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on Discrete Choice Models |
| By: | Niels Erik Kaaber Rasmussen; Marianne Frank Hansen (Danish Rational Economic Agents Model, DREAM); Peter Stephensen (Danish Rational Economic Agents Model, DREAM) |
| Abstract: | Determining transition probabilities is a vital part of dynamic microsimulation models. Modelling individual behaviour by a large number of covariates reduces the number of observations with identical characteristics. This challenges determination of the response structure. Data mining using conditional inference trees (CTREEs) is found to be a useful tool to quantify a discrete response variable conditional on multiple individual characteristics and is generally believed to provide better covariate interactions than traditional parametric discrete choice models, i.e. logit and probit models. Deriving transition probabilities from conditional inference trees is a core method used in the SMILE microsimulation model forecasting household demand for dwellings. The properties of CTREEs are investigated through an empirical application aiming to describe the household decision of moving from a number of covariates representing various demographic and dwelling characteristics. Using recursive binary partitioning, decision trees group individuals’ responses according to a selected number of conditioning covariates. Recursively splitting the population by characteristics results in smaller groups consisting of individuals with identical behaviour. Classification is induced by recognized statistical procedures evaluating heterogeneity and the number of observations within the group exposed to a potential split. If a split is statistically validated, binary partitioning results in two new tree nodes, each of which potentially can split further after the next evaluation. The recursion stops when indicated by the statistical test procedures. Nodes caused by the final split are called terminal nodes. The final tree is characterized by a minimum of variation between observations within a terminal node and maximum variation across terminal nodes. For each terminal node a transitional probability is calculated and used to describe the response of individuals with the same covariate structure as characterizing the given terminal node. That is, if a terminal node consists of single males aged 50 and above living in rental housing, individuals with such characteristics are assumed to behave identically with respect to moving when transitioning from one state to another. |
| Keywords: | conditional inference tree, CTREE, dynamic microsimulation, modelling transition probability |
| Date: | 2013–12 |
| URL: | http://d.repec.org/n?u=RePEc:dra:wpaper:201302&r=all |
| By: | Rommel, Jens; Sagebiel, Julian; Müller, Jakob R. |
| Abstract: | Consumers can choose from a wide range of electricity supply contracts, including green power options. Electricity produced from renewable energy involves information asymmetries. With a sample of more than 2,000 German electricity consumers, we tested the proposition of a “lemon market” for renewable energy in a discrete choice experiment. Specifically, we found that, compared to investor-owned firms, additional willingness-to-pay (WTP) for renewable energy is approximately double when offered by cooperatives or municipally-owned electricity utilities. Consumers who are experienced with switching suppliers have an additional WTP of one Eurocent per kilowatt hour for cooperatives and two Eurocents for public enterprises. The results demonstrate that organizational transformation in dynamically-changing electricity markets is not only driven by political initiatives but also by consumers’ choices on the market. Public policy may reduce information asymmetries by promoting government labeling of green energy products. |
| Keywords: | Cooperatives; Discrete Choice Experiment; Germany |
| JEL: | D12 L33 L94 |
| Date: | 2015 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:66195&r=all |
| By: | Merlo, Antonio (Rice University); Wolpin, Kenneth I. (Rice University) |
| Abstract: | In this paper, we study the relationship among schooling, youth employment and youth crime. The framework, a multinomial discrete choice vector autoregression, provides a comprehensive analysis of the dynamic interactions among a youth's schooling, work and crime decisions and arrest and incarceration outcomes. We allow for observable initial conditions, unobserved heterogeneity, measurement error and missing data. We use data from the NLSY97 on black male youths starting from age 14. The estimates indicate important roles both for heterogeneity in initial conditions and for stochastic events that arise during one's youth in determining outcomes as young adults. |
| Date: | 2015–07 |
| URL: | http://d.repec.org/n?u=RePEc:ecl:riceco:15-004&r=all |
| By: | Charles Raux (LET - Laboratoire d'économie des transports - CNRS - UL2 - Université Lumière - Lyon 2 - École Nationale des Travaux Publics de l'État [ENTPE]); Amandine Chevalier (LET - Laboratoire d'économie des transports - CNRS - UL2 - Université Lumière - Lyon 2 - École Nationale des Travaux Publics de l'État [ENTPE]); Emmanuel Bougna (LET - Laboratoire d'économie des transports - CNRS - UL2 - Université Lumière - Lyon 2 - École Nationale des Travaux Publics de l'État [ENTPE]); Denis Hilton (Université de Toulouse - Université de Toulouse) |
| Abstract: | The potential of psychological and fiscal incentives in motivating environmentally responsible behavior in a context of long distance leisure travel is explored thanks to a series of controlled experiments on 900 participants. Framing effects like information on CO2 emissions, injunctive and descriptive norms, in combination with fiscal incentives such as a carbon tax, a bonus-malus or a carbon trading scheme are tested. Providing CO2 information on emissions is highly effective and the injunctive norm reinforces this effect in the case of air and train. A quota scheme reinforces the injunctive norm effect in the case of these two modes. More strikingly, the amount of the financial sanction or reward has no effect on the probability of using the various travel modes, unlike the presence of the fiscal framing itself. These results reinforce the case for using psychologically framing effects, in association or not with fiscal instruments, in promoting effective pro-environmental behavior in transport choices. |
| Date: | 2015–01–11 |
| URL: | http://d.repec.org/n?u=RePEc:hal:journl:halshs-01158088&r=all |
| By: | Gopi Shah Goda; Matthew R. Levy; Colleen Flaherty Manchester; Aaron Sojourner; Joshua Tasoff |
| Abstract: | There is considerable variation in retirement savings within income, age, and educational categories. Using a broad sample of the U.S. population, we elicit time preference parameters from a quasi-hyperbolic discounting model, and perceptions of exponential growth. We find that present bias (PB), the tendency to value utility in the present over the future in a dynamically inconsistent way, and exponential-growth bias (EGB), the tendency to neglect compounding, are prevalent and distinct latent variables. PB, EGB, and the long-run discount factor are all highly significant in predicting retirement savings, even while controlling for measures of IQ and general financial literacy as well as a rich set of demographic controls. We find that lack of self-awareness of these biases has an additional independent negative impact on retirement savings. We assess potential threats to a causal interpretation of our results with a hypothetical choice experiment and several robustness exercises. Finally, we explore potential mechanisms for our findings. If the relationship we estimate is causal, our estimates suggest that eliminating PB and EGB would be associated with an increase in retirement savings of 12%, or as high as 70% using estimates that account for classical measurement error. |
| JEL: | H0 |
| Date: | 2015–08 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:21482&r=all |