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Coefficient of variation and Power Pen's parade computation

Kamdem, Jules Sadefo - HAL - 2011

Under the the assumption that income y is a power function of its rank among n individuals, we approximate the coefficient of variation and gini index as functions of the power degree of the Pen's parade. Reciprocally, for a given coefficient of variation or gini index, we propose the analytic...

Persistent link: https://www.econbiz.de/10009643220

Gini Index and Polynomial Pen's Parade

Kamdem, Jules Sadefo - HAL - 2011

In this paper, we propose a simple way to compute the Gini index when income y is a finite order k polynomial function of its rank among n individuals.

Persistent link: https://www.econbiz.de/10008923124

Dynamically consistent Choquet random walk and real investments

Kast, Robert; Lapied, André - HAL - 2010

In the real investments literature, the investigated cash flow is assumed to follow some known stochastic process (e.g. Brownian motion) and the criterion to decide between investments is the discounted utility of their cash flows. However, for most new investments the investor may be ambiguous...

Persistent link: https://www.econbiz.de/10008794725

Large sample properties of the matrix exponential spatial specification with an application to FDI

Debarsy, Nicolas; Jin, Fei; Lee, Lung-Fei - HAL - 2013

quasi-maximum likelihood estimator (QMLE) for the MESS is consistent under heteroskedasticity, a property not shared by the …,1), the QMLE can be consistent under unknown heteroskedasticity when the spatial weights matrices in the two MESS processes …

Persistent link: https://www.econbiz.de/10010935045

Large sample properties of the matrix exponential spatial specification with an application to FDI

Debarsy, Nicolas; Jin, Fei; Lee, Lung-Fei - HAL - 2014

Persistent link: https://www.econbiz.de/10010930191

Bootstrapping heteroskedasticity consistent covariance matrix estimator

Flachaire, Emmanuel - HAL - 2002

heteroskedasticity robust covariance matrix estimator. In this paper, we show that the wild bootstrap estimator can be calculated …

Persistent link: https://www.econbiz.de/10010750875

Estimation of k-Factor Gigarch Process: A Monte Carlo Study

Ka, Diongue Abdou; Guegan, Dominique - HAL - 2008

In this paper, we discuss the parameter estimation for a k-factor generalized long memory processwith conditionally heteroskedastic noise. Two estimation methods are proposed. The first method is based on the conditional distribution of the process and the second is obtained as an extension of...

Persistent link: https://www.econbiz.de/10010738665

Robust tests for heteroskedasticity in the one-way error components model

Montes-Rojas, Gabriel; Sosa-Escudero, Walter - HAL - 2010

This paper constructs tests for heteroskedasticity in one-way error components models, in line with Baltagi, Bresson … tests for heteroskedasticity in the individual component are shown to be negatively affected by heteroskedasticity in the … remainder component. We derive modified tests that are insensitive to heteroskedasticity in the component not being checked, and …

Persistent link: https://www.econbiz.de/10010820497

Robust tests for heteroskedasticity in the one-way error components model

Montes-Rojas, Gabriel; Sosa-Escudero, Walter - HAL - 2010

Persistent link: https://www.econbiz.de/10010820829

A better way to bootstrap pairs

Flachaire, Emmanuel - HAL - 1999

In this paper we are interested in heteroskedastic regression models, for which an appropriate bootstrap method is bootstrapping pairs, proposed by Freedman (1981). We propose an ameliorate version of it, with better numerical performance.

Persistent link: https://www.econbiz.de/10008791699