nep-dcm New Economics Papers
on Discrete Choice Models
Issue of 2013‒03‒30
four papers chosen by
Edoardo Marcucci
Universita' di Roma Tre

  1. Iteration Capping For Discrete Choice Models Using the EM Algorithm By Kabatek, J.
  2. Estimating Bayesian decision problems with heterogeneous priors By Stephen Eliot Hansen; Michael McMahon
  3. Individual Decisions And System Development - Integrating Modelling Approaches For The Heating Market By Klaas Bauermann; Stephan Spiecker; Christoph Weber
  4. The Impact of Individual Risk Preferences on Valuing Preservation of Threatened Species: an Application to Lynx Populations in Poland By Anna Bartczak; Susan Chilton; Jürgen Meyerhoff

  1. By: Kabatek, J. (Tilburg University, Center for Economic Research)
    Abstract: The Expectation-Maximization (EM) algorithm is a well-established estimation procedure which is used in many domains of econometric analysis. Recent application in a discrete choice framework (Train, 2008) facilitated estimation of latent class models allowing for very exible treatment of unobserved heterogeneity. The high exibility of these models is however counterweighted by often excessively long computation times, due to the iterative nature of the EM algorithm. This paper proposes a simple adjustment to the estimation procedure which proves to achieve substantial gains in terms of convergence speed without compromising any of the advantages of the original routine. The enhanced algorithm caps the number of iterations computed by the inner EM loop near its minimum, thereby avoiding optimization over suboptimally populated classes. Performance of the algorithm is assessed on a series of simulations, with the adjusted algorithm being 3-5 times faster than the original routine.
    Keywords: EM algorithm;discrete choice models;latent class models
    JEL: C14 C63
    Date: 2013
  2. By: Stephen Eliot Hansen; Michael McMahon
    Abstract: In many areas of economics there is a growing interest in how expertise and preferences drive individual and group decision making under uncertainty. Increasingly, we wish to estimate such models to quantify which of these drive decision making. In this paper we propose a new channel through which we can empirically identify expertise and preference parameters by using variation in decisions over heterogeneous priors. Relative to existing estimation approaches, our \Prior- Based Identification" extends the possible environments which can be estimated, and also substantially improves the accuracy and precision of estimates in those environments which can be estimated using existing methods.
    Keywords: Bayesian decision making; expertise; preferences; estimation.
    JEL: D72 D81 C13
    Date: 2013–03
  3. By: Klaas Bauermann; Stephan Spiecker; Christoph Weber (Chair for Management Sciences and Energy Economics, University of Duisburg-Essen)
    Abstract: Improvements in the building stock insulation and the replacement of heating systems will have to take place within the next decades in order to lower heat demand and the associated carbon emissions of the building sector. Moreover, continuous investments in heating systems are nec-essary due to replacement activities. Besides conventional heating technologies like gas- or oil-fired heating systems and combined heat and power (CHP) plants in district heating, increasing-ly renewable systems like heat pumps and pellet stoves will have to be installed to cover heat demand. The current study presents an integrated, iterative modelling approach to determine the development of the heating market. A system model captures the fundamental influencing factors on the investment decision while a logistic decision model describes in detail the build-ing owners’ behaviour, taking into account the heterogeneous building stock and possible non-economic factors influencing heating system choice. In the application case, the potentials for different heating technologies are investigated under three different economic scenarios for the German heating market until 2050.
    Keywords: Heating, Residential Energy Demand, Discrete Choice, Peak Load Pricing
    JEL: Q47 Q48 E61 C53 C35
    Date: 2013–02
  4. By: Anna Bartczak (Faculty of Economic Sciences, University of Warsaw); Susan Chilton (Newcastle University Business School); Jürgen Meyerhoff (Technische Universität Berlin, Institute for Landscape and Environmental Planning)
    Abstract: A recent innovation in environmental valuation surveys has been to acknowledge the inherent uncertainties surrounding the provision of environmental goods and services and to incorporate it into non-market survey designs. So far, little is known about how people assimilate and respond to such uncertainty, particularly in terms of how it affects their stated valuations. In this paper we focus on the impact of risk preferences on people’s investments in environment. Individual risk preferences are elicited through a standard, incentivized multiple price list mechanism and used as a independent variable in the analysis of a choice experiment valuing the preservation of two threatened lynx populations in Poland. We find that risk-seeking respondents were more likely to choose the status quo option, which was the riskiest option in terms of the survival of the two distinct lynx populations. Risk seekers revealed also a significantly lower willingness to pay for lynx preservations.
    Keywords: choice experiment, environmental good, lottery experiment, lynx preservation, risk preferences, status quo effect
    JEL: Q23 Q51 Q56 Q57
    Date: 2013

This nep-dcm issue is ©2013 by Edoardo Marcucci. It is provided as is without any express or implied warranty. It may be freely redistributed in whole or in part for any purpose. If distributed in part, please include this notice.
General information on the NEP project can be found at For comments please write to the director of NEP, Marco Novarese at <>. Put “NEP” in the subject, otherwise your mail may be rejected.
NEP’s infrastructure is sponsored by the School of Economics and Finance of Massey University in New Zealand.