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Stated Choice Methods

TL;DR: In this article, the authors focus on stated preference (SP) methods, placing decision makers in controlled experiments that yield hypothetical choices, rather than revealed preferences (RP) - actual choices in the market.
Abstract: Understanding and predicting the behaviour of decision makers when choosing among discrete goods has been one of the most fruitful areas of applied research over the last thirty years. An understanding of individual consumer behaviour can lead to significant changes in product or service design, pricing strategy, distribution channel and communication strategy selection, as well as public welfare analysis. This graduate and practitioner guide, first published in 2000, deals with the study and prediction of consumer choice behaviour, concentrating on stated preference (SP) methods - placing decision makers in controlled experiments that yield hypothetical choices - rather than revealed preferences (RP) - actual choices in the market. It shows how SP methods can be implemented, from experimental design to econometric modelling, and suggests how to combine RP and SP data to get the best from each type. The book also presents an update of econometric approaches to choice modelling.
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BookDOI
01 Jan 2008
TL;DR: Using Discrete Choice Experiments to Value Health and Health Care takes a fresh and contemporay look at the growing interest in the development and application of discrete choice experiments (DCEs) within the field of health economics.
Abstract: Using Discrete Choice Experiments to Value Health and Health Care takes a fresh and contemporay look at the growing interest in the development and application of discrete choice experiments (DCEs) within the field of health economics. The authors have written it with the purpose of giving the reader a better understanding of issues raised in the design and application of DCEs in health economics. The use of this relatively new instrument to value health and health care has now evolved to the point where a general text is necessary. The few existing books in this area are either research monographs or focus almost entirely on more advanced topics. By contrast, this book serves as a general reference for those applying the technique to health care for the first time as well as more experienced practitioners. Thus the book is relevant to post-graduate students and applied researchers with an interest in the use of DCEs for valuing health and health care and has international appeal. The book comprises Chapters by highly regarded academics with experience of applying DCEs in the area of health. The first part of the book summarises how DCEs can be implemented, from experimental design to data analysis and the interpretation of results. In many ways this can be regarded as a crash course on the conduct of DCEs. Extensive reference is made throughout to other sources of literature where the interested reader can find further details. The book also includes a series of case studies illustrating the breadth of applications in health economics and some key methodological issues. Finally there is an overview of research issues discussed which the editors believe are at the leading edge of this field.

668 citations

Journal ArticleDOI
TL;DR: In this article, the authors employ dichotomous, multinomial and conditional logit models to analyze the employment-migration behavior of some 380,000 U.K. university graduates.
Abstract: In this paper we employ dichotomous, multinomial and conditional logit models to analyze the employment-migration behavior of some 380,000 U.K. university graduates. By controlling for a range of variables related to human capital acquisition and local economic conditions, we are able to distinguish between different types of sequential migration behavior from domicile to higher education and on to employment. Our findings indicate that U.K. female graduates are generally more migratory than male graduates. We suggest that the explanation for this result lies in the fact that migration can be used as a partial compensation mechanism for gender bias in the labor market.

261 citations

Posted Content
TL;DR: The authors argue that consumers evaluate annuity products using a narrow investment frame that focuses on risk and return, rather than a "consumption frame" that considers the consequences for lifelong consumption.
Abstract: Rational models of risk-averse consumers have difficulty explaining limited annuity demand. We posit that consumers evaluate annuity products using a narrow "investment frame" that focuses on risk and return, rather than a "consumption frame" that considers the consequences for lifelong consumption. Under an investment frame, annuities are quite unattractive, exhibiting high risk without high returns. Survey evidence supports this hypothesis: whereas 72 percent of respondents prefer a life annuity over a savings account when the choice is framed in terms of consumption, only 21 percent of respondents prefer it when the choice is framed in terms of investment features.

255 citations

Journal ArticleDOI
TL;DR: The authors argue that consumers evaluate annuity products using a narrow investment frame that focuses on risk and return, rather than a "consumption frame" that considers the consequences for lifelong consumption.
Abstract: Rational models of risk-averse consumers have difficulty explaining limited annuity demand. We posit that consumers evaluate annuity products using a narrow "investment frame" that focuses on risk and return, rather than a "consumption frame" that considers the consequences for lifelong consumption. Under an investment frame, annuities are quite unattractive, exhibiting high risk without high returns. Survey evidence supports this hypothesis: whereas 72 percent of respondents prefer a life annuity over a savings account when the choice is framed in terms of consumption, only 21 percent of respondents prefer it when the choice is framed in terms of investment features.

244 citations

Journal ArticleDOI
TL;DR: This work calls for the use of a common nomenclature to describe what was done in a data collection effort for stated preference studies, and takes a first step at setting out such nomenClature.
Abstract: It is often difficult to determine what actually was done in work involving data collected with stated preference surveys because the terms used to describe various proce- dures have ambiguous and sometimes conflicting meanings. Further, terms used to describe data collection procedures often are confounded with terms used to describe statistical tech- niques. We call for the use of a common nomenclature to describe what was done in a data collection effort for stated preference studies, and take a first step at setting out such nomen- clature. We only seek to improve clarity in the communication of research results and take no position here on appropriateness of particular procedures.

239 citations