Recovering Income Distribution in the Presence of Interval-Censored Data
This paper proposes a method to analyze interval-censored data, using multiple imputation based on a heteroskedastic interval regression approach. The proposed model aims to obtain a synthetic data set that can be used for standard analysis, includ...
| Main Authors: | , , |
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| Language: | English English |
| Published: |
World Bank, Washington, DC
2022
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| Subjects: | |
| Online Access: | http://documents.worldbank.org/curated/en/099724408222262517/IDU04f787105008b604f5108f1a061fe88def833 http://hdl.handle.net/10986/37912 |
| Summary: | This paper proposes a method to
analyze interval-censored data, using multiple imputation
based on a heteroskedastic interval regression approach. The
proposed model aims to obtain a synthetic data set that can
be used for standard analysis, including standard linear
regression, quantile regression, or poverty and inequality
estimation. The paper presents two applications to show the
performance of the method. First, it runs a Monte Carlo
simulation to show the method's performance under the
assumption of multiplicative heteroskedasticity, with and
without conditional normality. Second, it uses the proposed
methodology to analyze labor income data in Grenada for
2013–20, where the salary data are interval-censored
according to the salary intervals prespecified in the survey
questionnaire. The results obtained are consistent across
both exercises. |
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