Publications des institutions partenaires

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Robust Lorenz Curves: A Semi-Parametric Approach

Lorenz curves and second-order dominance criteria are known to be sensitive to data contamination in the right tail of the distribution. We propose two ways of dealing with the problem: (1) Estimate Lorenz curves using parametric models for income distributions, and (2) Combine empirical estimation with a parametric (robust) estimation of the upper tail of the distribution using the...

Institution partenaire

Université de Genève

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English / 01/01/2001

Resistant Selection of the Smoothing Parameter for Smoothing Splines

Robust automatic selection techniques for the smoothing parameter of a smoothing spline are introduced. They are based on a robust predictive error criterion and can be viewed as robust versions of C p and cross-validation. They lead to smoothing splines which are stable and reliable in terms of mean squared error over a large spectrum of model distributions.

Institution partenaire

Université de Genève

Full Text

English / 01/01/2001

Robust Inference for Generalized Linear Models

By starting from a natural class of robust estimators for generalized linear models based on the notion of quasi-likelihood, we define robust deviances that can be used for stepwise model selection as in the classical framework. We derive the asymptotic distribution of tests based on robust deviances, and we investigate the stability of their asymptotic level under contamination. The...

Institution partenaire

Université de Genève

Full Text

English / 01/01/2001

Putting Robust Statistical Methods into Practice: Poverty Analysis in Tunisia

Poverty analysis often results in the computation of poverty indexes based on so-called poverty lines which can be region speci…c poverty lines. The poverty lines are made of two components, namely the amount of income to satisfy the food and the non food needs. For both components, one needs to estimate quantities such as local prices or the consummers' average basket, and this...

Institution partenaire

Université de Genève

Full Text

English / 01/01/2001

Distributional Dominance with Dirty Data

Distributional dominance criteria are commonly applied to draw welfare inferences about comparisons, but conclusions drawn from empirical implementations of dominance criteria may be inßuenced by data contamination. We examine a non-parametric approach to reÞning Lorenz-type comparisons and apply the technique to two important examples from the LIS data-base.

Institution partenaire

Université de Genève

Full Text

English / 01/01/2001

Term Structure Models in Multistage Stochastic Programming: Estimation and Approximation

This paper investigates some common interest rate models for scenario generation in financial applications of stochastic optimization. We discuss conditions for the underlying distributions of state variables which preserve convexity of value functions in a multistage stochastic program. One- and multi-factor term structure models are estimated based on historical data for the Swiss...

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English / 01/12/2000

Robust Portfolio Selection

Institution partenaire

Université de Genève

Full Text

English / 01/01/2000

A General Robust Approach to the Analysis of Income Distribution, Inequality and Poverty

Income distribution embeds a large field of research subjects in economics. It is important to study how incomes are distributed among the members of a population in order for example to determine tax policies for redistribution to decrease inequality, or to implement social policies to reduce poverty. The available data come mostly from surveys (and not censuses as it is often...

Institution partenaire

Université de Genève

Full Text

English / 01/01/2000

Robust Logistic Regression for Binomial Responses

In this paper robustness properties of the maximum likelihood estimator (MLE) and several robust estimators for the logistic regression model when the responses are binary are analysed analytically by means of the Influence Function (IF) and empirically by means of simulations. It is found that the MLE and the classical Rao's score test can be misleading in the presence of model...

Institution partenaire

Université de Genève

Full Text

English / 01/01/2000

Robust Income Estimation with Missing Data

With income distributions it is common to encounter the problem of missing data. When a parametric model is fitted to the data, the problem can be overcome by specifying the marginal distribution of the observed data. With classical methods of estimation such as the maximum likelihood (ML) an estimator of the parameters can be obtained in a straightforward manner. Unfortunately, it...

Institution partenaire

Université de Genève

Full Text

English / 01/01/2000

Distributional Analysis: a Robust Approach

Distributional dominance criteria are commonly applied to draw welfare inferences about comparisons, but conclusions drawn from empirical implementations of dominance criteria may be influenced by data contamination. We show the conditions under which this may occur and propose empirical methods to work round the proble using both non-parametric and parametric approaches.

Institution partenaire

Université de Genève

Full Text

English / 01/01/2000

Test problems in stochastic multistage programming

This paper provides a set of stochastic multistage programs where the evolvement of uncertain factors is given by stochastic processes. We treat a practical problem statement within the field of managing fixed-income securities. Detailed information on the used parameter values in various interest rate models is given. Barycentric approximation is applied to obtain computational...

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English / 01/01/2000

Statistical Inference for Welfare under Complete and Incomplete Information

We show how a collection of results in the literature on the empirical estimation of welfare indicators from sample data can be unified. We also demonstrate how some of these ideas can be extended to empirically important cases where the data have been trimmed or censored.

Institution partenaire

Université de Genève

Full Text

English / 01/01/1999

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