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Measuring Social Welfare - Matthew D. Adler - Bog - Oxford University Press Inc - Plusbog.dk

Measuring Social Welfare - Matthew D. Adler - Bog - Oxford University Press Inc - Plusbog.dk

Disputes over government policies rage in a number of areas. From taxation to climate change, from public finance to risk regulation, and from health care to infrastructure planning, advocates debate how policies affect multiple dimensions of individual well-being, how these effects balance against each other, and how trade-offs between overall well-being and inequality should be resolved.How to measure and balance well-being gains and losses, is a vexed issue. Matthew D. Adler advances the debate by introducing the social welfare function (SWF) framework and demonstrating how it can be used as a powerful tool for evaluating governmental policies. The framework originates in welfare economics and in philosophical scholarship regarding individual well-being, ethics, and distributive justice. It has three core components: a well-being measure, which translates each of the possible policy outcomes into an array of interpersonally comparable well-being numbers, quantifying how well off each person in the population would be in that outcome; a rule for ranking outcomes thus described ; and an uncertainty module, which orders policies understood as probability distributions over outcomes. The SWF framework is a significant improvement compared to cost-benefit analysis (CBA), which quantifies policy impacts in dollars, is thereby biased towards the rich, and is insensitive to the distribution of these monetized impacts. The SWF framework, by contrast, uses an unbiased measure of well-being and allows the policymaker to consider both efficiency (total well-being) and equity (the distribution of well-being). Because the SWF framework is a fully generic methodology for policy assessment, Adler also discusses how it can be implemented to inform government policies. He illustrates it through a detailed case study of risk regulation, contrasting the implication of results of SWF and CBA. This book provides an accessible, yet rigorous overview of the SWF approach that can inform policy-makers and students.

DKK 410.00
3

Automated Machine Learning for Business - Bog af Kai (Associate Professor of Information Systems R. Larsen - Paperback

Yoga for Singing - Judith E. Carman - Bog - Oxford University Press Inc - Plusbog.dk

Reproducible Econometrics Using R - Jeffrey S. Racine - Bog - Oxford University Press Inc - Plusbog.dk

Reproducible Econometrics Using R - Jeffrey S. Racine - Bog - Oxford University Press Inc - Plusbog.dk

Across the social sciences there has been increasing focus on reproducibility, i.e., the ability to examine a study''s data and methods to ensure accuracy by reproducing the study. Reproducible Econometrics Using R combines an overview of key issues and methods with an introduction to how to use them using open source software (R) and recently developed tools (R Markdown and bookdown) that allow the reader to engage in reproducible econometric research. Jeffrey S. Racine provides a step-by-step approach, and covers five sets of topics, i) linear time series models, ii) robust inference, iii) robust estimation, iv) model uncertainty, and v) advanced topics. The time series material highlights the difference between time-series analysis, which focuses on forecasting, versus cross-sectional analysis, where the focus is typically on model parameters that have economic interpretations. For the time series material, the reader begins with a discussion of random walks, white noise, and non-stationarity. The reader is next exposed to the pitfalls of using standard inferential procedures that are popular in cross sectional settings when modelling time series data, and is introduced to alternative procedures that form the basis for linear time series analysis. For the robust inference material, the reader is introduced to the potential advantages of bootstrapping and the Jackknifing versus the use of asymptotic theory, and a range of numerical approaches are presented. For the robust estimation material, the reader is presented with a discussion of issues surrounding outliers in data and methods for addressing their presence. Finally, the model uncertainly material outlines two dominant approaches for dealing with model uncertainty, namely model selection and model averaging.Throughout the book there is an emphasis on the benefits of using R and other open source tools for ensuring reproducibility. The advanced material covers machine learning methods (support vector machines that are useful for classification) and nonparametric kernel regression which provides the reader with more advanced methods for confronting model uncertainty. The book is well suited for advanced undergraduate and graduate students alike. Assignments, exams, slides, and a solution manual are available for instructors.

DKK 580.00
3

Natural Justice - Ken Binmore - Bog - Oxford University Press Inc - Plusbog.dk

Research Methods in Health Humanities - - Bog - Oxford University Press Inc - Plusbog.dk

Research Methods in Health Humanities - - Bog - Oxford University Press Inc - Plusbog.dk

Research Methods in Health Humanities surveys the diverse and unique research methods used by scholars in the growing, transdisciplinary field of health humanities. Appropriate for advanced undergraduates, but rich enough to engage more seasoned students and scholars, this volume is an essential teaching and reference tool for health humanities teachers and scholars. Health humanities is a field committed to social justice and to applying expertise to real world concerns, creating research that translates to participants and communities in meaningful and useful ways. The chapters in this field-defining volume reflect these values by examining the human aspects of health and health care that are critical, reflective, textual, contextual, qualitative, and quantitative. Divided into four sections, the volume demonstrates how to conduct research on texts, contexts, people, and programs. Readers will find research methods from traditional disciplines adapted to health humanities work, such as close reading of diverse texts, archival research, ethnography, interviews, and surveys. The book also features transdisciplinary methods unique to the health humanities, such as health and social justice studies, digital health humanities, and community dialogues. Each chapter provides learning objectives, step-by-step instructions, resources, and exercises, with illustrations of the method provided by the authors'' own research. An invaluable tool in learning, curricular development, and research design, this volume provides a grounding in the traditions of the humanities, fine arts, and social sciences for students considering health care careers, but also provides useful tools of inquiry for everyone, as we are all future patients and future caregivers of a loved one.

DKK 469.00
3

Natural Justice - Ken Binmore - Bog - Oxford University Press Inc - Plusbog.dk