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Book Time Series Analysis for the Social Sciences (Analytical Methods for Social Research)

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Time Series Analysis for the Social Sciences (Analytical Methods for Social Research)

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    Available in PDF - DJVU Format | Time Series Analysis for the Social Sciences (Analytical Methods for Social Research).pdf | Language: ENGLISH
    Janet M. Box-Steffensmeier(Author) John R. Freeman(Author) Matthew P. Hitt(Author) Jon C. W. Pevehouse(Author)&1more

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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 the 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.

Time Series Analysis for the Social Sciences provides accessible, up-to-date instruction and examples of the core methods in time series econometrics. The book covers ARIMA models, time series regression, unit-root diagnosis, vector autoregressive models, error-correction models, intervention models, fractional integration, ARCH models, structural breaks, and forecasting.

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Review Text

  • By Valjean on 2 March 2016

    Very good book for time series analysis.


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