Applied Time Series Analysis: A Practical Guide to Modeling and Forecasting

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Elsevier, Feb 8, 2019 - Business & Economics - 432 pages
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Written for those who need an introduction, Applied Time Series Analysis reviews applications of the popular econometric analysis technique across disciplines. Carefully balancing accessibility with rigor, it spans economics, finance, economic history, climatology, meteorology, and public health. Terence Mills provides a practical, step-by-step approach that emphasizes core theories and results without becoming bogged down by excessive technical details. Including univariate and multivariate techniques, Applied Time Series Analysis provides data sets and program files that support a broad range of multidisciplinary applications, distinguishing this book from others.



  • Focuses on practical application of time series analysis, using step-by-step techniques and without excessive technical detail
  • Supported by copious disciplinary examples, helping readers quickly adapt time series analysis to their area of study
  • Covers both univariate and multivariate techniques in one volume
  • Provides expert tips on, and helps mitigate common pitfalls of, powerful statistical software including EVIEWS and R
  • Written in jargon-free and clear English from a master educator with 30 years+ experience explaining time series to novices
  • Accompanied by a microsite with disciplinary data sets and files explaining how to build the calculations used in examples
 

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Contents

ARMA Models for Stationary Time Series
31
General AR and MA Processes
37
AutoregressiveMoving Average Models
43
Endnotes
55
Unit Roots Difference and Trend Stationarity
71
Breaking and Nonlinear Trends
103
An Introduction to Forecasting With Univariate
121
Unobserved Component Models Signal Extraction
131
13
211
23
225
Error Correction Spurious Regressions
233
Vector Autoregressions With Integrated Variables
255
Identification of Vector Error Correction Models
264
Vector Error Correction ModelX Models
271
Endnotes
279
State Space Models
299

Seasonality and Exponential Smoothing
145
Volatility and Generalized Autoregressive
161
Forecasting From an ARMAGARCH Model
168
Transfer Functions and Autoregressive Distributed
201
Some Concluding Remarks
311
Index
329
Copyright

Other editions - View all

Applied Time Series Analysis: A Practical Guide to Modeling and Forecasting
Terence C. Mills
Limited preview - 2019

Common terms and phrases

Àd exchange rate alternative ARDL model ARIMA ARMA model assumed asymptotically autoregressive Autoregressive Conditional Heteroskedastic beer sales behavior bilinear break date breaking trend Chapter coefficients cointegrating component conditional variance correlation critical values decomposition defined deterministic ENDNOTES equation error correction error variance estimated example exponential smoothing filter fitted forecast error frequency GARCH given global temperatures Granger HoltÀWinters I0ðÞ I1ðÞ implies impulse response innovations intercept interest rate Kalman filter linear trend logarithms long-run matrix moving average nonlinear nonstationary null hypothesis observations obtained p-value Perron polynomial procedure radiative forcing random walk residuals restrictions root tests SACF sample autocorrelations seasonal shocks shown in Fig squared standard error stationary stationary process stochastic test statistic tion trend function unit root unit root tests variables VECM vector Vector Autoregressions white noise zero τμ

About the author (2019)

Terence Mills is Professor of Applied Statistics and Econometrics at Loughborough University and has well over 200 publications, beginning in 1977 with a paper in the European Economic Review. He has since published in most of the international economic, economic history, econometrics, finance and statistics journals and in a range of other journals, including Journal of Climate, Climatic Change, Journal of Cosmology, International Journal of Body Composition Research, Physica A, Energy and Buildings, and Journal of Public Health. He has also written or edited almost 20 books, including a range of introductory statistics and econometric texts, handbooks on econometrics, and histories of time series analysis.

Bibliographic information

QR code for Applied Time Series Analysis
TitleApplied Time Series Analysis: A Practical Guide to Modeling and Forecasting
AuthorTerence C. Mills
PublisherElsevier, 2019
ISBN0128131179, 9780128131176
Length432 pages
Subjects › 

Business & Economics / Econometrics
  
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