Bootstrapping statistical inferences of decomposition methods for gender earnings differentials

Yue MA, Ying Chu NG

Research output: Journal PublicationsJournal Article (refereed)Researchpeer-review

Abstract

Applying the standard bootstrapping technique with corrections for heteroskedasticity for a sample of the 1997 Urban Household Survey in China, the present article attempts to test (1) whether the commonly used decomposition methods for gender earnings differentials give significantly different results and (2) whether the explained component is significantly different from the unexplained component (which is commonly referred to as discrimination) within each decomposition method. Based on a national data set, the empirical results indicated some significant differences in both tests. The implication of the results is that the proposed bootstrapping technique can be regarded as a guideline on applying which approach to decompose gender earnings differentials among different methods without losing important information, and on evaluating the relative importance of the decomposition components for any chosen method.
Original languageEnglish
Pages (from-to)1583-1593
Number of pages11
JournalApplied Economics
Volume40
Issue number12
DOIs
Publication statusPublished - 1 Jan 2008

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Bootstrapping
Statistical inference
Earnings differentials
Decomposition
Heteroskedasticity
Relative importance
Household survey
China
Discrimination
Empirical results

Cite this

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abstract = "Applying the standard bootstrapping technique with corrections for heteroskedasticity for a sample of the 1997 Urban Household Survey in China, the present article attempts to test (1) whether the commonly used decomposition methods for gender earnings differentials give significantly different results and (2) whether the explained component is significantly different from the unexplained component (which is commonly referred to as discrimination) within each decomposition method. Based on a national data set, the empirical results indicated some significant differences in both tests. The implication of the results is that the proposed bootstrapping technique can be regarded as a guideline on applying which approach to decompose gender earnings differentials among different methods without losing important information, and on evaluating the relative importance of the decomposition components for any chosen method.",
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Bootstrapping statistical inferences of decomposition methods for gender earnings differentials. / MA, Yue; NG, Ying Chu.

In: Applied Economics, Vol. 40, No. 12, 01.01.2008, p. 1583-1593.

Research output: Journal PublicationsJournal Article (refereed)Researchpeer-review

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AU - NG, Ying Chu

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AB - Applying the standard bootstrapping technique with corrections for heteroskedasticity for a sample of the 1997 Urban Household Survey in China, the present article attempts to test (1) whether the commonly used decomposition methods for gender earnings differentials give significantly different results and (2) whether the explained component is significantly different from the unexplained component (which is commonly referred to as discrimination) within each decomposition method. Based on a national data set, the empirical results indicated some significant differences in both tests. The implication of the results is that the proposed bootstrapping technique can be regarded as a guideline on applying which approach to decompose gender earnings differentials among different methods without losing important information, and on evaluating the relative importance of the decomposition components for any chosen method.

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