ENDOGENOUS GROWTH: Schumpeter s process of creative destruction

Size: px
Start display at page:

Download "ENDOGENOUS GROWTH: Schumpeter s process of creative destruction"

Transcription

1 Jon Vislie Ocober 20, Lecure noes, ECON 4350 ENDOGENOUS GROWTH: Schumpeer s process of creive desrucion Joseph Schumpeer mde erly conribuions wih permnen influence on our undersnding of he role of R&D; process nd produc innovions, invenions, imiions, produc developmen ec., issues we believe ffec he echnologicl developmen o lrge exen. The modern growh models building on Schumpeer s insigh re highly endogenous in he sense h he growh res emerging from hese models re derived from bsic decision principles. We will presen simple version of Schumpeer s ide of he process of creive desrucion, bsed on he work by Aghion & Howi A Model of Growh Through Creive Desrucion, Economeric 992 (Mrch); pp As in ll models of economic growh following he rdiionl neoclssicl se-up, he objecive hs been o undersnd he echnologicl progress s n imporn engine o economic growh. Some models wihin he re of endogenous economic growh relied hevily on lerning by doing, echnologicl spillovers/exernliies nd incresing reurns (exernl o he firms) due o he non-rivlry of knowledge. During he producion nd insllion of new mchines, one lerns more how o opere hem ec. The incresed knowledge ws seen s n uninended by-produc of cpil ccumulion, nd ws no ken ino ccoun when he gens mde heir invesmen decisions. This lerning by invesing genered n exernliy, s more knowledge ccrues o he gens free of chrge, in public good-fshion. The incresed knowledge will be diffused perfecly in he economy; no propery righ is needed s his civiy is no delibere pr of he decision-mking. (One wy he diffusion cn ke plce is hrough he mobiliy of key personl beween firms wihin he sme indusry.) The AK-model ws n exmple or specil cse where we impose some lerning or echnologicl spillovers. Knowledge is included in humn cpil h is reed s n ordinry cpil objec. We were ble o derive, under some resricive ssumpions, mcro producion funcion wih overll incresing reurns o scle nd incresing mrginl produciviy of cpil, wih growh re h ws incresing over ime. Wihin he re clled Schumpeerin growh focus is more on how knowledge is creed nd used. Focus is on innovion, he incenives o innove nd he implicions which re reled o he process of creive desrucion ; lso found in he puy-cly model of Leif Johnsen wih scrpping nd invesmen in new plns. Schumpeer emphsised he role of compeiion in his process. The model hs

2 2 perhps more obvious policy implicions hn some of he oher models we hve looked upon; specil emphsis on indusril policy or suppor like subsidies o promoe innovion desired speed, nd lso he role of good educionl sysem. One focus is on he relionship beween growh nd compeiion clim hs been h here is n inverse relionship: he more compeiive environmen, innovion would be discourged; hence growh would be reduced. Such n inverse relionship hs been difficul o deec from d. In he simplified version of he creive-desrucion-model we consider, we ll deec such n inverse relionship. In he version of creive desrucion we consider here, indusril innovions improve he quliy of producs: lower-quliy producs re driven ou by higherquliy producs (Greshm s lw which here is heory of obsolescence) nd progress crees gins nd losses, hrough he process of creive desrucion. More effecive producion processes replce old nd less effecive ones, bu h lso implies some desrucion. This cn be envisged s we move up quliy-ldder s progress is mde. Ech new innovion cn be seen s n upwrd sep on he ldder; ech poin in ime we move upwrds is rndom, bu once n innovion kes plce, he upwrds jump in quliy is of some given size. The process cn be illusred s: #3 #2 g # g Innovion # is inroduced poin in ime. This innovion will se he bes sndrd in some producion process, unil he nex innovion occurs, some uncerin fuure poin in ime; 2. (Hence he lengh of he period beween wo innovions 2 is rndom vrible.) Once n innovion is inroduced, he quliy is rised by fixed fcor g. The newes mehod will replce he old one, nd will domine unil he nex innovion kes plce.

3 3 The expeced growh re of he economy depends on he economy-wide moun of reserch, brough ino dynmic model wih forwrd-looking gens. When firm conemples underking some reserch civiy, he pyoff from his civiy is he period over which he resercher cn enjoy being monopolis, by hving monopoly ren in he nex period (enforced by some pen lws). The emporry monopoly period hs rndom durion or lengh, unil he nex innovion occurs, rendering he knowledge underlying he presen monopoly ren obsolee. The likelihood of geing one s own mehod or ide obsolee opr overhrown, depends on reserch effor exered by ouside firms, compeing o become he nex innovor, cpuring he subsequen monopoly ren. This is he process of creive desrucion, mking he expeced presen vlue of he rens negively ffeced by fuure reserch civiy or reserch produciviy (modelled s he Poisson rrivl re of he nex innovion). Aniciping more reserch in he fuure will discourge curren reserch. The incenive or crro o lloce resources on reserch for firm is he expeced monopoly profi h he firm migh cpure. The likelihood from desroying someone s monopoly power, for hen o be in emporry monopoly-posiion, is he driving force inducing or encourging creive civiy like innovions. Consider he he following model: We hve economy wih L persons (skilled lbour), ech person hving one uni of lbour, supplied inelsiclly; hence L is he lbour supply ech poin in ime. This lbour cn be used eiher in reserch or in ordinry mnufcuring. Oupu of some consumpion good is genered by using n inermedie good s he sole inpu. The oupu of his finl good per uni of ime is given by he producion funcion y Ax, where x is he (mos producive) inermedie good used s inpu (neglecing physicl cpil), wih 0. A is prmeer indicing he produciviy or quliy of he inermedie inpu. We hve lbour mrke for skilled lbour. In producing he inermedie good, only lbour is used, in n moun m, in one-o-one-mnner; i.e. xhm ( ) m; liner producion echnology. The moun of people enering reserch is n; hence we hve: ( L) L m n i) The R&D-sge R&D is modelled s process of improving he quliy or produciviy of he inermedie inpu. Through innovive civiies here is flow of new invenions mnifesed s beer-quliy vrieies of he inermedie good used s inpu h will replce older vrieies. This process is modelled s incresing he echnologicl prmeer A in he producion funcion by he consn fcor g from one

4 4 innovion o he nex. Ech innovion will herefore improve he quliy of he inermedie inpu from A o ga, wih g > mesuring he size of he innovion. Ech resercher llocing one uni of lbour o R&D will ener loery ( sochsic R&D-process). Suppose h during shor inervl of imed, eiher one or no innovion will occur. Ech innovion will give n increse in A equl o g. Wih men rrivl re 0, which cn be seen s he probbiliy per uni of ime of hving n innovion, he probbiliy h n innovion will occur in he shor ime inervl of lengh d, is d. Hence he probbiliy h n innovion will no occur is d. (As n pproximion: Le Z denoe he number of innovions king plce during some fixed ime inervl, disribued ccording o Poisson, wih ( d) d 2 Pr ( Z on 0, d) e d ( d 2 ( d)...) d.)! When n persons lloce heir lbour ime on reserch, ech hving he sme rrivl re, hen he probbiliy h n innovion occurs in he ime inervl of lengh d, will be nd. We cn consider s mesure of he produciviy of he reserch echnology. Wih probbiliy nd here will be n innovion or new inermedie inpu, mesured by jump g during some shor inervl of ime. Afer innovion #, he inpu is x, wih higher produciviy hn he previous one; A ga. m x y Ax L n g wih prob. nd during, d The innovion mens h one discovers n improved version (or higher quliy) of he inermedie inpu. We ssume h ech successful innovor hs imelimied monopoly power; lsing unil he nex innovion occurs, by some oher firm. (This period migh be considered s he period over which one hs n effecive pen unil new innovion kes over.) A remrk on he sochsic reserch process Suppose h some rndom even Z is governed by Poisson process, wih known rrivl re u 0. This mens h during some given ime period, of lengh T, he

5 5 number of innovions h is expeced o ke plce per uni of ime is u. We know z ( ut) ut h Pr( Z z) e, wih EZ ut VrZ. Then we know lso h he z! lengh of ime you hve o wi for Z o occur will be exponenilly disribued wih prmeer u which is hen he probbiliy per uni of ime h he even will occur or he flow probbiliy of he even. Le be he rndom de of innovion. The probbiliy for he innovion o occur before T is hen given by P( T): FT ( ). Then for he innovion no o occur r prior o or before T+d consiss of wo disjoin nd independen oucomes: no innovion in [0,T] nd no innovion in [T,T+d]. The ls probbiliy is ud, becuse ud is he probbiliy for he even o occur in he smll inervl of lengh d. If QT ( ) FT ( ) is he probbiliy for no innovion before T, we hve, when muliplying he wo probbiliies: QT ( d) QT ( ) QT ( d) QT ( ) ( ud) uqt ( ). d Le d 0, nd ssume differenibiliy, hen we ge: Q( T) d Q( T) Q( T) uqt ( ) uuse. (ln QT ( )), o give: QT ( ) d QT ( ) c ut ln QT ( ) cut QT ( ) e. Becuse Q(0), we hve QT ( ) e u. Hence: The u probbiliy for he even o occur before is: F( ) Q( ) e, wih u probbiliy densiy F ( ) f ( ) ue. The wiing ime in Poisson process wih prmeer u is exponenilly disribued, wih expeced wiing ime s given by u. *** A some sge during he process of innovions, when is he number of innovions h so fr hve been relized, he moun of reserch underken by n innovor, mus obey some equilibrium, free enry or rbirge condiion. The expeced gin from going for innovion #+ for some person is V w, where w is he wge under hese circumsnces, fer innovion # hs occurred. (This is he wge h is pid in he mnufcuring indusry fer innovion # hs occurred.) In equilibrium we herefore hve: ( A) w V A he mrgin, person is indifferen beween llocing his lbour beween he wo civiies. The reurn from working in he mnufcuring secor, producing he inermedie good for he finl-good-secor, mus in equilibrium be equl o he

6 6 expeced reurn from doing reserch, which, wih some probbiliy, mkes me monopolis for some uncerin period of ime. Hence, he curren wge hs o be blnced gins he discouned expeced reurn from using lbour in reserch o become he innovor #(+). In equilibrium his wge mus be equl o he discouned expeced mrginl gin from obining he prize (or monopoly ren) V ; muliplied by which is he probbiliy per uni of ime for successful innovion. Ech innovion crees monopoly for he innovor when selling x o he finl good secor, s emporry monopolis. An innovor blnces his or her mrginl reurn in he wo compeing civiies. The wo opions mus hve equl expeced mrginl reurn. If I win he rce, I will be monopolis unil new innovion desroys my monopoly posiion. How cn we clcule he vlue of innovion #+? This depends on he lengh of he period over which I cn rep he profi flow from his innovion. This lengh is rndom nd ffeced by he ouside (or subsequen) firms rying o become he new innovor: For fixed monopoly period 0,, nd some ime-invrin discoun re r, he presen discouned vlue of he profi flows is given by r r e v ( ) e d. r 0 The poin in ime when new innovion kes plce,, is no fixed bu rndom n vrible, being exponenilly disribued ( n ) ; i.e. wih densiyn e. (To ny fesible oucome of he lengh of he monopoly period; (0, ), we ch posiive densiy, which is depending on he subsequen choice of reserch effor by ouside firms. Fuure innovions underken by ouside firms will desroy my monopoly posiion.) We hen hve when V is he expeced presen discouned vlue of being innovor #(+), hving pen so s o opere s emporry monopolis:

7 7 n ( ) ( ) r n r n V v n e d e e d 0 0 n n ( rn) e e d r n 0 0 n n n 0 0 n n ( rn) e e r n r n 0 0 r n r r n r r n r r r n r n From which we ge: n V ( r n ) V rv n V V r r (*) (**) The second pr, (*), sys h ech poin in ime, s long s he pen is cive, he expeced reurn of hving he pen (like reurn on some sse or cpil objec) is equl he curren monopoly profi flow, minus he expeced cpil loss from being overhrown by new innovor. The new innovion occurs wih probbiliy n ; or wih probbiliy n he innovor #(+) will be replced by subsequen innovion; #(+2); so n V is he expeced cpil loss per uni ime of being overhrown by #(+2). The erm (**) shows h he presen expeced vlue of he monopoly posiion is he nnuiy of n infinie srem of he monopoly profi minus he nnuiy of he cpil loss due o new innovion. The equliy V shows he expeced presen vlue of hving r n monopoly posiion, where he discoun fcor is being reduced due o r n compeiion from subsequen innovions. The fuure ges lower weigh. The denominor in cn be inerpreed s n obsolescence-djused ineres r n re, nd will show he impc of creive desrucion. The more reserch is expeced o follow he innovion #(+), he shorer is he likely durion of he monopoly period, which will reduce he vlue of innovion. The creive desrucion elemen is cpured by replcing n old monopolis by new one, desroying he ren h moived he previous innovor or previous creion.

8 8 ii) The sge fer innovion #. The monopolis wih innovion #, will sell he inpu x o he compeiive finlgood or consumpion good indusry s monopolis, fcing demnd funcion derived from he decision-mking problem in he compeiive indusry. We hen hve: The finl good secor is compeiive; wih price se equl o one. If pying p per uni of x used s inpu in he mnufcuring secor, where p is mesured in unis of he finl good, hey will choose x so s o: Mx Ax px; wih firs-order condiion Ax p, which is he inverse demnd funcion fcing he supplier of he inermedie good, s given by vlue mrginl produciviy. The supplier of his inermedie good or inpu is he emprry or preliminry winner of he innovion cones; wih rndom lengh of he monopoly period, selling his or her oupu used s inpu in he producion of he finl good, s monopolis. If wge per uni of lbour fer innovion #, is w, hen innovor #, wih emporry monopoly, will solve he following problem: He or she cn sell he innovion or inermedie good s monopolis, price p( x) Ax s long s he monopoly posiion is no overhrown. When using m x, we hve : Mx x p( x) xwxax wx. 2 2 We hen ge: w Ax p w x Ax 2 2 x Arg mx x Ax wx : w w where : is he produciviydjused wge, nd wih wx. Boh x nd will be declining in. A A 2 We hve x : X( ) dx, wih 0 d. Le A X( ). We inser nd ge: 2 2 ( ) A( ) A( ) : A ( ) d. We esily see h 0, d where X( ) is lbour used in he producion of he inermedie good s funcion of he produciviy-djused wge.

9 9 iii) Equilibrium We now hve wo equions h chrcerise he equilibrium, when using h A ga : ( L) L X ( ) n w A ( ) g( ) ( A) w : r n A A r n A r n r n Consider sedy-se or blnced growh equilibrium; wih SS ( A) g X( ) g ( ) r nˆ r nˆ SS ( L) L nˆx( ) X( ) L nˆ nd n nˆ : ( A ) SS ( L ) SS ˆn L n Then: r g ( L nˆ ) g L SS ( A) nˆ nglr (,,,, ) 0 r nˆ g Assume h he higher is ˆn, he higher is he expeced growh re in his economy when growh iself is sochsic. r g L From nˆ nglr (,,,, ), we cn derive relion beween expeced g growh nd he prmeers of he model:

10 0 A higher discoun re r will reduce growh. The vlue of fuure monopoly ren will hen go down; hence he incenive o do reserch is wekened. A higher pool of skilled lbour will increse expeced growh, s he wge or opporuniy cos of doing reserch will go down; nd lso he fuure srem of profi will be higher. This clls for insiuionl rrngemens wih good educionl sysem providing sound knowledge bou growh-promoing subjecs; like mhemics, physics, chemisry, biology, medicine. A more producive reserch echnology (higher ) will hve posiive impc on expeced growh. A higher will increse he role of creive desrucion ( lower vlue of he pen), which, ce. pr., should hve negive impc on expeced growh. However, in in opposie direcion, here is he impc on he mrginl cos of producion. The ler effec domines. An increse in he size of he innovion (g goes up), will increse he nex period s monopoly profi; sronger incenive o do reserch. (We hve r g r nˆ L g( ) L L will be incresing in g.) Require good g g( ) pen sysem nd inellecul propery righs. The bsolue vlue of elsiciy of demnd in he finl good secor using he inermedie good sold by he monopolis, is Elx : p. If higher compeiion mens more elsic demnd curve fcing he monopolis, hen more compeiive environmen should be ssocied wih pproching one. p We hve from p( x) Ax A, h x ( ) ( ), so h A p px ( A) p kp kp. The closer is one, he more elsic is demnd, or he higher is he degree of compeiion. ( A( ) x becomes smller s goes o one.) Produc mrke compeiion is bd for R&D, nd hence for growh. More produc mrke compeiion will reduce fuure monopoly rens h cn be reped by successful innovor; hence he incenive o underke R&D is wekened.

4.8 Improper Integrals

4.8 Improper Integrals 4.8 Improper Inegrls Well you ve mde i hrough ll he inegrion echniques. Congrs! Unforunely for us, we sill need o cover one more inegrl. They re clled Improper Inegrls. A his poin, we ve only del wih inegrls

More information

3. Renewal Limit Theorems

3. Renewal Limit Theorems Virul Lborories > 14. Renewl Processes > 1 2 3 3. Renewl Limi Theorems In he inroducion o renewl processes, we noed h he rrivl ime process nd he couning process re inverses, in sens The rrivl ime process

More information

e t dt e t dt = lim e t dt T (1 e T ) = 1

e t dt e t dt = lim e t dt T (1 e T ) = 1 Improper Inegrls There re wo ypes of improper inegrls - hose wih infinie limis of inegrion, nd hose wih inegrnds h pproch some poin wihin he limis of inegrion. Firs we will consider inegrls wih infinie

More information

Motion. Part 2: Constant Acceleration. Acceleration. October Lab Physics. Ms. Levine 1. Acceleration. Acceleration. Units for Acceleration.

Motion. Part 2: Constant Acceleration. Acceleration. October Lab Physics. Ms. Levine 1. Acceleration. Acceleration. Units for Acceleration. Moion Accelerion Pr : Consn Accelerion Accelerion Accelerion Accelerion is he re of chnge of velociy. = v - vo = Δv Δ ccelerion = = v - vo chnge of velociy elpsed ime Accelerion is vecor, lhough in one-dimensionl

More information

The neoclassical version of the Johansen-vintage (putty-clay) growth model

The neoclassical version of the Johansen-vintage (putty-clay) growth model Jon Vislie Sepemer 2 Lecure noes ECON 435 The neoclssicl version of he Johnsen-vinge (puy-cly) growh model The vrious elemens we hve considered during he lecures cn e colleced so s o give us he following

More information

September 20 Homework Solutions

September 20 Homework Solutions College of Engineering nd Compuer Science Mechnicl Engineering Deprmen Mechnicl Engineering A Seminr in Engineering Anlysis Fll 7 Number 66 Insrucor: Lrry Creo Sepember Homework Soluions Find he specrum

More information

A new model for limit order book dynamics

A new model for limit order book dynamics Anewmodelforlimiorderbookdynmics JeffreyR.Russell UniversiyofChicgo,GrdueSchoolofBusiness TejinKim UniversiyofChicgo,DeprmenofSisics Absrc:Thispperproposesnewmodelforlimiorderbookdynmics.Thelimiorderbookconsiss

More information

0 for t < 0 1 for t > 0

0 for t < 0 1 for t > 0 8.0 Sep nd del funcions Auhor: Jeremy Orloff The uni Sep Funcion We define he uni sep funcion by u() = 0 for < 0 for > 0 I is clled he uni sep funcion becuse i kes uni sep = 0. I is someimes clled he Heviside

More information

Economic Growth & Development: Part 4 Vertical Innovation Models. By Kiminori Matsuyama. Updated on , 11:01:54 AM

Economic Growth & Development: Part 4 Vertical Innovation Models. By Kiminori Matsuyama. Updated on , 11:01:54 AM Economic Growh & Developmen: Par 4 Verical Innovaion Models By Kiminori Masuyama Updaed on 20-04-4 :0:54 AM Page of 7 Inroducion In he previous models R&D develops producs ha are new ie imperfec subsiues

More information

Lecture Notes 3: Quantitative Analysis in DSGE Models: New Keynesian Model

Lecture Notes 3: Quantitative Analysis in DSGE Models: New Keynesian Model Lecure Noes 3: Quaniaive Analysis in DSGE Models: New Keynesian Model Zhiwei Xu, Email: xuzhiwei@sju.edu.cn The moneary policy plays lile role in he basic moneary model wihou price sickiness. We now urn

More information

f t f a f x dx By Lin McMullin f x dx= f b f a. 2

f t f a f x dx By Lin McMullin f x dx= f b f a. 2 Accumulion: Thoughs On () By Lin McMullin f f f d = + The gols of he AP* Clculus progrm include he semen, Sudens should undersnd he definie inegrl s he ne ccumulion of chnge. 1 The Topicl Ouline includes

More information

1.0 Electrical Systems

1.0 Electrical Systems . Elecricl Sysems The ypes of dynmicl sysems we will e sudying cn e modeled in erms of lgeric equions, differenil equions, or inegrl equions. We will egin y looking fmilir mhemicl models of idel resisors,

More information

A 1.3 m 2.5 m 2.8 m. x = m m = 8400 m. y = 4900 m 3200 m = 1700 m

A 1.3 m 2.5 m 2.8 m. x = m m = 8400 m. y = 4900 m 3200 m = 1700 m PHYS : Soluions o Chper 3 Home Work. SSM REASONING The displcemen is ecor drwn from he iniil posiion o he finl posiion. The mgniude of he displcemen is he shores disnce beween he posiions. Noe h i is onl

More information

The solution is often represented as a vector: 2xI + 4X2 + 2X3 + 4X4 + 2X5 = 4 2xI + 4X2 + 3X3 + 3X4 + 3X5 = 4. 3xI + 6X2 + 6X3 + 3X4 + 6X5 = 6.

The solution is often represented as a vector: 2xI + 4X2 + 2X3 + 4X4 + 2X5 = 4 2xI + 4X2 + 3X3 + 3X4 + 3X5 = 4. 3xI + 6X2 + 6X3 + 3X4 + 6X5 = 6. [~ o o :- o o ill] i 1. Mrices, Vecors, nd Guss-Jordn Eliminion 1 x y = = - z= The soluion is ofen represened s vecor: n his exmple, he process of eliminion works very smoohly. We cn elimine ll enries

More information

T-Match: Matching Techniques For Driving Yagi-Uda Antennas: T-Match. 2a s. Z in. (Sections 9.5 & 9.7 of Balanis)

T-Match: Matching Techniques For Driving Yagi-Uda Antennas: T-Match. 2a s. Z in. (Sections 9.5 & 9.7 of Balanis) 3/0/018 _mch.doc Pge 1 of 6 T-Mch: Mching Techniques For Driving Ygi-Ud Anenns: T-Mch (Secions 9.5 & 9.7 of Blnis) l s l / l / in The T-Mch is shun-mching echnique h cn be used o feed he driven elemen

More information

Chapter 2: Evaluative Feedback

Chapter 2: Evaluative Feedback Chper 2: Evluive Feedbck Evluing cions vs. insrucing by giving correc cions Pure evluive feedbck depends olly on he cion ken. Pure insrucive feedbck depends no ll on he cion ken. Supervised lerning is

More information

Contraction Mapping Principle Approach to Differential Equations

Contraction Mapping Principle Approach to Differential Equations epl Journl of Science echnology 0 (009) 49-53 Conrcion pping Principle pproch o Differenil Equions Bishnu P. Dhungn Deprmen of hemics, hendr Rn Cmpus ribhuvn Universiy, Khmu epl bsrc Using n eension of

More information

ENGR 1990 Engineering Mathematics The Integral of a Function as a Function

ENGR 1990 Engineering Mathematics The Integral of a Function as a Function ENGR 1990 Engineering Mhemics The Inegrl of Funcion s Funcion Previously, we lerned how o esime he inegrl of funcion f( ) over some inervl y dding he res of finie se of rpezoids h represen he re under

More information

Final Exam Advanced Macroeconomics I

Final Exam Advanced Macroeconomics I Advanced Macroeconomics I WS 00/ Final Exam Advanced Macroeconomics I February 8, 0 Quesion (5%) An economy produces oupu according o α α Y = K (AL) of which a fracion s is invesed. echnology A is exogenous

More information

S Radio transmission and network access Exercise 1-2

S Radio transmission and network access Exercise 1-2 S-7.330 Rdio rnsmission nd nework ccess Exercise 1 - P1 In four-symbol digil sysem wih eqully probble symbols he pulses in he figure re used in rnsmission over AWGN-chnnel. s () s () s () s () 1 3 4 )

More information

A Kalman filtering simulation

A Kalman filtering simulation A Klmn filering simulion The performnce of Klmn filering hs been esed on he bsis of wo differen dynmicl models, ssuming eiher moion wih consn elociy or wih consn ccelerion. The former is epeced o beer

More information

Minimum Squared Error

Minimum Squared Error Minimum Squred Error LDF: Minimum Squred-Error Procedures Ide: conver o esier nd eer undersood prolem Percepron y i > for ll smples y i solve sysem of liner inequliies MSE procedure y i = i for ll smples

More information

Probability, Estimators, and Stationarity

Probability, Estimators, and Stationarity Chper Probbiliy, Esimors, nd Sionriy Consider signl genered by dynmicl process, R, R. Considering s funcion of ime, we re opering in he ime domin. A fundmenl wy o chrcerize he dynmics using he ime domin

More information

Minimum Squared Error

Minimum Squared Error Minimum Squred Error LDF: Minimum Squred-Error Procedures Ide: conver o esier nd eer undersood prolem Percepron y i > 0 for ll smples y i solve sysem of liner inequliies MSE procedure y i i for ll smples

More information

REAL ANALYSIS I HOMEWORK 3. Chapter 1

REAL ANALYSIS I HOMEWORK 3. Chapter 1 REAL ANALYSIS I HOMEWORK 3 CİHAN BAHRAN The quesions re from Sein nd Shkrchi s e. Chper 1 18. Prove he following sserion: Every mesurble funcion is he limi.e. of sequence of coninuous funcions. We firs

More information

Average & instantaneous velocity and acceleration Motion with constant acceleration

Average & instantaneous velocity and acceleration Motion with constant acceleration Physics 7: Lecure Reminders Discussion nd Lb secions sr meeing ne week Fill ou Pink dd/drop form if you need o swich o differen secion h is FULL. Do i TODAY. Homework Ch. : 5, 7,, 3,, nd 6 Ch.: 6,, 3 Submission

More information

2D Motion WS. A horizontally launched projectile s initial vertical velocity is zero. Solve the following problems with this information.

2D Motion WS. A horizontally launched projectile s initial vertical velocity is zero. Solve the following problems with this information. Nme D Moion WS The equions of moion h rele o projeciles were discussed in he Projecile Moion Anlsis Acii. ou found h projecile moes wih consn eloci in he horizonl direcion nd consn ccelerion in he ericl

More information

Macroeconomic Theory Ph.D. Qualifying Examination Fall 2005 ANSWER EACH PART IN A SEPARATE BLUE BOOK. PART ONE: ANSWER IN BOOK 1 WEIGHT 1/3

Macroeconomic Theory Ph.D. Qualifying Examination Fall 2005 ANSWER EACH PART IN A SEPARATE BLUE BOOK. PART ONE: ANSWER IN BOOK 1 WEIGHT 1/3 Macroeconomic Theory Ph.D. Qualifying Examinaion Fall 2005 Comprehensive Examinaion UCLA Dep. of Economics You have 4 hours o complee he exam. There are hree pars o he exam. Answer all pars. Each par has

More information

5.1-The Initial-Value Problems For Ordinary Differential Equations

5.1-The Initial-Value Problems For Ordinary Differential Equations 5.-The Iniil-Vlue Problems For Ordinry Differenil Equions Consider solving iniil-vlue problems for ordinry differenil equions: (*) y f, y, b, y. If we know he generl soluion y of he ordinry differenil

More information

Neural assembly binding in linguistic representation

Neural assembly binding in linguistic representation Neurl ssembly binding in linguisic represenion Frnk vn der Velde & Mrc de Kmps Cogniive Psychology Uni, Universiy of Leiden, Wssenrseweg 52, 2333 AK Leiden, The Neherlnds, vdvelde@fsw.leidenuniv.nl Absrc.

More information

INTEGRALS. Exercise 1. Let f : [a, b] R be bounded, and let P and Q be partitions of [a, b]. Prove that if P Q then U(P ) U(Q) and L(P ) L(Q).

INTEGRALS. Exercise 1. Let f : [a, b] R be bounded, and let P and Q be partitions of [a, b]. Prove that if P Q then U(P ) U(Q) and L(P ) L(Q). INTEGRALS JOHN QUIGG Eercise. Le f : [, b] R be bounded, nd le P nd Q be priions of [, b]. Prove h if P Q hen U(P ) U(Q) nd L(P ) L(Q). Soluion: Le P = {,..., n }. Since Q is obined from P by dding finiely

More information

Intermediate Macro In-Class Problems

Intermediate Macro In-Class Problems Inermediae Macro In-Class Problems Exploring Romer Model June 14, 016 Today we will explore he mechanisms of he simply Romer model by exploring how economies described by his model would reac o exogenous

More information

( ) ( ) ( ) ( ) ( ) ( y )

( ) ( ) ( ) ( ) ( ) ( y ) 8. Lengh of Plne Curve The mos fmous heorem in ll of mhemics is he Pyhgoren Theorem. I s formulion s he disnce formul is used o find he lenghs of line segmens in he coordine plne. In his secion you ll

More information

Seminar 4: Hotelling 2

Seminar 4: Hotelling 2 Seminar 4: Hoelling 2 November 3, 211 1 Exercise Par 1 Iso-elasic demand A non renewable resource of a known sock S can be exraced a zero cos. Demand for he resource is of he form: D(p ) = p ε ε > A a

More information

22.615, MHD Theory of Fusion Systems Prof. Freidberg Lecture 9: The High Beta Tokamak

22.615, MHD Theory of Fusion Systems Prof. Freidberg Lecture 9: The High Beta Tokamak .65, MHD Theory of Fusion Sysems Prof. Freidberg Lecure 9: The High e Tokmk Summry of he Properies of n Ohmic Tokmk. Advnges:. good euilibrium (smll shif) b. good sbiliy ( ) c. good confinemen ( τ nr )

More information

Properties of Logarithms. Solving Exponential and Logarithmic Equations. Properties of Logarithms. Properties of Logarithms. ( x)

Properties of Logarithms. Solving Exponential and Logarithmic Equations. Properties of Logarithms. Properties of Logarithms. ( x) Properies of Logrihms Solving Eponenil nd Logrihmic Equions Properies of Logrihms Produc Rule ( ) log mn = log m + log n ( ) log = log + log Properies of Logrihms Quoien Rule log m = logm logn n log7 =

More information

Tax Audit and Vertical Externalities

Tax Audit and Vertical Externalities T Audi nd Vericl Eernliies Hidey Ko Misuyoshi Yngihr Ngoy Keizi Universiy Ngoy Universiy 1. Inroducion The vericl fiscl eernliies rise when he differen levels of governmens, such s he federl nd se governmens,

More information

TIMELINESS, ACCURACY, AND RELEVANCE IN DYNAMIC INCENTIVE CONTRACTS

TIMELINESS, ACCURACY, AND RELEVANCE IN DYNAMIC INCENTIVE CONTRACTS TIMELINESS, ACCURACY, AND RELEVANCE IN DYNAMIC INCENTIVE CONTRACTS by Peer O. Chrisensen Universiy of Souhern Denmrk Odense, Denmrk Gerld A. Felhm Universiy of Briish Columbi Vncouver, Cnd Chrisin Hofmnn

More information

3.1.3 INTRODUCTION TO DYNAMIC OPTIMIZATION: DISCRETE TIME PROBLEMS. A. The Hamiltonian and First-Order Conditions in a Finite Time Horizon

3.1.3 INTRODUCTION TO DYNAMIC OPTIMIZATION: DISCRETE TIME PROBLEMS. A. The Hamiltonian and First-Order Conditions in a Finite Time Horizon 3..3 INRODUCION O DYNAMIC OPIMIZAION: DISCREE IME PROBLEMS A. he Hamilonian and Firs-Order Condiions in a Finie ime Horizon Define a new funcion, he Hamilonian funcion, H. H he change in he oal value of

More information

A Time Truncated Improved Group Sampling Plans for Rayleigh and Log - Logistic Distributions

A Time Truncated Improved Group Sampling Plans for Rayleigh and Log - Logistic Distributions ISSNOnline : 39-8753 ISSN Prin : 347-67 An ISO 397: 7 Cerified Orgnizion Vol. 5, Issue 5, My 6 A Time Trunced Improved Group Smpling Plns for Ryleigh nd og - ogisic Disribuions P.Kvipriy, A.R. Sudmni Rmswmy

More information

(b) 10 yr. (b) 13 m. 1.6 m s, m s m s (c) 13.1 s. 32. (a) 20.0 s (b) No, the minimum distance to stop = 1.00 km. 1.

(b) 10 yr. (b) 13 m. 1.6 m s, m s m s (c) 13.1 s. 32. (a) 20.0 s (b) No, the minimum distance to stop = 1.00 km. 1. Answers o Een Numbered Problems Chper. () 7 m s, 6 m s (b) 8 5 yr 4.. m ih 6. () 5. m s (b).5 m s (c).5 m s (d) 3.33 m s (e) 8. ().3 min (b) 64 mi..3 h. ().3 s (b) 3 m 4..8 mi wes of he flgpole 6. (b)

More information

UNIVERSITY OF OSLO DEPARTMENT OF ECONOMICS

UNIVERSITY OF OSLO DEPARTMENT OF ECONOMICS UNIVERSITY OF OSLO DEPARTMENT OF ECONOMICS Exam: ECON4325 Moneary Policy Dae of exam: Tuesday, May 24, 206 Grades are given: June 4, 206 Time for exam: 2.30 p.m. 5.30 p.m. The problem se covers 5 pages

More information

ANSWERS TO EVEN NUMBERED EXERCISES IN CHAPTER 2

ANSWERS TO EVEN NUMBERED EXERCISES IN CHAPTER 2 ANSWERS TO EVEN NUMBERED EXERCISES IN CHAPTER Seion Eerise -: Coninuiy of he uiliy funion Le λ ( ) be he monooni uiliy funion defined in he proof of eisene of uiliy funion If his funion is oninuous y hen

More information

Magnetostatics Bar Magnet. Magnetostatics Oersted s Experiment

Magnetostatics Bar Magnet. Magnetostatics Oersted s Experiment Mgneosics Br Mgne As fr bck s 4500 yers go, he Chinese discovered h cerin ypes of iron ore could rc ech oher nd cerin mels. Iron filings "mp" of br mgne s field Crefully suspended slivers of his mel were

More information

Final Exam. Tuesday, December hours

Final Exam. Tuesday, December hours San Francisco Sae Universiy Michael Bar ECON 560 Fall 03 Final Exam Tuesday, December 7 hours Name: Insrucions. This is closed book, closed noes exam.. No calculaors of any kind are allowed. 3. Show all

More information

PHYSICS 1210 Exam 1 University of Wyoming 14 February points

PHYSICS 1210 Exam 1 University of Wyoming 14 February points PHYSICS 1210 Em 1 Uniersiy of Wyoming 14 Februry 2013 150 poins This es is open-noe nd closed-book. Clculors re permied bu compuers re no. No collborion, consulion, or communicion wih oher people (oher

More information

Convergence of Singular Integral Operators in Weighted Lebesgue Spaces

Convergence of Singular Integral Operators in Weighted Lebesgue Spaces EUROPEAN JOURNAL OF PURE AND APPLIED MATHEMATICS Vol. 10, No. 2, 2017, 335-347 ISSN 1307-5543 www.ejpm.com Published by New York Business Globl Convergence of Singulr Inegrl Operors in Weighed Lebesgue

More information

Lecture Notes 5: Investment

Lecture Notes 5: Investment Lecure Noes 5: Invesmen Zhiwei Xu (xuzhiwei@sju.edu.cn) Invesmen decisions made by rms are one of he mos imporan behaviors in he economy. As he invesmen deermines how he capials accumulae along he ime,

More information

Phys 110. Answers to even numbered problems on Midterm Map

Phys 110. Answers to even numbered problems on Midterm Map Phys Answers o een numbered problems on Miderm Mp. REASONING The word per indices rio, so.35 mm per dy mens.35 mm/d, which is o be epressed s re in f/cenury. These unis differ from he gien unis in boh

More information

Economics 8105 Macroeconomic Theory Recitation 6

Economics 8105 Macroeconomic Theory Recitation 6 Economics 8105 Macroeconomic Theory Reciaion 6 Conor Ryan Ocober 11h, 2016 Ouline: Opimal Taxaion wih Governmen Invesmen 1 Governmen Expendiure in Producion In hese noes we will examine a model in which

More information

An integral having either an infinite limit of integration or an unbounded integrand is called improper. Here are two examples.

An integral having either an infinite limit of integration or an unbounded integrand is called improper. Here are two examples. Improper Inegrls To his poin we hve only considered inegrls f(x) wih he is of inegrion nd b finie nd he inegrnd f(x) bounded (nd in fc coninuous excep possibly for finiely mny jump disconinuiies) An inegrl

More information

Reinforcement learning

Reinforcement learning CS 75 Mchine Lening Lecue b einfocemen lening Milos Huskech milos@cs.pi.edu 539 Senno Sque einfocemen lening We wn o len conol policy: : X A We see emples of bu oupus e no given Insed of we ge feedbck

More information

A Dynamic Model of Economic Fluctuations

A Dynamic Model of Economic Fluctuations CHAPTER 15 A Dynamic Model of Economic Flucuaions Modified for ECON 2204 by Bob Murphy 2016 Worh Publishers, all righs reserved IN THIS CHAPTER, OU WILL LEARN: how o incorporae dynamics ino he AD-AS model

More information

This document was generated at 7:34 PM, 07/27/09 Copyright 2009 Richard T. Woodward

This document was generated at 7:34 PM, 07/27/09 Copyright 2009 Richard T. Woodward his documen was generaed a 7:34 PM, 07/27/09 Copyrigh 2009 Richard. Woodward 15. Bang-bang and mos rapid approach problems AGEC 637 - Summer 2009 here are some problems for which he opimal pah does no

More information

Macroeconomics I, UPF Professor Antonio Ciccone SOLUTIONS PROBLEM SET 1

Macroeconomics I, UPF Professor Antonio Ciccone SOLUTIONS PROBLEM SET 1 Macroeconomics I, UPF Professor Anonio Ciccone SOUTIONS PROBEM SET. (from Romer Advanced Macroeconomics Chaper ) Basic properies of growh raes which will be used over and over again. Use he fac ha he growh

More information

CBSE 2014 ANNUAL EXAMINATION ALL INDIA

CBSE 2014 ANNUAL EXAMINATION ALL INDIA CBSE ANNUAL EXAMINATION ALL INDIA SET Wih Complee Eplnions M Mrks : SECTION A Q If R = {(, y) : + y = 8} is relion on N, wrie he rnge of R Sol Since + y = 8 h implies, y = (8 ) R = {(, ), (, ), (6, )}

More information

( ) a system of differential equations with continuous parametrization ( T = R + These look like, respectively:

( ) a system of differential equations with continuous parametrization ( T = R + These look like, respectively: XIII. DIFFERENCE AND DIFFERENTIAL EQUATIONS Ofen funcions, or a sysem of funcion, are paramerized in erms of some variable, usually denoed as and inerpreed as ime. The variable is wrien as a funcion of

More information

Physics 2A HW #3 Solutions

Physics 2A HW #3 Solutions Chper 3 Focus on Conceps: 3, 4, 6, 9 Problems: 9, 9, 3, 41, 66, 7, 75, 77 Phsics A HW #3 Soluions Focus On Conceps 3-3 (c) The ccelerion due o grvi is he sme for boh blls, despie he fc h he hve differen

More information

SCHOOL OF ECONOMICS Adelaide University SA 5005 AUSTRALIA

SCHOOL OF ECONOMICS Adelaide University SA 5005 AUSTRALIA Open Economy chumpeerian Growh Raul A. Barreo and Kaori Kobayashi Working Paper -9 CHOOL OF ECONOMIC Adelaide Universiy A 55 AUTRALIA IN 444 8866 Open Economy chumpeerian Growh by Raul A. Barreo ** and

More information

International Transmission of Investment-Speci c Technology Shocks with Incomplete Asset Markets. Draft Copy - Not for Circulation or Citation

International Transmission of Investment-Speci c Technology Shocks with Incomplete Asset Markets. Draft Copy - Not for Circulation or Citation Inernionl Trnsmission of Invesmen-Speci c Technology Shocks wih Incomplee sse Mrkes Drf Copy - No for Circulion or Ciion Enrique Mrínez-Grcí y ederl Reserve Bnk of Dlls irs Drf: Sepember, Curren Drf: ebrury,

More information

Solutions Problem Set 3 Macro II (14.452)

Solutions Problem Set 3 Macro II (14.452) Soluions Problem Se 3 Macro II (14.452) Francisco A. Gallego 04/27/2005 1 Q heory of invesmen in coninuous ime and no uncerainy Consider he in nie horizon model of a rm facing adjusmen coss o invesmen.

More information

Forms of Energy. Mass = Energy. Page 1. SPH4U: Introduction to Work. Work & Energy. Particle Physics:

Forms of Energy. Mass = Energy. Page 1. SPH4U: Introduction to Work. Work & Energy. Particle Physics: SPH4U: Inroducion o ork ork & Energy ork & Energy Discussion Definiion Do Produc ork of consn force ork/kineic energy heore ork of uliple consn forces Coens One of he os iporn conceps in physics Alernive

More information

graph of unit step function t

graph of unit step function t .5 Piecewie coninuou forcing funcion...e.g. urning he forcing on nd off. The following Lplce rnform meril i ueful in yem where we urn forcing funcion on nd off, nd when we hve righ hnd ide "forcing funcion"

More information

= ( ) ) or a system of differential equations with continuous parametrization (T = R

= ( ) ) or a system of differential equations with continuous parametrization (T = R XIII. DIFFERENCE AND DIFFERENTIAL EQUATIONS Ofen funcions, or a sysem of funcion, are paramerized in erms of some variable, usually denoed as and inerpreed as ime. The variable is wrien as a funcion of

More information

Solutions to Assignment 1

Solutions to Assignment 1 MA 2326 Differenial Equaions Insrucor: Peronela Radu Friday, February 8, 203 Soluions o Assignmen. Find he general soluions of he following ODEs: (a) 2 x = an x Soluion: I is a separable equaion as we

More information

ECE Microwave Engineering

ECE Microwave Engineering EE 537-635 Microwve Engineering Adped from noes y Prof. Jeffery T. Willims Fll 8 Prof. Dvid R. Jcson Dep. of EE Noes Wveguiding Srucures Pr 7: Trnsverse Equivlen Newor (N) Wveguide Trnsmission Line Model

More information

ECE Microwave Engineering. Fall Prof. David R. Jackson Dept. of ECE. Notes 10. Waveguides Part 7: Transverse Equivalent Network (TEN)

ECE Microwave Engineering. Fall Prof. David R. Jackson Dept. of ECE. Notes 10. Waveguides Part 7: Transverse Equivalent Network (TEN) EE 537-635 Microwve Engineering Fll 7 Prof. Dvid R. Jcson Dep. of EE Noes Wveguides Pr 7: Trnsverse Equivlen Newor (N) Wveguide Trnsmission Line Model Our gol is o come up wih rnsmission line model for

More information

LAPLACE TRANSFORMS. 1. Basic transforms

LAPLACE TRANSFORMS. 1. Basic transforms LAPLACE TRANSFORMS. Bic rnform In hi coure, Lplce Trnform will be inroduced nd heir properie exmined; ble of common rnform will be buil up; nd rnform will be ued o olve ome dierenil equion by rnforming

More information

Problem Set on Differential Equations

Problem Set on Differential Equations Problem Se on Differenial Equaions 1. Solve he following differenial equaions (a) x () = e x (), x () = 3/ 4. (b) x () = e x (), x (1) =. (c) xe () = + (1 x ()) e, x () =.. (An asse marke model). Le p()

More information

SZG Macro 2011 Lecture 3: Dynamic Programming. SZG macro 2011 lecture 3 1

SZG Macro 2011 Lecture 3: Dynamic Programming. SZG macro 2011 lecture 3 1 SZG Macro 2011 Lecure 3: Dynamic Programming SZG macro 2011 lecure 3 1 Background Our previous discussion of opimal consumpion over ime and of opimal capial accumulaion sugges sudying he general decision

More information

BrainDrainandFiscalCompetition: a Theoretical Model for Europe

BrainDrainandFiscalCompetition: a Theoretical Model for Europe BrinDrinndFisclCompeiion: Theoreicl Model for Europe Pierpolo Ginnoccolo Absrc In his pper we sudy Brin Drin (BD) nd Fiscl Compeiion (FC) in unified frmework for he Europen Union (EU) specific conex. Poenil

More information

PARABOLA. moves such that PM. = e (constant > 0) (eccentricity) then locus of P is called a conic. or conic section.

PARABOLA. moves such that PM. = e (constant > 0) (eccentricity) then locus of P is called a conic. or conic section. wwwskshieducioncom PARABOLA Le S be given fixed poin (focus) nd le l be given fixed line (Direcrix) Le SP nd PM be he disnce of vrible poin P o he focus nd direcrix respecively nd P SP moves such h PM

More information

E β t log (C t ) + M t M t 1. = Y t + B t 1 P t. B t 0 (3) v t = P tc t M t Question 1. Find the FOC s for an optimum in the agent s problem.

E β t log (C t ) + M t M t 1. = Y t + B t 1 P t. B t 0 (3) v t = P tc t M t Question 1. Find the FOC s for an optimum in the agent s problem. Noes, M. Krause.. Problem Se 9: Exercise on FTPL Same model as in paper and lecure, only ha one-period govenmen bonds are replaced by consols, which are bonds ha pay one dollar forever. I has curren marke

More information

Chapter Direct Method of Interpolation

Chapter Direct Method of Interpolation Chper 5. Direc Mehod of Inerpolion Afer reding his chper, you should be ble o:. pply he direc mehod of inerpolion,. sole problems using he direc mehod of inerpolion, nd. use he direc mehod inerpolns o

More information

An object moving with speed v around a point at distance r, has an angular velocity. m/s m

An object moving with speed v around a point at distance r, has an angular velocity. m/s m Roion The mosphere roes wih he erh n moions wihin he mosphere clerly follow cure phs (cyclones, nicyclones, hurricnes, ornoes ec.) We nee o epress roion quniiely. For soli objec or ny mss h oes no isor

More information

Cooperative Ph.D. Program in School of Economic Sciences and Finance QUALIFYING EXAMINATION IN MACROECONOMICS. August 8, :45 a.m. to 1:00 p.m.

Cooperative Ph.D. Program in School of Economic Sciences and Finance QUALIFYING EXAMINATION IN MACROECONOMICS. August 8, :45 a.m. to 1:00 p.m. Cooperaive Ph.D. Program in School of Economic Sciences and Finance QUALIFYING EXAMINATION IN MACROECONOMICS Augus 8, 213 8:45 a.m. o 1: p.m. THERE ARE FIVE QUESTIONS ANSWER ANY FOUR OUT OF FIVE PROBLEMS.

More information

3 Motion with constant acceleration: Linear and projectile motion

3 Motion with constant acceleration: Linear and projectile motion 3 Moion wih consn ccelerion: Liner nd projecile moion cons, In he precedin Lecure we he considered moion wih consn ccelerion lon he is: Noe h,, cn be posiie nd neie h leds o rie of behiors. Clerl similr

More information

6. Gas dynamics. Ideal gases Speed of infinitesimal disturbances in still gas

6. Gas dynamics. Ideal gases Speed of infinitesimal disturbances in still gas 6. Gs dynmics Dr. Gergely Krisóf De. of Fluid echnics, BE Februry, 009. Seed of infiniesiml disurbnces in sill gs dv d, dv d, Coninuiy: ( dv)( ) dv omenum r r heorem: ( ( dv) ) d 3443 4 q m dv d dv llievi

More information

FM Applications of Integration 1.Centroid of Area

FM Applications of Integration 1.Centroid of Area FM Applicions of Inegrion.Cenroid of Are The cenroid of ody is is geomeric cenre. For n ojec mde of uniform meril, he cenroid coincides wih he poin which he ody cn e suppored in perfecly lnced se ie, is

More information

SOME USEFUL MATHEMATICS

SOME USEFUL MATHEMATICS SOME USEFU MAHEMAICS SOME USEFU MAHEMAICS I is esy o mesure n preic he behvior of n elecricl circui h conins only c volges n currens. However, mos useful elecricl signls h crry informion vry wih ime. Since

More information

The general Solow model

The general Solow model The general Solow model Back o a closed economy In he basic Solow model: no growh in GDP per worker in seady sae This conradics he empirics for he Wesern world (sylized fac #5) In he general Solow model:

More information

MATH 124 AND 125 FINAL EXAM REVIEW PACKET (Revised spring 2008)

MATH 124 AND 125 FINAL EXAM REVIEW PACKET (Revised spring 2008) MATH 14 AND 15 FINAL EXAM REVIEW PACKET (Revised spring 8) The following quesions cn be used s review for Mh 14/ 15 These quesions re no cul smples of quesions h will pper on he finl em, bu hey will provide

More information

1 Sterile Resources. This is the simplest case of exhaustion of a finite resource. We will use the terminology

1 Sterile Resources. This is the simplest case of exhaustion of a finite resource. We will use the terminology Cmbridge Universiy Press 978--5-8997-7 - Susinble Nurl Resource Mngemen for Scieniss nd Engineers Excerp More informion Serile Resources In his chper, we inroduce he simple concepion of scrce resource,

More information

P441 Analytical Mechanics - I. Coupled Oscillators. c Alex R. Dzierba

P441 Analytical Mechanics - I. Coupled Oscillators. c Alex R. Dzierba Lecure 3 Mondy - Deceber 5, 005 Wrien or ls upded: Deceber 3, 005 P44 Anlyicl Mechnics - I oupled Oscillors c Alex R. Dzierb oupled oscillors - rix echnique In Figure we show n exple of wo coupled oscillors,

More information

Introduction to choice over time

Introduction to choice over time Microeconomic Theory -- Choice over ime Inroducion o choice over ime Individual choice Income and subsiuion effecs 7 Walrasian equilibrium ineres rae 9 pages John Riley Ocober 9, 08 Microeconomic Theory

More information

Policy regimes Theory

Policy regimes Theory Advanced Moneary Theory and Policy EPOS 2012/13 Policy regimes Theory Giovanni Di Barolomeo giovanni.dibarolomeo@uniroma1.i The moneary policy regime The simple model: x = - s (i - p e ) + x e + e D p

More information

Solutions to Problems from Chapter 2

Solutions to Problems from Chapter 2 Soluions o Problems rom Chper Problem. The signls u() :5sgn(), u () :5sgn(), nd u h () :5sgn() re ploed respecively in Figures.,b,c. Noe h u h () :5sgn() :5; 8 including, bu u () :5sgn() is undeined..5

More information

Lecture 19. RBC and Sunspot Equilibria

Lecture 19. RBC and Sunspot Equilibria Lecure 9. RBC and Sunspo Equilibria In radiional RBC models, business cycles are propagaed by real echnological shocks. Thus he main sory comes from he supply side. In 994, a collecion of papers were published

More information

Essential Microeconomics : OPTIMAL CONTROL 1. Consider the following class of optimization problems

Essential Microeconomics : OPTIMAL CONTROL 1. Consider the following class of optimization problems Essenial Microeconomics -- 6.5: OPIMAL CONROL Consider he following class of opimizaion problems Max{ U( k, x) + U+ ( k+ ) k+ k F( k, x)}. { x, k+ } = In he language of conrol heory, he vecor k is he vecor

More information

1. Consider a PSA initially at rest in the beginning of the left-hand end of a long ISS corridor. Assume xo = 0 on the left end of the ISS corridor.

1. Consider a PSA initially at rest in the beginning of the left-hand end of a long ISS corridor. Assume xo = 0 on the left end of the ISS corridor. In Eercise 1, use sndrd recngulr Cresin coordine sysem. Le ime be represened long he horizonl is. Assume ll ccelerions nd decelerions re consn. 1. Consider PSA iniilly res in he beginning of he lef-hnd

More information

Suggested Solutions to Assignment 4 (REQUIRED) Submisson Deadline and Location: March 27 in Class

Suggested Solutions to Assignment 4 (REQUIRED) Submisson Deadline and Location: March 27 in Class EC 450 Advanced Macroeconomics Insrucor: Sharif F Khan Deparmen of Economics Wilfrid Laurier Universiy Winer 2008 Suggesed Soluions o Assignmen 4 (REQUIRED) Submisson Deadline and Locaion: March 27 in

More information

Some Inequalities variations on a common theme Lecture I, UL 2007

Some Inequalities variations on a common theme Lecture I, UL 2007 Some Inequliies vriions on common heme Lecure I, UL 2007 Finbrr Hollnd, Deprmen of Mhemics, Universiy College Cork, fhollnd@uccie; July 2, 2007 Three Problems Problem Assume i, b i, c i, i =, 2, 3 re rel

More information

Designing Information Devices and Systems I Spring 2019 Lecture Notes Note 17

Designing Information Devices and Systems I Spring 2019 Lecture Notes Note 17 EES 16A Designing Informaion Devices and Sysems I Spring 019 Lecure Noes Noe 17 17.1 apaciive ouchscreen In he las noe, we saw ha a capacior consiss of wo pieces on conducive maerial separaed by a nonconducive

More information

Dynamics of Firms and Trade in General Equilibrium. Robert Dekle, Hyeok Jeong and Nobuhiro Kiyotaki USC, KDI School and Princeton

Dynamics of Firms and Trade in General Equilibrium. Robert Dekle, Hyeok Jeong and Nobuhiro Kiyotaki USC, KDI School and Princeton Dynamics of Firms and Trade in General Equilibrium Rober Dekle, Hyeok Jeong and Nobuhiro Kiyoaki USC, KDI School and Princeon real exchange rae.5 2 Figure. Aggregae Exchange Rae Disconnec in Japan 98 99

More information

Think of the Relationship Between Time and Space Again

Think of the Relationship Between Time and Space Again Repor nd Opinion, 1(3),009 hp://wwwsciencepubne sciencepub@gmilcom Think of he Relionship Beween Time nd Spce Agin Yng F-cheng Compny of Ruid Cenre in Xinjing 15 Hongxing Sree, Klmyi, Xingjing 834000,

More information

BU Macro BU Macro Fall 2008, Lecture 4

BU Macro BU Macro Fall 2008, Lecture 4 Dynamic Programming BU Macro 2008 Lecure 4 1 Ouline 1. Cerainy opimizaion problem used o illusrae: a. Resricions on exogenous variables b. Value funcion c. Policy funcion d. The Bellman equaion and an

More information

A new model for solving fuzzy linear fractional programming problem with ranking function

A new model for solving fuzzy linear fractional programming problem with ranking function J. ppl. Res. Ind. Eng. Vol. 4 No. 07 89 96 Journl of pplied Reserch on Indusril Engineering www.journl-prie.com new model for solving fuzzy liner frcionl progrmming prolem wih rning funcion Spn Kumr Ds

More information

How to Prove the Riemann Hypothesis Author: Fayez Fok Al Adeh.

How to Prove the Riemann Hypothesis Author: Fayez Fok Al Adeh. How o Prove he Riemnn Hohesis Auhor: Fez Fok Al Adeh. Presiden of he Srin Cosmologicl Socie P.O.Bo,387,Dmscus,Sri Tels:963--77679,735 Emil:hf@scs-ne.org Commens: 3 ges Subj-Clss: Funcionl nlsis, comle

More information

MTH 146 Class 11 Notes

MTH 146 Class 11 Notes 8.- Are of Surfce of Revoluion MTH 6 Clss Noes Suppose we wish o revolve curve C round n is nd find he surfce re of he resuling solid. Suppose f( ) is nonnegive funcion wih coninuous firs derivive on he

More information

T. J. HOLMES AND T. J. KEHOE INTERNATIONAL TRADE AND PAYMENTS THEORY FALL 2011 EXAMINATION

T. J. HOLMES AND T. J. KEHOE INTERNATIONAL TRADE AND PAYMENTS THEORY FALL 2011 EXAMINATION ECON 841 T. J. HOLMES AND T. J. KEHOE INTERNATIONAL TRADE AND PAYMENTS THEORY FALL 211 EXAMINATION This exam has wo pars. Each par has wo quesions. Please answer one of he wo quesions in each par for a

More information