Bayesian estimation of Persistent Income Inequality using the Lognormal Stochastic Volatility Model

Haruhisa Nishino (), Kazuhiko Kakamu () and Takashi Oga ()
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Haruhisa Nishino: Chiba University
Kazuhiko Kakamu: Chiba University
Takashi Oga: Chiba University

Journal of Income Distribution, 2012, vol. 21, issue 1, 88-101

Abstract: We estimate inequality including Gini coefficients using a lognormal parametric model for an investigation of persistent inequality. The asymptotic theory of selected order statistics enables us to construct a linear model based on grouped data. We extend the linear model to a dynamic model in terms of a stochastic volatility (SV) model. Using Japanese data we estimate the SV model by the Markov chain Monte Carlo (MCMC) method and exploit a model comparison to choose a best model, concluding that the model with SV is better fitted to the data than the model without SV. It indicates the persistent inequality.

Keywords: Income Inequality; Lognormal distribution; Persistence; selected order statistics; stochastic volatility (SV) model; Markov Chain Monte Carlo (MCMC) method (search for similar items in EconPapers)
JEL-codes: C11 C22 C52 (search for similar items in EconPapers)
Date: 2012
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Citations: View citations in EconPapers (7)

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