We introduce DOSE--Dynamically Optimized Sequential Experimentation--to elicit preference parameters. DOSE starts with a model of preferences and a prior over the parameters of that model, then dynamically chooses a customized question sequence for each participant according to an...

We introduce DOSE - Dynamically Optimized Sequential Experimentation - to elicit preference parameters. DOSE starts with a model of preferences and a prior over the parameters of that model, then dynamically chooses a customized question sequence for each participant according to an...

We measure individual-level loss aversion using three incentivized, representative surveys of the U.S. population (combined N = 3,000). We find that around 50% of the U.S. population is loss tolerant, with many participants accepting negative-expected-value gambles. This is counter to earlier...

Frontmatter -- CONTENTS -- LIST OF CONTRIBUTORS -- PREFACE -- ACKNOWLEDGMENTS -- PART I: Introduction -- CHAPTER ONE. Behavioral Economics: Past, Present, Future / Camerer, Colin F. / Loewenstein, George -- PART II: Basic Topics -- REFERENCE-DEPENDENCE AND LOSS-AVERSION -- CHAPTER TWO....

We introduce DOSE - Dynamically Optimized Sequential Experimentation - and use it to estimate individual-level loss aversion in a representative sample of the U.S. population (N=2,000). DOSE elicitations are more accurate, more stable across time, and faster to administer than standard methods....