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Nonparametric tests for positive quadrant dependence

Contributors

Denuit, Michel; Scaillet, Olivier

Collection

  • Cahiers de recherche; 2002.05

Publication date

2002

Abstract

We consider distributional free inference to test for positive quadrant dependence, i.e. for the probability that two variables are simultaneously small (or large) being at least as great as it would be were they dependent. Tests for its generalisation in higher dimensions, namely positive orthant dependence, are also analysed. We propose two types of testing procedures. The first procedure is based on the specification of the dependence concepts in terms of distribution functions, while the second procedure exploits the copula representation. For each specification a distance test and an intersection-union test for inequality constraints are developed depending on the definition of null and alternative hypotheses. An empirical illustration is given for US and Danish insurance claim data. Practical implications for the design of reinsurance treaties are also discussed.

UNIGE affiliation entities

Citation (ISO format)

DENUIT, Michel, SCAILLET, Olivier. Nonparametric tests for positive quadrant dependence. 2002

Main files (1)

Report

Identifiers

  • PID : unige:5817
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2249downloads

Technical informations

Creation

15/04/2010 12:20:24

First validation

15/04/2010 12:20:24

Update

14/03/2023 15:26:42

Status update

14/03/2023 15:26:42

Last indexation

29/10/2024 14:23:55
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