Time Series Models for Business & Economic Forecasting

The econometric analysis of economic and business time series is a major field of research and application. The last few decades have witnessed an increasing interest in both theoretical and empirical developments in constructing time series models and in their important application in forecasting. In Time Series Models for Business and Economic Forecasting, Philip Franses examines recent developments in time series analysis. The early parts of the book focus on the typical features of time series data in business and economics. Part III is concerned with the discussion of some important concepts in time series analysis, the discussion focuses on the techniques which can be readily applied in practice. Parts IV-VIII suggest different modeling methods and model structures. Part IX extends the concepts in chapter three to multivariate time series. Part X examines common aspects across time series.* Philip Franses is a rising star within econometrics teaching and research, this textbook is based around his highly successful lecture programme * The follow up book to two very successful CUP books in this area (MILLS/The Econometric Modelling of Financial Time Series; HARVEY/The Forecasting of Structural Time Series) * An easy to follow, up-to-date exposition including numerous examples and case studies, making this the most accessible book in this area, and the best starting point for nonspecialists'Franses reviews the more recent developments in modeling time series to focus on generating ex ante forecasts: seasonal unit roots, period models, aberrant observations, and common features. For each method, intuitive motivation and practical considerations are discussed in detail, making the book very readable ... should be beneficial for students and instructors of applications-oriented courses as well as for practitioners who wish to obtain a first, but not too technical, impression of time series forecasting using modern , recently developed methods.' Journal of the American Statistical Association