Understanding Heterogeneous Preferences in Random Utility Models: A Latent Class Approach

A finite mixture approach toconditional logit models is developed in whichlatent classes are used to promoteunderstanding of systematic heterogeneity. The model is applied to wilderness recreationin which a branded choice experiment involvingchoice of one park from a demand system wasadministered to a sample of recreationists. The basis of membership in the classes orsegments in the sample involved attitudinalmeasures of motivations for taking a trip, aswell as their stated preferences overwilderness park attributes. The econometricanalysis suggested that four classes of peopleexist in the sample. Using the model toexamine welfare measures of some hypotheticalpolicy changes identified markedly differentwelfare effects than the standard singlesegment model, and provided insight into thedifferential impact of alternative policies.     

Using an integrated choice and latent variable model to understand the impact of “professional” respondents in a stated preference survey

Internet panels are increasingly used for stated preference research. Because members of such panels receive compensation for each completed survey, one concern is that over time this creates professional respondents who answer surveys solely for the monetary compensation. We identify professional respondents using data on panel tenure, survey response frequency, completion rate and total number of completed surveys. We find evidence of two types of professional respondents: “hyperactives” who answer surveys frequently and “experienced” who have long panel tenure and a large number of completed surveys. Using an integrated choice and latent variable model on stated preference survey data, we find that “hyperactive” respondents are less likely to choose the 'status quo’ and have a more stochastic choice process as seen from the econometrician's point of view, whereas “experienced” respondents have a relatively more deterministic choice process. Our results show that “hyperactive” respondents significantly impact estimated values.     

What You Don’t Know Might Hurt You: Some Unresolved Issues in the Design and Analysis of Discrete Choice Experiments

The papers and comments in this issue focus on four broad areas related to understanding and modeling choices: (1) The use of laboratory experiments to improve valuation methods; (2) The design of stated preference choice set and choice occasions; (3) Latent class models as means of identifying and accommodating preference heterogeneity; and (4) Accommodating uncertainty about the “true” model, modeling ranking and rating tasks and pooling data sources. In what follows I offer some comments on each area, and briefly discuss several unresolved issues associated with each area, closing with some comments about future research opportunities.     

Efficiency measurement using a latent class stochastic frontier model

Efficiency estimation in stochastic frontier models typically assumes that the underlying production technology is the same for all firms. There might, however, be unobserved differences in technologies that might be inappropriately labeled as inefficiency if such variations in technology are not taken into account. We address this issue by estimating a latent class stochastic frontier model in a panel data framework. An application of the model is presented using Spanish banking data. Our results show that bank-heterogeneity can be fully controlled when a model with four classes is estimated. This paper was written during Luis Oreas visit to Binghamton University in the summer of 2002. We would like to thank an associate editor of the journal and two anonymous referees for their detailed comments. However, we alone are responsible for any remaining errors.     

Inducing risk preferences in multi-stage multi-agent laboratory experiments

Though there has been some debate over the practical efficacy of using binary lotteries for controlling risk preferences in experimental environments, the question of its theoretical validity within the contexts it is often used, namely multi-stage multi-agent settings, has not been addressed. Whilst the original proof of its validity featured a single-agent single-stage context, its practical use has seen a wide range of implementations. Practitioners have implicitly assumed that whenever the setting and form of implementation they have chosen deviates from the original single-agent single-period proof, it remains theoretically valid. There has been virtually no debate in the practitioner literature on the theoretical validity of binary lotteries in a more general context, or on whether the form of implementation matters. The current article addresses these questions, establishes limitations on validity and suggests some design principles for future implementation of binary lotteries for the purpose of controlling risk preferences.     

More health care utilization with more insurance coverage? Evidence from a latent class model with German data

We analyse the impact of optional deductibles, private supplementary health insurance and income on the demand for health care utilization, measured as the number of physician visits with data from the German Socio-Economic Panel (SOEP). With a set of newly available variables for the years 2002, 2004 and 2006 that measure individual health more accurately and including risk-attitudes towards health we find that possible endogeneity of the insurance choice is not a problem. A latent class approach that takes into account the panel structure of the data reveals that especially individuals who have few doctor visits, the low users, respond strongest to insurance status and income. In this group we find that more insurance increases the demand for physician visits and there is a pro-rich inequity in health care utilization. No such effects are found for the high users.     

Valuation in the Lab

Experimental methods have proven useful to explore the power and limits to nonmarket valuation through stated preference methods. We now understand better how people learn about and react to the incentives, institutions, and information created by surveys. This paper briefly reviews topics in experimental valuation, including ex ante bias corrections, ex post bias calibration, and examining the circumstances that strengthen or weaken the economist’s presumption of rational valuation.     

水安全思想约束下的城市水消费定价模式研究

水安全思想是城市水资源保护和水消费定价的基本经济依据。水作为稀缺性经济资源,涉及水安全的环境治理成本和节约用水成本,是城市水消费定价管理中不可忽视的重要组成,也是可持续性水消费理论的重要研究内容。     

Convenient estimators for the panel probit model: Further results

Bertschek and Lechner (1998) propose several variants of a GMM estimator based on the period specific regression functions for the panel probit model. The analysis is motivated by the complexity of maximum likelihood estimation and the possibly excessive amount of time involved in maximum simulated likelihood estimation. But, for applications of the size considered in their study, full likelihood estimation is actually straightforward, and resort to GMM estimation for convenience is unnecessary. In this note, we reconsider maximum likelihood based estimation of their panel probit model then examine some extensions which can exploit the heterogeneity contained in their panel data set. Empirical results are obtained using the data set employed in the earlier study. Helpful comments and suggestions by Irene Bertschek and Michael Lechner are gratefully acknowledged. This paper has also benefited from comments by two anonymous referees and from seminar participants at the Center for Health Economics at the University of York. Any remaining errors are the responsibility of the author.     

我国证券市场的国际化及战略选择

证券市场的国际化是世界经济全球化发展的必然结果。随着我国加入WTO，新兴的中国证券市场应积极创造条件，参与国际证券市场的竞争，并从证券市场国际化发展的过程中，总结经验，采取对策，积极稳妥地推进中国证券市场的国际化进程。     

Altruism and the Economic Values of Environmental and Social Policies

Altruism is a type of non-use value which can have different definitions depending on the type of goods entering the utility function of the altruists and their expectations about the contributions of others. The purpose of this paper is to measure the trade-offs between different types of altruist values originating from social and environmental policies. Environmental policies are concerned with reducing health effects from a power plant while social policies involve both the attainment of public facilities for education and leisure and an increase in the income of the affected population. The empirical application utilizes a choice experiment technique which allows for valuation of multiple goods. Health effects are decomposed into the values of the risk of becoming ill, the duration of the episodes and the limitations imposed by illness. Altruist values are elicited from a population that is not affected by pollution. Results show that altruism is significant for policies directed to reducing health effects and improving the income level of the affected population, whereas there is egoism for a policy aimed at improving public facilities in the polluted suburb. The value of altruism is significantly influenced by the expectations of net benefits to be received by the affected population.     

A Discussion of “Using Angler Characteristics and Attitudinal Data to Identify Environmental Preference Classes: A Latent-Class Model”

In the current issue of Environmental and Resource Economics, Morey et al. (2006) discuss a new approach to using attitudinal data in latent class modeling. We compare this approach with the one taken in Boxall and Adamowicz (2002), in the context of a discrete choice, random utility framework with heterogeneous preferences. We derive the respective likelihood functions of the two approaches to show that they are structurally similar, and discuss their implications for the use of attitudinal data. We conclude with a discussion comparing the relative merits of latent class and random parameters (mixed logit) modeling, offering the view that as a practical matter, choosing between them depends on the analyst’s judgment about the correlation of preference parameters.     

The Impact of Choice Inconsistencies in Stated Choice Studies

A new test procedure revealing mutuallyinconsistent choices has been developed andapplied to Stated Choice data. Our analysisshows that inconsistent choices commonly occurin several Stated Choice tasks. An applicationof the test to the Norwegian Value of Timestudy data shows that failing to excludeinconsistent choices resulted in asubstantially higher Value of time. Theinconsistent choices were made by less educatedparticipants. As the tasks were undertaken inthe easy context of choosing travelalternatives with three attributes,practitioners of more complex and cognitivedemanding designs should be particularilyconcerned with these results.