Estimation des modèles probit polytomiques : un survol des techniques

Parce qu’il admet des structures très générales d’interdépendance entre les modalités, le probit polytomique (MNP) fournit une des formes les plus intéressantes pour modéliser les choix discrets qui découlent d’une maximisation d’utilité aléatoire. L’obstacle majeur et bien connu dans l’estimation de ce type de modèle tient à la complexité que prennent les calculs lorsque le nombre de modalités considérées est élevé. Cette situation est due essentiellement à la présence d’intégrales normales multidimensionnelles qui définissent les probabilités de sélection. Au cours des deux dernières décennies, de nombreux efforts ont été effectués visant à produire des méthodes qui permettent de contourner les difficultés de calcul liées à l’estimation des modèles probit polytomiques. L’objectif de ce texte consiste à produire un survol critique des principales méthodes mises de l’avant jusqu’à maintenant pour rendre opérationnel le cadre MNP. Nous espérons qu’il éclairera les praticiens de ces modèles quant au choix de technique d’estimation à favoriser au cours des prochaines années.The Multinomial Probit (MNP) model provides the most general framework to allow for interdependent alternatives in discrete choice analysis. The primary impediment to this methodology is related to the dimensionality of the response probabilities which are multifold normal integrals of about the size of the choice set. During the last two decades, numerous researches have been devoted to develop practical methodologies to replace these hard to compute choice probabilities in the estimation process. The main objective of this paper is to survey the major and the most important of these techniques

Finding a closest point in a lattice of Voronoi's first kind

We show that for those lattices of Voronoi's first kind with known obtuse superbasis, a closest lattice point can be computed in $O(n^4)$ operations where $n$ is the dimension of the lattice. To achieve this a series of relevant lattice vectors that converges to a closest lattice point is found. We show that the series converges after at most $n$ terms. Each vector in the series can be efficiently computed in $O(n^3)$ operations using an algorithm to compute a minimum cut in an undirected flow network

EXTMOV: A Computer Spreadsheet Program For Analyzing Staffing Costs and Benefits

[Excerpt] EXTMOV is a LOTUS 1-2-3 spreadsheet program specially designed to assist those managing their human resources. The program allows you to construct a simulation of your workforce that can depict the dollar-valued implications of various selection, recruitment and turnover management strategies. The relationships in the computer program are based on the external employee movement utility model described in Boudreau and Berger\u27s Monograph, Decision- Theoretic Utility Analysis Applied to Employee Separations and Acquisitions (Boudreau & Berger, 1985). A case study illustrating how this program can be used to suppon managerial decisions about investments in recruitment, selection and turnover management is contained in another Center working paper #91-12 (Boudreau, 1991)

Neurobiological studies of risk assessment: A comparison of expected utility and mean-variance approaches

When modeling valuation under uncertainty, economists generally prefer expected utility because it has an axiomatic foundation, meaning that the resulting choices will satisfy a number of rationality requirements. In expected utility theory, values are computed by multiplying probabilities of each possible state of nature by the payoff in that state and summing the results. The drawback of this approach is that all state probabilities need to be dealt with separately, which becomes extremely cumbersome when it comes to learning. Finance academics and professionals, however, prefer to value risky prospects in terms of a trade-off between expected reward and risk, where the latter is usually measured in terms of reward variance. This mean-variance approach is fast and simple and greatly facilitates learning, but it impedes assigning values to new gambles on the basis of those of known ones. To date, it is unclear whether the human brain computes values in accordance with expected utility theory or with mean-variance analysis. In this article, we discuss the theoretical and empirical arguments that favor one or the other theory. We also propose a new experimental paradigm that could determine whether the human brain follows the expected utility or the mean-variance approach. Behavioral results of implementation of the paradigm are discussed

Using firm demographic microsimulation to evaluate land use and transport scenario evaluation - model calibration

Existing integrated land use transport interaction models simulate the level of employment in (aggregated) zones and lack the individual firm as a decision making unit. This research tries to improve the behavioural foundation of these models by applying a firm demographic modelling approach that first of all accounts for the individual firm as a decision making unit and secondly represents the urban system with high spatial detail. A firm demographic approach models transitions in the state of individual firms by simulating transitions and events such as the relocation decision, growth or shrinkage of firms or the death of a firm. Important advantage of such a decomposed approach is that it offers the opportunity to account for accessibility in each event in the desired way. The firm demographic model is linked to an urban transport model in order to obtain a dynamic simulation of mobility (and accessibility) developments. The paper describes the firm demographic model specifications as well as the interaction of the model with the urban transport model. The integrated simulation model can be used to analyse the effects of different spatial and transport planning scenarios on the location of economic activities and mobility.