Time Series Analysis for the Social Sciences

Datos Bibliográficos

ID6561539
AutoresJanet Box-Steffensmeier, Janet M Box-Steffensmeier, John R Freeman, Matthew P Hitt (0000-0003-0762-1929), Jon C W Pevehouse
Año2014
Páginas292
Fecha de publicación2014-01-01
Open AccessNo
TipoBOOK
RevistaTime Series Analysis for the Social Sciences (SOURCE_BOOK)
EditorialCambridge University Press (PUBLISHER • US)
DOI10.1017/cbo9781139025287
ISBN9781139025287
Open LibraryOL28534439M
IdiomaEN
Citas recibidas82

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 · Mathematical models · Political science