This book presents both methodological papers on and examples of applying behavioral predictive models to specific economic problems, with a focus on how to take into account people's behavior when making economic predictions. This is an important issue, since traditional economic models assumed that people make wise economic decisions based on a detailed rational analysis of all the relevant aspects. However, in reality – as Nobel Prize-winning research has shown – people have a limited ability to process information and, as a result, their decisions are not always optimal. Discussing the need for prediction-oriented statistical techniques, since many statistical methods currently used in economics focus more on model fitting and do not always lead to good predictions, the book is a valuable resource for researchers and students interested in the latest results and challenges and for practitioners wanting to learn how to use state-of-the-art techniques.

A timely investigation of the potential economic effects, both realized and unrealized, of artificial intelligence within the United States healthcare system. In sweeping conversations about the impact of artificial intelligence on many sectors of the economy, healthcare has received relatively little attention. Yet it seems unlikely that an industry that represents nearly one-fifth of the economy could escape the efficiency and cost-driven disruptions of AI. The Economics of Artificial Intelligence: Health Care Challenges brings together contributions from health economists, physicians, philosophers, and scholars in law, public health, and machine learning to identify the primary barriers to entry of AI in the healthcare sector. Across original papers and in wide-ranging responses, the contributors analyze barriers of four types: incentives, management, data availability, and regulation. They also suggest that AI has the potential to improve outcomes and lower costs. Understanding both the benefits of and barriers to AI adoption is essential for designing policies that will affect the evolution of the healthcare system.

Harness the full power of the behavioral data in your company by learning tools specifically designed for behavioral data analysis. Common data science algorithms and predictive analytics tools treat customer behavioral data, such as clicks on a website or purchases in a supermarket, the same as any other data. Instead, this practical guide introduces powerful methods specifically tailored for behavioral data analysis. Advanced experimental design helps you get the most out of your A/B tests, while causal diagrams allow you to tease out the causes of behaviors even when you can't run experiments. Written in an accessible style for data scientists, business analysts, and behavioral scientists, thispractical book provides complete examples and exercises in R and Python to help you gain more insight from your data--immediately. Understand the specifics of behavioral data Explore the differences between measurement and prediction Learn how to clean and prepare behavioral data Design and analyze experiments to drive optimal business decisions Use behavioral data to understand and measure cause and effect Segment customers in a transparent and insightful way

Taken from the first definitive introduction to behavioral economics, The Foundations of Behavioral Economic Analysis: Other-Regarding Preferences is an authoritative and cutting edge guide to this essential topic for advanced undergraduate and postgraduate students. It considers the evidence from experimental games on human sociality, and gives models and applications of inequity aversion, intention based reciprocity, conditional cooperation, human virtues, and social identity. This updated extract from Dhami's leading textbook allows the reader to pursue subsections of this vast and rapidly growing field and to tailor their reading to their specific interests in behavioural economics.

Today, behavioral economics has become virtually mainstream.

This book is intended as a textbook for a course in behavioral economics for advanced undergraduate and graduate students who have already learned basic economics. The book will also be useful for introducing behavioral economics to researchers. Unlike some general audience books that discuss behavioral economics, this book does not take a position of completely negating traditional economics. Its position is that both behavioral and traditional economics are tools that have their own uses and limitations. Moreover, this work makes clear that knowledge of traditional economics is a necessary basis to fully understand behavioral economics. Some of the special features compared with other textbooks on behavioral economics are that this volume has full chapters on neuroeconomics, cultural and identity economics, and economics of happiness. These are distinctive subfields of economics that are different from, but closely related to, behavioral economics with many important overlaps with behavioral economics. Neuroeconomics, which is developing fast partly because of technological progress, seeks to understand how the workings of our minds affect our economic decision making. In addition to a full chapter on neuroeconomics, the book provides explanations of findings in neuroeconomics in chapters on prospect theory (a major decision theory of behavioral economics under uncertainty), intertemporal economic behavior, and social preferences (preferences that exhibit concerns for others). Cultural and identity economics seek to explain how cultures and people’s identities affect economic behaviors, and economics of happiness utilizes measures of subjective well-being. There is also a full chapter on behavioral normative economics, which evaluates economic policies based on findings and theories of behavioral economics.

Conventional wisdom once held that the demand for addictive substances like cigarettes, alcohol, and drugs was unlike that for any other economic good and, therefore, unresponsive to traditional market forces. Recently, however, researchers from two disparate fields, economics and behavioral psychology, have found that increases in the overall price of an addictive substance can significantly reduce both the number of users and the amounts those users consume. Changes in the "full price" of addictive substances—including monetary value, time outlay, effort to obtain, and potential penalties for illegal use—yield marked variations in behavioral outcomes and demand. The Economic Analysis of Substance Use and Abuse brings these distinctive fields of study together and presents for the first time an integrated assessment of their data and results. Unique and innovative, this multidisciplinary volume will serve as an important resource in the current debates concerning alcohol and drug use and abuse and the impacts of legalizing illicit drugs.