Comparing discrete choice models: some housing market examples

Introduction: Since the mid nineteen seventies there has been strong interest within variolls branches of social science in the adaptation of the discrete choice modeling methodology towards a wide range of research problems. This has required recognition of a wide variety of alternative decision-contexts (Landau et a1. 1982) and behaviour-patterns (Lerman, 1979), and has also raised general issues concerning the variable extent to which individual or subgroup choices may be restricted by spatial and temporal constraints. Further interest has been expressed about the spatial and temporal transferability of alternative discrete choice models (Atherton and Ben-Akiva, 1976: Galbraith and Hensher, 1982). This substantive diversification has been accompanied by a variety of technical and methodological refinements of the multinomiallogit (MNL) and multinomial probit (MNP) models, ranging from new estimation procedures (Hausman and Wise, 1978) to the development of less-restrictive, computationally tractable discrete choice model forms (for example, Williams, 1977: Daly and Zachary, 1978). Faced with both a wider selection of methodological tools and a broader spectrum of substantive enquiry, there exists a clear need for formal comparison procedures which the analyst can call upon to evaluate a given model specification or framework. In this paper, I attempt to review briefly some trends amongst recent housing choice studies which employ discrete choice modeling methods. A new procedure is then presented (Hubert and Golledge, 1981; Halperin et al. 1984) which may be used to compare discrete choice models specified and/or structured in accordance with different a priori hypotheses. It is argued that this method fills a gap between existing discrete choice model comparison-procedures which are inapplicable to 'nonnested' model specifications, that is, to competing discrete choice models which comprise totally different variable specifications and that such procedures can usefully aid selection of the discrete choice model most appropriate to any given decision context

Determinants of farm diversification and interaction with the CAP. An application to FADN of Marche region (Italy)

This work analyzes farm diversification activities in an Italian region (Marche). The study examines 387 farms from Farm Accountancy Data Network (FADN) over a six-year period (2000-2005), applying Discrete Choice Models to identify their business. Recognizing the driving forces of such diversification strategy can be useful to better design those agricultural policies explicitly aimed at promoting agricultural multifunctionality as well as social and environmental sustainability. The linkage between diversification choices and CAP payments is thus also investigated.Farm diversification, Discrete Choice Models, Multifunctionality, Agricultural and Food Policy, Farm Management,

Can social interaction contribute to explain business cycles?

Recent literature has been able to include into standard optimal growth models some hypotheses that allow for the generation of endogenous long run fluctuations. This paper contributes to this endogenous business cycles literature by considering social interactions. In the proposed model, individuals can choose, under a discrete choice rule, to which social group they prefer to belong to. This selection process is constrained essentially by the dimension of the group, which is the main determinant regarding the utility individuals withdraw from social interaction. The proposed setup implies the presence of cycles and chaotic motion describing the evolution of group dimension over time. Because being member of a group involves costs to households, the inclusion of these costs in a standard Ramsey growth model will imply that endogenous cycles might arise in the time trajectory of the growth rate of output.Social interaction; Business cycles; Growth models; Nonlinear dynamics and Chaos; Discrete choice

Interdependent binary choices under social influence: phase diagram for homogeneous unbiased populations

Coupled Ising models are studied in a discrete choice theory framework, where they can be understood to represent interdependent choice making processes for homogeneous populations under social influence. Two different coupling schemes are considered. The nonlocal or group interdependence model is used to study two interrelated groups making the same binary choice. The local or individual interdependence model represents a single group where agents make two binary choices which depend on each other. For both models, phase diagrams, and their implications in socioeconomic contexts, are described and compared in the absence of private deterministic utilities (zero opinion fields).Comment: 17 pages, 3 figures. This is the pre-peer reviewed version of the following article: Ana Fern\'andez del R\'io, Elka Korutcheva and Javier de la Rubia, Interdependent binary choices under social influence, Wiley's Complexity, 2012; which has been published in final form at http://onlinelibrary.wiley.com/doi/10.1002/cplx.21397/abstrac

A Low-key Social Insurance Reform - Treatment Effects for Back Pain Patients in Norway

This paper estimates treatment effects for back pain patients using observational data from a low-key social insurance reform in Norway. Using a latent variable model we estimate the average treatment effects (ATE), the average effect of treatment on the treated (TT), and the distribution of treatment effects for outpatient treatment at three different locations. To estimate these parameters and the distribution of treatment effects we use a discrete choice model with unobservables generated by a factor structure model. Distance to nearest hospital (in kilometers) is used as an instrument in estimating the different treatment effects. We find a positive effect of treatment of 6 percentage points on the probability of leaving sickness benefits after allowing for selection effects and full heterogeneity in treatment effects. We also find that there are sound arguments for increasing the outpatient program of treating back pain patients.Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Project Evaluation; Social Discount Rate; General; Unemployment: Models; Duration; Incidence; and Job Search.

Hybrid choice models : principles and recent progress incorporating social influence and nonlinear utility functions

AbstractHybrid choice models have been developed as an extension of discrete choice models, particularly multinomial logit models, in an attempt to include attitudinal variables. The quintessence of hybrid choice models is that a model of attitude formation is estimated and the estimated attitudes are added to the commonly used set of attributes in discrete choice models: attributes of the choice alternatives and socio-demographic variables. The most commonly applied model is based on linear specifications, both for the attitude model and the utility function. In this review paper, we discuss the principles underlying the hybrid choice model, summarize the specifications used in previous applications of the model and then continue discussing recent progress that added social influence to the model specification and replaced the linear specification of the utility function with a nonlinear function

Fishing for Understanding: A Mixed Logit Model of Freshwater Angler Preferences

Freshwater fisheries management requires knowledge of not only the resource but angler preferences and the extent to which preferences vary. This paper reports results from an internet-based stated preference survey of anglers in the North Canterbury region. Discrete choice models are used to investigate how the quality of fishery attributes impact anglers’ selection of fishing sites. The models reveal significant preference heterogeneity between anglers for particular fishing site attributes. Furthermore, anglers’ preference intensities for identical attributes vary between sites. Consequently, efficient allocation of resources entails spatial and social components.discrete choice analysis, latent class, mixed logit, angler heterogeneity, New Zealand recreational trout fisheries, Agricultural and Food Policy, Environmental Economics and Policy, Research Methods/ Statistical Methods,

Improving the analysis of road pricing acceptability surveys by using hybrid models

Several international studies have analyzed the acceptability of road pricing schemes by means of an attitude survey in combination with the results of a stated choice experiment using both a descriptive analysis and a discrete-choice model with binary choice (?accept? or ?not accept? the toll). However, the use of hybrid discrete choice models constitutes an innovative alternative for integrating subjective attitudes and perceptions deriving from the survey of attitudes with the more objective variables from the stated choice experiment. This paper analyzes the results of applying these models to measure the acceptability of interurban road pricing among different groups of stakeholders (road freight and passenger operators, highway concessionaires, and associations of private car users) with qualitatively significant opinions on road pricing measures. Our results show that hybrid models are better suited to explaining the acceptability of a road pricing scheme by different groups of stakeholders than a separate analysis of the survey of attitudes and a discrete-choice model applied on a stated choice experiment. A particular finding was that the strong psycho-social latent variable of the perception of fairness explains the rejection or acceptance of a toll scheme by road stakeholders