The techniques of simple random sampling are seldom appropriate in the empirical analysis of income distributions. Various types of weighting schemes are usually required either from the point of view of welfare-economic considerations (the mapping of household/family distributions into...

Standardmethoden zur Schätzung von Disparitätsmaßen aus klassierten Daten basieren entweder auf der Bestimmung von Schranken, die den wahren Wert des jeweiligen Disparitätsmaßes einschließen (nichtparametrischer Ansatz) oder aber auf Annahmen bezüglich der den Daten zugrunde liegenden...

In this research are analyzed, from the perspective of the diseconomies of agglomeration, the effects of environmental pollution in related diseases in the Metropolitan Zone of the Valley of Mexico (ZMVM). Spatial econometrics is used to verify the increasing effects of air pollution on the...

Economists use various metrics for measuring income inequality. Here, the most commonly used measures—the Lorenz curve, the Gini coefficient, decile ratios, the Palma ratio, and the Theil index—are discussed in relation to their benefits and limitations. Equally important is the choice of...

This work studies trends in income distributions and inequality in the European Union using data from the European Union Statistics on Income and Living Conditions. We model the income distribution for each country under a Dagum distribution assumption and using maximum likelihood techniques. We...

Although different approaches and methods have been used to measure inequality aversion, there remains no consensus about its drivers at the individual level. We conducted an experiment on a sample of more than 1800 first-year undergraduate economics and business students in Uruguay to...

We introduce a new jackknife variance estimator for panel-data regressions. Our variance estimator can be motivated as the conventional leave-one-out jackknife variance estimator on a transformed space of the regressors and residuals using orthonormal trigonometric basis functions. We prove the...

A popular approach to perform inference on a target parameter in the presence of nuisance parameters is to construct estimating equations that are orthogonal to the nuisance parameters, in the sense that their expected first derivative is zero. Such first-order orthogonalization may, however,...

This paper explores a semiparametric version of a time-varying regression, where a subset of the regressors have a fixed coefficient and the rest a time-varying one. We provide an estimation method and establish associated theoretical properties of the estimates and standard errors in extended...