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Time Series Analysis for the Social Sciences
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  • Cited by 18
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    This book has been cited by the following publications. This list is generated based on data provided by CrossRef.

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    Hom, Andrew R 2018. Timing is Everything: Toward a Better Understanding of Time and International Politics. International Studies Quarterly, Vol. 62, Issue. 1, p. 69.

    Hossain, KSM Tozammel Gao, Shuyang Kennedy, Brendan Galstyan, Aram and Natarajan, Prem 2018. Forecasting violent events in the Middle East and North Africa using the Hidden Markov Model and regularized autoregressive models. The Journal of Defense Modeling and Simulation: Applications, Methodology, Technology, p. 154851291881469.

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    de Haan-Rietdijk, Silvia Voelkle, Manuel C. Keijsers, Loes and Hamaker, Ellen L. 2017. Discrete- vs. Continuous-Time Modeling of Unequally Spaced Experience Sampling Method Data. Frontiers in Psychology, Vol. 8, Issue. ,

    Bogliaccini, Juan A. and Egan, Patrick J. W. 2017. Foreign direct investment and inequality in developing countries: Does sector matter?. Economics & Politics, Vol. 29, Issue. 3, p. 209.

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    Ondercin, Heather L. 2017. Who Is Responsible for the Gender Gap? The Dynamics of Men’s and Women’s Democratic Macropartisanship, 1950–2012. Political Research Quarterly, Vol. 70, Issue. 4, p. 749.

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    Enns, Peter K. Kelly, Nathan J. Masaki, Takaaki and Wohlfarth, Patrick C. 2016. Don’t jettison the general error correction model just yet: A practical guide to avoiding spurious regression with the GECM. Research & Politics, Vol. 3, Issue. 2, p. 205316801664334.

    2015. Publications Received. Contemporary Sociology: A Journal of Reviews, Vol. 44, Issue. 3, p. 442.

    Aima, Khan and Zaheer, Abbas 2015. Portfolio balance approach: An empirical testing. Journal of Economics and International Finance, Vol. 7, Issue. 6, p. 137.

    Zhu, He Wilson, Fernando A. Stimpson, Jim P. and Hilsenrath, Peter E. 2015. Rising gasoline prices increase new motorcycle sales and fatalities. Injury Epidemiology, Vol. 2, Issue. 1,


Book description

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.

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