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Time Series Analysis for the Social Sciences

Matthew P Hitt author Janet M Box-Steffensmeier author John R Freeman author Jon C W Pevehouse author

Format:Paperback

Publisher:Cambridge University Press

Published:22nd Dec '14

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Time Series Analysis for the Social Sciences cover

This book provides instruction and examples of the core methods in time series econometrics, drawing from several main fields of the social sciences.

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.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.

ISBN: 9780521691550

Dimensions: 226mm x 152mm x 23mm

Weight: 390g

298 pages