Parametric Lorenz Curves: Models and Applications

Sarabia, José Marı́a

doi:10.1007/978-0-387-72796-7_9

Cited by 42 publications

(38 citation statements)

References 60 publications

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“…For parametric expressions of L F (p), we refer to Gastwirth (1971), Kakwani and Podder (1973), as well as to more recent works of Sarabia (2008), Sarabia et al (2010), and references therein. Hence, the Gini index is…”

Section: The Classical Gini Index Revisitedmentioning

confidence: 99%

From the Classical Gini Index of Income Inequality to a New Zenga-Type Relative Measure of Risk: A Modeller’s Perspective

Greselin

Zitikis

2018

Econometrics

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Abstract:The underlying idea behind the construction of indices of economic inequality is based on measuring deviations of various portions of low incomes from certain references or benchmarks, which could be point measures like the population mean or median, or curves like the hypotenuse of the right triangle into which every Lorenz curve falls. In this paper, we argue that, by appropriately choosing population-based references (called societal references) and distributions of personal positions (called gambles, which are random), we can meaningfully unify classical and contemporary indices of economic inequality, and various measures of risk. To illustrate the herein proposed approach, we put forward and explore a risk measure that takes into account the relativity of large risks with respect to small ones.

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Section: The Classical Gini Index Revisitedmentioning

confidence: 99%

From the Classical Gini Index of Income Inequality to a New Zenga-Type Relative Measure of Risk: A Modeller’s Perspective

Greselin

Zitikis

2018

Econometrics

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“…The theory is profound and the idea has central applications in quantifying the growth of an economy and income inequality. The literature covering the topic is rich (see for instance [21], [22], [23] or [24]). Financial applications also exist ( [25] and [26]).…”

Section: Lorenz Curve and Gini Indexmentioning

confidence: 99%

From Power Curves to Discriminative Power: Measuring Model Performance of LGD Models

Frontczak¹,

Jaeger²,

Schumacher³

2017

JMF

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Measuring model performance of rating systems is a major task for banks.The concept of discrimination, i.e. the discriminative power, is used in credit risk modeling to assess the quality of a risk model concerning the separation of extreme events. For PD models CAP (Cumulative Accuracy Profile) or ROC (Receiver Operating Characteristic) curves are used to build a quantity called Accuracy Ratio, which is used to measure the discriminative power. These ideas are well known and broadly used in practice. Although such a measure is also desirable for models of the loss given default (LGD models), it is not documented in the literature. In this note we close this gap. We develop a measure for the discriminative power of LGD models based on Lorenz curves. We study first properties and introduce some alternatives for its calculation from a practical point of view.

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“…74 We consider distribution-free methods. For parametric Lorenz curve comparisons, see Sarabia (2008).…”

Section: Ranking and Dominance: Implementationmentioning

confidence: 99%

Statistical Methods for Distributional Analysis

Cowell

Flachaire

2015

Handbook of Income Distribution

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Parametric Lorenz Curves: Models and Applications

Cited by 42 publications

References 60 publications

From the Classical Gini Index of Income Inequality to a New Zenga-Type Relative Measure of Risk: A Modeller’s Perspective

From the Classical Gini Index of Income Inequality to a New Zenga-Type Relative Measure of Risk: A Modeller’s Perspective

From Power Curves to Discriminative Power: Measuring Model Performance of LGD Models

Statistical Methods for Distributional Analysis

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