SØK/ECON 535 Imperfect Competition and Strategic Interaction. In the absence of entry barriers firms cannot make supernormal profits.
|
|
- Bertina James
- 6 years ago
- Views:
Transcription
1 SØK/ECON 535 Imprfct Comptton and Stratgc Intracton ENTRY AND EXIT Lctur nots Introducton In th absnc of ntry barrrs frms cannot mak suprnormal profts. Barrrs to ntry govrnmnt rgulatons tchnologcal barrrs conoms of scal accss to (ffcnt) producton tchnologs, nputs tc. product dffrntaton, consumr swtchng costs, patnts stratgc barrrs Ban (1956) blockadd ntry dtrrd ntry accommodatd ntry Contstabl markts Potntal (as opposd to ral) comptton (Baumol t al, 1986) sunk costs ht and run stratgs Markt charactrsaton Consdr an xampl n whch frms produc on homognous products may b gnralsd to mult-product frms and dffrntatd products All frms hav accss to th sam tchnology 0 whn q = 0 C( q ) = > 0othrws
2 E Dmand functon: = ( p) Q Q. Markt confguraton: { q, q,..., q, p } 1 A markt confguraton s fasbl f Q p = q 1 ( ) = ( ) n pq C q 0, = 1,,..., n A markt confguraton s sustanabl f thr dos not xst whr p and q n p p and ( ) ( ) q Q p such that pq C q 0, ar th ntrants prc and quantty. A prfctly contstabl markt s markt for whch all markt confguratons ar fasbl and sustanabl. Exampl: natural monopoly C( q) = f + cq, q > 0 fgur (sustanabl markt confguraton whr th dmand curv cuts th avrag-cost curv) Th sustanabl markt confguraton s cost ffcnt and scond-bst (n th Ramsy sns). Gnralsaton to mult-product markts total costs ar mnmsd no frm arns postv proft no cross-subsdsaton Ramsy condtons ar fulflld f th numbr of frms xcds on Not: prc quals margnal cost Parto optmalty dstngush btwn fxd and sunk costs barrrs to ntry ar assocatd wth sunk costs Ht and run Consdr an xampl wth a sngl frm n th markt (natural monopoly).
3 A potntal ntrant can offr th markt a contract at tm 0 that spcfs quantty q prc p, and duraton τ. Th duraton of contract should b thought of as th tm t taks th stablshd frm to ract (.. chang ts prc offr). Lt β b th unt prc of captal at tm 0 α b th unt prc of captal at tm τ Th usr cost of captal µ may b dfnd mplctly by [ β α ] τ r rτ rt rτ 1 0 β α = µ dt µ = βr + Th stablshd frm may consquntly hold a prc that xcds ts own usr cost of captal ( β r ). L C q q and C( q, βr) q. p mplctly dfnd by L L L pq p C( Q p, µ ) = 0; that s, whr th dmand curv cuts th Fgur ( (,µ ) ( ) ( ) avrag-cost curv of th potntal frm). Concluson: th markt s prfctly contstabl f ntry s fr frms fac th sam prc of captal ( β ) frms hav accss to th sam tchnology (C, Q ) xt s costlss β α 1 = 0 rτ [ ] Stratgc ntry barrrs Crdbl ntry dtrrnc An ntry gam btwn a (potntal) ntrant () and an ncumbnt frm (): Stag 1: ntrant dcds whthr or not to ntr th markt; Stag : ncumbnt (havng obsrvd th ntrant s choc) dcds whthr or not to fght th ntrant; 3
4 ) ( Π 0, Π 0 ) payoffs: (Π, Π f ntry s mt by fght ; fght ; and (Π,0 Rsults m ) f thr s no ntry. th stratgy fght s crdbl only f Π Π 0 ; fght lads to dtrrnc only f Π 0 ; f ntry s not mt by f Π 0 and Π <, thn th stratgy combnaton {fght, stay out} s a Π 0 Nash qulbrum but not a Subgam Prfct Equlbrum. Not: t s th x post markt stuaton that s rlvant. Lmt-prcng classc thory : Ban, Sylos-Labn, Modglan gam-thortc crtqu: Spnc, Dxt asymmtrc nformaton and sgnallng: Mlgrom and Robrts A stratgc ntry gam W consdr a nw gam n whch th ncumbnt may tak actons x ant n ordr to dtr ntry; subsquntly a gam smlar to th on abov s playd (ths s summarsd n th rducd-form proft functons): Stag 1: ncumbnt dcds on lvl of ntry barrr b ( b = 0 corrsponds to no barrr); Stag : ntrant dcds whthr or not to ntr; payoffs: ( Π ( b), Π( b ) f ntry taks plac and Π m ( b ),0 othrws. Dfntons ) ( ) ntry s blockadd f Π ( 0) < 0; dtrrnc possbl f thr xsts b such that Π ( b ) < 0 dtrrnc proftabl f Πm( b ) Π ( 0), whr ( ) accommodaton f Π ( b ) < Π ( 0). Issus m Π b = 0 ; b must b rrvrsbl (cannot b changd upon ntry) what forms can b tak?; how dos dffrnt forms of b affct potntal ntrants compttv poston; asymmtrc nformaton; olgopoly. 4
5 Th Spnc-Dxt modl b = k s capacty. Homognous product, lnar dmand: p = 1 Q. Costs x ant (bfor nvstmnt): C( q, ) = +, k ck f q k x post (aftr nvstmnt): (, ) = 0, C q k q k. Aftr ntry has takn plac, frm choos quantty smultanously wth frm choosng both quantty and capacty. Th x post duopoly gam (gvn ntry and k ): clarly not proftabl for frm to hold xcss capacty, hnc q = k ; racton functons: = { mn, 1 } frm s proft: 1 q c 4 f. Not that dtrrnc rqurs q 1 c crdbl f 1 q k k and k = 1 q c f k c f and [ ] Th x post subgam f frm rmans a monopolst: [ ] { } max 1 q q q k ; q 1+ c 3 1 c f,.. c f. at qulbrum w must hav q = k snc margnal rvnu s gratr for a monopolst than for a duopolst and xcss capacty cannot b optmal. Consdr thn th frst-stag choc of frm and suppos frst that th choc nvolvs dtrrnc: { } max [ 1 k c] k f k 1 c f [ ] blockadd ntry f [ ] dtrrnc f [ ] 1 c 1 c f,or c 1 4 f ; { } k = max 1 c,1 c f ; 1 c < 1 c f, yldng profts f 1 c f f. Consdr nxt th frst-stag choc n th cas of accommodaton: xcss capacty clarly unproftabl; { } max 1 k ( ) k3 k c k f whr k( k) = [ k c ] 1 5
6 rsult s k = [ 1 c] and profts [ c] 1 8 f It follows that frm chooss dtrrnc rathr than accommodaton f f 1 c f > [ 1 c] 8, or c 1 4 f, and vc vrsa. Numrcal xampl: f = 0.01: ntry blockadd f c 0.6 ; dtrrnc crdbl f c 0.35 ; dtrrnc blockadd f c Concluson ntry dtrrnc by ovr-nvstmnt n capacty; no xcss capacty; stratgc ncntv for ovr-nvstmnt also n th cas of accommodaton (cf Stacklbrg); prc s low du to larg capacty, but no lmt prcng. Varatons Prc comptton at th post-ntry stag. Multpl ncumbnts dtrrnc s a publc good ; prc > margnal costs; Glbrt and Vvs (1986) show that scond ffct domnats and hnc dtrrnc s vn mor lkly wth many ncumbnts. Stratgc typs and typs of stratgs Consdr th cas n whch th ncumbnt accommodats ntry Proft functons ncumbnt: Π ( q, q, k ) ntrant: Π ( q, q, k ) Frst-ordr condton for ncumbnt s x ant dcson dπ Π dq dq π = = + dk q dq dk k 0 6
7 Th frst lmnt on th rght-hand sd consttuts th stratgc ffct, and sgn Π q = sgn Π q ) so (assumng ( ) ( ) sgn Π (.. ) = sgn dq sgn dq strat ff q dk dq Around th opn loop pont ( Π k =0 ) w hav Π k < 0. Consquntly, a ngatv (rsp. postv) stratgc ffct wll lad to ovrnvstmnt (rsp. undr-nvstmnt). Dfntons Π Frm s tough (rsp. soft) f sgn dq < 0 q dk (rsp. > 0 ); Stratgs ar stratgc substtuts (rsp. complmnts) f racton dq functons ar ncrasng (rsp. dcrasng), or sgn > 0 (rsp. < 0 ). dq Ex ant nvstmnt maks th ncumbnt frm Though Soft Stratgc complmnts Puppy Dog Fat Cat Stratgc substtuts Top Dog Lan and Hungry Lool Entry dtrrnc: only toughnss/softnss dtrmns stratgy (ffct on compttor s profts). Entry accommodaton: typ of stratgs mattrs also (ffct on own proft). Quantty comptton: Top Dog n both cass. Prc comptton: Top Dog f dtrrnc, Puppy Dog f accommodaton. Exampls: gnrc advrtsng and prc comptton: xcssv advrtsng whn accommodatng ntry (Fat Cat); brand advrtsng and quantty comptton: xcssv to dtr ntry (Top Dog); locaton (product dffrntaton): Th Prncpl of Dffrntaton (Puppy Dog); larnng-by-dong: xcssv producton to dtr ntry (Top Dog); 7
8 most-favourd-customr-claus wth prc comptton (Puppy Dog) Ext Industrs n dcln fght to survv. War of attrton Two symmtrc frms supplyng a homognous good. Producton cost pr unt of tm: C( q ) = f + Brtrand comptton: p1 = p = c Monopoly gross profts (not ncludng fxd costs): Π m m, Π > f At any pont n tm, ach frm may choos to lav th markt (rcvs 0 profts aftrwards cannot r-ntr). W ar lookng for a symmtrc qulbrum (n mxd stratgs). Lt x () t b th probablty that a frm lavs th markt at tm t. Thn th othr frm wll b ndffrnt btwn stayng n an lavng ovr th nxt prod of tm dt f cq m Π f fr f dt + xdt = 0 x = Π m r f. Concluson bfor xst happns, both frms run dfcts (ovr a prod wth stochastc lngth); xpctd profts ar zro (x post th rmanng frm arns postv profts); wlfar loss both bfor (du to duplcaton of fxd costs) and aftr xt (bcaus of monopoly prcng); n th a cas of prc colluson (mayb tact) th xt rat would b lowr, and hnc wlfar would b lowr also (du to both hghr prc and mor duplcaton x ant) Wll small frms xst bfor larg frms? If contracton s not an opton, larg frms wll lav frst (Ghmawat and Nalbuff, 1985). 8
9 If contracton s possbl, larg frms wll contract bfor xt taks plac (Whnston, 1986, and Ghmawat and Nalbuff, 1987). 9
Economics 600: August, 2007 Dynamic Part: Problem Set 5. Problems on Differential Equations and Continuous Time Optimization
THE UNIVERSITY OF MARYLAND COLLEGE PARK, MARYLAND Economcs 600: August, 007 Dynamc Part: Problm St 5 Problms on Dffrntal Equatons and Contnuous Tm Optmzaton Quston Solv th followng two dffrntal quatons.
More informationAggregate demand. Aggregate Demand and supply. Graphical Derivation of AD. Shifts of AD. Remarks ( )
Aggrgat dmand Aggrgat Dmand and suppl Th ntrscton of th IS- curvs shows th valus of and such that th mon markt clars and actual and plannd xpndturs ar qual for gvn valu of,, G and T. To s how th IS- curvs
More informationThe Hyperelastic material is examined in this section.
4. Hyprlastcty h Hyprlastc matral s xad n ths scton. 4..1 Consttutv Equatons h rat of chang of ntrnal nrgy W pr unt rfrnc volum s gvn by th strss powr, whch can b xprssd n a numbr of dffrnt ways (s 3.7.6):
More informationGrand Canonical Ensemble
Th nsmbl of systms mmrsd n a partcl-hat rsrvor at constant tmpratur T, prssur P, and chmcal potntal. Consdr an nsmbl of M dntcal systms (M =,, 3,...M).. Thy ar mutually sharng th total numbr of partcls
More informationOptimal Ordering Policy in a Two-Level Supply Chain with Budget Constraint
Optmal Ordrng Polcy n a Two-Lvl Supply Chan wth Budgt Constrant Rasoul aj Alrza aj Babak aj ABSTRACT Ths papr consdrs a two- lvl supply chan whch consst of a vndor and svral rtalrs. Unsatsfd dmands n rtalrs
More informationAdvanced Macroeconomics
Advancd Macroconomcs Chaptr 18 INFLATION, UNEMPLOYMENT AND AGGREGATE SUPPLY Thms of th chaptr Nomnal rgdts, xpctatonal rrors and mploymnt fluctuatons. Th short-run trad-off btwn nflaton and unmploymnt.
More informationLecture 14. Relic neutrinos Temperature at neutrino decoupling and today Effective degeneracy factor Neutrino mass limits Saha equation
Lctur Rlc nutrnos mpratur at nutrno dcoupln and today Effctv dnracy factor Nutrno mass lmts Saha quaton Physcal Cosmoloy Lnt 005 Rlc Nutrnos Nutrnos ar wakly ntractn partcls (lptons),,,,,,, typcal ractons
More informationAnalyzing Frequencies
Frquncy (# ndvduals) Frquncy (# ndvduals) /3/16 H o : No dffrnc n obsrvd sz frquncs and that prdctd by growth modl How would you analyz ths data? 15 Obsrvd Numbr 15 Expctd Numbr from growth modl 1 1 5
More informationEpistemic Foundations of Game Theory. Lecture 1
Royal Nthrlands cadmy of rts and Scncs (KNW) Mastr Class mstrdam, Fbruary 8th, 2007 Epstmc Foundatons of Gam Thory Lctur Gacomo onanno (http://www.con.ucdavs.du/faculty/bonanno/) QUESTION: What stratgs
More informationChapter 6 Student Lecture Notes 6-1
Chaptr 6 Studnt Lctur Nots 6-1 Chaptr Goals QM353: Busnss Statstcs Chaptr 6 Goodnss-of-Ft Tsts and Contngncy Analyss Aftr compltng ths chaptr, you should b abl to: Us th ch-squar goodnss-of-ft tst to dtrmn
More informationLucas Test is based on Euler s theorem which states that if n is any integer and a is coprime to n, then a φ(n) 1modn.
Modul 10 Addtonal Topcs 10.1 Lctur 1 Prambl: Dtrmnng whthr a gvn ntgr s prm or compost s known as prmalty tstng. Thr ar prmalty tsts whch mrly tll us whthr a gvn ntgr s prm or not, wthout gvng us th factors
More informationA test of collusive behavior based on incentives
A tst of collusv bhavor basd on ncntvs Rcardo Cabral Workng Papr January 28 Abstract hs papr proposs a novl colluson tst basd on th analyss of ncntvs facd by ach frm n a colludng coalton. In fact, onc
More informationFrom Structural Analysis to FEM. Dhiman Basu
From Structural Analyss to FEM Dhman Basu Acknowldgmnt Followng txt books wr consultd whl prparng ths lctur nots: Znkwcz, OC O.C. andtaylor Taylor, R.L. (000). Th FntElmnt Mthod, Vol. : Th Bass, Ffth dton,
More informationte Finance (4th Edition), July 2017.
Appndx Chaptr. Tchncal Background Gnral Mathmatcal and Statstcal Background Fndng a bas: 3 2 = 9 3 = 9 1 /2 x a = b x = b 1/a A powr of 1 / 2 s also quvalnt to th squar root opraton. Fndng an xponnt: 3
More informationCHAPTER 33: PARTICLE PHYSICS
Collg Physcs Studnt s Manual Chaptr 33 CHAPTER 33: PARTICLE PHYSICS 33. THE FOUR BASIC FORCES 4. (a) Fnd th rato of th strngths of th wak and lctromagntc forcs undr ordnary crcumstancs. (b) What dos that
More informationFakultät III Univ.-Prof. Dr. Jan Franke-Viebach
Unv.Prof. r. J. FrankVbach WS 067: Intrnatonal Economcs ( st xam prod) Unvrstät Sgn Fakultät III Unv.Prof. r. Jan FrankVbach Exam Intrnatonal Economcs Wntr Smstr 067 ( st Exam Prod) Avalabl tm: 60 mnuts
More informationSUNK COST EFFICIENCY WITH DISCRETE COMPETITORS
Sunk Cost Efficincy with Discrt Comptitors SUNK COST EFFICIENCY WITH DISCRETE COMPETITORS Linus Wilson, Univrsity of Louisiana at Lafaytt ABSTRACT Whn ntrants only diffr in thir xognous ntry costs, th
More informationDiploma Macro Paper 2
Diploma Macro Papr 2 Montary Macroconomics Lctur 6 Aggrgat supply and putting AD and AS togthr Mark Hays 1 Exognous: M, G, T, i*, π Goods markt KX and IS (Y, C, I) Mony markt (LM) (i, Y) Labour markt (P,
More informationFakultät III Wirtschaftswissenschaften Univ.-Prof. Dr. Jan Franke-Viebach
Unvrstät Sgn Fakultät III Wrtschaftswssnschaftn Unv.-rof. Dr. Jan Frank-Vbach Exam Intrnatonal Fnancal Markts Summr Smstr 206 (2 nd Exam rod) Avalabl tm: 45 mnuts Soluton For your attnton:. las do not
More informationCost Pass-Through with Network Externalities
Intrnatonal Journal of Busnss and Economcs, 011, Vol. 10, No. 3, 177-199 Cost Pass-Through wth Ntwor Extrnalts Anna Laura Barald * Dpartmnt of Europan tuds, cond Unvrsty of Napls, Italy Chrstan Rojas Dpartmnt
More informationΕρωτήσεις και ασκησεις Κεφ. 10 (για μόρια) ΠΑΡΑΔΟΣΗ 29/11/2016. (d)
Ερωτήσεις και ασκησεις Κεφ 0 (για μόρια ΠΑΡΑΔΟΣΗ 9//06 Th coffcnt A of th van r Waals ntracton s: (a A r r / ( r r ( (c a a a a A r r / ( r r ( a a a a A r r / ( r r a a a a A r r / ( r r 4 a a a a 0 Th
More informationA Note on Estimability in Linear Models
Intrnatonal Journal of Statstcs and Applcatons 2014, 4(4): 212-216 DOI: 10.5923/j.statstcs.20140404.06 A Not on Estmablty n Lnar Modls S. O. Adymo 1,*, F. N. Nwob 2 1 Dpartmnt of Mathmatcs and Statstcs,
More informationSeptember 27, Introduction to Ordinary Differential Equations. ME 501A Seminar in Engineering Analysis Page 1. Outline
Introucton to Ornar Dffrntal Equatons Sptmbr 7, 7 Introucton to Ornar Dffrntal Equatons Larr artto Mchancal Engnrng AB Smnar n Engnrng Analss Sptmbr 7, 7 Outln Rvw numrcal solutons Bascs of ffrntal quatons
More informationTax Evasion and Auditing in a Federal Economy *
Tax Evason and Audtng n a Fdral Economy * Svn Stöwhas Chrstan Traxlr Unvrsty of Munch Unvrsty of Munch Frst Draft Ths Vrson: Aprl 004 Plas do not quot or ct wthout prmsson of th Authors. Abstract Ths papr
More informationRandom Access Techniques: ALOHA (cont.)
Random Accss Tchniqus: ALOHA (cont.) 1 Exampl [ Aloha avoiding collision ] A pur ALOHA ntwork transmits a 200-bit fram on a shard channl Of 200 kbps at tim. What is th rquirmnt to mak this fram collision
More informationST 524 NCSU - Fall 2008 One way Analysis of variance Variances not homogeneous
ST 54 NCSU - Fall 008 On way Analyss of varanc Varancs not homognous On way Analyss of varanc Exampl (Yandll, 997) A plant scntst masurd th concntraton of a partcular vrus n plant sap usng ELISA (nzym-lnkd
More informationChapter 13 Aggregate Supply
Chaptr 13 Aggrgat Supply 0 1 Larning Objctivs thr modls of aggrgat supply in which output dpnds positivly on th pric lvl in th short run th short-run tradoff btwn inflation and unmploymnt known as th Phillips
More information4. Money cannot be neutral in the short-run the neutrality of money is exclusively a medium run phenomenon.
PART I TRUE/FALSE/UNCERTAIN (5 points ach) 1. Lik xpansionary montary policy, xpansionary fiscal policy rturns output in th mdium run to its natural lvl, and incrass prics. Thrfor, fiscal policy is also
More informationConsider a system of 2 simultaneous first order linear equations
Soluon of sysms of frs ordr lnar quaons onsdr a sysm of smulanous frs ordr lnar quaons a b c d I has h alrna mar-vcor rprsnaon a b c d Or, n shorhand A, f A s alrady known from con W know ha h abov sysm
More informationApproximately Maximizing Efficiency and Revenue in Polyhedral Environments
Approxmatly Maxmzng Effcncy and Rvnu n olyhdral Envronmnts Thành Nguyn Cntr for Appld Mathmatcs Cornll Unvrsty Ithaca, NY, USA. thanh@cs.cornll.du Éva Tardos Computr Scnc Dpartmnt Cornll Unvrsty Ithaca,
More informationHeisenberg Model. Sayed Mohammad Mahdi Sadrnezhaad. Supervisor: Prof. Abdollah Langari
snbrg Modl Sad Mohammad Mahd Sadrnhaad Survsor: Prof. bdollah Langar bstract: n ths rsarch w tr to calculat analtcall gnvalus and gnvctors of fnt chan wth ½-sn artcls snbrg modl. W drov gnfuctons for closd
More informationCapital Allocation and International Equilibrium with Pollution Permits *
Modrn conomy 3 87-99 http://dx.do.org/.436/m..36 Publshd Onln March (http://www.scrp.org/journal/m) Captal Allocaton Intrnatonal qulbrum wth Polluton Prmts * Prr-André Jouvt Glls Rotllon conomx Unvrsty
More information3.2. Cournot Model Cournot Model
Matlde Machado Assumptons: All frms produce an homogenous product The market prce s therefore the result of the total supply (same prce for all frms) Frms decde smultaneously how much to produce Quantty
More informationCOMPLEX NUMBER PAIRWISE COMPARISON AND COMPLEX NUMBER AHP
ISAHP 00, Bal, Indonsa, August -9, 00 COMPLEX NUMBER PAIRWISE COMPARISON AND COMPLEX NUMBER AHP Chkako MIYAKE, Kkch OHSAWA, Masahro KITO, and Masaak SHINOHARA Dpartmnt of Mathmatcal Informaton Engnrng
More informationChapter 14 Aggregate Supply and the Short-run Tradeoff Between Inflation and Unemployment
Chaptr 14 Aggrgat Supply and th Short-run Tradoff Btwn Inflation and Unmploymnt Modifid by Yun Wang Eco 3203 Intrmdiat Macroconomics Florida Intrnational Univrsity Summr 2017 2016 Worth Publishrs, all
More informationA Propagating Wave Packet Group Velocity Dispersion
Lctur 8 Phys 375 A Propagating Wav Packt Group Vlocity Disprsion Ovrviw and Motivation: In th last lctur w lookd at a localizd solution t) to th 1D fr-particl Schrödingr quation (SE) that corrsponds to
More informationChapter 13 GMM for Linear Factor Models in Discount Factor form. GMM on the pricing errors gives a crosssectional
Chaptr 13 GMM for Linar Factor Modls in Discount Factor form GMM on th pricing rrors givs a crosssctional rgrssion h cas of xcss rturns Hors rac sting for charactristic sting for pricd factors: lambdas
More informationInflation and Unemployment
C H A P T E R 13 Aggrgat Supply and th Short-run Tradoff Btwn Inflation and Unmploymnt MACROECONOMICS SIXTH EDITION N. GREGORY MANKIW PowrPoint Slids by Ron Cronovich 2008 Worth Publishrs, all rights rsrvd
More informationElectrochemical Equilibrium Electromotive Force. Relation between chemical and electric driving forces
C465/865, 26-3, Lctur 7, 2 th Sp., 26 lctrochmcal qulbrum lctromotv Forc Rlaton btwn chmcal and lctrc drvng forcs lctrochmcal systm at constant T and p: consdr G Consdr lctrochmcal racton (nvolvng transfr
More informationA Probabilistic Characterization of Simulation Model Uncertainties
A Proalstc Charactrzaton of Sulaton Modl Uncrtants Vctor Ontvros Mohaad Modarrs Cntr for Rsk and Rlalty Unvrsty of Maryland 1 Introducton Thr s uncrtanty n odl prdctons as wll as uncrtanty n xprnts Th
More information+ f. e f. Ch. 8 Inflation, Interest Rates & FX Rates. Purchasing Power Parity. Purchasing Power Parity
Ch. 8 Inlation, Intrst Rats & FX Rats Topics Purchasing Powr Parity Intrnational Fishr Ect Purchasing Powr Parity Purchasing Powr Parity (PPP: Th purchasing powr o a consumr will b similar whn purchasing
More informationSec 2.3 Modeling with First Order Equations
Sc.3 Modling with First Ordr Equations Mathmatical modls charactriz physical systms, oftn using diffrntial quations. Modl Construction: Translating physical situation into mathmatical trms. Clarly stat
More information:2;$-$(01*%<*=,-./-*=0;"%/;"-*
!"#$%'()%"*#%*+,-./-*+01.2(.*3+456789*!"#$%"'()'*+,-."/0.%+1'23"45'46'7.89:89'/' ;8-,"$4351415,8:+#9' Dr. Ptr T. Gallaghr Astrphyscs Rsarch Grup Trnty Cllg Dubln :2;$-$(01*%
More informationFunction Spaces. a x 3. (Letting x = 1 =)) a(0) + b + c (1) = 0. Row reducing the matrix. b 1. e 4 3. e 9. >: (x = 1 =)) a(0) + b + c (1) = 0
unction Spacs Prrquisit: Sction 4.7, Coordinatization n this sction, w apply th tchniqus of Chaptr 4 to vctor spacs whos lmnts ar functions. Th vctor spacs P n and P ar familiar xampls of such spacs. Othr
More informationProblem Set 6 Solutions
6.04/18.06J Mathmatics for Computr Scinc March 15, 005 Srini Dvadas and Eric Lhman Problm St 6 Solutions Du: Monday, March 8 at 9 PM in Room 3-044 Problm 1. Sammy th Shark is a financial srvic providr
More informationPhysics 256: Lecture 2. Physics
Physcs 56: Lctur Intro to Quantum Physcs Agnda for Today Complx Numbrs Intrfrnc of lght Intrfrnc Two slt ntrfrnc Dffracton Sngl slt dffracton Physcs 01: Lctur 1, Pg 1 Constructv Intrfrnc Ths wll occur
More informationANALYSIS: The mass rate balance for the one-inlet, one-exit control volume at steady state is
Problm 4.47 Fgur P4.47 provds stady stat opratng data for a pump drawng watr from a rsrvor and dlvrng t at a prssur of 3 bar to a storag tank prchd 5 m abov th rsrvor. Th powr nput to th pump s 0.5 kw.
More informationIntroduction to Arithmetic Geometry Fall 2013 Lecture #20 11/14/2013
18.782 Introduction to Arithmtic Gomtry Fall 2013 Lctur #20 11/14/2013 20.1 Dgr thorm for morphisms of curvs Lt us rstat th thorm givn at th nd of th last lctur, which w will now prov. Thorm 20.1. Lt φ:
More informationThe Open Economy in the Short Run
Economics 442 Mnzi D. Chinn Spring 208 Social Scincs 748 Univrsity of Wisconsin-Madison Th Opn Economy in th Short Run This st of nots outlins th IS-LM modl of th opn conomy. First, it covrs an accounting
More information10/7/14. Mixture Models. Comp 135 Introduction to Machine Learning and Data Mining. Maximum likelihood estimation. Mixture of Normals in 1D
Comp 35 Introducton to Machn Larnng and Data Mnng Fall 204 rofssor: Ron Khardon Mxtur Modls Motvatd by soft k-mans w dvlopd a gnratv modl for clustrng. Assum thr ar k clustrs Clustrs ar not rqurd to hav
More informationReview - Probabilistic Classification
Mmoral Unvrsty of wfoundland Pattrn Rcognton Lctur 8 May 5, 6 http://www.ngr.mun.ca/~charlsr Offc Hours: Tusdays Thursdays 8:3-9:3 PM E- (untl furthr notc) Gvn lablld sampls { ɛc,,,..., } {. Estmat Rvw
More informationPrice competition with capacity constraints. Consumers are rationed at the low-price firm. But who are the rationed ones?
Prce competton wth capacty constrants Consumers are ratoned at the low-prce frm. But who are the ratoned ones? As before: two frms; homogeneous goods. Effcent ratonng If p < p and q < D(p ), then the resdual
More informationCournot Equilibrium with N firms
Recap Last class (September 8, Thursday) Examples of games wth contnuous acton sets Tragedy of the commons Duopoly models: ournot o class on Sept. 13 due to areer Far Today (September 15, Thursday) Duopoly
More informationdr Bartłomiej Rokicki Chair of Macroeconomics and International Trade Theory Faculty of Economic Sciences, University of Warsaw
dr Bartłomij Rokicki Chair of Macroconomics and Intrnational Trad Thory Faculty of Economic Scincs, Univrsity of Warsaw dr Bartłomij Rokicki Opn Economy Macroconomics Small opn conomy. Main assumptions
More informationOutlier-tolerant parameter estimation
Outlr-tolrant paramtr stmaton Baysan thods n physcs statstcs machn larnng and sgnal procssng (SS 003 Frdrch Fraundorfr fraunfr@cg.tu-graz.ac.at Computr Graphcs and Vson Graz Unvrsty of Tchnology Outln
More informationCOHORT MBA. Exponential function. MATH review (part2) by Lucian Mitroiu. The LOG and EXP functions. Properties: e e. lim.
MTH rviw part b Lucian Mitroiu Th LOG and EXP functions Th ponntial function p : R, dfind as Proprtis: lim > lim p Eponntial function Y 8 6 - -8-6 - - X Th natural logarithm function ln in US- log: function
More informationA NEW GENERALISATION OF SAM-SOLAI S MULTIVARIATE ADDITIVE GAMMA DISTRIBUTION*
A NEW GENERALISATION OF SAM-SOLAI S MULTIVARIATE ADDITIVE GAMMA DISTRIBUTION* Dr. G.S. Davd Sam Jayakumar, Assstant Profssor, Jamal Insttut of Managmnt, Jamal Mohamd Collg, Truchraall 620 020, South Inda,
More information22/ Breakdown of the Born-Oppenheimer approximation. Selection rules for rotational-vibrational transitions. P, R branches.
Subjct Chmistry Papr No and Titl Modul No and Titl Modul Tag 8/ Physical Spctroscopy / Brakdown of th Born-Oppnhimr approximation. Slction ruls for rotational-vibrational transitions. P, R branchs. CHE_P8_M
More informationComputing and Communications -- Network Coding
89 90 98 00 Computing and Communications -- Ntwork Coding Dr. Zhiyong Chn Institut of Wirlss Communications Tchnology Shanghai Jiao Tong Univrsity China Lctur 5- Nov. 05 0 Classical Information Thory Sourc
More informationInter-Technology versus Intra-Technology Competition in Network Markets by Tobias Langenberg *
EURAS Yarbook of Standardization, Vol 5 Homo Oconomicus XXI1(1) (ACCEDO, Munich 005) Intr-Tchnology vrsus Intra-Tchnology Comptition in Ntwork Markts by Tobias Langnbrg * Abstract: Th modl analyzs th comptition
More informationLecture 3: Phasor notation, Transfer Functions. Context
EECS 5 Fall 4, ctur 3 ctur 3: Phasor notaton, Transfr Functons EECS 5 Fall 3, ctur 3 Contxt In th last lctur, w dscussd: how to convrt a lnar crcut nto a st of dffrntal quatons, How to convrt th st of
More informationSupplementary Materials
6 Supplmntary Matrials APPENDIX A PHYSICAL INTERPRETATION OF FUEL-RATE-SPEED FUNCTION A truck running on a road with grad/slop θ positiv if moving up and ngativ if moving down facs thr rsistancs: arodynamic
More information8. Linear Contracts under Risk Neutrality
8. Lnr Contrcts undr Rsk Nutrlty Lnr contrcts r th smplst form of contrcts nd thy r vry populr n pplctons. Thy offr smpl ncntv mchnsm. Exmpls of lnr contrcts r mny: contrctul jont vnturs, quty jont vnturs,
More informationEconomics 201b Spring 2010 Solutions to Problem Set 3 John Zhu
Economics 20b Spring 200 Solutions to Problm St 3 John Zhu. Not in th 200 vrsion of Profssor Andrson s ctur 4 Nots, th charactrization of th firm in a Robinson Cruso conomy is that it maximizs profit ovr
More informationTwo Stage Procurement Processes With Competitive Suppliers and Uncertain Supplier Quality
Unvrsty of Nbraska - Lncoln DgtalCommons@Unvrsty of Nbraska - Lncoln Supply Chan Managmnt and Analytcs Publcatons Busnss, Collg of 2014 Two Stag Procurmnt Procsss Wth Compttv Supplrs and Uncrtan Supplr
More information8-node quadrilateral element. Numerical integration
Fnt Elmnt Mthod lctur nots _nod quadrlatral lmnt Pag of 0 -nod quadrlatral lmnt. Numrcal ntgraton h tchnqu usd for th formulaton of th lnar trangl can b formall tndd to construct quadrlatral lmnts as wll
More informationCh. 24 Molecular Reaction Dynamics 1. Collision Theory
Ch. 4 Molcular Raction Dynamics 1. Collision Thory Lctur 16. Diffusion-Controlld Raction 3. Th Matrial Balanc Equation 4. Transition Stat Thory: Th Eyring Equation 5. Transition Stat Thory: Thrmodynamic
More informationAlpha and beta decay equation practice
Alpha and bta dcay quation practic Introduction Alpha and bta particls may b rprsntd in quations in svral diffrnt ways. Diffrnt xam boards hav thir own prfrnc. For xampl: Alpha Bta α β alpha bta Dspit
More informationEcon107 Applied Econometrics Topic 10: Dummy Dependent Variable (Studenmund, Chapter 13)
Pag- Econ7 Appld Economtrcs Topc : Dummy Dpndnt Varabl (Studnmund, Chaptr 3) I. Th Lnar Probablty Modl Suppos w hav a cross scton of 8-24 yar-olds. W spcfy a smpl 2-varabl rgrsson modl. Th probablty of
More informationPolytropic Process. A polytropic process is a quasiequilibrium process described by
Polytropc Procss A polytropc procss s a quasqulbrum procss dscrbd by pv n = constant (Eq. 3.5 Th xponnt, n, may tak on any valu from to dpndng on th partcular procss. For any gas (or lqud, whn n = 0, th
More informationON THE COMPLEXITY OF K-STEP AND K-HOP DOMINATING SETS IN GRAPHS
MATEMATICA MONTISNIRI Vol XL (2017) MATEMATICS ON TE COMPLEXITY OF K-STEP AN K-OP OMINATIN SETS IN RAPS M FARAI JALALVAN AN N JAFARI RA partmnt of Mathmatcs Shahrood Unrsty of Tchnology Shahrood Iran Emals:
More informationWhat are those βs anyway? Understanding Design Matrix & Odds ratios
Ral paramtr stimat WILD 750 - Wildlif Population Analysis of 6 What ar thos βs anyway? Undrsting Dsign Matrix & Odds ratios Rfrncs Hosmr D.W.. Lmshow. 000. Applid logistic rgrssion. John Wily & ons Inc.
More informationThe Interaction and Sequencing of Policy Reforms*
Fral Rsrv Bank of Mnnapols Rsarch Dpartmnt Staff Rport 521 May 2016 Th Intracton an Squncng of Polcy Rforms* Jos Asturas School of Forgn Srvc n Qatar, Gorgtown Unvrsy Swon Hur Unvrsy of Ptsburgh Tmothy
More informationA duopoly of transportation network companies and traditional radio-taxi dispatch service agencies
EJTIR Issu 8(), 08 pp. 96- ISSN: 567-74 http://tlo.tbm.tudlft.nl/jtr A duopoly of transportaton ntwork compans and tradtonal rado-tax dspatch srvc agncs Thorstn Hlkr Insttut of Transport Economcs, Unvrsty
More informationEECE 301 Signals & Systems Prof. Mark Fowler
EECE 301 Signals & Systms Prof. Mark Fowlr ot St #21 D-T Signals: Rlation btwn DFT, DTFT, & CTFT 1/16 W can us th DFT to implmnt numrical FT procssing This nabls us to numrically analyz a signal to find
More informationThe Ramsey Model. Reading: Firms. Households. Behavior of Households and Firms. Romer, Chapter 2-A;
Th Ramsy Modl Rading: Romr, Chaptr 2-A; Dvlopd by Ramsy (1928), latr dvlopd furthr by Cass (1965) and Koopmans (1965). Similar to th Solow modl: labor and knowldg grow at xognous rats. Important diffrnc:
More informationSummary: Solving a Homogeneous System of Two Linear First Order Equations in Two Unknowns
Summary: Solvng a Homognous Sysm of Two Lnar Frs Ordr Equaons n Two Unknowns Gvn: A Frs fnd h wo gnvalus, r, and hr rspcv corrspondng gnvcors, k, of h coffcn mar A Dpndng on h gnvalus and gnvcors, h gnral
More informationElements of Statistical Thermodynamics
24 Elmnts of Statistical Thrmodynamics Statistical thrmodynamics is a branch of knowldg that has its own postulats and tchniqus. W do not attmpt to giv hr vn an introduction to th fild. In this chaptr,
More informationConstruction of asymmetric orthogonal arrays of strength three via a replacement method
isid/ms/26/2 Fbruary, 26 http://www.isid.ac.in/ statmath/indx.php?modul=prprint Construction of asymmtric orthogonal arrays of strngth thr via a rplacmnt mthod Tian-fang Zhang, Qiaoling Dng and Alok Dy
More informationWeek 3: Connected Subgraphs
Wk 3: Connctd Subgraphs Sptmbr 19, 2016 1 Connctd Graphs Path, Distanc: A path from a vrtx x to a vrtx y in a graph G is rfrrd to an xy-path. Lt X, Y V (G). An (X, Y )-path is an xy-path with x X and y
More informationNetwork Congestion Games
Ntwork Congstion Gams Assistant Profssor Tas A&M Univrsity Collg Station, TX TX Dallas Collg Station Austin Houston Bst rout dpnds on othrs Ntwork Congstion Gams Travl tim incrass with congstion Highway
More informationThe Fourier Transform
/9/ Th ourr Transform Jan Baptst Josph ourr 768-83 Effcnt Data Rprsntaton Data can b rprsntd n many ways. Advantag usng an approprat rprsntaton. Eampls: osy ponts along a ln Color spac rd/grn/blu v.s.
More informationThe Matrix Exponential
Th Matrix Exponntial (with xrciss) by D. Klain Vrsion 207.0.05 Corrctions and commnts ar wlcom. Th Matrix Exponntial For ach n n complx matrix A, dfin th xponntial of A to b th matrix A A k I + A + k!
More informationRelate p and T at equilibrium between two phases. An open system where a new phase may form or a new component can be added
4.3, 4.4 Phas Equlbrum Dtrmn th slops of th f lns Rlat p and at qulbrum btwn two phass ts consdr th Gbbs functon dg η + V Appls to a homognous systm An opn systm whr a nw phas may form or a nw componnt
More informationFolding of Regular CW-Complexes
Ald Mathmatcal Scncs, Vol. 6,, no. 83, 437-446 Foldng of Rgular CW-Comlxs E. M. El-Kholy and S N. Daoud,3. Dartmnt of Mathmatcs, Faculty of Scnc Tanta Unvrsty,Tanta,Egyt. Dartmnt of Mathmatcs, Faculty
More informationorbiting electron turns out to be wrong even though it Unfortunately, the classical visualization of the
Lctur 22-1 Byond Bohr Modl Unfortunatly, th classical visualization of th orbiting lctron turns out to b wrong vn though it still givs us a simpl way to think of th atom. Quantum Mchanics is ndd to truly
More informationIn this lecture... Subsonic and supersonic nozzles Working of these nozzles Performance parameters for nozzles
Lct-30 Lct-30 In this lctur... Subsonic and suprsonic nozzls Working of ths nozzls rformanc paramtrs for nozzls rof. Bhaskar Roy, rof. A M radp, Dpartmnt of Arospac, II Bombay Lct-30 Variation of fluid
More informationHardy-Littlewood Conjecture and Exceptional real Zero. JinHua Fei. ChangLing Company of Electronic Technology Baoji Shannxi P.R.
Hardy-Littlwood Conjctur and Excptional ral Zro JinHua Fi ChangLing Company of Elctronic Tchnology Baoji Shannxi P.R.China E-mail: fijinhuayoujian@msn.com Abstract. In this papr, w assum that Hardy-Littlwood
More informationBasic Electrical Engineering for Welding [ ] --- Introduction ---
Basc Elctrcal Engnrng for Wldng [] --- Introducton --- akayosh OHJI Profssor Ertus, Osaka Unrsty Dr. of Engnrng VIUAL WELD CO.,LD t-ohj@alc.co.jp OK 15 Ex. Basc A.C. crcut h fgurs n A-group show thr typcal
More information[ ] 1+ lim G( s) 1+ s + s G s s G s Kacc SYSTEM PERFORMANCE. Since. Lecture 10: Steady-state Errors. Steady-state Errors. Then
SYSTEM PERFORMANCE Lctur 0: Stady-tat Error Stady-tat Error Lctur 0: Stady-tat Error Dr.alyana Vluvolu Stady-tat rror can b found by applying th final valu thorm and i givn by lim ( t) lim E ( ) t 0 providd
More informationcycle that does not cross any edges (including its own), then it has at least
W prov th following thorm: Thorm If a K n is drawn in th plan in such a way that it has a hamiltonian cycl that dos not cross any dgs (including its own, thn it has at last n ( 4 48 π + O(n crossings Th
More information3.4 Properties of the Stress Tensor
cto.4.4 Proprts of th trss sor.4. trss rasformato Lt th compots of th Cauchy strss tsor a coordat systm wth bas vctors b. h compots a scod coordat systm wth bas vctors j,, ar gv by th tsor trasformato
More informationThe Matrix Exponential
Th Matrix Exponntial (with xrciss) by Dan Klain Vrsion 28928 Corrctions and commnts ar wlcom Th Matrix Exponntial For ach n n complx matrix A, dfin th xponntial of A to b th matrix () A A k I + A + k!
More informationECE602 Exam 1 April 5, You must show ALL of your work for full credit.
ECE62 Exam April 5, 27 Nam: Solution Scor: / This xam is closd-book. You must show ALL of your work for full crdit. Plas rad th qustions carfully. Plas chck your answrs carfully. Calculators may NOT b
More informationEAcos θ, where θ is the angle between the electric field and
8.4. Modl: Th lctric flux flows out of a closd surfac around a rgion of spac containing a nt positiv charg and into a closd surfac surrounding a nt ngativ charg. Visualiz: Plas rfr to Figur EX8.4. Lt A
More informationSoft k-means Clustering. Comp 135 Machine Learning Computer Science Tufts University. Mixture Models. Mixture of Normals in 1D
Comp 35 Machn Larnng Computr Scnc Tufts Unvrsty Fall 207 Ron Khardon Th EM Algorthm Mxtur Modls Sm-Suprvsd Larnng Soft k-mans Clustrng ck k clustr cntrs : Assocat xampls wth cntrs p,j ~~ smlarty b/w cntr
More informationBayesian Decision Theory
Baysian Dcision Thory Baysian Dcision Thory Know probabiity distribution of th catgoris Amost nvr th cas in ra if! Nvrthss usfu sinc othr cass can b rducd to this on aftr som work Do not vn nd training
More informationMoral considerations in trading pollution permits. Johan Eyckmans and Snorre Kverndokk
Moral consdratons n tradng olluton rmts Johan yckmans and Snorr Kvrndokk HUB RSARCH PAPR 2008/12. FBRUARI 2008 Frst draft. Fbruary 2008 Moral consdratons n tradng olluton rmts 1 by Johan yckmans uroan
More informationEEO 401 Digital Signal Processing Prof. Mark Fowler
EEO 401 Digital Signal Procssing Prof. Mark Fowlr ot St #18 Introduction to DFT (via th DTFT) Rading Assignmnt: Sct. 7.1 of Proakis & Manolakis 1/24 Discrt Fourir Transform (DFT) W v sn that th DTFT is
More informationUNIT 8 TWO-WAY ANOVA WITH m OBSERVATIONS PER CELL
UNIT 8 TWO-WAY ANOVA WITH OBSERVATIONS PER CELL Two-Way Anova wth Obsrvatons Pr Cll Structur 81 Introducton Obctvs 8 ANOVA Modl for Two-way Classfd Data wth Obsrvatons r Cll 83 Basc Assutons 84 Estaton
More information