University of Dundee. A non-perpetual shirking model Chen, Yu-Fu; Zoega, Gylfi. Published in: Economics Letters. DOI: /j.econlet

Size: px
Start display at page:

Download "University of Dundee. A non-perpetual shirking model Chen, Yu-Fu; Zoega, Gylfi. Published in: Economics Letters. DOI: /j.econlet"

Transcription

1 nvrsy of Dund A non-prpual shrkng modl hn, Yu-Fu; Zoga, Gylf Publshd n: conomcs Lrs DOI: /j.conl Publcaon da: 2015 Documn Vrson Pr rvwd vrson Lnk o publcaon n Dscovry Rsarch Poral aon for publshd vrson (APA: hn, Y-F., & Zoga, G. (2015. A non-prpual shrkng modl. conomcs Lrs, 134, DOI: /j.conl Gnral rghs opyrgh and moral rghs for h publcaons mad accssbl n Dscovry Rsarch Poral ar rand by h auhors and/or ohr copyrgh ownrs and s a condon of accssng publcaons ha usrs rcogns and abd by h lgal rqurmns assocad wh hs rghs. srs may download and prn on copy of any publcaon from Dscovry Rsarch Poral for h purpos of prva sudy or rsarch. You may no furhr dsrbu h maral or us for any prof-makng acvy or commrcal gan. You may frly dsrbu h RL dnfyng h publcaon n h publc poral. ak down polcy If you blv ha hs documn brachs copyrgh plas conac us provdng dals, and w wll rmov accss o h work mmdaly and nvsga your clam. Download da: 19. Nov. 2017

2 Accpd Manuscrp A non-prpual shrkng modl Yu-Fu hn, Gylf Zoga PII: S ( DOI: hp://dx.do.org/ /j.conl Rfrnc: OL 6812 o appar n: conomcs Lrs Rcvd da: 6 March 2015 Rvsd da: 29 Jun 2015 Accpd da: 30 Jun 2015 Plas c hs arcl as: hn, Y.-F., Zoga, G., A non-prpual shrkng modl. conomcs Lrs (2015, hp://dx.do.org/ /j.conl hs s a PDF fl of an undd manuscrp ha has bn accpd for publcaon. As a srvc o our cusomrs w ar provdng hs arly vrson of h manuscrp. h manuscrp wll undrgo copydng, ypsng, and rvw of h rsulng proof bfor s publshd n s fnal form. Plas no ha durng h producon procss rrors may b dscovrd whch could affc h conn, and all lgal dsclamrs ha apply o h journal pran.

3 *Hghlghs (for rvw W drv a fn-horzon vrson of h Shapro-Sglz shrkng modl of unmploymn. Workrs bhavor may chang as hy approach h nd of an mploymn conrac. Our modl prdcs ha wags should b rsng n ag for an unchangd ra of unmploymn.

4 *l Pag A Non-prpual Shrkng Modl Yu-Fu hn a and Gylf Zoga b, c* a conomc Suds, nvrsy of Dund, 3 Prh Road, Dund, K b Dparmn of conomcs, nvrsy of Icland, 101 Rykjavk, Icland c Dparmn of conomcs, Brkbck ollg, Mal Sr, London, K Jun 2015 Absrac W provd a fn-horzon counrpar o h Shapro and Sglz modl of unmploymn o show how workrs ffor falls as hy approach h nd of an mploymn spll. h modl provds a rason for wags rsng mor rapdly han producvy. Kywords: Wags, shrkng, fn horzons, rrmn. JL lassfcaon: J31, J21 * orrspondng auhor: Gylf Zoga, Dparmn of conomcs, nvrsy of Icland, Sæmundargaa, 101 Rykjavk, Icland. mal: gz@h.s; lphon: ; fax: Fnancal suppor from h Iclandc nr for Rsarch and h nvrsy of Icland Rsarch Fund s grafully acknowldgd. W ar graful o an anonymous rfr for commns.

5 *Manuscrp lck hr o vw lnkd Rfrncs 1. Inroducon vry mploymn conrac has a m dmnson. hr ar workrs on mporary conracs; workrs who hav bn gvn an advanc noc of dsmssal know ha hr days on h job ar numbrd; and vn workrs who hav saf prmann jobs ralz ha hy wll vnually rr. In hs papr w xnd and gnralz h wll-known modl of wag sng by Shapro and Sglz (S-S (1984 o show how a workr s propnsy o shrk hs dus vars from h bgnnng o h nd of an mploymn conrac. 2. A non-prpual modl W modl a workr s ffor dcson whn h has fn horzons lavng h nfn horzon cas dscrbd n h S-S papr as a spcal cas. hr ar hr sas of nrmporal uls n h S-S modl for workrs wh ransory probabls o alrnav sas. hs ar h valu of bng mployd, V (whn no shrkng and V S (whn shrkng, and h valu of bng unmployd, V. Workrs rcv h wag w whn mployd and unmploymn bnfs b u whn unmployd. ffor s xrd whn mployd workrs ar no shrkng hr dus whl no ffor s xrd whn workrs shrk. Workrs dscoun fuur uly a ra ρ, fac a consan probably of job rmnaon b durng h conrac prod and h probably q of bng frd f caugh shrkng. W sar wh a rprsnav sa ρ( s, (1 V u s ds wh ransory probably p j of movng o h alrnav sa j V,whr u s s h mmda uly a m s for h sa. W can now nroduc fn horzons by dvdng h nr-mporal ngral V no h prods of m and m whr dnos h m rmanng unl h nd of horzon: ρ( s ρ( s ρ( s + V u s ds u s ds u s ds. (2 0

6 h ngral u s ρ( s ds for m prod m can b rwrn as follows ρ( s ρ( ρ( s u s ds u s ds. (3 p ( j hrfor, w nd o dscoun h ngral by h facor f w would lk o rplac wh snc ovr h m prod from o, h ngral dprcas a h ra of p j : quaon (2 can now b rwrn as whr ρ( ρ( s ( ρ+ p j ( ρ( s u s ds u s ds u s ρ( s ds. (4 ρ( s ( ρ+ p j ( ρ( s ( ρ+ p j ( + + V u s ds u s ds V V, (5 ρ( s. Rarrangng gvs V u s ds V 1 V. j p ρ+ (6 quaon (6 shows h rlaonshp bwn h prpual and non-prpual nrmporal ngrals for h sa. On can hn apply quaon (6 o hr sas: V, V S, and V, wh corrspondng ransory probabls: p b, p S b+q, and p a, whr ( V w ds ρ( s s h non-prpual ngral for h valu of bng a non- shrkng mployd workr who facs h probably b of movng o h unmployd sa, ( s s h dsuly of ffor, V w ρ ds s h non-prpual ngral for h valu S of bng a shrkng workr who facs h probably b+q of movng o h unmploymn ( s sa and V b ρ ds s h non-prpual ngral for an unmployd workr who u bcoms mployd wh probably a, whch dnos h probably of fndng jobs. W can drv h followng hr ass prcng quaons by subsung quaon (6 no h Bllman quaons of h prpual cas of h S-S modl; 1

7 ( ρ + b( ( ρ + b( 1 ( ( 1 + ( ρ + a( ρv w b V V 1 ( ρ + b+ q( ( ρ + b+ q( 1 S ( 1 + ( + ( ρ + a( S ρv w b q V V 1 ( ρ + a( ( ρ + a( 1 u ( 1 + ( ρ + b( ρv b a V V 1, (7, (8. (9 sng h no-shrkng condon such ha V V for quaon (8 gvs S ( ρ + b+ q( ( ρ + b+ q( 1 ( 1 + ( + ( ρ + a( ρv w b q V V 1 hr ar hr unknown varabls, V, hr quaons gvs ( ρ ( ρ + b( V 2. (10, w, for (7, (9 and (10. Rarrangng hos ( ρ + b( ( ρ + b( ( b V b V ( a( w ρ + 1 ( ρ ( ρ + b+ q( ( ρ + b+ q(, ( b + q V b + q V 1 0 ( a( w ρ +, (12 1 ( ρ + a( ( ρ + a( + u ( 1 1 a V ( b( ( ρ a V b ρ + 1. (13 Fnally, usng ramr s rul gvs h no-shrkng condon for wags (s Appndx for dals w ( 1 B A a ( b + q bub ( ρ + b + q + ( B A bu ρq + ρ ( a + b + ρ + q ( 1 B A ( ρ + b( ρ + a + aq + ρq ( b( ( 1 ρ + ( b q( ( 1 ρ + + whr A and B. No ha snc A < B w fnd ha (1 B/A s ngav. h numraor of (14 falls fasr han h dnomnaor and h frm nds o pay wags ha rs as h nd of h conrac prod approachs. Bcaus h ffcv dscoun ras for h shrkng sa s ρ + b + q and hghr han h ffcv, (14

8 dscoun ra for h non-shrkng sa ρ + b, shrkng s lss harmful o workrs whos conrac wll xpr soon. For h prpual cas, w hav AB. hus h no-shrkng condon bcoms bu ρq + ρ a + b + ρ + q w bu + + ( a + b + ρ, (15 ρq q whch s h orgnal no-shrkng condon of Shapro and Sglz. Now dno h numbr of mployd workrs of ag by L. In sady sa, h ouflow from mploymn o unmploymn quals bl and should qual o nflow of workrs from unmploymn o mploymn a(n -L whr N s h numbr of workrs of ag n h labor forc. bl a( N L. ( a + b bl N L + b bn N L bn N L b u and w g hus 1 a b u u. Subsung back no (14 gvs h no-shrkng condon n qulbrum as a rlaonshp bwn wags and unmploymn. w ( 1 B A b( ( 1 u u ( b + q bub ( ρ + b + q ( 1 ( + ( + (( 1 + (( 1 + ( B A bu ρq + ρ ( b u + ρ + q + ( 1 (( 1 ( 1 B A ρ b ρ b u u b u u q ρq. B A ρ + b ( ρ + b u u + b ( u u q + ρq (17 I follows ha ach cohor of workrs has a dsnc wag curv or no-shrkng consran dscrbd by quaon (17. h non-shrkng consran s drawn n Fgur 1 blow as an upward-slopng nonshrkng consran for dffrn ag groups wh bnchmark valus blow h fgur. hr ar only small dffrncs bwn young and mddl-agd workrs. Bu h wag curvs for oldr workrs ar subsanally hghr. I follows ha h wag or unmploymn ndd o prvn a 40-yar old workr from shrkng hs dus s no much hghr han ha ndd o prvn a 20 yar old workr from dong so bu a sgnfcanly hghr wag s ndd o prvn a 50 yar old workr from shrkng han s h cas of h 40 yar old on. 3

9 As shown n Fgur 2 w fnd ha h wag rqurd o prvn shrkng rss rapdly n h yars ag group whn unmploymn s 10%, n h yars ag group whn unmploymn s 20% and n h group whn unmploymn s a saggrng 40%. 3. Dscusson Our modl prdcs ha wags nd o ncras as a workr approachs h nd of a conrac whn s dffcul o monor ffor and unmploymn s hld consan. I follows ha wags ar ncrasng n ag for a gvn unmploymn ra. h modl dscrbs wag sng n labor marks whr hr s subsanal asymmrc nformaon abou workrs ffor and monorng s dffcul, such as h mark for profssonals, managrs, ducad workrs and also n larg frms. In such marks oldr workrs wll hr fac a hghr unmploymn ra, whch rducs h cos of mployng hm, b mor producv du o xprnc or pushd no rrmn. W ar no h frs o propos an xplanaon for wags rsng fasr han producvy wh ag. Lazar (1979, 1981 drvd a modl whr wags ar s blow producvy for young workrs and hn abov producvy for workrs approachng rrmn for ncnv rasons, hnc also provdng a jusfcaon for mandaory rrmn. Anohr xplanaon for rsng wag profls s ha of Frank and Huchns (1993 who assum ha sasfacon dpnds on h ra of chang of consumpon. Rsng wag profls may b dsrd by workrs who fnd dffcul o pospon consumpon hrough volunary savngs. Whl rsng wag profls may provd ncnvs and b dsrd by h workforc our modl provds addonal nsghs no h rlaonshp bwn m unl rrmn and producvy. hr s vdnc ha h bhavor of workrs may chang as hy approach h nd of nur. Fglo (1995 found ha h dcson o rr from polcs rsuls n polcal shrkng manng lss pary dscpln usng a mul-yar panl daa s. n (2001 also found ha volunarly rrng mmbrs of ongrss shrkd by falng o rprsn h nrss of hr consuns. Parkr and Powrs (2002 found ha spndng on forgn ravl s hghr among mmbrs of ongrss who ar abou o lav offc. DBackr (2012 dcs shrkng by snaors n hr las rm 4

10 ha s lmd by polcal pars ha consran h polcan dpndng on hs pos- Sna carr chocs. In spors, Kraumann and Solow (2009 xamnd ncnvs n basball conracs and found ha playrs who ar lss lkly o sgn a subsqun conrac showd wors prformanc. hr ar mprcal suds ha suppor h prdcons of our modl. Mdoff and Abraham (1981 fnd an assocaon bwn xprnc and rlav arnng bu no assocaon bwn xprnc and rlav prformanc for managrs and profssonals n wo larg.s. compans. Dos (2006 us anadan daa and fnds ha producvy s lowr han wags for oldr workrs who hav a las an undrgradua dgr alhough h vdnc on h drc ffc of ag on producvy s mxd. Lallmand and Ryck (2009 arbu low mploymn ras among oldr workrs n Blgum o oldr workrs bng mor cosly o mploy and lss producv han prm ag workrs. Sudyng producvy daa from larg Blgan frms hy fnd ha a hghr shar of oldr workrs lowrs avrag producvy. In conras, Börsch-Supan and Wss (2008 sudy producvy n a Grman car manufacurng company and fnd ha xprnc kps h producvy of oldr workrs from fallng by gvng hm an ably o avod makng srous rrors. 4. onclusons By xndng h modl of Shapro and Sglz (1984 w hav found ha workrs ndncy o shrk hr dus ncrass as hy approach h nd of nur. Morovr, h hra of unmploymn has a smallr ffc on hs workrs rqurng frms o ras hr wags or mak hm rdundan. 5

11 Rfrncs Börsch-Supan, Axl H. and Mahas Wss (2008, Producvy and h Ag omposon of Work ams: vdnc from h Assmbly Ln, MA Dscusson Papr No Avalabl a SSRN: hp://ssrn.com/absrac or hp://dx.do.org/ /ssrn DBackr, Jason (2012, Polcal Pars and Polcal Shrkng, Publc hoc, 150 (3-4, Dos, B. (2006, Wags, Producvy and Agng, D conoms, 159, Fglo, Davd N. (1995, h ffc of Rrmn On Polcal Shrkng: vdnc From ongrssonal Vong, Publc Fnanc Rvw, 23 (2, Frank, Robr H. and Robr M. Huchns (1993, Wags, Snory, and h Dmand for Rsng onsumpon Profls, Journal of conomc Bhavor & Organzaon, 21 (3, Kraumann, Anhony. and John L. Solowhp://js.sagpub.com/conn/10/1/6.shor - aff-2 (2009, h Dynamcs of Prformanc Ovr h Duraon of Major Lagu Basball Long-rm onracs, Journal of Spors conomcs, 10 (1, Lallmand,. and F. Ryck (2009, Ar Oldr Workrs Harmful for Frm Producvy?, D conoms, 157, pp Lazar, dward P. (1979, Why Is hr Mandaory Rrmn? h Journal of Polcal conomy, 87 (6, Lazar, dward P. (1981, Agncy, arnngs Profls, Producvy, and Hours Rsrcons, Amrcan conomc Rvw, 71, Mdoff, Jams L. and Kaharn G. Abraham (1980, xprnc, Prformanc, and arnngs, h Quarrly Journal of conomcs, 95 (4, Parkr, Glnn R. and Sphn. Powrs (2002, Sarchng for Sympoms of Polcal Shrkng: ongrssonal Forgn ravl, Publc hoc, 110 (1-2, Shapro, arl and Josph. Sglz (1984, qulbrum nmploymn as a Workr Dscpln Dvc, Amrcan conomc Rvw, 74 (3, n, harls (2001, Rprsnaon, Volunary Rrmn, and Shrkng n h Las rm, Publc hoc, 106 (1-2,

12 Appndx quaons (11-(13 can b wrn as follows: A ρ + b V b V Aw A, (A1 B ρ + b + q V b + q V Bw, (A2 0 a V + a V bu, A (A3 ( ρ whr ( b( ( 1 ρ + b q A, B 1 ρ + + a, and 1 ρ +. ramr s rul gvs h soluons for no-shrkng condons wags A + b b A B b q b q 0 ( ρ ( ρ + + ( + (A4 w a A ( ρ + a b + b A b A + b + q b + q B B a A ( ρ + a 0 ( ρ ( ρ u. xpandng h drmnans gvs (A5 ( ρ + ( + + ( ρ + + ( ρ + ( + u ( ρ + + A( ρ + b + q( ρ + a + Bab Ba ( b + q B ( ρ + b( ρ + a Bbu b b q A b q a Ba b q Abb b q w quaon (A5 can furhr b smplfd as follows,. (A6 w ( B A bub ( ρ + b + q + Bbu ρq + ( A B a ( b + q + A ρ ( a + b + ρ + q ( A B ( ρ + b( ρ + a + aq + Aρq ( A B a ( b + q bub ( ρ + b + q + Bbu ρq + A ρ ( a + b + ρ + q ( A B ( ρ + b( ρ + a + aq + Aρq ( 1 B A a ( b + q bub ( ρ + b + q + ( B A bu ρq + ρ ( a + b + ρ + q. ( 1 B A ( ρ + b( ρ + a + aq + ρq 7

13 Fgur 1. Ag-dpndn wag curvs 10 Wags of NS ag60 ag55 ag50 ag40 ag mploymn Paramr valus: ρ 0.1, b 0.1, q 0.3, 1.0, b u 1, N No ha 45 mpls ha ag 20; and 5 mans ha ag 60, f w assum ha ag 65 s h ag a whch workrs ar no longr wllng o work. Fgur 2. h non-shrkng wag and ag Paramr valus: Sam as n Fgur 1. 8

9. Simple Rules for Monetary Policy

9. Simple Rules for Monetary Policy 9. Smpl Ruls for Monar Polc John B. Talor, Ma 0, 03 Woodford, AR 00 ovrvw papr Purpos s o consdr o wha xn hs prscrpon rsmbls h sor of polc ha conomc hor would rcommnd Bu frs, l s rvw how hs sor of polc

More information

Supplementary Figure 1. Experiment and simulation with finite qudit. anharmonicity. (a), Experimental data taken after a 60 ns three-tone pulse.

Supplementary Figure 1. Experiment and simulation with finite qudit. anharmonicity. (a), Experimental data taken after a 60 ns three-tone pulse. Supplmnar Fgur. Eprmn and smulaon wh fn qud anharmonc. a, Eprmnal daa akn afr a 6 ns hr-on puls. b, Smulaon usng h amlonan. Supplmnar Fgur. Phagoran dnamcs n h m doman. a, Eprmnal daa. Th hr-on puls s

More information

Advanced Queueing Theory. M/G/1 Queueing Systems

Advanced Queueing Theory. M/G/1 Queueing Systems Advand Quung Thory Ths slds ar rad by Dr. Yh Huang of Gorg Mason Unvrsy. Sudns rgsrd n Dr. Huang's ourss a GMU an ma a sngl mahn-radabl opy and prn a sngl opy of ah sld for hr own rfrn, so long as ah sld

More information

Consider a system of 2 simultaneous first order linear equations

Consider a system of 2 simultaneous first order linear equations Soluon of sysms of frs ordr lnar quaons onsdr a sysm of smulanous frs ordr lnar quaons a b c d I has h alrna mar-vcor rprsnaon a b c d Or, n shorhand A, f A s alrady known from con W know ha h abov sysm

More information

The Variance-Covariance Matrix

The Variance-Covariance Matrix Th Varanc-Covaranc Marx Our bggs a so-ar has bn ng a lnar uncon o a s o daa by mnmzng h las squars drncs rom h o h daa wh mnsarch. Whn analyzng non-lnar daa you hav o us a program l Malab as many yps o

More information

Summary: Solving a Homogeneous System of Two Linear First Order Equations in Two Unknowns

Summary: Solving a Homogeneous System of Two Linear First Order Equations in Two Unknowns Summary: Solvng a Homognous Sysm of Two Lnar Frs Ordr Equaons n Two Unknowns Gvn: A Frs fnd h wo gnvalus, r, and hr rspcv corrspondng gnvcors, k, of h coffcn mar A Dpndng on h gnvalus and gnvcors, h gnral

More information

innovations shocks white noise

innovations shocks white noise Innovaons Tm-srs modls ar consrucd as lnar funcons of fundamnal forcasng rrors, also calld nnovaons or shocks Ths basc buldng blocks sasf var σ Srall uncorrlad Ths rrors ar calld wh nos In gnral, f ou

More information

Published in: Proceedings of the Twenty Second Nordic Seminar on Computational Mechanics

Published in: Proceedings of the Twenty Second Nordic Seminar on Computational Mechanics Downloadd from vbn.aau.dk on: aprl 09, 019 Aalborg Unvrs Implmnaon of Moldng Consrans n Topology Opmzaon Marx, S.; Krsnsn, Andrs Schmd Publshd n: Procdngs of h Twny Scond Nordc Smnar on Compuaonal Mchancs

More information

Homework: Introduction to Motion

Homework: Introduction to Motion Homwork: Inroducon o Moon Dsanc vs. Tm Graphs Nam Prod Drcons: Answr h foowng qusons n h spacs provdd. 1. Wha do you do o cra a horzona n on a dsancm graph? 2. How do you wak o cra a sragh n ha sops up?

More information

CHAPTER CHAPTER14. Expectations: The Basic Tools. Prepared by: Fernando Quijano and Yvonn Quijano

CHAPTER CHAPTER14. Expectations: The Basic Tools. Prepared by: Fernando Quijano and Yvonn Quijano Expcaions: Th Basic Prpard by: Frnando Quijano and Yvonn Quijano CHAPTER CHAPTER14 2006 Prnic Hall Businss Publishing Macroconomics, 4/ Olivir Blanchard 14-1 Today s Lcur Chapr 14:Expcaions: Th Basic Th

More information

ELEN E4830 Digital Image Processing

ELEN E4830 Digital Image Processing ELEN E48 Dgal Imag Procssng Mrm Eamnaon Sprng Soluon Problm Quanzaon and Human Encodng r k u P u P u r r 6 6 6 6 5 6 4 8 8 4 P r 6 6 P r 4 8 8 6 8 4 r 8 4 8 4 7 8 r 6 6 6 6 P r 8 4 8 P r 6 6 8 5 P r /

More information

Theoretical Seismology

Theoretical Seismology Thorcal Ssmology Lcur 9 Sgnal Procssng Fourr analyss Fourr sudd a h Écol Normal n Pars, augh by Lagrang, who Fourr dscrbd as h frs among Europan mn of scnc, Laplac, who Fourr rad lss hghly, and by Mong.

More information

t=0 t>0: + vr - i dvc Continuation

t=0 t>0: + vr - i dvc Continuation hapr Ga Dlay and rcus onnuaon s rcu Equaon >: S S Ths dffrnal quaon, oghr wh h nal condon, fully spcfs bhaor of crcu afr swch closs Our n challng: larn how o sol such quaons TUE/EE 57 nwrk analys 4/5 NdM

More information

UNIT #5 EXPONENTIAL AND LOGARITHMIC FUNCTIONS

UNIT #5 EXPONENTIAL AND LOGARITHMIC FUNCTIONS Answr Ky Nam: Da: UNIT # EXPONENTIAL AND LOGARITHMIC FUNCTIONS Par I Qusions. Th prssion is quivaln o () () 6 6 6. Th ponnial funcion y 6 could rwrin as y () y y 6 () y y (). Th prssion a is quivaln o

More information

Frequency Response. Response of an LTI System to Eigenfunction

Frequency Response. Response of an LTI System to Eigenfunction Frquncy Rsons Las m w Rvsd formal dfnons of lnary and m-nvaranc Found an gnfuncon for lnar m-nvaran sysms Found h frquncy rsons of a lnar sysm o gnfuncon nu Found h frquncy rsons for cascad, fdbac, dffrnc

More information

FAULT TOLERANT SYSTEMS

FAULT TOLERANT SYSTEMS FAULT TOLERANT SYSTEMS hp://www.cs.umass.du/c/orn/faultolransysms ar 4 Analyss Mhods Chapr HW Faul Tolranc ar.4.1 Duplx Sysms Boh procssors xcu h sam as If oupus ar n agrmn - rsul s assumd o b corrc If

More information

EE243 Advanced Electromagnetic Theory Lec # 10: Poynting s Theorem, Time- Harmonic EM Fields

EE243 Advanced Electromagnetic Theory Lec # 10: Poynting s Theorem, Time- Harmonic EM Fields Appl M Fall 6 Nuruhr Lcur # r 9/6/6 4 Avanc lcromagnc Thory Lc # : Poynng s Thorm Tm- armonc M Fls Poynng s Thorm Consrvaon o nrgy an momnum Poynng s Thorm or Lnar sprsv Ma Poynng s Thorm or Tm-armonc

More information

UNIVERSITAT AUTÒNOMA DE BARCELONA MARCH 2017 EXAMINATION

UNIVERSITAT AUTÒNOMA DE BARCELONA MARCH 2017 EXAMINATION INTERNATIONAL TRADE T. J. KEHOE UNIVERSITAT AUTÒNOMA DE BARCELONA MARCH 27 EXAMINATION Please answer wo of he hree quesons. You can consul class noes, workng papers, and arcles whle you are workng on he

More information

10.5 Linear Viscoelasticity and the Laplace Transform

10.5 Linear Viscoelasticity and the Laplace Transform Scn.5.5 Lnar Vclacy and h Lalac ranfrm h Lalac ranfrm vry uful n cnrucng and analyng lnar vclac mdl..5. h Lalac ranfrm h frmula fr h Lalac ranfrm f h drvav f a funcn : L f f L f f f f f c..5. whr h ranfrm

More information

Conventional Hot-Wire Anemometer

Conventional Hot-Wire Anemometer Convnonal Ho-Wr Anmomr cro Ho Wr Avanag much mallr prob z mm o µm br paal roluon array o h nor hghr rquncy rpon lowr co prormanc/co abrcaon roc I µm lghly op p layr 8µm havly boron op ch op layr abrcaon

More information

NAME: ANSWER KEY DATE: PERIOD. DIRECTIONS: MULTIPLE CHOICE. Choose the letter of the correct answer.

NAME: ANSWER KEY DATE: PERIOD. DIRECTIONS: MULTIPLE CHOICE. Choose the letter of the correct answer. R A T T L E R S S L U G S NAME: ANSWER KEY DATE: PERIOD PREAP PHYSICS REIEW TWO KINEMATICS / GRAPHING FORM A DIRECTIONS: MULTIPLE CHOICE. Chs h r f h rr answr. Us h fgur bw answr qusns 1 and 2. 0 10 20

More information

CIVL 8/ D Boundary Value Problems - Triangular Elements (T6) 1/8

CIVL 8/ D Boundary Value Problems - Triangular Elements (T6) 1/8 CIVL 8/7 -D Boundar Valu Problm - rangular Elmn () /8 SI-ODE RIAGULAR ELEMES () A quadracall nrpolad rangular lmn dfnd b nod, hr a h vrc and hr a h mddl a ach d. h mddl nod, dpndng on locaon, ma dfn a

More information

Graduate Macroeconomics 2 Problem set 5. - Solutions

Graduate Macroeconomics 2 Problem set 5. - Solutions Graduae Macroeconomcs 2 Problem se. - Soluons Queson 1 To answer hs queson we need he frms frs order condons and he equaon ha deermnes he number of frms n equlbrum. The frms frs order condons are: F K

More information

Partition Functions for independent and distinguishable particles

Partition Functions for independent and distinguishable particles 0.0J /.77J / 5.60J hrodynacs of oolcular Syss Insrucors: Lnda G. Grffh, Kbrly Haad-Schffrl, Moung G. awnd, Robr W. Fld Lcur 5 5.60/0.0/.77 vs. q for dsngushabl vs ndsngushabl syss Drvaon of hrodynac Proprs

More information

(heat loss divided by total enthalpy flux) is of the order of 8-16 times

(heat loss divided by total enthalpy flux) is of the order of 8-16 times 16.51, Rok Prolson Prof. Manl Marnz-Sanhz r 8: Convv Ha ransfr: Ohr Effs Ovrall Ha oss and Prforman Effs of Ha oss (1) Ovrall Ha oss h loal ha loss r n ara s q = ρ ( ) ngrad ha loss s a S, and sng m =

More information

Overview of Course/Syllabus

Overview of Course/Syllabus Ovrvw of Cours/Syllabus Wha s Macroconomcs Macroconomcs sudy of aggrga flucuaons n mploymn, oupu and nflaon Subjc sard by Kyns 936: Th Gnral Thory of Employmn, Inrs and Mony Sard wh amps o xplan h Gra

More information

4.1 The Uniform Distribution Def n: A c.r.v. X has a continuous uniform distribution on [a, b] when its pdf is = 1 a x b

4.1 The Uniform Distribution Def n: A c.r.v. X has a continuous uniform distribution on [a, b] when its pdf is = 1 a x b 4. Th Uniform Disribuion Df n: A c.r.v. has a coninuous uniform disribuion on [a, b] whn is pdf is f x a x b b a Also, b + a b a µ E and V Ex4. Suppos, h lvl of unblivabiliy a any poin in a Transformrs

More information

Yutaka Suzuki Faculty of Economics, Hosei University. Abstract

Yutaka Suzuki Faculty of Economics, Hosei University. Abstract Equlbrum ncnvs and accumulaon of rlaonal sklls n a dynamc modl of hold up Yuaka uzuk Faculy of Economcs, Hos Unvrsy Absrac W consruc a dynamc modl of Holdup by applyng a framwork n capal accumulaon gams,

More information

Chapter 7 Stead St y- ate Errors

Chapter 7 Stead St y- ate Errors Char 7 Say-Sa rror Inroucon Conrol ym analy an gn cfcaon a. rann ron b. Sably c. Say-a rror fnon of ay-a rror : u c a whr u : nu, c: ouu Val only for abl ym chck ym ably fr! nu for ay-a a nu analy U o

More information

Wave Superposition Principle

Wave Superposition Principle Physcs 36: Was Lcur 5 /7/8 Wa Suroson Prncl I s qu a common suaon for wo or mor was o arr a h sam on n sac or o xs oghr along h sam drcon. W wll consdr oday sral moran cass of h combnd ffcs of wo or mor

More information

1. Inverse Matrix 4[(3 7) (02)] 1[(0 7) (3 2)] Recall that the inverse of A is equal to:

1. Inverse Matrix 4[(3 7) (02)] 1[(0 7) (3 2)] Recall that the inverse of A is equal to: Rfrncs Brnank, B. and I. Mihov (1998). Masuring monary policy, Quarrly Journal of Economics CXIII, 315-34. Blanchard, O. R. Proi (00). An mpirical characrizaion of h dynamic ffcs of changs in govrnmn spnding

More information

Analysis of influential factors responsible for the effect of tax reduction on GDP

Analysis of influential factors responsible for the effect of tax reduction on GDP Analyss of nflunal facors rsponsbl for h ffc of ax rducon on GDP Shgak Ogbayash, Kous Takashma and Yuhsuk Koyama 3, School of Socal Sysms Scnc, Chba Insu of Tchnology, Chba 75-006, Japan. shgak.ogbayash@-chba.ac.jp,

More information

Engineering Circuit Analysis 8th Edition Chapter Nine Exercise Solutions

Engineering Circuit Analysis 8th Edition Chapter Nine Exercise Solutions Engnrng rcu naly 8h Eon hapr Nn Exrc Soluon. = KΩ, = µf, an uch ha h crcu rpon oramp. a For Sourc-fr paralll crcu: For oramp or b H 9V, V / hoo = H.7.8 ra / 5..7..9 9V 9..9..9 5.75,.5 5.75.5..9 . = nh,

More information

Boosting and Ensemble Methods

Boosting and Ensemble Methods Boosng and Ensmbl Mhods PAC Larnng modl Som dsrbuon D ovr doman X Eampls: c* s h arg funcon Goal: Wh hgh probably -d fnd h n H such ha rrorh,c* < d and ar arbrarly small. Inro o ML 2 Wak Larnng

More information

Institute of Actuaries of India

Institute of Actuaries of India Insiu of Acuaris of India ubjc CT3 Probabiliy and Mahmaical aisics Novmbr Examinaions INDICATIVE OLUTION Pag of IAI CT3 Novmbr ol. a sampl man = 35 sampl sandard dviaion = 36.6 b for = uppr bound = 35+*36.6

More information

Grand Canonical Ensemble

Grand Canonical Ensemble Th nsmbl of systms mmrsd n a partcl-hat rsrvor at constant tmpratur T, prssur P, and chmcal potntal. Consdr an nsmbl of M dntcal systms (M =,, 3,...M).. Thy ar mutually sharng th total numbr of partcls

More information

SIMEON BALL AND AART BLOKHUIS

SIMEON BALL AND AART BLOKHUIS A BOUND FOR THE MAXIMUM WEIGHT OF A LINEAR CODE SIMEON BALL AND AART BLOKHUIS Absrac. I s shown ha h paramrs of a lnar cod ovr F q of lngh n, dmnson k, mnmum wgh d and maxmum wgh m sasfy a cran congrunc

More information

State Observer Design

State Observer Design Sa Obsrvr Dsgn A. Khak Sdgh Conrol Sysms Group Faculy of Elcrcal and Compur Engnrng K. N. Toos Unvrsy of Tchnology Fbruary 2009 1 Problm Formulaon A ky assumpon n gnvalu assgnmn and sablzng sysms usng

More information

Transient Analysis of Two-dimensional State M/G/1 Queueing Model with Multiple Vacations and Bernoulli Schedule

Transient Analysis of Two-dimensional State M/G/1 Queueing Model with Multiple Vacations and Bernoulli Schedule Inrnaonal Journal of Compur Applcaons (975 8887) Volum 4 No.3, Fbruary 22 Transn Analyss of Two-dmnsonal Sa M/G/ Quung Modl wh Mulpl Vacaons and Brnoull Schdul Indra Assoca rofssor Dparmn of Sascs and

More information

Lucas Test is based on Euler s theorem which states that if n is any integer and a is coprime to n, then a φ(n) 1modn.

Lucas Test is based on Euler s theorem which states that if n is any integer and a is coprime to n, then a φ(n) 1modn. Modul 10 Addtonal Topcs 10.1 Lctur 1 Prambl: Dtrmnng whthr a gvn ntgr s prm or compost s known as prmalty tstng. Thr ar prmalty tsts whch mrly tll us whthr a gvn ntgr s prm or not, wthout gvng us th factors

More information

Midterm Examination (100 pts)

Midterm Examination (100 pts) Econ 509 Spring 2012 S.L. Parn Midrm Examinaion (100 ps) Par I. 30 poins 1. Dfin h Law of Diminishing Rurns (5 ps.) Incrasing on inpu, call i inpu x, holding all ohr inpus fixd, on vnuall runs ino h siuaion

More information

Fakultät III Wirtschaftswissenschaften Univ.-Prof. Dr. Jan Franke-Viebach

Fakultät III Wirtschaftswissenschaften Univ.-Prof. Dr. Jan Franke-Viebach Unvrstät Sgn Fakultät III Wrtschaftswssnschaftn Unv.-rof. Dr. Jan Frank-Vbach Exam Intrnatonal Fnancal Markts Summr Smstr 206 (2 nd Exam rod) Avalabl tm: 45 mnuts Soluton For your attnton:. las do not

More information

EXERCISE - 01 CHECK YOUR GRASP

EXERCISE - 01 CHECK YOUR GRASP DIFFERENTIAL EQUATION EXERCISE - CHECK YOUR GRASP 7. m hn D() m m, D () m m. hn givn D () m m D D D + m m m m m m + m m m m + ( m ) (m ) (m ) (m + ) m,, Hnc numbr of valus of mn will b. n ( ) + c sinc

More information

8. Queueing systems. Contents. Simple teletraffic model. Pure queueing system

8. Queueing systems. Contents. Simple teletraffic model. Pure queueing system 8. Quug sysms Cos 8. Quug sysms Rfrshr: Sml lraffc modl Quug dscl M/M/ srvr wag lacs Alcao o ack lvl modllg of daa raffc M/M/ srvrs wag lacs lc8. S-38.45 Iroduco o Tlraffc Thory Srg 5 8. Quug sysms 8.

More information

Lecture 4 : Backpropagation Algorithm. Prof. Seul Jung ( Intelligent Systems and Emotional Engineering Laboratory) Chungnam National University

Lecture 4 : Backpropagation Algorithm. Prof. Seul Jung ( Intelligent Systems and Emotional Engineering Laboratory) Chungnam National University Lcur 4 : Bacpropagaon Algorhm Pro. Sul Jung Inllgn Sm and moonal ngnrng Laboraor Chungnam Naonal Unvr Inroducon o Bacpropagaon algorhm 969 Mn and Papr aac. 980 Parr and Wrbo dcovrd bac propagaon algorhm.

More information

THE SHORT-RUN AGGREGATE SUPPLY CURVE WITH A POSITIVE SLOPE. Based on EXPECTATIONS: Lecture. t t t t

THE SHORT-RUN AGGREGATE SUPPLY CURVE WITH A POSITIVE SLOPE. Based on EXPECTATIONS: Lecture. t t t t THE SHORT-RUN AGGREGATE SUL CURVE WITH A OSITIVE SLOE. Basd on EXECTATIONS: Lcur., 0. In Mankiw:, 0 Ths quaions sa ha oupu dvias from is naural ra whn h pric lvl dvias from h xpcd pric lvl. Th paramr a

More information

Charging of capacitor through inductor and resistor

Charging of capacitor through inductor and resistor cur 4&: R circui harging of capacior hrough inducor and rsisor us considr a capacior of capacianc is conncd o a D sourc of.m.f. E hrough a rsisr of rsisanc R, an inducor of inducanc and a y K in sris.

More information

Fakultät III Univ.-Prof. Dr. Jan Franke-Viebach

Fakultät III Univ.-Prof. Dr. Jan Franke-Viebach Unv.Prof. r. J. FrankVbach WS 067: Intrnatonal Economcs ( st xam prod) Unvrstät Sgn Fakultät III Unv.Prof. r. Jan FrankVbach Exam Intrnatonal Economcs Wntr Smstr 067 ( st Exam Prod) Avalabl tm: 60 mnuts

More information

CONTINUOUS TIME DYNAMIC PROGRAMMING

CONTINUOUS TIME DYNAMIC PROGRAMMING Eon. 511b Sprng 1993 C. Sms I. Th Opmaon Problm CONTINUOUS TIME DYNAMIC PROGRAMMING W onsdr h problm of maxmng subj o and EU(C, ) d (1) j ^ d = (C, ) d + σ (C, ) dw () h(c, ), (3) whr () and (3) hold for

More information

Microscopic Flow Characteristics Time Headway - Distribution

Microscopic Flow Characteristics Time Headway - Distribution CE57: Traffic Flow Thory Spring 20 Wk 2 Modling Hadway Disribuion Microscopic Flow Characrisics Tim Hadway - Disribuion Tim Hadway Dfiniion Tim Hadway vrsus Gap Ahmd Abdl-Rahim Civil Enginring Dparmn,

More information

Problem 1: Consider the following stationary data generation process for a random variable y t. e t ~ N(0,1) i.i.d.

Problem 1: Consider the following stationary data generation process for a random variable y t. e t ~ N(0,1) i.i.d. A/CN C m Sr Anal Profor Òcar Jordà Wnr conomc.c. Dav POBLM S SOLIONS Par I Analcal Quon Problm : Condr h followng aonar daa gnraon proc for a random varabl - N..d. wh < and N -. a Oban h populaon man varanc

More information

The Mathematics of Harmonic Oscillators

The Mathematics of Harmonic Oscillators Th Mhcs of Hronc Oscllors Spl Hronc Moon In h cs of on-nsonl spl hronc oon (SHM nvolvng sprng wh sprng consn n wh no frcon, you rv h quon of oon usng Nwon's scon lw: con wh gvs: 0 Ths s sos wrn usng h

More information

Chain DOUBLE PITCH TYPE RS TYPE RS POLY-STEEL TYPE

Chain DOUBLE PITCH TYPE RS TYPE RS POLY-STEEL TYPE d Fr Flw OULE IC YE YE OLY-EEL YE Oubard wh d s (d ) s usd fr fr flw vya. Usually w srads ar usd h qupm. d s basd sadard rllr ha wh sd rllrs salld xdd ps. hr ar hr yps f bas ha: (1) ubl ph rllr ha wh sadard

More information

Safety and Reliability of Embedded Systems. (Sicherheit und Zuverlässigkeit eingebetteter Systeme) Stochastic Reliability Analysis

Safety and Reliability of Embedded Systems. (Sicherheit und Zuverlässigkeit eingebetteter Systeme) Stochastic Reliability Analysis Safy and Rlably of Embddd Sysms (Schrh und Zuvrlässgk ngbr Sysm) Sochasc Rlably Analyss Safy and Rlably of Embddd Sysms Conn Dfnon of Rlably Hardwar- vs. Sofwar Rlably Tool Asssd Rlably Modlng Dscrpons

More information

On the Derivatives of Bessel and Modified Bessel Functions with Respect to the Order and the Argument

On the Derivatives of Bessel and Modified Bessel Functions with Respect to the Order and the Argument Inrnaional Rsarch Journal of Applid Basic Scincs 03 Aailabl onlin a wwwirjabscom ISSN 5-838X / Vol 4 (): 47-433 Scinc Eplorr Publicaions On h Driais of Bssl Modifid Bssl Funcions wih Rspc o h Ordr h Argumn

More information

An Indian Journal FULL PAPER. Trade Science Inc. A stage-structured model of a single-species with density-dependent and birth pulses ABSTRACT

An Indian Journal FULL PAPER. Trade Science Inc. A stage-structured model of a single-species with density-dependent and birth pulses ABSTRACT [Typ x] [Typ x] [Typ x] ISSN : 974-7435 Volum 1 Issu 24 BioTchnology 214 An Indian Journal FULL PAPE BTAIJ, 1(24), 214 [15197-1521] A sag-srucurd modl of a singl-spcis wih dnsiy-dpndn and birh pulss LI

More information

Lecture 1: Numerical Integration The Trapezoidal and Simpson s Rule

Lecture 1: Numerical Integration The Trapezoidal and Simpson s Rule Lcur : Numrical ngraion Th Trapzoidal and Simpson s Rul A problm Th probabiliy of a normally disribud (man µ and sandard dviaion σ ) vn occurring bwn h valus a and b is B A P( a x b) d () π whr a µ b -

More information

Safety and Reliability of Embedded Systems. (Sicherheit und Zuverlässigkeit eingebetteter Systeme) Stochastic Reliability Analysis

Safety and Reliability of Embedded Systems. (Sicherheit und Zuverlässigkeit eingebetteter Systeme) Stochastic Reliability Analysis (Schrh und Zuvrlässgk ngbr Sysm) Sochasc Rlably Analyss Conn Dfnon of Rlably Hardwar- vs. Sofwar Rlably Tool Asssd Rlably Modlng Dscrpons of Falurs ovr Tm Rlably Modlng Exampls of Dsrbuon Funcons Th xponnal

More information

Chap 2: Reliability and Availability Models

Chap 2: Reliability and Availability Models Chap : lably ad valably Modls lably = prob{s s fully fucog [,]} Suppos from [,] m prod, w masur ou of N compos, of whch N : # of compos oprag corrcly a m N f : # of compos whch hav fald a m rlably of h

More information

Economics 302 (Sec. 001) Intermediate Macroeconomic Theory and Policy (Spring 2011) 3/28/2012. UW Madison

Economics 302 (Sec. 001) Intermediate Macroeconomic Theory and Policy (Spring 2011) 3/28/2012. UW Madison Economics 302 (Sc. 001) Inrmdia Macroconomic Thory and Policy (Spring 2011) 3/28/2012 Insrucor: Prof. Mnzi Chinn Insrucor: Prof. Mnzi Chinn UW Madison 16 1 Consumpion Th Vry Forsighd dconsumr A vry forsighd

More information

Chapter 13 Aggregate Supply

Chapter 13 Aggregate Supply Chaptr 13 Aggrgat Supply 0 1 Larning Objctivs thr modls of aggrgat supply in which output dpnds positivly on th pric lvl in th short run th short-run tradoff btwn inflation and unmploymnt known as th Phillips

More information

Applying Software Reliability Techniques to Low Retail Demand Estimation

Applying Software Reliability Techniques to Low Retail Demand Estimation Applyng Sofwar Rlably Tchnqus o Low Ral Dmand Esmaon Ma Lndsy Unvrsy of Norh Txas ITDS Dp P.O. Box 30549 Dnon, TX 7603-549 940 565 3174 lndsym@un.du Robr Pavur Unvrsy of Norh Txas ITDS Dp P.O. Box 30549

More information

CHAPTER 33: PARTICLE PHYSICS

CHAPTER 33: PARTICLE PHYSICS Collg Physcs Studnt s Manual Chaptr 33 CHAPTER 33: PARTICLE PHYSICS 33. THE FOUR BASIC FORCES 4. (a) Fnd th rato of th strngths of th wak and lctromagntc forcs undr ordnary crcumstancs. (b) What dos that

More information

Economics 302 (Sec. 001) Intermediate Macroeconomic Theory and Policy (Spring 2011) 4/25/2011. UW Madison

Economics 302 (Sec. 001) Intermediate Macroeconomic Theory and Policy (Spring 2011) 4/25/2011. UW Madison conomics 302 (Sc. 001) Inrmdia Macroconomic Thory and Policy (Spring 2011) 4/25/2011 Insrucor: Prof. Mnzi Chinn Insrucor: Prof. Mnzi Chinn UW Madison 21 1 Th Mdium Run ε = P * P Thr ar wo ways in which

More information

Advanced Macroeconomics

Advanced Macroeconomics Advancd Macroconomcs Chaptr 18 INFLATION, UNEMPLOYMENT AND AGGREGATE SUPPLY Thms of th chaptr Nomnal rgdts, xpctatonal rrors and mploymnt fluctuatons. Th short-run trad-off btwn nflaton and unmploymnt.

More information

Valuation and Analysis of Basket Credit Linked Notes with Issuer Default Risk

Valuation and Analysis of Basket Credit Linked Notes with Issuer Default Risk Valuaon and Analy of Ba Crd Lnd o wh ur Dfaul R Po-Chng Wu * * Dparmn of Banng and Fnanc Kanan Unvry Addr: o. Kanan Rd. Luchu Shang aoyuan 33857 awan R.O.C. E-mal: pcwu@mal.nu.du.w l.: 886-3-34500 x. 67

More information

CPSC 211 Data Structures & Implementations (c) Texas A&M University [ 259] B-Trees

CPSC 211 Data Structures & Implementations (c) Texas A&M University [ 259] B-Trees CPSC 211 Daa Srucurs & Implmnaions (c) Txas A&M Univrsiy [ 259] B-Trs Th AVL r and rd-black r allowd som variaion in h lnghs of h diffrn roo-o-laf pahs. An alrnaiv ida is o mak sur ha all roo-o-laf pahs

More information

Two-Dimensional Quantum Harmonic Oscillator

Two-Dimensional Quantum Harmonic Oscillator D Qa Haroc Oscllaor Two-Dsoal Qa Haroc Oscllaor 6 Qa Mchacs Prof. Y. F. Ch D Qa Haroc Oscllaor D Qa Haroc Oscllaor ch5 Schrödgr cosrcd h cohr sa of h D H.O. o dscrb a classcal arcl wh a wav ack whos cr

More information

Economics 600: August, 2007 Dynamic Part: Problem Set 5. Problems on Differential Equations and Continuous Time Optimization

Economics 600: August, 2007 Dynamic Part: Problem Set 5. Problems on Differential Equations and Continuous Time Optimization THE UNIVERSITY OF MARYLAND COLLEGE PARK, MARYLAND Economcs 600: August, 007 Dynamc Part: Problm St 5 Problms on Dffrntal Equatons and Contnuous Tm Optmzaton Quston Solv th followng two dffrntal quatons.

More information

Mathematical Statistics. Chapter VIII Sampling Distributions and the Central Limit Theorem

Mathematical Statistics. Chapter VIII Sampling Distributions and the Central Limit Theorem Mahmacal ascs 8 Chapr VIII amplg Dsrbos ad h Cral Lm Thorm Fcos of radom arabls ar sall of rs sascal applcao Cosdr a s of obsrabl radom arabls L For ampl sppos h arabls ar a radom sampl of s from a poplao

More information

Improved Exponential Estimator for Population Variance Using Two Auxiliary Variables

Improved Exponential Estimator for Population Variance Using Two Auxiliary Variables Improvd Epoal Emaor for Populao Varac Ug Two Aular Varabl Rajh gh Dparm of ac,baara Hdu Uvr(U.P., Ida (rgha@ahoo.com Pakaj Chauha ad rmala awa chool of ac, DAVV, Idor (M.P., Ida Flor maradach Dparm of

More information

Poisson process Markov process

Poisson process Markov process E2200 Quuing hory and lraffic 2nd lcur oion proc Markov proc Vikoria Fodor KTH Laboraory for Communicaion nwork, School of Elcrical Enginring 1 Cour oulin Sochaic proc bhind quuing hory L2-L3 oion proc

More information

Chapter 7. Now, for 2) 1. 1, if z = 1, Thus, Eq. (7.20) holds

Chapter 7. Now, for 2) 1. 1, if z = 1, Thus, Eq. (7.20) holds Chapr 7, n, 7 Ipuls rspons of h ovng avrag flr s: h[, ohrws sn / / Is frquny rspons s: sn / Now, for a BR ransfr funon,, For h ovng-avrag flr, sn / W shall show by nduon ha sn / sn / sn /,, Now, for sn

More information

Convergence of Quintic Spline Interpolation

Convergence of Quintic Spline Interpolation Inrnaonal Journal o ompur Applcaons 97 8887 Volum 7 No., Aprl onvrgnc o Qunc Spln Inrpolaon Y.P. Dub Dparmn O Mamacs, L.N..T. Jabalpur 8 Anl Sukla Dparmn O Mamacs Gan Ganga ollg O Tcnog, Jabalpur 8 ASTRAT

More information

Currency crisis: unique equilibrium and transparency

Currency crisis: unique equilibrium and transparency Currncy crss: unqu qulbrum and ransparncy Ch-Tng Chn Dparmn of Rsk Managmn and Insuranc, Mng Chuan Unvrsy Absrac Morrs and Shn (998) nroduc h global gam no h slf-fulfllng currncy crss modl and show ha

More information

2.1. Differential Equations and Solutions #3, 4, 17, 20, 24, 35

2.1. Differential Equations and Solutions #3, 4, 17, 20, 24, 35 MATH 5 PS # Summr 00.. Diffrnial Equaions and Soluions PS.# Show ha ()C #, 4, 7, 0, 4, 5 ( / ) is a gnral soluion of h diffrnial quaion. Us a compur or calculaor o skch h soluions for h givn valus of h

More information

MECE 3320 Measurements & Instrumentation. Static and Dynamic Characteristics of Signals

MECE 3320 Measurements & Instrumentation. Static and Dynamic Characteristics of Signals MECE 330 MECE 330 Masurms & Isrumao Sac ad Damc Characrscs of Sgals Dr. Isaac Chouapall Dparm of Mchacal Egrg Uvrs of Txas Pa Amrca MECE 330 Sgal Cocps A sgal s h phscal formao abou a masurd varabl bg

More information

Chapter 9 Transient Response

Chapter 9 Transient Response har 9 Transn sons har 9: Ouln N F n F Frs-Ordr Transns Frs-Ordr rcus Frs ordr crcus: rcus conan onl on nducor or on caacor gornd b frs-ordr dffrnal quaons. Zro-nu rsons: h crcu has no ald sourc afr a cran

More information

te Finance (4th Edition), July 2017.

te Finance (4th Edition), July 2017. Appndx Chaptr. Tchncal Background Gnral Mathmatcal and Statstcal Background Fndng a bas: 3 2 = 9 3 = 9 1 /2 x a = b x = b 1/a A powr of 1 / 2 s also quvalnt to th squar root opraton. Fndng an xponnt: 3

More information

8-node quadrilateral element. Numerical integration

8-node quadrilateral element. Numerical integration Fnt Elmnt Mthod lctur nots _nod quadrlatral lmnt Pag of 0 -nod quadrlatral lmnt. Numrcal ntgraton h tchnqu usd for th formulaton of th lnar trangl can b formall tndd to construct quadrlatral lmnts as wll

More information

Chapter 14 Aggregate Supply and the Short-run Tradeoff Between Inflation and Unemployment

Chapter 14 Aggregate Supply and the Short-run Tradeoff Between Inflation and Unemployment Chaptr 14 Aggrgat Supply and th Short-run Tradoff Btwn Inflation and Unmploymnt Modifid by Yun Wang Eco 3203 Intrmdiat Macroconomics Florida Intrnational Univrsity Summr 2017 2016 Worth Publishrs, all

More information

Final Exam : Solutions

Final Exam : Solutions Comp : Algorihm and Daa Srucur Final Exam : Soluion. Rcuriv Algorihm. (a) To bgin ind h mdian o {x, x,... x n }. Sinc vry numbr xcp on in h inrval [0, n] appar xacly onc in h li, w hav ha h mdian mu b

More information

NDC Dynamic Equilibrium model with financial and

NDC Dynamic Equilibrium model with financial and 9 July 009 NDC Dynamc Equlbrum modl wh fnancal and dmograhc rsks rr DEVOLDER, Inmaculada DOMÍNGUEZ-FABIÁN, Aurél MILLER ABSTRACT Classcal socal scury nson schms, combnng a dfnd bnf hlosohy and a ay as

More information

Inflation and Unemployment

Inflation and Unemployment C H A P T E R 13 Aggrgat Supply and th Short-run Tradoff Btwn Inflation and Unmploymnt MACROECONOMICS SIXTH EDITION N. GREGORY MANKIW PowrPoint Slids by Ron Cronovich 2008 Worth Publishrs, all rights rsrvd

More information

Bethe-Salpeter Equation Green s Function and the Bethe-Salpeter Equation for Effective Interaction in the Ladder Approximation

Bethe-Salpeter Equation Green s Function and the Bethe-Salpeter Equation for Effective Interaction in the Ladder Approximation Bh-Salp Equaon n s Funcon and h Bh-Salp Equaon fo Effcv Inacon n h Ladd Appoxmaon Csa A. Z. Vasconcllos Insuo d Físca-UFRS - upo: Físca d Hadons Sngl-Pacl Popagao. Dagam xpanson of popagao. W consd as

More information

A Note on Estimability in Linear Models

A Note on Estimability in Linear Models Intrnatonal Journal of Statstcs and Applcatons 2014, 4(4): 212-216 DOI: 10.5923/j.statstcs.20140404.06 A Not on Estmablty n Lnar Modls S. O. Adymo 1,*, F. N. Nwob 2 1 Dpartmnt of Mathmatcs and Statstcs,

More information

Applied Statistics and Probability for Engineers, 6 th edition October 17, 2016

Applied Statistics and Probability for Engineers, 6 th edition October 17, 2016 Applid Saisics and robabiliy for Enginrs, 6 h diion Ocobr 7, 6 CHATER Scion - -. a d. 679.. b. d. 88 c d d d. 987 d. 98 f d.. Thn, = ln. =. g d.. Thn, = ln.9 =.. -7. a., by symmry. b.. d...6. 7.. c...

More information

Series of New Information Divergences, Properties and Corresponding Series of Metric Spaces

Series of New Information Divergences, Properties and Corresponding Series of Metric Spaces Srs of Nw Iforao Dvrgcs, Proprs ad Corrspodg Srs of Mrc Spacs K.C.Ja, Praphull Chhabra Profssor, Dpar of Mahacs, Malavya Naoal Isu of Tchology, Japur (Rajasha), Ida Ph.d Scholar, Dpar of Mahacs, Malavya

More information

AR(1) Process. The first-order autoregressive process, AR(1) is. where e t is WN(0, σ 2 )

AR(1) Process. The first-order autoregressive process, AR(1) is. where e t is WN(0, σ 2 ) AR() Procss Th firs-ordr auorgrssiv procss, AR() is whr is WN(0, σ ) Condiional Man and Varianc of AR() Condiional man: Condiional varianc: ) ( ) ( Ω Ω E E ) var( ) ) ( var( ) var( σ Ω Ω Ω Ω E Auocovarianc

More information

Double Slits in Space and Time

Double Slits in Space and Time Doubl Slis in Sac an Tim Gorg Jons As has bn ror rcnly in h mia, a am l by Grhar Paulus has monsra an inrsing chniqu for ionizing argon aoms by using ulra-shor lasr ulss. Each lasr uls is ffcivly on an

More information

Salim Hamad Suleiman * Najat Nassor Suleiman Ministry of Trade, Industry and Marketing, PO box 601, Migombani, Zanzibar

Salim Hamad Suleiman * Najat Nassor Suleiman Ministry of Trade, Industry and Marketing, PO box 601, Migombani, Zanzibar Journal of Economcs and Susanabl Dvlopmn ISS -700 (Papr) ISS -855 (Onln) Vol.8 o.0 07 www.s.org rad Opnnss and Economc Growh n Eas Afrcan Communy (EAC) Mmbr Counrs Salm Hamad Sulman aja assor Sulman Mnsry

More information

Guo, James C.Y. (1998). "Overland Flow on a Pervious Surface," IWRA International J. of Water, Vol 23, No 2, June.

Guo, James C.Y. (1998). Overland Flow on a Pervious Surface, IWRA International J. of Water, Vol 23, No 2, June. Guo, Jams C.Y. (006). Knmatc Wav Unt Hyrograph for Storm Watr Prctons, Vol 3, No. 4, ASCE J. of Irrgaton an Dranag Engnrng, July/August. Guo, Jams C.Y. (998). "Ovrlan Flow on a Prvous Surfac," IWRA Intrnatonal

More information

EAcos θ, where θ is the angle between the electric field and

EAcos θ, where θ is the angle between the electric field and 8.4. Modl: Th lctric flux flows out of a closd surfac around a rgion of spac containing a nt positiv charg and into a closd surfac surrounding a nt ngativ charg. Visualiz: Plas rfr to Figur EX8.4. Lt A

More information

3(8 ) (8 x x ) 3x x (8 )

3(8 ) (8 x x ) 3x x (8 ) Scion - CHATER -. a d.. b. d.86 c d 8 d d.9997 f g 6. d. d. Thn, = ln. =. =.. d Thn, = ln.9 =.7 8 -. a d.6 6 6 6 6 8 8 8 b 9 d 6 6 6 8 c d.8 6 6 6 6 8 8 7 7 d 6 d.6 6 6 6 6 6 6 8 u u u u du.9 6 6 6 6 6

More information

The Fourier Transform

The Fourier Transform /9/ Th ourr Transform Jan Baptst Josph ourr 768-83 Effcnt Data Rprsntaton Data can b rprsntd n many ways. Advantag usng an approprat rprsntaton. Eampls: osy ponts along a ln Color spac rd/grn/blu v.s.

More information

NBER WORKING PAPER SERIES THE INNER WORKINGS OF THE PATIENT CENTERED MEDICAL HOME MODEL. Guy David Philip A. Saynisch Aaron Smith-McLallen

NBER WORKING PAPER SERIES THE INNER WORKINGS OF THE PATIENT CENTERED MEDICAL HOME MODEL. Guy David Philip A. Saynisch Aaron Smith-McLallen NBER WORKING PAPER SERIES TE INNER WORKINGS OF TE PATIENT CENTERED MEDICA OME MODE Guy Davd Phlp A. Saynsch Aaron Smh-Mcalln Workng Papr 49 hp://www.nbr.org/paprs/w49 NATIONA BUREAU OF ECONOMIC RESEARC

More information

On One Analytic Method of. Constructing Program Controls

On One Analytic Method of. Constructing Program Controls Appled Mahemacal Scences, Vol. 9, 05, no. 8, 409-407 HIKARI Ld, www.m-hkar.com hp://dx.do.org/0.988/ams.05.54349 On One Analyc Mehod of Consrucng Program Conrols A. N. Kvko, S. V. Chsyakov and Yu. E. Balyna

More information

One dimensional steady state heat transfer of composite slabs

One dimensional steady state heat transfer of composite slabs BUILDING PHYSICS On dmnsonal sady sa a ransfr of compos slas Par 2 Ass. Prof. Dr. Norr Harmay Budaps Unvrsy of Tcnology and Economcs Dparmn of Buldng Enrgcs and Buldng Srvc Engnrng Inroducon - Buldng Pyscs

More information

Phys463.nb Conductivity. Another equivalent definition of the Fermi velocity is

Phys463.nb Conductivity. Another equivalent definition of the Fermi velocity is 39 Anohr quival dfiniion of h Fri vlociy is pf vf (6.4) If h rgy is a quadraic funcion of k H k L, hs wo dfiniions ar idical. If is NOT a quadraic funcion of k (which could happ as will b discussd in h

More information