Analytics, policy, and governance / edited by Jennifer Bachner, Benjamin Ginsberg, and Kathryn Wagner Hill.

Includes bibliographical references and index.

Measuring political and policy preferences using item response scaling / Joshua D. Clinton -- Causal inference with observational data / Justin Esarey -- Causal inference with experimental data / David W. Nickerson -- Descriptive network analysis: interest group lobbying dynamics around immigration policy / Alexander Furnas and Lee Drutman -- Learning from place in the era of geolocation / Ryan T. Moore and Andrew Reeves -- Text analysis: estimating policy preferences from written and spoken words / Kenneth Benoit and Alexander Herzog -- Machine learning and governance / Alex C. Engler -- Governing a data-driven society / Kathryn Wagner Hill -- Big data and privacy / Priscilla M. Regan -- Reflections on analytics: knowledge and power / Benjamin Ginsberg.

Print version record.

The first available textbook on the rapidly growing and increasingly important field of government analytics This first textbook on the increasingly important field of government analytics provides invaluable knowledge and training for students of government in the synthesis, interpretation, and communication of "big data," which is now an integral part of governance and policy making. Integrating all the major components of this rapidly growing field, this invaluable text explores the intricate relationship of data analytics to governance while providing innovative strategies for the retrieval and management of information.

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