Global governance has come under increasing pressure since the end of the Cold War. In some issue areas, these pressures have led to significant changes in the architecture of governance institutions. In others, institutions have resisted pressures for change. This volume explores what accounts for this divergence in architecture by identifying three modes of governance: hierarchies, networks, and markets. The authors apply these ideal types to different issue areas in order to assess how global governance has changed and why. In most issue areas, hierarchical modes of governance, established after World War II, have given way to alternative forms of organization focused on market or network-based architectures. Each chapter explores whether these changes are likely to lead to more or less effective global governance across a wide range of issue areas. This provides a novel and coherent theoretical framework for analysing change in global governance. This title is 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.

Global governance has come under increasing pressure since the end of the Cold War. In some issue areas, these pressures have led to significant changes in the architecture of governance institutions. In others, institutions have resisted pressures for change. This volume explores what accounts for this divergence in architecture by identifying three modes of governance: hierarchies, networks, and markets. The authors apply these ideal types to different issue areas in order to assess how global governance has changed and why. In most issue areas, hierarchical modes of governance, established after World War II, have given way to alternative forms of organization focused on market or network-based architectures. Each chapter explores whether these changes are likely to lead to more or less effective global governance across a wide range of issue areas. This provides a novel and coherent theoretical framework for analysing change in global governance. This title is 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.