Arbeitspapier

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, 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.

Language
Englisch

Bibliographic citation
Series: IZA Discussion Papers ; No. 15921

Classification
Wirtschaft
Statistical Simulation Methods: General
Multiple or Simultaneous Equation Models: Truncated and Censored Models; Switching Regression Models
Subject
interval-censored data
Monte Carlo simulation
heteroskedastic interval regression
wages

Event
Geistige Schöpfung
(who)
Canavire Bacarreza, Gustavo J.
Rios-Avila, Fernando
Sacco-Capurro, Flavia
Event
Veröffentlichung
(who)
Institute of Labor Economics (IZA)
(where)
Bonn
(when)
2023

Handle
Last update
10.03.2025, 11:43 AM CET

Data provider

This object is provided by:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.

Object type

  • Arbeitspapier

Associated

  • Canavire Bacarreza, Gustavo J.
  • Rios-Avila, Fernando
  • Sacco-Capurro, Flavia
  • Institute of Labor Economics (IZA)

Time of origin

  • 2023

Other Objects (12)