nep-dcm New Economics Papers
on Discrete Choice Models
Issue of 2015‒01‒09
five papers chosen by
Edoardo Marcucci
Università degli studi Roma Tre

  1. Social norms, Morals and Self-interest as Determinants of Pro-environment Behaviours By Czajkowski, Mikolaj; Hanley, Nick; Nyborg, Karine
  2. The Effects of Experience on Preferences: Theory and Empirics for Environmental Public Goods By Mikolaj Czajkowski; Nick Hanley; Jacob LaRiviere
  3. Iteration Capping For Discrete Choice Models Using the EM Algorithm By Kabatek, J.
  4. When Is The Best Time To Give Birth - Career Effects Of Early Birth Decisions By Frühwirth-Schnatter, Sylvia; Pamminger, Christoph; Weber, Andrea; Winter-Ebmer, Rudolf
  5. The effects of energy costs on firm re-location decisions By Lucia Lavric; Nick Hanley

  1. By: Czajkowski, Mikolaj (University of Warsaw, Faculty of Economic Sciences, Poland); Hanley, Nick (University of St Andrews, School of Geography and Sustainable Development, UK,); Nyborg, Karine (Dept. of Economics, University of Oslo)
    Abstract: This paper considers the role which selfish, moral and social incentives and pressures play in explaining the extent to which stated choices over pro-environment behaviours vary across individuals. The empirical context is choices over household waste contracts and recycling actions in Poland. A theoretical model is used to show how cost-based motives and the desire for a positive self- and social image combine to determine the utility from alternative choices of recycling behaviour. We then describe a choice experiment designed to empirically investigate the effects such drivers have on stated choices. Using a latent class model, we distingush three types of individual who are described as duty-orientated recyclers, budget recyclers and homo oeconomicus. These groups vary in their preferences for how frequently waste is collected, and the number of categories into which household waste must be recycled. Our results have implications for the design of future policies aimed at improving participation in recycling schemes.
    Keywords: Household recycling; choice experiment; latent class model
    JEL: D01 D64 Q53
    Date: 2014–08–30
  2. By: Mikolaj Czajkowski (Faculty of Economic Sciences, University of Warsaw, Poland); Nick Hanley (School of Geography and Sustainable Development, University of St. Andrews); Jacob LaRiviere (Department of Economics, University of Tennessee)
    Abstract: This paper develops a choice model for environmental public goods which allows for consumers to learn about their preferences through consumption experiences. We develop a theoretical model of Bayesian updating, perform comparative statics over the model, and show how the theoretical model can be consistently incorporated into a reduced form econometric model. Our main findings are that in a Random Utility Model (RUM) discrete choice model, a subject’s scale should increase and the variability of scale should decrease with experience if subjects are Bayesians. We then estimate the model using field data regarding preferences for one particular public good, water quality. We find strong evidence that additional experience increases scale, thereby makes consumer preferences more predictable from the econometrician’s perspective. We find supportive but less convincing evidence that experience decreases the variability of scale across subjects.
    Keywords: Bayesian updating,choice experiment,learning,scale, scale variance
    JEL: C51 D83 Q51 H43
    Date: 2014–09
  3. 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
  4. By: Frühwirth-Schnatter, Sylvia; Pamminger, Christoph; Weber, Andrea; Winter-Ebmer, Rudolf
    Abstract: Using Bayesian Markov chain clustering analysis we investigate career paths of Austrian women after their first birth. This data-driven method allows characterizing long-term career paths of mothers over up to 19 years by transitions between parental leave, non-employment and different forms of employment. We, thus, classify women into five cluster-groups with very different long-run career costs of childbearing. We model group membership with a multinomial specification within the finite mixture model. This approach gives insights into the determinants of the long-run family gap. Giving birth late in life may lead very diverse outcomes: on the one hand, it increases the odds to drop out of labor force, and on the other hand, it increases the odds to reach a high-wage career track.
    Keywords: family gap; fertility; Markov Chain Monte Carlo; Multinomial Logit; Panel Data; timing of birth; Transition Data
    JEL: J13
    Date: 2014–09
  5. By: Lucia Lavric (Department of Economics, Duke University); Nick Hanley (School of Geography and Sustainable Development, University of St. Andrews)
    Abstract: Energy costs are partly driven by environmental policy choices. In this paper, the effects of variations in energy costs – as measured by end-user electricity prices – on firm relocation decisions are investigated. Using a discrete choice model a nd a data base which has not previously been exploited to study this problem, we investigate the effects of variations in energy costs both for a sub-set of re-locating European firms in terms of which country they move to; and then for a larger set of firms in terms of the decision to re-locate or not in response to higher energy prices. We find that energy costs play a significant role in determining relocation destinations, and that this effect is asymmetric between firms moving into and out of a country , and between high energy intensity and low energy intensity sectors. The findings of the paper have implications for the Pollution Havens Hypothesis, since they show the extent to which the effects of climate policy on domestic energy costs can be expected to impact on firm relocation decisions both into and out of a country.
    Keywords: firm re-location, energy costs, Pollution Havens Hypothesis, climate policy, carbonleakage
    JEL: D22 F18 Q41 Q52
    Date: 2014–08

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