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THE INCIDENCE AND THE EFFECT OF OVERSKILLING ON INDIVIDUALS EARNINGS IN MALAYSIA: A QUANTILE REGRESSION APPROACH

Jurnal Ekonomi Malaysia

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Title THE INCIDENCE AND THE EFFECT OF OVERSKILLING ON INDIVIDUALS EARNINGS IN MALAYSIA: A QUANTILE REGRESSION APPROACH
 
Creator Zakariya, Zainizam
Abdul Jalil, Norasibah
Khoo, Yin Yin
 
Subject overskilling, quantile regression, unobserved ability, earnings
I2; J24;J31
 
Description This paper examines the incidence and the effect of overskilling on earnings by taking individuals’ unobserved heterogeneity in ability using a quantile regression (QR) method. Using data from the second Malaysia Productivity Investment Climate Survey (PICS-2), the incidence of overskilling was reported around 31% - for which moderately overskilled accounted for 23% and severely overskilled accounted for 8 percent. Preliminary analysis revealed that overskilling was found to be heavily concentrated within low-ability segments of the workers’ conditional wage distributions. Using quantile regression (QR) method, the results revealed that although being overskilled resulted in wage penalty, the penalty however was heterogeneous across the entire workers’ conditional earnings distribution. Indeed, the penalty for moderately overskilled was greater at the lower deciles and became smaller or even disappears as one moved up the earnings distribution. This may be consistent with the view that the overskilled workers are likely amongst the low-ability workers. By contrast, the penalty for severely overskilled, in particular women was evident all the way through the conditional wage distribution. This perhaps suggests that unobserved heterogeneity unable to explain the earnings penalty for mismatched women. Nevertheless, this study may suggest the importance of including explicit controls for individuals’ unobserved ability where possible, as a mean to avoid bias estimation of the wage impacts of the overskilling.
 
Publisher Universiti Kebangsaan Malaysia
 
Contributor The authors acknowledge the World Bank Enterprise Survey (WBES) from whom the 2007 Productivity Investment Climate Survey (PICS) data was acquired. This organisation has no bear any responsibility for the authors’ analysis and interpretations of the data.
 
Date 2017-08-15
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Peer-reviewed Article
 
Identifier http://ejournal.ukm.my/jem/article/view/12543
 
Source Jurnal Ekonomi Malaysia; Vol 51, No 1 (2017): Jurnal Ekonomi Malaysia; 41-56
0126-1962
 
Language en
 
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