The Science Of Public Policy

This Handbook assembles state-of-the-art insights into the co-evolutionary and precarious relations between science and public policy. Beyond this, it also offers a fresh outlook on emerging challenges for science (including technology and innovation) in changing societies, and related policy requirements, as well as the challenges for public policy in view of science-driven economic, societal, and cultural changes. In short, this book deals with science as a policy-triggered project as well as public policy as a science-driven venture.

"Studying Publisc Policy develops an analytical framework of the subject for students in public policy course. Instead of focussing on the substantive policy of a particular policy area, the book examines the theoretical and conceptual foundations of, and approaches used in, the policy sciences."--Provided by publisher.

Public Policy Analytics: Code & Context for Data Science in Government teaches readers how to address complex public policy problems with data and analytics using reproducible methods in R. Each of the eight chapters provides a detailed case study, showing readers: how to develop exploratory indicators; understand ‘spatial process’ and develop spatial analytics; how to develop ‘useful’ predictive analytics; how to convey these outputs to non-technical decision-makers through the medium of data visualization; and why, ultimately, data science and ‘Planning’ are one and the same. A graduate-level introduction to data science, this book will appeal to researchers and data scientists at the intersection of data analytics and public policy, as well as readers who wish to understand how algorithms will affect the future of government.

Field experiments -- randomized controlled trials -- have become ever more popular in political science, as well as in other disciplines, such as economics, social policy and development. Policy-makers have also increasingly used randomization to evaluate public policies, designing trials of tax reminders, welfare policies and international aid programs to name just a few of the interventions tested in this way. Field experiments have become successful because they assess causal claims in ways that other methods of evaluation find hard to emulate. Social scientists and evaluators have rediscovered how to design and analyze field experiments, but they have paid much less attention to the challenges of organizing and managing them. Field experiments pose unique challenges and opportunities for the researcher and evaluator which come from working in the field. The research experience can be challenging and at times hard to predict. This book aims to help researchers and evaluators plan and manage their field experiments so they can avoid common pitfalls. It is also intended to open up discussion about the context and backdrop to trials so that these practical aspects of field experiments are better understood. The book sets out ten steps researchers can use to plan their field experiments, then nine threats to watch out for when they implement them. There are cases studies of voting and political participation, elites, welfare and employment, nudging citizens, and developing countries.

This textbook presents the essential tools and core concepts of data science to public officials, policy analysts, and economists among others in order to further their application in the public sector. An expansion of the quantitative economics frameworks presented in policy and business schools, this book emphasizes the process of asking relevant questions to inform public policy. Its techniques and approaches emphasize data-driven practices, beginning with the basic programming paradigms that occupy the majority of an analyst’s time and advancing to the practical applications of statistical learning and machine learning. The text considers two divergent, competing perspectives to support its applications, incorporating techniques from both causal inference and prediction. Additionally, the book includes open-sourced data as well as live code, written in R and presented in notebook form, which readers can use and modify to practice working with data.

Bringing the major current insights in implementation research and theory together, Public Policy, Implementation and Governance reviews the literature on public policy implementation, relating it to contemporary developments in thinking about governance. The text stresses the continuing importance of a focus upon implementation processes and explores its central relevance to the practice of public administration. In light of the changing nature of governance, Hill and Hupe suggest strategies for both future research on and management of public policy implementation. Their basic approach is two-fold: firstly, to understand the process of implementation and secondly, to address how one might control and affect this process. Re-exploring the state of the art of the study of implementation as a sub-discipline of political science and public administration, this book will be essential reading for students and researchers in public policy, social policy, public management, public adminstration and governance. `This is an excellent and much needed book. Hill and Hupe have provided a well written and highly accessible account of the development of implementation studies which will be immensely valuable to everyone concerned with understanding implementation in modern policy making.' - Professor Wayne Parsons, University of London