PARC Working Paper Series
Document Type
Working Paper
Date of this Version
10-2012
Abstract
Research on income risk typically treats its proxy—income volatility, the expected magnitude of income changes—as if it were unchanged for an individual over time, the same for everyone at a point in time, or both. In reality, income risk evolves over time, and some people face more of it than others. To model heterogeneity and dynamics in (unobserved) income volatility, we develop a novel semiparametric Bayesian stochastic volatility model. Our Markovian hierarchical Dirichlet process (MHDP) prior augments the recently developed hierarchical Dirichlet process (HDP) prior to accommodate the serial dependence of panel data. We document dynamics and substantial heterogeneity in income volatility.
Keywords
hierarchical Dirichlet process, income volatility, state-space models
Date Posted: 07 November 2012
Comments
Jensen, Shane T., and Stephen H. Shore. 2012. "Semiparametric Bayesian Modeling of Income Volatility Heterogeneity." PARC Working Paper Series, WPS 12-03.