Time Series Analysis for the Social Sciences

✍ Scribed by Janet M. Box-Steffensmeier; John R. Freeman; Jon C. Pevehouse; Matthew Perry Hitt

Publisher: Cambridge University Press
Year: 2014
Tongue: English
Leaves: 298
Series: Analytical Methods for Social Research
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

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.

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