Causality between Output and Income Inequality across U.S. States: Evidence from a Heterogeneous Mixed Panel Approach
Rangan Gupta () and
Stephen Miller ()
Additional contact information
Shinhye Chang: University of Pretoria
Hsiao-Ping Chu: Ling-Tung University
No 2018-07, Working papers from University of Connecticut, Department of Economics
In this paper, we investigate the causal relationship between output, proxied by personal income, and income inequality in a panel data of 48 states from 1929 to 2012. We employ the causality methodology proposed by Emirmahmutoglu and Kose (2011), as it incorporates possible slope heterogeneity and cross-sectional dependence in a multivariate panel. Evidence of bi-directional causal relationship exists for several inequality measures -- the Atkinson Index, Gini Coefficient, the Relative Mean Deviation, Theil’s entropy Index and Top 10% -- but no evidence of the causal relationship for the Top 1 % measure. Also, this paper finds state-specific causal relationships between personal income and inequality.
Keywords: Income inequality; Panel data; Personal Income; Granger causality (search for similar items in EconPapers)
JEL-codes: C33 D31 D63 (search for similar items in EconPapers)
Note: Stephen Miller is the corresponding author
References: Add references at CitEc
Citations: Track citations by RSS feed
Downloads: (external link)
https://media.economics.uconn.edu/working/2018-07.pdf Full text (application/pdf)
Working Paper: Causality between Output and Income Inequality across US States: Evidence from a Heterogeneous Mixed Panel Approach (2017)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:uct:uconnp:2018-07
Access Statistics for this paper
More papers in Working papers from University of Connecticut, Department of Economics University of Connecticut 365 Fairfield Way, Unit 1063 Storrs, CT 06269-1063. Contact information at EDIRC.
Bibliographic data for series maintained by Mark McConnel ().