Conditional Logit with one Binary Covariate: Link between the Static and Dynamic Cases

Disentangling state dependence from unobserved heterogeneity is a common issue in economics. It arises for instance when studying transitions between different states on the labor market. When the outcome variable is binary, one of the usual strategies consists in using a conditional logit model with an appropriate conditioning suitable for a dynamic framework. Although static conditional logit procedures are widely available, these procedures cannot be used directly in a dynamic framework. Indeed, it is inappropriate to use them with a lag dependent variable in the list of regressors. Moreover, reprogramming this kind of procedures in a dynamic framework can prove quite cumbersome because the likelihood can have a very high number of terms when the number of periods increases. Here, we consider the case of a conditional logit model with one binary regressor which can be either exogenous or the lagged dependent variable itself. We provide closed forms for the conditional likelihoods in both cases and show the link between them. These results show that in order to evaluate a conditional logit model with one lag of state dependence and no other covariate, it is possible to simply generate a two variable dataset and use standard procedures originally intended for models without state dependence. Moreover, the closed forms help reduce the computational burden even in the static case in which preimplemented procedures usually exist.conditional logit, state dependence, binary model, incidental parameter

Sobre AntropologED;a Cibernetica De La Arquitectura

The present work aims to propose the necessary bases for an anthropology of architecture from the cybernetic approach that is the science that studies the processes of communication and control present in technical biological and social devices For this purpose the cybernetic notion of self- organization is used at its different levels of complexity according to the movement of reality to be addressed in its relations with architecture that is physical biological and social reality self-organization self-eco- organization and self-eco-productio

Dynamic Estimation of Health Expenditure: A new approach for simulating individual expenditure

This study compares estimates of outpatient expenditure computed with different models. Our aim is to predict annual health expenditures. We use a French panel dataset over a six year period (2000-2006) for 7112 individuals. Our article is based on the estimations of five different models. The first model is a simple two part model estimated in cross section. The other models (models 2 to 5) are estimated with selection models (or generalized tobit models). Model 2 is a basic sample selection model in cross section. Model 3 is similar to model 2, but takes into account the panel dimension. It includes constant unobserved heterogeneity to deal with state dependency. Model 4 is a dynamic sample selection model (with lagged adjustement), while in model 5, we take into account the possible heteroskedasticity of residuals in the dynamic model. We find that all the models have the same properties in the cross section dimension (distribution, probability of health care use by gender and age, health expenditure by gender and age) but model 5 gives better results reflecting the temporal correlation with health expenditure. Indeed, the retransformation of predicted log transformed expenditures in homoscedastic models (models 1 to 4) generates very poor temporal correlation for " heavy consumers ", although the data show the contrary. Incorporation of heteroskedasticity gives better results in terms of temporal correlation.Health econometrics, expenditures, panel data, selection models

Fixed effects models, random effects models, mixed models or multilevel models: properties and implementation of modeling of the heterogeneity in presence of clustered data

This document presents the different ways to model heterogeneity in case of clustering, such pupils achievement in classroom or schools. In the linear framework, it essentially discusses the pertinence of fixed or random effects assumptions depending upon the goal pursued and the empirical evidence displayed by data. Statistical assumptions of the different models are introduced and successively discussed, as well as the properties of the estimators that are derived. For each model, SAS code is provided. Hausman tests, and their use to choose models, are explained. Beyond the linear framework, binary models are presented in the last chapter.fixed effect, random effect, Hausman test, multilevel model, mixed model

To Weight or not to Weight? The Eternal Question of Econometricians facing Survey Data

A recurrent problem in economic studies based on survey data is to determine whether survey weights should be used or not. We show that weighted estimators are more robust than unweighted ones, but less accurate when unweighted estimators are consistent. In some circumstances, a compatibility test between the assumptions underlying the selection mechanism (i.e., the survey design and nonresponse) and the econometric model at hand can be implemented, by comparing these two estimators. Finally, we present some methods to compute the accuracy of weighted estimators.survey weights, sample selection, inverse probability weighting, Hausman test

Empirical Process Results for Exchangeable Arrays

Exchangeable arrays are natural tools to model common forms of dependence between units of a sample. Jointly exchangeable arrays are well suited to dyadic data, where observed random variables are indexed by two units from the same population. Examples include trade flows between countries or relationships in a network. Separately exchangeable arrays are well suited to multiway clustering, where units sharing the same cluster (e.g. geographical areas or sectors of activity when considering individual wages) may be dependent in an unrestricted way. We prove uniform laws of large numbers and central limit theorems for such exchangeable arrays. We obtain these results under the same moment restrictions and conditions on the class of functions as those typically assumed with i.i.d. data. We also show the convergence of bootstrap processes adapted to such arrays.Comment: main paper until page 23, then supplement. The paper supersedes our previous paper "Asymptotic results under multiway clustering

Le Grand Paris, le joker de l'économie française

Cet article est rédigé à partir d’une note préparée pour la mission de configuration du Grand Paris. Il vise, à deux mois de sa mise en place, à évaluer les enjeux et les dynamiques, en termes de « macroéconomie locale » de la mise en place du Grand Paris. Sont examinés successivement le poids de son économie en France et dans la région Île-de-France, le fait que,contrairement à sa région, le Grand Paris se conforme au modèle de dynamique métropolitaine qui s’est développé depuis 15 ans dans le pays (et dans les autres pays industriels), en rupture avec ce que l’on observait dans les années antérieures. Il rend compte également du fait qu’à cette concentration métropolitaine, à l’échelle du pays, vient s’ajouter une concentration urbaine au sein des grandes aires urbaines, avec, dans le cas du Grand Paris, un retournement des dynamiques, favorables hier à la « deuxième couronne » de la région et aujourd’hui à son cœur « grand parisien » et particulièrement au centre, dans Paris et ses communes limitrophes. On examine, enfin, l’évolution actuelle du marché de l’emploi de ce territoire, son intégration croissante avec le reste de la région et la transformation d’un modèle radial en un nouveau modèle, de plus en plus concentrique