Technology transfers from universities and innovation

Mas e in Economics: Empi ical Applica ions and Policies Uni e si y o he Basque Coun y UPV/EHU Mas e Thesis Technology ans e s om uni e si ies and inno a ion Mi ian Oiz Chueca Supe ised by Ja ie Ga deazabal Ma ías July 22nd, 2024 Mi ian Oiz / Mas e in Economics: Empi ical Applica ions and Policies - 2 - Table o con en s 1. INTRODUCTION …………………………………………………………… 4 2. LITERATURE REVIEW ……………………………………………………. 5 3. DATA DESCRIPTION ……………………………………………………… 6 3.1. Va iable de ini ion ……………….…………………...…………….…… 7 3.2. Desc ip i e analysis ………………………..…………………….……… 9 4. METHODOLOGY …………………………………………...……………... 10 5. RESULTS …………………………………………………………………... 12 5.1. E ec o collabo a ion wi h uni e si ies ……………….……………… 12 5.2. Compa ison wi h he e ec o collabo a ion wi h o he companies ……. 20 5.3. Compa ison wi h he e ec o collabo a ion wi h any ype o o ganiza ion ……………………………………………………………. 21 6. CONCLUSIONS …………………………………………….……………... 22 7. REFERENCES ……………………………………………………….…….. 24 8. APPENDIX ..………………………………………………………………. 26 Mi ian Oiz / Mas e in Economics: Empi ical Applica ions and Policies - 3 - Abs ac This s udy uses causal in e ence me hods o assess he impac o uni e si y esea ch and de elopmen (R&D) ans e s on i m inno a ion, u ilizing he Spanish su ey (PITEC) spanning he pe iod om 2003 o 2016. In pa icula , mul i a ia e Nea es Neighbo Ma ching (NNM) me hod is employed o he es ima ion o he A e age T ea men E ec on he T ea ed (ATET). The indings indica e ha uni e si y collabo a ion has a mos ly posi i e impac on a ange o inno a ion ou comes, including p ocess inno a ion, p oduc inno a ion, and pa en egis a ion, bu i mainly no signi ican . These indings lend suppo o he p oposi ion ha uni e si y R&D ans e s a e an impo an ac o in s imula ing i m inno a ion. Finally, he esea ch acknowledges he limi a ions o i s me hodology and sugges s a enues o u u e esea ch. Key wo ds: R&D ans e s, inno a ion, uni e si ies Mi ian Oiz / Mas e in Economics: Empi ical Applica ions and Policies - 4 - 1. INTRODUCTION In he con empo a y business en i onmen , cha ac e ized by apid change and in ense compe i ion, he capaci y o inno a e is o pa amoun impo ance o i ms seeking o succeed and gain a compe i i e ad an age. Uni e si ies, wi h hei subs an ial in ellec ual capi al and pionee ing esea ch, se e as a impo an condui o ins illing an en i onmen conduci e o inno a ion. In ligh o his, he e has been a no able inc ease in he numbe o uni e si y-indus y collabo a ions, wi h i ms p oac i ely engaging wi h uni e si ies in o de o gain access o hei expe ise and knowledge esou ces. This esea ch explo es he complex in e ela ionship be ween uni e si y R&D collabo a ion wi h i ms and his las ones’ inno a ion. This s udy speci ically examines he impac o uni e si y collabo a ion on a i m's inno a i e pe o mance, encompassing p ocess inno a ion, p oduc inno a ion, and pa en egis a ion. The analysis employs da a om he Spanish su ey, PITEC (Panel de Inno ación Tecnológica, Panel o Technological Inno a ion), which co e s R&D ans o ma ion in companies om 2003 o 2016. The su ey ga he s comp ehensi e da a on a ange o inno a ion- ela ed opics, including uni e si y-indus y collabo a ion, inno a ion ou comes, and i m cha ac e is ics, o be used o he esea ch analysis. The me hodology employed combines mul i a ia e nea es neighbo ma ching, wi h accoun s o obse ed con ounding, and di e ence-in-di e ence, which accoun s o ime in a ian unobse ed con ounding. This esea ch is d i en by he esea ch ques ion: does he ans e o esea ch and de elopmen (R&D) om uni e si ies o i ms lead o inc eased inno a ion in hose i ms? By analyzing da a om he PITEC su ey and employing a obus me hodology, his s udy aims o answe his ques ion and con ibu e o he unde s anding o he ole ha his uni e si y ans e s plays in d i ing inno a ion in i ms. The analysis will commence wi h a e iew o he ex an li e a u e, ollowed by a comp ehensi e accoun o he a ailable da a and he me hodology o be employed. Subsequen ly, he indings will be p esen ed, and some conclusions will be d awn. Mi ian Oiz / Mas e in Economics: Empi ical Applica ions and Policies - 5 - 2. LITERATURE REVIEW The con e gence o academic esea ch and indus ial inno a ion ep esen s a signi ican d i e o economic g ow h. This e iew examines he impac o uni e si y esea ch and de elopmen (R&D) ans e s on i m inno a ion. This s udy examines he ole o uni e si ies as ca alys s, acili a ing he ans o ma ion o knowledge in o cu ing- edge p oduc s and p ocesses. Se e al s udies suppo a posi i e associa ion be ween uni e si y echnology ans e and i m inno a ion. Ga cía-Vega & Vicen e-Chi i ella (2020) demons a e a signi ican ise in inno a i eness o i ms acqui ing R&D om uni e si ies. Ca boni & Medda (2021) ein o ces his link, highligh ing he e ec i eness o uni e si y R&D in p omo ing p oduc inno a ion. Fu he mo e, Li & Tan (2020) ind a posi i e spillo e e ec om uni e si y R&D ac i i ies on i m inno a ion wi hin he same geog aphic loca ion. The e ec i eness o uni e si y R&D ans e s depends on a ious ac o s. Bellucci & Pennacchio (2015) emphasize he impo ance o a uni e si y's en ep eneu ial spi i and he quali y o i s esea ch. Fi ms wi h open sea ch s a egies and a ocus on adical inno a ion bene i mo e om uni e si y knowledge (Bellucci & Pennacchio, 2015). Addi ionally, Ga cía-Vega & Vicen e-Chi i ella (2024) sugges ha a i m's abso p i e capaci y, i s abili y o unde s and and u ilize ex e nal knowledge, plays a c i ical ole in le e aging uni e si y R&D e ec i ely. Uni e si y R&D ans e s can also gene a e posi i e ex e nali ies beyond di ec knowledge acquisi ion. Ga cía-Vega & Vicen e-Chi i ella (2020) ind ha hese ans e s enhance i ms' in e nal R&D capabili ies, po en ially c ea ing a i uous cycle o inno a ion. Simila ly, Acos a e al. (2009) highligh he ole o uni e si y g adua es as a sou ce o knowledge spillo e s, con ibu ing o new business o ma ion in high- echnology sec o s. Collabo a ion ne wo ks u he in luence he bene i s i ms de i e om uni e si y R&D. Bolí a -Ramos (2017) inds ha i ms collabo a ing wi h uni e si ies in na ional Mi ian Oiz / Mas e in Economics: Empi ical Applica ions and Policies - 6 - o egional ne wo ks show a s onge pa en ing p opensi y compa ed o hose wi hou such collabo a ions. Howe e , Becke e al. (2023) sugges ha uni e si y spillo e s can be limi ed, wi h some e idence o posi i e e ec s on pa en ing and new- o- ma ke inno a ion in speci ic ci cums ances. While uni e si y R&D ans e s o e signi ican ad an ages, challenges emain. Kanama & Nishikawa (2015) iden i y a ious obs acles in inno a ion ac i i ies, such as inancial and echnological limi a ions, ha d i e i ms o seek uni e si y knowledge. Howe e , access o uni e si y knowledge may no always ansla e in o p o i able inno a ion. In conclusion, a g owing body o esea ch suppo s he posi i e impac o uni e si y R&D ans e s on i m inno a ion. The e ec i eness o hese ans e s depends on ac o s such as he i m's abso p i e capaci y, he uni e si y's esea ch en i onmen , and he na u e o collabo a ion ne wo ks. Fu he esea ch is needed o explo e he mechanisms unde lying uni e si y R&D spillo e s and iden i y s a egies o maximize hei bene i s o i ms. 3. DATA DESCRIPTION This sec ion p esen s a desc ip ion o he da abase used, he a iables employed o he analysis, and he new a iables ha ha e been gene a ed om he exis ing ones. I will conclude wi h a b ie desc ip i e analysis o he sample. In o de o asce ain he in luence o collabo a ion wi h uni e si ies on o ganiza ional inno a ion, he p esen s udy u ilizes an exis ing da abase om a Spanish su ey, namely PITEC, conduc ed be ween 2003 and 2016. The PITEC (Panel de Inno ación Tecnológica, Panel o Technological Inno a ion) p ojec has he objec i e o ep esen ing he si ua ion and e olu ion o inno a i e companies in Spain, as well as he de ec ion o oppo uni ies and needs in his ield. The p ojec commenced in 2003 wi h he collabo a ion o he FECYT (Fundación Española pa a la Ciencia y la Tecnología, Spanish Founda ion o Science and Technology) and Mi ian Oiz / Mas e in Economics: Empi ical Applica ions and Policies - 7 - he Co ec Founda ion, wi h he inpu o a g oup o esea che s om a ious uni e si ies. Howe e , his ceased o be ca ied ou in 2016. The da a om his pe iod o e s mo e han 460 a iables de i ed om app oxima ely 12,000 companies su eyed om 2003 onwa d, acili a ing he cons uc ion o ime se ies ha can be used o s udy he e olu ion and impac o inno a ion in he business sec o , as well as o iden i y he di e se inno a ion s a egies employed by companies in ques ion. As i is a ixed panel, an annual obse a ion is collec ed om each i m, which ensu es ha he da a ob ained a e o high quali y and eliabili y. The panel o companies is selec ed om he na ional su eys ca ied ou by he INE (Ins i u o Nacional de Es adís ica, Na ional S a is ics Ins i u e) in he inno a ion sec o : "Su ey on Technological Inno a ion in Companies" and "S a is ics on R&D ac i i ies". 3.1. Va iable de ini ion As p e iously s a ed, he da abase comp ises a mul i ude o a iables measu ing di e se quali ies, om which we ha e iden i ied hose pe inen o ou in es iga ion. The p ima y a iable o in e es , which will se e as he basis o in e ence, is he ans e o esea ch and de elopmen (R&D) unds om uni e si ies o i ms. They appea as 'Pu chase o R&D se ices in Spain/uni e si ies' and 'Pu chase o R&D se ices ab oad/uni e si ies'. They ep esen he p opo ion o ex e nal R&D expendi u e in he i m, along wi h he pu chase o se ices in o he en i ies, which we will la e addi ionally analyze. F om hese, he main ea men a iable o he s udy has been c ea ed, which akes alue o 1 i he i m has ecei ed ans e s om uni e si ies and 0 i i has no . Fu he mo e, as in Ga cía-Vega and Vicen e-Chi i ella (2020), we ha e de ined a class o i ms ha ha e been called "s a e s". This denomina ion is accompanied by he yea in which he company collabo a es wi h a uni e si y o he i s ime ( i s ime i ecei es ans e s). In his way, as many s a e a iables ha e been gene a ed as he e a e yea s in he da abase, wi h a dummy ca ego y and a alue o 1 i he company is a s a e ha yea and 0 o he wise. In able 1 he s a e coun o each yea can be seen. The numbe o s a e s o each yea o he sample is sp ead o e he yea s, wi h all yea s Mi ian Oiz / Mas e in Economics: Empi ical Applica ions and Policies - 8 - ha ing igu es in he app oxima e ange o be ween 400 and 800, excep yea 2014, wi h mo e han 1800, and 2015 wi h 203 i ms. Table 1 S a e s ( i s ime ecei ing ans e s) Yea Numbe o s a e s 2004 591 2005 884 2006 503 2007 631 2008 547 2009 516 2010 511 2011 468 2012 409 2013 426 2014 1826 2015 203 2016 575 Sou ce: Own elabo a ion wi h PITEC da a The a iables employed as ea men a e he ‘s a e s’ ones discussed in he p eceding pa ag aphs, wi h 2006 being he example yea : he p e- ea men pe iod is de ined as spanning 2003 o 2005, while he pos - ea men pe iod, du ing which he e ec s o ea men can be obse ed, is de ined as spanning 2006 o 2016. The ea ed g oup is de ined as he i ms which commenced collabo a ion wi h uni e si ies in 2006, while he con ol g oup is de ined as he i ms ha nei he collabo a ed wi h uni e si ies no any o he o he en i ies. As o he dependen a iables, di e en ou comes ha e been aken as indica o s o he deg ee o inno a ion o inno a i e capaci y o he i ms. These a e whe he o no he company has had a p ocess inno a ion in he p e ious wo yea s, whe he o no i has had a p oduc inno a ion in he p e ious wo yea s, whe he o no i has had a pa en applica ion and he numbe o pa en s egis e ed. The impac o collabo a ion be ween companies and uni e si ies on he ou has been in es iga ed o e he cou se o he ollowing yea s. Mi ian Oiz / Mas e in Economics: Empi ical Applica ions and Policies - 9 - In closing, se e al con ol a iables ha e been selec ed o use as co a ia es in he es ima ion o e ec s. These include he numbe o employees o he i m, he amoun o physical capi al, he amoun o ex e nal esea ch and de elopmen expendi u e, he amoun o in e nal esea ch and de elopmen expendi u e, he p esence o absence o expo s, and inally, whe he he i m belongs o a business g oup. 3.2. Desc ip i e analysis P io o es ima ing he e ec s in ques ion, a b ie desc ip i e analysis was conduc ed o gain a comp ehensi e unde s anding o he sample. The da a a e p esen ed in Table 2, which shows he numbe o obse a ions, he mean, and he s anda d de ia ion o he ull sample, as well as o he obse a ions o i ms ha ha e ecei ed uni e si y ans e s and hose ha ha e no , sepa a ely. Table 2 Desc ip i e s a is ics Full sample Wi h uni e si y ans e s Wi hou uni e si y ans e s Obs. Mean S d. de . Obs. Mean S d. de . Obs. Mean S d. de . T ea men Va i a b l e T ans e s om uni e si ies 171.511 0,261 0,439 44.812 1 0 126.699 0 0 Ou come a iables P ocess inno a ion 135.798 0,467 0,498 9.110 0,704 0,457 126.688 0,451 0,498 P oduc inno a ion 135.799 0,464 0,498 9.110 0,744 0,437 126.689 0,445 0,497 Pa en s 135.797 0,101 0,301 9.109 0,311 0,463 126.688 0,086 0,281 Numbe o pa en s 125.717 0,487 5,938 8.325 2,238 14,385 117.392 0,363 4,781 Con ol a iables Employmen 135.810 333,624 1.527,846 9.111 393,854 1.337,530 126.699 329,296 1.540,540 Physical in es men 135.810 4,507 12,970 9.111 10,807 17,271 126.699 4,055 12,482 Resea che s in R&D 135.810 6,765 18,684 9.111 23,904 23,773 126.699 5,533 17,634 In e nal R&D 135.810 39,609 43,815 9.111 66,055 26,574 126.699 37,708 44,195 Expo s 171.511 0,628 0,483 44.812 0,937 0,243 126.699 0,519 0,500 G oup 135.724 0,411 0,492 9.088 0,503 0,500 126.636 0,405 0,491 Sou ce: Own elabo a ion wi h PITEC da a Mi ian Oiz / Mas e in Economics: Empi ical Applica ions and Policies - 16 - Figu e 2 shows he e ec s in a imeline ashion, and al hough as no ed abo e mos o hem a e posi i e, hey a e no as obus o ep esen a i e as migh be expec ed a i s . Figu e 2 Impac o ea men on p oduc inno a ion Sou ce: Own elabo a ion wi h PITEC da a A simila pa e n eme ges wi h espec o he p obabili y o iling a pa en when ini ia ing collabo a ion wi h uni e si ies. This ou come unde sco es ha , excep o a ew yea s in he 2006 coho and owa ds he end o 2015 and 2016, he p obabili y o iling a pa en is highe when s a ing o collabo a e wi h uni e si ies. The nume ical e ec s a e p esen ed in Table 5. I is in his ou come ha he e ec s a e mos signi ican , and hus i can be s a ed ha , wi h ega d o inno a ion, he mos no able e ec obse ed in he -.12 -.08 -.04 0 .04 .08 .12 Impac 2011 2012 2013 2014 2015 2016 Da e Impac es ima e 95% con idence in e al Da a om 2011-2016 Impac on P oduc Inno a ion o 2011 s a e s Mi ian Oiz / Mas e in Economics: Empi ical Applica ions and Policies - 17 - analysis is he inc ease in he p opo ion o hose who ha e egis e ed pa en s wi h espec o hose who ha e no egis e ed any. Fu he mo e, as illus a ed in Figu e 3, mos e ec s a e posi i e, wi h alues exceeding ze o. Table 5 Change in he p obabili y o egis e ing a pa en Impac in yea 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 S a e o 2006 .0011 (.0152) .0243 (.0178) .0209 (.0205) -.0124 (.0206) .0080 (.0216) -.0170 (.0210) -.0163 (.0218) .0070 (.0227) -.0180 (.0241) .0015 (.0238) -.0115 (.0235) 2007 .0322** (.0156) .0373** (.0182) .0269 (.0197) .0247 (.0211) .0244 (.0216) .0251 (.0219) .0359 (.0223) .0242 (.0237) .0478** (.0240) .0308 (.0234) 2008 .0499*** (.0169) .0281 (.0185) .0401* (.0209) .0291 (.0218) .0328 (.0221) .0634*** (.0226) .0361 (0238) .0471* (.0241) .0304 (.0247) 2009 .0082 (.0165) .0283 (.0196) .0204 (.0216) .0438** (.0221) .0589** (.0240) .0467* (.0254) .0319 (.0254) .0299 (.0252) 2010 -.0048 (.0173) -.0181 (.0195) .0084 (.0202) .0254 (.0233) .0202 (.0241) .0210 (.0239) .0301 (.0237) 2011 .0065 (.0183) .0136 (.0205) .0458** (.0227) .0289 (.0237) .0146 (.0246) .0099 (.0261) 2012 .0264 (.0194) .0383* (.0213) .0247 (.0236) .0093 (.0251) -.0073 (.0258) 2013 .0514** (.0199) .0402* (.0212) .0195 (.0228) .0010 (.0249) 2014 .0210 (.0218) .0243 (.0225) .0133 (.0114) 2015 .0171 (.0203) -.0153 (.0219) 2016 -.0224 (.0246) ∗ Signi ican a 10%; ∗∗ Signi ican a 5%; ∗∗∗ signi ican a 1%. Sou ce: Own elabo a ion wi h PITEC da a Mi ian Oiz / Mas e in Economics: Empi ical Applica ions and Policies - 18 - Figu e 3 Impac o ea men on pa en egis a ion Sou ce: Own elabo a ion wi h PITEC da a Finally, he las ou come o be analyzed is he change in he numbe o pa en s iled (Table 6). The es ima es ob ained exhibi a high a iabili y, and he e is no clea pa e n o posi i e o nega i e e ec s wi h almos all es ima es being insigni ican ly di e en om ze o, so no i m conclusions can be d awn abou hese e ec s. I can also be seen ha he s anda d e o s a e conside ably la ge han he o he s, and all his could be ela ed o he con inuous na u e o he ou come. Mi ian Oiz / Mas e in Economics: Empi ical Applica ions and Policies - 19 - Table 6 Change in he numbe o egis e ed pa en s Impac in yea 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 S a e o 2006 .0438 (.0920) .1165 (.2004) -.4500 (.6423) -.0622 (.3324) .0164 (.4542) -.2942 (.2816) -.1071 (.4754) .1195 (.4782) .3030 (.5500) -.1630 (.5754) -.1946 (.6685) 2007 .1545 (.1819) -1.163 (1.339) .1819 (.2491) .2150 (.3651) -.0374 (.2029) .0055 (.3950) .0041 (.4108) .1086 (.4862) -.4652 (.8415) -.6558 (.8689) 2008 -.6358 (.8092) .2230 (.2658) .1796 (.3966) -.3360 (.3484) .2267 (.5077) -.1975 (.5495) .3050 (.4998) -.8837 (1.377) -.8229 (1.328) 2009 .9361 (.9608) 1.128 (.9464) .5410 (.9700) 1.040 (1.016) 1.091 (.9966) .6151 (.9276) -.9582 (1.569) -1.029 (1.494) 2010 .0302 (.2256) -.6533* (.3855) .0250 (.4572) -.4365 (.3945) -.2279 (.4886) -.6273 (.5424) -1.141 (.7150) 2011 -.7564 (.5721) -.3828 (.3853) -.3576 (.4088) .2046 (.5254) -1.997 (1.423) -1.629 (1.636) 2012 .3527 (.4991) .4364 (.4661) .5516 (.5408) -1.387 (1.594) -1.483 (1.554) 2013 .2240 (.1956) .5124* (.2846) -1.538 (1.601) -1.046 (1.679) 2014 .6782 (.5710) -.4408 (.9640) -.3039 (.2792) 2015 -1.539 (.9540) -2.17** (1.012) 2016 -.7493 (.5091) ∗ Signi ican a 10%; ∗∗ Signi ican a 5%; ∗∗∗ signi ican a 1%. Sou ce: Own elabo a ion wi h PITEC da a G aphically, we also ind mo e i egula lines han in he g aphs o he o he esul s, highligh ing a d op in he numbe o pa en s egis e ed in 2008, p obably ela ed o he Spanish c isis o ha yea , which can be analyzed in he g aphs o se e al o he s a e s. Mi ian Oiz / Mas e in Economics: Empi ical Applica ions and Policies - 20 - Figu e 4 Impac o ea men on numbe o pa en egis a ion Sou ce: Own elabo a ion wi h PITEC da a 5.2. Compa ison wi h he e ec o collabo a ion wi h o he companies (p oduc inno a ion) Wi h he in en ion o ex ending he analysis ca ied ou and inding new cha ac e is ics o he de e minan s o en ep eneu ial inno a ion, he ini ial a iables and he ATET es ima es we e e o mula ed, bu conside ing ha he ea men was now collabo a ion wi h o he i ms. In his way, he e ec on en ep eneu ial inno a ion can be compa ed wi h he es ima es ob ained o collabo a ion wi h uni e si ies. Mi ian Oiz / Mas e in Economics: Empi ical Applica ions and Policies - 21 - Due o he size o he esul s ables, one esul (in his case p oduc inno a ion) has been selec ed and included in Appendix 1. The esul s o R&D ans e s wi h o he en e p ises a e simila o hose o uni e si ies. Fo mos s a e s, he e ec on he p obabili y o ha ing a p oduc inno a ion is posi i e when hey s a o pu chase esea ch se ices om o he en e p ises, wi h hese igu es being e y signi ican o s a e s en e p ises in ecen yea s. Figu e 5 shows ha he e ec s ollow a simila pa e n o bo h ypes o collabo a ion and ha he ange o he es ima es and he con idence in e als a e he same (collabo a ion wi h uni e si ies is he blue line and wi h companies he ed line). Figu e 5 Compa ison o p oduc inno a ion o s a e s o 2008 and 2009 Sou ce: Own elabo a ion wi h PITEC da a 5.3. Compa ison wi h he e ec o collabo a ion wi h any ype o o ganiza ion (pa en egis a ion) To comple e his ex ension o he s udy, a di e en ea men g oup was again selec ed, consis ing o hose en e p ises ha s a ed o collabo a e wi h one o he o ganiza ions o which he sample p o ides da a (g oup en e p ises, o he en e p ises, uni e si ies, public adminis a ion o ganiza ions, p i a e non-p o i o ganiza ions and Mi ian Oiz / Mas e in Economics: Empi ical Applica ions and Policies - 22 - in e na ional o ganiza ions). The con ol g oup includes all i ms ha ha e ne e collabo a ed wi h anyone, and o show he compa ison o esul s, he ou come o pa en ing has been chosen ( he able o es ima es can be ound in Appendix 2). As expec ed, he e ec ound is also p edominan ly posi i e. I he indi idual collabo a ions wi h uni e si ies and o he companies we e posi i e, we would expec an e en la ge change in he p obabili y o iling a pa en . Howe e , he obse ed e ec is no as signi ican as an icipa ed and canno be ex ended o he en i e popula ion (only o some s a e s in he sample). This compa ison can also be seen in g aphical o m in Figu e 6, whe e collabo a ion wi h uni e si ies is ep esen ed by he blue line and join collabo a ion by he g een line. Figu e 6 Compa ison o pa en egis a ion o s a e s o 2009 and 2010 Sou ce: Own elabo a ion wi h PITEC da a 6. CONCLUSIONS This s udy p o ides weak e idence in suppo o he p oposi ion ha uni e si y collabo a ions os e inno a ion wi hin i ms. The indings illus a e ha he majo i y o pa icipa ing o ganiza ions ha e expe ienced posi i e bu mos ly insigni ican impac s on a ious inno a ion ou comes, including p ocess and p oduc inno a ion. These esul s a e Mi ian Oiz / Mas e in Economics: Empi ical Applica ions and Policies - 23 - no qui e in acco dance wi h exis ing esea ch which has iden i ied he impo an ole played by he ans e o uni e si y esea ch and de elopmen o i ms in s imula ing inno a ion. I is impo an o acknowledge ha he indings o his s udy a e subjec o ce ain limi a ions. The me hodology employed di e s om ha desc ibed in he o iginal pape s. Fu he mo e, he s udy concen a es on he in luence o uni e si y collabo a ion, whe eas o he ac o s, including he abili ies and expe ise o employees, business ac i i y, inancial esou ces, and echnological in as uc u e, also exe a conside able in luence on inno a ion. Fu he esea ch should in es iga e hese mul i ace ed ac o s in g ea e dep h in o de o gain a mo e comp ehensi e unde s anding o hei in e ac ion wi h uni e si y collabo a ion and i s ul ima e impac on i m inno a ion. By in es iga ing he mode a ing and media ing e ec s o hese a iables, esea che s can p o ide mo e de ailed knowledge o he ci cums ances unde which uni e si y collabo a ions a e mos e ec i e in d i ing inno a ion. Despi e hese limi a ions, he indings o his s udy highligh he signi ican ole o ins i u ional collabo a ion in s imula ing inno a ion wi hin i ms. By le e aging he expe ise and esou ces o uni e si ies, i ms can enhance hei inno a i e capabili ies, leading o he de elopmen o new p oduc s, p ocesses, and se ices ha d i e economic g ow h and socie al well-being. Mi ian Oiz / Mas e in Economics: Empi ical Applica ions and Policies - 24 - 7. REFERENCES Abadie, A., & Imbens, G. W. (2011). Bias-Co ec ed Ma ching Es ima o s o A e age T ea men E ec s. Jou nal O Business & Economic S a is ics, 29(1), 1-11. h ps://doi.o g/10.1198/jbes.2009.07333 Abadie, A., D ukke , D., He , J. L., & Imbens, G. W. (2004). 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