nep-dcm New Economics Papers
on Discrete Choice Models
Issue of 2013‒03‒09
seven papers chosen by
Edoardo Marcucci
Universita' di Roma Tre

  1. Comparing models of unobserved heterogeneity in environmental choice experiments By Kragt, Marit Ellen
  2. Identification in Models with Discrete Variables. By Laffers, Lukas
  3. Conditional Expected Utility By Massimiliano Amarante
  4. Providing Preference-Based Support for Forest Ecosystem Service Management in Poland By Mikołaj Czajkowski; Anna Bartczak; Marek Giergiczny; Stale Navrud; Tomasz Żylicz
  5. The application of discrete choice experiments in health economics: a systematic review of the literature By Alessandro Mengoni; Chiara Seghieri; Sabina Nuti
  6. Twenty Thousand Sterling Under the Sea: Estimating the value of protecting deep-sea biodiversity By Hanley, Nicholas; Hynes, Stephen; Jobstvogt, Niels; Kenter, Jasper; Witte, Ursula
  7. Spatio-Temporal Analysis of Car Distance, Greenhouse Gases and the Effect of Built Environment: a Latent Class Regression Analysis By Zahabi, Seyed Amir H.; Miranda-Moreno, Luis; Patterson, Zachary; Barla, Philippe

  1. By: Kragt, Marit Ellen
    Abstract: Choice experiments have become a widespread approach to non-market environmental valuation. Given the vast range of public opinions towards environmental management changes, it is desirable that analysis of discrete choice data accounts for the possibility of unobserved heterogeneity amongst the population. There is, however, no consensus about the best way to model individual heterogeneity. This paper presents four approaches to modelling heterogeneity that are increasingly used in the literature. Latent class, mixed logit, scaled multinomial logit and generalised mixed logit (GMXL) models are estimated using case study data for catchment environmental management in Australia. A GMXL model that accounts for preference and scale heterogeneity performs best. I evaluate the impacts of models on welfare estimates and discuss the merits of each modelling approach.
    Keywords: Choice Modelling, Econometrics, Random Parameters, Scale Heterogeneity, Unobserved Preference Heterogeneity, Environmental Economics and Policy, Research Methods/ Statistical Methods, C01, Q51 and Q59,
    Date: 2013–02–10
  2. By: Laffers, Lukas (Dept. of Economics, Norwegian School of Economics and Business Administration)
    Abstract: This paper provides a new simple and computationally tractable method for determining an identified set that can account for a broad set of economic models when economic variables are discrete. Using this method it is shown on a simple example how can imperfect instruments affect the size of the identified set when strict exogeneity is relaxed. It could be of great interest to know to what extent are the results driven by the exogeneity assumption which is often a subject of controversy. Moreover, flexibility gained from the new proposed method suggests that the determination of the identified set need not be application-specific anymore. This paper presents a unifying framework that approaches identification in an algorithmic way.
    Keywords: Identification; Models; Discrete Variables.
    JEL: C10 C21 C26 C61
    Date: 2013–01–08
  3. By: Massimiliano Amarante
    Abstract: Let E be a class of event. Conditionally Expected Utility decision makers are decision makers whose conditional preferences %E, E 2 E, satisfy the axioms of Subjective Expected Utility theory (SEU). We extend the notion of unconditional preference that is conditionally EU to unconditional preferences that are not necessarily SEU. We give a representation theorem for a class of such preferences, and show that they are Invariant Bi-separable in the sense of Ghirardato et al.[7]. Then, we consider the special case where the unconditional preference is itself SEU, and compare our results with those of Fishburn [6].
    Date: 2013
  4. By: Mikołaj Czajkowski (Faculty of Economic Sciences, University of Warsaw); Anna Bartczak (Faculty of Economic Sciences, University of Warsaw); Marek Giergiczny (Faculty of Economic Sciences, University of Warsaw); Stale Navrud (Norwegian University of Life Sciences); Tomasz Żylicz (Faculty of Economic Sciences, University of Warsaw)
    Abstract: The paper looks at people’s preferences for the changes in selected ecosystem services resulting from new management strategies of forest areas in Poland. It applies a generalized multinomial logit (G-MNL) model to interpret the results of a discrete choice experiment (DCE) study administered to a representative sample of 1001 Poles. The questionnaire included three physical attributes, namely: protecting the most ecologically valuable forest ecosystems, reducing litter in forests, and improving recreation infrastructure. The selection of these attributes was motivated by extensive qualitative research of what indicators of biodiversity, nature protection and recreation possibilities people are the most sensitive to. The fourth attribute was monetary – additional cost of the new programs which would have to be financed out of increased taxes. The results allowed for a robust estimation of implicit prices of the choice attributes and calculating welfare measures of specific forest management scenarios. In addition, the study revealed interesting connections between respondents’ current forest recreation patterns and the importance they place on different attributes of forests. The results make it possible to utilize respondents’ preference heterogeneity, to a large extent determined by their current recreational use patterns, in designing future forest management strategies.
    Keywords: biodiversity, forest recreation, discrete choice modeling, generalized multinomial logit model
    JEL: D12 H44 Q23 Q26 Q51
    Date: 2013
  5. By: Alessandro Mengoni; Chiara Seghieri (Istituto di Management - Scuola Superiore Sant’Anna, Pisa); Sabina Nuti (Istituto di Management - Scuola Superiore Sant’Anna, Pisa)
    Abstract: Objectives. In recent years, there has been a growing interest in the development and application of discrete choice experiments (DCEs) within health economics. Even though the literature include several reviews of the methodology associated with conducting DCEs and analysing the resultant choice data, a detailed classification of the areas covered by DCEs is lacking. The aim of this paper is to provide, after a brief description of the most important phases of a DCE, a comprehensive categorization of the various areas in which DCEs in health care have been performed. Methods. A systematic literature review was conducted to identify published studies using stated preferences DCEs within a health context between January 1990 and May 2011. Results. 256 DCEs were included in the review. Compared to the 1990-2000 period, the number of DCEs has increased quickly, with experiments carried out in 30 different countries. A growing number of studies primarily investigated patients’ preferences during the years, collecting a greater number of responses in comparison to the baseline period. A significant proportion of publications estimated the benefits of health care services, like specialistic surgical and medical services, generic medical services, services for chronics and elderly people, maternity and childbirth services and diagnostic facilities. Nevertheless, DCEs has also been used to value health outcomes, examine preferences for pharmaceutical products, investigate labour-market choices as well as healthcare systems characteristics and health policies. Conclusions. This paper adds to the body of literature reviewing the growing stock of published DCEs in health economics, providing a new detailed taxonomy of the various areas in which such experiments have been applied. Together with the methodological refinements, future research should continue to explore new contexts of analysis.
    Keywords: choice experiments, review, areas of application, health economics
    JEL: I10
    Date: 2013–01–01
  6. By: Hanley, Nicholas; Hynes, Stephen; Jobstvogt, Niels; Kenter, Jasper; Witte, Ursula
    Abstract: The deep-sea includes over 90% of the world oceans and is thought to be one of the most diverse ecosystems in the World. It supplies society with valuable ecosystem services, including the provision of food, the regeneration of nutrients and the sequestration of carbon. Technological advancements in the second half of the 20th century made large-scale exploitation of mineral-, hydrocarbon- and fish resources possible. These economic activities, combined with climate change impacts, constitute a considerable threat to deep-sea biodiversity. Many governments, including that of the UK, have therefore decided to implement additional protected areas in their waters of national jurisdiction. To support the decision process and to improve our understanding for the acceptance of marine conservation plans across the general public, a choice experiment survey asked Scottish households for their willingness-to-pay for additional marine protected areas in the Scottish deep-sea. This study is one of the first to use valuation methodologies to investigate public preferences for the protection of deep-sea ecosystems. The experiment focused on the elicitation of economic values for two aspects of biodiversity: (i) the existence value for deep-sea species and (ii) the option-use value of deep-sea organisms as a source for future medicinal products.
    Keywords: existence value; option-use value; choice experiment; Deep-sea biodive rsity
    Date: 2013
  7. By: Zahabi, Seyed Amir H.; Miranda-Moreno, Luis; Patterson, Zachary; Barla, Philippe
    Abstract: This work examines the temporal-spatial variations of daily automobile distance traveled and greenhouse gas emissions (GHGs) and their association with built environment attributes and household socio-demographics. A GHGs household inventory is determined using link-level average speeds for a large and representative sample of households in three origin-destination surveys (1998, 2003 and 2008) in Montreal, Canada. For the emission inventories, different sources of data are combined including link-level average speeds in the network, vehicle occupancy levels and fuel consumption characteristics of the vehicle fleet. Built environment indicators over time such as population density, land use mix and transit accessibility are generated for each household in each of the three waves. A latent class (LC) regression modeling framework is then implemented to investigate the association of built environment and socio-demographics with GHGs and automobile distance traveled. Among other results, it is found that population density, transit accessibility and land-use mix have small but statistically significant negative impact on GHGs and car usage. Despite that this is in accordance with past studies, the estimated elasticities are greater than those reported in the literature for North American cities. Moreover, different household subpopulations are identified in which the effect of built environment varies significantly. Also, a reduction of the average GHGs at the household level is observed over time. According to our estimates, households produced 15% and 10% more GHGs in 1998 and 2003 respectively, compared to 2008. This reduction is associated to the improvement of the fuel economy of vehicle fleet and the decrease of motor-vehicle usage. A strong link is also observed between socio-demographics and the two travel outcomes. While number of workers is positively associated with car distance and GHGs, low and medium income households pollute less than high-income households.
    Keywords: Greenhouse gas emissions, spatio-temporal variations, built environment, latent class regression, household clusters, Environmental Economics and Policy, R42, R48, Q54, Q58,
    Date: 2013–01

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