LEADER 00861cam2 22002531 450 001 SOBE00036694 005 20130930114036.0 100 $a20130930d2005 |||||ita|0103 ba 101 $aita 102 $aIT 200 0 $a6$fa cura di Maria Grazia Vacchina 210 $aAosta$c[s.n.]$d2005$eAosta$gTipografia ITLA 215 $a230 p.$d24 cm 461 1$1001SOBE00036693$12001 $aAttualitą dell'antico / a cura di Maria Grazia Vacchina$v6 702 1$aVacchina, Mariagrazia$3A600200049298$4070 801 0$aIT$bUNISOB$c20130930$gRICA 850 $aUNISOB 852 $aUNISOB$jFondo|Cosenza$m161399 912 $aSOBE00036694 940 $aM 102 Monografia moderna SBN 941 $aW 957 $aFondo|Cosenza$b000513$i-6$gSI$d161399$hCosenza$rdono$tN$1menle$2UNISOB$3UNISOB$420130930113931.0$520130930113957.0$6menle 996 $a6$963441 997 $aUNISOB LEADER 02976nam 22004935 450 001 9910255030003321 005 20240628121258.0 010 $a9781137313034 010 $a113731303X 024 7 $a10.1057/978-1-137-31303-4 035 $a(CKB)3710000001363102 035 $a(DE-He213)978-1-137-31303-4 035 $a(MiAaPQ)EBC4856765 035 $a(Perlego)3505549 035 $a(EXLCZ)993710000001363102 100 $a20170509d2017 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aMultivariate Modelling of Non-Stationary Economic Time Series /$fby John Hunter, Simon P. Burke, Alessandra Canepa 205 $a2nd ed. 2017. 210 1$aLondon :$cPalgrave Macmillan UK :$cImprint: Palgrave Macmillan,$d2017. 215 $a1 online resource (XIII, 502 p.) 225 1 $aPalgrave Texts in Econometrics,$x2662-6608 311 08$a9780230243309 311 08$a0230243304 320 $aIncludes bibliographical references and index. 327 $aChapter 1. Introduction: Time Series, Common Trends and Equilibrium -- Chapter 2. Multivariate Time Series -- Chapter 3. Cointegration -- Chapter 4. Testing for Cointegration: Under Standard and Non-Standard Conditions -- Chapter 5. Structure and Evaluation -- Chapter 6. Testing in VECMs with Small Sample -- Chapter 7. Heteroscedasticity and Multivariate Volatility -- Chapter 8. Models with Alternative Orders of Integration -- Chapter 9. The Structural Analysis of Time Series. 330 $aThis book examines conventional time series in the context of stationary data prior to a discussion of cointegration, with a focus on multivariate models. The authors provide a detailed and extensive study of impulse responses and forecasting in the stationary and non-stationary context, considering small sample correction, volatility and the impact of different orders of integration. Models with expectations are considered along with alternate methods such as Singular Spectrum Analysis (SSA), the Kalman Filter and Structural Time Series, all in relation to cointegration. Using single equations methods to develop topics, and as examples of the notion of cointegration, Burke, Hunter, and Canepa provide direction and guidance to the now vast literature facing students and graduate economists. 410 0$aPalgrave Texts in Econometrics,$x2662-6608 606 $aEconometrics 606 $aEconometrics 615 0$aEconometrics. 615 14$aEconometrics. 676 $a330.015195 700 $aHunter$b John$4aut$4http://id.loc.gov/vocabulary/relators/aut$0424730 702 $aBurke$b Simon P$4aut$4http://id.loc.gov/vocabulary/relators/aut 702 $aCanepa$b Alessandra$4aut$4http://id.loc.gov/vocabulary/relators/aut 906 $aBOOK 912 $a9910255030003321 996 $aMultivariate Modelling of Non-Stationary Economic Time Series$91942939 997 $aUNINA