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Jurnal Ekonomi Malaysia

51 (1) 2017 39 – 54

The Incidence and the Effect of Overskilling on Individuals’ Wages in Malaysia: A Quantile Regression Approach
Insiden dan Kesan Terlebih Kemahiran ke atas Upah Individu di Malaysia: Satu Pendekatan Regresi Kuantil

Department of Economics.
Universiti Pendidikan Sultan Idris
35900 Tanjung Malim
Perak

zainizam@fpe.upsi.edu.my

Department of Economics.
Universiti Pendidikan Sultan Idris
35900 Tanjung Malim
Perak

norasibah@fpe.upsi.edu.my

Department of Economics.
Universiti Pendidikan Sultan Idris
35900 Tanjung Malim
Perak

khoo@fpe.upsi.edu.my

Department of Economics.
Universiti Pendidikan Sultan Idris
35900 Tanjung Malim
Perak

nfazlin22@yahoo.com

Abstract

This paper examines the incidence and the effect of overskilling on wages by taking individuals’ unobserved heterogeneity in ability using quantile regression (QR) method. Using data from the second Malaysia Productivity and Investment Climate Survey (PICS-2), the incidence of overskilling was reported around 31 percent – for which moderately overskilled accounted for 23 percent 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 wages distribution. Indeed, the penalty for moderately overskilled was greater at the lower deciles and became smaller or even disappears as one moved up the wages distribution. This may be consistent with the view that the overskilled workers are likely amongst the lowability 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 wages 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.

Keywords

Overskilling; quantile regression; unobserved ability; Wages

Author’s Acknowledgement

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.

https://doi.org/10.17576/JEM-2017-5101-4
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Zakariya, , Abdul Jalil, , Khoo, , & Mohamed Noor, (2017). The Incidence and the Effect of Overskilling on Individuals’ Wages in Malaysia: A Quantile Regression Approach. Jurnal Ekonomi Malaysia, 51(1), 39–54. https://doi.org/10.17576/JEM-2017-5101-4

@article{zakariya2017incidents,
  title={The Incidence and the Effect of Overskilling on Individuals’ Wages in Malaysia: A Quantile Regression Approach},
  author={Zakariya, Zainizam and Abdul Jalil, Norasibah and Khoo, Yin Yin and Mohamed Noor, Noor Fazlin},
  journal={Jurnal Ekonomi Malaysia},
  volume={51},
  number={1},
  pages={39—54},
 

year={2017},
}

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