Gini index estimation within pre-specified error bound: Application to Indian household survey data

Artikel

The Gini index, a widely used economic inequality measure, is computed using data whose designs involve clustering and stratification, generally known as complex household surveys. Under complex household survey, we develop two novel procedures for estimating Gini index with a pre-specified error bound and confidence level. The two proposed approaches are based on the concept of sequential analysis which is known to be economical in the sense of obtaining an optimal cluster size which reduces project cost (that is total sampling cost) thereby achieving the pre-specified error bound and the confidence level under reasonable assumptions. Some large sample properties of the proposed procedures are examined without assuming any specific distribution. Empirical illustrations of both procedures are provided using the consumption expenditure data obtained by National Sample Survey (NSS) Organization in India.

Angaben zum Objekt

• Sprache: Englisch

Verweise und Beziehungen

• Erschienen in: Journal: Econometrics ; ISSN: 2225-1146 ; Volume: 8 ; Year: 2020 ; Issue: 2 ; Pages: 1-20 ; Basel: MDPI

Klassifikation und Themen

• Klassifikation: Wirtschaft
• Thema: complex household survey ; confidence interval ; income distribution ; inequality ; sequential analysis

Beteiligte, Orts- und Zeitangaben

• Ereignis: Geistige Schöpfung
• (wer): Bilson Darku, Francis ; Konietschke, Frank ; Chattopadhyay, Bhargab
• Ereignis: Veröffentlichung
• (wer): MDPI
• (wo): Basel
• (wann): 2020

Weitere Informationen

• DOI: doi:10.3390/econometrics8020026
• Handle: http://hdl.handle.net/10419/247574
• Letzte Aktualisierung: 10.03.2025, 11:41 MEZ