182 research outputs found
Eat AND Study but Wii OR Ski! Differentiating Between ‘Basic’ and ‘Non-basic’ Dimensions in a Multidimensional Index
No full textMeasuring and monitoring multidimensional wellbeing have become central issues in international policy debates in recent years. Interpreting heterogeneity in achievement levels across dimensions in terms of individual freedom of choice, and arguing that the degree of substitutability should not only depend on this variation, but also on the typology of dimensions, we propose a Generalized Multidimensional Synthetic index that introduces several layers of flexibility in the aggregation methodology. We classify dimensions into different groups, for example basic and non-basic, and allow for varying substitutability rates within as well as between groups. After examining the theoretical properties of the new index, we perform simulation experiments which highlight the salient features of our index compared to other frequently used indices
Model-based multidimensional poverty indices: theoretical construction and statistical properties
No full textThis thesis is concerned with the operationalisation of the "Capability Approach" (CA) in order to obtain quantitative measures of Human Development in various domains. It consists of three essays that quantify well-being, poverty and female empowerment in the "capability" space. The first essay applies the methodology developed by Krishnakumar (Journal of Human Development 2007) for operationalizing the CA using structural equation latent variable modelling, for estimating and analyzing basic capabilities in the knowledge and living conditions domains for Bolivian children. The second essay extends this model-based approach for measuring deprivation in the functioning-capability space, in the presence of multiple-dimensions and multiple-indicators. Finally, the third essay proposes a structural model for measuring female empowerment in a capability perspective, using the intra-household gender dynamics literature as the theoretical support. These three key contributions show the importance of going beyond descriptive measures to adequately target the most vulnerable groups
An Application of an Error Correction Model with Higher Order Cointegrated Variables to the Demand for Money in Switzerland
No full textThis paper applies the maximum likelihood technique to estimate the parameters of a money demand equation for Switzerland in which there are variable integrated of different orders and in particular of order greater than 1. The estimation method developed by the authors has been explained in detail in Krishnakumar and Gueye (1998) which also derives the limiting distributions of the resulting estimators. The procedure was implemented in MATLAB for estimating our empirical model.Unit Roots ; Cointegration ; Money ; Models
Time Invariant Variables and Panel Data Models : A Generalised Frisch-Vaugh Theorem and its Implications
No full textMundlak (1978) showed that when individual effects are correlated with the explanatory variables in an error component (EC) model, the GLS estimator is given by the within. In this paper we bring out some additional interesting properties of the within estimator in Mundlak’s model and go on to show that the within estimator remains valid in an extended EC model with time invariant variables and correlated specific effects. Adding an auxiliary regression to take account of possible correlation between the explanatory variables and the individual effects, we find that not only the elegant results obtained by Mundlak but also the above mentioned special features carry over to the extended case with interesting interpretations. We obtain these results using a generalised version of the Frisch-Waugh theorem, stated and proved in the paper. Finally, for both the EC models with and without time invariant variables we have shown that the estimates of the coefficients of the auxiliary variables can also be arrived at by following a two-step procedure.panel data, error components, correlated effects, within estimator.
Econometric modeling of informal employment in Latin-American countries
No full textL'emploi informel est une caractéristique omniprésente des marchés du travail Latino-Américains. Même si sa présence peut avoir des implications positives liées à l'entrepreneuriat, il est fondamentalement lié à de mauvaises conditions de travail, à l'évasion fiscale et au déséquilibre des marchés du travail. L'informalité est devenue un sujet de recherche important car plusieurs problèmes statistiques caractérisent les données disponibles, ainsi, cette Thèse présente trois articles traitant de sujets micro et macro-économétriques fondamentaux présents dans la littérature. Le premier s'occupe de la spécification d'un modèle micro-économétrique qui permet la classification probabiliste des travailleurs informels en ‘exclus' et ‘non exclus' (ou ‘volontaires' ou pas). Le deuxième, propose une méthodologie d'identification et correction des erreurs de mesure implicites dans l'indicateur du travail informel publié para le BIT. Le troisième estime une relation macro-économétrique micro-fondée entre l'informalité et la libéralisation commerciale, en traitant les problèmes d'inférence découlant du modèle empirique par une méthode semi-paramétrique robuste
Contributions to the theory and practice of latent variable modelling and causal inference
No full textUnobservable concepts are frequent in economics: utility, expectations, beliefs, competitiveness of firms, productivity of a worker can all be viewed as latent variables. Although not directly observable, each of these concepts can be indirectly measured by some related observable indicators. The first two chapters of this thesis provide a deeper understanding of the tools available to empirical researchers to measure latent variables. In the first chapter, we use factor analysis to measure decent work which was originally conceptualized by the International Labour Organization. In the second chapter, we investigate bias correction methods when factor scores are used as regressors. Focusing on nonlinear regression including covariates, we propose two bias-corrected estimators. Finally, in the third chapter, we show the detrimental effect of small amounts of contaminated data on the estimated causal impact of treatment and propose robust version of standard causal inference estimators
Discrete choice pseudo panel data models
No full textLes données de panel sont aujourd'hui d'une importance capitale dans l'analyse du comportement des micro-unités. Or dans beaucoup de pays, ces données n'existent pas encore. A la place, les chercheurs peuvent utiliser des enquêtes répétées. Dans un pareil cas, vu l'impossibilité de suivre la même unité dans le temps, on passe au niveau cohorte tout en introduisant l'hétérogénéité individuelle dans le modèle. Des cohortes construites selon des critères d'homogénéité sont les « individus » du nouveau panel. Cette approche est dite approche des données pseudo panel. Ainsi cette thèse comporte trois chapitres. Le premier traite de l'estimation de modèles à choix binaires avec des effets individuels quand on a des données pseudo-panels. Le deuxième propose une approximation de la distribution théorique exacte obtenue dans le premier chapitre, par la distribution beta. Le troisième chapitre analyse l'impact de l'autonomie des femmes sur l'utilisation des soins de santé en Inde avec des données pseudo-panels
A study on how to continue and optimize project activities in pandemic times for NGOs
No full textThroughout this paper I aim to bring my readers along my practical and academic journey during my internship with child's rights-based NGO CRY. In a period of uncertainty and restrictions imposed by the onset of COVID-19, NGOs, in the field of social and sustainable change, such as CRY, are in need of a guide on how to best continue their activities and preserve their intended effects for the communities, I thus attempt at providing a theoretical answer to this inquiry through the concepts of adaptation, community resilience, vulnerability reduction assessment and a number of other important aspects to consider in these circumstances. This research becomes not only relevant in the present, for NGOs such as CRY, yet also in the future due to the likely perpetuation of pandemics like COVID-19
Estimation of simultaneous-equations models with panel data and censored endogenous variables
No full textIn this research we develop an estimation methodology for a system of simultaneous equations where the endogenous variables are subject to censorship and where the data follows a panel structure. The likelihood function of such a model presents several complications, so that traditional optimization procedures cannot be employed. We propose the application of a simulation-based estimator that mimics the Expectation-Maximization (EM) algorithm and also inherits its likelihood-maximizing properties. Simulation exercises for both random-effects and fixed-effect models verify that this estimation methodology performs remarkably well in comparison to traditional methods, without a high cost in terms of loss of efficiency. The same idea is then extended to other types of data limitations and to a dynamic model
Parametric and nonparametric analysis of simultaneous equation models with latent variables: theory and applications
No full textCette thèse de doctorat est composée de trois chapitres. La principale contribution consiste à présenter deux cadres théoriques, paramétrique et non-paramétrique, pour faire des comparaisons et évaluations des concepts théoriques non-observables utilisés dans différents contextes tels que le bien-être, le développement, la santé et l'inégalité entre autres.Le premier chapitre présente le modèle paramétrique avec une méthode d'estimation et un exemple numérique avec des simulations. Le deuxième chapitre est une application, sur des données françaises, de ce type de modèles dans le contexte de la santé, en opérationnalisant l'approche des capabilités d'Amartya Sen. Finalement, le troisième chapitre consiste en une alternative non-paramétrique accompagnée d'une application sur des données indiennes dans le contexte du bien-être, pour tester la dominance stochastique multivariée de premier ordre
- …
