are log-ransformed varables [ex: k = ln( K ) ]. Here, p s he number of regsered paens for a gven ndusry secor, l he number of research workers, k he sze of he accumulaed sock of knowledge, and u he resdual erm proposed by Sakkonen (1991), sasfyng he assumpons needed for he esmaon. 5 In hs case, he DSUR esmaor for he correspondng coeffcen s as follows: ˆ β ˆ δ p _ dsur dsur = T P = p+ 1 W Ω uu W 1 T P = p+ 1 W Ω uu p In equaon (8), W = ( X, Z ), X = ( l, k ), and Z s he lead and lag varables of he wo ndependen varables. Ω, he long-erm conegraed esmae and he mos uu mporan esmae n he above esmaon, s esmaed n wo separae seps [see Marke e al, 2005, pp ]. The above DSUR esmaor, specfcally nended for cases where each of he samples has a dfferen coeffcen, enables he esmaon of he coeffcens usng he nformaon on he muual neracon beween he samples. The degree of he effcency of he DSUR esmaor vares dependng on he degree of dspary beween he coeffcens. In hs case, wheher he coeffcens are dencal across he samples can be esed usng he Wald sasc. The laer, esmaed under he resrcon ha all coeffcens are dencal across all samples, has an 2 asympoc χ dsrbuon, makes possble o es he resrcve hypohess a an approprae level of sascal sgnfcance. The advanages of he DSUR esmaor expressed n equaon (8) above, concernng hs sudy, are as follows: Frs, he DSUR esmaor s more effcen han oher esmaors, when esmang he parameers of knowledge producon 4 Esmaors by Kao e al, (2000) and Mark e al. (2003) are currenly he wo mos popular esmaors for emprcal analyss of panel daa. 5 For deals on how relaed varables were seleced and defned, refer o Chaper 3. (8) 82

4 funcons of ndusry secors beween whch neracon exss n hs area. Second, provded a sound paramerc desgn, knowledge producon funcons can be more accuraely esmaed hrough a paramerc esmaor han hrough a non-paramerc esmaor. Thrd and fnally, he larger he varey of samples, he greaer he conssency of DSUR esmaes; n oher words, parameer esmaes converge faser o rue parameer. In nex secon, we aemp o make he mos of hese mehodologcal advanages of he DSUR model for our esmaon of knowledge producon funcons for 15 Souh Korean ndusry secors based on daa from a perod beween 1982 and IV. EMPIRICAL RESULT A. Daa The daa used n hs sudy regard he number of paen applcaons and ha of research workers n 15 ndusry secors, over a 21-year perod beween 1982 and To conver he number of paens no he sock of knowledge of correspondng magnude, we chose 1982 as he benchmark year and esmaed he sock of knowledge capal of each of he 15 secors for hs year. The nal sock of knowledge capal was nduced usng equaon (7) gven below [see Hall, e al. 1995, p.270]: P K 0 = (9) g,1982 a ν + δ Here, K, 0 s he sock of knowledge capal n he year 1982 per ndusry secor, P, 1982 he number of paen applcaons n g aν 1982, and he average percenage change n he number of paen applcaons over he perod , assumng he rae of ncrease n he accumulaed sock of knowledge and number of paens remans consan. Fnally, δ sands for he rae of deprecaon for knowledge capal n each ndusry secor. The deprecaon rae on knowledge capal was se o 5% n annual rae over a perod of 20 years, correspondng o he paen erm. Afer obanng he sze of he nal sock of knowledge capal, we esmaed he oal sock of knowledge capal for each of he years suded by addng he number of new paens, n oher words, he new knowledge oupu for he year, o he deprecaon rae and he sze of accumulaed sock a he ouse, as n equaon (8) below: suded, and ha sarng from he year 1990, he rae of ncrease n he sock of knowledge surpassed ha n he number of research workers. 6 These vsual observaons, however, do no perm us o gauge he respecve conrbuons of he sze of research work force and he exsng sock of knowledge. Therefore, n order o precsely measure he exens of her conrbuons, one needs o proceed o a quanave esmaon Paens Sock Researchers Fg. 1 Trends n Accumulaed Sock of Knowledge and Research Work s Snce 1982 Table I lss he knowledge sock and sze of R&D work force n 15 ndusry secors for he years 1982 and The growh rae of knowledge accumulaon n Souh Korea over he pas 21 years s measured a 28% n annual average. The number of R&D workers rose a an annual average rae of 12% across all secors, excep he mber and wood produc ndusry. A comparave examnaon of 15 ndusry secors suded reveals ha he chemcal ndusry was he secor experencng he hghes accumulaon of knowledge n 1982, and ha hs poson was clamed n 2002 by he general machnery and equpmen secor. The sze of R& D work force was he larges n he chemcal secor n 1982, and n 2002, n he elecrc and elecronc ndusry. The compound annual growh rae (CAGR) of knowledge accumulaon was he hghes n he elecrc and elecronc secor, measured a 37%. The precson machnery secor opped he ls records a CAGR of 17% n he number of R&D workers. K ( δ + P (10) = 1 ) K 1 The wo graphs n Fg. 1 show he cross-secor rends n he aggregae sock of knowledge and number of research workers for 15 Souh Korean ndusres. The graphs ndcae ha boh he number of research workers and sze of he aggregae sock of knowledge ncreased seadly hroughou he enre perod 6 The knowledge accumulaon rend curve, when esmaed hrough a smple regresson equaon, has a me-varyng coeffcen of and s sascally sgnfcan. 83

5 TABLE I ACCUMULATED KNOWLEDGE STOCK AND NUMBER OF RESEARCH WORKERS BY INDUSTRY SECTOR Average Rae of Increase (%) Secor Food, Beverages and Tobacco (1) Texle, Apparel and Leaher (2) Tmber and Wood Producs (3) Pulp, Paper, Prn and Publshng (4) Peroleum and Perochemcal Producs (5) Knowle dge Sock Sze of R&D Work Knowle dge Sock Sze of R&D Work Knowle dge Sock Sze of R&D Work , , Chemcals (6) 1,000 1,375 1,505 10, Rubber and Plasc Producs (7) Nonmeal Mneral Producs (8) Basc Meal Producs (9) Fabrcaed Meal Producs (10) General Machnery and Equpmen (11) Elecrc and Elecroncs (12) Precson Machnery(13) Transporaon Equpmen (14) Furnure and Oher Manufacured Goods (15) , , ,596 6, , , , , , Toal 3,852 9,013 6,876 93, V. ESTIMATION RESULTS Ths sudy esmaed knowledge producon funcons for 15 ndusry secors n Souh Korea over a 21-year perod beween 1982 and 2002, usng he parameer esmaes explaned n Chaper 2 of hs paper. Before proceedng o he emprcal analyss, we examned he correlaons ha may exs beween ndusry secors suded, n he area of knowledge producon. 7 We used a smple DOLS esmaor and esmaed a knowledge producon funcon va equaon (7) for each of he 15 secors. Nex, usng he coeffcen esmaes so obaned, we calculaed resdual erms for each secor and examned he correlaons beween he resdual esmaes. Table II provdes he coeffcens of correlaon beween he 15 secors suded. The coeffcens of correlaon were generally hgh beween mos secors. These correlaon daa, refleced n he esmaon of he parameers of knowledge producon funcons, can conrbue oward he greaer effcency of he esmaor. In oher words, he degree of correlaon exsng beween hese 15 secors suggess ha hey are bes esmaed hrough a smulaneous equaon raher han hrough separae equaons. Sec or TABLE II INTER-SECTOR CORRELATIONS IN KNOWLEDGE PRODUCTIONS The resuls of esmang knowledge producon funcons for Souh Korean ndusres are gven n Table III. The resuls of he DSUR esmaon hrough a smulaneous equaon, measurng he degree of conrbuon of he sze of R&D work force o he creaon of new knowledge, ranged from negave values o The same range of varaon was observed n he coeffcens expressng he degree of conrbuon of he accumulaed sock of knowledge. Nex, we esed he hypohess ha he coeffcens for he 15 ndusry secors are dencal and obaned resuls ha rejec he null hypohess o he effec ha he coeffcens are dencal. 8 Hence, he DSUR esmaes of he knowledge producon funcon for he overall Korean ndusry are 0.25 for he conrbuon of he sze of R&D work force and for ha of he exsng sock of knowledge. 9 Ths means ha a 1% ncrease n he accumulaed sock of knowledge s accompaned by a 0.35% ncrease n he creaon of new knowledge. 7 Before one can proceed o he esmaon of conegraed coeffcens, s necessary o es wheher each of he relaed varables are nonsaonary. We used he panel un roo es procedure developed by Maddala and Wu for hs purpose and found ha he varables have un roos. We dd no nclude he resuls of he panel un roo es n hs paper, as hey have only modes pernence o he man subjec of hs sudy. 8 The p-value beng 0.00, he null hypohess o he effec ha coeffcen esmaes are dencal across all secors was rejeced. 9 The coeffcens relaed respecvely o he R&D work force and he exsng sock of knowledge, esmaed under he assumpon ha coeffcen esmaes are dencal across all secors, were 0.39 and When a me varable was ncluded n he funcon, correspondng fgures were 0.29 and

6 There has been praccally no aemp o drecly esmae knowledge producon funcons from he perspecve of knowledge-based growh heores. However, he exsng leraure on he relaonshp beween he accumulaon of R&D capal and oal facor producvy provdes que a few examples of sudes reporng esmaes ha are very smlar o ours. Grlches (1994), for example, esmaed he degree of conrbuon of he sock of R&D capal o he growh of facor producvy a The correspondng fgure repored by Scherer (1982) s The resuls reached by hs sudy ndcae ha he degree of conrbuon of he sze of R&D work force o he creaon of new knowledge does no sgnfcanly dffer from ha of he exsng sock of knowledge, repored by prevous sudes. However, hs sudy s que dsnc from s predecessors, n erms of desgn of knowledge producon funcon and facors of producon, as well as a he level of esmaon mehod. Hence, s relaonshp o exsng sudes may be bes descrbed complemenary. TABLE III RESULTS OF ESTIMATING KNOWLEDGE PRODUCTION FUNCTIONS FOR 15 SOUTH KOREAN INDUSTRY SECTORS Indusry Secor Conrbuon of R&D Work Sandard Error Conrbuon of Accumulaed Sock of Knowledge Sandard Error DSUR Esmaes The mplcaons of he above esmaon resuls are as follows: Frs, n Souh Korea, boh he ncrease n he number of research workers and he exsng sock of knowledge play an mporan role n he creaon of new knowledge. Of he wo facors of knowledge producon, he accumulaed sock of knowledge had a greaer mpac han he oher. Wha hs resul suggess s ha, n he case of Souh Korea, he creaon of a knowledge managemen sysem o effcenly manage he exsng sock of knowledge, o effecvely faclae he dffuson and o broadly share knowledge asses s of paramoun mporance for he creaon of new knowledge. Second, φ for Souh Korea was less han 1, whch s he hreshold value crucal n R&D-based growh heores. Ths resul lends he posve evdence for he exsng vew ha n Korea, he rae of economc growh s deermned manly by elasces relaed o producon funcons of goods and servces and he rae of populaon growh, and ha, for hs reason, he governmen mus shf he focus n s R&D polcy from a drec nervenon-cenered model o one nvolvng ndrec measures o faclae he managemen and dffuson of knowledge and he creaon of an effecve knowledge sharng sysem. The resul also suggess ha he weaker endogenous growh models lke he ones proposed by Jones (1995) and Korum (1997) whch suppose φ < 1 are more adaped o Korean realy han hose ohers developed by Romer (1990), Grossman e al. (1991) and Aghon e al. (1992) whch supposeφ = 1. Fnally, we calculae he degree of conrbuon of he exsng sock of knowledge needed for Souh Korea o acheve a growh rae of 5%, frequenly quoed as he opmal rae of economc growh. Gven he esmae of he conrbuon of he sze of R&D work force a and assumng a 1.5% labor force growh rae, he rae of conrbuon by he exsng sock of knowledge n order o acheve a 5% economc growh mus be 0.75 a he very leas. Ths s more han he double he curren rae of conrbuon by he accumulaed sock of knowledge n Souh Korea. I s no mpossble o aan hs hgh level of elascy of producon of new knowledge wh regard o he accumulaed sock of knowledge, provded an effcen sysem for managng R&D s n place. VI. CONCLUSION AND IMPLICATIONS The goal of hs sudy s o esmae knowledge producon funcons, whch s he one of he mos mporan elemens consung heores of endogenous economc growh ha emerged n he recen decade by usng he mos effcen possble esmaor. Havng chosen he DSUR esmaor proposed by Mark e al. (2005), we analyzed long-erm daa for he perod , from 15 Souh Korean ndusry secors, o emprcally esmae he exen of conrbuon of he accumulaed knowledge sock and he sze of R&D labor force o creang new knowledge. Our resuls ndcae ha a 1% ncrease n he number of R&D workers would conrbues a 0.25% growh n new knowledge, and a 1% ncrease n he sze of he accumulaed knowledge sock, a 0.353% growh. Ths sudy has he mporan heorecal and polcy mplcaons. I conrbues o he sudy of endogenous economc growh heores by provdng emprcal suppor o relaed heorecal models proposed by Jones (2005) and Korum (1997). Meanwhle, for polcymakers, we demonsrae hrough concree evdence ha, o ensure he connued growh of he Souh Korean economy, he governmen polcy n R&D mus assgn greaer mporance o nfrasrucure for dffusng and sharng knowledge han drec suppor oward research projecs. 85

7 Selecng approprae varables opmally capurng he sae of knowledge and developng a measuremen mehod whch can mprove accuracy and mgae he sensvy of parameer esmaes would be wo of he mos mporan asks for fuure research. Also, for greaer rgor n he esmaon of knowledge producon funcons, he scope of research mus be connuously broadened, by ncludng eher more dverse ndusry secors or counres, o expand he body of knowledge n hs research feld. REFERENCES [1] Aghon, P., How, P., "A Model of Growh hrough Creave Desrucon", Economerca, Vol. 60, 1992, pp [2] Caballero, R., Jaffe, A, "How Hgh are he Gans' Shoulders?" NBER Macroeconomcs Annual, MIT Press [3] Grlches, Z., R&D and Producvy: The Economerc Evdence, Unversy of Chcago Press, [4] Grossman G., Helpman, E., Innovaon and Growh n he Global Economy, MIT Press, [5] Jones, C., "R&D based Models of Economc Growh", Journal of Polcal Economy, Vol. 137, 1995, pp [6] Jones, C., "Growh and Ideas," Handbook of Economc Growh, Vol. 1B, 2005, pp [7] Kao, C., Chang, M., "On he esmaon and Inference of a Conegraed Regresson n Panel Daa", Advances n Economercs, Vol. 15, 2000, pp [8] Korum, S., "Research, Paens and Technology Change", Economerca, Vol. 65, 1997, pp [9] Maddala, G., Wu, S., "A Comparave Sudy of Un Roo Tess wh Panel Daa and a New Smple Tes", Oxford Bullen of Economcs and Sascs, Vol. 61, 1999, pp [10] Mark, N., Sul, G., "Conegraon Vecor Esmaon by Panel DOLS and Long Run Money Demand", Oxford Bullen of Economcs and Sascs, Vol. 65, 2003, pp [11] Mark, M., Ogak, M., Sul, G., "Dynamc Seemngly Unrelaed Regressons", Revew of Economc Sudy, Vol. 72, 2005, pp [12] Moon, R., "A Noe on Fully Modfed Esmaon of Seemngly Unrelaed Regresson Models wh Inegraed Regressors", Economcs Leers, Vol. 65, 1999, pp [13] Olsson, O., "Knowledge as a Se n Idea Space: An Epsemologcal Vew on Growh" Journal of Evoluonary Growh, Vol. 5, 2000, pp [14] Romer, P., "Endogenous Technologcal Change", Journal of Polcal Economy, Vol. 98, 1990, S