Determinants of the efficiency of regional innovation systems

Transcription

1 Determnants of the effcency of regonal nnovaton systems Mchael Frtsch & Vktor Slavtchev February 2008 Abstract Ths paper analyzes dfferences n the effcency of regonal nnovaton systems (RIS). Alternatve measures for the effcency of RIS based on the concept of a knowledge producton functon are dscussed. The emprcal fndngs suggest that both spllovers wthn the prvate sector as well as from unverstes and other publc research nsttutons have a postve effect on the effcency of prvate sector R&D. It s the ntensty of nteractons between prvate and publc sector R&D that leads to hgh effcency. Regons domnated by large establshments tend to be less effcent than regons wth a lower average establshment sze. JEL-classfcaton: O31, O18, R12 Keywords: Techncal effcency, nnovaton, patents, knowledge, spllovers, regonal nnovaton system. Fredrch-Schller-Unversty Jena, School of Economcs and Busness Admnstraton, Carl-Zess-Str. 3, 07743, Germany. German Insttute for Economc Research (DIW) Berln, and Max Planck Insttute of Economcs, Jena, Germany. E-mal: m.frtsch@un-jena.de; vktor.slavtchev@un-jena.de

2 II Contents 1. Introducton Assessng the effcency of RIS The dstrbuton of RIS effcency Possble determnants of effcency of RIS Emprcal results Summary and conclusons References Appendx... 27

3 1 1. Introducton Inventons and nnovatons are not evenly dstrbuted n space but tend to be clustered n certan locatons (FELDMAN, 1994; PACI and USAI, 1999, 2000; MORENO, PACI and USAI, 2005). Possble reasons for ths phenomenon are regonal dfferences n the avalablty and the qualty of local nputs as well as geographcally bounded knowledge spllovers (GREUNZ, 2003; FRITSCH and SLAVTCHEV, 2007, 2008). A further reason may be that locatons dffer wth regard to the qualty or the effcency of regonal nnovaton systems (RIS) leadng to dfferent levels of nnovatve output even f the nputs are dentcal n quanttatve as well as n qualtatve terms. The avalable emprcal evdence for such dfferences n RIS effcency s, however, sparse and not at all convncng. We stll know only rather lttle about the condtons that are conducve or unfavorable for nnovaton actvty and how polcy could help to mprove the functonng of RIS. Moreover, t s not clear how to assess the effcency of regonal nnovaton processes. Ths paper elaborates on the determnants of the effcency of RIS. We frst ntroduce two dfferent measures for RIS effcency, whch are both based on the concept of a knowledge producton functon (secton 2), and descrbe the spatal dstrbuton of effcency among the German plannng regons (secton 3). Secton 4 dscusses the possble determnants of the effcency of RIS. The results of multvarate regresson analyses of the mpact of dfferent factors on the effcency of RIS are presented n secton 5. Fnally, we draw conclusons for further research (secton 6). 2. Assessng the effcency of RIS Our understandng of the effcency of RIS 1 corresponds to the concept of techncal effcency as ntroduced by FARRELL (1957). Farrell regards an economc unt as beng neffcent f t fals to generate the maxmum feasble output from a gven set of nputs. Reasons for techncal neffcency can be manfold and comprse all sorts of msmanagement such as napproprate

4 2 work organzaton and mproper use of technology, scarcty of nputs as well as X-neffcency as exposed by LEIBENSTEIN s (1966) semnal work. Applyng ths defnton to the concept of a regonal nnovaton system means that a regon s techncally effcent f t s able to produce the possble maxmum of nnovatve output from a gven amount of nnovatve nput. Accordngly, a RIS s regarded as techncally neffcent f ts output falls below the maxmum possble value. In ths paper, we use the concept of a knowledge producton functon (KPF) for analyzng the relatonshp between nput and output of the nnovaton process that s essental for assessng the techncal effcency of regonal nnovaton systems. The basc hypothess behnd the KPF s that nventons do not completely fall from heaven but result predomnantly from respectve R&D actvtes. Accordng to GRILICHES (1979) and JAFFE (1989), who assume a Cobb-Douglas type functon for the relaton between nput and output, the KPF can be expressed as β (1) Y = A X. Y denotes the nnovatve output of a regon, and X s a set of nputs. A = α e u s an neffcency parameter, wth α as a constant term, whch s common for all regons, whle [ 0;1 ] certan regon. u denotes the techncal neffcency of a Our measure for nnovatve output s based on the number of dsclosed regonal patent applcatons n the years 1995 to Ths data has been provded by the German Patent Offce (Deutsches Patent- und Markenamt) as publshed n GREIF and SCHMIEDL (2002). A patent applcaton ndcates that an nventon has been made that extends the exstng knowledge pool. However, a number of lmtatons of the number of patents as a measure of nnovatve output should be mentoned. Frst, patents reflect an nventon whch s not necessarly transformed nto an nnovaton,.e. a new producton

5 3 technology or a product new to the market. Second, rather products than processes apply for patent (COHEN, NELSON and WALSH 2000). Thrd, as there are other possbltes to approprate the benefts of an nventon (cf. COHEN, NELSON and WALSH 2002), the number of patents may underestmate the actual nnovatve output. The German Patent Offce provdes nformaton on the number of regonal patent applcatons n 31 dfferent technologcal felds and from three dstnct sources: prvate companes, publc research and prvate persons. However, although the classfcaton n dfferent technologcal felds s based on the Internatonal Patent Classfcaton (IPC) 2, the level of aggregaton nto technologcal felds does not allow to assgn patent applcatons to R&D actvtes n a certan ndustry or n a certan academc dscplne. As ths paper focuses on the effcency of prvate R&D only corporate patent applcatons are analyzed n ths paper,.e. patent applcatons by publc research nsttutons or prvate persons are omtted. 3 The patent applcatons are assgned to the regon n whch the nventor has hs resdence. 4 As a proxy for the nput to the nnovaton process n the prvate sector, we use the number of R&D employees n ths sector (R&D). Ths nformaton s taken from the establshment fle of the German Socal Insurance Statstcs (Statstk der sozalverscherungspflchtg Beschaeftgten) as descrbed and documented by FRITSCH and BRIXY (2004). Employees are classfed as workng n R&D f they have a tertary degree n engneerng or n natural scences. Only the regonal prvate sector R&D employment s ncluded as an explanatory varable nto the knowledge producton functon whle other nput varables are omtted. The reason s that prvate sector R&D employees appear the only factor that drectly mpacts the nnovatve output n that sector. Knowledge spllovers from adjacent regons or spllovers from other sources such as publc research nsttutons may also make a consderable contrbuton to the nnovaton process n the prvate sector, however, ther

6 4 mpact s rather ndrect n nature, manly through the prvate sector R&D employees. 5 When relatng knowledge nput to nnovatve output, we have to assume that there s a tme lag. The man reason s that R&D actvty requres tme for attanng a patentable result. Moreover, patent applcatons are publshed only about twelve to eghteen months after submsson. Ths s the tme necessary for the patent offce to verfy whether an applcaton fulfls the basc precondtons for beng granted a patent and to complete the patent documents (GREIF and SCHMIEDL, 2002). Therefore, a tme lag between nnovatve nputs and output of at least two years should be assumed. 6 However, because relable data on R&D employment n East Germany are only avalable for the years 1996 onwards, we reduce the tme lag between R&D nput and the patent applcaton to a perod of one year n order to have more observatons and degrees of freedom. Hence, the R&D output for the perod s related to R&D nput between 1996 and Ths appears justfed because there are no great fluctuatons of both nnovaton nput and nnovaton output over these years. Moreover, the dfferences between the estmated parameters of a KPF wth a tme lag of one year and wth a tme lag of three years are neglgble. 7 The spatal framework used for the analyss of the effcency of RIS are the 97 German plannng regons (Raumordnungsregonen). The man advantage of usng plannng regons s that they are functonal unts that account for travel to work areas, and they nclude at least one core cty as well as ts surroundngs. 8 Ths s partcularly mportant because the patents n our database are assgned to the nventors resdence; thus, they would not be related to the locaton of the respectve R&D actvty f the place of employment and the place of the nventor s resdence do not concde (DEYLE and GRUPP, 2005). Choosng plannng regons as spatal unts of analyss may largely avod such spatal dstortons. For hstorcal reasons, the ctes of Berln, Hamburg and Bremen are defned as plannng regons even though

7 5 they are not functonal economc unts. In order to avod possble dstortons, we merged these ctes wth adjacent plannng regons (Berln wth the regon of Havelland-Flaemng, Hamburg wth the regon of Schleswg-Holsten-South and Bremen wth Bremerhaven and Bremen-Umland). Hence, the estmaton approach appled n ths paper s based on observatons for 93 regons over 4 years. From the perspectve of the KPF, there are two possble reasons why a regon s nnovatve output s lower than the hghest possble level. The frst reason s due to a relatvely low value of the slope parameter β, whch can be nterpreted as the margnal patent productvty or output elastcty of prvate sector R&D employees. A second reason could be dfferences n the level of the functon wth a gven slope. Such dfferences reflect the varous levels of R&D output wth a certan nput n terms of average productvty and would correspond wth dfferent values of the constant term of the functon. Accordng to these two types of dfferences, we apply two approaches for assessng the effcency of RIS (for further dscusson see KALIRAJAN and SHAND, 1999). The frst approach reles on the dea of regonal dfferences n the slope of the knowledge producton functon. To estmate the specfc productvty of each regon n terms of the margnal return to R&D nput, we nclude a bnary dummy varable for each regon, ( D D = 1 f =, otherwse 0), that s multpled wth the respectve number of prvate sector R&D employees. The constant term A s assumed to be dentcal for all regons. Hence, the equaton (1) can be rewrtten as (2) ( Number of patents ) = ln A + β * D *ln R & D prv ) + ln ε, ( wth β as a measure of the output elastcty of prvate sector R&D employment n the th regon ( = 1,, 93). Based on the estmated values for

8 6 the output elastcty of prvate sector R&D, we defne the effcency of a certan regon as the quotent of the observed output of a partcular regon and the maxmum possble value,.e., (3) TE DET ( ln( Number of patents ) ( ln A + β *ln( R D prv ) + ε )) = exp & max, where β max { β } = max s the maxmum estmated output elastcty of R&D nput. Accordngly, at least one regon s assumed to be fully effcent. We label ths approach as determnstc because t mples that all devatons from the maxmum value are due to neffcency and neglects, therefore, the possblty that values could be affected by measurement errors or by random dsturbances. 9 The output elastcty of prvate sector R&D s estmated by means of a negatve bnomal regresson technque (GREENE, 2003, ). Due to the relatvely short length of the tme seres (four years) the data are pooled. Accordng to the second approach, the produced output may fall systematcally below the maxmum, not because of lower output elastctes of the factors of producton, but rather because of a lower level of the functon. In ths case β s dentcal for all regons ( β = β, ). Thus, the knowledge producton functon can be expressed as β v (4) u Number of patents = α R & D prv e e, where ν denotes effects of the regon-specfc envronment on nnovatve output and u represents the stochastc error term. The techncal effcency of a regon can, therefore, be calculated as SFA v (5) TE = e.

9 7 Therefore, a RIS acheves ts maxmum feasble output f, and only f, t s fully effcent ( v = 0 ). The value of v provdes a measure for the devaton of observed output from the possble maxmum. Ths type of approach s called stochastc fronter functon (SFA) because t allows for stochastc dsturbances. Ths mples that extreme values are not necessarly taken as the benchmark for the measurement of effcency. The yearly data for the regons are pooled, and the techncal effcency s estmated as the average value per regon. In order to separate the mpact of techncal neffcency from the general stochastc effects u, an a pror assumpton about the dstrbuton of techncal neffcency s necessary. The general assumpton n ths respect s that the dstrbuton of techncal effcency has a negatve skewness (SCHMIDT and LIN, 1984),.e. that most regons are clustered close to the effcency fronter. Several specfcatons for the neffcency term v are possble: v can be assumed to be ndependently and exponentally + 2 dstrbuted wth varance σ, or ndependently and half-normally N ( ; σ ) + 2 dstrbuted, or ndependently ( μ σ ) 2 ν ; ν 0 ν N dstrbuted wth a truncaton pont at 0. Due to the fact that the choce of the dstrbutonal assumpton s a pror not clear, we estmate the effcency measure accordng all three alternatves n order to check the robustness of the results. Table A1 n the Appendx provdes descrptve statstcs of prvate sector R&D nput and output used to estmate the effcency of RIS. v 3. The dstrbuton of RIS effcency There are consderable dfferences between the values of techncal effcency for the German plannng regons. The effcency levels estmated by means of both approaches, the determnstc fronter functon and the stochastc fronter functon show a wde spread wth the least effcent regon attanng only 6.7 and 9.9 percent of the hghest value (table 1 and fgure 1). As compared to the stochastc fronter method, the determnstc approach leads to a slghtly more dfferentated assessment of RIS effcency. However, the spatal

10 8 dstrbuton of the techncal effcency of RIS accordng to the dfferent approaches s vrtually dentcal. The Pearson correlaton coeffcents suggest almost perfect correlaton between the effcency values estmated by the dfferent approaches (table 1). Table 1: Descrptve statstcs for the dstrbuton of techncal effcency n German plannng regons No. Varable Mean Medan Mn. Max. Std. Dev. Pearson correlaton coeffcent DET 1 TE TE SFA (half-normal) TE SFA (truncated normal) TE SFA (exponental) Note: Number of observatons (regons) = 93. The spatal dstrbuton of the effcency values (fgure 1) suggests that regons wth smlar values of techncal effcency tend to be clustered n space. Plannng regons wth the hghest values of techncal effcency are located n the south, n the west and n the center of the country. None of the plannng regons n the north or n the east of Germany fall nto ths category. In partcular, the values for the techncal effcency of RIS tend to be relatvely hgh n larger, densely populated areas such as Munch, Stuttgart, Cologne and Frankfurt. The Berln regon, whch has a poston n the mddle range of the effcency rankng, s an excepton n the East German nnovaton landscape. Regons wth relatvely low values for the effcency of ther nnovaton system are entrely located n the north and n the east. Generally, locaton n border regons seems to be unfavorable. Regons wth moderate values of techncal effcency are found to be located predomnantly n the center of the country, separatng the west from the east as well as the south from the north. Ths ndcates that the German nnovaton system s spatally dvded nto dfferent regmes wth dvergng levels of performance.

11 9 Effcency of RIS (determnstc approach) Effcency of RIS (SFA, half-normal) Effcency of RIS (SFA, truncated normal) Effcency of RIS (SFA, exponental) Fgure 1: The spatal dstrbuton of effcency of RIS n Germany 4. Possble determnants of effcency of RIS The factors that determne the effcency of RIS can be manfold. It s plausble to assume that the ablty of prvate sector R&D employees to produce nnovatve output may depend on the avalablty and the qualty of knowledge and other nnovatve nputs n the regon. Gven that nnovaton

12 10 processes are characterzed by a pronounced dvson of labor 10, one may expect that the effcency of a RIS depends on how ntensely the regonal knowledge base s exploted and further developed through the nteracton of regonal agents. The effcency of RIS may, therefore, be strongly nfluenced by the level and the qualty of nteracton and exchange between ts dfferent elements and the respectve knowledge flows (spllovers). Ths nteracton may be crtcally dependent on the avalablty of potental cooperaton partners n the regon such as other prvate frms workng n the respectve technologcal feld, publc research nsttutes as well as supplers of nnovatve nputs and servces. Therefore, the densty and ndustral composton of the regonal actors, the accessblty of the regon as well as the technologcal, ndustral and nsttutonal nfrastructure (e.g., the networks ) may play an mportant role. 11 The nteracton between the dfferent elements of RIS generates partly self-enforcng systemc effects that may result n specfc knowledge as well as specfc technologes and methods of problem solvng (GERTLER, 2003), whch can be expected to affect the workablty of the system (LEYDESDORFF and FRITSCH, 2006). We assume that the amount of knowledge spllovers wthn the prvate sector s related to the number of R&D employees n ths sector. The larger the number of R&D employees s, the greater the opportunty to fnd a sutable partner for cooperaton and knowledge exchange s. The ndcator for knowledge spllovers wthn the prvate sector s the share of R&D employment n that sector (R&D). The knowledge that s generated and accumulated by unverstes may consttute a basc precondton for prvate sector R&D actvtes (JAFFE, 1989). However, snce unverstes are non-proft organzatons, they can hardly market the results of ther own R&D n terms of new products or technologes. For ths reason, ther knowledge has to spll over to other actors (e.g. prvate companes) n order to become commercally effectve. The ways n whch such knowledge transfers occur can be manfold (see

13 11 VARGA, 1998, for an overvew). In partcular, channels for transfer of academc knowledge such as R&D cooperaton wth prvate sector frms or the provson of nnovaton related servces play a major role for prvate sector nnovatve actvtes (MANSFIELD and LEE, 1996; COHEN, NELSON, and WALSH 2002). However, the mpact of unverstes on nnovatve performance of prvate sector frms may dffer consderably accordng to the qualty of a unversty s research and the ntensty n whch the unversty nteracts wth the frms (e.g., FELDMAN and DESROCHERS, 2003; MANSFIELD and LEE, 1996; FRITSCH and SLAVTCHEV, 2007, 2008). In order to test the mpact of unverstes for the performance of the prvate sector, we ntroduce the amount of thrd-party funds that the unverstes gan from prvate frms (TPF- PRIV). Unverstes thrd-party funds n general can be regarded as an ndcator of the amount and the qualty of the research. The man reason s that the allocaton of unverstes thrd-party funds s usually based on some compettve procedure and s, therefore, largely dependent on the qualty of the research conducted. Accordng to HORNBOSTEL (2001), there s a dstnct correspondence between ndcators that are based on thrd-party funds and bblometrc ndcators for hgh qualty research such as SCI publcatons. Funds from prvate sector frms, n partcular, can be regarded compensaton for academc R&D or for other servces. Hence, these revenues are well suted to ndcate the relevance of academc research for commercal applcatons as well as the ntensty of unversty-ndustry lnkages, whch may lead to pronounced knowledge spllovers (FRITSCH and SLAVTCHEV, 2007, 2008). Although we have no detaled nformaton about the locaton of the prvate frms that cooperate wth the unverstes, one can assume that, n most cases, unverstes and the cooperatng prvate frms are co-located n the same plannng regon (FRITSCH and SCHWIRTEN, 1999). 12 In order to avod possble scale effects of large unverstes, whch are lkely to attract larger amounts of thrd-party funds from prvate frms, we use the average amount of thrd-party funds from prvate sector frms per unversty professor.

14 12 Non-unversty publc research nsttutons such as the Max-Planck- Socety (MPG) and the Fraunhofer-Socety (FhG) may also have a postve effect on the techncal effcency of prvate sector R&D employees. Unfortunately, we do not have nformaton about the thrd-party funds of these nsttutes avalable; thus, we ntroduce the regonal number of nsttutes n our analyss. As far as a technology s unque n the sense that the transfer and the applcaton of respectve knowledge requres specfc sklls or a specfc common language, the strength of knowledge spllovers depends crtcally on the degree of technologcal smlarty between the partes (JAFFE, 1986; NADIRI, 1993). Therefore, we ntroduce the technologcal proxmty between publc and prvate sector R&D as a measure of correspondence and potental nterplay of the regonal actors n the nnovaton process (PROXTECH). The technologcal proxmty between publc and prvate sector R&D s measured as the degree of congruence between the technologcal felds of the patent output of publc research nsttutons (PATACAD) and prvate sector frms (PATPRIV): 13 (6) PROXTECH = PAT PAT ACAD ACAD * PAT * PAT ' PRIV PRIV. Ths ndex can assume values between one and zero. The larger the value s, the closer the technologcal proxmty between publc and prvate sector R&D s and the greater the possbltes for cooperaton and occurrence of knowledge spllovers should be. The servce sector may provde mportant support for the R&D actvtes n dverse ways such as counselng, techncal servces, provson of venture captal, etc. Ths s partcularly true for knowledge ntensve busness servces, whch n some cases have been even assocated wth the emergence of hgh-tech regons such as Slcon Valley and Route 128

15 13 (SAXENIAN, 1985; DORFMAN, 1983). Accordng to FELDMAN and FLORIDA (1994), the presence of busness servces at certan locaton also ndcates relatvely well developed nfrastructure that may be benefcal for nnovaton. One could, therefore, expect a postve mpact of the share of the regonal servce sector (SERVICES) on RIS effcency. On the other hand, a hgh share of the servce sector n the regon may have a negatve effect due to the relatvely low propensty to patent n ths sector (GREIF and POTKOWIK, 1990; BODE, 2004). Populaton densty (number of nhabtants n the regon per squared klometer, POPDEN) s a measure, not only of the effects of urbanzaton economes on RIS performance, but can also be regarded as a catch-all varable for dverse types of unobserved regon-specfc nfluences. Lterature suggests that hgh populaton densty should be conducve to nnovaton actvty because t s related to ntensve contacts and cooperaton (see FELDMAN, 2000, and FRITSCH, 2000, for an overvew). One could, therefore, expect a postve sgn for ths varable. The average number of employees per establshment (SIZE) s supposed to capture the effects of establshment sze. Accordng to a number of prevous emprcal studes, the number of patents per employee s hgher n smaller frms than n large frms (see COHEN and KLEPPER, 1996, for a dscusson); therefore, a negatve sgn could be expected. Two bnary dummy varables are supposed to capture addtonal unobserved effects of a locaton n West Germany (WEST) and n the perphery (PERIPHERY). We expect a postve sgn for a locaton n West Germany due to the generally weaker performance of the economy n the Eastern part of the country, whch became rather obvous n the assessment of RIS effcency as shown n fgure 1. Gven that a locaton n the perphery s unfavorable for nnovaton actvty due to relatvely large geographcal dstance to other actors, we expect a negatve sgn for ths varable.

16 14 Table 2: Defnton of varables and expected sgn of coeffcent Varable Operatonal defnton Expected sgn R&D Share of R&D employees n the prvate sector; source: + Socal Insurance Statstcs. TPF-PRIV Thrd-party funds per unversty professor (ncludng + Fachhochschulen) n 1,000s of Euro; source: German Unversty Statstcs. MPG Number of nsttutes of the Max Planck Socety; source: + FhG BUNDESMINISTERIUM FUER BILDUNG UND FORSCHUNG (2004). Number of nsttutes of the Fraunhofer Socety; source: BUNDESMINISTERIUM FUER BILDUNG UND FORSCHUNG (2004). PROXTECH Correspondence of the technologcal felds of publc and + prvate sector R&D; source: own calculaton based on Patent Statstcs (GREIF and SCHMIEDL, 2002). POPDEN Populaton densty; source: BUNDESAMT FUER BAUWESEN UND + RAUMORDNUNG - BBR. SERVICES Employment share n the servce sector; source: Socal + / - Insurance Statstcs. SIZE Average number of employees per establshment; source: - Socal Insurance Statstcs. WEST Dummy for locaton n West Germany (yes=1; no=0) + PERIPHERY Dummy for locaton of a plannng regon at the border of the - country (yes=1; no=0) TRANSPORT Employment share n transportaton engneerng; source: + Socal Insurance Statstcs. ELECTRICAL Employment share n electrcal engneerng; source: Socal + Insurance Statstcs. OPTICS Employment share n optcs and measurement engneerng; source: Socal Insurance Statstcs. + CHEMICALS Employment share n chemstry; source: Socal Insurance + Statstcs. +

17 15 Table 3: Descrptve statstcs for ndependent varables Varable Mean Medan Mn. Max. Std. Dev. R&D TPF-PRIV MPG FhG PROXTECH SERVICES SIZE POPDEN , TRANSPORT ELECTRICAL OPTICS CHEMISTRY Note: Number of observatons (regons) = 93. As the propensty to patent the results of R&D may dffer between the ndustres (f there are, for example, alternatve ways to approprate the returns of R&D), effcency of RIS may be subject to ndustry specfc effects. In order to control for the mpact of regonal specalzaton n certan ndustres wth a relatvely hgh level of patentng, we nclude the share of employees n transportaton engneerng (TRANSPORT), n electrcal engneerng (ELECTRICAL), n measurement engneerng and optcs (OPTICS) as well as n chemstry (ncludng bochemstry) (CHEMICALS) nto our model. These are, accordng to GREIF and SCHMIEDL (2002), the technologcal felds wth the hghest share of patent applcatons n Germany. 14 Table 2 gves an overvew on the defnton of varables and respectve data sources. Descrptve statstcs for the varables used n the analyss are provded n table 3. Table A2 n the Appendx shows the correlatons between the varables. For estmatng the model, we transform the dependent as well as the ndependent varables nto log-values. Important advantage of loggng both sdes of the equaton s that the estmated coeffcents can be regarded as elastctes that can be drectly compared wth each other. In order to assess the presence and the mportance of nterdependences between the geographcal unts of nvestgaton, we have carred out several dagnostc

18 16 tests (Moran s I, LM-Error, robust LM-Error, LM-Lag and robust LM-Lag) for such spatal dependences. These tests ndcate the presence of spatal dependence that takes the form of a spatal autoregressve process n the error term. Therefore, we apply a spatal error model (7) Y = Xβ + ε, where ε = λ W ε + μ, λ denotes the spatal autoregressve parameter, μ denotes a homoscedastc and uncorrelated error term, and W row standardzed spatal weghts matrx based on a frst order contguty (ANSELIN, 1988; ANSELIN and BERA, 1998). The relatve mportance of dfferent determnants s calculated by applyng a robust varance-covarance estmator (WHITE, 1980). 5. Emprcal results The mpact of dfferent determnants on the effcency of RIS accordng to the determnstc and the stochastc fronter approach are reported n table 4. Wth respect to the stochastc fronter approach, there are three partcular forms that refer to dfferent assumptons about the dstrbuton of the neffcency term: half-normal dstrbuton, normal dstrbuton wth a truncaton pont at zero and exponental dstrbuton. However, snce the effcency measures obtaned accordng to all the three approaches are almost perfectly correlated (see table 1), we compare the determnstc fronter only to the stochastc fronter approach wth half-normal dstrbuton. 15 The share of prvate sector R&D employment (R&D) has a pronounced postve mpact on the effcency of RIS. The estmated coeffcent provdes clear evdence for the relevance of scale economes,.e., an ncrease of the share of prvate sector R&D employment at a certan locaton can lead to hgher effcency of nnovaton processes. Obvously, hgh R&D ntensty at a certan locaton may stmulate knowledge spllovers between actors. However, f more measures for regonal specalzaton n certan ndustres

19 17 are ncluded, the mpact of the share of R&D employment becomes slghtly weaker. Ths holds partcularly for the share of regonal employment n electrcal engneerng (ELECTRICAL). The average amount of thrd-party funds from prvate sector sources per unversty professor (TPF-PRIV) has a postve mpact on the effcency of RIS. Ths suggests that the ntensty of unversty-ndustry lnkages, as ndcated by the money pad by prvate frms for unversty R&D, s conducve to regonal nnovaton actvty. Substtutng TPF-PRIV by other unversty related ndcators such as the number of academc personnel shows hardly any statstcally sgnfcant mpact for the respectve varable and results n a consderable reducton of the loglkelhood of the model. These results clearly confrm prevous fndngs for the role of academc research on nnovaton actvty n Germany (FRITSCH and SLAVTCHEV, 2007, 2008). A postve mpact can also be found for non-unversty publc research establshments as ndcated by the number of research nsttutes of the Max- Planck Socety (MPG) and of the Fraunhofer Socety (FhG). These results suggest that there are knowledge spllovers from both types of research, basc research that s conducted at the Max-Planck-Insttutes, and from more appled research as typcally carred out by the nsttutes of the Fraunhofer Socety, whch ncrease the techncal effcency of a RIS. 16 Regons wth a hgh effcency of nnovaton actvty are characterzed by pronounced technologcal proxmty between publc and prvate R&D as measured by the PROXTECH-varable. 17 A possble explanaton for ths fndng s that the knowledge exchange between the two sectors mght become more lkely as publc and prvate research s n smlar technologcal felds.

20 18 Table 4: Determnants of the effcency of RIS DET Techncal effcency accordng to the determnstc fronter approach, TE SFA Techncal effcency accordng to the stochastc fronter approach, TE Intercept (1.321) (1.305) (1.361) (1.268) (1.205) (1.283) (1.262) (1.152) (1.141) (1.171) (1.115) (1.050) (1.095) (1.062) R&D [ln] 0.307** 0.302** 0.279* 0.286** 0.274* 0.259* 0.286* 0.249* 0.247* 0.226* 0.233* 0.215* 0.203* 0.233* (0.112) (0.113) (0.116) (0.108) (0.115) (0.105) (0.111) (0.104) (0.106) (0.107) (0.101) (0.104) (0.094) (0.100) TPF-PRIV [ln] 0.051* 0.051* 0.046* 0.048* 0.052* 0.054** 0.054** 0.050* 0.052** 0.055** (0.022) (0.022) (0.023) (0.021) (0.022) (0.019) (0.019) (0.020) (0.018) (0.019) MPG [lm] 0.112* 0.107* (0.054) (0.049) FhG [ln] 0.104* 0.099* (0.049) (0.050) PROXTECH [ln] 0.295* 0.275* (0.142) (0.128) POPDEN [ln] 0.317** 0.316** 0.286** 0.306** 0.314** 0.232** 0.245** 0.280** 0.279** 0.253** 0.272** 0.276** 0.203** 0.214** (0.076) (0.076) (0.075) (0.075) (0.076) (0.069) (0.079) (0.070) (0.071) (0.067) (0.069) (0.071) (0.059) (0.071) SERVICES [ln] ** ** ** ** ** ** ** ** ** ** ** ** ** ** (0.230) (0.245) (0.228) (0.230) (0.227) (0.243) (0.212) (0.212) (0.225) (0.214) (0.214) (0.207) (0.228) (0.197) SIZE [ln] ** ** ** ** ** ** ** ** ** ** ** ** ** ** (0.399) (0.393) (0.411) (0.386) (0.362) (0.401) (0.388) (0.344) (0.340) (0.349) (0.338) (0.313) (0.334) (0.323) WEST 1.253** 1.244** 1.170** 1.214** 1.224** 1.242** 1.159** 1.165** 1.161** 1.092** 1.136** 1.134** 1.165** 1.084** (0.129) (0.129) (0.130) (0.133) (0.153) (0.103) (0.129) (0.117) (0.117) (0.117) (0.121) (0.135) (0.092) (0.116) PERIPHERY (0.073) (0.073) (0.073) (0.072) (0.073) (0.070) (0.073) (0.066) (0.066) (0.066) (0.065) (0.065) (0.063) (0.066) TRANSPORT [ln] (0.043) (0.037) ELECTRICAL [ln] (0.075) (0.072) (0.078) (0.066) (0.061) (0.067) OPTICS [ln] (0.050) (0.044) CHEMICALS [ln] (0.040) (0.033) λ 0.485** 0.487** 0.379* 0.462** 0.498** ** 0.464** ** 0.477** (0.129) (0.129) (0.195) (0.133) (0.126) (0.232) (0.214) (0.136) (0.136) (0.201) (0.138) (0.130) (0.225) (0.212) Squared corr Log lkelhood Wald (λ=0) LM-Error (λ=0) Notes: Robust standard errors n parentheses; * sgnfcant at 5% level; ** sgnfcant at 1% level. Crtcal value for the Wald test-statstc and LM-Error wth one degree of freedom s 3.48 (p = 0.05); spatal weghts are row-standardzed: W s 1 st order contguty matrx. Number of observatons (regons) = 93.

21 19 The postve coeffcent for populaton densty (POPDEN) ndcates the presence of urbanzaton economes. Ths suggests that densely populated regons provde a varety of opportuntes for nteracton, rch supples of nputs as well as a comprehensve physcal and nsttutonal nfrastructure that s advantageous for nnovaton actvty. The coeffcent for the share of servce sector employment (SERVICE) ndcates a negatve mpact on the effcency of a RIS. Ths means that despte ther supportng functon, resources allocated to the servce sector are less effcent n terms of patentng than n manufacturng. Ths confrms prevous results of BODE (2004), who found negatve mpact of servcemanufacturng rato on regonal nnovaton output. As ndcated by the sgnfcantly negatve coeffcent for average frm sze (SIZE), patentng effcency tends to be lower n regons that are characterzed by a hgh share of large establshments. Ths result s n lne wth other studes, whch fnd that the number of patents per unt of R&D nput s hgher n the smaller frms than n larger ones (ACS and AUDRETSCH, 1990; COHEN and KLEPPER, 1996). Accordng to the postve and hghly sgnfcant coeffcent of the dummy varable for a locaton n West Germany (WEST), nnovaton actvtes n regons located n the western part of the country are more effcent than n East Germany. Ths result suggests that there are stll consderable dfferences n the effcency of the nnovatve process n the two parts of the country even after the reunfcaton n There are at least two possble explanatons for ths dfference. Frst, a relatvely pronounced ndustral monostructure 18 and a concentraton on less nnovatve ndustres may cause a technologcal shortfall of East Germany. Second, and probably most mportant, catchng up can only be possble n a relatvely long run f current technologcal sklls and nnovatve performance are subject to a path dependent process. The estmated coeffcent for the dummy varable for regons located n the perphery of Germany s not statstcally sgnfcant.

22 20 Control for the local presence of ndustres wth relatvely hgh patent ntensty provdes evdence whch may ncrease the effcency of the regon provdes evdence for postve mpact (at 10 percent sgnfcance level) only wth respect to electrcal engneerng (ELECTRICAL). Nevertheless, to control for the ndustry structure n the regon appears mportant for at least two reasons. Frstly, ntroducng the share of the electrcal engneerng ndustry sgnfcantly ncreases the goodness of ft (squared correlaton, log lkelhood) of the model. Secondly, the parameter of spatal dependence λ becomes nsgnfcant f a control for the sze of ths ndustry n the regon s ncluded. 6. Summary and conclusons The objectve of ths paper s to provde an answer to the queston about what determnes the dfferences n the effcency of RIS. For ths purpose, we frst ntroduce alternatve measures for the effcency of RIS based on the concept of a KPF. These approaches for assessng the effcency of RIS lead to vrtually dentcal results. Partcularly, the spatal dstrbuton of effcency estmates turns out to be very smlar. We have found a number of factors that have an effect on the effcency of RIS. Our results suggest that both knowledge spllovers wthn the prvate sector as well as between publc research nsttutons (unverstes as well as non-unversty research nsttutes) and actors n the prvate sector have a postve mpact on prvate sector nnovaton actvtes. The presence and the nteracton of unverstes and other publc research nsttutes wth prvate sector frms also proved to be conducve. Ths effect s, partcularly, hgh f the technologcal felds of research pursued n publc research nsttutes correspond to those of nnovaton actvty n the prvate sector. Populaton densty has a postve effect on nnovaton performance ndcatng that R&D actvty s more productve n agglomeratons than n rural areas. The negatve effect of the employment share n the servce sector and of the average establshment sze corresponds wth the relatvely low patent

23 21 ntensty n the servce ndustres and n larger frms, whch has been found n other emprcal studes. RIS n West Germany are consderably more effcent than those n the eastern part of the country even after controllng for all other nfluences that have a sgnfcant effect. There s no ndcaton for lower effcency of nnovaton actvtes n regons located at the perphery of the country. All n all, our results are consstent wth the vew that the performance of RIS s strongly nfluenced by the level and the qualty of nteracton and exchange between ther dfferent elements. To put t dfferently, a pronounced dvson of nnovatve labor leads to relatvely hgh effcency. Our results rase some mportant questons for further research. A man ssue n ths respect s the ways of knowledge transfer between the dfferent actors that need to be further llumnated. A polcy that ams at mprovng the effcency of RIS should be able to dentfy the most relevant ways of knowledge transfer and needs nformaton on how such knowledge transfer can be stmulated. What stmulates knowledge spllovers and the dvson of nnovatve labor between the elements of a RIS? What are the mpedments n ths respect? Lastly, regardng the role of ndustral specalzaton for nnovaton, more nformaton about the role of the ndustral structure of a regon for the effcency of nnovaton actvty would be helpful n order to derve reasonable polcy mplcatons. The low effcency of RIS n East Germany ndcates that there may be a consderable degree of pathdependency that shapes the performance of these regons. Ths mples that t may take qute a long tme untl a polcy, whch ams at mprovng the performance of RIS, produces sgnfcant results.

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29 27 Appendx Table A1: Descrptve statstcs of prvate sector R&D output and nput Varable Obs. Mean Medan Mnmum Maxmum Standard Devaton PAT PRIV , R&D 372 6, , , , Note: Number of observatons = 372. Table A2: Correlaton between varables No. Varable TE DE [ln] TE SFA (half-normal) [ln] TE SFA (truncated normal) [ln] TE SFA (exponental) [ln] R&D [ln] TPF-PRIV [ln] MPG [ln] FhG [ln] PROXTECH [ln] SERVICES [ln] SIZE [ln] POPDEN [ln] TRANSPORT [ln] ELECTRICAL [ln] OPTICS [ln] CHEMISTRY [ln]