The findings and conclusions in this article are those of the authors and do not necessarily represent the views of the Centers for Disease Control and Prevention.
Health Economics Letter
EVALUATION OF VARIANCE ESTIMATORS FOR THE CONCENTRATION AND HEALTH ACHIEVEMENT INDICES: A MONTE CARLO SIMULATION†
Version of Record online: 28 SEP 2011
Published 2011. This article is a US Government work and is in the public domain in the USA.
Volume 21, Issue 11, pages 1375–1381, November 2012
How to Cite
Chen, Z., Roy, K. and Gotway Crawford, C. A. (2012), EVALUATION OF VARIANCE ESTIMATORS FOR THE CONCENTRATION AND HEALTH ACHIEVEMENT INDICES: A MONTE CARLO SIMULATION. Health Econ., 21: 1375–1381. doi: 10.1002/hec.1796
- Issue online: 2 OCT 2012
- Version of Record online: 28 SEP 2011
- Manuscript Accepted: 24 AUG 2011
- Manuscript Revised: 27 MAY 2011
- Manuscript Received: 15 APR 2010
- concentration index;
- health achievement index;
- health inequalities;
- Monte Carlo simulation;
- statistical inference
Although the concentration index (CI) and the health achievement index (HAI) have been extensively used, previous studies have relied on bootstrapping to compute the variance of the HAI, whereas competing variance estimators exist for the CI. This paper provides methods of statistical inference for the HAI and compares the available variance estimators for both the CI and the HAI using Monte Carlo simulation. Results for both the CI and the HAI suggest that analytical methods and bootstrapping are well behaved. The convenient regression method gives standard errors close to the other methods, provided the CI is not too large (< 0.2), but otherwise tends to understate the standard errors. In our simulation setting, the improvement from the Newey–West correction over the convenient regression method has mixed evidence when the CI ≤ 0.1 and is modest when the CI > 0.1. Published 2011. This article is a US Government work and is in the public domain in the USA.