{"product_id":"a-companion-to-economic-forecasting-isbn-9781405126236","title":"A Companion to Economic Forecasting","description":"\u003ci\u003eA Companion to Economic Forecasting\u003c\/i\u003e provides an accessible and comprehensive account of recent developments in economic forecasting. Each of the chapters has been specially written by an expert in the field, bringing together in a single volume a range of contrasting approaches and views. Uniquely surveying forecasting in a single volume, the \u003ci\u003eCompanion\u003c\/i\u003e provides a comprehensive account of the leading approaches and modeling strategies that are routinely employed.  \u003cp\u003e\u003ci\u003eList of Contributors ix\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e\u003ci\u003ePreface xi\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e\u003ci\u003eAcknowledgments xiii\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e1 An Overview of Economic Forecasting 1\u003cbr\u003e \u003ci\u003eMichael P. Clements and David F. Hendry\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e2 Predictable Uncertainty in Economic Forecasting 19\u003cbr\u003e \u003ci\u003eNeil R. Ericsson\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e3 Density Forecasting: A Survey 45\u003cbr\u003e \u003ci\u003eAnthony S. Tay and Kenneth F. Wallis\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e4 Statistical Approaches to Modeling and Forecasting Time Series 69\u003cbr\u003e \u003ci\u003eDiego J. Pedregal and Peter C. Young\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e5 Forecasting with Structural Time-Series Models 105\u003cbr\u003e \u003ci\u003eTommaso Proietti\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e6 Judgmental Forecasting 133\u003cbr\u003e \u003ci\u003eDilek Önkal-Atay, Mary E. Thomson, and Andrew C. Pollock\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e7 Forecasting for Policy 152\u003cbr\u003e \u003ci\u003eAdrian R. Pagan and John Robertson\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e8 Forecasting Cointegrated VARMA Processes 179\u003cbr\u003e \u003ci\u003eHelmut Lütkepohl\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e9 Multi-Step Forecasting 206\u003cbr\u003e \u003ci\u003eR.J. Bhansali\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e10 The Rationality and Efficiency of Individuals’ Forecasts 222\u003cbr\u003e \u003ci\u003eHerman O. Stekler\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e11 Decision-Based Methods for Forecast Evaluation 241\u003cbr\u003e \u003ci\u003eM. Hashem Pesaran and Spyros Skouras\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e12 Forecast Combination and Encompassing 268\u003cbr\u003e \u003ci\u003ePaul Newbold and David I. Harvey\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e13 Testing Forecast Accuracy 284\u003cbr\u003e \u003ci\u003eRoberto S. Mariano\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e14 Inference About Predictive Ability 299\u003cbr\u003e \u003ci\u003eMichael W. McCracken and Kenneth D. West\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e15 Forecasting Competitions: Their Role in Improving Forecasting Practice and Research 322\u003cbr\u003e \u003ci\u003eRobert Fildes and Keith Ord\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e16 Empirical Comparisons of Inflation Models’ Forecast Accuracy 354\u003cbr\u003e \u003ci\u003eØyvind Eitrheim, Tore Anders Husebø, and Ragnar Nymoen\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e17 The Forecasting Performance of the OECD Composite Leading Indicators for France, Germany, Italy, and the U.K. 386\u003cbr\u003e \u003ci\u003eGonzalo Camba-Mendez, George Kapetanios, Martin R. Weale, and Richard J. Smith\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e18 Unit-Root Versus Deterministic Representations of Seasonality for Forecasting 409\u003cbr\u003e \u003ci\u003eDenise R. Osborn\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e19 Forecasting with Periodic Autoregressive Time-Series Models 432\u003cbr\u003e \u003ci\u003ePhilip Hans Franses and Richard Paap\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e20 Nonlinear Models and Forecasting 453\u003cbr\u003e \u003ci\u003eRuey S. Tsay\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e21 Forecasting with Smooth Transition Autoregressive Models 485\u003cbr\u003e \u003ci\u003eStefan Lundbergh and Timo Teräsvirta\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e22 Forecasting Financial Variables 510\u003cbr\u003e \u003ci\u003eTerence C. Mills\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e23 Explaining Forecast Failure in Macroeconomics 539\u003cbr\u003e \u003ci\u003eMichael P. Clements and David F. Hendry\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e\u003ci\u003eAuthor Index 572\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e\u003ci\u003eSubject Index 583\u003c\/i\u003e\u003c\/p\u003e  \"\u003ci\u003eA Companion to Economic Forecasting\u003c\/i\u003e offers an insightful and authoritative overview of the diverse issues, methods, and applications falling under the broad umbrella of economic and financial forecasting. It belongs on every practitioner's bookshelf, and on every student's reading list.\" \u003ci\u003eFrancis X. Diebold, University of Pennsylvania\u003c\/i\u003e \u003c!--end--\u003e\u003cbr\u003e \u003cp\u003e\"Economic forecasting methods, models, applications, evaluation, and diagnostics, all in one encompassing volume by leaders in the field. This collection of lucid chapters defines where economic forecasting is today. An invaluable addition to the library of anyone working with economic data.\" \u003ci\u003eCharles Nelson, University of Washington\u003c\/i\u003e\u003c\/p\u003e  \u003cb\u003eMichael P. Clements\u003c\/b\u003e is a Reader in Economics at the University of Warwick. He is co-author with David Hendry of Forecasting Economic Time Series (1998) and Forecasting Non-stationary Economic Time Series (1999), and has published in academic journals on a variety of time-series econometrics topics.\u003cbr\u003e \u003cp\u003e\u003cbr\u003e \u003c\/p\u003e \u003cp\u003e\u003cbr\u003e \u003c\/p\u003e \u003cp\u003e\u003cb\u003eDavid F. Hendry\u003c\/b\u003e, Professor of Economics at Oxford University, is a past President and Honorary Vice-President of the Royal Economic Society, Fellow of the British Academy and Econometric Society, and a Foreign Honorary Member of both the American Academy of Arts and Sciences and the American Economic Association. He has published more than twenty books, as well as over 150 articles and papers on time-series econometrics, econometric modeling, economic forecasting, the history of econometrics, Monte Carlo methods, econometric computing and empirical applications.\u003c\/p\u003e  \u003ci\u003eA Companion to Economic Forecasting\u003c\/i\u003e provides an accessible and comprehensive account of recent developments in economic forecasting. Each of the chapters has been specially written by an expert in the field, bringing together a range of contrasting approaches and views. Forecasting is a practical venture, so many of the chapters are aimed at practitioners and nonspecialists.\u003cbr\u003e \u003cp\u003e\u003cbr\u003e \u003c\/p\u003e \u003cp\u003eThis book surveys a field that has expanded rapidly in recent years. There are no other up-to-date treatments that survey forecasting in a single volume. The \u003ci\u003eCompanion\u003c\/i\u003e provides a comprehensive account of the leading approaches and modeling strategies that are routinely employed. An extensive editorial overview places the contributions in context, and shows their interconnections and commonalities.\u003c\/p\u003e","brand":"Wiley-Blackwell","offers":[{"title":"Default Title","offer_id":47988605911269,"sku":"NP9781405126236","price":92.95,"currency_code":"USD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1842\/7735\/files\/9781405126236.jpg?v=1761780944","url":"https:\/\/k12savings.com\/products\/a-companion-to-economic-forecasting-isbn-9781405126236","provider":"K12savings","version":"1.0","type":"link"}