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Dig ita l Da rk ma tte r By Sha ne Gre e nste in F o r CAI DA WI - PowerPoint PPT Presentation

Dig ita l Da rk ma tte r By Sha ne Gre e nste in F o r CAI DA WI E T he a g e nda GDP is the to ta l flo w o f fina l g o o ds a nd se rvic e s in a n e c o no my o ve r a spe c ific pe rio d o f time (witho ut do ub le c o unting


  1. Dig ita l Da rk ma tte r By Sha ne Gre e nste in F o r CAI DA WI E

  2. T he a g e nda  GDP is the to ta l flo w o f fina l g o o ds a nd se rvic e s in a n e c o no my o ve r a spe c ific pe rio d o f time (witho ut do ub le c o unting ).  E ve ry de ve lo pe d c o untry me a sure s GDP, c a pita l sto c ks, la b o r sto c k, c a pita l flo ws a nd la b o r flo ws. Bro a d e ffo rt to unde rsta nd c o ntrib utio ns fro m va rio us pa rts.  Digital dar k matte r : Asse t w/ o a ppa re nt mo ne ta ry va lue , tha t c a n b e re plic a te d witho ut limit, & a c t a s I T input into pro duc tio n.  if pric e is ze ro , it c o ntrib ute s no thing to GDP  I nc re a sing ro le o f “inta ng ib le ” c a pita l in the e c o no my.  At this sta g e : de mo nstra ting pr oof of c onc e pt.

  3. One wa y to mo tiva te it: One o f se ve ra l me a sure me nt issue s due to a ze ro pric e . Ze r o Pr ic e in most of the output Positive pr ic e in most of the output   Ze ro Pric e in Wikipe dia . oid pho ne use s L inux ke rne l. Andr   mo st o f the inux F o unda tio ns um . Apac he / L Unlic e nse d spe c tr   inputs Github . Alg o rithms fo r mac hine le ar ning  And mor e … .   Po sitive Pric e B. F re e o utput, a ds ra ise Ma nufa c turing iPhone . Google / F  in mo st o f re ve nue . Ne tflix pa y lic e nse s. Sub sc rib e rs pa y  the inputs B . Se e a b o ve . fe e . Comme r c ial WE  Ca rrie r pa id lic e nse for spe c tr um .

  4. Wha t the first study do e s (Gre e nste in a nd Na g le , 2015)  T a ke s a o ne pe rc e nt sa mple o f a ll I P a ddre sse s a nd e stima te s the to ta l numb e r o f Apa c he se rve rs in the US in 2011. Pr oof of c onc e pt e xe r c ise .  Atta c h a va lue to o pe n so urc e se rve rs using sta nda rd pro c e dure s fo r “ne a r ma rke t g o o ds,” a s de fine d b y No rdha us, 2006.  Apa c he a c c o unts fo r a misme a sure me nt o f so me whe re b / w $2 b illio n a nd $12 b illio n in so ftwa re in the US in 2011.  L ge . E ar q ua te s to b / w 1.3 % & 8.7 % o f sto c k o f pre pa c ka g e d so ftwa re in priva te fixe d inve stme nt in the US  High ROR. Re turn o n Apa c he a lo ne wo uld ha ve g e ne ra te d suffic ie nt ra te o f re turn to justify inve stme nt in I nte rne t R&D b y F e de ra l g o ve rnme nt.  Omission biase s. L a rg e .  Attrib utio n b ia s? No .

  5. Wha t the se c o nd study do e s (Ac ke rma nn a nd Gre e nste in, 2018)  T a ke s a b ig sa mple o f o utwa rd fa c ing se rve rs in the pla ne t in 2012. Apa c he , ng inx, & I I S in 2012. Pro o f o f c o nc e pt a t a global le ve l.  L o c a te s a se rve r in a c o untry using me tho ds fo r a ssig ning l ong/ lat to I P a ddre sse s,. Co mpa re a c ro ss c o untrie s.

  6. Ma ps: whe re se rve rs a re lo c a te d

  7. Wha t the se c o nd study do e s (Ac ke rma nn a nd Gre e nste in, 2018)  T a ke s a b ig sa mple o f o utwa rd fa c ing se rve rs in the pla ne t in 2012. Apa c he , ng inx, & I I S in 2012. Pro o f o f c o nc e pt a t a global le ve l.  L o c a te s a se rve r in a c o untry using me tho ds fo r a ssig ning long/ lat to I P a ddre sse s,. Co mpa re a c ro ss c o untrie s.  Ske we d a c ro ss the wo rld.  US ha s 44% o f se rve rs. Ne xt b ig g e st is China , whic h is six time s sma lle r.  Ana lyze who ha s mo re a nd why?  Be st pre dic to rs o f se rve r a nd pe r-c a pita se rve rs a re the q ua lity o f the ne two rk a nd the so phistic a tio n o f the la b o r ma rke t fo r te c hnic a l g o o ds.  Rule o f la w a nd indic a tio ns o f “fa ile d” institutio ns do no t ma tte r  Ve xing . Ca nnot e a sily fore c a st ope n sourc e sha re

  8. T hird study fro m Wa yb a c k Ma c hine (Gre e nste in, Murc ia no -Go ro ff & Zhuo , 2018) Sma ll & me dium firms L a rg e firms L a rg e st firms * Pre limina ry: Usa g e sha re s fo r we b site s a t 200k+ US firms. A who le a sse t c la ss fo r whic h we ha ve NO inve stme nt da ta . Me a sure d fo r the first time . Ve ry diffic ult to c le a n up. * Pro o f o f c o nc e pt. L a rg e (? ) misme a sure me nt o f inta ng ib le c a pita l inside firms. * Ve ry diffe re nt a do ptio n a nd upg ra de b e ha vio r a c ro ss diffe re nt type s o f firms.

  9. Ope n q ue stio ns:  Othe r e xa mple s?  F ra nk Na g le ha s sho wn tha t muc h OS ha s a dire c t pr oduc tivity impa c t o n the firms who de plo y it.  T c e ? E .g ., L inux, F ire fo x, PE RL , he sa me me c ha nisms. Any ope n sour PHP, 802.11 so ftwa re .  Spillove r sity R&D witho ut lic e nsing . E .g ., WWW, s fr om unive r b ro wse rs, T CP/ I P so ftwa re pro to c o ls, e tc .  Cr e ative c ommons: Wikipe dia , K a hn Ac a de my, Github ? Unme a sure d g a ins c o uld b e la rg e due to me a sure d b y a udie nc e size .  T he spe c tr um in Wifi e q uipme nt? Sta nda rds fro m I E E E  Be yo nd pro o f o f c o nc e pt? Mo re tha n a ro unding e rro r. L a rg e e no ug h va lue to ma tte r.

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