Bivariate income distributions with lognormal conditionals

Sarabia, José Marı́a; Castillo, Enrique; Pascual, Marta; Sarabia, María

doi:10.1007/s10888-006-9044-6

Cited by 13 publications

(8 citation statements)

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“…The classical multivariate lognormal distribution is defined in terms of a monotone marginal transformation of the classical multivariate normal distribution. Other possible alternatives have been proposed by Sarabia et al [41] based on conditional specification. In both previous models, we can obtain a bivariate Lorenz surface.…”

Section: Bivariate Sl Lorenz Surfaces With Lognormal Marginalsmentioning

confidence: 99%

Lorenz Surfaces Based on the Sarmanov–Lee Distribution with Applications to Multidimensional Inequality in Well-Being

Sarabia

Jordá

2020

Mathematics

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The purpose of this paper is to derive analytic expressions for the multivariate Lorenz surface for a relevant type of models based on the class of distributions with given marginals described by Sarmanov and Lee. The expression of the bivariate Lorenz surface can be conveniently interpreted as the convex linear combination of products of classical and concentrated univariate Lorenz curves. Thus, the generalized Gini index associated with this surface is expressed as a function of marginal Gini indices and concentration indices. This measure is additively decomposable in two factors, corresponding to inequality within and between variables. We present different parametric models using several marginal distributions including the classical Beta, the GB1, the Gamma, the lognormal distributions and others. We illustrate the use of these models to measure multidimensional inequality using data on two dimensions of well-being, wealth and health, in five developing countries.

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Section: Bivariate Sl Lorenz Surfaces With Lognormal Marginalsmentioning

confidence: 99%

Lorenz Surfaces Based on the Sarmanov–Lee Distribution with Applications to Multidimensional Inequality in Well-Being

Sarabia

Jordá

2020

Mathematics

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“…Arnold et al (2000), with reference to Normal Conditionals, have inquired multimodal density functions. Sarabia et al (2007) proposed multimodal probability distributions, which have Log-Skew-Normal and Lognormal Conditionals.…”

Section: Relationship Between Consecutive Headwaysmentioning

confidence: 99%

Transit vehicles’ headway distribution and service irregularity

Bellei

Gkoumas

2010

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Pairing, or bunching, of vehicles on a public transportation line influences\ud the adaptive choice at stops due to the random headways and waiting times it determines.\ud In order to ensure consistency with the characteristics of service perturbations,\ud as represented by a transit operation model, it is important to identify the headway\ud distributions representing service perturbations. A stochastic simulation model is developed\ud for a one-way transit line, which accounts for several service characteristics\ud (dwell time at stops, capacity constraint and arrivals during the dwell time). Samples\ud of headways at the main stops are utilized to build histograms of the headway’s frequencies\ud by their length, which allow to identify the functional forms and parameters\ud of the headway distributions. For these stops, density plots of consecutive headways\ud are also produced. Sensitivity analysis is carried out to identify the effect of key parameters\ud (dispatching headway, maximum load and running time)

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“…Some applications have been provided by Sarabia et al (2004) and Sarabia et al (2005). The class of bivariate distributions with lognormal conditionals has been fully characterized by Sarabia et al (2007). Now, we need some notation.…”

Section: Conditional Specification Modelsmentioning

confidence: 99%