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Time series analysis for the social sciences /

"Time-series, or longitudinal, data are ubiquitous in the social sciences. Unfortunately, analysts often treat the time-series properties of their data as a nuisance rather than a substantively meaningful dynamic process to be modeled and interpreted. Time-Series Analysis for Social Sciences pr...

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Bibliographic Details
Main Authors: Box-Steffensmeier, Janet M., 1965- (Author)
Group Author: Freeman, John R.; Hitt, Matthew P.; Pevehouse, Jon C. W.
Published: Cambridge University Press,
Publisher Address: New York :
Publication Dates: [2014]
Literature type: Book
Language: English
Series: Analytical methods for social research
Subjects:
Time-series analysis.
Summary: "Time-series, or longitudinal, data are ubiquitous in the social sciences. Unfortunately, analysts often treat the time-series properties of their data as a nuisance rather than a substantively meaningful dynamic process to be modeled and interpreted. Time-Series Analysis for Social Sciences provides accessible, up-to-date instruction and examples of the core methods in time-series econometrics. Janet M. Box-Steffensmeier, John R. Freeman, Jon C. Pevehouse, and Matthew P. Hitt cover a wide range of topics including ARIMA models, time-series regression, unit-root diagnosis, vector autoregressive models, error-correction models, intervention models, fractional integration, ARCH models, structural breaks, and forecasting. This book is aimed at researchers and graduate students who have taken at least one course in multivariate regression. Examples are drawn from several areas of social science, including political behavior, elections, international conflict, criminology, and comparative political economy"--
Carrier Form: xv, 280 pages : illustrations ; 23 cm.
Bibliography: Includes bibliographical references and index.
ISBN: 9780521871167 (hardback) :
0521871166 (hardback)
9780521691550 (paperback)
0521691559 (paperback)
Index Number: HA30
CLC: C32
Call Number: C32/B788
Contents: 1. Modeling social dynamics -- 2. Univariate time-series models -- 3. Dynamic regression models -- 4. Modeling the dynamics of social systems -- 5. Univariate, nonstationary processes: tests and modeling -- 6. Cointegration and error correction models -- 7. Selections on time series analysis -- 8. Concluding thoughts for the time series analyst.

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