Jon C. W. Pevehouse

The number of international human rights institutions and countries participating in them has risen dramatically in recent decades, precipitating debates about why countries make such commitments and whether these commitments improve member's human rights behavior. These debates have centered on a small number of human rights treaties, with far less attention paid to the larger number of international organizations (IOs) that aim to promote human rights. The Element argues and then demonstrates that state decisions about joining these IOs depends on the institutional design of the organizations, specifically sovereignty costs for member states. These costs stem from the constraints that IOs impose and vary substantially. Emerging democracies are most likely to enter high sovereignty cost IOs. Furthermore, organizations that generate higher sovereignty costs tend to produce better human rights outcomes than those generating fewer sovereignty costs for all regimes. This title is also available as Open Access on Cambridge Core.

The number of international human rights institutions and countries participating in them has risen dramatically in recent decades, precipitating debates about why countries make such commitments and whether these commitments improve member's human rights behavior. These debates have centered on a small number of human rights treaties, with far less attention paid to the larger number of international organizations (IOs) that aim to promote human rights. The Element argues and then demonstrates that state decisions about joining these IOs depends on the institutional design of the organizations, specifically sovereignty costs for member states. These costs stem from the constraints that IOs impose and vary substantially. Emerging democracies are most likely to enter high sovereignty cost IOs. Furthermore, organizations that generate higher sovereignty costs tend to produce better human rights outcomes than those generating fewer sovereignty costs for all regimes. This title is also available as Open Access on Cambridge Core.

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.