New evidences on the link between public capital and economic growth. from a small island economy.

Size: px
Start display at page:

Download "New evidences on the link between public capital and economic growth. from a small island economy."

Transcription

1 New evidence on he link beween public capial and economic growh from a mall iland economy. Jameel Khadharoo, Univeriy of Mauriiu, Redui, Mauriiu jkhadaroo@uom.ac.mu Boopen Seeanah, Univeriy of Technology, Mauriiu Poine-Aux-Sable, Mauriiu b.eeanah@um.inne.mu

2 New evidence on he link beween public capial and economic growh from a mall iland economy. -Abrac- The conribuion of public capial on economic growh ha been he focu of only few udie and ha o dae focued mainly on developed counrie. Moreover i i only laely ha he link ha been analyed in a dynamic framework, allowing for feedback effec. The empirical lieraure ha hardly deal wih mall economie uch a Mauriiu. The preen paper build on a producion funcion approach, uing a unique ime erie daae over he period , o derive he aociaion beween public capial and economic performance and economic growh for Mauriiu. Given he non-aionary characeriic of he daa, a vecor-error-correcion mechanim (VECM) i ued o model he dynamic. Public capial i hown o have ignificanly conribued o Mauriian economic performance. Moreover reul ugge ha here may be indirec effec via privae capial accumulaion a well. Key word Public capial, Economic Growh, Vecor-error-correcion mechanim. 2

3 I. Inroducion Capial formaion originae from boh he privae and public ecor of he economy. Economic udie have moly concenraed on he link beween privae and oal capial accumulaion and developmen. The conribuion of public capial in he above conex ha been he focu of only few udie. Even hen he majoriy of hee udie have been baed on aeing he conribuion of he public capial inpu in an exended Cobb- Dougla pecificaion uing a aic framework (ee Achauer (989), Munnell (990, 992)). I i only laely ha cholar have analyed he link uing dynamic economeric framework (ee Pereira and De Fruco (999), Surm, Jacob and Grooe (999), Lighhar (2000), Pereira (2000), Pereira and Andraz (200) and Pereira and Roca Sagale (2003) among oher). Thee udie have reaed public inpu a an unpaid facor and have overall eablihed poiive impac of public capial on economic growh. There have alo been a few excepion which repored inignifican effec (ee Taom (99), Hulen and Schwab (993) and Holz-Eakin (994)). More imporanly however, mo of exiing lieraure aemping o uppor he public capial-growh hypohei ha been baed on developed economie cae uch a US and Weern Europe. Among he very carce udie on developing counrie are hoe from Looney (997) who udied he link for he cae of Pakian and Ghali (998) for he cae of Tuniia. In he fir cae public capial wa repored no o have been inigaing privae ecor expanion while in he econd cae public capial were even een o have a negaive effec on privae invemen and hu oupu. 3

4 The preen udy aemp o fill a gap in he lieraure by analying he link beween public capial accumulaion and economic growh for he cae of an iland economy, namely, Mauriiu. I ue a uniquely conruced ime erie daae daing back ince 950 whereby he oal capial ock ha decoupled ino public and privae capial ock. Moreover boh are allowed o ener imulaneouly in an exended Cobb-Dougla producion funcion, wih public capial enering a an unpaid inpu. Dynamic economeric echnique i ued, namely a Vecor Error correcion model (VECM), o analye feedback effec in he yem. The paper addree hu iue peraining o exogeneiy, crowding in and ou and caualiy direcion a well. The rucure of hi paper i a follow Secion 2 decribe he preferred modelling funcion ued and elaborae on he proxie ued and he daa e conrucion. Secion 4 inveigae he empirical link beween he public capial and economic growh for he cae of Mauriiu and ecion 5 conclude and dicue policy implicaion. II. Mehodology and Analyi Dynamic feedback iue and VAR The analyi ue dynamic economeric echnique in a Cobb-Dougla producion funcion framework, namely a Vecor Auoregreive model (VAR), following recen 4

5 udie in public capial-economic growh debae (ee Ghali (998), Surm, Jacob and Grooe (999), Pereira and De Fruco (999), Lighhar (2000) and Pereira and Roca Sagale (2003)) o model he hypohei. I hu ake ino accoun he poibiliy of dynamic feedback among he variable in he model. In fac public capial being an addiional unpaid inpu in he producion funcion, no only affec a counry oupu direcly bu alo indirecly i may affec privae capial and employmen. Moreover he income level of a counry can alo be een o ranlae ino he creaion of more public capial. Daa conrucion and ource Since he overall and alo decoupled privae and public capial ock value for he counry were unavailable, hey had o be conruced uing he Perpeual Invenory Mehod (PIM) a recommended by OECD (200) and he US Bureau of Economic Analyi (999). Thi approach ha been widely ued in he lieraure 2. Conrucion of hee capial ock required diaggregaed invemen daa erie o feed he above mehodology. The Penn-World able (6.) only provided oal invemen figure ince he 950. In an aemp o eparae he oal invemen ino he above componen, we gahered daa on oal governmen capial invemen over he whole period under udy ( ). Thee were available from he variou individual Accounan General See Pereira and De Fruco (999) and Lighhar (2000) for a complee reamen of feedback effec. 2 Thi mehodology ha alo been widely ued in boh claical and recen lieraure) for inance by Munnell (990) and Surm and de Haan (995)). More recenly Jacob e al (997), Lighhar (2000), Canning and Bennahan (2000), and Kamp (2003) among oher alo conruced capial ock uing he PIM. 5

6 Annual Repor of he counry and alo from he Financial Accoun of he Mauriian Colony for period before independence (pre-968). To meaure labour we ued employmen level figure available from he Cenral Saiical Office (CSO) and he Bi-annual Dige of Saiic (variou iue). The dependen variable oupu wa proxied by he real Gro Domeic Produc a conan price and wa generaed from he Penn World Table (6.). Model Specificaion and preliminary e We exend a claical Cobb Dougla funcion and diaggregae he capial ock ino privae and public capial. I implie wriing he following heoreical model β β 2 β 3 Q A ( K ) ( G ) ( L ) equaion Q denoe he economy oupu, A () he hif in he producion funcion aribued o echnical progre, which i aumed o be Hick neural, K he privae capial ock, G i he public capial ock and L labour. Taking log on boh ide of he equaion and denoing he lowercae variable a he naural log of he repecive uppercae variable reul in he following: y 3 α β k β 2g β l ε equaion 2 6

7 Before conidering he appropriae pecificaion of he VAR, he univariae properie of aionariy of he daa erie are inveigaed uing he Augmened Dickey-Fuller (ADF) (979) and Phillip-Perron (PP) (988) uni-roo e. The reul are ummaried in able and 2. Te for aionariy (refer o able and 2) how ha all our variable are inegraed of order (I()) and hu aionary in difference. Furher analyi in erm of coinegraion uing he Johanen Maximum Likelihood approach have been underaken and i repored in able 3. The Schwarz Bayeian crierion (SBC) uggeed a VAR of order 2. Evidence from boh race and maximal eigenvalue e ugge ha here i a mo a ingle coinegraing vecor or analogouly 2 independen common ochaic rend wihin he 3 variable equaion. A he 5% level, race value and maximum eigenvalue e 3 boh how here i one coinegraing vecor. Engle and Granger (987) howed by he error-repreenaion heorem ha coinegraed variable implie in effec an error correcion model (ECM). He argued ha regreion of he fir difference of coinegraed variable would reul in mipecificaion error. Accordingly, he VAR wa accordingly formulaed in a Vecor Error Correcion model (VECM) o analye he dynamic of he relaionhip. Thi involve he incluion of he lagged error of he coinegraing regreion a one of he independen variable in he regreion equaion. 3 For he maximum Eigen Value, he relevan compued aiic i a compared o 2.2 and for he race value, compued aiic i 7.97 compared o criical

8 The Vecor Error Correcion Model We derive he model following Johanen (988, 996), Hendry (995), Ender (995), and Ghali (998) and pecify he following Z Ψ Z Ψ2Z 2... Ψk Z k μ η equaion 3 Where Z vecor of (n k) dimenion Ψ k vecor of (n n) dimenion η Vecor of unanicipaed impule (movemen in X ) niid(0,σ) Where n i he number of variable in he VAR, k i he dimenion of he VAR, and i ime. For he preen analyi, our VAR coni of four endogenou variable [ (n4), Z y, g, k, l ] and a conan erm and he dummy variable 4. The yem feaure 2 lag (k2) ha were choen uing SBC. So z i a 4 x vecor conaining y, k, l and g where again y i real GDP, k i privae capial ock, l i he level of employmen and g i our public capial ock. 4 Eimae of a VECM wihou any dummy wa underaken for boh pecificaion and howed ha he reidual were no random and depiced a marked drop in he year 960. Upon inveigaion we realied ha hi wa due o cyclone Carol, he mo devaaing cyclone of all ime. Thu a dummy variable wa included o ake hi ino accoun. Moreover he regreion wa alo run including a ime rend, dummy for oher major cyclone and wih a po independen dummy (independenly and ogeher). However heir repecive coefficien proved o be aiically inignifican and were judged no appropriae in our analyi. In any cae he reul obained were no oo differen from he acual one. 8

9 Since he variable are I () variable ha are I (0) afer applying he difference filer once and a i ha been eablihed hey are alo coinegraed of order, we may impoe hi conrain upon our unrericed VAR o enable a Vecor Error Correcion Model formulaion. The hor run dynamic can be udied uing he following general Vecor Error Correcion Model (VECM): Z Γ Z Γ Z Γ Z ΠZ μ η k k k equaion 4 Where Z i he vecor of growh rae of he above four variable, and he Γ are eimable parameer, i a difference operaor, η i a defined above. Π i he long run parameer marix wih rank equal o r (in our cae i i one), he number of coinegraing vecor uch ha <r<n-. Wih r coinegraing vecor (< r< 4), Π having a rank of r can be decompoed a Πα β, wih α and β boh being (n x k), or 4 x marice. α i defined a he adjumen or loading coefficien which meaure he rengh of he coinegraing vecor in he VEC model or in oher word he peed of adjumen. The β are parameer in he coinegraing relaionhip and repreen he long run coefficien. Small leer denoe ha he variable are in naural logarihmic erm. The yem feaure 2 lag (k2) ha were choen uing SBC. Analyi 9

10 The eimae of α and β are preened in he following able. The long run eimae of β indicae ha all he variable, including public capial have a poiive and ignifican effec on he level of oupu of he counry. In fac he oupu elaiciy wih repec o public capial i and indicae ha a 0% increae in public capial ock of he counry i likely o bring a 3.56% increae in he economic growh. Thi value i no oo far from wha oher cholar repored in heir udie, for inance Achauer (989) and Munnell (992) repored an elaiciy of around 0.4, Eber (997) an elaiciy of 0.38 and Pereira and De Fruo (999) an elaiciy of 0.65 for he cae of USA and Lighhar (2000) oberved an elaiciy of 0.20 for Porugee cae. Privae capial ock conribuion, a expeced, i repored o be he highe and a poiive relaionhip for labour a well i oberved. Weak exogeneiy e on each of he equaion below were alo performed, ha i eing repecively if α 0, α 2 0, α 3 0 and α 4 0 (refer o yem of equaion below). The Walde yield Likelihood or Chi quare value obained are 5.58, 0.56, , and 4.47 repecively. The reul enable u o rejec he null hypohei of weak exogeneiy a 95% ignificance level in all cae and we hu proceeded wih an unchanged yem of equaion. Now he vecor error correcion repreenaion can be expanded in he following e of equaion 0

11 l g k y y, 4, 3, 2,, 0 ε α υ θ θ θ θ θ i) l g k y k 2, 2 4, 3, 2,, 0 ε υ α δ δ δ δ δ ii) l g k y g 3, 3 4, 3, 2,, 0 ε υ α ρ ρ ρ ρ ρ iii) l g k y l 4, 4 4, 3, 2,, 0 ε υ α μ μ μ μ μ iv) where i he number of feaured lag θ,δ,ρ,μ are he hor erm parameer of he lagged variable α, α 2, α 3 and α 4 are he adjumen coefficien and ν i he coinegraing vecor. Eimae of he Error-Correcion Model OLS eimae of he error-correcion model are preened in able 5. The yem of equaion pae he diagnoi e relaed o erial correlaion (baed on Lagrange muliplier e of reidual erial correlaion) and heerocedaiciy (baed on he regreion of quared reidual on quared fied value).

12 The VECM model reveal ha he hor run parameer in privae capial, public capial and employmen ha a poiive and ignifican effec on he level of oupu of he counry. The analyi how ha public capial (wih an oupu elaiciy of 0.223) indeed conribue o economic performance, hough no o he ame exen a privae capial (wih an oupu elaiciy of 0.72). Referring o column 2 above, i i alo inereing o noe ha public capial eem alo o impac poiively on privae capial hu concluding ha ome indirec effec migh alo be preen. Thee reul are in line wih heoreical raionale. Moreover i can be oberved ha he adjumen parameer i which indicae a relaively average adjumen peed of he yem o i long run equilibrium. I reflec he peed a which he diequilibrium i made for in he nex period. Thi adjumen peed coupled wih he fac ha he hor run parameer i maller han he long run parameer migh indeed alo ugge ha public capial ake ime o aain i full impac on he economy. ECM baed Caualiy e In our eing (refer o he yem of equaion 5i 5v), he analyi of a Granger-caual relaion from infrarucure on GDP boil down o eing wheher he um of he θ 3, (or θ 3, in equaion 5i) elemen in above equaion differ from zero. However, we canno ue ordinary F-e, which apply o he individual equaion, becaue he error erm may be correlaed over he equaion, and g affec y hrough hee correlaed error erm. Following Geweke e al (983), who indicaed ha he Granger procedure conduced uing a Wald chi-quare e aiic ouperform oher caualiy e in a erie of 2

13 Mone-Carlo experimen, we accordingly apply Wald e o e erie of pair-wie caualiy. Thu o e wheher public invemen Granger caue growh, we e he null hypohei H 0 : θ 3, 0 uing a Chi quare aiic. In equaion 5i, rericing θ 3, 0, yield a Chi Square aiic of , and i aiically ignifican a 95% ignificance. Thi rejec he null hypohei and confirm a caualiy effec from public capial o GDP 5. Same direcion of caualiy i oberved for he cae of privae capial accumulaion and employmen and economic growh (refer o able 6) Revere Caualiy Teing for revere caualiy, would be o examine if growh Granger caue public invemen and hi would mean eing he null hypohei H 0 : ρ, 0 in he hird equaion (in equaion 8 iii). The Wald e for he above gave a Chi Square aiic of The null hypohei i hu acceped and implie non-caual effec from growh o public capial. So deciion o inve eem o be independen of economic ae of he economy. On he oher hand, here i evidence of revere cauaion from GDP o privae invemen and bi-direcionaliy beween hee wo variable. Crowding-in or Crowding-ou? 5 We alo performed block caualiy e and i confirm he reul. 3

14 The null hypohei H 0 : δ 3, 0, uing equaion 5ii above, i eed o inveigae wheher public invemen Ganger caue privae invemen. i a e of A Wald e reuled in a Chi Square value of which i more han he criical value a 90% ignificance level hu indicaing ha public capial arac privae invemen. However here i no indicaion of caualiy from privae o public capial accumulaion. The reul of ECM baed caualiy are ummaried in able 6. Reul obained from he ECM baed caualiy have been found in general o conolidae hoe from he VECM approach. Moreover impule repone analyi performed i alo in line wih he above finding 6. IV. Summary of reul The udy aemped o fill a gap in he lieraure by uing a mulivariae dynamic framework o udy link beween public capial and economic performance for a mall iland economy. Reul from he analyi revealed ha public capial ha been an inrumenal elemen in he economic progre of he economy over he period of udy. The oupu elaiciie are eimaed o be in he hor run and in he long run uggeing ha public capial ake ome ime o be fully producive. The ECM baed caualiy and impule repone analyi alo end o confirm he above link. Furher analyi of variable indicae ha here exi no feedback from he counry level of 6 Deailed analyi of impule repone funcion are available from he auhor upon reque. 4

15 oupu o he invemen in public capial and alo ha public capial eem o arac privae capial hu uggeing he poibiliy of crowding in effec. However he udy could no eablih revere cauaion effec in boh of he above cae hu indicaing ha he public capial i poible an exogenou iem for he cae of Mauriiu. I i recommended above all ha governmen refrain ielf in undergoing draic cu, paricularly in ranpor capial expendiure, even in difficul ime. I i believed ha he governmen would be beer off in aking advanage of World Bank and oher inernaional iniuion infrarucural and developmenal loan inead of capial expendiure cu from he budge. Governmen need o ake immediae acion o formulae and adop a long erm viion and pell ou inegraed infrarucural policie involving all ake holder. Broad paricipaion of differen inere group and conumer i eenial for he effecivene of uch planning. The long erm plan hould alo incorporae he developmen of a land managemen regime o avoid miue of land. Given governmen budge conrain and in he ligh of our empirical analyi, he cae of privae financing and join public/privae financing arrangemen hould be le ambiguou o long here i addiion o he counry ock capial, no maer who i financing i. Governmen hould enure ha he privae ecor have ufficien incenive o inve in ranpor capial and in i ervice a well. To hi end, he governmen need o develop a efficien iniuional framework and furher improvemen are alo required in 5

16 a number of area o creae a conducive environmen: Thee include improving he legilaive and regulaory environmen, including he formulaion of a BOT law, removing unneceary bureaucraic procedure and pracice, markeing he poenial of Mauriiu o he inernaional inveor communiy. Reference Achauer, D (989), I public expendiure producive?, Journal of Moneary Economic, Vol. 23, pp Dickey, D.A and W.A. Fuller (979), Diribuion of he eimaor for auoregreive ime erie wih a uni roo, Journal of he American Saiical Aociaion. Eber, R.W (990), Public infrarucure and regional economic developmen, Economic Review, Federal Reerve Bank of Cleveland, 26(): pp 5-27 Fernald, G. J.(999), Road o properiy? Aeing he link beween public capial and Produciviy, The American Economic Review, June 999 pp

17 Fiher R.C (997), The effec of ae and local public ervice on economic developmen, New England Economic review, March 997, pp Garcia-Mila, T, T.J McGuire (992), The conribuion of publicly provided inpu o ae' economie, Regional Science and Urban Economic, Vol.22, pp Ghali, K.H.(998) Public invemen and privae capial formaion in a vecor-errorcorrecion model of growh, Applied Economic Vol.30, pp Hendry, D.(995), Dynamic Economeric, Oxford univeriy Pre Heon A, R Summer and B.Aen (2002), Penn World Table Verion 6., Cener for Inernaional Comparion a he Univeriy of Pennylvania (CICUP) Holz-Eakin, D.(994), Public ecor capial and he produciviy puzzle, The review of economic and Saiic LXXVI, pp 2-2 Hulen, C. and R. Schwab(993), Public capial formaion and he growh of regional manufacuring indurie, Naional Tax Journal XLVI, pp Johanen, S (988), Saiical Analyi of coinegraion vecor, Journal of Economic Dynamic and Conrol, Vol.2, pp

18 Lighhar, J.E.(2000), Public Capial and oupu growh in Porugal: An Empirical Analyi, IMF working paper WP/00/ Looney, R.E (997), Infrarucure and Privae Secor Invemen in Pakian, Journal of Aian Economic. Munnell, A (990), Why ha produciviy declined? Produciviy and public invemen, New England economic Review, Vol. Jan/Feb pp 2-22 OECD (200a), A manual on he meauremen of capial ock, Conumpion of fixed Capial and Capial Service, Pari. Available a Pereira, A.M. and R.F. De Fruo (999), Public Capial Accumulaion and privae ecor Performance, Journal of Urban economic, Vol.46, pp Pereira, A.M (2000), I all public capial equal?, The review of Economic and Saiic, Vol.82(3), pp Pereira M A and Andraz J M (200), On he impac of public invemen on he performance of U.S indurie, Public Finance Review Vol. 3 No Pereira, A. M. and O Roca-Sagale (2003), Spillover effec of public capial formaion: evidence from he Spanih Region, Journal of Urban economic Vol. 53 pp

19 Phillip, P.C.B and Perron,P (988), Teing for a uni roo in ime erie regreion, Biomerica, Vol.75, pp Srum J. and Jacob J and Grooe J (999), Oupu effec of infrarucure invemen in he Neherland , Journal of Macroeconomic, Vol. 2, pp Taom, J.(99), Public capial and privae ecor performance, Review of he Federal Reerve Bank of S Loui, pp 3-5 9

20 Table : Summary reul of Uni Roo Te in level form: Dickey-Fuller and Phillip/Perron Te Variable Lag Aug. Phillip Criical Variable Aug Dickey Criical Variable (in log) elecion Dickey Perron Value Type Fuller Value Type Fuller (ime rend () y I() I() k I() I() g I() I() l I() I() Table 2: Summary reul of Uni Roo Te in fir difference : D/F and Phillip/Perron Te Variable Lag Aug. Phillip Criical Variable Aug Dickey Criical Variable (in log) elecion Dickey Perron Value Type Fuller(wih Value Type Fuller ime rend() y I(0) I(0) k I(0) I(0) g I(0) I(0) l I(0) I(0) 20

21 Table 3: Te reul from Johanen procedure Johanen Maximum Likelihood procedure of he coinegraing regreion y (k,g,l) :number of coinegraing vecor() uing he coinegraion likelihood raio. Null Alernaive Te Criical Value Criical Value Hypohei Hypohei Saiic 5% 0% Maximal eigenvalue of he ochaic r0 r marix r< r r<2 r Trace of he r0 r> ochaic marix r< r> r<2 r> Table 4: α and β vecor Variable β -raio α -raio y *** k -0.79*** *** 3.25 g *** ** l -0.55* ** 2. ignifican a 0%, ** ignifican a 5%, ***ignifican a % 2

22 Table 5 :Eimae of he Error-Correcion Model Variable y k g l Conan -2.0*** 0.767*** ** y * k 0.79*** 0.746*** g 0.228* 0.** 0.487*** 0.266* l 0.25* ** Dum *** 0.037* ** υ -0.25*** -0.64*** -0.94** 0.204*** 2 R *ignifican a 0%, ** ignifican a 5%, ***ignifican a % Table 6 : Summary of ECM-baed caualiy e Direcion of cauaion Χ 2 aiic Concluion g caue y Χ Caualiy exi k caue y Χ Caualiy exi y caue g Χ Caualiy doe no exi y caue k Χ Caualiy exi g caue k Χ Caualiy exi k caue g Χ 2.5 Caualiy doe no exi 22

Notes on cointegration of real interest rates and real exchange rates. ρ (2)

Notes on cointegration of real interest rates and real exchange rates. ρ (2) Noe on coinegraion of real inere rae and real exchange rae Charle ngel, Univeriy of Wiconin Le me ar wih he obervaion ha while he lieraure (mo prominenly Meee and Rogoff (988) and dion and Paul (993))

More information

Investment-specific Technology Shocks, Neutral Technology Shocks and the Dunlop-Tarshis Observation: Theory and Evidence

Investment-specific Technology Shocks, Neutral Technology Shocks and the Dunlop-Tarshis Observation: Theory and Evidence Invemen-pecific Technology Shock, Neural Technology Shock and he Dunlop-Tarhi Obervaion: Theory and Evidence Moren O. Ravn, European Univeriy Iniue and he CEPR Saverio Simonelli, European Univeriy Iniue

More information

Vectorautoregressive Model and Cointegration Analysis. Time Series Analysis Dr. Sevtap Kestel 1

Vectorautoregressive Model and Cointegration Analysis. Time Series Analysis Dr. Sevtap Kestel 1 Vecorauoregressive Model and Coinegraion Analysis Par V Time Series Analysis Dr. Sevap Kesel 1 Vecorauoregression Vecor auoregression (VAR) is an economeric model used o capure he evoluion and he inerdependencies

More information

Exercises, Part IV: THE LONG RUN

Exercises, Part IV: THE LONG RUN Exercie, Par IV: THE LOG RU 4. The olow Growh Model onider he olow rowh model wihou echnoloy prore and wih conan populaion. a) Define he eady ae condiion and repreen i raphically. b) how he effec of chane

More information

NECESSARY AND SUFFICIENT CONDITIONS FOR LATENT SEPARABILITY

NECESSARY AND SUFFICIENT CONDITIONS FOR LATENT SEPARABILITY NECESSARY AND SUFFICIENT CONDITIONS FOR LATENT SEPARABILITY Ian Crawford THE INSTITUTE FOR FISCAL STUDIES DEPARTMENT OF ECONOMICS, UCL cemmap working paper CWP02/04 Neceary and Sufficien Condiion for Laen

More information

u(t) Figure 1. Open loop control system

u(t) Figure 1. Open loop control system Open loop conrol v cloed loop feedbac conrol The nex wo figure preen he rucure of open loop and feedbac conrol yem Figure how an open loop conrol yem whoe funcion i o caue he oupu y o follow he reference

More information

CHAPTER 7: SECOND-ORDER CIRCUITS

CHAPTER 7: SECOND-ORDER CIRCUITS EEE5: CI RCUI T THEORY CHAPTER 7: SECOND-ORDER CIRCUITS 7. Inroducion Thi chaper conider circui wih wo orage elemen. Known a econd-order circui becaue heir repone are decribed by differenial equaion ha

More information

Ready for euro? Empirical study of the actual monetary policy independence in Poland VECM modelling

Ready for euro? Empirical study of the actual monetary policy independence in Poland VECM modelling Macroeconomerics Handou 2 Ready for euro? Empirical sudy of he acual moneary policy independence in Poland VECM modelling 1. Inroducion This classes are based on: Łukasz Goczek & Dagmara Mycielska, 2013.

More information

How to Deal with Structural Breaks in Practical Cointegration Analysis

How to Deal with Structural Breaks in Practical Cointegration Analysis How o Deal wih Srucural Breaks in Pracical Coinegraion Analysis Roselyne Joyeux * School of Economic and Financial Sudies Macquarie Universiy December 00 ABSTRACT In his noe we consider he reamen of srucural

More information

Randomized Perfect Bipartite Matching

Randomized Perfect Bipartite Matching Inenive Algorihm Lecure 24 Randomized Perfec Biparie Maching Lecurer: Daniel A. Spielman April 9, 208 24. Inroducion We explain a randomized algorihm by Ahih Goel, Michael Kapralov and Sanjeev Khanna for

More information

2. VECTORS. R Vectors are denoted by bold-face characters such as R, V, etc. The magnitude of a vector, such as R, is denoted as R, R, V

2. VECTORS. R Vectors are denoted by bold-face characters such as R, V, etc. The magnitude of a vector, such as R, is denoted as R, R, V ME 352 VETS 2. VETS Vecor algebra form he mahemaical foundaion for kinemaic and dnamic. Geomer of moion i a he hear of boh he kinemaic and dnamic of mechanical em. Vecor anali i he imehonored ool for decribing

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

Stat13 Homework 7. Suggested Solutions

Stat13 Homework 7. Suggested Solutions Sa3 Homework 7 hp://www.a.ucla.edu/~dinov/coure_uden.hml Suggeed Soluion Queion 7.50 Le denoe infeced and denoe noninfeced. H 0 : Malaria doe no affec red cell coun (µ µ ) H A : Malaria reduce red cell

More information

Lecture 5. Time series: ECM. Bernardina Algieri Department Economics, Statistics and Finance

Lecture 5. Time series: ECM. Bernardina Algieri Department Economics, Statistics and Finance Lecure 5 Time series: ECM Bernardina Algieri Deparmen Economics, Saisics and Finance Conens Time Series Modelling Coinegraion Error Correcion Model Two Seps, Engle-Granger procedure Error Correcion Model

More information

Introduction to Congestion Games

Introduction to Congestion Games Algorihmic Game Theory, Summer 2017 Inroducion o Congeion Game Lecure 1 (5 page) Inrucor: Thoma Keelheim In hi lecure, we ge o know congeion game, which will be our running example for many concep in game

More information

International Business Cycle Models

International Business Cycle Models Inernaional Buine Cycle Model Sewon Hur January 19, 2015 Overview In hi lecure, we will cover variou inernaional buine cycle model Endowmen model wih complee marke and nancial auarky Cole and Obfeld 1991

More information

EECE 301 Signals & Systems Prof. Mark Fowler

EECE 301 Signals & Systems Prof. Mark Fowler EECE 31 Signal & Syem Prof. Mark Fowler Noe Se #27 C-T Syem: Laplace Tranform Power Tool for yem analyi Reading Aignmen: Secion 6.1 6.3 of Kamen and Heck 1/18 Coure Flow Diagram The arrow here how concepual

More information

Problem Set If all directed edges in a network have distinct capacities, then there is a unique maximum flow.

Problem Set If all directed edges in a network have distinct capacities, then there is a unique maximum flow. CSE 202: Deign and Analyi of Algorihm Winer 2013 Problem Se 3 Inrucor: Kamalika Chaudhuri Due on: Tue. Feb 26, 2013 Inrucion For your proof, you may ue any lower bound, algorihm or daa rucure from he ex

More information

Explaining Total Factor Productivity. Ulrich Kohli University of Geneva December 2015

Explaining Total Factor Productivity. Ulrich Kohli University of Geneva December 2015 Explaining Toal Facor Produciviy Ulrich Kohli Universiy of Geneva December 2015 Needed: A Theory of Toal Facor Produciviy Edward C. Presco (1998) 2 1. Inroducion Toal Facor Produciviy (TFP) has become

More information

13.1 Circuit Elements in the s Domain Circuit Analysis in the s Domain The Transfer Function and Natural Response 13.

13.1 Circuit Elements in the s Domain Circuit Analysis in the s Domain The Transfer Function and Natural Response 13. Chaper 3 The Laplace Tranform in Circui Analyi 3. Circui Elemen in he Domain 3.-3 Circui Analyi in he Domain 3.4-5 The Tranfer Funcion and Naural Repone 3.6 The Tranfer Funcion and he Convoluion Inegral

More information

Distribution and growth in France and Germany single equation. estimations and model simulations based on the Bhaduri/Marglin-model *

Distribution and growth in France and Germany single equation. estimations and model simulations based on the Bhaduri/Marglin-model * Diribuion and growh in France and Germany ingle equaion eimaion and model imulaion baed on he Bhaduri/Marglin-model * Eckhard Hein and Lena Vogel - revied verion - Correponding auhor PD Dr. Eckhard Hein

More information

Review of Economic Dynamics

Review of Economic Dynamics Review of Economic Dynamic 14 2011 136 155 Conen li available a ScienceDirec Review of Economic Dynamic www.elevier.com/locae/red Invemen-pecific echnology hock and inernaional buine cycle: An empirical

More information

Let. x y. denote a bivariate time series with zero mean.

Let. x y. denote a bivariate time series with zero mean. Linear Filer Le x y : T denoe a bivariae ime erie wih zero mean. Suppoe ha he ime erie {y : T} i conruced a follow: y a x The ime erie {y : T} i aid o be conruced from {x : T} by mean of a Linear Filer.

More information

Unit Root Time Series. Univariate random walk

Unit Root Time Series. Univariate random walk Uni Roo ime Series Univariae random walk Consider he regression y y where ~ iid N 0, he leas squares esimae of is: ˆ yy y y yy Now wha if = If y y hen le y 0 =0 so ha y j j If ~ iid N 0, hen y ~ N 0, he

More information

Macroeconomics 1. Ali Shourideh. Final Exam

Macroeconomics 1. Ali Shourideh. Final Exam 4780 - Macroeconomic 1 Ali Shourideh Final Exam Problem 1. A Model of On-he-Job Search Conider he following verion of he McCall earch model ha allow for on-he-job-earch. In paricular, uppoe ha ime i coninuou

More information

Bias in Conditional and Unconditional Fixed Effects Logit Estimation: a Correction * Tom Coupé

Bias in Conditional and Unconditional Fixed Effects Logit Estimation: a Correction * Tom Coupé Bias in Condiional and Uncondiional Fixed Effecs Logi Esimaion: a Correcion * Tom Coupé Economics Educaion and Research Consorium, Naional Universiy of Kyiv Mohyla Academy Address: Vul Voloska 10, 04070

More information

Lecture 26. Lucas and Stokey: Optimal Monetary and Fiscal Policy in an Economy without Capital (JME 1983) t t

Lecture 26. Lucas and Stokey: Optimal Monetary and Fiscal Policy in an Economy without Capital (JME 1983) t t Lecure 6. Luca and Sokey: Opimal Moneary and Fical Policy in an Economy wihou Capial (JME 983. A argued in Kydland and Preco (JPE 977, Opimal governmen policy i likely o be ime inconien. Fiher (JEDC 98

More information

ANSWERS TO ODD NUMBERED EXERCISES IN CHAPTER

ANSWERS TO ODD NUMBERED EXERCISES IN CHAPTER John Riley 6 December 200 NWER TO ODD NUMBERED EXERCIE IN CHPTER 7 ecion 7 Exercie 7-: m m uppoe ˆ, m=,, M (a For M = 2, i i eay o how ha I implie I From I, for any probabiliy vecor ( p, p 2, 2 2 ˆ ( p,

More information

Algorithmic Discrete Mathematics 6. Exercise Sheet

Algorithmic Discrete Mathematics 6. Exercise Sheet Algorihmic Dicree Mahemaic. Exercie Shee Deparmen of Mahemaic SS 0 PD Dr. Ulf Lorenz 7. and 8. Juni 0 Dipl.-Mah. David Meffer Verion of June, 0 Groupwork Exercie G (Heap-Sor) Ue Heap-Sor wih a min-heap

More information

Modeling the Evolution of Demand Forecasts with Application to Safety Stock Analysis in Production/Distribution Systems

Modeling the Evolution of Demand Forecasts with Application to Safety Stock Analysis in Production/Distribution Systems Modeling he Evoluion of Demand oreca wih Applicaion o Safey Sock Analyi in Producion/Diribuion Syem David Heah and Peer Jackon Preened by Kai Jiang Thi ummary preenaion baed on: Heah, D.C., and P.L. Jackon.

More information

Price of Stability and Introduction to Mechanism Design

Price of Stability and Introduction to Mechanism Design Algorihmic Game Theory Summer 2017, Week 5 ETH Zürich Price of Sabiliy and Inroducion o Mechanim Deign Paolo Penna Thi i he lecure where we ar deigning yem which involve elfih player. Roughly peaking,

More information

, the. L and the L. x x. max. i n. It is easy to show that these two norms satisfy the following relation: x x n x = (17.3) max

, the. L and the L. x x. max. i n. It is easy to show that these two norms satisfy the following relation: x x n x = (17.3) max ecure 8 7. Sabiliy Analyi For an n dimenional vecor R n, he and he vecor norm are defined a: = T = i n i (7.) I i eay o how ha hee wo norm aify he following relaion: n (7.) If a vecor i ime-dependen, hen

More information

6.8 Laplace Transform: General Formulas

6.8 Laplace Transform: General Formulas 48 HAP. 6 Laplace Tranform 6.8 Laplace Tranform: General Formula Formula Name, ommen Sec. F() l{ f ()} e f () d f () l {F()} Definiion of Tranform Invere Tranform 6. l{af () bg()} al{f ()} bl{g()} Lineariy

More information

Methodology. -ratios are biased and that the appropriate critical values have to be increased by an amount. that depends on the sample size.

Methodology. -ratios are biased and that the appropriate critical values have to be increased by an amount. that depends on the sample size. Mehodology. Uni Roo Tess A ime series is inegraed when i has a mean revering propery and a finie variance. I is only emporarily ou of equilibrium and is called saionary in I(0). However a ime series ha

More information

Average Case Lower Bounds for Monotone Switching Networks

Average Case Lower Bounds for Monotone Switching Networks Average Cae Lower Bound for Monoone Swiching Nework Yuval Filmu, Toniann Piai, Rober Robere, Sephen Cook Deparmen of Compuer Science Univeriy of Torono Monoone Compuaion (Refreher) Monoone circui were

More information

Suggested Solutions to Midterm Exam Econ 511b (Part I), Spring 2004

Suggested Solutions to Midterm Exam Econ 511b (Part I), Spring 2004 Suggeed Soluion o Miderm Exam Econ 511b (Par I), Spring 2004 1. Conider a compeiive equilibrium neoclaical growh model populaed by idenical conumer whoe preference over conumpion ream are given by P β

More information

Chapter 7: Inverse-Response Systems

Chapter 7: Inverse-Response Systems Chaper 7: Invere-Repone Syem Normal Syem Invere-Repone Syem Baic Sar ou in he wrong direcion End up in he original eady-ae gain value Two or more yem wih differen magniude and cale in parallel Main yem

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

What is maximum Likelihood? History Features of ML method Tools used Advantages Disadvantages Evolutionary models

What is maximum Likelihood? History Features of ML method Tools used Advantages Disadvantages Evolutionary models Wha i maximum Likelihood? Hiory Feaure of ML mehod Tool ued Advanage Diadvanage Evoluionary model Maximum likelihood mehod creae all he poible ree conaining he e of organim conidered, and hen ue he aiic

More information

To become more mathematically correct, Circuit equations are Algebraic Differential equations. from KVL, KCL from the constitutive relationship

To become more mathematically correct, Circuit equations are Algebraic Differential equations. from KVL, KCL from the constitutive relationship Laplace Tranform (Lin & DeCarlo: Ch 3) ENSC30 Elecric Circui II The Laplace ranform i an inegral ranformaion. I ranform: f ( ) F( ) ime variable complex variable From Euler > Lagrange > Laplace. Hence,

More information

Index Number Concepts, Measures and Decompositions of Productivity Growth

Index Number Concepts, Measures and Decompositions of Productivity Growth C Journal of Produciviy Analyi, 9, 27 59, 2003 2003 Kluwer Academic Publiher. Manufacured in The Neherl. Inde Number Concep, Meaure Decompoiion of Produciviy Growh W. ERWIN DIEWERT diewer@econ.ubc.ca Deparmen

More information

Assignment 16. Malaria does not affect the red cell count in the lizards.

Assignment 16. Malaria does not affect the red cell count in the lizards. ignmen 16 7.3.5 If he null hypohei i no rejeced ha he wo ample are differen, hen he Type of Error would be ype II 7.3.9 Fale. The cieni rejeced baed on a bad calculaion, no baed upon ample ha yielded an

More information

Testing for a Single Factor Model in the Multivariate State Space Framework

Testing for a Single Factor Model in the Multivariate State Space Framework esing for a Single Facor Model in he Mulivariae Sae Space Framework Chen C.-Y. M. Chiba and M. Kobayashi Inernaional Graduae School of Social Sciences Yokohama Naional Universiy Japan Faculy of Economics

More information

EE Control Systems LECTURE 2

EE Control Systems LECTURE 2 Copyrigh F.L. Lewi 999 All righ reerved EE 434 - Conrol Syem LECTURE REVIEW OF LAPLACE TRANSFORM LAPLACE TRANSFORM The Laplace ranform i very ueful in analyi and deign for yem ha are linear and ime-invarian

More information

The Brock-Mirman Stochastic Growth Model

The Brock-Mirman Stochastic Growth Model c December 3, 208, Chrisopher D. Carroll BrockMirman The Brock-Mirman Sochasic Growh Model Brock and Mirman (972) provided he firs opimizing growh model wih unpredicable (sochasic) shocks. The social planner

More information

5.2 GRAPHICAL VELOCITY ANALYSIS Polygon Method

5.2 GRAPHICAL VELOCITY ANALYSIS Polygon Method ME 352 GRHICL VELCITY NLYSIS 52 GRHICL VELCITY NLYSIS olygon Mehod Velociy analyi form he hear of kinemaic and dynamic of mechanical yem Velociy analyi i uually performed following a poiion analyi; ie,

More information

Cointegration and Implications for Forecasting

Cointegration and Implications for Forecasting Coinegraion and Implicaions for Forecasing Two examples (A) Y Y 1 1 1 2 (B) Y 0.3 0.9 1 1 2 Example B: Coinegraion Y and coinegraed wih coinegraing vecor [1, 0.9] because Y 0.9 0.3 is a saionary process

More information

Network Flow. Data Structures and Algorithms Andrei Bulatov

Network Flow. Data Structures and Algorithms Andrei Bulatov Nework Flow Daa Srucure and Algorihm Andrei Bulao Algorihm Nework Flow 24-2 Flow Nework Think of a graph a yem of pipe We ue hi yem o pump waer from he ource o ink Eery pipe/edge ha limied capaciy Flow

More information

1 Motivation and Basic Definitions

1 Motivation and Basic Definitions CSCE : Deign and Analyi of Algorihm Noe on Max Flow Fall 20 (Baed on he preenaion in Chaper 26 of Inroducion o Algorihm, 3rd Ed. by Cormen, Leieron, Rive and Sein.) Moivaion and Baic Definiion Conider

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

Network Flows: Introduction & Maximum Flow

Network Flows: Introduction & Maximum Flow CSC 373 - lgorihm Deign, nalyi, and Complexiy Summer 2016 Lalla Mouaadid Nework Flow: Inroducion & Maximum Flow We now urn our aenion o anoher powerful algorihmic echnique: Local Search. In a local earch

More information

Financial Econometrics Jeffrey R. Russell Midterm Winter 2009 SOLUTIONS

Financial Econometrics Jeffrey R. Russell Midterm Winter 2009 SOLUTIONS Name SOLUTIONS Financial Economerics Jeffrey R. Russell Miderm Winer 009 SOLUTIONS You have 80 minues o complee he exam. Use can use a calculaor and noes. Try o fi all your work in he space provided. If

More information

Problem Set 5. Graduate Macro II, Spring 2017 The University of Notre Dame Professor Sims

Problem Set 5. Graduate Macro II, Spring 2017 The University of Notre Dame Professor Sims Problem Se 5 Graduae Macro II, Spring 2017 The Universiy of Nore Dame Professor Sims Insrucions: You may consul wih oher members of he class, bu please make sure o urn in your own work. Where applicable,

More information

Additional Methods for Solving DSGE Models

Additional Methods for Solving DSGE Models Addiional Mehod for Solving DSGE Model Karel Meren, Cornell Univeriy Reference King, R. G., Ploer, C. I. & Rebelo, S. T. (1988), Producion, growh and buine cycle: I. he baic neoclaical model, Journal of

More information

NEUTRON DIFFUSION THEORY

NEUTRON DIFFUSION THEORY NEUTRON DIFFUSION THEORY M. Ragheb 4//7. INTRODUCTION The diffuion heory model of neuron ranpor play a crucial role in reacor heory ince i i imple enough o allow cienific inigh, and i i ufficienly realiic

More information

Time series Decomposition method

Time series Decomposition method Time series Decomposiion mehod A ime series is described using a mulifacor model such as = f (rend, cyclical, seasonal, error) = f (T, C, S, e) Long- Iner-mediaed Seasonal Irregular erm erm effec, effec,

More information

On Measuring Pro-Poor Growth. 1. On Various Ways of Measuring Pro-Poor Growth: A Short Review of the Literature

On Measuring Pro-Poor Growth. 1. On Various Ways of Measuring Pro-Poor Growth: A Short Review of the Literature On Measuring Pro-Poor Growh 1. On Various Ways of Measuring Pro-Poor Growh: A Shor eview of he Lieraure During he pas en years or so here have been various suggesions concerning he way one should check

More information

( ) (, ) F K L = F, Y K N N N N. 8. Economic growth 8.1. Production function: Capital as production factor

( ) (, ) F K L = F, Y K N N N N. 8. Economic growth 8.1. Production function: Capital as production factor 8. Economic growh 8.. Producion funcion: Capial as producion facor Y = α N Y (, ) = F K N Diminishing marginal produciviy of capial and labor: (, ) F K L F K 2 ( K, L) K 2 (, ) F K L F L 2 ( K, L) L 2

More information

Do Steel Consumption and Production Cause Economic Growth?: A Case Study of Six Southeast Asian Countries

Do Steel Consumption and Production Cause Economic Growth?: A Case Study of Six Southeast Asian Countries JOURNAL OF INTERNATIONAL AND AREA STUDIES Volume 5, Number, 008, pp.-5 Do Seel Consumpion and Producion Cause Economic Growh?: A Case Sudy of Six Souheas Asian Counries Hee-Ryang Ra This sudy aims o deermine

More information

18.03SC Unit 3 Practice Exam and Solutions

18.03SC Unit 3 Practice Exam and Solutions Sudy Guide on Sep, Dela, Convoluion, Laplace You can hink of he ep funcion u() a any nice mooh funcion which i for < a and for > a, where a i a poiive number which i much maller han any ime cale we care

More information

EE202 Circuit Theory II

EE202 Circuit Theory II EE202 Circui Theory II 2017-2018, Spring Dr. Yılmaz KALKAN I. Inroducion & eview of Fir Order Circui (Chaper 7 of Nilon - 3 Hr. Inroducion, C and L Circui, Naural and Sep epone of Serie and Parallel L/C

More information

CS4445/9544 Analysis of Algorithms II Solution for Assignment 1

CS4445/9544 Analysis of Algorithms II Solution for Assignment 1 Conider he following flow nework CS444/944 Analyi of Algorihm II Soluion for Aignmen (0 mark) In he following nework a minimum cu ha capaciy 0 Eiher prove ha hi aemen i rue, or how ha i i fale Uing he

More information

Introduction D P. r = constant discount rate, g = Gordon Model (1962): constant dividend growth rate.

Introduction D P. r = constant discount rate, g = Gordon Model (1962): constant dividend growth rate. Inroducion Gordon Model (1962): D P = r g r = consan discoun rae, g = consan dividend growh rae. If raional expecaions of fuure discoun raes and dividend growh vary over ime, so should he D/P raio. Since

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

10. State Space Methods

10. State Space Methods . Sae Space Mehods. Inroducion Sae space modelling was briefly inroduced in chaper. Here more coverage is provided of sae space mehods before some of heir uses in conrol sysem design are covered in he

More information

Bayesian Designs for Michaelis-Menten kinetics

Bayesian Designs for Michaelis-Menten kinetics Bayeian Deign for ichaeli-enen kineic John ahew and Gilly Allcock Deparen of Saiic Univeriy of Newcale upon Tyne.n..ahew@ncl.ac.uk Reference ec. on hp://www.a.ncl.ac.uk/~nn/alk/ile.h Enzyology any biocheical

More information

Licenciatura de ADE y Licenciatura conjunta Derecho y ADE. Hoja de ejercicios 2 PARTE A

Licenciatura de ADE y Licenciatura conjunta Derecho y ADE. Hoja de ejercicios 2 PARTE A Licenciaura de ADE y Licenciaura conjuna Derecho y ADE Hoja de ejercicios PARTE A 1. Consider he following models Δy = 0.8 + ε (1 + 0.8L) Δ 1 y = ε where ε and ε are independen whie noise processes. In

More information

Topic 3. Single factor ANOVA [ST&D Ch. 7]

Topic 3. Single factor ANOVA [ST&D Ch. 7] Topic 3. Single facor ANOVA [ST&D Ch. 7] "The analyi of variance i more han a echnique for aiical analyi. Once i i underood, ANOVA i a ool ha can provide an inigh ino he naure of variaion of naural even"

More information

Sample Final Exam (finals03) Covering Chapters 1-9 of Fundamentals of Signals & Systems

Sample Final Exam (finals03) Covering Chapters 1-9 of Fundamentals of Signals & Systems Sample Final Exam Covering Chaper 9 (final04) Sample Final Exam (final03) Covering Chaper 9 of Fundamenal of Signal & Syem Problem (0 mar) Conider he caual opamp circui iniially a re depiced below. I LI

More information

Vehicle Arrival Models : Headway

Vehicle Arrival Models : Headway Chaper 12 Vehicle Arrival Models : Headway 12.1 Inroducion Modelling arrival of vehicle a secion of road is an imporan sep in raffic flow modelling. I has imporan applicaion in raffic flow simulaion where

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

A Specification Test for Linear Dynamic Stochastic General Equilibrium Models

A Specification Test for Linear Dynamic Stochastic General Equilibrium Models Journal of Saisical and Economeric Mehods, vol.1, no.2, 2012, 65-70 ISSN: 2241-0384 (prin), 2241-0376 (online) Scienpress Ld, 2012 A Specificaion Tes for Linear Dynamic Sochasic General Equilibrium Models

More information

Graphs III - Network Flow

Graphs III - Network Flow Graph III - Nework Flow Flow nework eup graph G=(V,E) edge capaciy w(u,v) 0 - if edge doe no exi, hen w(u,v)=0 pecial verice: ource verex ; ink verex - no edge ino and no edge ou of Aume every verex v

More information

A Theoretical Model of a Voltage Controlled Oscillator

A Theoretical Model of a Voltage Controlled Oscillator A Theoreical Model of a Volage Conrolled Ocillaor Yenming Chen Advior: Dr. Rober Scholz Communicaion Science Iniue Univeriy of Souhern California UWB Workhop, April 11-1, 6 Inroducion Moivaion The volage

More information

Buckling of a structure means failure due to excessive displacements (loss of structural stiffness), and/or

Buckling of a structure means failure due to excessive displacements (loss of structural stiffness), and/or Buckling Buckling of a rucure mean failure due o exceive diplacemen (lo of rucural iffne), and/or lo of abiliy of an equilibrium configuraion of he rucure The rule of humb i ha buckling i conidered a mode

More information

The multisubset sum problem for finite abelian groups

The multisubset sum problem for finite abelian groups Alo available a hp://amc-journal.eu ISSN 1855-3966 (prined edn.), ISSN 1855-3974 (elecronic edn.) ARS MATHEMATICA CONTEMPORANEA 8 (2015) 417 423 The muliube um problem for finie abelian group Amela Muraović-Ribić

More information

A Note on Raising the Mandatory Retirement Age and. Its Effect on Long-run Income and Pay As You Go (PAYG) Pensions

A Note on Raising the Mandatory Retirement Age and. Its Effect on Long-run Income and Pay As You Go (PAYG) Pensions The Sociey for Economic Sudies The Universiy of Kiakyushu Working Paper Series No.2017-5 (acceped in March, 2018) A Noe on Raising he Mandaory Reiremen Age and Is Effec on Long-run Income and Pay As You

More information

ACE 562 Fall Lecture 4: Simple Linear Regression Model: Specification and Estimation. by Professor Scott H. Irwin

ACE 562 Fall Lecture 4: Simple Linear Regression Model: Specification and Estimation. by Professor Scott H. Irwin ACE 56 Fall 005 Lecure 4: Simple Linear Regression Model: Specificaion and Esimaion by Professor Sco H. Irwin Required Reading: Griffihs, Hill and Judge. "Simple Regression: Economic and Saisical Model

More information

Unemployment and Mismatch in the UK

Unemployment and Mismatch in the UK Unemploymen and Mismach in he UK Jennifer C. Smih Universiy of Warwick, UK CAGE (Cenre for Compeiive Advanage in he Global Economy) BoE/LSE Conference on Macroeconomics and Moneary Policy: Unemploymen,

More information

Why is Chinese Provincial Output Diverging? Joakim Westerlund, University of Gothenburg David Edgerton, Lund University Sonja Opper, Lund University

Why is Chinese Provincial Output Diverging? Joakim Westerlund, University of Gothenburg David Edgerton, Lund University Sonja Opper, Lund University Why is Chinese Provincial Oupu Diverging? Joakim Weserlund, Universiy of Gohenburg David Edgeron, Lund Universiy Sonja Opper, Lund Universiy Purpose of his paper. We re-examine he resul of Pedroni and

More information

Innova Junior College H2 Mathematics JC2 Preliminary Examinations Paper 2 Solutions 0 (*)

Innova Junior College H2 Mathematics JC2 Preliminary Examinations Paper 2 Solutions 0 (*) Soluion 3 x 4x3 x 3 x 0 4x3 x 4x3 x 4x3 x 4x3 x x 3x 3 4x3 x Innova Junior College H Mahemaics JC Preliminary Examinaions Paper Soluions 3x 3 4x 3x 0 4x 3 4x 3 0 (*) 0 0 + + + - 3 3 4 3 3 3 3 Hence x or

More information

Flow networks. Flow Networks. A flow on a network. Flow networks. The maximum-flow problem. Introduction to Algorithms, Lecture 22 December 5, 2001

Flow networks. Flow Networks. A flow on a network. Flow networks. The maximum-flow problem. Introduction to Algorithms, Lecture 22 December 5, 2001 CS 545 Flow Nework lon Efra Slide courey of Charle Leieron wih mall change by Carola Wenk Flow nework Definiion. flow nework i a direced graph G = (V, E) wih wo diinguihed verice: a ource and a ink. Each

More information

Mean Reversion of Balance of Payments GEvidence from Sequential Trend Break Unit Root Tests. Abstract

Mean Reversion of Balance of Payments GEvidence from Sequential Trend Break Unit Root Tests. Abstract Mean Reversion of Balance of Paymens GEvidence from Sequenial Trend Brea Uni Roo Tess Mei-Yin Lin Deparmen of Economics, Shih Hsin Universiy Jue-Shyan Wang Deparmen of Public Finance, Naional Chengchi

More information

Chapter 16. Regression with Time Series Data

Chapter 16. Regression with Time Series Data Chaper 16 Regression wih Time Series Daa The analysis of ime series daa is of vial ineres o many groups, such as macroeconomiss sudying he behavior of naional and inernaional economies, finance economiss

More information

Solutions to Odd Number Exercises in Chapter 6

Solutions to Odd Number Exercises in Chapter 6 1 Soluions o Odd Number Exercises in 6.1 R y eˆ 1.7151 y 6.3 From eˆ ( T K) ˆ R 1 1 SST SST SST (1 R ) 55.36(1.7911) we have, ˆ 6.414 T K ( ) 6.5 y ye ye y e 1 1 Consider he erms e and xe b b x e y e b

More information

Physics 240: Worksheet 16 Name

Physics 240: Worksheet 16 Name Phyic 4: Workhee 16 Nae Non-unifor circular oion Each of hee proble involve non-unifor circular oion wih a conan α. (1) Obain each of he equaion of oion for non-unifor circular oion under a conan acceleraion,

More information

Has the Business Cycle Changed? Evidence and Explanations. Appendix

Has the Business Cycle Changed? Evidence and Explanations. Appendix Has he Business Ccle Changed? Evidence and Explanaions Appendix Augus 2003 James H. Sock Deparmen of Economics, Harvard Universi and he Naional Bureau of Economic Research and Mark W. Wason* Woodrow Wilson

More information

INFERENTIAL THEORY FOR FACTOR MODELS OF LARGE DIMENSIONS. By Jushan Bai 1

INFERENTIAL THEORY FOR FACTOR MODELS OF LARGE DIMENSIONS. By Jushan Bai 1 Economerica, Vol. 7, o. January, 2003, 35 7 IFEREIAL HEORY FOR FACOR MODELS OF LARGE DIMESIOS By Juhan Bai hi paper develop an inferenial heory for facor model of large dimenion. he principal componen

More information

STATE-SPACE MODELLING. A mass balance across the tank gives:

STATE-SPACE MODELLING. A mass balance across the tank gives: B. Lennox and N.F. Thornhill, 9, Sae Space Modelling, IChemE Process Managemen and Conrol Subjec Group Newsleer STE-SPACE MODELLING Inroducion: Over he pas decade or so here has been an ever increasing

More information

BOKDSGE: A DSGE Model for the Korean Economy

BOKDSGE: A DSGE Model for the Korean Economy BOKDSGE: A DSGE Model for he Korean Economy June 4, 2008 Joong Shik Lee, Head Macroeconomeric Model Secion Research Deparmen The Bank of Korea Ouline 1. Background 2. Model srucure & parameer values 3.

More information

The Residual Graph. 11 Augmenting Path Algorithms. Augmenting Path Algorithm. Augmenting Path Algorithm

The Residual Graph. 11 Augmenting Path Algorithms. Augmenting Path Algorithm. Augmenting Path Algorithm Augmening Pah Algorihm Greedy-algorihm: ar wih f (e) = everywhere find an - pah wih f (e) < c(e) on every edge augmen flow along he pah repea a long a poible The Reidual Graph From he graph G = (V, E,

More information

Admin MAX FLOW APPLICATIONS. Flow graph/networks. Flow constraints 4/30/13. CS lunch today Grading. in-flow = out-flow for every vertex (except s, t)

Admin MAX FLOW APPLICATIONS. Flow graph/networks. Flow constraints 4/30/13. CS lunch today Grading. in-flow = out-flow for every vertex (except s, t) /0/ dmin lunch oday rading MX LOW PPLIION 0, pring avid Kauchak low graph/nework low nework direced, weighed graph (V, ) poiive edge weigh indicaing he capaciy (generally, aume ineger) conain a ingle ource

More information

CS 473G Lecture 15: Max-Flow Algorithms and Applications Fall 2005

CS 473G Lecture 15: Max-Flow Algorithms and Applications Fall 2005 CS 473G Lecure 1: Max-Flow Algorihm and Applicaion Fall 200 1 Max-Flow Algorihm and Applicaion (November 1) 1.1 Recap Fix a direced graph G = (V, E) ha doe no conain boh an edge u v and i reveral v u,

More information

Dynamic Econometric Models: Y t = + 0 X t + 1 X t X t k X t-k + e t. A. Autoregressive Model:

Dynamic Econometric Models: Y t = + 0 X t + 1 X t X t k X t-k + e t. A. Autoregressive Model: Dynamic Economeric Models: A. Auoregressive Model: Y = + 0 X 1 Y -1 + 2 Y -2 + k Y -k + e (Wih lagged dependen variable(s) on he RHS) B. Disribued-lag Model: Y = + 0 X + 1 X -1 + 2 X -2 + + k X -k + e

More information

MASSACHUSETTS INSTITUTE OF TECHNOLOGY Department of Civil and Environmental Engineering

MASSACHUSETTS INSTITUTE OF TECHNOLOGY Department of Civil and Environmental Engineering MASSACHUSETTS INSTITUTE OF TECHNOLOGY Deparmen of Civil and Environmenal Engineering 1.731 Waer Reource Syem Lecure 17 River Bain Planning Screening Model Nov. 7 2006 River Bain Planning River bain planning

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

ESTIMATION OF DYNAMIC PANEL DATA MODELS WHEN REGRESSION COEFFICIENTS AND INDIVIDUAL EFFECTS ARE TIME-VARYING

ESTIMATION OF DYNAMIC PANEL DATA MODELS WHEN REGRESSION COEFFICIENTS AND INDIVIDUAL EFFECTS ARE TIME-VARYING Inernaional Journal of Social Science and Economic Research Volume:02 Issue:0 ESTIMATION OF DYNAMIC PANEL DATA MODELS WHEN REGRESSION COEFFICIENTS AND INDIVIDUAL EFFECTS ARE TIME-VARYING Chung-ki Min Professor

More information

Time Series Test of Nonlinear Convergence and Transitional Dynamics. Terence Tai-Leung Chong

Time Series Test of Nonlinear Convergence and Transitional Dynamics. Terence Tai-Leung Chong Time Series Tes of Nonlinear Convergence and Transiional Dynamics Terence Tai-Leung Chong Deparmen of Economics, The Chinese Universiy of Hong Kong Melvin J. Hinich Signal and Informaion Sciences Laboraory

More information

Diebold, Chapter 7. Francis X. Diebold, Elements of Forecasting, 4th Edition (Mason, Ohio: Cengage Learning, 2006). Chapter 7. Characterizing Cycles

Diebold, Chapter 7. Francis X. Diebold, Elements of Forecasting, 4th Edition (Mason, Ohio: Cengage Learning, 2006). Chapter 7. Characterizing Cycles Diebold, Chaper 7 Francis X. Diebold, Elemens of Forecasing, 4h Ediion (Mason, Ohio: Cengage Learning, 006). Chaper 7. Characerizing Cycles Afer compleing his reading you should be able o: Define covariance

More information

The Validity of the Tourism-Led Growth Hypothesis for Thailand

The Validity of the Tourism-Led Growth Hypothesis for Thailand MPRA Munich Personal RePEc Archive The Validiy of he Tourism-Led Growh Hypohesis for Thailand Komain Jiranyakul Naional Insiue of Developmen Adminisraion Augus 206 Online a hps://mpra.ub.uni-muenchen.de/72806/

More information