nep-dcm New Economics Papers
on Discrete Choice Models
Issue of 2007‒05‒12
seven papers chosen by
Philip Yu
Hong Kong University

  1. Estimation of aggregated modal split mode By Patrick Bonnel
  2. Physical Dating Violence Among College Students in Chile By Jocelyn A. Lehrer; Vivian L. Lehrer; Evelyn L. Lehrer; Zhenxiang Zhao
  3. College Education and Wages in the U.K.: Estimating Conditional Average Structural Functions in Nonadditive Models with Binary Endogenous Variables By Tobias J. Klein
  4. The Role of Association Agreements within European Union Enlargement to Central and Eastern European Countries By Christophe Rault; Robert Sova; Ana Maria Sova
  5. Household Choices of Child Labor and Schooling: A Simple Model with Application to Brazil By Diana Kruger; Rodrigo R. Soares; Matias Berthelon
  6. Awareness and the Demand of Safe Drinking Water Practices By Eatzaz Ahmed; Abdul Sattar
  7. Are two-part tariffs efficient when consumers plan ahead?: An empirical study By Laura Fernàndez-Villadangos

  1. By: Patrick Bonnel (LET - Laboratoire d'économie des transports - [CNRS : UMR5593] - [Université Lumière - Lyon II] - [Ecole Nationale des Travaux Publics de l'Etat])
    Abstract: In spite of the fact that disaggregate modelling has undergone considerable development in the last twenty years, many studies are still based on aggregate modelling. In France, for example, aggregate models are still in much more common use than disaggregate models, even for modal split. The estimation of aggregate models is still therefore an important issue.<br /><br />In France, for most studies it is possible to use behavioural data from household surveys, which are conducted every ten years in most French conurbations. These household surveys provide data on the socioeconomic characteristics both of individuals and the households to which they belong and data on modal choice for all the trips made the day before the survey. The sampling rate is generally of 1% of the population, which gives about 50,000 trips for a conurbation of 1 million inhabitants. However, matrices that contain several hundred rows and columns are frequently used. We therefore have to construct several modal matrices that contain more than 10,000 cells (in the case of a small matrix with only 100 rows) with less than 50,000 trips (to take the above example). Obviously, the matrices will contain a large number of empty cells and the precision of almost all the cells will be very low. It is consequently not possible to estimate the model at this level of zoning.<br /><br />The solution which is generally chosen is to aggregate zones. This must comply with two contradictory objectives:<br />- the number of zones must be as small as possible in order to increase the number of surveyed trips that can be used during estimation and hence the accuracy of the O-D matrices for trips conducted on each mode;<br />- the zones must be as small as possible in order to produce accurate data for the explanatory variables such as the generalized cost for each of the transport modes considered. When the size of the zone increases, it is more difficult to evaluate the access and regress time for public transport and there are several alternative routes with different travel times between each origin zone and each destination. Therefore more uncertainty is associated with the generalized cost that represents the quality of service available between the two zones. The generally adopted solution is to produce a weighted average of all the generalized costs computed from the most disaggregated matrix. However, there is no guarantee that this weighted mean will be accurate for the origin-destination pair in question.<br /><br />When the best compromise has been made, some of the matrix cells are generally empty or suffer from an insufficient level of precision. To deal with this problem we generally keep only the cells for which the data is sufficiently precise by selecting those cells in which the number of surveyed trips exceeds a certain threshold. However, this process involves rejecting part of the data which cannot be used for estimation purposes. When a fairly large number of zones is used, the origin destination pairs which are selected for the estimation of the model mainly involve trips that are performed in the centre of the conurbation or radial trips between the centre and the suburbs. These origin-destination pairs are also those for which public transport's share is generally the highest. The result is to reduce the variance of the data and therefore the quality of the estimation.<br /><br />To cope with this problem we propose a different aggregation process which makes it possible to retain all the trips and use a more disaggregate zoning system. The principle of the method is very simple. We shall apply the method to the model most commonly used for modal split, which is the logit model. When there are only two modes of transport, the share of each mode is obtained directly from the difference in the utility between the two modes with the logit function. We can therefore aggregate the origin-destination pairs for which the difference between the utility of the two modes is very small in order to obtain enough surveyed trips to ensure sufficient data accuracy. This process is justified by the fact that generally the data used to calculate the utility of each mode is as accurate or even more accurate at a more disaggregate level of zoning. The problem with this method is that the utility function coefficients have to be estimated at the same time as the logit model. An iterative process is therefore necessary. The steps of the method are summarised below:<br />- selection of initialization values for the utility function coefficients for the two transport modes in order to intitialize the iteration process. These values can, for example, be obtained from a previous study or calibration performed according to the classical method described in Section 1.2;<br />- the utility for each mode is computed on the basis of the above coefficients, followed by the difference in the utility for each O-D pair in the smallest scale zoning system for which explanatory variables with an adequate level of accuracy are available (therefore with very limited zonal aggregation or even none at all);<br />- the O-D pairs are classified on the basis of increasing utility difference;<br />- the O-D pairs are then aggregated. This is done on the basis of closeness of utility difference. The method involves taking the O-D link with the smallest utility difference then combining it with the next O-D pair (in order of increasing utility difference). This process is continued until the number of surveyed trips in the grouping is greater than a threshold value that is decided on the basis of the level of accuracy that is required for trip flow estimation. When this threshold is reached the construction of the second grouping is commenced, and so on and so forth until each O-D pair has been assigned to a group;<br />- for each new class of O-D pairs it is necessary to compute the values of the explanatory variables which make up the utility functions for each class. This value is obtained on the basis of the weighted average of the values for each O-D pair in the class;<br />- a new estimation of the utility function coefficients.<br /><br />This process is repeated until the values of the utility function coefficients converge. We have tested this method for the Lyon conurbation with data from the most recent household travel survey conducted in 1995/96. We have conducted a variety of tests in order to identify the best application of the method and to test the stability of the results. It would seem that this method always produces better results than the more traditional method that involves zoning aggregation. The paper presents both the methodology and the results obtained from different aggregation methods. In particular, we analyse how the choice of zoning system affects the results of the estimation.
    Keywords: Aggregate modelling ; choice modal ; Zoning system ; Urban mobility ; Conurbation (Lyon, France) ; Estimation method
    Date: 2007–04–30
  2. By: Jocelyn A. Lehrer (University of California, San Francisco); Vivian L. Lehrer (Urban Justice Center); Evelyn L. Lehrer (University of Illinois at Chicago and IZA); Zhenxiang Zhao (University of Illinois at Chicago)
    Abstract: Dating violence is a serious public health concern both per se and because victimization in the young adult years can be a precursor to more severe incidents of domestic violence later, in the context of cohabitation or marriage. To date, no quantitative studies have examined dating violence among college students in Chile. To address this gap, a survey on this topic was administered to students at a major public university. The present analyses focused on the female sample (n=441). Generalized ordered logit models were used to assess factors associated with physical victimization since age 14, considering three categories: no victimization, victimization with no injury, and victimization with injury. Approximately 21% of subjects reported one or more incidents of physical dating violence not involving injury since age 14, and another 5.0% reported at least one incident resulting in injury during this time period. The corresponding figures for the past 12 months were 12.9% and 2.4%, respectively. Childhood sexual abuse and witnessing domestic violence as a child were associated with substantially elevated odds of physical victimization later in life. Low parental education was also associated with higher vulnerability, in part because of its linkage with childhood experiences with aggression. Protective factors included maternal employment and religious service participation at age 14, residence in the parental home during the college years, and never having had sexual intercourse. The findings suggest that it would be desirable to develop public health initiatives to prevent and respond to this form of violence among Chilean college students.
    Keywords: domestic violence, dating violence, physical victimization
    JEL: J4 J16 I12 I18
    Date: 2007–04
  3. By: Tobias J. Klein (University of Mannheim and IZA)
    Abstract: We propose and implement an estimator for identifiable features of correlated random coefficient models with binary endogenous variables and nonadditive errors in the outcome equation. It is suitable, e.g., for estimation of the average returns to college education when they are heterogeneous across individuals and correlated with the schooling choice. The estimated features are of central interest to economists and are directly linked to the marginal and average treatment effect in policy evaluation. The advantage of the approach that is taken in this paper is that it allows for non-trivial selection patterns. Identification relies on assumptions weaker than typical functional form and exclusion restrictions used in the context of classical instrumental variables analysis. In the empirical application, we relate wage levels, wage gains from a college degree and selection into college to unobserved ability. Our results yield a deepened understanding of individual heterogeneity which is relevant for the design of educational policy.
    Keywords: returns to college education, correlated random coefficient model, local instrumental variables, local linear regression
    JEL: C14 C31 J31
    Date: 2007–04
  4. By: Christophe Rault (LEO, University of Orleans and IZA); Robert Sova (CES, Sorbonne University and A.S.E); Ana Maria Sova (CES, Sorbonne University and A.S.E)
    Abstract: The main goal of regionalization is the creation of free trade areas and the guarantee for countries to accede to a widened market. Many studies dealing with the effects of regional free trade agreements on trade flows already exist in the economic literature and the explosion in the number of regional agreements among countries has recently stressed the key role of regionalization. However, the effects of agreements on trade were sometimes contradictory in those studies. These diverging results can be explained by the potential endogeneity bias of the agreement variable. Our research in this paper aims at reassessing the genuine role of associations. For this matter, we particularly study the association of Central and Eastern European countries (CEEC) with European Union countries. Our econometric analysis based on qualitative choice models highlights in particular why European countries chose to conclude an association agreement with CEEC, and stresses the fact that European Union countries select endogenously the conclusion of association agreements. We are also particularly interested in modeling the effect of the association agreement on export performances between countries, and to quantify its impact. When considering annual data for 4 CEEC and 19 OECD countries (1990-2004), we find a 0.17 positive impact of the association agreement on bilateral exports.
    Keywords: regionalization, European integration, qualitative choice models, gravity model
    JEL: E61 F13 F15 C25
    Date: 2007–04
  5. By: Diana Kruger (Pontificia Universidad Católica de Valparaíso); Rodrigo R. Soares (University of Maryland, Catholic University of Rio de Janeiro, NBER and IZA); Matias Berthelon (Pontificia Universidad Católica de Valparaíso)
    Abstract: This paper develops and estimates a simple structural model of household decisions regarding child labor and schooling. We argue that part of the conflicting results from the previous literature - related to the effect of improvements in economic conditions on child labor - derives from the different income and substitution effects implicit in different types of income variation. Our model leads to an empirical specification where income and substitution effects can be clearly identified. We apply our model to Brazil and use agricultural shocks to local economic activity (coffee and overall agricultural production) to distinguish between the effects of increases in household income and increases in the opportunity cost of children’s time. The results show that higher parental wages and household wealth are associated with lower child labor and higher school attendance. Nevertheless, conditional on family income and socioeconomic status, exogenous temporary increases in local economic activity are associated with increased opportunity cost of children’s time and, therefore, higher child labor and lower schooling. The results reconcile economic theory with seemingly contradictory evidence from the previous empirical literature.
    Keywords: child labor, schooling, generalized ordered logit, Brazil
    JEL: D13 J22
    Date: 2007–05
  6. By: Eatzaz Ahmed (Quaid-i-Azam University, Islamabad); Abdul Sattar (Ministry of Finance, Islamabad)
    Abstract: The demand for environmental goods is often low in developing countries. The major causes are awareness regarding the contamination of water and poverty, but less attention has been paid to the former reason. We use a household survey from Hyderabad city and estimate the contribution of awareness and income on households’ water purification behaviour. The study finds out that measures of awareness such as different level of schooling of decision-makers and household heads and their exposure to mass media have statistically significant effects on home purification methods for drinking water, while other members of households can effect this behaviour only when they get higher levels of schooling.
    Keywords: Demand, Awareness, Safe Drinking Water, Logit Model, Probit Model
    JEL: D12 D13 D31 Q21 Q25 Q51 R21
    Date: 2007
  7. By: Laura Fernàndez-Villadangos (Grup de Recerca en Polítiques Públiques i Regulació Económiques (GPRE), Institut de Recerca d'Economia Aplicada (IREA), Departament de Política Econòmica i EEM, Universitat de Barcelona)
    Abstract: During the last two decades there has been an increase in using dynamic tariffs for billing household electricity consumption. This has questioned the suitability of traditional pricing schemes, such as two-part tariffs, since they contribute to create marked peak and offpeak demands. The aim of this paper is to assess if two-part tariffs are an efficient pricing scheme using Spanish household electricity microdata. An ordered probit model with instrumental variables on the determinants of power level choice and non-paramentric spline regressions on the electricity price distribution will allow us to distinguish between the tariff structure choice and the simultaneous demand decisions. We conclude that electricity consumption and dwellings’ and individuals’ characteristics are key determinants of the fixed charge paid by Spanish households Finally, the results point to the inefficiency of the two-part tariff as those consumers who consume more electricity pay a lower price than the others.
    Keywords: Regulation, electricity, consumer behavior: empirical analysis.
    JEL: L94 Q41 D12
    Date: 2006–10

This nep-dcm issue is ©2007 by Philip Yu. 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.