Modelling Trends and Cycles in Economic Time Series

Informationen zum Autor TERENCE C. MILLS is Professor of Applied Statistics and Econometrics and the Head of the department of Economics at Loughborough University. He previously held professorial appointments at City University business school and Hull. He is the author of Time Series Techniques for Economists and The Econometric Modelling of Financial Time Series , plus over one hundred articles in journals and books. Klappentext Modelling trends and cycles in economic time series has a long history, with the use of linear trends and moving averages forming the basic tool kit of economists until the 1970s. Several developments in econometrics then led to an overhaul of the techniques used to extract trends and cycles from time series. Terence Mills introduces these various approaches to allow students and researchers to appreciate the variety of techniques and the considerations that underpin their choice for modelling trends and cycles. Zusammenfassung Modelling trends and cycles in economic time series has a long history, with the use of linear trends and moving averages forming the basic tool kit of economists until the 1970s. Inhaltsverzeichnis Introduction 'Classical' Techniques of Modelling Trends and Cycles Stochastic Trends and Cycles Filtering Economic Time Series Nonlinear and Nonparametric Trend Modelling Multivariate Modelling of Trends and Cycles Conclusions References Index

Product details

• Authors: T Mills, T. Mills, Terence Mills, Terence C. Mills
• Publisher: Palgrave UK
• Languages: English
• Product format: Paperback / Softback
• Released: 30.05.2003
• EAN: 9781403902092
• ISBN: 978-1-4039-0209-2
• Dimensions: 138 mm x 215 mm x 10 mm
• Series: Palgrave Texts in Econometrics; Palgrave Texts in Econometrics
• Subjects: Social sciences, law, business > Business > Economics; B, Economics, finance, business & management, Statistics, Management science, Probability & statistics, Palgrave Economics & Finance Collection, Econometrics, econometrics;modeling;time series