{"product_id":"applied-time-series-modelling-and-forecasting-isbn-9780470844434","title":"Applied Time Series Modelling and Forecasting","description":"\u003ci\u003eApplied Time Series Modelling and Forecasting\u003c\/i\u003e provides a relatively non-technical introduction to applied time series econometrics and forecasting involving non-stationary data.  The emphasis is very much on the why and how and, as much as possible, the authors confine technical material to boxes or point to the relevant sources for more detailed information.  \u003cp\u003eThis book is based on an earlier title \u003ci\u003eUsing Cointegration Analysis in Econometric Modelling\u003c\/i\u003e by Richard Harris.  As well as updating material covered in the earlier book, there are two major additions involving panel tests for unit roots and cointegration and forecasting of financial time series.  Harris and Sollis have also incorporated as many of the latest techniques in the area as possible including: testing for periodic integration and cointegration; GLS detrending when testing for unit roots; structural breaks and season unit root testing; testing for cointegration with a structural break; asymmetric tests for cointegration; testing for super-exogeniety; seasonal cointegration in multivariate models; and approaches to structural macroeconomic modelling.  In addition, the discussion of certain topics, such as testing for unique vectors, has been simplified.\u003c\/p\u003e  Preface.  \u003cp\u003e1. Introduction and Overview.\u003c\/p\u003e \u003cp\u003eSome Initial Concepts.\u003c\/p\u003e \u003cp\u003eForecasting.\u003c\/p\u003e \u003cp\u003eOutline of the Book.\u003c\/p\u003e \u003cp\u003e2. Short- and Long-run Models.\u003c\/p\u003e \u003cp\u003eLong-run Models.\u003c\/p\u003e \u003cp\u003eStationary and Non-stationary Time Series.\u003c\/p\u003e \u003cp\u003eSpurious Regressions.\u003c\/p\u003e \u003cp\u003eCointegration.\u003c\/p\u003e \u003cp\u003eShort-run Models.\u003c\/p\u003e \u003cp\u003eConclusion.\u003c\/p\u003e \u003cp\u003e3. Testing for Unit Roots.\u003c\/p\u003e \u003cp\u003eThe Dickey–Fuller Test.\u003c\/p\u003e \u003cp\u003eAugmented Dickey–Fuller Test.\u003c\/p\u003e \u003cp\u003ePower and Level of Unit Root Tests.\u003c\/p\u003e \u003cp\u003eStructural Breaks and Unit Root Tests.\u003c\/p\u003e \u003cp\u003eSeasonal Unit Roots.\u003c\/p\u003e \u003cp\u003eStructural Breaks and Seasonal Unit Root Tests.\u003c\/p\u003e \u003cp\u003ePeriodic Integration and Unit Root-testing.\u003c\/p\u003e \u003cp\u003eConclusion on Unit Root Tests.\u003c\/p\u003e \u003cp\u003e4. Cointegration in Single Equations.\u003c\/p\u003e \u003cp\u003eThe Engle–Granger (EG) Approach.\u003c\/p\u003e \u003cp\u003eTesting for Cointegration with a Structural Break.\u003c\/p\u003e \u003cp\u003eAlternative Approaches.\u003c\/p\u003e \u003cp\u003eProblems with the Single Equation Approach.\u003c\/p\u003e \u003cp\u003eEstimating the Short-run Dynamic Model.\u003c\/p\u003e \u003cp\u003eSeasonal Cointegration.\u003c\/p\u003e \u003cp\u003ePeriodic Cointegration.\u003c\/p\u003e \u003cp\u003eAsymmetric Tests for Cointegration.\u003c\/p\u003e \u003cp\u003eConclusion s.\u003c\/p\u003e \u003cp\u003e5. Cointegration in Multivariate Systems.\u003c\/p\u003e \u003cp\u003eThe Johansen Approach.\u003c\/p\u003e \u003cp\u003eTesting the Order of Integration of the Variables.\u003c\/p\u003e \u003cp\u003eFormulation of the Dynamic Model.\u003c\/p\u003e \u003cp\u003eTesting for Reduced Rank.\u003c\/p\u003e \u003cp\u003eDeterministic Components in the Multivariate Model.\u003c\/p\u003e \u003cp\u003eTesting of Weak Exogeneity and VECM with Exogenous \u003ci\u003eI\u003c\/i\u003e (l) Variables.\u003c\/p\u003e \u003cp\u003eTesting for Linear Hypotheses on Cointegration Relations.\u003c\/p\u003e \u003cp\u003eTesting for Unique Cointegration Vectors.\u003c\/p\u003e \u003cp\u003eJoint Tests of Restrictions on \u003cb\u003eα\u003c\/b\u003e and \u003cb\u003eβ\u003c\/b\u003e Seasonal Unit Roots.\u003c\/p\u003e \u003cp\u003eSeasonal Cointegration.\u003c\/p\u003e \u003cp\u003eConclusions.\u003c\/p\u003e \u003cp\u003eAppendix 1: Programming in \u003ci\u003eSHAZAM.\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e6. Modelling the Short-run Multivariate System.\u003c\/p\u003e \u003cp\u003eIntroduction.\u003c\/p\u003e \u003cp\u003eEstimating the Long-run Cointegration Relationships.\u003c\/p\u003e \u003cp\u003eParsimonious VECM.\u003c\/p\u003e \u003cp\u003eConditional PVECM.\u003c\/p\u003e \u003cp\u003eStructural Modelling.\u003c\/p\u003e \u003cp\u003eStructural Macroeconomic Modelling.\u003c\/p\u003e \u003cp\u003e7. Panel Data Models and Cointegration.\u003c\/p\u003e \u003cp\u003eIntroduction.\u003c\/p\u003e \u003cp\u003ePanel Data and Modelling Techniques.\u003c\/p\u003e \u003cp\u003ePanel Unit Root Tests.\u003c\/p\u003e \u003cp\u003eTesting for Cointegration in Panels.\u003c\/p\u003e \u003cp\u003eEstimating Panel Cointegration Models.\u003c\/p\u003e \u003cp\u003eConclusion on Testing for Unit Roots and Cointegration in Panel Data.\u003c\/p\u003e \u003cp\u003e8. Modelling and Forecasting Financial Times Series.\u003c\/p\u003e \u003cp\u003eIntroduction.\u003c\/p\u003e \u003cp\u003eARCH and GARCH.\u003c\/p\u003e \u003cp\u003eMultivariate GARCH.\u003c\/p\u003e \u003cp\u003eEstimation and Testing.\u003c\/p\u003e \u003cp\u003eAn Empirical Application of ARCH and GARCH Models.\u003c\/p\u003e \u003cp\u003eARCH-M.\u003c\/p\u003e \u003cp\u003eAsymmetric GARCH Models.\u003c\/p\u003e \u003cp\u003eIntegrated and Fractionally Integrated GARCH Models.\u003c\/p\u003e \u003cp\u003eConditional Heteroscedasticity, Unit Roots and Cointegration.\u003c\/p\u003e \u003cp\u003eForecasting with GARCH Models.\u003c\/p\u003e \u003cp\u003eFurther Methods for Forecast Evaluation.\u003c\/p\u003e \u003cp\u003eConclusions on Modelling and Forecasting Financial Time Series.\u003c\/p\u003e \u003cp\u003eAppendix: Cointegration Analysis Using the Johansen Technique: A Practitioner’s Guide to \u003ci\u003ePcGive 10.1.\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eStatistical Appendix.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003eIndex.\u003c\/p\u003e  \u003cb\u003eRichard Harris\u003c\/b\u003e is a Professor in the Department of Economics and Finance at the University of Durham. His areas of research are in the field of applied econometrics and he has published widely in numerous journals.  \u003cp\u003e\u003cb\u003eRobert Sollis\u003c\/b\u003e is a Lecturer in the Department of Economics and Finance at the University of Durham. His research interests are in time series econometrics with particular focus on nonlinear models for macroeconomic and financial time series.\u003c\/p\u003e  \u003cb\u003e\u003ci\u003eApplied Time Series Modelling and Forecasting\u003c\/i\u003e\u003c\/b\u003e provides a relatively non-technical introduction to applied time series econometrics and forecasting involving non-stationary data. The emphasis is very much on the \u003ci\u003ewhy\u003c\/i\u003e and \u003ci\u003ehow\u003c\/i\u003e and, as much as possible, the authors confine technical material to boxes or point to the relevant sources for more detailed information.  \u003cp\u003eThis book is based on an earlier title \u003cb\u003e\u003ci\u003eUsing Cointegration Analysis in Econometric Modelling\u003c\/i\u003e\u003c\/b\u003e by \u003cb\u003eRichard Harris.\u003c\/b\u003e As well as updating material covered in the earlier book, there are two major additions involving panel tests for unit roots and cointegration and forecasting of financial time series. \u003cb\u003eHarris\u003c\/b\u003e and \u003cb\u003eSollis\u003c\/b\u003e have also incorporated as many of the latest techniques in the area as possible including: testing for periodic integration and cointegration; GLS detrending when testing for unit roots; structural breaks and season unit root testing; testing for cointegration with a structural break; asymmetric tests for cointegration; testing for super-exogeniety; seasonal cointegration in multivariate models; and approaches to structural macroeconomic modelling. In addition, the discussion of certain topics, such as testing for unique vectors, has been simplified.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e\u003ci\u003eApplied Time Series Modelling and Forecasting\u003c\/i\u003e\u003c\/b\u003e has been written for students taking courses in financial economics and forecasting, applied time series, and econometrics at advanced undergraduate and postgraduate levels. It will also be useful for practitioners who wish to understand the application of time series modelling e.g. financial brokers.\u003c\/p\u003e \u003cp\u003eData sets and econometric code for implementing some of the more recent procedures covered in the book can be found on the following web site www.wiley.co.uk\/harris\u003c\/p\u003e","brand":"Wiley","offers":[{"title":"Default Title","offer_id":47988754514149,"sku":"NP9780470844434","price":65.0,"currency_code":"USD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1842\/7735\/files\/9780470844434.jpg?v=1761781460","url":"https:\/\/k12savings.com\/es\/products\/applied-time-series-modelling-and-forecasting-isbn-9780470844434","provider":"K12savings","version":"1.0","type":"link"}