Browsing by Subject "Discrete choice"

Now showing 1 - 4 of 4
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    Efficient Semiparametric Scoring Estimation of Sample Selection Models
    (Center for Economic Research, Department of Economics, University of Minnesota, 1990-02) Lee, Lung-Fei
    A semi parametric profile likelihood method is proposed for estimation of sample selection models. The method is a two step scoring semi parametric estimation procedure based on index formulation and kernel density estimation. Under some regularity conditions, the estimator is asymptotically normal. This method can be applied to estimation of general sample selection models with multiple regimes and sequential choice models with selectivity. For the binary choice sample selection model, the estimator is asymptotically efficiency in the sense that its asymptotic variance matrix attains the asymptotic bound of G. Chamberlain.
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    Equity Impacts of Transportation Improvements On Core and Peripheral Cities
    (Journal of Transport and Land Use, 2008) Leck, Eran; Bekhor, Shlomo; Gat, Daniel
    The aim of this paper is to assess the short-term impact of transportation improvements on the reduction of socioeconomic disparities between core and peripheral cities. Data used in the analysis was extracted from the 1995 Israel Census. The methodology applied in the study was to estimate discrete choice models in an attempt to identify key variables affecting commuting decisions. Policy simulations are employed to illustrate the effect of diminishing spatial friction on wage convergence between poor southern towns and affluent core cities. The empirical evidence suggests that transportation improvements, especially in the form of introducing new rail links in underserved cities, could significantly contribute to the alleviation of spatial wage disparities between core and peripheral cities.
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    Identification of Semiparametric Discrete Choice Models
    (Center for Economic Research, Department of Economics, University of Minnesota, 1989-09) Thompson, T. Scott
    The question of model identification is analyzed for the semiparametric random utility model of discrete choice. Attention is focused on settings where agents face a common choice between a set of J+l alternatives, but where actual choices are only partially observed. Necessary conditions are derived for the setting where the only data on actual choices consists of a binary indicator for one of the alternatives. Sufficient conditions are developed in this setting for a linear in parameters specification of indirect utility. It is found that relative to the parametric case, only a mild continuity restriction on the distribution of regressors is needed in the semiparametric model. Under these circumstances all of the choice probabilities are identified, even though actual choices are only partially observed. It is shown that estimators that rely only on the index structure of the model require substantially stronger prior restrictions on the parameters for identification when the number of alternatives is large. Finally, results on the model with partial observability of choices are used to analyze the special case of full observability.
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    The role of location in residential location choice models: a review of literature
    (Journal of Transport and Land Use, 2014) Schirmer, Patrick; van Eggermond, Michael A.B.; Axhausen, Kay
    Geospatial data available to researchers has increased tremendously over the last several decades, opening up opportunities to define residential location in multiple ways. This has led to a myriad of variables to define "location'' in residential location choice models. In this paper, we propose a common classification for location variables and categorize findings from a wide range of studies. We find similar preferences but different measurement methods and market segments for locations across different study regions. Recent studies consider the residential unit as choice alternative, making it possible to include a detailed description of the built environment. However, these studies are still limited in number and the inclusion of socioeconomic environment is more common. Transport land-use models can benefit from the inclusion of points of interest, such as schools, network distances, and the distance to previous locations. For the results of location choice models to be transferable to different disciplines, and avoid multi-collinearity, it is necessary to present different model specifications, including variables of interest in different disciplines.