Inference for the Neighborhood Inequality Index

Luxembourg Institute of Socio-Economic Research (LISER) Working Paper Series 2018-19

36 Pages Posted: 27 Dec 2018 Last revised: 10 Jan 2019

See all articles by Andreoli Francesco

Andreoli Francesco

Luxembourg Institute of Socio-Economic Research (LISER)

Date Written: November 12, 2018

Abstract

The neighborhood inequality (NI) index measures aspects of spatial inequality in the distribution of incomes within the city. The NI index is defi ned as a population average of the normalized income gap between each individual's income (observed at a given location in the city) and the incomes of the neighbors, living within a certain distance range from that individual. This paper provides minimum bounds for the NI index standard error and shows that unbiased estimators can be identified ed under fairly common hypothesis in spatial statistics. These estimators are shown to depend exclusively on the variogram, a measure of spatial dependence in the data. Rich income data are then used to infer about trends of neighborhood inequality in Chicago, IL over the last 35 years. Results from a Monte Carlo study support the relevance of the standard error approximations.

Keywords: Income Inequality, Individual Neighborhood, Geostatistics, Variogram, Census, ACS, Ratio Measures, Variance Approximation, Chicago, Monte Carlo

JEL Classification: C12, C46, D63, R23

Suggested Citation

Francesco, Andreoli, Inference for the Neighborhood Inequality Index (November 12, 2018). Luxembourg Institute of Socio-Economic Research (LISER) Working Paper Series 2018-19, Available at SSRN: https://ssrn.com/abstract=3289087 or http://dx.doi.org/10.2139/ssrn.3289087

Andreoli Francesco (Contact Author)

Luxembourg Institute of Socio-Economic Research (LISER) ( email )

11, Porte des Sciences
Campus Belval – Maison des Sciences Humaines
Esch-sur-Alzette, L-4366
Luxembourg

HOME PAGE: http://www.liser.lu

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