Key ideas: trading financial assets, complete security markets, incomplete security markets, implicit state claims prices. Arrow-Debreu equilibrium 3

Size: px
Start display at page:

Download "Key ideas: trading financial assets, complete security markets, incomplete security markets, implicit state claims prices. Arrow-Debreu equilibrium 3"

Transcription

1 Eentil Microeconomic -- EQUILBRIUM IN FINANCIAL MARKETS 8.2 SECURITY MARKET EQUILIBRIUM Key ide: trding finncil et, complete ecurity mrket, incomplete ecurity mrket, implicit tte clim price Arrow-Debreu equilibrium 3 Security mrket equilibrium 4 Equivlence wit pnning 6 Multiple Period, Stte, Commoditie nd Production 3 Replcing A-D Stte-Contingent Mrket by Trde in Security Mrket 7 Incomplete mrket 22 Jon Riley November 5, 202

2 Eentil Microeconomic -2- In te previou ection we exmined equilibrium wen conumer trde directly in tte- contingent mrket. Here we exmine equilibrium wen conumer trde finncil et. Initilly we conider one-good excnge economy in wic tere re S tte. Conumer H = {,..., H} tte-contingent endowment ω = ( ω,..., ω S ). Let x = ( x,..., x S ) be i conumption vector. We ume tt conumer trictly increing expected utility function S U ( x ) = π u ( x ). = Jon Riley November 5, 202

3 Eentil Microeconomic -3- Arrow-Debreu equilibrium We introduce mrket for ec of te S commoditie. Te lloction { x X } H i n A-D equilibrium lloction if for ome p >> 0, (i) p x p ω conumption lloction re in budget et (ii) U ( xˆ ) > U ( x ) p xˆ > p x no trictly preferred lloction i in conumer budget et (iii) H H F f x = ω + = = f = y mrket cler. Jon Riley November 5, 202

4 Eentil Microeconomic -4- Security mrket (SM) equilibrium Suppoe tt individul do not trde tte-contingent commoditie but inted trde finncil et. Aet, A = {,..., A} price P nd tte-contingent dividend d = ( d,..., ds ). Note: Te AD equilibrium i equivlent to n SM equilibrium in wic tere re S ecuritie. Aet, wit price p dividend of p in tte nd dividend of zero in every oter tte. Conumer cn trnfer welt cro tte by buying nd elling et. Aet olding: Conumer portfolio of et olding ξ = ( ξ,..., ξ A ). Conumer begin wit no finncil et o te mrket vlue of ti portfolio cnnot be poitive. Given our umption tt utility i trictly increing te mrket vlue of te portfolio cnnot be negtive. Ten te portfolio contrint i A P ξ = 0. Given uc portfolio, conumer finl conumption of x = ω + d ξ. A Jon Riley November 5, 202

5 Eentil Microeconomic -5- Becue we ve plced no retriction on te ign of te dividend, n et price my be poitive or negtive. Definition: SM equilibrium S S An lloction { x X, ξ } were H x = ω + dξ i (Wlrin) ecurity mrket equilibrium lloction if for ome P= ( P,..., P A ), A (i) P ξ = 0 A =,..., H conumption lloction re in budget et (ii) ( ˆ ) ( ) ˆ U ω + d ξ > U x P ξ > 0 A no trictly preferred lloction i in conumer budget et (iii) x = ω, nd ξ = 0. H H H mrket cler. Jon Riley November 5, 202

6 Eentil Microeconomic -6- Spnning Suppoe firt tt tere re t let mny et tte nd tt te dividend vector { d } pn A S. Witout lo of generlity, we my relbel te et o tt te dividend vector of te firt S et re linerly independent. Ten, ny lloction in S cn be expreed liner combintion S ξ d of te firt S et. It follow tt for every tere i ome portfolio = ξ = 0, > ) uc tt ξ (wit x ω = A d ξ. (8.2-) Jon Riley November 5, 202

7 Eentil Microeconomic -7- Note: Portfolio ξ tifie x ω d ξ. (8.2-2) = A Propoition 8.2-: An A-D equilibrium i SM equilibrium if te et dividend pn Proof: Step : Portfolio contrint tified S Let { x X } H be n A-D equilibrium wit equilibrium price p. It follow from (8.2-) tt p x p ω = p d ξ. A Define P = p d, =,..., A. Ten p x p ω = Pξ. A An A-D lloction mut lie in individul budget et. Terefore Pξ = p x p ω 0. Tu te portfolio contrint re tified. A Jon Riley November 5, 202

8 Eentil Microeconomic -8- Note: Portfolio ξ tifie x ω d ξ. (8.2-3) Step 2: Aet mrket cler Summing (8.2-) over, = A x ω = d ξ = d ξ = D ξ H H A A H H were D i mtrix of te S column vector of dividend. In te A-D equilibrium mrket cler, tu D H ξ = x ω = 0. H Becue te column of D re linerly independent it follow tt D i invertible nd o ξ = 0. Tu et mrket cler. H Jon Riley November 5, 202

9 Eentil Microeconomic -9- Step 3: Any trictly preferred lloction i not feible. Finlly let xˆ = d ˆ ξ + ω be trictly preferred to A x. Becue x i A-D equilibrium wit ttecontingent price vector p, it follow tt xˆ mut cot trictly more. Tt i ˆ ˆ ˆ p x p ω = p d ξ = Pξ > 0. A A It follow tt ny trictly preferred portfolio violte te portfolio budget contrint. Ten te lloction { x, ξ } H = i n SM equilibrium lloction wit et price P = p d, =,..., A. Q.E.D. Jon Riley November 5, 202

10 Eentil Microeconomic -0- We now prove te convere. Te proof i imilr. We begin wit SM equilibrium in wic te dividend of te A et pn te complete tte pce S. Given completene we cn define implicit price for ec tte. We ten ow tt ti implicit price vector i n A-D equilibrium. Jon Riley November 5, 202

11 Eentil Microeconomic -- Propoition 8.2-2: An SM equilibrium i n A-D equilibrium if te et dividend pn Proof: Let { x X S, ξ S } H = were x A ω dξ = S = + be n SM equilibrium lloction nd let P= ( P,..., P A ) be te equilibrium vector of ecurity price. Relbel te et o tt te dividend vector of te firt S et re linerly independent. A in te proof of te previou propoition define D to be te mtrix of column of dividend vector. Becue tee column re independent, tere exit unique tte-contingent p uc tt p D = P. (8.2-4) Alo, for ec, tere exit ome portfolio ξ = ( ξ,..., ξ ) uc tt Dξ =. Ti portfolio mut S ve trictly poitive price, oterwie conumption in tte i unbounded. Tu P ξ > 0, =,..., S. Rewriting tee reult in mtrix form, D[ ξ,..., ξ S ] = I nd P [ ξ,..., ξ S ] > 0. Subtituting from (8.2-2), p D[ ξ,..., ξ ] = p I = p >> 0. S Tu te vector p i trictly poitive. Jon Riley November 5, 202

12 Eentil Microeconomic -2- Te ret of te proof prllel tt of te previou propoition. Suppoe tt individul trictly prefer x ˆ over te SM equilibrium lloction ome portfolio ˆ ξ uc tt x. Becue te et mrket re complete tere i xˆ ω =D ˆ ξ. From te definition of n SM equilibrium, ti cnnot tify te individul portfolio contrint. Terefore ˆ P ξ > 0 nd o ( ) ˆ ˆ p x ω = p D ξ = P ξ > 0. Tu no trictly preferred conumption bundle i feible if te price vector i p. It follow tt te lloction i n A-D equilibrium t te price vector p > 0. Q.E.D. Jon Riley November 5, 202

13 Eentil Microeconomic -3- Multiple Period, Stte, Commoditie nd Production Tu fr we ve focued on trding in ecurity mrket wit ingle commodity. We now conider n economy wit production nd L commoditie delivered t ec dte nd in ec tte. To implify f te expoition we ume tt tere re two dte, dte 0 nd dte. Let y 0 be te dte 0 production vector of firm f nd let f y be te dte production vector in tte of firm f. We write te production f f f f vector of firm f y = ( y0, y,..., y S ). Firm f production et Y f. Tt i, f f y Y. Conumer conumption vector x nd von Neumnn expected utility function ( S+ ) L S = π 0 = U ( x ) u ( x, x ). Finlly let f k be conumer reolding of firm f nd let ω be conumer endowment vector. A-D equilibrium Te A-D equilibrium of ti economy i n lloction { x } H,{ f } F = y f = nd price vector p > 0 tifying mrket clering nd individul rtionlity given ec conumer budget contrint In tt equilibrium, mrket for ll ( S + ) Lcommoditie re open t dte 0. Tu conumer cn mke ll of teir trde in te firt period. Jon Riley November 5, 202

14 Eentil Microeconomic -4- Te condition for n A-D equilibrium re (i) p yˆ > p y yˆ Y f f f f (ii) F f f p x = p ω + θ p y f = (iii) u ( xˆ ) > u ( x ) p xˆ > p x. A-D equilibrium wit pot mrket reopening in period 2 Tere i no need for ny mrket to reopen in lter period. But uppoe tt tte occur nd te L commodity mrket unexpectedly reopen. We et xˆ define become = x nd yˆ f = y f for ll, f nd ll, nd f Y to be te feible production pln in tte. Condition (i) (iii) for n A-D equilibrium (i) p yˆ > p y yˆ Y f f f f (ii) F f f = ω + θ f = p x p p y (iii) u ( xˆ ) > u ( x ) p xˆ > p x. Jon Riley November 5, 202

15 Eentil Microeconomic -5- Alo H H F x = ω + y = = f =. Condition (iii) revel tt if te tte pot price vector p i equl to te dte 0 contingent price vector p, no conumer will wi to trde gin t dte. Tu te future pot mrket ll cler in period. Of coure ny multiple of ti price vector i WE well. Ten for ny number r > te price vector p = ( + r ) p i WE future pot price vector. Equivlently p p =. + r Tu te A-D tte pot price i te preent vlue of te future pot price were te interet rte r i tte dependent. Becue it will be ueful lter, note tt becue p dollr in tte ve dte 0 vlue (i.e. preent vlue) of p p =, one dollr in tte preent vlue of + r + r. Next uppoe tt individul nticipte tt mrket will reopen. Now conumer cn purce unit of commodity l in tte in te A-D mrket t dte 0 or plce p l dollr in bnk, ern interet Jon Riley November 5, 202

16 Eentil Microeconomic -6- r nd tu ve p ( + r ) = p in tte. Tu tere i no rbitrge opportunity nd conumer re l l indifferent to weter tey trde in te A-D mrket or trde firt wit finncil intermediry nd ten in te future pot mrket. Jon Riley November 5, 202

17 Eentil Microeconomic -7- Replcing A-D Stte-Contingent Mrket by Trde in Security Mrket If it eem fr-fetced to imgine being ble to trde in tte-contingent mrket in ll commoditie, you re rigt! We now rgue tt tere i imple wy to economize on te number of mrket. Inted of trding in every commodity, ll tt i necery i for n individul to be ble to move welt cro time nd tte nd ten trde in future pot mrket. Let W be te extr welt in tte tt individul need to finnce i purce, tt i F f f = ω θ f = W p x p p y, =,..., S. (8.2-5) Summing over te conumer H H H F f f W = ( p x p ω ) θ p y = = = f = H H F f f ( p x p ω ) θ p y = = f = = H F f p x ω y = f =, becue reolding mut um to = ( ) Jon Riley November 5, 202

18 Eentil Microeconomic -8- = 0, becue upply equl demnd in n A-D equilibrium. Ti mut be true becue tere cn be no ggregte trnfer of welt in or out of tte, even toug individul cn ift welt cro time nd tte. Similrly let W 0 be te dte 0 welt needed to finnce tee trde; tt i F f f 0 = 0 ω0 + θ f = W p p y p x. (8.2-6) Te A-D lifetime budget contrint i S S F S f f f = 0 ω0 + ω + θ = = f = = p x p x p p ( p y p y ) Tt i, te vlue of conumption equl te vlue of te endowment plu te vlue of te profit in ec period (ditributed dividend). Ti budget contrint cn be written follow. S F F f f f f p x ω k y p0 x0 ω0 θ y0 = f = f = ( ) + ( ) = 0 k p y f f Note tt we re uming tt reolder firt-period dividend of 0 0 i reponible for finncing i re of te cot of te firm dte 0 input. from firm f. Alterntively, if ti i negtive, reolder Jon Riley November 5, 202

19 Eentil Microeconomic -9- Subtituting from (8.2-3) nd (8.2-4), S = W = W 0 Tu inted of trding in te tte clim mrket, individul imply need ome wy of trnferring welt cro time nd tte. Jon Riley November 5, 202

20 Eentil Microeconomic -20- Stock Mrket Equilibrium Tu fr we ve not conidered trding in tock mrket. If te dte 0 vlue of te dte dividend of te F firm pn S, ten te previou rgument pply directly. By trding in te tock mrket nd commodity mrket, te tock mrket equilibrium replicte te A-D equilibrium. Te dte 0 mrket vlue of te firm i imply it dte 0 vlue in te A-D equilibrium, tt i P f f = p y. Jon Riley November 5, 202

21 Eentil Microeconomic -2- Perfect Foreigt At firt blu it pper tt we ve eliminted ot of mrket t no cot. Rter tn trde t dte 0 in ll future contingencie, it i equivlent to defer mny trde to lter period by moving welt cro dte vi trde in ecuritie mrket. Becue mrket re not cotle to operte, it i tempting to conclude tt trding in ecurity mrket dominte trding in tte- contingent mrket. However, tere i one very importnt qulifiction. In te A-D equilibrium, conumer nd firm oberve te price of every contingent commodity. However, in te SM equilibrium, individul trding t dte 0 do not oberve te price of commoditie in te future pot mrket. Tu wt we ve relly etblied i tt te SM equilibrium replicte te A-D equilibrium if every conumer correctly forect tee future pot price. Ti i obviouly very trong umption. However, it i not prepoterou it my eem. For mny commoditie ggregte ock tend to be igly correlted cro mrket. Tu reltive price cnge re mll. For commoditie woe reltive price do vry widely cro tte, tere i n incentive for finncil intermedirie to crete new finncil intrument. Te more preciely ti finncil engineering i focued on prticulr commodity nd tte, te more likely it i tt te tte clim price cn be inferred from te price of te finncil et. Jon Riley November 5, 202

22 Eentil Microeconomic -22- Incomplete Mrket Suppoe tt te dividend in ecurity mrket equilibrium do not pn S but inted ome ubpce of dimenion J. We firt conider pecil ce in wic te A-D equilibrium lloction i till cieved. We ten look t n exmple in wic te SM equilibrium lloction differ. Suppoe tt conumer n initil portfolio ξ of te A et. Aet (rel) dividend of d in tte. Ec conumer te me omotetic expected utility function S U( x) = π ux ( ), =,..., H. = Given te omoteticity umption te complete mrket equilibrium i te no-trde equilibrium of ingle repreenttive conumer. Te totl welt i A W = p d. Conumer, wit welt = = A ξ = W p d kwconume frction k of te totl dividend. Tt i, finl conumption i A x k d = =. It follow tt inted of trding in te A-D mrket, ec conumer cn imply purce mutul fund tt perfectly trck te mrket portfolio. Tu te A-D equilibrium lloction Jon Riley November 5, 202

23 Eentil Microeconomic -23- i cieved imply by trding in te et mrket, regrdle of te dimenion of te ubpce pnned by te dividend vector. Wt if we dd initil endowment tt re not trded in te ecurity mrket. Intuitively, long ec conumer endowment vector i pnned by te dividend vector, ti rgument will continue to old. For ten ec conumer totl endowment plu initil portfolio cn be written weigted verge of te dividend vector. We terefore conider n exmple were ti i not te ce. Jon Riley November 5, 202

24 Eentil Microeconomic -24- An exmple: Solving for n incomplete ecurity mrket equilibrium one-good, two-conumer, 3 eqully likely tte, 2 ecuritie wit dividend: d = (, 0,), d 2 = (0,,) Te two conumer ve te me logritmic expected utility function 3 3 π 3 = = U( x) = ux ( ) = ln x, =,2. Contructing n SM equilibrium It i not poible to olve nlyticlly for te olution to portfolio optimiztion problem o we contruct n equilibrium by working bckwrd. Let x = (2, 4,2) be te SM equilibrium conumption of conumer. At ti conumption bundle te mrginl rte of ubtitution or implicit price r = MRS ( x, x ) = π u ( x )/ π u ( x ) re follow: r x x x = (,, ) = (,3,). x x2 x3 Jon Riley November 5, 202

25 Eentil Microeconomic -25- Cooing n optiml portfolio Conumer, wit endowment ω nd portfolio ξ finl conumption of x = ω + ξ d He olve te following problem: 3 Mx{ π u( ω + ξ d ) P ξ 0} ξ = Lgrngin: 3 L = π u( ω + ξ d ) λp ξ, FOC: = 3 = π u ( x ) d ) λp = 0, =, 2 Eliminting te dow price, 3 π u ( x ) d = P2 = 3 P π u ( x ) d =. We cn rewrite ti in term of te implicit price. r d2 P2 = r d P Jon Riley November 5, 202

26 Eentil Microeconomic -26- Conumer : r = (,3,) (, 0,) d =, d 2 = (0,,) (,3,) (,,) 4 P2 Terefore = = (,3,) (, 0,) 2 P. Tu te finl conumption i optiml if te et price rtio i 2. Conumer 2: Note tt for n SM equilibrium r d r d P r d r d P = = 2. r d2 P2 Appeling to te rtio rule it follow lo tt = r d P were r = r2 r = (0, r2, r3). r2 + r3 r2 Terefore = + = 2 r r 3 3. Terefore te FOC old for conumer 2 if r2 = r3 =. Jon Riley November 5, 202

27 Eentil Microeconomic -27- But r =. r = (,3,). Terefore 2 (,4,2) r = MRS ( x, x ) = π u ( x )/ π u ( x ) Terefore: r x x x = (,, ) = (,4,2) x x2 x3 Tu if we cooe 2 x = 8, conumer 2 conumption vector i 2 x = (8,2,4). Conumer portfolio contrint i Ti i tified if ξ = (2, ). Ten P ξ = ξ + 2ξ = 0. x 2 ω = ξ D= (2,,) nd o ω = (0,5,) For mrket clering, ξ + ξ = 0. Terefore ξ = ( 2,) nd o ω = (0,,5). Jon Riley November 5, 202

28 Eentil Microeconomic -28- Comprion wit te AD equilibrium Becue te conumer ve te me omotetic preference, te A-D equilibrium i no-trde equilibrium for te repreenttive conumer. Te normlized A-D equilibrium price vector i x x (, p, p ) = (,, ) = (,3, ), ince x= ω = (20,6,6) x2 x3 Note tt te A-D equilibrium price vector lie between te two implicit price vector r = (,3,) nd 2 r = (,4,2) ocited wit te incomplete mrket equilibrium. p d2 65 P2 Note lo tt = < 2 =. Tu te reltive vlue of ecurity i iger wen mrket re p d 27 P complete. Terefore, if n individul or firm cn predict te effect of dding new ecurity on te reltive price of current ecuritie, tere re profitble rbitrge opportunitie. Tu in n incomplete mrket, finncil intermediry trong incentive to crete new ecuritie. Jon Riley November 5, 202

Econ 401A Three extra questions John Riley. Homework 3 Due Tuesday, Nov 28

Econ 401A Three extra questions John Riley. Homework 3 Due Tuesday, Nov 28 Econ 40 ree etr uestions Jon Riley Homework Due uesdy, Nov 8 Finncil engineering in coconut economy ere re two risky ssets Plnttion s gross stte contingent return of z (60,80) e mrket vlue of tis lnttion

More information

1 Review: Volumes of Solids (Stewart )

1 Review: Volumes of Solids (Stewart ) Lecture : Some Bic Appliction of Te Integrl (Stewrt 6.,6.,.,.) ul Krin eview: Volume of Solid (Stewrt 6.-6.) ecll: we d provided two metod for determining te volume of olid of revolution. Te rt w by dic

More information

Econ 401A Version 3 John Riley. Homework 3 Due Tuesday, Nov 28. Answers. (a) Double both sides of the second equation and subtract the second equation

Econ 401A Version 3 John Riley. Homework 3 Due Tuesday, Nov 28. Answers. (a) Double both sides of the second equation and subtract the second equation Econ 40 Version John Riley Homeork Due uesdy, Nov 8 nsers nser to question () Double both sides of the second eqution nd subtrct the second eqution 60q 0q 0 60q 0q 0 b b 00q 0 hen q 0 (b) he vlue of the

More information

APPENDIX 2 LAPLACE TRANSFORMS

APPENDIX 2 LAPLACE TRANSFORMS APPENDIX LAPLACE TRANSFORMS Thi ppendix preent hort introduction to Lplce trnform, the bic tool ued in nlyzing continuou ytem in the frequency domin. The Lplce trnform convert liner ordinry differentil

More information

3. THE EXCHANGE ECONOMY

3. THE EXCHANGE ECONOMY Essential Microeconomics -1-3. THE EXCHNGE ECONOMY Pareto efficient allocations 2 Edgewort box analysis 5 Market clearing prices 13 Walrasian Equilibrium 16 Equilibrium and Efficiency 22 First welfare

More information

Inference for Two Stage Cluster Sampling: Equal SSU per PSU. Projections of SSU Random Variables on Each SSU selection.

Inference for Two Stage Cluster Sampling: Equal SSU per PSU. Projections of SSU Random Variables on Each SSU selection. Inference for Two Stage Cluter Sampling: Equal SSU per PSU Projection of SSU andom Variable on Eac SSU election By Ed Stanek Introduction We review etimating equation for PSU mean in a two tage cluter

More information

Essential Microeconomics : EQUILIBRIUM AND EFFICIENCY WITH PRODUCTION Key ideas: Walrasian equilibrium, first and second welfare theorems

Essential Microeconomics : EQUILIBRIUM AND EFFICIENCY WITH PRODUCTION Key ideas: Walrasian equilibrium, first and second welfare theorems Essential Microeconomics -- 5.2: EQUILIBRIUM AND EFFICIENCY WITH PRODUCTION Key ideas: Walrasian equilibrium, irst and second welare teorems A general model 2 First welare Teorem 7 Second welare teorem

More information

Walrasian Equilibrium in an exchange economy

Walrasian Equilibrium in an exchange economy Microeconomic Teory -1- Walrasian equilibrium Walrasian Equilibrium in an ecange economy 1. Homotetic preferences 2 2. Walrasian equilibrium in an ecange economy 11 3. Te market value of attributes 18

More information

a b [^ab] ^a [^ab] [^ab]

a b [^ab] ^a [^ab] [^ab] Genertion of Pttern-Mtcing Algoritm y Extended Regulr Expreion Ikuo NAKATA 3 Summry. It i dicult to expre te denition of te comment of C lnguge in regulr expreion. However, te denition cn e expreed y imple

More information

PHYS 601 HW 5 Solution. We wish to find a Fourier expansion of e sin ψ so that the solution can be written in the form

PHYS 601 HW 5 Solution. We wish to find a Fourier expansion of e sin ψ so that the solution can be written in the form 5 Solving Kepler eqution Conider the Kepler eqution ωt = ψ e in ψ We wih to find Fourier expnion of e in ψ o tht the olution cn be written in the form ψωt = ωt + A n innωt, n= where A n re the Fourier

More information

Accelerator Physics. G. A. Krafft Jefferson Lab Old Dominion University Lecture 5

Accelerator Physics. G. A. Krafft Jefferson Lab Old Dominion University Lecture 5 Accelertor Phyic G. A. Krfft Jefferon L Old Dominion Univerity Lecture 5 ODU Accelertor Phyic Spring 15 Inhomogeneou Hill Eqution Fundmentl trnvere eqution of motion in prticle ccelertor for mll devition

More information

3.2 THE FUNDAMENTAL WELFARE THEOREMS

3.2 THE FUNDAMENTAL WELFARE THEOREMS Essential Microeconomics -1-3.2 THE FUNDMENTL WELFRE THEOREMS Walrasian Equilibrium 2 First welfare teorem 3 Second welfare teorem (conve, differentiable economy) 12 Te omotetic preference 2 2 economy

More information

STABILITY and Routh-Hurwitz Stability Criterion

STABILITY and Routh-Hurwitz Stability Criterion Krdeniz Technicl Univerity Deprtment of Electricl nd Electronic Engineering 6080 Trbzon, Turkey Chpter 8- nd Routh-Hurwitz Stbility Criterion Bu der notlrı dece bu deri ln öğrencilerin kullnımın çık olup,

More information

16z z q. q( B) Max{2 z z z z B} r z r z r z r z B. John Riley 19 October Econ 401A: Microeconomic Theory. Homework 2 Answers

16z z q. q( B) Max{2 z z z z B} r z r z r z r z B. John Riley 19 October Econ 401A: Microeconomic Theory. Homework 2 Answers John Riley 9 Otober 6 Eon 4A: Miroeonomi Theory Homework Answers Constnt returns to sle prodution funtion () If (,, q) S then 6 q () 4 We need to show tht (,, q) S 6( ) ( ) ( q) q [ q ] 4 4 4 4 4 4 Appeling

More information

This appendix derives Equations (16) and (17) from Equations (12) and (13).

This appendix derives Equations (16) and (17) from Equations (12) and (13). Capital growt pat of te neoclaical growt model Online Supporting Information Ti appendix derive Equation (6) and (7) from Equation () and (3). Equation () and (3) owed te evolution of pyical and uman capital

More information

International Journal of Scientific & Engineering Research, Volume 4, Issue 8, August ISSN

International Journal of Scientific & Engineering Research, Volume 4, Issue 8, August ISSN Interntionl Journl of Scientific & Engineering Reerc Volume Iue 8 ugut- 68 ISSN 9-558 n Inventory Moel wit llowble Sortge Uing rpezoil Fuzzy Number P. Prvti He & ocite Profeor eprtment of Mtemtic ui- E

More information

Artificial Intelligence Markov Decision Problems

Artificial Intelligence Markov Decision Problems rtificil Intelligence Mrkov eciion Problem ilon - briefly mentioned in hpter Ruell nd orvig - hpter 7 Mrkov eciion Problem; pge of Mrkov eciion Problem; pge of exmple: probbilitic blockworld ction outcome

More information

Internet Appendix for Informational Frictions and Commodity Markets

Internet Appendix for Informational Frictions and Commodity Markets Internet ppendix for Informational Friction and Commodity Market MICHEL SOCKIN and WEI XIONG In ti appendix, we preent in detail an extended model wit a future market, in upplement to te ummary of te model

More information

Lecture Note 4: Numerical differentiation and integration. Xiaoqun Zhang Shanghai Jiao Tong University

Lecture Note 4: Numerical differentiation and integration. Xiaoqun Zhang Shanghai Jiao Tong University Lecture Note 4: Numericl differentition nd integrtion Xioqun Zng Sngi Jio Tong University Lst updted: November, 0 Numericl Anlysis. Numericl differentition.. Introduction Find n pproximtion of f (x 0 ),

More information

20.2. The Transform and its Inverse. Introduction. Prerequisites. Learning Outcomes

20.2. The Transform and its Inverse. Introduction. Prerequisites. Learning Outcomes The Trnform nd it Invere 2.2 Introduction In thi Section we formlly introduce the Lplce trnform. The trnform i only pplied to cul function which were introduced in Section 2.1. We find the Lplce trnform

More information

Reinforcement learning

Reinforcement learning Reinforcement lerning Regulr MDP Given: Trnition model P Rewrd function R Find: Policy π Reinforcement lerning Trnition model nd rewrd function initilly unknown Still need to find the right policy Lern

More information

Problem Set 7: Monopoly and Game Theory

Problem Set 7: Monopoly and Game Theory ECON 000 Problem Set 7: Monopoly nd Gme Theory. () The monopolist will choose the production level tht mximizes its profits: The FOC of monopolist s problem is: So, the monopolist would set the quntity

More information

Module 6: LINEAR TRANSFORMATIONS

Module 6: LINEAR TRANSFORMATIONS Module 6: LINEAR TRANSFORMATIONS. Trnsformtions nd mtrices Trnsformtions re generliztions of functions. A vector x in some set S n is mpped into m nother vector y T( x). A trnsformtion is liner if, for

More information

SUMMER KNOWHOW STUDY AND LEARNING CENTRE

SUMMER KNOWHOW STUDY AND LEARNING CENTRE SUMMER KNOWHOW STUDY AND LEARNING CENTRE Indices & Logrithms 2 Contents Indices.2 Frctionl Indices.4 Logrithms 6 Exponentil equtions. Simplifying Surds 13 Opertions on Surds..16 Scientific Nottion..18

More information

ARCHIVUM MATHEMATICUM (BRNO) Tomus 47 (2011), Kristína Rostás

ARCHIVUM MATHEMATICUM (BRNO) Tomus 47 (2011), Kristína Rostás ARCHIVUM MAHEMAICUM (BRNO) omu 47 (20), 23 33 MINIMAL AND MAXIMAL SOLUIONS OF FOURH ORDER IERAED DIFFERENIAL EQUAIONS WIH SINGULAR NONLINEARIY Kritín Rotá Abtrct. In thi pper we re concerned with ufficient

More information

Key words. Numerical quadrature, piecewise polynomial, convergence rate, trapezoidal rule, midpoint rule, Simpson s rule, spectral accuracy.

Key words. Numerical quadrature, piecewise polynomial, convergence rate, trapezoidal rule, midpoint rule, Simpson s rule, spectral accuracy. O SPECTRA ACCURACY OF QUADRATURE FORMUAE BASED O PIECEWISE POYOMIA ITERPOATIO A KURGAOV AD S TSYKOV Abstrct It is well-known tt te trpezoidl rule, wile being only second-order ccurte in generl, improves

More information

Logarithms and Exponential Functions. Gerda de Vries & John S. Macnab. match as necessary, or to work these results into other lessons.

Logarithms and Exponential Functions. Gerda de Vries & John S. Macnab. match as necessary, or to work these results into other lessons. Logritms nd Eponentil Functions Gerd de Vries & Jon S. Mcn It is epected tt students re lred fmilir wit tis mteril. We include it ere for completeness. Te tree lessons given ere re ver sort. Te tecer is

More information

Topic 6b Finite Difference Approximations

Topic 6b Finite Difference Approximations /8/8 Course Instructor Dr. Rymond C. Rump Oice: A 7 Pone: (95) 747 6958 E Mil: rcrump@utep.edu Topic 6b Finite Dierence Approximtions EE 486/5 Computtionl Metods in EE Outline Wt re inite dierence pproximtions?

More information

How do we solve these things, especially when they get complicated? How do we know when a system has a solution, and when is it unique?

How do we solve these things, especially when they get complicated? How do we know when a system has a solution, and when is it unique? XII. LINEAR ALGEBRA: SOLVING SYSTEMS OF EQUATIONS Tody we re going to tlk bout solving systems of liner equtions. These re problems tht give couple of equtions with couple of unknowns, like: 6 2 3 7 4

More information

Equilibrium and Pareto Efficiency in an exchange economy

Equilibrium and Pareto Efficiency in an exchange economy Microeconomic Teory -1- Equilibrium and efficiency Equilibrium and Pareto Efficiency in an excange economy 1. Efficient economies 2 2. Gains from excange 6 3. Edgewort-ox analysis 15 4. Properties of a

More information

Assignment for Mathematics for Economists Fall 2016

Assignment for Mathematics for Economists Fall 2016 Due date: Mon. Nov. 1. Reading: CSZ, Ch. 5, Ch. 8.1 Aignment for Mathematic for Economit Fall 016 We now turn to finihing our coverage of concavity/convexity. There are two part: Jenen inequality for concave/convex

More information

Math Week 5 concepts and homework, due Friday February 10

Math Week 5 concepts and homework, due Friday February 10 Mt 2280-00 Week 5 concepts nd omework, due Fridy Februry 0 Recll tt ll problems re good for seeing if you cn work wit te underlying concepts; tt te underlined problems re to be nded in; nd tt te Fridy

More information

A P P E N D I X POWERS OF TEN AND SCIENTIFIC NOTATION A P P E N D I X SIGNIFICANT FIGURES

A P P E N D I X POWERS OF TEN AND SCIENTIFIC NOTATION A P P E N D I X SIGNIFICANT FIGURES A POWERS OF TEN AND SCIENTIFIC NOTATION In science, very lrge nd very smll deciml numbers re conveniently expressed in terms of powers of ten, some of wic re listed below: 0 3 0 0 0 000 0 3 0 0 0 0.00

More information

Section P.1 Notes Page 1 Section P.1 Precalculus and Trigonometry Review

Section P.1 Notes Page 1 Section P.1 Precalculus and Trigonometry Review Secion P Noe Pge Secion P Preclculu nd Trigonomer Review ALGEBRA AND PRECALCULUS Eponen Lw: Emple: 8 Emple: Emple: Emple: b b Emple: 9 EXAMPLE: Simplif: nd wrie wi poiive eponen Fir I will flip e frcion

More information

2. The Laplace Transform

2. The Laplace Transform . The Lplce Trnform. Review of Lplce Trnform Theory Pierre Simon Mrqui de Lplce (749-87 French tronomer, mthemticin nd politicin, Miniter of Interior for 6 wee under Npoleon, Preident of Acdemie Frncie

More information

CAPITAL ASSET PRICING MODEL (CAPM)

CAPITAL ASSET PRICING MODEL (CAPM) Finnce -- 5 y 202 CAPIAL ASSE PRICING ODEL (CAP) Finnce -2-5 y 202 Portfolio of one riskless nd one risky sset Consider portfolio consisting of the riskless sset with men return per dollr 0 = + r nd mutul

More information

TP 10:Importance Sampling-The Metropolis Algorithm-The Ising Model-The Jackknife Method

TP 10:Importance Sampling-The Metropolis Algorithm-The Ising Model-The Jackknife Method TP 0:Importnce Smpling-The Metropoli Algorithm-The Iing Model-The Jckknife Method June, 200 The Cnonicl Enemble We conider phyicl ytem which re in therml contct with n environment. The environment i uully

More information

Applicability of Matrix Inverse in Simple Model of Economics An Analysis

Applicability of Matrix Inverse in Simple Model of Economics An Analysis IOSR Journl of Mthemtic IOSR-JM e-issn: 78-578, p-issn: 39-765X. Volume, Iue 5 Ver. VI Sep-Oct. 4, PP 7-34 pplicility of Mtrix Invere in Simple Moel of Economic n nlyi Mr. nupm Srm Deprtment of Economic

More information

4-4 E-field Calculations using Coulomb s Law

4-4 E-field Calculations using Coulomb s Law 1/11/5 ection_4_4_e-field_clcultion_uing_coulomb_lw_empty.doc 1/1 4-4 E-field Clcultion uing Coulomb Lw Reding Aignment: pp. 9-98 Specificlly: 1. HO: The Uniform, Infinite Line Chrge. HO: The Uniform Dik

More information

TCER WORKING PAPER SERIES GOLDEN RULE OPTIMALITY IN STOCHASTIC OLG ECONOMIES. Eisei Ohtaki. June 2012

TCER WORKING PAPER SERIES GOLDEN RULE OPTIMALITY IN STOCHASTIC OLG ECONOMIES. Eisei Ohtaki. June 2012 TCER WORKING PAPER SERIES GOLDEN RULE OPTIMALITY IN STOCHASTIC OLG ECONOMIES Eiei Ohtaki June 2012 Working Paper E-44 http://www.tcer.or.jp/wp/pdf/e44.pdf TOKYO CENTER FOR ECONOMIC RESEARCH 1-7-10 Iidabahi,

More information

Online Supplements to Performance-Based Contracts for Outpatient Medical Services

Online Supplements to Performance-Based Contracts for Outpatient Medical Services Jing, Png nd Svin: Performnce-bsed Contrcts Article submitted to Mnufcturing & Service Opertions Mngement; mnuscript no. MSOM-11-270.R2 1 Online Supplements to Performnce-Bsed Contrcts for Outptient Medicl

More information

Section 4.2 Analysis of synchronous machines Part II

Section 4.2 Analysis of synchronous machines Part II Section 4. Anlyi of ynchronou mchine Prt 4.. Sttor flux linkge in non-lient pole ynchronou motor due to rotor The ir-gp field produced by the rotor produce flux linkge with individul phe winding. Thee

More information

Econ 401A Draft 5 John & Ksenia. Homework 4 Answers. 1. WE in an economy with constant rturns to scale and identical homothetic preferences.

Econ 401A Draft 5 John & Ksenia. Homework 4 Answers. 1. WE in an economy with constant rturns to scale and identical homothetic preferences. Econ 0A Drft 5 John & Kseni Homework Answers WE in n economy with constnt rturns to scle nd identicl homothetic preferences () U( q, q ) ln q ln q ln( z ) ( z ) ln( z ) ( z ) / / / / Choose ie z, z ln

More information

Bogoliubov Transformation in Classical Mechanics

Bogoliubov Transformation in Classical Mechanics Bogoliubov Tranformation in Claical Mechanic Canonical Tranformation Suppoe we have a et of complex canonical variable, {a j }, and would like to conider another et of variable, {b }, b b ({a j }). How

More information

Patrice Cassagnard Université Montesquieu Bordeaux IV LAREefi. Abstract

Patrice Cassagnard Université Montesquieu Bordeaux IV LAREefi. Abstract A useful grpicl metod under Cournot competition Ptrice Cssgnrd Université Montesquieu Bordeux IV LAEefi Astrct Tis note proposes grpicl pproc useful in gme teor. Tis metod consists in representing incentives

More information

Online Appendix for Corporate Control Activism

Online Appendix for Corporate Control Activism Online Appendix for Corporate Control Activim B Limited veto power and tender offer In thi ection we extend the baeline model by allowing the bidder to make a tender offer directly to target hareholder.

More information

4. UNBALANCED 3 FAULTS

4. UNBALANCED 3 FAULTS 4. UNBALANCED AULTS So fr: we hve tudied lned fult ut unlned fult re more ommon. Need: to nlye unlned ytem. Could: nlye three-wire ytem V n V n V n Mot ommon fult type = ingle-phe to ground i.e. write

More information

1 Online Learning and Regret Minimization

1 Online Learning and Regret Minimization 2.997 Decision-Mking in Lrge-Scle Systems My 10 MIT, Spring 2004 Hndout #29 Lecture Note 24 1 Online Lerning nd Regret Minimiztion In this lecture, we consider the problem of sequentil decision mking in

More information

Duality # Second iteration for HW problem. Recall our LP example problem we have been working on, in equality form, is given below.

Duality # Second iteration for HW problem. Recall our LP example problem we have been working on, in equality form, is given below. Dulity #. Second itertion for HW problem Recll our LP emple problem we hve been working on, in equlity form, is given below.,,,, 8 m F which, when written in slightly different form, is 8 F Recll tht we

More information

Finite Difference Formulae for Unequal Sub- Intervals Using Lagrange s Interpolation Formula

Finite Difference Formulae for Unequal Sub- Intervals Using Lagrange s Interpolation Formula Int. Journal o Mat. Analyi, Vol., 9, no. 7, 85-87 Finite Dierence Formulae or Unequal Sub- Interval Uing Lagrange Interpolation Formula Aok K. Sing a and B. S. Badauria b Department o Matematic, Faculty

More information

IGC. 50 th. 50 th INDIAN GEOTECHNICAL CONFERENCE SEISMIC ACTIVE EARTH PRESSURE ON RETAINING WALL CONSIDERING SOIL AMPLIFICATION

IGC. 50 th. 50 th INDIAN GEOTECHNICAL CONFERENCE SEISMIC ACTIVE EARTH PRESSURE ON RETAINING WALL CONSIDERING SOIL AMPLIFICATION INDIAN GEOTECHNICAL CONFERENCE SEISMIC ACTIVE EARTH PRESSURE ON RETAINING WALL CONSIDERING SOIL AMPLIFICATION Obaidur Raaman 1 and Priati Raycowdury 2 ABSTRACT Te quet for te realitic etimation of eimic

More information

Math 2142 Homework 2 Solutions. Problem 1. Prove the following formulas for Laplace transforms for s > 0. a s 2 + a 2 L{cos at} = e st.

Math 2142 Homework 2 Solutions. Problem 1. Prove the following formulas for Laplace transforms for s > 0. a s 2 + a 2 L{cos at} = e st. Mth 2142 Homework 2 Solution Problem 1. Prove the following formul for Lplce trnform for >. L{1} = 1 L{t} = 1 2 L{in t} = 2 + 2 L{co t} = 2 + 2 Solution. For the firt Lplce trnform, we need to clculte:

More information

COUNTING DESCENTS, RISES, AND LEVELS, WITH PRESCRIBED FIRST ELEMENT, IN WORDS

COUNTING DESCENTS, RISES, AND LEVELS, WITH PRESCRIBED FIRST ELEMENT, IN WORDS COUNTING DESCENTS, RISES, AND LEVELS, WITH PRESCRIBED FIRST ELEMENT, IN WORDS Sergey Kitev The Mthemtic Intitute, Reykvik Univerity, IS-03 Reykvik, Icelnd ergey@rui Toufik Mnour Deprtment of Mthemtic,

More information

A New Estimator Using Auxiliary Information in Stratified Adaptive Cluster Sampling

A New Estimator Using Auxiliary Information in Stratified Adaptive Cluster Sampling Ope Jourl of ttitic, 03, 3, 78-8 ttp://d.doi.org/0.436/oj.03.3403 Publied Olie eptember 03 (ttp://www.cirp.org/jourl/oj) New Etimtor Uig uilir Iformtio i trtified dptive Cluter mplig Nippor Cutim *, Moc

More information

Improper Integrals, and Differential Equations

Improper Integrals, and Differential Equations Improper Integrls, nd Differentil Equtions October 22, 204 5.3 Improper Integrls Previously, we discussed how integrls correspond to res. More specificlly, we sid tht for function f(x), the region creted

More information

Hilbert-Space Integration

Hilbert-Space Integration Hilbert-Space Integration. Introduction. We often tink of a PDE, like te eat equation u t u xx =, a an evolution equation a itorically wa done for ODE. In te eat equation example two pace derivative are

More information

Laplace Transformation

Laplace Transformation Univerity of Technology Electromechanical Department Energy Branch Advance Mathematic Laplace Tranformation nd Cla Lecture 6 Page of 7 Laplace Tranformation Definition Suppoe that f(t) i a piecewie continuou

More information

A High Throughput String Matching Architecture for Intrusion Detection and Prevention

A High Throughput String Matching Architecture for Intrusion Detection and Prevention A Hig Trougput tring Matcing Arcitecture for Intruion Detection and Prevention Lin Tan, Timoty erwood Appeared in ICA 25 Preented by: aile Kumar Dicuion Leader: Max Podleny Overview Overview of ID/IP ytem»

More information

EE Control Systems LECTURE 8

EE Control Systems LECTURE 8 Coyright F.L. Lewi 999 All right reerved Udted: Sundy, Ferury, 999 EE 44 - Control Sytem LECTURE 8 REALIZATION AND CANONICAL FORMS A liner time-invrint (LTI) ytem cn e rereented in mny wy, including: differentil

More information

A REVIEW OF CALCULUS CONCEPTS FOR JDEP 384H. Thomas Shores Department of Mathematics University of Nebraska Spring 2007

A REVIEW OF CALCULUS CONCEPTS FOR JDEP 384H. Thomas Shores Department of Mathematics University of Nebraska Spring 2007 A REVIEW OF CALCULUS CONCEPTS FOR JDEP 384H Thoms Shores Deprtment of Mthemtics University of Nebrsk Spring 2007 Contents Rtes of Chnge nd Derivtives 1 Dierentils 4 Are nd Integrls 5 Multivrite Clculus

More information

Solutions Problem Set 2. Problem (a) Let M denote the DFA constructed by swapping the accept and non-accepting state in M.

Solutions Problem Set 2. Problem (a) Let M denote the DFA constructed by swapping the accept and non-accepting state in M. Solution Prolem Set 2 Prolem.4 () Let M denote the DFA contructed y wpping the ccept nd non-ccepting tte in M. For ny tring w B, w will e ccepted y M, tht i, fter conuming the tring w, M will e in n ccepting

More information

Chapter 23. Geometric Optics

Chapter 23. Geometric Optics Cpter 23 Geometric Optic Ligt Wt i ligt? Wve or prticle? ot Geometric optic: ligt trvel i trigt-lie pt clled ry Ti i true if typicl ditce re muc lrger t te wvelegt Geometric Optic 2 Wt it i out eome ddreed

More information

Volume 29, Issue 3. Existence of competitive equilibrium in economies with multi-member households

Volume 29, Issue 3. Existence of competitive equilibrium in economies with multi-member households Volume 29, Issue 3 Existence of competitive equilibrium in economies wit multi-member ouseolds Noriisa Sato Graduate Scool of Economics, Waseda University Abstract Tis paper focuses on te existence of

More information

DIRECT CURRENT CIRCUITS

DIRECT CURRENT CIRCUITS DRECT CURRENT CUTS ELECTRC POWER Consider the circuit shown in the Figure where bttery is connected to resistor R. A positive chrge dq will gin potentil energy s it moves from point to point b through

More information

MA FINAL EXAM INSTRUCTIONS

MA FINAL EXAM INSTRUCTIONS MA 33 FINAL EXAM INSTRUCTIONS NAME INSTRUCTOR. Intructor nme: Chen, Dong, Howrd, or Lundberg 2. Coure number: MA33. 3. SECTION NUMBERS: 6 for MWF :3AM-:2AM REC 33 cl by Erik Lundberg 7 for MWF :3AM-:2AM

More information

Math 116 Calculus II

Math 116 Calculus II Mth 6 Clculus II Contents 5 Exponentil nd Logrithmic functions 5. Review........................................... 5.. Exponentil functions............................... 5.. Logrithmic functions...............................

More information

Properties of Integrals, Indefinite Integrals. Goals: Definition of the Definite Integral Integral Calculations using Antiderivatives

Properties of Integrals, Indefinite Integrals. Goals: Definition of the Definite Integral Integral Calculations using Antiderivatives Block #6: Properties of Integrls, Indefinite Integrls Gols: Definition of the Definite Integrl Integrl Clcultions using Antiderivtives Properties of Integrls The Indefinite Integrl 1 Riemnn Sums - 1 Riemnn

More information

CHOOSING THE NUMBER OF MODELS OF THE REFERENCE MODEL USING MULTIPLE MODELS ADAPTIVE CONTROL SYSTEM

CHOOSING THE NUMBER OF MODELS OF THE REFERENCE MODEL USING MULTIPLE MODELS ADAPTIVE CONTROL SYSTEM Interntionl Crpthin Control Conference ICCC 00 ALENOVICE, CZEC REPUBLIC y 7-30, 00 COOSING TE NUBER OF ODELS OF TE REFERENCE ODEL USING ULTIPLE ODELS ADAPTIVE CONTROL SYSTE rin BICĂ, Victor-Vleriu PATRICIU

More information

Bases for Vector Spaces

Bases for Vector Spaces Bses for Vector Spces 2-26-25 A set is independent if, roughly speking, there is no redundncy in the set: You cn t uild ny vector in the set s liner comintion of the others A set spns if you cn uild everything

More information

How do we solve these things, especially when they get complicated? How do we know when a system has a solution, and when is it unique?

How do we solve these things, especially when they get complicated? How do we know when a system has a solution, and when is it unique? XII. LINEAR ALGEBRA: SOLVING SYSTEMS OF EQUATIONS Tody we re going to tlk out solving systems of liner equtions. These re prolems tht give couple of equtions with couple of unknowns, like: 6= x + x 7=

More information

PRACTICE EXAM 2 SOLUTIONS

PRACTICE EXAM 2 SOLUTIONS MASSACHUSETTS INSTITUTE OF TECHNOLOGY Deprtment of Phyic Phyic 8.01x Fll Term 00 PRACTICE EXAM SOLUTIONS Proble: Thi i reltively trihtforwrd Newton Second Lw problem. We et up coordinte ytem which i poitive

More information

A recursive construction of efficiently decodable list-disjunct matrices

A recursive construction of efficiently decodable list-disjunct matrices CSE 709: Compressed Sensing nd Group Testing. Prt I Lecturers: Hung Q. Ngo nd Atri Rudr SUNY t Bufflo, Fll 2011 Lst updte: October 13, 2011 A recursive construction of efficiently decodble list-disjunct

More information

I1 = I2 I1 = I2 + I3 I1 + I2 = I3 + I4 I 3

I1 = I2 I1 = I2 + I3 I1 + I2 = I3 + I4 I 3 2 The Prllel Circuit Electric Circuits: Figure 2- elow show ttery nd multiple resistors rrnged in prllel. Ech resistor receives portion of the current from the ttery sed on its resistnce. The split is

More information

Imperfect Signaling and the Local Credibility Test

Imperfect Signaling and the Local Credibility Test Imperfect Signaling and the Local Credibility Tet Hongbin Cai, John Riley and Lixin Ye* Abtract In thi paper we tudy equilibrium refinement in ignaling model. We propoe a Local Credibility Tet (LCT) which

More information

Online Appendix for Managerial Attention and Worker Performance by Marina Halac and Andrea Prat

Online Appendix for Managerial Attention and Worker Performance by Marina Halac and Andrea Prat Online Appendix for Managerial Attention and Worker Performance by Marina Halac and Andrea Prat Thi Online Appendix contain the proof of our reult for the undicounted limit dicued in Section 2 of the paper,

More information

Jim Lambers MAT 169 Fall Semester Lecture 4 Notes

Jim Lambers MAT 169 Fall Semester Lecture 4 Notes Jim Lmbers MAT 169 Fll Semester 2009-10 Lecture 4 Notes These notes correspond to Section 8.2 in the text. Series Wht is Series? An infinte series, usully referred to simply s series, is n sum of ll of

More information

Kinematics equations, some numbers

Kinematics equations, some numbers Kinemtics equtions, some numbers Kinemtics equtions: x = x 0 + v 0 t + 1 2 t2, v = v 0 + t. They describe motion with constnt ccelertion. Brking exmple, = 1m/s. Initil: x 0 = 10m, v 0 = 10m/s. x(t=1s)

More information

Moral Hazard and Endogenous Monitoring

Moral Hazard and Endogenous Monitoring Morl Hzrd nd Endogenous Monitoring Ofer Setty * Tel Aviv University This Drft: Februry 2014 Abstrct How do principl s incentives to monitor depend on n gent s outside option? The principl cn incentivize

More information

Chapter 18 Two-Port Circuits

Chapter 18 Two-Port Circuits Cpter 8 Two-Port Circuits 8. Te Terminl Equtions 8. Te Two-Port Prmeters 8.3 Anlysis of te Terminted Two-Port Circuit 8.4 nterconnected Two-Port Circuits Motivtion Tévenin nd Norton equivlent circuits

More information

(b) Is the game below solvable by iterated strict dominance? Does it have a unique Nash equilibrium?

(b) Is the game below solvable by iterated strict dominance? Does it have a unique Nash equilibrium? 14.1 Final Exam Anwer all quetion. You have 3 hour in which to complete the exam. 1. (60 Minute 40 Point) Anwer each of the following ubquetion briefly. Pleae how your calculation and provide rough explanation

More information

12 Basic Integration in R

12 Basic Integration in R 14.102, Mt for Economists Fll 2004 Lecture Notes, 10/14/2004 Tese notes re primrily bsed on tose written by Andrei Bremzen for 14.102 in 2002/3, nd by Mrek Pyci for te MIT Mt Cmp in 2003/4. I ve mde only

More information

ARITHMETIC OPERATIONS. The real numbers have the following properties: a b c ab ac

ARITHMETIC OPERATIONS. The real numbers have the following properties: a b c ab ac REVIEW OF ALGEBRA Here we review the bsic rules nd procedures of lgebr tht you need to know in order to be successful in clculus. ARITHMETIC OPERATIONS The rel numbers hve the following properties: b b

More information

Mechanics Physics 151

Mechanics Physics 151 Mechanic Phyic 151 Lecture 7 Scattering Problem (Chapter 3) What We Did Lat Time Dicued Central Force Problem l Problem i reduced to one equation mr = + f () r 3 mr Analyzed qualitative behavior Unbounded,

More information

Chapter 2. Numerical Integration also called quadrature. 2.2 Trapezoidal Rule. 2.1 A basic principle Extending the Trapezoidal Rule DRAWINGS

Chapter 2. Numerical Integration also called quadrature. 2.2 Trapezoidal Rule. 2.1 A basic principle Extending the Trapezoidal Rule DRAWINGS S Cpter Numericl Integrtion lso clled qudrture Te gol of numericl integrtion is to pproximte numericlly. f(x)dx Tis is useful for difficult integrls like sin(x) ; sin(x ); x + x 4 Or worse still for multiple-dimensionl

More information

SPACE VECTOR PULSE- WIDTH-MODULATED (SV-PWM) INVERTERS

SPACE VECTOR PULSE- WIDTH-MODULATED (SV-PWM) INVERTERS CHAPTER 7 SPACE VECTOR PULSE- WIDTH-MODULATED (SV-PWM) INVERTERS 7-1 INTRODUCTION In Chpter 5, we briefly icue current-regulte PWM inverter uing current-hyterei control, in which the witching frequency

More information

Imperfect Signaling and the Local Credibility Test

Imperfect Signaling and the Local Credibility Test Imperfect Signaling and the Local Credibility Tet Hongbin Cai, John Riley and Lixin Ye* November, 004 Abtract In thi paper we tudy equilibrium refinement in ignaling model. We propoe a Local Credibility

More information

HW3, Math 307. CSUF. Spring 2007.

HW3, Math 307. CSUF. Spring 2007. HW, Mth 7. CSUF. Spring 7. Nsser M. Abbsi Spring 7 Compiled on November 5, 8 t 8:8m public Contents Section.6, problem Section.6, problem Section.6, problem 5 Section.6, problem 7 6 5 Section.6, problem

More information

Chapter 2 Differentiation

Chapter 2 Differentiation Cpter Differentition. Introduction In its initil stges differentition is lrgely mtter of finding limiting vlues, wen te vribles ( δ ) pproces zero, nd to begin tis cpter few emples will be tken. Emple..:

More information

Recitation 3: More Applications of the Derivative

Recitation 3: More Applications of the Derivative Mth 1c TA: Pdric Brtlett Recittion 3: More Applictions of the Derivtive Week 3 Cltech 2012 1 Rndom Question Question 1 A grph consists of the following: A set V of vertices. A set E of edges where ech

More information

How do you know you have SLE?

How do you know you have SLE? Simultneous Liner Equtions Simultneous Liner Equtions nd Liner Algebr Simultneous liner equtions (SLE s) occur frequently in Sttics, Dynmics, Circuits nd other engineering clsses Need to be ble to, nd

More information

Section 3.1: Derivatives of Polynomials and Exponential Functions

Section 3.1: Derivatives of Polynomials and Exponential Functions Section 3.1: Derivatives of Polynomials and Exponential Functions In previous sections we developed te concept of te derivative and derivative function. Te only issue wit our definition owever is tat it

More information

Modeling in the Frequency Domain

Modeling in the Frequency Domain T W O Modeling in the Frequency Domain SOLUTIONS TO CASE STUDIES CHALLENGES Antenna Control: Tranfer Function Finding each tranfer function: Pot: V i θ i 0 π ; Pre-Amp: V p V i K; Power Amp: E a V p 50

More information

1.2. Linear Variable Coefficient Equations. y + b "! = a y + b " Remark: The case b = 0 and a non-constant can be solved with the same idea as above.

1.2. Linear Variable Coefficient Equations. y + b ! = a y + b  Remark: The case b = 0 and a non-constant can be solved with the same idea as above. 1 12 Liner Vrible Coefficient Equtions Section Objective(s): Review: Constnt Coefficient Equtions Solving Vrible Coefficient Equtions The Integrting Fctor Method The Bernoulli Eqution 121 Review: Constnt

More information

Lecture 8: Period Finding: Simon s Problem over Z N

Lecture 8: Period Finding: Simon s Problem over Z N Quantum Computation (CMU 8-859BB, Fall 205) Lecture 8: Period Finding: Simon Problem over Z October 5, 205 Lecturer: John Wright Scribe: icola Rech Problem A mentioned previouly, period finding i a rephraing

More information

Math 31A Discussion Notes Week 4 October 20 and October 22, 2015

Math 31A Discussion Notes Week 4 October 20 and October 22, 2015 Mat 3A Discussion Notes Week 4 October 20 and October 22, 205 To prepare for te first midterm, we ll spend tis week working eamples resembling te various problems you ve seen so far tis term. In tese notes

More information

Chapter 4. The Laplace Transform Method

Chapter 4. The Laplace Transform Method Chapter 4. The Laplace Tranform Method The Laplace Tranform i a tranformation, meaning that it change a function into a new function. Actually, it i a linear tranformation, becaue it convert a linear combination

More information

Kiel Probes. General Information

Kiel Probes. General Information Kiel s Generl Informtion Aerodynmic Properties Kiel probes re used to mesure totl pressure in fluid strem were te direction of flow is unknown or vries wit operting conditions. Teir correction fctor is

More information

Velocity or 60 km/h. a labelled vector arrow, v 1

Velocity or 60 km/h. a labelled vector arrow, v 1 11.7 Velocity en you are outide and notice a brik wind blowing, or you are riding in a car at 60 km/, you are imply conidering te peed of motion a calar quantity. ometime, owever, direction i alo important

More information

Reinforcement Learning and Policy Reuse

Reinforcement Learning and Policy Reuse Reinforcement Lerning nd Policy Reue Mnuel M. Veloo PEL Fll 206 Reding: Reinforcement Lerning: An Introduction R. Sutton nd A. Brto Probbilitic policy reue in reinforcement lerning gent Fernndo Fernndez

More information

Adding and Subtracting Rational Expressions

Adding and Subtracting Rational Expressions 6.4 Adding nd Subtrcting Rtionl Epressions Essentil Question How cn you determine the domin of the sum or difference of two rtionl epressions? You cn dd nd subtrct rtionl epressions in much the sme wy

More information