The application of time series techniques in economics has become increasingly important, both for forecasting purposes and in the empirical analysis of time series in general. This book brings together recent research at the frontiers of the subject and analyzes the areas of time series analysis of most importance to applied economics. The author discusses three basic areas of time series analysis: univariate models, multivariate models, and nonlinear models. Particular emphasis is placed on applications of the theory to important areas of applied economics and on the computer software and programs needed to implement the techniques. It is an up-to-date text, extending the basic techniques of analysis to cover the development of methods that can be used to analyze a wide range of economic problems.
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"...I am favorably impressed with TSTE's clear exposition and numerous empirical examples....The author is to be congratulated for his diligent efforts in providing students and researchers a very good synthesis of the time series econometrics literature and a very comprehensive and useful bibliography." Econometrics Reviews
"...this book is admirable. It should be widely read, and is likely to persuade many readers of the value of time series methods, expanding the range of sensible applications of these methods to economic data." Paul Newbold, Journal of Economic Literature
"...this book is admirable. It should be widely read, and is likely to persuade many readers of the value of time series methods, expanding the range of sensible applications of these methods to economic data." Paul Newbold, Journal of Economic Literature
Book Description
The application of time series techniques in economics has become increasingly important for forecasting and in the empirical analysis of time series. Three basic areas of analysis models are discussed: univariate, multivariate and nonlinear.
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2 of 3 people found the following review helpful:
4.0 out of 5 stars
Excellent foundation for empirical work.,
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This review is from: Time Series Techniques for Economists (Paperback)
This book is suitable for Econometricians looking for a book without too much theoretical work. Sufficient explaination given for empirical work. Easy to read.
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First Sentence:
As a consequence of the highly influential book by Tukey (1977), exploratory data analysis, often referred to by its acronym EDA, has gained enormously in importance in all areas of applied statistical research over the last decade. Read the first page Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
innovation accounting decompositions, housing starts series, eventual forecast function, linear filter representation, hypothesised distribution, conditional variance models, stochastic time series models, homogeneous nonstationarity, fitted counts, seasonal time series, impulse response weights, second differencing, airline model, consol yield, portmanteau tests, strict exogeneity, economic time series, secular component, portmanteau statistic, cointegrating regression, forecast functions, series analysed, model selection criteria, exponential smoothing model, seasonal model Key Phrases - Capitalized Phrases (CAPs): (learn more)
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Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
As a consequence of the highly influential book by Tukey (1977), exploratory data analysis, often referred to by its acronym EDA, has gained enormously in importance in all areas of applied statistical research over the last decade. Read the first page Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
innovation accounting decompositions, housing starts series, eventual forecast function, linear filter representation, hypothesised distribution, conditional variance models, stochastic time series models, homogeneous nonstationarity, fitted counts, seasonal time series, impulse response weights, second differencing, airline model, consol yield, portmanteau tests, strict exogeneity, economic time series, secular component, portmanteau statistic, cointegrating regression, forecast functions, series analysed, model selection criteria, exponential smoothing model, seasonal model Key Phrases - Capitalized Phrases (CAPs): (learn more)
Monte Carlo, Count Fitted New!
Books on Related Topics | Concordance | Text Stats Browse Sample Pages:
Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
Citations (learn more)
This book cites 49
books:
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32
books
cite this book:
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- Time Series Analysis: Forecasting & Control (3rd Edition) by George Box on 5 pages
- Time Series Analysis (Science Paperbacks) by E. J. Hannan on 4 pages
- Seasonal Analysis of Economic Time Series by Arnold Zellner in Back Matter (1), Back Matter (2), and Back Matter (3)
- Time Series Analysis by M . B . Priestley in Back Matter (1), and Back Matter (2)
- Forecasting in Business and Economics, Second Edition (Economic Theory, Econometrics, and Mathematical Economics) (Economic Theory, Econometrics, and Mathematical Economics) by C. W. J. Granger in Back Matter (1), and Back Matter (2)
See all 49 books this book cites
- Growth and Variability in State Tax Revenue: An Anatomy of State Fiscal Crises (Contributions in Economics and Economic History) by Randall G. Holcombe on page 94, and Back Matter
- Modern Perspectives on the Gold Standard by Tamim Bayoumi in Front Matter, and page 49
- The Japanese Foreign Exchange Market (Routledge Studies in the Growth Economies of Asia) by Beate Reszat in Back Matter
- Implications of the EU Banana Trade Regime for Selected Import Markets: Economic Analysis and Political Dimension by Patrick Verissimo in Back Matter
- Transformational Growth and the Business Cycle (Studies in Transformational Growth) by Edward Nell in Back Matter
See all 32 books citing this book
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