Time Series Analysis for the Social Sciences

By: Janet M. Box-steffensmeier and John R. Freeman and Matthew P. Hitt and Jon C. W. Pevehouse

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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 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.

Book Quality:: Publisher Quality
ISBN-13:: 9781316053393
Publisher:: Cambridge University Press
Date of Addition:: 02/06/15
Copyrighted By:: Janet M. Box-Steffensmeier, John R. Freeman, Matthew P. Hitt, Jon C. W. Pevehouse
Adult content:: No
Language:: English
Has Image Descriptions:: No
Categories:: Nonfiction, Mathematics and Statistics
Submitted By:: Bookshare Staff
Usage Restrictions:: This is a copyrighted book.