{"id":37209,"date":"2019-10-31T22:16:21","date_gmt":"2019-10-31T19:16:21","guid":{"rendered":"https:\/\/prohoster.info\/blog\/zolotoe-sechenie-v-ekonomike-chto-eto\/"},"modified":"2019-10-31T22:16:21","modified_gmt":"2019-10-31T19:16:21","slug":"zolotoe-sechenie-v-ekonomike-chto-eto","status":"publish","type":"post","link":"https:\/\/prohoster.info\/hr\/blog\/news\/zolotoe-sechenie-v-ekonomike-chto-eto","title":{"rendered":"\u0160to je \u201ezlatni rez\u201c u ekonomiji?","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"

Nekoliko rije\u010di o 'zlatnom omjeru' u tradicionalnom smislu<\/h4>\n

\nVjeruje se da, ako se segment podijeli na dijelove na takav na\u010din da se manji dio odnosi na ve\u0107i kao ve\u0107i dio na cijeli segment, takvo dijeljenje daje omjer 1\/1,618, koji su stari Grci, posudiv\u0161i ga od jo\u0161 starijih Egip\u0107ana, nazvali 'zlatnim omjerom'. I da su mnoge arhitektonske gra\u0111evine \u2013 omjeri kontura zgrada, omjeri izme\u0111u njihovih klju\u010dnih elemenata \u2014 od egipatskih piramida do teoretskih konstrukcija Le Corbusiera \u2014 temeljene na ovom omjeru.
\nNjemu odgovaraju Fibonacci brojevi, \u010dija spirala daje razra\u0111enu geometrijsku ilustraciju ovog omjera. <\/p>\n

\u0160tovi\u0161e, dimenzije ljudskog tijela (od stopala do pupka, od pupka do glave, od glave do prstiju podignutih ruku), po\u010dev\u0161i od idealnih proporcija vi\u0111enih u Srednjem vijeku (vitruvijanski \u010dovjek i dr.) i zavr\u0161avaju\u0107i antropometrijskim mjerenjima populacije SSSR-a, prili\u010dno su bliske ovom omjeru.
\n<\/a><\/noindex>
\nA ako se doda da se sli\u010dne figure nalaze u potpuno heterogenim biolo\u0161kim objektima: \u0161koljkama meku\u0161aca, rasporedu sjemena u suncokretu i u borovim \u0161i\u0161arcima, jasno je za\u0161to se iracionalni broj, koji po\u010dinje kao 1,618, progla\u0161ava 'bo\u017eanskim' \u2014 njegovi tragovi se prate \u010dak i u obliku galaksija koje te\u017ee Fibonacci spirali!<\/p>\n

S obzirom na sve navedene primjere, mo\u017ee se pretpostaviti: <\/p>\n

    \n
  1. mi imamo posla s istinskim \"velikim podacima\", <\/li>\n
  2. \u010dak i u prvom pribli\u017eavanju oni ukazuju na neku, ako ne op\u0107nost, onda iznimno \u0161iroku prisutnost 'zlatnog omjera' i vrijednosti bliskih njemu.<\/li>\n<\/ol>\n

    <\/p>\n

    U ekonomiji<\/h4>\n

    \n\u0160iroko su poznate i intenzivno se koriste Lorencove dijagrame za vizualizaciju prihoda populacije. Ovaj mo\u0107an makroekonomski alat s raznolikim varijacijama i poja\u0161njenjima (decilski koeficijent, Gini indeks) koristi se u statistici za socio-ekonomsko uspore\u0111ivanje zemalja i njihovih zna\u010dajki i mo\u017ee poslu\u017eiti kao opravdanje za dono\u0161enje velikih politi\u010dkih i bud\u017eetskih odluka u podru\u010dju oporezivanja, zdravstva, izrade razvojnih planova za zemlje i regije.<\/p>\n

    Iako su u normalnoj svakodnevnoj svijesti prihodi i rashodi \u010dvrsto povezani, to u Googleu nije slu\u010daj... \u010cudno je, ali sam povezanost Lorenzovih dijagrama s raspodjelom rashoda uspio prona\u0107i samo kod dvojice ruskih autora (bio bih zahvalan ako netko zna sli\u010dne radove u ruskom i engleskom sektoru interneta). <\/p>\n

    Prvi je disertacija T. M. Bueve. Disertacija je, izme\u0111u ostalog, bila posve\u0107ena optimizaciji rashoda na marijskim farmama peradi.<\/p>\n

    Drugi autor, V.V. Matohin (postoje uzajamne reference autora), pristupa temi na \u0161iri na\u010din. Matohin, fizi\u010dar po obrazovanju, bavi se statisti\u010dkom obradom podataka koji se koriste pri dono\u0161enju upravlja\u010dkih odluka, kao i procjenom prilagodljivosti i upravljivosti poduze\u0107a.<\/p>\n

    Koncept i primjeri koji se navode u nastavku preuzeti su iz radova V. Matohina i njegovih kolega (Matohin, 1995), (Antoniou i dr., 2002), (Kryanev i dr., 1998), (Matohin i dr., 2018). U tom smislu treba dodati da su mogu\u0107e gre\u0161ke u tuma\u010denju njihovih radova isklju\u010divo odgovornost autora ovih redaka i ne mogu se pripisati izvorim akademskim tekstovima. <\/p>\n

    Neo\u010dekivana konstanta<\/h4>\n

    \nPrikazano na grafikama u nastavku.<\/p>\n

    1. Raspodjela grantova prema natje\u010daju za znanstveno-tehni\u010dke radove u okviru Dr\u017eavnog programa \"Visokotemperaturna superprovodljivost\". (Matohin, 1995)
    \n\"\u0160to
    \nSlika 1. Proporcije u godi\u0161njoj raspodjeli sredstava po projektima u razdoblju 1988-1994.<\/i>
    \nOsnovne karakteristike godi\u0161njih raspodjela prikazane su u Tablici 3, gdje je SN \u2014 godi\u0161nji iznos raspore\u0111enih sredstava (u milijunima rubalja), a N \u2014 broj financiranih projekata. S obzirom na to da se tijekom tih godina mijenjao osobni sastav \u017eirija natje\u010daja, prora\u010dun natje\u010daja i \u010dak razmjeri sredstava (prije i poslije reforme 1991. godine), stabilnost stvarnih krivulja kroz vrijeme nevjerojatna je. Crna linija na grafikonu sastavljena je od eksperimentalnih to\u010daka.<\/p>\n\n\n\n\n
    <\/td>\n1988<\/td>\n1989<\/td>\n1990<\/td>\n1991<\/td>\n1992<\/td>\n1993<\/td>\n1994<\/td>\n<\/td>\n<\/tr>\n
    S<\/td>\n273<\/td>\n362<\/td>\n432<\/td>\n553<\/td>\n345<\/td>\n353<\/td>\n253<\/td>\nX<\/td>\n<\/tr>\n
    Sn<\/td>\n143.1<\/td>\n137.6<\/td>\n136.9<\/td>\n411.2<\/td>\n109.4<\/td>\n920<\/td>\n977<\/td>\nY<\/td>\n<\/tr>\n<\/table>\n

    \nTablica 3<\/i><\/p>\n

    2. Krivulja rashoda povezanih s prodajom zaliha (Kotlyar, 1989)
    \n\"\u0160to
    \nSlika 2<\/i> <\/p>\n

    3. Tarifna mre\u017ea pla\u0107a po \u010dinovima<\/p>\n

    Kao primjer za izradu dijagrama kori\u0161teni su podaci iz dokumenta \"Izvje\u0161\u0107e: koliko kojim \u010dinovima prema obi\u010dnim godi\u0161njim pla\u0107ama pripada imati godi\u0161nje\" (Suvorov, 2014)(\"Znanje pobje\u0111uje\"). <\/p>\n\n\n
    \n\n\n\n\n\n\n\n\n\n\n
    Cin<\/td>\nPla\u0107a (rub.)<\/td>\n<\/tr>\n
    Pukovnik<\/td>\n585<\/td>\n<\/tr>\n
    Potpukovnik<\/td>\n351<\/td>\n<\/tr>\n
    Major primjer<\/td>\n292<\/td>\n<\/tr>\n
    Majore Sekunda<\/td>\n243<\/td>\n<\/tr>\n
    \u010cetvrtmaster<\/td>\n117<\/td>\n<\/tr>\n
    Pomo\u0107nik<\/td>\n117<\/td>\n<\/tr>\n
    Komesar<\/td>\n98<\/td>\n<\/tr>\n
    \u2026<\/td>\n\u2026<\/td>\n<\/tr>\n<\/table>\n

    \n<\/td>\n

    		\"\u0160to
    \nSlika 3. Dijagram proporcionalnosti godi\u0161njih pla\u0107a prema \u010dinovima\n<\/td>\n<\/tr>\n<\/table>\n

    4. Prose\u010dan radni raspored ameri\u010dkog srednjeg menad\u017eera (Mintzberg, 1973)
    \n \"\u0160to
    \nSlika 4 <\/i> <\/p>\n

    Prikazani normirani grafikoni sugeriraju da u ilustrovanim poslovnim aktivnostima postoji zajedni\u010dka zakonitost. Iako postoji radikalna razlika u specifi\u010dnosti poslovne delatnosti, njenom mestu i vremenu, vrlo je verovatno da je sli\u010dnost grafikona dictated neki fundamentalni uslov funkcionisanja ekonomskih sistema. Ne mo\u017ee se druga\u010dije nego \u0161to su tokom milenijuma vo\u0111enja poslovanja, na osnovu ogromnog broja probnih i gre\u0161aka, subjekti te delatnosti prona\u0161li neku optimalnu strategiju raspodele resursa. I intuitivno je koriste u trenutnim aktivnostima. Ova pretpostavka se dobro sla\u017ee sa poznatim Pareto principom: 20% na\u0161ih napora donosi 80% rezultata. Ovdje se jasno vidi ne\u0161to sli\u010dno. Prikazani grafikoni izra\u017eavaju empirijsku zakonitost koja, kada se pretvori u Lorencov dijagram, sa dovoljnom ta\u010dno\u0161\u0107u opisuje se sa koeficijentom \u201ealfa\u201c jednakim 2. Pri tom koeficijentu, Lorencov dijagram postaje deo kru\u017enice.<\/p>\n

    Ovu karakteristiku, koja jo\u0161 uvek nema stabilno ime, mo\u017eemo nazvati pre\u017eivljavanjem. Po analogiji s pre\u017eivljavanjem u divljini, pre\u017eivljavanje poslovnog sistema odre\u0111uje se njegovim ste\u010denim prilago\u0111avanjem uslovima socio-ekonomske sredine i sposobno\u0161\u0107u adaptacije na promene tr\u017ei\u0161nih uslova.<\/p>\n

    To zna\u010di da sistem u kojem je raspodela tro\u0161kova blizu idealnoj (sa koeficijentom \u201ealfa\u201c jednakim 2 ili raspodelom tro\u0161kova \u201epo kru\u017enici\u201c), ima najve\u0107e \u0161anse da ostane u postoje\u0107em obliku. Zanimljivo je da u nekim slu\u010dajevima takva raspodela odre\u0111uje i najve\u0107u rentabilnost preduze\u0107a. Na primer, ovde. \u0160to je manji koeficijent odstupanja od idealnog, to je vi\u0161a rentabilnost preduze\u0107a (Bueva, 2002).<\/p>\n

    Tabela (fragment)<\/p>\n\n\n\n\n\n\n\n\n\n\n\n\n
    <\/td>\nNaziv gazdinstva, region<\/td>\nRentabilnost (%)<\/td>\nKoeficijent odstupanja<\/td>\n<\/tr>\n
    1<\/td>\nGUP p\/f 'Vol\u017eska' Vol\u017eskog regiona<\/td>\n13,0<\/td>\n0,336<\/td>\n<\/tr>\n
    2<\/td>\nSPK p\/f 'Gornomariski'<\/td>\n11,1<\/td>\n0,18<\/td>\n<\/tr>\n
    3<\/td>\nUMSP s-z 'Zvenigovski'<\/td>\n33,7<\/td>\n0,068<\/td>\n<\/tr>\n
    4<\/td>\nZAO \u00abMarijensko\u00bb Medvedevskog okruga<\/td>\n7,5<\/td>\n0,195<\/td>\n<\/tr>\n
    5<\/td>\nOAO \u00abTepli\u010dno\u00bb Medvedevskog okruga<\/td>\n16,3<\/td>\n0,107<\/td>\n<\/tr>\n
    \u2026<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/tr>\n
    47<\/td>\nSPK (k-z) \u00abRassvet\u00bb Sovetskoga okruga<\/td>\n3,2<\/td>\n0,303<\/td>\n<\/tr>\n
    48<\/td>\nS-z \u00abBronjevik\u00bb Kilemarskog okruga<\/td>\n14,2<\/td>\n0,117<\/td>\n<\/tr>\n
    49<\/td>\nSPK SHA \u00abAvangard\u00bb Morkinskog okruga<\/td>\n6,5<\/td>\n0,261<\/td>\n<\/tr>\n
    50<\/td>\nSHA k-z im. Petrov\u0430 Morkinskog okruga<\/td>\n22,5<\/td>\n0,135<\/td>\n<\/tr>\n<\/table>\n

    Prakti\u010dni zaklju\u010dci<\/h4>\n

    \nKada planirate tro\u0161kove, kako za kompanije, tako i za doma\u0107instva, korisno je izraditi Lorencovu krivulju i uporediti je s idealnom. \u0160to \u0107e va\u0161a dijagram biti bli\u017ea idealu, ve\u0107a je verovatno\u0107a da pravilno planirate i da \u0107e va\u0161a aktivnost biti uspe\u0161na. Takva bliskost potvr\u0111uje da su va\u0161i planovi bliski iskustvu ljudske ekonomske delatnosti, koji se odra\u017eava u op\u0161teprihva\u0107enim empirijskim zakonitostima, poput Pareto principa.<\/p>\n

    Me\u0111utim, mo\u017ee se pretpostaviti da se ovde radi o funkcionisanju zrele ekonomske sistema orijentisanog na profitabilnost. Ako se, me\u0111utim, ne radi o maksimizaciji profita, ve\u0107, na primer, o modernizaciji kompanije ili o principijelnom pove\u0107anju njenog tr\u017ei\u0161nog udela, va\u0161a krivulja raspodele tro\u0161kova \u0107e odstupati od kruga. <\/p>\n

    O\u010digledno je da \u0107e, \u010dak i u slu\u010daju start-upa sa svojom specifi\u010dnom ekonomijom, Lorencova dijagrama koja odgovara najve\u0107oj verovatno\u0107i uspeha tako\u0111e odstupati od kruga. Mo\u017ee se izniti hipoteza da odstupanja krivulje raspodele tro\u0161kova unutar kruga odgovaraju pove\u0107anim rizicima, kao i smanjenoj adaptivnosti kompanije. Me\u0111utim, bez oslanjanja na velike statisti\u010dke skupove o start-upima (kako uspe\u0161nim, tako i neuspe\u0161nim), osnovani kvalifikovani prognoze \u0107e te\u0161ko biti mogu\u0107i. <\/p>\n

    Prema drugoj hipotezi, odstupanje krivulje raspodele tro\u0161kova od kruga ka spolja mo\u017ee biti signal kako prekomerne regulacije upravljanja, tako i signal nadolaze\u0107eg bankrota. Za proveru ove hipoteze tako\u0111er je potrebna odre\u0111ena referentna baza koja, poput start-upova, te\u0161ko da postoji u javnom pristupu.<\/p>\n

    Umjesto zaklju\u010dka<\/h4>\n

    \nPrve velike publikacije na ovu temu datiraju iz 1995. godine (Matohin, 1995). I malo poznatost ovih radova, s obzirom na njihovu univerzalnost i radikalno novu upotrebu \u0161iroko primenjivanih ekonomskih modela i alata, ostaje u nekom smislu zagonetka...
    \n
    Izvor: habr.com<\/a><\/p>","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"excerpt":{"rendered":"

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